opencv 4.11版本

GameAssist/GameAssist/Assist.vcxproj

@@ -148,8 +148,8 @@
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GameAssist/GameAssist/include/cv2/opencv2/calib3d.hpp

@@ -0,0 +1,4146 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CALIB3D_HPP
+#define OPENCV_CALIB3D_HPP
+
+#include "opencv2/core.hpp"
+#include "opencv2/core/types.hpp"
+#include "opencv2/features2d.hpp"
+#include "opencv2/core/affine.hpp"
+#include "opencv2/core/utils/logger.hpp"
+
+/**
+  @defgroup calib3d Camera Calibration and 3D Reconstruction
+
+The functions in this section use a so-called pinhole camera model. The view of a scene
+is obtained by projecting a scene's 3D point \f$P_w\f$ into the image plane using a perspective
+transformation which forms the corresponding pixel \f$p\f$. Both \f$P_w\f$ and \f$p\f$ are
+represented in homogeneous coordinates, i.e. as 3D and 2D homogeneous vector respectively. You will
+find a brief introduction to projective geometry, homogeneous vectors and homogeneous
+transformations at the end of this section's introduction. For more succinct notation, we often drop
+the 'homogeneous' and say vector instead of homogeneous vector.
+
+The distortion-free projective transformation given by a  pinhole camera model is shown below.
+
+\f[s \; p = A \begin{bmatrix} R|t \end{bmatrix} P_w,\f]
+
+where \f$P_w\f$ is a 3D point expressed with respect to the world coordinate system,
+\f$p\f$ is a 2D pixel in the image plane, \f$A\f$ is the camera intrinsic matrix,
+\f$R\f$ and \f$t\f$ are the rotation and translation that describe the change of coordinates from
+world to camera coordinate systems (or camera frame) and \f$s\f$ is the projective transformation's
+arbitrary scaling and not part of the camera model.
+
+The camera intrinsic matrix \f$A\f$ (notation used as in @cite Zhang2000 and also generally notated
+as \f$K\f$) projects 3D points given in the camera coordinate system to 2D pixel coordinates, i.e.
+
+\f[p = A P_c.\f]
+
+The camera intrinsic matrix \f$A\f$ is composed of the focal lengths \f$f_x\f$ and \f$f_y\f$, which are
+expressed in pixel units, and the principal point \f$(c_x, c_y)\f$, that is usually close to the
+image center:
+
+\f[A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1},\f]
+
+and thus
+
+\f[s \vecthree{u}{v}{1} = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1} \vecthree{X_c}{Y_c}{Z_c}.\f]
+
+The matrix of intrinsic parameters does not depend on the scene viewed. So, once estimated, it can
+be re-used as long as the focal length is fixed (in case of a zoom lens). Thus, if an image from the
+camera is scaled by a factor, all of these parameters need to be scaled (multiplied/divided,
+respectively) by the same factor.
+
+The joint rotation-translation matrix \f$[R|t]\f$ is the matrix product of a projective
+transformation and a homogeneous transformation. The 3-by-4 projective transformation maps 3D points
+represented in camera coordinates to 2D points in the image plane and represented in normalized
+camera coordinates \f$x' = X_c / Z_c\f$ and \f$y' = Y_c / Z_c\f$:
+
+\f[Z_c \begin{bmatrix}
+x' \\
+y' \\
+1
+\end{bmatrix} = \begin{bmatrix}
+1 & 0 & 0 & 0 \\
+0 & 1 & 0 & 0 \\
+0 & 0 & 1 & 0
+\end{bmatrix}
+\begin{bmatrix}
+X_c \\
+Y_c \\
+Z_c \\
+1
+\end{bmatrix}.\f]
+
+The homogeneous transformation is encoded by the extrinsic parameters \f$R\f$ and \f$t\f$ and
+represents the change of basis from world coordinate system \f$w\f$ to the camera coordinate sytem
+\f$c\f$. Thus, given the representation of the point \f$P\f$ in world coordinates, \f$P_w\f$, we
+obtain \f$P\f$'s representation in the camera coordinate system, \f$P_c\f$, by
+
+\f[P_c = \begin{bmatrix}
+R & t \\
+0 & 1
+\end{bmatrix} P_w,\f]
+
+This homogeneous transformation is composed out of \f$R\f$, a 3-by-3 rotation matrix, and \f$t\f$, a
+3-by-1 translation vector:
+
+\f[\begin{bmatrix}
+R & t \\
+0 & 1
+\end{bmatrix} = \begin{bmatrix}
+r_{11} & r_{12} & r_{13} & t_x \\
+r_{21} & r_{22} & r_{23} & t_y \\
+r_{31} & r_{32} & r_{33} & t_z \\
+0 & 0 & 0 & 1
+\end{bmatrix},
+\f]
+
+and therefore
+
+\f[\begin{bmatrix}
+X_c \\
+Y_c \\
+Z_c \\
+1
+\end{bmatrix} = \begin{bmatrix}
+r_{11} & r_{12} & r_{13} & t_x \\
+r_{21} & r_{22} & r_{23} & t_y \\
+r_{31} & r_{32} & r_{33} & t_z \\
+0 & 0 & 0 & 1
+\end{bmatrix}
+\begin{bmatrix}
+X_w \\
+Y_w \\
+Z_w \\
+1
+\end{bmatrix}.\f]
+
+Combining the projective transformation and the homogeneous transformation, we obtain the projective
+transformation that maps 3D points in world coordinates into 2D points in the image plane and in
+normalized camera coordinates:
+
+\f[Z_c \begin{bmatrix}
+x' \\
+y' \\
+1
+\end{bmatrix} = \begin{bmatrix} R|t \end{bmatrix} \begin{bmatrix}
+X_w \\
+Y_w \\
+Z_w \\
+1
+\end{bmatrix} = \begin{bmatrix}
+r_{11} & r_{12} & r_{13} & t_x \\
+r_{21} & r_{22} & r_{23} & t_y \\
+r_{31} & r_{32} & r_{33} & t_z
+\end{bmatrix}
+\begin{bmatrix}
+X_w \\
+Y_w \\
+Z_w \\
+1
+\end{bmatrix},\f]
+
+with \f$x' = X_c / Z_c\f$ and \f$y' = Y_c / Z_c\f$. Putting the equations for instrincs and extrinsics together, we can write out
+\f$s \; p = A \begin{bmatrix} R|t \end{bmatrix} P_w\f$ as
+
+\f[s \vecthree{u}{v}{1} = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}
+\begin{bmatrix}
+r_{11} & r_{12} & r_{13} & t_x \\
+r_{21} & r_{22} & r_{23} & t_y \\
+r_{31} & r_{32} & r_{33} & t_z
+\end{bmatrix}
+\begin{bmatrix}
+X_w \\
+Y_w \\
+Z_w \\
+1
+\end{bmatrix}.\f]
+
+If \f$Z_c \ne 0\f$, the transformation above is equivalent to the following,
+
+\f[\begin{bmatrix}
+u \\
+v
+\end{bmatrix} = \begin{bmatrix}
+f_x X_c/Z_c + c_x \\
+f_y Y_c/Z_c + c_y
+\end{bmatrix}\f]
+
+with
+
+\f[\vecthree{X_c}{Y_c}{Z_c} = \begin{bmatrix}
+R|t
+\end{bmatrix} \begin{bmatrix}
+X_w \\
+Y_w \\
+Z_w \\
+1
+\end{bmatrix}.\f]
+
+The following figure illustrates the pinhole camera model.
+
+![Pinhole camera model](pics/pinhole_camera_model.png)
+
+Real lenses usually have some distortion, mostly radial distortion, and slight tangential distortion.
+So, the above model is extended as:
+
+\f[\begin{bmatrix}
+u \\
+v
+\end{bmatrix} = \begin{bmatrix}
+f_x x'' + c_x \\
+f_y y'' + c_y
+\end{bmatrix}\f]
+
+where
+
+\f[\begin{bmatrix}
+x'' \\
+y''
+\end{bmatrix} = \begin{bmatrix}
+x' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6} + 2 p_1 x' y' + p_2(r^2 + 2 x'^2) + s_1 r^2 + s_2 r^4 \\
+y' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6} + p_1 (r^2 + 2 y'^2) + 2 p_2 x' y' + s_3 r^2 + s_4 r^4 \\
+\end{bmatrix}\f]
+
+with
+
+\f[r^2 = x'^2 + y'^2\f]
+
+and
+
+\f[\begin{bmatrix}
+x'\\
+y'
+\end{bmatrix} = \begin{bmatrix}
+X_c/Z_c \\
+Y_c/Z_c
+\end{bmatrix},\f]
+
+if \f$Z_c \ne 0\f$.
+
+The distortion parameters are the radial coefficients \f$k_1\f$, \f$k_2\f$, \f$k_3\f$, \f$k_4\f$, \f$k_5\f$, and \f$k_6\f$
+,\f$p_1\f$ and \f$p_2\f$ are the tangential distortion coefficients, and \f$s_1\f$, \f$s_2\f$, \f$s_3\f$, and \f$s_4\f$,
+are the thin prism distortion coefficients. Higher-order coefficients are not considered in OpenCV.
+
+The next figures show two common types of radial distortion: barrel distortion
+(\f$ 1 + k_1 r^2 + k_2 r^4 + k_3 r^6 \f$ monotonically decreasing)
+and pincushion distortion (\f$ 1 + k_1 r^2 + k_2 r^4 + k_3 r^6 \f$ monotonically increasing).
+Radial distortion is always monotonic for real lenses,
+and if the estimator produces a non-monotonic result,
+this should be considered a calibration failure.
+More generally, radial distortion must be monotonic and the distortion function must be bijective.
+A failed estimation result may look deceptively good near the image center
+but will work poorly in e.g. AR/SFM applications.
+The optimization method used in OpenCV camera calibration does not include these constraints as
+the framework does not support the required integer programming and polynomial inequalities.
+See [issue #15992](https://github.com/opencv/opencv/issues/15992) for additional information.
+
+![](pics/distortion_examples.png)
+![](pics/distortion_examples2.png)
+
+In some cases, the image sensor may be tilted in order to focus an oblique plane in front of the
+camera (Scheimpflug principle). This can be useful for particle image velocimetry (PIV) or
+triangulation with a laser fan. The tilt causes a perspective distortion of \f$x''\f$ and
+\f$y''\f$. This distortion can be modeled in the following way, see e.g. @cite Louhichi07.
+
+\f[\begin{bmatrix}
+u \\
+v
+\end{bmatrix} = \begin{bmatrix}
+f_x x''' + c_x \\
+f_y y''' + c_y
+\end{bmatrix},\f]
+
+where
+
+\f[s\vecthree{x'''}{y'''}{1} =
+\vecthreethree{R_{33}(\tau_x, \tau_y)}{0}{-R_{13}(\tau_x, \tau_y)}
+{0}{R_{33}(\tau_x, \tau_y)}{-R_{23}(\tau_x, \tau_y)}
+{0}{0}{1} R(\tau_x, \tau_y) \vecthree{x''}{y''}{1}\f]
+
+and the matrix \f$R(\tau_x, \tau_y)\f$ is defined by two rotations with angular parameter
+\f$\tau_x\f$ and \f$\tau_y\f$, respectively,
+
+\f[
+R(\tau_x, \tau_y) =
+\vecthreethree{\cos(\tau_y)}{0}{-\sin(\tau_y)}{0}{1}{0}{\sin(\tau_y)}{0}{\cos(\tau_y)}
+\vecthreethree{1}{0}{0}{0}{\cos(\tau_x)}{\sin(\tau_x)}{0}{-\sin(\tau_x)}{\cos(\tau_x)} =
+\vecthreethree{\cos(\tau_y)}{\sin(\tau_y)\sin(\tau_x)}{-\sin(\tau_y)\cos(\tau_x)}
+{0}{\cos(\tau_x)}{\sin(\tau_x)}
+{\sin(\tau_y)}{-\cos(\tau_y)\sin(\tau_x)}{\cos(\tau_y)\cos(\tau_x)}.
+\f]
+
+In the functions below the coefficients are passed or returned as
+
+\f[(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f]
+
+vector. That is, if the vector contains four elements, it means that \f$k_3=0\f$ . The distortion
+coefficients do not depend on the scene viewed. Thus, they also belong to the intrinsic camera
+parameters. And they remain the same regardless of the captured image resolution. If, for example, a
+camera has been calibrated on images of 320 x 240 resolution, absolutely the same distortion
+coefficients can be used for 640 x 480 images from the same camera while \f$f_x\f$, \f$f_y\f$,
+\f$c_x\f$, and \f$c_y\f$ need to be scaled appropriately.
+
+The functions below use the above model to do the following:
+
+-   Project 3D points to the image plane given intrinsic and extrinsic parameters.
+-   Compute extrinsic parameters given intrinsic parameters, a few 3D points, and their
+projections.
+-   Estimate intrinsic and extrinsic camera parameters from several views of a known calibration
+pattern (every view is described by several 3D-2D point correspondences).
+-   Estimate the relative position and orientation of the stereo camera "heads" and compute the
+*rectification* transformation that makes the camera optical axes parallel.
+
+<B> Homogeneous Coordinates </B><br>
+Homogeneous Coordinates are a system of coordinates that are used in projective geometry. Their use
+allows to represent points at infinity by finite coordinates and simplifies formulas when compared
+to the cartesian counterparts, e.g. they have the advantage that affine transformations can be
+expressed as linear homogeneous transformation.
+
+One obtains the homogeneous vector \f$P_h\f$ by appending a 1 along an n-dimensional cartesian
+vector \f$P\f$ e.g. for a 3D cartesian vector the mapping \f$P \rightarrow P_h\f$ is:
+
+\f[\begin{bmatrix}
+X \\
+Y \\
+Z
+\end{bmatrix} \rightarrow \begin{bmatrix}
+X \\
+Y \\
+Z \\
+1
+\end{bmatrix}.\f]
+
+For the inverse mapping \f$P_h \rightarrow P\f$, one divides all elements of the homogeneous vector
+by its last element, e.g. for a 3D homogeneous vector one gets its 2D cartesian counterpart by:
+
+\f[\begin{bmatrix}
+X \\
+Y \\
+W
+\end{bmatrix} \rightarrow \begin{bmatrix}
+X / W \\
+Y / W
+\end{bmatrix},\f]
+
+if \f$W \ne 0\f$.
+
+Due to this mapping, all multiples \f$k P_h\f$, for \f$k \ne 0\f$, of a homogeneous point represent
+the same point \f$P_h\f$. An intuitive understanding of this property is that under a projective
+transformation, all multiples of \f$P_h\f$ are mapped to the same point. This is the physical
+observation one does for pinhole cameras, as all points along a ray through the camera's pinhole are
+projected to the same image point, e.g. all points along the red ray in the image of the pinhole
+camera model above would be mapped to the same image coordinate. This property is also the source
+for the scale ambiguity s in the equation of the pinhole camera model.
+
+As mentioned, by using homogeneous coordinates we can express any change of basis parameterized by
+\f$R\f$ and \f$t\f$ as a linear transformation, e.g. for the change of basis from coordinate system
+0 to coordinate system 1 becomes:
+
+\f[P_1 = R P_0 + t \rightarrow P_{h_1} = \begin{bmatrix}
+R & t \\
+0 & 1
+\end{bmatrix} P_{h_0}.\f]
+
+@note
+    -   Many functions in this module take a camera intrinsic matrix as an input parameter. Although all
+        functions assume the same structure of this parameter, they may name it differently. The
+        parameter's description, however, will be clear in that a camera intrinsic matrix with the structure
+        shown above is required.
+    -   A calibration sample for 3 cameras in a horizontal position can be found at
+        opencv_source_code/samples/cpp/3calibration.cpp
+    -   A calibration sample based on a sequence of images can be found at
+        opencv_source_code/samples/cpp/calibration.cpp
+    -   A calibration sample in order to do 3D reconstruction can be found at
+        opencv_source_code/samples/cpp/build3dmodel.cpp
+    -   A calibration example on stereo calibration can be found at
+        opencv_source_code/samples/cpp/stereo_calib.cpp
+    -   A calibration example on stereo matching can be found at
+        opencv_source_code/samples/cpp/stereo_match.cpp
+    -   (Python) A camera calibration sample can be found at
+        opencv_source_code/samples/python/calibrate.py
+
+  @{
+    @defgroup calib3d_fisheye Fisheye camera model
+
+    Definitions: Let P be a point in 3D of coordinates X in the world reference frame (stored in the
+    matrix X) The coordinate vector of P in the camera reference frame is:
+
+    \f[Xc = R X + T\f]
+
+    where R is the rotation matrix corresponding to the rotation vector om: R = rodrigues(om); call x, y
+    and z the 3 coordinates of Xc:
+
+    \f[\begin{array}{l} x = Xc_1 \\ y = Xc_2 \\ z = Xc_3 \end{array} \f]
+
+    The pinhole projection coordinates of P is [a; b] where
+
+    \f[\begin{array}{l} a = x / z \ and \ b = y / z \\ r^2 = a^2 + b^2 \\ \theta = atan(r) \end{array} \f]
+
+    Fisheye distortion:
+
+    \f[\theta_d = \theta (1 + k_1 \theta^2 + k_2 \theta^4 + k_3 \theta^6 + k_4 \theta^8)\f]
+
+    The distorted point coordinates are [x'; y'] where
+
+    \f[\begin{array}{l} x' = (\theta_d / r) a \\ y' = (\theta_d / r) b \end{array} \f]
+
+    Finally, conversion into pixel coordinates: The final pixel coordinates vector [u; v] where:
+
+    \f[\begin{array}{l} u = f_x (x' + \alpha y') + c_x \\
+    v = f_y y' + c_y \end{array} \f]
+
+    Summary:
+    Generic camera model @cite Kannala2006 with perspective projection and without distortion correction
+
+  @}
+ */
+
+namespace cv
+{
+
+//! @addtogroup calib3d
+//! @{
+
+//! type of the robust estimation algorithm
+enum { LMEDS  = 4,  //!< least-median of squares algorithm
+       RANSAC = 8,  //!< RANSAC algorithm
+       RHO    = 16, //!< RHO algorithm
+       USAC_DEFAULT  = 32, //!< USAC algorithm, default settings
+       USAC_PARALLEL = 33, //!< USAC, parallel version
+       USAC_FM_8PTS = 34,  //!< USAC, fundamental matrix 8 points
+       USAC_FAST = 35,     //!< USAC, fast settings
+       USAC_ACCURATE = 36, //!< USAC, accurate settings
+       USAC_PROSAC = 37,   //!< USAC, sorted points, runs PROSAC
+       USAC_MAGSAC = 38    //!< USAC, runs MAGSAC++
+     };
+
+enum SolvePnPMethod {
+    SOLVEPNP_ITERATIVE   = 0, //!< Pose refinement using non-linear Levenberg-Marquardt minimization scheme @cite Madsen04 @cite Eade13 \n
+                              //!< Initial solution for non-planar "objectPoints" needs at least 6 points and uses the DLT algorithm. \n
+                              //!< Initial solution for planar "objectPoints" needs at least 4 points and uses pose from homography decomposition.
+    SOLVEPNP_EPNP        = 1, //!< EPnP: Efficient Perspective-n-Point Camera Pose Estimation @cite lepetit2009epnp
+    SOLVEPNP_P3P         = 2, //!< Complete Solution Classification for the Perspective-Three-Point Problem @cite gao2003complete
+    SOLVEPNP_DLS         = 3, //!< **Broken implementation. Using this flag will fallback to EPnP.** \n
+                              //!< A Direct Least-Squares (DLS) Method for PnP @cite hesch2011direct
+    SOLVEPNP_UPNP        = 4, //!< **Broken implementation. Using this flag will fallback to EPnP.** \n
+                              //!< Exhaustive Linearization for Robust Camera Pose and Focal Length Estimation @cite penate2013exhaustive
+    SOLVEPNP_AP3P        = 5, //!< An Efficient Algebraic Solution to the Perspective-Three-Point Problem @cite Ke17
+    SOLVEPNP_IPPE        = 6, //!< Infinitesimal Plane-Based Pose Estimation @cite Collins14 \n
+                              //!< Object points must be coplanar.
+    SOLVEPNP_IPPE_SQUARE = 7, //!< Infinitesimal Plane-Based Pose Estimation @cite Collins14 \n
+                              //!< This is a special case suitable for marker pose estimation.\n
+                              //!< 4 coplanar object points must be defined in the following order:
+                              //!<   - point 0: [-squareLength / 2,  squareLength / 2, 0]
+                              //!<   - point 1: [ squareLength / 2,  squareLength / 2, 0]
+                              //!<   - point 2: [ squareLength / 2, -squareLength / 2, 0]
+                              //!<   - point 3: [-squareLength / 2, -squareLength / 2, 0]
+    SOLVEPNP_SQPNP       = 8, //!< SQPnP: A Consistently Fast and Globally OptimalSolution to the Perspective-n-Point Problem @cite Terzakis2020SQPnP
+#ifndef CV_DOXYGEN
+    SOLVEPNP_MAX_COUNT        //!< Used for count
+#endif
+};
+
+enum { CALIB_CB_ADAPTIVE_THRESH = 1,
+       CALIB_CB_NORMALIZE_IMAGE = 2,
+       CALIB_CB_FILTER_QUADS    = 4,
+       CALIB_CB_FAST_CHECK      = 8,
+       CALIB_CB_EXHAUSTIVE      = 16,
+       CALIB_CB_ACCURACY        = 32,
+       CALIB_CB_LARGER          = 64,
+       CALIB_CB_MARKER          = 128,
+       CALIB_CB_PLAIN           = 256
+     };
+
+enum { CALIB_CB_SYMMETRIC_GRID  = 1,
+       CALIB_CB_ASYMMETRIC_GRID = 2,
+       CALIB_CB_CLUSTERING      = 4
+     };
+
+enum { CALIB_NINTRINSIC          = 18,
+       CALIB_USE_INTRINSIC_GUESS = 0x00001,
+       CALIB_FIX_ASPECT_RATIO    = 0x00002,
+       CALIB_FIX_PRINCIPAL_POINT = 0x00004,
+       CALIB_ZERO_TANGENT_DIST   = 0x00008,
+       CALIB_FIX_FOCAL_LENGTH    = 0x00010,
+       CALIB_FIX_K1              = 0x00020,
+       CALIB_FIX_K2              = 0x00040,
+       CALIB_FIX_K3              = 0x00080,
+       CALIB_FIX_K4              = 0x00800,
+       CALIB_FIX_K5              = 0x01000,
+       CALIB_FIX_K6              = 0x02000,
+       CALIB_RATIONAL_MODEL      = 0x04000,
+       CALIB_THIN_PRISM_MODEL    = 0x08000,
+       CALIB_FIX_S1_S2_S3_S4     = 0x10000,
+       CALIB_TILTED_MODEL        = 0x40000,
+       CALIB_FIX_TAUX_TAUY       = 0x80000,
+       CALIB_USE_QR              = 0x100000, //!< use QR instead of SVD decomposition for solving. Faster but potentially less precise
+       CALIB_FIX_TANGENT_DIST    = 0x200000,
+       // only for stereo
+       CALIB_FIX_INTRINSIC       = 0x00100,
+       CALIB_SAME_FOCAL_LENGTH   = 0x00200,
+       // for stereo rectification
+       CALIB_ZERO_DISPARITY      = 0x00400,
+       CALIB_USE_LU              = (1 << 17), //!< use LU instead of SVD decomposition for solving. much faster but potentially less precise
+       CALIB_USE_EXTRINSIC_GUESS = (1 << 22)  //!< for stereoCalibrate
+     };
+
+//! the algorithm for finding fundamental matrix
+enum { FM_7POINT = 1, //!< 7-point algorithm
+       FM_8POINT = 2, //!< 8-point algorithm
+       FM_LMEDS  = 4, //!< least-median algorithm. 7-point algorithm is used.
+       FM_RANSAC = 8  //!< RANSAC algorithm. It needs at least 15 points. 7-point algorithm is used.
+     };
+
+enum HandEyeCalibrationMethod
+{
+    CALIB_HAND_EYE_TSAI         = 0, //!< A New Technique for Fully Autonomous and Efficient 3D Robotics Hand/Eye Calibration @cite Tsai89
+    CALIB_HAND_EYE_PARK         = 1, //!< Robot Sensor Calibration: Solving AX = XB on the Euclidean Group @cite Park94
+    CALIB_HAND_EYE_HORAUD       = 2, //!< Hand-eye Calibration @cite Horaud95
+    CALIB_HAND_EYE_ANDREFF      = 3, //!< On-line Hand-Eye Calibration @cite Andreff99
+    CALIB_HAND_EYE_DANIILIDIS   = 4  //!< Hand-Eye Calibration Using Dual Quaternions @cite Daniilidis98
+};
+
+enum RobotWorldHandEyeCalibrationMethod
+{
+    CALIB_ROBOT_WORLD_HAND_EYE_SHAH = 0, //!< Solving the robot-world/hand-eye calibration problem using the kronecker product @cite Shah2013SolvingTR
+    CALIB_ROBOT_WORLD_HAND_EYE_LI   = 1  //!< Simultaneous robot-world and hand-eye calibration using dual-quaternions and kronecker product @cite Li2010SimultaneousRA
+};
+
+enum SamplingMethod { SAMPLING_UNIFORM=0, SAMPLING_PROGRESSIVE_NAPSAC=1, SAMPLING_NAPSAC=2,
+        SAMPLING_PROSAC=3 };
+enum LocalOptimMethod {LOCAL_OPTIM_NULL=0, LOCAL_OPTIM_INNER_LO=1, LOCAL_OPTIM_INNER_AND_ITER_LO=2,
+        LOCAL_OPTIM_GC=3, LOCAL_OPTIM_SIGMA=4};
+enum ScoreMethod {SCORE_METHOD_RANSAC=0, SCORE_METHOD_MSAC=1, SCORE_METHOD_MAGSAC=2, SCORE_METHOD_LMEDS=3};
+enum NeighborSearchMethod { NEIGH_FLANN_KNN=0, NEIGH_GRID=1, NEIGH_FLANN_RADIUS=2 };
+enum PolishingMethod { NONE_POLISHER=0, LSQ_POLISHER=1, MAGSAC=2, COV_POLISHER=3 };
+
+struct CV_EXPORTS_W_SIMPLE UsacParams
+{ // in alphabetical order
+    CV_WRAP UsacParams();
+    CV_PROP_RW double confidence;
+    CV_PROP_RW bool isParallel;
+    CV_PROP_RW int loIterations;
+    CV_PROP_RW LocalOptimMethod loMethod;
+    CV_PROP_RW int loSampleSize;
+    CV_PROP_RW int maxIterations;
+    CV_PROP_RW NeighborSearchMethod neighborsSearch;
+    CV_PROP_RW int randomGeneratorState;
+    CV_PROP_RW SamplingMethod sampler;
+    CV_PROP_RW ScoreMethod score;
+    CV_PROP_RW double threshold;
+    CV_PROP_RW PolishingMethod final_polisher;
+    CV_PROP_RW int final_polisher_iterations;
+};
+
+/** @brief Converts a rotation matrix to a rotation vector or vice versa.
+
+@param src Input rotation vector (3x1 or 1x3) or rotation matrix (3x3).
+@param dst Output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively.
+@param jacobian Optional output Jacobian matrix, 3x9 or 9x3, which is a matrix of partial
+derivatives of the output array components with respect to the input array components.
+
+\f[\begin{array}{l} \theta \leftarrow norm(r) \\ r  \leftarrow r/ \theta \\ R =  \cos(\theta) I + (1- \cos{\theta} ) r r^T +  \sin(\theta) \vecthreethree{0}{-r_z}{r_y}{r_z}{0}{-r_x}{-r_y}{r_x}{0} \end{array}\f]
+
+Inverse transformation can be also done easily, since
+
+\f[\sin ( \theta ) \vecthreethree{0}{-r_z}{r_y}{r_z}{0}{-r_x}{-r_y}{r_x}{0} = \frac{R - R^T}{2}\f]
+
+A rotation vector is a convenient and most compact representation of a rotation matrix (since any
+rotation matrix has just 3 degrees of freedom). The representation is used in the global 3D geometry
+optimization procedures like @ref calibrateCamera, @ref stereoCalibrate, or @ref solvePnP .
+
+@note More information about the computation of the derivative of a 3D rotation matrix with respect to its exponential coordinate
+can be found in:
+    - A Compact Formula for the Derivative of a 3-D Rotation in Exponential Coordinates, Guillermo Gallego, Anthony J. Yezzi @cite Gallego2014ACF
+
+@note Useful information on SE(3) and Lie Groups can be found in:
+    - A tutorial on SE(3) transformation parameterizations and on-manifold optimization, Jose-Luis Blanco @cite blanco2010tutorial
+    - Lie Groups for 2D and 3D Transformation, Ethan Eade @cite Eade17
+    - A micro Lie theory for state estimation in robotics, Joan Solà, Jérémie Deray, Dinesh Atchuthan @cite Sol2018AML
+ */
+CV_EXPORTS_W void Rodrigues( InputArray src, OutputArray dst, OutputArray jacobian = noArray() );
+
+
+
+/** Levenberg-Marquardt solver. Starting with the specified vector of parameters it
+    optimizes the target vector criteria "err"
+    (finds local minima of each target vector component absolute value).
+
+    When needed, it calls user-provided callback.
+*/
+class CV_EXPORTS LMSolver : public Algorithm
+{
+public:
+    class CV_EXPORTS Callback
+    {
+    public:
+        virtual ~Callback() {}
+        /**
+         computes error and Jacobian for the specified vector of parameters
+
+         @param param the current vector of parameters
+         @param err output vector of errors: err_i = actual_f_i - ideal_f_i
+         @param J output Jacobian: J_ij = d(ideal_f_i)/d(param_j)
+
+         when J=noArray(), it means that it does not need to be computed.
+         Dimensionality of error vector and param vector can be different.
+         The callback should explicitly allocate (with "create" method) each output array
+         (unless it's noArray()).
+        */
+        virtual bool compute(InputArray param, OutputArray err, OutputArray J) const = 0;
+    };
+
+    /**
+       Runs Levenberg-Marquardt algorithm using the passed vector of parameters as the start point.
+       The final vector of parameters (whether the algorithm converged or not) is stored at the same
+       vector. The method returns the number of iterations used. If it's equal to the previously specified
+       maxIters, there is a big chance the algorithm did not converge.
+
+       @param param initial/final vector of parameters.
+
+       Note that the dimensionality of parameter space is defined by the size of param vector,
+       and the dimensionality of optimized criteria is defined by the size of err vector
+       computed by the callback.
+    */
+    virtual int run(InputOutputArray param) const = 0;
+
+    /**
+       Sets the maximum number of iterations
+       @param maxIters the number of iterations
+    */
+    virtual void setMaxIters(int maxIters) = 0;
+    /**
+       Retrieves the current maximum number of iterations
+    */
+    virtual int getMaxIters() const = 0;
+
+    /**
+       Creates Levenberg-Marquard solver
+
+       @param cb callback
+       @param maxIters maximum number of iterations that can be further
+         modified using setMaxIters() method.
+    */
+    static Ptr<LMSolver> create(const Ptr<LMSolver::Callback>& cb, int maxIters);
+    static Ptr<LMSolver> create(const Ptr<LMSolver::Callback>& cb, int maxIters, double eps);
+};
+
+
+
+/** @example samples/cpp/tutorial_code/features2D/Homography/pose_from_homography.cpp
+An example program about pose estimation from coplanar points
+
+Check @ref tutorial_homography "the corresponding tutorial" for more details
+*/
+
+/** @brief Finds a perspective transformation between two planes.
+
+@param srcPoints Coordinates of the points in the original plane, a matrix of the type CV_32FC2
+or vector\<Point2f\> .
+@param dstPoints Coordinates of the points in the target plane, a matrix of the type CV_32FC2 or
+a vector\<Point2f\> .
+@param method Method used to compute a homography matrix. The following methods are possible:
+-   **0** - a regular method using all the points, i.e., the least squares method
+-   @ref RANSAC - RANSAC-based robust method
+-   @ref LMEDS - Least-Median robust method
+-   @ref RHO - PROSAC-based robust method
+@param ransacReprojThreshold Maximum allowed reprojection error to treat a point pair as an inlier
+(used in the RANSAC and RHO methods only). That is, if
+\f[\| \texttt{dstPoints} _i -  \texttt{convertPointsHomogeneous} ( \texttt{H} \cdot \texttt{srcPoints} _i) \|_2  >  \texttt{ransacReprojThreshold}\f]
+then the point \f$i\f$ is considered as an outlier. If srcPoints and dstPoints are measured in pixels,
+it usually makes sense to set this parameter somewhere in the range of 1 to 10.
+@param mask Optional output mask set by a robust method ( RANSAC or LMeDS ). Note that the input
+mask values are ignored.
+@param maxIters The maximum number of RANSAC iterations.
+@param confidence Confidence level, between 0 and 1.
+
+The function finds and returns the perspective transformation \f$H\f$ between the source and the
+destination planes:
+
+\f[s_i  \vecthree{x'_i}{y'_i}{1} \sim H  \vecthree{x_i}{y_i}{1}\f]
+
+so that the back-projection error
+
+\f[\sum _i \left ( x'_i- \frac{h_{11} x_i + h_{12} y_i + h_{13}}{h_{31} x_i + h_{32} y_i + h_{33}} \right )^2+ \left ( y'_i- \frac{h_{21} x_i + h_{22} y_i + h_{23}}{h_{31} x_i + h_{32} y_i + h_{33}} \right )^2\f]
+
+is minimized. If the parameter method is set to the default value 0, the function uses all the point
+pairs to compute an initial homography estimate with a simple least-squares scheme.
+
+However, if not all of the point pairs ( \f$srcPoints_i\f$, \f$dstPoints_i\f$ ) fit the rigid perspective
+transformation (that is, there are some outliers), this initial estimate will be poor. In this case,
+you can use one of the three robust methods. The methods RANSAC, LMeDS and RHO try many different
+random subsets of the corresponding point pairs (of four pairs each, collinear pairs are discarded), estimate the homography matrix
+using this subset and a simple least-squares algorithm, and then compute the quality/goodness of the
+computed homography (which is the number of inliers for RANSAC or the least median re-projection error for
+LMeDS). The best subset is then used to produce the initial estimate of the homography matrix and
+the mask of inliers/outliers.
+
+Regardless of the method, robust or not, the computed homography matrix is refined further (using
+inliers only in case of a robust method) with the Levenberg-Marquardt method to reduce the
+re-projection error even more.
+
+The methods RANSAC and RHO can handle practically any ratio of outliers but need a threshold to
+distinguish inliers from outliers. The method LMeDS does not need any threshold but it works
+correctly only when there are more than 50% of inliers. Finally, if there are no outliers and the
+noise is rather small, use the default method (method=0).
+
+The function is used to find initial intrinsic and extrinsic matrices. Homography matrix is
+determined up to a scale. If \f$h_{33}\f$ is non-zero, the matrix is normalized so that \f$h_{33}=1\f$.
+@note Whenever an \f$H\f$ matrix cannot be estimated, an empty one will be returned.
+
+@sa
+getAffineTransform, estimateAffine2D, estimateAffinePartial2D, getPerspectiveTransform, warpPerspective,
+perspectiveTransform
+ */
+CV_EXPORTS_W Mat findHomography( InputArray srcPoints, InputArray dstPoints,
+                                 int method = 0, double ransacReprojThreshold = 3,
+                                 OutputArray mask=noArray(), const int maxIters = 2000,
+                                 const double confidence = 0.995);
+
+/** @overload */
+CV_EXPORTS Mat findHomography( InputArray srcPoints, InputArray dstPoints,
+                               OutputArray mask, int method = 0, double ransacReprojThreshold = 3 );
+
+
+CV_EXPORTS_W Mat findHomography(InputArray srcPoints, InputArray dstPoints, OutputArray mask,
+                   const UsacParams &params);
+
+/** @brief Computes an RQ decomposition of 3x3 matrices.
+
+@param src 3x3 input matrix.
+@param mtxR Output 3x3 upper-triangular matrix.
+@param mtxQ Output 3x3 orthogonal matrix.
+@param Qx Optional output 3x3 rotation matrix around x-axis.
+@param Qy Optional output 3x3 rotation matrix around y-axis.
+@param Qz Optional output 3x3 rotation matrix around z-axis.
+
+The function computes a RQ decomposition using the given rotations. This function is used in
+#decomposeProjectionMatrix to decompose the left 3x3 submatrix of a projection matrix into a camera
+and a rotation matrix.
+
+It optionally returns three rotation matrices, one for each axis, and the three Euler angles in
+degrees (as the return value) that could be used in OpenGL. Note, there is always more than one
+sequence of rotations about the three principal axes that results in the same orientation of an
+object, e.g. see @cite Slabaugh . Returned three rotation matrices and corresponding three Euler angles
+are only one of the possible solutions.
+ */
+CV_EXPORTS_W Vec3d RQDecomp3x3( InputArray src, OutputArray mtxR, OutputArray mtxQ,
+                                OutputArray Qx = noArray(),
+                                OutputArray Qy = noArray(),
+                                OutputArray Qz = noArray());
+
+/** @brief Decomposes a projection matrix into a rotation matrix and a camera intrinsic matrix.
+
+@param projMatrix 3x4 input projection matrix P.
+@param cameraMatrix Output 3x3 camera intrinsic matrix \f$\cameramatrix{A}\f$.
+@param rotMatrix Output 3x3 external rotation matrix R.
+@param transVect Output 4x1 translation vector T.
+@param rotMatrixX Optional 3x3 rotation matrix around x-axis.
+@param rotMatrixY Optional 3x3 rotation matrix around y-axis.
+@param rotMatrixZ Optional 3x3 rotation matrix around z-axis.
+@param eulerAngles Optional three-element vector containing three Euler angles of rotation in
+degrees.
+
+The function computes a decomposition of a projection matrix into a calibration and a rotation
+matrix and the position of a camera.
+
+It optionally returns three rotation matrices, one for each axis, and three Euler angles that could
+be used in OpenGL. Note, there is always more than one sequence of rotations about the three
+principal axes that results in the same orientation of an object, e.g. see @cite Slabaugh . Returned
+three rotation matrices and corresponding three Euler angles are only one of the possible solutions.
+
+The function is based on #RQDecomp3x3 .
+ */
+CV_EXPORTS_W void decomposeProjectionMatrix( InputArray projMatrix, OutputArray cameraMatrix,
+                                             OutputArray rotMatrix, OutputArray transVect,
+                                             OutputArray rotMatrixX = noArray(),
+                                             OutputArray rotMatrixY = noArray(),
+                                             OutputArray rotMatrixZ = noArray(),
+                                             OutputArray eulerAngles =noArray() );
+
+/** @brief Computes partial derivatives of the matrix product for each multiplied matrix.
+
+@param A First multiplied matrix.
+@param B Second multiplied matrix.
+@param dABdA First output derivative matrix d(A\*B)/dA of size
+\f$\texttt{A.rows*B.cols} \times {A.rows*A.cols}\f$ .
+@param dABdB Second output derivative matrix d(A\*B)/dB of size
+\f$\texttt{A.rows*B.cols} \times {B.rows*B.cols}\f$ .
+
+The function computes partial derivatives of the elements of the matrix product \f$A*B\f$ with regard to
+the elements of each of the two input matrices. The function is used to compute the Jacobian
+matrices in #stereoCalibrate but can also be used in any other similar optimization function.
+ */
+CV_EXPORTS_W void matMulDeriv( InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB );
+
+/** @brief Combines two rotation-and-shift transformations.
+
+@param rvec1 First rotation vector.
+@param tvec1 First translation vector.
+@param rvec2 Second rotation vector.
+@param tvec2 Second translation vector.
+@param rvec3 Output rotation vector of the superposition.
+@param tvec3 Output translation vector of the superposition.
+@param dr3dr1 Optional output derivative of rvec3 with regard to rvec1
+@param dr3dt1 Optional output derivative of rvec3 with regard to tvec1
+@param dr3dr2 Optional output derivative of rvec3 with regard to rvec2
+@param dr3dt2 Optional output derivative of rvec3 with regard to tvec2
+@param dt3dr1 Optional output derivative of tvec3 with regard to rvec1
+@param dt3dt1 Optional output derivative of tvec3 with regard to tvec1
+@param dt3dr2 Optional output derivative of tvec3 with regard to rvec2
+@param dt3dt2 Optional output derivative of tvec3 with regard to tvec2
+
+The functions compute:
+
+\f[\begin{array}{l} \texttt{rvec3} =  \mathrm{rodrigues} ^{-1} \left ( \mathrm{rodrigues} ( \texttt{rvec2} )  \cdot \mathrm{rodrigues} ( \texttt{rvec1} ) \right )  \\ \texttt{tvec3} =  \mathrm{rodrigues} ( \texttt{rvec2} )  \cdot \texttt{tvec1} +  \texttt{tvec2} \end{array} ,\f]
+
+where \f$\mathrm{rodrigues}\f$ denotes a rotation vector to a rotation matrix transformation, and
+\f$\mathrm{rodrigues}^{-1}\f$ denotes the inverse transformation. See #Rodrigues for details.
+
+Also, the functions can compute the derivatives of the output vectors with regards to the input
+vectors (see #matMulDeriv ). The functions are used inside #stereoCalibrate but can also be used in
+your own code where Levenberg-Marquardt or another gradient-based solver is used to optimize a
+function that contains a matrix multiplication.
+ */
+CV_EXPORTS_W void composeRT( InputArray rvec1, InputArray tvec1,
+                             InputArray rvec2, InputArray tvec2,
+                             OutputArray rvec3, OutputArray tvec3,
+                             OutputArray dr3dr1 = noArray(), OutputArray dr3dt1 = noArray(),
+                             OutputArray dr3dr2 = noArray(), OutputArray dr3dt2 = noArray(),
+                             OutputArray dt3dr1 = noArray(), OutputArray dt3dt1 = noArray(),
+                             OutputArray dt3dr2 = noArray(), OutputArray dt3dt2 = noArray() );
+
+/** @brief Projects 3D points to an image plane.
+
+@param objectPoints Array of object points expressed wrt. the world coordinate frame. A 3xN/Nx3
+1-channel or 1xN/Nx1 3-channel (or vector\<Point3f\> ), where N is the number of points in the view.
+@param rvec The rotation vector (@ref Rodrigues) that, together with tvec, performs a change of
+basis from world to camera coordinate system, see @ref calibrateCamera for details.
+@param tvec The translation vector, see parameter description above.
+@param cameraMatrix Camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$ . If the vector is empty, the zero distortion coefficients are assumed.
+@param imagePoints Output array of image points, 1xN/Nx1 2-channel, or
+vector\<Point2f\> .
+@param jacobian Optional output 2Nx(10+\<numDistCoeffs\>) jacobian matrix of derivatives of image
+points with respect to components of the rotation vector, translation vector, focal lengths,
+coordinates of the principal point and the distortion coefficients. In the old interface different
+components of the jacobian are returned via different output parameters.
+@param aspectRatio Optional "fixed aspect ratio" parameter. If the parameter is not 0, the
+function assumes that the aspect ratio (\f$f_x / f_y\f$) is fixed and correspondingly adjusts the
+jacobian matrix.
+
+The function computes the 2D projections of 3D points to the image plane, given intrinsic and
+extrinsic camera parameters. Optionally, the function computes Jacobians -matrices of partial
+derivatives of image points coordinates (as functions of all the input parameters) with respect to
+the particular parameters, intrinsic and/or extrinsic. The Jacobians are used during the global
+optimization in @ref calibrateCamera, @ref solvePnP, and @ref stereoCalibrate. The function itself
+can also be used to compute a re-projection error, given the current intrinsic and extrinsic
+parameters.
+
+@note By setting rvec = tvec = \f$[0, 0, 0]\f$, or by setting cameraMatrix to a 3x3 identity matrix,
+or by passing zero distortion coefficients, one can get various useful partial cases of the
+function. This means, one can compute the distorted coordinates for a sparse set of points or apply
+a perspective transformation (and also compute the derivatives) in the ideal zero-distortion setup.
+ */
+CV_EXPORTS_W void projectPoints( InputArray objectPoints,
+                                 InputArray rvec, InputArray tvec,
+                                 InputArray cameraMatrix, InputArray distCoeffs,
+                                 OutputArray imagePoints,
+                                 OutputArray jacobian = noArray(),
+                                 double aspectRatio = 0 );
+
+/** @example samples/cpp/tutorial_code/features2D/Homography/homography_from_camera_displacement.cpp
+An example program about homography from the camera displacement
+
+Check @ref tutorial_homography "the corresponding tutorial" for more details
+*/
+
+/** @brief Finds an object pose from 3D-2D point correspondences.
+
+@see @ref calib3d_solvePnP
+
+This function returns the rotation and the translation vectors that transform a 3D point expressed in the object
+coordinate frame to the camera coordinate frame, using different methods:
+- P3P methods (@ref SOLVEPNP_P3P, @ref SOLVEPNP_AP3P): need 4 input points to return a unique solution.
+- @ref SOLVEPNP_IPPE Input points must be >= 4 and object points must be coplanar.
+- @ref SOLVEPNP_IPPE_SQUARE Special case suitable for marker pose estimation.
+Number of input points must be 4. Object points must be defined in the following order:
+  - point 0: [-squareLength / 2,  squareLength / 2, 0]
+  - point 1: [ squareLength / 2,  squareLength / 2, 0]
+  - point 2: [ squareLength / 2, -squareLength / 2, 0]
+  - point 3: [-squareLength / 2, -squareLength / 2, 0]
+- for all the other flags, number of input points must be >= 4 and object points can be in any configuration.
+
+@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or
+1xN/Nx1 3-channel, where N is the number of points. vector\<Point3d\> can be also passed here.
+@param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+where N is the number of points. vector\<Point2d\> can be also passed here.
+@param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is NULL/empty, the zero distortion coefficients are
+assumed.
+@param rvec Output rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+the model coordinate system to the camera coordinate system.
+@param tvec Output translation vector.
+@param useExtrinsicGuess Parameter used for #SOLVEPNP_ITERATIVE. If true (1), the function uses
+the provided rvec and tvec values as initial approximations of the rotation and translation
+vectors, respectively, and further optimizes them.
+@param flags Method for solving a PnP problem: see @ref calib3d_solvePnP_flags
+
+More information about Perspective-n-Points is described in @ref calib3d_solvePnP
+
+@note
+   -   An example of how to use solvePnP for planar augmented reality can be found at
+        opencv_source_code/samples/python/plane_ar.py
+   -   If you are using Python:
+        - Numpy array slices won't work as input because solvePnP requires contiguous
+        arrays (enforced by the assertion using cv::Mat::checkVector() around line 55 of
+        modules/calib3d/src/solvepnp.cpp version 2.4.9)
+        - The P3P algorithm requires image points to be in an array of shape (N,1,2) due
+        to its calling of #undistortPoints (around line 75 of modules/calib3d/src/solvepnp.cpp version 2.4.9)
+        which requires 2-channel information.
+        - Thus, given some data D = np.array(...) where D.shape = (N,M), in order to use a subset of
+        it as, e.g., imagePoints, one must effectively copy it into a new array: imagePoints =
+        np.ascontiguousarray(D[:,:2]).reshape((N,1,2))
+   -   The methods @ref SOLVEPNP_DLS and @ref SOLVEPNP_UPNP cannot be used as the current implementations are
+       unstable and sometimes give completely wrong results. If you pass one of these two
+       flags, @ref SOLVEPNP_EPNP method will be used instead.
+   -   The minimum number of points is 4 in the general case. In the case of @ref SOLVEPNP_P3P and @ref SOLVEPNP_AP3P
+       methods, it is required to use exactly 4 points (the first 3 points are used to estimate all the solutions
+       of the P3P problem, the last one is used to retain the best solution that minimizes the reprojection error).
+   -   With @ref SOLVEPNP_ITERATIVE method and `useExtrinsicGuess=true`, the minimum number of points is 3 (3 points
+       are sufficient to compute a pose but there are up to 4 solutions). The initial solution should be close to the
+       global solution to converge.
+   -   With @ref SOLVEPNP_IPPE input points must be >= 4 and object points must be coplanar.
+   -   With @ref SOLVEPNP_IPPE_SQUARE this is a special case suitable for marker pose estimation.
+       Number of input points must be 4. Object points must be defined in the following order:
+         - point 0: [-squareLength / 2,  squareLength / 2, 0]
+         - point 1: [ squareLength / 2,  squareLength / 2, 0]
+         - point 2: [ squareLength / 2, -squareLength / 2, 0]
+         - point 3: [-squareLength / 2, -squareLength / 2, 0]
+    -  With @ref SOLVEPNP_SQPNP input points must be >= 3
+ */
+CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
+                            InputArray cameraMatrix, InputArray distCoeffs,
+                            OutputArray rvec, OutputArray tvec,
+                            bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE );
+
+/** @brief Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
+
+@see @ref calib3d_solvePnP
+
+@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or
+1xN/Nx1 3-channel, where N is the number of points. vector\<Point3d\> can be also passed here.
+@param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+where N is the number of points. vector\<Point2d\> can be also passed here.
+@param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is NULL/empty, the zero distortion coefficients are
+assumed.
+@param rvec Output rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+the model coordinate system to the camera coordinate system.
+@param tvec Output translation vector.
+@param useExtrinsicGuess Parameter used for @ref SOLVEPNP_ITERATIVE. If true (1), the function uses
+the provided rvec and tvec values as initial approximations of the rotation and translation
+vectors, respectively, and further optimizes them.
+@param iterationsCount Number of iterations.
+@param reprojectionError Inlier threshold value used by the RANSAC procedure. The parameter value
+is the maximum allowed distance between the observed and computed point projections to consider it
+an inlier.
+@param confidence The probability that the algorithm produces a useful result.
+@param inliers Output vector that contains indices of inliers in objectPoints and imagePoints .
+@param flags Method for solving a PnP problem (see @ref solvePnP ).
+
+The function estimates an object pose given a set of object points, their corresponding image
+projections, as well as the camera intrinsic matrix and the distortion coefficients. This function finds such
+a pose that minimizes reprojection error, that is, the sum of squared distances between the observed
+projections imagePoints and the projected (using @ref projectPoints ) objectPoints. The use of RANSAC
+makes the function resistant to outliers.
+
+@note
+   -   An example of how to use solvePNPRansac for object detection can be found at
+        opencv_source_code/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/
+   -   The default method used to estimate the camera pose for the Minimal Sample Sets step
+       is #SOLVEPNP_EPNP. Exceptions are:
+         - if you choose #SOLVEPNP_P3P or #SOLVEPNP_AP3P, these methods will be used.
+         - if the number of input points is equal to 4, #SOLVEPNP_P3P is used.
+   -   The method used to estimate the camera pose using all the inliers is defined by the
+       flags parameters unless it is equal to #SOLVEPNP_P3P or #SOLVEPNP_AP3P. In this case,
+       the method #SOLVEPNP_EPNP will be used instead.
+ */
+CV_EXPORTS_W bool solvePnPRansac( InputArray objectPoints, InputArray imagePoints,
+                                  InputArray cameraMatrix, InputArray distCoeffs,
+                                  OutputArray rvec, OutputArray tvec,
+                                  bool useExtrinsicGuess = false, int iterationsCount = 100,
+                                  float reprojectionError = 8.0, double confidence = 0.99,
+                                  OutputArray inliers = noArray(), int flags = SOLVEPNP_ITERATIVE );
+
+
+/*
+Finds rotation and translation vector.
+If cameraMatrix is given then run P3P. Otherwise run linear P6P and output cameraMatrix too.
+*/
+CV_EXPORTS_W bool solvePnPRansac( InputArray objectPoints, InputArray imagePoints,
+                     InputOutputArray cameraMatrix, InputArray distCoeffs,
+                     OutputArray rvec, OutputArray tvec, OutputArray inliers,
+                     const UsacParams &params=UsacParams());
+
+/** @brief Finds an object pose from 3 3D-2D point correspondences.
+
+@see @ref calib3d_solvePnP
+
+@param objectPoints Array of object points in the object coordinate space, 3x3 1-channel or
+1x3/3x1 3-channel. vector\<Point3f\> can be also passed here.
+@param imagePoints Array of corresponding image points, 3x2 1-channel or 1x3/3x1 2-channel.
+ vector\<Point2f\> can be also passed here.
+@param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is NULL/empty, the zero distortion coefficients are
+assumed.
+@param rvecs Output rotation vectors (see @ref Rodrigues ) that, together with tvecs, brings points from
+the model coordinate system to the camera coordinate system. A P3P problem has up to 4 solutions.
+@param tvecs Output translation vectors.
+@param flags Method for solving a P3P problem:
+-   @ref SOLVEPNP_P3P Method is based on the paper of X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang
+"Complete Solution Classification for the Perspective-Three-Point Problem" (@cite gao2003complete).
+-   @ref SOLVEPNP_AP3P Method is based on the paper of T. Ke and S. Roumeliotis.
+"An Efficient Algebraic Solution to the Perspective-Three-Point Problem" (@cite Ke17).
+
+The function estimates the object pose given 3 object points, their corresponding image
+projections, as well as the camera intrinsic matrix and the distortion coefficients.
+
+@note
+The solutions are sorted by reprojection errors (lowest to highest).
+ */
+CV_EXPORTS_W int solveP3P( InputArray objectPoints, InputArray imagePoints,
+                           InputArray cameraMatrix, InputArray distCoeffs,
+                           OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
+                           int flags );
+
+/** @brief Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame
+to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.
+
+@see @ref calib3d_solvePnP
+
+@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or 1xN/Nx1 3-channel,
+where N is the number of points. vector\<Point3d\> can also be passed here.
+@param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+where N is the number of points. vector\<Point2d\> can also be passed here.
+@param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is NULL/empty, the zero distortion coefficients are
+assumed.
+@param rvec Input/Output rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+the model coordinate system to the camera coordinate system. Input values are used as an initial solution.
+@param tvec Input/Output translation vector. Input values are used as an initial solution.
+@param criteria Criteria when to stop the Levenberg-Marquard iterative algorithm.
+
+The function refines the object pose given at least 3 object points, their corresponding image
+projections, an initial solution for the rotation and translation vector,
+as well as the camera intrinsic matrix and the distortion coefficients.
+The function minimizes the projection error with respect to the rotation and the translation vectors, according
+to a Levenberg-Marquardt iterative minimization @cite Madsen04 @cite Eade13 process.
+ */
+CV_EXPORTS_W void solvePnPRefineLM( InputArray objectPoints, InputArray imagePoints,
+                                    InputArray cameraMatrix, InputArray distCoeffs,
+                                    InputOutputArray rvec, InputOutputArray tvec,
+                                    TermCriteria criteria = TermCriteria(TermCriteria::EPS + TermCriteria::COUNT, 20, FLT_EPSILON));
+
+/** @brief Refine a pose (the translation and the rotation that transform a 3D point expressed in the object coordinate frame
+to the camera coordinate frame) from a 3D-2D point correspondences and starting from an initial solution.
+
+@see @ref calib3d_solvePnP
+
+@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or 1xN/Nx1 3-channel,
+where N is the number of points. vector\<Point3d\> can also be passed here.
+@param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+where N is the number of points. vector\<Point2d\> can also be passed here.
+@param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is NULL/empty, the zero distortion coefficients are
+assumed.
+@param rvec Input/Output rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+the model coordinate system to the camera coordinate system. Input values are used as an initial solution.
+@param tvec Input/Output translation vector. Input values are used as an initial solution.
+@param criteria Criteria when to stop the Levenberg-Marquard iterative algorithm.
+@param VVSlambda Gain for the virtual visual servoing control law, equivalent to the \f$\alpha\f$
+gain in the Damped Gauss-Newton formulation.
+
+The function refines the object pose given at least 3 object points, their corresponding image
+projections, an initial solution for the rotation and translation vector,
+as well as the camera intrinsic matrix and the distortion coefficients.
+The function minimizes the projection error with respect to the rotation and the translation vectors, using a
+virtual visual servoing (VVS) @cite Chaumette06 @cite Marchand16 scheme.
+ */
+CV_EXPORTS_W void solvePnPRefineVVS( InputArray objectPoints, InputArray imagePoints,
+                                     InputArray cameraMatrix, InputArray distCoeffs,
+                                     InputOutputArray rvec, InputOutputArray tvec,
+                                     TermCriteria criteria = TermCriteria(TermCriteria::EPS + TermCriteria::COUNT, 20, FLT_EPSILON),
+                                     double VVSlambda = 1);
+
+/** @brief Finds an object pose from 3D-2D point correspondences.
+
+@see @ref calib3d_solvePnP
+
+This function returns a list of all the possible solutions (a solution is a <rotation vector, translation vector>
+couple), depending on the number of input points and the chosen method:
+- P3P methods (@ref SOLVEPNP_P3P, @ref SOLVEPNP_AP3P): 3 or 4 input points. Number of returned solutions can be between 0 and 4 with 3 input points.
+- @ref SOLVEPNP_IPPE Input points must be >= 4 and object points must be coplanar. Returns 2 solutions.
+- @ref SOLVEPNP_IPPE_SQUARE Special case suitable for marker pose estimation.
+Number of input points must be 4 and 2 solutions are returned. Object points must be defined in the following order:
+  - point 0: [-squareLength / 2,  squareLength / 2, 0]
+  - point 1: [ squareLength / 2,  squareLength / 2, 0]
+  - point 2: [ squareLength / 2, -squareLength / 2, 0]
+  - point 3: [-squareLength / 2, -squareLength / 2, 0]
+- for all the other flags, number of input points must be >= 4 and object points can be in any configuration.
+Only 1 solution is returned.
+
+@param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or
+1xN/Nx1 3-channel, where N is the number of points. vector\<Point3d\> can be also passed here.
+@param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+where N is the number of points. vector\<Point2d\> can be also passed here.
+@param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is NULL/empty, the zero distortion coefficients are
+assumed.
+@param rvecs Vector of output rotation vectors (see @ref Rodrigues ) that, together with tvecs, brings points from
+the model coordinate system to the camera coordinate system.
+@param tvecs Vector of output translation vectors.
+@param useExtrinsicGuess Parameter used for #SOLVEPNP_ITERATIVE. If true (1), the function uses
+the provided rvec and tvec values as initial approximations of the rotation and translation
+vectors, respectively, and further optimizes them.
+@param flags Method for solving a PnP problem: see @ref calib3d_solvePnP_flags
+@param rvec Rotation vector used to initialize an iterative PnP refinement algorithm, when flag is @ref SOLVEPNP_ITERATIVE
+and useExtrinsicGuess is set to true.
+@param tvec Translation vector used to initialize an iterative PnP refinement algorithm, when flag is @ref SOLVEPNP_ITERATIVE
+and useExtrinsicGuess is set to true.
+@param reprojectionError Optional vector of reprojection error, that is the RMS error
+(\f$ \text{RMSE} = \sqrt{\frac{\sum_{i}^{N} \left ( \hat{y_i} - y_i \right )^2}{N}} \f$) between the input image points
+and the 3D object points projected with the estimated pose.
+
+More information is described in @ref calib3d_solvePnP
+
+@note
+   -   An example of how to use solvePnP for planar augmented reality can be found at
+        opencv_source_code/samples/python/plane_ar.py
+   -   If you are using Python:
+        - Numpy array slices won't work as input because solvePnP requires contiguous
+        arrays (enforced by the assertion using cv::Mat::checkVector() around line 55 of
+        modules/calib3d/src/solvepnp.cpp version 2.4.9)
+        - The P3P algorithm requires image points to be in an array of shape (N,1,2) due
+        to its calling of #undistortPoints (around line 75 of modules/calib3d/src/solvepnp.cpp version 2.4.9)
+        which requires 2-channel information.
+        - Thus, given some data D = np.array(...) where D.shape = (N,M), in order to use a subset of
+        it as, e.g., imagePoints, one must effectively copy it into a new array: imagePoints =
+        np.ascontiguousarray(D[:,:2]).reshape((N,1,2))
+   -   The methods @ref SOLVEPNP_DLS and @ref SOLVEPNP_UPNP cannot be used as the current implementations are
+       unstable and sometimes give completely wrong results. If you pass one of these two
+       flags, @ref SOLVEPNP_EPNP method will be used instead.
+   -   The minimum number of points is 4 in the general case. In the case of @ref SOLVEPNP_P3P and @ref SOLVEPNP_AP3P
+       methods, it is required to use exactly 4 points (the first 3 points are used to estimate all the solutions
+       of the P3P problem, the last one is used to retain the best solution that minimizes the reprojection error).
+   -   With @ref SOLVEPNP_ITERATIVE method and `useExtrinsicGuess=true`, the minimum number of points is 3 (3 points
+       are sufficient to compute a pose but there are up to 4 solutions). The initial solution should be close to the
+       global solution to converge.
+   -   With @ref SOLVEPNP_IPPE input points must be >= 4 and object points must be coplanar.
+   -   With @ref SOLVEPNP_IPPE_SQUARE this is a special case suitable for marker pose estimation.
+       Number of input points must be 4. Object points must be defined in the following order:
+         - point 0: [-squareLength / 2,  squareLength / 2, 0]
+         - point 1: [ squareLength / 2,  squareLength / 2, 0]
+         - point 2: [ squareLength / 2, -squareLength / 2, 0]
+         - point 3: [-squareLength / 2, -squareLength / 2, 0]
+ */
+CV_EXPORTS_W int solvePnPGeneric( InputArray objectPoints, InputArray imagePoints,
+                                  InputArray cameraMatrix, InputArray distCoeffs,
+                                  OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
+                                  bool useExtrinsicGuess = false, SolvePnPMethod flags = SOLVEPNP_ITERATIVE,
+                                  InputArray rvec = noArray(), InputArray tvec = noArray(),
+                                  OutputArray reprojectionError = noArray() );
+
+/** @brief Finds an initial camera intrinsic matrix from 3D-2D point correspondences.
+
+@param objectPoints Vector of vectors of the calibration pattern points in the calibration pattern
+coordinate space. In the old interface all the per-view vectors are concatenated. See
+#calibrateCamera for details.
+@param imagePoints Vector of vectors of the projections of the calibration pattern points. In the
+old interface all the per-view vectors are concatenated.
+@param imageSize Image size in pixels used to initialize the principal point.
+@param aspectRatio If it is zero or negative, both \f$f_x\f$ and \f$f_y\f$ are estimated independently.
+Otherwise, \f$f_x = f_y \cdot \texttt{aspectRatio}\f$ .
+
+The function estimates and returns an initial camera intrinsic matrix for the camera calibration process.
+Currently, the function only supports planar calibration patterns, which are patterns where each
+object point has z-coordinate =0.
+ */
+CV_EXPORTS_W Mat initCameraMatrix2D( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints,
+                                     Size imageSize, double aspectRatio = 1.0 );
+
+/** @brief Finds the positions of internal corners of the chessboard.
+
+@param image Source chessboard view. It must be an 8-bit grayscale or color image.
+@param patternSize Number of inner corners per a chessboard row and column
+( patternSize = cv::Size(points_per_row,points_per_colum) = cv::Size(columns,rows) ).
+@param corners Output array of detected corners.
+@param flags Various operation flags that can be zero or a combination of the following values:
+-   @ref CALIB_CB_ADAPTIVE_THRESH Use adaptive thresholding to convert the image to black
+and white, rather than a fixed threshold level (computed from the average image brightness).
+-   @ref CALIB_CB_NORMALIZE_IMAGE Normalize the image gamma with #equalizeHist before
+applying fixed or adaptive thresholding.
+-   @ref CALIB_CB_FILTER_QUADS Use additional criteria (like contour area, perimeter,
+square-like shape) to filter out false quads extracted at the contour retrieval stage.
+-   @ref CALIB_CB_FAST_CHECK Run a fast check on the image that looks for chessboard corners,
+and shortcut the call if none is found. This can drastically speed up the call in the
+degenerate condition when no chessboard is observed.
+-   @ref CALIB_CB_PLAIN All other flags are ignored. The input image is taken as is.
+No image processing is done to improve to find the checkerboard. This has the effect of speeding up the
+execution of the function but could lead to not recognizing the checkerboard if the image
+is not previously binarized in the appropriate manner.
+
+The function attempts to determine whether the input image is a view of the chessboard pattern and
+locate the internal chessboard corners. The function returns a non-zero value if all of the corners
+are found and they are placed in a certain order (row by row, left to right in every row).
+Otherwise, if the function fails to find all the corners or reorder them, it returns 0. For example,
+a regular chessboard has 8 x 8 squares and 7 x 7 internal corners, that is, points where the black
+squares touch each other. The detected coordinates are approximate, and to determine their positions
+more accurately, the function calls #cornerSubPix. You also may use the function #cornerSubPix with
+different parameters if returned coordinates are not accurate enough.
+
+Sample usage of detecting and drawing chessboard corners: :
+@code
+    Size patternsize(8,6); //interior number of corners
+    Mat gray = ....; //source image
+    vector<Point2f> corners; //this will be filled by the detected corners
+
+    //CALIB_CB_FAST_CHECK saves a lot of time on images
+    //that do not contain any chessboard corners
+    bool patternfound = findChessboardCorners(gray, patternsize, corners,
+            CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE
+            + CALIB_CB_FAST_CHECK);
+
+    if(patternfound)
+      cornerSubPix(gray, corners, Size(11, 11), Size(-1, -1),
+        TermCriteria(CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 30, 0.1));
+
+    drawChessboardCorners(img, patternsize, Mat(corners), patternfound);
+@endcode
+@note The function requires white space (like a square-thick border, the wider the better) around
+the board to make the detection more robust in various environments. Otherwise, if there is no
+border and the background is dark, the outer black squares cannot be segmented properly and so the
+square grouping and ordering algorithm fails.
+
+Use gen_pattern.py (@ref tutorial_camera_calibration_pattern) to create checkerboard.
+ */
+CV_EXPORTS_W bool findChessboardCorners( InputArray image, Size patternSize, OutputArray corners,
+                                         int flags = CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE );
+
+/*
+   Checks whether the image contains chessboard of the specific size or not.
+   If yes, nonzero value is returned.
+*/
+CV_EXPORTS_W bool checkChessboard(InputArray img, Size size);
+
+/** @brief Finds the positions of internal corners of the chessboard using a sector based approach.
+
+@param image Source chessboard view. It must be an 8-bit grayscale or color image.
+@param patternSize Number of inner corners per a chessboard row and column
+( patternSize = cv::Size(points_per_row,points_per_colum) = cv::Size(columns,rows) ).
+@param corners Output array of detected corners.
+@param flags Various operation flags that can be zero or a combination of the following values:
+-   @ref CALIB_CB_NORMALIZE_IMAGE Normalize the image gamma with equalizeHist before detection.
+-   @ref CALIB_CB_EXHAUSTIVE Run an exhaustive search to improve detection rate.
+-   @ref CALIB_CB_ACCURACY Up sample input image to improve sub-pixel accuracy due to aliasing effects.
+-   @ref CALIB_CB_LARGER The detected pattern is allowed to be larger than patternSize (see description).
+-   @ref CALIB_CB_MARKER The detected pattern must have a marker (see description).
+This should be used if an accurate camera calibration is required.
+@param meta Optional output arrray of detected corners (CV_8UC1 and size = cv::Size(columns,rows)).
+Each entry stands for one corner of the pattern and can have one of the following values:
+-   0 = no meta data attached
+-   1 = left-top corner of a black cell
+-   2 = left-top corner of a white cell
+-   3 = left-top corner of a black cell with a white marker dot
+-   4 = left-top corner of a white cell with a black marker dot (pattern origin in case of markers otherwise first corner)
+
+The function is analog to #findChessboardCorners but uses a localized radon
+transformation approximated by box filters being more robust to all sort of
+noise, faster on larger images and is able to directly return the sub-pixel
+position of the internal chessboard corners. The Method is based on the paper
+@cite duda2018 "Accurate Detection and Localization of Checkerboard Corners for
+Calibration" demonstrating that the returned sub-pixel positions are more
+accurate than the one returned by cornerSubPix allowing a precise camera
+calibration for demanding applications.
+
+In the case, the flags @ref CALIB_CB_LARGER or @ref CALIB_CB_MARKER are given,
+the result can be recovered from the optional meta array. Both flags are
+helpful to use calibration patterns exceeding the field of view of the camera.
+These oversized patterns allow more accurate calibrations as corners can be
+utilized, which are as close as possible to the image borders.  For a
+consistent coordinate system across all images, the optional marker (see image
+below) can be used to move the origin of the board to the location where the
+black circle is located.
+
+@note The function requires a white boarder with roughly the same width as one
+of the checkerboard fields around the whole board to improve the detection in
+various environments. In addition, because of the localized radon
+transformation it is beneficial to use round corners for the field corners
+which are located on the outside of the board. The following figure illustrates
+a sample checkerboard optimized for the detection. However, any other checkerboard
+can be used as well.
+
+Use gen_pattern.py (@ref tutorial_camera_calibration_pattern) to create checkerboard.
+![Checkerboard](pics/checkerboard_radon.png)
+ */
+CV_EXPORTS_AS(findChessboardCornersSBWithMeta)
+bool findChessboardCornersSB(InputArray image,Size patternSize, OutputArray corners,
+                             int flags,OutputArray meta);
+/** @overload */
+CV_EXPORTS_W inline
+bool findChessboardCornersSB(InputArray image, Size patternSize, OutputArray corners,
+                             int flags = 0)
+{
+    return findChessboardCornersSB(image, patternSize, corners, flags, noArray());
+}
+
+/** @brief Estimates the sharpness of a detected chessboard.
+
+Image sharpness, as well as brightness, are a critical parameter for accuracte
+camera calibration. For accessing these parameters for filtering out
+problematic calibraiton images, this method calculates edge profiles by traveling from
+black to white chessboard cell centers. Based on this, the number of pixels is
+calculated required to transit from black to white. This width of the
+transition area is a good indication of how sharp the chessboard is imaged
+and should be below ~3.0 pixels.
+
+@param image Gray image used to find chessboard corners
+@param patternSize Size of a found chessboard pattern
+@param corners Corners found by #findChessboardCornersSB
+@param rise_distance Rise distance 0.8 means 10% ... 90% of the final signal strength
+@param vertical By default edge responses for horizontal lines are calculated
+@param sharpness Optional output array with a sharpness value for calculated edge responses (see description)
+
+The optional sharpness array is of type CV_32FC1 and has for each calculated
+profile one row with the following five entries:
+* 0 = x coordinate of the underlying edge in the image
+* 1 = y coordinate of the underlying edge in the image
+* 2 = width of the transition area (sharpness)
+* 3 = signal strength in the black cell (min brightness)
+* 4 = signal strength in the white cell (max brightness)
+
+@return Scalar(average sharpness, average min brightness, average max brightness,0)
+*/
+CV_EXPORTS_W Scalar estimateChessboardSharpness(InputArray image, Size patternSize, InputArray corners,
+                                                float rise_distance=0.8F,bool vertical=false,
+                                                OutputArray sharpness=noArray());
+
+
+//! finds subpixel-accurate positions of the chessboard corners
+CV_EXPORTS_W bool find4QuadCornerSubpix( InputArray img, InputOutputArray corners, Size region_size );
+
+/** @brief Renders the detected chessboard corners.
+
+@param image Destination image. It must be an 8-bit color image.
+@param patternSize Number of inner corners per a chessboard row and column
+(patternSize = cv::Size(points_per_row,points_per_column)).
+@param corners Array of detected corners, the output of #findChessboardCorners.
+@param patternWasFound Parameter indicating whether the complete board was found or not. The
+return value of #findChessboardCorners should be passed here.
+
+The function draws individual chessboard corners detected either as red circles if the board was not
+found, or as colored corners connected with lines if the board was found.
+ */
+CV_EXPORTS_W void drawChessboardCorners( InputOutputArray image, Size patternSize,
+                                         InputArray corners, bool patternWasFound );
+
+/** @brief Draw axes of the world/object coordinate system from pose estimation. @sa solvePnP
+
+@param image Input/output image. It must have 1 or 3 channels. The number of channels is not altered.
+@param cameraMatrix Input 3x3 floating-point matrix of camera intrinsic parameters.
+\f$\cameramatrix{A}\f$
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is empty, the zero distortion coefficients are assumed.
+@param rvec Rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+the model coordinate system to the camera coordinate system.
+@param tvec Translation vector.
+@param length Length of the painted axes in the same unit than tvec (usually in meters).
+@param thickness Line thickness of the painted axes.
+
+This function draws the axes of the world/object coordinate system w.r.t. to the camera frame.
+OX is drawn in red, OY in green and OZ in blue.
+ */
+CV_EXPORTS_W void drawFrameAxes(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs,
+                                InputArray rvec, InputArray tvec, float length, int thickness=3);
+
+struct CV_EXPORTS_W_SIMPLE CirclesGridFinderParameters
+{
+    CV_WRAP CirclesGridFinderParameters();
+    CV_PROP_RW cv::Size2f densityNeighborhoodSize;
+    CV_PROP_RW float minDensity;
+    CV_PROP_RW int kmeansAttempts;
+    CV_PROP_RW int minDistanceToAddKeypoint;
+    CV_PROP_RW int keypointScale;
+    CV_PROP_RW float minGraphConfidence;
+    CV_PROP_RW float vertexGain;
+    CV_PROP_RW float vertexPenalty;
+    CV_PROP_RW float existingVertexGain;
+    CV_PROP_RW float edgeGain;
+    CV_PROP_RW float edgePenalty;
+    CV_PROP_RW float convexHullFactor;
+    CV_PROP_RW float minRNGEdgeSwitchDist;
+
+    enum GridType
+    {
+      SYMMETRIC_GRID, ASYMMETRIC_GRID
+    };
+    GridType gridType;
+
+    CV_PROP_RW float squareSize; //!< Distance between two adjacent points. Used by CALIB_CB_CLUSTERING.
+    CV_PROP_RW float maxRectifiedDistance; //!< Max deviation from prediction. Used by CALIB_CB_CLUSTERING.
+};
+
+#ifndef DISABLE_OPENCV_3_COMPATIBILITY
+typedef CirclesGridFinderParameters CirclesGridFinderParameters2;
+#endif
+
+/** @brief Finds centers in the grid of circles.
+
+@param image grid view of input circles; it must be an 8-bit grayscale or color image.
+@param patternSize number of circles per row and column
+( patternSize = Size(points_per_row, points_per_colum) ).
+@param centers output array of detected centers.
+@param flags various operation flags that can be one of the following values:
+-   @ref CALIB_CB_SYMMETRIC_GRID uses symmetric pattern of circles.
+-   @ref CALIB_CB_ASYMMETRIC_GRID uses asymmetric pattern of circles.
+-   @ref CALIB_CB_CLUSTERING uses a special algorithm for grid detection. It is more robust to
+perspective distortions but much more sensitive to background clutter.
+@param blobDetector feature detector that finds blobs like dark circles on light background.
+                    If `blobDetector` is NULL then `image` represents Point2f array of candidates.
+@param parameters struct for finding circles in a grid pattern.
+
+The function attempts to determine whether the input image contains a grid of circles. If it is, the
+function locates centers of the circles. The function returns a non-zero value if all of the centers
+have been found and they have been placed in a certain order (row by row, left to right in every
+row). Otherwise, if the function fails to find all the corners or reorder them, it returns 0.
+
+Sample usage of detecting and drawing the centers of circles: :
+@code
+    Size patternsize(7,7); //number of centers
+    Mat gray = ...; //source image
+    vector<Point2f> centers; //this will be filled by the detected centers
+
+    bool patternfound = findCirclesGrid(gray, patternsize, centers);
+
+    drawChessboardCorners(img, patternsize, Mat(centers), patternfound);
+@endcode
+@note The function requires white space (like a square-thick border, the wider the better) around
+the board to make the detection more robust in various environments.
+ */
+CV_EXPORTS_W bool findCirclesGrid( InputArray image, Size patternSize,
+                                   OutputArray centers, int flags,
+                                   const Ptr<FeatureDetector> &blobDetector,
+                                   const CirclesGridFinderParameters& parameters);
+
+/** @overload */
+CV_EXPORTS_W bool findCirclesGrid( InputArray image, Size patternSize,
+                                   OutputArray centers, int flags = CALIB_CB_SYMMETRIC_GRID,
+                                   const Ptr<FeatureDetector> &blobDetector = SimpleBlobDetector::create());
+
+/** @brief Finds the camera intrinsic and extrinsic parameters from several views of a calibration
+pattern.
+
+@param objectPoints In the new interface it is a vector of vectors of calibration pattern points in
+the calibration pattern coordinate space (e.g. std::vector<std::vector<cv::Vec3f>>). The outer
+vector contains as many elements as the number of pattern views. If the same calibration pattern
+is shown in each view and it is fully visible, all the vectors will be the same. Although, it is
+possible to use partially occluded patterns or even different patterns in different views. Then,
+the vectors will be different. Although the points are 3D, they all lie in the calibration pattern's
+XY coordinate plane (thus 0 in the Z-coordinate), if the used calibration pattern is a planar rig.
+In the old interface all the vectors of object points from different views are concatenated
+together.
+@param imagePoints In the new interface it is a vector of vectors of the projections of calibration
+pattern points (e.g. std::vector<std::vector<cv::Vec2f>>). imagePoints.size() and
+objectPoints.size(), and imagePoints[i].size() and objectPoints[i].size() for each i, must be equal,
+respectively. In the old interface all the vectors of object points from different views are
+concatenated together.
+@param imageSize Size of the image used only to initialize the camera intrinsic matrix.
+@param cameraMatrix Input/output 3x3 floating-point camera intrinsic matrix
+\f$\cameramatrix{A}\f$ . If @ref CALIB_USE_INTRINSIC_GUESS
+and/or @ref CALIB_FIX_ASPECT_RATIO, @ref CALIB_FIX_PRINCIPAL_POINT or @ref CALIB_FIX_FOCAL_LENGTH
+are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
+@param distCoeffs Input/output vector of distortion coefficients
+\f$\distcoeffs\f$.
+@param rvecs Output vector of rotation vectors (@ref Rodrigues ) estimated for each pattern view
+(e.g. std::vector<cv::Mat>>). That is, each i-th rotation vector together with the corresponding
+i-th translation vector (see the next output parameter description) brings the calibration pattern
+from the object coordinate space (in which object points are specified) to the camera coordinate
+space. In more technical terms, the tuple of the i-th rotation and translation vector performs
+a change of basis from object coordinate space to camera coordinate space. Due to its duality, this
+tuple is equivalent to the position of the calibration pattern with respect to the camera coordinate
+space.
+@param tvecs Output vector of translation vectors estimated for each pattern view, see parameter
+describtion above.
+@param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic
+parameters. Order of deviations values:
+\f$(f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
+ s_4, \tau_x, \tau_y)\f$ If one of parameters is not estimated, it's deviation is equals to zero.
+@param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic
+parameters. Order of deviations values: \f$(R_0, T_0, \dotsc , R_{M - 1}, T_{M - 1})\f$ where M is
+the number of pattern views. \f$R_i, T_i\f$ are concatenated 1x3 vectors.
+ @param perViewErrors Output vector of the RMS re-projection error estimated for each pattern view.
+@param flags Different flags that may be zero or a combination of the following values:
+-   @ref CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of
+fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image
+center ( imageSize is used), and focal distances are computed in a least-squares fashion.
+Note, that if intrinsic parameters are known, there is no need to use this function just to
+estimate extrinsic parameters. Use @ref solvePnP instead.
+-   @ref CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global
+optimization. It stays at the center or at a different location specified when
+ @ref CALIB_USE_INTRINSIC_GUESS is set too.
+-   @ref CALIB_FIX_ASPECT_RATIO The functions consider only fy as a free parameter. The
+ratio fx/fy stays the same as in the input cameraMatrix . When
+ @ref CALIB_USE_INTRINSIC_GUESS is not set, the actual input values of fx and fy are
+ignored, only their ratio is computed and used further.
+-   @ref CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \f$(p_1, p_2)\f$ are set
+to zeros and stay zero.
+-   @ref CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if
+ @ref CALIB_USE_INTRINSIC_GUESS is set.
+-   @ref CALIB_FIX_K1,..., @ref CALIB_FIX_K6 The corresponding radial distortion
+coefficient is not changed during the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is
+set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
+-   @ref CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the
+backward compatibility, this extra flag should be explicitly specified to make the
+calibration function use the rational model and return 8 coefficients or more.
+-   @ref CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the
+backward compatibility, this extra flag should be explicitly specified to make the
+calibration function use the thin prism model and return 12 coefficients or more.
+-   @ref CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during
+the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the
+supplied distCoeffs matrix is used. Otherwise, it is set to 0.
+-   @ref CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the
+backward compatibility, this extra flag should be explicitly specified to make the
+calibration function use the tilted sensor model and return 14 coefficients.
+-   @ref CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during
+the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the
+supplied distCoeffs matrix is used. Otherwise, it is set to 0.
+@param criteria Termination criteria for the iterative optimization algorithm.
+
+@return the overall RMS re-projection error.
+
+The function estimates the intrinsic camera parameters and extrinsic parameters for each of the
+views. The algorithm is based on @cite Zhang2000 and @cite BouguetMCT . The coordinates of 3D object
+points and their corresponding 2D projections in each view must be specified. That may be achieved
+by using an object with known geometry and easily detectable feature points. Such an object is
+called a calibration rig or calibration pattern, and OpenCV has built-in support for a chessboard as
+a calibration rig (see @ref findChessboardCorners). Currently, initialization of intrinsic
+parameters (when @ref CALIB_USE_INTRINSIC_GUESS is not set) is only implemented for planar calibration
+patterns (where Z-coordinates of the object points must be all zeros). 3D calibration rigs can also
+be used as long as initial cameraMatrix is provided.
+
+The algorithm performs the following steps:
+
+-   Compute the initial intrinsic parameters (the option only available for planar calibration
+    patterns) or read them from the input parameters. The distortion coefficients are all set to
+    zeros initially unless some of CALIB_FIX_K? are specified.
+
+-   Estimate the initial camera pose as if the intrinsic parameters have been already known. This is
+    done using @ref solvePnP .
+
+-   Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error,
+    that is, the total sum of squared distances between the observed feature points imagePoints and
+    the projected (using the current estimates for camera parameters and the poses) object points
+    objectPoints. See @ref projectPoints for details.
+
+@note
+    If you use a non-square (i.e. non-N-by-N) grid and @ref findChessboardCorners for calibration,
+    and @ref calibrateCamera returns bad values (zero distortion coefficients, \f$c_x\f$ and
+    \f$c_y\f$ very far from the image center, and/or large differences between \f$f_x\f$ and
+    \f$f_y\f$ (ratios of 10:1 or more)), then you are probably using patternSize=cvSize(rows,cols)
+    instead of using patternSize=cvSize(cols,rows) in @ref findChessboardCorners.
+
+@note
+    The function may throw exceptions, if unsupported combination of parameters is provided or
+    the system is underconstrained.
+
+@sa
+   calibrateCameraRO, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate,
+   undistort
+ */
+CV_EXPORTS_AS(calibrateCameraExtended) double calibrateCamera( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints, Size imageSize,
+                                     InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
+                                     OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
+                                     OutputArray stdDeviationsIntrinsics,
+                                     OutputArray stdDeviationsExtrinsics,
+                                     OutputArray perViewErrors,
+                                     int flags = 0, TermCriteria criteria = TermCriteria(
+                                        TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
+
+/** @overload */
+CV_EXPORTS_W double calibrateCamera( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints, Size imageSize,
+                                     InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
+                                     OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
+                                     int flags = 0, TermCriteria criteria = TermCriteria(
+                                        TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
+
+/** @brief Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
+
+This function is an extension of #calibrateCamera with the method of releasing object which was
+proposed in @cite strobl2011iccv. In many common cases with inaccurate, unmeasured, roughly planar
+targets (calibration plates), this method can dramatically improve the precision of the estimated
+camera parameters. Both the object-releasing method and standard method are supported by this
+function. Use the parameter **iFixedPoint** for method selection. In the internal implementation,
+#calibrateCamera is a wrapper for this function.
+
+@param objectPoints Vector of vectors of calibration pattern points in the calibration pattern
+coordinate space. See #calibrateCamera for details. If the method of releasing object to be used,
+the identical calibration board must be used in each view and it must be fully visible, and all
+objectPoints[i] must be the same and all points should be roughly close to a plane. **The calibration
+target has to be rigid, or at least static if the camera (rather than the calibration target) is
+shifted for grabbing images.**
+@param imagePoints Vector of vectors of the projections of calibration pattern points. See
+#calibrateCamera for details.
+@param imageSize Size of the image used only to initialize the intrinsic camera matrix.
+@param iFixedPoint The index of the 3D object point in objectPoints[0] to be fixed. It also acts as
+a switch for calibration method selection. If object-releasing method to be used, pass in the
+parameter in the range of [1, objectPoints[0].size()-2], otherwise a value out of this range will
+make standard calibration method selected. Usually the top-right corner point of the calibration
+board grid is recommended to be fixed when object-releasing method being utilized. According to
+\cite strobl2011iccv, two other points are also fixed. In this implementation, objectPoints[0].front
+and objectPoints[0].back.z are used. With object-releasing method, accurate rvecs, tvecs and
+newObjPoints are only possible if coordinates of these three fixed points are accurate enough.
+@param cameraMatrix Output 3x3 floating-point camera matrix. See #calibrateCamera for details.
+@param distCoeffs Output vector of distortion coefficients. See #calibrateCamera for details.
+@param rvecs Output vector of rotation vectors estimated for each pattern view. See #calibrateCamera
+for details.
+@param tvecs Output vector of translation vectors estimated for each pattern view.
+@param newObjPoints The updated output vector of calibration pattern points. The coordinates might
+be scaled based on three fixed points. The returned coordinates are accurate only if the above
+mentioned three fixed points are accurate. If not needed, noArray() can be passed in. This parameter
+is ignored with standard calibration method.
+@param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
+See #calibrateCamera for details.
+@param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
+See #calibrateCamera for details.
+@param stdDeviationsObjPoints Output vector of standard deviations estimated for refined coordinates
+of calibration pattern points. It has the same size and order as objectPoints[0] vector. This
+parameter is ignored with standard calibration method.
+ @param perViewErrors Output vector of the RMS re-projection error estimated for each pattern view.
+@param flags Different flags that may be zero or a combination of some predefined values. See
+#calibrateCamera for details. If the method of releasing object is used, the calibration time may
+be much longer. CALIB_USE_QR or CALIB_USE_LU could be used for faster calibration with potentially
+less precise and less stable in some rare cases.
+@param criteria Termination criteria for the iterative optimization algorithm.
+
+@return the overall RMS re-projection error.
+
+The function estimates the intrinsic camera parameters and extrinsic parameters for each of the
+views. The algorithm is based on @cite Zhang2000, @cite BouguetMCT and @cite strobl2011iccv. See
+#calibrateCamera for other detailed explanations.
+@sa
+   calibrateCamera, findChessboardCorners, solvePnP, initCameraMatrix2D, stereoCalibrate, undistort
+ */
+CV_EXPORTS_AS(calibrateCameraROExtended) double calibrateCameraRO( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints, Size imageSize, int iFixedPoint,
+                                     InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
+                                     OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
+                                     OutputArray newObjPoints,
+                                     OutputArray stdDeviationsIntrinsics,
+                                     OutputArray stdDeviationsExtrinsics,
+                                     OutputArray stdDeviationsObjPoints,
+                                     OutputArray perViewErrors,
+                                     int flags = 0, TermCriteria criteria = TermCriteria(
+                                        TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
+
+/** @overload */
+CV_EXPORTS_W double calibrateCameraRO( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints, Size imageSize, int iFixedPoint,
+                                     InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
+                                     OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
+                                     OutputArray newObjPoints,
+                                     int flags = 0, TermCriteria criteria = TermCriteria(
+                                        TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
+
+/** @brief Computes useful camera characteristics from the camera intrinsic matrix.
+
+@param cameraMatrix Input camera intrinsic matrix that can be estimated by #calibrateCamera or
+#stereoCalibrate .
+@param imageSize Input image size in pixels.
+@param apertureWidth Physical width in mm of the sensor.
+@param apertureHeight Physical height in mm of the sensor.
+@param fovx Output field of view in degrees along the horizontal sensor axis.
+@param fovy Output field of view in degrees along the vertical sensor axis.
+@param focalLength Focal length of the lens in mm.
+@param principalPoint Principal point in mm.
+@param aspectRatio \f$f_y/f_x\f$
+
+The function computes various useful camera characteristics from the previously estimated camera
+matrix.
+
+@note
+   Do keep in mind that the unity measure 'mm' stands for whatever unit of measure one chooses for
+    the chessboard pitch (it can thus be any value).
+ */
+CV_EXPORTS_W void calibrationMatrixValues( InputArray cameraMatrix, Size imageSize,
+                                           double apertureWidth, double apertureHeight,
+                                           CV_OUT double& fovx, CV_OUT double& fovy,
+                                           CV_OUT double& focalLength, CV_OUT Point2d& principalPoint,
+                                           CV_OUT double& aspectRatio );
+
+/** @brief Calibrates a stereo camera set up. This function finds the intrinsic parameters
+for each of the two cameras and the extrinsic parameters between the two cameras.
+
+@param objectPoints Vector of vectors of the calibration pattern points. The same structure as
+in @ref calibrateCamera. For each pattern view, both cameras need to see the same object
+points. Therefore, objectPoints.size(), imagePoints1.size(), and imagePoints2.size() need to be
+equal as well as objectPoints[i].size(), imagePoints1[i].size(), and imagePoints2[i].size() need to
+be equal for each i.
+@param imagePoints1 Vector of vectors of the projections of the calibration pattern points,
+observed by the first camera. The same structure as in @ref calibrateCamera.
+@param imagePoints2 Vector of vectors of the projections of the calibration pattern points,
+observed by the second camera. The same structure as in @ref calibrateCamera.
+@param cameraMatrix1 Input/output camera intrinsic matrix for the first camera, the same as in
+@ref calibrateCamera. Furthermore, for the stereo case, additional flags may be used, see below.
+@param distCoeffs1 Input/output vector of distortion coefficients, the same as in
+@ref calibrateCamera.
+@param cameraMatrix2 Input/output second camera intrinsic matrix for the second camera. See description for
+cameraMatrix1.
+@param distCoeffs2 Input/output lens distortion coefficients for the second camera. See
+description for distCoeffs1.
+@param imageSize Size of the image used only to initialize the camera intrinsic matrices.
+@param R Output rotation matrix. Together with the translation vector T, this matrix brings
+points given in the first camera's coordinate system to points in the second camera's
+coordinate system. In more technical terms, the tuple of R and T performs a change of basis
+from the first camera's coordinate system to the second camera's coordinate system. Due to its
+duality, this tuple is equivalent to the position of the first camera with respect to the
+second camera coordinate system.
+@param T Output translation vector, see description above.
+@param E Output essential matrix.
+@param F Output fundamental matrix.
+@param rvecs Output vector of rotation vectors ( @ref Rodrigues ) estimated for each pattern view in the
+coordinate system of the first camera of the stereo pair (e.g. std::vector<cv::Mat>). More in detail, each
+i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter
+description) brings the calibration pattern from the object coordinate space (in which object points are
+specified) to the camera coordinate space of the first camera of the stereo pair. In more technical terms,
+the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space
+to camera coordinate space of the first camera of the stereo pair.
+@param tvecs Output vector of translation vectors estimated for each pattern view, see parameter description
+of previous output parameter ( rvecs ).
+@param perViewErrors Output vector of the RMS re-projection error estimated for each pattern view.
+@param flags Different flags that may be zero or a combination of the following values:
+-   @ref CALIB_FIX_INTRINSIC Fix cameraMatrix? and distCoeffs? so that only R, T, E, and F
+matrices are estimated.
+-   @ref CALIB_USE_INTRINSIC_GUESS Optimize some or all of the intrinsic parameters
+according to the specified flags. Initial values are provided by the user.
+-   @ref CALIB_USE_EXTRINSIC_GUESS R and T contain valid initial values that are optimized further.
+Otherwise R and T are initialized to the median value of the pattern views (each dimension separately).
+-   @ref CALIB_FIX_PRINCIPAL_POINT Fix the principal points during the optimization.
+-   @ref CALIB_FIX_FOCAL_LENGTH Fix \f$f^{(j)}_x\f$ and \f$f^{(j)}_y\f$ .
+-   @ref CALIB_FIX_ASPECT_RATIO Optimize \f$f^{(j)}_y\f$ . Fix the ratio \f$f^{(j)}_x/f^{(j)}_y\f$
+.
+-   @ref CALIB_SAME_FOCAL_LENGTH Enforce \f$f^{(0)}_x=f^{(1)}_x\f$ and \f$f^{(0)}_y=f^{(1)}_y\f$ .
+-   @ref CALIB_ZERO_TANGENT_DIST Set tangential distortion coefficients for each camera to
+zeros and fix there.
+-   @ref CALIB_FIX_K1,..., @ref CALIB_FIX_K6 Do not change the corresponding radial
+distortion coefficient during the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is set,
+the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
+-   @ref CALIB_RATIONAL_MODEL Enable coefficients k4, k5, and k6. To provide the backward
+compatibility, this extra flag should be explicitly specified to make the calibration
+function use the rational model and return 8 coefficients. If the flag is not set, the
+function computes and returns only 5 distortion coefficients.
+-   @ref CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the
+backward compatibility, this extra flag should be explicitly specified to make the
+calibration function use the thin prism model and return 12 coefficients. If the flag is not
+set, the function computes and returns only 5 distortion coefficients.
+-   @ref CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during
+the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the
+supplied distCoeffs matrix is used. Otherwise, it is set to 0.
+-   @ref CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the
+backward compatibility, this extra flag should be explicitly specified to make the
+calibration function use the tilted sensor model and return 14 coefficients. If the flag is not
+set, the function computes and returns only 5 distortion coefficients.
+-   @ref CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during
+the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the
+supplied distCoeffs matrix is used. Otherwise, it is set to 0.
+@param criteria Termination criteria for the iterative optimization algorithm.
+
+The function estimates the transformation between two cameras making a stereo pair. If one computes
+the poses of an object relative to the first camera and to the second camera,
+( \f$R_1\f$,\f$T_1\f$ ) and (\f$R_2\f$,\f$T_2\f$), respectively, for a stereo camera where the
+relative position and orientation between the two cameras are fixed, then those poses definitely
+relate to each other. This means, if the relative position and orientation (\f$R\f$,\f$T\f$) of the
+two cameras is known, it is possible to compute (\f$R_2\f$,\f$T_2\f$) when (\f$R_1\f$,\f$T_1\f$) is
+given. This is what the described function does. It computes (\f$R\f$,\f$T\f$) such that:
+
+\f[R_2=R R_1\f]
+\f[T_2=R T_1 + T.\f]
+
+Therefore, one can compute the coordinate representation of a 3D point for the second camera's
+coordinate system when given the point's coordinate representation in the first camera's coordinate
+system:
+
+\f[\begin{bmatrix}
+X_2 \\
+Y_2 \\
+Z_2 \\
+1
+\end{bmatrix} = \begin{bmatrix}
+R & T \\
+0 & 1
+\end{bmatrix} \begin{bmatrix}
+X_1 \\
+Y_1 \\
+Z_1 \\
+1
+\end{bmatrix}.\f]
+
+
+Optionally, it computes the essential matrix E:
+
+\f[E= \vecthreethree{0}{-T_2}{T_1}{T_2}{0}{-T_0}{-T_1}{T_0}{0} R\f]
+
+where \f$T_i\f$ are components of the translation vector \f$T\f$ : \f$T=[T_0, T_1, T_2]^T\f$ .
+And the function can also compute the fundamental matrix F:
+
+\f[F = cameraMatrix2^{-T}\cdot E \cdot cameraMatrix1^{-1}\f]
+
+Besides the stereo-related information, the function can also perform a full calibration of each of
+the two cameras. However, due to the high dimensionality of the parameter space and noise in the
+input data, the function can diverge from the correct solution. If the intrinsic parameters can be
+estimated with high accuracy for each of the cameras individually (for example, using
+#calibrateCamera ), you are recommended to do so and then pass @ref CALIB_FIX_INTRINSIC flag to the
+function along with the computed intrinsic parameters. Otherwise, if all the parameters are
+estimated at once, it makes sense to restrict some parameters, for example, pass
+ @ref CALIB_SAME_FOCAL_LENGTH and @ref CALIB_ZERO_TANGENT_DIST flags, which is usually a
+reasonable assumption.
+
+Similarly to #calibrateCamera, the function minimizes the total re-projection error for all the
+points in all the available views from both cameras. The function returns the final value of the
+re-projection error.
+ */
+CV_EXPORTS_AS(stereoCalibrateExtended) double stereoCalibrate( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
+                                     InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1,
+                                     InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2,
+                                     Size imageSize, InputOutputArray R, InputOutputArray T, OutputArray E, OutputArray F,
+                                     OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, OutputArray perViewErrors, int flags = CALIB_FIX_INTRINSIC,
+                                     TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) );
+
+/// @overload
+CV_EXPORTS_W double stereoCalibrate( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
+                                     InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1,
+                                     InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2,
+                                     Size imageSize, OutputArray R,OutputArray T, OutputArray E, OutputArray F,
+                                     int flags = CALIB_FIX_INTRINSIC,
+                                     TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) );
+
+/// @overload
+CV_EXPORTS_W double stereoCalibrate( InputArrayOfArrays objectPoints,
+                                     InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
+                                     InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1,
+                                     InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2,
+                                     Size imageSize, InputOutputArray R, InputOutputArray T, OutputArray E, OutputArray F,
+                                     OutputArray perViewErrors, int flags = CALIB_FIX_INTRINSIC,
+                                     TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) );
+
+/** @brief Computes rectification transforms for each head of a calibrated stereo camera.
+
+@param cameraMatrix1 First camera intrinsic matrix.
+@param distCoeffs1 First camera distortion parameters.
+@param cameraMatrix2 Second camera intrinsic matrix.
+@param distCoeffs2 Second camera distortion parameters.
+@param imageSize Size of the image used for stereo calibration.
+@param R Rotation matrix from the coordinate system of the first camera to the second camera,
+see @ref stereoCalibrate.
+@param T Translation vector from the coordinate system of the first camera to the second camera,
+see @ref stereoCalibrate.
+@param R1 Output 3x3 rectification transform (rotation matrix) for the first camera. This matrix
+brings points given in the unrectified first camera's coordinate system to points in the rectified
+first camera's coordinate system. In more technical terms, it performs a change of basis from the
+unrectified first camera's coordinate system to the rectified first camera's coordinate system.
+@param R2 Output 3x3 rectification transform (rotation matrix) for the second camera. This matrix
+brings points given in the unrectified second camera's coordinate system to points in the rectified
+second camera's coordinate system. In more technical terms, it performs a change of basis from the
+unrectified second camera's coordinate system to the rectified second camera's coordinate system.
+@param P1 Output 3x4 projection matrix in the new (rectified) coordinate systems for the first
+camera, i.e. it projects points given in the rectified first camera coordinate system into the
+rectified first camera's image.
+@param P2 Output 3x4 projection matrix in the new (rectified) coordinate systems for the second
+camera, i.e. it projects points given in the rectified first camera coordinate system into the
+rectified second camera's image.
+@param Q Output \f$4 \times 4\f$ disparity-to-depth mapping matrix (see @ref reprojectImageTo3D).
+@param flags Operation flags that may be zero or @ref CALIB_ZERO_DISPARITY . If the flag is set,
+the function makes the principal points of each camera have the same pixel coordinates in the
+rectified views. And if the flag is not set, the function may still shift the images in the
+horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the
+useful image area.
+@param alpha Free scaling parameter. If it is -1 or absent, the function performs the default
+scaling. Otherwise, the parameter should be between 0 and 1. alpha=0 means that the rectified
+images are zoomed and shifted so that only valid pixels are visible (no black areas after
+rectification). alpha=1 means that the rectified image is decimated and shifted so that all the
+pixels from the original images from the cameras are retained in the rectified images (no source
+image pixels are lost). Any intermediate value yields an intermediate result between
+those two extreme cases.
+@param newImageSize New image resolution after rectification. The same size should be passed to
+#initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0)
+is passed (default), it is set to the original imageSize . Setting it to a larger value can help you
+preserve details in the original image, especially when there is a big radial distortion.
+@param validPixROI1 Optional output rectangles inside the rectified images where all the pixels
+are valid. If alpha=0 , the ROIs cover the whole images. Otherwise, they are likely to be smaller
+(see the picture below).
+@param validPixROI2 Optional output rectangles inside the rectified images where all the pixels
+are valid. If alpha=0 , the ROIs cover the whole images. Otherwise, they are likely to be smaller
+(see the picture below).
+
+The function computes the rotation matrices for each camera that (virtually) make both camera image
+planes the same plane. Consequently, this makes all the epipolar lines parallel and thus simplifies
+the dense stereo correspondence problem. The function takes the matrices computed by #stereoCalibrate
+as input. As output, it provides two rotation matrices and also two projection matrices in the new
+coordinates. The function distinguishes the following two cases:
+
+-   **Horizontal stereo**: the first and the second camera views are shifted relative to each other
+    mainly along the x-axis (with possible small vertical shift). In the rectified images, the
+    corresponding epipolar lines in the left and right cameras are horizontal and have the same
+    y-coordinate. P1 and P2 look like:
+
+    \f[\texttt{P1} = \begin{bmatrix}
+                        f & 0 & cx_1 & 0 \\
+                        0 & f & cy & 0 \\
+                        0 & 0 & 1 & 0
+                     \end{bmatrix}\f]
+
+    \f[\texttt{P2} = \begin{bmatrix}
+                        f & 0 & cx_2 & T_x \cdot f \\
+                        0 & f & cy & 0 \\
+                        0 & 0 & 1 & 0
+                     \end{bmatrix} ,\f]
+
+    \f[\texttt{Q} = \begin{bmatrix}
+                        1 & 0 & 0 & -cx_1 \\
+                        0 & 1 & 0 & -cy \\
+                        0 & 0 & 0 & f \\
+                        0 & 0 & -\frac{1}{T_x} & \frac{cx_1 - cx_2}{T_x}
+                    \end{bmatrix} \f]
+
+    where \f$T_x\f$ is a horizontal shift between the cameras and \f$cx_1=cx_2\f$ if
+    @ref CALIB_ZERO_DISPARITY is set.
+
+-   **Vertical stereo**: the first and the second camera views are shifted relative to each other
+    mainly in the vertical direction (and probably a bit in the horizontal direction too). The epipolar
+    lines in the rectified images are vertical and have the same x-coordinate. P1 and P2 look like:
+
+    \f[\texttt{P1} = \begin{bmatrix}
+                        f & 0 & cx & 0 \\
+                        0 & f & cy_1 & 0 \\
+                        0 & 0 & 1 & 0
+                     \end{bmatrix}\f]
+
+    \f[\texttt{P2} = \begin{bmatrix}
+                        f & 0 & cx & 0 \\
+                        0 & f & cy_2 & T_y \cdot f \\
+                        0 & 0 & 1 & 0
+                     \end{bmatrix},\f]
+
+    \f[\texttt{Q} = \begin{bmatrix}
+                        1 & 0 & 0 & -cx \\
+                        0 & 1 & 0 & -cy_1 \\
+                        0 & 0 & 0 & f \\
+                        0 & 0 & -\frac{1}{T_y} & \frac{cy_1 - cy_2}{T_y}
+                    \end{bmatrix} \f]
+
+    where \f$T_y\f$ is a vertical shift between the cameras and \f$cy_1=cy_2\f$ if
+    @ref CALIB_ZERO_DISPARITY is set.
+
+As you can see, the first three columns of P1 and P2 will effectively be the new "rectified" camera
+matrices. The matrices, together with R1 and R2 , can then be passed to #initUndistortRectifyMap to
+initialize the rectification map for each camera.
+
+See below the screenshot from the stereo_calib.cpp sample. Some red horizontal lines pass through
+the corresponding image regions. This means that the images are well rectified, which is what most
+stereo correspondence algorithms rely on. The green rectangles are roi1 and roi2 . You see that
+their interiors are all valid pixels.
+
+![image](pics/stereo_undistort.jpg)
+ */
+CV_EXPORTS_W void stereoRectify( InputArray cameraMatrix1, InputArray distCoeffs1,
+                                 InputArray cameraMatrix2, InputArray distCoeffs2,
+                                 Size imageSize, InputArray R, InputArray T,
+                                 OutputArray R1, OutputArray R2,
+                                 OutputArray P1, OutputArray P2,
+                                 OutputArray Q, int flags = CALIB_ZERO_DISPARITY,
+                                 double alpha = -1, Size newImageSize = Size(),
+                                 CV_OUT Rect* validPixROI1 = 0, CV_OUT Rect* validPixROI2 = 0 );
+
+/** @brief Computes a rectification transform for an uncalibrated stereo camera.
+
+@param points1 Array of feature points in the first image.
+@param points2 The corresponding points in the second image. The same formats as in
+#findFundamentalMat are supported.
+@param F Input fundamental matrix. It can be computed from the same set of point pairs using
+#findFundamentalMat .
+@param imgSize Size of the image.
+@param H1 Output rectification homography matrix for the first image.
+@param H2 Output rectification homography matrix for the second image.
+@param threshold Optional threshold used to filter out the outliers. If the parameter is greater
+than zero, all the point pairs that do not comply with the epipolar geometry (that is, the points
+for which \f$|\texttt{points2[i]}^T \cdot \texttt{F} \cdot \texttt{points1[i]}|>\texttt{threshold}\f$ )
+are rejected prior to computing the homographies. Otherwise, all the points are considered inliers.
+
+The function computes the rectification transformations without knowing intrinsic parameters of the
+cameras and their relative position in the space, which explains the suffix "uncalibrated". Another
+related difference from #stereoRectify is that the function outputs not the rectification
+transformations in the object (3D) space, but the planar perspective transformations encoded by the
+homography matrices H1 and H2 . The function implements the algorithm @cite Hartley99 .
+
+@note
+   While the algorithm does not need to know the intrinsic parameters of the cameras, it heavily
+    depends on the epipolar geometry. Therefore, if the camera lenses have a significant distortion,
+    it would be better to correct it before computing the fundamental matrix and calling this
+    function. For example, distortion coefficients can be estimated for each head of stereo camera
+    separately by using #calibrateCamera . Then, the images can be corrected using #undistort , or
+    just the point coordinates can be corrected with #undistortPoints .
+ */
+CV_EXPORTS_W bool stereoRectifyUncalibrated( InputArray points1, InputArray points2,
+                                             InputArray F, Size imgSize,
+                                             OutputArray H1, OutputArray H2,
+                                             double threshold = 5 );
+
+//! computes the rectification transformations for 3-head camera, where all the heads are on the same line.
+CV_EXPORTS_W float rectify3Collinear( InputArray cameraMatrix1, InputArray distCoeffs1,
+                                      InputArray cameraMatrix2, InputArray distCoeffs2,
+                                      InputArray cameraMatrix3, InputArray distCoeffs3,
+                                      InputArrayOfArrays imgpt1, InputArrayOfArrays imgpt3,
+                                      Size imageSize, InputArray R12, InputArray T12,
+                                      InputArray R13, InputArray T13,
+                                      OutputArray R1, OutputArray R2, OutputArray R3,
+                                      OutputArray P1, OutputArray P2, OutputArray P3,
+                                      OutputArray Q, double alpha, Size newImgSize,
+                                      CV_OUT Rect* roi1, CV_OUT Rect* roi2, int flags );
+
+/** @brief Returns the new camera intrinsic matrix based on the free scaling parameter.
+
+@param cameraMatrix Input camera intrinsic matrix.
+@param distCoeffs Input vector of distortion coefficients
+\f$\distcoeffs\f$. If the vector is NULL/empty, the zero distortion coefficients are
+assumed.
+@param imageSize Original image size.
+@param alpha Free scaling parameter between 0 (when all the pixels in the undistorted image are
+valid) and 1 (when all the source image pixels are retained in the undistorted image). See
+#stereoRectify for details.
+@param newImgSize Image size after rectification. By default, it is set to imageSize .
+@param validPixROI Optional output rectangle that outlines all-good-pixels region in the
+undistorted image. See roi1, roi2 description in #stereoRectify .
+@param centerPrincipalPoint Optional flag that indicates whether in the new camera intrinsic matrix the
+principal point should be at the image center or not. By default, the principal point is chosen to
+best fit a subset of the source image (determined by alpha) to the corrected image.
+@return new_camera_matrix Output new camera intrinsic matrix.
+
+The function computes and returns the optimal new camera intrinsic matrix based on the free scaling parameter.
+By varying this parameter, you may retrieve only sensible pixels alpha=0 , keep all the original
+image pixels if there is valuable information in the corners alpha=1 , or get something in between.
+When alpha\>0 , the undistorted result is likely to have some black pixels corresponding to
+"virtual" pixels outside of the captured distorted image. The original camera intrinsic matrix, distortion
+coefficients, the computed new camera intrinsic matrix, and newImageSize should be passed to
+#initUndistortRectifyMap to produce the maps for #remap .
+ */
+CV_EXPORTS_W Mat getOptimalNewCameraMatrix( InputArray cameraMatrix, InputArray distCoeffs,
+                                            Size imageSize, double alpha, Size newImgSize = Size(),
+                                            CV_OUT Rect* validPixROI = 0,
+                                            bool centerPrincipalPoint = false);
+
+/** @brief Computes Hand-Eye calibration: \f$_{}^{g}\textrm{T}_c\f$
+
+@param[in] R_gripper2base Rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the gripper frame to the robot base frame (\f$_{}^{b}\textrm{T}_g\f$).
+This is a vector (`vector<Mat>`) that contains the rotation, `(3x3)` rotation matrices or `(3x1)` rotation vectors,
+for all the transformations from gripper frame to robot base frame.
+@param[in] t_gripper2base Translation part extracted from the homogeneous matrix that transforms a point
+expressed in the gripper frame to the robot base frame (\f$_{}^{b}\textrm{T}_g\f$).
+This is a vector (`vector<Mat>`) that contains the `(3x1)` translation vectors for all the transformations
+from gripper frame to robot base frame.
+@param[in] R_target2cam Rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the target frame to the camera frame (\f$_{}^{c}\textrm{T}_t\f$).
+This is a vector (`vector<Mat>`) that contains the rotation, `(3x3)` rotation matrices or `(3x1)` rotation vectors,
+for all the transformations from calibration target frame to camera frame.
+@param[in] t_target2cam Rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the target frame to the camera frame (\f$_{}^{c}\textrm{T}_t\f$).
+This is a vector (`vector<Mat>`) that contains the `(3x1)` translation vectors for all the transformations
+from calibration target frame to camera frame.
+@param[out] R_cam2gripper Estimated `(3x3)` rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the camera frame to the gripper frame (\f$_{}^{g}\textrm{T}_c\f$).
+@param[out] t_cam2gripper Estimated `(3x1)` translation part extracted from the homogeneous matrix that transforms a point
+expressed in the camera frame to the gripper frame (\f$_{}^{g}\textrm{T}_c\f$).
+@param[in] method One of the implemented Hand-Eye calibration method, see cv::HandEyeCalibrationMethod
+
+The function performs the Hand-Eye calibration using various methods. One approach consists in estimating the
+rotation then the translation (separable solutions) and the following methods are implemented:
+  - R. Tsai, R. Lenz A New Technique for Fully Autonomous and Efficient 3D Robotics Hand/EyeCalibration \cite Tsai89
+  - F. Park, B. Martin Robot Sensor Calibration: Solving AX = XB on the Euclidean Group \cite Park94
+  - R. Horaud, F. Dornaika Hand-Eye Calibration \cite Horaud95
+
+Another approach consists in estimating simultaneously the rotation and the translation (simultaneous solutions),
+with the following implemented methods:
+  - N. Andreff, R. Horaud, B. Espiau On-line Hand-Eye Calibration \cite Andreff99
+  - K. Daniilidis Hand-Eye Calibration Using Dual Quaternions \cite Daniilidis98
+
+The following picture describes the Hand-Eye calibration problem where the transformation between a camera ("eye")
+mounted on a robot gripper ("hand") has to be estimated. This configuration is called eye-in-hand.
+
+The eye-to-hand configuration consists in a static camera observing a calibration pattern mounted on the robot
+end-effector. The transformation from the camera to the robot base frame can then be estimated by inputting
+the suitable transformations to the function, see below.
+
+![](pics/hand-eye_figure.png)
+
+The calibration procedure is the following:
+  - a static calibration pattern is used to estimate the transformation between the target frame
+  and the camera frame
+  - the robot gripper is moved in order to acquire several poses
+  - for each pose, the homogeneous transformation between the gripper frame and the robot base frame is recorded using for
+  instance the robot kinematics
+\f[
+    \begin{bmatrix}
+    X_b\\
+    Y_b\\
+    Z_b\\
+    1
+    \end{bmatrix}
+    =
+    \begin{bmatrix}
+    _{}^{b}\textrm{R}_g & _{}^{b}\textrm{t}_g \\
+    0_{1 \times 3} & 1
+    \end{bmatrix}
+    \begin{bmatrix}
+    X_g\\
+    Y_g\\
+    Z_g\\
+    1
+    \end{bmatrix}
+\f]
+  - for each pose, the homogeneous transformation between the calibration target frame and the camera frame is recorded using
+  for instance a pose estimation method (PnP) from 2D-3D point correspondences
+\f[
+    \begin{bmatrix}
+    X_c\\
+    Y_c\\
+    Z_c\\
+    1
+    \end{bmatrix}
+    =
+    \begin{bmatrix}
+    _{}^{c}\textrm{R}_t & _{}^{c}\textrm{t}_t \\
+    0_{1 \times 3} & 1
+    \end{bmatrix}
+    \begin{bmatrix}
+    X_t\\
+    Y_t\\
+    Z_t\\
+    1
+    \end{bmatrix}
+\f]
+
+The Hand-Eye calibration procedure returns the following homogeneous transformation
+\f[
+    \begin{bmatrix}
+    X_g\\
+    Y_g\\
+    Z_g\\
+    1
+    \end{bmatrix}
+    =
+    \begin{bmatrix}
+    _{}^{g}\textrm{R}_c & _{}^{g}\textrm{t}_c \\
+    0_{1 \times 3} & 1
+    \end{bmatrix}
+    \begin{bmatrix}
+    X_c\\
+    Y_c\\
+    Z_c\\
+    1
+    \end{bmatrix}
+\f]
+
+This problem is also known as solving the \f$\mathbf{A}\mathbf{X}=\mathbf{X}\mathbf{B}\f$ equation:
+  - for an eye-in-hand configuration
+\f[
+    \begin{align*}
+    ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(1)} &=
+    \hspace{0.1em} ^{b}{\textrm{T}_g}^{(2)} \hspace{0.2em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} \\
+
+    (^{b}{\textrm{T}_g}^{(2)})^{-1} \hspace{0.2em} ^{b}{\textrm{T}_g}^{(1)} \hspace{0.2em} ^{g}\textrm{T}_c &=
+    \hspace{0.1em} ^{g}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} (^{c}{\textrm{T}_t}^{(1)})^{-1} \\
+
+    \textrm{A}_i \textrm{X} &= \textrm{X} \textrm{B}_i \\
+    \end{align*}
+\f]
+
+  - for an eye-to-hand configuration
+\f[
+    \begin{align*}
+    ^{g}{\textrm{T}_b}^{(1)} \hspace{0.2em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(1)} &=
+    \hspace{0.1em} ^{g}{\textrm{T}_b}^{(2)} \hspace{0.2em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} \\
+
+    (^{g}{\textrm{T}_b}^{(2)})^{-1} \hspace{0.2em} ^{g}{\textrm{T}_b}^{(1)} \hspace{0.2em} ^{b}\textrm{T}_c &=
+    \hspace{0.1em} ^{b}\textrm{T}_c \hspace{0.2em} ^{c}{\textrm{T}_t}^{(2)} (^{c}{\textrm{T}_t}^{(1)})^{-1} \\
+
+    \textrm{A}_i \textrm{X} &= \textrm{X} \textrm{B}_i \\
+    \end{align*}
+\f]
+
+\note
+Additional information can be found on this [website](http://campar.in.tum.de/Chair/HandEyeCalibration).
+\note
+A minimum of 2 motions with non parallel rotation axes are necessary to determine the hand-eye transformation.
+So at least 3 different poses are required, but it is strongly recommended to use many more poses.
+
+ */
+CV_EXPORTS_W void calibrateHandEye( InputArrayOfArrays R_gripper2base, InputArrayOfArrays t_gripper2base,
+                                    InputArrayOfArrays R_target2cam, InputArrayOfArrays t_target2cam,
+                                    OutputArray R_cam2gripper, OutputArray t_cam2gripper,
+                                    HandEyeCalibrationMethod method=CALIB_HAND_EYE_TSAI );
+
+/** @brief Computes Robot-World/Hand-Eye calibration: \f$_{}^{w}\textrm{T}_b\f$ and \f$_{}^{c}\textrm{T}_g\f$
+
+@param[in] R_world2cam Rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the world frame to the camera frame (\f$_{}^{c}\textrm{T}_w\f$).
+This is a vector (`vector<Mat>`) that contains the rotation, `(3x3)` rotation matrices or `(3x1)` rotation vectors,
+for all the transformations from world frame to the camera frame.
+@param[in] t_world2cam Translation part extracted from the homogeneous matrix that transforms a point
+expressed in the world frame to the camera frame (\f$_{}^{c}\textrm{T}_w\f$).
+This is a vector (`vector<Mat>`) that contains the `(3x1)` translation vectors for all the transformations
+from world frame to the camera frame.
+@param[in] R_base2gripper Rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the robot base frame to the gripper frame (\f$_{}^{g}\textrm{T}_b\f$).
+This is a vector (`vector<Mat>`) that contains the rotation, `(3x3)` rotation matrices or `(3x1)` rotation vectors,
+for all the transformations from robot base frame to the gripper frame.
+@param[in] t_base2gripper Rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the robot base frame to the gripper frame (\f$_{}^{g}\textrm{T}_b\f$).
+This is a vector (`vector<Mat>`) that contains the `(3x1)` translation vectors for all the transformations
+from robot base frame to the gripper frame.
+@param[out] R_base2world Estimated `(3x3)` rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the robot base frame to the world frame (\f$_{}^{w}\textrm{T}_b\f$).
+@param[out] t_base2world Estimated `(3x1)` translation part extracted from the homogeneous matrix that transforms a point
+expressed in the robot base frame to the world frame (\f$_{}^{w}\textrm{T}_b\f$).
+@param[out] R_gripper2cam Estimated `(3x3)` rotation part extracted from the homogeneous matrix that transforms a point
+expressed in the gripper frame to the camera frame (\f$_{}^{c}\textrm{T}_g\f$).
+@param[out] t_gripper2cam Estimated `(3x1)` translation part extracted from the homogeneous matrix that transforms a point
+expressed in the gripper frame to the camera frame (\f$_{}^{c}\textrm{T}_g\f$).
+@param[in] method One of the implemented Robot-World/Hand-Eye calibration method, see cv::RobotWorldHandEyeCalibrationMethod
+
+The function performs the Robot-World/Hand-Eye calibration using various methods. One approach consists in estimating the
+rotation then the translation (separable solutions):
+  - M. Shah, Solving the robot-world/hand-eye calibration problem using the kronecker product \cite Shah2013SolvingTR
+
+Another approach consists in estimating simultaneously the rotation and the translation (simultaneous solutions),
+with the following implemented method:
+  - A. Li, L. Wang, and D. Wu, Simultaneous robot-world and hand-eye calibration using dual-quaternions and kronecker product \cite Li2010SimultaneousRA
+
+The following picture describes the Robot-World/Hand-Eye calibration problem where the transformations between a robot and a world frame
+and between a robot gripper ("hand") and a camera ("eye") mounted at the robot end-effector have to be estimated.
+
+![](pics/robot-world_hand-eye_figure.png)
+
+The calibration procedure is the following:
+  - a static calibration pattern is used to estimate the transformation between the target frame
+  and the camera frame
+  - the robot gripper is moved in order to acquire several poses
+  - for each pose, the homogeneous transformation between the gripper frame and the robot base frame is recorded using for
+  instance the robot kinematics
+\f[
+    \begin{bmatrix}
+    X_g\\
+    Y_g\\
+    Z_g\\
+    1
+    \end{bmatrix}
+    =
+    \begin{bmatrix}
+    _{}^{g}\textrm{R}_b & _{}^{g}\textrm{t}_b \\
+    0_{1 \times 3} & 1
+    \end{bmatrix}
+    \begin{bmatrix}
+    X_b\\
+    Y_b\\
+    Z_b\\
+    1
+    \end{bmatrix}
+\f]
+  - for each pose, the homogeneous transformation between the calibration target frame (the world frame) and the camera frame is recorded using
+  for instance a pose estimation method (PnP) from 2D-3D point correspondences
+\f[
+    \begin{bmatrix}
+    X_c\\
+    Y_c\\
+    Z_c\\
+    1
+    \end{bmatrix}
+    =
+    \begin{bmatrix}
+    _{}^{c}\textrm{R}_w & _{}^{c}\textrm{t}_w \\
+    0_{1 \times 3} & 1
+    \end{bmatrix}
+    \begin{bmatrix}
+    X_w\\
+    Y_w\\
+    Z_w\\
+    1
+    \end{bmatrix}
+\f]
+
+The Robot-World/Hand-Eye calibration procedure returns the following homogeneous transformations
+\f[
+    \begin{bmatrix}
+    X_w\\
+    Y_w\\
+    Z_w\\
+    1
+    \end{bmatrix}
+    =
+    \begin{bmatrix}
+    _{}^{w}\textrm{R}_b & _{}^{w}\textrm{t}_b \\
+    0_{1 \times 3} & 1
+    \end{bmatrix}
+    \begin{bmatrix}
+    X_b\\
+    Y_b\\
+    Z_b\\
+    1
+    \end{bmatrix}
+\f]
+\f[
+    \begin{bmatrix}
+    X_c\\
+    Y_c\\
+    Z_c\\
+    1
+    \end{bmatrix}
+    =
+    \begin{bmatrix}
+    _{}^{c}\textrm{R}_g & _{}^{c}\textrm{t}_g \\
+    0_{1 \times 3} & 1
+    \end{bmatrix}
+    \begin{bmatrix}
+    X_g\\
+    Y_g\\
+    Z_g\\
+    1
+    \end{bmatrix}
+\f]
+
+This problem is also known as solving the \f$\mathbf{A}\mathbf{X}=\mathbf{Z}\mathbf{B}\f$ equation, with:
+  - \f$\mathbf{A} \Leftrightarrow \hspace{0.1em} _{}^{c}\textrm{T}_w\f$
+  - \f$\mathbf{X} \Leftrightarrow \hspace{0.1em} _{}^{w}\textrm{T}_b\f$
+  - \f$\mathbf{Z} \Leftrightarrow \hspace{0.1em} _{}^{c}\textrm{T}_g\f$
+  - \f$\mathbf{B} \Leftrightarrow \hspace{0.1em} _{}^{g}\textrm{T}_b\f$
+
+\note
+At least 3 measurements are required (input vectors size must be greater or equal to 3).
+
+ */
+CV_EXPORTS_W void calibrateRobotWorldHandEye( InputArrayOfArrays R_world2cam, InputArrayOfArrays t_world2cam,
+                                              InputArrayOfArrays R_base2gripper, InputArrayOfArrays t_base2gripper,
+                                              OutputArray R_base2world, OutputArray t_base2world,
+                                              OutputArray R_gripper2cam, OutputArray t_gripper2cam,
+                                              RobotWorldHandEyeCalibrationMethod method=CALIB_ROBOT_WORLD_HAND_EYE_SHAH );
+
+/** @brief Converts points from Euclidean to homogeneous space.
+
+@param src Input vector of N-dimensional points.
+@param dst Output vector of N+1-dimensional points.
+
+The function converts points from Euclidean to homogeneous space by appending 1's to the tuple of
+point coordinates. That is, each point (x1, x2, ..., xn) is converted to (x1, x2, ..., xn, 1).
+ */
+CV_EXPORTS_W void convertPointsToHomogeneous( InputArray src, OutputArray dst );
+
+/** @brief Converts points from homogeneous to Euclidean space.
+
+@param src Input vector of N-dimensional points.
+@param dst Output vector of N-1-dimensional points.
+
+The function converts points homogeneous to Euclidean space using perspective projection. That is,
+each point (x1, x2, ... x(n-1), xn) is converted to (x1/xn, x2/xn, ..., x(n-1)/xn). When xn=0, the
+output point coordinates will be (0,0,0,...).
+ */
+CV_EXPORTS_W void convertPointsFromHomogeneous( InputArray src, OutputArray dst );
+
+/** @brief Converts points to/from homogeneous coordinates.
+
+@param src Input array or vector of 2D, 3D, or 4D points.
+@param dst Output vector of 2D, 3D, or 4D points.
+
+The function converts 2D or 3D points from/to homogeneous coordinates by calling either
+#convertPointsToHomogeneous or #convertPointsFromHomogeneous.
+
+@note The function is obsolete. Use one of the previous two functions instead.
+ */
+CV_EXPORTS void convertPointsHomogeneous( InputArray src, OutputArray dst );
+
+/** @brief Calculates a fundamental matrix from the corresponding points in two images.
+
+@param points1 Array of N points from the first image. The point coordinates should be
+floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1 .
+@param method Method for computing a fundamental matrix.
+-   @ref FM_7POINT for a 7-point algorithm. \f$N = 7\f$
+-   @ref FM_8POINT for an 8-point algorithm. \f$N \ge 8\f$
+-   @ref FM_RANSAC for the RANSAC algorithm. \f$N \ge 8\f$
+-   @ref FM_LMEDS for the LMedS algorithm. \f$N \ge 8\f$
+@param ransacReprojThreshold Parameter used only for RANSAC. It is the maximum distance from a point to an epipolar
+line in pixels, beyond which the point is considered an outlier and is not used for computing the
+final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the
+point localization, image resolution, and the image noise.
+@param confidence Parameter used for the RANSAC and LMedS methods only. It specifies a desirable level
+of confidence (probability) that the estimated matrix is correct.
+@param[out] mask optional output mask
+@param maxIters The maximum number of robust method iterations.
+
+The epipolar geometry is described by the following equation:
+
+\f[[p_2; 1]^T F [p_1; 1] = 0\f]
+
+where \f$F\f$ is a fundamental matrix, \f$p_1\f$ and \f$p_2\f$ are corresponding points in the first and the
+second images, respectively.
+
+The function calculates the fundamental matrix using one of four methods listed above and returns
+the found fundamental matrix. Normally just one matrix is found. But in case of the 7-point
+algorithm, the function may return up to 3 solutions ( \f$9 \times 3\f$ matrix that stores all 3
+matrices sequentially).
+
+The calculated fundamental matrix may be passed further to #computeCorrespondEpilines that finds the
+epipolar lines corresponding to the specified points. It can also be passed to
+#stereoRectifyUncalibrated to compute the rectification transformation. :
+@code
+    // Example. Estimation of fundamental matrix using the RANSAC algorithm
+    int point_count = 100;
+    vector<Point2f> points1(point_count);
+    vector<Point2f> points2(point_count);
+
+    // initialize the points here ...
+    for( int i = 0; i < point_count; i++ )
+    {
+        points1[i] = ...;
+        points2[i] = ...;
+    }
+
+    Mat fundamental_matrix =
+     findFundamentalMat(points1, points2, FM_RANSAC, 3, 0.99);
+@endcode
+ */
+CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
+                                     int method, double ransacReprojThreshold, double confidence,
+                                     int maxIters, OutputArray mask = noArray() );
+
+/** @overload */
+CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
+                                     int method = FM_RANSAC,
+                                     double ransacReprojThreshold = 3., double confidence = 0.99,
+                                     OutputArray mask = noArray() );
+
+/** @overload */
+CV_EXPORTS Mat findFundamentalMat( InputArray points1, InputArray points2,
+                                   OutputArray mask, int method = FM_RANSAC,
+                                   double ransacReprojThreshold = 3., double confidence = 0.99 );
+
+
+CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
+                        OutputArray mask, const UsacParams &params);
+
+/** @brief Calculates an essential matrix from the corresponding points in two images.
+
+@param points1 Array of N (N \>= 5) 2D points from the first image. The point coordinates should
+be floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1.
+@param cameraMatrix Camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+Note that this function assumes that points1 and points2 are feature points from cameras with the
+same camera intrinsic matrix. If this assumption does not hold for your use case, use another
+function overload or #undistortPoints with `P = cv::NoArray()` for both cameras to transform image
+points to normalized image coordinates, which are valid for the identity camera intrinsic matrix.
+When passing these coordinates, pass the identity matrix for this parameter.
+@param method Method for computing an essential matrix.
+-   @ref RANSAC for the RANSAC algorithm.
+-   @ref LMEDS for the LMedS algorithm.
+@param prob Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of
+confidence (probability) that the estimated matrix is correct.
+@param threshold Parameter used for RANSAC. It is the maximum distance from a point to an epipolar
+line in pixels, beyond which the point is considered an outlier and is not used for computing the
+final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the
+point localization, image resolution, and the image noise.
+@param mask Output array of N elements, every element of which is set to 0 for outliers and to 1
+for the other points. The array is computed only in the RANSAC and LMedS methods.
+@param maxIters The maximum number of robust method iterations.
+
+This function estimates essential matrix based on the five-point algorithm solver in @cite Nister03 .
+@cite SteweniusCFS is also a related. The epipolar geometry is described by the following equation:
+
+\f[[p_2; 1]^T K^{-T} E K^{-1} [p_1; 1] = 0\f]
+
+where \f$E\f$ is an essential matrix, \f$p_1\f$ and \f$p_2\f$ are corresponding points in the first and the
+second images, respectively. The result of this function may be passed further to
+#decomposeEssentialMat or #recoverPose to recover the relative pose between cameras.
+ */
+CV_EXPORTS_W
+Mat findEssentialMat(
+    InputArray points1, InputArray points2,
+    InputArray cameraMatrix, int method = RANSAC,
+    double prob = 0.999, double threshold = 1.0,
+    int maxIters = 1000, OutputArray mask = noArray()
+);
+
+/** @overload */
+CV_EXPORTS
+Mat findEssentialMat(
+    InputArray points1, InputArray points2,
+    InputArray cameraMatrix, int method,
+    double prob, double threshold,
+    OutputArray mask
+);  // TODO remove from OpenCV 5.0
+
+/** @overload
+@param points1 Array of N (N \>= 5) 2D points from the first image. The point coordinates should
+be floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1 .
+@param focal focal length of the camera. Note that this function assumes that points1 and points2
+are feature points from cameras with same focal length and principal point.
+@param pp principal point of the camera.
+@param method Method for computing a fundamental matrix.
+-   @ref RANSAC for the RANSAC algorithm.
+-   @ref LMEDS for the LMedS algorithm.
+@param threshold Parameter used for RANSAC. It is the maximum distance from a point to an epipolar
+line in pixels, beyond which the point is considered an outlier and is not used for computing the
+final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the
+point localization, image resolution, and the image noise.
+@param prob Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of
+confidence (probability) that the estimated matrix is correct.
+@param mask Output array of N elements, every element of which is set to 0 for outliers and to 1
+for the other points. The array is computed only in the RANSAC and LMedS methods.
+@param maxIters The maximum number of robust method iterations.
+
+This function differs from the one above that it computes camera intrinsic matrix from focal length and
+principal point:
+
+\f[A =
+\begin{bmatrix}
+f & 0 & x_{pp}  \\
+0 & f & y_{pp}  \\
+0 & 0 & 1
+\end{bmatrix}\f]
+ */
+CV_EXPORTS_W
+Mat findEssentialMat(
+    InputArray points1, InputArray points2,
+    double focal = 1.0, Point2d pp = Point2d(0, 0),
+    int method = RANSAC, double prob = 0.999,
+    double threshold = 1.0, int maxIters = 1000,
+    OutputArray mask = noArray()
+);
+
+/** @overload */
+CV_EXPORTS
+Mat findEssentialMat(
+    InputArray points1, InputArray points2,
+    double focal, Point2d pp,
+    int method, double prob,
+    double threshold, OutputArray mask
+);  // TODO remove from OpenCV 5.0
+
+/** @brief Calculates an essential matrix from the corresponding points in two images from potentially two different cameras.
+
+@param points1 Array of N (N \>= 5) 2D points from the first image. The point coordinates should
+be floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1.
+@param cameraMatrix1 Camera matrix for the first camera \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param cameraMatrix2 Camera matrix for the second camera \f$K = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param distCoeffs1 Input vector of distortion coefficients for the first camera
+\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
+@param distCoeffs2 Input vector of distortion coefficients for the second camera
+\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
+@param method Method for computing an essential matrix.
+-   @ref RANSAC for the RANSAC algorithm.
+-   @ref LMEDS for the LMedS algorithm.
+@param prob Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of
+confidence (probability) that the estimated matrix is correct.
+@param threshold Parameter used for RANSAC. It is the maximum distance from a point to an epipolar
+line in pixels, beyond which the point is considered an outlier and is not used for computing the
+final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the
+point localization, image resolution, and the image noise.
+@param mask Output array of N elements, every element of which is set to 0 for outliers and to 1
+for the other points. The array is computed only in the RANSAC and LMedS methods.
+
+This function estimates essential matrix based on the five-point algorithm solver in @cite Nister03 .
+@cite SteweniusCFS is also a related. The epipolar geometry is described by the following equation:
+
+\f[[p_2; 1]^T K^{-T} E K^{-1} [p_1; 1] = 0\f]
+
+where \f$E\f$ is an essential matrix, \f$p_1\f$ and \f$p_2\f$ are corresponding points in the first and the
+second images, respectively. The result of this function may be passed further to
+#decomposeEssentialMat or  #recoverPose to recover the relative pose between cameras.
+ */
+CV_EXPORTS_W Mat findEssentialMat( InputArray points1, InputArray points2,
+                                 InputArray cameraMatrix1, InputArray distCoeffs1,
+                                 InputArray cameraMatrix2, InputArray distCoeffs2,
+                                 int method = RANSAC,
+                                 double prob = 0.999, double threshold = 1.0,
+                                 OutputArray mask = noArray() );
+
+
+CV_EXPORTS_W Mat findEssentialMat( InputArray points1, InputArray points2,
+                      InputArray cameraMatrix1, InputArray cameraMatrix2,
+                      InputArray dist_coeff1, InputArray dist_coeff2, OutputArray mask,
+                      const UsacParams &params);
+
+/** @brief Decompose an essential matrix to possible rotations and translation.
+
+@param E The input essential matrix.
+@param R1 One possible rotation matrix.
+@param R2 Another possible rotation matrix.
+@param t One possible translation.
+
+This function decomposes the essential matrix E using svd decomposition @cite HartleyZ00. In
+general, four possible poses exist for the decomposition of E. They are \f$[R_1, t]\f$,
+\f$[R_1, -t]\f$, \f$[R_2, t]\f$, \f$[R_2, -t]\f$.
+
+If E gives the epipolar constraint \f$[p_2; 1]^T A^{-T} E A^{-1} [p_1; 1] = 0\f$ between the image
+points \f$p_1\f$ in the first image and \f$p_2\f$ in second image, then any of the tuples
+\f$[R_1, t]\f$, \f$[R_1, -t]\f$, \f$[R_2, t]\f$, \f$[R_2, -t]\f$ is a change of basis from the first
+camera's coordinate system to the second camera's coordinate system. However, by decomposing E, one
+can only get the direction of the translation. For this reason, the translation t is returned with
+unit length.
+ */
+CV_EXPORTS_W void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t );
+
+/** @brief Recovers the relative camera rotation and the translation from corresponding points in two images from two different cameras, using cheirality check. Returns the number of
+inliers that pass the check.
+
+@param points1 Array of N 2D points from the first image. The point coordinates should be
+floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1 .
+@param cameraMatrix1 Input/output camera matrix for the first camera, the same as in
+@ref calibrateCamera. Furthermore, for the stereo case, additional flags may be used, see below.
+@param distCoeffs1 Input/output vector of distortion coefficients, the same as in
+@ref calibrateCamera.
+@param cameraMatrix2 Input/output camera matrix for the first camera, the same as in
+@ref calibrateCamera. Furthermore, for the stereo case, additional flags may be used, see below.
+@param distCoeffs2 Input/output vector of distortion coefficients, the same as in
+@ref calibrateCamera.
+@param E The output essential matrix.
+@param R Output rotation matrix. Together with the translation vector, this matrix makes up a tuple
+that performs a change of basis from the first camera's coordinate system to the second camera's
+coordinate system. Note that, in general, t can not be used for this tuple, see the parameter
+described below.
+@param t Output translation vector. This vector is obtained by @ref decomposeEssentialMat and
+therefore is only known up to scale, i.e. t is the direction of the translation vector and has unit
+length.
+@param method Method for computing an essential matrix.
+-   @ref RANSAC for the RANSAC algorithm.
+-   @ref LMEDS for the LMedS algorithm.
+@param prob Parameter used for the RANSAC or LMedS methods only. It specifies a desirable level of
+confidence (probability) that the estimated matrix is correct.
+@param threshold Parameter used for RANSAC. It is the maximum distance from a point to an epipolar
+line in pixels, beyond which the point is considered an outlier and is not used for computing the
+final fundamental matrix. It can be set to something like 1-3, depending on the accuracy of the
+point localization, image resolution, and the image noise.
+@param mask Input/output mask for inliers in points1 and points2. If it is not empty, then it marks
+inliers in points1 and points2 for then given essential matrix E. Only these inliers will be used to
+recover pose. In the output mask only inliers which pass the cheirality check.
+
+This function decomposes an essential matrix using @ref decomposeEssentialMat and then verifies
+possible pose hypotheses by doing cheirality check. The cheirality check means that the
+triangulated 3D points should have positive depth. Some details can be found in @cite Nister03.
+
+This function can be used to process the output E and mask from @ref findEssentialMat. In this
+scenario, points1 and points2 are the same input for findEssentialMat.:
+@code
+    // Example. Estimation of fundamental matrix using the RANSAC algorithm
+    int point_count = 100;
+    vector<Point2f> points1(point_count);
+    vector<Point2f> points2(point_count);
+
+    // initialize the points here ...
+    for( int i = 0; i < point_count; i++ )
+    {
+        points1[i] = ...;
+        points2[i] = ...;
+    }
+
+    // Input: camera calibration of both cameras, for example using intrinsic chessboard calibration.
+    Mat cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2;
+
+    // Output: Essential matrix, relative rotation and relative translation.
+    Mat E, R, t, mask;
+
+    recoverPose(points1, points2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, E, R, t, mask);
+@endcode
+ */
+CV_EXPORTS_W int recoverPose( InputArray points1, InputArray points2,
+                            InputArray cameraMatrix1, InputArray distCoeffs1,
+                            InputArray cameraMatrix2, InputArray distCoeffs2,
+                            OutputArray E, OutputArray R, OutputArray t,
+                            int method = cv::RANSAC, double prob = 0.999, double threshold = 1.0,
+                            InputOutputArray mask = noArray());
+
+/** @brief Recovers the relative camera rotation and the translation from an estimated essential
+matrix and the corresponding points in two images, using chirality check. Returns the number of
+inliers that pass the check.
+
+@param E The input essential matrix.
+@param points1 Array of N 2D points from the first image. The point coordinates should be
+floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1 .
+@param cameraMatrix Camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+Note that this function assumes that points1 and points2 are feature points from cameras with the
+same camera intrinsic matrix.
+@param R Output rotation matrix. Together with the translation vector, this matrix makes up a tuple
+that performs a change of basis from the first camera's coordinate system to the second camera's
+coordinate system. Note that, in general, t can not be used for this tuple, see the parameter
+described below.
+@param t Output translation vector. This vector is obtained by @ref decomposeEssentialMat and
+therefore is only known up to scale, i.e. t is the direction of the translation vector and has unit
+length.
+@param mask Input/output mask for inliers in points1 and points2. If it is not empty, then it marks
+inliers in points1 and points2 for the given essential matrix E. Only these inliers will be used to
+recover pose. In the output mask only inliers which pass the chirality check.
+
+This function decomposes an essential matrix using @ref decomposeEssentialMat and then verifies
+possible pose hypotheses by doing chirality check. The chirality check means that the
+triangulated 3D points should have positive depth. Some details can be found in @cite Nister03.
+
+This function can be used to process the output E and mask from @ref findEssentialMat. In this
+scenario, points1 and points2 are the same input for #findEssentialMat :
+@code
+    // Example. Estimation of fundamental matrix using the RANSAC algorithm
+    int point_count = 100;
+    vector<Point2f> points1(point_count);
+    vector<Point2f> points2(point_count);
+
+    // initialize the points here ...
+    for( int i = 0; i < point_count; i++ )
+    {
+        points1[i] = ...;
+        points2[i] = ...;
+    }
+
+    // cametra matrix with both focal lengths = 1, and principal point = (0, 0)
+    Mat cameraMatrix = Mat::eye(3, 3, CV_64F);
+
+    Mat E, R, t, mask;
+
+    E = findEssentialMat(points1, points2, cameraMatrix, RANSAC, 0.999, 1.0, mask);
+    recoverPose(E, points1, points2, cameraMatrix, R, t, mask);
+@endcode
+ */
+CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2,
+                            InputArray cameraMatrix, OutputArray R, OutputArray t,
+                            InputOutputArray mask = noArray() );
+
+/** @overload
+@param E The input essential matrix.
+@param points1 Array of N 2D points from the first image. The point coordinates should be
+floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1 .
+@param R Output rotation matrix. Together with the translation vector, this matrix makes up a tuple
+that performs a change of basis from the first camera's coordinate system to the second camera's
+coordinate system. Note that, in general, t can not be used for this tuple, see the parameter
+description below.
+@param t Output translation vector. This vector is obtained by @ref decomposeEssentialMat and
+therefore is only known up to scale, i.e. t is the direction of the translation vector and has unit
+length.
+@param focal Focal length of the camera. Note that this function assumes that points1 and points2
+are feature points from cameras with same focal length and principal point.
+@param pp principal point of the camera.
+@param mask Input/output mask for inliers in points1 and points2. If it is not empty, then it marks
+inliers in points1 and points2 for the given essential matrix E. Only these inliers will be used to
+recover pose. In the output mask only inliers which pass the chirality check.
+
+This function differs from the one above that it computes camera intrinsic matrix from focal length and
+principal point:
+
+\f[A =
+\begin{bmatrix}
+f & 0 & x_{pp}  \\
+0 & f & y_{pp}  \\
+0 & 0 & 1
+\end{bmatrix}\f]
+ */
+CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2,
+                            OutputArray R, OutputArray t,
+                            double focal = 1.0, Point2d pp = Point2d(0, 0),
+                            InputOutputArray mask = noArray() );
+
+/** @overload
+@param E The input essential matrix.
+@param points1 Array of N 2D points from the first image. The point coordinates should be
+floating-point (single or double precision).
+@param points2 Array of the second image points of the same size and format as points1.
+@param cameraMatrix Camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+Note that this function assumes that points1 and points2 are feature points from cameras with the
+same camera intrinsic matrix.
+@param R Output rotation matrix. Together with the translation vector, this matrix makes up a tuple
+that performs a change of basis from the first camera's coordinate system to the second camera's
+coordinate system. Note that, in general, t can not be used for this tuple, see the parameter
+description below.
+@param t Output translation vector. This vector is obtained by @ref decomposeEssentialMat and
+therefore is only known up to scale, i.e. t is the direction of the translation vector and has unit
+length.
+@param distanceThresh threshold distance which is used to filter out far away points (i.e. infinite
+points).
+@param mask Input/output mask for inliers in points1 and points2. If it is not empty, then it marks
+inliers in points1 and points2 for the given essential matrix E. Only these inliers will be used to
+recover pose. In the output mask only inliers which pass the chirality check.
+@param triangulatedPoints 3D points which were reconstructed by triangulation.
+
+This function differs from the one above that it outputs the triangulated 3D point that are used for
+the chirality check.
+ */
+CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2,
+                            InputArray cameraMatrix, OutputArray R, OutputArray t, double distanceThresh, InputOutputArray mask = noArray(),
+                            OutputArray triangulatedPoints = noArray());
+
+/** @brief For points in an image of a stereo pair, computes the corresponding epilines in the other image.
+
+@param points Input points. \f$N \times 1\f$ or \f$1 \times N\f$ matrix of type CV_32FC2 or
+vector\<Point2f\> .
+@param whichImage Index of the image (1 or 2) that contains the points .
+@param F Fundamental matrix that can be estimated using #findFundamentalMat or #stereoRectify .
+@param lines Output vector of the epipolar lines corresponding to the points in the other image.
+Each line \f$ax + by + c=0\f$ is encoded by 3 numbers \f$(a, b, c)\f$ .
+
+For every point in one of the two images of a stereo pair, the function finds the equation of the
+corresponding epipolar line in the other image.
+
+From the fundamental matrix definition (see #findFundamentalMat ), line \f$l^{(2)}_i\f$ in the second
+image for the point \f$p^{(1)}_i\f$ in the first image (when whichImage=1 ) is computed as:
+
+\f[l^{(2)}_i = F p^{(1)}_i\f]
+
+And vice versa, when whichImage=2, \f$l^{(1)}_i\f$ is computed from \f$p^{(2)}_i\f$ as:
+
+\f[l^{(1)}_i = F^T p^{(2)}_i\f]
+
+Line coefficients are defined up to a scale. They are normalized so that \f$a_i^2+b_i^2=1\f$ .
+ */
+CV_EXPORTS_W void computeCorrespondEpilines( InputArray points, int whichImage,
+                                             InputArray F, OutputArray lines );
+
+/** @brief This function reconstructs 3-dimensional points (in homogeneous coordinates) by using
+their observations with a stereo camera.
+
+@param projMatr1 3x4 projection matrix of the first camera, i.e. this matrix projects 3D points
+given in the world's coordinate system into the first image.
+@param projMatr2 3x4 projection matrix of the second camera, i.e. this matrix projects 3D points
+given in the world's coordinate system into the second image.
+@param projPoints1 2xN array of feature points in the first image. In the case of the c++ version,
+it can be also a vector of feature points or two-channel matrix of size 1xN or Nx1.
+@param projPoints2 2xN array of corresponding points in the second image. In the case of the c++
+version, it can be also a vector of feature points or two-channel matrix of size 1xN or Nx1.
+@param points4D 4xN array of reconstructed points in homogeneous coordinates. These points are
+returned in the world's coordinate system.
+
+@note
+   Keep in mind that all input data should be of float type in order for this function to work.
+
+@note
+   If the projection matrices from @ref stereoRectify are used, then the returned points are
+   represented in the first camera's rectified coordinate system.
+
+@sa
+   reprojectImageTo3D
+ */
+CV_EXPORTS_W void triangulatePoints( InputArray projMatr1, InputArray projMatr2,
+                                     InputArray projPoints1, InputArray projPoints2,
+                                     OutputArray points4D );
+
+/** @brief Refines coordinates of corresponding points.
+
+@param F 3x3 fundamental matrix.
+@param points1 1xN array containing the first set of points.
+@param points2 1xN array containing the second set of points.
+@param newPoints1 The optimized points1.
+@param newPoints2 The optimized points2.
+
+The function implements the Optimal Triangulation Method (see Multiple View Geometry @cite HartleyZ00 for details).
+For each given point correspondence points1[i] \<-\> points2[i], and a fundamental matrix F, it
+computes the corrected correspondences newPoints1[i] \<-\> newPoints2[i] that minimize the geometric
+error \f$d(points1[i], newPoints1[i])^2 + d(points2[i],newPoints2[i])^2\f$ (where \f$d(a,b)\f$ is the
+geometric distance between points \f$a\f$ and \f$b\f$ ) subject to the epipolar constraint
+\f$newPoints2^T \cdot F \cdot newPoints1 = 0\f$ .
+ */
+CV_EXPORTS_W void correctMatches( InputArray F, InputArray points1, InputArray points2,
+                                  OutputArray newPoints1, OutputArray newPoints2 );
+
+/** @brief Filters off small noise blobs (speckles) in the disparity map
+
+@param img The input 16-bit signed disparity image
+@param newVal The disparity value used to paint-off the speckles
+@param maxSpeckleSize The maximum speckle size to consider it a speckle. Larger blobs are not
+affected by the algorithm
+@param maxDiff Maximum difference between neighbor disparity pixels to put them into the same
+blob. Note that since StereoBM, StereoSGBM and may be other algorithms return a fixed-point
+disparity map, where disparity values are multiplied by 16, this scale factor should be taken into
+account when specifying this parameter value.
+@param buf The optional temporary buffer to avoid memory allocation within the function.
+ */
+CV_EXPORTS_W void filterSpeckles( InputOutputArray img, double newVal,
+                                  int maxSpeckleSize, double maxDiff,
+                                  InputOutputArray buf = noArray() );
+
+//! computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by #stereoRectify)
+CV_EXPORTS_W Rect getValidDisparityROI( Rect roi1, Rect roi2,
+                                        int minDisparity, int numberOfDisparities,
+                                        int blockSize );
+
+//! validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm
+CV_EXPORTS_W void validateDisparity( InputOutputArray disparity, InputArray cost,
+                                     int minDisparity, int numberOfDisparities,
+                                     int disp12MaxDisp = 1 );
+
+/** @brief Reprojects a disparity image to 3D space.
+
+@param disparity Input single-channel 8-bit unsigned, 16-bit signed, 32-bit signed or 32-bit
+floating-point disparity image. The values of 8-bit / 16-bit signed formats are assumed to have no
+fractional bits. If the disparity is 16-bit signed format, as computed by @ref StereoBM or
+@ref StereoSGBM and maybe other algorithms, it should be divided by 16 (and scaled to float) before
+being used here.
+@param _3dImage Output 3-channel floating-point image of the same size as disparity. Each element of
+_3dImage(x,y) contains 3D coordinates of the point (x,y) computed from the disparity map. If one
+uses Q obtained by @ref stereoRectify, then the returned points are represented in the first
+camera's rectified coordinate system.
+@param Q \f$4 \times 4\f$ perspective transformation matrix that can be obtained with
+@ref stereoRectify.
+@param handleMissingValues Indicates, whether the function should handle missing values (i.e.
+points where the disparity was not computed). If handleMissingValues=true, then pixels with the
+minimal disparity that corresponds to the outliers (see StereoMatcher::compute ) are transformed
+to 3D points with a very large Z value (currently set to 10000).
+@param ddepth The optional output array depth. If it is -1, the output image will have CV_32F
+depth. ddepth can also be set to CV_16S, CV_32S or CV_32F.
+
+The function transforms a single-channel disparity map to a 3-channel image representing a 3D
+surface. That is, for each pixel (x,y) and the corresponding disparity d=disparity(x,y) , it
+computes:
+
+\f[\begin{bmatrix}
+X \\
+Y \\
+Z \\
+W
+\end{bmatrix} = Q \begin{bmatrix}
+x \\
+y \\
+\texttt{disparity} (x,y) \\
+1
+\end{bmatrix}.\f]
+
+@sa
+   To reproject a sparse set of points {(x,y,d),...} to 3D space, use perspectiveTransform.
+ */
+CV_EXPORTS_W void reprojectImageTo3D( InputArray disparity,
+                                      OutputArray _3dImage, InputArray Q,
+                                      bool handleMissingValues = false,
+                                      int ddepth = -1 );
+
+/** @brief Calculates the Sampson Distance between two points.
+
+The function cv::sampsonDistance calculates and returns the first order approximation of the geometric error as:
+\f[
+sd( \texttt{pt1} , \texttt{pt2} )=
+\frac{(\texttt{pt2}^t \cdot \texttt{F} \cdot \texttt{pt1})^2}
+{((\texttt{F} \cdot \texttt{pt1})(0))^2 +
+((\texttt{F} \cdot \texttt{pt1})(1))^2 +
+((\texttt{F}^t \cdot \texttt{pt2})(0))^2 +
+((\texttt{F}^t \cdot \texttt{pt2})(1))^2}
+\f]
+The fundamental matrix may be calculated using the #findFundamentalMat function. See @cite HartleyZ00 11.4.3 for details.
+@param pt1 first homogeneous 2d point
+@param pt2 second homogeneous 2d point
+@param F fundamental matrix
+@return The computed Sampson distance.
+*/
+CV_EXPORTS_W double sampsonDistance(InputArray pt1, InputArray pt2, InputArray F);
+
+/** @brief Computes an optimal affine transformation between two 3D point sets.
+
+It computes
+\f[
+\begin{bmatrix}
+x\\
+y\\
+z\\
+\end{bmatrix}
+=
+\begin{bmatrix}
+a_{11} & a_{12} & a_{13}\\
+a_{21} & a_{22} & a_{23}\\
+a_{31} & a_{32} & a_{33}\\
+\end{bmatrix}
+\begin{bmatrix}
+X\\
+Y\\
+Z\\
+\end{bmatrix}
++
+\begin{bmatrix}
+b_1\\
+b_2\\
+b_3\\
+\end{bmatrix}
+\f]
+
+@param src First input 3D point set containing \f$(X,Y,Z)\f$.
+@param dst Second input 3D point set containing \f$(x,y,z)\f$.
+@param out Output 3D affine transformation matrix \f$3 \times 4\f$ of the form
+\f[
+\begin{bmatrix}
+a_{11} & a_{12} & a_{13} & b_1\\
+a_{21} & a_{22} & a_{23} & b_2\\
+a_{31} & a_{32} & a_{33} & b_3\\
+\end{bmatrix}
+\f]
+@param inliers Output vector indicating which points are inliers (1-inlier, 0-outlier).
+@param ransacThreshold Maximum reprojection error in the RANSAC algorithm to consider a point as
+an inlier.
+@param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything
+between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation
+significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.
+
+The function estimates an optimal 3D affine transformation between two 3D point sets using the
+RANSAC algorithm.
+ */
+CV_EXPORTS_W  int estimateAffine3D(InputArray src, InputArray dst,
+                                   OutputArray out, OutputArray inliers,
+                                   double ransacThreshold = 3, double confidence = 0.99);
+
+/** @brief Computes an optimal affine transformation between two 3D point sets.
+
+It computes \f$R,s,t\f$ minimizing \f$\sum{i} dst_i - c \cdot R \cdot src_i \f$
+where \f$R\f$ is a 3x3 rotation matrix, \f$t\f$ is a 3x1 translation vector and \f$s\f$ is a
+scalar size value. This is an implementation of the algorithm by Umeyama \cite umeyama1991least .
+The estimated affine transform has a homogeneous scale which is a subclass of affine
+transformations with 7 degrees of freedom. The paired point sets need to comprise at least 3
+points each.
+
+@param src First input 3D point set.
+@param dst Second input 3D point set.
+@param scale If null is passed, the scale parameter c will be assumed to be 1.0.
+Else the pointed-to variable will be set to the optimal scale.
+@param force_rotation If true, the returned rotation will never be a reflection.
+This might be unwanted, e.g. when optimizing a transform between a right- and a
+left-handed coordinate system.
+@return 3D affine transformation matrix \f$3 \times 4\f$ of the form
+\f[T =
+\begin{bmatrix}
+R & t\\
+\end{bmatrix}
+\f]
+
+ */
+CV_EXPORTS_W   cv::Mat estimateAffine3D(InputArray src, InputArray dst,
+                                        CV_OUT double* scale = nullptr, bool force_rotation = true);
+
+/** @brief Computes an optimal translation between two 3D point sets.
+ *
+ * It computes
+ * \f[
+ * \begin{bmatrix}
+ * x\\
+ * y\\
+ * z\\
+ * \end{bmatrix}
+ * =
+ * \begin{bmatrix}
+ * X\\
+ * Y\\
+ * Z\\
+ * \end{bmatrix}
+ * +
+ * \begin{bmatrix}
+ * b_1\\
+ * b_2\\
+ * b_3\\
+ * \end{bmatrix}
+ * \f]
+ *
+ * @param src First input 3D point set containing \f$(X,Y,Z)\f$.
+ * @param dst Second input 3D point set containing \f$(x,y,z)\f$.
+ * @param out Output 3D translation vector \f$3 \times 1\f$ of the form
+ * \f[
+ * \begin{bmatrix}
+ * b_1 \\
+ * b_2 \\
+ * b_3 \\
+ * \end{bmatrix}
+ * \f]
+ * @param inliers Output vector indicating which points are inliers (1-inlier, 0-outlier).
+ * @param ransacThreshold Maximum reprojection error in the RANSAC algorithm to consider a point as
+ * an inlier.
+ * @param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything
+ * between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation
+ * significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.
+ *
+ * The function estimates an optimal 3D translation between two 3D point sets using the
+ * RANSAC algorithm.
+ *  */
+CV_EXPORTS_W  int estimateTranslation3D(InputArray src, InputArray dst,
+                                        OutputArray out, OutputArray inliers,
+                                        double ransacThreshold = 3, double confidence = 0.99);
+
+/** @brief Computes an optimal affine transformation between two 2D point sets.
+
+It computes
+\f[
+\begin{bmatrix}
+x\\
+y\\
+\end{bmatrix}
+=
+\begin{bmatrix}
+a_{11} & a_{12}\\
+a_{21} & a_{22}\\
+\end{bmatrix}
+\begin{bmatrix}
+X\\
+Y\\
+\end{bmatrix}
++
+\begin{bmatrix}
+b_1\\
+b_2\\
+\end{bmatrix}
+\f]
+
+@param from First input 2D point set containing \f$(X,Y)\f$.
+@param to Second input 2D point set containing \f$(x,y)\f$.
+@param inliers Output vector indicating which points are inliers (1-inlier, 0-outlier).
+@param method Robust method used to compute transformation. The following methods are possible:
+-   @ref RANSAC - RANSAC-based robust method
+-   @ref LMEDS - Least-Median robust method
+RANSAC is the default method.
+@param ransacReprojThreshold Maximum reprojection error in the RANSAC algorithm to consider
+a point as an inlier. Applies only to RANSAC.
+@param maxIters The maximum number of robust method iterations.
+@param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything
+between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation
+significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.
+@param refineIters Maximum number of iterations of refining algorithm (Levenberg-Marquardt).
+Passing 0 will disable refining, so the output matrix will be output of robust method.
+
+@return Output 2D affine transformation matrix \f$2 \times 3\f$ or empty matrix if transformation
+could not be estimated. The returned matrix has the following form:
+\f[
+\begin{bmatrix}
+a_{11} & a_{12} & b_1\\
+a_{21} & a_{22} & b_2\\
+\end{bmatrix}
+\f]
+
+The function estimates an optimal 2D affine transformation between two 2D point sets using the
+selected robust algorithm.
+
+The computed transformation is then refined further (using only inliers) with the
+Levenberg-Marquardt method to reduce the re-projection error even more.
+
+@note
+The RANSAC method can handle practically any ratio of outliers but needs a threshold to
+distinguish inliers from outliers. The method LMeDS does not need any threshold but it works
+correctly only when there are more than 50% of inliers.
+
+@sa estimateAffinePartial2D, getAffineTransform
+*/
+CV_EXPORTS_W cv::Mat estimateAffine2D(InputArray from, InputArray to, OutputArray inliers = noArray(),
+                                  int method = RANSAC, double ransacReprojThreshold = 3,
+                                  size_t maxIters = 2000, double confidence = 0.99,
+                                  size_t refineIters = 10);
+
+
+CV_EXPORTS_W cv::Mat estimateAffine2D(InputArray pts1, InputArray pts2, OutputArray inliers,
+                     const UsacParams &params);
+
+/** @brief Computes an optimal limited affine transformation with 4 degrees of freedom between
+two 2D point sets.
+
+@param from First input 2D point set.
+@param to Second input 2D point set.
+@param inliers Output vector indicating which points are inliers.
+@param method Robust method used to compute transformation. The following methods are possible:
+-   @ref RANSAC - RANSAC-based robust method
+-   @ref LMEDS - Least-Median robust method
+RANSAC is the default method.
+@param ransacReprojThreshold Maximum reprojection error in the RANSAC algorithm to consider
+a point as an inlier. Applies only to RANSAC.
+@param maxIters The maximum number of robust method iterations.
+@param confidence Confidence level, between 0 and 1, for the estimated transformation. Anything
+between 0.95 and 0.99 is usually good enough. Values too close to 1 can slow down the estimation
+significantly. Values lower than 0.8-0.9 can result in an incorrectly estimated transformation.
+@param refineIters Maximum number of iterations of refining algorithm (Levenberg-Marquardt).
+Passing 0 will disable refining, so the output matrix will be output of robust method.
+
+@return Output 2D affine transformation (4 degrees of freedom) matrix \f$2 \times 3\f$ or
+empty matrix if transformation could not be estimated.
+
+The function estimates an optimal 2D affine transformation with 4 degrees of freedom limited to
+combinations of translation, rotation, and uniform scaling. Uses the selected algorithm for robust
+estimation.
+
+The computed transformation is then refined further (using only inliers) with the
+Levenberg-Marquardt method to reduce the re-projection error even more.
+
+Estimated transformation matrix is:
+\f[ \begin{bmatrix} \cos(\theta) \cdot s & -\sin(\theta) \cdot s & t_x \\
+                \sin(\theta) \cdot s & \cos(\theta) \cdot s & t_y
+\end{bmatrix} \f]
+Where \f$ \theta \f$ is the rotation angle, \f$ s \f$ the scaling factor and \f$ t_x, t_y \f$ are
+translations in \f$ x, y \f$ axes respectively.
+
+@note
+The RANSAC method can handle practically any ratio of outliers but need a threshold to
+distinguish inliers from outliers. The method LMeDS does not need any threshold but it works
+correctly only when there are more than 50% of inliers.
+
+@sa estimateAffine2D, getAffineTransform
+*/
+CV_EXPORTS_W cv::Mat estimateAffinePartial2D(InputArray from, InputArray to, OutputArray inliers = noArray(),
+                                  int method = RANSAC, double ransacReprojThreshold = 3,
+                                  size_t maxIters = 2000, double confidence = 0.99,
+                                  size_t refineIters = 10);
+
+/** @example samples/cpp/tutorial_code/features2D/Homography/decompose_homography.cpp
+An example program with homography decomposition.
+
+Check @ref tutorial_homography "the corresponding tutorial" for more details.
+*/
+
+/** @brief Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).
+
+@param H The input homography matrix between two images.
+@param K The input camera intrinsic matrix.
+@param rotations Array of rotation matrices.
+@param translations Array of translation matrices.
+@param normals Array of plane normal matrices.
+
+This function extracts relative camera motion between two views of a planar object and returns up to
+four mathematical solution tuples of rotation, translation, and plane normal. The decomposition of
+the homography matrix H is described in detail in @cite Malis2007.
+
+If the homography H, induced by the plane, gives the constraint
+\f[s_i \vecthree{x'_i}{y'_i}{1} \sim H \vecthree{x_i}{y_i}{1}\f] on the source image points
+\f$p_i\f$ and the destination image points \f$p'_i\f$, then the tuple of rotations[k] and
+translations[k] is a change of basis from the source camera's coordinate system to the destination
+camera's coordinate system. However, by decomposing H, one can only get the translation normalized
+by the (typically unknown) depth of the scene, i.e. its direction but with normalized length.
+
+If point correspondences are available, at least two solutions may further be invalidated, by
+applying positive depth constraint, i.e. all points must be in front of the camera.
+ */
+CV_EXPORTS_W int decomposeHomographyMat(InputArray H,
+                                        InputArray K,
+                                        OutputArrayOfArrays rotations,
+                                        OutputArrayOfArrays translations,
+                                        OutputArrayOfArrays normals);
+
+/** @brief Filters homography decompositions based on additional information.
+
+@param rotations Vector of rotation matrices.
+@param normals Vector of plane normal matrices.
+@param beforePoints Vector of (rectified) visible reference points before the homography is applied
+@param afterPoints Vector of (rectified) visible reference points after the homography is applied
+@param possibleSolutions Vector of int indices representing the viable solution set after filtering
+@param pointsMask optional Mat/Vector of 8u type representing the mask for the inliers as given by the #findHomography function
+
+This function is intended to filter the output of the #decomposeHomographyMat based on additional
+information as described in @cite Malis2007 . The summary of the method: the #decomposeHomographyMat function
+returns 2 unique solutions and their "opposites" for a total of 4 solutions. If we have access to the
+sets of points visible in the camera frame before and after the homography transformation is applied,
+we can determine which are the true potential solutions and which are the opposites by verifying which
+homographies are consistent with all visible reference points being in front of the camera. The inputs
+are left unchanged; the filtered solution set is returned as indices into the existing one.
+
+*/
+CV_EXPORTS_W void filterHomographyDecompByVisibleRefpoints(InputArrayOfArrays rotations,
+                                                           InputArrayOfArrays normals,
+                                                           InputArray beforePoints,
+                                                           InputArray afterPoints,
+                                                           OutputArray possibleSolutions,
+                                                           InputArray pointsMask = noArray());
+
+/** @brief The base class for stereo correspondence algorithms.
+ */
+class CV_EXPORTS_W StereoMatcher : public Algorithm
+{
+public:
+    enum { DISP_SHIFT = 4,
+           DISP_SCALE = (1 << DISP_SHIFT)
+         };
+
+    /** @brief Computes disparity map for the specified stereo pair
+
+    @param left Left 8-bit single-channel image.
+    @param right Right image of the same size and the same type as the left one.
+    @param disparity Output disparity map. It has the same size as the input images. Some algorithms,
+    like StereoBM or StereoSGBM compute 16-bit fixed-point disparity map (where each disparity value
+    has 4 fractional bits), whereas other algorithms output 32-bit floating-point disparity map.
+     */
+    CV_WRAP virtual void compute( InputArray left, InputArray right,
+                                  OutputArray disparity ) = 0;
+
+    CV_WRAP virtual int getMinDisparity() const = 0;
+    CV_WRAP virtual void setMinDisparity(int minDisparity) = 0;
+
+    CV_WRAP virtual int getNumDisparities() const = 0;
+    CV_WRAP virtual void setNumDisparities(int numDisparities) = 0;
+
+    CV_WRAP virtual int getBlockSize() const = 0;
+    CV_WRAP virtual void setBlockSize(int blockSize) = 0;
+
+    CV_WRAP virtual int getSpeckleWindowSize() const = 0;
+    CV_WRAP virtual void setSpeckleWindowSize(int speckleWindowSize) = 0;
+
+    CV_WRAP virtual int getSpeckleRange() const = 0;
+    CV_WRAP virtual void setSpeckleRange(int speckleRange) = 0;
+
+    CV_WRAP virtual int getDisp12MaxDiff() const = 0;
+    CV_WRAP virtual void setDisp12MaxDiff(int disp12MaxDiff) = 0;
+};
+
+
+/** @brief Class for computing stereo correspondence using the block matching algorithm, introduced and
+contributed to OpenCV by K. Konolige.
+ */
+class CV_EXPORTS_W StereoBM : public StereoMatcher
+{
+public:
+    enum { PREFILTER_NORMALIZED_RESPONSE = 0,
+           PREFILTER_XSOBEL              = 1
+         };
+
+    CV_WRAP virtual int getPreFilterType() const = 0;
+    CV_WRAP virtual void setPreFilterType(int preFilterType) = 0;
+
+    CV_WRAP virtual int getPreFilterSize() const = 0;
+    CV_WRAP virtual void setPreFilterSize(int preFilterSize) = 0;
+
+    CV_WRAP virtual int getPreFilterCap() const = 0;
+    CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0;
+
+    CV_WRAP virtual int getTextureThreshold() const = 0;
+    CV_WRAP virtual void setTextureThreshold(int textureThreshold) = 0;
+
+    CV_WRAP virtual int getUniquenessRatio() const = 0;
+    CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0;
+
+    CV_WRAP virtual int getSmallerBlockSize() const = 0;
+    CV_WRAP virtual void setSmallerBlockSize(int blockSize) = 0;
+
+    CV_WRAP virtual Rect getROI1() const = 0;
+    CV_WRAP virtual void setROI1(Rect roi1) = 0;
+
+    CV_WRAP virtual Rect getROI2() const = 0;
+    CV_WRAP virtual void setROI2(Rect roi2) = 0;
+
+    /** @brief Creates StereoBM object
+
+    @param numDisparities the disparity search range. For each pixel algorithm will find the best
+    disparity from 0 (default minimum disparity) to numDisparities. The search range can then be
+    shifted by changing the minimum disparity.
+    @param blockSize the linear size of the blocks compared by the algorithm. The size should be odd
+    (as the block is centered at the current pixel). Larger block size implies smoother, though less
+    accurate disparity map. Smaller block size gives more detailed disparity map, but there is higher
+    chance for algorithm to find a wrong correspondence.
+
+    The function create StereoBM object. You can then call StereoBM::compute() to compute disparity for
+    a specific stereo pair.
+     */
+    CV_WRAP static Ptr<StereoBM> create(int numDisparities = 0, int blockSize = 21);
+};
+
+/** @brief The class implements the modified H. Hirschmuller algorithm @cite HH08 that differs from the original
+one as follows:
+
+-   By default, the algorithm is single-pass, which means that you consider only 5 directions
+instead of 8. Set mode=StereoSGBM::MODE_HH in createStereoSGBM to run the full variant of the
+algorithm but beware that it may consume a lot of memory.
+-   The algorithm matches blocks, not individual pixels. Though, setting blockSize=1 reduces the
+blocks to single pixels.
+-   Mutual information cost function is not implemented. Instead, a simpler Birchfield-Tomasi
+sub-pixel metric from @cite BT98 is used. Though, the color images are supported as well.
+-   Some pre- and post- processing steps from K. Konolige algorithm StereoBM are included, for
+example: pre-filtering (StereoBM::PREFILTER_XSOBEL type) and post-filtering (uniqueness
+check, quadratic interpolation and speckle filtering).
+
+@note
+   -   (Python) An example illustrating the use of the StereoSGBM matching algorithm can be found
+        at opencv_source_code/samples/python/stereo_match.py
+ */
+class CV_EXPORTS_W StereoSGBM : public StereoMatcher
+{
+public:
+    enum
+    {
+        MODE_SGBM = 0,
+        MODE_HH   = 1,
+        MODE_SGBM_3WAY = 2,
+        MODE_HH4  = 3
+    };
+
+    CV_WRAP virtual int getPreFilterCap() const = 0;
+    CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0;
+
+    CV_WRAP virtual int getUniquenessRatio() const = 0;
+    CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0;
+
+    CV_WRAP virtual int getP1() const = 0;
+    CV_WRAP virtual void setP1(int P1) = 0;
+
+    CV_WRAP virtual int getP2() const = 0;
+    CV_WRAP virtual void setP2(int P2) = 0;
+
+    CV_WRAP virtual int getMode() const = 0;
+    CV_WRAP virtual void setMode(int mode) = 0;
+
+    /** @brief Creates StereoSGBM object
+
+    @param minDisparity Minimum possible disparity value. Normally, it is zero but sometimes
+    rectification algorithms can shift images, so this parameter needs to be adjusted accordingly.
+    @param numDisparities Maximum disparity minus minimum disparity. The value is always greater than
+    zero. In the current implementation, this parameter must be divisible by 16.
+    @param blockSize Matched block size. It must be an odd number \>=1 . Normally, it should be
+    somewhere in the 3..11 range.
+    @param P1 The first parameter controlling the disparity smoothness. See below.
+    @param P2 The second parameter controlling the disparity smoothness. The larger the values are,
+    the smoother the disparity is. P1 is the penalty on the disparity change by plus or minus 1
+    between neighbor pixels. P2 is the penalty on the disparity change by more than 1 between neighbor
+    pixels. The algorithm requires P2 \> P1 . See stereo_match.cpp sample where some reasonably good
+    P1 and P2 values are shown (like 8\*number_of_image_channels\*blockSize\*blockSize and
+    32\*number_of_image_channels\*blockSize\*blockSize , respectively).
+    @param disp12MaxDiff Maximum allowed difference (in integer pixel units) in the left-right
+    disparity check. Set it to a non-positive value to disable the check.
+    @param preFilterCap Truncation value for the prefiltered image pixels. The algorithm first
+    computes x-derivative at each pixel and clips its value by [-preFilterCap, preFilterCap] interval.
+    The result values are passed to the Birchfield-Tomasi pixel cost function.
+    @param uniquenessRatio Margin in percentage by which the best (minimum) computed cost function
+    value should "win" the second best value to consider the found match correct. Normally, a value
+    within the 5-15 range is good enough.
+    @param speckleWindowSize Maximum size of smooth disparity regions to consider their noise speckles
+    and invalidate. Set it to 0 to disable speckle filtering. Otherwise, set it somewhere in the
+    50-200 range.
+    @param speckleRange Maximum disparity variation within each connected component. If you do speckle
+    filtering, set the parameter to a positive value, it will be implicitly multiplied by 16.
+    Normally, 1 or 2 is good enough.
+    @param mode Set it to StereoSGBM::MODE_HH to run the full-scale two-pass dynamic programming
+    algorithm. It will consume O(W\*H\*numDisparities) bytes, which is large for 640x480 stereo and
+    huge for HD-size pictures. By default, it is set to false .
+
+    The first constructor initializes StereoSGBM with all the default parameters. So, you only have to
+    set StereoSGBM::numDisparities at minimum. The second constructor enables you to set each parameter
+    to a custom value.
+     */
+    CV_WRAP static Ptr<StereoSGBM> create(int minDisparity = 0, int numDisparities = 16, int blockSize = 3,
+                                          int P1 = 0, int P2 = 0, int disp12MaxDiff = 0,
+                                          int preFilterCap = 0, int uniquenessRatio = 0,
+                                          int speckleWindowSize = 0, int speckleRange = 0,
+                                          int mode = StereoSGBM::MODE_SGBM);
+};
+
+
+//! cv::undistort mode
+enum UndistortTypes
+{
+    PROJ_SPHERICAL_ORTHO  = 0,
+    PROJ_SPHERICAL_EQRECT = 1
+};
+
+/** @brief Transforms an image to compensate for lens distortion.
+
+The function transforms an image to compensate radial and tangential lens distortion.
+
+The function is simply a combination of #initUndistortRectifyMap (with unity R ) and #remap
+(with bilinear interpolation). See the former function for details of the transformation being
+performed.
+
+Those pixels in the destination image, for which there is no correspondent pixels in the source
+image, are filled with zeros (black color).
+
+A particular subset of the source image that will be visible in the corrected image can be regulated
+by newCameraMatrix. You can use #getOptimalNewCameraMatrix to compute the appropriate
+newCameraMatrix depending on your requirements.
+
+The camera matrix and the distortion parameters can be determined using #calibrateCamera. If
+the resolution of images is different from the resolution used at the calibration stage, \f$f_x,
+f_y, c_x\f$ and \f$c_y\f$ need to be scaled accordingly, while the distortion coefficients remain
+the same.
+
+@param src Input (distorted) image.
+@param dst Output (corrected) image that has the same size and type as src .
+@param cameraMatrix Input camera matrix \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
+@param newCameraMatrix Camera matrix of the distorted image. By default, it is the same as
+cameraMatrix but you may additionally scale and shift the result by using a different matrix.
+ */
+CV_EXPORTS_W void undistort( InputArray src, OutputArray dst,
+                             InputArray cameraMatrix,
+                             InputArray distCoeffs,
+                             InputArray newCameraMatrix = noArray() );
+
+/** @brief Computes the undistortion and rectification transformation map.
+
+The function computes the joint undistortion and rectification transformation and represents the
+result in the form of maps for #remap. The undistorted image looks like original, as if it is
+captured with a camera using the camera matrix =newCameraMatrix and zero distortion. In case of a
+monocular camera, newCameraMatrix is usually equal to cameraMatrix, or it can be computed by
+#getOptimalNewCameraMatrix for a better control over scaling. In case of a stereo camera,
+newCameraMatrix is normally set to P1 or P2 computed by #stereoRectify .
+
+Also, this new camera is oriented differently in the coordinate space, according to R. That, for
+example, helps to align two heads of a stereo camera so that the epipolar lines on both images
+become horizontal and have the same y- coordinate (in case of a horizontally aligned stereo camera).
+
+The function actually builds the maps for the inverse mapping algorithm that is used by #remap. That
+is, for each pixel \f$(u, v)\f$ in the destination (corrected and rectified) image, the function
+computes the corresponding coordinates in the source image (that is, in the original image from
+camera). The following process is applied:
+\f[
+\begin{array}{l}
+x  \leftarrow (u - {c'}_x)/{f'}_x  \\
+y  \leftarrow (v - {c'}_y)/{f'}_y  \\
+{[X\,Y\,W]} ^T  \leftarrow R^{-1}*[x \, y \, 1]^T  \\
+x'  \leftarrow X/W  \\
+y'  \leftarrow Y/W  \\
+r^2  \leftarrow x'^2 + y'^2 \\
+x''  \leftarrow x' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6}
++ 2p_1 x' y' + p_2(r^2 + 2 x'^2)  + s_1 r^2 + s_2 r^4\\
+y''  \leftarrow y' \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6}
++ p_1 (r^2 + 2 y'^2) + 2 p_2 x' y' + s_3 r^2 + s_4 r^4 \\
+s\vecthree{x'''}{y'''}{1} =
+\vecthreethree{R_{33}(\tau_x, \tau_y)}{0}{-R_{13}((\tau_x, \tau_y)}
+{0}{R_{33}(\tau_x, \tau_y)}{-R_{23}(\tau_x, \tau_y)}
+{0}{0}{1} R(\tau_x, \tau_y) \vecthree{x''}{y''}{1}\\
+map_x(u,v)  \leftarrow x''' f_x + c_x  \\
+map_y(u,v)  \leftarrow y''' f_y + c_y
+\end{array}
+\f]
+where \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+are the distortion coefficients.
+
+In case of a stereo camera, this function is called twice: once for each camera head, after
+#stereoRectify, which in its turn is called after #stereoCalibrate. But if the stereo camera
+was not calibrated, it is still possible to compute the rectification transformations directly from
+the fundamental matrix using #stereoRectifyUncalibrated. For each camera, the function computes
+homography H as the rectification transformation in a pixel domain, not a rotation matrix R in 3D
+space. R can be computed from H as
+\f[\texttt{R} = \texttt{cameraMatrix} ^{-1} \cdot \texttt{H} \cdot \texttt{cameraMatrix}\f]
+where cameraMatrix can be chosen arbitrarily.
+
+@param cameraMatrix Input camera matrix \f$A=\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
+@param R Optional rectification transformation in the object space (3x3 matrix). R1 or R2 ,
+computed by #stereoRectify can be passed here. If the matrix is empty, the identity transformation
+is assumed. In #initUndistortRectifyMap R assumed to be an identity matrix.
+@param newCameraMatrix New camera matrix \f$A'=\vecthreethree{f_x'}{0}{c_x'}{0}{f_y'}{c_y'}{0}{0}{1}\f$.
+@param size Undistorted image size.
+@param m1type Type of the first output map that can be CV_32FC1, CV_32FC2 or CV_16SC2, see #convertMaps
+@param map1 The first output map.
+@param map2 The second output map.
+ */
+CV_EXPORTS_W
+void initUndistortRectifyMap(InputArray cameraMatrix, InputArray distCoeffs,
+                             InputArray R, InputArray newCameraMatrix,
+                             Size size, int m1type, OutputArray map1, OutputArray map2);
+
+/** @brief Computes the projection and inverse-rectification transformation map. In essense, this is the inverse of
+#initUndistortRectifyMap to accomodate stereo-rectification of projectors ('inverse-cameras') in projector-camera pairs.
+
+The function computes the joint projection and inverse rectification transformation and represents the
+result in the form of maps for #remap. The projected image looks like a distorted version of the original which,
+once projected by a projector, should visually match the original. In case of a monocular camera, newCameraMatrix
+is usually equal to cameraMatrix, or it can be computed by
+#getOptimalNewCameraMatrix for a better control over scaling. In case of a projector-camera pair,
+newCameraMatrix is normally set to P1 or P2 computed by #stereoRectify .
+
+The projector is oriented differently in the coordinate space, according to R. In case of projector-camera pairs,
+this helps align the projector (in the same manner as #initUndistortRectifyMap for the camera) to create a stereo-rectified pair. This
+allows epipolar lines on both images to become horizontal and have the same y-coordinate (in case of a horizontally aligned projector-camera pair).
+
+The function builds the maps for the inverse mapping algorithm that is used by #remap. That
+is, for each pixel \f$(u, v)\f$ in the destination (projected and inverse-rectified) image, the function
+computes the corresponding coordinates in the source image (that is, in the original digital image). The following process is applied:
+
+\f[
+\begin{array}{l}
+\text{newCameraMatrix}\\
+x  \leftarrow (u - {c'}_x)/{f'}_x  \\
+y  \leftarrow (v - {c'}_y)/{f'}_y  \\
+
+\\\text{Undistortion}
+\\\scriptsize{\textit{though equation shown is for radial undistortion, function implements cv::undistortPoints()}}\\
+r^2  \leftarrow x^2 + y^2 \\
+\theta \leftarrow \frac{1 + k_1 r^2 + k_2 r^4 + k_3 r^6}{1 + k_4 r^2 + k_5 r^4 + k_6 r^6}\\
+x' \leftarrow \frac{x}{\theta} \\
+y'  \leftarrow \frac{y}{\theta} \\
+
+\\\text{Rectification}\\
+{[X\,Y\,W]} ^T  \leftarrow R*[x' \, y' \, 1]^T  \\
+x''  \leftarrow X/W  \\
+y''  \leftarrow Y/W  \\
+
+\\\text{cameraMatrix}\\
+map_x(u,v)  \leftarrow x'' f_x + c_x  \\
+map_y(u,v)  \leftarrow y'' f_y + c_y
+\end{array}
+\f]
+where \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+are the distortion coefficients vector distCoeffs.
+
+In case of a stereo-rectified projector-camera pair, this function is called for the projector while #initUndistortRectifyMap is called for the camera head.
+This is done after #stereoRectify, which in turn is called after #stereoCalibrate. If the projector-camera pair
+is not calibrated, it is still possible to compute the rectification transformations directly from
+the fundamental matrix using #stereoRectifyUncalibrated. For the projector and camera, the function computes
+homography H as the rectification transformation in a pixel domain, not a rotation matrix R in 3D
+space. R can be computed from H as
+\f[\texttt{R} = \texttt{cameraMatrix} ^{-1} \cdot \texttt{H} \cdot \texttt{cameraMatrix}\f]
+where cameraMatrix can be chosen arbitrarily.
+
+@param cameraMatrix Input camera matrix \f$A=\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
+@param R Optional rectification transformation in the object space (3x3 matrix). R1 or R2,
+computed by #stereoRectify can be passed here. If the matrix is empty, the identity transformation
+is assumed.
+@param newCameraMatrix New camera matrix \f$A'=\vecthreethree{f_x'}{0}{c_x'}{0}{f_y'}{c_y'}{0}{0}{1}\f$.
+@param size Distorted image size.
+@param m1type Type of the first output map. Can be CV_32FC1, CV_32FC2 or CV_16SC2, see #convertMaps
+@param map1 The first output map for #remap.
+@param map2 The second output map for #remap.
+ */
+CV_EXPORTS_W
+void initInverseRectificationMap( InputArray cameraMatrix, InputArray distCoeffs,
+                           InputArray R, InputArray newCameraMatrix,
+                           const Size& size, int m1type, OutputArray map1, OutputArray map2 );
+
+//! initializes maps for #remap for wide-angle
+CV_EXPORTS
+float initWideAngleProjMap(InputArray cameraMatrix, InputArray distCoeffs,
+                           Size imageSize, int destImageWidth,
+                           int m1type, OutputArray map1, OutputArray map2,
+                           enum UndistortTypes projType = PROJ_SPHERICAL_EQRECT, double alpha = 0);
+static inline
+float initWideAngleProjMap(InputArray cameraMatrix, InputArray distCoeffs,
+                           Size imageSize, int destImageWidth,
+                           int m1type, OutputArray map1, OutputArray map2,
+                           int projType, double alpha = 0)
+{
+    return initWideAngleProjMap(cameraMatrix, distCoeffs, imageSize, destImageWidth,
+                                m1type, map1, map2, (UndistortTypes)projType, alpha);
+}
+
+/** @brief Returns the default new camera matrix.
+
+The function returns the camera matrix that is either an exact copy of the input cameraMatrix (when
+centerPrinicipalPoint=false ), or the modified one (when centerPrincipalPoint=true).
+
+In the latter case, the new camera matrix will be:
+
+\f[\begin{bmatrix} f_x && 0 && ( \texttt{imgSize.width} -1)*0.5  \\ 0 && f_y && ( \texttt{imgSize.height} -1)*0.5  \\ 0 && 0 && 1 \end{bmatrix} ,\f]
+
+where \f$f_x\f$ and \f$f_y\f$ are \f$(0,0)\f$ and \f$(1,1)\f$ elements of cameraMatrix, respectively.
+
+By default, the undistortion functions in OpenCV (see #initUndistortRectifyMap, #undistort) do not
+move the principal point. However, when you work with stereo, it is important to move the principal
+points in both views to the same y-coordinate (which is required by most of stereo correspondence
+algorithms), and may be to the same x-coordinate too. So, you can form the new camera matrix for
+each view where the principal points are located at the center.
+
+@param cameraMatrix Input camera matrix.
+@param imgsize Camera view image size in pixels.
+@param centerPrincipalPoint Location of the principal point in the new camera matrix. The
+parameter indicates whether this location should be at the image center or not.
+ */
+CV_EXPORTS_W
+Mat getDefaultNewCameraMatrix(InputArray cameraMatrix, Size imgsize = Size(),
+                              bool centerPrincipalPoint = false);
+
+/** @brief Computes the ideal point coordinates from the observed point coordinates.
+
+The function is similar to #undistort and #initUndistortRectifyMap but it operates on a
+sparse set of points instead of a raster image. Also the function performs a reverse transformation
+to  #projectPoints. In case of a 3D object, it does not reconstruct its 3D coordinates, but for a
+planar object, it does, up to a translation vector, if the proper R is specified.
+
+For each observed point coordinate \f$(u, v)\f$ the function computes:
+\f[
+\begin{array}{l}
+x^{"}  \leftarrow (u - c_x)/f_x  \\
+y^{"}  \leftarrow (v - c_y)/f_y  \\
+(x',y') = undistort(x^{"},y^{"}, \texttt{distCoeffs}) \\
+{[X\,Y\,W]} ^T  \leftarrow R*[x' \, y' \, 1]^T  \\
+x  \leftarrow X/W  \\
+y  \leftarrow Y/W  \\
+\text{only performed if P is specified:} \\
+u'  \leftarrow x {f'}_x + {c'}_x  \\
+v'  \leftarrow y {f'}_y + {c'}_y
+\end{array}
+\f]
+
+where *undistort* is an approximate iterative algorithm that estimates the normalized original
+point coordinates out of the normalized distorted point coordinates ("normalized" means that the
+coordinates do not depend on the camera matrix).
+
+The function can be used for both a stereo camera head or a monocular camera (when R is empty).
+@param src Observed point coordinates, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel (CV_32FC2 or CV_64FC2) (or
+vector\<Point2f\> ).
+@param dst Output ideal point coordinates (1xN/Nx1 2-channel or vector\<Point2f\> ) after undistortion and reverse perspective
+transformation. If matrix P is identity or omitted, dst will contain normalized point coordinates.
+@param cameraMatrix Camera matrix \f$\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+@param distCoeffs Input vector of distortion coefficients
+\f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6[, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])\f$
+of 4, 5, 8, 12 or 14 elements. If the vector is NULL/empty, the zero distortion coefficients are assumed.
+@param R Rectification transformation in the object space (3x3 matrix). R1 or R2 computed by
+#stereoRectify can be passed here. If the matrix is empty, the identity transformation is used.
+@param P New camera matrix (3x3) or new projection matrix (3x4) \f$\begin{bmatrix} {f'}_x & 0 & {c'}_x & t_x \\ 0 & {f'}_y & {c'}_y & t_y \\ 0 & 0 & 1 & t_z \end{bmatrix}\f$. P1 or P2 computed by
+#stereoRectify can be passed here. If the matrix is empty, the identity new camera matrix is used.
+ */
+CV_EXPORTS_W
+void undistortPoints(InputArray src, OutputArray dst,
+                     InputArray cameraMatrix, InputArray distCoeffs,
+                     InputArray R = noArray(), InputArray P = noArray());
+/** @overload
+    @note Default version of #undistortPoints does 5 iterations to compute undistorted points.
+ */
+CV_EXPORTS_AS(undistortPointsIter)
+void undistortPoints(InputArray src, OutputArray dst,
+                     InputArray cameraMatrix, InputArray distCoeffs,
+                     InputArray R, InputArray P, TermCriteria criteria);
+
+/**
+ * @brief Compute undistorted image points position
+ *
+ * @param src Observed points position, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel (CV_32FC2 or
+CV_64FC2) (or vector\<Point2f\> ).
+ * @param dst Output undistorted points position (1xN/Nx1 2-channel or vector\<Point2f\> ).
+ * @param cameraMatrix Camera matrix \f$\vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ .
+ * @param distCoeffs Distortion coefficients
+ */
+CV_EXPORTS_W
+void undistortImagePoints(InputArray src, OutputArray dst, InputArray cameraMatrix,
+                          InputArray distCoeffs,
+                          TermCriteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5,
+                                                      0.01));
+
+//! @} calib3d
+
+/** @brief The methods in this namespace use a so-called fisheye camera model.
+  @ingroup calib3d_fisheye
+*/
+namespace fisheye
+{
+//! @addtogroup calib3d_fisheye
+//! @{
+
+    enum{
+        CALIB_USE_INTRINSIC_GUESS   = 1 << 0,
+        CALIB_RECOMPUTE_EXTRINSIC   = 1 << 1,
+        CALIB_CHECK_COND            = 1 << 2,
+        CALIB_FIX_SKEW              = 1 << 3,
+        CALIB_FIX_K1                = 1 << 4,
+        CALIB_FIX_K2                = 1 << 5,
+        CALIB_FIX_K3                = 1 << 6,
+        CALIB_FIX_K4                = 1 << 7,
+        CALIB_FIX_INTRINSIC         = 1 << 8,
+        CALIB_FIX_PRINCIPAL_POINT   = 1 << 9,
+        CALIB_ZERO_DISPARITY        = 1 << 10,
+        CALIB_FIX_FOCAL_LENGTH      = 1 << 11
+    };
+
+    /** @brief Projects points using fisheye model
+
+    @param objectPoints Array of object points, 1xN/Nx1 3-channel (or vector\<Point3f\> ), where N is
+    the number of points in the view.
+    @param imagePoints Output array of image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, or
+    vector\<Point2f\>.
+    @param affine
+    @param K Camera intrinsic matrix \f$\cameramatrix{K}\f$.
+    @param D Input vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param alpha The skew coefficient.
+    @param jacobian Optional output 2Nx15 jacobian matrix of derivatives of image points with respect
+    to components of the focal lengths, coordinates of the principal point, distortion coefficients,
+    rotation vector, translation vector, and the skew. In the old interface different components of
+    the jacobian are returned via different output parameters.
+
+    The function computes projections of 3D points to the image plane given intrinsic and extrinsic
+    camera parameters. Optionally, the function computes Jacobians - matrices of partial derivatives of
+    image points coordinates (as functions of all the input parameters) with respect to the particular
+    parameters, intrinsic and/or extrinsic.
+     */
+    CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, const Affine3d& affine,
+        InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
+
+    /** @overload */
+    CV_EXPORTS_W void projectPoints(InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec,
+        InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
+
+    /** @brief Distorts 2D points using fisheye model.
+
+    @param undistorted Array of object points, 1xN/Nx1 2-channel (or vector\<Point2f\> ), where N is
+    the number of points in the view.
+    @param K Camera intrinsic matrix \f$\cameramatrix{K}\f$.
+    @param D Input vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param alpha The skew coefficient.
+    @param distorted Output array of image points, 1xN/Nx1 2-channel, or vector\<Point2f\> .
+
+    Note that the function assumes the camera intrinsic matrix of the undistorted points to be identity.
+    This means if you want to distort image points you have to multiply them with \f$K^{-1}\f$ or
+    use another function overload.
+     */
+    CV_EXPORTS_W void distortPoints(InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha = 0);
+
+    /** @overload
+    Overload of distortPoints function to handle cases when undistorted points are obtained with non-identity
+    camera matrix, e.g. output of #estimateNewCameraMatrixForUndistortRectify.
+    @param undistorted Array of object points, 1xN/Nx1 2-channel (or vector\<Point2f\> ), where N is
+    the number of points in the view.
+    @param Kundistorted Camera intrinsic matrix used as new camera matrix for undistortion.
+    @param K Camera intrinsic matrix \f$\cameramatrix{K}\f$.
+    @param D Input vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param alpha The skew coefficient.
+    @param distorted Output array of image points, 1xN/Nx1 2-channel, or vector\<Point2f\> .
+    @sa estimateNewCameraMatrixForUndistortRectify
+    */
+    CV_EXPORTS_W void distortPoints(InputArray undistorted, OutputArray distorted, InputArray Kundistorted, InputArray K, InputArray D, double alpha = 0);
+
+    /** @brief Undistorts 2D points using fisheye model
+
+    @param distorted Array of object points, 1xN/Nx1 2-channel (or vector\<Point2f\> ), where N is the
+    number of points in the view.
+    @param K Camera intrinsic matrix \f$\cameramatrix{K}\f$.
+    @param D Input vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param R Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3
+    1-channel or 1x1 3-channel
+    @param P New camera intrinsic matrix (3x3) or new projection matrix (3x4)
+    @param criteria Termination criteria
+    @param undistorted Output array of image points, 1xN/Nx1 2-channel, or vector\<Point2f\> .
+     */
+    CV_EXPORTS_W void undistortPoints(InputArray distorted, OutputArray undistorted,
+        InputArray K, InputArray D, InputArray R = noArray(), InputArray P  = noArray(),
+                TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 10, 1e-8));
+
+    /** @brief Computes undistortion and rectification maps for image transform by #remap. If D is empty zero
+    distortion is used, if R or P is empty identity matrixes are used.
+
+    @param K Camera intrinsic matrix \f$\cameramatrix{K}\f$.
+    @param D Input vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param R Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3
+    1-channel or 1x1 3-channel
+    @param P New camera intrinsic matrix (3x3) or new projection matrix (3x4)
+    @param size Undistorted image size.
+    @param m1type Type of the first output map that can be CV_32FC1 or CV_16SC2 . See #convertMaps
+    for details.
+    @param map1 The first output map.
+    @param map2 The second output map.
+     */
+    CV_EXPORTS_W void initUndistortRectifyMap(InputArray K, InputArray D, InputArray R, InputArray P,
+        const cv::Size& size, int m1type, OutputArray map1, OutputArray map2);
+
+    /** @brief Transforms an image to compensate for fisheye lens distortion.
+
+    @param distorted image with fisheye lens distortion.
+    @param undistorted Output image with compensated fisheye lens distortion.
+    @param K Camera intrinsic matrix \f$\cameramatrix{K}\f$.
+    @param D Input vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param Knew Camera intrinsic matrix of the distorted image. By default, it is the identity matrix but you
+    may additionally scale and shift the result by using a different matrix.
+    @param new_size the new size
+
+    The function transforms an image to compensate radial and tangential lens distortion.
+
+    The function is simply a combination of #fisheye::initUndistortRectifyMap (with unity R ) and #remap
+    (with bilinear interpolation). See the former function for details of the transformation being
+    performed.
+
+    See below the results of undistortImage.
+       -   a\) result of undistort of perspective camera model (all possible coefficients (k_1, k_2, k_3,
+            k_4, k_5, k_6) of distortion were optimized under calibration)
+        -   b\) result of #fisheye::undistortImage of fisheye camera model (all possible coefficients (k_1, k_2,
+            k_3, k_4) of fisheye distortion were optimized under calibration)
+        -   c\) original image was captured with fisheye lens
+
+    Pictures a) and b) almost the same. But if we consider points of image located far from the center
+    of image, we can notice that on image a) these points are distorted.
+
+    ![image](pics/fisheye_undistorted.jpg)
+     */
+    CV_EXPORTS_W void undistortImage(InputArray distorted, OutputArray undistorted,
+        InputArray K, InputArray D, InputArray Knew = cv::noArray(), const Size& new_size = Size());
+
+    /** @brief Estimates new camera intrinsic matrix for undistortion or rectification.
+
+    @param K Camera intrinsic matrix \f$\cameramatrix{K}\f$.
+    @param image_size Size of the image
+    @param D Input vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param R Rectification transformation in the object space: 3x3 1-channel, or vector: 3x1/1x3
+    1-channel or 1x1 3-channel
+    @param P New camera intrinsic matrix (3x3) or new projection matrix (3x4)
+    @param balance Sets the new focal length in range between the min focal length and the max focal
+    length. Balance is in range of [0, 1].
+    @param new_size the new size
+    @param fov_scale Divisor for new focal length.
+     */
+    CV_EXPORTS_W void estimateNewCameraMatrixForUndistortRectify(InputArray K, InputArray D, const Size &image_size, InputArray R,
+        OutputArray P, double balance = 0.0, const Size& new_size = Size(), double fov_scale = 1.0);
+
+    /** @brief Performs camera calibration
+
+    @param objectPoints vector of vectors of calibration pattern points in the calibration pattern
+    coordinate space.
+    @param imagePoints vector of vectors of the projections of calibration pattern points.
+    imagePoints.size() and objectPoints.size() and imagePoints[i].size() must be equal to
+    objectPoints[i].size() for each i.
+    @param image_size Size of the image used only to initialize the camera intrinsic matrix.
+    @param K Output 3x3 floating-point camera intrinsic matrix
+    \f$\cameramatrix{A}\f$ . If
+    @ref fisheye::CALIB_USE_INTRINSIC_GUESS is specified, some or all of fx, fy, cx, cy must be
+    initialized before calling the function.
+    @param D Output vector of distortion coefficients \f$\distcoeffsfisheye\f$.
+    @param rvecs Output vector of rotation vectors (see @ref Rodrigues ) estimated for each pattern view.
+    That is, each k-th rotation vector together with the corresponding k-th translation vector (see
+    the next output parameter description) brings the calibration pattern from the model coordinate
+    space (in which object points are specified) to the world coordinate space, that is, a real
+    position of the calibration pattern in the k-th pattern view (k=0.. *M* -1).
+    @param tvecs Output vector of translation vectors estimated for each pattern view.
+    @param flags Different flags that may be zero or a combination of the following values:
+    -    @ref fisheye::CALIB_USE_INTRINSIC_GUESS  cameraMatrix contains valid initial values of
+    fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image
+    center ( imageSize is used), and focal distances are computed in a least-squares fashion.
+    -    @ref fisheye::CALIB_RECOMPUTE_EXTRINSIC  Extrinsic will be recomputed after each iteration
+    of intrinsic optimization.
+    -    @ref fisheye::CALIB_CHECK_COND  The functions will check validity of condition number.
+    -    @ref fisheye::CALIB_FIX_SKEW  Skew coefficient (alpha) is set to zero and stay zero.
+    -    @ref fisheye::CALIB_FIX_K1,..., @ref fisheye::CALIB_FIX_K4 Selected distortion coefficients
+    are set to zeros and stay zero.
+    -    @ref fisheye::CALIB_FIX_PRINCIPAL_POINT  The principal point is not changed during the global
+optimization. It stays at the center or at a different location specified when @ref fisheye::CALIB_USE_INTRINSIC_GUESS is set too.
+    -    @ref fisheye::CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global
+optimization. It is the \f$max(width,height)/\pi\f$ or the provided \f$f_x\f$, \f$f_y\f$ when @ref fisheye::CALIB_USE_INTRINSIC_GUESS is set too.
+    @param criteria Termination criteria for the iterative optimization algorithm.
+     */
+    CV_EXPORTS_W double calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size,
+        InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0,
+            TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
+
+    /** @brief Stereo rectification for fisheye camera model
+
+    @param K1 First camera intrinsic matrix.
+    @param D1 First camera distortion parameters.
+    @param K2 Second camera intrinsic matrix.
+    @param D2 Second camera distortion parameters.
+    @param imageSize Size of the image used for stereo calibration.
+    @param R Rotation matrix between the coordinate systems of the first and the second
+    cameras.
+    @param tvec Translation vector between coordinate systems of the cameras.
+    @param R1 Output 3x3 rectification transform (rotation matrix) for the first camera.
+    @param R2 Output 3x3 rectification transform (rotation matrix) for the second camera.
+    @param P1 Output 3x4 projection matrix in the new (rectified) coordinate systems for the first
+    camera.
+    @param P2 Output 3x4 projection matrix in the new (rectified) coordinate systems for the second
+    camera.
+    @param Q Output \f$4 \times 4\f$ disparity-to-depth mapping matrix (see #reprojectImageTo3D ).
+    @param flags Operation flags that may be zero or @ref fisheye::CALIB_ZERO_DISPARITY . If the flag is set,
+    the function makes the principal points of each camera have the same pixel coordinates in the
+    rectified views. And if the flag is not set, the function may still shift the images in the
+    horizontal or vertical direction (depending on the orientation of epipolar lines) to maximize the
+    useful image area.
+    @param newImageSize New image resolution after rectification. The same size should be passed to
+    #initUndistortRectifyMap (see the stereo_calib.cpp sample in OpenCV samples directory). When (0,0)
+    is passed (default), it is set to the original imageSize . Setting it to larger value can help you
+    preserve details in the original image, especially when there is a big radial distortion.
+    @param balance Sets the new focal length in range between the min focal length and the max focal
+    length. Balance is in range of [0, 1].
+    @param fov_scale Divisor for new focal length.
+     */
+    CV_EXPORTS_W void stereoRectify(InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec,
+        OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize = Size(),
+        double balance = 0.0, double fov_scale = 1.0);
+
+    /** @brief Performs stereo calibration
+
+    @param objectPoints Vector of vectors of the calibration pattern points.
+    @param imagePoints1 Vector of vectors of the projections of the calibration pattern points,
+    observed by the first camera.
+    @param imagePoints2 Vector of vectors of the projections of the calibration pattern points,
+    observed by the second camera.
+    @param K1 Input/output first camera intrinsic matrix:
+    \f$\vecthreethree{f_x^{(j)}}{0}{c_x^{(j)}}{0}{f_y^{(j)}}{c_y^{(j)}}{0}{0}{1}\f$ , \f$j = 0,\, 1\f$ . If
+    any of @ref fisheye::CALIB_USE_INTRINSIC_GUESS , @ref fisheye::CALIB_FIX_INTRINSIC are specified,
+    some or all of the matrix components must be initialized.
+    @param D1 Input/output vector of distortion coefficients \f$\distcoeffsfisheye\f$ of 4 elements.
+    @param K2 Input/output second camera intrinsic matrix. The parameter is similar to K1 .
+    @param D2 Input/output lens distortion coefficients for the second camera. The parameter is
+    similar to D1 .
+    @param imageSize Size of the image used only to initialize camera intrinsic matrix.
+    @param R Output rotation matrix between the 1st and the 2nd camera coordinate systems.
+    @param T Output translation vector between the coordinate systems of the cameras.
+    @param rvecs Output vector of rotation vectors ( @ref Rodrigues ) estimated for each pattern view in the
+    coordinate system of the first camera of the stereo pair (e.g. std::vector<cv::Mat>). More in detail, each
+    i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter
+    description) brings the calibration pattern from the object coordinate space (in which object points are
+    specified) to the camera coordinate space of the first camera of the stereo pair. In more technical terms,
+    the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space
+    to camera coordinate space of the first camera of the stereo pair.
+    @param tvecs Output vector of translation vectors estimated for each pattern view, see parameter description
+    of previous output parameter ( rvecs ).
+    @param flags Different flags that may be zero or a combination of the following values:
+    -    @ref fisheye::CALIB_FIX_INTRINSIC  Fix K1, K2? and D1, D2? so that only R, T matrices
+    are estimated.
+    -    @ref fisheye::CALIB_USE_INTRINSIC_GUESS  K1, K2 contains valid initial values of
+    fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image
+    center (imageSize is used), and focal distances are computed in a least-squares fashion.
+    -    @ref fisheye::CALIB_RECOMPUTE_EXTRINSIC  Extrinsic will be recomputed after each iteration
+    of intrinsic optimization.
+    -    @ref fisheye::CALIB_CHECK_COND  The functions will check validity of condition number.
+    -    @ref fisheye::CALIB_FIX_SKEW  Skew coefficient (alpha) is set to zero and stay zero.
+    -   @ref fisheye::CALIB_FIX_K1,..., @ref fisheye::CALIB_FIX_K4 Selected distortion coefficients are set to zeros and stay
+    zero.
+    @param criteria Termination criteria for the iterative optimization algorithm.
+     */
+    CV_EXPORTS_W double stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
+                                  InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize,
+                                  OutputArray R, OutputArray T, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = fisheye::CALIB_FIX_INTRINSIC,
+                                  TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
+
+    /// @overload
+    CV_EXPORTS_W double stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
+                                  InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize,
+                                  OutputArray R, OutputArray T, int flags = fisheye::CALIB_FIX_INTRINSIC,
+                                  TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
+
+    /**
+    @brief Finds an object pose from 3D-2D point correspondences for fisheye camera moodel.
+
+    @param objectPoints Array of object points in the object coordinate space, Nx3 1-channel or
+    1xN/Nx1 3-channel, where N is the number of points. vector\<Point3d\> can be also passed here.
+    @param imagePoints Array of corresponding image points, Nx2 1-channel or 1xN/Nx1 2-channel,
+    where N is the number of points. vector\<Point2d\> can be also passed here.
+    @param cameraMatrix Input camera intrinsic matrix \f$\cameramatrix{A}\f$ .
+    @param distCoeffs Input vector of distortion coefficients (4x1/1x4).
+    @param rvec Output rotation vector (see @ref Rodrigues ) that, together with tvec, brings points from
+    the model coordinate system to the camera coordinate system.
+    @param tvec Output translation vector.
+    @param useExtrinsicGuess Parameter used for #SOLVEPNP_ITERATIVE. If true (1), the function uses
+    the provided rvec and tvec values as initial approximations of the rotation and translation
+    vectors, respectively, and further optimizes them.
+    @param flags Method for solving a PnP problem: see @ref calib3d_solvePnP_flags
+    This function returns the rotation and the translation vectors that transform a 3D point expressed in the object
+    coordinate frame to the camera coordinate frame, using different methods:
+    - P3P methods (@ref SOLVEPNP_P3P, @ref SOLVEPNP_AP3P): need 4 input points to return a unique solution.
+    - @ref SOLVEPNP_IPPE Input points must be >= 4 and object points must be coplanar.
+    - @ref SOLVEPNP_IPPE_SQUARE Special case suitable for marker pose estimation.
+    Number of input points must be 4. Object points must be defined in the following order:
+    - point 0: [-squareLength / 2,  squareLength / 2, 0]
+    - point 1: [ squareLength / 2,  squareLength / 2, 0]
+    - point 2: [ squareLength / 2, -squareLength / 2, 0]
+    - point 3: [-squareLength / 2, -squareLength / 2, 0]
+    - for all the other flags, number of input points must be >= 4 and object points can be in any configuration.
+    @param criteria Termination criteria for internal undistortPoints call.
+    The function interally undistorts points with @ref undistortPoints and call @ref cv::solvePnP,
+    thus the input are very similar. More information about Perspective-n-Points is described in @ref calib3d_solvePnP
+    for more information.
+    */
+    CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
+                                InputArray cameraMatrix, InputArray distCoeffs,
+                                OutputArray rvec, OutputArray tvec,
+                                bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE,
+                                TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 10, 1e-8)
+                              );
+
+//! @} calib3d_fisheye
+} // end namespace fisheye
+
+} //end namespace cv
+
+#if 0 //def __cplusplus
+//////////////////////////////////////////////////////////////////////////////////////////
+class CV_EXPORTS CvLevMarq
+{
+public:
+    CvLevMarq();
+    CvLevMarq( int nparams, int nerrs, CvTermCriteria criteria=
+              cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
+              bool completeSymmFlag=false );
+    ~CvLevMarq();
+    void init( int nparams, int nerrs, CvTermCriteria criteria=
+              cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
+              bool completeSymmFlag=false );
+    bool update( const CvMat*& param, CvMat*& J, CvMat*& err );
+    bool updateAlt( const CvMat*& param, CvMat*& JtJ, CvMat*& JtErr, double*& errNorm );
+
+    void clear();
+    void step();
+    enum { DONE=0, STARTED=1, CALC_J=2, CHECK_ERR=3 };
+
+    cv::Ptr<CvMat> mask;
+    cv::Ptr<CvMat> prevParam;
+    cv::Ptr<CvMat> param;
+    cv::Ptr<CvMat> J;
+    cv::Ptr<CvMat> err;
+    cv::Ptr<CvMat> JtJ;
+    cv::Ptr<CvMat> JtJN;
+    cv::Ptr<CvMat> JtErr;
+    cv::Ptr<CvMat> JtJV;
+    cv::Ptr<CvMat> JtJW;
+    double prevErrNorm, errNorm;
+    int lambdaLg10;
+    CvTermCriteria criteria;
+    int state;
+    int iters;
+    bool completeSymmFlag;
+    int solveMethod;
+};
+#endif
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/calib3d/calib3d.hpp

@@ -0,0 +1,48 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifdef __OPENCV_BUILD
+#error this is a compatibility header which should not be used inside the OpenCV library
+#endif
+
+#include "opencv2/calib3d.hpp"

GameAssist/GameAssist/include/cv2/opencv2/calib3d/calib3d_c.h

@@ -0,0 +1,150 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CALIB3D_C_H
+#define OPENCV_CALIB3D_C_H
+
+#include "opencv2/core/types_c.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/* Calculates fundamental matrix given a set of corresponding points */
+#define CV_FM_7POINT 1
+#define CV_FM_8POINT 2
+
+#define CV_LMEDS 4
+#define CV_RANSAC 8
+
+#define CV_FM_LMEDS_ONLY  CV_LMEDS
+#define CV_FM_RANSAC_ONLY CV_RANSAC
+#define CV_FM_LMEDS CV_LMEDS
+#define CV_FM_RANSAC CV_RANSAC
+
+enum
+{
+    CV_ITERATIVE = 0,
+    CV_EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation"
+    CV_P3P = 2, // X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem"
+    CV_DLS = 3 // Joel A. Hesch and Stergios I. Roumeliotis. "A Direct Least-Squares (DLS) Method for PnP"
+};
+
+#define CV_CALIB_CB_ADAPTIVE_THRESH  1
+#define CV_CALIB_CB_NORMALIZE_IMAGE  2
+#define CV_CALIB_CB_FILTER_QUADS     4
+#define CV_CALIB_CB_FAST_CHECK       8
+
+#define CV_CALIB_USE_INTRINSIC_GUESS  1
+#define CV_CALIB_FIX_ASPECT_RATIO     2
+#define CV_CALIB_FIX_PRINCIPAL_POINT  4
+#define CV_CALIB_ZERO_TANGENT_DIST    8
+#define CV_CALIB_FIX_FOCAL_LENGTH 16
+#define CV_CALIB_FIX_K1  32
+#define CV_CALIB_FIX_K2  64
+#define CV_CALIB_FIX_K3  128
+#define CV_CALIB_FIX_K4  2048
+#define CV_CALIB_FIX_K5  4096
+#define CV_CALIB_FIX_K6  8192
+#define CV_CALIB_RATIONAL_MODEL 16384
+#define CV_CALIB_THIN_PRISM_MODEL 32768
+#define CV_CALIB_FIX_S1_S2_S3_S4  65536
+#define CV_CALIB_TILTED_MODEL  262144
+#define CV_CALIB_FIX_TAUX_TAUY  524288
+#define CV_CALIB_FIX_TANGENT_DIST 2097152
+
+#define CV_CALIB_NINTRINSIC 18
+
+#define CV_CALIB_FIX_INTRINSIC  256
+#define CV_CALIB_SAME_FOCAL_LENGTH 512
+
+#define CV_CALIB_ZERO_DISPARITY 1024
+
+/* stereo correspondence parameters and functions */
+#define CV_STEREO_BM_NORMALIZED_RESPONSE  0
+#define CV_STEREO_BM_XSOBEL               1
+
+#ifdef __cplusplus
+} // extern "C"
+
+//////////////////////////////////////////////////////////////////////////////////////////
+class CV_EXPORTS CvLevMarq
+{
+public:
+    CvLevMarq();
+    CvLevMarq( int nparams, int nerrs, CvTermCriteria criteria=
+              cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
+              bool completeSymmFlag=false );
+    ~CvLevMarq();
+    void init( int nparams, int nerrs, CvTermCriteria criteria=
+              cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
+              bool completeSymmFlag=false );
+    bool update( const CvMat*& param, CvMat*& J, CvMat*& err );
+    bool updateAlt( const CvMat*& param, CvMat*& JtJ, CvMat*& JtErr, double*& errNorm );
+
+    void clear();
+    void step();
+    enum { DONE=0, STARTED=1, CALC_J=2, CHECK_ERR=3 };
+
+    cv::Ptr<CvMat> mask;
+    cv::Ptr<CvMat> prevParam;
+    cv::Ptr<CvMat> param;
+    cv::Ptr<CvMat> J;
+    cv::Ptr<CvMat> err;
+    cv::Ptr<CvMat> JtJ;
+    cv::Ptr<CvMat> JtJN;
+    cv::Ptr<CvMat> JtErr;
+    cv::Ptr<CvMat> JtJV;
+    cv::Ptr<CvMat> JtJW;
+    double prevErrNorm, errNorm;
+    int lambdaLg10;
+    CvTermCriteria criteria;
+    int state;
+    int iters;
+    bool completeSymmFlag;
+    int solveMethod;
+};
+
+#endif
+
+#endif /* OPENCV_CALIB3D_C_H */

GameAssist/GameAssist/include/cv2/opencv2/core.hpp

@@ -0,0 +1,3419 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2015, Intel Corporation, all rights reserved.
+// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2015, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_HPP
+#define OPENCV_CORE_HPP
+
+#ifndef __cplusplus
+#  error core.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/core/cvdef.h"
+#include "opencv2/core/base.hpp"
+#include "opencv2/core/cvstd.hpp"
+#include "opencv2/core/traits.hpp"
+#include "opencv2/core/matx.hpp"
+#include "opencv2/core/types.hpp"
+#include "opencv2/core/mat.hpp"
+#include "opencv2/core/persistence.hpp"
+
+/**
+@defgroup core Core functionality
+
+The Core module is the backbone of OpenCV, offering fundamental data structures, matrix operations,
+and utility functions that other modules depend on. It’s essential for handling image data,
+performing mathematical computations, and managing memory efficiently within the OpenCV ecosystem.
+
+@{
+    @defgroup core_basic Basic structures
+    @defgroup core_array Operations on arrays
+    @defgroup core_async Asynchronous API
+    @defgroup core_xml XML/YAML/JSON Persistence
+    @defgroup core_cluster Clustering
+    @defgroup core_utils Utility and system functions and macros
+    @{
+        @defgroup core_logging Logging facilities
+        @defgroup core_utils_sse SSE utilities
+        @defgroup core_utils_neon NEON utilities
+        @defgroup core_utils_vsx VSX utilities
+        @defgroup core_utils_softfloat Softfloat support
+        @defgroup core_utils_samples Utility functions for OpenCV samples
+    @}
+    @defgroup core_opengl OpenGL interoperability
+    @defgroup core_optim Optimization Algorithms
+    @defgroup core_directx DirectX interoperability
+    @defgroup core_eigen Eigen support
+    @defgroup core_opencl OpenCL support
+    @defgroup core_va_intel Intel VA-API/OpenCL (CL-VA) interoperability
+    @defgroup core_hal Hardware Acceleration Layer
+    @{
+        @defgroup core_hal_functions Functions
+        @defgroup core_hal_interface Interface
+        @defgroup core_hal_intrin Universal intrinsics
+        @{
+            @defgroup core_hal_intrin_impl Private implementation helpers
+        @}
+        @defgroup core_lowlevel_api Low-level API for external libraries / plugins
+    @}
+    @defgroup core_parallel Parallel Processing
+    @{
+        @defgroup core_parallel_backend Parallel backends API
+    @}
+    @defgroup core_quaternion Quaternion
+@}
+ */
+
+namespace cv {
+
+//! @addtogroup core_utils
+//! @{
+
+/*! @brief Class passed to an error.
+
+This class encapsulates all or almost all necessary
+information about the error happened in the program. The exception is
+usually constructed and thrown implicitly via CV_Error and CV_Error_ macros.
+@see error
+ */
+class CV_EXPORTS Exception : public std::exception
+{
+public:
+    /*!
+     Default constructor
+     */
+    Exception();
+    /*!
+     Full constructor. Normally the constructor is not called explicitly.
+     Instead, the macros CV_Error(), CV_Error_() and CV_Assert() are used.
+    */
+    Exception(int _code, const String& _err, const String& _func, const String& _file, int _line);
+    virtual ~Exception() CV_NOEXCEPT;
+
+    /*!
+     \return the error description and the context as a text string.
+    */
+    virtual const char *what() const CV_NOEXCEPT CV_OVERRIDE;
+    void formatMessage();
+
+    String msg; ///< the formatted error message
+
+    int code; ///< error code @see CVStatus
+    String err; ///< error description
+    String func; ///< function name. Available only when the compiler supports getting it
+    String file; ///< source file name where the error has occurred
+    int line; ///< line number in the source file where the error has occurred
+};
+
+/*! @brief Signals an error and raises the exception.
+
+By default the function prints information about the error to stderr,
+then it either stops if cv::setBreakOnError() had been called before or raises the exception.
+It is possible to alternate error processing by using #redirectError().
+@param exc the exception raisen.
+@deprecated drop this version
+ */
+CV_EXPORTS CV_NORETURN void error(const Exception& exc);
+
+enum SortFlags { SORT_EVERY_ROW    = 0, //!< each matrix row is sorted independently
+                 SORT_EVERY_COLUMN = 1, //!< each matrix column is sorted
+                                        //!< independently; this flag and the previous one are
+                                        //!< mutually exclusive.
+                 SORT_ASCENDING    = 0, //!< each matrix row is sorted in the ascending
+                                        //!< order.
+                 SORT_DESCENDING   = 16 //!< each matrix row is sorted in the
+                                        //!< descending order; this flag and the previous one are also
+                                        //!< mutually exclusive.
+               };
+
+//! @} core_utils
+
+//! @addtogroup core_array
+//! @{
+
+//! Covariation flags
+enum CovarFlags {
+    /** The output covariance matrix is calculated as:
+       \f[\texttt{scale}   \cdot  [  \texttt{vects}  [0]-  \texttt{mean}  , \texttt{vects}  [1]-  \texttt{mean}  ,...]^T  \cdot  [ \texttt{vects}  [0]- \texttt{mean}  , \texttt{vects}  [1]- \texttt{mean}  ,...],\f]
+       The covariance matrix will be nsamples x nsamples. Such an unusual covariance matrix is used
+       for fast PCA of a set of very large vectors (see, for example, the EigenFaces technique for
+       face recognition). Eigenvalues of this "scrambled" matrix match the eigenvalues of the true
+       covariance matrix. The "true" eigenvectors can be easily calculated from the eigenvectors of
+       the "scrambled" covariance matrix. */
+    COVAR_SCRAMBLED = 0,
+    /**The output covariance matrix is calculated as:
+        \f[\texttt{scale}   \cdot  [  \texttt{vects}  [0]-  \texttt{mean}  , \texttt{vects}  [1]-  \texttt{mean}  ,...]  \cdot  [ \texttt{vects}  [0]- \texttt{mean}  , \texttt{vects}  [1]- \texttt{mean}  ,...]^T,\f]
+        covar will be a square matrix of the same size as the total number of elements in each input
+        vector. One and only one of #COVAR_SCRAMBLED and #COVAR_NORMAL must be specified.*/
+    COVAR_NORMAL    = 1,
+    /** If the flag is specified, the function does not calculate mean from
+        the input vectors but, instead, uses the passed mean vector. This is useful if mean has been
+        pre-calculated or known in advance, or if the covariance matrix is calculated by parts. In
+        this case, mean is not a mean vector of the input sub-set of vectors but rather the mean
+        vector of the whole set.*/
+    COVAR_USE_AVG   = 2,
+    /** If the flag is specified, the covariance matrix is scaled. In the
+        "normal" mode, scale is 1./nsamples . In the "scrambled" mode, scale is the reciprocal of the
+        total number of elements in each input vector. By default (if the flag is not specified), the
+        covariance matrix is not scaled ( scale=1 ).*/
+    COVAR_SCALE     = 4,
+    /** If the flag is
+        specified, all the input vectors are stored as rows of the samples matrix. mean should be a
+        single-row vector in this case.*/
+    COVAR_ROWS      = 8,
+    /** If the flag is
+        specified, all the input vectors are stored as columns of the samples matrix. mean should be a
+        single-column vector in this case.*/
+    COVAR_COLS      = 16
+};
+
+enum ReduceTypes { REDUCE_SUM = 0, //!< the output is the sum of all rows/columns of the matrix.
+                   REDUCE_AVG = 1, //!< the output is the mean vector of all rows/columns of the matrix.
+                   REDUCE_MAX = 2, //!< the output is the maximum (column/row-wise) of all rows/columns of the matrix.
+                   REDUCE_MIN = 3,  //!< the output is the minimum (column/row-wise) of all rows/columns of the matrix.
+                   REDUCE_SUM2 = 4  //!< the output is the sum of all squared rows/columns of the matrix.
+                 };
+
+/** @brief Swaps two matrices
+*/
+CV_EXPORTS void swap(Mat& a, Mat& b);
+/** @overload */
+CV_EXPORTS void swap( UMat& a, UMat& b );
+
+/** @brief Computes the source location of an extrapolated pixel.
+
+The function computes and returns the coordinate of a donor pixel corresponding to the specified
+extrapolated pixel when using the specified extrapolation border mode. For example, if you use
+cv::BORDER_WRAP mode in the horizontal direction, cv::BORDER_REFLECT_101 in the vertical direction and
+want to compute value of the "virtual" pixel Point(-5, 100) in a floating-point image img, it
+looks like:
+@code{.cpp}
+    float val = img.at<float>(borderInterpolate(100, img.rows, cv::BORDER_REFLECT_101),
+                              borderInterpolate(-5, img.cols, cv::BORDER_WRAP));
+@endcode
+Normally, the function is not called directly. It is used inside filtering functions and also in
+copyMakeBorder.
+@param p 0-based coordinate of the extrapolated pixel along one of the axes, likely \<0 or \>= len
+@param len Length of the array along the corresponding axis.
+@param borderType Border type, one of the #BorderTypes, except for #BORDER_TRANSPARENT and
+#BORDER_ISOLATED. When borderType==#BORDER_CONSTANT, the function always returns -1, regardless
+of p and len.
+
+@sa copyMakeBorder
+*/
+CV_EXPORTS_W int borderInterpolate(int p, int len, int borderType);
+
+/** @example samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp
+An example using copyMakeBorder function.
+Check @ref tutorial_copyMakeBorder "the corresponding tutorial" for more details
+*/
+
+/** @brief Forms a border around an image.
+
+The function copies the source image into the middle of the destination image. The areas to the
+left, to the right, above and below the copied source image will be filled with extrapolated
+pixels. This is not what filtering functions based on it do (they extrapolate pixels on-fly), but
+what other more complex functions, including your own, may do to simplify image boundary handling.
+
+The function supports the mode when src is already in the middle of dst . In this case, the
+function does not copy src itself but simply constructs the border, for example:
+
+@code{.cpp}
+    // let border be the same in all directions
+    int border=2;
+    // constructs a larger image to fit both the image and the border
+    Mat gray_buf(rgb.rows + border*2, rgb.cols + border*2, rgb.depth());
+    // select the middle part of it w/o copying data
+    Mat gray(gray_canvas, Rect(border, border, rgb.cols, rgb.rows));
+    // convert image from RGB to grayscale
+    cvtColor(rgb, gray, COLOR_RGB2GRAY);
+    // form a border in-place
+    copyMakeBorder(gray, gray_buf, border, border,
+                   border, border, BORDER_REPLICATE);
+    // now do some custom filtering ...
+    ...
+@endcode
+@note When the source image is a part (ROI) of a bigger image, the function will try to use the
+pixels outside of the ROI to form a border. To disable this feature and always do extrapolation, as
+if src was not a ROI, use borderType | #BORDER_ISOLATED.
+
+@param src Source image.
+@param dst Destination image of the same type as src and the size Size(src.cols+left+right,
+src.rows+top+bottom) .
+@param top the top pixels
+@param bottom the bottom pixels
+@param left the left pixels
+@param right Parameter specifying how many pixels in each direction from the source image rectangle
+to extrapolate. For example, top=1, bottom=1, left=1, right=1 mean that 1 pixel-wide border needs
+to be built.
+@param borderType Border type. See borderInterpolate for details.
+@param value Border value if borderType==BORDER_CONSTANT .
+
+@sa  borderInterpolate
+*/
+CV_EXPORTS_W void copyMakeBorder(InputArray src, OutputArray dst,
+                                 int top, int bottom, int left, int right,
+                                 int borderType, const Scalar& value = Scalar() );
+
+/** @brief Calculates the per-element sum of two arrays or an array and a scalar.
+
+The function add calculates:
+- Sum of two arrays when both input arrays have the same size and the same number of channels:
+\f[\texttt{dst}(I) =  \texttt{saturate} ( \texttt{src1}(I) +  \texttt{src2}(I)) \quad \texttt{if mask}(I) \ne0\f]
+- Sum of an array and a scalar when src2 is constructed from Scalar or has the same number of
+elements as `src1.channels()`:
+\f[\texttt{dst}(I) =  \texttt{saturate} ( \texttt{src1}(I) +  \texttt{src2} ) \quad \texttt{if mask}(I) \ne0\f]
+- Sum of a scalar and an array when src1 is constructed from Scalar or has the same number of
+elements as `src2.channels()`:
+\f[\texttt{dst}(I) =  \texttt{saturate} ( \texttt{src1} +  \texttt{src2}(I) ) \quad \texttt{if mask}(I) \ne0\f]
+where `I` is a multi-dimensional index of array elements. In case of multi-channel arrays, each
+channel is processed independently.
+
+The first function in the list above can be replaced with matrix expressions:
+@code{.cpp}
+    dst = src1 + src2;
+    dst += src1; // equivalent to add(dst, src1, dst);
+@endcode
+The input arrays and the output array can all have the same or different depths. For example, you
+can add a 16-bit unsigned array to a 8-bit signed array and store the sum as a 32-bit
+floating-point array. Depth of the output array is determined by the dtype parameter. In the second
+and third cases above, as well as in the first case, when src1.depth() == src2.depth(), dtype can
+be set to the default -1. In this case, the output array will have the same depth as the input
+array, be it src1, src2 or both.
+@note Saturation is not applied when the output array has the depth CV_32S. You may even get
+result of an incorrect sign in the case of overflow.
+@note (Python) Be careful to difference behaviour between src1/src2 are single number and they are tuple/array.
+`add(src,X)` means `add(src,(X,X,X,X))`.
+`add(src,(X,))` means `add(src,(X,0,0,0))`.
+@param src1 first input array or a scalar.
+@param src2 second input array or a scalar.
+@param dst output array that has the same size and number of channels as the input array(s); the
+depth is defined by dtype or src1/src2.
+@param mask optional operation mask - 8-bit single channel array, that specifies elements of the
+output array to be changed.
+@param dtype optional depth of the output array (see the discussion below).
+@sa subtract, addWeighted, scaleAdd, Mat::convertTo
+*/
+CV_EXPORTS_W void add(InputArray src1, InputArray src2, OutputArray dst,
+                      InputArray mask = noArray(), int dtype = -1);
+
+/** @brief Calculates the per-element difference between two arrays or array and a scalar.
+
+The function subtract calculates:
+- Difference between two arrays, when both input arrays have the same size and the same number of
+channels:
+    \f[\texttt{dst}(I) =  \texttt{saturate} ( \texttt{src1}(I) -  \texttt{src2}(I)) \quad \texttt{if mask}(I) \ne0\f]
+- Difference between an array and a scalar, when src2 is constructed from Scalar or has the same
+number of elements as `src1.channels()`:
+    \f[\texttt{dst}(I) =  \texttt{saturate} ( \texttt{src1}(I) -  \texttt{src2} ) \quad \texttt{if mask}(I) \ne0\f]
+- Difference between a scalar and an array, when src1 is constructed from Scalar or has the same
+number of elements as `src2.channels()`:
+    \f[\texttt{dst}(I) =  \texttt{saturate} ( \texttt{src1} -  \texttt{src2}(I) ) \quad \texttt{if mask}(I) \ne0\f]
+- The reverse difference between a scalar and an array in the case of `SubRS`:
+    \f[\texttt{dst}(I) =  \texttt{saturate} ( \texttt{src2} -  \texttt{src1}(I) ) \quad \texttt{if mask}(I) \ne0\f]
+where I is a multi-dimensional index of array elements. In case of multi-channel arrays, each
+channel is processed independently.
+
+The first function in the list above can be replaced with matrix expressions:
+@code{.cpp}
+    dst = src1 - src2;
+    dst -= src1; // equivalent to subtract(dst, src1, dst);
+@endcode
+The input arrays and the output array can all have the same or different depths. For example, you
+can subtract to 8-bit unsigned arrays and store the difference in a 16-bit signed array. Depth of
+the output array is determined by dtype parameter. In the second and third cases above, as well as
+in the first case, when src1.depth() == src2.depth(), dtype can be set to the default -1. In this
+case the output array will have the same depth as the input array, be it src1, src2 or both.
+@note Saturation is not applied when the output array has the depth CV_32S. You may even get
+result of an incorrect sign in the case of overflow.
+@note (Python) Be careful to difference behaviour between src1/src2 are single number and they are tuple/array.
+`subtract(src,X)` means `subtract(src,(X,X,X,X))`.
+`subtract(src,(X,))` means `subtract(src,(X,0,0,0))`.
+@param src1 first input array or a scalar.
+@param src2 second input array or a scalar.
+@param dst output array of the same size and the same number of channels as the input array.
+@param mask optional operation mask; this is an 8-bit single channel array that specifies elements
+of the output array to be changed.
+@param dtype optional depth of the output array
+@sa  add, addWeighted, scaleAdd, Mat::convertTo
+  */
+CV_EXPORTS_W void subtract(InputArray src1, InputArray src2, OutputArray dst,
+                           InputArray mask = noArray(), int dtype = -1);
+
+
+/** @brief Calculates the per-element scaled product of two arrays.
+
+The function multiply calculates the per-element product of two arrays:
+
+\f[\texttt{dst} (I)= \texttt{saturate} ( \texttt{scale} \cdot \texttt{src1} (I)  \cdot \texttt{src2} (I))\f]
+
+There is also a @ref MatrixExpressions -friendly variant of the first function. See Mat::mul .
+
+For a not-per-element matrix product, see gemm .
+
+@note Saturation is not applied when the output array has the depth
+CV_32S. You may even get result of an incorrect sign in the case of
+overflow.
+@note (Python) Be careful to difference behaviour between src1/src2 are single number and they are tuple/array.
+`multiply(src,X)` means `multiply(src,(X,X,X,X))`.
+`multiply(src,(X,))` means `multiply(src,(X,0,0,0))`.
+@param src1 first input array.
+@param src2 second input array of the same size and the same type as src1.
+@param dst output array of the same size and type as src1.
+@param scale optional scale factor.
+@param dtype optional depth of the output array
+@sa add, subtract, divide, scaleAdd, addWeighted, accumulate, accumulateProduct, accumulateSquare,
+Mat::convertTo
+*/
+CV_EXPORTS_W void multiply(InputArray src1, InputArray src2,
+                           OutputArray dst, double scale = 1, int dtype = -1);
+
+/** @brief Performs per-element division of two arrays or a scalar by an array.
+
+The function cv::divide divides one array by another:
+\f[\texttt{dst(I) = saturate(src1(I)*scale/src2(I))}\f]
+or a scalar by an array when there is no src1 :
+\f[\texttt{dst(I) = saturate(scale/src2(I))}\f]
+
+Different channels of multi-channel arrays are processed independently.
+
+For integer types when src2(I) is zero, dst(I) will also be zero.
+
+@note In case of floating point data there is no special defined behavior for zero src2(I) values.
+Regular floating-point division is used.
+Expect correct IEEE-754 behaviour for floating-point data (with NaN, Inf result values).
+
+@note Saturation is not applied when the output array has the depth CV_32S. You may even get
+result of an incorrect sign in the case of overflow.
+@note (Python) Be careful to difference behaviour between src1/src2 are single number and they are tuple/array.
+`divide(src,X)` means `divide(src,(X,X,X,X))`.
+`divide(src,(X,))` means `divide(src,(X,0,0,0))`.
+@param src1 first input array.
+@param src2 second input array of the same size and type as src1.
+@param scale scalar factor.
+@param dst output array of the same size and type as src2.
+@param dtype optional depth of the output array; if -1, dst will have depth src2.depth(), but in
+case of an array-by-array division, you can only pass -1 when src1.depth()==src2.depth().
+@sa  multiply, add, subtract
+*/
+CV_EXPORTS_W void divide(InputArray src1, InputArray src2, OutputArray dst,
+                         double scale = 1, int dtype = -1);
+
+/** @overload */
+CV_EXPORTS_W void divide(double scale, InputArray src2,
+                         OutputArray dst, int dtype = -1);
+
+/** @brief Calculates the sum of a scaled array and another array.
+
+The function scaleAdd is one of the classical primitive linear algebra operations, known as DAXPY
+or SAXPY in [BLAS](http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms). It calculates
+the sum of a scaled array and another array:
+\f[\texttt{dst} (I)= \texttt{scale} \cdot \texttt{src1} (I) +  \texttt{src2} (I)\f]
+The function can also be emulated with a matrix expression, for example:
+@code{.cpp}
+    Mat A(3, 3, CV_64F);
+    ...
+    A.row(0) = A.row(1)*2 + A.row(2);
+@endcode
+@param src1 first input array.
+@param alpha scale factor for the first array.
+@param src2 second input array of the same size and type as src1.
+@param dst output array of the same size and type as src1.
+@sa add, addWeighted, subtract, Mat::dot, Mat::convertTo
+*/
+CV_EXPORTS_W void scaleAdd(InputArray src1, double alpha, InputArray src2, OutputArray dst);
+
+/** @brief Calculates the weighted sum of two arrays.
+
+The function addWeighted calculates the weighted sum of two arrays as follows:
+\f[\texttt{dst} (I)= \texttt{saturate} ( \texttt{src1} (I)* \texttt{alpha} +  \texttt{src2} (I)* \texttt{beta} +  \texttt{gamma} )\f]
+where I is a multi-dimensional index of array elements. In case of multi-channel arrays, each
+channel is processed independently.
+The function can be replaced with a matrix expression:
+@code{.cpp}
+    dst = src1*alpha + src2*beta + gamma;
+@endcode
+@note Saturation is not applied when the output array has the depth CV_32S. You may even get
+result of an incorrect sign in the case of overflow.
+@param src1 first input array.
+@param alpha weight of the first array elements.
+@param src2 second input array of the same size and channel number as src1.
+@param beta weight of the second array elements.
+@param gamma scalar added to each sum.
+@param dst output array that has the same size and number of channels as the input arrays.
+@param dtype optional depth of the output array; when both input arrays have the same depth, dtype
+can be set to -1, which will be equivalent to src1.depth().
+@sa  add, subtract, scaleAdd, Mat::convertTo
+*/
+CV_EXPORTS_W void addWeighted(InputArray src1, double alpha, InputArray src2,
+                              double beta, double gamma, OutputArray dst, int dtype = -1);
+
+/** @brief Scales, calculates absolute values, and converts the result to 8-bit.
+
+On each element of the input array, the function convertScaleAbs
+performs three operations sequentially: scaling, taking an absolute
+value, conversion to an unsigned 8-bit type:
+\f[\texttt{dst} (I)= \texttt{saturate\_cast<uchar>} (| \texttt{src} (I)* \texttt{alpha} +  \texttt{beta} |)\f]
+In case of multi-channel arrays, the function processes each channel
+independently. When the output is not 8-bit, the operation can be
+emulated by calling the Mat::convertTo method (or by using matrix
+expressions) and then by calculating an absolute value of the result.
+For example:
+@code{.cpp}
+    Mat_<float> A(30,30);
+    randu(A, Scalar(-100), Scalar(100));
+    Mat_<float> B = A*5 + 3;
+    B = abs(B);
+    // Mat_<float> B = abs(A*5+3) will also do the job,
+    // but it will allocate a temporary matrix
+@endcode
+@param src input array.
+@param dst output array.
+@param alpha optional scale factor.
+@param beta optional delta added to the scaled values.
+@sa  Mat::convertTo, cv::abs(const Mat&)
+*/
+CV_EXPORTS_W void convertScaleAbs(InputArray src, OutputArray dst,
+                                  double alpha = 1, double beta = 0);
+
+/** @brief Converts an array to half precision floating number.
+
+This function converts FP32 (single precision floating point) from/to FP16 (half precision floating point). CV_16S format is used to represent FP16 data.
+There are two use modes (src -> dst): CV_32F -> CV_16S and CV_16S -> CV_32F. The input array has to have type of CV_32F or
+CV_16S to represent the bit depth. If the input array is neither of them, the function will raise an error.
+The format of half precision floating point is defined in IEEE 754-2008.
+
+@param src input array.
+@param dst output array.
+
+@deprecated Use Mat::convertTo with CV_16F instead.
+*/
+CV_EXPORTS_W void convertFp16(InputArray src, OutputArray dst);
+
+/** @example samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp
+Check @ref tutorial_how_to_scan_images "the corresponding tutorial" for more details
+*/
+
+/** @brief Performs a look-up table transform of an array.
+
+The function LUT fills the output array with values from the look-up table. Indices of the entries
+are taken from the input array. That is, the function processes each element of src as follows:
+\f[\texttt{dst} (I)  \leftarrow \texttt{lut(src(I) + d)}\f]
+where
+\f[d =  \fork{0}{if \(\texttt{src}\) has depth \(\texttt{CV_8U}\)}{128}{if \(\texttt{src}\) has depth \(\texttt{CV_8S}\)}\f]
+@param src input array of 8-bit elements.
+@param lut look-up table of 256 elements; in case of multi-channel input array, the table should
+either have a single channel (in this case the same table is used for all channels) or the same
+number of channels as in the input array.
+@param dst output array of the same size and number of channels as src, and the same depth as lut.
+@sa  convertScaleAbs, Mat::convertTo
+*/
+CV_EXPORTS_W void LUT(InputArray src, InputArray lut, OutputArray dst);
+
+/** @brief Calculates the sum of array elements.
+
+The function cv::sum calculates and returns the sum of array elements,
+independently for each channel.
+@param src input array that must have from 1 to 4 channels.
+@sa  countNonZero, mean, meanStdDev, norm, minMaxLoc, reduce
+*/
+CV_EXPORTS_AS(sumElems) Scalar sum(InputArray src);
+
+/** @brief Checks for the presence of at least one non-zero array element.
+
+The function returns whether there are non-zero elements in src
+
+The function do not work with multi-channel arrays. If you need to check non-zero array
+elements across all the channels, use Mat::reshape first to reinterpret the array as
+single-channel. Or you may extract the particular channel using either extractImageCOI, or
+mixChannels, or split.
+
+@note
+- If the location of non-zero array elements is important, @ref findNonZero is helpful.
+- If the count of non-zero array elements is important, @ref countNonZero is helpful.
+@param src single-channel array.
+@sa  mean, meanStdDev, norm, minMaxLoc, calcCovarMatrix
+@sa  findNonZero, countNonZero
+*/
+CV_EXPORTS_W bool hasNonZero( InputArray src );
+
+/** @brief Counts non-zero array elements.
+
+The function returns the number of non-zero elements in src :
+\f[\sum _{I: \; \texttt{src} (I) \ne0 } 1\f]
+
+The function do not work with multi-channel arrays. If you need to count non-zero array
+elements across all the channels, use Mat::reshape first to reinterpret the array as
+single-channel. Or you may extract the particular channel using either extractImageCOI, or
+mixChannels, or split.
+
+@note
+- If only whether there are non-zero elements is important, @ref hasNonZero is helpful.
+- If the location of non-zero array elements is important, @ref findNonZero is helpful.
+@param src single-channel array.
+@sa  mean, meanStdDev, norm, minMaxLoc, calcCovarMatrix
+@sa  findNonZero, hasNonZero
+*/
+CV_EXPORTS_W int countNonZero( InputArray src );
+
+/** @brief Returns the list of locations of non-zero pixels
+
+Given a binary matrix (likely returned from an operation such
+as threshold(), compare(), >, ==, etc, return all of
+the non-zero indices as a cv::Mat or std::vector<cv::Point> (x,y)
+For example:
+@code{.cpp}
+    cv::Mat binaryImage; // input, binary image
+    cv::Mat locations;   // output, locations of non-zero pixels
+    cv::findNonZero(binaryImage, locations);
+
+    // access pixel coordinates
+    Point pnt = locations.at<Point>(i);
+@endcode
+or
+@code{.cpp}
+    cv::Mat binaryImage; // input, binary image
+    vector<Point> locations;   // output, locations of non-zero pixels
+    cv::findNonZero(binaryImage, locations);
+
+    // access pixel coordinates
+    Point pnt = locations[i];
+@endcode
+
+The function do not work with multi-channel arrays. If you need to find non-zero
+elements across all the channels, use Mat::reshape first to reinterpret the array as
+single-channel. Or you may extract the particular channel using either extractImageCOI, or
+mixChannels, or split.
+
+@note
+- If only count of non-zero array elements is important, @ref countNonZero is helpful.
+- If only whether there are non-zero elements is important, @ref hasNonZero is helpful.
+@param src single-channel array
+@param idx the output array, type of cv::Mat or std::vector<Point>, corresponding to non-zero indices in the input
+@sa  countNonZero, hasNonZero
+*/
+CV_EXPORTS_W void findNonZero( InputArray src, OutputArray idx );
+
+/** @brief Calculates an average (mean) of array elements.
+
+The function cv::mean calculates the mean value M of array elements,
+independently for each channel, and return it:
+\f[\begin{array}{l} N =  \sum _{I: \; \texttt{mask} (I) \ne 0} 1 \\ M_c =  \left ( \sum _{I: \; \texttt{mask} (I) \ne 0}{ \texttt{mtx} (I)_c} \right )/N \end{array}\f]
+When all the mask elements are 0's, the function returns Scalar::all(0)
+@param src input array that should have from 1 to 4 channels so that the result can be stored in
+Scalar_ .
+@param mask optional operation mask.
+@sa  countNonZero, meanStdDev, norm, minMaxLoc
+*/
+CV_EXPORTS_W Scalar mean(InputArray src, InputArray mask = noArray());
+
+/** Calculates a mean and standard deviation of array elements.
+
+The function cv::meanStdDev calculates the mean and the standard deviation M
+of array elements independently for each channel and returns it via the
+output parameters:
+\f[\begin{array}{l} N =  \sum _{I, \texttt{mask} (I)  \ne 0} 1 \\ \texttt{mean} _c =  \frac{\sum_{ I: \; \texttt{mask}(I) \ne 0} \texttt{src} (I)_c}{N} \\ \texttt{stddev} _c =  \sqrt{\frac{\sum_{ I: \; \texttt{mask}(I) \ne 0} \left ( \texttt{src} (I)_c -  \texttt{mean} _c \right )^2}{N}} \end{array}\f]
+When all the mask elements are 0's, the function returns
+mean=stddev=Scalar::all(0).
+@note The calculated standard deviation is only the diagonal of the
+complete normalized covariance matrix. If the full matrix is needed, you
+can reshape the multi-channel array M x N to the single-channel array
+M\*N x mtx.channels() (only possible when the matrix is continuous) and
+then pass the matrix to calcCovarMatrix .
+@param src input array that should have from 1 to 4 channels so that the results can be stored in
+Scalar_ 's.
+@param mean output parameter: calculated mean value.
+@param stddev output parameter: calculated standard deviation.
+@param mask optional operation mask.
+@sa  countNonZero, mean, norm, minMaxLoc, calcCovarMatrix
+*/
+CV_EXPORTS_W void meanStdDev(InputArray src, OutputArray mean, OutputArray stddev,
+                             InputArray mask=noArray());
+
+/** @brief Calculates the  absolute norm of an array.
+
+This version of #norm calculates the absolute norm of src1. The type of norm to calculate is specified using #NormTypes.
+
+As example for one array consider the function \f$r(x)= \begin{pmatrix} x \\ 1-x \end{pmatrix}, x \in [-1;1]\f$.
+The \f$ L_{1}, L_{2} \f$ and \f$ L_{\infty} \f$ norm for the sample value \f$r(-1) = \begin{pmatrix} -1 \\ 2 \end{pmatrix}\f$
+is calculated as follows
+\f{align*}
+    \| r(-1) \|_{L_1} &= |-1| + |2| = 3 \\
+    \| r(-1) \|_{L_2} &= \sqrt{(-1)^{2} + (2)^{2}} = \sqrt{5} \\
+    \| r(-1) \|_{L_\infty} &= \max(|-1|,|2|) = 2
+\f}
+and for \f$r(0.5) = \begin{pmatrix} 0.5 \\ 0.5 \end{pmatrix}\f$ the calculation is
+\f{align*}
+    \| r(0.5) \|_{L_1} &= |0.5| + |0.5| = 1 \\
+    \| r(0.5) \|_{L_2} &= \sqrt{(0.5)^{2} + (0.5)^{2}} = \sqrt{0.5} \\
+    \| r(0.5) \|_{L_\infty} &= \max(|0.5|,|0.5|) = 0.5.
+\f}
+The following graphic shows all values for the three norm functions \f$\| r(x) \|_{L_1}, \| r(x) \|_{L_2}\f$ and \f$\| r(x) \|_{L_\infty}\f$.
+It is notable that the \f$ L_{1} \f$ norm forms the upper and the \f$ L_{\infty} \f$ norm forms the lower border for the example function \f$ r(x) \f$.
+![Graphs for the different norm functions from the above example](pics/NormTypes_OneArray_1-2-INF.png)
+
+When the mask parameter is specified and it is not empty, the norm is
+
+If normType is not specified, #NORM_L2 is used.
+calculated only over the region specified by the mask.
+
+Multi-channel input arrays are treated as single-channel arrays, that is,
+the results for all channels are combined.
+
+Hamming norms can only be calculated with CV_8U depth arrays.
+
+@param src1 first input array.
+@param normType type of the norm (see #NormTypes).
+@param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type.
+*/
+CV_EXPORTS_W double norm(InputArray src1, int normType = NORM_L2, InputArray mask = noArray());
+
+/** @brief Calculates an absolute difference norm or a relative difference norm.
+
+This version of cv::norm calculates the absolute difference norm
+or the relative difference norm of arrays src1 and src2.
+The type of norm to calculate is specified using #NormTypes.
+
+@param src1 first input array.
+@param src2 second input array of the same size and the same type as src1.
+@param normType type of the norm (see #NormTypes).
+@param mask optional operation mask; it must have the same size as src1 and CV_8UC1 type.
+*/
+CV_EXPORTS_W double norm(InputArray src1, InputArray src2,
+                         int normType = NORM_L2, InputArray mask = noArray());
+/** @overload
+@param src first input array.
+@param normType type of the norm (see #NormTypes).
+*/
+CV_EXPORTS double norm( const SparseMat& src, int normType );
+
+/** @brief Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric.
+
+This function calculates the Peak Signal-to-Noise Ratio (PSNR) image quality metric in decibels (dB),
+between two input arrays src1 and src2. The arrays must have the same type.
+
+The PSNR is calculated as follows:
+
+\f[
+\texttt{PSNR} = 10 \cdot \log_{10}{\left( \frac{R^2}{MSE} \right) }
+\f]
+
+where R is the maximum integer value of depth (e.g. 255 in the case of CV_8U data)
+and MSE is the mean squared error between the two arrays.
+
+@param src1 first input array.
+@param src2 second input array of the same size as src1.
+@param R the maximum pixel value (255 by default)
+
+  */
+CV_EXPORTS_W double PSNR(InputArray src1, InputArray src2, double R=255.);
+
+/** @brief naive nearest neighbor finder
+
+see http://en.wikipedia.org/wiki/Nearest_neighbor_search
+@todo document
+  */
+CV_EXPORTS_W void batchDistance(InputArray src1, InputArray src2,
+                                OutputArray dist, int dtype, OutputArray nidx,
+                                int normType = NORM_L2, int K = 0,
+                                InputArray mask = noArray(), int update = 0,
+                                bool crosscheck = false);
+
+/** @brief Normalizes the norm or value range of an array.
+
+The function cv::normalize normalizes scale and shift the input array elements so that
+\f[\| \texttt{dst} \| _{L_p}= \texttt{alpha}\f]
+(where p=Inf, 1 or 2) when normType=NORM_INF, NORM_L1, or NORM_L2, respectively; or so that
+\f[\min _I  \texttt{dst} (I)= \texttt{alpha} , \, \, \max _I  \texttt{dst} (I)= \texttt{beta}\f]
+
+when normType=NORM_MINMAX (for dense arrays only). The optional mask specifies a sub-array to be
+normalized. This means that the norm or min-n-max are calculated over the sub-array, and then this
+sub-array is modified to be normalized. If you want to only use the mask to calculate the norm or
+min-max but modify the whole array, you can use norm and Mat::convertTo.
+
+In case of sparse matrices, only the non-zero values are analyzed and transformed. Because of this,
+the range transformation for sparse matrices is not allowed since it can shift the zero level.
+
+Possible usage with some positive example data:
+@code{.cpp}
+    vector<double> positiveData = { 2.0, 8.0, 10.0 };
+    vector<double> normalizedData_l1, normalizedData_l2, normalizedData_inf, normalizedData_minmax;
+
+    // Norm to probability (total count)
+    // sum(numbers) = 20.0
+    // 2.0      0.1     (2.0/20.0)
+    // 8.0      0.4     (8.0/20.0)
+    // 10.0     0.5     (10.0/20.0)
+    normalize(positiveData, normalizedData_l1, 1.0, 0.0, NORM_L1);
+
+    // Norm to unit vector: ||positiveData|| = 1.0
+    // 2.0      0.15
+    // 8.0      0.62
+    // 10.0     0.77
+    normalize(positiveData, normalizedData_l2, 1.0, 0.0, NORM_L2);
+
+    // Norm to max element
+    // 2.0      0.2     (2.0/10.0)
+    // 8.0      0.8     (8.0/10.0)
+    // 10.0     1.0     (10.0/10.0)
+    normalize(positiveData, normalizedData_inf, 1.0, 0.0, NORM_INF);
+
+    // Norm to range [0.0;1.0]
+    // 2.0      0.0     (shift to left border)
+    // 8.0      0.75    (6.0/8.0)
+    // 10.0     1.0     (shift to right border)
+    normalize(positiveData, normalizedData_minmax, 1.0, 0.0, NORM_MINMAX);
+@endcode
+
+@param src input array.
+@param dst output array of the same size as src .
+@param alpha norm value to normalize to or the lower range boundary in case of the range
+normalization.
+@param beta upper range boundary in case of the range normalization; it is not used for the norm
+normalization.
+@param norm_type normalization type (see cv::NormTypes).
+@param dtype when negative, the output array has the same type as src; otherwise, it has the same
+number of channels as src and the depth =CV_MAT_DEPTH(dtype).
+@param mask optional operation mask.
+@sa norm, Mat::convertTo, SparseMat::convertTo
+*/
+CV_EXPORTS_W void normalize( InputArray src, InputOutputArray dst, double alpha = 1, double beta = 0,
+                             int norm_type = NORM_L2, int dtype = -1, InputArray mask = noArray());
+
+/** @overload
+@param src input array.
+@param dst output array of the same size as src .
+@param alpha norm value to normalize to or the lower range boundary in case of the range
+normalization.
+@param normType normalization type (see cv::NormTypes).
+*/
+CV_EXPORTS void normalize( const SparseMat& src, SparseMat& dst, double alpha, int normType );
+
+/** @brief Finds the global minimum and maximum in an array.
+
+The function cv::minMaxLoc finds the minimum and maximum element values and their positions. The
+extrema are searched across the whole array or, if mask is not an empty array, in the specified
+array region.
+
+In C++, if the input is multi-channel, you should omit the minLoc, maxLoc, and mask arguments
+(i.e. leave them as NULL, NULL, and noArray() respectively). These arguments are not
+supported for multi-channel input arrays. If working with multi-channel input and you
+need the minLoc, maxLoc, or mask arguments, then use Mat::reshape first to reinterpret
+the array as single-channel. Alternatively, you can extract the particular channel using either
+extractImageCOI, mixChannels, or split.
+
+In Python, multi-channel input is not supported at all due to a limitation in the
+binding generation process (there is no way to set minLoc and maxLoc to NULL). A
+workaround is to operate on each channel individually or to use NumPy to achieve the same
+functionality.
+
+@param src input single-channel array.
+@param minVal pointer to the returned minimum value; NULL is used if not required.
+@param maxVal pointer to the returned maximum value; NULL is used if not required.
+@param minLoc pointer to the returned minimum location (in 2D case); NULL is used if not required.
+@param maxLoc pointer to the returned maximum location (in 2D case); NULL is used if not required.
+@param mask optional mask used to select a sub-array.
+@sa max, min, reduceArgMin, reduceArgMax, compare, inRange, extractImageCOI, mixChannels, split, Mat::reshape
+*/
+CV_EXPORTS_W void minMaxLoc(InputArray src, CV_OUT double* minVal,
+                            CV_OUT double* maxVal = 0, CV_OUT Point* minLoc = 0,
+                            CV_OUT Point* maxLoc = 0, InputArray mask = noArray());
+
+/**
+ * @brief Finds indices of min elements along provided axis
+ *
+ * @note
+ *      - If input or output array is not continuous, this function will create an internal copy.
+ *      - NaN handling is left unspecified, see patchNaNs().
+ *      - The returned index is always in bounds of input matrix.
+ *
+ * @param src input single-channel array.
+ * @param dst output array of type CV_32SC1 with the same dimensionality as src,
+ * except for axis being reduced - it should be set to 1.
+ * @param lastIndex whether to get the index of first or last occurrence of min.
+ * @param axis axis to reduce along.
+ * @sa reduceArgMax, minMaxLoc, min, max, compare, reduce
+ */
+CV_EXPORTS_W void reduceArgMin(InputArray src, OutputArray dst, int axis, bool lastIndex = false);
+
+/**
+ * @brief Finds indices of max elements along provided axis
+ *
+ * @note
+ *      - If input or output array is not continuous, this function will create an internal copy.
+ *      - NaN handling is left unspecified, see patchNaNs().
+ *      - The returned index is always in bounds of input matrix.
+ *
+ * @param src input single-channel array.
+ * @param dst output array of type CV_32SC1 with the same dimensionality as src,
+ * except for axis being reduced - it should be set to 1.
+ * @param lastIndex whether to get the index of first or last occurrence of max.
+ * @param axis axis to reduce along.
+ * @sa reduceArgMin, minMaxLoc, min, max, compare, reduce
+ */
+CV_EXPORTS_W void reduceArgMax(InputArray src, OutputArray dst, int axis, bool lastIndex = false);
+
+/** @brief Finds the global minimum and maximum in an array
+
+The function cv::minMaxIdx finds the minimum and maximum element values and their positions. The
+extremums are searched across the whole array or, if mask is not an empty array, in the specified
+array region. In case of a sparse matrix, the minimum is found among non-zero elements
+only. Multi-channel input is supported without mask and extremums indexes (should be nullptr).
+@note When minIdx is not NULL, it must have at least 2 elements (as well as maxIdx), even if src is
+a single-row or single-column matrix. In OpenCV (following MATLAB) each array has at least 2
+dimensions, i.e. single-column matrix is Mx1 matrix (and therefore minIdx/maxIdx will be
+(i1,0)/(i2,0)) and single-row matrix is 1xN matrix (and therefore minIdx/maxIdx will be
+(0,j1)/(0,j2)).
+@param src input single-channel array.
+@param minVal pointer to the returned minimum value; NULL is used if not required.
+@param maxVal pointer to the returned maximum value; NULL is used if not required.
+@param minIdx pointer to the returned minimum location (in nD case); NULL is used if not required;
+Otherwise, it must point to an array of src.dims elements, the coordinates of the minimum element
+in each dimension are stored there sequentially.
+@param maxIdx pointer to the returned maximum location (in nD case). NULL is used if not required.
+@param mask specified array region
+*/
+CV_EXPORTS void minMaxIdx(InputArray src, double* minVal, double* maxVal = 0,
+                          int* minIdx = 0, int* maxIdx = 0, InputArray mask = noArray());
+
+/** @overload
+@param a input single-channel array.
+@param minVal pointer to the returned minimum value; NULL is used if not required.
+@param maxVal pointer to the returned maximum value; NULL is used if not required.
+@param minIdx pointer to the returned minimum location (in nD case); NULL is used if not required;
+Otherwise, it must point to an array of src.dims elements, the coordinates of the minimum element
+in each dimension are stored there sequentially.
+@param maxIdx pointer to the returned maximum location (in nD case). NULL is used if not required.
+*/
+CV_EXPORTS void minMaxLoc(const SparseMat& a, double* minVal,
+                          double* maxVal, int* minIdx = 0, int* maxIdx = 0);
+
+/** @brief Reduces a matrix to a vector.
+
+The function #reduce reduces the matrix to a vector by treating the matrix rows/columns as a set of
+1D vectors and performing the specified operation on the vectors until a single row/column is
+obtained. For example, the function can be used to compute horizontal and vertical projections of a
+raster image. In case of #REDUCE_MAX and #REDUCE_MIN, the output image should have the same type as the source one.
+In case of #REDUCE_SUM, #REDUCE_SUM2 and #REDUCE_AVG, the output may have a larger element bit-depth to preserve accuracy.
+And multi-channel arrays are also supported in these two reduction modes.
+
+The following code demonstrates its usage for a single channel matrix.
+@snippet snippets/core_reduce.cpp example
+
+And the following code demonstrates its usage for a two-channel matrix.
+@snippet snippets/core_reduce.cpp example2
+
+@param src input 2D matrix.
+@param dst output vector. Its size and type is defined by dim and dtype parameters.
+@param dim dimension index along which the matrix is reduced. 0 means that the matrix is reduced to
+a single row. 1 means that the matrix is reduced to a single column.
+@param rtype reduction operation that could be one of #ReduceTypes
+@param dtype when negative, the output vector will have the same type as the input matrix,
+otherwise, its type will be CV_MAKE_TYPE(CV_MAT_DEPTH(dtype), src.channels()).
+@sa repeat, reduceArgMin, reduceArgMax
+*/
+CV_EXPORTS_W void reduce(InputArray src, OutputArray dst, int dim, int rtype, int dtype = -1);
+
+/** @brief Creates one multi-channel array out of several single-channel ones.
+
+The function cv::merge merges several arrays to make a single multi-channel array. That is, each
+element of the output array will be a concatenation of the elements of the input arrays, where
+elements of i-th input array are treated as mv[i].channels()-element vectors.
+
+The function cv::split does the reverse operation. If you need to shuffle channels in some other
+advanced way, use cv::mixChannels.
+
+The following example shows how to merge 3 single channel matrices into a single 3-channel matrix.
+@snippet snippets/core_merge.cpp example
+
+@param mv input array of matrices to be merged; all the matrices in mv must have the same
+size and the same depth.
+@param count number of input matrices when mv is a plain C array; it must be greater than zero.
+@param dst output array of the same size and the same depth as mv[0]; The number of channels will
+be equal to the parameter count.
+@sa  mixChannels, split, Mat::reshape
+*/
+CV_EXPORTS void merge(const Mat* mv, size_t count, OutputArray dst);
+
+/** @overload
+@param mv input vector of matrices to be merged; all the matrices in mv must have the same
+size and the same depth.
+@param dst output array of the same size and the same depth as mv[0]; The number of channels will
+be the total number of channels in the matrix array.
+  */
+CV_EXPORTS_W void merge(InputArrayOfArrays mv, OutputArray dst);
+
+/** @brief Divides a multi-channel array into several single-channel arrays.
+
+The function cv::split splits a multi-channel array into separate single-channel arrays:
+\f[\texttt{mv} [c](I) =  \texttt{src} (I)_c\f]
+If you need to extract a single channel or do some other sophisticated channel permutation, use
+mixChannels.
+
+The following example demonstrates how to split a 3-channel matrix into 3 single channel matrices.
+@snippet snippets/core_split.cpp example
+
+@param src input multi-channel array.
+@param mvbegin output array; the number of arrays must match src.channels(); the arrays themselves are
+reallocated, if needed.
+@sa merge, mixChannels, cvtColor
+*/
+CV_EXPORTS void split(const Mat& src, Mat* mvbegin);
+
+/** @overload
+@param m input multi-channel array.
+@param mv output vector of arrays; the arrays themselves are reallocated, if needed.
+*/
+CV_EXPORTS_W void split(InputArray m, OutputArrayOfArrays mv);
+
+/** @brief Copies specified channels from input arrays to the specified channels of
+output arrays.
+
+The function cv::mixChannels provides an advanced mechanism for shuffling image channels.
+
+cv::split,cv::merge,cv::extractChannel,cv::insertChannel and some forms of cv::cvtColor are partial cases of cv::mixChannels.
+
+In the example below, the code splits a 4-channel BGRA image into a 3-channel BGR (with B and R
+channels swapped) and a separate alpha-channel image:
+@code{.cpp}
+    Mat bgra( 100, 100, CV_8UC4, Scalar(255,0,0,255) );
+    Mat bgr( bgra.rows, bgra.cols, CV_8UC3 );
+    Mat alpha( bgra.rows, bgra.cols, CV_8UC1 );
+
+    // forming an array of matrices is a quite efficient operation,
+    // because the matrix data is not copied, only the headers
+    Mat out[] = { bgr, alpha };
+    // bgra[0] -> bgr[2], bgra[1] -> bgr[1],
+    // bgra[2] -> bgr[0], bgra[3] -> alpha[0]
+    int from_to[] = { 0,2, 1,1, 2,0, 3,3 };
+    mixChannels( &bgra, 1, out, 2, from_to, 4 );
+@endcode
+@note Unlike many other new-style C++ functions in OpenCV (see the introduction section and
+Mat::create ), cv::mixChannels requires the output arrays to be pre-allocated before calling the
+function.
+@param src input array or vector of matrices; all of the matrices must have the same size and the
+same depth.
+@param nsrcs number of matrices in `src`.
+@param dst output array or vector of matrices; all the matrices **must be allocated**; their size and
+depth must be the same as in `src[0]`.
+@param ndsts number of matrices in `dst`.
+@param fromTo array of index pairs specifying which channels are copied and where; fromTo[k\*2] is
+a 0-based index of the input channel in src, fromTo[k\*2+1] is an index of the output channel in
+dst; the continuous channel numbering is used: the first input image channels are indexed from 0 to
+src[0].channels()-1, the second input image channels are indexed from src[0].channels() to
+src[0].channels() + src[1].channels()-1, and so on, the same scheme is used for the output image
+channels; as a special case, when fromTo[k\*2] is negative, the corresponding output channel is
+filled with zero .
+@param npairs number of index pairs in `fromTo`.
+@sa split, merge, extractChannel, insertChannel, cvtColor
+*/
+CV_EXPORTS void mixChannels(const Mat* src, size_t nsrcs, Mat* dst, size_t ndsts,
+                            const int* fromTo, size_t npairs);
+
+/** @overload
+@param src input array or vector of matrices; all of the matrices must have the same size and the
+same depth.
+@param dst output array or vector of matrices; all the matrices **must be allocated**; their size and
+depth must be the same as in src[0].
+@param fromTo array of index pairs specifying which channels are copied and where; fromTo[k\*2] is
+a 0-based index of the input channel in src, fromTo[k\*2+1] is an index of the output channel in
+dst; the continuous channel numbering is used: the first input image channels are indexed from 0 to
+src[0].channels()-1, the second input image channels are indexed from src[0].channels() to
+src[0].channels() + src[1].channels()-1, and so on, the same scheme is used for the output image
+channels; as a special case, when fromTo[k\*2] is negative, the corresponding output channel is
+filled with zero .
+@param npairs number of index pairs in fromTo.
+*/
+CV_EXPORTS void mixChannels(InputArrayOfArrays src, InputOutputArrayOfArrays dst,
+                            const int* fromTo, size_t npairs);
+
+/** @overload
+@param src input array or vector of matrices; all of the matrices must have the same size and the
+same depth.
+@param dst output array or vector of matrices; all the matrices **must be allocated**; their size and
+depth must be the same as in src[0].
+@param fromTo array of index pairs specifying which channels are copied and where; fromTo[k\*2] is
+a 0-based index of the input channel in src, fromTo[k\*2+1] is an index of the output channel in
+dst; the continuous channel numbering is used: the first input image channels are indexed from 0 to
+src[0].channels()-1, the second input image channels are indexed from src[0].channels() to
+src[0].channels() + src[1].channels()-1, and so on, the same scheme is used for the output image
+channels; as a special case, when fromTo[k\*2] is negative, the corresponding output channel is
+filled with zero .
+*/
+CV_EXPORTS_W void mixChannels(InputArrayOfArrays src, InputOutputArrayOfArrays dst,
+                              const std::vector<int>& fromTo);
+
+/** @brief Extracts a single channel from src (coi is 0-based index)
+@param src input array
+@param dst output array
+@param coi index of channel to extract
+@sa mixChannels, split
+*/
+CV_EXPORTS_W void extractChannel(InputArray src, OutputArray dst, int coi);
+
+/** @brief Inserts a single channel to dst (coi is 0-based index)
+@param src input array
+@param dst output array
+@param coi index of channel for insertion
+@sa mixChannels, merge
+*/
+CV_EXPORTS_W void insertChannel(InputArray src, InputOutputArray dst, int coi);
+
+/** @brief Flips a 2D array around vertical, horizontal, or both axes.
+
+The function cv::flip flips the array in one of three different ways (row
+and column indices are 0-based):
+\f[\texttt{dst} _{ij} =
+\left\{
+\begin{array}{l l}
+\texttt{src} _{\texttt{src.rows}-i-1,j} & if\;  \texttt{flipCode} = 0 \\
+\texttt{src} _{i, \texttt{src.cols} -j-1} & if\;  \texttt{flipCode} > 0 \\
+\texttt{src} _{ \texttt{src.rows} -i-1, \texttt{src.cols} -j-1} & if\; \texttt{flipCode} < 0 \\
+\end{array}
+\right.\f]
+The example scenarios of using the function are the following:
+*   Vertical flipping of the image (flipCode == 0) to switch between
+    top-left and bottom-left image origin. This is a typical operation
+    in video processing on Microsoft Windows\* OS.
+*   Horizontal flipping of the image with the subsequent horizontal
+    shift and absolute difference calculation to check for a
+    vertical-axis symmetry (flipCode \> 0).
+*   Simultaneous horizontal and vertical flipping of the image with
+    the subsequent shift and absolute difference calculation to check
+    for a central symmetry (flipCode \< 0).
+*   Reversing the order of point arrays (flipCode \> 0 or
+    flipCode == 0).
+@param src input array.
+@param dst output array of the same size and type as src.
+@param flipCode a flag to specify how to flip the array; 0 means
+flipping around the x-axis and positive value (for example, 1) means
+flipping around y-axis. Negative value (for example, -1) means flipping
+around both axes.
+@sa transpose, repeat, completeSymm
+*/
+CV_EXPORTS_W void flip(InputArray src, OutputArray dst, int flipCode);
+
+/** @brief Flips a n-dimensional at given axis
+ *  @param src input array
+ *  @param dst output array that has the same shape of src
+ *  @param axis axis that performs a flip on. 0 <= axis < src.dims.
+ */
+CV_EXPORTS_W void flipND(InputArray src, OutputArray dst, int axis);
+
+/** @brief Broadcast the given Mat to the given shape.
+ * @param src input array
+ * @param shape target shape. Should be a list of CV_32S numbers. Note that negative values are not supported.
+ * @param dst output array that has the given shape
+ */
+CV_EXPORTS_W void broadcast(InputArray src, InputArray shape, OutputArray dst);
+
+enum RotateFlags {
+    ROTATE_90_CLOCKWISE = 0, //!<Rotate 90 degrees clockwise
+    ROTATE_180 = 1, //!<Rotate 180 degrees clockwise
+    ROTATE_90_COUNTERCLOCKWISE = 2, //!<Rotate 270 degrees clockwise
+};
+/** @brief Rotates a 2D array in multiples of 90 degrees.
+The function cv::rotate rotates the array in one of three different ways:
+*   Rotate by 90 degrees clockwise (rotateCode = ROTATE_90_CLOCKWISE).
+*   Rotate by 180 degrees clockwise (rotateCode = ROTATE_180).
+*   Rotate by 270 degrees clockwise (rotateCode = ROTATE_90_COUNTERCLOCKWISE).
+@param src input array.
+@param dst output array of the same type as src.  The size is the same with ROTATE_180,
+and the rows and cols are switched for ROTATE_90_CLOCKWISE and ROTATE_90_COUNTERCLOCKWISE.
+@param rotateCode an enum to specify how to rotate the array; see the enum #RotateFlags
+@sa transpose, repeat, completeSymm, flip, RotateFlags
+*/
+CV_EXPORTS_W void rotate(InputArray src, OutputArray dst, int rotateCode);
+
+/** @brief Fills the output array with repeated copies of the input array.
+
+The function cv::repeat duplicates the input array one or more times along each of the two axes:
+\f[\texttt{dst} _{ij}= \texttt{src} _{i\mod src.rows, \; j\mod src.cols }\f]
+The second variant of the function is more convenient to use with @ref MatrixExpressions.
+@param src input array to replicate.
+@param ny Flag to specify how many times the `src` is repeated along the
+vertical axis.
+@param nx Flag to specify how many times the `src` is repeated along the
+horizontal axis.
+@param dst output array of the same type as `src`.
+@sa cv::reduce
+*/
+CV_EXPORTS_W void repeat(InputArray src, int ny, int nx, OutputArray dst);
+
+/** @overload
+@param src input array to replicate.
+@param ny Flag to specify how many times the `src` is repeated along the
+vertical axis.
+@param nx Flag to specify how many times the `src` is repeated along the
+horizontal axis.
+  */
+CV_EXPORTS Mat repeat(const Mat& src, int ny, int nx);
+
+/** @brief Applies horizontal concatenation to given matrices.
+
+The function horizontally concatenates two or more cv::Mat matrices (with the same number of rows).
+@code{.cpp}
+    cv::Mat matArray[] = { cv::Mat(4, 1, CV_8UC1, cv::Scalar(1)),
+                           cv::Mat(4, 1, CV_8UC1, cv::Scalar(2)),
+                           cv::Mat(4, 1, CV_8UC1, cv::Scalar(3)),};
+
+    cv::Mat out;
+    cv::hconcat( matArray, 3, out );
+    //out:
+    //[1, 2, 3;
+    // 1, 2, 3;
+    // 1, 2, 3;
+    // 1, 2, 3]
+@endcode
+@param src input array or vector of matrices. all of the matrices must have the same number of rows and the same depth.
+@param nsrc number of matrices in src.
+@param dst output array. It has the same number of rows and depth as the src, and the sum of cols of the src.
+@sa cv::vconcat(const Mat*, size_t, OutputArray), @sa cv::vconcat(InputArrayOfArrays, OutputArray) and @sa cv::vconcat(InputArray, InputArray, OutputArray)
+*/
+CV_EXPORTS void hconcat(const Mat* src, size_t nsrc, OutputArray dst);
+/** @overload
+ @code{.cpp}
+    cv::Mat_<float> A = (cv::Mat_<float>(3, 2) << 1, 4,
+                                                  2, 5,
+                                                  3, 6);
+    cv::Mat_<float> B = (cv::Mat_<float>(3, 2) << 7, 10,
+                                                  8, 11,
+                                                  9, 12);
+
+    cv::Mat C;
+    cv::hconcat(A, B, C);
+    //C:
+    //[1, 4, 7, 10;
+    // 2, 5, 8, 11;
+    // 3, 6, 9, 12]
+ @endcode
+ @param src1 first input array to be considered for horizontal concatenation.
+ @param src2 second input array to be considered for horizontal concatenation.
+ @param dst output array. It has the same number of rows and depth as the src1 and src2, and the sum of cols of the src1 and src2.
+ */
+CV_EXPORTS void hconcat(InputArray src1, InputArray src2, OutputArray dst);
+/** @overload
+ @code{.cpp}
+    std::vector<cv::Mat> matrices = { cv::Mat(4, 1, CV_8UC1, cv::Scalar(1)),
+                                      cv::Mat(4, 1, CV_8UC1, cv::Scalar(2)),
+                                      cv::Mat(4, 1, CV_8UC1, cv::Scalar(3)),};
+
+    cv::Mat out;
+    cv::hconcat( matrices, out );
+    //out:
+    //[1, 2, 3;
+    // 1, 2, 3;
+    // 1, 2, 3;
+    // 1, 2, 3]
+ @endcode
+ @param src input array or vector of matrices. all of the matrices must have the same number of rows and the same depth.
+ @param dst output array. It has the same number of rows and depth as the src, and the sum of cols of the src.
+same depth.
+ */
+CV_EXPORTS_W void hconcat(InputArrayOfArrays src, OutputArray dst);
+
+/** @brief Applies vertical concatenation to given matrices.
+
+The function vertically concatenates two or more cv::Mat matrices (with the same number of cols).
+@code{.cpp}
+    cv::Mat matArray[] = { cv::Mat(1, 4, CV_8UC1, cv::Scalar(1)),
+                           cv::Mat(1, 4, CV_8UC1, cv::Scalar(2)),
+                           cv::Mat(1, 4, CV_8UC1, cv::Scalar(3)),};
+
+    cv::Mat out;
+    cv::vconcat( matArray, 3, out );
+    //out:
+    //[1,   1,   1,   1;
+    // 2,   2,   2,   2;
+    // 3,   3,   3,   3]
+@endcode
+@param src input array or vector of matrices. all of the matrices must have the same number of cols and the same depth.
+@param nsrc number of matrices in src.
+@param dst output array. It has the same number of cols and depth as the src, and the sum of rows of the src.
+@sa cv::hconcat(const Mat*, size_t, OutputArray), @sa cv::hconcat(InputArrayOfArrays, OutputArray) and @sa cv::hconcat(InputArray, InputArray, OutputArray)
+*/
+CV_EXPORTS void vconcat(const Mat* src, size_t nsrc, OutputArray dst);
+/** @overload
+ @code{.cpp}
+    cv::Mat_<float> A = (cv::Mat_<float>(3, 2) << 1, 7,
+                                                  2, 8,
+                                                  3, 9);
+    cv::Mat_<float> B = (cv::Mat_<float>(3, 2) << 4, 10,
+                                                  5, 11,
+                                                  6, 12);
+
+    cv::Mat C;
+    cv::vconcat(A, B, C);
+    //C:
+    //[1, 7;
+    // 2, 8;
+    // 3, 9;
+    // 4, 10;
+    // 5, 11;
+    // 6, 12]
+ @endcode
+ @param src1 first input array to be considered for vertical concatenation.
+ @param src2 second input array to be considered for vertical concatenation.
+ @param dst output array. It has the same number of cols and depth as the src1 and src2, and the sum of rows of the src1 and src2.
+ */
+CV_EXPORTS void vconcat(InputArray src1, InputArray src2, OutputArray dst);
+/** @overload
+ @code{.cpp}
+    std::vector<cv::Mat> matrices = { cv::Mat(1, 4, CV_8UC1, cv::Scalar(1)),
+                                      cv::Mat(1, 4, CV_8UC1, cv::Scalar(2)),
+                                      cv::Mat(1, 4, CV_8UC1, cv::Scalar(3)),};
+
+    cv::Mat out;
+    cv::vconcat( matrices, out );
+    //out:
+    //[1,   1,   1,   1;
+    // 2,   2,   2,   2;
+    // 3,   3,   3,   3]
+ @endcode
+ @param src input array or vector of matrices. all of the matrices must have the same number of cols and the same depth
+ @param dst output array. It has the same number of cols and depth as the src, and the sum of rows of the src.
+same depth.
+ */
+CV_EXPORTS_W void vconcat(InputArrayOfArrays src, OutputArray dst);
+
+/** @brief computes bitwise conjunction of the two arrays (dst = src1 & src2)
+Calculates the per-element bit-wise conjunction of two arrays or an
+array and a scalar.
+
+The function cv::bitwise_and calculates the per-element bit-wise logical conjunction for:
+*   Two arrays when src1 and src2 have the same size:
+    \f[\texttt{dst} (I) =  \texttt{src1} (I)  \wedge \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f]
+*   An array and a scalar when src2 is constructed from Scalar or has
+    the same number of elements as `src1.channels()`:
+    \f[\texttt{dst} (I) =  \texttt{src1} (I)  \wedge \texttt{src2} \quad \texttt{if mask} (I) \ne0\f]
+*   A scalar and an array when src1 is constructed from Scalar or has
+    the same number of elements as `src2.channels()`:
+    \f[\texttt{dst} (I) =  \texttt{src1}  \wedge \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f]
+In case of floating-point arrays, their machine-specific bit
+representations (usually IEEE754-compliant) are used for the operation.
+In case of multi-channel arrays, each channel is processed
+independently. In the second and third cases above, the scalar is first
+converted to the array type.
+@param src1 first input array or a scalar.
+@param src2 second input array or a scalar.
+@param dst output array that has the same size and type as the input
+arrays.
+@param mask optional operation mask, 8-bit single channel array, that
+specifies elements of the output array to be changed.
+*/
+CV_EXPORTS_W void bitwise_and(InputArray src1, InputArray src2,
+                              OutputArray dst, InputArray mask = noArray());
+
+/** @brief Calculates the per-element bit-wise disjunction of two arrays or an
+array and a scalar.
+
+The function cv::bitwise_or calculates the per-element bit-wise logical disjunction for:
+*   Two arrays when src1 and src2 have the same size:
+    \f[\texttt{dst} (I) =  \texttt{src1} (I)  \vee \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f]
+*   An array and a scalar when src2 is constructed from Scalar or has
+    the same number of elements as `src1.channels()`:
+    \f[\texttt{dst} (I) =  \texttt{src1} (I)  \vee \texttt{src2} \quad \texttt{if mask} (I) \ne0\f]
+*   A scalar and an array when src1 is constructed from Scalar or has
+    the same number of elements as `src2.channels()`:
+    \f[\texttt{dst} (I) =  \texttt{src1}  \vee \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f]
+In case of floating-point arrays, their machine-specific bit
+representations (usually IEEE754-compliant) are used for the operation.
+In case of multi-channel arrays, each channel is processed
+independently. In the second and third cases above, the scalar is first
+converted to the array type.
+@param src1 first input array or a scalar.
+@param src2 second input array or a scalar.
+@param dst output array that has the same size and type as the input
+arrays.
+@param mask optional operation mask, 8-bit single channel array, that
+specifies elements of the output array to be changed.
+*/
+CV_EXPORTS_W void bitwise_or(InputArray src1, InputArray src2,
+                             OutputArray dst, InputArray mask = noArray());
+
+/** @brief Calculates the per-element bit-wise "exclusive or" operation on two
+arrays or an array and a scalar.
+
+The function cv::bitwise_xor calculates the per-element bit-wise logical "exclusive-or"
+operation for:
+*   Two arrays when src1 and src2 have the same size:
+    \f[\texttt{dst} (I) =  \texttt{src1} (I)  \oplus \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f]
+*   An array and a scalar when src2 is constructed from Scalar or has
+    the same number of elements as `src1.channels()`:
+    \f[\texttt{dst} (I) =  \texttt{src1} (I)  \oplus \texttt{src2} \quad \texttt{if mask} (I) \ne0\f]
+*   A scalar and an array when src1 is constructed from Scalar or has
+    the same number of elements as `src2.channels()`:
+    \f[\texttt{dst} (I) =  \texttt{src1}  \oplus \texttt{src2} (I) \quad \texttt{if mask} (I) \ne0\f]
+In case of floating-point arrays, their machine-specific bit
+representations (usually IEEE754-compliant) are used for the operation.
+In case of multi-channel arrays, each channel is processed
+independently. In the 2nd and 3rd cases above, the scalar is first
+converted to the array type.
+@param src1 first input array or a scalar.
+@param src2 second input array or a scalar.
+@param dst output array that has the same size and type as the input
+arrays.
+@param mask optional operation mask, 8-bit single channel array, that
+specifies elements of the output array to be changed.
+*/
+CV_EXPORTS_W void bitwise_xor(InputArray src1, InputArray src2,
+                              OutputArray dst, InputArray mask = noArray());
+
+/** @brief  Inverts every bit of an array.
+
+The function cv::bitwise_not calculates per-element bit-wise inversion of the input
+array:
+\f[\texttt{dst} (I) =  \neg \texttt{src} (I)\f]
+In case of a floating-point input array, its machine-specific bit
+representation (usually IEEE754-compliant) is used for the operation. In
+case of multi-channel arrays, each channel is processed independently.
+@param src input array.
+@param dst output array that has the same size and type as the input
+array.
+@param mask optional operation mask, 8-bit single channel array, that
+specifies elements of the output array to be changed.
+*/
+CV_EXPORTS_W void bitwise_not(InputArray src, OutputArray dst,
+                              InputArray mask = noArray());
+
+/** @brief Calculates the per-element absolute difference between two arrays or between an array and a scalar.
+
+The function cv::absdiff calculates:
+*   Absolute difference between two arrays when they have the same
+    size and type:
+    \f[\texttt{dst}(I) =  \texttt{saturate} (| \texttt{src1}(I) -  \texttt{src2}(I)|)\f]
+*   Absolute difference between an array and a scalar when the second
+    array is constructed from Scalar or has as many elements as the
+    number of channels in `src1`:
+    \f[\texttt{dst}(I) =  \texttt{saturate} (| \texttt{src1}(I) -  \texttt{src2} |)\f]
+*   Absolute difference between a scalar and an array when the first
+    array is constructed from Scalar or has as many elements as the
+    number of channels in `src2`:
+    \f[\texttt{dst}(I) =  \texttt{saturate} (| \texttt{src1} -  \texttt{src2}(I) |)\f]
+    where I is a multi-dimensional index of array elements. In case of
+    multi-channel arrays, each channel is processed independently.
+@note Saturation is not applied when the arrays have the depth CV_32S.
+You may even get a negative value in the case of overflow.
+@note (Python) Be careful to difference behaviour between src1/src2 are single number and they are tuple/array.
+`absdiff(src,X)` means `absdiff(src,(X,X,X,X))`.
+`absdiff(src,(X,))` means `absdiff(src,(X,0,0,0))`.
+@param src1 first input array or a scalar.
+@param src2 second input array or a scalar.
+@param dst output array that has the same size and type as input arrays.
+@sa cv::abs(const Mat&)
+*/
+CV_EXPORTS_W void absdiff(InputArray src1, InputArray src2, OutputArray dst);
+
+/** @brief  This is an overloaded member function, provided for convenience (python)
+Copies the matrix to another one.
+When the operation mask is specified, if the Mat::create call shown above reallocates the matrix, the newly allocated matrix is initialized with all zeros before copying the data.
+@param src source matrix.
+@param dst Destination matrix. If it does not have a proper size or type before the operation, it is
+reallocated.
+@param mask Operation mask of the same size as \*this. Its non-zero elements indicate which matrix
+elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels.
+*/
+
+void CV_EXPORTS_W copyTo(InputArray src, OutputArray dst, InputArray mask);
+/** @brief  Checks if array elements lie between the elements of two other arrays.
+
+The function checks the range as follows:
+-   For every element of a single-channel input array:
+    \f[\texttt{dst} (I)= \texttt{lowerb} (I)_0  \leq \texttt{src} (I)_0 \leq  \texttt{upperb} (I)_0\f]
+-   For two-channel arrays:
+    \f[\texttt{dst} (I)= \texttt{lowerb} (I)_0  \leq \texttt{src} (I)_0 \leq  \texttt{upperb} (I)_0  \land \texttt{lowerb} (I)_1  \leq \texttt{src} (I)_1 \leq  \texttt{upperb} (I)_1\f]
+-   and so forth.
+
+That is, dst (I) is set to 255 (all 1 -bits) if src (I) is within the
+specified 1D, 2D, 3D, ... box and 0 otherwise.
+
+When the lower and/or upper boundary parameters are scalars, the indexes
+(I) at lowerb and upperb in the above formulas should be omitted.
+@param src first input array.
+@param lowerb inclusive lower boundary array or a scalar.
+@param upperb inclusive upper boundary array or a scalar.
+@param dst output array of the same size as src and CV_8U type.
+*/
+CV_EXPORTS_W void inRange(InputArray src, InputArray lowerb,
+                          InputArray upperb, OutputArray dst);
+
+/** @brief Performs the per-element comparison of two arrays or an array and scalar value.
+
+The function compares:
+*   Elements of two arrays when src1 and src2 have the same size:
+    \f[\texttt{dst} (I) =  \texttt{src1} (I)  \,\texttt{cmpop}\, \texttt{src2} (I)\f]
+*   Elements of src1 with a scalar src2 when src2 is constructed from
+    Scalar or has a single element:
+    \f[\texttt{dst} (I) =  \texttt{src1}(I) \,\texttt{cmpop}\,  \texttt{src2}\f]
+*   src1 with elements of src2 when src1 is constructed from Scalar or
+    has a single element:
+    \f[\texttt{dst} (I) =  \texttt{src1}  \,\texttt{cmpop}\, \texttt{src2} (I)\f]
+When the comparison result is true, the corresponding element of output
+array is set to 255. The comparison operations can be replaced with the
+equivalent matrix expressions:
+@code{.cpp}
+    Mat dst1 = src1 >= src2;
+    Mat dst2 = src1 < 8;
+    ...
+@endcode
+@param src1 first input array or a scalar; when it is an array, it must have a single channel.
+@param src2 second input array or a scalar; when it is an array, it must have a single channel.
+@param dst output array of type ref CV_8U that has the same size and the same number of channels as
+    the input arrays.
+@param cmpop a flag, that specifies correspondence between the arrays (cv::CmpTypes)
+@sa checkRange, min, max, threshold
+*/
+CV_EXPORTS_W void compare(InputArray src1, InputArray src2, OutputArray dst, int cmpop);
+
+/** @brief Calculates per-element minimum of two arrays or an array and a scalar.
+
+The function cv::min calculates the per-element minimum of two arrays:
+\f[\texttt{dst} (I)= \min ( \texttt{src1} (I), \texttt{src2} (I))\f]
+or array and a scalar:
+\f[\texttt{dst} (I)= \min ( \texttt{src1} (I), \texttt{value} )\f]
+@param src1 first input array.
+@param src2 second input array of the same size and type as src1.
+@param dst output array of the same size and type as src1.
+@sa max, compare, inRange, minMaxLoc
+*/
+CV_EXPORTS_W void min(InputArray src1, InputArray src2, OutputArray dst);
+/** @overload
+needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare)
+*/
+CV_EXPORTS void min(const Mat& src1, const Mat& src2, Mat& dst);
+/** @overload
+needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare)
+*/
+CV_EXPORTS void min(const UMat& src1, const UMat& src2, UMat& dst);
+
+/** @brief Calculates per-element maximum of two arrays or an array and a scalar.
+
+The function cv::max calculates the per-element maximum of two arrays:
+\f[\texttt{dst} (I)= \max ( \texttt{src1} (I), \texttt{src2} (I))\f]
+or array and a scalar:
+\f[\texttt{dst} (I)= \max ( \texttt{src1} (I), \texttt{value} )\f]
+@param src1 first input array.
+@param src2 second input array of the same size and type as src1 .
+@param dst output array of the same size and type as src1.
+@sa  min, compare, inRange, minMaxLoc, @ref MatrixExpressions
+*/
+CV_EXPORTS_W void max(InputArray src1, InputArray src2, OutputArray dst);
+/** @overload
+needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare)
+*/
+CV_EXPORTS void max(const Mat& src1, const Mat& src2, Mat& dst);
+/** @overload
+needed to avoid conflicts with const _Tp& std::min(const _Tp&, const _Tp&, _Compare)
+*/
+CV_EXPORTS void max(const UMat& src1, const UMat& src2, UMat& dst);
+
+/** @brief Calculates a square root of array elements.
+
+The function cv::sqrt calculates a square root of each input array element.
+In case of multi-channel arrays, each channel is processed
+independently. The accuracy is approximately the same as of the built-in
+std::sqrt .
+@param src input floating-point array.
+@param dst output array of the same size and type as src.
+*/
+CV_EXPORTS_W void sqrt(InputArray src, OutputArray dst);
+
+/** @brief Raises every array element to a power.
+
+The function cv::pow raises every element of the input array to power :
+\f[\texttt{dst} (I) =  \fork{\texttt{src}(I)^{power}}{if \(\texttt{power}\) is integer}{|\texttt{src}(I)|^{power}}{otherwise}\f]
+
+So, for a non-integer power exponent, the absolute values of input array
+elements are used. However, it is possible to get true values for
+negative values using some extra operations. In the example below,
+computing the 5th root of array src shows:
+@code{.cpp}
+    Mat mask = src < 0;
+    pow(src, 1./5, dst);
+    subtract(Scalar::all(0), dst, dst, mask);
+@endcode
+For some values of power, such as integer values, 0.5 and -0.5,
+specialized faster algorithms are used.
+
+Special values (NaN, Inf) are not handled.
+@param src input array.
+@param power exponent of power.
+@param dst output array of the same size and type as src.
+@sa sqrt, exp, log, cartToPolar, polarToCart
+*/
+CV_EXPORTS_W void pow(InputArray src, double power, OutputArray dst);
+
+/** @brief Calculates the exponent of every array element.
+
+The function cv::exp calculates the exponent of every element of the input
+array:
+\f[\texttt{dst} [I] = e^{ src(I) }\f]
+
+The maximum relative error is about 7e-6 for single-precision input and
+less than 1e-10 for double-precision input. Currently, the function
+converts denormalized values to zeros on output. Special values (NaN,
+Inf) are not handled.
+@param src input array.
+@param dst output array of the same size and type as src.
+@sa log, cartToPolar, polarToCart, phase, pow, sqrt, magnitude
+*/
+CV_EXPORTS_W void exp(InputArray src, OutputArray dst);
+
+/** @brief Calculates the natural logarithm of every array element.
+
+The function cv::log calculates the natural logarithm of every element of the input array:
+\f[\texttt{dst} (I) =  \log (\texttt{src}(I)) \f]
+
+Output on zero, negative and special (NaN, Inf) values is undefined.
+
+@param src input array.
+@param dst output array of the same size and type as src .
+@sa exp, cartToPolar, polarToCart, phase, pow, sqrt, magnitude
+*/
+CV_EXPORTS_W void log(InputArray src, OutputArray dst);
+
+/** @brief Calculates x and y coordinates of 2D vectors from their magnitude and angle.
+
+The function cv::polarToCart calculates the Cartesian coordinates of each 2D
+vector represented by the corresponding elements of magnitude and angle:
+\f[\begin{array}{l} \texttt{x} (I) =  \texttt{magnitude} (I) \cos ( \texttt{angle} (I)) \\ \texttt{y} (I) =  \texttt{magnitude} (I) \sin ( \texttt{angle} (I)) \\ \end{array}\f]
+
+The relative accuracy of the estimated coordinates is about 1e-6.
+@param magnitude input floating-point array of magnitudes of 2D vectors;
+it can be an empty matrix (=Mat()), in this case, the function assumes
+that all the magnitudes are =1; if it is not empty, it must have the
+same size and type as angle.
+@param angle input floating-point array of angles of 2D vectors.
+@param x output array of x-coordinates of 2D vectors; it has the same
+size and type as angle.
+@param y output array of y-coordinates of 2D vectors; it has the same
+size and type as angle.
+@param angleInDegrees when true, the input angles are measured in
+degrees, otherwise, they are measured in radians.
+@sa cartToPolar, magnitude, phase, exp, log, pow, sqrt
+*/
+CV_EXPORTS_W void polarToCart(InputArray magnitude, InputArray angle,
+                              OutputArray x, OutputArray y, bool angleInDegrees = false);
+
+/** @brief Calculates the magnitude and angle of 2D vectors.
+
+The function cv::cartToPolar calculates either the magnitude, angle, or both
+for every 2D vector (x(I),y(I)):
+\f[\begin{array}{l} \texttt{magnitude} (I)= \sqrt{\texttt{x}(I)^2+\texttt{y}(I)^2} , \\ \texttt{angle} (I)= \texttt{atan2} ( \texttt{y} (I), \texttt{x} (I))[ \cdot180 / \pi ] \end{array}\f]
+
+The angles are calculated with accuracy about 0.3 degrees. For the point
+(0,0), the angle is set to 0.
+@param x array of x-coordinates; this must be a single-precision or
+double-precision floating-point array.
+@param y array of y-coordinates, that must have the same size and same type as x.
+@param magnitude output array of magnitudes of the same size and type as x.
+@param angle output array of angles that has the same size and type as
+x; the angles are measured in radians (from 0 to 2\*Pi) or in degrees (0 to 360 degrees).
+@param angleInDegrees a flag, indicating whether the angles are measured
+in radians (which is by default), or in degrees.
+@sa Sobel, Scharr
+*/
+CV_EXPORTS_W void cartToPolar(InputArray x, InputArray y,
+                              OutputArray magnitude, OutputArray angle,
+                              bool angleInDegrees = false);
+
+/** @brief Calculates the rotation angle of 2D vectors.
+
+The function cv::phase calculates the rotation angle of each 2D vector that
+is formed from the corresponding elements of x and y :
+\f[\texttt{angle} (I) =  \texttt{atan2} ( \texttt{y} (I), \texttt{x} (I))\f]
+
+The angle estimation accuracy is about 0.3 degrees. When x(I)=y(I)=0 ,
+the corresponding angle(I) is set to 0.
+@param x input floating-point array of x-coordinates of 2D vectors.
+@param y input array of y-coordinates of 2D vectors; it must have the
+same size and the same type as x.
+@param angle output array of vector angles; it has the same size and
+same type as x .
+@param angleInDegrees when true, the function calculates the angle in
+degrees, otherwise, they are measured in radians.
+*/
+CV_EXPORTS_W void phase(InputArray x, InputArray y, OutputArray angle,
+                        bool angleInDegrees = false);
+
+/** @brief Calculates the magnitude of 2D vectors.
+
+The function cv::magnitude calculates the magnitude of 2D vectors formed
+from the corresponding elements of x and y arrays:
+\f[\texttt{dst} (I) =  \sqrt{\texttt{x}(I)^2 + \texttt{y}(I)^2}\f]
+@param x floating-point array of x-coordinates of the vectors.
+@param y floating-point array of y-coordinates of the vectors; it must
+have the same size as x.
+@param magnitude output array of the same size and type as x.
+@sa cartToPolar, polarToCart, phase, sqrt
+*/
+CV_EXPORTS_W void magnitude(InputArray x, InputArray y, OutputArray magnitude);
+
+/** @brief Checks every element of an input array for invalid values.
+
+The function cv::checkRange checks that every array element is neither NaN nor infinite. When minVal \>
+-DBL_MAX and maxVal \< DBL_MAX, the function also checks that each value is between minVal and
+maxVal. In case of multi-channel arrays, each channel is processed independently. If some values
+are out of range, position of the first outlier is stored in pos (when pos != NULL). Then, the
+function either returns false (when quiet=true) or throws an exception.
+@param a input array.
+@param quiet a flag, indicating whether the functions quietly return false when the array elements
+are out of range or they throw an exception.
+@param pos optional output parameter, when not NULL, must be a pointer to array of src.dims
+elements.
+@param minVal inclusive lower boundary of valid values range.
+@param maxVal exclusive upper boundary of valid values range.
+*/
+CV_EXPORTS_W bool checkRange(InputArray a, bool quiet = true, CV_OUT Point* pos = 0,
+                            double minVal = -DBL_MAX, double maxVal = DBL_MAX);
+
+/** @brief Replaces NaNs by given number
+@param a input/output matrix (CV_32F type).
+@param val value to convert the NaNs
+*/
+CV_EXPORTS_W void patchNaNs(InputOutputArray a, double val = 0);
+
+/** @brief Performs generalized matrix multiplication.
+
+The function cv::gemm performs generalized matrix multiplication similar to the
+gemm functions in BLAS level 3. For example,
+`gemm(src1, src2, alpha, src3, beta, dst, GEMM_1_T + GEMM_3_T)`
+corresponds to
+\f[\texttt{dst} =  \texttt{alpha} \cdot \texttt{src1} ^T  \cdot \texttt{src2} +  \texttt{beta} \cdot \texttt{src3} ^T\f]
+
+In case of complex (two-channel) data, performed a complex matrix
+multiplication.
+
+The function can be replaced with a matrix expression. For example, the
+above call can be replaced with:
+@code{.cpp}
+    dst = alpha*src1.t()*src2 + beta*src3.t();
+@endcode
+@param src1 first multiplied input matrix that could be real(CV_32FC1,
+CV_64FC1) or complex(CV_32FC2, CV_64FC2).
+@param src2 second multiplied input matrix of the same type as src1.
+@param alpha weight of the matrix product.
+@param src3 third optional delta matrix added to the matrix product; it
+should have the same type as src1 and src2.
+@param beta weight of src3.
+@param dst output matrix; it has the proper size and the same type as
+input matrices.
+@param flags operation flags (cv::GemmFlags)
+@sa mulTransposed, transform
+*/
+CV_EXPORTS_W void gemm(InputArray src1, InputArray src2, double alpha,
+                       InputArray src3, double beta, OutputArray dst, int flags = 0);
+
+/** @brief Calculates the product of a matrix and its transposition.
+
+The function cv::mulTransposed calculates the product of src and its
+transposition:
+\f[\texttt{dst} = \texttt{scale} ( \texttt{src} - \texttt{delta} )^T ( \texttt{src} - \texttt{delta} )\f]
+if aTa=true, and
+\f[\texttt{dst} = \texttt{scale} ( \texttt{src} - \texttt{delta} ) ( \texttt{src} - \texttt{delta} )^T\f]
+otherwise. The function is used to calculate the covariance matrix. With
+zero delta, it can be used as a faster substitute for general matrix
+product A\*B when B=A'
+@param src input single-channel matrix. Note that unlike gemm, the
+function can multiply not only floating-point matrices.
+@param dst output square matrix.
+@param aTa Flag specifying the multiplication ordering. See the
+description below.
+@param delta Optional delta matrix subtracted from src before the
+multiplication. When the matrix is empty ( delta=noArray() ), it is
+assumed to be zero, that is, nothing is subtracted. If it has the same
+size as src, it is simply subtracted. Otherwise, it is "repeated" (see
+repeat ) to cover the full src and then subtracted. Type of the delta
+matrix, when it is not empty, must be the same as the type of created
+output matrix. See the dtype parameter description below.
+@param scale Optional scale factor for the matrix product.
+@param dtype Optional type of the output matrix. When it is negative,
+the output matrix will have the same type as src . Otherwise, it will be
+type=CV_MAT_DEPTH(dtype) that should be either CV_32F or CV_64F .
+@sa calcCovarMatrix, gemm, repeat, reduce
+*/
+CV_EXPORTS_W void mulTransposed( InputArray src, OutputArray dst, bool aTa,
+                                 InputArray delta = noArray(),
+                                 double scale = 1, int dtype = -1 );
+
+/** @brief Transposes a matrix.
+
+The function cv::transpose transposes the matrix src :
+\f[\texttt{dst} (i,j) =  \texttt{src} (j,i)\f]
+@note No complex conjugation is done in case of a complex matrix. It
+should be done separately if needed.
+@param src input array.
+@param dst output array of the same type as src.
+*/
+CV_EXPORTS_W void transpose(InputArray src, OutputArray dst);
+
+/** @brief Transpose for n-dimensional matrices.
+ *
+ * @note Input should be continuous single-channel matrix.
+ * @param src input array.
+ * @param order a permutation of [0,1,..,N-1] where N is the number of axes of src.
+ * The i'th axis of dst will correspond to the axis numbered order[i] of the input.
+ * @param dst output array of the same type as src.
+ */
+CV_EXPORTS_W void transposeND(InputArray src, const std::vector<int>& order, OutputArray dst);
+
+/** @brief Performs the matrix transformation of every array element.
+
+The function cv::transform performs the matrix transformation of every
+element of the array src and stores the results in dst :
+\f[\texttt{dst} (I) =  \texttt{m} \cdot \texttt{src} (I)\f]
+(when m.cols=src.channels() ), or
+\f[\texttt{dst} (I) =  \texttt{m} \cdot [ \texttt{src} (I); 1]\f]
+(when m.cols=src.channels()+1 )
+
+Every element of the N -channel array src is interpreted as N -element
+vector that is transformed using the M x N or M x (N+1) matrix m to
+M-element vector - the corresponding element of the output array dst .
+
+The function may be used for geometrical transformation of
+N -dimensional points, arbitrary linear color space transformation (such
+as various kinds of RGB to YUV transforms), shuffling the image
+channels, and so forth.
+@param src input array that must have as many channels (1 to 4) as
+m.cols or m.cols-1.
+@param dst output array of the same size and depth as src; it has as
+many channels as m.rows.
+@param m transformation 2x2 or 2x3 floating-point matrix.
+@sa perspectiveTransform, getAffineTransform, estimateAffine2D, warpAffine, warpPerspective
+*/
+CV_EXPORTS_W void transform(InputArray src, OutputArray dst, InputArray m );
+
+/** @brief Performs the perspective matrix transformation of vectors.
+
+The function cv::perspectiveTransform transforms every element of src by
+treating it as a 2D or 3D vector, in the following way:
+\f[(x, y, z)  \rightarrow (x'/w, y'/w, z'/w)\f]
+where
+\f[(x', y', z', w') =  \texttt{mat} \cdot \begin{bmatrix} x & y & z & 1  \end{bmatrix}\f]
+and
+\f[w =  \fork{w'}{if \(w' \ne 0\)}{\infty}{otherwise}\f]
+
+Here a 3D vector transformation is shown. In case of a 2D vector
+transformation, the z component is omitted.
+
+@note The function transforms a sparse set of 2D or 3D vectors. If you
+want to transform an image using perspective transformation, use
+warpPerspective . If you have an inverse problem, that is, you want to
+compute the most probable perspective transformation out of several
+pairs of corresponding points, you can use getPerspectiveTransform or
+findHomography .
+@param src input two-channel or three-channel floating-point array; each
+element is a 2D/3D vector to be transformed.
+@param dst output array of the same size and type as src.
+@param m 3x3 or 4x4 floating-point transformation matrix.
+@sa  transform, warpPerspective, getPerspectiveTransform, findHomography
+*/
+CV_EXPORTS_W void perspectiveTransform(InputArray src, OutputArray dst, InputArray m );
+
+/** @brief Copies the lower or the upper half of a square matrix to its another half.
+
+The function cv::completeSymm copies the lower or the upper half of a square matrix to
+its another half. The matrix diagonal remains unchanged:
+ - \f$\texttt{m}_{ij}=\texttt{m}_{ji}\f$ for \f$i > j\f$ if
+    lowerToUpper=false
+ - \f$\texttt{m}_{ij}=\texttt{m}_{ji}\f$ for \f$i < j\f$ if
+    lowerToUpper=true
+
+@param m input-output floating-point square matrix.
+@param lowerToUpper operation flag; if true, the lower half is copied to
+the upper half. Otherwise, the upper half is copied to the lower half.
+@sa flip, transpose
+*/
+CV_EXPORTS_W void completeSymm(InputOutputArray m, bool lowerToUpper = false);
+
+/** @brief Initializes a scaled identity matrix.
+
+The function cv::setIdentity initializes a scaled identity matrix:
+\f[\texttt{mtx} (i,j)= \fork{\texttt{value}}{ if \(i=j\)}{0}{otherwise}\f]
+
+The function can also be emulated using the matrix initializers and the
+matrix expressions:
+@code
+    Mat A = Mat::eye(4, 3, CV_32F)*5;
+    // A will be set to [[5, 0, 0], [0, 5, 0], [0, 0, 5], [0, 0, 0]]
+@endcode
+@param mtx matrix to initialize (not necessarily square).
+@param s value to assign to diagonal elements.
+@sa Mat::zeros, Mat::ones, Mat::setTo, Mat::operator=
+*/
+CV_EXPORTS_W void setIdentity(InputOutputArray mtx, const Scalar& s = Scalar(1));
+
+/** @brief Returns the determinant of a square floating-point matrix.
+
+The function cv::determinant calculates and returns the determinant of the
+specified matrix. For small matrices ( mtx.cols=mtx.rows\<=3 ), the
+direct method is used. For larger matrices, the function uses LU
+factorization with partial pivoting.
+
+For symmetric positively-determined matrices, it is also possible to use
+eigen decomposition to calculate the determinant.
+@param mtx input matrix that must have CV_32FC1 or CV_64FC1 type and
+square size.
+@sa trace, invert, solve, eigen, @ref MatrixExpressions
+*/
+CV_EXPORTS_W double determinant(InputArray mtx);
+
+/** @brief Returns the trace of a matrix.
+
+The function cv::trace returns the sum of the diagonal elements of the
+matrix mtx .
+\f[\mathrm{tr} ( \texttt{mtx} ) =  \sum _i  \texttt{mtx} (i,i)\f]
+@param mtx input matrix.
+*/
+CV_EXPORTS_W Scalar trace(InputArray mtx);
+
+/** @brief Finds the inverse or pseudo-inverse of a matrix.
+
+The function cv::invert inverts the matrix src and stores the result in dst
+. When the matrix src is singular or non-square, the function calculates
+the pseudo-inverse matrix (the dst matrix) so that norm(src\*dst - I) is
+minimal, where I is an identity matrix.
+
+In case of the #DECOMP_LU method, the function returns non-zero value if
+the inverse has been successfully calculated and 0 if src is singular.
+
+In case of the #DECOMP_SVD method, the function returns the inverse
+condition number of src (the ratio of the smallest singular value to the
+largest singular value) and 0 if src is singular. The SVD method
+calculates a pseudo-inverse matrix if src is singular.
+
+Similarly to #DECOMP_LU, the method #DECOMP_CHOLESKY works only with
+non-singular square matrices that should also be symmetrical and
+positively defined. In this case, the function stores the inverted
+matrix in dst and returns non-zero. Otherwise, it returns 0.
+
+@param src input floating-point M x N matrix.
+@param dst output matrix of N x M size and the same type as src.
+@param flags inversion method (cv::DecompTypes)
+@sa solve, SVD
+*/
+CV_EXPORTS_W double invert(InputArray src, OutputArray dst, int flags = DECOMP_LU);
+
+/** @brief Solves one or more linear systems or least-squares problems.
+
+The function cv::solve solves a linear system or least-squares problem (the
+latter is possible with SVD or QR methods, or by specifying the flag
+#DECOMP_NORMAL ):
+\f[\texttt{dst} =  \arg \min _X \| \texttt{src1} \cdot \texttt{X} -  \texttt{src2} \|\f]
+
+If #DECOMP_LU or #DECOMP_CHOLESKY method is used, the function returns 1
+if src1 (or \f$\texttt{src1}^T\texttt{src1}\f$ ) is non-singular. Otherwise,
+it returns 0. In the latter case, dst is not valid. Other methods find a
+pseudo-solution in case of a singular left-hand side part.
+
+@note If you want to find a unity-norm solution of an under-defined
+singular system \f$\texttt{src1}\cdot\texttt{dst}=0\f$ , the function solve
+will not do the work. Use SVD::solveZ instead.
+
+@param src1 input matrix on the left-hand side of the system.
+@param src2 input matrix on the right-hand side of the system.
+@param dst output solution.
+@param flags solution (matrix inversion) method (#DecompTypes)
+@sa invert, SVD, eigen
+*/
+CV_EXPORTS_W bool solve(InputArray src1, InputArray src2,
+                        OutputArray dst, int flags = DECOMP_LU);
+
+/** @brief Sorts each row or each column of a matrix.
+
+The function cv::sort sorts each matrix row or each matrix column in
+ascending or descending order. So you should pass two operation flags to
+get desired behaviour. If you want to sort matrix rows or columns
+lexicographically, you can use STL std::sort generic function with the
+proper comparison predicate.
+
+@param src input single-channel array.
+@param dst output array of the same size and type as src.
+@param flags operation flags, a combination of #SortFlags
+@sa sortIdx, randShuffle
+*/
+CV_EXPORTS_W void sort(InputArray src, OutputArray dst, int flags);
+
+/** @brief Sorts each row or each column of a matrix.
+
+The function cv::sortIdx sorts each matrix row or each matrix column in the
+ascending or descending order. So you should pass two operation flags to
+get desired behaviour. Instead of reordering the elements themselves, it
+stores the indices of sorted elements in the output array. For example:
+@code
+    Mat A = Mat::eye(3,3,CV_32F), B;
+    sortIdx(A, B, SORT_EVERY_ROW + SORT_ASCENDING);
+    // B will probably contain
+    // (because of equal elements in A some permutations are possible):
+    // [[1, 2, 0], [0, 2, 1], [0, 1, 2]]
+@endcode
+@param src input single-channel array.
+@param dst output integer array of the same size as src.
+@param flags operation flags that could be a combination of cv::SortFlags
+@sa sort, randShuffle
+*/
+CV_EXPORTS_W void sortIdx(InputArray src, OutputArray dst, int flags);
+
+/** @brief Finds the real roots of a cubic equation.
+
+The function solveCubic finds the real roots of a cubic equation:
+-   if coeffs is a 4-element vector:
+\f[\texttt{coeffs} [0] x^3 +  \texttt{coeffs} [1] x^2 +  \texttt{coeffs} [2] x +  \texttt{coeffs} [3] = 0\f]
+-   if coeffs is a 3-element vector:
+\f[x^3 +  \texttt{coeffs} [0] x^2 +  \texttt{coeffs} [1] x +  \texttt{coeffs} [2] = 0\f]
+
+The roots are stored in the roots array.
+@param coeffs equation coefficients, an array of 3 or 4 elements.
+@param roots output array of real roots that has 1 or 3 elements.
+@return number of real roots. It can be 0, 1 or 2.
+*/
+CV_EXPORTS_W int solveCubic(InputArray coeffs, OutputArray roots);
+
+/** @brief Finds the real or complex roots of a polynomial equation.
+
+The function cv::solvePoly finds real and complex roots of a polynomial equation:
+\f[\texttt{coeffs} [n] x^{n} +  \texttt{coeffs} [n-1] x^{n-1} + ... +  \texttt{coeffs} [1] x +  \texttt{coeffs} [0] = 0\f]
+@param coeffs array of polynomial coefficients.
+@param roots output (complex) array of roots.
+@param maxIters maximum number of iterations the algorithm does.
+*/
+CV_EXPORTS_W double solvePoly(InputArray coeffs, OutputArray roots, int maxIters = 300);
+
+/** @brief Calculates eigenvalues and eigenvectors of a symmetric matrix.
+
+The function cv::eigen calculates just eigenvalues, or eigenvalues and eigenvectors of the symmetric
+matrix src:
+@code
+    src*eigenvectors.row(i).t() = eigenvalues.at<srcType>(i)*eigenvectors.row(i).t()
+@endcode
+
+@note Use cv::eigenNonSymmetric for calculation of real eigenvalues and eigenvectors of non-symmetric matrix.
+
+@param src input matrix that must have CV_32FC1 or CV_64FC1 type, square size and be symmetrical
+(src ^T^ == src).
+@param eigenvalues output vector of eigenvalues of the same type as src; the eigenvalues are stored
+in the descending order.
+@param eigenvectors output matrix of eigenvectors; it has the same size and type as src; the
+eigenvectors are stored as subsequent matrix rows, in the same order as the corresponding
+eigenvalues.
+@sa eigenNonSymmetric, completeSymm, PCA
+*/
+CV_EXPORTS_W bool eigen(InputArray src, OutputArray eigenvalues,
+                        OutputArray eigenvectors = noArray());
+
+/** @brief Calculates eigenvalues and eigenvectors of a non-symmetric matrix (real eigenvalues only).
+
+@note Assumes real eigenvalues.
+
+The function calculates eigenvalues and eigenvectors (optional) of the square matrix src:
+@code
+    src*eigenvectors.row(i).t() = eigenvalues.at<srcType>(i)*eigenvectors.row(i).t()
+@endcode
+
+@param src input matrix (CV_32FC1 or CV_64FC1 type).
+@param eigenvalues output vector of eigenvalues (type is the same type as src).
+@param eigenvectors output matrix of eigenvectors (type is the same type as src). The eigenvectors are stored as subsequent matrix rows, in the same order as the corresponding eigenvalues.
+@sa eigen
+*/
+CV_EXPORTS_W void eigenNonSymmetric(InputArray src, OutputArray eigenvalues,
+                                    OutputArray eigenvectors);
+
+/** @brief Calculates the covariance matrix of a set of vectors.
+
+The function cv::calcCovarMatrix calculates the covariance matrix and, optionally, the mean vector of
+the set of input vectors.
+@param samples samples stored as separate matrices
+@param nsamples number of samples
+@param covar output covariance matrix of the type ctype and square size.
+@param mean input or output (depending on the flags) array as the average value of the input vectors.
+@param flags operation flags as a combination of #CovarFlags
+@param ctype type of the matrixl; it equals 'CV_64F' by default.
+@sa PCA, mulTransposed, Mahalanobis
+@todo InputArrayOfArrays
+*/
+CV_EXPORTS void calcCovarMatrix( const Mat* samples, int nsamples, Mat& covar, Mat& mean,
+                                 int flags, int ctype = CV_64F);
+
+/** @overload
+@note use #COVAR_ROWS or #COVAR_COLS flag
+@param samples samples stored as rows/columns of a single matrix.
+@param covar output covariance matrix of the type ctype and square size.
+@param mean input or output (depending on the flags) array as the average value of the input vectors.
+@param flags operation flags as a combination of #CovarFlags
+@param ctype type of the matrixl; it equals 'CV_64F' by default.
+*/
+CV_EXPORTS_W void calcCovarMatrix( InputArray samples, OutputArray covar,
+                                   InputOutputArray mean, int flags, int ctype = CV_64F);
+
+/** wrap PCA::operator() */
+CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean,
+                             OutputArray eigenvectors, int maxComponents = 0);
+
+/** wrap PCA::operator() and add eigenvalues output parameter */
+CV_EXPORTS_AS(PCACompute2) void PCACompute(InputArray data, InputOutputArray mean,
+                                           OutputArray eigenvectors, OutputArray eigenvalues,
+                                           int maxComponents = 0);
+
+/** wrap PCA::operator() */
+CV_EXPORTS_W void PCACompute(InputArray data, InputOutputArray mean,
+                             OutputArray eigenvectors, double retainedVariance);
+
+/** wrap PCA::operator() and add eigenvalues output parameter */
+CV_EXPORTS_AS(PCACompute2) void PCACompute(InputArray data, InputOutputArray mean,
+                                           OutputArray eigenvectors, OutputArray eigenvalues,
+                                           double retainedVariance);
+
+/** wrap PCA::project */
+CV_EXPORTS_W void PCAProject(InputArray data, InputArray mean,
+                             InputArray eigenvectors, OutputArray result);
+
+/** wrap PCA::backProject */
+CV_EXPORTS_W void PCABackProject(InputArray data, InputArray mean,
+                                 InputArray eigenvectors, OutputArray result);
+
+/** wrap SVD::compute */
+CV_EXPORTS_W void SVDecomp( InputArray src, OutputArray w, OutputArray u, OutputArray vt, int flags = 0 );
+
+/** wrap SVD::backSubst */
+CV_EXPORTS_W void SVBackSubst( InputArray w, InputArray u, InputArray vt,
+                               InputArray rhs, OutputArray dst );
+
+/** @brief Calculates the Mahalanobis distance between two vectors.
+
+The function cv::Mahalanobis calculates and returns the weighted distance between two vectors:
+\f[d( \texttt{vec1} , \texttt{vec2} )= \sqrt{\sum_{i,j}{\texttt{icovar(i,j)}\cdot(\texttt{vec1}(I)-\texttt{vec2}(I))\cdot(\texttt{vec1(j)}-\texttt{vec2(j)})} }\f]
+The covariance matrix may be calculated using the #calcCovarMatrix function and then inverted using
+the invert function (preferably using the #DECOMP_SVD method, as the most accurate).
+@param v1 first 1D input vector.
+@param v2 second 1D input vector.
+@param icovar inverse covariance matrix.
+*/
+CV_EXPORTS_W double Mahalanobis(InputArray v1, InputArray v2, InputArray icovar);
+
+/** @brief Performs a forward or inverse Discrete Fourier transform of a 1D or 2D floating-point array.
+
+The function cv::dft performs one of the following:
+-   Forward the Fourier transform of a 1D vector of N elements:
+    \f[Y = F^{(N)}  \cdot X,\f]
+    where \f$F^{(N)}_{jk}=\exp(-2\pi i j k/N)\f$ and \f$i=\sqrt{-1}\f$
+-   Inverse the Fourier transform of a 1D vector of N elements:
+    \f[\begin{array}{l} X'=  \left (F^{(N)} \right )^{-1}  \cdot Y =  \left (F^{(N)} \right )^*  \cdot y  \\ X = (1/N)  \cdot X, \end{array}\f]
+    where \f$F^*=\left(\textrm{Re}(F^{(N)})-\textrm{Im}(F^{(N)})\right)^T\f$
+-   Forward the 2D Fourier transform of a M x N matrix:
+    \f[Y = F^{(M)}  \cdot X  \cdot F^{(N)}\f]
+-   Inverse the 2D Fourier transform of a M x N matrix:
+    \f[\begin{array}{l} X'=  \left (F^{(M)} \right )^*  \cdot Y  \cdot \left (F^{(N)} \right )^* \\ X =  \frac{1}{M \cdot N} \cdot X' \end{array}\f]
+
+In case of real (single-channel) data, the output spectrum of the forward Fourier transform or input
+spectrum of the inverse Fourier transform can be represented in a packed format called *CCS*
+(complex-conjugate-symmetrical). It was borrowed from IPL (Intel\* Image Processing Library). Here
+is how 2D *CCS* spectrum looks:
+\f[\begin{bmatrix} Re Y_{0,0} & Re Y_{0,1} & Im Y_{0,1} & Re Y_{0,2} & Im Y_{0,2} &  \cdots & Re Y_{0,N/2-1} & Im Y_{0,N/2-1} & Re Y_{0,N/2}  \\ Re Y_{1,0} & Re Y_{1,1} & Im Y_{1,1} & Re Y_{1,2} & Im Y_{1,2} &  \cdots & Re Y_{1,N/2-1} & Im Y_{1,N/2-1} & Re Y_{1,N/2}  \\ Im Y_{1,0} & Re Y_{2,1} & Im Y_{2,1} & Re Y_{2,2} & Im Y_{2,2} &  \cdots & Re Y_{2,N/2-1} & Im Y_{2,N/2-1} & Im Y_{1,N/2}  \\ \hdotsfor{9} \\ Re Y_{M/2-1,0} &  Re Y_{M-3,1}  & Im Y_{M-3,1} &  \hdotsfor{3} & Re Y_{M-3,N/2-1} & Im Y_{M-3,N/2-1}& Re Y_{M/2-1,N/2}  \\ Im Y_{M/2-1,0} &  Re Y_{M-2,1}  & Im Y_{M-2,1} &  \hdotsfor{3} & Re Y_{M-2,N/2-1} & Im Y_{M-2,N/2-1}& Im Y_{M/2-1,N/2}  \\ Re Y_{M/2,0}  &  Re Y_{M-1,1} &  Im Y_{M-1,1} &  \hdotsfor{3} & Re Y_{M-1,N/2-1} & Im Y_{M-1,N/2-1}& Re Y_{M/2,N/2} \end{bmatrix}\f]
+
+In case of 1D transform of a real vector, the output looks like the first row of the matrix above.
+
+So, the function chooses an operation mode depending on the flags and size of the input array:
+-   If #DFT_ROWS is set or the input array has a single row or single column, the function
+    performs a 1D forward or inverse transform of each row of a matrix when #DFT_ROWS is set.
+    Otherwise, it performs a 2D transform.
+-   If the input array is real and #DFT_INVERSE is not set, the function performs a forward 1D or
+    2D transform:
+    -   When #DFT_COMPLEX_OUTPUT is set, the output is a complex matrix of the same size as
+        input.
+    -   When #DFT_COMPLEX_OUTPUT is not set, the output is a real matrix of the same size as
+        input. In case of 2D transform, it uses the packed format as shown above. In case of a
+        single 1D transform, it looks like the first row of the matrix above. In case of
+        multiple 1D transforms (when using the #DFT_ROWS flag), each row of the output matrix
+        looks like the first row of the matrix above.
+-   If the input array is complex and either #DFT_INVERSE or #DFT_REAL_OUTPUT are not set, the
+    output is a complex array of the same size as input. The function performs a forward or
+    inverse 1D or 2D transform of the whole input array or each row of the input array
+    independently, depending on the flags DFT_INVERSE and DFT_ROWS.
+-   When #DFT_INVERSE is set and the input array is real, or it is complex but #DFT_REAL_OUTPUT
+    is set, the output is a real array of the same size as input. The function performs a 1D or 2D
+    inverse transformation of the whole input array or each individual row, depending on the flags
+    #DFT_INVERSE and #DFT_ROWS.
+
+If #DFT_SCALE is set, the scaling is done after the transformation.
+
+Unlike dct, the function supports arrays of arbitrary size. But only those arrays are processed
+efficiently, whose sizes can be factorized in a product of small prime numbers (2, 3, and 5 in the
+current implementation). Such an efficient DFT size can be calculated using the getOptimalDFTSize
+method.
+
+The sample below illustrates how to calculate a DFT-based convolution of two 2D real arrays:
+@code
+    void convolveDFT(InputArray A, InputArray B, OutputArray C)
+    {
+        // reallocate the output array if needed
+        C.create(abs(A.rows - B.rows)+1, abs(A.cols - B.cols)+1, A.type());
+        Size dftSize;
+        // calculate the size of DFT transform
+        dftSize.width = getOptimalDFTSize(A.cols + B.cols - 1);
+        dftSize.height = getOptimalDFTSize(A.rows + B.rows - 1);
+
+        // allocate temporary buffers and initialize them with 0's
+        Mat tempA(dftSize, A.type(), Scalar::all(0));
+        Mat tempB(dftSize, B.type(), Scalar::all(0));
+
+        // copy A and B to the top-left corners of tempA and tempB, respectively
+        Mat roiA(tempA, Rect(0,0,A.cols,A.rows));
+        A.copyTo(roiA);
+        Mat roiB(tempB, Rect(0,0,B.cols,B.rows));
+        B.copyTo(roiB);
+
+        // now transform the padded A & B in-place;
+        // use "nonzeroRows" hint for faster processing
+        dft(tempA, tempA, 0, A.rows);
+        dft(tempB, tempB, 0, B.rows);
+
+        // multiply the spectrums;
+        // the function handles packed spectrum representations well
+        mulSpectrums(tempA, tempB, tempA);
+
+        // transform the product back from the frequency domain.
+        // Even though all the result rows will be non-zero,
+        // you need only the first C.rows of them, and thus you
+        // pass nonzeroRows == C.rows
+        dft(tempA, tempA, DFT_INVERSE + DFT_SCALE, C.rows);
+
+        // now copy the result back to C.
+        tempA(Rect(0, 0, C.cols, C.rows)).copyTo(C);
+
+        // all the temporary buffers will be deallocated automatically
+    }
+@endcode
+To optimize this sample, consider the following approaches:
+-   Since nonzeroRows != 0 is passed to the forward transform calls and since A and B are copied to
+    the top-left corners of tempA and tempB, respectively, it is not necessary to clear the whole
+    tempA and tempB. It is only necessary to clear the tempA.cols - A.cols ( tempB.cols - B.cols)
+    rightmost columns of the matrices.
+-   This DFT-based convolution does not have to be applied to the whole big arrays, especially if B
+    is significantly smaller than A or vice versa. Instead, you can calculate convolution by parts.
+    To do this, you need to split the output array C into multiple tiles. For each tile, estimate
+    which parts of A and B are required to calculate convolution in this tile. If the tiles in C are
+    too small, the speed will decrease a lot because of repeated work. In the ultimate case, when
+    each tile in C is a single pixel, the algorithm becomes equivalent to the naive convolution
+    algorithm. If the tiles are too big, the temporary arrays tempA and tempB become too big and
+    there is also a slowdown because of bad cache locality. So, there is an optimal tile size
+    somewhere in the middle.
+-   If different tiles in C can be calculated in parallel and, thus, the convolution is done by
+    parts, the loop can be threaded.
+
+All of the above improvements have been implemented in #matchTemplate and #filter2D . Therefore, by
+using them, you can get the performance even better than with the above theoretically optimal
+implementation. Though, those two functions actually calculate cross-correlation, not convolution,
+so you need to "flip" the second convolution operand B vertically and horizontally using flip .
+@note
+-   An example using the discrete fourier transform can be found at
+    opencv_source_code/samples/cpp/dft.cpp
+-   (Python) An example using the dft functionality to perform Wiener deconvolution can be found
+    at opencv_source/samples/python/deconvolution.py
+-   (Python) An example rearranging the quadrants of a Fourier image can be found at
+    opencv_source/samples/python/dft.py
+@param src input array that could be real or complex.
+@param dst output array whose size and type depends on the flags .
+@param flags transformation flags, representing a combination of the #DftFlags
+@param nonzeroRows when the parameter is not zero, the function assumes that only the first
+nonzeroRows rows of the input array (#DFT_INVERSE is not set) or only the first nonzeroRows of the
+output array (#DFT_INVERSE is set) contain non-zeros, thus, the function can handle the rest of the
+rows more efficiently and save some time; this technique is very useful for calculating array
+cross-correlation or convolution using DFT.
+@sa dct, getOptimalDFTSize, mulSpectrums, filter2D, matchTemplate, flip, cartToPolar,
+magnitude, phase
+*/
+CV_EXPORTS_W void dft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0);
+
+/** @brief Calculates the inverse Discrete Fourier Transform of a 1D or 2D array.
+
+idft(src, dst, flags) is equivalent to dft(src, dst, flags | #DFT_INVERSE) .
+@note None of dft and idft scales the result by default. So, you should pass #DFT_SCALE to one of
+dft or idft explicitly to make these transforms mutually inverse.
+@sa dft, dct, idct, mulSpectrums, getOptimalDFTSize
+@param src input floating-point real or complex array.
+@param dst output array whose size and type depend on the flags.
+@param flags operation flags (see dft and #DftFlags).
+@param nonzeroRows number of dst rows to process; the rest of the rows have undefined content (see
+the convolution sample in dft description.
+*/
+CV_EXPORTS_W void idft(InputArray src, OutputArray dst, int flags = 0, int nonzeroRows = 0);
+
+/** @brief Performs a forward or inverse discrete Cosine transform of 1D or 2D array.
+
+The function cv::dct performs a forward or inverse discrete Cosine transform (DCT) of a 1D or 2D
+floating-point array:
+-   Forward Cosine transform of a 1D vector of N elements:
+    \f[Y = C^{(N)}  \cdot X\f]
+    where
+    \f[C^{(N)}_{jk}= \sqrt{\alpha_j/N} \cos \left ( \frac{\pi(2k+1)j}{2N} \right )\f]
+    and
+    \f$\alpha_0=1\f$, \f$\alpha_j=2\f$ for *j \> 0*.
+-   Inverse Cosine transform of a 1D vector of N elements:
+    \f[X =  \left (C^{(N)} \right )^{-1}  \cdot Y =  \left (C^{(N)} \right )^T  \cdot Y\f]
+    (since \f$C^{(N)}\f$ is an orthogonal matrix, \f$C^{(N)} \cdot \left(C^{(N)}\right)^T = I\f$ )
+-   Forward 2D Cosine transform of M x N matrix:
+    \f[Y = C^{(N)}  \cdot X  \cdot \left (C^{(N)} \right )^T\f]
+-   Inverse 2D Cosine transform of M x N matrix:
+    \f[X =  \left (C^{(N)} \right )^T  \cdot X  \cdot C^{(N)}\f]
+
+The function chooses the mode of operation by looking at the flags and size of the input array:
+-   If (flags & #DCT_INVERSE) == 0, the function does a forward 1D or 2D transform. Otherwise, it
+    is an inverse 1D or 2D transform.
+-   If (flags & #DCT_ROWS) != 0, the function performs a 1D transform of each row.
+-   If the array is a single column or a single row, the function performs a 1D transform.
+-   If none of the above is true, the function performs a 2D transform.
+
+@note Currently dct supports even-size arrays (2, 4, 6 ...). For data analysis and approximation, you
+can pad the array when necessary.
+Also, the function performance depends very much, and not monotonically, on the array size (see
+getOptimalDFTSize ). In the current implementation DCT of a vector of size N is calculated via DFT
+of a vector of size N/2 . Thus, the optimal DCT size N1 \>= N can be calculated as:
+@code
+    size_t getOptimalDCTSize(size_t N) { return 2*getOptimalDFTSize((N+1)/2); }
+    N1 = getOptimalDCTSize(N);
+@endcode
+@param src input floating-point array.
+@param dst output array of the same size and type as src .
+@param flags transformation flags as a combination of cv::DftFlags (DCT_*)
+@sa dft, getOptimalDFTSize, idct
+*/
+CV_EXPORTS_W void dct(InputArray src, OutputArray dst, int flags = 0);
+
+/** @brief Calculates the inverse Discrete Cosine Transform of a 1D or 2D array.
+
+idct(src, dst, flags) is equivalent to dct(src, dst, flags | DCT_INVERSE).
+@param src input floating-point single-channel array.
+@param dst output array of the same size and type as src.
+@param flags operation flags.
+@sa  dct, dft, idft, getOptimalDFTSize
+*/
+CV_EXPORTS_W void idct(InputArray src, OutputArray dst, int flags = 0);
+
+/** @brief Performs the per-element multiplication of two Fourier spectrums.
+
+The function cv::mulSpectrums performs the per-element multiplication of the two CCS-packed or complex
+matrices that are results of a real or complex Fourier transform.
+
+The function, together with dft and idft, may be used to calculate convolution (pass conjB=false )
+or correlation (pass conjB=true ) of two arrays rapidly. When the arrays are complex, they are
+simply multiplied (per element) with an optional conjugation of the second-array elements. When the
+arrays are real, they are assumed to be CCS-packed (see dft for details).
+@param a first input array.
+@param b second input array of the same size and type as src1 .
+@param c output array of the same size and type as src1 .
+@param flags operation flags; currently, the only supported flag is cv::DFT_ROWS, which indicates that
+each row of src1 and src2 is an independent 1D Fourier spectrum. If you do not want to use this flag, then simply add a `0` as value.
+@param conjB optional flag that conjugates the second input array before the multiplication (true)
+or not (false).
+*/
+CV_EXPORTS_W void mulSpectrums(InputArray a, InputArray b, OutputArray c,
+                               int flags, bool conjB = false);
+
+/** @brief Returns the optimal DFT size for a given vector size.
+
+DFT performance is not a monotonic function of a vector size. Therefore, when you calculate
+convolution of two arrays or perform the spectral analysis of an array, it usually makes sense to
+pad the input data with zeros to get a bit larger array that can be transformed much faster than the
+original one. Arrays whose size is a power-of-two (2, 4, 8, 16, 32, ...) are the fastest to process.
+Though, the arrays whose size is a product of 2's, 3's, and 5's (for example, 300 = 5\*5\*3\*2\*2)
+are also processed quite efficiently.
+
+The function cv::getOptimalDFTSize returns the minimum number N that is greater than or equal to vecsize
+so that the DFT of a vector of size N can be processed efficiently. In the current implementation N
+= 2 ^p^ \* 3 ^q^ \* 5 ^r^ for some integer p, q, r.
+
+The function returns a negative number if vecsize is too large (very close to INT_MAX ).
+
+While the function cannot be used directly to estimate the optimal vector size for DCT transform
+(since the current DCT implementation supports only even-size vectors), it can be easily processed
+as getOptimalDFTSize((vecsize+1)/2)\*2.
+@param vecsize vector size.
+@sa dft, dct, idft, idct, mulSpectrums
+*/
+CV_EXPORTS_W int getOptimalDFTSize(int vecsize);
+
+/** @brief Returns the default random number generator.
+
+The function cv::theRNG returns the default random number generator. For each thread, there is a
+separate random number generator, so you can use the function safely in multi-thread environments.
+If you just need to get a single random number using this generator or initialize an array, you can
+use randu or randn instead. But if you are going to generate many random numbers inside a loop, it
+is much faster to use this function to retrieve the generator and then use RNG::operator _Tp() .
+@sa RNG, randu, randn
+*/
+CV_EXPORTS RNG& theRNG();
+
+/** @brief Sets state of default random number generator.
+
+The function cv::setRNGSeed sets state of default random number generator to custom value.
+@param seed new state for default random number generator
+@sa RNG, randu, randn
+*/
+CV_EXPORTS_W void setRNGSeed(int seed);
+
+/** @brief Generates a single uniformly-distributed random number or an array of random numbers.
+
+Non-template variant of the function fills the matrix dst with uniformly-distributed
+random numbers from the specified range:
+\f[\texttt{low} _c  \leq \texttt{dst} (I)_c <  \texttt{high} _c\f]
+@param dst output array of random numbers; the array must be pre-allocated.
+@param low inclusive lower boundary of the generated random numbers.
+@param high exclusive upper boundary of the generated random numbers.
+@sa RNG, randn, theRNG
+*/
+CV_EXPORTS_W void randu(InputOutputArray dst, InputArray low, InputArray high);
+
+/** @brief Fills the array with normally distributed random numbers.
+
+The function cv::randn fills the matrix dst with normally distributed random numbers with the specified
+mean vector and the standard deviation matrix. The generated random numbers are clipped to fit the
+value range of the output array data type.
+@param dst output array of random numbers; the array must be pre-allocated and have 1 to 4 channels.
+@param mean mean value (expectation) of the generated random numbers.
+@param stddev standard deviation of the generated random numbers; it can be either a vector (in
+which case a diagonal standard deviation matrix is assumed) or a square matrix.
+@sa RNG, randu
+*/
+CV_EXPORTS_W void randn(InputOutputArray dst, InputArray mean, InputArray stddev);
+
+/** @brief Shuffles the array elements randomly.
+
+The function cv::randShuffle shuffles the specified 1D array by randomly choosing pairs of elements and
+swapping them. The number of such swap operations will be dst.rows\*dst.cols\*iterFactor .
+@param dst input/output numerical 1D array.
+@param iterFactor scale factor that determines the number of random swap operations (see the details
+below).
+@param rng optional random number generator used for shuffling; if it is zero, theRNG () is used
+instead.
+@sa RNG, sort
+*/
+CV_EXPORTS_W void randShuffle(InputOutputArray dst, double iterFactor = 1., RNG* rng = 0);
+
+/** @brief Principal Component Analysis
+
+The class is used to calculate a special basis for a set of vectors. The
+basis will consist of eigenvectors of the covariance matrix calculated
+from the input set of vectors. The class %PCA can also transform
+vectors to/from the new coordinate space defined by the basis. Usually,
+in this new coordinate system, each vector from the original set (and
+any linear combination of such vectors) can be quite accurately
+approximated by taking its first few components, corresponding to the
+eigenvectors of the largest eigenvalues of the covariance matrix.
+Geometrically it means that you calculate a projection of the vector to
+a subspace formed by a few eigenvectors corresponding to the dominant
+eigenvalues of the covariance matrix. And usually such a projection is
+very close to the original vector. So, you can represent the original
+vector from a high-dimensional space with a much shorter vector
+consisting of the projected vector's coordinates in the subspace. Such a
+transformation is also known as Karhunen-Loeve Transform, or KLT.
+See http://en.wikipedia.org/wiki/Principal_component_analysis
+
+The sample below is the function that takes two matrices. The first
+function stores a set of vectors (a row per vector) that is used to
+calculate PCA. The second function stores another "test" set of vectors
+(a row per vector). First, these vectors are compressed with PCA, then
+reconstructed back, and then the reconstruction error norm is computed
+and printed for each vector. :
+
+@code{.cpp}
+using namespace cv;
+
+PCA compressPCA(const Mat& pcaset, int maxComponents,
+                const Mat& testset, Mat& compressed)
+{
+    PCA pca(pcaset, // pass the data
+            Mat(), // we do not have a pre-computed mean vector,
+                   // so let the PCA engine to compute it
+            PCA::DATA_AS_ROW, // indicate that the vectors
+                                // are stored as matrix rows
+                                // (use PCA::DATA_AS_COL if the vectors are
+                                // the matrix columns)
+            maxComponents // specify, how many principal components to retain
+            );
+    // if there is no test data, just return the computed basis, ready-to-use
+    if( !testset.data )
+        return pca;
+    CV_Assert( testset.cols == pcaset.cols );
+
+    compressed.create(testset.rows, maxComponents, testset.type());
+
+    Mat reconstructed;
+    for( int i = 0; i < testset.rows; i++ )
+    {
+        Mat vec = testset.row(i), coeffs = compressed.row(i), reconstructed;
+        // compress the vector, the result will be stored
+        // in the i-th row of the output matrix
+        pca.project(vec, coeffs);
+        // and then reconstruct it
+        pca.backProject(coeffs, reconstructed);
+        // and measure the error
+        printf("%d. diff = %g\n", i, norm(vec, reconstructed, NORM_L2));
+    }
+    return pca;
+}
+@endcode
+@sa calcCovarMatrix, mulTransposed, SVD, dft, dct
+*/
+class CV_EXPORTS PCA
+{
+public:
+    enum Flags { DATA_AS_ROW = 0, //!< indicates that the input samples are stored as matrix rows
+                 DATA_AS_COL = 1, //!< indicates that the input samples are stored as matrix columns
+                 USE_AVG     = 2  //!
+               };
+
+    /** @brief default constructor
+
+    The default constructor initializes an empty %PCA structure. The other
+    constructors initialize the structure and call PCA::operator()().
+    */
+    PCA();
+
+    /** @overload
+    @param data input samples stored as matrix rows or matrix columns.
+    @param mean optional mean value; if the matrix is empty (@c noArray()),
+    the mean is computed from the data.
+    @param flags operation flags; currently the parameter is only used to
+    specify the data layout (PCA::Flags)
+    @param maxComponents maximum number of components that %PCA should
+    retain; by default, all the components are retained.
+    */
+    PCA(InputArray data, InputArray mean, int flags, int maxComponents = 0);
+
+    /** @overload
+    @param data input samples stored as matrix rows or matrix columns.
+    @param mean optional mean value; if the matrix is empty (noArray()),
+    the mean is computed from the data.
+    @param flags operation flags; currently the parameter is only used to
+    specify the data layout (PCA::Flags)
+    @param retainedVariance Percentage of variance that PCA should retain.
+    Using this parameter will let the PCA decided how many components to
+    retain but it will always keep at least 2.
+    */
+    PCA(InputArray data, InputArray mean, int flags, double retainedVariance);
+
+    /** @brief performs %PCA
+
+    The operator performs %PCA of the supplied dataset. It is safe to reuse
+    the same PCA structure for multiple datasets. That is, if the structure
+    has been previously used with another dataset, the existing internal
+    data is reclaimed and the new @ref eigenvalues, @ref eigenvectors and @ref
+    mean are allocated and computed.
+
+    The computed @ref eigenvalues are sorted from the largest to the smallest and
+    the corresponding @ref eigenvectors are stored as eigenvectors rows.
+
+    @param data input samples stored as the matrix rows or as the matrix
+    columns.
+    @param mean optional mean value; if the matrix is empty (noArray()),
+    the mean is computed from the data.
+    @param flags operation flags; currently the parameter is only used to
+    specify the data layout. (Flags)
+    @param maxComponents maximum number of components that PCA should
+    retain; by default, all the components are retained.
+    */
+    PCA& operator()(InputArray data, InputArray mean, int flags, int maxComponents = 0);
+
+    /** @overload
+    @param data input samples stored as the matrix rows or as the matrix
+    columns.
+    @param mean optional mean value; if the matrix is empty (noArray()),
+    the mean is computed from the data.
+    @param flags operation flags; currently the parameter is only used to
+    specify the data layout. (PCA::Flags)
+    @param retainedVariance Percentage of variance that %PCA should retain.
+    Using this parameter will let the %PCA decided how many components to
+    retain but it will always keep at least 2.
+     */
+    PCA& operator()(InputArray data, InputArray mean, int flags, double retainedVariance);
+
+    /** @brief Projects vector(s) to the principal component subspace.
+
+    The methods project one or more vectors to the principal component
+    subspace, where each vector projection is represented by coefficients in
+    the principal component basis. The first form of the method returns the
+    matrix that the second form writes to the result. So the first form can
+    be used as a part of expression while the second form can be more
+    efficient in a processing loop.
+    @param vec input vector(s); must have the same dimensionality and the
+    same layout as the input data used at %PCA phase, that is, if
+    DATA_AS_ROW are specified, then `vec.cols==data.cols`
+    (vector dimensionality) and `vec.rows` is the number of vectors to
+    project, and the same is true for the PCA::DATA_AS_COL case.
+    */
+    Mat project(InputArray vec) const;
+
+    /** @overload
+    @param vec input vector(s); must have the same dimensionality and the
+    same layout as the input data used at PCA phase, that is, if
+    DATA_AS_ROW are specified, then `vec.cols==data.cols`
+    (vector dimensionality) and `vec.rows` is the number of vectors to
+    project, and the same is true for the PCA::DATA_AS_COL case.
+    @param result output vectors; in case of PCA::DATA_AS_COL, the
+    output matrix has as many columns as the number of input vectors, this
+    means that `result.cols==vec.cols` and the number of rows match the
+    number of principal components (for example, `maxComponents` parameter
+    passed to the constructor).
+     */
+    void project(InputArray vec, OutputArray result) const;
+
+    /** @brief Reconstructs vectors from their PC projections.
+
+    The methods are inverse operations to PCA::project. They take PC
+    coordinates of projected vectors and reconstruct the original vectors.
+    Unless all the principal components have been retained, the
+    reconstructed vectors are different from the originals. But typically,
+    the difference is small if the number of components is large enough (but
+    still much smaller than the original vector dimensionality). As a
+    result, PCA is used.
+    @param vec coordinates of the vectors in the principal component
+    subspace, the layout and size are the same as of PCA::project output
+    vectors.
+     */
+    Mat backProject(InputArray vec) const;
+
+    /** @overload
+    @param vec coordinates of the vectors in the principal component
+    subspace, the layout and size are the same as of PCA::project output
+    vectors.
+    @param result reconstructed vectors; the layout and size are the same as
+    of PCA::project input vectors.
+     */
+    void backProject(InputArray vec, OutputArray result) const;
+
+    /** @brief write PCA objects
+
+    Writes @ref eigenvalues @ref eigenvectors and @ref mean to specified FileStorage
+     */
+    void write(FileStorage& fs) const;
+
+    /** @brief load PCA objects
+
+    Loads @ref eigenvalues @ref eigenvectors and @ref mean from specified FileNode
+     */
+    void read(const FileNode& fn);
+
+    Mat eigenvectors; //!< eigenvectors of the covariation matrix
+    Mat eigenvalues; //!< eigenvalues of the covariation matrix
+    Mat mean; //!< mean value subtracted before the projection and added after the back projection
+};
+
+/** @example samples/cpp/pca.cpp
+An example using %PCA for dimensionality reduction while maintaining an amount of variance
+*/
+
+/** @example samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp
+Check @ref tutorial_introduction_to_pca "the corresponding tutorial" for more details
+*/
+
+/**
+@brief Linear Discriminant Analysis
+@todo document this class
+*/
+class CV_EXPORTS LDA
+{
+public:
+    /** @brief constructor
+    Initializes a LDA with num_components (default 0).
+    */
+    explicit LDA(int num_components = 0);
+
+    /** Initializes and performs a Discriminant Analysis with Fisher's
+     Optimization Criterion on given data in src and corresponding labels
+     in labels. If 0 (or less) number of components are given, they are
+     automatically determined for given data in computation.
+    */
+    LDA(InputArrayOfArrays src, InputArray labels, int num_components = 0);
+
+    /** Serializes this object to a given filename.
+      */
+    void save(const String& filename) const;
+
+    /** Deserializes this object from a given filename.
+      */
+    void load(const String& filename);
+
+    /** Serializes this object to a given cv::FileStorage.
+      */
+    void save(FileStorage& fs) const;
+
+    /** Deserializes this object from a given cv::FileStorage.
+      */
+    void load(const FileStorage& node);
+
+    /** destructor
+      */
+    ~LDA();
+
+    /** Compute the discriminants for data in src (row aligned) and labels.
+      */
+    void compute(InputArrayOfArrays src, InputArray labels);
+
+    /** Projects samples into the LDA subspace.
+        src may be one or more row aligned samples.
+      */
+    Mat project(InputArray src);
+
+    /** Reconstructs projections from the LDA subspace.
+        src may be one or more row aligned projections.
+      */
+    Mat reconstruct(InputArray src);
+
+    /** Returns the eigenvectors of this LDA.
+      */
+    Mat eigenvectors() const { return _eigenvectors; }
+
+    /** Returns the eigenvalues of this LDA.
+      */
+    Mat eigenvalues() const { return _eigenvalues; }
+
+    static Mat subspaceProject(InputArray W, InputArray mean, InputArray src);
+    static Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src);
+
+protected:
+    int _num_components;
+    Mat _eigenvectors;
+    Mat _eigenvalues;
+    void lda(InputArrayOfArrays src, InputArray labels);
+};
+
+/** @brief Singular Value Decomposition
+
+Class for computing Singular Value Decomposition of a floating-point
+matrix. The Singular Value Decomposition is used to solve least-square
+problems, under-determined linear systems, invert matrices, compute
+condition numbers, and so on.
+
+If you want to compute a condition number of a matrix or an absolute value of
+its determinant, you do not need `u` and `vt`. You can pass
+flags=SVD::NO_UV|... . Another flag SVD::FULL_UV indicates that full-size u
+and vt must be computed, which is not necessary most of the time.
+
+@sa invert, solve, eigen, determinant
+*/
+class CV_EXPORTS SVD
+{
+public:
+    enum Flags {
+        /** allow the algorithm to modify the decomposed matrix; it can save space and speed up
+            processing. currently ignored. */
+        MODIFY_A = 1,
+        /** indicates that only a vector of singular values `w` is to be processed, while u and vt
+            will be set to empty matrices */
+        NO_UV    = 2,
+        /** when the matrix is not square, by default the algorithm produces u and vt matrices of
+            sufficiently large size for the further A reconstruction; if, however, FULL_UV flag is
+            specified, u and vt will be full-size square orthogonal matrices.*/
+        FULL_UV  = 4
+    };
+
+    /** @brief the default constructor
+
+    initializes an empty SVD structure
+      */
+    SVD();
+
+    /** @overload
+    initializes an empty SVD structure and then calls SVD::operator()
+    @param src decomposed matrix. The depth has to be CV_32F or CV_64F.
+    @param flags operation flags (SVD::Flags)
+      */
+    SVD( InputArray src, int flags = 0 );
+
+    /** @brief the operator that performs SVD. The previously allocated u, w and vt are released.
+
+    The operator performs the singular value decomposition of the supplied
+    matrix. The u,`vt` , and the vector of singular values w are stored in
+    the structure. The same SVD structure can be reused many times with
+    different matrices. Each time, if needed, the previous u,`vt` , and w
+    are reclaimed and the new matrices are created, which is all handled by
+    Mat::create.
+    @param src decomposed matrix. The depth has to be CV_32F or CV_64F.
+    @param flags operation flags (SVD::Flags)
+      */
+    SVD& operator ()( InputArray src, int flags = 0 );
+
+    /** @brief decomposes matrix and stores the results to user-provided matrices
+
+    The methods/functions perform SVD of matrix. Unlike SVD::SVD constructor
+    and SVD::operator(), they store the results to the user-provided
+    matrices:
+
+    @code{.cpp}
+    Mat A, w, u, vt;
+    SVD::compute(A, w, u, vt);
+    @endcode
+
+    @param src decomposed matrix. The depth has to be CV_32F or CV_64F.
+    @param w calculated singular values
+    @param u calculated left singular vectors
+    @param vt transposed matrix of right singular vectors
+    @param flags operation flags - see SVD::Flags.
+      */
+    static void compute( InputArray src, OutputArray w,
+                         OutputArray u, OutputArray vt, int flags = 0 );
+
+    /** @overload
+    computes singular values of a matrix
+    @param src decomposed matrix. The depth has to be CV_32F or CV_64F.
+    @param w calculated singular values
+    @param flags operation flags - see SVD::Flags.
+      */
+    static void compute( InputArray src, OutputArray w, int flags = 0 );
+
+    /** @brief performs back substitution
+      */
+    static void backSubst( InputArray w, InputArray u,
+                           InputArray vt, InputArray rhs,
+                           OutputArray dst );
+
+    /** @brief solves an under-determined singular linear system
+
+    The method finds a unit-length solution x of a singular linear system
+    A\*x = 0. Depending on the rank of A, there can be no solutions, a
+    single solution or an infinite number of solutions. In general, the
+    algorithm solves the following problem:
+    \f[dst =  \arg \min _{x:  \| x \| =1}  \| src  \cdot x  \|\f]
+    @param src left-hand-side matrix.
+    @param dst found solution.
+      */
+    static void solveZ( InputArray src, OutputArray dst );
+
+    /** @brief performs a singular value back substitution.
+
+    The method calculates a back substitution for the specified right-hand
+    side:
+
+    \f[\texttt{x} =  \texttt{vt} ^T  \cdot diag( \texttt{w} )^{-1}  \cdot \texttt{u} ^T  \cdot \texttt{rhs} \sim \texttt{A} ^{-1}  \cdot \texttt{rhs}\f]
+
+    Using this technique you can either get a very accurate solution of the
+    convenient linear system, or the best (in the least-squares terms)
+    pseudo-solution of an overdetermined linear system.
+
+    @param rhs right-hand side of a linear system (u\*w\*v')\*dst = rhs to
+    be solved, where A has been previously decomposed.
+
+    @param dst found solution of the system.
+
+    @note Explicit SVD with the further back substitution only makes sense
+    if you need to solve many linear systems with the same left-hand side
+    (for example, src ). If all you need is to solve a single system
+    (possibly with multiple rhs immediately available), simply call solve
+    add pass #DECOMP_SVD there. It does absolutely the same thing.
+      */
+    void backSubst( InputArray rhs, OutputArray dst ) const;
+
+    /** @todo document */
+    template<typename _Tp, int m, int n, int nm> static
+    void compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w, Matx<_Tp, m, nm>& u, Matx<_Tp, n, nm>& vt );
+
+    /** @todo document */
+    template<typename _Tp, int m, int n, int nm> static
+    void compute( const Matx<_Tp, m, n>& a, Matx<_Tp, nm, 1>& w );
+
+    /** @todo document */
+    template<typename _Tp, int m, int n, int nm, int nb> static
+    void backSubst( const Matx<_Tp, nm, 1>& w, const Matx<_Tp, m, nm>& u, const Matx<_Tp, n, nm>& vt, const Matx<_Tp, m, nb>& rhs, Matx<_Tp, n, nb>& dst );
+
+    Mat u, w, vt;
+};
+
+/** @brief Random Number Generator
+
+Random number generator. It encapsulates the state (currently, a 64-bit
+integer) and has methods to return scalar random values and to fill
+arrays with random values. Currently it supports uniform and Gaussian
+(normal) distributions. The generator uses Multiply-With-Carry
+algorithm, introduced by G. Marsaglia (
+<http://en.wikipedia.org/wiki/Multiply-with-carry> ).
+Gaussian-distribution random numbers are generated using the Ziggurat
+algorithm ( <http://en.wikipedia.org/wiki/Ziggurat_algorithm> ),
+introduced by G. Marsaglia and W. W. Tsang.
+*/
+class CV_EXPORTS RNG
+{
+public:
+    enum { UNIFORM = 0,
+           NORMAL  = 1
+         };
+
+    /** @brief constructor
+
+    These are the RNG constructors. The first form sets the state to some
+    pre-defined value, equal to 2\*\*32-1 in the current implementation. The
+    second form sets the state to the specified value. If you passed state=0
+    , the constructor uses the above default value instead to avoid the
+    singular random number sequence, consisting of all zeros.
+    */
+    RNG();
+    /** @overload
+    @param state 64-bit value used to initialize the RNG.
+    */
+    RNG(uint64 state);
+    /**The method updates the state using the MWC algorithm and returns the
+    next 32-bit random number.*/
+    unsigned next();
+
+    /**Each of the methods updates the state using the MWC algorithm and
+    returns the next random number of the specified type. In case of integer
+    types, the returned number is from the available value range for the
+    specified type. In case of floating-point types, the returned value is
+    from [0,1) range.
+    */
+    operator uchar();
+    /** @overload */
+    operator schar();
+    /** @overload */
+    operator ushort();
+    /** @overload */
+    operator short();
+    /** @overload */
+    operator unsigned();
+    /** @overload */
+    operator int();
+    /** @overload */
+    operator float();
+    /** @overload */
+    operator double();
+
+    /** @brief returns a random integer sampled uniformly from [0, N).
+
+    The methods transform the state using the MWC algorithm and return the
+    next random number. The first form is equivalent to RNG::next . The
+    second form returns the random number modulo N, which means that the
+    result is in the range [0, N) .
+    */
+    unsigned operator ()();
+    /** @overload
+    @param N upper non-inclusive boundary of the returned random number.
+    */
+    unsigned operator ()(unsigned N);
+
+    /** @brief returns uniformly distributed integer random number from [a,b) range
+
+    The methods transform the state using the MWC algorithm and return the
+    next uniformly-distributed random number of the specified type, deduced
+    from the input parameter type, from the range [a, b) . There is a nuance
+    illustrated by the following sample:
+
+    @code{.cpp}
+    RNG rng;
+
+    // always produces 0
+    double a = rng.uniform(0, 1);
+
+    // produces double from [0, 1)
+    double a1 = rng.uniform((double)0, (double)1);
+
+    // produces float from [0, 1)
+    float b = rng.uniform(0.f, 1.f);
+
+    // produces double from [0, 1)
+    double c = rng.uniform(0., 1.);
+
+    // may cause compiler error because of ambiguity:
+    //  RNG::uniform(0, (int)0.999999)? or RNG::uniform((double)0, 0.99999)?
+    double d = rng.uniform(0, 0.999999);
+    @endcode
+
+    The compiler does not take into account the type of the variable to
+    which you assign the result of RNG::uniform . The only thing that
+    matters to the compiler is the type of a and b parameters. So, if you
+    want a floating-point random number, but the range boundaries are
+    integer numbers, either put dots in the end, if they are constants, or
+    use explicit type cast operators, as in the a1 initialization above.
+    @param a lower inclusive boundary of the returned random number.
+    @param b upper non-inclusive boundary of the returned random number.
+    */
+    int uniform(int a, int b);
+    /** @overload */
+    float uniform(float a, float b);
+    /** @overload */
+    double uniform(double a, double b);
+
+    /** @brief Fills arrays with random numbers.
+
+    @param mat 2D or N-dimensional matrix; currently matrices with more than
+    4 channels are not supported by the methods, use Mat::reshape as a
+    possible workaround.
+    @param distType distribution type, RNG::UNIFORM or RNG::NORMAL.
+    @param a first distribution parameter; in case of the uniform
+    distribution, this is an inclusive lower boundary, in case of the normal
+    distribution, this is a mean value.
+    @param b second distribution parameter; in case of the uniform
+    distribution, this is a non-inclusive upper boundary, in case of the
+    normal distribution, this is a standard deviation (diagonal of the
+    standard deviation matrix or the full standard deviation matrix).
+    @param saturateRange pre-saturation flag; for uniform distribution only;
+    if true, the method will first convert a and b to the acceptable value
+    range (according to the mat datatype) and then will generate uniformly
+    distributed random numbers within the range [saturate(a), saturate(b)),
+    if saturateRange=false, the method will generate uniformly distributed
+    random numbers in the original range [a, b) and then will saturate them,
+    it means, for example, that
+    <tt>theRNG().fill(mat_8u, RNG::UNIFORM, -DBL_MAX, DBL_MAX)</tt> will likely
+    produce array mostly filled with 0's and 255's, since the range (0, 255)
+    is significantly smaller than [-DBL_MAX, DBL_MAX).
+
+    Each of the methods fills the matrix with the random values from the
+    specified distribution. As the new numbers are generated, the RNG state
+    is updated accordingly. In case of multiple-channel images, every
+    channel is filled independently, which means that RNG cannot generate
+    samples from the multi-dimensional Gaussian distribution with
+    non-diagonal covariance matrix directly. To do that, the method
+    generates samples from multi-dimensional standard Gaussian distribution
+    with zero mean and identity covariation matrix, and then transforms them
+    using transform to get samples from the specified Gaussian distribution.
+    */
+    void fill( InputOutputArray mat, int distType, InputArray a, InputArray b, bool saturateRange = false );
+
+    /** @brief Returns the next random number sampled from the Gaussian distribution
+    @param sigma standard deviation of the distribution.
+
+    The method transforms the state using the MWC algorithm and returns the
+    next random number from the Gaussian distribution N(0,sigma) . That is,
+    the mean value of the returned random numbers is zero and the standard
+    deviation is the specified sigma .
+    */
+    double gaussian(double sigma);
+
+    uint64 state;
+
+    bool operator ==(const RNG& other) const;
+};
+
+/** @brief Mersenne Twister random number generator
+
+Inspired by http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/CODES/mt19937ar.c
+@todo document
+*/
+class CV_EXPORTS RNG_MT19937
+{
+public:
+    RNG_MT19937();
+    RNG_MT19937(unsigned s);
+    void seed(unsigned s);
+
+    unsigned next();
+
+    operator int();
+    operator unsigned();
+    operator float();
+    operator double();
+
+    unsigned operator ()(unsigned N);
+    unsigned operator ()();
+
+    /** @brief returns uniformly distributed integer random number from [a,b) range*/
+    int uniform(int a, int b);
+    /** @brief returns uniformly distributed floating-point random number from [a,b) range*/
+    float uniform(float a, float b);
+    /** @brief returns uniformly distributed double-precision floating-point random number from [a,b) range*/
+    double uniform(double a, double b);
+
+private:
+    enum PeriodParameters {N = 624, M = 397};
+    unsigned state[N];
+    int mti;
+};
+
+//! @} core_array
+
+//! @addtogroup core_cluster
+//!  @{
+
+//! k-means flags
+enum KmeansFlags {
+    /** Select random initial centers in each attempt.*/
+    KMEANS_RANDOM_CENTERS     = 0,
+    /** Use kmeans++ center initialization by Arthur and Vassilvitskii [Arthur2007].*/
+    KMEANS_PP_CENTERS         = 2,
+    /** During the first (and possibly the only) attempt, use the
+        user-supplied labels instead of computing them from the initial centers. For the second and
+        further attempts, use the random or semi-random centers. Use one of KMEANS_\*_CENTERS flag
+        to specify the exact method.*/
+    KMEANS_USE_INITIAL_LABELS = 1
+};
+
+/** @example samples/cpp/kmeans.cpp
+An example on k-means clustering
+*/
+
+/** @brief Finds centers of clusters and groups input samples around the clusters.
+
+The function kmeans implements a k-means algorithm that finds the centers of cluster_count clusters
+and groups the input samples around the clusters. As an output, \f$\texttt{bestLabels}_i\f$ contains a
+0-based cluster index for the sample stored in the \f$i^{th}\f$ row of the samples matrix.
+
+@note
+-   (Python) An example on k-means clustering can be found at
+    opencv_source_code/samples/python/kmeans.py
+@param data Data for clustering. An array of N-Dimensional points with float coordinates is needed.
+Examples of this array can be:
+-   Mat points(count, 2, CV_32F);
+-   Mat points(count, 1, CV_32FC2);
+-   Mat points(1, count, CV_32FC2);
+-   std::vector\<cv::Point2f\> points(sampleCount);
+@param K Number of clusters to split the set by.
+@param bestLabels Input/output integer array that stores the cluster indices for every sample.
+@param criteria The algorithm termination criteria, that is, the maximum number of iterations and/or
+the desired accuracy. The accuracy is specified as criteria.epsilon. As soon as each of the cluster
+centers moves by less than criteria.epsilon on some iteration, the algorithm stops.
+@param attempts Flag to specify the number of times the algorithm is executed using different
+initial labellings. The algorithm returns the labels that yield the best compactness (see the last
+function parameter).
+@param flags Flag that can take values of cv::KmeansFlags
+@param centers Output matrix of the cluster centers, one row per each cluster center.
+@return The function returns the compactness measure that is computed as
+\f[\sum _i  \| \texttt{samples} _i -  \texttt{centers} _{ \texttt{labels} _i} \| ^2\f]
+after every attempt. The best (minimum) value is chosen and the corresponding labels and the
+compactness value are returned by the function. Basically, you can use only the core of the
+function, set the number of attempts to 1, initialize labels each time using a custom algorithm,
+pass them with the ( flags = #KMEANS_USE_INITIAL_LABELS ) flag, and then choose the best
+(most-compact) clustering.
+*/
+CV_EXPORTS_W double kmeans( InputArray data, int K, InputOutputArray bestLabels,
+                            TermCriteria criteria, int attempts,
+                            int flags, OutputArray centers = noArray() );
+
+//! @} core_cluster
+
+//! @addtogroup core_basic
+//! @{
+
+/////////////////////////////// Formatted output of cv::Mat ///////////////////////////
+
+/** @todo document */
+class CV_EXPORTS Formatted
+{
+public:
+    virtual const char* next() = 0;
+    virtual void reset() = 0;
+    virtual ~Formatted();
+};
+
+/** @todo document */
+class CV_EXPORTS Formatter
+{
+public:
+    enum FormatType {
+           FMT_DEFAULT = 0,
+           FMT_MATLAB  = 1,
+           FMT_CSV     = 2,
+           FMT_PYTHON  = 3,
+           FMT_NUMPY   = 4,
+           FMT_C       = 5
+         };
+
+    virtual ~Formatter();
+
+    virtual Ptr<Formatted> format(const Mat& mtx) const = 0;
+
+    virtual void set16fPrecision(int p = 4) = 0;
+    virtual void set32fPrecision(int p = 8) = 0;
+    virtual void set64fPrecision(int p = 16) = 0;
+    virtual void setMultiline(bool ml = true) = 0;
+
+    static Ptr<Formatter> get(Formatter::FormatType fmt = FMT_DEFAULT);
+
+};
+
+static inline
+String& operator << (String& out, Ptr<Formatted> fmtd)
+{
+    fmtd->reset();
+    for(const char* str = fmtd->next(); str; str = fmtd->next())
+        out += cv::String(str);
+    return out;
+}
+
+static inline
+String& operator << (String& out, const Mat& mtx)
+{
+    return out << Formatter::get()->format(mtx);
+}
+
+//////////////////////////////////////// Algorithm ////////////////////////////////////
+
+class CV_EXPORTS Algorithm;
+
+template<typename _Tp, typename _EnumTp = void> struct ParamType {};
+
+
+/** @brief This is a base class for all more or less complex algorithms in OpenCV
+
+especially for classes of algorithms, for which there can be multiple implementations. The examples
+are stereo correspondence (for which there are algorithms like block matching, semi-global block
+matching, graph-cut etc.), background subtraction (which can be done using mixture-of-gaussians
+models, codebook-based algorithm etc.), optical flow (block matching, Lucas-Kanade, Horn-Schunck
+etc.).
+
+Here is example of SimpleBlobDetector use in your application via Algorithm interface:
+@snippet snippets/core_various.cpp Algorithm
+*/
+class CV_EXPORTS_W Algorithm
+{
+public:
+    Algorithm();
+    virtual ~Algorithm();
+
+    /** @brief Clears the algorithm state
+    */
+    CV_WRAP virtual void clear() {}
+
+    /** @brief Stores algorithm parameters in a file storage
+    */
+    CV_WRAP virtual void write(FileStorage& fs) const { CV_UNUSED(fs); }
+
+    /**
+    * @overload
+    */
+    CV_WRAP void write(FileStorage& fs, const String& name) const;
+#if CV_VERSION_MAJOR < 5
+    /** @deprecated */
+    void write(const Ptr<FileStorage>& fs, const String& name = String()) const;
+#endif
+
+    /** @brief Reads algorithm parameters from a file storage
+    */
+    CV_WRAP virtual void read(const FileNode& fn) { CV_UNUSED(fn); }
+
+    /** @brief Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
+    */
+    CV_WRAP virtual bool empty() const { return false; }
+
+    /** @brief Reads algorithm from the file node
+
+    This is static template method of Algorithm. It's usage is following (in the case of SVM):
+    @code
+    cv::FileStorage fsRead("example.xml", FileStorage::READ);
+    Ptr<SVM> svm = Algorithm::read<SVM>(fsRead.root());
+    @endcode
+    In order to make this method work, the derived class must overwrite Algorithm::read(const
+    FileNode& fn) and also have static create() method without parameters
+    (or with all the optional parameters)
+    */
+    template<typename _Tp> static Ptr<_Tp> read(const FileNode& fn)
+    {
+        Ptr<_Tp> obj = _Tp::create();
+        obj->read(fn);
+        return !obj->empty() ? obj : Ptr<_Tp>();
+    }
+
+    /** @brief Loads algorithm from the file
+
+    @param filename Name of the file to read.
+    @param objname The optional name of the node to read (if empty, the first top-level node will be used)
+
+    This is static template method of Algorithm. It's usage is following (in the case of SVM):
+    @code
+    Ptr<SVM> svm = Algorithm::load<SVM>("my_svm_model.xml");
+    @endcode
+    In order to make this method work, the derived class must overwrite Algorithm::read(const
+    FileNode& fn).
+    */
+    template<typename _Tp> static Ptr<_Tp> load(const String& filename, const String& objname=String())
+    {
+        FileStorage fs(filename, FileStorage::READ);
+        CV_Assert(fs.isOpened());
+        FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname];
+        if (fn.empty()) return Ptr<_Tp>();
+        Ptr<_Tp> obj = _Tp::create();
+        obj->read(fn);
+        return !obj->empty() ? obj : Ptr<_Tp>();
+    }
+
+    /** @brief Loads algorithm from a String
+
+    @param strModel The string variable containing the model you want to load.
+    @param objname The optional name of the node to read (if empty, the first top-level node will be used)
+
+    This is static template method of Algorithm. It's usage is following (in the case of SVM):
+    @code
+    Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);
+    @endcode
+    */
+    template<typename _Tp> static Ptr<_Tp> loadFromString(const String& strModel, const String& objname=String())
+    {
+        FileStorage fs(strModel, FileStorage::READ + FileStorage::MEMORY);
+        FileNode fn = objname.empty() ? fs.getFirstTopLevelNode() : fs[objname];
+        Ptr<_Tp> obj = _Tp::create();
+        obj->read(fn);
+        return !obj->empty() ? obj : Ptr<_Tp>();
+    }
+
+    /** Saves the algorithm to a file.
+    In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs). */
+    CV_WRAP virtual void save(const String& filename) const;
+
+    /** Returns the algorithm string identifier.
+    This string is used as top level xml/yml node tag when the object is saved to a file or string. */
+    CV_WRAP virtual String getDefaultName() const;
+
+protected:
+    void writeFormat(FileStorage& fs) const;
+};
+
+enum struct Param {
+    INT=0, BOOLEAN=1, REAL=2, STRING=3, MAT=4, MAT_VECTOR=5, ALGORITHM=6, FLOAT=7,
+    UNSIGNED_INT=8, UINT64=9, UCHAR=11, SCALAR=12
+};
+
+
+
+template<> struct ParamType<bool>
+{
+    typedef bool const_param_type;
+    typedef bool member_type;
+
+    static const Param type = Param::BOOLEAN;
+};
+
+template<> struct ParamType<int>
+{
+    typedef int const_param_type;
+    typedef int member_type;
+
+    static const Param type = Param::INT;
+};
+
+template<> struct ParamType<double>
+{
+    typedef double const_param_type;
+    typedef double member_type;
+
+    static const Param type = Param::REAL;
+};
+
+template<> struct ParamType<String>
+{
+    typedef const String& const_param_type;
+    typedef String member_type;
+
+    static const Param type = Param::STRING;
+};
+
+template<> struct ParamType<Mat>
+{
+    typedef const Mat& const_param_type;
+    typedef Mat member_type;
+
+    static const Param type = Param::MAT;
+};
+
+template<> struct ParamType<std::vector<Mat> >
+{
+    typedef const std::vector<Mat>& const_param_type;
+    typedef std::vector<Mat> member_type;
+
+    static const Param type = Param::MAT_VECTOR;
+};
+
+template<> struct ParamType<Algorithm>
+{
+    typedef const Ptr<Algorithm>& const_param_type;
+    typedef Ptr<Algorithm> member_type;
+
+    static const Param type = Param::ALGORITHM;
+};
+
+template<> struct ParamType<float>
+{
+    typedef float const_param_type;
+    typedef float member_type;
+
+    static const Param type = Param::FLOAT;
+};
+
+template<> struct ParamType<unsigned>
+{
+    typedef unsigned const_param_type;
+    typedef unsigned member_type;
+
+    static const Param type = Param::UNSIGNED_INT;
+};
+
+template<> struct ParamType<uint64>
+{
+    typedef uint64 const_param_type;
+    typedef uint64 member_type;
+
+    static const Param type = Param::UINT64;
+};
+
+template<> struct ParamType<uchar>
+{
+    typedef uchar const_param_type;
+    typedef uchar member_type;
+
+    static const Param type = Param::UCHAR;
+};
+
+template<> struct ParamType<Scalar>
+{
+    typedef const Scalar& const_param_type;
+    typedef Scalar member_type;
+
+    static const Param type = Param::SCALAR;
+};
+
+template<typename _Tp>
+struct ParamType<_Tp, typename std::enable_if< std::is_enum<_Tp>::value >::type>
+{
+    typedef typename std::underlying_type<_Tp>::type const_param_type;
+    typedef typename std::underlying_type<_Tp>::type member_type;
+
+    static const Param type = Param::INT;
+};
+
+//! @} core_basic
+
+} //namespace cv
+
+#include "opencv2/core/operations.hpp"
+#include "opencv2/core/cvstd.inl.hpp"
+#include "opencv2/core/utility.hpp"
+#include "opencv2/core/optim.hpp"
+#include "opencv2/core/ovx.hpp"
+
+#endif /*OPENCV_CORE_HPP*/

GameAssist/GameAssist/include/cv2/opencv2/core/affine.hpp

@@ -0,0 +1,678 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_AFFINE3_HPP
+#define OPENCV_CORE_AFFINE3_HPP
+
+#ifdef __cplusplus
+
+#include <opencv2/core.hpp>
+
+namespace cv
+{
+
+//! @addtogroup core_eigen
+//! @{
+
+    /** @brief Affine transform
+     *
+     * It represents a 4x4 homogeneous transformation matrix \f$T\f$
+     *
+     *  \f[T =
+     *  \begin{bmatrix}
+     *  R & t\\
+     *  0 & 1\\
+     *  \end{bmatrix}
+     *  \f]
+     *
+     *  where \f$R\f$ is a 3x3 rotation matrix and \f$t\f$ is a 3x1 translation vector.
+     *
+     *  You can specify \f$R\f$ either by a 3x3 rotation matrix or by a 3x1 rotation vector,
+     *  which is converted to a 3x3 rotation matrix by the Rodrigues formula.
+     *
+     *  To construct a matrix \f$T\f$ representing first rotation around the axis \f$r\f$ with rotation
+     *  angle \f$|r|\f$ in radian (right hand rule) and then translation by the vector \f$t\f$, you can use
+     *
+     *  @code
+     *  cv::Vec3f r, t;
+     *  cv::Affine3f T(r, t);
+     *  @endcode
+     *
+     *  If you already have the rotation matrix \f$R\f$, then you can use
+     *
+     *  @code
+     *  cv::Matx33f R;
+     *  cv::Affine3f T(R, t);
+     *  @endcode
+     *
+     *  To extract the rotation matrix \f$R\f$ from \f$T\f$, use
+     *
+     *  @code
+     *  cv::Matx33f R = T.rotation();
+     *  @endcode
+     *
+     *  To extract the translation vector \f$t\f$ from \f$T\f$, use
+     *
+     *  @code
+     *  cv::Vec3f t = T.translation();
+     *  @endcode
+     *
+     *  To extract the rotation vector \f$r\f$ from \f$T\f$, use
+     *
+     *  @code
+     *  cv::Vec3f r = T.rvec();
+     *  @endcode
+     *
+     *  Note that since the mapping from rotation vectors to rotation matrices
+     *  is many to one. The returned rotation vector is not necessarily the one
+     *  you used before to set the matrix.
+     *
+     *  If you have two transformations \f$T = T_1 * T_2\f$, use
+     *
+     *  @code
+     *  cv::Affine3f T, T1, T2;
+     *  T = T2.concatenate(T1);
+     *  @endcode
+     *
+     *  To get the inverse transform of \f$T\f$, use
+     *
+     *  @code
+     *  cv::Affine3f T, T_inv;
+     *  T_inv = T.inv();
+     *  @endcode
+     *
+     */
+    template<typename T>
+    class Affine3
+    {
+    public:
+        typedef T float_type;
+        typedef Matx<float_type, 3, 3> Mat3;
+        typedef Matx<float_type, 4, 4> Mat4;
+        typedef Vec<float_type, 3> Vec3;
+
+       //! Default constructor. It represents a 4x4 identity matrix.
+        Affine3();
+
+        //! Augmented affine matrix
+        Affine3(const Mat4& affine);
+
+        /**
+         *  The resulting 4x4 matrix is
+         *
+         *  \f[
+         *  \begin{bmatrix}
+         *  R & t\\
+         *  0 & 1\\
+         *  \end{bmatrix}
+         *  \f]
+         *
+         * @param R 3x3 rotation matrix.
+         * @param t 3x1 translation vector.
+         */
+        Affine3(const Mat3& R, const Vec3& t = Vec3::all(0));
+
+        /**
+         * Rodrigues vector.
+         *
+         * The last row of the current matrix is set to [0,0,0,1].
+         *
+         * @param rvec 3x1 rotation vector. Its direction indicates the rotation axis and its length
+         *             indicates the rotation angle in radian (using right hand rule).
+         * @param t 3x1 translation vector.
+         */
+        Affine3(const Vec3& rvec, const Vec3& t = Vec3::all(0));
+
+        /**
+         * Combines all constructors above. Supports 4x4, 3x4, 3x3, 1x3, 3x1 sizes of data matrix.
+         *
+         * The last row of the current matrix is set to [0,0,0,1] when data is not 4x4.
+         *
+         * @param data 1-channel matrix.
+         *             when it is 4x4, it is copied to the current matrix and t is not used.
+         *             When it is 3x4, it is copied to the upper part 3x4 of the current matrix and t is not used.
+         *             When it is 3x3, it is copied to the upper left 3x3 part of the current matrix.
+         *             When it is 3x1 or 1x3, it is treated as a rotation vector and the Rodrigues formula is used
+         *                             to compute a 3x3 rotation matrix.
+         * @param t 3x1 translation vector. It is used only when data is neither 4x4 nor 3x4.
+         */
+        explicit Affine3(const Mat& data, const Vec3& t = Vec3::all(0));
+
+        //! From 16-element array
+        explicit Affine3(const float_type* vals);
+
+        //! Create an 4x4 identity transform
+        static Affine3 Identity();
+
+        /**
+         * Rotation matrix.
+         *
+         * Copy the rotation matrix to the upper left 3x3 part of the current matrix.
+         * The remaining elements of the current matrix are not changed.
+         *
+         * @param R 3x3 rotation matrix.
+         *
+         */
+        void rotation(const Mat3& R);
+
+        /**
+         * Rodrigues vector.
+         *
+         * It sets the upper left 3x3 part of the matrix. The remaining part is unaffected.
+         *
+         * @param rvec 3x1 rotation vector. The direction indicates the rotation axis and
+         *             its length indicates the rotation angle in radian (using the right thumb convention).
+         */
+        void rotation(const Vec3& rvec);
+
+        /**
+         * Combines rotation methods above. Supports 3x3, 1x3, 3x1 sizes of data matrix.
+         *
+         * It sets the upper left 3x3 part of the matrix. The remaining part is unaffected.
+         *
+         * @param data 1-channel matrix.
+         *             When it is a 3x3 matrix, it sets the upper left 3x3 part of the current matrix.
+         *             When it is a 1x3 or 3x1 matrix, it is used as a rotation vector. The Rodrigues formula
+         *             is used to compute the rotation matrix and sets the upper left 3x3 part of the current matrix.
+         */
+        void rotation(const Mat& data);
+
+        /**
+         * Copy the 3x3 matrix L to the upper left part of the current matrix
+         *
+         * It sets the upper left 3x3 part of the matrix. The remaining part is unaffected.
+         *
+         * @param L 3x3 matrix.
+         */
+        void linear(const Mat3& L);
+
+        /**
+         * Copy t to the first three elements of the last column of the current matrix
+         *
+         * It sets the upper right 3x1 part of the matrix. The remaining part is unaffected.
+         *
+         * @param t 3x1 translation vector.
+         */
+        void translation(const Vec3& t);
+
+        //! @return the upper left 3x3 part
+        Mat3 rotation() const;
+
+        //! @return the upper left 3x3 part
+        Mat3 linear() const;
+
+        //! @return the upper right 3x1 part
+        Vec3 translation() const;
+
+        //! Rodrigues vector.
+        //! @return a vector representing the upper left 3x3 rotation matrix of the current matrix.
+        //! @warning  Since the mapping between rotation vectors and rotation matrices is many to one,
+        //!           this function returns only one rotation vector that represents the current rotation matrix,
+        //!           which is not necessarily the same one set by `rotation(const Vec3& rvec)`.
+        Vec3 rvec() const;
+
+        //! @return the inverse of the current matrix.
+        Affine3 inv(int method = cv::DECOMP_SVD) const;
+
+        //! a.rotate(R) is equivalent to Affine(R, 0) * a;
+        Affine3 rotate(const Mat3& R) const;
+
+        //! a.rotate(rvec) is equivalent to Affine(rvec, 0) * a;
+        Affine3 rotate(const Vec3& rvec) const;
+
+        //! a.translate(t) is equivalent to Affine(E, t) * a, where E is an identity matrix
+        Affine3 translate(const Vec3& t) const;
+
+        //! a.concatenate(affine) is equivalent to affine * a;
+        Affine3 concatenate(const Affine3& affine) const;
+
+        template <typename Y> operator Affine3<Y>() const;
+
+        template <typename Y> Affine3<Y> cast() const;
+
+        Mat4 matrix;
+
+#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H
+        Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine);
+        Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine);
+        operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const;
+        operator Eigen::Transform<T, 3, Eigen::Affine>() const;
+#endif
+    };
+
+    template<typename T> static
+    Affine3<T> operator*(const Affine3<T>& affine1, const Affine3<T>& affine2);
+
+    //! V is a 3-element vector with member fields x, y and z
+    template<typename T, typename V> static
+    V operator*(const Affine3<T>& affine, const V& vector);
+
+    typedef Affine3<float> Affine3f;
+    typedef Affine3<double> Affine3d;
+
+    static Vec3f operator*(const Affine3f& affine, const Vec3f& vector);
+    static Vec3d operator*(const Affine3d& affine, const Vec3d& vector);
+
+    template<typename _Tp> class DataType< Affine3<_Tp> >
+    {
+    public:
+        typedef Affine3<_Tp>                               value_type;
+        typedef Affine3<typename DataType<_Tp>::work_type> work_type;
+        typedef _Tp                                        channel_type;
+
+        enum { generic_type = 0,
+               channels     = 16,
+               fmt          = traits::SafeFmt<channel_type>::fmt + ((channels - 1) << 8)
+#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED
+               ,depth        = DataType<channel_type>::depth
+               ,type         = CV_MAKETYPE(depth, channels)
+#endif
+             };
+
+        typedef Vec<channel_type, channels> vec_type;
+    };
+
+    namespace traits {
+    template<typename _Tp>
+    struct Depth< Affine3<_Tp> > { enum { value = Depth<_Tp>::value }; };
+    template<typename _Tp>
+    struct Type< Affine3<_Tp> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, 16) }; };
+    } // namespace
+
+//! @} core
+
+}
+
+//! @cond IGNORED
+
+///////////////////////////////////////////////////////////////////////////////////
+// Implementation
+
+template<typename T> inline
+cv::Affine3<T>::Affine3()
+    : matrix(Mat4::eye())
+{}
+
+template<typename T> inline
+cv::Affine3<T>::Affine3(const Mat4& affine)
+    : matrix(affine)
+{}
+
+template<typename T> inline
+cv::Affine3<T>::Affine3(const Mat3& R, const Vec3& t)
+{
+    rotation(R);
+    translation(t);
+    matrix.val[12] = matrix.val[13] = matrix.val[14] = 0;
+    matrix.val[15] = 1;
+}
+
+template<typename T> inline
+cv::Affine3<T>::Affine3(const Vec3& _rvec, const Vec3& t)
+{
+    rotation(_rvec);
+    translation(t);
+    matrix.val[12] = matrix.val[13] = matrix.val[14] = 0;
+    matrix.val[15] = 1;
+}
+
+template<typename T> inline
+cv::Affine3<T>::Affine3(const cv::Mat& data, const Vec3& t)
+{
+    CV_Assert(data.type() == cv::traits::Type<T>::value);
+    CV_Assert(data.channels() == 1);
+
+    if (data.cols == 4 && data.rows == 4)
+    {
+        data.copyTo(matrix);
+        return;
+    }
+    else if (data.cols == 4 && data.rows == 3)
+    {
+        rotation(data(Rect(0, 0, 3, 3)));
+        translation(data(Rect(3, 0, 1, 3)));
+    }
+    else
+    {
+        rotation(data);
+        translation(t);
+    }
+
+    matrix.val[12] = matrix.val[13] = matrix.val[14] = 0;
+    matrix.val[15] = 1;
+}
+
+template<typename T> inline
+cv::Affine3<T>::Affine3(const float_type* vals) : matrix(vals)
+{}
+
+template<typename T> inline
+cv::Affine3<T> cv::Affine3<T>::Identity()
+{
+    return Affine3<T>(cv::Affine3<T>::Mat4::eye());
+}
+
+template<typename T> inline
+void cv::Affine3<T>::rotation(const Mat3& R)
+{
+    linear(R);
+}
+
+template<typename T> inline
+void cv::Affine3<T>::rotation(const Vec3& _rvec)
+{
+    double theta = norm(_rvec);
+
+    if (theta < DBL_EPSILON)
+        rotation(Mat3::eye());
+    else
+    {
+        double c = std::cos(theta);
+        double s = std::sin(theta);
+        double c1 = 1. - c;
+        double itheta = (theta != 0) ? 1./theta : 0.;
+
+        Point3_<T> r = _rvec*itheta;
+
+        Mat3 rrt( r.x*r.x, r.x*r.y, r.x*r.z, r.x*r.y, r.y*r.y, r.y*r.z, r.x*r.z, r.y*r.z, r.z*r.z );
+        Mat3 r_x( 0, -r.z, r.y, r.z, 0, -r.x, -r.y, r.x, 0 );
+
+        // R = cos(theta)*I + (1 - cos(theta))*r*rT + sin(theta)*[r_x]
+        // where [r_x] is [0 -rz ry; rz 0 -rx; -ry rx 0]
+        Mat3 R = c*Mat3::eye() + c1*rrt + s*r_x;
+
+        rotation(R);
+    }
+}
+
+//Combines rotation methods above. Supports 3x3, 1x3, 3x1 sizes of data matrix;
+template<typename T> inline
+void cv::Affine3<T>::rotation(const cv::Mat& data)
+{
+    CV_Assert(data.type() == cv::traits::Type<T>::value);
+    CV_Assert(data.channels() == 1);
+
+    if (data.cols == 3 && data.rows == 3)
+    {
+        Mat3 R;
+        data.copyTo(R);
+        rotation(R);
+    }
+    else if ((data.cols == 3 && data.rows == 1) || (data.cols == 1 && data.rows == 3))
+    {
+        Vec3 _rvec;
+        data.reshape(1, 3).copyTo(_rvec);
+        rotation(_rvec);
+    }
+    else
+        CV_Error(Error::StsError, "Input matrix can only be 3x3, 1x3 or 3x1");
+}
+
+template<typename T> inline
+void cv::Affine3<T>::linear(const Mat3& L)
+{
+    matrix.val[0] = L.val[0]; matrix.val[1] = L.val[1];  matrix.val[ 2] = L.val[2];
+    matrix.val[4] = L.val[3]; matrix.val[5] = L.val[4];  matrix.val[ 6] = L.val[5];
+    matrix.val[8] = L.val[6]; matrix.val[9] = L.val[7];  matrix.val[10] = L.val[8];
+}
+
+template<typename T> inline
+void cv::Affine3<T>::translation(const Vec3& t)
+{
+    matrix.val[3] = t[0]; matrix.val[7] = t[1]; matrix.val[11] = t[2];
+}
+
+template<typename T> inline
+typename cv::Affine3<T>::Mat3 cv::Affine3<T>::rotation() const
+{
+    return linear();
+}
+
+template<typename T> inline
+typename cv::Affine3<T>::Mat3 cv::Affine3<T>::linear() const
+{
+    typename cv::Affine3<T>::Mat3 R;
+    R.val[0] = matrix.val[0];  R.val[1] = matrix.val[1];  R.val[2] = matrix.val[ 2];
+    R.val[3] = matrix.val[4];  R.val[4] = matrix.val[5];  R.val[5] = matrix.val[ 6];
+    R.val[6] = matrix.val[8];  R.val[7] = matrix.val[9];  R.val[8] = matrix.val[10];
+    return R;
+}
+
+template<typename T> inline
+typename cv::Affine3<T>::Vec3 cv::Affine3<T>::translation() const
+{
+    return Vec3(matrix.val[3], matrix.val[7], matrix.val[11]);
+}
+
+template<typename T> inline
+typename cv::Affine3<T>::Vec3 cv::Affine3<T>::rvec() const
+{
+    cv::Vec3d w;
+    cv::Matx33d u, vt, R = rotation();
+    cv::SVD::compute(R, w, u, vt, cv::SVD::FULL_UV + cv::SVD::MODIFY_A);
+    R = u * vt;
+
+    double rx = R.val[7] - R.val[5];
+    double ry = R.val[2] - R.val[6];
+    double rz = R.val[3] - R.val[1];
+
+    double s = std::sqrt((rx*rx + ry*ry + rz*rz)*0.25);
+    double c = (R.val[0] + R.val[4] + R.val[8] - 1) * 0.5;
+    c = c > 1.0 ? 1.0 : c < -1.0 ? -1.0 : c;
+    double theta = std::acos(c);
+
+    if( s < 1e-5 )
+    {
+        if( c > 0 )
+            rx = ry = rz = 0;
+        else
+        {
+            double t;
+            t = (R.val[0] + 1) * 0.5;
+            rx = std::sqrt(std::max(t, 0.0));
+            t = (R.val[4] + 1) * 0.5;
+            ry = std::sqrt(std::max(t, 0.0)) * (R.val[1] < 0 ? -1.0 : 1.0);
+            t = (R.val[8] + 1) * 0.5;
+            rz = std::sqrt(std::max(t, 0.0)) * (R.val[2] < 0 ? -1.0 : 1.0);
+
+            if( fabs(rx) < fabs(ry) && fabs(rx) < fabs(rz) && (R.val[5] > 0) != (ry*rz > 0) )
+                rz = -rz;
+            theta /= std::sqrt(rx*rx + ry*ry + rz*rz);
+            rx *= theta;
+            ry *= theta;
+            rz *= theta;
+        }
+    }
+    else
+    {
+        double vth = 1/(2*s);
+        vth *= theta;
+        rx *= vth; ry *= vth; rz *= vth;
+    }
+
+    return cv::Vec3d(rx, ry, rz);
+}
+
+template<typename T> inline
+cv::Affine3<T> cv::Affine3<T>::inv(int method) const
+{
+    return matrix.inv(method);
+}
+
+template<typename T> inline
+cv::Affine3<T> cv::Affine3<T>::rotate(const Mat3& R) const
+{
+    Mat3 Lc = linear();
+    Vec3 tc = translation();
+    Mat4 result;
+    result.val[12] = result.val[13] = result.val[14] = 0;
+    result.val[15] = 1;
+
+    for(int j = 0; j < 3; ++j)
+    {
+        for(int i = 0; i < 3; ++i)
+        {
+            float_type value = 0;
+            for(int k = 0; k < 3; ++k)
+                value += R(j, k) * Lc(k, i);
+            result(j, i) = value;
+        }
+
+        result(j, 3) = R.row(j).dot(tc.t());
+    }
+    return result;
+}
+
+template<typename T> inline
+cv::Affine3<T> cv::Affine3<T>::rotate(const Vec3& _rvec) const
+{
+    return rotate(Affine3f(_rvec).rotation());
+}
+
+template<typename T> inline
+cv::Affine3<T> cv::Affine3<T>::translate(const Vec3& t) const
+{
+    Mat4 m = matrix;
+    m.val[ 3] += t[0];
+    m.val[ 7] += t[1];
+    m.val[11] += t[2];
+    return m;
+}
+
+template<typename T> inline
+cv::Affine3<T> cv::Affine3<T>::concatenate(const Affine3<T>& affine) const
+{
+    return (*this).rotate(affine.rotation()).translate(affine.translation());
+}
+
+template<typename T> template <typename Y> inline
+cv::Affine3<T>::operator Affine3<Y>() const
+{
+    return Affine3<Y>(matrix);
+}
+
+template<typename T> template <typename Y> inline
+cv::Affine3<Y> cv::Affine3<T>::cast() const
+{
+    return Affine3<Y>(matrix);
+}
+
+template<typename T> inline
+cv::Affine3<T> cv::operator*(const cv::Affine3<T>& affine1, const cv::Affine3<T>& affine2)
+{
+    return affine2.concatenate(affine1);
+}
+
+template<typename T, typename V> inline
+V cv::operator*(const cv::Affine3<T>& affine, const V& v)
+{
+    const typename Affine3<T>::Mat4& m = affine.matrix;
+
+    V r;
+    r.x = m.val[0] * v.x + m.val[1] * v.y + m.val[ 2] * v.z + m.val[ 3];
+    r.y = m.val[4] * v.x + m.val[5] * v.y + m.val[ 6] * v.z + m.val[ 7];
+    r.z = m.val[8] * v.x + m.val[9] * v.y + m.val[10] * v.z + m.val[11];
+    return r;
+}
+
+static inline
+cv::Vec3f cv::operator*(const cv::Affine3f& affine, const cv::Vec3f& v)
+{
+    const cv::Matx44f& m = affine.matrix;
+    cv::Vec3f r;
+    r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3];
+    r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7];
+    r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11];
+    return r;
+}
+
+static inline
+cv::Vec3d cv::operator*(const cv::Affine3d& affine, const cv::Vec3d& v)
+{
+    const cv::Matx44d& m = affine.matrix;
+    cv::Vec3d r;
+    r.val[0] = m.val[0] * v[0] + m.val[1] * v[1] + m.val[ 2] * v[2] + m.val[ 3];
+    r.val[1] = m.val[4] * v[0] + m.val[5] * v[1] + m.val[ 6] * v[2] + m.val[ 7];
+    r.val[2] = m.val[8] * v[0] + m.val[9] * v[1] + m.val[10] * v[2] + m.val[11];
+    return r;
+}
+
+
+
+#if defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H
+
+template<typename T> inline
+cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>& affine)
+{
+    cv::Mat(4, 4, cv::traits::Type<T>::value, affine.matrix().data()).copyTo(matrix);
+}
+
+template<typename T> inline
+cv::Affine3<T>::Affine3(const Eigen::Transform<T, 3, Eigen::Affine>& affine)
+{
+    Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> a = affine;
+    cv::Mat(4, 4, cv::traits::Type<T>::value, a.matrix().data()).copyTo(matrix);
+}
+
+template<typename T> inline
+cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>() const
+{
+    Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)> r;
+    cv::Mat hdr(4, 4, cv::traits::Type<T>::value, r.matrix().data());
+    cv::Mat(matrix, false).copyTo(hdr);
+    return r;
+}
+
+template<typename T> inline
+cv::Affine3<T>::operator Eigen::Transform<T, 3, Eigen::Affine>() const
+{
+    return this->operator Eigen::Transform<T, 3, Eigen::Affine, (Eigen::RowMajor)>();
+}
+
+#endif /* defined EIGEN_WORLD_VERSION && defined EIGEN_GEOMETRY_MODULE_H */
+
+//! @endcond
+
+#endif /* __cplusplus */
+
+#endif /* OPENCV_CORE_AFFINE3_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/async.hpp

@@ -0,0 +1,101 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_ASYNC_HPP
+#define OPENCV_CORE_ASYNC_HPP
+
+#include <opencv2/core/mat.hpp>
+
+//#include <future>
+#include <chrono>
+
+namespace cv {
+
+/** @addtogroup core_async
+
+@{
+*/
+
+
+/** @brief Returns result of asynchronous operations
+
+Object has attached asynchronous state.
+Assignment operator doesn't clone asynchronous state (it is shared between all instances).
+
+Result can be fetched via get() method only once.
+
+*/
+class CV_EXPORTS_W AsyncArray
+{
+public:
+    ~AsyncArray() CV_NOEXCEPT;
+    CV_WRAP AsyncArray() CV_NOEXCEPT;
+    AsyncArray(const AsyncArray& o) CV_NOEXCEPT;
+    AsyncArray& operator=(const AsyncArray& o) CV_NOEXCEPT;
+    CV_WRAP void release() CV_NOEXCEPT;
+
+    /** Fetch the result.
+    @param[out] dst destination array
+
+    Waits for result until container has valid result.
+    Throws exception if exception was stored as a result.
+
+    Throws exception on invalid container state.
+
+    @note Result or stored exception can be fetched only once.
+    */
+    CV_WRAP void get(OutputArray dst) const;
+
+    /** Retrieving the result with timeout
+    @param[out] dst destination array
+    @param[in] timeoutNs timeout in nanoseconds, -1 for infinite wait
+
+    @returns true if result is ready, false if the timeout has expired
+
+    @note Result or stored exception can be fetched only once.
+    */
+    bool get(OutputArray dst, int64 timeoutNs) const;
+
+    CV_WRAP inline
+    bool get(OutputArray dst, double timeoutNs) const { return get(dst, (int64)timeoutNs); }
+
+    bool wait_for(int64 timeoutNs) const;
+
+    CV_WRAP inline
+    bool wait_for(double timeoutNs) const { return wait_for((int64)timeoutNs); }
+
+    CV_WRAP bool valid() const CV_NOEXCEPT;
+
+    inline AsyncArray(AsyncArray&& o) { p = o.p; o.p = NULL; }
+    inline AsyncArray& operator=(AsyncArray&& o) CV_NOEXCEPT { std::swap(p, o.p); return *this; }
+
+    template<typename _Rep, typename _Period>
+    inline bool get(OutputArray dst, const std::chrono::duration<_Rep, _Period>& timeout)
+    {
+        return get(dst, (int64)(std::chrono::nanoseconds(timeout).count()));
+    }
+
+    template<typename _Rep, typename _Period>
+    inline bool wait_for(const std::chrono::duration<_Rep, _Period>& timeout)
+    {
+        return wait_for((int64)(std::chrono::nanoseconds(timeout).count()));
+    }
+
+#if 0
+    std::future<Mat> getFutureMat() const;
+    std::future<UMat> getFutureUMat() const;
+#endif
+
+
+    // PImpl
+    struct Impl; friend struct Impl;
+    inline void* _getImpl() const CV_NOEXCEPT { return p; }
+protected:
+    Impl* p;
+};
+
+
+//! @}
+} // namespace
+#endif // OPENCV_CORE_ASYNC_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/base.hpp

@@ -0,0 +1,682 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2014, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_BASE_HPP
+#define OPENCV_CORE_BASE_HPP
+
+#ifndef __cplusplus
+#  error base.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/opencv_modules.hpp"
+
+#include <climits>
+#include <algorithm>
+
+#include "opencv2/core/cvdef.h"
+#include "opencv2/core/cvstd.hpp"
+
+namespace cv
+{
+
+//! @addtogroup core_utils
+//! @{
+
+namespace Error {
+//! error codes
+enum Code {
+    StsOk=                       0,  //!< everything is ok
+    StsBackTrace=               -1,  //!< pseudo error for back trace
+    StsError=                   -2,  //!< unknown /unspecified error
+    StsInternal=                -3,  //!< internal error (bad state)
+    StsNoMem=                   -4,  //!< insufficient memory
+    StsBadArg=                  -5,  //!< function arg/param is bad
+    StsBadFunc=                 -6,  //!< unsupported function
+    StsNoConv=                  -7,  //!< iteration didn't converge
+    StsAutoTrace=               -8,  //!< tracing
+    HeaderIsNull=               -9,  //!< image header is NULL
+    BadImageSize=              -10,  //!< image size is invalid
+    BadOffset=                 -11,  //!< offset is invalid
+    BadDataPtr=                -12,  //!<
+    BadStep=                   -13,  //!< image step is wrong, this may happen for a non-continuous matrix.
+    BadModelOrChSeq=           -14,  //!<
+    BadNumChannels=            -15,  //!< bad number of channels, for example, some functions accept only single channel matrices.
+    BadNumChannel1U=           -16,  //!<
+    BadDepth=                  -17,  //!< input image depth is not supported by the function
+    BadAlphaChannel=           -18,  //!<
+    BadOrder=                  -19,  //!< number of dimensions is out of range
+    BadOrigin=                 -20,  //!< incorrect input origin
+    BadAlign=                  -21,  //!< incorrect input align
+    BadCallBack=               -22,  //!<
+    BadTileSize=               -23,  //!<
+    BadCOI=                    -24,  //!< input COI is not supported
+    BadROISize=                -25,  //!< incorrect input roi
+    MaskIsTiled=               -26,  //!<
+    StsNullPtr=                -27,  //!< null pointer
+    StsVecLengthErr=           -28,  //!< incorrect vector length
+    StsFilterStructContentErr= -29,  //!< incorrect filter structure content
+    StsKernelStructContentErr= -30,  //!< incorrect transform kernel content
+    StsFilterOffsetErr=        -31,  //!< incorrect filter offset value
+    StsBadSize=                -201, //!< the input/output structure size is incorrect
+    StsDivByZero=              -202, //!< division by zero
+    StsInplaceNotSupported=    -203, //!< in-place operation is not supported
+    StsObjectNotFound=         -204, //!< request can't be completed
+    StsUnmatchedFormats=       -205, //!< formats of input/output arrays differ
+    StsBadFlag=                -206, //!< flag is wrong or not supported
+    StsBadPoint=               -207, //!< bad CvPoint
+    StsBadMask=                -208, //!< bad format of mask (neither 8uC1 nor 8sC1)
+    StsUnmatchedSizes=         -209, //!< sizes of input/output structures do not match
+    StsUnsupportedFormat=      -210, //!< the data format/type is not supported by the function
+    StsOutOfRange=             -211, //!< some of parameters are out of range
+    StsParseError=             -212, //!< invalid syntax/structure of the parsed file
+    StsNotImplemented=         -213, //!< the requested function/feature is not implemented
+    StsBadMemBlock=            -214, //!< an allocated block has been corrupted
+    StsAssert=                 -215, //!< assertion failed
+    GpuNotSupported=           -216, //!< no CUDA support
+    GpuApiCallError=           -217, //!< GPU API call error
+    OpenGlNotSupported=        -218, //!< no OpenGL support
+    OpenGlApiCallError=        -219, //!< OpenGL API call error
+    OpenCLApiCallError=        -220, //!< OpenCL API call error
+    OpenCLDoubleNotSupported=  -221,
+    OpenCLInitError=           -222, //!< OpenCL initialization error
+    OpenCLNoAMDBlasFft=        -223
+};
+} //Error
+
+//! @} core_utils
+
+//! @addtogroup core_array
+//! @{
+
+//! matrix decomposition types
+enum DecompTypes {
+    /** Gaussian elimination with the optimal pivot element chosen. */
+    DECOMP_LU       = 0,
+    /** singular value decomposition (SVD) method; the system can be over-defined and/or the matrix
+    src1 can be singular */
+    DECOMP_SVD      = 1,
+    /** eigenvalue decomposition; the matrix src1 must be symmetrical */
+    DECOMP_EIG      = 2,
+    /** Cholesky \f$LL^T\f$ factorization; the matrix src1 must be symmetrical and positively
+    defined */
+    DECOMP_CHOLESKY = 3,
+    /** QR factorization; the system can be over-defined and/or the matrix src1 can be singular */
+    DECOMP_QR       = 4,
+    /** while all the previous flags are mutually exclusive, this flag can be used together with
+    any of the previous; it means that the normal equations
+    \f$\texttt{src1}^T\cdot\texttt{src1}\cdot\texttt{dst}=\texttt{src1}^T\texttt{src2}\f$ are
+    solved instead of the original system
+    \f$\texttt{src1}\cdot\texttt{dst}=\texttt{src2}\f$ */
+    DECOMP_NORMAL   = 16
+};
+
+/** norm types
+
+src1 and src2 denote input arrays.
+*/
+
+enum NormTypes {
+                /**
+                \f[
+                norm =  \forkthree
+                {\|\texttt{src1}\|_{L_{\infty}} =  \max _I | \texttt{src1} (I)|}{if  \(\texttt{normType} = \texttt{NORM_INF}\) }
+                {\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} =  \max _I | \texttt{src1} (I) -  \texttt{src2} (I)|}{if  \(\texttt{normType} = \texttt{NORM_INF}\) }
+                {\frac{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}}    }{\|\texttt{src2}\|_{L_{\infty}} }}{if  \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_INF}\) }
+                \f]
+                */
+                NORM_INF       = 1,
+                /**
+                \f[
+                norm =  \forkthree
+                {\| \texttt{src1} \| _{L_1} =  \sum _I | \texttt{src1} (I)|}{if  \(\texttt{normType} = \texttt{NORM_L1}\)}
+                { \| \texttt{src1} - \texttt{src2} \| _{L_1} =  \sum _I | \texttt{src1} (I) -  \texttt{src2} (I)|}{if  \(\texttt{normType} = \texttt{NORM_L1}\) }
+                { \frac{\|\texttt{src1}-\texttt{src2}\|_{L_1} }{\|\texttt{src2}\|_{L_1}} }{if  \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L1}\) }
+                \f]*/
+                 NORM_L1        = 2,
+                 /**
+                 \f[
+                 norm =  \forkthree
+                 { \| \texttt{src1} \| _{L_2} =  \sqrt{\sum_I \texttt{src1}(I)^2} }{if  \(\texttt{normType} = \texttt{NORM_L2}\) }
+                 { \| \texttt{src1} - \texttt{src2} \| _{L_2} =  \sqrt{\sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2} }{if  \(\texttt{normType} = \texttt{NORM_L2}\) }
+                 { \frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}} }{if  \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L2}\) }
+                 \f]
+                 */
+                 NORM_L2        = 4,
+                 /**
+                 \f[
+                 norm =  \forkthree
+                 { \| \texttt{src1} \| _{L_2} ^{2} = \sum_I \texttt{src1}(I)^2} {if  \(\texttt{normType} = \texttt{NORM_L2SQR}\)}
+                 { \| \texttt{src1} - \texttt{src2} \| _{L_2} ^{2} =  \sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2 }{if  \(\texttt{normType} = \texttt{NORM_L2SQR}\) }
+                 { \left(\frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}}\right)^2 }{if  \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L2SQR}\) }
+                 \f]
+                 */
+                 NORM_L2SQR     = 5,
+                 /**
+                 In the case of one input array, calculates the Hamming distance of the array from zero,
+                 In the case of two input arrays, calculates the Hamming distance between the arrays.
+                 */
+                 NORM_HAMMING   = 6,
+                 /**
+                 Similar to NORM_HAMMING, but in the calculation, each two bits of the input sequence will
+                 be added and treated as a single bit to be used in the same calculation as NORM_HAMMING.
+                 */
+                 NORM_HAMMING2  = 7,
+                 NORM_TYPE_MASK = 7, //!< bit-mask which can be used to separate norm type from norm flags
+                 NORM_RELATIVE  = 8, //!< flag
+                 NORM_MINMAX    = 32 //!< flag
+               };
+
+//! comparison types
+enum CmpTypes { CMP_EQ = 0, //!< src1 is equal to src2.
+                CMP_GT = 1, //!< src1 is greater than src2.
+                CMP_GE = 2, //!< src1 is greater than or equal to src2.
+                CMP_LT = 3, //!< src1 is less than src2.
+                CMP_LE = 4, //!< src1 is less than or equal to src2.
+                CMP_NE = 5  //!< src1 is unequal to src2.
+              };
+
+//! generalized matrix multiplication flags
+enum GemmFlags { GEMM_1_T = 1, //!< transposes src1
+                 GEMM_2_T = 2, //!< transposes src2
+                 GEMM_3_T = 4 //!< transposes src3
+               };
+
+enum DftFlags {
+    /** performs an inverse 1D or 2D transform instead of the default forward
+        transform. */
+    DFT_INVERSE        = 1,
+    /** scales the result: divide it by the number of array elements. Normally, it is
+        combined with DFT_INVERSE. */
+    DFT_SCALE          = 2,
+    /** performs a forward or inverse transform of every individual row of the input
+        matrix; this flag enables you to transform multiple vectors simultaneously and can be used to
+        decrease the overhead (which is sometimes several times larger than the processing itself) to
+        perform 3D and higher-dimensional transformations and so forth.*/
+    DFT_ROWS           = 4,
+    /** performs a forward transformation of 1D or 2D real array; the result,
+        though being a complex array, has complex-conjugate symmetry (*CCS*, see the function
+        description below for details), and such an array can be packed into a real array of the same
+        size as input, which is the fastest option and which is what the function does by default;
+        however, you may wish to get a full complex array (for simpler spectrum analysis, and so on) -
+        pass the flag to enable the function to produce a full-size complex output array. */
+    DFT_COMPLEX_OUTPUT = 16,
+    /** performs an inverse transformation of a 1D or 2D complex array; the
+        result is normally a complex array of the same size, however, if the input array has
+        conjugate-complex symmetry (for example, it is a result of forward transformation with
+        DFT_COMPLEX_OUTPUT flag), the output is a real array; while the function itself does not
+        check whether the input is symmetrical or not, you can pass the flag and then the function
+        will assume the symmetry and produce the real output array (note that when the input is packed
+        into a real array and inverse transformation is executed, the function treats the input as a
+        packed complex-conjugate symmetrical array, and the output will also be a real array). */
+    DFT_REAL_OUTPUT    = 32,
+    /** specifies that input is complex input. If this flag is set, the input must have 2 channels.
+        On the other hand, for backwards compatibility reason, if input has 2 channels, input is
+        already considered complex. */
+    DFT_COMPLEX_INPUT  = 64,
+    /** performs an inverse 1D or 2D transform instead of the default forward transform. */
+    DCT_INVERSE        = DFT_INVERSE,
+    /** performs a forward or inverse transform of every individual row of the input
+        matrix. This flag enables you to transform multiple vectors simultaneously and can be used to
+        decrease the overhead (which is sometimes several times larger than the processing itself) to
+        perform 3D and higher-dimensional transforms and so forth.*/
+    DCT_ROWS           = DFT_ROWS
+};
+
+//! Various border types, image boundaries are denoted with `|`
+//! @see borderInterpolate, copyMakeBorder
+enum BorderTypes {
+    BORDER_CONSTANT    = 0, //!< `iiiiii|abcdefgh|iiiiiii`  with some specified `i`
+    BORDER_REPLICATE   = 1, //!< `aaaaaa|abcdefgh|hhhhhhh`
+    BORDER_REFLECT     = 2, //!< `fedcba|abcdefgh|hgfedcb`
+    BORDER_WRAP        = 3, //!< `cdefgh|abcdefgh|abcdefg`
+    BORDER_REFLECT_101 = 4, //!< `gfedcb|abcdefgh|gfedcba`
+    BORDER_TRANSPARENT = 5, //!< `uvwxyz|abcdefgh|ijklmno` - Treats outliers as transparent.
+
+    BORDER_REFLECT101  = BORDER_REFLECT_101, //!< same as BORDER_REFLECT_101
+    BORDER_DEFAULT     = BORDER_REFLECT_101, //!< same as BORDER_REFLECT_101
+    BORDER_ISOLATED    = 16 //!< Interpolation restricted within the ROI boundaries.
+};
+
+//! @} core_array
+
+//! @addtogroup core_utils
+//! @{
+
+/*! @brief Signals an error and raises the exception.
+
+By default the function prints information about the error to stderr,
+then it either stops if setBreakOnError() had been called before or raises the exception.
+It is possible to alternate error processing by using redirectError().
+@param code - error code (Error::Code)
+@param err - error description
+@param func - function name. Available only when the compiler supports getting it
+@param file - source file name where the error has occurred
+@param line - line number in the source file where the error has occurred
+@see CV_Error, CV_Error_, CV_Assert, CV_DbgAssert
+ */
+CV_EXPORTS CV_NORETURN void error(int code, const String& err, const char* func, const char* file, int line);
+
+/*! @brief Signals an error and terminate application.
+
+By default the function prints information about the error to stderr, then it terminates application
+with std::terminate. The function is designed for invariants check in functions and methods with
+noexcept attribute.
+@param code - error code (Error::Code)
+@param err - error description
+@param func - function name. Available only when the compiler supports getting it
+@param file - source file name where the error has occurred
+@param line - line number in the source file where the error has occurred
+@see CV_AssertTerminate
+ */
+CV_EXPORTS CV_NORETURN void terminate(int code, const String& err, const char* func, const char* file, int line) CV_NOEXCEPT;
+
+
+#ifdef CV_STATIC_ANALYSIS
+
+// In practice, some macro are not processed correctly (noreturn is not detected).
+// We need to use simplified definition for them.
+#define CV_Error(code, msg) do { (void)(code); (void)(msg); abort(); } while (0)
+#define CV_Error_(code, args) do { (void)(code); (void)(cv::format args); abort(); } while (0)
+#define CV_Assert( expr ) do { if (!(expr)) abort(); } while (0)
+
+#else // CV_STATIC_ANALYSIS
+
+/** @brief Call the error handler.
+
+Currently, the error handler prints the error code and the error message to the standard
+error stream `stderr`. In the Debug configuration, it then provokes memory access violation, so that
+the execution stack and all the parameters can be analyzed by the debugger. In the Release
+configuration, the exception is thrown.
+
+@param code one of Error::Code
+@param msg error message
+*/
+#define CV_Error( code, msg ) cv::error( code, msg, CV_Func, __FILE__, __LINE__ )
+
+/**  @brief Call the error handler.
+
+This macro can be used to construct an error message on-fly to include some dynamic information,
+for example:
+@code
+    // note the extra parentheses around the formatted text message
+    CV_Error_(Error::StsOutOfRange,
+    ("the value at (%d, %d)=%g is out of range", badPt.x, badPt.y, badValue));
+@endcode
+@param code one of Error::Code
+@param args printf-like formatted error message in parentheses
+*/
+#define CV_Error_( code, args ) cv::error( code, cv::format args, CV_Func, __FILE__, __LINE__ )
+
+/** @brief Checks a condition at runtime and throws exception if it fails
+
+The macros CV_Assert (and CV_DbgAssert(expr)) evaluate the specified expression. If it is 0, the macros
+raise an error (see cv::error). The macro CV_Assert checks the condition in both Debug and Release
+configurations while CV_DbgAssert is only retained in the Debug configuration.
+CV_AssertTerminate is analog of CV_Assert for invariants check in functions with noexcept attribute.
+It does not throw exception, but terminates the application.
+*/
+#define CV_Assert( expr ) do { if(!!(expr)) ; else cv::error( cv::Error::StsAssert, #expr, CV_Func, __FILE__, __LINE__ ); } while(0)
+#define CV_AssertTerminate( expr ) do { if(!!(expr)) ; else cv::terminate( #expr, CV_Func, __FILE__, __LINE__ ); } while(0)
+
+#endif // CV_STATIC_ANALYSIS
+
+//! @cond IGNORED
+#if !defined(__OPENCV_BUILD)  // TODO: backward compatibility only
+#ifndef CV_ErrorNoReturn
+#define CV_ErrorNoReturn CV_Error
+#endif
+#ifndef CV_ErrorNoReturn_
+#define CV_ErrorNoReturn_ CV_Error_
+#endif
+#endif
+
+#define CV_Assert_1 CV_Assert
+#define CV_Assert_2( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_1( __VA_ARGS__ ))
+#define CV_Assert_3( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_2( __VA_ARGS__ ))
+#define CV_Assert_4( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_3( __VA_ARGS__ ))
+#define CV_Assert_5( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_4( __VA_ARGS__ ))
+#define CV_Assert_6( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_5( __VA_ARGS__ ))
+#define CV_Assert_7( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_6( __VA_ARGS__ ))
+#define CV_Assert_8( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_7( __VA_ARGS__ ))
+#define CV_Assert_9( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_8( __VA_ARGS__ ))
+#define CV_Assert_10( expr, ... ) CV_Assert_1(expr); __CV_EXPAND(CV_Assert_9( __VA_ARGS__ ))
+
+#define CV_Assert_N(...) do { __CV_EXPAND(__CV_CAT(CV_Assert_, __CV_VA_NUM_ARGS(__VA_ARGS__)) (__VA_ARGS__)); } while(0)
+
+//! @endcond
+
+#if defined _DEBUG || defined CV_STATIC_ANALYSIS
+#  define CV_DbgAssert(expr) CV_Assert(expr)
+#else
+/** replaced with CV_Assert(expr) in Debug configuration */
+#  define CV_DbgAssert(expr)
+#endif
+
+/*
+ * Hamming distance functor - counts the bit differences between two strings - useful for the Brief descriptor
+ * bit count of A exclusive XOR'ed with B
+ */
+struct CV_EXPORTS Hamming
+{
+    static const NormTypes normType = NORM_HAMMING;
+    typedef unsigned char ValueType;
+    typedef int ResultType;
+
+    /** this will count the bits in a ^ b
+     */
+    ResultType operator()( const unsigned char* a, const unsigned char* b, int size ) const;
+};
+
+typedef Hamming HammingLUT;
+
+/////////////////////////////////// inline norms ////////////////////////////////////
+
+template<typename _Tp> inline _Tp cv_abs(_Tp x) { return std::abs(x); }
+inline int cv_abs(uchar x) { return x; }
+inline int cv_abs(schar x) { return std::abs(x); }
+inline int cv_abs(ushort x) { return x; }
+inline int cv_abs(short x) { return std::abs(x); }
+
+template<typename _Tp, typename _AccTp> static inline
+_AccTp normL2Sqr(const _Tp* a, int n)
+{
+    _AccTp s = 0;
+    int i=0;
+#if CV_ENABLE_UNROLLED
+    for( ; i <= n - 4; i += 4 )
+    {
+        _AccTp v0 = a[i], v1 = a[i+1], v2 = a[i+2], v3 = a[i+3];
+        s += v0*v0 + v1*v1 + v2*v2 + v3*v3;
+    }
+#endif
+    for( ; i < n; i++ )
+    {
+        _AccTp v = a[i];
+        s += v*v;
+    }
+    return s;
+}
+
+template<typename _Tp, typename _AccTp> static inline
+_AccTp normL1(const _Tp* a, int n)
+{
+    _AccTp s = 0;
+    int i = 0;
+#if CV_ENABLE_UNROLLED
+    for(; i <= n - 4; i += 4 )
+    {
+        s += (_AccTp)cv_abs(a[i]) + (_AccTp)cv_abs(a[i+1]) +
+            (_AccTp)cv_abs(a[i+2]) + (_AccTp)cv_abs(a[i+3]);
+    }
+#endif
+    for( ; i < n; i++ )
+        s += cv_abs(a[i]);
+    return s;
+}
+
+template<typename _Tp, typename _AccTp> static inline
+_AccTp normInf(const _Tp* a, int n)
+{
+    _AccTp s = 0;
+    for( int i = 0; i < n; i++ )
+        s = std::max(s, (_AccTp)cv_abs(a[i]));
+    return s;
+}
+
+template<typename _Tp, typename _AccTp> static inline
+_AccTp normL2Sqr(const _Tp* a, const _Tp* b, int n)
+{
+    _AccTp s = 0;
+    int i= 0;
+#if CV_ENABLE_UNROLLED
+    for(; i <= n - 4; i += 4 )
+    {
+        _AccTp v0 = _AccTp(a[i] - b[i]), v1 = _AccTp(a[i+1] - b[i+1]), v2 = _AccTp(a[i+2] - b[i+2]), v3 = _AccTp(a[i+3] - b[i+3]);
+        s += v0*v0 + v1*v1 + v2*v2 + v3*v3;
+    }
+#endif
+    for( ; i < n; i++ )
+    {
+        _AccTp v = _AccTp(a[i] - b[i]);
+        s += v*v;
+    }
+    return s;
+}
+
+static inline float normL2Sqr(const float* a, const float* b, int n)
+{
+    float s = 0.f;
+    for( int i = 0; i < n; i++ )
+    {
+        float v = a[i] - b[i];
+        s += v*v;
+    }
+    return s;
+}
+
+template<typename _Tp, typename _AccTp> static inline
+_AccTp normL1(const _Tp* a, const _Tp* b, int n)
+{
+    _AccTp s = 0;
+    int i= 0;
+#if CV_ENABLE_UNROLLED
+    for(; i <= n - 4; i += 4 )
+    {
+        _AccTp v0 = _AccTp(a[i] - b[i]), v1 = _AccTp(a[i+1] - b[i+1]), v2 = _AccTp(a[i+2] - b[i+2]), v3 = _AccTp(a[i+3] - b[i+3]);
+        s += std::abs(v0) + std::abs(v1) + std::abs(v2) + std::abs(v3);
+    }
+#endif
+    for( ; i < n; i++ )
+    {
+        _AccTp v = _AccTp(a[i] - b[i]);
+        s += std::abs(v);
+    }
+    return s;
+}
+
+inline float normL1(const float* a, const float* b, int n)
+{
+    float s = 0.f;
+    for( int i = 0; i < n; i++ )
+    {
+        s += std::abs(a[i] - b[i]);
+    }
+    return s;
+}
+
+inline int normL1(const uchar* a, const uchar* b, int n)
+{
+    int s = 0;
+    for( int i = 0; i < n; i++ )
+    {
+        s += std::abs(a[i] - b[i]);
+    }
+    return s;
+}
+
+template<typename _Tp, typename _AccTp> static inline
+_AccTp normInf(const _Tp* a, const _Tp* b, int n)
+{
+    _AccTp s = 0;
+    for( int i = 0; i < n; i++ )
+    {
+        _AccTp v0 = a[i] - b[i];
+        s = std::max(s, std::abs(v0));
+    }
+    return s;
+}
+
+/** @brief Computes the cube root of an argument.
+
+ The function cubeRoot computes \f$\sqrt[3]{\texttt{val}}\f$. Negative arguments are handled correctly.
+ NaN and Inf are not handled. The accuracy approaches the maximum possible accuracy for
+ single-precision data.
+ @param val A function argument.
+ */
+CV_EXPORTS_W float cubeRoot(float val);
+
+/** @overload
+
+cubeRoot with argument of `double` type calls `std::cbrt(double)`
+*/
+static inline
+double cubeRoot(double val)
+{
+    return std::cbrt(val);
+}
+
+/** @brief Calculates the angle of a 2D vector in degrees.
+
+ The function fastAtan2 calculates the full-range angle of an input 2D vector. The angle is measured
+ in degrees and varies from 0 to 360 degrees. The accuracy is about 0.3 degrees.
+ @param x x-coordinate of the vector.
+ @param y y-coordinate of the vector.
+ */
+CV_EXPORTS_W float fastAtan2(float y, float x);
+
+/** proxy for hal::LU */
+CV_EXPORTS int LU(float* A, size_t astep, int m, float* b, size_t bstep, int n);
+/** proxy for hal::LU */
+CV_EXPORTS int LU(double* A, size_t astep, int m, double* b, size_t bstep, int n);
+/** proxy for hal::Cholesky */
+CV_EXPORTS bool Cholesky(float* A, size_t astep, int m, float* b, size_t bstep, int n);
+/** proxy for hal::Cholesky */
+CV_EXPORTS bool Cholesky(double* A, size_t astep, int m, double* b, size_t bstep, int n);
+
+////////////////// forward declarations for important OpenCV types //////////////////
+
+//! @cond IGNORED
+
+template<typename _Tp, int cn> class Vec;
+template<typename _Tp, int m, int n> class Matx;
+
+template<typename _Tp> class Complex;
+template<typename _Tp> class Point_;
+template<typename _Tp> class Point3_;
+template<typename _Tp> class Size_;
+template<typename _Tp> class Rect_;
+template<typename _Tp> class Scalar_;
+
+class CV_EXPORTS RotatedRect;
+class CV_EXPORTS Range;
+class CV_EXPORTS TermCriteria;
+class CV_EXPORTS KeyPoint;
+class CV_EXPORTS DMatch;
+class CV_EXPORTS RNG;
+
+class CV_EXPORTS Mat;
+class CV_EXPORTS MatExpr;
+
+class CV_EXPORTS UMat;
+
+class CV_EXPORTS SparseMat;
+typedef Mat MatND;
+
+template<typename _Tp> class Mat_;
+template<typename _Tp> class SparseMat_;
+
+class CV_EXPORTS MatConstIterator;
+class CV_EXPORTS SparseMatIterator;
+class CV_EXPORTS SparseMatConstIterator;
+template<typename _Tp> class MatIterator_;
+template<typename _Tp> class MatConstIterator_;
+template<typename _Tp> class SparseMatIterator_;
+template<typename _Tp> class SparseMatConstIterator_;
+
+namespace ogl
+{
+    class CV_EXPORTS Buffer;
+    class CV_EXPORTS Texture2D;
+    class CV_EXPORTS Arrays;
+}
+
+namespace cuda
+{
+    class CV_EXPORTS GpuMat;
+    class CV_EXPORTS HostMem;
+    class CV_EXPORTS Stream;
+    class CV_EXPORTS Event;
+}
+
+namespace cudev
+{
+    template <typename _Tp> class GpuMat_;
+}
+
+namespace ipp
+{
+CV_EXPORTS   unsigned long long getIppFeatures();
+CV_EXPORTS   void setIppStatus(int status, const char * const funcname = NULL, const char * const filename = NULL,
+                             int line = 0);
+CV_EXPORTS   int getIppStatus();
+CV_EXPORTS   String getIppErrorLocation();
+CV_EXPORTS_W bool   useIPP();
+CV_EXPORTS_W void   setUseIPP(bool flag);
+CV_EXPORTS_W String getIppVersion();
+
+// IPP Not-Exact mode. This function may force use of IPP then both IPP and OpenCV provide proper results
+// but have internal accuracy differences which have too much direct or indirect impact on accuracy tests.
+CV_EXPORTS_W bool useIPP_NotExact();
+CV_EXPORTS_W void setUseIPP_NotExact(bool flag);
+#ifndef DISABLE_OPENCV_3_COMPATIBILITY
+static inline bool useIPP_NE() { return useIPP_NotExact(); }
+static inline void setUseIPP_NE(bool flag) { setUseIPP_NotExact(flag); }
+#endif
+
+} // ipp
+
+//! @endcond
+
+//! @} core_utils
+
+
+
+
+} // cv
+
+#include "opencv2/core/neon_utils.hpp"
+#include "opencv2/core/vsx_utils.hpp"
+#include "opencv2/core/check.hpp"
+
+#endif //OPENCV_CORE_BASE_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/bindings_utils.hpp

@@ -0,0 +1,357 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_BINDINGS_UTILS_HPP
+#define OPENCV_CORE_BINDINGS_UTILS_HPP
+
+#include <opencv2/core/async.hpp>
+#include <opencv2/core/detail/async_promise.hpp>
+#include <opencv2/core/utils/logger.hpp>
+
+#include <stdexcept>
+
+namespace cv { namespace utils {
+//! @addtogroup core_utils
+//! @{
+
+CV_EXPORTS_W String dumpInputArray(InputArray argument);
+
+CV_EXPORTS_W String dumpInputArrayOfArrays(InputArrayOfArrays argument);
+
+CV_EXPORTS_W String dumpInputOutputArray(InputOutputArray argument);
+
+CV_EXPORTS_W String dumpInputOutputArrayOfArrays(InputOutputArrayOfArrays argument);
+
+CV_WRAP static inline
+String dumpBool(bool argument)
+{
+    return (argument) ? String("Bool: True") : String("Bool: False");
+}
+
+CV_WRAP static inline
+String dumpInt(int argument)
+{
+    return cv::format("Int: %d", argument);
+}
+
+CV_WRAP static inline
+String dumpInt64(int64 argument)
+{
+    std::ostringstream oss("Int64: ", std::ios::ate);
+    oss << argument;
+    return oss.str();
+}
+
+CV_WRAP static inline
+String dumpSizeT(size_t argument)
+{
+    std::ostringstream oss("size_t: ", std::ios::ate);
+    oss << argument;
+    return oss.str();
+}
+
+CV_WRAP static inline
+String dumpFloat(float argument)
+{
+    return cv::format("Float: %.2f", argument);
+}
+
+CV_WRAP static inline
+String dumpDouble(double argument)
+{
+    return cv::format("Double: %.2f", argument);
+}
+
+CV_WRAP static inline
+String dumpCString(const char* argument)
+{
+    return cv::format("String: %s", argument);
+}
+
+CV_WRAP static inline
+String dumpString(const String& argument)
+{
+    return cv::format("String: %s", argument.c_str());
+}
+
+CV_WRAP static inline
+String dumpRect(const Rect& argument)
+{
+    return format("rect: (x=%d, y=%d, w=%d, h=%d)", argument.x, argument.y,
+                  argument.width, argument.height);
+}
+
+CV_WRAP static inline
+String dumpTermCriteria(const TermCriteria& argument)
+{
+    return format("term_criteria: (type=%d, max_count=%d, epsilon=%lf",
+                  argument.type, argument.maxCount, argument.epsilon);
+}
+
+CV_WRAP static inline
+String dumpRotatedRect(const RotatedRect& argument)
+{
+    return format("rotated_rect: (c_x=%f, c_y=%f, w=%f, h=%f, a=%f)",
+                  argument.center.x, argument.center.y, argument.size.width,
+                  argument.size.height, argument.angle);
+}
+
+CV_WRAP static inline
+String dumpRange(const Range& argument)
+{
+    if (argument == Range::all())
+    {
+        return "range: all";
+    }
+    else
+    {
+        return format("range: (s=%d, e=%d)", argument.start, argument.end);
+    }
+}
+
+CV_EXPORTS_W String dumpVectorOfInt(const std::vector<int>& vec);
+
+CV_EXPORTS_W String dumpVectorOfDouble(const std::vector<double>& vec);
+
+CV_EXPORTS_W String dumpVectorOfRect(const std::vector<Rect>& vec);
+
+
+//! @cond IGNORED
+
+CV_WRAP static inline
+String testOverloadResolution(int value, const Point& point = Point(42, 24))
+{
+    return format("overload (int=%d, point=(x=%d, y=%d))", value, point.x,
+                  point.y);
+}
+
+CV_WRAP static inline
+String testOverloadResolution(const Rect& rect)
+{
+    return format("overload (rect=(x=%d, y=%d, w=%d, h=%d))", rect.x, rect.y,
+                  rect.width, rect.height);
+}
+
+CV_WRAP static inline
+RotatedRect testRotatedRect(float x, float y, float w, float h, float angle)
+{
+    return RotatedRect(Point2f(x, y), Size2f(w, h), angle);
+}
+
+CV_WRAP static inline
+std::vector<RotatedRect> testRotatedRectVector(float x, float y, float w, float h, float angle)
+{
+    std::vector<RotatedRect> result;
+    for (int i = 0; i < 10; i++)
+        result.push_back(RotatedRect(Point2f(x + i, y + 2 * i), Size2f(w, h), angle + 10 * i));
+    return result;
+}
+
+CV_WRAP static inline
+int testOverwriteNativeMethod(int argument)
+{
+    return argument;
+}
+
+CV_WRAP static inline
+String testReservedKeywordConversion(int positional_argument, int lambda = 2, int from = 3)
+{
+    return format("arg=%d, lambda=%d, from=%d", positional_argument, lambda, from);
+}
+
+CV_WRAP static inline
+void generateVectorOfRect(size_t len, CV_OUT std::vector<Rect>& vec)
+{
+    vec.resize(len);
+    if (len > 0)
+    {
+        RNG rng(12345);
+        Mat tmp(static_cast<int>(len), 1, CV_32SC4);
+        rng.fill(tmp, RNG::UNIFORM, 10, 20);
+        tmp.copyTo(vec);
+    }
+}
+
+CV_WRAP static inline
+void generateVectorOfInt(size_t len, CV_OUT std::vector<int>& vec)
+{
+    vec.resize(len);
+    if (len > 0)
+    {
+        RNG rng(554433);
+        Mat tmp(static_cast<int>(len), 1, CV_32SC1);
+        rng.fill(tmp, RNG::UNIFORM, -10, 10);
+        tmp.copyTo(vec);
+    }
+}
+
+CV_WRAP static inline
+void generateVectorOfMat(size_t len, int rows, int cols, int dtype, CV_OUT std::vector<Mat>& vec)
+{
+    vec.resize(len);
+    if (len > 0)
+    {
+        RNG rng(65431);
+        for (size_t i = 0; i < len; ++i)
+        {
+            vec[i].create(rows, cols, dtype);
+            rng.fill(vec[i], RNG::UNIFORM, 0, 10);
+        }
+    }
+}
+
+CV_WRAP static inline
+void testRaiseGeneralException()
+{
+    throw std::runtime_error("exception text");
+}
+
+CV_WRAP static inline
+AsyncArray testAsyncArray(InputArray argument)
+{
+    AsyncPromise p;
+    p.setValue(argument);
+    return p.getArrayResult();
+}
+
+CV_WRAP static inline
+AsyncArray testAsyncException()
+{
+    AsyncPromise p;
+    try
+    {
+        CV_Error(Error::StsOk, "Test: Generated async error");
+    }
+    catch (const cv::Exception& e)
+    {
+        p.setException(e);
+    }
+    return p.getArrayResult();
+}
+
+CV_WRAP static inline
+String dumpVec2i(const cv::Vec2i value = cv::Vec2i(42, 24)) {
+    return format("Vec2i(%d, %d)", value[0], value[1]);
+}
+
+struct CV_EXPORTS_W_SIMPLE ClassWithKeywordProperties {
+    CV_PROP_RW int lambda;
+    CV_PROP int except;
+
+    CV_WRAP explicit ClassWithKeywordProperties(int lambda_arg = 24, int except_arg = 42)
+    {
+        lambda = lambda_arg;
+        except = except_arg;
+    }
+};
+
+struct CV_EXPORTS_W_PARAMS FunctionParams
+{
+    CV_PROP_RW int lambda = -1;
+    CV_PROP_RW float sigma = 0.0f;
+
+    FunctionParams& setLambda(int value) CV_NOEXCEPT
+    {
+        lambda = value;
+        return *this;
+    }
+
+    FunctionParams& setSigma(float value) CV_NOEXCEPT
+    {
+        sigma = value;
+        return *this;
+    }
+};
+
+CV_WRAP static inline String
+copyMatAndDumpNamedArguments(InputArray src, OutputArray dst,
+                             const FunctionParams& params = FunctionParams())
+{
+    src.copyTo(dst);
+    return format("lambda=%d, sigma=%.1f", params.lambda,
+                  params.sigma);
+}
+
+namespace nested {
+CV_WRAP static inline bool testEchoBooleanFunction(bool flag) {
+    return flag;
+}
+
+class CV_EXPORTS_W CV_WRAP_AS(ExportClassName) OriginalClassName
+{
+public:
+    struct CV_EXPORTS_W_SIMPLE Params
+    {
+        CV_PROP_RW int int_value;
+        CV_PROP_RW float float_value;
+
+        CV_WRAP explicit Params(int int_param = 123, float float_param = 3.5f)
+        {
+            int_value = int_param;
+            float_value = float_param;
+        }
+    };
+
+    explicit OriginalClassName(const OriginalClassName::Params& params = OriginalClassName::Params())
+    {
+        params_ = params;
+    }
+
+    CV_WRAP int getIntParam() const
+    {
+        return params_.int_value;
+    }
+
+    CV_WRAP float getFloatParam() const
+    {
+        return params_.float_value;
+    }
+
+    CV_WRAP static std::string originalName()
+    {
+        return "OriginalClassName";
+    }
+
+    CV_WRAP static Ptr<OriginalClassName>
+    create(const OriginalClassName::Params& params = OriginalClassName::Params())
+    {
+        return makePtr<OriginalClassName>(params);
+    }
+
+private:
+    OriginalClassName::Params params_;
+};
+
+typedef OriginalClassName::Params OriginalClassName_Params;
+} // namespace nested
+
+//! @endcond IGNORED
+
+namespace fs {
+    CV_EXPORTS_W cv::String getCacheDirectoryForDownloads();
+} // namespace fs
+
+//! @}  // core_utils
+}  // namespace cv::utils
+
+//! @cond IGNORED
+
+CV_WRAP static inline
+int setLogLevel(int level)
+{
+    // NB: Binding generators doesn't work with enums properly yet, so we define separate overload here
+    return cv::utils::logging::setLogLevel((cv::utils::logging::LogLevel)level);
+}
+
+CV_WRAP static inline
+int getLogLevel()
+{
+    return cv::utils::logging::getLogLevel();
+}
+
+//! @endcond IGNORED
+
+} // namespaces cv /  utils
+
+#endif // OPENCV_CORE_BINDINGS_UTILS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/bufferpool.hpp

@@ -0,0 +1,40 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+//
+// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
+
+#ifndef OPENCV_CORE_BUFFER_POOL_HPP
+#define OPENCV_CORE_BUFFER_POOL_HPP
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable: 4265)
+#endif
+
+namespace cv
+{
+
+//! @addtogroup core_opencl
+//! @{
+
+class BufferPoolController
+{
+protected:
+    ~BufferPoolController() { }
+public:
+    virtual size_t getReservedSize() const = 0;
+    virtual size_t getMaxReservedSize() const = 0;
+    virtual void setMaxReservedSize(size_t size) = 0;
+    virtual void freeAllReservedBuffers() = 0;
+};
+
+//! @}
+
+}
+
+#ifdef _MSC_VER
+#pragma warning(pop)
+#endif
+
+#endif // OPENCV_CORE_BUFFER_POOL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/check.hpp

@@ -0,0 +1,173 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_CHECK_HPP
+#define OPENCV_CORE_CHECK_HPP
+
+#include <opencv2/core/base.hpp>
+
+namespace cv {
+
+/** Returns string of cv::Mat depth value: CV_8U -> "CV_8U" or "<invalid depth>" */
+CV_EXPORTS const char* depthToString(int depth);
+
+/** Returns string of cv::Mat depth value: CV_8UC3 -> "CV_8UC3" or "<invalid type>" */
+CV_EXPORTS String typeToString(int type);
+
+
+//! @cond IGNORED
+namespace detail {
+
+/** Returns string of cv::Mat depth value: CV_8U -> "CV_8U" or NULL */
+CV_EXPORTS const char* depthToString_(int depth);
+
+/** Returns string of cv::Mat depth value: CV_8UC3 -> "CV_8UC3" or cv::String() */
+CV_EXPORTS cv::String typeToString_(int type);
+
+enum TestOp {
+  TEST_CUSTOM = 0,
+  TEST_EQ = 1,
+  TEST_NE = 2,
+  TEST_LE = 3,
+  TEST_LT = 4,
+  TEST_GE = 5,
+  TEST_GT = 6,
+  CV__LAST_TEST_OP
+};
+
+struct CheckContext {
+    const char* func;
+    const char* file;
+    int line;
+    enum TestOp testOp;
+    const char* message;
+    const char* p1_str;
+    const char* p2_str;
+};
+
+#ifndef CV__CHECK_FILENAME
+# define CV__CHECK_FILENAME __FILE__
+#endif
+
+#ifndef CV__CHECK_FUNCTION
+# if defined _MSC_VER
+#   define CV__CHECK_FUNCTION __FUNCSIG__
+# elif defined __GNUC__
+#   define CV__CHECK_FUNCTION __PRETTY_FUNCTION__
+# else
+#   define CV__CHECK_FUNCTION "<unknown>"
+# endif
+#endif
+
+#define CV__CHECK_LOCATION_VARNAME(id) CVAUX_CONCAT(CVAUX_CONCAT(__cv_check_, id), __LINE__)
+#define CV__DEFINE_CHECK_CONTEXT(id, message, testOp, p1_str, p2_str) \
+    static const cv::detail::CheckContext CV__CHECK_LOCATION_VARNAME(id) = \
+            { CV__CHECK_FUNCTION, CV__CHECK_FILENAME, __LINE__, testOp, "" message, "" p1_str, "" p2_str }
+
+CV_EXPORTS void CV_NORETURN check_failed_auto(const bool v1, const bool v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const int v1, const int v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const size_t v1, const size_t v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const float v1, const float v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const double v1, const double v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const Size_<int> v1, const Size_<int> v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_MatDepth(const int v1, const int v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_MatType(const int v1, const int v2, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_MatChannels(const int v1, const int v2, const CheckContext& ctx);
+
+CV_EXPORTS void CV_NORETURN check_failed_true(const bool v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_false(const bool v, const CheckContext& ctx);
+
+CV_EXPORTS void CV_NORETURN check_failed_auto(const int v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const size_t v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const float v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const double v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const Size_<int> v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_auto(const std::string& v1, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_MatDepth(const int v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_MatType(const int v, const CheckContext& ctx);
+CV_EXPORTS void CV_NORETURN check_failed_MatChannels(const int v, const CheckContext& ctx);
+
+
+#define CV__TEST_EQ(v1, v2) ((v1) == (v2))
+#define CV__TEST_NE(v1, v2) ((v1) != (v2))
+#define CV__TEST_LE(v1, v2) ((v1) <= (v2))
+#define CV__TEST_LT(v1, v2) ((v1) < (v2))
+#define CV__TEST_GE(v1, v2) ((v1) >= (v2))
+#define CV__TEST_GT(v1, v2) ((v1) > (v2))
+
+#define CV__CHECK(id, op, type, v1, v2, v1_str, v2_str, msg_str) do { \
+    if(CV__TEST_##op((v1), (v2))) ; else { \
+        CV__DEFINE_CHECK_CONTEXT(id, msg_str, cv::detail::TEST_ ## op, v1_str, v2_str); \
+        cv::detail::check_failed_ ## type((v1), (v2), CV__CHECK_LOCATION_VARNAME(id)); \
+    } \
+} while (0)
+
+#define CV__CHECK_CUSTOM_TEST(id, type, v, test_expr, v_str, test_expr_str, msg_str) do { \
+    if(!!(test_expr)) ; else { \
+        CV__DEFINE_CHECK_CONTEXT(id, msg_str, cv::detail::TEST_CUSTOM, v_str, test_expr_str); \
+        cv::detail::check_failed_ ## type((v), CV__CHECK_LOCATION_VARNAME(id)); \
+    } \
+} while (0)
+
+} // namespace
+//! @endcond
+
+
+/// Supported values of these types: int, float, double
+#define CV_CheckEQ(v1, v2, msg)  CV__CHECK(_, EQ, auto, v1, v2, #v1, #v2, msg)
+#define CV_CheckNE(v1, v2, msg)  CV__CHECK(_, NE, auto, v1, v2, #v1, #v2, msg)
+#define CV_CheckLE(v1, v2, msg)  CV__CHECK(_, LE, auto, v1, v2, #v1, #v2, msg)
+#define CV_CheckLT(v1, v2, msg)  CV__CHECK(_, LT, auto, v1, v2, #v1, #v2, msg)
+#define CV_CheckGE(v1, v2, msg)  CV__CHECK(_, GE, auto, v1, v2, #v1, #v2, msg)
+#define CV_CheckGT(v1, v2, msg)  CV__CHECK(_, GT, auto, v1, v2, #v1, #v2, msg)
+
+/// Check with additional "decoding" of type values in error message
+#define CV_CheckTypeEQ(t1, t2, msg)  CV__CHECK(_, EQ, MatType, t1, t2, #t1, #t2, msg)
+/// Check with additional "decoding" of depth values in error message
+#define CV_CheckDepthEQ(d1, d2, msg)  CV__CHECK(_, EQ, MatDepth, d1, d2, #d1, #d2, msg)
+
+#define CV_CheckChannelsEQ(c1, c2, msg)  CV__CHECK(_, EQ, MatChannels, c1, c2, #c1, #c2, msg)
+
+/// Example: type == CV_8UC1 || type == CV_8UC3
+#define CV_CheckType(t, test_expr, msg)  CV__CHECK_CUSTOM_TEST(_, MatType, t, (test_expr), #t, #test_expr, msg)
+
+/// Example: depth == CV_32F || depth == CV_64F
+#define CV_CheckDepth(t, test_expr, msg)  CV__CHECK_CUSTOM_TEST(_, MatDepth, t, (test_expr), #t, #test_expr, msg)
+
+/// Example: channel == 1 || channel == 3
+#define CV_CheckChannels(t, test_expr, msg)  CV__CHECK_CUSTOM_TEST(_, MatChannels, t, (test_expr), #t, #test_expr, msg)
+
+/// Example: v == A || v == B
+#define CV_Check(v, test_expr, msg)  CV__CHECK_CUSTOM_TEST(_, auto, v, (test_expr), #v, #test_expr, msg)
+
+/// Example: v == true
+#define CV_CheckTrue(v, msg)  CV__CHECK_CUSTOM_TEST(_, true, v, v, #v, "", msg)
+
+/// Example: v == false
+#define CV_CheckFalse(v, msg)  CV__CHECK_CUSTOM_TEST(_, false, v, (!(v)), #v, "", msg)
+
+/// Some complex conditions: CV_Check(src2, src2.empty() || (src2.type() == src1.type() && src2.size() == src1.size()), "src2 should have same size/type as src1")
+// TODO define pretty-printers
+
+#ifndef NDEBUG
+#define CV_DbgCheck(v, test_expr, msg)  CV__CHECK_CUSTOM_TEST(_, auto, v, (test_expr), #v, #test_expr, msg)
+#define CV_DbgCheckEQ(v1, v2, msg)  CV__CHECK(_, EQ, auto, v1, v2, #v1, #v2, msg)
+#define CV_DbgCheckNE(v1, v2, msg)  CV__CHECK(_, NE, auto, v1, v2, #v1, #v2, msg)
+#define CV_DbgCheckLE(v1, v2, msg)  CV__CHECK(_, LE, auto, v1, v2, #v1, #v2, msg)
+#define CV_DbgCheckLT(v1, v2, msg)  CV__CHECK(_, LT, auto, v1, v2, #v1, #v2, msg)
+#define CV_DbgCheckGE(v1, v2, msg)  CV__CHECK(_, GE, auto, v1, v2, #v1, #v2, msg)
+#define CV_DbgCheckGT(v1, v2, msg)  CV__CHECK(_, GT, auto, v1, v2, #v1, #v2, msg)
+#else
+#define CV_DbgCheck(v, test_expr, msg)  do { } while (0)
+#define CV_DbgCheckEQ(v1, v2, msg)  do { } while (0)
+#define CV_DbgCheckNE(v1, v2, msg)  do { } while (0)
+#define CV_DbgCheckLE(v1, v2, msg)  do { } while (0)
+#define CV_DbgCheckLT(v1, v2, msg)  do { } while (0)
+#define CV_DbgCheckGE(v1, v2, msg)  do { } while (0)
+#define CV_DbgCheckGT(v1, v2, msg)  do { } while (0)
+#endif
+
+} // namespace
+
+#endif // OPENCV_CORE_CHECK_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/core.hpp

@@ -0,0 +1,48 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifdef __OPENCV_BUILD
+#error this is a compatibility header which should not be used inside the OpenCV library
+#endif
+
+#include "opencv2/core.hpp"

GameAssist/GameAssist/include/cv2/opencv2/core/core_c.h

@@ -0,0 +1,3128 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+
+#ifndef OPENCV_CORE_C_H
+#define OPENCV_CORE_C_H
+
+#include "opencv2/core/types_c.h"
+
+#ifdef __cplusplus
+/* disable MSVC warning C4190 / clang-cl -Wreturn-type-c-linkage:
+       'function' has C-linkage specified, but returns UDT 'typename'
+       which is incompatible with C
+
+   It is OK to disable it because we only extend few plain structures with
+   C++ constructors for simpler interoperability with C++ API of the library
+*/
+#  if defined(__clang__)
+     // handle clang on Linux and clang-cl (i. e. clang on Windows) first
+#    pragma GCC diagnostic ignored "-Wreturn-type-c-linkage"
+#  elif defined(_MSC_VER)
+     // then handle MSVC
+#    pragma warning(disable:4190)
+#  endif
+#endif
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/** @addtogroup core_c
+    @{
+*/
+
+/****************************************************************************************\
+*          Array allocation, deallocation, initialization and access to elements         *
+\****************************************************************************************/
+
+/** `malloc` wrapper.
+   If there is no enough memory, the function
+   (as well as other OpenCV functions that call cvAlloc)
+   raises an error. */
+CVAPI(void*)  cvAlloc( size_t size );
+
+/** `free` wrapper.
+   Here and further all the memory releasing functions
+   (that all call cvFree) take double pointer in order to
+   to clear pointer to the data after releasing it.
+   Passing pointer to NULL pointer is Ok: nothing happens in this case
+*/
+CVAPI(void)   cvFree_( void* ptr );
+#define cvFree(ptr) (cvFree_(*(ptr)), *(ptr)=0)
+
+/** @brief Creates an image header but does not allocate the image data.
+
+@param size Image width and height
+@param depth Image depth (see cvCreateImage )
+@param channels Number of channels (see cvCreateImage )
+ */
+CVAPI(IplImage*)  cvCreateImageHeader( CvSize size, int depth, int channels );
+
+/** @brief Initializes an image header that was previously allocated.
+
+The returned IplImage\* points to the initialized header.
+@param image Image header to initialize
+@param size Image width and height
+@param depth Image depth (see cvCreateImage )
+@param channels Number of channels (see cvCreateImage )
+@param origin Top-left IPL_ORIGIN_TL or bottom-left IPL_ORIGIN_BL
+@param align Alignment for image rows, typically 4 or 8 bytes
+ */
+CVAPI(IplImage*) cvInitImageHeader( IplImage* image, CvSize size, int depth,
+                                   int channels, int origin CV_DEFAULT(0),
+                                   int align CV_DEFAULT(4));
+
+/** @brief Creates an image header and allocates the image data.
+
+This function call is equivalent to the following code:
+@code
+    header = cvCreateImageHeader(size, depth, channels);
+    cvCreateData(header);
+@endcode
+@param size Image width and height
+@param depth Bit depth of image elements. See IplImage for valid depths.
+@param channels Number of channels per pixel. See IplImage for details. This function only creates
+images with interleaved channels.
+ */
+CVAPI(IplImage*)  cvCreateImage( CvSize size, int depth, int channels );
+
+/** @brief Deallocates an image header.
+
+This call is an analogue of :
+@code
+    if(image )
+    {
+        iplDeallocate(*image, IPL_IMAGE_HEADER | IPL_IMAGE_ROI);
+        *image = 0;
+    }
+@endcode
+but it does not use IPL functions by default (see the CV_TURN_ON_IPL_COMPATIBILITY macro).
+@param image Double pointer to the image header
+ */
+CVAPI(void)  cvReleaseImageHeader( IplImage** image );
+
+/** @brief Deallocates the image header and the image data.
+
+This call is a shortened form of :
+@code
+    if(*image )
+    {
+        cvReleaseData(*image);
+        cvReleaseImageHeader(image);
+    }
+@endcode
+@param image Double pointer to the image header
+*/
+CVAPI(void)  cvReleaseImage( IplImage** image );
+
+/** Creates a copy of IPL image (widthStep may differ) */
+CVAPI(IplImage*) cvCloneImage( const IplImage* image );
+
+/** @brief Sets the channel of interest in an IplImage.
+
+If the ROI is set to NULL and the coi is *not* 0, the ROI is allocated. Most OpenCV functions do
+*not* support the COI setting, so to process an individual image/matrix channel one may copy (via
+cvCopy or cvSplit) the channel to a separate image/matrix, process it and then copy the result
+back (via cvCopy or cvMerge) if needed.
+@param image A pointer to the image header
+@param coi The channel of interest. 0 - all channels are selected, 1 - first channel is selected,
+etc. Note that the channel indices become 1-based.
+ */
+CVAPI(void)  cvSetImageCOI( IplImage* image, int coi );
+
+/** @brief Returns the index of the channel of interest.
+
+Returns the channel of interest of in an IplImage. Returned values correspond to the coi in
+cvSetImageCOI.
+@param image A pointer to the image header
+ */
+CVAPI(int)  cvGetImageCOI( const IplImage* image );
+
+/** @brief Sets an image Region Of Interest (ROI) for a given rectangle.
+
+If the original image ROI was NULL and the rect is not the whole image, the ROI structure is
+allocated.
+
+Most OpenCV functions support the use of ROI and treat the image rectangle as a separate image. For
+example, all of the pixel coordinates are counted from the top-left (or bottom-left) corner of the
+ROI, not the original image.
+@param image A pointer to the image header
+@param rect The ROI rectangle
+ */
+CVAPI(void)  cvSetImageROI( IplImage* image, CvRect rect );
+
+/** @brief Resets the image ROI to include the entire image and releases the ROI structure.
+
+This produces a similar result to the following, but in addition it releases the ROI structure. :
+@code
+    cvSetImageROI(image, cvRect(0, 0, image->width, image->height ));
+    cvSetImageCOI(image, 0);
+@endcode
+@param image A pointer to the image header
+ */
+CVAPI(void)  cvResetImageROI( IplImage* image );
+
+/** @brief Returns the image ROI.
+
+If there is no ROI set, cvRect(0,0,image-\>width,image-\>height) is returned.
+@param image A pointer to the image header
+ */
+CVAPI(CvRect) cvGetImageROI( const IplImage* image );
+
+/** @brief Creates a matrix header but does not allocate the matrix data.
+
+The function allocates a new matrix header and returns a pointer to it. The matrix data can then be
+allocated using cvCreateData or set explicitly to user-allocated data via cvSetData.
+@param rows Number of rows in the matrix
+@param cols Number of columns in the matrix
+@param type Type of the matrix elements, see cvCreateMat
+ */
+CVAPI(CvMat*)  cvCreateMatHeader( int rows, int cols, int type );
+
+#define CV_AUTOSTEP  0x7fffffff
+
+/** @brief Initializes a pre-allocated matrix header.
+
+This function is often used to process raw data with OpenCV matrix functions. For example, the
+following code computes the matrix product of two matrices, stored as ordinary arrays:
+@code
+    double a[] = { 1, 2, 3, 4,
+                   5, 6, 7, 8,
+                   9, 10, 11, 12 };
+
+    double b[] = { 1, 5, 9,
+                   2, 6, 10,
+                   3, 7, 11,
+                   4, 8, 12 };
+
+    double c[9];
+    CvMat Ma, Mb, Mc ;
+
+    cvInitMatHeader(&Ma, 3, 4, CV_64FC1, a);
+    cvInitMatHeader(&Mb, 4, 3, CV_64FC1, b);
+    cvInitMatHeader(&Mc, 3, 3, CV_64FC1, c);
+
+    cvMatMulAdd(&Ma, &Mb, 0, &Mc);
+    // the c array now contains the product of a (3x4) and b (4x3)
+@endcode
+@param mat A pointer to the matrix header to be initialized
+@param rows Number of rows in the matrix
+@param cols Number of columns in the matrix
+@param type Type of the matrix elements, see cvCreateMat .
+@param data Optional: data pointer assigned to the matrix header
+@param step Optional: full row width in bytes of the assigned data. By default, the minimal
+possible step is used which assumes there are no gaps between subsequent rows of the matrix.
+ */
+CVAPI(CvMat*) cvInitMatHeader( CvMat* mat, int rows, int cols,
+                              int type, void* data CV_DEFAULT(NULL),
+                              int step CV_DEFAULT(CV_AUTOSTEP) );
+
+/** @brief Creates a matrix header and allocates the matrix data.
+
+The function call is equivalent to the following code:
+@code
+    CvMat* mat = cvCreateMatHeader(rows, cols, type);
+    cvCreateData(mat);
+@endcode
+@param rows Number of rows in the matrix
+@param cols Number of columns in the matrix
+@param type The type of the matrix elements in the form
+CV_\<bit depth\>\<S|U|F\>C\<number of channels\> , where S=signed, U=unsigned, F=float. For
+example, CV _ 8UC1 means the elements are 8-bit unsigned and the there is 1 channel, and CV _
+32SC2 means the elements are 32-bit signed and there are 2 channels.
+ */
+CVAPI(CvMat*)  cvCreateMat( int rows, int cols, int type );
+
+/** @brief Deallocates a matrix.
+
+The function decrements the matrix data reference counter and deallocates matrix header. If the data
+reference counter is 0, it also deallocates the data. :
+@code
+    if(*mat )
+        cvDecRefData(*mat);
+    cvFree((void**)mat);
+@endcode
+@param mat Double pointer to the matrix
+ */
+CVAPI(void)  cvReleaseMat( CvMat** mat );
+
+/** @brief Decrements an array data reference counter.
+
+The function decrements the data reference counter in a CvMat or CvMatND if the reference counter
+
+pointer is not NULL. If the counter reaches zero, the data is deallocated. In the current
+implementation the reference counter is not NULL only if the data was allocated using the
+cvCreateData function. The counter will be NULL in other cases such as: external data was assigned
+to the header using cvSetData, header is part of a larger matrix or image, or the header was
+converted from an image or n-dimensional matrix header.
+@param arr Pointer to an array header
+ */
+CV_INLINE  void  cvDecRefData( CvArr* arr )
+{
+    if( CV_IS_MAT( arr ))
+    {
+        CvMat* mat = (CvMat*)arr;
+        mat->data.ptr = NULL;
+        if( mat->refcount != NULL && --*mat->refcount == 0 )
+            cvFree( &mat->refcount );
+        mat->refcount = NULL;
+    }
+    else if( CV_IS_MATND( arr ))
+    {
+        CvMatND* mat = (CvMatND*)arr;
+        mat->data.ptr = NULL;
+        if( mat->refcount != NULL && --*mat->refcount == 0 )
+            cvFree( &mat->refcount );
+        mat->refcount = NULL;
+    }
+}
+
+/** @brief Increments array data reference counter.
+
+The function increments CvMat or CvMatND data reference counter and returns the new counter value if
+the reference counter pointer is not NULL, otherwise it returns zero.
+@param arr Array header
+ */
+CV_INLINE  int  cvIncRefData( CvArr* arr )
+{
+    int refcount = 0;
+    if( CV_IS_MAT( arr ))
+    {
+        CvMat* mat = (CvMat*)arr;
+        if( mat->refcount != NULL )
+            refcount = ++*mat->refcount;
+    }
+    else if( CV_IS_MATND( arr ))
+    {
+        CvMatND* mat = (CvMatND*)arr;
+        if( mat->refcount != NULL )
+            refcount = ++*mat->refcount;
+    }
+    return refcount;
+}
+
+
+/** Creates an exact copy of the input matrix (except, may be, step value) */
+CVAPI(CvMat*) cvCloneMat( const CvMat* mat );
+
+
+/** @brief Returns matrix header corresponding to the rectangular sub-array of input image or matrix.
+
+The function returns header, corresponding to a specified rectangle of the input array. In other
+
+words, it allows the user to treat a rectangular part of input array as a stand-alone array. ROI is
+taken into account by the function so the sub-array of ROI is actually extracted.
+@param arr Input array
+@param submat Pointer to the resultant sub-array header
+@param rect Zero-based coordinates of the rectangle of interest
+ */
+CVAPI(CvMat*) cvGetSubRect( const CvArr* arr, CvMat* submat, CvRect rect );
+#define cvGetSubArr cvGetSubRect
+
+/** @brief Returns array row or row span.
+
+The function returns the header, corresponding to a specified row/row span of the input array.
+cvGetRow(arr, submat, row) is a shortcut for cvGetRows(arr, submat, row, row+1).
+@param arr Input array
+@param submat Pointer to the resulting sub-array header
+@param start_row Zero-based index of the starting row (inclusive) of the span
+@param end_row Zero-based index of the ending row (exclusive) of the span
+@param delta_row Index step in the row span. That is, the function extracts every delta_row -th
+row from start_row and up to (but not including) end_row .
+ */
+CVAPI(CvMat*) cvGetRows( const CvArr* arr, CvMat* submat,
+                        int start_row, int end_row,
+                        int delta_row CV_DEFAULT(1));
+
+/** @overload
+@param arr Input array
+@param submat Pointer to the resulting sub-array header
+@param row Zero-based index of the selected row
+*/
+CV_INLINE  CvMat*  cvGetRow( const CvArr* arr, CvMat* submat, int row )
+{
+    return cvGetRows( arr, submat, row, row + 1, 1 );
+}
+
+
+/** @brief Returns one of more array columns.
+
+The function returns the header, corresponding to a specified column span of the input array. That
+
+is, no data is copied. Therefore, any modifications of the submatrix will affect the original array.
+If you need to copy the columns, use cvCloneMat. cvGetCol(arr, submat, col) is a shortcut for
+cvGetCols(arr, submat, col, col+1).
+@param arr Input array
+@param submat Pointer to the resulting sub-array header
+@param start_col Zero-based index of the starting column (inclusive) of the span
+@param end_col Zero-based index of the ending column (exclusive) of the span
+ */
+CVAPI(CvMat*) cvGetCols( const CvArr* arr, CvMat* submat,
+                        int start_col, int end_col );
+
+/** @overload
+@param arr Input array
+@param submat Pointer to the resulting sub-array header
+@param col Zero-based index of the selected column
+*/
+CV_INLINE  CvMat*  cvGetCol( const CvArr* arr, CvMat* submat, int col )
+{
+    return cvGetCols( arr, submat, col, col + 1 );
+}
+
+/** @brief Returns one of array diagonals.
+
+The function returns the header, corresponding to a specified diagonal of the input array.
+@param arr Input array
+@param submat Pointer to the resulting sub-array header
+@param diag Index of the array diagonal. Zero value corresponds to the main diagonal, -1
+corresponds to the diagonal above the main, 1 corresponds to the diagonal below the main, and so
+forth.
+ */
+CVAPI(CvMat*) cvGetDiag( const CvArr* arr, CvMat* submat,
+                            int diag CV_DEFAULT(0));
+
+/** low-level scalar <-> raw data conversion functions */
+CVAPI(void) cvScalarToRawData( const CvScalar* scalar, void* data, int type,
+                              int extend_to_12 CV_DEFAULT(0) );
+
+CVAPI(void) cvRawDataToScalar( const void* data, int type, CvScalar* scalar );
+
+/** @brief Creates a new matrix header but does not allocate the matrix data.
+
+The function allocates a header for a multi-dimensional dense array. The array data can further be
+allocated using cvCreateData or set explicitly to user-allocated data via cvSetData.
+@param dims Number of array dimensions
+@param sizes Array of dimension sizes
+@param type Type of array elements, see cvCreateMat
+ */
+CVAPI(CvMatND*)  cvCreateMatNDHeader( int dims, const int* sizes, int type );
+
+/** @brief Creates the header and allocates the data for a multi-dimensional dense array.
+
+This function call is equivalent to the following code:
+@code
+    CvMatND* mat = cvCreateMatNDHeader(dims, sizes, type);
+    cvCreateData(mat);
+@endcode
+@param dims Number of array dimensions. This must not exceed CV_MAX_DIM (32 by default, but can be
+changed at build time).
+@param sizes Array of dimension sizes.
+@param type Type of array elements, see cvCreateMat .
+ */
+CVAPI(CvMatND*)  cvCreateMatND( int dims, const int* sizes, int type );
+
+/** @brief Initializes a pre-allocated multi-dimensional array header.
+
+@param mat A pointer to the array header to be initialized
+@param dims The number of array dimensions
+@param sizes An array of dimension sizes
+@param type Type of array elements, see cvCreateMat
+@param data Optional data pointer assigned to the matrix header
+ */
+CVAPI(CvMatND*)  cvInitMatNDHeader( CvMatND* mat, int dims, const int* sizes,
+                                    int type, void* data CV_DEFAULT(NULL) );
+
+/** @brief Deallocates a multi-dimensional array.
+
+The function decrements the array data reference counter and releases the array header. If the
+reference counter reaches 0, it also deallocates the data. :
+@code
+    if(*mat )
+        cvDecRefData(*mat);
+    cvFree((void**)mat);
+@endcode
+@param mat Double pointer to the array
+ */
+CV_INLINE  void  cvReleaseMatND( CvMatND** mat )
+{
+    cvReleaseMat( (CvMat**)mat );
+}
+
+/** Creates a copy of CvMatND (except, may be, steps) */
+CVAPI(CvMatND*) cvCloneMatND( const CvMatND* mat );
+
+/** @brief Creates sparse array.
+
+The function allocates a multi-dimensional sparse array. Initially the array contain no elements,
+that is PtrND and other related functions will return 0 for every index.
+@param dims Number of array dimensions. In contrast to the dense matrix, the number of dimensions is
+practically unlimited (up to \f$2^{16}\f$ ).
+@param sizes Array of dimension sizes
+@param type Type of array elements. The same as for CvMat
+ */
+CVAPI(CvSparseMat*)  cvCreateSparseMat( int dims, const int* sizes, int type );
+
+/** @brief Deallocates sparse array.
+
+The function releases the sparse array and clears the array pointer upon exit.
+@param mat Double pointer to the array
+ */
+CVAPI(void)  cvReleaseSparseMat( CvSparseMat** mat );
+
+/** Creates a copy of CvSparseMat (except, may be, zero items) */
+CVAPI(CvSparseMat*) cvCloneSparseMat( const CvSparseMat* mat );
+
+/** @brief Initializes sparse array elements iterator.
+
+The function initializes iterator of sparse array elements and returns pointer to the first element,
+or NULL if the array is empty.
+@param mat Input array
+@param mat_iterator Initialized iterator
+ */
+CVAPI(CvSparseNode*) cvInitSparseMatIterator( const CvSparseMat* mat,
+                                              CvSparseMatIterator* mat_iterator );
+
+/** @brief Returns the next sparse matrix element
+
+The function moves iterator to the next sparse matrix element and returns pointer to it. In the
+current version there is no any particular order of the elements, because they are stored in the
+hash table. The sample below demonstrates how to iterate through the sparse matrix:
+@code
+    // print all the non-zero sparse matrix elements and compute their sum
+    double sum = 0;
+    int i, dims = cvGetDims(sparsemat);
+    CvSparseMatIterator it;
+    CvSparseNode* node = cvInitSparseMatIterator(sparsemat, &it);
+
+    for(; node != 0; node = cvGetNextSparseNode(&it))
+    {
+        int* idx = CV_NODE_IDX(array, node);
+        float val = *(float*)CV_NODE_VAL(array, node);
+        printf("M");
+        for(i = 0; i < dims; i++ )
+            printf("[%d]", idx[i]);
+        printf("=%g\n", val);
+
+        sum += val;
+    }
+
+    printf("nTotal sum = %g\n", sum);
+@endcode
+@param mat_iterator Sparse array iterator
+ */
+CV_INLINE CvSparseNode* cvGetNextSparseNode( CvSparseMatIterator* mat_iterator )
+{
+    if( mat_iterator->node->next )
+        return mat_iterator->node = mat_iterator->node->next;
+    else
+    {
+        int idx;
+        for( idx = ++mat_iterator->curidx; idx < mat_iterator->mat->hashsize; idx++ )
+        {
+            CvSparseNode* node = (CvSparseNode*)mat_iterator->mat->hashtable[idx];
+            if( node )
+            {
+                mat_iterator->curidx = idx;
+                return mat_iterator->node = node;
+            }
+        }
+        return NULL;
+    }
+}
+
+
+#define CV_MAX_ARR 10
+
+/** matrix iterator: used for n-ary operations on dense arrays */
+typedef struct CvNArrayIterator
+{
+    int count; /**< number of arrays */
+    int dims; /**< number of dimensions to iterate */
+    CvSize size; /**< maximal common linear size: { width = size, height = 1 } */
+    uchar* ptr[CV_MAX_ARR]; /**< pointers to the array slices */
+    int stack[CV_MAX_DIM]; /**< for internal use */
+    CvMatND* hdr[CV_MAX_ARR]; /**< pointers to the headers of the
+                                 matrices that are processed */
+}
+CvNArrayIterator;
+
+#define CV_NO_DEPTH_CHECK     1
+#define CV_NO_CN_CHECK        2
+#define CV_NO_SIZE_CHECK      4
+
+/** initializes iterator that traverses through several arrays simultaneously
+   (the function together with cvNextArraySlice is used for
+    N-ari element-wise operations) */
+CVAPI(int) cvInitNArrayIterator( int count, CvArr** arrs,
+                                 const CvArr* mask, CvMatND* stubs,
+                                 CvNArrayIterator* array_iterator,
+                                 int flags CV_DEFAULT(0) );
+
+/** returns zero value if iteration is finished, non-zero (slice length) otherwise */
+CVAPI(int) cvNextNArraySlice( CvNArrayIterator* array_iterator );
+
+
+/** @brief Returns type of array elements.
+
+The function returns type of the array elements. In the case of IplImage the type is converted to
+CvMat-like representation. For example, if the image has been created as:
+@code
+    IplImage* img = cvCreateImage(cvSize(640, 480), IPL_DEPTH_8U, 3);
+@endcode
+The code cvGetElemType(img) will return CV_8UC3.
+@param arr Input array
+ */
+CVAPI(int) cvGetElemType( const CvArr* arr );
+
+/** @brief Return number of array dimensions
+
+The function returns the array dimensionality and the array of dimension sizes. In the case of
+IplImage or CvMat it always returns 2 regardless of number of image/matrix rows. For example, the
+following code calculates total number of array elements:
+@code
+    int sizes[CV_MAX_DIM];
+    int i, total = 1;
+    int dims = cvGetDims(arr, size);
+    for(i = 0; i < dims; i++ )
+        total *= sizes[i];
+@endcode
+@param arr Input array
+@param sizes Optional output vector of the array dimension sizes. For 2d arrays the number of rows
+(height) goes first, number of columns (width) next.
+ */
+CVAPI(int) cvGetDims( const CvArr* arr, int* sizes CV_DEFAULT(NULL) );
+
+
+/** @brief Returns array size along the specified dimension.
+
+@param arr Input array
+@param index Zero-based dimension index (for matrices 0 means number of rows, 1 means number of
+columns; for images 0 means height, 1 means width)
+ */
+CVAPI(int) cvGetDimSize( const CvArr* arr, int index );
+
+
+/** @brief Return pointer to a particular array element.
+
+The functions return a pointer to a specific array element. Number of array dimension should match
+to the number of indices passed to the function except for cvPtr1D function that can be used for
+sequential access to 1D, 2D or nD dense arrays.
+
+The functions can be used for sparse arrays as well - if the requested node does not exist they
+create it and set it to zero.
+
+All these as well as other functions accessing array elements ( cvGetND , cvGetRealND , cvSet
+, cvSetND , cvSetRealND ) raise an error in case if the element index is out of range.
+@param arr Input array
+@param idx0 The first zero-based component of the element index
+@param type Optional output parameter: type of matrix elements
+ */
+CVAPI(uchar*) cvPtr1D( const CvArr* arr, int idx0, int* type CV_DEFAULT(NULL));
+/** @overload */
+CVAPI(uchar*) cvPtr2D( const CvArr* arr, int idx0, int idx1, int* type CV_DEFAULT(NULL) );
+/** @overload */
+CVAPI(uchar*) cvPtr3D( const CvArr* arr, int idx0, int idx1, int idx2,
+                      int* type CV_DEFAULT(NULL));
+/** @overload
+@param arr Input array
+@param idx Array of the element indices
+@param type Optional output parameter: type of matrix elements
+@param create_node Optional input parameter for sparse matrices. Non-zero value of the parameter
+means that the requested element is created if it does not exist already.
+@param precalc_hashval Optional input parameter for sparse matrices. If the pointer is not NULL,
+the function does not recalculate the node hash value, but takes it from the specified location.
+It is useful for speeding up pair-wise operations (TODO: provide an example)
+*/
+CVAPI(uchar*) cvPtrND( const CvArr* arr, const int* idx, int* type CV_DEFAULT(NULL),
+                      int create_node CV_DEFAULT(1),
+                      unsigned* precalc_hashval CV_DEFAULT(NULL));
+
+/** @brief Return a specific array element.
+
+The functions return a specific array element. In the case of a sparse array the functions return 0
+if the requested node does not exist (no new node is created by the functions).
+@param arr Input array
+@param idx0 The first zero-based component of the element index
+ */
+CVAPI(CvScalar) cvGet1D( const CvArr* arr, int idx0 );
+/** @overload */
+CVAPI(CvScalar) cvGet2D( const CvArr* arr, int idx0, int idx1 );
+/** @overload */
+CVAPI(CvScalar) cvGet3D( const CvArr* arr, int idx0, int idx1, int idx2 );
+/** @overload
+@param arr Input array
+@param idx Array of the element indices
+*/
+CVAPI(CvScalar) cvGetND( const CvArr* arr, const int* idx );
+
+/** @brief Return a specific element of single-channel 1D, 2D, 3D or nD array.
+
+Returns a specific element of a single-channel array. If the array has multiple channels, a runtime
+error is raised. Note that Get?D functions can be used safely for both single-channel and
+multiple-channel arrays though they are a bit slower.
+
+In the case of a sparse array the functions return 0 if the requested node does not exist (no new
+node is created by the functions).
+@param arr Input array. Must have a single channel.
+@param idx0 The first zero-based component of the element index
+ */
+CVAPI(double) cvGetReal1D( const CvArr* arr, int idx0 );
+/** @overload */
+CVAPI(double) cvGetReal2D( const CvArr* arr, int idx0, int idx1 );
+/** @overload */
+CVAPI(double) cvGetReal3D( const CvArr* arr, int idx0, int idx1, int idx2 );
+/** @overload
+@param arr Input array. Must have a single channel.
+@param idx Array of the element indices
+*/
+CVAPI(double) cvGetRealND( const CvArr* arr, const int* idx );
+
+/** @brief Change the particular array element.
+
+The functions assign the new value to a particular array element. In the case of a sparse array the
+functions create the node if it does not exist yet.
+@param arr Input array
+@param idx0 The first zero-based component of the element index
+@param value The assigned value
+ */
+CVAPI(void) cvSet1D( CvArr* arr, int idx0, CvScalar value );
+/** @overload */
+CVAPI(void) cvSet2D( CvArr* arr, int idx0, int idx1, CvScalar value );
+/** @overload */
+CVAPI(void) cvSet3D( CvArr* arr, int idx0, int idx1, int idx2, CvScalar value );
+/** @overload
+@param arr Input array
+@param idx Array of the element indices
+@param value The assigned value
+*/
+CVAPI(void) cvSetND( CvArr* arr, const int* idx, CvScalar value );
+
+/** @brief Change a specific array element.
+
+The functions assign a new value to a specific element of a single-channel array. If the array has
+multiple channels, a runtime error is raised. Note that the Set\*D function can be used safely for
+both single-channel and multiple-channel arrays, though they are a bit slower.
+
+In the case of a sparse array the functions create the node if it does not yet exist.
+@param arr Input array
+@param idx0 The first zero-based component of the element index
+@param value The assigned value
+ */
+CVAPI(void) cvSetReal1D( CvArr* arr, int idx0, double value );
+/** @overload */
+CVAPI(void) cvSetReal2D( CvArr* arr, int idx0, int idx1, double value );
+/** @overload */
+CVAPI(void) cvSetReal3D( CvArr* arr, int idx0,
+                        int idx1, int idx2, double value );
+/** @overload
+@param arr Input array
+@param idx Array of the element indices
+@param value The assigned value
+*/
+CVAPI(void) cvSetRealND( CvArr* arr, const int* idx, double value );
+
+/** clears element of ND dense array,
+   in case of sparse arrays it deletes the specified node */
+CVAPI(void) cvClearND( CvArr* arr, const int* idx );
+
+/** @brief Returns matrix header for arbitrary array.
+
+The function returns a matrix header for the input array that can be a matrix - CvMat, an image -
+IplImage, or a multi-dimensional dense array - CvMatND (the third option is allowed only if
+allowND != 0) . In the case of matrix the function simply returns the input pointer. In the case of
+IplImage\* or CvMatND it initializes the header structure with parameters of the current image ROI
+and returns &header. Because COI is not supported by CvMat, it is returned separately.
+
+The function provides an easy way to handle both types of arrays - IplImage and CvMat using the same
+code. Input array must have non-zero data pointer, otherwise the function will report an error.
+
+@note If the input array is IplImage with planar data layout and COI set, the function returns the
+pointer to the selected plane and COI == 0. This feature allows user to process IplImage structures
+with planar data layout, even though OpenCV does not support such images.
+@param arr Input array
+@param header Pointer to CvMat structure used as a temporary buffer
+@param coi Optional output parameter for storing COI
+@param allowND If non-zero, the function accepts multi-dimensional dense arrays (CvMatND\*) and
+returns 2D matrix (if CvMatND has two dimensions) or 1D matrix (when CvMatND has 1 dimension or
+more than 2 dimensions). The CvMatND array must be continuous.
+@sa cvGetImage, cvarrToMat.
+ */
+CVAPI(CvMat*) cvGetMat( const CvArr* arr, CvMat* header,
+                       int* coi CV_DEFAULT(NULL),
+                       int allowND CV_DEFAULT(0));
+
+/** @brief Returns image header for arbitrary array.
+
+The function returns the image header for the input array that can be a matrix (CvMat) or image
+(IplImage). In the case of an image the function simply returns the input pointer. In the case of
+CvMat it initializes an image_header structure with the parameters of the input matrix. Note that
+if we transform IplImage to CvMat using cvGetMat and then transform CvMat back to IplImage using
+this function, we will get different headers if the ROI is set in the original image.
+@param arr Input array
+@param image_header Pointer to IplImage structure used as a temporary buffer
+ */
+CVAPI(IplImage*) cvGetImage( const CvArr* arr, IplImage* image_header );
+
+
+/** @brief Changes the shape of a multi-dimensional array without copying the data.
+
+The function is an advanced version of cvReshape that can work with multi-dimensional arrays as
+well (though it can work with ordinary images and matrices) and change the number of dimensions.
+
+Below are the two samples from the cvReshape description rewritten using cvReshapeMatND:
+@code
+    IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3);
+    IplImage gray_img_hdr, *gray_img;
+    gray_img = (IplImage*)cvReshapeMatND(color_img, sizeof(gray_img_hdr), &gray_img_hdr, 1, 0, 0);
+    ...
+    int size[] = { 2, 2, 2 };
+    CvMatND* mat = cvCreateMatND(3, size, CV_32F);
+    CvMat row_header, *row;
+    row = (CvMat*)cvReshapeMatND(mat, sizeof(row_header), &row_header, 0, 1, 0);
+@endcode
+In C, the header file for this function includes a convenient macro cvReshapeND that does away with
+the sizeof_header parameter. So, the lines containing the call to cvReshapeMatND in the examples
+may be replaced as follow:
+@code
+    gray_img = (IplImage*)cvReshapeND(color_img, &gray_img_hdr, 1, 0, 0);
+    ...
+    row = (CvMat*)cvReshapeND(mat, &row_header, 0, 1, 0);
+@endcode
+@param arr Input array
+@param sizeof_header Size of output header to distinguish between IplImage, CvMat and CvMatND
+output headers
+@param header Output header to be filled
+@param new_cn New number of channels. new_cn = 0 means that the number of channels remains
+unchanged.
+@param new_dims New number of dimensions. new_dims = 0 means that the number of dimensions
+remains the same.
+@param new_sizes Array of new dimension sizes. Only new_dims-1 values are used, because the
+total number of elements must remain the same. Thus, if new_dims = 1, new_sizes array is not
+used.
+ */
+CVAPI(CvArr*) cvReshapeMatND( const CvArr* arr,
+                             int sizeof_header, CvArr* header,
+                             int new_cn, int new_dims, int* new_sizes );
+
+#define cvReshapeND( arr, header, new_cn, new_dims, new_sizes )   \
+      cvReshapeMatND( (arr), sizeof(*(header)), (header),         \
+                      (new_cn), (new_dims), (new_sizes))
+
+/** @brief Changes shape of matrix/image without copying data.
+
+The function initializes the CvMat header so that it points to the same data as the original array
+but has a different shape - different number of channels, different number of rows, or both.
+
+The following example code creates one image buffer and two image headers, the first is for a
+320x240x3 image and the second is for a 960x240x1 image:
+@code
+    IplImage* color_img = cvCreateImage(cvSize(320,240), IPL_DEPTH_8U, 3);
+    CvMat gray_mat_hdr;
+    IplImage gray_img_hdr, *gray_img;
+    cvReshape(color_img, &gray_mat_hdr, 1);
+    gray_img = cvGetImage(&gray_mat_hdr, &gray_img_hdr);
+@endcode
+And the next example converts a 3x3 matrix to a single 1x9 vector:
+@code
+    CvMat* mat = cvCreateMat(3, 3, CV_32F);
+    CvMat row_header, *row;
+    row = cvReshape(mat, &row_header, 0, 1);
+@endcode
+@param arr Input array
+@param header Output header to be filled
+@param new_cn New number of channels. 'new_cn = 0' means that the number of channels remains
+unchanged.
+@param new_rows New number of rows. 'new_rows = 0' means that the number of rows remains
+unchanged unless it needs to be changed according to new_cn value.
+*/
+CVAPI(CvMat*) cvReshape( const CvArr* arr, CvMat* header,
+                        int new_cn, int new_rows CV_DEFAULT(0) );
+
+/** Repeats source 2d array several times in both horizontal and
+   vertical direction to fill destination array */
+CVAPI(void) cvRepeat( const CvArr* src, CvArr* dst );
+
+/** @brief Allocates array data
+
+The function allocates image, matrix or multi-dimensional dense array data. Note that in the case of
+matrix types OpenCV allocation functions are used. In the case of IplImage they are used unless
+CV_TURN_ON_IPL_COMPATIBILITY() has been called before. In the latter case IPL functions are used
+to allocate the data.
+@param arr Array header
+ */
+CVAPI(void)  cvCreateData( CvArr* arr );
+
+/** @brief Releases array data.
+
+The function releases the array data. In the case of CvMat or CvMatND it simply calls
+cvDecRefData(), that is the function can not deallocate external data. See also the note to
+cvCreateData .
+@param arr Array header
+ */
+CVAPI(void)  cvReleaseData( CvArr* arr );
+
+/** @brief Assigns user data to the array header.
+
+The function assigns user data to the array header. Header should be initialized before using
+cvCreateMatHeader, cvCreateImageHeader, cvCreateMatNDHeader, cvInitMatHeader,
+cvInitImageHeader or cvInitMatNDHeader.
+@param arr Array header
+@param data User data
+@param step Full row length in bytes
+ */
+CVAPI(void)  cvSetData( CvArr* arr, void* data, int step );
+
+/** @brief Retrieves low-level information about the array.
+
+The function fills output variables with low-level information about the array data. All output
+
+parameters are optional, so some of the pointers may be set to NULL. If the array is IplImage with
+ROI set, the parameters of ROI are returned.
+
+The following example shows how to get access to array elements. It computes absolute values of the
+array elements :
+@code
+    float* data;
+    int step;
+    CvSize size;
+
+    cvGetRawData(array, (uchar**)&data, &step, &size);
+    step /= sizeof(data[0]);
+
+    for(int y = 0; y < size.height; y++, data += step )
+        for(int x = 0; x < size.width; x++ )
+            data[x] = (float)fabs(data[x]);
+@endcode
+@param arr Array header
+@param data Output pointer to the whole image origin or ROI origin if ROI is set
+@param step Output full row length in bytes
+@param roi_size Output ROI size
+ */
+CVAPI(void) cvGetRawData( const CvArr* arr, uchar** data,
+                         int* step CV_DEFAULT(NULL),
+                         CvSize* roi_size CV_DEFAULT(NULL));
+
+/** @brief Returns size of matrix or image ROI.
+
+The function returns number of rows (CvSize::height) and number of columns (CvSize::width) of the
+input matrix or image. In the case of image the size of ROI is returned.
+@param arr array header
+ */
+CVAPI(CvSize) cvGetSize( const CvArr* arr );
+
+/** @brief Copies one array to another.
+
+The function copies selected elements from an input array to an output array:
+
+\f[\texttt{dst} (I)= \texttt{src} (I)  \quad \text{if} \quad \texttt{mask} (I)  \ne 0.\f]
+
+If any of the passed arrays is of IplImage type, then its ROI and COI fields are used. Both arrays
+must have the same type, the same number of dimensions, and the same size. The function can also
+copy sparse arrays (mask is not supported in this case).
+@param src The source array
+@param dst The destination array
+@param mask Operation mask, 8-bit single channel array; specifies elements of the destination array
+to be changed
+ */
+CVAPI(void)  cvCopy( const CvArr* src, CvArr* dst,
+                     const CvArr* mask CV_DEFAULT(NULL) );
+
+/** @brief Sets every element of an array to a given value.
+
+The function copies the scalar value to every selected element of the destination array:
+\f[\texttt{arr} (I)= \texttt{value} \quad \text{if} \quad \texttt{mask} (I)  \ne 0\f]
+If array arr is of IplImage type, then is ROI used, but COI must not be set.
+@param arr The destination array
+@param value Fill value
+@param mask Operation mask, 8-bit single channel array; specifies elements of the destination
+array to be changed
+ */
+CVAPI(void)  cvSet( CvArr* arr, CvScalar value,
+                    const CvArr* mask CV_DEFAULT(NULL) );
+
+/** @brief Clears the array.
+
+The function clears the array. In the case of dense arrays (CvMat, CvMatND or IplImage),
+cvZero(array) is equivalent to cvSet(array,cvScalarAll(0),0). In the case of sparse arrays all the
+elements are removed.
+@param arr Array to be cleared
+ */
+CVAPI(void)  cvSetZero( CvArr* arr );
+#define cvZero  cvSetZero
+
+
+/** Splits a multi-channel array into the set of single-channel arrays or
+   extracts particular [color] plane */
+CVAPI(void)  cvSplit( const CvArr* src, CvArr* dst0, CvArr* dst1,
+                      CvArr* dst2, CvArr* dst3 );
+
+/** Merges a set of single-channel arrays into the single multi-channel array
+   or inserts one particular [color] plane to the array */
+CVAPI(void)  cvMerge( const CvArr* src0, const CvArr* src1,
+                      const CvArr* src2, const CvArr* src3,
+                      CvArr* dst );
+
+/** Copies several channels from input arrays to
+   certain channels of output arrays */
+CVAPI(void)  cvMixChannels( const CvArr** src, int src_count,
+                            CvArr** dst, int dst_count,
+                            const int* from_to, int pair_count );
+
+/** @brief Converts one array to another with optional linear transformation.
+
+The function has several different purposes, and thus has several different names. It copies one
+array to another with optional scaling, which is performed first, and/or optional type conversion,
+performed after:
+
+\f[\texttt{dst} (I) =  \texttt{scale} \texttt{src} (I) + ( \texttt{shift} _0, \texttt{shift} _1,...)\f]
+
+All the channels of multi-channel arrays are processed independently.
+
+The type of conversion is done with rounding and saturation, that is if the result of scaling +
+conversion can not be represented exactly by a value of the destination array element type, it is
+set to the nearest representable value on the real axis.
+@param src Source array
+@param dst Destination array
+@param scale Scale factor
+@param shift Value added to the scaled source array elements
+ */
+CVAPI(void)  cvConvertScale( const CvArr* src, CvArr* dst,
+                             double scale CV_DEFAULT(1),
+                             double shift CV_DEFAULT(0) );
+#define cvCvtScale cvConvertScale
+#define cvScale  cvConvertScale
+#define cvConvert( src, dst )  cvConvertScale( (src), (dst), 1, 0 )
+
+
+/** Performs linear transformation on every source array element,
+   stores absolute value of the result:
+   dst(x,y,c) = abs(scale*src(x,y,c)+shift).
+   destination array must have 8u type.
+   In other cases one may use cvConvertScale + cvAbsDiffS */
+CVAPI(void)  cvConvertScaleAbs( const CvArr* src, CvArr* dst,
+                                double scale CV_DEFAULT(1),
+                                double shift CV_DEFAULT(0) );
+#define cvCvtScaleAbs  cvConvertScaleAbs
+
+
+/** checks termination criteria validity and
+   sets eps to default_eps (if it is not set),
+   max_iter to default_max_iters (if it is not set)
+*/
+CVAPI(CvTermCriteria) cvCheckTermCriteria( CvTermCriteria criteria,
+                                           double default_eps,
+                                           int default_max_iters );
+
+/****************************************************************************************\
+*                   Arithmetic, logic and comparison operations                          *
+\****************************************************************************************/
+
+/** dst(mask) = src1(mask) + src2(mask) */
+CVAPI(void)  cvAdd( const CvArr* src1, const CvArr* src2, CvArr* dst,
+                    const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(mask) = src(mask) + value */
+CVAPI(void)  cvAddS( const CvArr* src, CvScalar value, CvArr* dst,
+                     const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(mask) = src1(mask) - src2(mask) */
+CVAPI(void)  cvSub( const CvArr* src1, const CvArr* src2, CvArr* dst,
+                    const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(mask) = src(mask) - value = src(mask) + (-value) */
+CV_INLINE  void  cvSubS( const CvArr* src, CvScalar value, CvArr* dst,
+                         const CvArr* mask CV_DEFAULT(NULL))
+{
+    cvAddS( src, cvScalar( -value.val[0], -value.val[1], -value.val[2], -value.val[3]),
+            dst, mask );
+}
+
+/** dst(mask) = value - src(mask) */
+CVAPI(void)  cvSubRS( const CvArr* src, CvScalar value, CvArr* dst,
+                      const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(idx) = src1(idx) * src2(idx) * scale
+   (scaled element-wise multiplication of 2 arrays) */
+CVAPI(void)  cvMul( const CvArr* src1, const CvArr* src2,
+                    CvArr* dst, double scale CV_DEFAULT(1) );
+
+/** element-wise division/inversion with scaling:
+    dst(idx) = src1(idx) * scale / src2(idx)
+    or dst(idx) = scale / src2(idx) if src1 == 0 */
+CVAPI(void)  cvDiv( const CvArr* src1, const CvArr* src2,
+                    CvArr* dst, double scale CV_DEFAULT(1));
+
+/** dst = src1 * scale + src2 */
+CVAPI(void)  cvScaleAdd( const CvArr* src1, CvScalar scale,
+                         const CvArr* src2, CvArr* dst );
+#define cvAXPY( A, real_scalar, B, C ) cvScaleAdd(A, cvRealScalar(real_scalar), B, C)
+
+/** dst = src1 * alpha + src2 * beta + gamma */
+CVAPI(void)  cvAddWeighted( const CvArr* src1, double alpha,
+                            const CvArr* src2, double beta,
+                            double gamma, CvArr* dst );
+
+/** @brief Calculates the dot product of two arrays in Euclidean metrics.
+
+The function calculates and returns the Euclidean dot product of two arrays.
+
+\f[src1  \bullet src2 =  \sum _I ( \texttt{src1} (I)  \texttt{src2} (I))\f]
+
+In the case of multiple channel arrays, the results for all channels are accumulated. In particular,
+cvDotProduct(a,a) where a is a complex vector, will return \f$||\texttt{a}||^2\f$. The function can
+process multi-dimensional arrays, row by row, layer by layer, and so on.
+@param src1 The first source array
+@param src2 The second source array
+ */
+CVAPI(double)  cvDotProduct( const CvArr* src1, const CvArr* src2 );
+
+/** dst(idx) = src1(idx) & src2(idx) */
+CVAPI(void) cvAnd( const CvArr* src1, const CvArr* src2,
+                  CvArr* dst, const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(idx) = src(idx) & value */
+CVAPI(void) cvAndS( const CvArr* src, CvScalar value,
+                   CvArr* dst, const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(idx) = src1(idx) | src2(idx) */
+CVAPI(void) cvOr( const CvArr* src1, const CvArr* src2,
+                 CvArr* dst, const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(idx) = src(idx) | value */
+CVAPI(void) cvOrS( const CvArr* src, CvScalar value,
+                  CvArr* dst, const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(idx) = src1(idx) ^ src2(idx) */
+CVAPI(void) cvXor( const CvArr* src1, const CvArr* src2,
+                  CvArr* dst, const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(idx) = src(idx) ^ value */
+CVAPI(void) cvXorS( const CvArr* src, CvScalar value,
+                   CvArr* dst, const CvArr* mask CV_DEFAULT(NULL));
+
+/** dst(idx) = ~src(idx) */
+CVAPI(void) cvNot( const CvArr* src, CvArr* dst );
+
+/** dst(idx) = lower(idx) <= src(idx) < upper(idx) */
+CVAPI(void) cvInRange( const CvArr* src, const CvArr* lower,
+                      const CvArr* upper, CvArr* dst );
+
+/** dst(idx) = lower <= src(idx) < upper */
+CVAPI(void) cvInRangeS( const CvArr* src, CvScalar lower,
+                       CvScalar upper, CvArr* dst );
+
+#define CV_CMP_EQ   0
+#define CV_CMP_GT   1
+#define CV_CMP_GE   2
+#define CV_CMP_LT   3
+#define CV_CMP_LE   4
+#define CV_CMP_NE   5
+
+/** The comparison operation support single-channel arrays only.
+   Destination image should be 8uC1 or 8sC1 */
+
+/** dst(idx) = src1(idx) _cmp_op_ src2(idx) */
+CVAPI(void) cvCmp( const CvArr* src1, const CvArr* src2, CvArr* dst, int cmp_op );
+
+/** dst(idx) = src1(idx) _cmp_op_ value */
+CVAPI(void) cvCmpS( const CvArr* src, double value, CvArr* dst, int cmp_op );
+
+/** dst(idx) = min(src1(idx),src2(idx)) */
+CVAPI(void) cvMin( const CvArr* src1, const CvArr* src2, CvArr* dst );
+
+/** dst(idx) = max(src1(idx),src2(idx)) */
+CVAPI(void) cvMax( const CvArr* src1, const CvArr* src2, CvArr* dst );
+
+/** dst(idx) = min(src(idx),value) */
+CVAPI(void) cvMinS( const CvArr* src, double value, CvArr* dst );
+
+/** dst(idx) = max(src(idx),value) */
+CVAPI(void) cvMaxS( const CvArr* src, double value, CvArr* dst );
+
+/** dst(x,y,c) = abs(src1(x,y,c) - src2(x,y,c)) */
+CVAPI(void) cvAbsDiff( const CvArr* src1, const CvArr* src2, CvArr* dst );
+
+/** dst(x,y,c) = abs(src(x,y,c) - value(c)) */
+CVAPI(void) cvAbsDiffS( const CvArr* src, CvArr* dst, CvScalar value );
+#define cvAbs( src, dst ) cvAbsDiffS( (src), (dst), cvScalarAll(0))
+
+/****************************************************************************************\
+*                                Math operations                                         *
+\****************************************************************************************/
+
+/** Does cartesian->polar coordinates conversion.
+   Either of output components (magnitude or angle) is optional */
+CVAPI(void)  cvCartToPolar( const CvArr* x, const CvArr* y,
+                            CvArr* magnitude, CvArr* angle CV_DEFAULT(NULL),
+                            int angle_in_degrees CV_DEFAULT(0));
+
+/** Does polar->cartesian coordinates conversion.
+   Either of output components (magnitude or angle) is optional.
+   If magnitude is missing it is assumed to be all 1's */
+CVAPI(void)  cvPolarToCart( const CvArr* magnitude, const CvArr* angle,
+                            CvArr* x, CvArr* y,
+                            int angle_in_degrees CV_DEFAULT(0));
+
+/** Does powering: dst(idx) = src(idx)^power */
+CVAPI(void)  cvPow( const CvArr* src, CvArr* dst, double power );
+
+/** Does exponention: dst(idx) = exp(src(idx)).
+   Overflow is not handled yet. Underflow is handled.
+   Maximal relative error is ~7e-6 for single-precision input */
+CVAPI(void)  cvExp( const CvArr* src, CvArr* dst );
+
+/** Calculates natural logarithms: dst(idx) = log(abs(src(idx))).
+   Logarithm of 0 gives large negative number(~-700)
+   Maximal relative error is ~3e-7 for single-precision output
+*/
+CVAPI(void)  cvLog( const CvArr* src, CvArr* dst );
+
+/** Fast arctangent calculation */
+CVAPI(float) cvFastArctan( float y, float x );
+
+/** Fast cubic root calculation */
+CVAPI(float)  cvCbrt( float value );
+
+#define  CV_CHECK_RANGE    1
+#define  CV_CHECK_QUIET    2
+/** Checks array values for NaNs, Infs or simply for too large numbers
+   (if CV_CHECK_RANGE is set). If CV_CHECK_QUIET is set,
+   no runtime errors is raised (function returns zero value in case of "bad" values).
+   Otherwise cvError is called */
+CVAPI(int)  cvCheckArr( const CvArr* arr, int flags CV_DEFAULT(0),
+                        double min_val CV_DEFAULT(0), double max_val CV_DEFAULT(0));
+#define cvCheckArray cvCheckArr
+
+#define CV_RAND_UNI      0
+#define CV_RAND_NORMAL   1
+
+/** @brief Fills an array with random numbers and updates the RNG state.
+
+The function fills the destination array with uniformly or normally distributed random numbers.
+@param rng CvRNG state initialized by cvRNG
+@param arr The destination array
+@param dist_type Distribution type
+> -   **CV_RAND_UNI** uniform distribution
+> -   **CV_RAND_NORMAL** normal or Gaussian distribution
+@param param1 The first parameter of the distribution. In the case of a uniform distribution it is
+the inclusive lower boundary of the random numbers range. In the case of a normal distribution it
+is the mean value of the random numbers.
+@param param2 The second parameter of the distribution. In the case of a uniform distribution it
+is the exclusive upper boundary of the random numbers range. In the case of a normal distribution
+it is the standard deviation of the random numbers.
+@sa randu, randn, RNG::fill.
+ */
+CVAPI(void) cvRandArr( CvRNG* rng, CvArr* arr, int dist_type,
+                      CvScalar param1, CvScalar param2 );
+
+CVAPI(void) cvRandShuffle( CvArr* mat, CvRNG* rng,
+                           double iter_factor CV_DEFAULT(1.));
+
+#define CV_SORT_EVERY_ROW 0
+#define CV_SORT_EVERY_COLUMN 1
+#define CV_SORT_ASCENDING 0
+#define CV_SORT_DESCENDING 16
+
+CVAPI(void) cvSort( const CvArr* src, CvArr* dst CV_DEFAULT(NULL),
+                    CvArr* idxmat CV_DEFAULT(NULL),
+                    int flags CV_DEFAULT(0));
+
+/** Finds real roots of a cubic equation */
+CVAPI(int) cvSolveCubic( const CvMat* coeffs, CvMat* roots );
+
+/** Finds all real and complex roots of a polynomial equation */
+CVAPI(void) cvSolvePoly(const CvMat* coeffs, CvMat *roots2,
+      int maxiter CV_DEFAULT(20), int fig CV_DEFAULT(100));
+
+/****************************************************************************************\
+*                                Matrix operations                                       *
+\****************************************************************************************/
+
+/** @brief Calculates the cross product of two 3D vectors.
+
+The function calculates the cross product of two 3D vectors:
+\f[\texttt{dst} =  \texttt{src1} \times \texttt{src2}\f]
+or:
+\f[\begin{array}{l} \texttt{dst} _1 =  \texttt{src1} _2  \texttt{src2} _3 -  \texttt{src1} _3  \texttt{src2} _2 \\ \texttt{dst} _2 =  \texttt{src1} _3  \texttt{src2} _1 -  \texttt{src1} _1  \texttt{src2} _3 \\ \texttt{dst} _3 =  \texttt{src1} _1  \texttt{src2} _2 -  \texttt{src1} _2  \texttt{src2} _1 \end{array}\f]
+@param src1 The first source vector
+@param src2 The second source vector
+@param dst The destination vector
+ */
+CVAPI(void)  cvCrossProduct( const CvArr* src1, const CvArr* src2, CvArr* dst );
+
+/** Matrix transform: dst = A*B + C, C is optional */
+#define cvMatMulAdd( src1, src2, src3, dst ) cvGEMM( (src1), (src2), 1., (src3), 1., (dst), 0 )
+#define cvMatMul( src1, src2, dst )  cvMatMulAdd( (src1), (src2), NULL, (dst))
+
+#define CV_GEMM_A_T 1
+#define CV_GEMM_B_T 2
+#define CV_GEMM_C_T 4
+/** Extended matrix transform:
+   dst = alpha*op(A)*op(B) + beta*op(C), where op(X) is X or X^T */
+CVAPI(void)  cvGEMM( const CvArr* src1, const CvArr* src2, double alpha,
+                     const CvArr* src3, double beta, CvArr* dst,
+                     int tABC CV_DEFAULT(0));
+#define cvMatMulAddEx cvGEMM
+
+/** Transforms each element of source array and stores
+   resultant vectors in destination array */
+CVAPI(void)  cvTransform( const CvArr* src, CvArr* dst,
+                          const CvMat* transmat,
+                          const CvMat* shiftvec CV_DEFAULT(NULL));
+#define cvMatMulAddS cvTransform
+
+/** Does perspective transform on every element of input array */
+CVAPI(void)  cvPerspectiveTransform( const CvArr* src, CvArr* dst,
+                                     const CvMat* mat );
+
+/** Calculates (A-delta)*(A-delta)^T (order=0) or (A-delta)^T*(A-delta) (order=1) */
+CVAPI(void) cvMulTransposed( const CvArr* src, CvArr* dst, int order,
+                             const CvArr* delta CV_DEFAULT(NULL),
+                             double scale CV_DEFAULT(1.) );
+
+/** Transposes matrix. Square matrices can be transposed in-place */
+CVAPI(void)  cvTranspose( const CvArr* src, CvArr* dst );
+#define cvT cvTranspose
+
+/** Completes the symmetric matrix from the lower (LtoR=0) or from the upper (LtoR!=0) part */
+CVAPI(void)  cvCompleteSymm( CvMat* matrix, int LtoR CV_DEFAULT(0) );
+
+/** Mirror array data around horizontal (flip=0),
+   vertical (flip=1) or both(flip=-1) axises:
+   cvFlip(src) flips images vertically and sequences horizontally (inplace) */
+CVAPI(void)  cvFlip( const CvArr* src, CvArr* dst CV_DEFAULT(NULL),
+                     int flip_mode CV_DEFAULT(0));
+#define cvMirror cvFlip
+
+
+#define CV_SVD_MODIFY_A   1
+#define CV_SVD_U_T        2
+#define CV_SVD_V_T        4
+
+/** Performs Singular Value Decomposition of a matrix */
+CVAPI(void)   cvSVD( CvArr* A, CvArr* W, CvArr* U CV_DEFAULT(NULL),
+                     CvArr* V CV_DEFAULT(NULL), int flags CV_DEFAULT(0));
+
+/** Performs Singular Value Back Substitution (solves A*X = B):
+   flags must be the same as in cvSVD */
+CVAPI(void)   cvSVBkSb( const CvArr* W, const CvArr* U,
+                        const CvArr* V, const CvArr* B,
+                        CvArr* X, int flags );
+
+#define CV_LU  0
+#define CV_SVD 1
+#define CV_SVD_SYM 2
+#define CV_CHOLESKY 3
+#define CV_QR  4
+#define CV_NORMAL 16
+
+/** Inverts matrix */
+CVAPI(double)  cvInvert( const CvArr* src, CvArr* dst,
+                         int method CV_DEFAULT(CV_LU));
+#define cvInv cvInvert
+
+/** Solves linear system (src1)*(dst) = (src2)
+   (returns 0 if src1 is a singular and CV_LU method is used) */
+CVAPI(int)  cvSolve( const CvArr* src1, const CvArr* src2, CvArr* dst,
+                     int method CV_DEFAULT(CV_LU));
+
+/** Calculates determinant of input matrix */
+CVAPI(double) cvDet( const CvArr* mat );
+
+/** Calculates trace of the matrix (sum of elements on the main diagonal) */
+CVAPI(CvScalar) cvTrace( const CvArr* mat );
+
+/** Finds eigen values and vectors of a symmetric matrix */
+CVAPI(void)  cvEigenVV( CvArr* mat, CvArr* evects, CvArr* evals,
+                        double eps CV_DEFAULT(0),
+                        int lowindex CV_DEFAULT(-1),
+                        int highindex CV_DEFAULT(-1));
+
+///* Finds selected eigen values and vectors of a symmetric matrix */
+//CVAPI(void)  cvSelectedEigenVV( CvArr* mat, CvArr* evects, CvArr* evals,
+//                                int lowindex, int highindex );
+
+/** Makes an identity matrix (mat_ij = i == j) */
+CVAPI(void)  cvSetIdentity( CvArr* mat, CvScalar value CV_DEFAULT(cvRealScalar(1)) );
+
+/** Fills matrix with given range of numbers */
+CVAPI(CvArr*)  cvRange( CvArr* mat, double start, double end );
+
+/**   @anchor core_c_CovarFlags
+@name Flags for cvCalcCovarMatrix
+@see cvCalcCovarMatrix
+  @{
+*/
+
+/** flag for cvCalcCovarMatrix, transpose([v1-avg, v2-avg,...]) * [v1-avg,v2-avg,...] */
+#define CV_COVAR_SCRAMBLED 0
+
+/** flag for cvCalcCovarMatrix, [v1-avg, v2-avg,...] * transpose([v1-avg,v2-avg,...]) */
+#define CV_COVAR_NORMAL    1
+
+/** flag for cvCalcCovarMatrix, do not calc average (i.e. mean vector) - use the input vector instead
+   (useful for calculating covariance matrix by parts) */
+#define CV_COVAR_USE_AVG   2
+
+/** flag for cvCalcCovarMatrix, scale the covariance matrix coefficients by number of the vectors */
+#define CV_COVAR_SCALE     4
+
+/** flag for cvCalcCovarMatrix, all the input vectors are stored in a single matrix, as its rows */
+#define CV_COVAR_ROWS      8
+
+/** flag for cvCalcCovarMatrix, all the input vectors are stored in a single matrix, as its columns */
+#define CV_COVAR_COLS     16
+
+/** @} */
+
+/** Calculates covariation matrix for a set of vectors
+@see @ref core_c_CovarFlags "flags"
+*/
+CVAPI(void)  cvCalcCovarMatrix( const CvArr** vects, int count,
+                                CvArr* cov_mat, CvArr* avg, int flags );
+
+#define CV_PCA_DATA_AS_ROW 0
+#define CV_PCA_DATA_AS_COL 1
+#define CV_PCA_USE_AVG 2
+CVAPI(void)  cvCalcPCA( const CvArr* data, CvArr* mean,
+                        CvArr* eigenvals, CvArr* eigenvects, int flags );
+
+CVAPI(void)  cvProjectPCA( const CvArr* data, const CvArr* mean,
+                           const CvArr* eigenvects, CvArr* result );
+
+CVAPI(void)  cvBackProjectPCA( const CvArr* proj, const CvArr* mean,
+                               const CvArr* eigenvects, CvArr* result );
+
+/** Calculates Mahalanobis(weighted) distance */
+CVAPI(double)  cvMahalanobis( const CvArr* vec1, const CvArr* vec2, const CvArr* mat );
+#define cvMahalonobis  cvMahalanobis
+
+/****************************************************************************************\
+*                                    Array Statistics                                    *
+\****************************************************************************************/
+
+/** Finds sum of array elements */
+CVAPI(CvScalar)  cvSum( const CvArr* arr );
+
+/** Calculates number of non-zero pixels */
+CVAPI(int)  cvCountNonZero( const CvArr* arr );
+
+/** Calculates mean value of array elements */
+CVAPI(CvScalar)  cvAvg( const CvArr* arr, const CvArr* mask CV_DEFAULT(NULL) );
+
+/** Calculates mean and standard deviation of pixel values */
+CVAPI(void)  cvAvgSdv( const CvArr* arr, CvScalar* mean, CvScalar* std_dev,
+                       const CvArr* mask CV_DEFAULT(NULL) );
+
+/** Finds global minimum, maximum and their positions */
+CVAPI(void)  cvMinMaxLoc( const CvArr* arr, double* min_val, double* max_val,
+                          CvPoint* min_loc CV_DEFAULT(NULL),
+                          CvPoint* max_loc CV_DEFAULT(NULL),
+                          const CvArr* mask CV_DEFAULT(NULL) );
+
+/** @anchor core_c_NormFlags
+  @name Flags for cvNorm and cvNormalize
+  @{
+*/
+#define CV_C            1
+#define CV_L1           2
+#define CV_L2           4
+#define CV_NORM_MASK    7
+#define CV_RELATIVE     8
+#define CV_DIFF         16
+#define CV_MINMAX       32
+
+#define CV_DIFF_C       (CV_DIFF | CV_C)
+#define CV_DIFF_L1      (CV_DIFF | CV_L1)
+#define CV_DIFF_L2      (CV_DIFF | CV_L2)
+#define CV_RELATIVE_C   (CV_RELATIVE | CV_C)
+#define CV_RELATIVE_L1  (CV_RELATIVE | CV_L1)
+#define CV_RELATIVE_L2  (CV_RELATIVE | CV_L2)
+/** @} */
+
+/** Finds norm, difference norm or relative difference norm for an array (or two arrays)
+@see ref core_c_NormFlags "flags"
+*/
+CVAPI(double)  cvNorm( const CvArr* arr1, const CvArr* arr2 CV_DEFAULT(NULL),
+                       int norm_type CV_DEFAULT(CV_L2),
+                       const CvArr* mask CV_DEFAULT(NULL) );
+
+/** @see ref core_c_NormFlags "flags" */
+CVAPI(void)  cvNormalize( const CvArr* src, CvArr* dst,
+                          double a CV_DEFAULT(1.), double b CV_DEFAULT(0.),
+                          int norm_type CV_DEFAULT(CV_L2),
+                          const CvArr* mask CV_DEFAULT(NULL) );
+
+/** @anchor core_c_ReduceFlags
+  @name Flags for cvReduce
+  @{
+*/
+#define CV_REDUCE_SUM 0
+#define CV_REDUCE_AVG 1
+#define CV_REDUCE_MAX 2
+#define CV_REDUCE_MIN 3
+/** @} */
+
+/** @see @ref core_c_ReduceFlags "flags" */
+CVAPI(void)  cvReduce( const CvArr* src, CvArr* dst, int dim CV_DEFAULT(-1),
+                       int op CV_DEFAULT(CV_REDUCE_SUM) );
+
+/****************************************************************************************\
+*                      Discrete Linear Transforms and Related Functions                  *
+\****************************************************************************************/
+
+/** @anchor core_c_DftFlags
+  @name Flags for cvDFT, cvDCT and cvMulSpectrums
+  @{
+  */
+#define CV_DXT_FORWARD  0
+#define CV_DXT_INVERSE  1
+#define CV_DXT_SCALE    2 /**< divide result by size of array */
+#define CV_DXT_INV_SCALE (CV_DXT_INVERSE + CV_DXT_SCALE)
+#define CV_DXT_INVERSE_SCALE CV_DXT_INV_SCALE
+#define CV_DXT_ROWS     4 /**< transform each row individually */
+#define CV_DXT_MUL_CONJ 8 /**< conjugate the second argument of cvMulSpectrums */
+/** @} */
+
+/** Discrete Fourier Transform:
+    complex->complex,
+    real->ccs (forward),
+    ccs->real (inverse)
+@see core_c_DftFlags "flags"
+*/
+CVAPI(void)  cvDFT( const CvArr* src, CvArr* dst, int flags,
+                    int nonzero_rows CV_DEFAULT(0) );
+#define cvFFT cvDFT
+
+/** Multiply results of DFTs: DFT(X)*DFT(Y) or DFT(X)*conj(DFT(Y))
+@see core_c_DftFlags "flags"
+*/
+CVAPI(void)  cvMulSpectrums( const CvArr* src1, const CvArr* src2,
+                             CvArr* dst, int flags );
+
+/** Finds optimal DFT vector size >= size0 */
+CVAPI(int)  cvGetOptimalDFTSize( int size0 );
+
+/** Discrete Cosine Transform
+@see core_c_DftFlags "flags"
+*/
+CVAPI(void)  cvDCT( const CvArr* src, CvArr* dst, int flags );
+
+/****************************************************************************************\
+*                              Dynamic data structures                                   *
+\****************************************************************************************/
+
+/** Calculates length of sequence slice (with support of negative indices). */
+CVAPI(int) cvSliceLength( CvSlice slice, const CvSeq* seq );
+
+
+/** Creates new memory storage.
+   block_size == 0 means that default,
+   somewhat optimal size, is used (currently, it is 64K) */
+CVAPI(CvMemStorage*)  cvCreateMemStorage( int block_size CV_DEFAULT(0));
+
+
+/** Creates a memory storage that will borrow memory blocks from parent storage */
+CVAPI(CvMemStorage*)  cvCreateChildMemStorage( CvMemStorage* parent );
+
+
+/** Releases memory storage. All the children of a parent must be released before
+   the parent. A child storage returns all the blocks to parent when it is released */
+CVAPI(void)  cvReleaseMemStorage( CvMemStorage** storage );
+
+
+/** Clears memory storage. This is the only way(!!!) (besides cvRestoreMemStoragePos)
+   to reuse memory allocated for the storage - cvClearSeq,cvClearSet ...
+   do not free any memory.
+   A child storage returns all the blocks to the parent when it is cleared */
+CVAPI(void)  cvClearMemStorage( CvMemStorage* storage );
+
+/** Remember a storage "free memory" position */
+CVAPI(void)  cvSaveMemStoragePos( const CvMemStorage* storage, CvMemStoragePos* pos );
+
+/** Restore a storage "free memory" position */
+CVAPI(void)  cvRestoreMemStoragePos( CvMemStorage* storage, CvMemStoragePos* pos );
+
+/** Allocates continuous buffer of the specified size in the storage */
+CVAPI(void*) cvMemStorageAlloc( CvMemStorage* storage, size_t size );
+
+/** Allocates string in memory storage */
+//CVAPI(CvString) cvMemStorageAllocString( CvMemStorage* storage, const char* ptr,
+//                                         int len CV_DEFAULT(-1) );
+
+/** Creates new empty sequence that will reside in the specified storage */
+CVAPI(CvSeq*)  cvCreateSeq( int seq_flags, size_t header_size,
+                            size_t elem_size, CvMemStorage* storage );
+
+/** Changes default size (granularity) of sequence blocks.
+   The default size is ~1Kbyte */
+CVAPI(void)  cvSetSeqBlockSize( CvSeq* seq, int delta_elems );
+
+
+/** Adds new element to the end of sequence. Returns pointer to the element */
+CVAPI(schar*)  cvSeqPush( CvSeq* seq, const void* element CV_DEFAULT(NULL));
+
+
+/** Adds new element to the beginning of sequence. Returns pointer to it */
+CVAPI(schar*)  cvSeqPushFront( CvSeq* seq, const void* element CV_DEFAULT(NULL));
+
+
+/** Removes the last element from sequence and optionally saves it */
+CVAPI(void)  cvSeqPop( CvSeq* seq, void* element CV_DEFAULT(NULL));
+
+
+/** Removes the first element from sequence and optioanally saves it */
+CVAPI(void)  cvSeqPopFront( CvSeq* seq, void* element CV_DEFAULT(NULL));
+
+
+#define CV_FRONT 1
+#define CV_BACK 0
+/** Adds several new elements to the end of sequence */
+CVAPI(void)  cvSeqPushMulti( CvSeq* seq, const void* elements,
+                             int count, int in_front CV_DEFAULT(0) );
+
+/** Removes several elements from the end of sequence and optionally saves them */
+CVAPI(void)  cvSeqPopMulti( CvSeq* seq, void* elements,
+                            int count, int in_front CV_DEFAULT(0) );
+
+/** Inserts a new element in the middle of sequence.
+   cvSeqInsert(seq,0,elem) == cvSeqPushFront(seq,elem) */
+CVAPI(schar*)  cvSeqInsert( CvSeq* seq, int before_index,
+                            const void* element CV_DEFAULT(NULL));
+
+/** Removes specified sequence element */
+CVAPI(void)  cvSeqRemove( CvSeq* seq, int index );
+
+
+/** Removes all the elements from the sequence. The freed memory
+   can be reused later only by the same sequence unless cvClearMemStorage
+   or cvRestoreMemStoragePos is called */
+CVAPI(void)  cvClearSeq( CvSeq* seq );
+
+
+/** Retrieves pointer to specified sequence element.
+   Negative indices are supported and mean counting from the end
+   (e.g -1 means the last sequence element) */
+CVAPI(schar*)  cvGetSeqElem( const CvSeq* seq, int index );
+
+/** Calculates index of the specified sequence element.
+   Returns -1 if element does not belong to the sequence */
+CVAPI(int)  cvSeqElemIdx( const CvSeq* seq, const void* element,
+                         CvSeqBlock** block CV_DEFAULT(NULL) );
+
+/** Initializes sequence writer. The new elements will be added to the end of sequence */
+CVAPI(void)  cvStartAppendToSeq( CvSeq* seq, CvSeqWriter* writer );
+
+
+/** Combination of cvCreateSeq and cvStartAppendToSeq */
+CVAPI(void)  cvStartWriteSeq( int seq_flags, int header_size,
+                              int elem_size, CvMemStorage* storage,
+                              CvSeqWriter* writer );
+
+/** Closes sequence writer, updates sequence header and returns pointer
+   to the resultant sequence
+   (which may be useful if the sequence was created using cvStartWriteSeq))
+*/
+CVAPI(CvSeq*)  cvEndWriteSeq( CvSeqWriter* writer );
+
+
+/** Updates sequence header. May be useful to get access to some of previously
+   written elements via cvGetSeqElem or sequence reader */
+CVAPI(void)   cvFlushSeqWriter( CvSeqWriter* writer );
+
+
+/** Initializes sequence reader.
+   The sequence can be read in forward or backward direction */
+CVAPI(void) cvStartReadSeq( const CvSeq* seq, CvSeqReader* reader,
+                           int reverse CV_DEFAULT(0) );
+
+
+/** Returns current sequence reader position (currently observed sequence element) */
+CVAPI(int)  cvGetSeqReaderPos( CvSeqReader* reader );
+
+
+/** Changes sequence reader position. It may seek to an absolute or
+   to relative to the current position */
+CVAPI(void)   cvSetSeqReaderPos( CvSeqReader* reader, int index,
+                                 int is_relative CV_DEFAULT(0));
+
+/** Copies sequence content to a continuous piece of memory */
+CVAPI(void*)  cvCvtSeqToArray( const CvSeq* seq, void* elements,
+                               CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ) );
+
+/** Creates sequence header for array.
+   After that all the operations on sequences that do not alter the content
+   can be applied to the resultant sequence */
+CVAPI(CvSeq*) cvMakeSeqHeaderForArray( int seq_type, int header_size,
+                                       int elem_size, void* elements, int total,
+                                       CvSeq* seq, CvSeqBlock* block );
+
+/** Extracts sequence slice (with or without copying sequence elements) */
+CVAPI(CvSeq*) cvSeqSlice( const CvSeq* seq, CvSlice slice,
+                         CvMemStorage* storage CV_DEFAULT(NULL),
+                         int copy_data CV_DEFAULT(0));
+
+CV_INLINE CvSeq* cvCloneSeq( const CvSeq* seq, CvMemStorage* storage CV_DEFAULT(NULL))
+{
+    return cvSeqSlice( seq, CV_WHOLE_SEQ, storage, 1 );
+}
+
+/** Removes sequence slice */
+CVAPI(void)  cvSeqRemoveSlice( CvSeq* seq, CvSlice slice );
+
+/** Inserts a sequence or array into another sequence */
+CVAPI(void)  cvSeqInsertSlice( CvSeq* seq, int before_index, const CvArr* from_arr );
+
+/** a < b ? -1 : a > b ? 1 : 0 */
+typedef int (CV_CDECL* CvCmpFunc)(const void* a, const void* b, void* userdata );
+
+/** Sorts sequence in-place given element comparison function */
+CVAPI(void) cvSeqSort( CvSeq* seq, CvCmpFunc func, void* userdata CV_DEFAULT(NULL) );
+
+/** Finds element in a [sorted] sequence */
+CVAPI(schar*) cvSeqSearch( CvSeq* seq, const void* elem, CvCmpFunc func,
+                           int is_sorted, int* elem_idx,
+                           void* userdata CV_DEFAULT(NULL) );
+
+/** Reverses order of sequence elements in-place */
+CVAPI(void) cvSeqInvert( CvSeq* seq );
+
+/** Splits sequence into one or more equivalence classes using the specified criteria */
+CVAPI(int)  cvSeqPartition( const CvSeq* seq, CvMemStorage* storage,
+                            CvSeq** labels, CvCmpFunc is_equal, void* userdata );
+
+/************ Internal sequence functions ************/
+CVAPI(void)  cvChangeSeqBlock( void* reader, int direction );
+CVAPI(void)  cvCreateSeqBlock( CvSeqWriter* writer );
+
+
+/** Creates a new set */
+CVAPI(CvSet*)  cvCreateSet( int set_flags, int header_size,
+                            int elem_size, CvMemStorage* storage );
+
+/** Adds new element to the set and returns pointer to it */
+CVAPI(int)  cvSetAdd( CvSet* set_header, CvSetElem* elem CV_DEFAULT(NULL),
+                      CvSetElem** inserted_elem CV_DEFAULT(NULL) );
+
+/** Fast variant of cvSetAdd */
+CV_INLINE  CvSetElem* cvSetNew( CvSet* set_header )
+{
+    CvSetElem* elem = set_header->free_elems;
+    if( elem )
+    {
+        set_header->free_elems = elem->next_free;
+        elem->flags = elem->flags & CV_SET_ELEM_IDX_MASK;
+        set_header->active_count++;
+    }
+    else
+        cvSetAdd( set_header, NULL, &elem );
+    return elem;
+}
+
+/** Removes set element given its pointer */
+CV_INLINE  void cvSetRemoveByPtr( CvSet* set_header, void* elem )
+{
+    CvSetElem* _elem = (CvSetElem*)elem;
+    assert( _elem->flags >= 0 /*&& (elem->flags & CV_SET_ELEM_IDX_MASK) < set_header->total*/ );
+    _elem->next_free = set_header->free_elems;
+    _elem->flags = (_elem->flags & CV_SET_ELEM_IDX_MASK) | CV_SET_ELEM_FREE_FLAG;
+    set_header->free_elems = _elem;
+    set_header->active_count--;
+}
+
+/** Removes element from the set by its index  */
+CVAPI(void)   cvSetRemove( CvSet* set_header, int index );
+
+/** Returns a set element by index. If the element doesn't belong to the set,
+   NULL is returned */
+CV_INLINE CvSetElem* cvGetSetElem( const CvSet* set_header, int idx )
+{
+    CvSetElem* elem = (CvSetElem*)(void *)cvGetSeqElem( (CvSeq*)set_header, idx );
+    return elem && CV_IS_SET_ELEM( elem ) ? elem : 0;
+}
+
+/** Removes all the elements from the set */
+CVAPI(void)  cvClearSet( CvSet* set_header );
+
+/** Creates new graph */
+CVAPI(CvGraph*)  cvCreateGraph( int graph_flags, int header_size,
+                                int vtx_size, int edge_size,
+                                CvMemStorage* storage );
+
+/** Adds new vertex to the graph */
+CVAPI(int)  cvGraphAddVtx( CvGraph* graph, const CvGraphVtx* vtx CV_DEFAULT(NULL),
+                           CvGraphVtx** inserted_vtx CV_DEFAULT(NULL) );
+
+
+/** Removes vertex from the graph together with all incident edges */
+CVAPI(int)  cvGraphRemoveVtx( CvGraph* graph, int index );
+CVAPI(int)  cvGraphRemoveVtxByPtr( CvGraph* graph, CvGraphVtx* vtx );
+
+
+/** Link two vertices specified by indices or pointers if they
+   are not connected or return pointer to already existing edge
+   connecting the vertices.
+   Functions return 1 if a new edge was created, 0 otherwise */
+CVAPI(int)  cvGraphAddEdge( CvGraph* graph,
+                            int start_idx, int end_idx,
+                            const CvGraphEdge* edge CV_DEFAULT(NULL),
+                            CvGraphEdge** inserted_edge CV_DEFAULT(NULL) );
+
+CVAPI(int)  cvGraphAddEdgeByPtr( CvGraph* graph,
+                               CvGraphVtx* start_vtx, CvGraphVtx* end_vtx,
+                               const CvGraphEdge* edge CV_DEFAULT(NULL),
+                               CvGraphEdge** inserted_edge CV_DEFAULT(NULL) );
+
+/** Remove edge connecting two vertices */
+CVAPI(void)  cvGraphRemoveEdge( CvGraph* graph, int start_idx, int end_idx );
+CVAPI(void)  cvGraphRemoveEdgeByPtr( CvGraph* graph, CvGraphVtx* start_vtx,
+                                     CvGraphVtx* end_vtx );
+
+/** Find edge connecting two vertices */
+CVAPI(CvGraphEdge*)  cvFindGraphEdge( const CvGraph* graph, int start_idx, int end_idx );
+CVAPI(CvGraphEdge*)  cvFindGraphEdgeByPtr( const CvGraph* graph,
+                                           const CvGraphVtx* start_vtx,
+                                           const CvGraphVtx* end_vtx );
+#define cvGraphFindEdge cvFindGraphEdge
+#define cvGraphFindEdgeByPtr cvFindGraphEdgeByPtr
+
+/** Remove all vertices and edges from the graph */
+CVAPI(void)  cvClearGraph( CvGraph* graph );
+
+
+/** Count number of edges incident to the vertex */
+CVAPI(int)  cvGraphVtxDegree( const CvGraph* graph, int vtx_idx );
+CVAPI(int)  cvGraphVtxDegreeByPtr( const CvGraph* graph, const CvGraphVtx* vtx );
+
+
+/** Retrieves graph vertex by given index */
+#define cvGetGraphVtx( graph, idx ) (CvGraphVtx*)cvGetSetElem((CvSet*)(graph), (idx))
+
+/** Retrieves index of a graph vertex given its pointer */
+#define cvGraphVtxIdx( graph, vtx ) ((vtx)->flags & CV_SET_ELEM_IDX_MASK)
+
+/** Retrieves index of a graph edge given its pointer */
+#define cvGraphEdgeIdx( graph, edge ) ((edge)->flags & CV_SET_ELEM_IDX_MASK)
+
+#define cvGraphGetVtxCount( graph ) ((graph)->active_count)
+#define cvGraphGetEdgeCount( graph ) ((graph)->edges->active_count)
+
+#define  CV_GRAPH_VERTEX        1
+#define  CV_GRAPH_TREE_EDGE     2
+#define  CV_GRAPH_BACK_EDGE     4
+#define  CV_GRAPH_FORWARD_EDGE  8
+#define  CV_GRAPH_CROSS_EDGE    16
+#define  CV_GRAPH_ANY_EDGE      30
+#define  CV_GRAPH_NEW_TREE      32
+#define  CV_GRAPH_BACKTRACKING  64
+#define  CV_GRAPH_OVER          -1
+
+#define  CV_GRAPH_ALL_ITEMS    -1
+
+/** flags for graph vertices and edges */
+#define  CV_GRAPH_ITEM_VISITED_FLAG  (1 << 30)
+#define  CV_IS_GRAPH_VERTEX_VISITED(vtx) \
+    (((CvGraphVtx*)(vtx))->flags & CV_GRAPH_ITEM_VISITED_FLAG)
+#define  CV_IS_GRAPH_EDGE_VISITED(edge) \
+    (((CvGraphEdge*)(edge))->flags & CV_GRAPH_ITEM_VISITED_FLAG)
+#define  CV_GRAPH_SEARCH_TREE_NODE_FLAG   (1 << 29)
+#define  CV_GRAPH_FORWARD_EDGE_FLAG       (1 << 28)
+
+typedef struct CvGraphScanner
+{
+    CvGraphVtx* vtx;       /* current graph vertex (or current edge origin) */
+    CvGraphVtx* dst;       /* current graph edge destination vertex */
+    CvGraphEdge* edge;     /* current edge */
+
+    CvGraph* graph;        /* the graph */
+    CvSeq*   stack;        /* the graph vertex stack */
+    int      index;        /* the lower bound of certainly visited vertices */
+    int      mask;         /* event mask */
+}
+CvGraphScanner;
+
+/** Creates new graph scanner. */
+CVAPI(CvGraphScanner*)  cvCreateGraphScanner( CvGraph* graph,
+                                             CvGraphVtx* vtx CV_DEFAULT(NULL),
+                                             int mask CV_DEFAULT(CV_GRAPH_ALL_ITEMS));
+
+/** Releases graph scanner. */
+CVAPI(void) cvReleaseGraphScanner( CvGraphScanner** scanner );
+
+/** Get next graph element */
+CVAPI(int)  cvNextGraphItem( CvGraphScanner* scanner );
+
+/** Creates a copy of graph */
+CVAPI(CvGraph*) cvCloneGraph( const CvGraph* graph, CvMemStorage* storage );
+
+
+/** Does look-up transformation. Elements of the source array
+   (that should be 8uC1 or 8sC1) are used as indexes in lutarr 256-element table */
+CVAPI(void) cvLUT( const CvArr* src, CvArr* dst, const CvArr* lut );
+
+
+/******************* Iteration through the sequence tree *****************/
+typedef struct CvTreeNodeIterator
+{
+    const void* node;
+    int level;
+    int max_level;
+}
+CvTreeNodeIterator;
+
+CVAPI(void) cvInitTreeNodeIterator( CvTreeNodeIterator* tree_iterator,
+                                   const void* first, int max_level );
+CVAPI(void*) cvNextTreeNode( CvTreeNodeIterator* tree_iterator );
+CVAPI(void*) cvPrevTreeNode( CvTreeNodeIterator* tree_iterator );
+
+/** Inserts sequence into tree with specified "parent" sequence.
+   If parent is equal to frame (e.g. the most external contour),
+   then added contour will have null pointer to parent. */
+CVAPI(void) cvInsertNodeIntoTree( void* node, void* parent, void* frame );
+
+/** Removes contour from tree (together with the contour children). */
+CVAPI(void) cvRemoveNodeFromTree( void* node, void* frame );
+
+/** Gathers pointers to all the sequences,
+   accessible from the `first`, to the single sequence */
+CVAPI(CvSeq*) cvTreeToNodeSeq( const void* first, int header_size,
+                              CvMemStorage* storage );
+
+/** The function implements the K-means algorithm for clustering an array of sample
+   vectors in a specified number of classes */
+#define CV_KMEANS_USE_INITIAL_LABELS    1
+CVAPI(int) cvKMeans2( const CvArr* samples, int cluster_count, CvArr* labels,
+                      CvTermCriteria termcrit, int attempts CV_DEFAULT(1),
+                      CvRNG* rng CV_DEFAULT(0), int flags CV_DEFAULT(0),
+                      CvArr* _centers CV_DEFAULT(0), double* compactness CV_DEFAULT(0) );
+
+/****************************************************************************************\
+*                                    System functions                                    *
+\****************************************************************************************/
+
+/** Loads optimized functions from IPP, MKL etc. or switches back to pure C code */
+CVAPI(int)  cvUseOptimized( int on_off );
+
+typedef IplImage* (CV_STDCALL* Cv_iplCreateImageHeader)
+                            (int,int,int,char*,char*,int,int,int,int,int,
+                            IplROI*,IplImage*,void*,IplTileInfo*);
+typedef void (CV_STDCALL* Cv_iplAllocateImageData)(IplImage*,int,int);
+typedef void (CV_STDCALL* Cv_iplDeallocate)(IplImage*,int);
+typedef IplROI* (CV_STDCALL* Cv_iplCreateROI)(int,int,int,int,int);
+typedef IplImage* (CV_STDCALL* Cv_iplCloneImage)(const IplImage*);
+
+/** @brief Makes OpenCV use IPL functions for allocating IplImage and IplROI structures.
+
+Normally, the function is not called directly. Instead, a simple macro
+CV_TURN_ON_IPL_COMPATIBILITY() is used that calls cvSetIPLAllocators and passes there pointers
+to IPL allocation functions. :
+@code
+    ...
+    CV_TURN_ON_IPL_COMPATIBILITY()
+    ...
+@endcode
+@param create_header pointer to a function, creating IPL image header.
+@param allocate_data pointer to a function, allocating IPL image data.
+@param deallocate pointer to a function, deallocating IPL image.
+@param create_roi pointer to a function, creating IPL image ROI (i.e. Region of Interest).
+@param clone_image pointer to a function, cloning an IPL image.
+ */
+CVAPI(void) cvSetIPLAllocators( Cv_iplCreateImageHeader create_header,
+                               Cv_iplAllocateImageData allocate_data,
+                               Cv_iplDeallocate deallocate,
+                               Cv_iplCreateROI create_roi,
+                               Cv_iplCloneImage clone_image );
+
+#define CV_TURN_ON_IPL_COMPATIBILITY()                                  \
+    cvSetIPLAllocators( iplCreateImageHeader, iplAllocateImage,         \
+                        iplDeallocate, iplCreateROI, iplCloneImage )
+
+/****************************************************************************************\
+*                                    Data Persistence                                    *
+\****************************************************************************************/
+
+#if 0
+/********************************** High-level functions ********************************/
+
+/** @brief Opens file storage for reading or writing data.
+
+The function opens file storage for reading or writing data. In the latter case, a new file is
+created or an existing file is rewritten. The type of the read or written file is determined by the
+filename extension: .xml for XML, .yml or .yaml for YAML and .json for JSON.
+
+At the same time, it also supports adding parameters like "example.xml?base64".
+
+The function returns a pointer to the CvFileStorage structure.
+If the file cannot be opened then the function returns NULL.
+@param filename Name of the file associated with the storage
+@param memstorage Memory storage used for temporary data and for
+:   storing dynamic structures, such as CvSeq or CvGraph . If it is NULL, a temporary memory
+    storage is created and used.
+@param flags Can be one of the following:
+> -   **CV_STORAGE_READ** the storage is open for reading
+> -   **CV_STORAGE_WRITE** the storage is open for writing
+      (use **CV_STORAGE_WRITE | CV_STORAGE_WRITE_BASE64** to write rawdata in Base64)
+@param encoding
+ */
+CVAPI(CvFileStorage*)  cvOpenFileStorage( const char* filename, CvMemStorage* memstorage,
+                                          int flags, const char* encoding CV_DEFAULT(NULL) );
+
+/** @brief Releases file storage.
+
+The function closes the file associated with the storage and releases all the temporary structures.
+It must be called after all I/O operations with the storage are finished.
+@param fs Double pointer to the released file storage
+ */
+CVAPI(void) cvReleaseFileStorage( CvFileStorage** fs );
+
+/** returns attribute value or 0 (NULL) if there is no such attribute */
+CVAPI(const char*) cvAttrValue( const CvAttrList* attr, const char* attr_name );
+
+/** @brief Starts writing a new structure.
+
+The function starts writing a compound structure (collection) that can be a sequence or a map. After
+all the structure fields, which can be scalars or structures, are written, cvEndWriteStruct should
+be called. The function can be used to group some objects or to implement the write function for a
+some user object (see CvTypeInfo).
+@param fs File storage
+@param name Name of the written structure. The structure can be accessed by this name when the
+storage is read.
+@param struct_flags A combination one of the following values:
+-   **CV_NODE_SEQ** the written structure is a sequence (see discussion of CvFileStorage ),
+    that is, its elements do not have a name.
+-   **CV_NODE_MAP** the written structure is a map (see discussion of CvFileStorage ), that
+    is, all its elements have names.
+One and only one of the two above flags must be specified
+-   **CV_NODE_FLOW** the optional flag that makes sense only for YAML streams. It means that
+     the structure is written as a flow (not as a block), which is more compact. It is
+     recommended to use this flag for structures or arrays whose elements are all scalars.
+@param type_name Optional parameter - the object type name. In
+    case of XML it is written as a type_id attribute of the structure opening tag. In the case of
+    YAML it is written after a colon following the structure name (see the example in
+    CvFileStorage description). In case of JSON it is written as a name/value pair.
+    Mainly it is used with user objects. When the storage is read, the
+    encoded type name is used to determine the object type (see CvTypeInfo and cvFindType ).
+@param attributes This parameter is not used in the current implementation
+ */
+CVAPI(void) cvStartWriteStruct( CvFileStorage* fs, const char* name,
+                                int struct_flags, const char* type_name CV_DEFAULT(NULL),
+                                CvAttrList attributes CV_DEFAULT(cvAttrList()));
+
+/** @brief Finishes writing to a file node collection.
+@param fs File storage
+@sa cvStartWriteStruct.
+ */
+CVAPI(void) cvEndWriteStruct( CvFileStorage* fs );
+
+/** @brief Writes an integer value.
+
+The function writes a single integer value (with or without a name) to the file storage.
+@param fs File storage
+@param name Name of the written value. Should be NULL if and only if the parent structure is a
+sequence.
+@param value The written value
+ */
+CVAPI(void) cvWriteInt( CvFileStorage* fs, const char* name, int value );
+
+/** @brief Writes a floating-point value.
+
+The function writes a single floating-point value (with or without a name) to file storage. Special
+values are encoded as follows: NaN (Not A Number) as .NaN, infinity as +.Inf or -.Inf.
+
+The following example shows how to use the low-level writing functions to store custom structures,
+such as termination criteria, without registering a new type. :
+@code
+    void write_termcriteria( CvFileStorage* fs, const char* struct_name,
+                             CvTermCriteria* termcrit )
+    {
+        cvStartWriteStruct( fs, struct_name, CV_NODE_MAP, NULL, cvAttrList(0,0));
+        cvWriteComment( fs, "termination criteria", 1 ); // just a description
+        if( termcrit->type & CV_TERMCRIT_ITER )
+            cvWriteInteger( fs, "max_iterations", termcrit->max_iter );
+        if( termcrit->type & CV_TERMCRIT_EPS )
+            cvWriteReal( fs, "accuracy", termcrit->epsilon );
+        cvEndWriteStruct( fs );
+    }
+@endcode
+@param fs File storage
+@param name Name of the written value. Should be NULL if and only if the parent structure is a
+sequence.
+@param value The written value
+*/
+CVAPI(void) cvWriteReal( CvFileStorage* fs, const char* name, double value );
+
+/** @brief Writes a text string.
+
+The function writes a text string to file storage.
+@param fs File storage
+@param name Name of the written string . Should be NULL if and only if the parent structure is a
+sequence.
+@param str The written text string
+@param quote If non-zero, the written string is put in quotes, regardless of whether they are
+required. Otherwise, if the flag is zero, quotes are used only when they are required (e.g. when
+the string starts with a digit or contains spaces).
+ */
+CVAPI(void) cvWriteString( CvFileStorage* fs, const char* name,
+                           const char* str, int quote CV_DEFAULT(0) );
+
+/** @brief Writes a comment.
+
+The function writes a comment into file storage. The comments are skipped when the storage is read.
+@param fs File storage
+@param comment The written comment, single-line or multi-line
+@param eol_comment If non-zero, the function tries to put the comment at the end of current line.
+If the flag is zero, if the comment is multi-line, or if it does not fit at the end of the current
+line, the comment starts a new line.
+ */
+CVAPI(void) cvWriteComment( CvFileStorage* fs, const char* comment,
+                            int eol_comment );
+
+/** @brief Writes an object to file storage.
+
+The function writes an object to file storage. First, the appropriate type info is found using
+cvTypeOf. Then, the write method associated with the type info is called.
+
+Attributes are used to customize the writing procedure. The standard types support the following
+attributes (all the dt attributes have the same format as in cvWriteRawData):
+
+-# CvSeq
+    -   **header_dt** description of user fields of the sequence header that follow CvSeq, or
+        CvChain (if the sequence is a Freeman chain) or CvContour (if the sequence is a contour or
+        point sequence)
+    -   **dt** description of the sequence elements.
+    -   **recursive** if the attribute is present and is not equal to "0" or "false", the whole
+        tree of sequences (contours) is stored.
+-# CvGraph
+    -   **header_dt** description of user fields of the graph header that follows CvGraph;
+    -   **vertex_dt** description of user fields of graph vertices
+    -   **edge_dt** description of user fields of graph edges (note that the edge weight is
+        always written, so there is no need to specify it explicitly)
+
+Below is the code that creates the YAML file shown in the CvFileStorage description:
+@code
+    #include "cxcore.h"
+
+    int main( int argc, char** argv )
+    {
+        CvMat* mat = cvCreateMat( 3, 3, CV_32F );
+        CvFileStorage* fs = cvOpenFileStorage( "example.yml", 0, CV_STORAGE_WRITE );
+
+        cvSetIdentity( mat );
+        cvWrite( fs, "A", mat, cvAttrList(0,0) );
+
+        cvReleaseFileStorage( &fs );
+        cvReleaseMat( &mat );
+        return 0;
+    }
+@endcode
+@param fs File storage
+@param name Name of the written object. Should be NULL if and only if the parent structure is a
+sequence.
+@param ptr Pointer to the object
+@param attributes The attributes of the object. They are specific for each particular type (see
+the discussion below).
+ */
+CVAPI(void) cvWrite( CvFileStorage* fs, const char* name, const void* ptr,
+                         CvAttrList attributes CV_DEFAULT(cvAttrList()));
+
+/** @brief Starts the next stream.
+
+The function finishes the currently written stream and starts the next stream. In the case of XML
+the file with multiple streams looks like this:
+@code{.xml}
+    <opencv_storage>
+    <!-- stream #1 data -->
+    </opencv_storage>
+    <opencv_storage>
+    <!-- stream #2 data -->
+    </opencv_storage>
+    ...
+@endcode
+The YAML file will look like this:
+@code{.yaml}
+    %YAML 1.0
+    # stream #1 data
+    ...
+    ---
+    # stream #2 data
+@endcode
+This is useful for concatenating files or for resuming the writing process.
+@param fs File storage
+ */
+CVAPI(void) cvStartNextStream( CvFileStorage* fs );
+
+/** @brief Writes multiple numbers.
+
+The function writes an array, whose elements consist of single or multiple numbers. The function
+call can be replaced with a loop containing a few cvWriteInt and cvWriteReal calls, but a single
+call is more efficient. Note that because none of the elements have a name, they should be written
+to a sequence rather than a map.
+@param fs File storage
+@param src Pointer to the written array
+@param len Number of the array elements to write
+@param dt Specification of each array element, see @ref format_spec "format specification"
+ */
+CVAPI(void) cvWriteRawData( CvFileStorage* fs, const void* src,
+                                int len, const char* dt );
+
+/** @brief Writes multiple numbers in Base64.
+
+If either CV_STORAGE_WRITE_BASE64 or cv::FileStorage::WRITE_BASE64 is used,
+this function will be the same as cvWriteRawData. If neither, the main
+difference is that it outputs a sequence in Base64 encoding rather than
+in plain text.
+
+This function can only be used to write a sequence with a type "binary".
+
+@param fs File storage
+@param src Pointer to the written array
+@param len Number of the array elements to write
+@param dt Specification of each array element, see @ref format_spec "format specification"
+*/
+CVAPI(void) cvWriteRawDataBase64( CvFileStorage* fs, const void* src,
+                                 int len, const char* dt );
+
+/** @brief Returns a unique pointer for a given name.
+
+The function returns a unique pointer for each particular file node name. This pointer can be then
+passed to the cvGetFileNode function that is faster than cvGetFileNodeByName because it compares
+text strings by comparing pointers rather than the strings' content.
+
+Consider the following example where an array of points is encoded as a sequence of 2-entry maps:
+@code
+    points:
+      - { x: 10, y: 10 }
+      - { x: 20, y: 20 }
+      - { x: 30, y: 30 }
+      # ...
+@endcode
+Then, it is possible to get hashed "x" and "y" pointers to speed up decoding of the points. :
+@code
+    #include "cxcore.h"
+
+    int main( int argc, char** argv )
+    {
+        CvFileStorage* fs = cvOpenFileStorage( "points.yml", 0, CV_STORAGE_READ );
+        CvStringHashNode* x_key = cvGetHashedNode( fs, "x", -1, 1 );
+        CvStringHashNode* y_key = cvGetHashedNode( fs, "y", -1, 1 );
+        CvFileNode* points = cvGetFileNodeByName( fs, 0, "points" );
+
+        if( CV_NODE_IS_SEQ(points->tag) )
+        {
+            CvSeq* seq = points->data.seq;
+            int i, total = seq->total;
+            CvSeqReader reader;
+            cvStartReadSeq( seq, &reader, 0 );
+            for( i = 0; i < total; i++ )
+            {
+                CvFileNode* pt = (CvFileNode*)reader.ptr;
+    #if 1 // faster variant
+                CvFileNode* xnode = cvGetFileNode( fs, pt, x_key, 0 );
+                CvFileNode* ynode = cvGetFileNode( fs, pt, y_key, 0 );
+                assert( xnode && CV_NODE_IS_INT(xnode->tag) &&
+                        ynode && CV_NODE_IS_INT(ynode->tag));
+                int x = xnode->data.i; // or x = cvReadInt( xnode, 0 );
+                int y = ynode->data.i; // or y = cvReadInt( ynode, 0 );
+    #elif 1 // slower variant; does not use x_key & y_key
+                CvFileNode* xnode = cvGetFileNodeByName( fs, pt, "x" );
+                CvFileNode* ynode = cvGetFileNodeByName( fs, pt, "y" );
+                assert( xnode && CV_NODE_IS_INT(xnode->tag) &&
+                        ynode && CV_NODE_IS_INT(ynode->tag));
+                int x = xnode->data.i; // or x = cvReadInt( xnode, 0 );
+                int y = ynode->data.i; // or y = cvReadInt( ynode, 0 );
+    #else // the slowest yet the easiest to use variant
+                int x = cvReadIntByName( fs, pt, "x", 0 );
+                int y = cvReadIntByName( fs, pt, "y", 0 );
+    #endif
+                CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
+                printf("
+            }
+        }
+        cvReleaseFileStorage( &fs );
+        return 0;
+    }
+@endcode
+Please note that whatever method of accessing a map you are using, it is still much slower than
+using plain sequences; for example, in the above example, it is more efficient to encode the points
+as pairs of integers in a single numeric sequence.
+@param fs File storage
+@param name Literal node name
+@param len Length of the name (if it is known apriori), or -1 if it needs to be calculated
+@param create_missing Flag that specifies, whether an absent key should be added into the hash table
+*/
+CVAPI(CvStringHashNode*) cvGetHashedKey( CvFileStorage* fs, const char* name,
+                                        int len CV_DEFAULT(-1),
+                                        int create_missing CV_DEFAULT(0));
+
+/** @brief Retrieves one of the top-level nodes of the file storage.
+
+The function returns one of the top-level file nodes. The top-level nodes do not have a name, they
+correspond to the streams that are stored one after another in the file storage. If the index is out
+of range, the function returns a NULL pointer, so all the top-level nodes can be iterated by
+subsequent calls to the function with stream_index=0,1,..., until the NULL pointer is returned.
+This function can be used as a base for recursive traversal of the file storage.
+@param fs File storage
+@param stream_index Zero-based index of the stream. See cvStartNextStream . In most cases,
+there is only one stream in the file; however, there can be several.
+ */
+CVAPI(CvFileNode*) cvGetRootFileNode( const CvFileStorage* fs,
+                                     int stream_index CV_DEFAULT(0) );
+
+/** @brief Finds a node in a map or file storage.
+
+The function finds a file node. It is a faster version of cvGetFileNodeByName (see
+cvGetHashedKey discussion). Also, the function can insert a new node, if it is not in the map yet.
+@param fs File storage
+@param map The parent map. If it is NULL, the function searches a top-level node. If both map and
+key are NULLs, the function returns the root file node - a map that contains top-level nodes.
+@param key Unique pointer to the node name, retrieved with cvGetHashedKey
+@param create_missing Flag that specifies whether an absent node should be added to the map
+ */
+CVAPI(CvFileNode*) cvGetFileNode( CvFileStorage* fs, CvFileNode* map,
+                                 const CvStringHashNode* key,
+                                 int create_missing CV_DEFAULT(0) );
+
+/** @brief Finds a node in a map or file storage.
+
+The function finds a file node by name. The node is searched either in map or, if the pointer is
+NULL, among the top-level file storage nodes. Using this function for maps and cvGetSeqElem (or
+sequence reader) for sequences, it is possible to navigate through the file storage. To speed up
+multiple queries for a certain key (e.g., in the case of an array of structures) one may use a
+combination of cvGetHashedKey and cvGetFileNode.
+@param fs File storage
+@param map The parent map. If it is NULL, the function searches in all the top-level nodes
+(streams), starting with the first one.
+@param name The file node name
+ */
+CVAPI(CvFileNode*) cvGetFileNodeByName( const CvFileStorage* fs,
+                                       const CvFileNode* map,
+                                       const char* name );
+
+/** @brief Retrieves an integer value from a file node.
+
+The function returns an integer that is represented by the file node. If the file node is NULL, the
+default_value is returned (thus, it is convenient to call the function right after cvGetFileNode
+without checking for a NULL pointer). If the file node has type CV_NODE_INT, then node-\>data.i is
+returned. If the file node has type CV_NODE_REAL, then node-\>data.f is converted to an integer
+and returned. Otherwise the error is reported.
+@param node File node
+@param default_value The value that is returned if node is NULL
+ */
+CV_INLINE int cvReadInt( const CvFileNode* node, int default_value CV_DEFAULT(0) )
+{
+    return !node ? default_value :
+        CV_NODE_IS_INT(node->tag) ? node->data.i :
+        CV_NODE_IS_REAL(node->tag) ? cvRound(node->data.f) : 0x7fffffff;
+}
+
+/** @brief Finds a file node and returns its value.
+
+The function is a simple superposition of cvGetFileNodeByName and cvReadInt.
+@param fs File storage
+@param map The parent map. If it is NULL, the function searches a top-level node.
+@param name The node name
+@param default_value The value that is returned if the file node is not found
+ */
+CV_INLINE int cvReadIntByName( const CvFileStorage* fs, const CvFileNode* map,
+                         const char* name, int default_value CV_DEFAULT(0) )
+{
+    return cvReadInt( cvGetFileNodeByName( fs, map, name ), default_value );
+}
+
+/** @brief Retrieves a floating-point value from a file node.
+
+The function returns a floating-point value that is represented by the file node. If the file node
+is NULL, the default_value is returned (thus, it is convenient to call the function right after
+cvGetFileNode without checking for a NULL pointer). If the file node has type CV_NODE_REAL ,
+then node-\>data.f is returned. If the file node has type CV_NODE_INT , then node-:math:\>data.f
+is converted to floating-point and returned. Otherwise the result is not determined.
+@param node File node
+@param default_value The value that is returned if node is NULL
+ */
+CV_INLINE double cvReadReal( const CvFileNode* node, double default_value CV_DEFAULT(0.) )
+{
+    return !node ? default_value :
+        CV_NODE_IS_INT(node->tag) ? (double)node->data.i :
+        CV_NODE_IS_REAL(node->tag) ? node->data.f : 1e300;
+}
+
+/** @brief Finds a file node and returns its value.
+
+The function is a simple superposition of cvGetFileNodeByName and cvReadReal .
+@param fs File storage
+@param map The parent map. If it is NULL, the function searches a top-level node.
+@param name The node name
+@param default_value The value that is returned if the file node is not found
+ */
+CV_INLINE double cvReadRealByName( const CvFileStorage* fs, const CvFileNode* map,
+                        const char* name, double default_value CV_DEFAULT(0.) )
+{
+    return cvReadReal( cvGetFileNodeByName( fs, map, name ), default_value );
+}
+
+/** @brief Retrieves a text string from a file node.
+
+The function returns a text string that is represented by the file node. If the file node is NULL,
+the default_value is returned (thus, it is convenient to call the function right after
+cvGetFileNode without checking for a NULL pointer). If the file node has type CV_NODE_STR , then
+node-:math:\>data.str.ptr is returned. Otherwise the result is not determined.
+@param node File node
+@param default_value The value that is returned if node is NULL
+ */
+CV_INLINE const char* cvReadString( const CvFileNode* node,
+                        const char* default_value CV_DEFAULT(NULL) )
+{
+    return !node ? default_value : CV_NODE_IS_STRING(node->tag) ? node->data.str.ptr : 0;
+}
+
+/** @brief Finds a file node by its name and returns its value.
+
+The function is a simple superposition of cvGetFileNodeByName and cvReadString .
+@param fs File storage
+@param map The parent map. If it is NULL, the function searches a top-level node.
+@param name The node name
+@param default_value The value that is returned if the file node is not found
+ */
+CV_INLINE const char* cvReadStringByName( const CvFileStorage* fs, const CvFileNode* map,
+                        const char* name, const char* default_value CV_DEFAULT(NULL) )
+{
+    return cvReadString( cvGetFileNodeByName( fs, map, name ), default_value );
+}
+
+
+/** @brief Decodes an object and returns a pointer to it.
+
+The function decodes a user object (creates an object in a native representation from the file
+storage subtree) and returns it. The object to be decoded must be an instance of a registered type
+that supports the read method (see CvTypeInfo). The type of the object is determined by the type
+name that is encoded in the file. If the object is a dynamic structure, it is created either in
+memory storage and passed to cvOpenFileStorage or, if a NULL pointer was passed, in temporary
+memory storage, which is released when cvReleaseFileStorage is called. Otherwise, if the object is
+not a dynamic structure, it is created in a heap and should be released with a specialized function
+or by using the generic cvRelease.
+@param fs File storage
+@param node The root object node
+@param attributes Unused parameter
+ */
+CVAPI(void*) cvRead( CvFileStorage* fs, CvFileNode* node,
+                        CvAttrList* attributes CV_DEFAULT(NULL));
+
+/** @brief Finds an object by name and decodes it.
+
+The function is a simple superposition of cvGetFileNodeByName and cvRead.
+@param fs File storage
+@param map The parent map. If it is NULL, the function searches a top-level node.
+@param name The node name
+@param attributes Unused parameter
+ */
+CV_INLINE void* cvReadByName( CvFileStorage* fs, const CvFileNode* map,
+                              const char* name, CvAttrList* attributes CV_DEFAULT(NULL) )
+{
+    return cvRead( fs, cvGetFileNodeByName( fs, map, name ), attributes );
+}
+
+
+/** @brief Initializes the file node sequence reader.
+
+The function initializes the sequence reader to read data from a file node. The initialized reader
+can be then passed to cvReadRawDataSlice.
+@param fs File storage
+@param src The file node (a sequence) to read numbers from
+@param reader Pointer to the sequence reader
+ */
+CVAPI(void) cvStartReadRawData( const CvFileStorage* fs, const CvFileNode* src,
+                               CvSeqReader* reader );
+
+/** @brief Initializes file node sequence reader.
+
+The function reads one or more elements from the file node, representing a sequence, to a
+user-specified array. The total number of read sequence elements is a product of total and the
+number of components in each array element. For example, if dt=2if, the function will read total\*3
+sequence elements. As with any sequence, some parts of the file node sequence can be skipped or read
+repeatedly by repositioning the reader using cvSetSeqReaderPos.
+@param fs File storage
+@param reader The sequence reader. Initialize it with cvStartReadRawData .
+@param count The number of elements to read
+@param dst Pointer to the destination array
+@param dt Specification of each array element. It has the same format as in cvWriteRawData .
+ */
+CVAPI(void) cvReadRawDataSlice( const CvFileStorage* fs, CvSeqReader* reader,
+                               int count, void* dst, const char* dt );
+
+/** @brief Reads multiple numbers.
+
+The function reads elements from a file node that represents a sequence of scalars.
+@param fs File storage
+@param src The file node (a sequence) to read numbers from
+@param dst Pointer to the destination array
+@param dt Specification of each array element. It has the same format as in cvWriteRawData .
+ */
+CVAPI(void) cvReadRawData( const CvFileStorage* fs, const CvFileNode* src,
+                          void* dst, const char* dt );
+
+/** @brief Writes a file node to another file storage.
+
+The function writes a copy of a file node to file storage. Possible applications of the function are
+merging several file storages into one and conversion between XML, YAML and JSON formats.
+@param fs Destination file storage
+@param new_node_name New name of the file node in the destination file storage. To keep the
+existing name, use cvcvGetFileNodeName
+@param node The written node
+@param embed If the written node is a collection and this parameter is not zero, no extra level of
+hierarchy is created. Instead, all the elements of node are written into the currently written
+structure. Of course, map elements can only be embedded into another map, and sequence elements
+can only be embedded into another sequence.
+ */
+CVAPI(void) cvWriteFileNode( CvFileStorage* fs, const char* new_node_name,
+                            const CvFileNode* node, int embed );
+
+/** @brief Returns the name of a file node.
+
+The function returns the name of a file node or NULL, if the file node does not have a name or if
+node is NULL.
+@param node File node
+ */
+CVAPI(const char*) cvGetFileNodeName( const CvFileNode* node );
+
+/*********************************** Adding own types ***********************************/
+
+/** @brief Registers a new type.
+
+The function registers a new type, which is described by info . The function creates a copy of the
+structure, so the user should delete it after calling the function.
+@param info Type info structure
+ */
+CVAPI(void) cvRegisterType( const CvTypeInfo* info );
+
+/** @brief Unregisters the type.
+
+The function unregisters a type with a specified name. If the name is unknown, it is possible to
+locate the type info by an instance of the type using cvTypeOf or by iterating the type list,
+starting from cvFirstType, and then calling cvUnregisterType(info-\>typeName).
+@param type_name Name of an unregistered type
+ */
+CVAPI(void) cvUnregisterType( const char* type_name );
+
+/** @brief Returns the beginning of a type list.
+
+The function returns the first type in the list of registered types. Navigation through the list can
+be done via the prev and next fields of the CvTypeInfo structure.
+ */
+CVAPI(CvTypeInfo*) cvFirstType(void);
+
+/** @brief Finds a type by its name.
+
+The function finds a registered type by its name. It returns NULL if there is no type with the
+specified name.
+@param type_name Type name
+ */
+CVAPI(CvTypeInfo*) cvFindType( const char* type_name );
+
+/** @brief Returns the type of an object.
+
+The function finds the type of a given object. It iterates through the list of registered types and
+calls the is_instance function/method for every type info structure with that object until one of
+them returns non-zero or until the whole list has been traversed. In the latter case, the function
+returns NULL.
+@param struct_ptr The object pointer
+ */
+CVAPI(CvTypeInfo*) cvTypeOf( const void* struct_ptr );
+
+#endif
+
+/** @brief Releases an object.
+
+ The function finds the type of a given object and calls release with the double pointer.
+ @param struct_ptr Double pointer to the object
+ */
+CVAPI(void) cvRelease( void** struct_ptr );
+
+/** @brief Makes a clone of an object.
+
+The function finds the type of a given object and calls clone with the passed object. Of course, if
+you know the object type, for example, struct_ptr is CvMat\*, it is faster to call the specific
+function, like cvCloneMat.
+@param struct_ptr The object to clone
+ */
+CVAPI(void*) cvClone( const void* struct_ptr );
+
+/*********************************** Measuring Execution Time ***************************/
+
+/** helper functions for RNG initialization and accurate time measurement:
+   uses internal clock counter on x86 */
+CVAPI(int64)  cvGetTickCount( void );
+CVAPI(double) cvGetTickFrequency( void );
+
+/*********************************** CPU capabilities ***********************************/
+
+CVAPI(int) cvCheckHardwareSupport(int feature);
+
+/*********************************** Multi-Threading ************************************/
+
+/** retrieve/set the number of threads used in OpenMP implementations */
+CVAPI(int)  cvGetNumThreads( void );
+CVAPI(void) cvSetNumThreads( int threads CV_DEFAULT(0) );
+/** get index of the thread being executed */
+CVAPI(int)  cvGetThreadNum( void );
+
+
+/********************************** Error Handling **************************************/
+
+/** Get current OpenCV error status */
+CVAPI(int) cvGetErrStatus( void );
+
+/** Sets error status silently */
+CVAPI(void) cvSetErrStatus( int status );
+
+#define CV_ErrModeLeaf     0   /* Print error and exit program */
+#define CV_ErrModeParent   1   /* Print error and continue */
+#define CV_ErrModeSilent   2   /* Don't print and continue */
+
+/** Retrieves current error processing mode */
+CVAPI(int)  cvGetErrMode( void );
+
+/** Sets error processing mode, returns previously used mode */
+CVAPI(int) cvSetErrMode( int mode );
+
+/** Sets error status and performs some additional actions (displaying message box,
+ writing message to stderr, terminating application etc.)
+ depending on the current error mode */
+CVAPI(void) cvError( int status, const char* func_name,
+                    const char* err_msg, const char* file_name, int line );
+
+/** Retrieves textual description of the error given its code */
+CVAPI(const char*) cvErrorStr( int status );
+
+/** Retrieves detailed information about the last error occurred */
+CVAPI(int) cvGetErrInfo( const char** errcode_desc, const char** description,
+                        const char** filename, int* line );
+
+/** Maps IPP error codes to the counterparts from OpenCV */
+CVAPI(int) cvErrorFromIppStatus( int ipp_status );
+
+typedef int (CV_CDECL *CvErrorCallback)( int status, const char* func_name,
+                                        const char* err_msg, const char* file_name, int line, void* userdata );
+
+/** Assigns a new error-handling function */
+CVAPI(CvErrorCallback) cvRedirectError( CvErrorCallback error_handler,
+                                       void* userdata CV_DEFAULT(NULL),
+                                       void** prev_userdata CV_DEFAULT(NULL) );
+
+/** Output nothing */
+CVAPI(int) cvNulDevReport( int status, const char* func_name, const char* err_msg,
+                          const char* file_name, int line, void* userdata );
+
+/** Output to console(fprintf(stderr,...)) */
+CVAPI(int) cvStdErrReport( int status, const char* func_name, const char* err_msg,
+                          const char* file_name, int line, void* userdata );
+
+/** Output to MessageBox(WIN32) */
+CVAPI(int) cvGuiBoxReport( int status, const char* func_name, const char* err_msg,
+                          const char* file_name, int line, void* userdata );
+
+#define OPENCV_ERROR(status,func,context)                           \
+cvError((status),(func),(context),__FILE__,__LINE__)
+
+#define OPENCV_ASSERT(expr,func,context)                            \
+{if (! (expr))                                      \
+{OPENCV_ERROR(CV_StsInternal,(func),(context));}}
+
+#define OPENCV_CALL( Func )                                         \
+{                                                                   \
+Func;                                                           \
+}
+
+
+/** CV_FUNCNAME macro defines icvFuncName constant which is used by CV_ERROR macro */
+#ifdef CV_NO_FUNC_NAMES
+#define CV_FUNCNAME( Name )
+#define cvFuncName ""
+#else
+#define CV_FUNCNAME( Name )  \
+static char cvFuncName[] = Name
+#endif
+
+
+/**
+ CV_ERROR macro unconditionally raises error with passed code and message.
+ After raising error, control will be transferred to the exit label.
+ */
+#define CV_ERROR( Code, Msg )                                       \
+{                                                                   \
+    cvError( (Code), cvFuncName, Msg, __FILE__, __LINE__ );        \
+    __CV_EXIT__;                                                   \
+}
+
+/**
+ CV_CHECK macro checks error status after CV (or IPL)
+ function call. If error detected, control will be transferred to the exit
+ label.
+ */
+#define CV_CHECK()                                                  \
+{                                                                   \
+    if( cvGetErrStatus() < 0 )                                      \
+        CV_ERROR( CV_StsBackTrace, "Inner function failed." );      \
+}
+
+
+/**
+ CV_CALL macro calls CV (or IPL) function, checks error status and
+ signals a error if the function failed. Useful in "parent node"
+ error processing mode
+ */
+#define CV_CALL( Func )                                             \
+{                                                                   \
+    Func;                                                           \
+    CV_CHECK();                                                     \
+}
+
+
+/** Runtime assertion macro */
+#define CV_ASSERT( Condition )                                          \
+{                                                                       \
+    if( !(Condition) )                                                  \
+        CV_ERROR( CV_StsInternal, "Assertion: " #Condition " failed" ); \
+}
+
+#define __CV_BEGIN__       {
+#define __CV_END__         goto exit; exit: ; }
+#define __CV_EXIT__        goto exit
+
+/** @} core_c */
+
+#ifdef __cplusplus
+} // extern "C"
+#endif
+
+#ifdef __cplusplus
+
+#include "opencv2/core/utility.hpp"
+
+namespace cv
+{
+
+//! @addtogroup core_c_glue
+//! @{
+
+/////////////////////////////////////////// glue ///////////////////////////////////////////
+
+//! converts array (CvMat or IplImage) to cv::Mat
+CV_EXPORTS Mat cvarrToMat(const CvArr* arr, bool copyData=false,
+                          bool allowND=true, int coiMode=0,
+                          AutoBuffer<double>* buf=0);
+
+static inline Mat cvarrToMatND(const CvArr* arr, bool copyData=false, int coiMode=0)
+{
+    return cvarrToMat(arr, copyData, true, coiMode);
+}
+
+
+//! extracts Channel of Interest from CvMat or IplImage and makes cv::Mat out of it.
+CV_EXPORTS void extractImageCOI(const CvArr* arr, OutputArray coiimg, int coi=-1);
+//! inserts single-channel cv::Mat into a multi-channel CvMat or IplImage
+CV_EXPORTS void insertImageCOI(InputArray coiimg, CvArr* arr, int coi=-1);
+
+
+
+////// specialized implementations of DefaultDeleter::operator() for classic OpenCV types //////
+
+template<> struct DefaultDeleter<CvMat>{ CV_EXPORTS void operator ()(CvMat* obj) const; };
+template<> struct DefaultDeleter<IplImage>{ CV_EXPORTS void operator ()(IplImage* obj) const; };
+template<> struct DefaultDeleter<CvMatND>{ CV_EXPORTS void operator ()(CvMatND* obj) const; };
+template<> struct DefaultDeleter<CvSparseMat>{ CV_EXPORTS void operator ()(CvSparseMat* obj) const; };
+template<> struct DefaultDeleter<CvMemStorage>{ CV_EXPORTS void operator ()(CvMemStorage* obj) const; };
+
+////////////// convenient wrappers for operating old-style dynamic structures //////////////
+
+template<typename _Tp> class SeqIterator;
+
+typedef Ptr<CvMemStorage> MemStorage;
+
+/*!
+ Template Sequence Class derived from CvSeq
+
+ The class provides more convenient access to sequence elements,
+ STL-style operations and iterators.
+
+ \note The class is targeted for simple data types,
+    i.e. no constructors or destructors
+    are called for the sequence elements.
+*/
+template<typename _Tp> class Seq
+{
+public:
+    typedef SeqIterator<_Tp> iterator;
+    typedef SeqIterator<_Tp> const_iterator;
+
+    //! the default constructor
+    Seq();
+    //! the constructor for wrapping CvSeq structure. The real element type in CvSeq should match _Tp.
+    Seq(const CvSeq* seq);
+    //! creates the empty sequence that resides in the specified storage
+    Seq(MemStorage& storage, int headerSize = sizeof(CvSeq));
+    //! returns read-write reference to the specified element
+    _Tp& operator [](int idx);
+    //! returns read-only reference to the specified element
+    const _Tp& operator[](int idx) const;
+    //! returns iterator pointing to the beginning of the sequence
+    SeqIterator<_Tp> begin() const;
+    //! returns iterator pointing to the element following the last sequence element
+    SeqIterator<_Tp> end() const;
+    //! returns the number of elements in the sequence
+    size_t size() const;
+    //! returns the type of sequence elements (CV_8UC1 ... CV_64FC(CV_CN_MAX) ...)
+    int type() const;
+    //! returns the depth of sequence elements (CV_8U ... CV_64F)
+    int depth() const;
+    //! returns the number of channels in each sequence element
+    int channels() const;
+    //! returns the size of each sequence element
+    size_t elemSize() const;
+    //! returns index of the specified sequence element
+    size_t index(const _Tp& elem) const;
+    //! appends the specified element to the end of the sequence
+    void push_back(const _Tp& elem);
+    //! appends the specified element to the front of the sequence
+    void push_front(const _Tp& elem);
+    //! appends zero or more elements to the end of the sequence
+    void push_back(const _Tp* elems, size_t count);
+    //! appends zero or more elements to the front of the sequence
+    void push_front(const _Tp* elems, size_t count);
+    //! inserts the specified element to the specified position
+    void insert(int idx, const _Tp& elem);
+    //! inserts zero or more elements to the specified position
+    void insert(int idx, const _Tp* elems, size_t count);
+    //! removes element at the specified position
+    void remove(int idx);
+    //! removes the specified subsequence
+    void remove(const Range& r);
+
+    //! returns reference to the first sequence element
+    _Tp& front();
+    //! returns read-only reference to the first sequence element
+    const _Tp& front() const;
+    //! returns reference to the last sequence element
+    _Tp& back();
+    //! returns read-only reference to the last sequence element
+    const _Tp& back() const;
+    //! returns true iff the sequence contains no elements
+    bool empty() const;
+
+    //! removes all the elements from the sequence
+    void clear();
+    //! removes the first element from the sequence
+    void pop_front();
+    //! removes the last element from the sequence
+    void pop_back();
+    //! removes zero or more elements from the beginning of the sequence
+    void pop_front(_Tp* elems, size_t count);
+    //! removes zero or more elements from the end of the sequence
+    void pop_back(_Tp* elems, size_t count);
+
+    //! copies the whole sequence or the sequence slice to the specified vector
+    void copyTo(std::vector<_Tp>& vec, const Range& range=Range::all()) const;
+    //! returns the vector containing all the sequence elements
+    operator std::vector<_Tp>() const;
+
+    CvSeq* seq;
+};
+
+
+/*!
+ STL-style Sequence Iterator inherited from the CvSeqReader structure
+*/
+template<typename _Tp> class SeqIterator : public CvSeqReader
+{
+public:
+    //! the default constructor
+    SeqIterator();
+    //! the constructor setting the iterator to the beginning or to the end of the sequence
+    SeqIterator(const Seq<_Tp>& seq, bool seekEnd=false);
+    //! positions the iterator within the sequence
+    void seek(size_t pos);
+    //! reports the current iterator position
+    size_t tell() const;
+    //! returns reference to the current sequence element
+    _Tp& operator *();
+    //! returns read-only reference to the current sequence element
+    const _Tp& operator *() const;
+    //! moves iterator to the next sequence element
+    SeqIterator& operator ++();
+    //! moves iterator to the next sequence element
+    SeqIterator operator ++(int) const;
+    //! moves iterator to the previous sequence element
+    SeqIterator& operator --();
+    //! moves iterator to the previous sequence element
+    SeqIterator operator --(int) const;
+
+    //! moves iterator forward by the specified offset (possibly negative)
+    SeqIterator& operator +=(int);
+    //! moves iterator backward by the specified offset (possibly negative)
+    SeqIterator& operator -=(int);
+
+    // this is index of the current element module seq->total*2
+    // (to distinguish between 0 and seq->total)
+    int index;
+};
+
+
+
+// bridge C++ => C Seq API
+CV_EXPORTS schar*  seqPush( CvSeq* seq, const void* element=0);
+CV_EXPORTS schar*  seqPushFront( CvSeq* seq, const void* element=0);
+CV_EXPORTS void  seqPop( CvSeq* seq, void* element=0);
+CV_EXPORTS void  seqPopFront( CvSeq* seq, void* element=0);
+CV_EXPORTS void  seqPopMulti( CvSeq* seq, void* elements,
+                              int count, int in_front=0 );
+CV_EXPORTS void  seqRemove( CvSeq* seq, int index );
+CV_EXPORTS void  clearSeq( CvSeq* seq );
+CV_EXPORTS schar*  getSeqElem( const CvSeq* seq, int index );
+CV_EXPORTS void  seqRemoveSlice( CvSeq* seq, CvSlice slice );
+CV_EXPORTS void  seqInsertSlice( CvSeq* seq, int before_index, const CvArr* from_arr );
+
+template<typename _Tp> inline Seq<_Tp>::Seq() : seq(0) {}
+template<typename _Tp> inline Seq<_Tp>::Seq( const CvSeq* _seq ) : seq((CvSeq*)_seq)
+{
+    CV_Assert(!_seq || _seq->elem_size == sizeof(_Tp));
+}
+
+template<typename _Tp> inline Seq<_Tp>::Seq( MemStorage& storage,
+                                             int headerSize )
+{
+    CV_Assert(headerSize >= (int)sizeof(CvSeq));
+    seq = cvCreateSeq(DataType<_Tp>::type, headerSize, sizeof(_Tp), storage);
+}
+
+template<typename _Tp> inline _Tp& Seq<_Tp>::operator [](int idx)
+{ return *(_Tp*)getSeqElem(seq, idx); }
+
+template<typename _Tp> inline const _Tp& Seq<_Tp>::operator [](int idx) const
+{ return *(_Tp*)getSeqElem(seq, idx); }
+
+template<typename _Tp> inline SeqIterator<_Tp> Seq<_Tp>::begin() const
+{ return SeqIterator<_Tp>(*this); }
+
+template<typename _Tp> inline SeqIterator<_Tp> Seq<_Tp>::end() const
+{ return SeqIterator<_Tp>(*this, true); }
+
+template<typename _Tp> inline size_t Seq<_Tp>::size() const
+{ return seq ? seq->total : 0; }
+
+template<typename _Tp> inline int Seq<_Tp>::type() const
+{ return seq ? CV_MAT_TYPE(seq->flags) : 0; }
+
+template<typename _Tp> inline int Seq<_Tp>::depth() const
+{ return seq ? CV_MAT_DEPTH(seq->flags) : 0; }
+
+template<typename _Tp> inline int Seq<_Tp>::channels() const
+{ return seq ? CV_MAT_CN(seq->flags) : 0; }
+
+template<typename _Tp> inline size_t Seq<_Tp>::elemSize() const
+{ return seq ? seq->elem_size : 0; }
+
+template<typename _Tp> inline size_t Seq<_Tp>::index(const _Tp& elem) const
+{ return cvSeqElemIdx(seq, &elem); }
+
+template<typename _Tp> inline void Seq<_Tp>::push_back(const _Tp& elem)
+{ cvSeqPush(seq, &elem); }
+
+template<typename _Tp> inline void Seq<_Tp>::push_front(const _Tp& elem)
+{ cvSeqPushFront(seq, &elem); }
+
+template<typename _Tp> inline void Seq<_Tp>::push_back(const _Tp* elem, size_t count)
+{ cvSeqPushMulti(seq, elem, (int)count, 0); }
+
+template<typename _Tp> inline void Seq<_Tp>::push_front(const _Tp* elem, size_t count)
+{ cvSeqPushMulti(seq, elem, (int)count, 1); }
+
+template<typename _Tp> inline _Tp& Seq<_Tp>::back()
+{ return *(_Tp*)getSeqElem(seq, -1); }
+
+template<typename _Tp> inline const _Tp& Seq<_Tp>::back() const
+{ return *(const _Tp*)getSeqElem(seq, -1); }
+
+template<typename _Tp> inline _Tp& Seq<_Tp>::front()
+{ return *(_Tp*)getSeqElem(seq, 0); }
+
+template<typename _Tp> inline const _Tp& Seq<_Tp>::front() const
+{ return *(const _Tp*)getSeqElem(seq, 0); }
+
+template<typename _Tp> inline bool Seq<_Tp>::empty() const
+{ return !seq || seq->total == 0; }
+
+template<typename _Tp> inline void Seq<_Tp>::clear()
+{ if(seq) clearSeq(seq); }
+
+template<typename _Tp> inline void Seq<_Tp>::pop_back()
+{ seqPop(seq); }
+
+template<typename _Tp> inline void Seq<_Tp>::pop_front()
+{ seqPopFront(seq); }
+
+template<typename _Tp> inline void Seq<_Tp>::pop_back(_Tp* elem, size_t count)
+{ seqPopMulti(seq, elem, (int)count, 0); }
+
+template<typename _Tp> inline void Seq<_Tp>::pop_front(_Tp* elem, size_t count)
+{ seqPopMulti(seq, elem, (int)count, 1); }
+
+template<typename _Tp> inline void Seq<_Tp>::insert(int idx, const _Tp& elem)
+{ seqInsert(seq, idx, &elem); }
+
+template<typename _Tp> inline void Seq<_Tp>::insert(int idx, const _Tp* elems, size_t count)
+{
+    CvMat m = cvMat(1, count, DataType<_Tp>::type, elems);
+    seqInsertSlice(seq, idx, &m);
+}
+
+template<typename _Tp> inline void Seq<_Tp>::remove(int idx)
+{ seqRemove(seq, idx); }
+
+template<typename _Tp> inline void Seq<_Tp>::remove(const Range& r)
+{ seqRemoveSlice(seq, cvSlice(r.start, r.end)); }
+
+template<typename _Tp> inline void Seq<_Tp>::copyTo(std::vector<_Tp>& vec, const Range& range) const
+{
+    size_t len = !seq ? 0 : range == Range::all() ? seq->total : range.end - range.start;
+    vec.resize(len);
+    if( seq && len )
+        cvCvtSeqToArray(seq, &vec[0], cvSlice(range));
+}
+
+template<typename _Tp> inline Seq<_Tp>::operator std::vector<_Tp>() const
+{
+    std::vector<_Tp> vec;
+    copyTo(vec);
+    return vec;
+}
+
+template<typename _Tp> inline SeqIterator<_Tp>::SeqIterator()
+{ memset(this, 0, sizeof(*this)); }
+
+template<typename _Tp> inline SeqIterator<_Tp>::SeqIterator(const Seq<_Tp>& _seq, bool seekEnd)
+{
+    cvStartReadSeq(_seq.seq, this);
+    index = seekEnd ? _seq.seq->total : 0;
+}
+
+template<typename _Tp> inline void SeqIterator<_Tp>::seek(size_t pos)
+{
+    cvSetSeqReaderPos(this, (int)pos, false);
+    index = pos;
+}
+
+template<typename _Tp> inline size_t SeqIterator<_Tp>::tell() const
+{ return index; }
+
+template<typename _Tp> inline _Tp& SeqIterator<_Tp>::operator *()
+{ return *(_Tp*)ptr; }
+
+template<typename _Tp> inline const _Tp& SeqIterator<_Tp>::operator *() const
+{ return *(const _Tp*)ptr; }
+
+template<typename _Tp> inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator ++()
+{
+    CV_NEXT_SEQ_ELEM(sizeof(_Tp), *this);
+    if( ++index >= seq->total*2 )
+        index = 0;
+    return *this;
+}
+
+template<typename _Tp> inline SeqIterator<_Tp> SeqIterator<_Tp>::operator ++(int) const
+{
+    SeqIterator<_Tp> it = *this;
+    ++*this;
+    return it;
+}
+
+template<typename _Tp> inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator --()
+{
+    CV_PREV_SEQ_ELEM(sizeof(_Tp), *this);
+    if( --index < 0 )
+        index = seq->total*2-1;
+    return *this;
+}
+
+template<typename _Tp> inline SeqIterator<_Tp> SeqIterator<_Tp>::operator --(int) const
+{
+    SeqIterator<_Tp> it = *this;
+    --*this;
+    return it;
+}
+
+template<typename _Tp> inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator +=(int delta)
+{
+    cvSetSeqReaderPos(this, delta, 1);
+    index += delta;
+    int n = seq->total*2;
+    if( index < 0 )
+        index += n;
+    if( index >= n )
+        index -= n;
+    return *this;
+}
+
+template<typename _Tp> inline SeqIterator<_Tp>& SeqIterator<_Tp>::operator -=(int delta)
+{
+    return (*this += -delta);
+}
+
+template<typename _Tp> inline ptrdiff_t operator - (const SeqIterator<_Tp>& a,
+                                                    const SeqIterator<_Tp>& b)
+{
+    ptrdiff_t delta = a.index - b.index, n = a.seq->total;
+    if( delta > n || delta < -n )
+        delta += delta < 0 ? n : -n;
+    return delta;
+}
+
+template<typename _Tp> inline bool operator == (const SeqIterator<_Tp>& a,
+                                                const SeqIterator<_Tp>& b)
+{
+    return a.seq == b.seq && a.index == b.index;
+}
+
+template<typename _Tp> inline bool operator != (const SeqIterator<_Tp>& a,
+                                                const SeqIterator<_Tp>& b)
+{
+    return !(a == b);
+}
+
+//! @}
+
+} // cv
+
+#endif
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/cuda.hpp

@@ -0,0 +1,1339 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_CUDA_HPP
+#define OPENCV_CORE_CUDA_HPP
+
+#ifndef __cplusplus
+#  error cuda.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/core.hpp"
+#include "opencv2/core/cuda_types.hpp"
+
+/**
+  @defgroup cuda CUDA-accelerated Computer Vision
+  @{
+    @defgroup cudacore Core part
+    @{
+      @defgroup cudacore_init Initialization and Information
+      @defgroup cudacore_struct Data Structures
+    @}
+  @}
+ */
+
+namespace cv { namespace cuda {
+
+//! @addtogroup cudacore_struct
+//! @{
+
+//===================================================================================
+// GpuMat
+//===================================================================================
+
+/** @brief Base storage class for GPU memory with reference counting.
+
+Its interface matches the Mat interface with the following limitations:
+
+-   no arbitrary dimensions support (only 2D)
+-   no functions that return references to their data (because references on GPU are not valid for
+    CPU)
+-   no expression templates technique support
+
+Beware that the latter limitation may lead to overloaded matrix operators that cause memory
+allocations. The GpuMat class is convertible to cuda::PtrStepSz and cuda::PtrStep so it can be
+passed directly to the kernel.
+
+@note In contrast with Mat, in most cases GpuMat::isContinuous() == false . This means that rows are
+aligned to a size depending on the hardware. Single-row GpuMat is always a continuous matrix.
+
+@note You are not recommended to leave static or global GpuMat variables allocated, that is, to rely
+on its destructor. The destruction order of such variables and CUDA context is undefined. GPU memory
+release function returns error if the CUDA context has been destroyed before.
+
+Some member functions are described as a "Blocking Call" while some are described as a
+"Non-Blocking Call". Blocking functions are synchronous to host. It is guaranteed that the GPU
+operation is finished when the function returns. However, non-blocking functions are asynchronous to
+host. Those functions may return even if the GPU operation is not finished.
+
+Compared to their blocking counterpart, non-blocking functions accept Stream as an additional
+argument. If a non-default stream is passed, the GPU operation may overlap with operations in other
+streams.
+
+@sa Mat
+ */
+class CV_EXPORTS_W GpuMat
+{
+public:
+    class CV_EXPORTS_W Allocator
+    {
+    public:
+        virtual ~Allocator() {}
+
+        // allocator must fill data, step and refcount fields
+        virtual bool allocate(GpuMat* mat, int rows, int cols, size_t elemSize) = 0;
+        virtual void free(GpuMat* mat) = 0;
+    };
+
+    //! default allocator
+    CV_WRAP static GpuMat::Allocator* defaultAllocator();
+    CV_WRAP static void setDefaultAllocator(GpuMat::Allocator* allocator);
+    CV_WRAP static GpuMat::Allocator* getStdAllocator();
+
+    //! default constructor
+    CV_WRAP explicit GpuMat(GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
+
+    //! constructs GpuMat of the specified size and type
+    CV_WRAP GpuMat(int rows, int cols, int type, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
+    CV_WRAP GpuMat(Size size, int type, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
+
+    //! constructs GpuMat and fills it with the specified value _s
+    CV_WRAP GpuMat(int rows, int cols, int type, Scalar s, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
+    CV_WRAP GpuMat(Size size, int type, Scalar s, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
+
+    //! copy constructor
+    CV_WRAP GpuMat(const GpuMat& m);
+
+    //! constructor for GpuMat headers pointing to user-allocated data
+    GpuMat(int rows, int cols, int type, void* data, size_t step = Mat::AUTO_STEP);
+    GpuMat(Size size, int type, void* data, size_t step = Mat::AUTO_STEP);
+
+    //! creates a GpuMat header for a part of the bigger matrix
+    CV_WRAP GpuMat(const GpuMat& m, Range rowRange, Range colRange);
+    CV_WRAP GpuMat(const GpuMat& m, Rect roi);
+
+    //! builds GpuMat from host memory (Blocking call)
+    CV_WRAP explicit GpuMat(InputArray arr, GpuMat::Allocator* allocator = GpuMat::defaultAllocator());
+
+    //! destructor - calls release()
+    ~GpuMat();
+
+    //! assignment operators
+    GpuMat& operator =(const GpuMat& m);
+
+    //! allocates new GpuMat data unless the GpuMat already has specified size and type
+    CV_WRAP void create(int rows, int cols, int type);
+    CV_WRAP void create(Size size, int type);
+
+    //! decreases reference counter, deallocate the data when reference counter reaches 0
+    CV_WRAP void release();
+
+    //! swaps with other smart pointer
+    CV_WRAP void swap(GpuMat& mat);
+
+    /** @brief Performs data upload to GpuMat (Blocking call)
+
+    This function copies data from host memory to device memory. As being a blocking call, it is
+    guaranteed that the copy operation is finished when this function returns.
+    */
+    CV_WRAP void upload(InputArray arr);
+
+    /** @brief Performs data upload to GpuMat (Non-Blocking call)
+
+    This function copies data from host memory to device memory. As being a non-blocking call, this
+    function may return even if the copy operation is not finished.
+
+    The copy operation may be overlapped with operations in other non-default streams if \p stream is
+    not the default stream and \p dst is HostMem allocated with HostMem::PAGE_LOCKED option.
+    */
+    CV_WRAP void upload(InputArray arr, Stream& stream);
+
+    /** @brief Performs data download from GpuMat (Blocking call)
+
+    This function copies data from device memory to host memory. As being a blocking call, it is
+    guaranteed that the copy operation is finished when this function returns.
+    */
+    CV_WRAP void download(OutputArray dst) const;
+
+    /** @brief Performs data download from GpuMat (Non-Blocking call)
+
+    This function copies data from device memory to host memory. As being a non-blocking call, this
+    function may return even if the copy operation is not finished.
+
+    The copy operation may be overlapped with operations in other non-default streams if \p stream is
+    not the default stream and \p dst is HostMem allocated with HostMem::PAGE_LOCKED option.
+    */
+    CV_WRAP void download(OutputArray dst, Stream& stream) const;
+
+    //! returns deep copy of the GpuMat, i.e. the data is copied
+    CV_WRAP GpuMat clone() const;
+
+    //! copies the GpuMat content to device memory (Blocking call)
+    void copyTo(OutputArray dst) const;
+    //! bindings overload which copies the GpuMat content to device memory (Blocking call)
+    CV_WRAP void copyTo(CV_OUT GpuMat& dst) const {
+        copyTo(static_cast<OutputArray>(dst));
+    }
+
+    //! copies the GpuMat content to device memory (Non-Blocking call)
+    void copyTo(OutputArray dst, Stream& stream) const;
+    //! bindings overload which copies the GpuMat content to device memory (Non-Blocking call)
+    CV_WRAP void copyTo(CV_OUT GpuMat& dst, Stream& stream) const {
+        copyTo(static_cast<OutputArray>(dst), stream);
+    }
+
+    //! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Blocking call)
+    void copyTo(OutputArray dst, InputArray mask) const;
+    //! bindings overload which copies those GpuMat elements to "m" that are marked with non-zero mask elements (Blocking call)
+    CV_WRAP void copyTo(CV_OUT GpuMat& dst, GpuMat& mask) const {
+        copyTo(static_cast<OutputArray>(dst), static_cast<InputArray>(mask));
+    }
+
+    //! copies those GpuMat elements to "m" that are marked with non-zero mask elements (Non-Blocking call)
+    void copyTo(OutputArray dst, InputArray mask, Stream& stream) const;
+    //! bindings overload which copies those GpuMat elements to "m" that are marked with non-zero mask elements (Non-Blocking call)
+    CV_WRAP void copyTo(CV_OUT GpuMat& dst, GpuMat& mask, Stream& stream) const {
+        copyTo(static_cast<OutputArray>(dst), static_cast<InputArray>(mask), stream);
+    }
+
+    //! sets some of the GpuMat elements to s (Blocking call)
+    CV_WRAP GpuMat& setTo(Scalar s);
+
+    //! sets some of the GpuMat elements to s (Non-Blocking call)
+    CV_WRAP GpuMat& setTo(Scalar s, Stream& stream);
+
+    //! sets some of the GpuMat elements to s, according to the mask (Blocking call)
+    CV_WRAP GpuMat& setTo(Scalar s, InputArray mask);
+
+    //! sets some of the GpuMat elements to s, according to the mask (Non-Blocking call)
+    CV_WRAP GpuMat& setTo(Scalar s, InputArray mask, Stream& stream);
+
+    //! converts GpuMat to another datatype (Blocking call)
+    void convertTo(OutputArray dst, int rtype) const;
+
+    //! converts GpuMat to another datatype (Non-Blocking call)
+    void convertTo(OutputArray dst, int rtype, Stream& stream) const;
+    //! bindings overload which converts GpuMat to another datatype (Non-Blocking call)
+    CV_WRAP void convertTo(CV_OUT GpuMat& dst, int rtype, Stream& stream) const {
+        convertTo(static_cast<OutputArray>(dst), rtype, stream);
+    }
+
+    //! converts GpuMat to another datatype with scaling (Blocking call)
+    void convertTo(OutputArray dst, int rtype, double alpha, double beta = 0.0) const;
+    //! bindings overload which converts GpuMat to another datatype with scaling(Blocking call)
+    CV_WRAP void convertTo(CV_OUT GpuMat& dst, int rtype, double alpha = 1.0, double beta = 0.0) const {
+        convertTo(static_cast<OutputArray>(dst), rtype, alpha, beta);
+    }
+
+    //! converts GpuMat to another datatype with scaling (Non-Blocking call)
+    void convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const;
+
+    //! converts GpuMat to another datatype with scaling (Non-Blocking call)
+    void convertTo(OutputArray dst, int rtype, double alpha, double beta, Stream& stream) const;
+    //! bindings overload which converts GpuMat to another datatype with scaling (Non-Blocking call)
+    CV_WRAP void convertTo(CV_OUT GpuMat& dst, int rtype, double alpha, double beta, Stream& stream) const {
+        convertTo(static_cast<OutputArray>(dst), rtype, alpha, beta, stream);
+    }
+
+    CV_WRAP void assignTo(GpuMat& m, int type = -1) const;
+
+    //! returns pointer to y-th row
+    uchar* ptr(int y = 0);
+    const uchar* ptr(int y = 0) const;
+
+    //! template version of the above method
+    template<typename _Tp> _Tp* ptr(int y = 0);
+    template<typename _Tp> const _Tp* ptr(int y = 0) const;
+
+    template <typename _Tp> operator PtrStepSz<_Tp>() const;
+    template <typename _Tp> operator PtrStep<_Tp>() const;
+
+    //! returns a new GpuMat header for the specified row
+    CV_WRAP GpuMat row(int y) const;
+
+    //! returns a new GpuMat header for the specified column
+    CV_WRAP GpuMat col(int x) const;
+
+    //! ... for the specified row span
+    CV_WRAP GpuMat rowRange(int startrow, int endrow) const;
+    CV_WRAP GpuMat rowRange(Range r) const;
+
+    //! ... for the specified column span
+    CV_WRAP GpuMat colRange(int startcol, int endcol) const;
+    CV_WRAP GpuMat colRange(Range r) const;
+
+    //! extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.)
+    GpuMat operator ()(Range rowRange, Range colRange) const;
+    GpuMat operator ()(Rect roi) const;
+
+    //! creates alternative GpuMat header for the same data, with different
+    //! number of channels and/or different number of rows
+    CV_WRAP GpuMat reshape(int cn, int rows = 0) const;
+
+    //! locates GpuMat header within a parent GpuMat
+    CV_WRAP void locateROI(Size& wholeSize, Point& ofs) const;
+
+    //! moves/resizes the current GpuMat ROI inside the parent GpuMat
+    CV_WRAP GpuMat& adjustROI(int dtop, int dbottom, int dleft, int dright);
+
+    //! returns true iff the GpuMat data is continuous
+    //! (i.e. when there are no gaps between successive rows)
+    CV_WRAP bool isContinuous() const;
+
+    //! returns element size in bytes
+    CV_WRAP size_t elemSize() const;
+
+    //! returns the size of element channel in bytes
+    CV_WRAP size_t elemSize1() const;
+
+    //! returns element type
+    CV_WRAP int type() const;
+
+    //! returns element type
+    CV_WRAP int depth() const;
+
+    //! returns number of channels
+    CV_WRAP int channels() const;
+
+    //! returns step/elemSize1()
+    CV_WRAP size_t step1() const;
+
+    //! returns GpuMat size : width == number of columns, height == number of rows
+    CV_WRAP Size size() const;
+
+    //! returns true if GpuMat data is NULL
+    CV_WRAP bool empty() const;
+
+    // returns pointer to cuda memory
+    CV_WRAP void* cudaPtr() const;
+
+    //! internal use method: updates the continuity flag
+    CV_WRAP void updateContinuityFlag();
+
+    /*! includes several bit-fields:
+    - the magic signature
+    - continuity flag
+    - depth
+    - number of channels
+    */
+    int flags;
+
+    //! the number of rows and columns
+    int rows, cols;
+
+    //! a distance between successive rows in bytes; includes the gap if any
+    CV_PROP size_t step;
+
+    //! pointer to the data
+    uchar* data;
+
+    //! pointer to the reference counter;
+    //! when GpuMat points to user-allocated data, the pointer is NULL
+    int* refcount;
+
+    //! helper fields used in locateROI and adjustROI
+    uchar* datastart;
+    const uchar* dataend;
+
+    //! allocator
+    Allocator* allocator;
+};
+
+struct CV_EXPORTS_W GpuData
+{
+    explicit GpuData(size_t _size);
+     ~GpuData();
+
+    GpuData(const GpuData&) = delete;
+    GpuData& operator=(const GpuData&) = delete;
+
+    GpuData(GpuData&&) = delete;
+    GpuData& operator=(GpuData&&) = delete;
+
+    uchar* data;
+    size_t size;
+};
+
+class CV_EXPORTS_W GpuMatND
+{
+public:
+    using SizeArray = std::vector<int>;
+    using StepArray = std::vector<size_t>;
+    using IndexArray = std::vector<int>;
+
+    //! destructor
+    ~GpuMatND();
+
+    //! default constructor
+    GpuMatND();
+
+    /** @overload
+    @param size Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_16FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    */
+    GpuMatND(SizeArray size, int type);
+
+    /** @overload
+    @param size Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_16FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
+    allocate matrix data. Instead, they just initialize the matrix header that points to the specified
+    data, which means that no data is copied. This operation is very efficient and can be used to
+    process external data using OpenCV functions. The external data is not automatically deallocated, so
+    you should take care of it.
+    @param step Array of _size.size() or _size.size()-1 steps in case of a multi-dimensional array
+    (if specified, the last step must be equal to the element size, otherwise it will be added as such).
+    If not specified, the matrix is assumed to be continuous.
+    */
+    GpuMatND(SizeArray size, int type, void* data, StepArray step = StepArray());
+
+    /** @brief Allocates GPU memory.
+    Suppose there is some GPU memory already allocated. In that case, this method may choose to reuse that
+    GPU memory under the specific condition: it must be of the same size and type, not externally allocated,
+    the GPU memory is continuous(i.e., isContinuous() is true), and is not a sub-matrix of another GpuMatND
+    (i.e., isSubmatrix() is false). In other words, this method guarantees that the GPU memory allocated by
+    this method is always continuous and is not a sub-region of another GpuMatND.
+    */
+    void create(SizeArray size, int type);
+
+    void release();
+
+    void swap(GpuMatND& m) noexcept;
+
+    /** @brief Creates a full copy of the array and the underlying data.
+    The method creates a full copy of the array. It mimics the behavior of Mat::clone(), i.e.
+    the original step is not taken into account. So, the array copy is a continuous array
+    occupying total()\*elemSize() bytes.
+    */
+    GpuMatND clone() const;
+
+    /** @overload
+    This overload is non-blocking, so it may return even if the copy operation is not finished.
+    */
+    GpuMatND clone(Stream& stream) const;
+
+    /** @brief Extracts a sub-matrix.
+    The operator makes a new header for the specified sub-array of \*this.
+    The operator is an O(1) operation, that is, no matrix data is copied.
+    @param ranges Array of selected ranges along each dimension.
+    */
+    GpuMatND operator()(const std::vector<Range>& ranges) const;
+
+    /** @brief Creates a GpuMat header for a 2D plane part of an n-dim matrix.
+    @note The returned GpuMat is constructed with the constructor for user-allocated data.
+    That is, It does not perform reference counting.
+    @note This function does not increment this GpuMatND's reference counter.
+    */
+    GpuMat createGpuMatHeader(IndexArray idx, Range rowRange, Range colRange) const;
+
+    /** @overload
+    Creates a GpuMat header if this GpuMatND is effectively 2D.
+    @note The returned GpuMat is constructed with the constructor for user-allocated data.
+    That is, It does not perform reference counting.
+    @note This function does not increment this GpuMatND's reference counter.
+    */
+    GpuMat createGpuMatHeader() const;
+
+    /** @brief Extracts a 2D plane part of an n-dim matrix.
+    It differs from createGpuMatHeader(IndexArray, Range, Range) in that it clones a part of this
+    GpuMatND to the returned GpuMat.
+    @note This operator does not increment this GpuMatND's reference counter;
+    */
+    GpuMat operator()(IndexArray idx, Range rowRange, Range colRange) const;
+
+    /** @brief Extracts a 2D plane part of an n-dim matrix if this GpuMatND is effectively 2D.
+    It differs from createGpuMatHeader() in that it clones a part of this GpuMatND.
+    @note This operator does not increment this GpuMatND's reference counter;
+    */
+    operator GpuMat() const;
+
+    GpuMatND(const GpuMatND&) = default;
+    GpuMatND& operator=(const GpuMatND&) = default;
+
+#if defined(__GNUC__) && __GNUC__ < 5
+    // error: function '...' defaulted on its first declaration with an exception-specification
+    // that differs from the implicit declaration '...'
+
+    GpuMatND(GpuMatND&&) = default;
+    GpuMatND& operator=(GpuMatND&&) = default;
+#else
+    GpuMatND(GpuMatND&&) noexcept = default;
+    GpuMatND& operator=(GpuMatND&&) noexcept = default;
+#endif
+
+    void upload(InputArray src);
+    void upload(InputArray src, Stream& stream);
+    void download(OutputArray dst) const;
+    void download(OutputArray dst, Stream& stream) const;
+
+    //! returns true iff the GpuMatND data is continuous
+    //! (i.e. when there are no gaps between successive rows)
+    bool isContinuous() const;
+
+    //! returns true if the matrix is a sub-matrix of another matrix
+    bool isSubmatrix() const;
+
+    //! returns element size in bytes
+    size_t elemSize() const;
+
+    //! returns the size of element channel in bytes
+    size_t elemSize1() const;
+
+    //! returns true if data is null
+    bool empty() const;
+
+    //! returns true if not empty and points to external(user-allocated) gpu memory
+    bool external() const;
+
+    //! returns pointer to the first byte of the GPU memory
+    uchar* getDevicePtr() const;
+
+    //! returns the total number of array elements
+    size_t total() const;
+
+    //! returns the size of underlying memory in bytes
+    size_t totalMemSize() const;
+
+    //! returns element type
+    int type() const;
+
+private:
+    //! internal use
+    void setFields(SizeArray size, int type, StepArray step = StepArray());
+
+public:
+    /*! includes several bit-fields:
+    - the magic signature
+    - continuity flag
+    - depth
+    - number of channels
+    */
+    int flags;
+
+    //! matrix dimensionality
+    int dims;
+
+    //! shape of this array
+    SizeArray size;
+
+    /*! step values
+    Their semantics is identical to the semantics of step for Mat.
+    */
+    StepArray step;
+
+private:
+    /*! internal use
+    If this GpuMatND holds external memory, this is empty.
+    */
+    std::shared_ptr<GpuData> data_;
+
+    /*! internal use
+    If this GpuMatND manages memory with reference counting, this value is
+    always equal to data_->data. If this GpuMatND holds external memory,
+    data_ is empty and data points to the external memory.
+    */
+    uchar* data;
+
+    /*! internal use
+    If this GpuMatND is a sub-matrix of a larger matrix, this value is the
+    difference of the first byte between the sub-matrix and the whole matrix.
+    */
+    size_t offset;
+};
+
+/** @brief Creates a continuous matrix.
+
+@param rows Row count.
+@param cols Column count.
+@param type Type of the matrix.
+@param arr Destination matrix. This parameter changes only if it has a proper type and area (
+\f$\texttt{rows} \times \texttt{cols}\f$ ).
+
+Matrix is called continuous if its elements are stored continuously, that is, without gaps at the
+end of each row.
+ */
+CV_EXPORTS_W void createContinuous(int rows, int cols, int type, OutputArray arr);
+
+/** @brief Ensures that the size of a matrix is big enough and the matrix has a proper type.
+
+@param rows Minimum desired number of rows.
+@param cols Minimum desired number of columns.
+@param type Desired matrix type.
+@param arr Destination matrix.
+
+The function does not reallocate memory if the matrix has proper attributes already.
+ */
+CV_EXPORTS_W void ensureSizeIsEnough(int rows, int cols, int type, OutputArray arr);
+
+/** @brief Bindings overload to create a GpuMat from existing GPU memory.
+@param rows Row count.
+@param cols Column count.
+@param type Type of the matrix.
+@param cudaMemoryAddress Address of the allocated GPU memory on the device. This does not allocate matrix data. Instead, it just initializes the matrix header that points to the specified \a cudaMemoryAddress, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it.
+@param step Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. If the parameter is missing (set to Mat::AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize(). See GpuMat::elemSize.
+@note Overload for generation of bindings only, not exported or intended for use internally from C++.
+ */
+CV_EXPORTS_W GpuMat inline createGpuMatFromCudaMemory(int rows, int cols, int type, size_t cudaMemoryAddress, size_t step = Mat::AUTO_STEP) {
+    return GpuMat(rows, cols, type, reinterpret_cast<void*>(cudaMemoryAddress), step);
+}
+
+ /** @overload
+@param size 2D array size: Size(cols, rows). In the Size() constructor, the number of rows and the number of columns go in the reverse order.
+@param type Type of the matrix.
+@param cudaMemoryAddress Address of the allocated GPU memory on the device. This does not allocate matrix data. Instead, it just initializes the matrix header that points to the specified \a cudaMemoryAddress, which means that no data is copied. This operation is very efficient and can be used to process external data using OpenCV functions. The external data is not automatically deallocated, so you should take care of it.
+@param step Number of bytes each matrix row occupies. The value should include the padding bytes at the end of each row, if any. If the parameter is missing (set to Mat::AUTO_STEP ), no padding is assumed and the actual step is calculated as cols*elemSize(). See GpuMat::elemSize.
+@note Overload for generation of bindings only, not exported or intended for use internally from C++.
+ */
+CV_EXPORTS_W inline GpuMat createGpuMatFromCudaMemory(Size size, int type, size_t cudaMemoryAddress, size_t step = Mat::AUTO_STEP) {
+    return GpuMat(size, type, reinterpret_cast<void*>(cudaMemoryAddress), step);
+}
+
+/** @brief BufferPool for use with CUDA streams
+
+BufferPool utilizes Stream's allocator to create new buffers for GpuMat's. It is
+only useful when enabled with #setBufferPoolUsage.
+
+@code
+    setBufferPoolUsage(true);
+@endcode
+
+@note #setBufferPoolUsage must be called \em before any Stream declaration.
+
+Users may specify custom allocator for Stream and may implement their own stream based
+functions utilizing the same underlying GPU memory management.
+
+If custom allocator is not specified, BufferPool utilizes StackAllocator by
+default. StackAllocator allocates a chunk of GPU device memory beforehand,
+and when GpuMat is declared later on, it is given the pre-allocated memory.
+This kind of strategy reduces the number of calls for memory allocating APIs
+such as cudaMalloc or cudaMallocPitch.
+
+Below is an example that utilizes BufferPool with StackAllocator:
+
+@code
+    #include <opencv2/opencv.hpp>
+
+    using namespace cv;
+    using namespace cv::cuda
+
+    int main()
+    {
+        setBufferPoolUsage(true);                               // Tell OpenCV that we are going to utilize BufferPool
+        setBufferPoolConfig(getDevice(), 1024 * 1024 * 64, 2);  // Allocate 64 MB, 2 stacks (default is 10 MB, 5 stacks)
+
+        Stream stream1, stream2;                                // Each stream uses 1 stack
+        BufferPool pool1(stream1), pool2(stream2);
+
+        GpuMat d_src1 = pool1.getBuffer(4096, 4096, CV_8UC1);   // 16MB
+        GpuMat d_dst1 = pool1.getBuffer(4096, 4096, CV_8UC3);   // 48MB, pool1 is now full
+
+        GpuMat d_src2 = pool2.getBuffer(1024, 1024, CV_8UC1);   // 1MB
+        GpuMat d_dst2 = pool2.getBuffer(1024, 1024, CV_8UC3);   // 3MB
+
+        cvtColor(d_src1, d_dst1, cv::COLOR_GRAY2BGR, 0, stream1);
+        cvtColor(d_src2, d_dst2, cv::COLOR_GRAY2BGR, 0, stream2);
+    }
+@endcode
+
+If we allocate another GpuMat on pool1 in the above example, it will be carried out by
+the DefaultAllocator since the stack for pool1 is full.
+
+@code
+    GpuMat d_add1 = pool1.getBuffer(1024, 1024, CV_8UC1);   // Stack for pool1 is full, memory is allocated with DefaultAllocator
+@endcode
+
+If a third stream is declared in the above example, allocating with #getBuffer
+within that stream will also be carried out by the DefaultAllocator because we've run out of
+stacks.
+
+@code
+    Stream stream3;                                         // Only 2 stacks were allocated, we've run out of stacks
+    BufferPool pool3(stream3);
+    GpuMat d_src3 = pool3.getBuffer(1024, 1024, CV_8UC1);   // Memory is allocated with DefaultAllocator
+@endcode
+
+@warning When utilizing StackAllocator, deallocation order is important.
+
+Just like a stack, deallocation must be done in LIFO order. Below is an example of
+erroneous usage that violates LIFO rule. If OpenCV is compiled in Debug mode, this
+sample code will emit CV_Assert error.
+
+@code
+    int main()
+    {
+        setBufferPoolUsage(true);                               // Tell OpenCV that we are going to utilize BufferPool
+        Stream stream;                                          // A default size (10 MB) stack is allocated to this stream
+        BufferPool pool(stream);
+
+        GpuMat mat1 = pool.getBuffer(1024, 1024, CV_8UC1);      // Allocate mat1 (1MB)
+        GpuMat mat2 = pool.getBuffer(1024, 1024, CV_8UC1);      // Allocate mat2 (1MB)
+
+        mat1.release();                                         // erroneous usage : mat2 must be deallocated before mat1
+    }
+@endcode
+
+Since C++ local variables are destroyed in the reverse order of construction,
+the code sample below satisfies the LIFO rule. Local GpuMat's are deallocated
+and the corresponding memory is automatically returned to the pool for later usage.
+
+@code
+    int main()
+    {
+        setBufferPoolUsage(true);                               // Tell OpenCV that we are going to utilize BufferPool
+        setBufferPoolConfig(getDevice(), 1024 * 1024 * 64, 2);  // Allocate 64 MB, 2 stacks (default is 10 MB, 5 stacks)
+
+        Stream stream1, stream2;                                // Each stream uses 1 stack
+        BufferPool pool1(stream1), pool2(stream2);
+
+        for (int i = 0; i < 10; i++)
+        {
+            GpuMat d_src1 = pool1.getBuffer(4096, 4096, CV_8UC1);   // 16MB
+            GpuMat d_dst1 = pool1.getBuffer(4096, 4096, CV_8UC3);   // 48MB, pool1 is now full
+
+            GpuMat d_src2 = pool2.getBuffer(1024, 1024, CV_8UC1);   // 1MB
+            GpuMat d_dst2 = pool2.getBuffer(1024, 1024, CV_8UC3);   // 3MB
+
+            d_src1.setTo(Scalar(i), stream1);
+            d_src2.setTo(Scalar(i), stream2);
+
+            cvtColor(d_src1, d_dst1, cv::COLOR_GRAY2BGR, 0, stream1);
+            cvtColor(d_src2, d_dst2, cv::COLOR_GRAY2BGR, 0, stream2);
+                                                                    // The order of destruction of the local variables is:
+                                                                    //   d_dst2 => d_src2 => d_dst1 => d_src1
+                                                                    // LIFO rule is satisfied, this code runs without error
+        }
+    }
+@endcode
+ */
+class CV_EXPORTS_W BufferPool
+{
+public:
+
+    //! Gets the BufferPool for the given stream.
+    CV_WRAP explicit BufferPool(Stream& stream);
+
+    //! Allocates a new GpuMat of given size and type.
+    CV_WRAP GpuMat getBuffer(int rows, int cols, int type);
+
+// WARNING: unreachable code using Ninja
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(push)
+#pragma warning(disable: 4702)
+#endif
+    //! Allocates a new GpuMat of given size and type.
+    CV_WRAP GpuMat getBuffer(Size size, int type) { return getBuffer(size.height, size.width, type); }
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(pop)
+#endif
+
+    //! Returns the allocator associated with the stream.
+    CV_WRAP Ptr<GpuMat::Allocator> getAllocator() const { return allocator_; }
+
+private:
+    Ptr<GpuMat::Allocator> allocator_;
+};
+
+//! BufferPool management (must be called before Stream creation)
+CV_EXPORTS_W void setBufferPoolUsage(bool on);
+CV_EXPORTS_W void setBufferPoolConfig(int deviceId, size_t stackSize, int stackCount);
+
+//===================================================================================
+// HostMem
+//===================================================================================
+
+/** @brief Class with reference counting wrapping special memory type allocation functions from CUDA.
+
+Its interface is also Mat-like but with additional memory type parameters.
+
+-   **PAGE_LOCKED** sets a page locked memory type used commonly for fast and asynchronous
+    uploading/downloading data from/to GPU.
+-   **SHARED** specifies a zero copy memory allocation that enables mapping the host memory to GPU
+    address space, if supported.
+-   **WRITE_COMBINED** sets the write combined buffer that is not cached by CPU. Such buffers are
+    used to supply GPU with data when GPU only reads it. The advantage is a better CPU cache
+    utilization.
+
+@note Allocation size of such memory types is usually limited. For more details, see *CUDA 2.2
+Pinned Memory APIs* document or *CUDA C Programming Guide*.
+ */
+class CV_EXPORTS_W HostMem
+{
+public:
+    enum AllocType { PAGE_LOCKED = 1, SHARED = 2, WRITE_COMBINED = 4 };
+
+    static MatAllocator* getAllocator(HostMem::AllocType alloc_type = HostMem::AllocType::PAGE_LOCKED);
+
+    CV_WRAP explicit HostMem(HostMem::AllocType alloc_type = HostMem::AllocType::PAGE_LOCKED);
+
+    HostMem(const HostMem& m);
+
+    CV_WRAP HostMem(int rows, int cols, int type, HostMem::AllocType alloc_type = HostMem::AllocType::PAGE_LOCKED);
+    CV_WRAP HostMem(Size size, int type, HostMem::AllocType alloc_type = HostMem::AllocType::PAGE_LOCKED);
+
+    //! creates from host memory with coping data
+    CV_WRAP explicit HostMem(InputArray arr, HostMem::AllocType alloc_type = HostMem::AllocType::PAGE_LOCKED);
+
+    ~HostMem();
+
+    HostMem& operator =(const HostMem& m);
+
+    //! swaps with other smart pointer
+    CV_WRAP void swap(HostMem& b);
+
+    //! returns deep copy of the matrix, i.e. the data is copied
+    CV_WRAP HostMem clone() const;
+
+    //! allocates new matrix data unless the matrix already has specified size and type.
+    CV_WRAP void create(int rows, int cols, int type);
+    void create(Size size, int type);
+
+    //! creates alternative HostMem header for the same data, with different
+    //! number of channels and/or different number of rows
+    CV_WRAP HostMem reshape(int cn, int rows = 0) const;
+
+    //! decrements reference counter and released memory if needed.
+    void release();
+
+    //! returns matrix header with disabled reference counting for HostMem data.
+    CV_WRAP Mat createMatHeader() const;
+
+    /** @brief Maps CPU memory to GPU address space and creates the cuda::GpuMat header without reference counting
+    for it.
+
+    This can be done only if memory was allocated with the SHARED flag and if it is supported by the
+    hardware. Laptops often share video and CPU memory, so address spaces can be mapped, which
+    eliminates an extra copy.
+     */
+    GpuMat createGpuMatHeader() const;
+
+    // Please see cv::Mat for descriptions
+    CV_WRAP bool isContinuous() const;
+    CV_WRAP size_t elemSize() const;
+    CV_WRAP size_t elemSize1() const;
+    CV_WRAP int type() const;
+    CV_WRAP int depth() const;
+    CV_WRAP int channels() const;
+    CV_WRAP size_t step1() const;
+    CV_WRAP Size size() const;
+    CV_WRAP bool empty() const;
+
+    // Please see cv::Mat for descriptions
+    int flags;
+    int rows, cols;
+    CV_PROP size_t step;
+
+    uchar* data;
+    int* refcount;
+
+    uchar* datastart;
+    const uchar* dataend;
+
+    AllocType alloc_type;
+};
+
+/** @brief Page-locks the memory of matrix and maps it for the device(s).
+
+@param m Input matrix.
+ */
+CV_EXPORTS_W void registerPageLocked(Mat& m);
+
+/** @brief Unmaps the memory of matrix and makes it pageable again.
+
+@param m Input matrix.
+ */
+CV_EXPORTS_W void unregisterPageLocked(Mat& m);
+
+//===================================================================================
+// Stream
+//===================================================================================
+
+/** @brief This class encapsulates a queue of asynchronous calls.
+
+@note Currently, you may face problems if an operation is enqueued twice with different data. Some
+functions use the constant GPU memory, and next call may update the memory before the previous one
+has been finished. But calling different operations asynchronously is safe because each operation
+has its own constant buffer. Memory copy/upload/download/set operations to the buffers you hold are
+also safe.
+
+@note The Stream class is not thread-safe. Please use different Stream objects for different CPU threads.
+
+@code
+void thread1()
+{
+    cv::cuda::Stream stream1;
+    cv::cuda::func1(..., stream1);
+}
+
+void thread2()
+{
+    cv::cuda::Stream stream2;
+    cv::cuda::func2(..., stream2);
+}
+@endcode
+
+@note By default all CUDA routines are launched in Stream::Null() object, if the stream is not specified by user.
+In multi-threading environment the stream objects must be passed explicitly (see previous note).
+ */
+class CV_EXPORTS_W Stream
+{
+    typedef void (Stream::*bool_type)() const;
+    void this_type_does_not_support_comparisons() const {}
+
+public:
+    typedef void (*StreamCallback)(int status, void* userData);
+
+    //! creates a new asynchronous stream
+    CV_WRAP Stream();
+
+    //! creates a new asynchronous stream with custom allocator
+    CV_WRAP Stream(const Ptr<GpuMat::Allocator>& allocator);
+
+    /** @brief creates a new Stream using the cudaFlags argument to determine the behaviors of the stream
+
+    @note The cudaFlags parameter is passed to the underlying api cudaStreamCreateWithFlags() and
+    supports the same parameter values.
+    @code
+        // creates an OpenCV cuda::Stream that manages an asynchronous, non-blocking,
+        // non-default CUDA stream
+        cv::cuda::Stream cvStream(cudaStreamNonBlocking);
+    @endcode
+     */
+    CV_WRAP Stream(const size_t cudaFlags);
+
+    /** @brief Returns true if the current stream queue is finished. Otherwise, it returns false.
+    */
+    CV_WRAP bool queryIfComplete() const;
+
+    /** @brief Blocks the current CPU thread until all operations in the stream are complete.
+    */
+    CV_WRAP void waitForCompletion();
+
+    /** @brief Makes a compute stream wait on an event.
+    */
+    CV_WRAP void waitEvent(const Event& event);
+
+    /** @brief Adds a callback to be called on the host after all currently enqueued items in the stream have
+    completed.
+
+    @note Callbacks must not make any CUDA API calls. Callbacks must not perform any synchronization
+    that may depend on outstanding device work or other callbacks that are not mandated to run earlier.
+    Callbacks without a mandated order (in independent streams) execute in undefined order and may be
+    serialized.
+     */
+    void enqueueHostCallback(StreamCallback callback, void* userData);
+
+    //! return Stream object for default CUDA stream
+    CV_WRAP static Stream& Null();
+
+    //! returns true if stream object is not default (!= 0)
+    operator bool_type() const;
+
+    //! return Pointer to CUDA stream
+    CV_WRAP void* cudaPtr() const;
+
+    class Impl;
+
+private:
+    Ptr<Impl> impl_;
+    Stream(const Ptr<Impl>& impl);
+
+    friend struct StreamAccessor;
+    friend class BufferPool;
+    friend class DefaultDeviceInitializer;
+};
+
+
+/** @brief Bindings overload to create a Stream object from the address stored in an existing CUDA Runtime API stream pointer (cudaStream_t).
+@param cudaStreamMemoryAddress Memory address stored in a CUDA Runtime API stream pointer (cudaStream_t). The created Stream object does not perform any allocation or deallocation and simply wraps existing raw CUDA Runtime API stream pointer.
+@note Overload for generation of bindings only, not exported or intended for use internally from C++.
+ */
+CV_EXPORTS_W Stream wrapStream(size_t cudaStreamMemoryAddress);
+
+class CV_EXPORTS_W Event
+{
+public:
+    enum CreateFlags
+    {
+        DEFAULT        = 0x00,  /**< Default event flag */
+        BLOCKING_SYNC  = 0x01,  /**< Event uses blocking synchronization */
+        DISABLE_TIMING = 0x02,  /**< Event will not record timing data */
+        INTERPROCESS   = 0x04   /**< Event is suitable for interprocess use. DisableTiming must be set */
+    };
+
+    CV_WRAP explicit Event(const Event::CreateFlags flags = Event::CreateFlags::DEFAULT);
+
+    //! records an event
+    CV_WRAP void record(Stream& stream = Stream::Null());
+
+    //! queries an event's status
+    CV_WRAP bool queryIfComplete() const;
+
+    //! waits for an event to complete
+    CV_WRAP void waitForCompletion();
+
+    //! computes the elapsed time between events
+    CV_WRAP static float elapsedTime(const Event& start, const Event& end);
+
+    class Impl;
+
+private:
+    Ptr<Impl> impl_;
+    Event(const Ptr<Impl>& impl);
+
+    friend struct EventAccessor;
+};
+CV_ENUM_FLAGS(Event::CreateFlags)
+
+//! @} cudacore_struct
+
+//===================================================================================
+// Initialization & Info
+//===================================================================================
+
+//! @addtogroup cudacore_init
+//! @{
+
+/** @brief Returns the number of installed CUDA-enabled devices.
+
+Use this function before any other CUDA functions calls. If OpenCV is compiled without CUDA support,
+this function returns 0. If the CUDA driver is not installed, or is incompatible, this function
+returns -1.
+ */
+CV_EXPORTS_W int getCudaEnabledDeviceCount();
+
+/** @brief Sets a device and initializes it for the current thread.
+
+@param device System index of a CUDA device starting with 0.
+
+If the call of this function is omitted, a default device is initialized at the fist CUDA usage.
+ */
+CV_EXPORTS_W void setDevice(int device);
+
+/** @brief Returns the current device index set by cuda::setDevice or initialized by default.
+ */
+CV_EXPORTS_W int getDevice();
+
+/** @brief Explicitly destroys and cleans up all resources associated with the current device in the current
+process.
+
+Any subsequent API call to this device will reinitialize the device.
+ */
+CV_EXPORTS_W void resetDevice();
+
+/** @brief Enumeration providing CUDA computing features.
+ */
+enum FeatureSet
+{
+    FEATURE_SET_COMPUTE_10 = 10,
+    FEATURE_SET_COMPUTE_11 = 11,
+    FEATURE_SET_COMPUTE_12 = 12,
+    FEATURE_SET_COMPUTE_13 = 13,
+    FEATURE_SET_COMPUTE_20 = 20,
+    FEATURE_SET_COMPUTE_21 = 21,
+    FEATURE_SET_COMPUTE_30 = 30,
+    FEATURE_SET_COMPUTE_32 = 32,
+    FEATURE_SET_COMPUTE_35 = 35,
+    FEATURE_SET_COMPUTE_50 = 50,
+
+    GLOBAL_ATOMICS = FEATURE_SET_COMPUTE_11,
+    SHARED_ATOMICS = FEATURE_SET_COMPUTE_12,
+    NATIVE_DOUBLE = FEATURE_SET_COMPUTE_13,
+    WARP_SHUFFLE_FUNCTIONS = FEATURE_SET_COMPUTE_30,
+    DYNAMIC_PARALLELISM = FEATURE_SET_COMPUTE_35
+};
+
+//! checks whether current device supports the given feature
+CV_EXPORTS bool deviceSupports(FeatureSet feature_set);
+
+/** @brief Class providing a set of static methods to check what NVIDIA\* card architecture the CUDA module was
+built for.
+
+According to the CUDA C Programming Guide Version 3.2: "PTX code produced for some specific compute
+capability can always be compiled to binary code of greater or equal compute capability".
+ */
+class CV_EXPORTS_W TargetArchs
+{
+public:
+    /** @brief The following method checks whether the module was built with the support of the given feature:
+
+    @param feature_set Features to be checked. See :ocvcuda::FeatureSet.
+     */
+    static bool builtWith(FeatureSet feature_set);
+
+    /** @brief There is a set of methods to check whether the module contains intermediate (PTX) or binary CUDA
+    code for the given architecture(s):
+
+    @param major Major compute capability version.
+    @param minor Minor compute capability version.
+     */
+    CV_WRAP static bool has(int major, int minor);
+    CV_WRAP static bool hasPtx(int major, int minor);
+    CV_WRAP static bool hasBin(int major, int minor);
+
+    CV_WRAP static bool hasEqualOrLessPtx(int major, int minor);
+    CV_WRAP static bool hasEqualOrGreater(int major, int minor);
+    CV_WRAP static bool hasEqualOrGreaterPtx(int major, int minor);
+    CV_WRAP static bool hasEqualOrGreaterBin(int major, int minor);
+};
+
+/** @brief Class providing functionality for querying the specified GPU properties.
+ */
+class CV_EXPORTS_W DeviceInfo
+{
+public:
+    //! creates DeviceInfo object for the current GPU
+    CV_WRAP DeviceInfo();
+
+    /** @brief The constructors.
+
+    @param device_id System index of the CUDA device starting with 0.
+
+    Constructs the DeviceInfo object for the specified device. If device_id parameter is missed, it
+    constructs an object for the current device.
+     */
+    CV_WRAP DeviceInfo(int device_id);
+
+    /** @brief Returns system index of the CUDA device starting with 0.
+    */
+    CV_WRAP int deviceID() const;
+
+    //! ASCII string identifying device
+    const char* name() const;
+
+    //! global memory available on device in bytes
+    CV_WRAP size_t totalGlobalMem() const;
+
+    //! shared memory available per block in bytes
+    CV_WRAP size_t sharedMemPerBlock() const;
+
+    //! 32-bit registers available per block
+    CV_WRAP int regsPerBlock() const;
+
+    //! warp size in threads
+    CV_WRAP int warpSize() const;
+
+    //! maximum pitch in bytes allowed by memory copies
+    CV_WRAP size_t memPitch() const;
+
+    //! maximum number of threads per block
+    CV_WRAP int maxThreadsPerBlock() const;
+
+    //! maximum size of each dimension of a block
+    CV_WRAP Vec3i maxThreadsDim() const;
+
+    //! maximum size of each dimension of a grid
+    CV_WRAP Vec3i maxGridSize() const;
+
+    //! clock frequency in kilohertz
+    CV_WRAP int clockRate() const;
+
+    //! constant memory available on device in bytes
+    CV_WRAP size_t totalConstMem() const;
+
+    //! major compute capability
+    CV_WRAP int majorVersion() const;
+
+    //! minor compute capability
+    CV_WRAP int minorVersion() const;
+
+    //! alignment requirement for textures
+    CV_WRAP size_t textureAlignment() const;
+
+    //! pitch alignment requirement for texture references bound to pitched memory
+    CV_WRAP size_t texturePitchAlignment() const;
+
+    //! number of multiprocessors on device
+    CV_WRAP int multiProcessorCount() const;
+
+    //! specified whether there is a run time limit on kernels
+    CV_WRAP bool kernelExecTimeoutEnabled() const;
+
+    //! device is integrated as opposed to discrete
+    CV_WRAP bool integrated() const;
+
+    //! device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer
+    CV_WRAP bool canMapHostMemory() const;
+
+    enum ComputeMode
+    {
+        ComputeModeDefault,         /**< default compute mode (Multiple threads can use cudaSetDevice with this device) */
+        ComputeModeExclusive,       /**< compute-exclusive-thread mode (Only one thread in one process will be able to use cudaSetDevice with this device) */
+        ComputeModeProhibited,      /**< compute-prohibited mode (No threads can use cudaSetDevice with this device) */
+        ComputeModeExclusiveProcess /**< compute-exclusive-process mode (Many threads in one process will be able to use cudaSetDevice with this device) */
+    };
+
+    //! compute mode
+    CV_WRAP DeviceInfo::ComputeMode computeMode() const;
+
+    //! maximum 1D texture size
+    CV_WRAP int maxTexture1D() const;
+
+    //! maximum 1D mipmapped texture size
+    CV_WRAP int maxTexture1DMipmap() const;
+
+    //! maximum size for 1D textures bound to linear memory
+    CV_WRAP int maxTexture1DLinear() const;
+
+    //! maximum 2D texture dimensions
+    CV_WRAP Vec2i maxTexture2D() const;
+
+    //! maximum 2D mipmapped texture dimensions
+    CV_WRAP Vec2i maxTexture2DMipmap() const;
+
+    //! maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory
+    CV_WRAP Vec3i maxTexture2DLinear() const;
+
+    //! maximum 2D texture dimensions if texture gather operations have to be performed
+    CV_WRAP Vec2i maxTexture2DGather() const;
+
+    //! maximum 3D texture dimensions
+    CV_WRAP Vec3i maxTexture3D() const;
+
+    //! maximum Cubemap texture dimensions
+    CV_WRAP int maxTextureCubemap() const;
+
+    //! maximum 1D layered texture dimensions
+    CV_WRAP Vec2i maxTexture1DLayered() const;
+
+    //! maximum 2D layered texture dimensions
+    CV_WRAP Vec3i maxTexture2DLayered() const;
+
+    //! maximum Cubemap layered texture dimensions
+    CV_WRAP Vec2i maxTextureCubemapLayered() const;
+
+    //! maximum 1D surface size
+    CV_WRAP int maxSurface1D() const;
+
+    //! maximum 2D surface dimensions
+    CV_WRAP Vec2i maxSurface2D() const;
+
+    //! maximum 3D surface dimensions
+    CV_WRAP Vec3i maxSurface3D() const;
+
+    //! maximum 1D layered surface dimensions
+    CV_WRAP Vec2i maxSurface1DLayered() const;
+
+    //! maximum 2D layered surface dimensions
+    CV_WRAP Vec3i maxSurface2DLayered() const;
+
+    //! maximum Cubemap surface dimensions
+    CV_WRAP int maxSurfaceCubemap() const;
+
+    //! maximum Cubemap layered surface dimensions
+    CV_WRAP Vec2i maxSurfaceCubemapLayered() const;
+
+    //! alignment requirements for surfaces
+    CV_WRAP size_t surfaceAlignment() const;
+
+    //! device can possibly execute multiple kernels concurrently
+    CV_WRAP bool concurrentKernels() const;
+
+    //! device has ECC support enabled
+    CV_WRAP bool ECCEnabled() const;
+
+    //! PCI bus ID of the device
+    CV_WRAP int pciBusID() const;
+
+    //! PCI device ID of the device
+    CV_WRAP int pciDeviceID() const;
+
+    //! PCI domain ID of the device
+    CV_WRAP int pciDomainID() const;
+
+    //! true if device is a Tesla device using TCC driver, false otherwise
+    CV_WRAP bool tccDriver() const;
+
+    //! number of asynchronous engines
+    CV_WRAP int asyncEngineCount() const;
+
+    //! device shares a unified address space with the host
+    CV_WRAP bool unifiedAddressing() const;
+
+    //! peak memory clock frequency in kilohertz
+    CV_WRAP int memoryClockRate() const;
+
+    //! global memory bus width in bits
+    CV_WRAP int memoryBusWidth() const;
+
+    //! size of L2 cache in bytes
+    CV_WRAP int l2CacheSize() const;
+
+    //! maximum resident threads per multiprocessor
+    CV_WRAP int maxThreadsPerMultiProcessor() const;
+
+    //! gets free and total device memory
+    CV_WRAP void queryMemory(size_t& totalMemory, size_t& freeMemory) const;
+    CV_WRAP size_t freeMemory() const;
+    CV_WRAP size_t totalMemory() const;
+
+    /** @brief Provides information on CUDA feature support.
+
+    @param feature_set Features to be checked. See cuda::FeatureSet.
+
+    This function returns true if the device has the specified CUDA feature. Otherwise, it returns false
+     */
+    bool supports(FeatureSet feature_set) const;
+
+    /** @brief Checks the CUDA module and device compatibility.
+
+    This function returns true if the CUDA module can be run on the specified device. Otherwise, it
+    returns false .
+     */
+    CV_WRAP bool isCompatible() const;
+
+private:
+    int device_id_;
+};
+
+CV_EXPORTS_W void printCudaDeviceInfo(int device);
+CV_EXPORTS_W void printShortCudaDeviceInfo(int device);
+
+/** @brief Converts an array to half precision floating number.
+
+@param _src input array.
+@param _dst output array.
+@param stream Stream for the asynchronous version.
+@sa convertFp16
+*/
+CV_EXPORTS void convertFp16(InputArray _src, OutputArray _dst, Stream& stream = Stream::Null());
+
+//! @} cudacore_init
+
+}} // namespace cv { namespace cuda {
+
+
+#include "opencv2/core/cuda.inl.hpp"
+
+#endif /* OPENCV_CORE_CUDA_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda.inl.hpp

@@ -0,0 +1,763 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_CUDAINL_HPP
+#define OPENCV_CORE_CUDAINL_HPP
+
+#include "opencv2/core/cuda.hpp"
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda {
+
+//===================================================================================
+// GpuMat
+//===================================================================================
+
+inline
+GpuMat::GpuMat(Allocator* allocator_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
+{}
+
+inline
+GpuMat::GpuMat(int rows_, int cols_, int type_, Allocator* allocator_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
+{
+    if (rows_ > 0 && cols_ > 0)
+        create(rows_, cols_, type_);
+}
+
+inline
+GpuMat::GpuMat(Size size_, int type_, Allocator* allocator_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
+{
+    if (size_.height > 0 && size_.width > 0)
+        create(size_.height, size_.width, type_);
+}
+
+// WARNING: unreachable code using Ninja
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(push)
+#pragma warning(disable: 4702)
+#endif
+inline
+GpuMat::GpuMat(int rows_, int cols_, int type_, Scalar s_, Allocator* allocator_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
+{
+    if (rows_ > 0 && cols_ > 0)
+    {
+        create(rows_, cols_, type_);
+        setTo(s_);
+    }
+}
+
+inline
+GpuMat::GpuMat(Size size_, int type_, Scalar s_, Allocator* allocator_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
+{
+    if (size_.height > 0 && size_.width > 0)
+    {
+        create(size_.height, size_.width, type_);
+        setTo(s_);
+    }
+}
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(pop)
+#endif
+
+inline
+GpuMat::GpuMat(const GpuMat& m)
+    : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), allocator(m.allocator)
+{
+    if (refcount)
+        CV_XADD(refcount, 1);
+}
+
+inline
+GpuMat::GpuMat(InputArray arr, Allocator* allocator_) :
+    flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), allocator(allocator_)
+{
+    upload(arr);
+}
+
+inline
+GpuMat::~GpuMat()
+{
+    release();
+}
+
+inline
+GpuMat& GpuMat::operator =(const GpuMat& m)
+{
+    if (this != &m)
+    {
+        GpuMat temp(m);
+        swap(temp);
+    }
+
+    return *this;
+}
+
+inline
+void GpuMat::create(Size size_, int type_)
+{
+    create(size_.height, size_.width, type_);
+}
+
+inline
+void GpuMat::swap(GpuMat& b)
+{
+    std::swap(flags, b.flags);
+    std::swap(rows, b.rows);
+    std::swap(cols, b.cols);
+    std::swap(step, b.step);
+    std::swap(data, b.data);
+    std::swap(datastart, b.datastart);
+    std::swap(dataend, b.dataend);
+    std::swap(refcount, b.refcount);
+    std::swap(allocator, b.allocator);
+}
+
+inline
+GpuMat GpuMat::clone() const
+{
+    GpuMat m;
+    copyTo(m);
+    return m;
+}
+
+// WARNING: unreachable code using Ninja
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(push)
+#pragma warning(disable: 4702)
+#endif
+inline
+void GpuMat::copyTo(OutputArray dst, InputArray mask) const
+{
+    copyTo(dst, mask, Stream::Null());
+}
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(pop)
+#endif
+
+inline
+GpuMat& GpuMat::setTo(Scalar s)
+{
+    return setTo(s, Stream::Null());
+}
+
+inline
+GpuMat& GpuMat::setTo(Scalar s, InputArray mask)
+{
+    return setTo(s, mask, Stream::Null());
+}
+
+// WARNING: unreachable code using Ninja
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(push)
+#pragma warning(disable: 4702)
+#endif
+inline
+void GpuMat::convertTo(OutputArray dst, int rtype) const
+{
+    convertTo(dst, rtype, Stream::Null());
+}
+
+inline
+void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, double beta) const
+{
+    convertTo(dst, rtype, alpha, beta, Stream::Null());
+}
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(pop)
+#endif
+
+inline
+void GpuMat::convertTo(OutputArray dst, int rtype, double alpha, Stream& stream) const
+{
+    convertTo(dst, rtype, alpha, 0.0, stream);
+}
+
+inline
+void GpuMat::assignTo(GpuMat& m, int _type) const
+{
+    if (_type < 0)
+        m = *this;
+    else
+        convertTo(m, _type);
+}
+
+inline
+uchar* GpuMat::ptr(int y)
+{
+    CV_DbgAssert( (unsigned)y < (unsigned)rows );
+    return data + step * y;
+}
+
+inline
+const uchar* GpuMat::ptr(int y) const
+{
+    CV_DbgAssert( (unsigned)y < (unsigned)rows );
+    return data + step * y;
+}
+
+template<typename _Tp> inline
+_Tp* GpuMat::ptr(int y)
+{
+    return (_Tp*)ptr(y);
+}
+
+template<typename _Tp> inline
+const _Tp* GpuMat::ptr(int y) const
+{
+    return (const _Tp*)ptr(y);
+}
+
+template <class T> inline
+GpuMat::operator PtrStepSz<T>() const
+{
+    return PtrStepSz<T>(rows, cols, (T*)data, step);
+}
+
+template <class T> inline
+GpuMat::operator PtrStep<T>() const
+{
+    return PtrStep<T>((T*)data, step);
+}
+
+inline
+GpuMat GpuMat::row(int y) const
+{
+    return GpuMat(*this, Range(y, y+1), Range::all());
+}
+
+inline
+GpuMat GpuMat::col(int x) const
+{
+    return GpuMat(*this, Range::all(), Range(x, x+1));
+}
+
+inline
+GpuMat GpuMat::rowRange(int startrow, int endrow) const
+{
+    return GpuMat(*this, Range(startrow, endrow), Range::all());
+}
+
+inline
+GpuMat GpuMat::rowRange(Range r) const
+{
+    return GpuMat(*this, r, Range::all());
+}
+
+inline
+GpuMat GpuMat::colRange(int startcol, int endcol) const
+{
+    return GpuMat(*this, Range::all(), Range(startcol, endcol));
+}
+
+inline
+GpuMat GpuMat::colRange(Range r) const
+{
+    return GpuMat(*this, Range::all(), r);
+}
+
+inline
+GpuMat GpuMat::operator ()(Range rowRange_, Range colRange_) const
+{
+    return GpuMat(*this, rowRange_, colRange_);
+}
+
+inline
+GpuMat GpuMat::operator ()(Rect roi) const
+{
+    return GpuMat(*this, roi);
+}
+
+inline
+bool GpuMat::isContinuous() const
+{
+    return (flags & Mat::CONTINUOUS_FLAG) != 0;
+}
+
+inline
+size_t GpuMat::elemSize() const
+{
+    return CV_ELEM_SIZE(flags);
+}
+
+inline
+size_t GpuMat::elemSize1() const
+{
+    return CV_ELEM_SIZE1(flags);
+}
+
+inline
+int GpuMat::type() const
+{
+    return CV_MAT_TYPE(flags);
+}
+
+inline
+int GpuMat::depth() const
+{
+    return CV_MAT_DEPTH(flags);
+}
+
+inline
+int GpuMat::channels() const
+{
+    return CV_MAT_CN(flags);
+}
+
+inline
+size_t GpuMat::step1() const
+{
+    return step / elemSize1();
+}
+
+inline
+Size GpuMat::size() const
+{
+    return Size(cols, rows);
+}
+
+inline
+bool GpuMat::empty() const
+{
+    return data == 0;
+}
+
+inline
+void* GpuMat::cudaPtr() const
+{
+    return data;
+}
+
+static inline
+GpuMat createContinuous(int rows, int cols, int type)
+{
+    GpuMat m;
+    createContinuous(rows, cols, type, m);
+    return m;
+}
+
+static inline
+void createContinuous(Size size, int type, OutputArray arr)
+{
+    createContinuous(size.height, size.width, type, arr);
+}
+
+static inline
+GpuMat createContinuous(Size size, int type)
+{
+    GpuMat m;
+    createContinuous(size, type, m);
+    return m;
+}
+
+static inline
+void ensureSizeIsEnough(Size size, int type, OutputArray arr)
+{
+    ensureSizeIsEnough(size.height, size.width, type, arr);
+}
+
+static inline
+void swap(GpuMat& a, GpuMat& b)
+{
+    a.swap(b);
+}
+
+//===================================================================================
+// GpuMatND
+//===================================================================================
+
+inline
+GpuMatND::GpuMatND() :
+    flags(0), dims(0), data(nullptr), offset(0)
+{
+}
+
+inline
+GpuMatND::GpuMatND(SizeArray _size, int _type) :
+    flags(0), dims(0), data(nullptr), offset(0)
+{
+    create(std::move(_size), _type);
+}
+
+inline
+void GpuMatND::swap(GpuMatND& m) noexcept
+{
+    std::swap(*this, m);
+}
+
+inline
+bool GpuMatND::isContinuous() const
+{
+    return (flags & Mat::CONTINUOUS_FLAG) != 0;
+}
+
+inline
+bool GpuMatND::isSubmatrix() const
+{
+    return (flags & Mat::SUBMATRIX_FLAG) != 0;
+}
+
+inline
+size_t GpuMatND::elemSize() const
+{
+    return CV_ELEM_SIZE(flags);
+}
+
+inline
+size_t GpuMatND::elemSize1() const
+{
+    return CV_ELEM_SIZE1(flags);
+}
+
+inline
+bool GpuMatND::empty() const
+{
+    return data == nullptr;
+}
+
+inline
+bool GpuMatND::external() const
+{
+    return !empty() && data_.use_count() == 0;
+}
+
+inline
+uchar* GpuMatND::getDevicePtr() const
+{
+    return data + offset;
+}
+
+inline
+size_t GpuMatND::total() const
+{
+    size_t p = 1;
+    for(auto s : size)
+        p *= s;
+    return p;
+}
+
+inline
+size_t GpuMatND::totalMemSize() const
+{
+    return size[0] * step[0];
+}
+
+inline
+int GpuMatND::type() const
+{
+    return CV_MAT_TYPE(flags);
+}
+
+//===================================================================================
+// HostMem
+//===================================================================================
+
+inline
+HostMem::HostMem(AllocType alloc_type_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
+{
+}
+
+inline
+HostMem::HostMem(const HostMem& m)
+    : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data), refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), alloc_type(m.alloc_type)
+{
+    if( refcount )
+        CV_XADD(refcount, 1);
+}
+
+inline
+HostMem::HostMem(int rows_, int cols_, int type_, AllocType alloc_type_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
+{
+    if (rows_ > 0 && cols_ > 0)
+        create(rows_, cols_, type_);
+}
+
+inline
+HostMem::HostMem(Size size_, int type_, AllocType alloc_type_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
+{
+    if (size_.height > 0 && size_.width > 0)
+        create(size_.height, size_.width, type_);
+}
+
+inline
+HostMem::HostMem(InputArray arr, AllocType alloc_type_)
+    : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), alloc_type(alloc_type_)
+{
+    arr.getMat().copyTo(*this);
+}
+
+inline
+HostMem::~HostMem()
+{
+    release();
+}
+
+inline
+HostMem& HostMem::operator =(const HostMem& m)
+{
+    if (this != &m)
+    {
+        HostMem temp(m);
+        swap(temp);
+    }
+
+    return *this;
+}
+
+inline
+void HostMem::swap(HostMem& b)
+{
+    std::swap(flags, b.flags);
+    std::swap(rows, b.rows);
+    std::swap(cols, b.cols);
+    std::swap(step, b.step);
+    std::swap(data, b.data);
+    std::swap(datastart, b.datastart);
+    std::swap(dataend, b.dataend);
+    std::swap(refcount, b.refcount);
+    std::swap(alloc_type, b.alloc_type);
+}
+
+inline
+HostMem HostMem::clone() const
+{
+    HostMem m(size(), type(), alloc_type);
+    createMatHeader().copyTo(m);
+    return m;
+}
+
+inline
+void HostMem::create(Size size_, int type_)
+{
+    create(size_.height, size_.width, type_);
+}
+
+inline
+Mat HostMem::createMatHeader() const
+{
+    return Mat(size(), type(), data, step);
+}
+
+inline
+bool HostMem::isContinuous() const
+{
+    return (flags & Mat::CONTINUOUS_FLAG) != 0;
+}
+
+inline
+size_t HostMem::elemSize() const
+{
+    return CV_ELEM_SIZE(flags);
+}
+
+inline
+size_t HostMem::elemSize1() const
+{
+    return CV_ELEM_SIZE1(flags);
+}
+
+inline
+int HostMem::type() const
+{
+    return CV_MAT_TYPE(flags);
+}
+
+inline
+int HostMem::depth() const
+{
+    return CV_MAT_DEPTH(flags);
+}
+
+inline
+int HostMem::channels() const
+{
+    return CV_MAT_CN(flags);
+}
+
+inline
+size_t HostMem::step1() const
+{
+    return step / elemSize1();
+}
+
+inline
+Size HostMem::size() const
+{
+    return Size(cols, rows);
+}
+
+inline
+bool HostMem::empty() const
+{
+    return data == 0;
+}
+
+static inline
+void swap(HostMem& a, HostMem& b)
+{
+    a.swap(b);
+}
+
+//===================================================================================
+// Stream
+//===================================================================================
+
+inline
+Stream::Stream(const Ptr<Impl>& impl)
+    : impl_(impl)
+{
+}
+
+//===================================================================================
+// Event
+//===================================================================================
+
+inline
+Event::Event(const Ptr<Impl>& impl)
+    : impl_(impl)
+{
+}
+
+//===================================================================================
+// Initialization & Info
+//===================================================================================
+
+// WARNING: unreachable code using Ninja
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(push)
+#pragma warning(disable: 4702)
+#endif
+inline
+bool TargetArchs::has(int major, int minor)
+{
+    return hasPtx(major, minor) || hasBin(major, minor);
+}
+
+inline
+bool TargetArchs::hasEqualOrGreater(int major, int minor)
+{
+    return hasEqualOrGreaterPtx(major, minor) || hasEqualOrGreaterBin(major, minor);
+}
+
+inline
+DeviceInfo::DeviceInfo()
+{
+    device_id_ = getDevice();
+}
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(pop)
+#endif
+
+inline
+DeviceInfo::DeviceInfo(int device_id)
+{
+    CV_Assert( device_id >= 0 && device_id < getCudaEnabledDeviceCount() );
+    device_id_ = device_id;
+}
+
+// WARNING: unreachable code using Ninja
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(push)
+#pragma warning(disable: 4702)
+#endif
+inline
+int DeviceInfo::deviceID() const
+{
+    return device_id_;
+}
+
+inline
+size_t DeviceInfo::freeMemory() const
+{
+    size_t _totalMemory = 0, _freeMemory = 0;
+    queryMemory(_totalMemory, _freeMemory);
+    return _freeMemory;
+}
+
+inline
+size_t DeviceInfo::totalMemory() const
+{
+    size_t _totalMemory = 0, _freeMemory = 0;
+    queryMemory(_totalMemory, _freeMemory);
+    return _totalMemory;
+}
+
+inline
+bool DeviceInfo::supports(FeatureSet feature_set) const
+{
+    int version = majorVersion() * 10 + minorVersion();
+    return version >= feature_set;
+}
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(pop)
+#endif
+
+
+}} // namespace cv { namespace cuda {
+
+//===================================================================================
+// Mat
+//===================================================================================
+
+namespace cv {
+
+inline
+Mat::Mat(const cuda::GpuMat& m)
+    : flags(0), dims(0), rows(0), cols(0), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows)
+{
+    m.download(*this);
+}
+
+}
+
+//! @endcond
+
+#endif // OPENCV_CORE_CUDAINL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/block.hpp

@@ -0,0 +1,211 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_DEVICE_BLOCK_HPP
+#define OPENCV_CUDA_DEVICE_BLOCK_HPP
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    struct Block
+    {
+        static __device__ __forceinline__ unsigned int id()
+        {
+            return blockIdx.x;
+        }
+
+        static __device__ __forceinline__ unsigned int stride()
+        {
+            return blockDim.x * blockDim.y * blockDim.z;
+        }
+
+        static __device__ __forceinline__ void sync()
+        {
+            __syncthreads();
+        }
+
+        static __device__ __forceinline__ int flattenedThreadId()
+        {
+            return threadIdx.z * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x;
+        }
+
+        template<typename It, typename T>
+        static __device__ __forceinline__ void fill(It beg, It end, const T& value)
+        {
+            int STRIDE = stride();
+            It t = beg + flattenedThreadId();
+
+            for(; t < end; t += STRIDE)
+                *t = value;
+        }
+
+        template<typename OutIt, typename T>
+        static __device__ __forceinline__ void yota(OutIt beg, OutIt end, T value)
+        {
+            int STRIDE = stride();
+            int tid = flattenedThreadId();
+            value += tid;
+
+            for(OutIt t = beg + tid; t < end; t += STRIDE, value += STRIDE)
+                *t = value;
+        }
+
+        template<typename InIt, typename OutIt>
+        static __device__ __forceinline__ void copy(InIt beg, InIt end, OutIt out)
+        {
+            int STRIDE = stride();
+            InIt  t = beg + flattenedThreadId();
+            OutIt o = out + (t - beg);
+
+            for(; t < end; t += STRIDE, o += STRIDE)
+                *o = *t;
+        }
+
+        template<typename InIt, typename OutIt, class UnOp>
+        static __device__ __forceinline__ void transform(InIt beg, InIt end, OutIt out, UnOp op)
+        {
+            int STRIDE = stride();
+            InIt  t = beg + flattenedThreadId();
+            OutIt o = out + (t - beg);
+
+            for(; t < end; t += STRIDE, o += STRIDE)
+                *o = op(*t);
+        }
+
+        template<typename InIt1, typename InIt2, typename OutIt, class BinOp>
+        static __device__ __forceinline__ void transform(InIt1 beg1, InIt1 end1, InIt2 beg2, OutIt out, BinOp op)
+        {
+            int STRIDE = stride();
+            InIt1 t1 = beg1 + flattenedThreadId();
+            InIt2 t2 = beg2 + flattenedThreadId();
+            OutIt o  = out + (t1 - beg1);
+
+            for(; t1 < end1; t1 += STRIDE, t2 += STRIDE, o += STRIDE)
+                *o = op(*t1, *t2);
+        }
+
+        template<int CTA_SIZE, typename T, class BinOp>
+        static __device__ __forceinline__ void reduce(volatile T* buffer, BinOp op)
+        {
+            int tid = flattenedThreadId();
+            T val =  buffer[tid];
+
+            if (CTA_SIZE >= 1024) { if (tid < 512) buffer[tid] = val = op(val, buffer[tid + 512]); __syncthreads(); }
+            if (CTA_SIZE >=  512) { if (tid < 256) buffer[tid] = val = op(val, buffer[tid + 256]); __syncthreads(); }
+            if (CTA_SIZE >=  256) { if (tid < 128) buffer[tid] = val = op(val, buffer[tid + 128]); __syncthreads(); }
+            if (CTA_SIZE >=  128) { if (tid <  64) buffer[tid] = val = op(val, buffer[tid +  64]); __syncthreads(); }
+
+            if (tid < 32)
+            {
+                if (CTA_SIZE >=   64) { buffer[tid] = val = op(val, buffer[tid +  32]); }
+                if (CTA_SIZE >=   32) { buffer[tid] = val = op(val, buffer[tid +  16]); }
+                if (CTA_SIZE >=   16) { buffer[tid] = val = op(val, buffer[tid +   8]); }
+                if (CTA_SIZE >=    8) { buffer[tid] = val = op(val, buffer[tid +   4]); }
+                if (CTA_SIZE >=    4) { buffer[tid] = val = op(val, buffer[tid +   2]); }
+                if (CTA_SIZE >=    2) { buffer[tid] = val = op(val, buffer[tid +   1]); }
+            }
+        }
+
+        template<int CTA_SIZE, typename T, class BinOp>
+        static __device__ __forceinline__ T reduce(volatile T* buffer, T init, BinOp op)
+        {
+            int tid = flattenedThreadId();
+            T val =  buffer[tid] = init;
+            __syncthreads();
+
+            if (CTA_SIZE >= 1024) { if (tid < 512) buffer[tid] = val = op(val, buffer[tid + 512]); __syncthreads(); }
+            if (CTA_SIZE >=  512) { if (tid < 256) buffer[tid] = val = op(val, buffer[tid + 256]); __syncthreads(); }
+            if (CTA_SIZE >=  256) { if (tid < 128) buffer[tid] = val = op(val, buffer[tid + 128]); __syncthreads(); }
+            if (CTA_SIZE >=  128) { if (tid <  64) buffer[tid] = val = op(val, buffer[tid +  64]); __syncthreads(); }
+
+            if (tid < 32)
+            {
+                if (CTA_SIZE >=   64) { buffer[tid] = val = op(val, buffer[tid +  32]); }
+                if (CTA_SIZE >=   32) { buffer[tid] = val = op(val, buffer[tid +  16]); }
+                if (CTA_SIZE >=   16) { buffer[tid] = val = op(val, buffer[tid +   8]); }
+                if (CTA_SIZE >=    8) { buffer[tid] = val = op(val, buffer[tid +   4]); }
+                if (CTA_SIZE >=    4) { buffer[tid] = val = op(val, buffer[tid +   2]); }
+                if (CTA_SIZE >=    2) { buffer[tid] = val = op(val, buffer[tid +   1]); }
+            }
+            __syncthreads();
+            return buffer[0];
+        }
+
+        template <typename T, class BinOp>
+        static __device__ __forceinline__ void reduce_n(T* data, unsigned int n, BinOp op)
+        {
+            int ftid = flattenedThreadId();
+            int sft = stride();
+
+            if (sft < n)
+            {
+                for (unsigned int i = sft + ftid; i < n; i += sft)
+                    data[ftid] = op(data[ftid], data[i]);
+
+                __syncthreads();
+
+                n = sft;
+            }
+
+            while (n > 1)
+            {
+                unsigned int half = n/2;
+
+                if (ftid < half)
+                    data[ftid] = op(data[ftid], data[n - ftid - 1]);
+
+                __syncthreads();
+
+                n = n - half;
+            }
+        }
+    };
+}}}
+
+//! @endcond
+
+#endif /* OPENCV_CUDA_DEVICE_BLOCK_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/border_interpolate.hpp

@@ -0,0 +1,722 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_BORDER_INTERPOLATE_HPP
+#define OPENCV_CUDA_BORDER_INTERPOLATE_HPP
+
+#include "saturate_cast.hpp"
+#include "vec_traits.hpp"
+#include "vec_math.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    //////////////////////////////////////////////////////////////
+    // BrdConstant
+
+    template <typename D> struct BrdRowConstant
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdRowConstant(int width_, const D& val_ = VecTraits<D>::all(0)) : width(width_), val(val_) {}
+
+        template <typename T> __device__ __forceinline__ D at_low(int x, const T* data) const
+        {
+            return x >= 0 ? saturate_cast<D>(data[x]) : val;
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int x, const T* data) const
+        {
+            return x < width ? saturate_cast<D>(data[x]) : val;
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int x, const T* data) const
+        {
+            return (x >= 0 && x < width) ? saturate_cast<D>(data[x]) : val;
+        }
+
+        int width;
+        D val;
+    };
+
+    template <typename D> struct BrdColConstant
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdColConstant(int height_, const D& val_ = VecTraits<D>::all(0)) : height(height_), val(val_) {}
+
+        template <typename T> __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const
+        {
+            return y >= 0 ? saturate_cast<D>(*(const T*)((const char*)data + y * step)) : val;
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const
+        {
+            return y < height ? saturate_cast<D>(*(const T*)((const char*)data + y * step)) : val;
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, const T* data, size_t step) const
+        {
+            return (y >= 0 && y < height) ? saturate_cast<D>(*(const T*)((const char*)data + y * step)) : val;
+        }
+
+        int height;
+        D val;
+    };
+
+    template <typename D> struct BrdConstant
+    {
+        typedef D result_type;
+
+        __host__ __device__ __forceinline__ BrdConstant(int height_, int width_, const D& val_ = VecTraits<D>::all(0)) : height(height_), width(width_), val(val_)
+        {
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const
+        {
+            return (x >= 0 && x < width && y >= 0 && y < height) ? saturate_cast<D>(((const T*)((const uchar*)data + y * step))[x]) : val;
+        }
+
+        template <typename Ptr2D> __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const
+        {
+            return (x >= 0 && x < width && y >= 0 && y < height) ? saturate_cast<D>(src(y, x)) : val;
+        }
+
+        int height;
+        int width;
+        D val;
+    };
+
+    //////////////////////////////////////////////////////////////
+    // BrdReplicate
+
+    template <typename D> struct BrdRowReplicate
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdRowReplicate(int width) : last_col(width - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdRowReplicate(int width, U) : last_col(width - 1) {}
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return ::max(x, 0);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return ::min(x, last_col);
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_low(idx_col_high(x));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_low(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_high(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col(x)]);
+        }
+
+        int last_col;
+    };
+
+    template <typename D> struct BrdColReplicate
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdColReplicate(int height) : last_row(height - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdColReplicate(int height, U) : last_row(height - 1) {}
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return ::max(y, 0);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return ::min(y, last_row);
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_low(idx_row_high(y));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const T*)((const char*)data + idx_row_low(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const T*)((const char*)data + idx_row_high(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const T*)((const char*)data + idx_row(y) * step));
+        }
+
+        int last_row;
+    };
+
+    template <typename D> struct BrdReplicate
+    {
+        typedef D result_type;
+
+        __host__ __device__ __forceinline__ BrdReplicate(int height, int width) : last_row(height - 1), last_col(width - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdReplicate(int height, int width, U) : last_row(height - 1), last_col(width - 1) {}
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return ::max(y, 0);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return ::min(y, last_row);
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_low(idx_row_high(y));
+        }
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return ::max(x, 0);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return ::min(x, last_col);
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_low(idx_col_high(x));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]);
+        }
+
+        template <typename Ptr2D> __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const
+        {
+            return saturate_cast<D>(src(idx_row(y), idx_col(x)));
+        }
+
+        int last_row;
+        int last_col;
+    };
+
+    //////////////////////////////////////////////////////////////
+    // BrdReflect101
+
+    template <typename D> struct BrdRowReflect101
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdRowReflect101(int width) : last_col(width - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdRowReflect101(int width, U) : last_col(width - 1) {}
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return ::abs(x) % (last_col + 1);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return ::abs(last_col - ::abs(last_col - x)) % (last_col + 1);
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_low(idx_col_high(x));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_low(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_high(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col(x)]);
+        }
+
+        int last_col;
+    };
+
+    template <typename D> struct BrdColReflect101
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdColReflect101(int height) : last_row(height - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdColReflect101(int height, U) : last_row(height - 1) {}
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return ::abs(y) % (last_row + 1);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return ::abs(last_row - ::abs(last_row - y)) % (last_row + 1);
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_low(idx_row_high(y));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row_low(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row_high(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row(y) * step));
+        }
+
+        int last_row;
+    };
+
+    template <typename D> struct BrdReflect101
+    {
+        typedef D result_type;
+
+        __host__ __device__ __forceinline__ BrdReflect101(int height, int width) : last_row(height - 1), last_col(width - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdReflect101(int height, int width, U) : last_row(height - 1), last_col(width - 1) {}
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return ::abs(y) % (last_row + 1);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return ::abs(last_row - ::abs(last_row - y)) % (last_row + 1);
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_low(idx_row_high(y));
+        }
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return ::abs(x) % (last_col + 1);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return ::abs(last_col - ::abs(last_col - x)) % (last_col + 1);
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_low(idx_col_high(x));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]);
+        }
+
+        template <typename Ptr2D> __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const
+        {
+            return saturate_cast<D>(src(idx_row(y), idx_col(x)));
+        }
+
+        int last_row;
+        int last_col;
+    };
+
+    //////////////////////////////////////////////////////////////
+    // BrdReflect
+
+    template <typename D> struct BrdRowReflect
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdRowReflect(int width) : last_col(width - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdRowReflect(int width, U) : last_col(width - 1) {}
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return (::abs(x) - (x < 0)) % (last_col + 1);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return ::abs(last_col - ::abs(last_col - x) + (x > last_col)) % (last_col + 1);
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_high(::abs(x) - (x < 0));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_low(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_high(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col(x)]);
+        }
+
+        int last_col;
+    };
+
+    template <typename D> struct BrdColReflect
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdColReflect(int height) : last_row(height - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdColReflect(int height, U) : last_row(height - 1) {}
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return (::abs(y) - (y < 0)) % (last_row + 1);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return ::abs(last_row - ::abs(last_row - y) + (y > last_row)) % (last_row + 1);
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_high(::abs(y) - (y < 0));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row_low(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row_high(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row(y) * step));
+        }
+
+        int last_row;
+    };
+
+    template <typename D> struct BrdReflect
+    {
+        typedef D result_type;
+
+        __host__ __device__ __forceinline__ BrdReflect(int height, int width) : last_row(height - 1), last_col(width - 1) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdReflect(int height, int width, U) : last_row(height - 1), last_col(width - 1) {}
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return (::abs(y) - (y < 0)) % (last_row + 1);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return /*::abs*/(last_row - ::abs(last_row - y) + (y > last_row)) /*% (last_row + 1)*/;
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_low(idx_row_high(y));
+        }
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return (::abs(x) - (x < 0)) % (last_col + 1);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return (last_col - ::abs(last_col - x) + (x > last_col));
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_low(idx_col_high(x));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]);
+        }
+
+        template <typename Ptr2D> __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const
+        {
+            return saturate_cast<D>(src(idx_row(y), idx_col(x)));
+        }
+
+        int last_row;
+        int last_col;
+    };
+
+    //////////////////////////////////////////////////////////////
+    // BrdWrap
+
+    template <typename D> struct BrdRowWrap
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdRowWrap(int width_) : width(width_) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdRowWrap(int width_, U) : width(width_) {}
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return (x >= 0) * x + (x < 0) * (x - ((x - width + 1) / width) * width);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return (x < width) * x + (x >= width) * (x % width);
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_high(idx_col_low(x));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_low(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col_high(x)]);
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int x, const T* data) const
+        {
+            return saturate_cast<D>(data[idx_col(x)]);
+        }
+
+        int width;
+    };
+
+    template <typename D> struct BrdColWrap
+    {
+        typedef D result_type;
+
+        explicit __host__ __device__ __forceinline__ BrdColWrap(int height_) : height(height_) {}
+        template <typename U> __host__ __device__ __forceinline__ BrdColWrap(int height_, U) : height(height_) {}
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return (y >= 0) * y + (y < 0) * (y - ((y - height + 1) / height) * height);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return (y < height) * y + (y >= height) * (y % height);
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_high(idx_row_low(y));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_low(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row_low(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at_high(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row_high(y) * step));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(*(const D*)((const char*)data + idx_row(y) * step));
+        }
+
+        int height;
+    };
+
+    template <typename D> struct BrdWrap
+    {
+        typedef D result_type;
+
+        __host__ __device__ __forceinline__ BrdWrap(int height_, int width_) :
+            height(height_), width(width_)
+        {
+        }
+        template <typename U>
+        __host__ __device__ __forceinline__ BrdWrap(int height_, int width_, U) :
+            height(height_), width(width_)
+        {
+        }
+
+        __device__ __forceinline__ int idx_row_low(int y) const
+        {
+            return (y >= 0) ? y : (y - ((y - height + 1) / height) * height);
+        }
+
+        __device__ __forceinline__ int idx_row_high(int y) const
+        {
+            return (y < height) ? y : (y % height);
+        }
+
+        __device__ __forceinline__ int idx_row(int y) const
+        {
+            return idx_row_high(idx_row_low(y));
+        }
+
+        __device__ __forceinline__ int idx_col_low(int x) const
+        {
+            return (x >= 0) ? x : (x - ((x - width + 1) / width) * width);
+        }
+
+        __device__ __forceinline__ int idx_col_high(int x) const
+        {
+            return (x < width) ? x : (x % width);
+        }
+
+        __device__ __forceinline__ int idx_col(int x) const
+        {
+            return idx_col_high(idx_col_low(x));
+        }
+
+        template <typename T> __device__ __forceinline__ D at(int y, int x, const T* data, size_t step) const
+        {
+            return saturate_cast<D>(((const T*)((const char*)data + idx_row(y) * step))[idx_col(x)]);
+        }
+
+        template <typename Ptr2D> __device__ __forceinline__ D at(typename Ptr2D::index_type y, typename Ptr2D::index_type x, const Ptr2D& src) const
+        {
+            return saturate_cast<D>(src(idx_row(y), idx_col(x)));
+        }
+
+        int height;
+        int width;
+    };
+
+    //////////////////////////////////////////////////////////////
+    // BorderReader
+
+    template <typename Ptr2D, typename B> struct BorderReader
+    {
+        typedef typename B::result_type elem_type;
+        typedef typename Ptr2D::index_type index_type;
+
+        __host__ __device__ __forceinline__ BorderReader(const Ptr2D& ptr_, const B& b_) : ptr(ptr_), b(b_) {}
+
+        __device__ __forceinline__ elem_type operator ()(index_type y, index_type x) const
+        {
+            return b.at(y, x, ptr);
+        }
+
+        Ptr2D ptr;
+        B b;
+    };
+
+    // under win32 there is some bug with templated types that passed as kernel parameters
+    // with this specialization all works fine
+    template <typename Ptr2D, typename D> struct BorderReader< Ptr2D, BrdConstant<D> >
+    {
+        typedef typename BrdConstant<D>::result_type elem_type;
+        typedef typename Ptr2D::index_type index_type;
+
+        __host__ __device__ __forceinline__ BorderReader(const Ptr2D& src_, const BrdConstant<D>& b) :
+            src(src_), height(b.height), width(b.width), val(b.val)
+        {
+        }
+
+        __device__ __forceinline__ D operator ()(index_type y, index_type x) const
+        {
+            return (x >= 0 && x < width && y >= 0 && y < height) ? saturate_cast<D>(src(y, x)) : val;
+        }
+
+        Ptr2D src;
+        int height;
+        int width;
+        D val;
+    };
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_BORDER_INTERPOLATE_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/color.hpp

@@ -0,0 +1,309 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_COLOR_HPP
+#define OPENCV_CUDA_COLOR_HPP
+
+#include "detail/color_detail.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    // All OPENCV_CUDA_IMPLEMENT_*_TRAITS(ColorSpace1_to_ColorSpace2, ...) macros implements
+    // template <typename T> class ColorSpace1_to_ColorSpace2_traits
+    // {
+    //     typedef ... functor_type;
+    //     static __host__ __device__ functor_type create_functor();
+    // };
+
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgr_to_rgb, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgr_to_bgra, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgr_to_rgba, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgra_to_bgr, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgra_to_rgb, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS(bgra_to_rgba, 4, 4, 2)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgr_to_bgr555, 3, 0, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgr_to_bgr565, 3, 0, 6)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgb_to_bgr555, 3, 2, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgb_to_bgr565, 3, 2, 6)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgra_to_bgr555, 4, 0, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(bgra_to_bgr565, 4, 0, 6)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgba_to_bgr555, 4, 2, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS(rgba_to_bgr565, 4, 2, 6)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2RGB5x5_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_rgb, 3, 2, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_rgb, 3, 2, 6)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_bgr, 3, 0, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_bgr, 3, 0, 6)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_rgba, 4, 2, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_rgba, 4, 2, 6)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr555_to_bgra, 4, 0, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS(bgr565_to_bgra, 4, 0, 6)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB5x52RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_GRAY2RGB_TRAITS(gray_to_bgr, 3)
+    OPENCV_CUDA_IMPLEMENT_GRAY2RGB_TRAITS(gray_to_bgra, 4)
+
+    #undef OPENCV_CUDA_IMPLEMENT_GRAY2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_GRAY2RGB5x5_TRAITS(gray_to_bgr555, 5)
+    OPENCV_CUDA_IMPLEMENT_GRAY2RGB5x5_TRAITS(gray_to_bgr565, 6)
+
+    #undef OPENCV_CUDA_IMPLEMENT_GRAY2RGB5x5_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB5x52GRAY_TRAITS(bgr555_to_gray, 5)
+    OPENCV_CUDA_IMPLEMENT_RGB5x52GRAY_TRAITS(bgr565_to_gray, 6)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB5x52GRAY_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(rgb_to_gray, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(bgr_to_gray, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(rgba_to_gray, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS(bgra_to_gray, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2GRAY_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgb_to_yuv, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgba_to_yuv, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgb_to_yuv4, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(rgba_to_yuv4, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgr_to_yuv, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgra_to_yuv, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgr_to_yuv4, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS(bgra_to_yuv4, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2YUV_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_rgb, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_rgba, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_rgb, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_rgba, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_bgr, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv_to_bgra, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_bgr, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS(yuv4_to_bgra, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_YUV2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgb_to_YCrCb, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgba_to_YCrCb, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgb_to_YCrCb4, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(rgba_to_YCrCb4, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgr_to_YCrCb, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgra_to_YCrCb, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgr_to_YCrCb4, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS(bgra_to_YCrCb4, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2YCrCb_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_rgb, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_rgba, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_rgb, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_rgba, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_bgr, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb_to_bgra, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_bgr, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS(YCrCb4_to_bgra, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_YCrCb2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgb_to_xyz, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgba_to_xyz, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgb_to_xyz4, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(rgba_to_xyz4, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgr_to_xyz, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgra_to_xyz, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgr_to_xyz4, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS(bgra_to_xyz4, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2XYZ_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_rgb, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_rgb, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_rgba, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_rgba, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_bgr, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_bgr, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz_to_bgra, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS(xyz4_to_bgra, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_XYZ2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgb_to_hsv, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgba_to_hsv, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgb_to_hsv4, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(rgba_to_hsv4, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgr_to_hsv, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgra_to_hsv, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgr_to_hsv4, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS(bgra_to_hsv4, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2HSV_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_rgb, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_rgba, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_rgb, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_rgba, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_bgr, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv_to_bgra, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_bgr, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS(hsv4_to_bgra, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_HSV2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgb_to_hls, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgba_to_hls, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgb_to_hls4, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(rgba_to_hls4, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgr_to_hls, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgra_to_hls, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgr_to_hls4, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS(bgra_to_hls4, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2HLS_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_rgb, 3, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_rgba, 3, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_rgb, 4, 3, 2)
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_rgba, 4, 4, 2)
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_bgr, 3, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls_to_bgra, 3, 4, 0)
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_bgr, 4, 3, 0)
+    OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS(hls4_to_bgra, 4, 4, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_HLS2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgb_to_lab, 3, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgba_to_lab, 4, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgb_to_lab4, 3, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(rgba_to_lab4, 4, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgr_to_lab, 3, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgra_to_lab, 4, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgr_to_lab4, 3, 4, true, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(bgra_to_lab4, 4, 4, true, 0)
+
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgb_to_lab, 3, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgba_to_lab, 4, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgb_to_lab4, 3, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lrgba_to_lab4, 4, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgr_to_lab, 3, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgra_to_lab, 4, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgr_to_lab4, 3, 4, false, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS(lbgra_to_lab4, 4, 4, false, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2Lab_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_rgb, 3, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_rgb, 4, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_rgba, 3, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_rgba, 4, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_bgr, 3, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_bgr, 4, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_bgra, 3, 4, true, 0)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_bgra, 4, 4, true, 0)
+
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lrgb, 3, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lrgb, 4, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lrgba, 3, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lrgba, 4, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lbgr, 3, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lbgr, 4, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab_to_lbgra, 3, 4, false, 0)
+    OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS(lab4_to_lbgra, 4, 4, false, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_Lab2RGB_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgb_to_luv, 3, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgba_to_luv, 4, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgb_to_luv4, 3, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(rgba_to_luv4, 4, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgr_to_luv, 3, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgra_to_luv, 4, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgr_to_luv4, 3, 4, true, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(bgra_to_luv4, 4, 4, true, 0)
+
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgb_to_luv, 3, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgba_to_luv, 4, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgb_to_luv4, 3, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lrgba_to_luv4, 4, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgr_to_luv, 3, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgra_to_luv, 4, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgr_to_luv4, 3, 4, false, 0)
+    OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS(lbgra_to_luv4, 4, 4, false, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_RGB2Luv_TRAITS
+
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_rgb, 3, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_rgb, 4, 3, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_rgba, 3, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_rgba, 4, 4, true, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_bgr, 3, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_bgr, 4, 3, true, 0)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_bgra, 3, 4, true, 0)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_bgra, 4, 4, true, 0)
+
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lrgb, 3, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lrgb, 4, 3, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lrgba, 3, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lrgba, 4, 4, false, 2)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lbgr, 3, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lbgr, 4, 3, false, 0)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv_to_lbgra, 3, 4, false, 0)
+    OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS(luv4_to_lbgra, 4, 4, false, 0)
+
+    #undef OPENCV_CUDA_IMPLEMENT_Luv2RGB_TRAITS
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_COLOR_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/common.hpp

@@ -0,0 +1,131 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_COMMON_HPP
+#define OPENCV_CUDA_COMMON_HPP
+
+#include <cuda_runtime.h>
+#include "opencv2/core/cuda_types.hpp"
+#include "opencv2/core/cvdef.h"
+#include "opencv2/core/base.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+#ifndef CV_PI_F
+    #ifndef CV_PI
+        #define CV_PI_F 3.14159265f
+    #else
+        #define CV_PI_F ((float)CV_PI)
+    #endif
+#endif
+
+namespace cv { namespace cuda {
+    static inline void checkCudaError(cudaError_t err, const char* file, const int line, const char* func)
+    {
+        if (cudaSuccess != err) {
+            cudaGetLastError(); // reset the last stored error to cudaSuccess
+            cv::error(cv::Error::GpuApiCallError, cudaGetErrorString(err), func, file, line);
+        }
+    }
+}}
+
+#ifndef cudaSafeCall
+    #define cudaSafeCall(expr)  cv::cuda::checkCudaError(expr, __FILE__, __LINE__, CV_Func)
+#endif
+
+namespace cv { namespace cuda
+{
+    template <typename T> static inline bool isAligned(const T* ptr, size_t size)
+    {
+        return reinterpret_cast<size_t>(ptr) % size == 0;
+    }
+
+    static inline bool isAligned(size_t step, size_t size)
+    {
+        return step % size == 0;
+    }
+}}
+
+namespace cv { namespace cuda
+{
+    namespace device
+    {
+        __host__ __device__ __forceinline__ int divUp(int total, int grain)
+        {
+            return (total + grain - 1) / grain;
+        }
+
+#if (CUDART_VERSION >= 12000)
+        template<class T> inline void createTextureObjectPitch2D(cudaTextureObject_t*, PtrStepSz<T>&, const cudaTextureDesc&) {
+            CV_Error(cv::Error::GpuNotSupported, "Function removed in CUDA SDK 12"); }
+#else
+        //TODO: remove from OpenCV 5.x
+        template<class T> inline void bindTexture(const textureReference* tex, const PtrStepSz<T>& img)
+        {
+            cudaChannelFormatDesc desc = cudaCreateChannelDesc<T>();
+            cudaSafeCall( cudaBindTexture2D(0, tex, img.ptr(), &desc, img.cols, img.rows, img.step) );
+        }
+
+        template<class T> inline void createTextureObjectPitch2D(cudaTextureObject_t* tex, PtrStepSz<T>& img, const cudaTextureDesc& texDesc)
+        {
+            cudaResourceDesc resDesc;
+            memset(&resDesc, 0, sizeof(resDesc));
+            resDesc.resType = cudaResourceTypePitch2D;
+            resDesc.res.pitch2D.devPtr = static_cast<void*>(img.ptr());
+            resDesc.res.pitch2D.height = img.rows;
+            resDesc.res.pitch2D.width = img.cols;
+            resDesc.res.pitch2D.pitchInBytes = img.step;
+            resDesc.res.pitch2D.desc = cudaCreateChannelDesc<T>();
+
+            cudaSafeCall( cudaCreateTextureObject(tex, &resDesc, &texDesc, NULL) );
+        }
+#endif
+    }
+}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_COMMON_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/datamov_utils.hpp

@@ -0,0 +1,113 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_DATAMOV_UTILS_HPP
+#define OPENCV_CUDA_DATAMOV_UTILS_HPP
+
+#include "common.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 200
+
+        // for Fermi memory space is detected automatically
+        template <typename T> struct ForceGlob
+        {
+            __device__ __forceinline__ static void Load(const T* ptr, int offset, T& val)  { val = ptr[offset];  }
+        };
+
+    #else // __CUDA_ARCH__ >= 200
+
+        #if defined(_WIN64) || defined(__LP64__)
+            // 64-bit register modifier for inlined asm
+            #define OPENCV_CUDA_ASM_PTR "l"
+        #else
+            // 32-bit register modifier for inlined asm
+            #define OPENCV_CUDA_ASM_PTR "r"
+        #endif
+
+        template<class T> struct ForceGlob;
+
+        #define OPENCV_CUDA_DEFINE_FORCE_GLOB(base_type, ptx_type, reg_mod) \
+            template <> struct ForceGlob<base_type> \
+            { \
+                __device__ __forceinline__ static void Load(const base_type* ptr, int offset, base_type& val) \
+                { \
+                    asm("ld.global."#ptx_type" %0, [%1];" : "="#reg_mod(val) : OPENCV_CUDA_ASM_PTR(ptr + offset)); \
+                } \
+            };
+
+        #define OPENCV_CUDA_DEFINE_FORCE_GLOB_B(base_type, ptx_type) \
+            template <> struct ForceGlob<base_type> \
+            { \
+                __device__ __forceinline__ static void Load(const base_type* ptr, int offset, base_type& val) \
+                { \
+                    asm("ld.global."#ptx_type" %0, [%1];" : "=r"(*reinterpret_cast<uint*>(&val)) : OPENCV_CUDA_ASM_PTR(ptr + offset)); \
+                } \
+            };
+
+            OPENCV_CUDA_DEFINE_FORCE_GLOB_B(uchar,  u8)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB_B(schar,  s8)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB_B(char,   b8)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB  (ushort, u16, h)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB  (short,  s16, h)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB  (uint,   u32, r)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB  (int,    s32, r)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB  (float,  f32, f)
+            OPENCV_CUDA_DEFINE_FORCE_GLOB  (double, f64, d)
+
+        #undef OPENCV_CUDA_DEFINE_FORCE_GLOB
+        #undef OPENCV_CUDA_DEFINE_FORCE_GLOB_B
+        #undef OPENCV_CUDA_ASM_PTR
+
+    #endif // __CUDA_ARCH__ >= 200
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_DATAMOV_UTILS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/detail/reduce.hpp

@@ -0,0 +1,394 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_REDUCE_DETAIL_HPP
+#define OPENCV_CUDA_REDUCE_DETAIL_HPP
+
+#include <thrust/tuple.h>
+#include "../warp.hpp"
+#include "../warp_shuffle.hpp"
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    namespace reduce_detail
+    {
+        template <typename T> struct GetType;
+        template <typename T> struct GetType<T*>
+        {
+            typedef T type;
+        };
+        template <typename T> struct GetType<volatile T*>
+        {
+            typedef T type;
+        };
+        template <typename T> struct GetType<T&>
+        {
+            typedef T type;
+        };
+
+        template <unsigned int I, unsigned int N>
+        struct For
+        {
+            template <class PointerTuple, class ValTuple>
+            static __device__ void loadToSmem(const PointerTuple& smem, const ValTuple& val, unsigned int tid)
+            {
+                thrust::get<I>(smem)[tid] = thrust::get<I>(val);
+
+                For<I + 1, N>::loadToSmem(smem, val, tid);
+            }
+            template <class PointerTuple, class ValTuple>
+            static __device__ void loadFromSmem(const PointerTuple& smem, const ValTuple& val, unsigned int tid)
+            {
+                thrust::get<I>(val) = thrust::get<I>(smem)[tid];
+
+                For<I + 1, N>::loadFromSmem(smem, val, tid);
+            }
+
+            template <class PointerTuple, class ValTuple, class OpTuple>
+            static __device__ void merge(const PointerTuple& smem, const ValTuple& val, unsigned int tid, unsigned int delta, const OpTuple& op)
+            {
+                typename GetType<typename thrust::tuple_element<I, PointerTuple>::type>::type reg = thrust::get<I>(smem)[tid + delta];
+                thrust::get<I>(smem)[tid] = thrust::get<I>(val) = thrust::get<I>(op)(thrust::get<I>(val), reg);
+
+                For<I + 1, N>::merge(smem, val, tid, delta, op);
+            }
+            template <class ValTuple, class OpTuple>
+            static __device__ void mergeShfl(const ValTuple& val, unsigned int delta, unsigned int width, const OpTuple& op)
+            {
+                typename GetType<typename thrust::tuple_element<I, ValTuple>::type>::type reg = shfl_down(thrust::get<I>(val), delta, width);
+                thrust::get<I>(val) = thrust::get<I>(op)(thrust::get<I>(val), reg);
+
+                For<I + 1, N>::mergeShfl(val, delta, width, op);
+            }
+        };
+        template <unsigned int N>
+        struct For<N, N>
+        {
+            template <class PointerTuple, class ValTuple>
+            static __device__ void loadToSmem(const PointerTuple&, const ValTuple&, unsigned int)
+            {
+            }
+            template <class PointerTuple, class ValTuple>
+            static __device__ void loadFromSmem(const PointerTuple&, const ValTuple&, unsigned int)
+            {
+            }
+
+            template <class PointerTuple, class ValTuple, class OpTuple>
+            static __device__ void merge(const PointerTuple&, const ValTuple&, unsigned int, unsigned int, const OpTuple&)
+            {
+            }
+            template <class ValTuple, class OpTuple>
+            static __device__ void mergeShfl(const ValTuple&, unsigned int, unsigned int, const OpTuple&)
+            {
+            }
+        };
+
+        template <typename T>
+        __device__ __forceinline__ void loadToSmem(volatile T* smem, T& val, unsigned int tid)
+        {
+            smem[tid] = val;
+        }
+        template <typename T>
+        __device__ __forceinline__ void loadFromSmem(volatile T* smem, T& val, unsigned int tid)
+        {
+            val = smem[tid];
+        }
+
+        template <typename T, class Op>
+        __device__ __forceinline__ void merge(volatile T* smem, T& val, unsigned int tid, unsigned int delta, const Op& op)
+        {
+            T reg = smem[tid + delta];
+            smem[tid] = val = op(val, reg);
+        }
+
+        template <typename T, class Op>
+        __device__ __forceinline__ void mergeShfl(T& val, unsigned int delta, unsigned int width, const Op& op)
+        {
+            T reg = shfl_down(val, delta, width);
+            val = op(val, reg);
+        }
+
+#if (CUDART_VERSION < 12040) // details: https://github.com/opencv/opencv_contrib/issues/3690
+        template <typename P0, typename P1, typename P2, typename P3, typename P4, typename P5, typename P6, typename P7, typename P8, typename P9,
+                  typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9>
+        __device__ __forceinline__ void loadToSmem(const thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>& smem,
+                                                       const thrust::tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
+                                                       unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9> >::value>::loadToSmem(smem, val, tid);
+        }
+
+        template <typename P0, typename P1, typename P2, typename P3, typename P4, typename P5, typename P6, typename P7, typename P8, typename P9,
+                  typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9>
+        __device__ __forceinline__ void loadFromSmem(const thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>& smem,
+                                                         const thrust::tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
+                                                         unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9> >::value>::loadFromSmem(smem, val, tid);
+        }
+
+        template <typename P0, typename P1, typename P2, typename P3, typename P4, typename P5, typename P6, typename P7, typename P8, typename P9,
+                  typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9,
+                  class Op0, class Op1, class Op2, class Op3, class Op4, class Op5, class Op6, class Op7, class Op8, class Op9>
+        __device__ __forceinline__ void merge(const thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>& smem,
+                                              const thrust::tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
+                                              unsigned int tid,
+                                              unsigned int delta,
+                                              const thrust::tuple<Op0, Op1, Op2, Op3, Op4, Op5, Op6, Op7, Op8, Op9>& op)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9> >::value>::merge(smem, val, tid, delta, op);
+        }
+        template <typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9,
+                  class Op0, class Op1, class Op2, class Op3, class Op4, class Op5, class Op6, class Op7, class Op8, class Op9>
+        __device__ __forceinline__ void mergeShfl(const thrust::tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
+                                                  unsigned int delta,
+                                                  unsigned int width,
+                                                  const thrust::tuple<Op0, Op1, Op2, Op3, Op4, Op5, Op6, Op7, Op8, Op9>& op)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9> >::value>::mergeShfl(val, delta, width, op);
+        }
+#else
+        template <typename... P, typename... R>
+        __device__ __forceinline__ void loadToSmem(const thrust::tuple<P...>& smem, const thrust::tuple<R...>& val, unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<P...> >::value>::loadToSmem(smem, val, tid);
+        }
+
+        template <typename... P, typename... R>
+        __device__ __forceinline__ void loadFromSmem(const thrust::tuple<P...>& smem, const thrust::tuple<R...>& val, unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<P...> >::value>::loadFromSmem(smem, val, tid);
+        }
+
+        template <typename... P, typename... R, class... Op>
+        __device__ __forceinline__ void merge(const thrust::tuple<P...>& smem, const thrust::tuple<R...>& val, unsigned int tid, unsigned int delta, const thrust::tuple<Op...>& op)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<P...> >::value>::merge(smem, val, tid, delta, op);
+        }
+
+        template <typename... R, class... Op>
+        __device__ __forceinline__ void mergeShfl(const thrust::tuple<R...>& val, unsigned int delta, unsigned int width, const thrust::tuple<Op...>& op)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<R...> >::value>::mergeShfl(val, delta, width, op);
+        }
+#endif
+        template <unsigned int N> struct Generic
+        {
+            template <typename Pointer, typename Reference, class Op>
+            static __device__ void reduce(Pointer smem, Reference val, unsigned int tid, Op op)
+            {
+                loadToSmem(smem, val, tid);
+                if (N >= 32)
+                    __syncthreads();
+
+                if (N >= 2048)
+                {
+                    if (tid < 1024)
+                        merge(smem, val, tid, 1024, op);
+
+                    __syncthreads();
+                }
+                if (N >= 1024)
+                {
+                    if (tid < 512)
+                        merge(smem, val, tid, 512, op);
+
+                    __syncthreads();
+                }
+                if (N >= 512)
+                {
+                    if (tid < 256)
+                        merge(smem, val, tid, 256, op);
+
+                    __syncthreads();
+                }
+                if (N >= 256)
+                {
+                    if (tid < 128)
+                        merge(smem, val, tid, 128, op);
+
+                    __syncthreads();
+                }
+                if (N >= 128)
+                {
+                    if (tid < 64)
+                        merge(smem, val, tid, 64, op);
+
+                    __syncthreads();
+                }
+                if (N >= 64)
+                {
+                    if (tid < 32)
+                        merge(smem, val, tid, 32, op);
+                }
+
+                if (tid < 16)
+                {
+                    merge(smem, val, tid, 16, op);
+                    merge(smem, val, tid, 8, op);
+                    merge(smem, val, tid, 4, op);
+                    merge(smem, val, tid, 2, op);
+                    merge(smem, val, tid, 1, op);
+                }
+            }
+        };
+
+        template <unsigned int I, typename Pointer, typename Reference, class Op>
+        struct Unroll
+        {
+            static __device__ void loopShfl(Reference val, Op op, unsigned int N)
+            {
+                mergeShfl(val, I, N, op);
+                Unroll<I / 2, Pointer, Reference, Op>::loopShfl(val, op, N);
+            }
+            static __device__ void loop(Pointer smem, Reference val, unsigned int tid, Op op)
+            {
+                merge(smem, val, tid, I, op);
+                Unroll<I / 2, Pointer, Reference, Op>::loop(smem, val, tid, op);
+            }
+        };
+        template <typename Pointer, typename Reference, class Op>
+        struct Unroll<0, Pointer, Reference, Op>
+        {
+            static __device__ void loopShfl(Reference, Op, unsigned int)
+            {
+            }
+            static __device__ void loop(Pointer, Reference, unsigned int, Op)
+            {
+            }
+        };
+
+        template <unsigned int N> struct WarpOptimized
+        {
+            template <typename Pointer, typename Reference, class Op>
+            static __device__ void reduce(Pointer smem, Reference val, unsigned int tid, Op op)
+            {
+            #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+                CV_UNUSED(smem);
+                CV_UNUSED(tid);
+
+                Unroll<N / 2, Pointer, Reference, Op>::loopShfl(val, op, N);
+            #else
+                loadToSmem(smem, val, tid);
+
+                if (tid < N / 2)
+                    Unroll<N / 2, Pointer, Reference, Op>::loop(smem, val, tid, op);
+            #endif
+            }
+        };
+
+        template <unsigned int N> struct GenericOptimized32
+        {
+            enum { M = N / 32 };
+
+            template <typename Pointer, typename Reference, class Op>
+            static __device__ void reduce(Pointer smem, Reference val, unsigned int tid, Op op)
+            {
+                const unsigned int laneId = Warp::laneId();
+
+            #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+                Unroll<16, Pointer, Reference, Op>::loopShfl(val, op, warpSize);
+
+                if (laneId == 0)
+                    loadToSmem(smem, val, tid / 32);
+            #else
+                loadToSmem(smem, val, tid);
+
+                if (laneId < 16)
+                    Unroll<16, Pointer, Reference, Op>::loop(smem, val, tid, op);
+
+                __syncthreads();
+
+                if (laneId == 0)
+                    loadToSmem(smem, val, tid / 32);
+            #endif
+
+                __syncthreads();
+
+                loadFromSmem(smem, val, tid);
+
+                if (tid < 32)
+                {
+                #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+                    Unroll<M / 2, Pointer, Reference, Op>::loopShfl(val, op, M);
+                #else
+                    Unroll<M / 2, Pointer, Reference, Op>::loop(smem, val, tid, op);
+                #endif
+                }
+            }
+        };
+
+        template <bool val, class T1, class T2> struct StaticIf;
+        template <class T1, class T2> struct StaticIf<true, T1, T2>
+        {
+            typedef T1 type;
+        };
+        template <class T1, class T2> struct StaticIf<false, T1, T2>
+        {
+            typedef T2 type;
+        };
+
+        template <unsigned int N> struct IsPowerOf2
+        {
+            enum { value = ((N != 0) && !(N & (N - 1))) };
+        };
+
+        template <unsigned int N> struct Dispatcher
+        {
+            typedef typename StaticIf<
+                (N <= 32) && IsPowerOf2<N>::value,
+                WarpOptimized<N>,
+                typename StaticIf<
+                    (N <= 1024) && IsPowerOf2<N>::value,
+                    GenericOptimized32<N>,
+                    Generic<N>
+                >::type
+            >::type reductor;
+        };
+    }
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_REDUCE_DETAIL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/detail/reduce_key_val.hpp

@@ -0,0 +1,567 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_PRED_VAL_REDUCE_DETAIL_HPP
+#define OPENCV_CUDA_PRED_VAL_REDUCE_DETAIL_HPP
+
+#include <thrust/tuple.h>
+#include "../warp.hpp"
+#include "../warp_shuffle.hpp"
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    namespace reduce_key_val_detail
+    {
+        template <typename T> struct GetType;
+        template <typename T> struct GetType<T*>
+        {
+            typedef T type;
+        };
+        template <typename T> struct GetType<volatile T*>
+        {
+            typedef T type;
+        };
+        template <typename T> struct GetType<T&>
+        {
+            typedef T type;
+        };
+
+        template <unsigned int I, unsigned int N>
+        struct For
+        {
+            template <class PointerTuple, class ReferenceTuple>
+            static __device__ void loadToSmem(const PointerTuple& smem, const ReferenceTuple& data, unsigned int tid)
+            {
+                thrust::get<I>(smem)[tid] = thrust::get<I>(data);
+
+                For<I + 1, N>::loadToSmem(smem, data, tid);
+            }
+            template <class PointerTuple, class ReferenceTuple>
+            static __device__ void loadFromSmem(const PointerTuple& smem, const ReferenceTuple& data, unsigned int tid)
+            {
+                thrust::get<I>(data) = thrust::get<I>(smem)[tid];
+
+                For<I + 1, N>::loadFromSmem(smem, data, tid);
+            }
+
+            template <class ReferenceTuple>
+            static __device__ void copyShfl(const ReferenceTuple& val, unsigned int delta, int width)
+            {
+                thrust::get<I>(val) = shfl_down(thrust::get<I>(val), delta, width);
+
+                For<I + 1, N>::copyShfl(val, delta, width);
+            }
+            template <class PointerTuple, class ReferenceTuple>
+            static __device__ void copy(const PointerTuple& svals, const ReferenceTuple& val, unsigned int tid, unsigned int delta)
+            {
+                thrust::get<I>(svals)[tid] = thrust::get<I>(val) = thrust::get<I>(svals)[tid + delta];
+
+                For<I + 1, N>::copy(svals, val, tid, delta);
+            }
+
+            template <class KeyReferenceTuple, class ValReferenceTuple, class CmpTuple>
+            static __device__ void mergeShfl(const KeyReferenceTuple& key, const ValReferenceTuple& val, const CmpTuple& cmp, unsigned int delta, int width)
+            {
+                typename GetType<typename thrust::tuple_element<I, KeyReferenceTuple>::type>::type reg = shfl_down(thrust::get<I>(key), delta, width);
+
+                if (thrust::get<I>(cmp)(reg, thrust::get<I>(key)))
+                {
+                    thrust::get<I>(key) = reg;
+                    thrust::get<I>(val) = shfl_down(thrust::get<I>(val), delta, width);
+                }
+
+                For<I + 1, N>::mergeShfl(key, val, cmp, delta, width);
+            }
+            template <class KeyPointerTuple, class KeyReferenceTuple, class ValPointerTuple, class ValReferenceTuple, class CmpTuple>
+            static __device__ void merge(const KeyPointerTuple& skeys, const KeyReferenceTuple& key,
+                                         const ValPointerTuple& svals, const ValReferenceTuple& val,
+                                         const CmpTuple& cmp,
+                                         unsigned int tid, unsigned int delta)
+            {
+                typename GetType<typename thrust::tuple_element<I, KeyPointerTuple>::type>::type reg = thrust::get<I>(skeys)[tid + delta];
+
+                if (thrust::get<I>(cmp)(reg, thrust::get<I>(key)))
+                {
+                    thrust::get<I>(skeys)[tid] = thrust::get<I>(key) = reg;
+                    thrust::get<I>(svals)[tid] = thrust::get<I>(val) = thrust::get<I>(svals)[tid + delta];
+                }
+
+                For<I + 1, N>::merge(skeys, key, svals, val, cmp, tid, delta);
+            }
+        };
+        template <unsigned int N>
+        struct For<N, N>
+        {
+            template <class PointerTuple, class ReferenceTuple>
+            static __device__ void loadToSmem(const PointerTuple&, const ReferenceTuple&, unsigned int)
+            {
+            }
+            template <class PointerTuple, class ReferenceTuple>
+            static __device__ void loadFromSmem(const PointerTuple&, const ReferenceTuple&, unsigned int)
+            {
+            }
+
+            template <class ReferenceTuple>
+            static __device__ void copyShfl(const ReferenceTuple&, unsigned int, int)
+            {
+            }
+            template <class PointerTuple, class ReferenceTuple>
+            static __device__ void copy(const PointerTuple&, const ReferenceTuple&, unsigned int, unsigned int)
+            {
+            }
+
+            template <class KeyReferenceTuple, class ValReferenceTuple, class CmpTuple>
+            static __device__ void mergeShfl(const KeyReferenceTuple&, const ValReferenceTuple&, const CmpTuple&, unsigned int, int)
+            {
+            }
+            template <class KeyPointerTuple, class KeyReferenceTuple, class ValPointerTuple, class ValReferenceTuple, class CmpTuple>
+            static __device__ void merge(const KeyPointerTuple&, const KeyReferenceTuple&,
+                                         const ValPointerTuple&, const ValReferenceTuple&,
+                                         const CmpTuple&,
+                                         unsigned int, unsigned int)
+            {
+            }
+        };
+
+        //////////////////////////////////////////////////////
+        // loadToSmem
+
+        template <typename T>
+        __device__ __forceinline__ void loadToSmem(volatile T* smem, T& data, unsigned int tid)
+        {
+            smem[tid] = data;
+        }
+        template <typename T>
+        __device__ __forceinline__ void loadFromSmem(volatile T* smem, T& data, unsigned int tid)
+        {
+            data = smem[tid];
+        }
+
+#if (CUDART_VERSION < 12040)
+        template <typename VP0, typename VP1, typename VP2, typename VP3, typename VP4, typename VP5, typename VP6, typename VP7, typename VP8, typename VP9,
+                  typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9>
+        __device__ __forceinline__ void loadToSmem(const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>& smem,
+                                                   const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& data,
+                                                   unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9> >::value>::loadToSmem(smem, data, tid);
+        }
+        template <typename VP0, typename VP1, typename VP2, typename VP3, typename VP4, typename VP5, typename VP6, typename VP7, typename VP8, typename VP9,
+                  typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9>
+        __device__ __forceinline__ void loadFromSmem(const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>& smem,
+                                                     const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& data,
+                                                     unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9> >::value>::loadFromSmem(smem, data, tid);
+        }
+#else
+        template <typename... VP, typename... VR>
+        __device__ __forceinline__ void loadToSmem(const thrust::tuple<VP...>& smem, const thrust::tuple<VR...>& data, unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP...> >::value>::loadToSmem(smem, data, tid);
+        }
+        template <typename... VP, typename... VR>
+        __device__ __forceinline__ void loadFromSmem(const thrust::tuple<VP...>& smem, const thrust::tuple<VR...>& data, unsigned int tid)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP...> >::value>::loadFromSmem(smem, data, tid);
+        }
+#endif
+
+        template <typename V>
+        __device__ __forceinline__ void copyValsShfl(V& val, unsigned int delta, int width)
+        {
+            val = shfl_down(val, delta, width);
+        }
+        template <typename V>
+        __device__ __forceinline__ void copyVals(volatile V* svals, V& val, unsigned int tid, unsigned int delta)
+        {
+            svals[tid] = val = svals[tid + delta];
+        }
+
+        template <typename K, typename V, class Cmp>
+        __device__ __forceinline__ void mergeShfl(K& key, V& val, const Cmp& cmp, unsigned int delta, int width)
+        {
+            K reg = shfl_down(key, delta, width);
+
+            if (cmp(reg, key))
+            {
+                key = reg;
+                copyValsShfl(val, delta, width);
+            }
+        }
+        template <typename K, typename V, class Cmp>
+        __device__ __forceinline__ void merge(volatile K* skeys, K& key, volatile V* svals, V& val, const Cmp& cmp, unsigned int tid, unsigned int delta)
+        {
+            K reg = skeys[tid + delta];
+
+            if (cmp(reg, key))
+            {
+                skeys[tid] = key = reg;
+                copyVals(svals, val, tid, delta);
+            }
+        }
+
+#if (CUDART_VERSION < 12040) // details: https://github.com/opencv/opencv_contrib/issues/3690
+        template <typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9>
+        __device__ __forceinline__ void copyValsShfl(const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                                     unsigned int delta,
+                                                     int width)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9> >::value>::copyShfl(val, delta, width);
+        }
+        template <typename VP0, typename VP1, typename VP2, typename VP3, typename VP4, typename VP5, typename VP6, typename VP7, typename VP8, typename VP9,
+                  typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9>
+        __device__ __forceinline__ void copyVals(const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>& svals,
+                                                 const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                                 unsigned int tid, unsigned int delta)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9> >::value>::copy(svals, val, tid, delta);
+        }
+
+        template <typename K,
+                  typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9,
+                  class Cmp>
+        __device__ __forceinline__ void mergeShfl(K& key,
+                                                  const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                                  const Cmp& cmp,
+                                                  unsigned int delta, int width)
+        {
+            K reg = shfl_down(key, delta, width);
+
+            if (cmp(reg, key))
+            {
+                key = reg;
+                copyValsShfl(val, delta, width);
+            }
+        }
+        template <typename K,
+                  typename VP0, typename VP1, typename VP2, typename VP3, typename VP4, typename VP5, typename VP6, typename VP7, typename VP8, typename VP9,
+                  typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9,
+                  class Cmp>
+        __device__ __forceinline__ void merge(volatile K* skeys, K& key,
+                                              const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>& svals,
+                                              const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                              const Cmp& cmp, unsigned int tid, unsigned int delta)
+        {
+            K reg = skeys[tid + delta];
+
+            if (cmp(reg, key))
+            {
+                skeys[tid] = key = reg;
+                copyVals(svals, val, tid, delta);
+            }
+        }
+        template <typename KR0, typename KR1, typename KR2, typename KR3, typename KR4, typename KR5, typename KR6, typename KR7, typename KR8, typename KR9,
+                  typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9,
+                  class Cmp0, class Cmp1, class Cmp2, class Cmp3, class Cmp4, class Cmp5, class Cmp6, class Cmp7, class Cmp8, class Cmp9>
+        __device__ __forceinline__ void mergeShfl(const thrust::tuple<KR0, KR1, KR2, KR3, KR4, KR5, KR6, KR7, KR8, KR9>& key,
+                                                  const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                                  const thrust::tuple<Cmp0, Cmp1, Cmp2, Cmp3, Cmp4, Cmp5, Cmp6, Cmp7, Cmp8, Cmp9>& cmp,
+                                                  unsigned int delta, int width)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<KR0, KR1, KR2, KR3, KR4, KR5, KR6, KR7, KR8, KR9> >::value>::mergeShfl(key, val, cmp, delta, width);
+        }
+        template <typename KP0, typename KP1, typename KP2, typename KP3, typename KP4, typename KP5, typename KP6, typename KP7, typename KP8, typename KP9,
+                  typename KR0, typename KR1, typename KR2, typename KR3, typename KR4, typename KR5, typename KR6, typename KR7, typename KR8, typename KR9,
+                  typename VP0, typename VP1, typename VP2, typename VP3, typename VP4, typename VP5, typename VP6, typename VP7, typename VP8, typename VP9,
+                  typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9,
+                  class Cmp0, class Cmp1, class Cmp2, class Cmp3, class Cmp4, class Cmp5, class Cmp6, class Cmp7, class Cmp8, class Cmp9>
+        __device__ __forceinline__ void merge(const thrust::tuple<KP0, KP1, KP2, KP3, KP4, KP5, KP6, KP7, KP8, KP9>& skeys,
+                                              const thrust::tuple<KR0, KR1, KR2, KR3, KR4, KR5, KR6, KR7, KR8, KR9>& key,
+                                              const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>& svals,
+                                              const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                              const thrust::tuple<Cmp0, Cmp1, Cmp2, Cmp3, Cmp4, Cmp5, Cmp6, Cmp7, Cmp8, Cmp9>& cmp,
+                                              unsigned int tid, unsigned int delta)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9> >::value>::merge(skeys, key, svals, val, cmp, tid, delta);
+        }
+#else
+        template <typename... VR>
+        __device__ __forceinline__ void copyValsShfl(const thrust::tuple<VR...>& val, unsigned int delta, int width)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VR...> >::value>::copyShfl(val, delta, width);
+        }
+        template <typename... VP, typename... VR>
+        __device__ __forceinline__ void copyVals(const thrust::tuple<VP...>& svals, const thrust::tuple<VR...>& val, unsigned int tid, unsigned int delta)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP...> >::value>::copy(svals, val, tid, delta);
+        }
+
+        template <typename K, typename... VR, class Cmp>
+        __device__ __forceinline__ void mergeShfl(K& key, const thrust::tuple<VR...>& val, const Cmp& cmp, unsigned int delta, int width)
+        {
+            K reg = shfl_down(key, delta, width);
+
+            if (cmp(reg, key))
+            {
+                key = reg;
+                copyValsShfl(val, delta, width);
+            }
+        }
+        template <typename K, typename... VP, typename... VR, class Cmp>
+        __device__ __forceinline__ void merge(volatile K* skeys, K& key, const thrust::tuple<VP...>& svals,
+                                              const thrust::tuple<VR...>& val, const Cmp& cmp, unsigned int tid, unsigned int delta)
+        {
+            K reg = skeys[tid + delta];
+
+            if (cmp(reg, key))
+            {
+                skeys[tid] = key = reg;
+                copyVals(svals, val, tid, delta);
+            }
+        }
+        template <typename... KR, typename... VR, class... Cmp>
+        __device__ __forceinline__ void mergeShfl(const thrust::tuple<KR...>& key,
+                                                  const thrust::tuple<VR...>& val,
+                                                  const thrust::tuple<Cmp...>& cmp,
+                                                  unsigned int delta, int width)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<KR...> >::value>::mergeShfl(key, val, cmp, delta, width);
+        }
+        template <typename... KP, typename... KR, typename... VP, typename... VR, class... Cmp>
+        __device__ __forceinline__ void merge(const thrust::tuple<KP...>& skeys,
+                                              const thrust::tuple<KR...>& key,
+                                              const thrust::tuple<VP...>& svals,
+                                              const thrust::tuple<VR...>& val,
+                                              const thrust::tuple<Cmp...>& cmp,
+                                              unsigned int tid, unsigned int delta)
+        {
+            For<0, thrust::tuple_size<thrust::tuple<VP...> >::value>::merge(skeys, key, svals, val, cmp, tid, delta);
+        }
+
+#endif
+        //////////////////////////////////////////////////////
+        // Generic
+
+        template <unsigned int N> struct Generic
+        {
+            template <class KP, class KR, class VP, class VR, class Cmp>
+            static __device__ void reduce(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp)
+            {
+                loadToSmem(skeys, key, tid);
+                loadValsToSmem(svals, val, tid);
+                if (N >= 32)
+                    __syncthreads();
+
+                if (N >= 2048)
+                {
+                    if (tid < 1024)
+                        merge(skeys, key, svals, val, cmp, tid, 1024);
+
+                    __syncthreads();
+                }
+                if (N >= 1024)
+                {
+                    if (tid < 512)
+                        merge(skeys, key, svals, val, cmp, tid, 512);
+
+                    __syncthreads();
+                }
+                if (N >= 512)
+                {
+                    if (tid < 256)
+                        merge(skeys, key, svals, val, cmp, tid, 256);
+
+                    __syncthreads();
+                }
+                if (N >= 256)
+                {
+                    if (tid < 128)
+                        merge(skeys, key, svals, val, cmp, tid, 128);
+
+                    __syncthreads();
+                }
+                if (N >= 128)
+                {
+                    if (tid < 64)
+                        merge(skeys, key, svals, val, cmp, tid, 64);
+
+                    __syncthreads();
+                }
+                if (N >= 64)
+                {
+                    if (tid < 32)
+                        merge(skeys, key, svals, val, cmp, tid, 32);
+                }
+
+                if (tid < 16)
+                {
+                    merge(skeys, key, svals, val, cmp, tid, 16);
+                    merge(skeys, key, svals, val, cmp, tid, 8);
+                    merge(skeys, key, svals, val, cmp, tid, 4);
+                    merge(skeys, key, svals, val, cmp, tid, 2);
+                    merge(skeys, key, svals, val, cmp, tid, 1);
+                }
+            }
+        };
+
+        template <unsigned int I, class KP, class KR, class VP, class VR, class Cmp>
+        struct Unroll
+        {
+            static __device__ void loopShfl(KR key, VR val, Cmp cmp, unsigned int N)
+            {
+                mergeShfl(key, val, cmp, I, N);
+                Unroll<I / 2, KP, KR, VP, VR, Cmp>::loopShfl(key, val, cmp, N);
+            }
+            static __device__ void loop(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp)
+            {
+                merge(skeys, key, svals, val, cmp, tid, I);
+                Unroll<I / 2, KP, KR, VP, VR, Cmp>::loop(skeys, key, svals, val, tid, cmp);
+            }
+        };
+        template <class KP, class KR, class VP, class VR, class Cmp>
+        struct Unroll<0, KP, KR, VP, VR, Cmp>
+        {
+            static __device__ void loopShfl(KR, VR, Cmp, unsigned int)
+            {
+            }
+            static __device__ void loop(KP, KR, VP, VR, unsigned int, Cmp)
+            {
+            }
+        };
+
+        template <unsigned int N> struct WarpOptimized
+        {
+            template <class KP, class KR, class VP, class VR, class Cmp>
+            static __device__ void reduce(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp)
+            {
+            #if 0 // __CUDA_ARCH__ >= 300
+                CV_UNUSED(skeys);
+                CV_UNUSED(svals);
+                CV_UNUSED(tid);
+
+                Unroll<N / 2, KP, KR, VP, VR, Cmp>::loopShfl(key, val, cmp, N);
+            #else
+                loadToSmem(skeys, key, tid);
+                loadToSmem(svals, val, tid);
+
+                if (tid < N / 2)
+                    Unroll<N / 2, KP, KR, VP, VR, Cmp>::loop(skeys, key, svals, val, tid, cmp);
+            #endif
+            }
+        };
+
+        template <unsigned int N> struct GenericOptimized32
+        {
+            enum { M = N / 32 };
+
+            template <class KP, class KR, class VP, class VR, class Cmp>
+            static __device__ void reduce(KP skeys, KR key, VP svals, VR val, unsigned int tid, Cmp cmp)
+            {
+                const unsigned int laneId = Warp::laneId();
+
+            #if 0 // __CUDA_ARCH__ >= 300
+                Unroll<16, KP, KR, VP, VR, Cmp>::loopShfl(key, val, cmp, warpSize);
+
+                if (laneId == 0)
+                {
+                    loadToSmem(skeys, key, tid / 32);
+                    loadToSmem(svals, val, tid / 32);
+                }
+            #else
+                loadToSmem(skeys, key, tid);
+                loadToSmem(svals, val, tid);
+
+                if (laneId < 16)
+                    Unroll<16, KP, KR, VP, VR, Cmp>::loop(skeys, key, svals, val, tid, cmp);
+
+                __syncthreads();
+
+                if (laneId == 0)
+                {
+                    loadToSmem(skeys, key, tid / 32);
+                    loadToSmem(svals, val, tid / 32);
+                }
+            #endif
+
+                __syncthreads();
+
+                loadFromSmem(skeys, key, tid);
+
+                if (tid < 32)
+                {
+                #if 0 // __CUDA_ARCH__ >= 300
+                    loadFromSmem(svals, val, tid);
+
+                    Unroll<M / 2, KP, KR, VP, VR, Cmp>::loopShfl(key, val, cmp, M);
+                #else
+                    Unroll<M / 2, KP, KR, VP, VR, Cmp>::loop(skeys, key, svals, val, tid, cmp);
+                #endif
+                }
+            }
+        };
+
+        template <bool val, class T1, class T2> struct StaticIf;
+        template <class T1, class T2> struct StaticIf<true, T1, T2>
+        {
+            typedef T1 type;
+        };
+        template <class T1, class T2> struct StaticIf<false, T1, T2>
+        {
+            typedef T2 type;
+        };
+
+        template <unsigned int N> struct IsPowerOf2
+        {
+            enum { value = ((N != 0) && !(N & (N - 1))) };
+        };
+
+        template <unsigned int N> struct Dispatcher
+        {
+            typedef typename StaticIf<
+                (N <= 32) && IsPowerOf2<N>::value,
+                WarpOptimized<N>,
+                typename StaticIf<
+                    (N <= 1024) && IsPowerOf2<N>::value,
+                    GenericOptimized32<N>,
+                    Generic<N>
+                >::type
+            >::type reductor;
+        };
+    }
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_PRED_VAL_REDUCE_DETAIL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/detail/transform_detail.hpp

@@ -0,0 +1,392 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_TRANSFORM_DETAIL_HPP
+#define OPENCV_CUDA_TRANSFORM_DETAIL_HPP
+
+#include "../common.hpp"
+#include "../vec_traits.hpp"
+#include "../functional.hpp"
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    namespace transform_detail
+    {
+        //! Read Write Traits
+
+        template <typename T, typename D, int shift> struct UnaryReadWriteTraits
+        {
+            typedef typename TypeVec<T, shift>::vec_type read_type;
+            typedef typename TypeVec<D, shift>::vec_type write_type;
+        };
+
+        template <typename T1, typename T2, typename D, int shift> struct BinaryReadWriteTraits
+        {
+            typedef typename TypeVec<T1, shift>::vec_type read_type1;
+            typedef typename TypeVec<T2, shift>::vec_type read_type2;
+            typedef typename TypeVec<D, shift>::vec_type write_type;
+        };
+
+        //! Transform kernels
+
+        template <int shift> struct OpUnroller;
+        template <> struct OpUnroller<1>
+        {
+            template <typename T, typename D, typename UnOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, UnOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src.x);
+            }
+
+            template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, BinOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src1.x, src2.x);
+            }
+        };
+        template <> struct OpUnroller<2>
+        {
+            template <typename T, typename D, typename UnOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, UnOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src.x);
+                if (mask(y, x_shifted + 1))
+                    dst.y = op(src.y);
+            }
+
+            template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, BinOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src1.x, src2.x);
+                if (mask(y, x_shifted + 1))
+                    dst.y = op(src1.y, src2.y);
+            }
+        };
+        template <> struct OpUnroller<3>
+        {
+            template <typename T, typename D, typename UnOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, const UnOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src.x);
+                if (mask(y, x_shifted + 1))
+                    dst.y = op(src.y);
+                if (mask(y, x_shifted + 2))
+                    dst.z = op(src.z);
+            }
+
+            template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, const BinOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src1.x, src2.x);
+                if (mask(y, x_shifted + 1))
+                    dst.y = op(src1.y, src2.y);
+                if (mask(y, x_shifted + 2))
+                    dst.z = op(src1.z, src2.z);
+            }
+        };
+        template <> struct OpUnroller<4>
+        {
+            template <typename T, typename D, typename UnOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, const UnOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src.x);
+                if (mask(y, x_shifted + 1))
+                    dst.y = op(src.y);
+                if (mask(y, x_shifted + 2))
+                    dst.z = op(src.z);
+                if (mask(y, x_shifted + 3))
+                    dst.w = op(src.w);
+            }
+
+            template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, const BinOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.x = op(src1.x, src2.x);
+                if (mask(y, x_shifted + 1))
+                    dst.y = op(src1.y, src2.y);
+                if (mask(y, x_shifted + 2))
+                    dst.z = op(src1.z, src2.z);
+                if (mask(y, x_shifted + 3))
+                    dst.w = op(src1.w, src2.w);
+            }
+        };
+        template <> struct OpUnroller<8>
+        {
+            template <typename T, typename D, typename UnOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T& src, D& dst, const Mask& mask, const UnOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.a0 = op(src.a0);
+                if (mask(y, x_shifted + 1))
+                    dst.a1 = op(src.a1);
+                if (mask(y, x_shifted + 2))
+                    dst.a2 = op(src.a2);
+                if (mask(y, x_shifted + 3))
+                    dst.a3 = op(src.a3);
+                if (mask(y, x_shifted + 4))
+                    dst.a4 = op(src.a4);
+                if (mask(y, x_shifted + 5))
+                    dst.a5 = op(src.a5);
+                if (mask(y, x_shifted + 6))
+                    dst.a6 = op(src.a6);
+                if (mask(y, x_shifted + 7))
+                    dst.a7 = op(src.a7);
+            }
+
+            template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+            static __device__ __forceinline__ void unroll(const T1& src1, const T2& src2, D& dst, const Mask& mask, const BinOp& op, int x_shifted, int y)
+            {
+                if (mask(y, x_shifted))
+                    dst.a0 = op(src1.a0, src2.a0);
+                if (mask(y, x_shifted + 1))
+                    dst.a1 = op(src1.a1, src2.a1);
+                if (mask(y, x_shifted + 2))
+                    dst.a2 = op(src1.a2, src2.a2);
+                if (mask(y, x_shifted + 3))
+                    dst.a3 = op(src1.a3, src2.a3);
+                if (mask(y, x_shifted + 4))
+                    dst.a4 = op(src1.a4, src2.a4);
+                if (mask(y, x_shifted + 5))
+                    dst.a5 = op(src1.a5, src2.a5);
+                if (mask(y, x_shifted + 6))
+                    dst.a6 = op(src1.a6, src2.a6);
+                if (mask(y, x_shifted + 7))
+                    dst.a7 = op(src1.a7, src2.a7);
+            }
+        };
+
+        template <typename T, typename D, typename UnOp, typename Mask>
+        static __global__ void transformSmart(const PtrStepSz<T> src_, PtrStep<D> dst_, const Mask mask, const UnOp op)
+        {
+            typedef TransformFunctorTraits<UnOp> ft;
+            typedef typename UnaryReadWriteTraits<T, D, ft::smart_shift>::read_type read_type;
+            typedef typename UnaryReadWriteTraits<T, D, ft::smart_shift>::write_type write_type;
+
+            const int x = threadIdx.x + blockIdx.x * blockDim.x;
+            const int y = threadIdx.y + blockIdx.y * blockDim.y;
+            const int x_shifted = x * ft::smart_shift;
+
+            if (y < src_.rows)
+            {
+                const T* src = src_.ptr(y);
+                D* dst = dst_.ptr(y);
+
+                if (x_shifted + ft::smart_shift - 1 < src_.cols)
+                {
+                    const read_type src_n_el = ((const read_type*)src)[x];
+                    OpUnroller<ft::smart_shift>::unroll(src_n_el, ((write_type*)dst)[x], mask, op, x_shifted, y);
+                }
+                else
+                {
+                    for (int real_x = x_shifted; real_x < src_.cols; ++real_x)
+                    {
+                        if (mask(y, real_x))
+                            dst[real_x] = op(src[real_x]);
+                    }
+                }
+            }
+        }
+
+        template <typename T, typename D, typename UnOp, typename Mask>
+        __global__ static void transformSimple(const PtrStepSz<T> src, PtrStep<D> dst, const Mask mask, const UnOp op)
+        {
+            const int x = blockDim.x * blockIdx.x + threadIdx.x;
+            const int y = blockDim.y * blockIdx.y + threadIdx.y;
+
+            if (x < src.cols && y < src.rows && mask(y, x))
+            {
+                dst.ptr(y)[x] = op(src.ptr(y)[x]);
+            }
+        }
+
+        template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+        static __global__ void transformSmart(const PtrStepSz<T1> src1_, const PtrStep<T2> src2_, PtrStep<D> dst_,
+            const Mask mask, const BinOp op)
+        {
+            typedef TransformFunctorTraits<BinOp> ft;
+            typedef typename BinaryReadWriteTraits<T1, T2, D, ft::smart_shift>::read_type1 read_type1;
+            typedef typename BinaryReadWriteTraits<T1, T2, D, ft::smart_shift>::read_type2 read_type2;
+            typedef typename BinaryReadWriteTraits<T1, T2, D, ft::smart_shift>::write_type write_type;
+
+            const int x = threadIdx.x + blockIdx.x * blockDim.x;
+            const int y = threadIdx.y + blockIdx.y * blockDim.y;
+            const int x_shifted = x * ft::smart_shift;
+
+            if (y < src1_.rows)
+            {
+                const T1* src1 = src1_.ptr(y);
+                const T2* src2 = src2_.ptr(y);
+                D* dst = dst_.ptr(y);
+
+                if (x_shifted + ft::smart_shift - 1 < src1_.cols)
+                {
+                    const read_type1 src1_n_el = ((const read_type1*)src1)[x];
+                    const read_type2 src2_n_el = ((const read_type2*)src2)[x];
+
+                    OpUnroller<ft::smart_shift>::unroll(src1_n_el, src2_n_el, ((write_type*)dst)[x], mask, op, x_shifted, y);
+                }
+                else
+                {
+                    for (int real_x = x_shifted; real_x < src1_.cols; ++real_x)
+                    {
+                        if (mask(y, real_x))
+                            dst[real_x] = op(src1[real_x], src2[real_x]);
+                    }
+                }
+            }
+        }
+
+        template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+        static __global__ void transformSimple(const PtrStepSz<T1> src1, const PtrStep<T2> src2, PtrStep<D> dst,
+            const Mask mask, const BinOp op)
+        {
+            const int x = blockDim.x * blockIdx.x + threadIdx.x;
+            const int y = blockDim.y * blockIdx.y + threadIdx.y;
+
+            if (x < src1.cols && y < src1.rows && mask(y, x))
+            {
+                const T1 src1_data = src1.ptr(y)[x];
+                const T2 src2_data = src2.ptr(y)[x];
+                dst.ptr(y)[x] = op(src1_data, src2_data);
+            }
+        }
+
+        template <bool UseSmart> struct TransformDispatcher;
+        template<> struct TransformDispatcher<false>
+        {
+            template <typename T, typename D, typename UnOp, typename Mask>
+            static void call(PtrStepSz<T> src, PtrStepSz<D> dst, UnOp op, Mask mask, cudaStream_t stream)
+            {
+                typedef TransformFunctorTraits<UnOp> ft;
+
+                const dim3 threads(ft::simple_block_dim_x, ft::simple_block_dim_y, 1);
+                const dim3 grid(divUp(src.cols, threads.x), divUp(src.rows, threads.y), 1);
+
+                transformSimple<T, D><<<grid, threads, 0, stream>>>(src, dst, mask, op);
+                cudaSafeCall( cudaGetLastError() );
+
+                if (stream == 0)
+                    cudaSafeCall( cudaDeviceSynchronize() );
+            }
+
+            template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+            static void call(PtrStepSz<T1> src1, PtrStepSz<T2> src2, PtrStepSz<D> dst, BinOp op, Mask mask, cudaStream_t stream)
+            {
+                typedef TransformFunctorTraits<BinOp> ft;
+
+                const dim3 threads(ft::simple_block_dim_x, ft::simple_block_dim_y, 1);
+                const dim3 grid(divUp(src1.cols, threads.x), divUp(src1.rows, threads.y), 1);
+
+                transformSimple<T1, T2, D><<<grid, threads, 0, stream>>>(src1, src2, dst, mask, op);
+                cudaSafeCall( cudaGetLastError() );
+
+                if (stream == 0)
+                    cudaSafeCall( cudaDeviceSynchronize() );
+            }
+        };
+        template<> struct TransformDispatcher<true>
+        {
+            template <typename T, typename D, typename UnOp, typename Mask>
+            static void call(PtrStepSz<T> src, PtrStepSz<D> dst, UnOp op, Mask mask, cudaStream_t stream)
+            {
+                typedef TransformFunctorTraits<UnOp> ft;
+
+                CV_StaticAssert(ft::smart_shift != 1, "");
+
+                if (!isAligned(src.data, ft::smart_shift * sizeof(T)) || !isAligned(src.step, ft::smart_shift * sizeof(T)) ||
+                    !isAligned(dst.data, ft::smart_shift * sizeof(D)) || !isAligned(dst.step, ft::smart_shift * sizeof(D)))
+                {
+                    TransformDispatcher<false>::call(src, dst, op, mask, stream);
+                    return;
+                }
+
+                const dim3 threads(ft::smart_block_dim_x, ft::smart_block_dim_y, 1);
+                const dim3 grid(divUp(src.cols, threads.x * ft::smart_shift), divUp(src.rows, threads.y), 1);
+
+                transformSmart<T, D><<<grid, threads, 0, stream>>>(src, dst, mask, op);
+                cudaSafeCall( cudaGetLastError() );
+
+                if (stream == 0)
+                    cudaSafeCall( cudaDeviceSynchronize() );
+            }
+
+            template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+            static void call(PtrStepSz<T1> src1, PtrStepSz<T2> src2, PtrStepSz<D> dst, BinOp op, Mask mask, cudaStream_t stream)
+            {
+                typedef TransformFunctorTraits<BinOp> ft;
+
+                CV_StaticAssert(ft::smart_shift != 1, "");
+
+                if (!isAligned(src1.data, ft::smart_shift * sizeof(T1)) || !isAligned(src1.step, ft::smart_shift * sizeof(T1)) ||
+                    !isAligned(src2.data, ft::smart_shift * sizeof(T2)) || !isAligned(src2.step, ft::smart_shift * sizeof(T2)) ||
+                    !isAligned(dst.data, ft::smart_shift * sizeof(D)) || !isAligned(dst.step, ft::smart_shift * sizeof(D)))
+                {
+                    TransformDispatcher<false>::call(src1, src2, dst, op, mask, stream);
+                    return;
+                }
+
+                const dim3 threads(ft::smart_block_dim_x, ft::smart_block_dim_y, 1);
+                const dim3 grid(divUp(src1.cols, threads.x * ft::smart_shift), divUp(src1.rows, threads.y), 1);
+
+                transformSmart<T1, T2, D><<<grid, threads, 0, stream>>>(src1, src2, dst, mask, op);
+                cudaSafeCall( cudaGetLastError() );
+
+                if (stream == 0)
+                    cudaSafeCall( cudaDeviceSynchronize() );
+            }
+        };
+    } // namespace transform_detail
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_TRANSFORM_DETAIL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/detail/type_traits_detail.hpp

@@ -0,0 +1,191 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_TYPE_TRAITS_DETAIL_HPP
+#define OPENCV_CUDA_TYPE_TRAITS_DETAIL_HPP
+
+#include "../common.hpp"
+#include "../vec_traits.hpp"
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    namespace type_traits_detail
+    {
+        template <bool, typename T1, typename T2> struct Select { typedef T1 type; };
+        template <typename T1, typename T2> struct Select<false, T1, T2> { typedef T2 type; };
+
+        template <typename T> struct IsSignedIntergral { enum {value = 0}; };
+        template <> struct IsSignedIntergral<schar> { enum {value = 1}; };
+        template <> struct IsSignedIntergral<char1> { enum {value = 1}; };
+        template <> struct IsSignedIntergral<short> { enum {value = 1}; };
+        template <> struct IsSignedIntergral<short1> { enum {value = 1}; };
+        template <> struct IsSignedIntergral<int> { enum {value = 1}; };
+        template <> struct IsSignedIntergral<int1> { enum {value = 1}; };
+
+        template <typename T> struct IsUnsignedIntegral { enum {value = 0}; };
+        template <> struct IsUnsignedIntegral<uchar> { enum {value = 1}; };
+        template <> struct IsUnsignedIntegral<uchar1> { enum {value = 1}; };
+        template <> struct IsUnsignedIntegral<ushort> { enum {value = 1}; };
+        template <> struct IsUnsignedIntegral<ushort1> { enum {value = 1}; };
+        template <> struct IsUnsignedIntegral<uint> { enum {value = 1}; };
+        template <> struct IsUnsignedIntegral<uint1> { enum {value = 1}; };
+
+        template <typename T> struct IsIntegral { enum {value = IsSignedIntergral<T>::value || IsUnsignedIntegral<T>::value}; };
+        template <> struct IsIntegral<char> { enum {value = 1}; };
+        template <> struct IsIntegral<bool> { enum {value = 1}; };
+
+        template <typename T> struct IsFloat { enum {value = 0}; };
+        template <> struct IsFloat<float> { enum {value = 1}; };
+        template <> struct IsFloat<double> { enum {value = 1}; };
+
+        template <typename T> struct IsVec { enum {value = 0}; };
+        template <> struct IsVec<uchar1> { enum {value = 1}; };
+        template <> struct IsVec<uchar2> { enum {value = 1}; };
+        template <> struct IsVec<uchar3> { enum {value = 1}; };
+        template <> struct IsVec<uchar4> { enum {value = 1}; };
+        template <> struct IsVec<uchar8> { enum {value = 1}; };
+        template <> struct IsVec<char1> { enum {value = 1}; };
+        template <> struct IsVec<char2> { enum {value = 1}; };
+        template <> struct IsVec<char3> { enum {value = 1}; };
+        template <> struct IsVec<char4> { enum {value = 1}; };
+        template <> struct IsVec<char8> { enum {value = 1}; };
+        template <> struct IsVec<ushort1> { enum {value = 1}; };
+        template <> struct IsVec<ushort2> { enum {value = 1}; };
+        template <> struct IsVec<ushort3> { enum {value = 1}; };
+        template <> struct IsVec<ushort4> { enum {value = 1}; };
+        template <> struct IsVec<ushort8> { enum {value = 1}; };
+        template <> struct IsVec<short1> { enum {value = 1}; };
+        template <> struct IsVec<short2> { enum {value = 1}; };
+        template <> struct IsVec<short3> { enum {value = 1}; };
+        template <> struct IsVec<short4> { enum {value = 1}; };
+        template <> struct IsVec<short8> { enum {value = 1}; };
+        template <> struct IsVec<uint1> { enum {value = 1}; };
+        template <> struct IsVec<uint2> { enum {value = 1}; };
+        template <> struct IsVec<uint3> { enum {value = 1}; };
+        template <> struct IsVec<uint4> { enum {value = 1}; };
+        template <> struct IsVec<uint8> { enum {value = 1}; };
+        template <> struct IsVec<int1> { enum {value = 1}; };
+        template <> struct IsVec<int2> { enum {value = 1}; };
+        template <> struct IsVec<int3> { enum {value = 1}; };
+        template <> struct IsVec<int4> { enum {value = 1}; };
+        template <> struct IsVec<int8> { enum {value = 1}; };
+        template <> struct IsVec<float1> { enum {value = 1}; };
+        template <> struct IsVec<float2> { enum {value = 1}; };
+        template <> struct IsVec<float3> { enum {value = 1}; };
+        template <> struct IsVec<float4> { enum {value = 1}; };
+        template <> struct IsVec<float8> { enum {value = 1}; };
+        template <> struct IsVec<double1> { enum {value = 1}; };
+        template <> struct IsVec<double2> { enum {value = 1}; };
+        template <> struct IsVec<double3> { enum {value = 1}; };
+        template <> struct IsVec<double4> { enum {value = 1}; };
+        template <> struct IsVec<double8> { enum {value = 1}; };
+
+        template <class U> struct AddParameterType { typedef const U& type; };
+        template <class U> struct AddParameterType<U&> { typedef U& type; };
+        template <> struct AddParameterType<void> { typedef void type; };
+
+        template <class U> struct ReferenceTraits
+        {
+            enum { value = false };
+            typedef U type;
+        };
+        template <class U> struct ReferenceTraits<U&>
+        {
+            enum { value = true };
+            typedef U type;
+        };
+
+        template <class U> struct PointerTraits
+        {
+            enum { value = false };
+            typedef void type;
+        };
+        template <class U> struct PointerTraits<U*>
+        {
+            enum { value = true };
+            typedef U type;
+        };
+        template <class U> struct PointerTraits<U*&>
+        {
+            enum { value = true };
+            typedef U type;
+        };
+
+        template <class U> struct UnConst
+        {
+            typedef U type;
+            enum { value = 0 };
+        };
+        template <class U> struct UnConst<const U>
+        {
+            typedef U type;
+            enum { value = 1 };
+        };
+        template <class U> struct UnConst<const U&>
+        {
+            typedef U& type;
+            enum { value = 1 };
+        };
+
+        template <class U> struct UnVolatile
+        {
+            typedef U type;
+            enum { value = 0 };
+        };
+        template <class U> struct UnVolatile<volatile U>
+        {
+            typedef U type;
+            enum { value = 1 };
+        };
+        template <class U> struct UnVolatile<volatile U&>
+        {
+            typedef U& type;
+            enum { value = 1 };
+        };
+    } // namespace type_traits_detail
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_TYPE_TRAITS_DETAIL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/detail/vec_distance_detail.hpp

@@ -0,0 +1,121 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_VEC_DISTANCE_DETAIL_HPP
+#define OPENCV_CUDA_VEC_DISTANCE_DETAIL_HPP
+
+#include "../datamov_utils.hpp"
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    namespace vec_distance_detail
+    {
+        template <int THREAD_DIM, int N> struct UnrollVecDiffCached
+        {
+            template <typename Dist, typename T1, typename T2>
+            static __device__ void calcCheck(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, int ind)
+            {
+                if (ind < len)
+                {
+                    T1 val1 = *vecCached++;
+
+                    T2 val2;
+                    ForceGlob<T2>::Load(vecGlob, ind, val2);
+
+                    dist.reduceIter(val1, val2);
+
+                    UnrollVecDiffCached<THREAD_DIM, N - 1>::calcCheck(vecCached, vecGlob, len, dist, ind + THREAD_DIM);
+                }
+            }
+
+            template <typename Dist, typename T1, typename T2>
+            static __device__ void calcWithoutCheck(const T1* vecCached, const T2* vecGlob, Dist& dist)
+            {
+                T1 val1 = *vecCached++;
+
+                T2 val2;
+                ForceGlob<T2>::Load(vecGlob, 0, val2);
+                vecGlob += THREAD_DIM;
+
+                dist.reduceIter(val1, val2);
+
+                UnrollVecDiffCached<THREAD_DIM, N - 1>::calcWithoutCheck(vecCached, vecGlob, dist);
+            }
+        };
+        template <int THREAD_DIM> struct UnrollVecDiffCached<THREAD_DIM, 0>
+        {
+            template <typename Dist, typename T1, typename T2>
+            static __device__ __forceinline__ void calcCheck(const T1*, const T2*, int, Dist&, int)
+            {
+            }
+
+            template <typename Dist, typename T1, typename T2>
+            static __device__ __forceinline__ void calcWithoutCheck(const T1*, const T2*, Dist&)
+            {
+            }
+        };
+
+        template <int THREAD_DIM, int MAX_LEN, bool LEN_EQ_MAX_LEN> struct VecDiffCachedCalculator;
+        template <int THREAD_DIM, int MAX_LEN> struct VecDiffCachedCalculator<THREAD_DIM, MAX_LEN, false>
+        {
+            template <typename Dist, typename T1, typename T2>
+            static __device__ __forceinline__ void calc(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, int tid)
+            {
+                UnrollVecDiffCached<THREAD_DIM, MAX_LEN / THREAD_DIM>::calcCheck(vecCached, vecGlob, len, dist, tid);
+            }
+        };
+        template <int THREAD_DIM, int MAX_LEN> struct VecDiffCachedCalculator<THREAD_DIM, MAX_LEN, true>
+        {
+            template <typename Dist, typename T1, typename T2>
+            static __device__ __forceinline__ void calc(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, int tid)
+            {
+                UnrollVecDiffCached<THREAD_DIM, MAX_LEN / THREAD_DIM>::calcWithoutCheck(vecCached, vecGlob + tid, dist);
+            }
+        };
+    } // namespace vec_distance_detail
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_VEC_DISTANCE_DETAIL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/dynamic_smem.hpp

@@ -0,0 +1,88 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_DYNAMIC_SMEM_HPP
+#define OPENCV_CUDA_DYNAMIC_SMEM_HPP
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template<class T> struct DynamicSharedMem
+    {
+        __device__ __forceinline__ operator T*()
+        {
+            extern __shared__ int __smem[];
+            return (T*)__smem;
+        }
+
+        __device__ __forceinline__ operator const T*() const
+        {
+            extern __shared__ int __smem[];
+            return (T*)__smem;
+        }
+    };
+
+    // specialize for double to avoid unaligned memory access compile errors
+    template<> struct DynamicSharedMem<double>
+    {
+        __device__ __forceinline__ operator double*()
+        {
+            extern __shared__ double __smem_d[];
+            return (double*)__smem_d;
+        }
+
+        __device__ __forceinline__ operator const double*() const
+        {
+            extern __shared__ double __smem_d[];
+            return (double*)__smem_d;
+        }
+    };
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_DYNAMIC_SMEM_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/emulation.hpp

@@ -0,0 +1,269 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_EMULATION_HPP_
+#define OPENCV_CUDA_EMULATION_HPP_
+
+#include "common.hpp"
+#include "warp_reduce.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    struct Emulation
+    {
+
+        static __device__ __forceinline__ int syncthreadsOr(int pred)
+        {
+#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 200)
+                // just campilation stab
+                return 0;
+#else
+                return __syncthreads_or(pred);
+#endif
+        }
+
+        template<int CTA_SIZE>
+        static __forceinline__ __device__ int Ballot(int predicate)
+        {
+#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ >= 200)
+            return __ballot(predicate);
+#else
+            __shared__ volatile int cta_buffer[CTA_SIZE];
+
+            int tid = threadIdx.x;
+            cta_buffer[tid] = predicate ? (1 << (tid & 31)) : 0;
+            return warp_reduce(cta_buffer);
+#endif
+        }
+
+        struct smem
+        {
+            enum { TAG_MASK = (1U << ( (sizeof(unsigned int) << 3) - 5U)) - 1U };
+
+            template<typename T>
+            static __device__ __forceinline__ T atomicInc(T* address, T val)
+            {
+#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
+                T count;
+                unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U);
+                do
+                {
+                    count = *address & TAG_MASK;
+                    count = tag | (count + 1);
+                    *address = count;
+                } while (*address != count);
+
+                return (count & TAG_MASK) - 1;
+#else
+                return ::atomicInc(address, val);
+#endif
+            }
+
+            template<typename T>
+            static __device__ __forceinline__ T atomicAdd(T* address, T val)
+            {
+#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
+                T count;
+                unsigned int tag = threadIdx.x << ( (sizeof(unsigned int) << 3) - 5U);
+                do
+                {
+                    count = *address & TAG_MASK;
+                    count = tag | (count + val);
+                    *address = count;
+                } while (*address != count);
+
+                return (count & TAG_MASK) - val;
+#else
+                return ::atomicAdd(address, val);
+#endif
+            }
+
+            template<typename T>
+            static __device__ __forceinline__ T atomicMin(T* address, T val)
+            {
+#if defined (__CUDA_ARCH__) && (__CUDA_ARCH__ < 120)
+                T count = ::min(*address, val);
+                do
+                {
+                    *address = count;
+                } while (*address > count);
+
+                return count;
+#else
+                return ::atomicMin(address, val);
+#endif
+            }
+        }; // struct cmem
+
+        struct glob
+        {
+            static __device__ __forceinline__ int atomicAdd(int* address, int val)
+            {
+                return ::atomicAdd(address, val);
+            }
+            static __device__ __forceinline__ unsigned int atomicAdd(unsigned int* address, unsigned int val)
+            {
+                return ::atomicAdd(address, val);
+            }
+            static __device__ __forceinline__ float atomicAdd(float* address, float val)
+            {
+            #if __CUDA_ARCH__ >= 200
+                return ::atomicAdd(address, val);
+            #else
+                int* address_as_i = (int*) address;
+                int old = *address_as_i, assumed;
+                do {
+                    assumed = old;
+                    old = ::atomicCAS(address_as_i, assumed,
+                        __float_as_int(val + __int_as_float(assumed)));
+                } while (assumed != old);
+                return __int_as_float(old);
+            #endif
+            }
+            static __device__ __forceinline__ double atomicAdd(double* address, double val)
+            {
+            #if __CUDA_ARCH__ >= 130
+                unsigned long long int* address_as_ull = (unsigned long long int*) address;
+                unsigned long long int old = *address_as_ull, assumed;
+                do {
+                    assumed = old;
+                    old = ::atomicCAS(address_as_ull, assumed,
+                        __double_as_longlong(val + __longlong_as_double(assumed)));
+                } while (assumed != old);
+                return __longlong_as_double(old);
+            #else
+                CV_UNUSED(address);
+                CV_UNUSED(val);
+                return 0.0;
+            #endif
+            }
+
+            static __device__ __forceinline__ int atomicMin(int* address, int val)
+            {
+                return ::atomicMin(address, val);
+            }
+            static __device__ __forceinline__ float atomicMin(float* address, float val)
+            {
+            #if __CUDA_ARCH__ >= 120
+                int* address_as_i = (int*) address;
+                int old = *address_as_i, assumed;
+                do {
+                    assumed = old;
+                    old = ::atomicCAS(address_as_i, assumed,
+                        __float_as_int(::fminf(val, __int_as_float(assumed))));
+                } while (assumed != old);
+                return __int_as_float(old);
+            #else
+                CV_UNUSED(address);
+                CV_UNUSED(val);
+                return 0.0f;
+            #endif
+            }
+            static __device__ __forceinline__ double atomicMin(double* address, double val)
+            {
+            #if __CUDA_ARCH__ >= 130
+                unsigned long long int* address_as_ull = (unsigned long long int*) address;
+                unsigned long long int old = *address_as_ull, assumed;
+                do {
+                    assumed = old;
+                    old = ::atomicCAS(address_as_ull, assumed,
+                        __double_as_longlong(::fmin(val, __longlong_as_double(assumed))));
+                } while (assumed != old);
+                return __longlong_as_double(old);
+            #else
+                CV_UNUSED(address);
+                CV_UNUSED(val);
+                return 0.0;
+            #endif
+            }
+
+            static __device__ __forceinline__ int atomicMax(int* address, int val)
+            {
+                return ::atomicMax(address, val);
+            }
+            static __device__ __forceinline__ float atomicMax(float* address, float val)
+            {
+            #if __CUDA_ARCH__ >= 120
+                int* address_as_i = (int*) address;
+                int old = *address_as_i, assumed;
+                do {
+                    assumed = old;
+                    old = ::atomicCAS(address_as_i, assumed,
+                        __float_as_int(::fmaxf(val, __int_as_float(assumed))));
+                } while (assumed != old);
+                return __int_as_float(old);
+            #else
+                CV_UNUSED(address);
+                CV_UNUSED(val);
+                return 0.0f;
+            #endif
+            }
+            static __device__ __forceinline__ double atomicMax(double* address, double val)
+            {
+            #if __CUDA_ARCH__ >= 130
+                unsigned long long int* address_as_ull = (unsigned long long int*) address;
+                unsigned long long int old = *address_as_ull, assumed;
+                do {
+                    assumed = old;
+                    old = ::atomicCAS(address_as_ull, assumed,
+                        __double_as_longlong(::fmax(val, __longlong_as_double(assumed))));
+                } while (assumed != old);
+                return __longlong_as_double(old);
+            #else
+                CV_UNUSED(address);
+                CV_UNUSED(val);
+                return 0.0;
+            #endif
+            }
+        };
+    }; //struct Emulation
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif /* OPENCV_CUDA_EMULATION_HPP_ */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/filters.hpp

@@ -0,0 +1,293 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_FILTERS_HPP
+#define OPENCV_CUDA_FILTERS_HPP
+
+#include "saturate_cast.hpp"
+#include "vec_traits.hpp"
+#include "vec_math.hpp"
+#include "type_traits.hpp"
+#include "nppdefs.h"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template <typename Ptr2D> struct PointFilter
+    {
+        typedef typename Ptr2D::elem_type elem_type;
+        typedef float index_type;
+
+        explicit __host__ __device__ __forceinline__ PointFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f)
+        : src(src_)
+        {
+            CV_UNUSED(fx);
+            CV_UNUSED(fy);
+        }
+
+        __device__ __forceinline__ elem_type operator ()(float y, float x) const
+        {
+            return src(__float2int_rz(y), __float2int_rz(x));
+        }
+
+        Ptr2D src;
+    };
+
+    template <typename Ptr2D> struct LinearFilter
+    {
+        typedef typename Ptr2D::elem_type elem_type;
+        typedef float index_type;
+
+        explicit __host__ __device__ __forceinline__ LinearFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f)
+        : src(src_)
+        {
+            CV_UNUSED(fx);
+            CV_UNUSED(fy);
+        }
+        __device__ __forceinline__ elem_type operator ()(float y, float x) const
+        {
+            typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
+
+            work_type out = VecTraits<work_type>::all(0);
+
+            const int x1 = __float2int_rd(x);
+            const int y1 = __float2int_rd(y);
+            if (x1 <= NPP_MIN_32S || x1 >= NPP_MAX_32S || y1 <= NPP_MIN_32S || y1 >= NPP_MAX_32S)
+            {
+                elem_type src_reg = src(y1, x1);
+                out = out + src_reg * 1.0f;
+                return saturate_cast<elem_type>(out);
+            }
+            const int x2 = x1 + 1;
+            const int y2 = y1 + 1;
+
+            elem_type src_reg = src(y1, x1);
+            out = out + src_reg * ((x2 - x) * (y2 - y));
+
+            src_reg = src(y1, x2);
+            out = out + src_reg * ((x - x1) * (y2 - y));
+
+            src_reg = src(y2, x1);
+            out = out + src_reg * ((x2 - x) * (y - y1));
+
+            src_reg = src(y2, x2);
+            out = out + src_reg * ((x - x1) * (y - y1));
+
+            return saturate_cast<elem_type>(out);
+        }
+
+        Ptr2D src;
+    };
+
+    template <typename Ptr2D> struct CubicFilter
+    {
+        typedef typename Ptr2D::elem_type elem_type;
+        typedef float index_type;
+        typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
+
+        explicit __host__ __device__ __forceinline__ CubicFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f)
+        : src(src_)
+        {
+            CV_UNUSED(fx);
+            CV_UNUSED(fy);
+        }
+
+        static __device__ __forceinline__ float bicubicCoeff(float x_)
+        {
+            float x = fabsf(x_);
+            if (x <= 1.0f)
+            {
+                return x * x * (1.5f * x - 2.5f) + 1.0f;
+            }
+            else if (x < 2.0f)
+            {
+                return x * (x * (-0.5f * x + 2.5f) - 4.0f) + 2.0f;
+            }
+            else
+            {
+                return 0.0f;
+            }
+        }
+
+        __device__ elem_type operator ()(float y, float x) const
+        {
+            const float xmin = ::ceilf(x - 2.0f);
+            const float xmax = ::floorf(x + 2.0f);
+
+            const float ymin = ::ceilf(y - 2.0f);
+            const float ymax = ::floorf(y + 2.0f);
+
+            work_type sum = VecTraits<work_type>::all(0);
+            float wsum = 0.0f;
+
+            for (float cy = ymin; cy <= ymax; cy += 1.0f)
+            {
+                for (float cx = xmin; cx <= xmax; cx += 1.0f)
+                {
+                    const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy);
+                    sum = sum + w * src(__float2int_rd(cy), __float2int_rd(cx));
+                    wsum += w;
+                }
+            }
+
+            work_type res = (!wsum)? VecTraits<work_type>::all(0) : sum / wsum;
+
+            return saturate_cast<elem_type>(res);
+        }
+
+        Ptr2D src;
+    };
+    // for integer scaling
+    template <typename Ptr2D> struct IntegerAreaFilter
+    {
+        typedef typename Ptr2D::elem_type elem_type;
+        typedef float index_type;
+
+        explicit __host__ __device__ __forceinline__ IntegerAreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_)
+            : src(src_), scale_x(scale_x_), scale_y(scale_y_), scale(1.f / (scale_x * scale_y)) {}
+
+        __device__ __forceinline__ elem_type operator ()(float y, float x) const
+        {
+            float fsx1 = x * scale_x;
+            float fsx2 = fsx1 + scale_x;
+
+            int sx1 = __float2int_ru(fsx1);
+            int sx2 = __float2int_rd(fsx2);
+
+            float fsy1 = y * scale_y;
+            float fsy2 = fsy1 + scale_y;
+
+            int sy1 = __float2int_ru(fsy1);
+            int sy2 = __float2int_rd(fsy2);
+
+            typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
+            work_type out = VecTraits<work_type>::all(0.f);
+
+            for(int dy = sy1; dy < sy2; ++dy)
+                for(int dx = sx1; dx < sx2; ++dx)
+                {
+                    out = out + src(dy, dx) * scale;
+                }
+
+            return saturate_cast<elem_type>(out);
+        }
+
+        Ptr2D src;
+        float scale_x, scale_y ,scale;
+    };
+
+    template <typename Ptr2D> struct AreaFilter
+    {
+        typedef typename Ptr2D::elem_type elem_type;
+        typedef float index_type;
+
+        explicit __host__ __device__ __forceinline__ AreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_)
+            : src(src_), scale_x(scale_x_), scale_y(scale_y_){}
+
+        __device__ __forceinline__ elem_type operator ()(float y, float x) const
+        {
+            float fsx1 = x * scale_x;
+            float fsx2 = fsx1 + scale_x;
+
+            int sx1 = __float2int_ru(fsx1);
+            int sx2 = __float2int_rd(fsx2);
+
+            float fsy1 = y * scale_y;
+            float fsy2 = fsy1 + scale_y;
+
+            int sy1 = __float2int_ru(fsy1);
+            int sy2 = __float2int_rd(fsy2);
+
+            float scale = 1.f / (fminf(scale_x, src.width - fsx1) * fminf(scale_y, src.height - fsy1));
+
+            typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
+            work_type out = VecTraits<work_type>::all(0.f);
+
+            for (int dy = sy1; dy < sy2; ++dy)
+            {
+                for (int dx = sx1; dx < sx2; ++dx)
+                    out = out + src(dy, dx) * scale;
+
+                if (sx1 > fsx1)
+                    out = out + src(dy, (sx1 -1) ) * ((sx1 - fsx1) * scale);
+
+                if (sx2 < fsx2)
+                    out = out + src(dy, sx2) * ((fsx2 -sx2) * scale);
+            }
+
+            if (sy1 > fsy1)
+                for (int dx = sx1; dx < sx2; ++dx)
+                    out = out + src( (sy1 - 1) , dx) * ((sy1 -fsy1) * scale);
+
+            if (sy2 < fsy2)
+                for (int dx = sx1; dx < sx2; ++dx)
+                    out = out + src(sy2, dx) * ((fsy2 -sy2) * scale);
+
+            if ((sy1 > fsy1) &&  (sx1 > fsx1))
+                out = out + src( (sy1 - 1) , (sx1 - 1)) * ((sy1 -fsy1) * (sx1 -fsx1) * scale);
+
+            if ((sy1 > fsy1) &&  (sx2 < fsx2))
+                out = out + src( (sy1 - 1) , sx2) * ((sy1 -fsy1) * (fsx2 -sx2) * scale);
+
+            if ((sy2 < fsy2) &&  (sx2 < fsx2))
+                out = out + src(sy2, sx2) * ((fsy2 -sy2) * (fsx2 -sx2) * scale);
+
+            if ((sy2 < fsy2) &&  (sx1 > fsx1))
+                out = out + src(sy2, (sx1 - 1)) * ((fsy2 -sy2) * (sx1 -fsx1) * scale);
+
+            return saturate_cast<elem_type>(out);
+        }
+
+        Ptr2D src;
+        float scale_x, scale_y;
+        int width, haight;
+    };
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_FILTERS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/funcattrib.hpp

@@ -0,0 +1,79 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_DEVICE_FUNCATTRIB_HPP
+#define OPENCV_CUDA_DEVICE_FUNCATTRIB_HPP
+
+#include <cstdio>
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template<class Func>
+    void printFuncAttrib(Func& func)
+    {
+
+        cudaFuncAttributes attrs;
+        cudaFuncGetAttributes(&attrs, func);
+
+        printf("=== Function stats ===\n");
+        printf("Name: \n");
+        printf("sharedSizeBytes    = %d\n", attrs.sharedSizeBytes);
+        printf("constSizeBytes     = %d\n", attrs.constSizeBytes);
+        printf("localSizeBytes     = %d\n", attrs.localSizeBytes);
+        printf("maxThreadsPerBlock = %d\n", attrs.maxThreadsPerBlock);
+        printf("numRegs            = %d\n", attrs.numRegs);
+        printf("ptxVersion         = %d\n", attrs.ptxVersion);
+        printf("binaryVersion      = %d\n", attrs.binaryVersion);
+        printf("\n");
+        fflush(stdout);
+    }
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif  /* OPENCV_CUDA_DEVICE_FUNCATTRIB_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/functional.hpp

@@ -0,0 +1,805 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_FUNCTIONAL_HPP
+#define OPENCV_CUDA_FUNCTIONAL_HPP
+
+#include <functional>
+#include "saturate_cast.hpp"
+#include "vec_traits.hpp"
+#include "type_traits.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    // Function Objects
+    template<typename Argument, typename Result> struct unary_function
+    {
+        typedef Argument argument_type;
+        typedef Result result_type;
+    };
+    template<typename Argument1, typename Argument2, typename Result> struct binary_function
+    {
+        typedef Argument1 first_argument_type;
+        typedef Argument2 second_argument_type;
+        typedef Result result_type;
+    };
+
+    // Arithmetic Operations
+    template <typename T> struct plus : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a + b;
+        }
+        __host__ __device__ __forceinline__ plus() {}
+        __host__ __device__ __forceinline__ plus(const plus&) {}
+    };
+
+    template <typename T> struct minus : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a - b;
+        }
+        __host__ __device__ __forceinline__ minus() {}
+        __host__ __device__ __forceinline__ minus(const minus&) {}
+    };
+
+    template <typename T> struct multiplies : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a * b;
+        }
+        __host__ __device__ __forceinline__ multiplies() {}
+        __host__ __device__ __forceinline__ multiplies(const multiplies&) {}
+    };
+
+    template <typename T> struct divides : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a / b;
+        }
+        __host__ __device__ __forceinline__ divides() {}
+        __host__ __device__ __forceinline__ divides(const divides&) {}
+    };
+
+    template <typename T> struct modulus : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a % b;
+        }
+        __host__ __device__ __forceinline__ modulus() {}
+        __host__ __device__ __forceinline__ modulus(const modulus&) {}
+    };
+
+    template <typename T> struct negate : unary_function<T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a) const
+        {
+            return -a;
+        }
+        __host__ __device__ __forceinline__ negate() {}
+        __host__ __device__ __forceinline__ negate(const negate&) {}
+    };
+
+    // Comparison Operations
+    template <typename T> struct equal_to : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a == b;
+        }
+        __host__ __device__ __forceinline__ equal_to() {}
+        __host__ __device__ __forceinline__ equal_to(const equal_to&) {}
+    };
+
+    template <typename T> struct not_equal_to : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a != b;
+        }
+        __host__ __device__ __forceinline__ not_equal_to() {}
+        __host__ __device__ __forceinline__ not_equal_to(const not_equal_to&) {}
+    };
+
+    template <typename T> struct greater : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a > b;
+        }
+        __host__ __device__ __forceinline__ greater() {}
+        __host__ __device__ __forceinline__ greater(const greater&) {}
+    };
+
+    template <typename T> struct less : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a < b;
+        }
+        __host__ __device__ __forceinline__ less() {}
+        __host__ __device__ __forceinline__ less(const less&) {}
+    };
+
+    template <typename T> struct greater_equal : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a >= b;
+        }
+        __host__ __device__ __forceinline__ greater_equal() {}
+        __host__ __device__ __forceinline__ greater_equal(const greater_equal&) {}
+    };
+
+    template <typename T> struct less_equal : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a <= b;
+        }
+        __host__ __device__ __forceinline__ less_equal() {}
+        __host__ __device__ __forceinline__ less_equal(const less_equal&) {}
+    };
+
+    // Logical Operations
+    template <typename T> struct logical_and : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a && b;
+        }
+        __host__ __device__ __forceinline__ logical_and() {}
+        __host__ __device__ __forceinline__ logical_and(const logical_and&) {}
+    };
+
+    template <typename T> struct logical_or : binary_function<T, T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
+                                                    typename TypeTraits<T>::ParameterType b) const
+        {
+            return a || b;
+        }
+        __host__ __device__ __forceinline__ logical_or() {}
+        __host__ __device__ __forceinline__ logical_or(const logical_or&) {}
+    };
+
+    template <typename T> struct logical_not : unary_function<T, bool>
+    {
+        __device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a) const
+        {
+            return !a;
+        }
+        __host__ __device__ __forceinline__ logical_not() {}
+        __host__ __device__ __forceinline__ logical_not(const logical_not&) {}
+    };
+
+    // Bitwise Operations
+    template <typename T> struct bit_and : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a & b;
+        }
+        __host__ __device__ __forceinline__ bit_and() {}
+        __host__ __device__ __forceinline__ bit_and(const bit_and&) {}
+    };
+
+    template <typename T> struct bit_or : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a | b;
+        }
+        __host__ __device__ __forceinline__ bit_or() {}
+        __host__ __device__ __forceinline__ bit_or(const bit_or&) {}
+    };
+
+    template <typename T> struct bit_xor : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
+                                                 typename TypeTraits<T>::ParameterType b) const
+        {
+            return a ^ b;
+        }
+        __host__ __device__ __forceinline__ bit_xor() {}
+        __host__ __device__ __forceinline__ bit_xor(const bit_xor&) {}
+    };
+
+    template <typename T> struct bit_not : unary_function<T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType v) const
+        {
+            return ~v;
+        }
+        __host__ __device__ __forceinline__ bit_not() {}
+        __host__ __device__ __forceinline__ bit_not(const bit_not&) {}
+    };
+
+    // Generalized Identity Operations
+    template <typename T> struct identity : unary_function<T, T>
+    {
+        __device__ __forceinline__ typename TypeTraits<T>::ParameterType operator()(typename TypeTraits<T>::ParameterType x) const
+        {
+            return x;
+        }
+        __host__ __device__ __forceinline__ identity() {}
+        __host__ __device__ __forceinline__ identity(const identity&) {}
+    };
+
+    template <typename T1, typename T2> struct project1st : binary_function<T1, T2, T1>
+    {
+        __device__ __forceinline__ typename TypeTraits<T1>::ParameterType operator()(typename TypeTraits<T1>::ParameterType lhs, typename TypeTraits<T2>::ParameterType rhs) const
+        {
+            return lhs;
+        }
+        __host__ __device__ __forceinline__ project1st() {}
+        __host__ __device__ __forceinline__ project1st(const project1st&) {}
+    };
+
+    template <typename T1, typename T2> struct project2nd : binary_function<T1, T2, T2>
+    {
+        __device__ __forceinline__ typename TypeTraits<T2>::ParameterType operator()(typename TypeTraits<T1>::ParameterType lhs, typename TypeTraits<T2>::ParameterType rhs) const
+        {
+            return rhs;
+        }
+        __host__ __device__ __forceinline__ project2nd() {}
+        __host__ __device__ __forceinline__ project2nd(const project2nd&) {}
+    };
+
+    // Min/Max Operations
+
+#define OPENCV_CUDA_IMPLEMENT_MINMAX(name, type, op) \
+    template <> struct name<type> : binary_function<type, type, type> \
+    { \
+        __device__ __forceinline__ type operator()(type lhs, type rhs) const {return op(lhs, rhs);} \
+        __host__ __device__ __forceinline__ name() {}\
+        __host__ __device__ __forceinline__ name(const name&) {}\
+    };
+
+    template <typename T> struct maximum : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator()(typename TypeTraits<T>::ParameterType lhs, typename TypeTraits<T>::ParameterType rhs) const
+        {
+            return max(lhs, rhs);
+        }
+        __host__ __device__ __forceinline__ maximum() {}
+        __host__ __device__ __forceinline__ maximum(const maximum&) {}
+    };
+
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, uchar, ::max)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, schar, ::max)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, char, ::max)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, ushort, ::max)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, short, ::max)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, int, ::max)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, uint, ::max)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, float, ::fmax)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(maximum, double, ::fmax)
+
+    template <typename T> struct minimum : binary_function<T, T, T>
+    {
+        __device__ __forceinline__ T operator()(typename TypeTraits<T>::ParameterType lhs, typename TypeTraits<T>::ParameterType rhs) const
+        {
+            return min(lhs, rhs);
+        }
+        __host__ __device__ __forceinline__ minimum() {}
+        __host__ __device__ __forceinline__ minimum(const minimum&) {}
+    };
+
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, uchar, ::min)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, schar, ::min)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, char, ::min)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, ushort, ::min)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, short, ::min)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, int, ::min)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, uint, ::min)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, float, ::fmin)
+    OPENCV_CUDA_IMPLEMENT_MINMAX(minimum, double, ::fmin)
+
+#undef OPENCV_CUDA_IMPLEMENT_MINMAX
+
+    // Math functions
+
+    template <typename T> struct abs_func : unary_function<T, T>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType x) const
+        {
+            return abs(x);
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<unsigned char> : unary_function<unsigned char, unsigned char>
+    {
+        __device__ __forceinline__ unsigned char operator ()(unsigned char x) const
+        {
+            return x;
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<signed char> : unary_function<signed char, signed char>
+    {
+        __device__ __forceinline__ signed char operator ()(signed char x) const
+        {
+            return ::abs((int)x);
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<char> : unary_function<char, char>
+    {
+        __device__ __forceinline__ char operator ()(char x) const
+        {
+            return ::abs((int)x);
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<unsigned short> : unary_function<unsigned short, unsigned short>
+    {
+        __device__ __forceinline__ unsigned short operator ()(unsigned short x) const
+        {
+            return x;
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<short> : unary_function<short, short>
+    {
+        __device__ __forceinline__ short operator ()(short x) const
+        {
+            return ::abs((int)x);
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<unsigned int> : unary_function<unsigned int, unsigned int>
+    {
+        __device__ __forceinline__ unsigned int operator ()(unsigned int x) const
+        {
+            return x;
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<int> : unary_function<int, int>
+    {
+        __device__ __forceinline__ int operator ()(int x) const
+        {
+            return ::abs(x);
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<float> : unary_function<float, float>
+    {
+        __device__ __forceinline__ float operator ()(float x) const
+        {
+            return ::fabsf(x);
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+    template <> struct abs_func<double> : unary_function<double, double>
+    {
+        __device__ __forceinline__ double operator ()(double x) const
+        {
+            return ::fabs(x);
+        }
+
+        __host__ __device__ __forceinline__ abs_func() {}
+        __host__ __device__ __forceinline__ abs_func(const abs_func&) {}
+    };
+
+#define OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(name, func) \
+    template <typename T> struct name ## _func : unary_function<T, float> \
+    { \
+        __device__ __forceinline__ float operator ()(typename TypeTraits<T>::ParameterType v) const \
+        { \
+            return func ## f(v); \
+        } \
+        __host__ __device__ __forceinline__ name ## _func() {} \
+        __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \
+    }; \
+    template <> struct name ## _func<double> : unary_function<double, double> \
+    { \
+        __device__ __forceinline__ double operator ()(double v) const \
+        { \
+            return func(v); \
+        } \
+        __host__ __device__ __forceinline__ name ## _func() {} \
+        __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \
+    };
+
+#define OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(name, func) \
+    template <typename T> struct name ## _func : binary_function<T, T, float> \
+    { \
+        __device__ __forceinline__ float operator ()(typename TypeTraits<T>::ParameterType v1, typename TypeTraits<T>::ParameterType v2) const \
+        { \
+            return func ## f(v1, v2); \
+        } \
+        __host__ __device__ __forceinline__ name ## _func() {} \
+        __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \
+    }; \
+    template <> struct name ## _func<double> : binary_function<double, double, double> \
+    { \
+        __device__ __forceinline__ double operator ()(double v1, double v2) const \
+        { \
+            return func(v1, v2); \
+        } \
+        __host__ __device__ __forceinline__ name ## _func() {} \
+        __host__ __device__ __forceinline__ name ## _func(const name ## _func&) {} \
+    };
+
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(sqrt, ::sqrt)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(exp, ::exp)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(exp2, ::exp2)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(exp10, ::exp10)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(log, ::log)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(log2, ::log2)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(log10, ::log10)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(sin, ::sin)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(cos, ::cos)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(tan, ::tan)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(asin, ::asin)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(acos, ::acos)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(atan, ::atan)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(sinh, ::sinh)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(cosh, ::cosh)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(tanh, ::tanh)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(asinh, ::asinh)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(acosh, ::acosh)
+    OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR(atanh, ::atanh)
+
+    OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(hypot, ::hypot)
+    OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(atan2, ::atan2)
+    OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR(pow, ::pow)
+
+    #undef OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR
+    #undef OPENCV_CUDA_IMPLEMENT_UN_FUNCTOR_NO_DOUBLE
+    #undef OPENCV_CUDA_IMPLEMENT_BIN_FUNCTOR
+
+    template<typename T> struct hypot_sqr_func : binary_function<T, T, float>
+    {
+        __device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType src1, typename TypeTraits<T>::ParameterType src2) const
+        {
+            return src1 * src1 + src2 * src2;
+        }
+        __host__ __device__ __forceinline__ hypot_sqr_func() {}
+        __host__ __device__ __forceinline__ hypot_sqr_func(const hypot_sqr_func&) {}
+    };
+
+    // Saturate Cast Functor
+    template <typename T, typename D> struct saturate_cast_func : unary_function<T, D>
+    {
+        __device__ __forceinline__ D operator ()(typename TypeTraits<T>::ParameterType v) const
+        {
+            return saturate_cast<D>(v);
+        }
+        __host__ __device__ __forceinline__ saturate_cast_func() {}
+        __host__ __device__ __forceinline__ saturate_cast_func(const saturate_cast_func&) {}
+    };
+
+    // Threshold Functors
+    template <typename T> struct thresh_binary_func : unary_function<T, T>
+    {
+        __host__ __device__ __forceinline__ thresh_binary_func(T thresh_, T maxVal_) : thresh(thresh_), maxVal(maxVal_) {}
+
+        __device__ __forceinline__ T operator()(typename TypeTraits<T>::ParameterType src) const
+        {
+            return (src > thresh) * maxVal;
+        }
+
+        __host__ __device__ __forceinline__ thresh_binary_func() {}
+        __host__ __device__ __forceinline__ thresh_binary_func(const thresh_binary_func& other)
+            : thresh(other.thresh), maxVal(other.maxVal) {}
+
+        T thresh;
+        T maxVal;
+    };
+
+    template <typename T> struct thresh_binary_inv_func : unary_function<T, T>
+    {
+        __host__ __device__ __forceinline__ thresh_binary_inv_func(T thresh_, T maxVal_) : thresh(thresh_), maxVal(maxVal_) {}
+
+        __device__ __forceinline__ T operator()(typename TypeTraits<T>::ParameterType src) const
+        {
+            return (src <= thresh) * maxVal;
+        }
+
+        __host__ __device__ __forceinline__ thresh_binary_inv_func() {}
+        __host__ __device__ __forceinline__ thresh_binary_inv_func(const thresh_binary_inv_func& other)
+            : thresh(other.thresh), maxVal(other.maxVal) {}
+
+        T thresh;
+        T maxVal;
+    };
+
+    template <typename T> struct thresh_trunc_func : unary_function<T, T>
+    {
+        explicit __host__ __device__ __forceinline__ thresh_trunc_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {CV_UNUSED(maxVal_);}
+
+        __device__ __forceinline__ T operator()(typename TypeTraits<T>::ParameterType src) const
+        {
+            return minimum<T>()(src, thresh);
+        }
+
+        __host__ __device__ __forceinline__ thresh_trunc_func() {}
+        __host__ __device__ __forceinline__ thresh_trunc_func(const thresh_trunc_func& other)
+            : thresh(other.thresh) {}
+
+        T thresh;
+    };
+
+    template <typename T> struct thresh_to_zero_func : unary_function<T, T>
+    {
+        explicit __host__ __device__ __forceinline__ thresh_to_zero_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {CV_UNUSED(maxVal_);}
+
+        __device__ __forceinline__ T operator()(typename TypeTraits<T>::ParameterType src) const
+        {
+            return (src > thresh) * src;
+        }
+
+        __host__ __device__ __forceinline__ thresh_to_zero_func() {}
+       __host__  __device__ __forceinline__ thresh_to_zero_func(const thresh_to_zero_func& other)
+            : thresh(other.thresh) {}
+
+        T thresh;
+    };
+
+    template <typename T> struct thresh_to_zero_inv_func : unary_function<T, T>
+    {
+        explicit __host__ __device__ __forceinline__ thresh_to_zero_inv_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {CV_UNUSED(maxVal_);}
+
+        __device__ __forceinline__ T operator()(typename TypeTraits<T>::ParameterType src) const
+        {
+            return (src <= thresh) * src;
+        }
+
+        __host__ __device__ __forceinline__ thresh_to_zero_inv_func() {}
+        __host__ __device__ __forceinline__ thresh_to_zero_inv_func(const thresh_to_zero_inv_func& other)
+            : thresh(other.thresh) {}
+
+        T thresh;
+    };
+
+    // Function Object Adaptors
+    template <typename Predicate> struct unary_negate : unary_function<typename Predicate::argument_type, bool>
+    {
+      explicit __host__ __device__ __forceinline__ unary_negate(const Predicate& p) : pred(p) {}
+
+      __device__ __forceinline__ bool operator()(typename TypeTraits<typename Predicate::argument_type>::ParameterType x) const
+      {
+          return !pred(x);
+      }
+
+      __host__ __device__ __forceinline__ unary_negate() {}
+      __host__ __device__ __forceinline__ unary_negate(const unary_negate& other) : pred(other.pred) {}
+
+      Predicate pred;
+    };
+
+    template <typename Predicate> __host__ __device__ __forceinline__ unary_negate<Predicate> not1(const Predicate& pred)
+    {
+        return unary_negate<Predicate>(pred);
+    }
+
+    template <typename Predicate> struct binary_negate : binary_function<typename Predicate::first_argument_type, typename Predicate::second_argument_type, bool>
+    {
+        explicit __host__ __device__ __forceinline__ binary_negate(const Predicate& p) : pred(p) {}
+
+        __device__ __forceinline__ bool operator()(typename TypeTraits<typename Predicate::first_argument_type>::ParameterType x,
+                                                   typename TypeTraits<typename Predicate::second_argument_type>::ParameterType y) const
+        {
+            return !pred(x,y);
+        }
+
+        __host__ __device__ __forceinline__ binary_negate() {}
+        __host__ __device__ __forceinline__ binary_negate(const binary_negate& other) : pred(other.pred) {}
+
+        Predicate pred;
+    };
+
+    template <typename BinaryPredicate> __host__ __device__ __forceinline__ binary_negate<BinaryPredicate> not2(const BinaryPredicate& pred)
+    {
+        return binary_negate<BinaryPredicate>(pred);
+    }
+
+    template <typename Op> struct binder1st : unary_function<typename Op::second_argument_type, typename Op::result_type>
+    {
+        __host__ __device__ __forceinline__ binder1st(const Op& op_, const typename Op::first_argument_type& arg1_) : op(op_), arg1(arg1_) {}
+
+        __device__ __forceinline__ typename Op::result_type operator ()(typename TypeTraits<typename Op::second_argument_type>::ParameterType a) const
+        {
+            return op(arg1, a);
+        }
+
+        __host__ __device__ __forceinline__ binder1st() {}
+        __host__ __device__ __forceinline__ binder1st(const binder1st& other) : op(other.op), arg1(other.arg1) {}
+
+        Op op;
+        typename Op::first_argument_type arg1;
+    };
+
+    template <typename Op, typename T> __host__ __device__ __forceinline__ binder1st<Op> bind1st(const Op& op, const T& x)
+    {
+        return binder1st<Op>(op, typename Op::first_argument_type(x));
+    }
+
+    template <typename Op> struct binder2nd : unary_function<typename Op::first_argument_type, typename Op::result_type>
+    {
+        __host__ __device__ __forceinline__ binder2nd(const Op& op_, const typename Op::second_argument_type& arg2_) : op(op_), arg2(arg2_) {}
+
+        __forceinline__ __device__ typename Op::result_type operator ()(typename TypeTraits<typename Op::first_argument_type>::ParameterType a) const
+        {
+            return op(a, arg2);
+        }
+
+        __host__ __device__ __forceinline__ binder2nd() {}
+        __host__ __device__ __forceinline__ binder2nd(const binder2nd& other) : op(other.op), arg2(other.arg2) {}
+
+        Op op;
+        typename Op::second_argument_type arg2;
+    };
+
+    template <typename Op, typename T> __host__ __device__ __forceinline__ binder2nd<Op> bind2nd(const Op& op, const T& x)
+    {
+        return binder2nd<Op>(op, typename Op::second_argument_type(x));
+    }
+
+    // Functor Traits
+    template <typename F> struct IsUnaryFunction
+    {
+        typedef char Yes;
+        struct No {Yes a[2];};
+
+        template <typename T, typename D> static Yes check(unary_function<T, D>);
+        static No check(...);
+
+        static F makeF();
+
+        enum { value = (sizeof(check(makeF())) == sizeof(Yes)) };
+    };
+
+    template <typename F> struct IsBinaryFunction
+    {
+        typedef char Yes;
+        struct No {Yes a[2];};
+
+        template <typename T1, typename T2, typename D> static Yes check(binary_function<T1, T2, D>);
+        static No check(...);
+
+        static F makeF();
+
+        enum { value = (sizeof(check(makeF())) == sizeof(Yes)) };
+    };
+
+    namespace functional_detail
+    {
+        template <size_t src_elem_size, size_t dst_elem_size> struct UnOpShift { enum { shift = 1 }; };
+        template <size_t src_elem_size> struct UnOpShift<src_elem_size, 1> { enum { shift = 4 }; };
+        template <size_t src_elem_size> struct UnOpShift<src_elem_size, 2> { enum { shift = 2 }; };
+
+        template <typename T, typename D> struct DefaultUnaryShift
+        {
+            enum { shift = UnOpShift<sizeof(T), sizeof(D)>::shift };
+        };
+
+        template <size_t src_elem_size1, size_t src_elem_size2, size_t dst_elem_size> struct BinOpShift { enum { shift = 1 }; };
+        template <size_t src_elem_size1, size_t src_elem_size2> struct BinOpShift<src_elem_size1, src_elem_size2, 1> { enum { shift = 4 }; };
+        template <size_t src_elem_size1, size_t src_elem_size2> struct BinOpShift<src_elem_size1, src_elem_size2, 2> { enum { shift = 2 }; };
+
+        template <typename T1, typename T2, typename D> struct DefaultBinaryShift
+        {
+            enum { shift = BinOpShift<sizeof(T1), sizeof(T2), sizeof(D)>::shift };
+        };
+
+        template <typename Func, bool unary = IsUnaryFunction<Func>::value> struct ShiftDispatcher;
+        template <typename Func> struct ShiftDispatcher<Func, true>
+        {
+            enum { shift = DefaultUnaryShift<typename Func::argument_type, typename Func::result_type>::shift };
+        };
+        template <typename Func> struct ShiftDispatcher<Func, false>
+        {
+            enum { shift = DefaultBinaryShift<typename Func::first_argument_type, typename Func::second_argument_type, typename Func::result_type>::shift };
+        };
+    }
+
+    template <typename Func> struct DefaultTransformShift
+    {
+        enum { shift = functional_detail::ShiftDispatcher<Func>::shift };
+    };
+
+    template <typename Func> struct DefaultTransformFunctorTraits
+    {
+        enum { simple_block_dim_x = 16 };
+        enum { simple_block_dim_y = 16 };
+
+        enum { smart_block_dim_x = 16 };
+        enum { smart_block_dim_y = 16 };
+        enum { smart_shift = DefaultTransformShift<Func>::shift };
+    };
+
+    template <typename Func> struct TransformFunctorTraits : DefaultTransformFunctorTraits<Func> {};
+
+#define OPENCV_CUDA_TRANSFORM_FUNCTOR_TRAITS(type) \
+    template <> struct TransformFunctorTraits< type > : DefaultTransformFunctorTraits< type >
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_FUNCTIONAL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/limits.hpp

@@ -0,0 +1,128 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_LIMITS_HPP
+#define OPENCV_CUDA_LIMITS_HPP
+
+#include <limits.h>
+#include <float.h>
+#include "common.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+template <class T> struct numeric_limits;
+
+template <> struct numeric_limits<bool>
+{
+    __device__ __forceinline__ static bool min() { return false; }
+    __device__ __forceinline__ static bool max() { return true;  }
+    static const bool is_signed = false;
+};
+
+template <> struct numeric_limits<signed char>
+{
+    __device__ __forceinline__ static signed char min() { return SCHAR_MIN; }
+    __device__ __forceinline__ static signed char max() { return SCHAR_MAX; }
+    static const bool is_signed = true;
+};
+
+template <> struct numeric_limits<unsigned char>
+{
+    __device__ __forceinline__ static unsigned char min() { return 0; }
+    __device__ __forceinline__ static unsigned char max() { return UCHAR_MAX; }
+    static const bool is_signed = false;
+};
+
+template <> struct numeric_limits<short>
+{
+    __device__ __forceinline__ static short min() { return SHRT_MIN; }
+    __device__ __forceinline__ static short max() { return SHRT_MAX; }
+    static const bool is_signed = true;
+};
+
+template <> struct numeric_limits<unsigned short>
+{
+    __device__ __forceinline__ static unsigned short min() { return 0; }
+    __device__ __forceinline__ static unsigned short max() { return USHRT_MAX; }
+    static const bool is_signed = false;
+};
+
+template <> struct numeric_limits<int>
+{
+    __device__ __forceinline__ static int min() { return INT_MIN; }
+    __device__ __forceinline__ static int max() { return INT_MAX; }
+    static const bool is_signed = true;
+};
+
+template <> struct numeric_limits<unsigned int>
+{
+    __device__ __forceinline__ static unsigned int min() { return 0; }
+    __device__ __forceinline__ static unsigned int max() { return UINT_MAX; }
+    static const bool is_signed = false;
+};
+
+template <> struct numeric_limits<float>
+{
+    __device__ __forceinline__ static float min() { return FLT_MIN; }
+    __device__ __forceinline__ static float max() { return FLT_MAX; }
+    __device__ __forceinline__ static float epsilon() { return FLT_EPSILON; }
+    static const bool is_signed = true;
+};
+
+template <> struct numeric_limits<double>
+{
+    __device__ __forceinline__ static double min() { return DBL_MIN; }
+    __device__ __forceinline__ static double max() { return DBL_MAX; }
+    __device__ __forceinline__ static double epsilon() { return DBL_EPSILON; }
+    static const bool is_signed = true;
+};
+}}} // namespace cv { namespace cuda { namespace cudev {
+
+//! @endcond
+
+#endif // OPENCV_CUDA_LIMITS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/reduce.hpp

@@ -0,0 +1,230 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_REDUCE_HPP
+#define OPENCV_CUDA_REDUCE_HPP
+
+#ifndef THRUST_DEBUG // eliminate -Wundef warning
+#define THRUST_DEBUG 0
+#endif
+
+#include <thrust/tuple.h>
+#include "detail/reduce.hpp"
+#include "detail/reduce_key_val.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template <int N, typename T, class Op>
+    __device__ __forceinline__ void reduce(volatile T* smem, T& val, unsigned int tid, const Op& op)
+    {
+        reduce_detail::Dispatcher<N>::reductor::template reduce<volatile T*, T&, const Op&>(smem, val, tid, op);
+    }
+    template <unsigned int N, typename K, typename V, class Cmp>
+    __device__ __forceinline__ void reduceKeyVal(volatile K* skeys, K& key, volatile V* svals, V& val, unsigned int tid, const Cmp& cmp)
+    {
+        reduce_key_val_detail::Dispatcher<N>::reductor::template reduce<volatile K*, K&, volatile V*, V&, const Cmp&>(skeys, key, svals, val, tid, cmp);
+    }
+#if (CUDART_VERSION < 12040) // details: https://github.com/opencv/opencv_contrib/issues/3690
+    template <int N,
+              typename P0, typename P1, typename P2, typename P3, typename P4, typename P5, typename P6, typename P7, typename P8, typename P9,
+              typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9,
+              class Op0, class Op1, class Op2, class Op3, class Op4, class Op5, class Op6, class Op7, class Op8, class Op9>
+    __device__ __forceinline__ void reduce(const thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>& smem,
+                                           const thrust::tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
+                                           unsigned int tid,
+                                           const thrust::tuple<Op0, Op1, Op2, Op3, Op4, Op5, Op6, Op7, Op8, Op9>& op)
+    {
+        reduce_detail::Dispatcher<N>::reductor::template reduce<
+                const thrust::tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>&,
+                const thrust::tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>&,
+                const thrust::tuple<Op0, Op1, Op2, Op3, Op4, Op5, Op6, Op7, Op8, Op9>&>(smem, val, tid, op);
+    }
+
+    template <unsigned int N,
+              typename K,
+              typename VP0, typename VP1, typename VP2, typename VP3, typename VP4, typename VP5, typename VP6, typename VP7, typename VP8, typename VP9,
+              typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9,
+              class Cmp>
+    __device__ __forceinline__ void reduceKeyVal(volatile K* skeys, K& key,
+                                                 const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>& svals,
+                                                 const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                                 unsigned int tid, const Cmp& cmp)
+    {
+        reduce_key_val_detail::Dispatcher<N>::reductor::template reduce<volatile K*, K&,
+                const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>&,
+                const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>&,
+                const Cmp&>(skeys, key, svals, val, tid, cmp);
+    }
+
+    template <unsigned int N,
+              typename KP0, typename KP1, typename KP2, typename KP3, typename KP4, typename KP5, typename KP6, typename KP7, typename KP8, typename KP9,
+              typename KR0, typename KR1, typename KR2, typename KR3, typename KR4, typename KR5, typename KR6, typename KR7, typename KR8, typename KR9,
+              typename VP0, typename VP1, typename VP2, typename VP3, typename VP4, typename VP5, typename VP6, typename VP7, typename VP8, typename VP9,
+              typename VR0, typename VR1, typename VR2, typename VR3, typename VR4, typename VR5, typename VR6, typename VR7, typename VR8, typename VR9,
+              class Cmp0, class Cmp1, class Cmp2, class Cmp3, class Cmp4, class Cmp5, class Cmp6, class Cmp7, class Cmp8, class Cmp9>
+    __device__ __forceinline__ void reduceKeyVal(const thrust::tuple<KP0, KP1, KP2, KP3, KP4, KP5, KP6, KP7, KP8, KP9>& skeys,
+                                                 const thrust::tuple<KR0, KR1, KR2, KR3, KR4, KR5, KR6, KR7, KR8, KR9>& key,
+                                                 const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>& svals,
+                                                 const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>& val,
+                                                 unsigned int tid,
+                                                 const thrust::tuple<Cmp0, Cmp1, Cmp2, Cmp3, Cmp4, Cmp5, Cmp6, Cmp7, Cmp8, Cmp9>& cmp)
+    {
+        reduce_key_val_detail::Dispatcher<N>::reductor::template reduce<
+                const thrust::tuple<KP0, KP1, KP2, KP3, KP4, KP5, KP6, KP7, KP8, KP9>&,
+                const thrust::tuple<KR0, KR1, KR2, KR3, KR4, KR5, KR6, KR7, KR8, KR9>&,
+                const thrust::tuple<VP0, VP1, VP2, VP3, VP4, VP5, VP6, VP7, VP8, VP9>&,
+                const thrust::tuple<VR0, VR1, VR2, VR3, VR4, VR5, VR6, VR7, VR8, VR9>&,
+                const thrust::tuple<Cmp0, Cmp1, Cmp2, Cmp3, Cmp4, Cmp5, Cmp6, Cmp7, Cmp8, Cmp9>&
+                >(skeys, key, svals, val, tid, cmp);
+    }
+#else
+    template <int N, typename... P, typename... R, class... Op>
+    __device__ __forceinline__ void reduce(const thrust::tuple<P...>& smem, const thrust::tuple<R...>& val, unsigned int tid, const thrust::tuple<Op...>& op)
+    {
+        reduce_detail::Dispatcher<N>::reductor::template reduce<const thrust::tuple<P...>&, const thrust::tuple<R...>&, const thrust::tuple<Op...>&>(smem, val, tid, op);
+    }
+
+    template <unsigned int N, typename K, typename... VP, typename... VR, class Cmp>
+    __device__ __forceinline__ void reduceKeyVal(volatile K* skeys, K& key, const thrust::tuple<VP...>& svals, const thrust::tuple<VR...>& val, unsigned int tid, const Cmp& cmp)
+    {
+        reduce_key_val_detail::Dispatcher<N>::reductor::template reduce<volatile K*, K&, const thrust::tuple<VP...>&, const thrust::tuple<VR...>&, const Cmp&>(skeys, key, svals, val, tid, cmp);
+    }
+
+    template <unsigned int N, typename... KP, typename... KR, typename... VP, typename... VR, class... Cmp>
+    __device__ __forceinline__ void reduceKeyVal(const thrust::tuple<KP...>& skeys, const thrust::tuple<KR...>& key, const thrust::tuple<VP...>& svals, const thrust::tuple<VR...>& val, unsigned int tid, const thrust::tuple<Cmp...>& cmp)
+    {
+        reduce_key_val_detail::Dispatcher<N>::reductor::template reduce<const thrust::tuple<KP...>&, const thrust::tuple<KR...>&, const thrust::tuple<VP...>&, const thrust::tuple<VR...>&, const thrust::tuple<Cmp...>&>(skeys, key, svals, val, tid, cmp);
+    }
+#endif
+
+    // smem_tuple
+
+    template <typename T0>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*>
+    smem_tuple(T0* t0)
+    {
+        return thrust::make_tuple((volatile T0*) t0);
+    }
+
+    template <typename T0, typename T1>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*>
+    smem_tuple(T0* t0, T1* t1)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1);
+    }
+
+    template <typename T0, typename T1, typename T2>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*>
+    smem_tuple(T0* t0, T1* t1, T2* t2)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2);
+    }
+
+    template <typename T0, typename T1, typename T2, typename T3>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*, volatile T3*>
+    smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3);
+    }
+
+    template <typename T0, typename T1, typename T2, typename T3, typename T4>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*, volatile T3*, volatile T4*>
+    smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4);
+    }
+
+    template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*, volatile T3*, volatile T4*, volatile T5*>
+    smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5);
+    }
+
+    template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename T6>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*, volatile T3*, volatile T4*, volatile T5*, volatile T6*>
+    smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6);
+    }
+
+    template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename T6, typename T7>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*, volatile T3*, volatile T4*, volatile T5*, volatile T6*, volatile T7*>
+    smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6, T7* t7)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6, (volatile T7*) t7);
+    }
+
+    template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename T6, typename T7, typename T8>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*, volatile T3*, volatile T4*, volatile T5*, volatile T6*, volatile T7*, volatile T8*>
+    smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6, T7* t7, T8* t8)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6, (volatile T7*) t7, (volatile T8*) t8);
+    }
+
+    template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename T6, typename T7, typename T8, typename T9>
+    __device__ __forceinline__
+    thrust::tuple<volatile T0*, volatile T1*, volatile T2*, volatile T3*, volatile T4*, volatile T5*, volatile T6*, volatile T7*, volatile T8*, volatile T9*>
+    smem_tuple(T0* t0, T1* t1, T2* t2, T3* t3, T4* t4, T5* t5, T6* t6, T7* t7, T8* t8, T9* t9)
+    {
+        return thrust::make_tuple((volatile T0*) t0, (volatile T1*) t1, (volatile T2*) t2, (volatile T3*) t3, (volatile T4*) t4, (volatile T5*) t5, (volatile T6*) t6, (volatile T7*) t7, (volatile T8*) t8, (volatile T9*) t9);
+    }
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_REDUCE_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/saturate_cast.hpp

@@ -0,0 +1,292 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_SATURATE_CAST_HPP
+#define OPENCV_CUDA_SATURATE_CAST_HPP
+
+#include "common.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(uchar v) { return _Tp(v); }
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(schar v) { return _Tp(v); }
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(ushort v) { return _Tp(v); }
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(short v) { return _Tp(v); }
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(uint v) { return _Tp(v); }
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(int v) { return _Tp(v); }
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(float v) { return _Tp(v); }
+    template<typename _Tp> __device__ __forceinline__ _Tp saturate_cast(double v) { return _Tp(v); }
+
+    template<> __device__ __forceinline__ uchar saturate_cast<uchar>(schar v)
+    {
+        uint res = 0;
+        int vi = v;
+        asm("cvt.sat.u8.s8 %0, %1;" : "=r"(res) : "r"(vi));
+        return res;
+    }
+    template<> __device__ __forceinline__ uchar saturate_cast<uchar>(short v)
+    {
+        uint res = 0;
+        asm("cvt.sat.u8.s16 %0, %1;" : "=r"(res) : "h"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ uchar saturate_cast<uchar>(ushort v)
+    {
+        uint res = 0;
+        asm("cvt.sat.u8.u16 %0, %1;" : "=r"(res) : "h"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ uchar saturate_cast<uchar>(int v)
+    {
+        uint res = 0;
+        asm("cvt.sat.u8.s32 %0, %1;" : "=r"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ uchar saturate_cast<uchar>(uint v)
+    {
+        uint res = 0;
+        asm("cvt.sat.u8.u32 %0, %1;" : "=r"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ uchar saturate_cast<uchar>(float v)
+    {
+        uint res = 0;
+        asm("cvt.rni.sat.u8.f32 %0, %1;" : "=r"(res) : "f"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ uchar saturate_cast<uchar>(double v)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
+        uint res = 0;
+        asm("cvt.rni.sat.u8.f64 %0, %1;" : "=r"(res) : "d"(v));
+        return res;
+    #else
+        return saturate_cast<uchar>((float)v);
+    #endif
+    }
+
+    template<> __device__ __forceinline__ schar saturate_cast<schar>(uchar v)
+    {
+        uint res = 0;
+        uint vi = v;
+        asm("cvt.sat.s8.u8 %0, %1;" : "=r"(res) : "r"(vi));
+        return res;
+    }
+    template<> __device__ __forceinline__ schar saturate_cast<schar>(short v)
+    {
+        uint res = 0;
+        asm("cvt.sat.s8.s16 %0, %1;" : "=r"(res) : "h"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ schar saturate_cast<schar>(ushort v)
+    {
+        uint res = 0;
+        asm("cvt.sat.s8.u16 %0, %1;" : "=r"(res) : "h"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ schar saturate_cast<schar>(int v)
+    {
+        uint res = 0;
+        asm("cvt.sat.s8.s32 %0, %1;" : "=r"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ schar saturate_cast<schar>(uint v)
+    {
+        uint res = 0;
+        asm("cvt.sat.s8.u32 %0, %1;" : "=r"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ schar saturate_cast<schar>(float v)
+    {
+        uint res = 0;
+        asm("cvt.rni.sat.s8.f32 %0, %1;" : "=r"(res) : "f"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ schar saturate_cast<schar>(double v)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
+        uint res = 0;
+        asm("cvt.rni.sat.s8.f64 %0, %1;" : "=r"(res) : "d"(v));
+        return res;
+    #else
+        return saturate_cast<schar>((float)v);
+    #endif
+    }
+
+    template<> __device__ __forceinline__ ushort saturate_cast<ushort>(schar v)
+    {
+        ushort res = 0;
+        int vi = v;
+        asm("cvt.sat.u16.s8 %0, %1;" : "=h"(res) : "r"(vi));
+        return res;
+    }
+    template<> __device__ __forceinline__ ushort saturate_cast<ushort>(short v)
+    {
+        ushort res = 0;
+        asm("cvt.sat.u16.s16 %0, %1;" : "=h"(res) : "h"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ ushort saturate_cast<ushort>(int v)
+    {
+        ushort res = 0;
+        asm("cvt.sat.u16.s32 %0, %1;" : "=h"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ ushort saturate_cast<ushort>(uint v)
+    {
+        ushort res = 0;
+        asm("cvt.sat.u16.u32 %0, %1;" : "=h"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ ushort saturate_cast<ushort>(float v)
+    {
+        ushort res = 0;
+        asm("cvt.rni.sat.u16.f32 %0, %1;" : "=h"(res) : "f"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ ushort saturate_cast<ushort>(double v)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
+        ushort res = 0;
+        asm("cvt.rni.sat.u16.f64 %0, %1;" : "=h"(res) : "d"(v));
+        return res;
+    #else
+        return saturate_cast<ushort>((float)v);
+    #endif
+    }
+
+    template<> __device__ __forceinline__ short saturate_cast<short>(ushort v)
+    {
+        short res = 0;
+        asm("cvt.sat.s16.u16 %0, %1;" : "=h"(res) : "h"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ short saturate_cast<short>(int v)
+    {
+        short res = 0;
+        asm("cvt.sat.s16.s32 %0, %1;" : "=h"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ short saturate_cast<short>(uint v)
+    {
+        short res = 0;
+        asm("cvt.sat.s16.u32 %0, %1;" : "=h"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ short saturate_cast<short>(float v)
+    {
+        short res = 0;
+        asm("cvt.rni.sat.s16.f32 %0, %1;" : "=h"(res) : "f"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ short saturate_cast<short>(double v)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
+        short res = 0;
+        asm("cvt.rni.sat.s16.f64 %0, %1;" : "=h"(res) : "d"(v));
+        return res;
+    #else
+        return saturate_cast<short>((float)v);
+    #endif
+    }
+
+    template<> __device__ __forceinline__ int saturate_cast<int>(uint v)
+    {
+        int res = 0;
+        asm("cvt.sat.s32.u32 %0, %1;" : "=r"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ int saturate_cast<int>(float v)
+    {
+        return __float2int_rn(v);
+    }
+    template<> __device__ __forceinline__ int saturate_cast<int>(double v)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
+        return __double2int_rn(v);
+    #else
+        return saturate_cast<int>((float)v);
+    #endif
+    }
+
+    template<> __device__ __forceinline__ uint saturate_cast<uint>(schar v)
+    {
+        uint res = 0;
+        int vi = v;
+        asm("cvt.sat.u32.s8 %0, %1;" : "=r"(res) : "r"(vi));
+        return res;
+    }
+    template<> __device__ __forceinline__ uint saturate_cast<uint>(short v)
+    {
+        uint res = 0;
+        asm("cvt.sat.u32.s16 %0, %1;" : "=r"(res) : "h"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ uint saturate_cast<uint>(int v)
+    {
+        uint res = 0;
+        asm("cvt.sat.u32.s32 %0, %1;" : "=r"(res) : "r"(v));
+        return res;
+    }
+    template<> __device__ __forceinline__ uint saturate_cast<uint>(float v)
+    {
+        return __float2uint_rn(v);
+    }
+    template<> __device__ __forceinline__ uint saturate_cast<uint>(double v)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
+        return __double2uint_rn(v);
+    #else
+        return saturate_cast<uint>((float)v);
+    #endif
+    }
+}}}
+
+//! @endcond
+
+#endif /* OPENCV_CUDA_SATURATE_CAST_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/scan.hpp

@@ -0,0 +1,258 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_SCAN_HPP
+#define OPENCV_CUDA_SCAN_HPP
+
+#include "opencv2/core/cuda/common.hpp"
+#include "opencv2/core/cuda/utility.hpp"
+#include "opencv2/core/cuda/warp.hpp"
+#include "opencv2/core/cuda/warp_shuffle.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    enum ScanKind { EXCLUSIVE = 0,  INCLUSIVE = 1 };
+
+    template <ScanKind Kind, typename T, typename F> struct WarpScan
+    {
+        __device__ __forceinline__ WarpScan() {}
+        __device__ __forceinline__ WarpScan(const WarpScan& other) { CV_UNUSED(other); }
+
+        __device__ __forceinline__ T operator()( volatile T *ptr , const unsigned int idx)
+        {
+            const unsigned int lane = idx & 31;
+            F op;
+
+            if ( lane >=  1) ptr [idx ] = op(ptr [idx -  1], ptr [idx]);
+            if ( lane >=  2) ptr [idx ] = op(ptr [idx -  2], ptr [idx]);
+            if ( lane >=  4) ptr [idx ] = op(ptr [idx -  4], ptr [idx]);
+            if ( lane >=  8) ptr [idx ] = op(ptr [idx -  8], ptr [idx]);
+            if ( lane >= 16) ptr [idx ] = op(ptr [idx - 16], ptr [idx]);
+
+            if( Kind == INCLUSIVE )
+                return ptr [idx];
+            else
+                return (lane > 0) ? ptr [idx - 1] : 0;
+        }
+
+        __device__ __forceinline__ unsigned int index(const unsigned int tid)
+        {
+            return tid;
+        }
+
+        __device__ __forceinline__ void init(volatile T *ptr){}
+
+        static const int warp_offset      = 0;
+
+        typedef WarpScan<INCLUSIVE, T, F>  merge;
+    };
+
+    template <ScanKind Kind , typename T, typename F> struct WarpScanNoComp
+    {
+        __device__ __forceinline__ WarpScanNoComp() {}
+        __device__ __forceinline__ WarpScanNoComp(const WarpScanNoComp& other) { CV_UNUSED(other); }
+
+        __device__ __forceinline__ T operator()( volatile T *ptr , const unsigned int idx)
+        {
+            const unsigned int lane = threadIdx.x & 31;
+            F op;
+
+            ptr [idx ] = op(ptr [idx -  1], ptr [idx]);
+            ptr [idx ] = op(ptr [idx -  2], ptr [idx]);
+            ptr [idx ] = op(ptr [idx -  4], ptr [idx]);
+            ptr [idx ] = op(ptr [idx -  8], ptr [idx]);
+            ptr [idx ] = op(ptr [idx - 16], ptr [idx]);
+
+            if( Kind == INCLUSIVE )
+                return ptr [idx];
+            else
+                return (lane > 0) ? ptr [idx - 1] : 0;
+        }
+
+        __device__ __forceinline__ unsigned int index(const unsigned int tid)
+        {
+            return (tid >> warp_log) * warp_smem_stride + 16 + (tid & warp_mask);
+        }
+
+        __device__ __forceinline__ void init(volatile T *ptr)
+        {
+            ptr[threadIdx.x] = 0;
+        }
+
+        static const int warp_smem_stride = 32 + 16 + 1;
+        static const int warp_offset      = 16;
+        static const int warp_log         = 5;
+        static const int warp_mask        = 31;
+
+        typedef WarpScanNoComp<INCLUSIVE, T, F> merge;
+    };
+
+    template <ScanKind Kind , typename T, typename Sc, typename F> struct BlockScan
+    {
+        __device__ __forceinline__ BlockScan() {}
+        __device__ __forceinline__ BlockScan(const BlockScan& other) { CV_UNUSED(other); }
+
+        __device__ __forceinline__ T operator()(volatile T *ptr)
+        {
+            const unsigned int tid  = threadIdx.x;
+            const unsigned int lane = tid & warp_mask;
+            const unsigned int warp = tid >> warp_log;
+
+            Sc scan;
+            typename Sc::merge merge_scan;
+            const unsigned int idx = scan.index(tid);
+
+            T val = scan(ptr, idx);
+            __syncthreads ();
+
+            if( warp == 0)
+                scan.init(ptr);
+            __syncthreads ();
+
+            if( lane == 31 )
+                ptr [scan.warp_offset + warp ] = (Kind == INCLUSIVE) ? val : ptr [idx];
+            __syncthreads ();
+
+            if( warp == 0 )
+                merge_scan(ptr, idx);
+            __syncthreads();
+
+            if ( warp > 0)
+                val = ptr [scan.warp_offset + warp - 1] + val;
+            __syncthreads ();
+
+            ptr[idx] = val;
+            __syncthreads ();
+
+            return val ;
+        }
+
+        static const int warp_log  = 5;
+        static const int warp_mask = 31;
+    };
+
+    template <typename T>
+    __device__ T warpScanInclusive(T idata, volatile T* s_Data, unsigned int tid)
+    {
+    #if __CUDA_ARCH__ >= 300
+        const unsigned int laneId = cv::cuda::device::Warp::laneId();
+
+        // scan on shuffl functions
+        #pragma unroll
+        for (int i = 1; i <= (OPENCV_CUDA_WARP_SIZE / 2); i *= 2)
+        {
+            const T n = cv::cuda::device::shfl_up(idata, i);
+            if (laneId >= i)
+                  idata += n;
+        }
+
+        return idata;
+    #else
+        unsigned int pos = 2 * tid - (tid & (OPENCV_CUDA_WARP_SIZE - 1));
+        s_Data[pos] = 0;
+        pos += OPENCV_CUDA_WARP_SIZE;
+        s_Data[pos] = idata;
+
+        s_Data[pos] += s_Data[pos - 1];
+        s_Data[pos] += s_Data[pos - 2];
+        s_Data[pos] += s_Data[pos - 4];
+        s_Data[pos] += s_Data[pos - 8];
+        s_Data[pos] += s_Data[pos - 16];
+
+        return s_Data[pos];
+    #endif
+    }
+
+    template <typename T>
+    __device__ __forceinline__ T warpScanExclusive(T idata, volatile T* s_Data, unsigned int tid)
+    {
+        return warpScanInclusive(idata, s_Data, tid) - idata;
+    }
+
+    template <int tiNumScanThreads, typename T>
+    __device__ T blockScanInclusive(T idata, volatile T* s_Data, unsigned int tid)
+    {
+        if (tiNumScanThreads > OPENCV_CUDA_WARP_SIZE)
+        {
+            //Bottom-level inclusive warp scan
+            T warpResult = warpScanInclusive(idata, s_Data, tid);
+
+            //Save top elements of each warp for exclusive warp scan
+            //sync to wait for warp scans to complete (because s_Data is being overwritten)
+            __syncthreads();
+            if ((tid & (OPENCV_CUDA_WARP_SIZE - 1)) == (OPENCV_CUDA_WARP_SIZE - 1))
+            {
+                s_Data[tid >> OPENCV_CUDA_LOG_WARP_SIZE] = warpResult;
+            }
+
+            //wait for warp scans to complete
+            __syncthreads();
+
+            if (tid < (tiNumScanThreads / OPENCV_CUDA_WARP_SIZE) )
+            {
+                //grab top warp elements
+                T val = s_Data[tid];
+                //calculate exclusive scan and write back to shared memory
+                s_Data[tid] = warpScanExclusive(val, s_Data, tid);
+            }
+
+            //return updated warp scans with exclusive scan results
+            __syncthreads();
+
+            return warpResult + s_Data[tid >> OPENCV_CUDA_LOG_WARP_SIZE];
+        }
+        else
+        {
+            return warpScanInclusive(idata, s_Data, tid);
+        }
+    }
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_SCAN_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/simd_functions.hpp

@@ -0,0 +1,869 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+/*
+ * Copyright (c) 2013 NVIDIA Corporation. All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are met:
+ *
+ *   Redistributions of source code must retain the above copyright notice,
+ *   this list of conditions and the following disclaimer.
+ *
+ *   Redistributions in binary form must reproduce the above copyright notice,
+ *   this list of conditions and the following disclaimer in the documentation
+ *   and/or other materials provided with the distribution.
+ *
+ *   Neither the name of NVIDIA Corporation nor the names of its contributors
+ *   may be used to endorse or promote products derived from this software
+ *   without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+ * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+ * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+ * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+ * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ * POSSIBILITY OF SUCH DAMAGE.
+ */
+
+#ifndef OPENCV_CUDA_SIMD_FUNCTIONS_HPP
+#define OPENCV_CUDA_SIMD_FUNCTIONS_HPP
+
+#include "common.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    // 2
+
+    static __device__ __forceinline__ unsigned int vadd2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vadd2.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vadd.u32.u32.u32.sat %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vadd.u32.u32.u32.sat %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s;
+        s = a ^ b;          // sum bits
+        r = a + b;          // actual sum
+        s = s ^ r;          // determine carry-ins for each bit position
+        s = s & 0x00010000; // carry-in to high word (= carry-out from low word)
+        r = r - s;          // subtract out carry-out from low word
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsub2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vsub2.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vsub.u32.u32.u32.sat %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vsub.u32.u32.u32.sat %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s;
+        s = a ^ b;          // sum bits
+        r = a - b;          // actual sum
+        s = s ^ r;          // determine carry-ins for each bit position
+        s = s & 0x00010000; // borrow to high word
+        r = r + s;          // compensate for borrow from low word
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vabsdiff2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vabsdiff2.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vabsdiff.u32.u32.u32.sat %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vabsdiff.u32.u32.u32.sat %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s, t, u, v;
+        s = a & 0x0000ffff; // extract low halfword
+        r = b & 0x0000ffff; // extract low halfword
+        u = ::max(r, s);    // maximum of low halfwords
+        v = ::min(r, s);    // minimum of low halfwords
+        s = a & 0xffff0000; // extract high halfword
+        r = b & 0xffff0000; // extract high halfword
+        t = ::max(r, s);    // maximum of high halfwords
+        s = ::min(r, s);    // minimum of high halfwords
+        r = u | t;          // maximum of both halfwords
+        s = v | s;          // minimum of both halfwords
+        r = r - s;          // |a - b| = max(a,b) - min(a,b);
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vavg2(unsigned int a, unsigned int b)
+    {
+        unsigned int r, s;
+
+        // HAKMEM #23: a + b = 2 * (a & b) + (a ^ b) ==>
+        // (a + b) / 2 = (a & b) + ((a ^ b) >> 1)
+        s = a ^ b;
+        r = a & b;
+        s = s & 0xfffefffe; // ensure shift doesn't cross halfword boundaries
+        s = s >> 1;
+        s = r + s;
+
+        return s;
+    }
+
+    static __device__ __forceinline__ unsigned int vavrg2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vavrg2.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        // HAKMEM #23: a + b = 2 * (a | b) - (a ^ b) ==>
+        // (a + b + 1) / 2 = (a | b) - ((a ^ b) >> 1)
+        unsigned int s;
+        s = a ^ b;
+        r = a | b;
+        s = s & 0xfffefffe; // ensure shift doesn't cross half-word boundaries
+        s = s >> 1;
+        r = r - s;
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vseteq2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset2.u32.u32.eq %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        unsigned int c;
+        r = a ^ b;          // 0x0000 if a == b
+        c = r | 0x80008000; // set msbs, to catch carry out
+        r = r ^ c;          // extract msbs, msb = 1 if r < 0x8000
+        c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000
+        c = r & ~c;         // msb = 1, if r was 0x0000
+        r = c >> 15;        // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpeq2(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vseteq2(a, b);
+        c = r << 16;        // convert bool
+        r = c - r;          //  into mask
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        r = a ^ b;          // 0x0000 if a == b
+        c = r | 0x80008000; // set msbs, to catch carry out
+        r = r ^ c;          // extract msbs, msb = 1 if r < 0x8000
+        c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000
+        c = r & ~c;         // msb = 1, if r was 0x0000
+        r = c >> 15;        // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetge2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset2.u32.u32.ge %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(b));
+        c = vavrg2(a, b);   // (a + ~b + 1) / 2 = (a - b) / 2
+        c = c & 0x80008000; // msb = carry-outs
+        r = c >> 15;        // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpge2(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetge2(a, b);
+        c = r << 16;        // convert bool
+        r = c - r;          //  into mask
+    #else
+        asm("not.b32 %0, %0;" : "+r"(b));
+        c = vavrg2(a, b);   // (a + ~b + 1) / 2 = (a - b) / 2
+        c = c & 0x80008000; // msb = carry-outs
+        r = c >> 15;        // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetgt2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset2.u32.u32.gt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(b));
+        c = vavg2(a, b);    // (a + ~b) / 2 = (a - b) / 2 [rounded down]
+        c = c & 0x80008000; // msbs = carry-outs
+        r = c >> 15;        // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpgt2(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetgt2(a, b);
+        c = r << 16;        // convert bool
+        r = c - r;          //  into mask
+    #else
+        asm("not.b32 %0, %0;" : "+r"(b));
+        c = vavg2(a, b);    // (a + ~b) / 2 = (a - b) / 2 [rounded down]
+        c = c & 0x80008000; // msbs = carry-outs
+        r = c >> 15;        // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetle2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset2.u32.u32.le %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavrg2(a, b);   // (b + ~a + 1) / 2 = (b - a) / 2
+        c = c & 0x80008000; // msb = carry-outs
+        r = c >> 15;        // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmple2(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetle2(a, b);
+        c = r << 16;        // convert bool
+        r = c - r;          //  into mask
+    #else
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavrg2(a, b);   // (b + ~a + 1) / 2 = (b - a) / 2
+        c = c & 0x80008000; // msb = carry-outs
+        r = c >> 15;        // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetlt2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset2.u32.u32.lt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavg2(a, b);    // (b + ~a) / 2 = (b - a) / 2 [rounded down]
+        c = c & 0x80008000; // msb = carry-outs
+        r = c >> 15;        // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmplt2(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetlt2(a, b);
+        c = r << 16;        // convert bool
+        r = c - r;          //  into mask
+    #else
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavg2(a, b);    // (b + ~a) / 2 = (b - a) / 2 [rounded down]
+        c = c & 0x80008000; // msb = carry-outs
+        r = c >> 15;        // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetne2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm ("vset2.u32.u32.ne %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        unsigned int c;
+        r = a ^ b;          // 0x0000 if a == b
+        c = r | 0x80008000; // set msbs, to catch carry out
+        c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000
+        c = r | c;          // msb = 1, if r was not 0x0000
+        c = c & 0x80008000; // extract msbs
+        r = c >> 15;        // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpne2(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetne2(a, b);
+        c = r << 16;        // convert bool
+        r = c - r;          //  into mask
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        r = a ^ b;          // 0x0000 if a == b
+        c = r | 0x80008000; // set msbs, to catch carry out
+        c = c - 0x00010001; // msb = 0, if r was 0x0000 or 0x8000
+        c = r | c;          // msb = 1, if r was not 0x0000
+        c = c & 0x80008000; // extract msbs
+        r = c >> 15;        // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vmax2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vmax2.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vmax.u32.u32.u32 %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmax.u32.u32.u32 %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s, t, u;
+        r = a & 0x0000ffff; // extract low halfword
+        s = b & 0x0000ffff; // extract low halfword
+        t = ::max(r, s);    // maximum of low halfwords
+        r = a & 0xffff0000; // extract high halfword
+        s = b & 0xffff0000; // extract high halfword
+        u = ::max(r, s);    // maximum of high halfwords
+        r = t | u;          // combine halfword maximums
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vmin2(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vmin2.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vmin.u32.u32.u32 %0.h0, %1.h0, %2.h0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmin.u32.u32.u32 %0.h1, %1.h1, %2.h1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s, t, u;
+        r = a & 0x0000ffff; // extract low halfword
+        s = b & 0x0000ffff; // extract low halfword
+        t = ::min(r, s);    // minimum of low halfwords
+        r = a & 0xffff0000; // extract high halfword
+        s = b & 0xffff0000; // extract high halfword
+        u = ::min(r, s);    // minimum of high halfwords
+        r = t | u;          // combine halfword minimums
+    #endif
+
+        return r;
+    }
+
+    // 4
+
+    static __device__ __forceinline__ unsigned int vadd4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vadd4.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vadd.u32.u32.u32.sat %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vadd.u32.u32.u32.sat %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vadd.u32.u32.u32.sat %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vadd.u32.u32.u32.sat %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s, t;
+        s = a ^ b;          // sum bits
+        r = a & 0x7f7f7f7f; // clear msbs
+        t = b & 0x7f7f7f7f; // clear msbs
+        s = s & 0x80808080; // msb sum bits
+        r = r + t;          // add without msbs, record carry-out in msbs
+        r = r ^ s;          // sum of msb sum and carry-in bits, w/o carry-out
+    #endif /* __CUDA_ARCH__ >= 300 */
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsub4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vsub4.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vsub.u32.u32.u32.sat %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vsub.u32.u32.u32.sat %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vsub.u32.u32.u32.sat %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vsub.u32.u32.u32.sat %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s, t;
+        s = a ^ ~b;         // inverted sum bits
+        r = a | 0x80808080; // set msbs
+        t = b & 0x7f7f7f7f; // clear msbs
+        s = s & 0x80808080; // inverted msb sum bits
+        r = r - t;          // subtract w/o msbs, record inverted borrows in msb
+        r = r ^ s;          // combine inverted msb sum bits and borrows
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vavg4(unsigned int a, unsigned int b)
+    {
+        unsigned int r, s;
+
+        // HAKMEM #23: a + b = 2 * (a & b) + (a ^ b) ==>
+        // (a + b) / 2 = (a & b) + ((a ^ b) >> 1)
+        s = a ^ b;
+        r = a & b;
+        s = s & 0xfefefefe; // ensure following shift doesn't cross byte boundaries
+        s = s >> 1;
+        s = r + s;
+
+        return s;
+    }
+
+    static __device__ __forceinline__ unsigned int vavrg4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vavrg4.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        // HAKMEM #23: a + b = 2 * (a | b) - (a ^ b) ==>
+        // (a + b + 1) / 2 = (a | b) - ((a ^ b) >> 1)
+        unsigned int c;
+        c = a ^ b;
+        r = a | b;
+        c = c & 0xfefefefe; // ensure following shift doesn't cross byte boundaries
+        c = c >> 1;
+        r = r - c;
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vseteq4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset4.u32.u32.eq %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        unsigned int c;
+        r = a ^ b;          // 0x00 if a == b
+        c = r | 0x80808080; // set msbs, to catch carry out
+        r = r ^ c;          // extract msbs, msb = 1 if r < 0x80
+        c = c - 0x01010101; // msb = 0, if r was 0x00 or 0x80
+        c = r & ~c;         // msb = 1, if r was 0x00
+        r = c >> 7;         // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpeq4(unsigned int a, unsigned int b)
+    {
+        unsigned int r, t;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vseteq4(a, b);
+        t = r << 8;         // convert bool
+        r = t - r;          //  to mask
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        t = a ^ b;          // 0x00 if a == b
+        r = t | 0x80808080; // set msbs, to catch carry out
+        t = t ^ r;          // extract msbs, msb = 1 if t < 0x80
+        r = r - 0x01010101; // msb = 0, if t was 0x00 or 0x80
+        r = t & ~r;         // msb = 1, if t was 0x00
+        t = r >> 7;         // build mask
+        t = r - t;          //  from
+        r = t | r;          //   msbs
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetle4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset4.u32.u32.le %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavrg4(a, b);   // (b + ~a + 1) / 2 = (b - a) / 2
+        c = c & 0x80808080; // msb = carry-outs
+        r = c >> 7;         // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmple4(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetle4(a, b);
+        c = r << 8;         // convert bool
+        r = c - r;          //  to mask
+    #else
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavrg4(a, b);   // (b + ~a + 1) / 2 = (b - a) / 2
+        c = c & 0x80808080; // msbs = carry-outs
+        r = c >> 7;         // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetlt4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset4.u32.u32.lt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavg4(a, b);    // (b + ~a) / 2 = (b - a) / 2 [rounded down]
+        c = c & 0x80808080; // msb = carry-outs
+        r = c >> 7;         // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmplt4(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetlt4(a, b);
+        c = r << 8;         // convert bool
+        r = c - r;          //  to mask
+    #else
+        asm("not.b32 %0, %0;" : "+r"(a));
+        c = vavg4(a, b);    // (b + ~a) / 2 = (b - a) / 2 [rounded down]
+        c = c & 0x80808080; // msbs = carry-outs
+        r = c >> 7;         // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetge4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset4.u32.u32.ge %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(b));
+        c = vavrg4(a, b);   // (a + ~b + 1) / 2 = (a - b) / 2
+        c = c & 0x80808080; // msb = carry-outs
+        r = c >> 7;         // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpge4(unsigned int a, unsigned int b)
+    {
+        unsigned int r, s;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetge4(a, b);
+        s = r << 8;         // convert bool
+        r = s - r;          //  to mask
+    #else
+        asm ("not.b32 %0,%0;" : "+r"(b));
+        r = vavrg4 (a, b);  // (a + ~b + 1) / 2 = (a - b) / 2
+        r = r & 0x80808080; // msb = carry-outs
+        s = r >> 7;         // build mask
+        s = r - s;          //  from
+        r = s | r;          //   msbs
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetgt4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset4.u32.u32.gt %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int c;
+        asm("not.b32 %0, %0;" : "+r"(b));
+        c = vavg4(a, b);    // (a + ~b) / 2 = (a - b) / 2 [rounded down]
+        c = c & 0x80808080; // msb = carry-outs
+        r = c >> 7;         // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpgt4(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetgt4(a, b);
+        c = r << 8;         // convert bool
+        r = c - r;          //  to mask
+    #else
+        asm("not.b32 %0, %0;" : "+r"(b));
+        c = vavg4(a, b);    // (a + ~b) / 2 = (a - b) / 2 [rounded down]
+        c = c & 0x80808080; // msb = carry-outs
+        r = c >> 7;         // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vsetne4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vset4.u32.u32.ne %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        unsigned int c;
+        r = a ^ b;          // 0x00 if a == b
+        c = r | 0x80808080; // set msbs, to catch carry out
+        c = c - 0x01010101; // msb = 0, if r was 0x00 or 0x80
+        c = r | c;          // msb = 1, if r was not 0x00
+        c = c & 0x80808080; // extract msbs
+        r = c >> 7;         // convert to bool
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vcmpne4(unsigned int a, unsigned int b)
+    {
+        unsigned int r, c;
+
+    #if __CUDA_ARCH__ >= 300
+        r = vsetne4(a, b);
+        c = r << 8;         // convert bool
+        r = c - r;          //  to mask
+    #else
+        // inspired by Alan Mycroft's null-byte detection algorithm:
+        // null_byte(x) = ((x - 0x01010101) & (~x & 0x80808080))
+        r = a ^ b;          // 0x00 if a == b
+        c = r | 0x80808080; // set msbs, to catch carry out
+        c = c - 0x01010101; // msb = 0, if r was 0x00 or 0x80
+        c = r | c;          // msb = 1, if r was not 0x00
+        c = c & 0x80808080; // extract msbs
+        r = c >> 7;         // convert
+        r = c - r;          //  msbs to
+        r = c | r;          //   mask
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vabsdiff4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vabsdiff4.u32.u32.u32.sat %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vabsdiff.u32.u32.u32.sat %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vabsdiff.u32.u32.u32.sat %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vabsdiff.u32.u32.u32.sat %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vabsdiff.u32.u32.u32.sat %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s;
+        s = vcmpge4(a, b);  // mask = 0xff if a >= b
+        r = a ^ b;          //
+        s = (r &  s) ^ b;   // select a when a >= b, else select b => max(a,b)
+        r = s ^ r;          // select a when b >= a, else select b => min(a,b)
+        r = s - r;          // |a - b| = max(a,b) - min(a,b);
+    #endif
+
+        return r;
+    }
+
+    static __device__ __forceinline__ unsigned int vmax4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vmax4.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vmax.u32.u32.u32 %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmax.u32.u32.u32 %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmax.u32.u32.u32 %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmax.u32.u32.u32 %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s;
+        s = vcmpge4(a, b);  // mask = 0xff if a >= b
+        r = a & s;          // select a when b >= a
+        s = b & ~s;         // select b when b < a
+        r = r | s;          // combine byte selections
+    #endif
+
+        return r;           // byte-wise unsigned maximum
+    }
+
+    static __device__ __forceinline__ unsigned int vmin4(unsigned int a, unsigned int b)
+    {
+        unsigned int r = 0;
+
+    #if __CUDA_ARCH__ >= 300
+        asm("vmin4.u32.u32.u32 %0, %1, %2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #elif __CUDA_ARCH__ >= 200
+        asm("vmin.u32.u32.u32 %0.b0, %1.b0, %2.b0, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmin.u32.u32.u32 %0.b1, %1.b1, %2.b1, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmin.u32.u32.u32 %0.b2, %1.b2, %2.b2, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+        asm("vmin.u32.u32.u32 %0.b3, %1.b3, %2.b3, %3;" : "=r"(r) : "r"(a), "r"(b), "r"(r));
+    #else
+        unsigned int s;
+        s = vcmpge4(b, a);  // mask = 0xff if a >= b
+        r = a & s;          // select a when b >= a
+        s = b & ~s;         // select b when b < a
+        r = r | s;          // combine byte selections
+    #endif
+
+        return r;
+    }
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_SIMD_FUNCTIONS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/transform.hpp

@@ -0,0 +1,75 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_TRANSFORM_HPP
+#define OPENCV_CUDA_TRANSFORM_HPP
+
+#include "common.hpp"
+#include "utility.hpp"
+#include "detail/transform_detail.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template <typename T, typename D, typename UnOp, typename Mask>
+    static inline void transform(PtrStepSz<T> src, PtrStepSz<D> dst, UnOp op, const Mask& mask, cudaStream_t stream)
+    {
+        typedef TransformFunctorTraits<UnOp> ft;
+        transform_detail::TransformDispatcher<VecTraits<T>::cn == 1 && VecTraits<D>::cn == 1 && ft::smart_shift != 1>::call(src, dst, op, mask, stream);
+    }
+
+    template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
+    static inline void transform(PtrStepSz<T1> src1, PtrStepSz<T2> src2, PtrStepSz<D> dst, BinOp op, const Mask& mask, cudaStream_t stream)
+    {
+        typedef TransformFunctorTraits<BinOp> ft;
+        transform_detail::TransformDispatcher<VecTraits<T1>::cn == 1 && VecTraits<T2>::cn == 1 && VecTraits<D>::cn == 1 && ft::smart_shift != 1>::call(src1, src2, dst, op, mask, stream);
+    }
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_TRANSFORM_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/type_traits.hpp

@@ -0,0 +1,90 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_TYPE_TRAITS_HPP
+#define OPENCV_CUDA_TYPE_TRAITS_HPP
+
+#include "detail/type_traits_detail.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template <typename T> struct IsSimpleParameter
+    {
+        enum {value = type_traits_detail::IsIntegral<T>::value || type_traits_detail::IsFloat<T>::value ||
+            type_traits_detail::PointerTraits<typename type_traits_detail::ReferenceTraits<T>::type>::value};
+    };
+
+    template <typename T> struct TypeTraits
+    {
+        typedef typename type_traits_detail::UnConst<T>::type                                                NonConstType;
+        typedef typename type_traits_detail::UnVolatile<T>::type                                             NonVolatileType;
+        typedef typename type_traits_detail::UnVolatile<typename type_traits_detail::UnConst<T>::type>::type UnqualifiedType;
+        typedef typename type_traits_detail::PointerTraits<UnqualifiedType>::type                            PointeeType;
+        typedef typename type_traits_detail::ReferenceTraits<T>::type                                        ReferredType;
+
+        enum { isConst          = type_traits_detail::UnConst<T>::value };
+        enum { isVolatile       = type_traits_detail::UnVolatile<T>::value };
+
+        enum { isReference      = type_traits_detail::ReferenceTraits<UnqualifiedType>::value };
+        enum { isPointer        = type_traits_detail::PointerTraits<typename type_traits_detail::ReferenceTraits<UnqualifiedType>::type>::value };
+
+        enum { isUnsignedInt    = type_traits_detail::IsUnsignedIntegral<UnqualifiedType>::value };
+        enum { isSignedInt      = type_traits_detail::IsSignedIntergral<UnqualifiedType>::value };
+        enum { isIntegral       = type_traits_detail::IsIntegral<UnqualifiedType>::value };
+        enum { isFloat          = type_traits_detail::IsFloat<UnqualifiedType>::value };
+        enum { isArith          = isIntegral || isFloat };
+        enum { isVec            = type_traits_detail::IsVec<UnqualifiedType>::value };
+
+        typedef typename type_traits_detail::Select<IsSimpleParameter<UnqualifiedType>::value,
+            T, typename type_traits_detail::AddParameterType<T>::type>::type ParameterType;
+    };
+}}}
+
+//! @endcond
+
+#endif // OPENCV_CUDA_TYPE_TRAITS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/utility.hpp

@@ -0,0 +1,230 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_UTILITY_HPP
+#define OPENCV_CUDA_UTILITY_HPP
+
+#include "saturate_cast.hpp"
+#include "datamov_utils.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    struct CV_EXPORTS ThrustAllocator
+    {
+        typedef uchar value_type;
+        virtual ~ThrustAllocator();
+        virtual __device__ __host__ uchar* allocate(size_t numBytes) = 0;
+        virtual __device__ __host__ void deallocate(uchar* ptr, size_t numBytes) = 0;
+        static ThrustAllocator& getAllocator();
+        static void setAllocator(ThrustAllocator* allocator);
+    };
+    #define OPENCV_CUDA_LOG_WARP_SIZE        (5)
+    #define OPENCV_CUDA_WARP_SIZE            (1 << OPENCV_CUDA_LOG_WARP_SIZE)
+    #define OPENCV_CUDA_LOG_MEM_BANKS        ((__CUDA_ARCH__ >= 200) ? 5 : 4) // 32 banks on fermi, 16 on tesla
+    #define OPENCV_CUDA_MEM_BANKS            (1 << OPENCV_CUDA_LOG_MEM_BANKS)
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // swap
+
+    template <typename T> void __device__ __host__ __forceinline__ swap(T& a, T& b)
+    {
+        const T temp = a;
+        a = b;
+        b = temp;
+    }
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // Mask Reader
+
+    struct SingleMask
+    {
+        explicit __host__ __device__ __forceinline__ SingleMask(PtrStepb mask_) : mask(mask_) {}
+        __host__ __device__ __forceinline__ SingleMask(const SingleMask& mask_): mask(mask_.mask){}
+
+        __device__ __forceinline__ bool operator()(int y, int x) const
+        {
+            return mask.ptr(y)[x] != 0;
+        }
+
+        PtrStepb mask;
+    };
+
+    struct SingleMaskChannels
+    {
+        __host__ __device__ __forceinline__ SingleMaskChannels(PtrStepb mask_, int channels_)
+        : mask(mask_), channels(channels_) {}
+        __host__ __device__ __forceinline__ SingleMaskChannels(const SingleMaskChannels& mask_)
+            :mask(mask_.mask), channels(mask_.channels){}
+
+        __device__ __forceinline__ bool operator()(int y, int x) const
+        {
+            return mask.ptr(y)[x / channels] != 0;
+        }
+
+        PtrStepb mask;
+        int channels;
+    };
+
+    struct MaskCollection
+    {
+        explicit __host__ __device__ __forceinline__ MaskCollection(PtrStepb* maskCollection_)
+            : maskCollection(maskCollection_) {}
+
+        __device__ __forceinline__ MaskCollection(const MaskCollection& masks_)
+            : maskCollection(masks_.maskCollection), curMask(masks_.curMask){}
+
+        __device__ __forceinline__ void next()
+        {
+            curMask = *maskCollection++;
+        }
+        __device__ __forceinline__ void setMask(int z)
+        {
+            curMask = maskCollection[z];
+        }
+
+        __device__ __forceinline__ bool operator()(int y, int x) const
+        {
+            uchar val;
+            return curMask.data == 0 || (ForceGlob<uchar>::Load(curMask.ptr(y), x, val), (val != 0));
+        }
+
+        const PtrStepb* maskCollection;
+        PtrStepb curMask;
+    };
+
+    struct WithOutMask
+    {
+        __host__ __device__ __forceinline__ WithOutMask(){}
+        __host__ __device__ __forceinline__ WithOutMask(const WithOutMask&){}
+
+        __device__ __forceinline__ void next() const
+        {
+        }
+        __device__ __forceinline__ void setMask(int) const
+        {
+        }
+
+        __device__ __forceinline__ bool operator()(int, int) const
+        {
+            return true;
+        }
+
+        __device__ __forceinline__ bool operator()(int, int, int) const
+        {
+            return true;
+        }
+
+        static __device__ __forceinline__ bool check(int, int)
+        {
+            return true;
+        }
+
+        static __device__ __forceinline__ bool check(int, int, int)
+        {
+            return true;
+        }
+    };
+
+    ///////////////////////////////////////////////////////////////////////////////
+    // Solve linear system
+
+    // solve 2x2 linear system Ax=b
+    template <typename T> __device__ __forceinline__ bool solve2x2(const T A[2][2], const T b[2], T x[2])
+    {
+        T det = A[0][0] * A[1][1] - A[1][0] * A[0][1];
+
+        if (det != 0)
+        {
+            double invdet = 1.0 / det;
+
+            x[0] = saturate_cast<T>(invdet * (b[0] * A[1][1] - b[1] * A[0][1]));
+
+            x[1] = saturate_cast<T>(invdet * (A[0][0] * b[1] - A[1][0] * b[0]));
+
+            return true;
+        }
+
+        return false;
+    }
+
+    // solve 3x3 linear system Ax=b
+    template <typename T> __device__ __forceinline__ bool solve3x3(const T A[3][3], const T b[3], T x[3])
+    {
+        T det = A[0][0] * (A[1][1] * A[2][2] - A[1][2] * A[2][1])
+              - A[0][1] * (A[1][0] * A[2][2] - A[1][2] * A[2][0])
+              + A[0][2] * (A[1][0] * A[2][1] - A[1][1] * A[2][0]);
+
+        if (det != 0)
+        {
+            double invdet = 1.0 / det;
+
+            x[0] = saturate_cast<T>(invdet *
+                (b[0]    * (A[1][1] * A[2][2] - A[1][2] * A[2][1]) -
+                 A[0][1] * (b[1]    * A[2][2] - A[1][2] * b[2]   ) +
+                 A[0][2] * (b[1]    * A[2][1] - A[1][1] * b[2]   )));
+
+            x[1] = saturate_cast<T>(invdet *
+                (A[0][0] * (b[1]    * A[2][2] - A[1][2] * b[2]   ) -
+                 b[0]    * (A[1][0] * A[2][2] - A[1][2] * A[2][0]) +
+                 A[0][2] * (A[1][0] * b[2]    - b[1]    * A[2][0])));
+
+            x[2] = saturate_cast<T>(invdet *
+                (A[0][0] * (A[1][1] * b[2]    - b[1]    * A[2][1]) -
+                 A[0][1] * (A[1][0] * b[2]    - b[1]    * A[2][0]) +
+                 b[0]    * (A[1][0] * A[2][1] - A[1][1] * A[2][0])));
+
+            return true;
+        }
+
+        return false;
+    }
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_UTILITY_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/vec_distance.hpp

@@ -0,0 +1,232 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_VEC_DISTANCE_HPP
+#define OPENCV_CUDA_VEC_DISTANCE_HPP
+
+#include "reduce.hpp"
+#include "functional.hpp"
+#include "detail/vec_distance_detail.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template <typename T> struct L1Dist
+    {
+        typedef int value_type;
+        typedef int result_type;
+
+        __device__ __forceinline__ L1Dist() : mySum(0) {}
+
+        __device__ __forceinline__ void reduceIter(int val1, int val2)
+        {
+            mySum = __sad(val1, val2, mySum);
+        }
+
+        template <int THREAD_DIM> __device__ __forceinline__ void reduceAll(int* smem, int tid)
+        {
+            reduce<THREAD_DIM>(smem, mySum, tid, plus<int>());
+        }
+
+        __device__ __forceinline__ operator int() const
+        {
+            return mySum;
+        }
+
+        int mySum;
+    };
+    template <> struct L1Dist<float>
+    {
+        typedef float value_type;
+        typedef float result_type;
+
+        __device__ __forceinline__ L1Dist() : mySum(0.0f) {}
+
+        __device__ __forceinline__ void reduceIter(float val1, float val2)
+        {
+            mySum += ::fabs(val1 - val2);
+        }
+
+        template <int THREAD_DIM> __device__ __forceinline__ void reduceAll(float* smem, int tid)
+        {
+            reduce<THREAD_DIM>(smem, mySum, tid, plus<float>());
+        }
+
+        __device__ __forceinline__ operator float() const
+        {
+            return mySum;
+        }
+
+        float mySum;
+    };
+
+    struct L2Dist
+    {
+        typedef float value_type;
+        typedef float result_type;
+
+        __device__ __forceinline__ L2Dist() : mySum(0.0f) {}
+
+        __device__ __forceinline__ void reduceIter(float val1, float val2)
+        {
+            float reg = val1 - val2;
+            mySum += reg * reg;
+        }
+
+        template <int THREAD_DIM> __device__ __forceinline__ void reduceAll(float* smem, int tid)
+        {
+            reduce<THREAD_DIM>(smem, mySum, tid, plus<float>());
+        }
+
+        __device__ __forceinline__ operator float() const
+        {
+            return sqrtf(mySum);
+        }
+
+        float mySum;
+    };
+
+    struct HammingDist
+    {
+        typedef int value_type;
+        typedef int result_type;
+
+        __device__ __forceinline__ HammingDist() : mySum(0) {}
+
+        __device__ __forceinline__ void reduceIter(int val1, int val2)
+        {
+            mySum += __popc(val1 ^ val2);
+        }
+
+        template <int THREAD_DIM> __device__ __forceinline__ void reduceAll(int* smem, int tid)
+        {
+            reduce<THREAD_DIM>(smem, mySum, tid, plus<int>());
+        }
+
+        __device__ __forceinline__ operator int() const
+        {
+            return mySum;
+        }
+
+        int mySum;
+    };
+
+    // calc distance between two vectors in global memory
+    template <int THREAD_DIM, typename Dist, typename T1, typename T2>
+    __device__ void calcVecDiffGlobal(const T1* vec1, const T2* vec2, int len, Dist& dist, typename Dist::result_type* smem, int tid)
+    {
+        for (int i = tid; i < len; i += THREAD_DIM)
+        {
+            T1 val1;
+            ForceGlob<T1>::Load(vec1, i, val1);
+
+            T2 val2;
+            ForceGlob<T2>::Load(vec2, i, val2);
+
+            dist.reduceIter(val1, val2);
+        }
+
+        dist.reduceAll<THREAD_DIM>(smem, tid);
+    }
+
+    // calc distance between two vectors, first vector is cached in register or shared memory, second vector is in global memory
+    template <int THREAD_DIM, int MAX_LEN, bool LEN_EQ_MAX_LEN, typename Dist, typename T1, typename T2>
+    __device__ __forceinline__ void calcVecDiffCached(const T1* vecCached, const T2* vecGlob, int len, Dist& dist, typename Dist::result_type* smem, int tid)
+    {
+        vec_distance_detail::VecDiffCachedCalculator<THREAD_DIM, MAX_LEN, LEN_EQ_MAX_LEN>::calc(vecCached, vecGlob, len, dist, tid);
+
+        dist.reduceAll<THREAD_DIM>(smem, tid);
+    }
+
+    // calc distance between two vectors in global memory
+    template <int THREAD_DIM, typename T1> struct VecDiffGlobal
+    {
+        explicit __device__ __forceinline__ VecDiffGlobal(const T1* vec1_, int = 0, void* = 0, int = 0, int = 0)
+        {
+            vec1 = vec1_;
+        }
+
+        template <typename T2, typename Dist>
+        __device__ __forceinline__ void calc(const T2* vec2, int len, Dist& dist, typename Dist::result_type* smem, int tid) const
+        {
+            calcVecDiffGlobal<THREAD_DIM>(vec1, vec2, len, dist, smem, tid);
+        }
+
+        const T1* vec1;
+    };
+
+    // calc distance between two vectors, first vector is cached in register memory, second vector is in global memory
+    template <int THREAD_DIM, int MAX_LEN, bool LEN_EQ_MAX_LEN, typename U> struct VecDiffCachedRegister
+    {
+        template <typename T1> __device__ __forceinline__ VecDiffCachedRegister(const T1* vec1, int len, U* smem, int glob_tid, int tid)
+        {
+            if (glob_tid < len)
+                smem[glob_tid] = vec1[glob_tid];
+            __syncthreads();
+
+            U* vec1ValsPtr = vec1Vals;
+
+            #pragma unroll
+            for (int i = tid; i < MAX_LEN; i += THREAD_DIM)
+                *vec1ValsPtr++ = smem[i];
+
+            __syncthreads();
+        }
+
+        template <typename T2, typename Dist>
+        __device__ __forceinline__ void calc(const T2* vec2, int len, Dist& dist, typename Dist::result_type* smem, int tid) const
+        {
+            calcVecDiffCached<THREAD_DIM, MAX_LEN, LEN_EQ_MAX_LEN>(vec1Vals, vec2, len, dist, smem, tid);
+        }
+
+        U vec1Vals[MAX_LEN / THREAD_DIM];
+    };
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_VEC_DISTANCE_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/vec_math.hpp

@@ -0,0 +1,923 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_VECMATH_HPP
+#define OPENCV_CUDA_VECMATH_HPP
+
+#include "vec_traits.hpp"
+#include "saturate_cast.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+
+// saturate_cast
+
+namespace vec_math_detail
+{
+    template <int cn, typename VecD> struct SatCastHelper;
+    template <typename VecD> struct SatCastHelper<1, VecD>
+    {
+        template <typename VecS> static __device__ __forceinline__ VecD cast(const VecS& v)
+        {
+            typedef typename VecTraits<VecD>::elem_type D;
+            return VecTraits<VecD>::make(saturate_cast<D>(v.x));
+        }
+    };
+    template <typename VecD> struct SatCastHelper<2, VecD>
+    {
+        template <typename VecS> static __device__ __forceinline__ VecD cast(const VecS& v)
+        {
+            typedef typename VecTraits<VecD>::elem_type D;
+            return VecTraits<VecD>::make(saturate_cast<D>(v.x), saturate_cast<D>(v.y));
+        }
+    };
+    template <typename VecD> struct SatCastHelper<3, VecD>
+    {
+        template <typename VecS> static __device__ __forceinline__ VecD cast(const VecS& v)
+        {
+            typedef typename VecTraits<VecD>::elem_type D;
+            return VecTraits<VecD>::make(saturate_cast<D>(v.x), saturate_cast<D>(v.y), saturate_cast<D>(v.z));
+        }
+    };
+    template <typename VecD> struct SatCastHelper<4, VecD>
+    {
+        template <typename VecS> static __device__ __forceinline__ VecD cast(const VecS& v)
+        {
+            typedef typename VecTraits<VecD>::elem_type D;
+            return VecTraits<VecD>::make(saturate_cast<D>(v.x), saturate_cast<D>(v.y), saturate_cast<D>(v.z), saturate_cast<D>(v.w));
+        }
+    };
+
+    template <typename VecD, typename VecS> static __device__ __forceinline__ VecD saturate_cast_helper(const VecS& v)
+    {
+        return SatCastHelper<VecTraits<VecD>::cn, VecD>::cast(v);
+    }
+}
+
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uchar1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const char1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const ushort1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const short1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uint1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const int1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const float1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const double1& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uchar2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const char2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const ushort2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const short2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uint2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const int2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const float2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const double2& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uchar3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const char3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const ushort3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const short3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uint3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const int3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const float3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const double3& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uchar4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const char4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const ushort4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const short4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const uint4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const int4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const float4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+template<typename T> static __device__ __forceinline__ T saturate_cast(const double4& v) {return vec_math_detail::saturate_cast_helper<T>(v);}
+
+// unary operators
+
+#define CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(op, input_type, output_type) \
+    __device__ __forceinline__ output_type ## 1 operator op(const input_type ## 1 & a) \
+    { \
+        return VecTraits<output_type ## 1>::make(op (a.x)); \
+    } \
+    __device__ __forceinline__ output_type ## 2 operator op(const input_type ## 2 & a) \
+    { \
+        return VecTraits<output_type ## 2>::make(op (a.x), op (a.y)); \
+    } \
+    __device__ __forceinline__ output_type ## 3 operator op(const input_type ## 3 & a) \
+    { \
+        return VecTraits<output_type ## 3>::make(op (a.x), op (a.y), op (a.z)); \
+    } \
+    __device__ __forceinline__ output_type ## 4 operator op(const input_type ## 4 & a) \
+    { \
+        return VecTraits<output_type ## 4>::make(op (a.x), op (a.y), op (a.z), op (a.w)); \
+    }
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, char, char)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, short, short)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, int, int)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(-, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(!, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, char, char)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, ushort, ushort)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, short, short)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, int, int)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_OP(~, uint, uint)
+
+#undef CV_CUDEV_IMPLEMENT_VEC_UNARY_OP
+
+// unary functions
+
+#define CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(func_name, func, input_type, output_type) \
+    __device__ __forceinline__ output_type ## 1 func_name(const input_type ## 1 & a) \
+    { \
+        return VecTraits<output_type ## 1>::make(func (a.x)); \
+    } \
+    __device__ __forceinline__ output_type ## 2 func_name(const input_type ## 2 & a) \
+    { \
+        return VecTraits<output_type ## 2>::make(func (a.x), func (a.y)); \
+    } \
+    __device__ __forceinline__ output_type ## 3 func_name(const input_type ## 3 & a) \
+    { \
+        return VecTraits<output_type ## 3>::make(func (a.x), func (a.y), func (a.z)); \
+    } \
+    __device__ __forceinline__ output_type ## 4 func_name(const input_type ## 4 & a) \
+    { \
+        return VecTraits<output_type ## 4>::make(func (a.x), func (a.y), func (a.z), func (a.w)); \
+    }
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(abs, ::fabsf, float, float)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrtf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sqrt, ::sqrt, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::expf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp, ::exp, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2f, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp2, ::exp2, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10f, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(exp10, ::exp10, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::logf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log, ::log, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2f, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log2, ::log2, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10f, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(log10, ::log10, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sinf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sin, ::sin, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cosf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cos, ::cos, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tanf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tan, ::tan, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asinf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asin, ::asin, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acosf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acos, ::acos, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atanf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atan, ::atan, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinhf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(sinh, ::sinh, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::coshf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(cosh, ::cosh, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanhf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(tanh, ::tanh, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinhf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(asinh, ::asinh, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acoshf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(acosh, ::acosh, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanhf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC(atanh, ::atanh, double, double)
+
+#undef CV_CUDEV_IMPLEMENT_VEC_UNARY_FUNC
+
+// binary operators (vec & vec)
+
+#define CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(op, input_type, output_type) \
+    __device__ __forceinline__ output_type ## 1 operator op(const input_type ## 1 & a, const input_type ## 1 & b) \
+    { \
+        return VecTraits<output_type ## 1>::make(a.x op b.x); \
+    } \
+    __device__ __forceinline__ output_type ## 2 operator op(const input_type ## 2 & a, const input_type ## 2 & b) \
+    { \
+        return VecTraits<output_type ## 2>::make(a.x op b.x, a.y op b.y); \
+    } \
+    __device__ __forceinline__ output_type ## 3 operator op(const input_type ## 3 & a, const input_type ## 3 & b) \
+    { \
+        return VecTraits<output_type ## 3>::make(a.x op b.x, a.y op b.y, a.z op b.z); \
+    } \
+    __device__ __forceinline__ output_type ## 4 operator op(const input_type ## 4 & a, const input_type ## 4 & b) \
+    { \
+        return VecTraits<output_type ## 4>::make(a.x op b.x, a.y op b.y, a.z op b.z, a.w op b.w); \
+    }
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, uchar, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, char, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, ushort, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, short, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, uint, uint)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(+, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, uchar, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, char, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, ushort, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, short, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, uint, uint)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(-, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, uchar, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, char, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, ushort, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, short, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, uint, uint)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(*, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, uchar, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, char, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, ushort, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, short, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, uint, uint)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(/, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(==, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(!=, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(>=, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(<=, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&&, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, char, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, ushort, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, short, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, int, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, uint, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, float, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(||, double, uchar)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, char, char)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, ushort, ushort)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, short, short)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(&, uint, uint)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, char, char)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, ushort, ushort)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, short, short)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(|, uint, uint)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, char, char)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, ushort, ushort)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, short, short)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_OP(^, uint, uint)
+
+#undef CV_CUDEV_IMPLEMENT_VEC_BINARY_OP
+
+// binary operators (vec & scalar)
+
+#define CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(op, input_type, scalar_type, output_type) \
+    __device__ __forceinline__ output_type ## 1 operator op(const input_type ## 1 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 1>::make(a.x op s); \
+    } \
+    __device__ __forceinline__ output_type ## 1 operator op(scalar_type s, const input_type ## 1 & b) \
+    { \
+        return VecTraits<output_type ## 1>::make(s op b.x); \
+    } \
+    __device__ __forceinline__ output_type ## 2 operator op(const input_type ## 2 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 2>::make(a.x op s, a.y op s); \
+    } \
+    __device__ __forceinline__ output_type ## 2 operator op(scalar_type s, const input_type ## 2 & b) \
+    { \
+        return VecTraits<output_type ## 2>::make(s op b.x, s op b.y); \
+    } \
+    __device__ __forceinline__ output_type ## 3 operator op(const input_type ## 3 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 3>::make(a.x op s, a.y op s, a.z op s); \
+    } \
+    __device__ __forceinline__ output_type ## 3 operator op(scalar_type s, const input_type ## 3 & b) \
+    { \
+        return VecTraits<output_type ## 3>::make(s op b.x, s op b.y, s op b.z); \
+    } \
+    __device__ __forceinline__ output_type ## 4 operator op(const input_type ## 4 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 4>::make(a.x op s, a.y op s, a.z op s, a.w op s); \
+    } \
+    __device__ __forceinline__ output_type ## 4 operator op(scalar_type s, const input_type ## 4 & b) \
+    { \
+        return VecTraits<output_type ## 4>::make(s op b.x, s op b.y, s op b.z, s op b.w); \
+    }
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uchar, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, char, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, ushort, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, short, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uint, uint, uint)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(+, double, double, double)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uchar, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, char, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, ushort, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, short, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uint, uint, uint)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(-, double, double, double)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uchar, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, char, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, ushort, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, short, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uint, uint, uint)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(*, double, double, double)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uchar, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, char, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, ushort, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, short, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uint, uint, uint)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(/, double, double, double)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(==, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(!=, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(>=, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(<=, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&&, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, char, char, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, ushort, ushort, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, short, short, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, int, int, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, uint, uint, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, float, float, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(||, double, double, uchar)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, char, char, char)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, ushort, ushort, ushort)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, short, short, short)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(&, uint, uint, uint)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, char, char, char)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, ushort, ushort, ushort)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, short, short, short)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(|, uint, uint, uint)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, char, char, char)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, ushort, ushort, ushort)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, short, short, short)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP(^, uint, uint, uint)
+
+#undef CV_CUDEV_IMPLEMENT_SCALAR_BINARY_OP
+
+// binary function (vec & vec)
+
+#define CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(func_name, func, input_type, output_type) \
+    __device__ __forceinline__ output_type ## 1 func_name(const input_type ## 1 & a, const input_type ## 1 & b) \
+    { \
+        return VecTraits<output_type ## 1>::make(func (a.x, b.x)); \
+    } \
+    __device__ __forceinline__ output_type ## 2 func_name(const input_type ## 2 & a, const input_type ## 2 & b) \
+    { \
+        return VecTraits<output_type ## 2>::make(func (a.x, b.x), func (a.y, b.y)); \
+    } \
+    __device__ __forceinline__ output_type ## 3 func_name(const input_type ## 3 & a, const input_type ## 3 & b) \
+    { \
+        return VecTraits<output_type ## 3>::make(func (a.x, b.x), func (a.y, b.y), func (a.z, b.z)); \
+    } \
+    __device__ __forceinline__ output_type ## 4 func_name(const input_type ## 4 & a, const input_type ## 4 & b) \
+    { \
+        return VecTraits<output_type ## 4>::make(func (a.x, b.x), func (a.y, b.y), func (a.z, b.z), func (a.w, b.w)); \
+    }
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, char, char)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, ushort, ushort)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, short, short)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, uint, uint)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::max, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::fmaxf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(max, ::fmax, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, uchar, uchar)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, char, char)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, ushort, ushort)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, short, short)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, uint, uint)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::min, int, int)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::fminf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(min, ::fmin, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, char, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, short, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, int, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypotf, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(hypot, ::hypot, double, double)
+
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, uchar, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, char, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, ushort, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, short, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, uint, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, int, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2f, float, float)
+CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC(atan2, ::atan2, double, double)
+
+#undef CV_CUDEV_IMPLEMENT_VEC_BINARY_FUNC
+
+// binary function (vec & scalar)
+
+#define CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(func_name, func, input_type, scalar_type, output_type) \
+    __device__ __forceinline__ output_type ## 1 func_name(const input_type ## 1 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 1>::make(func ((output_type) a.x, (output_type) s)); \
+    } \
+    __device__ __forceinline__ output_type ## 1 func_name(scalar_type s, const input_type ## 1 & b) \
+    { \
+        return VecTraits<output_type ## 1>::make(func ((output_type) s, (output_type) b.x)); \
+    } \
+    __device__ __forceinline__ output_type ## 2 func_name(const input_type ## 2 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 2>::make(func ((output_type) a.x, (output_type) s), func ((output_type) a.y, (output_type) s)); \
+    } \
+    __device__ __forceinline__ output_type ## 2 func_name(scalar_type s, const input_type ## 2 & b) \
+    { \
+        return VecTraits<output_type ## 2>::make(func ((output_type) s, (output_type) b.x), func ((output_type) s, (output_type) b.y)); \
+    } \
+    __device__ __forceinline__ output_type ## 3 func_name(const input_type ## 3 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 3>::make(func ((output_type) a.x, (output_type) s), func ((output_type) a.y, (output_type) s), func ((output_type) a.z, (output_type) s)); \
+    } \
+    __device__ __forceinline__ output_type ## 3 func_name(scalar_type s, const input_type ## 3 & b) \
+    { \
+        return VecTraits<output_type ## 3>::make(func ((output_type) s, (output_type) b.x), func ((output_type) s, (output_type) b.y), func ((output_type) s, (output_type) b.z)); \
+    } \
+    __device__ __forceinline__ output_type ## 4 func_name(const input_type ## 4 & a, scalar_type s) \
+    { \
+        return VecTraits<output_type ## 4>::make(func ((output_type) a.x, (output_type) s), func ((output_type) a.y, (output_type) s), func ((output_type) a.z, (output_type) s), func ((output_type) a.w, (output_type) s)); \
+    } \
+    __device__ __forceinline__ output_type ## 4 func_name(scalar_type s, const input_type ## 4 & b) \
+    { \
+        return VecTraits<output_type ## 4>::make(func ((output_type) s, (output_type) b.x), func ((output_type) s, (output_type) b.y), func ((output_type) s, (output_type) b.z), func ((output_type) s, (output_type) b.w)); \
+    }
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, char, char, char)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, ushort, ushort, ushort)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, short, short, short)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, uint, uint, uint)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::max, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmaxf, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(max, ::fmax, double, double, double)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, uchar, uchar, uchar)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, char, char, char)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, ushort, ushort, ushort)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, short, short, short)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, uint, uint, uint)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::min, int, int, int)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fminf, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(min, ::fmin, double, double, double)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypotf, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(hypot, ::hypot, double, double, double)
+
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, uchar, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, uchar, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, char, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, char, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, ushort, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, ushort, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, short, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, short, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, uint, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, uint, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, int, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, int, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2f, float, float, float)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, float, double, double)
+CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC(atan2, ::atan2, double, double, double)
+
+#undef CV_CUDEV_IMPLEMENT_SCALAR_BINARY_FUNC
+
+}}} // namespace cv { namespace cuda { namespace device
+
+//! @endcond
+
+#endif // OPENCV_CUDA_VECMATH_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/vec_traits.hpp

@@ -0,0 +1,288 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_VEC_TRAITS_HPP
+#define OPENCV_CUDA_VEC_TRAITS_HPP
+
+#include "common.hpp"
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template<typename T, int N> struct TypeVec;
+
+    struct __align__(8) uchar8
+    {
+        uchar a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ uchar8 make_uchar8(uchar a0, uchar a1, uchar a2, uchar a3, uchar a4, uchar a5, uchar a6, uchar a7)
+    {
+        uchar8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+    struct __align__(8) char8
+    {
+        schar a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ char8 make_char8(schar a0, schar a1, schar a2, schar a3, schar a4, schar a5, schar a6, schar a7)
+    {
+        char8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+    struct __align__(16) ushort8
+    {
+        ushort a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ ushort8 make_ushort8(ushort a0, ushort a1, ushort a2, ushort a3, ushort a4, ushort a5, ushort a6, ushort a7)
+    {
+        ushort8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+    struct __align__(16) short8
+    {
+        short a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ short8 make_short8(short a0, short a1, short a2, short a3, short a4, short a5, short a6, short a7)
+    {
+        short8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+    struct __align__(32) uint8
+    {
+        uint a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ uint8 make_uint8(uint a0, uint a1, uint a2, uint a3, uint a4, uint a5, uint a6, uint a7)
+    {
+        uint8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+    struct __align__(32) int8
+    {
+        int a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ int8 make_int8(int a0, int a1, int a2, int a3, int a4, int a5, int a6, int a7)
+    {
+        int8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+    struct __align__(32) float8
+    {
+        float a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ float8 make_float8(float a0, float a1, float a2, float a3, float a4, float a5, float a6, float a7)
+    {
+        float8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+    struct double8
+    {
+        double a0, a1, a2, a3, a4, a5, a6, a7;
+    };
+    static __host__ __device__ __forceinline__ double8 make_double8(double a0, double a1, double a2, double a3, double a4, double a5, double a6, double a7)
+    {
+        double8 val = {a0, a1, a2, a3, a4, a5, a6, a7};
+        return val;
+    }
+
+#define OPENCV_CUDA_IMPLEMENT_TYPE_VEC(type) \
+    template<> struct TypeVec<type, 1> { typedef type vec_type; }; \
+    template<> struct TypeVec<type ## 1, 1> { typedef type ## 1 vec_type; }; \
+    template<> struct TypeVec<type, 2> { typedef type ## 2 vec_type; }; \
+    template<> struct TypeVec<type ## 2, 2> { typedef type ## 2 vec_type; }; \
+    template<> struct TypeVec<type, 3> { typedef type ## 3 vec_type; }; \
+    template<> struct TypeVec<type ## 3, 3> { typedef type ## 3 vec_type; }; \
+    template<> struct TypeVec<type, 4> { typedef type ## 4 vec_type; }; \
+    template<> struct TypeVec<type ## 4, 4> { typedef type ## 4 vec_type; }; \
+    template<> struct TypeVec<type, 8> { typedef type ## 8 vec_type; }; \
+    template<> struct TypeVec<type ## 8, 8> { typedef type ## 8 vec_type; };
+
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(uchar)
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(char)
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(ushort)
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(short)
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(int)
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(uint)
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(float)
+    OPENCV_CUDA_IMPLEMENT_TYPE_VEC(double)
+
+    #undef OPENCV_CUDA_IMPLEMENT_TYPE_VEC
+
+    template<> struct TypeVec<schar, 1> { typedef schar vec_type; };
+    template<> struct TypeVec<schar, 2> { typedef char2 vec_type; };
+    template<> struct TypeVec<schar, 3> { typedef char3 vec_type; };
+    template<> struct TypeVec<schar, 4> { typedef char4 vec_type; };
+    template<> struct TypeVec<schar, 8> { typedef char8 vec_type; };
+
+    template<> struct TypeVec<bool, 1> { typedef uchar vec_type; };
+    template<> struct TypeVec<bool, 2> { typedef uchar2 vec_type; };
+    template<> struct TypeVec<bool, 3> { typedef uchar3 vec_type; };
+    template<> struct TypeVec<bool, 4> { typedef uchar4 vec_type; };
+    template<> struct TypeVec<bool, 8> { typedef uchar8 vec_type; };
+
+    template<typename T> struct VecTraits;
+
+#define OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(type) \
+    template<> struct VecTraits<type> \
+    { \
+        typedef type elem_type; \
+        enum {cn=1}; \
+        static __device__ __host__ __forceinline__ type all(type v) {return v;} \
+        static __device__ __host__ __forceinline__ type make(type x) {return x;} \
+        static __device__ __host__ __forceinline__ type make(const type* v) {return *v;} \
+    }; \
+    template<> struct VecTraits<type ## 1> \
+    { \
+        typedef type elem_type; \
+        enum {cn=1}; \
+        static __device__ __host__ __forceinline__ type ## 1 all(type v) {return make_ ## type ## 1(v);} \
+        static __device__ __host__ __forceinline__ type ## 1 make(type x) {return make_ ## type ## 1(x);} \
+        static __device__ __host__ __forceinline__ type ## 1 make(const type* v) {return make_ ## type ## 1(*v);} \
+    }; \
+    template<> struct VecTraits<type ## 2> \
+    { \
+        typedef type elem_type; \
+        enum {cn=2}; \
+        static __device__ __host__ __forceinline__ type ## 2 all(type v) {return make_ ## type ## 2(v, v);} \
+        static __device__ __host__ __forceinline__ type ## 2 make(type x, type y) {return make_ ## type ## 2(x, y);} \
+        static __device__ __host__ __forceinline__ type ## 2 make(const type* v) {return make_ ## type ## 2(v[0], v[1]);} \
+    }; \
+    template<> struct VecTraits<type ## 3> \
+    { \
+        typedef type elem_type; \
+        enum {cn=3}; \
+        static __device__ __host__ __forceinline__ type ## 3 all(type v) {return make_ ## type ## 3(v, v, v);} \
+        static __device__ __host__ __forceinline__ type ## 3 make(type x, type y, type z) {return make_ ## type ## 3(x, y, z);} \
+        static __device__ __host__ __forceinline__ type ## 3 make(const type* v) {return make_ ## type ## 3(v[0], v[1], v[2]);} \
+    }; \
+    template<> struct VecTraits<type ## 4> \
+    { \
+        typedef type elem_type; \
+        enum {cn=4}; \
+        static __device__ __host__ __forceinline__ type ## 4 all(type v) {return make_ ## type ## 4(v, v, v, v);} \
+        static __device__ __host__ __forceinline__ type ## 4 make(type x, type y, type z, type w) {return make_ ## type ## 4(x, y, z, w);} \
+        static __device__ __host__ __forceinline__ type ## 4 make(const type* v) {return make_ ## type ## 4(v[0], v[1], v[2], v[3]);} \
+    }; \
+    template<> struct VecTraits<type ## 8> \
+    { \
+        typedef type elem_type; \
+        enum {cn=8}; \
+        static __device__ __host__ __forceinline__ type ## 8 all(type v) {return make_ ## type ## 8(v, v, v, v, v, v, v, v);} \
+        static __device__ __host__ __forceinline__ type ## 8 make(type a0, type a1, type a2, type a3, type a4, type a5, type a6, type a7) {return make_ ## type ## 8(a0, a1, a2, a3, a4, a5, a6, a7);} \
+        static __device__ __host__ __forceinline__ type ## 8 make(const type* v) {return make_ ## type ## 8(v[0], v[1], v[2], v[3], v[4], v[5], v[6], v[7]);} \
+    };
+
+    OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(uchar)
+    OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(ushort)
+    OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(short)
+    OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(int)
+    OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(uint)
+    OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(float)
+    OPENCV_CUDA_IMPLEMENT_VEC_TRAITS(double)
+
+    #undef OPENCV_CUDA_IMPLEMENT_VEC_TRAITS
+
+    template<> struct VecTraits<char>
+    {
+        typedef char elem_type;
+        enum {cn=1};
+        static __device__ __host__ __forceinline__ char all(char v) {return v;}
+        static __device__ __host__ __forceinline__ char make(char x) {return x;}
+        static __device__ __host__ __forceinline__ char make(const char* x) {return *x;}
+    };
+    template<> struct VecTraits<schar>
+    {
+        typedef schar elem_type;
+        enum {cn=1};
+        static __device__ __host__ __forceinline__ schar all(schar v) {return v;}
+        static __device__ __host__ __forceinline__ schar make(schar x) {return x;}
+        static __device__ __host__ __forceinline__ schar make(const schar* x) {return *x;}
+    };
+    template<> struct VecTraits<char1>
+    {
+        typedef schar elem_type;
+        enum {cn=1};
+        static __device__ __host__ __forceinline__ char1 all(schar v) {return make_char1(v);}
+        static __device__ __host__ __forceinline__ char1 make(schar x) {return make_char1(x);}
+        static __device__ __host__ __forceinline__ char1 make(const schar* v) {return make_char1(v[0]);}
+    };
+    template<> struct VecTraits<char2>
+    {
+        typedef schar elem_type;
+        enum {cn=2};
+        static __device__ __host__ __forceinline__ char2 all(schar v) {return make_char2(v, v);}
+        static __device__ __host__ __forceinline__ char2 make(schar x, schar y) {return make_char2(x, y);}
+        static __device__ __host__ __forceinline__ char2 make(const schar* v) {return make_char2(v[0], v[1]);}
+    };
+    template<> struct VecTraits<char3>
+    {
+        typedef schar elem_type;
+        enum {cn=3};
+        static __device__ __host__ __forceinline__ char3 all(schar v) {return make_char3(v, v, v);}
+        static __device__ __host__ __forceinline__ char3 make(schar x, schar y, schar z) {return make_char3(x, y, z);}
+        static __device__ __host__ __forceinline__ char3 make(const schar* v) {return make_char3(v[0], v[1], v[2]);}
+    };
+    template<> struct VecTraits<char4>
+    {
+        typedef schar elem_type;
+        enum {cn=4};
+        static __device__ __host__ __forceinline__ char4 all(schar v) {return make_char4(v, v, v, v);}
+        static __device__ __host__ __forceinline__ char4 make(schar x, schar y, schar z, schar w) {return make_char4(x, y, z, w);}
+        static __device__ __host__ __forceinline__ char4 make(const schar* v) {return make_char4(v[0], v[1], v[2], v[3]);}
+    };
+    template<> struct VecTraits<char8>
+    {
+        typedef schar elem_type;
+        enum {cn=8};
+        static __device__ __host__ __forceinline__ char8 all(schar v) {return make_char8(v, v, v, v, v, v, v, v);}
+        static __device__ __host__ __forceinline__ char8 make(schar a0, schar a1, schar a2, schar a3, schar a4, schar a5, schar a6, schar a7) {return make_char8(a0, a1, a2, a3, a4, a5, a6, a7);}
+        static __device__ __host__ __forceinline__ char8 make(const schar* v) {return make_char8(v[0], v[1], v[2], v[3], v[4], v[5], v[6], v[7]);}
+    };
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif // OPENCV_CUDA_VEC_TRAITS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/warp.hpp

@@ -0,0 +1,139 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_DEVICE_WARP_HPP
+#define OPENCV_CUDA_DEVICE_WARP_HPP
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    struct Warp
+    {
+        enum
+        {
+            LOG_WARP_SIZE = 5,
+            WARP_SIZE     = 1 << LOG_WARP_SIZE,
+            STRIDE        = WARP_SIZE
+        };
+
+        /** \brief Returns the warp lane ID of the calling thread. */
+        static __device__ __forceinline__ unsigned int laneId()
+        {
+            unsigned int ret;
+            asm("mov.u32 %0, %%laneid;" : "=r"(ret) );
+            return ret;
+        }
+
+        template<typename It, typename T>
+        static __device__ __forceinline__ void fill(It beg, It end, const T& value)
+        {
+            for(It t = beg + laneId(); t < end; t += STRIDE)
+                *t = value;
+        }
+
+        template<typename InIt, typename OutIt>
+        static __device__ __forceinline__ OutIt copy(InIt beg, InIt end, OutIt out)
+        {
+            for(InIt t = beg + laneId(); t < end; t += STRIDE, out += STRIDE)
+                *out = *t;
+            return out;
+        }
+
+        template<typename InIt, typename OutIt, class UnOp>
+        static __device__ __forceinline__ OutIt transform(InIt beg, InIt end, OutIt out, UnOp op)
+        {
+            for(InIt t = beg + laneId(); t < end; t += STRIDE, out += STRIDE)
+                *out = op(*t);
+            return out;
+        }
+
+        template<typename InIt1, typename InIt2, typename OutIt, class BinOp>
+        static __device__ __forceinline__ OutIt transform(InIt1 beg1, InIt1 end1, InIt2 beg2, OutIt out, BinOp op)
+        {
+            unsigned int lane = laneId();
+
+            InIt1 t1 = beg1 + lane;
+            InIt2 t2 = beg2 + lane;
+            for(; t1 < end1; t1 += STRIDE, t2 += STRIDE, out += STRIDE)
+                *out = op(*t1, *t2);
+            return out;
+        }
+
+        template <class T, class BinOp>
+        static __device__ __forceinline__ T reduce(volatile T *ptr, BinOp op)
+        {
+            const unsigned int lane = laneId();
+
+            if (lane < 16)
+            {
+                T partial = ptr[lane];
+
+                ptr[lane] = partial = op(partial, ptr[lane + 16]);
+                ptr[lane] = partial = op(partial, ptr[lane + 8]);
+                ptr[lane] = partial = op(partial, ptr[lane + 4]);
+                ptr[lane] = partial = op(partial, ptr[lane + 2]);
+                ptr[lane] = partial = op(partial, ptr[lane + 1]);
+            }
+
+            return *ptr;
+        }
+
+        template<typename OutIt, typename T>
+        static __device__ __forceinline__ void yota(OutIt beg, OutIt end, T value)
+        {
+            unsigned int lane = laneId();
+            value += lane;
+
+            for(OutIt t = beg + lane; t < end; t += STRIDE, value += STRIDE)
+                *t = value;
+        }
+    };
+}}} // namespace cv { namespace cuda { namespace cudev
+
+//! @endcond
+
+#endif /* OPENCV_CUDA_DEVICE_WARP_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/warp_reduce.hpp

@@ -0,0 +1,76 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_WARP_REDUCE_HPP__
+#define OPENCV_CUDA_WARP_REDUCE_HPP__
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+    template <class T>
+    __device__ __forceinline__ T warp_reduce(volatile T *ptr , const unsigned int tid = threadIdx.x)
+    {
+        const unsigned int lane = tid & 31; // index of thread in warp (0..31)
+
+        if (lane < 16)
+        {
+            T partial = ptr[tid];
+
+            ptr[tid] = partial = partial + ptr[tid + 16];
+            ptr[tid] = partial = partial + ptr[tid + 8];
+            ptr[tid] = partial = partial + ptr[tid + 4];
+            ptr[tid] = partial = partial + ptr[tid + 2];
+            ptr[tid] = partial = partial + ptr[tid + 1];
+        }
+
+        return ptr[tid - lane];
+    }
+}}} // namespace cv { namespace cuda { namespace cudev {
+
+//! @endcond
+
+#endif /* OPENCV_CUDA_WARP_REDUCE_HPP__ */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda/warp_shuffle.hpp

@@ -0,0 +1,162 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CUDA_WARP_SHUFFLE_HPP
+#define OPENCV_CUDA_WARP_SHUFFLE_HPP
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+namespace cv { namespace cuda { namespace device
+{
+#if __CUDACC_VER_MAJOR__ >= 9
+#  define __shfl(x, y, z) __shfl_sync(0xFFFFFFFFU, x, y, z)
+#  define __shfl_up(x, y, z) __shfl_up_sync(0xFFFFFFFFU, x, y, z)
+#  define __shfl_down(x, y, z) __shfl_down_sync(0xFFFFFFFFU, x, y, z)
+#endif
+    template <typename T>
+    __device__ __forceinline__ T shfl(T val, int srcLane, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        return __shfl(val, srcLane, width);
+    #else
+        return T();
+    #endif
+    }
+    __device__ __forceinline__ unsigned int shfl(unsigned int val, int srcLane, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        return (unsigned int) __shfl((int) val, srcLane, width);
+    #else
+        return 0;
+    #endif
+    }
+    __device__ __forceinline__ double shfl(double val, int srcLane, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        int lo = __double2loint(val);
+        int hi = __double2hiint(val);
+
+        lo = __shfl(lo, srcLane, width);
+        hi = __shfl(hi, srcLane, width);
+
+        return __hiloint2double(hi, lo);
+    #else
+        return 0.0;
+    #endif
+    }
+
+    template <typename T>
+    __device__ __forceinline__ T shfl_down(T val, unsigned int delta, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        return __shfl_down(val, delta, width);
+    #else
+        return T();
+    #endif
+    }
+    __device__ __forceinline__ unsigned int shfl_down(unsigned int val, unsigned int delta, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        return (unsigned int) __shfl_down((int) val, delta, width);
+    #else
+        return 0;
+    #endif
+    }
+    __device__ __forceinline__ double shfl_down(double val, unsigned int delta, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        int lo = __double2loint(val);
+        int hi = __double2hiint(val);
+
+        lo = __shfl_down(lo, delta, width);
+        hi = __shfl_down(hi, delta, width);
+
+        return __hiloint2double(hi, lo);
+    #else
+        return 0.0;
+    #endif
+    }
+
+    template <typename T>
+    __device__ __forceinline__ T shfl_up(T val, unsigned int delta, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        return __shfl_up(val, delta, width);
+    #else
+        return T();
+    #endif
+    }
+    __device__ __forceinline__ unsigned int shfl_up(unsigned int val, unsigned int delta, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        return (unsigned int) __shfl_up((int) val, delta, width);
+    #else
+        return 0;
+    #endif
+    }
+    __device__ __forceinline__ double shfl_up(double val, unsigned int delta, int width = warpSize)
+    {
+    #if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 300
+        int lo = __double2loint(val);
+        int hi = __double2hiint(val);
+
+        lo = __shfl_up(lo, delta, width);
+        hi = __shfl_up(hi, delta, width);
+
+        return __hiloint2double(hi, lo);
+    #else
+        return 0.0;
+    #endif
+    }
+}}}
+
+#  undef __shfl
+#  undef __shfl_up
+#  undef __shfl_down
+
+//! @endcond
+
+#endif // OPENCV_CUDA_WARP_SHUFFLE_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cuda_stream_accessor.hpp

@@ -0,0 +1,86 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP
+#define OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP
+
+#ifndef __cplusplus
+#  error cuda_stream_accessor.hpp header must be compiled as C++
+#endif
+
+/** @file cuda_stream_accessor.hpp
+ * This is only header file that depends on CUDA Runtime API. All other headers are independent.
+ */
+
+#include <cuda_runtime.h>
+#include "opencv2/core/cuda.hpp"
+
+namespace cv
+{
+    namespace cuda
+    {
+
+//! @addtogroup cudacore_struct
+//! @{
+
+        /** @brief Class that enables getting cudaStream_t from cuda::Stream
+         */
+        struct StreamAccessor
+        {
+            CV_EXPORTS static cudaStream_t getStream(const Stream& stream);
+            CV_EXPORTS static Stream wrapStream(cudaStream_t stream);
+        };
+
+        /** @brief Class that enables getting cudaEvent_t from cuda::Event
+         */
+        struct EventAccessor
+        {
+            CV_EXPORTS static cudaEvent_t getEvent(const Event& event);
+            CV_EXPORTS static Event wrapEvent(cudaEvent_t event);
+        };
+
+//! @}
+
+    }
+}
+
+#endif /* OPENCV_CORE_CUDA_STREAM_ACCESSOR_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/cuda_types.hpp

@@ -0,0 +1,152 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_CUDA_TYPES_HPP
+#define OPENCV_CORE_CUDA_TYPES_HPP
+
+#ifndef __cplusplus
+#  error cuda_types.hpp header must be compiled as C++
+#endif
+
+#if defined(__OPENCV_BUILD) && defined(__clang__)
+#pragma clang diagnostic ignored "-Winconsistent-missing-override"
+#endif
+#if defined(__OPENCV_BUILD) && defined(__GNUC__) && __GNUC__ >= 5
+#pragma GCC diagnostic ignored "-Wsuggest-override"
+#endif
+
+/** @file
+ * @deprecated Use @ref cudev instead.
+ */
+
+//! @cond IGNORED
+
+#ifdef __CUDACC__
+    #define __CV_CUDA_HOST_DEVICE__ __host__ __device__ __forceinline__
+#else
+    #define __CV_CUDA_HOST_DEVICE__
+#endif
+
+#include "opencv2/core/cvdef.h"
+#include "opencv2/core.hpp"
+
+namespace cv
+{
+    namespace cuda
+    {
+
+        // Simple lightweight structures that encapsulates information about an image on device.
+        // It is intended to pass to nvcc-compiled code. GpuMat depends on headers that nvcc can't compile
+
+        template <typename T> struct DevPtr
+        {
+            typedef T elem_type;
+            typedef int index_type;
+
+            enum { elem_size = sizeof(elem_type) };
+
+            T* data;
+
+            __CV_CUDA_HOST_DEVICE__ DevPtr() : data(0) {}
+            __CV_CUDA_HOST_DEVICE__ DevPtr(T* data_) : data(data_) {}
+
+            __CV_CUDA_HOST_DEVICE__ size_t elemSize() const { return elem_size; }
+            __CV_CUDA_HOST_DEVICE__ operator       T*()       { return data; }
+            __CV_CUDA_HOST_DEVICE__ operator const T*() const { return data; }
+        };
+
+        template <typename T> struct PtrSz : public DevPtr<T>
+        {
+            __CV_CUDA_HOST_DEVICE__ PtrSz() : size(0) {}
+            __CV_CUDA_HOST_DEVICE__ PtrSz(T* data_, size_t size_) : DevPtr<T>(data_), size(size_) {}
+
+            size_t size;
+        };
+
+        template <typename T> struct PtrStep : public DevPtr<T>
+        {
+            __CV_CUDA_HOST_DEVICE__ PtrStep() : step(0) {}
+            __CV_CUDA_HOST_DEVICE__ PtrStep(T* data_, size_t step_) : DevPtr<T>(data_), step(step_) {}
+
+            size_t step;
+
+            __CV_CUDA_HOST_DEVICE__       T* ptr(int y = 0)       { return (      T*)( (      char*)(((DevPtr<T>*)this)->data) + y * step); }
+            __CV_CUDA_HOST_DEVICE__ const T* ptr(int y = 0) const { return (const T*)( (const char*)(((DevPtr<T>*)this)->data) + y * step); }
+
+            __CV_CUDA_HOST_DEVICE__       T& operator ()(int y, int x)       { return ptr(y)[x]; }
+            __CV_CUDA_HOST_DEVICE__ const T& operator ()(int y, int x) const { return ptr(y)[x]; }
+        };
+
+        template <typename T> struct PtrStepSz : public PtrStep<T>
+        {
+            __CV_CUDA_HOST_DEVICE__ PtrStepSz() : cols(0), rows(0) {}
+            __CV_CUDA_HOST_DEVICE__ PtrStepSz(int rows_, int cols_, T* data_, size_t step_)
+                : PtrStep<T>(data_, step_), cols(cols_), rows(rows_) {}
+
+            template <typename U>
+            explicit PtrStepSz(const PtrStepSz<U>& d) : PtrStep<T>((T*)d.data, d.step), cols(d.cols), rows(d.rows){}
+
+            int cols;
+            int rows;
+
+            CV_NODISCARD_STD __CV_CUDA_HOST_DEVICE__ Size size() const { return {cols, rows}; }
+            CV_NODISCARD_STD __CV_CUDA_HOST_DEVICE__ T& operator ()(const Point &pos)       { return (*this)(pos.y, pos.x); }
+            CV_NODISCARD_STD __CV_CUDA_HOST_DEVICE__ const T& operator ()(const Point &pos) const { return (*this)(pos.y, pos.x); }
+            using PtrStep<T>::operator();
+        };
+
+        typedef PtrStepSz<unsigned char> PtrStepSzb;
+        typedef PtrStepSz<unsigned short> PtrStepSzus;
+        typedef PtrStepSz<float> PtrStepSzf;
+        typedef PtrStepSz<int> PtrStepSzi;
+
+        typedef PtrStep<unsigned char> PtrStepb;
+        typedef PtrStep<unsigned short> PtrStepus;
+        typedef PtrStep<float> PtrStepf;
+        typedef PtrStep<int> PtrStepi;
+
+    }
+}
+
+//! @endcond
+
+#endif /* OPENCV_CORE_CUDA_TYPES_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/cv_cpu_dispatch.h

@@ -0,0 +1,395 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#if defined __OPENCV_BUILD \
+
+#include "cv_cpu_config.h"
+#include "cv_cpu_helper.h"
+
+#ifdef CV_CPU_DISPATCH_MODE
+#define CV_CPU_OPTIMIZATION_NAMESPACE __CV_CAT(opt_, CV_CPU_DISPATCH_MODE)
+#define CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN namespace __CV_CAT(opt_, CV_CPU_DISPATCH_MODE) {
+#define CV_CPU_OPTIMIZATION_NAMESPACE_END }
+#else
+#define CV_CPU_OPTIMIZATION_NAMESPACE cpu_baseline
+#define CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN namespace cpu_baseline {
+#define CV_CPU_OPTIMIZATION_NAMESPACE_END }
+#define CV_CPU_BASELINE_MODE 1
+#endif
+
+
+#define __CV_CPU_DISPATCH_CHAIN_END(fn, args, mode, ...)  /* done */
+#define __CV_CPU_DISPATCH(fn, args, mode, ...) __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+#define __CV_CPU_DISPATCH_EXPAND(fn, args, ...) __CV_EXPAND(__CV_CPU_DISPATCH(fn, args, __VA_ARGS__))
+#define CV_CPU_DISPATCH(fn, args, ...) __CV_CPU_DISPATCH_EXPAND(fn, args, __VA_ARGS__, END) // expand macros
+
+
+#if defined CV_ENABLE_INTRINSICS \
+    && !defined CV_DISABLE_OPTIMIZATION \
+    && !defined __CUDACC__ /* do not include SSE/AVX/NEON headers for NVCC compiler */ \
+
+#ifdef CV_CPU_COMPILE_SSE2
+#  include <emmintrin.h>
+#  define CV_MMX 1
+#  define CV_SSE 1
+#  define CV_SSE2 1
+#endif
+#ifdef CV_CPU_COMPILE_SSE3
+#  include <pmmintrin.h>
+#  define CV_SSE3 1
+#endif
+#ifdef CV_CPU_COMPILE_SSSE3
+#  include <tmmintrin.h>
+#  define CV_SSSE3 1
+#endif
+#ifdef CV_CPU_COMPILE_SSE4_1
+#  include <smmintrin.h>
+#  define CV_SSE4_1 1
+#endif
+#ifdef CV_CPU_COMPILE_SSE4_2
+#  include <nmmintrin.h>
+#  define CV_SSE4_2 1
+#endif
+#ifdef CV_CPU_COMPILE_POPCNT
+#  ifdef _MSC_VER
+#    include <nmmintrin.h>
+#    if defined(_M_X64)
+#      define CV_POPCNT_U64 (int)_mm_popcnt_u64
+#    endif
+#    define CV_POPCNT_U32 _mm_popcnt_u32
+#  else
+#    include <popcntintrin.h>
+#    if defined(__x86_64__)
+#      define CV_POPCNT_U64 __builtin_popcountll
+#    endif
+#    define CV_POPCNT_U32 __builtin_popcount
+#  endif
+#  define CV_POPCNT 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX
+#  include <immintrin.h>
+#  define CV_AVX 1
+#endif
+#ifdef CV_CPU_COMPILE_FP16
+#  if defined(__arm__) || defined(__aarch64__) || defined(_M_ARM) || defined(_M_ARM64)
+#    include <arm_neon.h>
+#  else
+#    include <immintrin.h>
+#  endif
+#  define CV_FP16 1
+#endif
+#ifdef CV_CPU_COMPILE_NEON_DOTPROD
+#  include <arm_neon.h>
+#  define CV_NEON_DOT 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX2
+#  include <immintrin.h>
+#  define CV_AVX2 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX_512F
+#  include <immintrin.h>
+#  define CV_AVX_512F 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX512_COMMON
+#  define CV_AVX512_COMMON 1
+#  define CV_AVX_512CD 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX512_KNL
+#  define CV_AVX512_KNL 1
+#  define CV_AVX_512ER 1
+#  define CV_AVX_512PF 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX512_KNM
+#  define CV_AVX512_KNM 1
+#  define CV_AVX_5124FMAPS 1
+#  define CV_AVX_5124VNNIW 1
+#  define CV_AVX_512VPOPCNTDQ 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX512_SKX
+#  define CV_AVX512_SKX 1
+#  define CV_AVX_512VL 1
+#  define CV_AVX_512BW 1
+#  define CV_AVX_512DQ 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX512_CNL
+#  define CV_AVX512_CNL 1
+#  define CV_AVX_512IFMA 1
+#  define CV_AVX_512VBMI 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX512_CLX
+#  define CV_AVX512_CLX 1
+#  define CV_AVX_512VNNI 1
+#endif
+#ifdef CV_CPU_COMPILE_AVX512_ICL
+#  define CV_AVX512_ICL 1
+#  undef CV_AVX_512IFMA
+#  define CV_AVX_512IFMA 1
+#  undef CV_AVX_512VBMI
+#  define CV_AVX_512VBMI 1
+#  undef CV_AVX_512VNNI
+#  define CV_AVX_512VNNI 1
+#  define CV_AVX_512VBMI2 1
+#  define CV_AVX_512BITALG 1
+#  define CV_AVX_512VPOPCNTDQ 1
+#endif
+#ifdef CV_CPU_COMPILE_FMA3
+#  define CV_FMA3 1
+#endif
+
+#if defined _WIN32 && (defined(_M_ARM) || defined(_M_ARM64)) && (defined(CV_CPU_COMPILE_NEON) || !defined(_MSC_VER))
+# include <Intrin.h>
+# include <arm_neon.h>
+# define CV_NEON 1
+#elif defined(__ARM_NEON)
+#  include <arm_neon.h>
+#  define CV_NEON 1
+#endif
+
+/* RVV-related macro states with different compiler
+// +--------------------+----------+----------+
+// | Macro              | Upstream | XuanTie  |
+// +--------------------+----------+----------+
+// | CV_CPU_COMPILE_RVV | defined  | defined  |
+// | CV_RVV             | 1        | 0        |
+// | CV_RVV071          | 0        | 1        |
+// | CV_TRY_RVV         | 1        | 1        |
+// +--------------------+----------+----------+
+*/
+#ifdef CV_CPU_COMPILE_RVV
+#  ifdef __riscv_vector_071
+#    define CV_RVV071 1
+#  else
+#    define CV_RVV 1
+#  endif
+#include <riscv_vector.h>
+#endif
+
+#ifdef CV_CPU_COMPILE_VSX
+#  include <altivec.h>
+#  undef vector
+#  undef pixel
+#  undef bool
+#  define CV_VSX 1
+#endif
+
+#ifdef CV_CPU_COMPILE_VSX3
+#  define CV_VSX3 1
+#endif
+
+#ifdef CV_CPU_COMPILE_MSA
+#  include "hal/msa_macros.h"
+#  define CV_MSA 1
+#endif
+
+#ifdef CV_CPU_COMPILE_LSX
+#  include <lsxintrin.h>
+#  define CV_LSX 1
+#endif
+
+#ifdef CV_CPU_COMPILE_LASX
+#  include <lasxintrin.h>
+#  define CV_LASX 1
+#endif
+
+#ifdef __EMSCRIPTEN__
+#  define CV_WASM_SIMD 1
+#  include <wasm_simd128.h>
+#endif
+
+#endif // CV_ENABLE_INTRINSICS && !CV_DISABLE_OPTIMIZATION && !__CUDACC__
+
+#if defined CV_CPU_COMPILE_AVX && !defined CV_CPU_BASELINE_COMPILE_AVX
+struct VZeroUpperGuard {
+#ifdef __GNUC__
+    __attribute__((always_inline))
+#endif
+    inline VZeroUpperGuard() { _mm256_zeroupper(); }
+#ifdef __GNUC__
+    __attribute__((always_inline))
+#endif
+    inline ~VZeroUpperGuard() { _mm256_zeroupper(); }
+};
+#define __CV_AVX_GUARD VZeroUpperGuard __vzeroupper_guard; CV_UNUSED(__vzeroupper_guard);
+#endif
+
+#ifdef __CV_AVX_GUARD
+#define CV_AVX_GUARD __CV_AVX_GUARD
+#else
+#define CV_AVX_GUARD
+#endif
+
+#endif // __OPENCV_BUILD
+
+
+
+#if !defined __OPENCV_BUILD /* Compatibility code */ \
+    && !defined __CUDACC__ /* do not include SSE/AVX/NEON headers for NVCC compiler */
+#if defined __SSE2__ || defined _M_X64 || (defined _M_IX86_FP && _M_IX86_FP >= 2)
+#  include <emmintrin.h>
+#  define CV_MMX 1
+#  define CV_SSE 1
+#  define CV_SSE2 1
+#elif defined _WIN32 && (defined(_M_ARM) || defined(_M_ARM64)) && (defined(CV_CPU_COMPILE_NEON) || !defined(_MSC_VER))
+# include <Intrin.h>
+# include <arm_neon.h>
+# define CV_NEON 1
+#elif defined(__ARM_NEON)
+#  include <arm_neon.h>
+#  define CV_NEON 1
+#elif defined(__VSX__) && defined(__PPC64__) && defined(__LITTLE_ENDIAN__)
+#  include <altivec.h>
+#  undef vector
+#  undef pixel
+#  undef bool
+#  define CV_VSX 1
+#endif
+
+#ifdef __F16C__
+#  include <immintrin.h>
+#  define CV_FP16 1
+#endif
+
+#endif // !__OPENCV_BUILD && !__CUDACC (Compatibility code)
+
+
+
+#ifndef CV_MMX
+#  define CV_MMX 0
+#endif
+#ifndef CV_SSE
+#  define CV_SSE 0
+#endif
+#ifndef CV_SSE2
+#  define CV_SSE2 0
+#endif
+#ifndef CV_SSE3
+#  define CV_SSE3 0
+#endif
+#ifndef CV_SSSE3
+#  define CV_SSSE3 0
+#endif
+#ifndef CV_SSE4_1
+#  define CV_SSE4_1 0
+#endif
+#ifndef CV_SSE4_2
+#  define CV_SSE4_2 0
+#endif
+#ifndef CV_POPCNT
+#  define CV_POPCNT 0
+#endif
+#ifndef CV_AVX
+#  define CV_AVX 0
+#endif
+#ifndef CV_FP16
+#  define CV_FP16 0
+#endif
+#ifndef CV_AVX2
+#  define CV_AVX2 0
+#endif
+#ifndef CV_FMA3
+#  define CV_FMA3 0
+#endif
+#ifndef CV_AVX_512F
+#  define CV_AVX_512F 0
+#endif
+#ifndef CV_AVX_512BW
+#  define CV_AVX_512BW 0
+#endif
+#ifndef CV_AVX_512CD
+#  define CV_AVX_512CD 0
+#endif
+#ifndef CV_AVX_512DQ
+#  define CV_AVX_512DQ 0
+#endif
+#ifndef CV_AVX_512ER
+#  define CV_AVX_512ER 0
+#endif
+#ifndef CV_AVX_512IFMA
+#  define CV_AVX_512IFMA 0
+#endif
+#define CV_AVX_512IFMA512 CV_AVX_512IFMA // deprecated
+#ifndef CV_AVX_512PF
+#  define CV_AVX_512PF 0
+#endif
+#ifndef CV_AVX_512VBMI
+#  define CV_AVX_512VBMI 0
+#endif
+#ifndef CV_AVX_512VL
+#  define CV_AVX_512VL 0
+#endif
+#ifndef CV_AVX_5124FMAPS
+#  define CV_AVX_5124FMAPS 0
+#endif
+#ifndef CV_AVX_5124VNNIW
+#  define CV_AVX_5124VNNIW 0
+#endif
+#ifndef CV_AVX_512VPOPCNTDQ
+#  define CV_AVX_512VPOPCNTDQ 0
+#endif
+#ifndef CV_AVX_512VNNI
+#  define CV_AVX_512VNNI 0
+#endif
+#ifndef CV_AVX_512VBMI2
+#  define CV_AVX_512VBMI2 0
+#endif
+#ifndef CV_AVX_512BITALG
+#  define CV_AVX_512BITALG 0
+#endif
+#ifndef CV_AVX512_COMMON
+#  define CV_AVX512_COMMON 0
+#endif
+#ifndef CV_AVX512_KNL
+#  define CV_AVX512_KNL 0
+#endif
+#ifndef CV_AVX512_KNM
+#  define CV_AVX512_KNM 0
+#endif
+#ifndef CV_AVX512_SKX
+#  define CV_AVX512_SKX 0
+#endif
+#ifndef CV_AVX512_CNL
+#  define CV_AVX512_CNL 0
+#endif
+#ifndef CV_AVX512_CLX
+#  define CV_AVX512_CLX 0
+#endif
+#ifndef CV_AVX512_ICL
+#  define CV_AVX512_ICL 0
+#endif
+
+#ifndef CV_NEON
+#  define CV_NEON 0
+#endif
+
+#ifndef CV_RVV071
+#  define CV_RVV071 0
+#endif
+
+#ifndef CV_VSX
+#  define CV_VSX 0
+#endif
+
+#ifndef CV_VSX3
+#  define CV_VSX3 0
+#endif
+
+#ifndef CV_MSA
+#  define CV_MSA 0
+#endif
+
+#ifndef CV_WASM_SIMD
+#  define CV_WASM_SIMD 0
+#endif
+
+#ifndef CV_RVV
+#  define CV_RVV 0
+#endif
+
+#ifndef CV_LSX
+#  define CV_LSX 0
+#endif
+
+#ifndef CV_LASX
+#  define CV_LASX 0
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/cv_cpu_helper.h

@@ -0,0 +1,613 @@
+// AUTOGENERATED, DO NOT EDIT
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE
+#  define CV_TRY_SSE 1
+#  define CV_CPU_FORCE_SSE 1
+#  define CV_CPU_HAS_SUPPORT_SSE 1
+#  define CV_CPU_CALL_SSE(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_SSE_(fn, args) return (opt_SSE::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE
+#  define CV_TRY_SSE 1
+#  define CV_CPU_FORCE_SSE 0
+#  define CV_CPU_HAS_SUPPORT_SSE (cv::checkHardwareSupport(CV_CPU_SSE))
+#  define CV_CPU_CALL_SSE(fn, args) if (CV_CPU_HAS_SUPPORT_SSE) return (opt_SSE::fn args)
+#  define CV_CPU_CALL_SSE_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE) return (opt_SSE::fn args)
+#else
+#  define CV_TRY_SSE 0
+#  define CV_CPU_FORCE_SSE 0
+#  define CV_CPU_HAS_SUPPORT_SSE 0
+#  define CV_CPU_CALL_SSE(fn, args)
+#  define CV_CPU_CALL_SSE_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_SSE(fn, args, mode, ...)  CV_CPU_CALL_SSE(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE2
+#  define CV_TRY_SSE2 1
+#  define CV_CPU_FORCE_SSE2 1
+#  define CV_CPU_HAS_SUPPORT_SSE2 1
+#  define CV_CPU_CALL_SSE2(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_SSE2_(fn, args) return (opt_SSE2::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE2
+#  define CV_TRY_SSE2 1
+#  define CV_CPU_FORCE_SSE2 0
+#  define CV_CPU_HAS_SUPPORT_SSE2 (cv::checkHardwareSupport(CV_CPU_SSE2))
+#  define CV_CPU_CALL_SSE2(fn, args) if (CV_CPU_HAS_SUPPORT_SSE2) return (opt_SSE2::fn args)
+#  define CV_CPU_CALL_SSE2_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE2) return (opt_SSE2::fn args)
+#else
+#  define CV_TRY_SSE2 0
+#  define CV_CPU_FORCE_SSE2 0
+#  define CV_CPU_HAS_SUPPORT_SSE2 0
+#  define CV_CPU_CALL_SSE2(fn, args)
+#  define CV_CPU_CALL_SSE2_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_SSE2(fn, args, mode, ...)  CV_CPU_CALL_SSE2(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE3
+#  define CV_TRY_SSE3 1
+#  define CV_CPU_FORCE_SSE3 1
+#  define CV_CPU_HAS_SUPPORT_SSE3 1
+#  define CV_CPU_CALL_SSE3(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_SSE3_(fn, args) return (opt_SSE3::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE3
+#  define CV_TRY_SSE3 1
+#  define CV_CPU_FORCE_SSE3 0
+#  define CV_CPU_HAS_SUPPORT_SSE3 (cv::checkHardwareSupport(CV_CPU_SSE3))
+#  define CV_CPU_CALL_SSE3(fn, args) if (CV_CPU_HAS_SUPPORT_SSE3) return (opt_SSE3::fn args)
+#  define CV_CPU_CALL_SSE3_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE3) return (opt_SSE3::fn args)
+#else
+#  define CV_TRY_SSE3 0
+#  define CV_CPU_FORCE_SSE3 0
+#  define CV_CPU_HAS_SUPPORT_SSE3 0
+#  define CV_CPU_CALL_SSE3(fn, args)
+#  define CV_CPU_CALL_SSE3_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_SSE3(fn, args, mode, ...)  CV_CPU_CALL_SSE3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSSE3
+#  define CV_TRY_SSSE3 1
+#  define CV_CPU_FORCE_SSSE3 1
+#  define CV_CPU_HAS_SUPPORT_SSSE3 1
+#  define CV_CPU_CALL_SSSE3(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_SSSE3_(fn, args) return (opt_SSSE3::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSSE3
+#  define CV_TRY_SSSE3 1
+#  define CV_CPU_FORCE_SSSE3 0
+#  define CV_CPU_HAS_SUPPORT_SSSE3 (cv::checkHardwareSupport(CV_CPU_SSSE3))
+#  define CV_CPU_CALL_SSSE3(fn, args) if (CV_CPU_HAS_SUPPORT_SSSE3) return (opt_SSSE3::fn args)
+#  define CV_CPU_CALL_SSSE3_(fn, args) if (CV_CPU_HAS_SUPPORT_SSSE3) return (opt_SSSE3::fn args)
+#else
+#  define CV_TRY_SSSE3 0
+#  define CV_CPU_FORCE_SSSE3 0
+#  define CV_CPU_HAS_SUPPORT_SSSE3 0
+#  define CV_CPU_CALL_SSSE3(fn, args)
+#  define CV_CPU_CALL_SSSE3_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_SSSE3(fn, args, mode, ...)  CV_CPU_CALL_SSSE3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE4_1
+#  define CV_TRY_SSE4_1 1
+#  define CV_CPU_FORCE_SSE4_1 1
+#  define CV_CPU_HAS_SUPPORT_SSE4_1 1
+#  define CV_CPU_CALL_SSE4_1(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_SSE4_1_(fn, args) return (opt_SSE4_1::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE4_1
+#  define CV_TRY_SSE4_1 1
+#  define CV_CPU_FORCE_SSE4_1 0
+#  define CV_CPU_HAS_SUPPORT_SSE4_1 (cv::checkHardwareSupport(CV_CPU_SSE4_1))
+#  define CV_CPU_CALL_SSE4_1(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_1) return (opt_SSE4_1::fn args)
+#  define CV_CPU_CALL_SSE4_1_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_1) return (opt_SSE4_1::fn args)
+#else
+#  define CV_TRY_SSE4_1 0
+#  define CV_CPU_FORCE_SSE4_1 0
+#  define CV_CPU_HAS_SUPPORT_SSE4_1 0
+#  define CV_CPU_CALL_SSE4_1(fn, args)
+#  define CV_CPU_CALL_SSE4_1_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_SSE4_1(fn, args, mode, ...)  CV_CPU_CALL_SSE4_1(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_SSE4_2
+#  define CV_TRY_SSE4_2 1
+#  define CV_CPU_FORCE_SSE4_2 1
+#  define CV_CPU_HAS_SUPPORT_SSE4_2 1
+#  define CV_CPU_CALL_SSE4_2(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_SSE4_2_(fn, args) return (opt_SSE4_2::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_SSE4_2
+#  define CV_TRY_SSE4_2 1
+#  define CV_CPU_FORCE_SSE4_2 0
+#  define CV_CPU_HAS_SUPPORT_SSE4_2 (cv::checkHardwareSupport(CV_CPU_SSE4_2))
+#  define CV_CPU_CALL_SSE4_2(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_2) return (opt_SSE4_2::fn args)
+#  define CV_CPU_CALL_SSE4_2_(fn, args) if (CV_CPU_HAS_SUPPORT_SSE4_2) return (opt_SSE4_2::fn args)
+#else
+#  define CV_TRY_SSE4_2 0
+#  define CV_CPU_FORCE_SSE4_2 0
+#  define CV_CPU_HAS_SUPPORT_SSE4_2 0
+#  define CV_CPU_CALL_SSE4_2(fn, args)
+#  define CV_CPU_CALL_SSE4_2_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_SSE4_2(fn, args, mode, ...)  CV_CPU_CALL_SSE4_2(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_POPCNT
+#  define CV_TRY_POPCNT 1
+#  define CV_CPU_FORCE_POPCNT 1
+#  define CV_CPU_HAS_SUPPORT_POPCNT 1
+#  define CV_CPU_CALL_POPCNT(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_POPCNT_(fn, args) return (opt_POPCNT::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_POPCNT
+#  define CV_TRY_POPCNT 1
+#  define CV_CPU_FORCE_POPCNT 0
+#  define CV_CPU_HAS_SUPPORT_POPCNT (cv::checkHardwareSupport(CV_CPU_POPCNT))
+#  define CV_CPU_CALL_POPCNT(fn, args) if (CV_CPU_HAS_SUPPORT_POPCNT) return (opt_POPCNT::fn args)
+#  define CV_CPU_CALL_POPCNT_(fn, args) if (CV_CPU_HAS_SUPPORT_POPCNT) return (opt_POPCNT::fn args)
+#else
+#  define CV_TRY_POPCNT 0
+#  define CV_CPU_FORCE_POPCNT 0
+#  define CV_CPU_HAS_SUPPORT_POPCNT 0
+#  define CV_CPU_CALL_POPCNT(fn, args)
+#  define CV_CPU_CALL_POPCNT_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_POPCNT(fn, args, mode, ...)  CV_CPU_CALL_POPCNT(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX
+#  define CV_TRY_AVX 1
+#  define CV_CPU_FORCE_AVX 1
+#  define CV_CPU_HAS_SUPPORT_AVX 1
+#  define CV_CPU_CALL_AVX(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX_(fn, args) return (opt_AVX::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX
+#  define CV_TRY_AVX 1
+#  define CV_CPU_FORCE_AVX 0
+#  define CV_CPU_HAS_SUPPORT_AVX (cv::checkHardwareSupport(CV_CPU_AVX))
+#  define CV_CPU_CALL_AVX(fn, args) if (CV_CPU_HAS_SUPPORT_AVX) return (opt_AVX::fn args)
+#  define CV_CPU_CALL_AVX_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX) return (opt_AVX::fn args)
+#else
+#  define CV_TRY_AVX 0
+#  define CV_CPU_FORCE_AVX 0
+#  define CV_CPU_HAS_SUPPORT_AVX 0
+#  define CV_CPU_CALL_AVX(fn, args)
+#  define CV_CPU_CALL_AVX_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX(fn, args, mode, ...)  CV_CPU_CALL_AVX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_FP16
+#  define CV_TRY_FP16 1
+#  define CV_CPU_FORCE_FP16 1
+#  define CV_CPU_HAS_SUPPORT_FP16 1
+#  define CV_CPU_CALL_FP16(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_FP16_(fn, args) return (opt_FP16::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_FP16
+#  define CV_TRY_FP16 1
+#  define CV_CPU_FORCE_FP16 0
+#  define CV_CPU_HAS_SUPPORT_FP16 (cv::checkHardwareSupport(CV_CPU_FP16))
+#  define CV_CPU_CALL_FP16(fn, args) if (CV_CPU_HAS_SUPPORT_FP16) return (opt_FP16::fn args)
+#  define CV_CPU_CALL_FP16_(fn, args) if (CV_CPU_HAS_SUPPORT_FP16) return (opt_FP16::fn args)
+#else
+#  define CV_TRY_FP16 0
+#  define CV_CPU_FORCE_FP16 0
+#  define CV_CPU_HAS_SUPPORT_FP16 0
+#  define CV_CPU_CALL_FP16(fn, args)
+#  define CV_CPU_CALL_FP16_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_FP16(fn, args, mode, ...)  CV_CPU_CALL_FP16(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX2
+#  define CV_TRY_AVX2 1
+#  define CV_CPU_FORCE_AVX2 1
+#  define CV_CPU_HAS_SUPPORT_AVX2 1
+#  define CV_CPU_CALL_AVX2(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX2_(fn, args) return (opt_AVX2::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX2
+#  define CV_TRY_AVX2 1
+#  define CV_CPU_FORCE_AVX2 0
+#  define CV_CPU_HAS_SUPPORT_AVX2 (cv::checkHardwareSupport(CV_CPU_AVX2))
+#  define CV_CPU_CALL_AVX2(fn, args) if (CV_CPU_HAS_SUPPORT_AVX2) return (opt_AVX2::fn args)
+#  define CV_CPU_CALL_AVX2_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX2) return (opt_AVX2::fn args)
+#else
+#  define CV_TRY_AVX2 0
+#  define CV_CPU_FORCE_AVX2 0
+#  define CV_CPU_HAS_SUPPORT_AVX2 0
+#  define CV_CPU_CALL_AVX2(fn, args)
+#  define CV_CPU_CALL_AVX2_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX2(fn, args, mode, ...)  CV_CPU_CALL_AVX2(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_FMA3
+#  define CV_TRY_FMA3 1
+#  define CV_CPU_FORCE_FMA3 1
+#  define CV_CPU_HAS_SUPPORT_FMA3 1
+#  define CV_CPU_CALL_FMA3(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_FMA3_(fn, args) return (opt_FMA3::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_FMA3
+#  define CV_TRY_FMA3 1
+#  define CV_CPU_FORCE_FMA3 0
+#  define CV_CPU_HAS_SUPPORT_FMA3 (cv::checkHardwareSupport(CV_CPU_FMA3))
+#  define CV_CPU_CALL_FMA3(fn, args) if (CV_CPU_HAS_SUPPORT_FMA3) return (opt_FMA3::fn args)
+#  define CV_CPU_CALL_FMA3_(fn, args) if (CV_CPU_HAS_SUPPORT_FMA3) return (opt_FMA3::fn args)
+#else
+#  define CV_TRY_FMA3 0
+#  define CV_CPU_FORCE_FMA3 0
+#  define CV_CPU_HAS_SUPPORT_FMA3 0
+#  define CV_CPU_CALL_FMA3(fn, args)
+#  define CV_CPU_CALL_FMA3_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_FMA3(fn, args, mode, ...)  CV_CPU_CALL_FMA3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX_512F
+#  define CV_TRY_AVX_512F 1
+#  define CV_CPU_FORCE_AVX_512F 1
+#  define CV_CPU_HAS_SUPPORT_AVX_512F 1
+#  define CV_CPU_CALL_AVX_512F(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX_512F_(fn, args) return (opt_AVX_512F::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX_512F
+#  define CV_TRY_AVX_512F 1
+#  define CV_CPU_FORCE_AVX_512F 0
+#  define CV_CPU_HAS_SUPPORT_AVX_512F (cv::checkHardwareSupport(CV_CPU_AVX_512F))
+#  define CV_CPU_CALL_AVX_512F(fn, args) if (CV_CPU_HAS_SUPPORT_AVX_512F) return (opt_AVX_512F::fn args)
+#  define CV_CPU_CALL_AVX_512F_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX_512F) return (opt_AVX_512F::fn args)
+#else
+#  define CV_TRY_AVX_512F 0
+#  define CV_CPU_FORCE_AVX_512F 0
+#  define CV_CPU_HAS_SUPPORT_AVX_512F 0
+#  define CV_CPU_CALL_AVX_512F(fn, args)
+#  define CV_CPU_CALL_AVX_512F_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX_512F(fn, args, mode, ...)  CV_CPU_CALL_AVX_512F(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_COMMON
+#  define CV_TRY_AVX512_COMMON 1
+#  define CV_CPU_FORCE_AVX512_COMMON 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_COMMON 1
+#  define CV_CPU_CALL_AVX512_COMMON(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_COMMON_(fn, args) return (opt_AVX512_COMMON::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_COMMON
+#  define CV_TRY_AVX512_COMMON 1
+#  define CV_CPU_FORCE_AVX512_COMMON 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_COMMON (cv::checkHardwareSupport(CV_CPU_AVX512_COMMON))
+#  define CV_CPU_CALL_AVX512_COMMON(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_COMMON) return (opt_AVX512_COMMON::fn args)
+#  define CV_CPU_CALL_AVX512_COMMON_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_COMMON) return (opt_AVX512_COMMON::fn args)
+#else
+#  define CV_TRY_AVX512_COMMON 0
+#  define CV_CPU_FORCE_AVX512_COMMON 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_COMMON 0
+#  define CV_CPU_CALL_AVX512_COMMON(fn, args)
+#  define CV_CPU_CALL_AVX512_COMMON_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_COMMON(fn, args, mode, ...)  CV_CPU_CALL_AVX512_COMMON(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_KNL
+#  define CV_TRY_AVX512_KNL 1
+#  define CV_CPU_FORCE_AVX512_KNL 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_KNL 1
+#  define CV_CPU_CALL_AVX512_KNL(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_KNL_(fn, args) return (opt_AVX512_KNL::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_KNL
+#  define CV_TRY_AVX512_KNL 1
+#  define CV_CPU_FORCE_AVX512_KNL 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_KNL (cv::checkHardwareSupport(CV_CPU_AVX512_KNL))
+#  define CV_CPU_CALL_AVX512_KNL(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_KNL) return (opt_AVX512_KNL::fn args)
+#  define CV_CPU_CALL_AVX512_KNL_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_KNL) return (opt_AVX512_KNL::fn args)
+#else
+#  define CV_TRY_AVX512_KNL 0
+#  define CV_CPU_FORCE_AVX512_KNL 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_KNL 0
+#  define CV_CPU_CALL_AVX512_KNL(fn, args)
+#  define CV_CPU_CALL_AVX512_KNL_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_KNL(fn, args, mode, ...)  CV_CPU_CALL_AVX512_KNL(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_KNM
+#  define CV_TRY_AVX512_KNM 1
+#  define CV_CPU_FORCE_AVX512_KNM 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_KNM 1
+#  define CV_CPU_CALL_AVX512_KNM(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_KNM_(fn, args) return (opt_AVX512_KNM::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_KNM
+#  define CV_TRY_AVX512_KNM 1
+#  define CV_CPU_FORCE_AVX512_KNM 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_KNM (cv::checkHardwareSupport(CV_CPU_AVX512_KNM))
+#  define CV_CPU_CALL_AVX512_KNM(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_KNM) return (opt_AVX512_KNM::fn args)
+#  define CV_CPU_CALL_AVX512_KNM_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_KNM) return (opt_AVX512_KNM::fn args)
+#else
+#  define CV_TRY_AVX512_KNM 0
+#  define CV_CPU_FORCE_AVX512_KNM 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_KNM 0
+#  define CV_CPU_CALL_AVX512_KNM(fn, args)
+#  define CV_CPU_CALL_AVX512_KNM_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_KNM(fn, args, mode, ...)  CV_CPU_CALL_AVX512_KNM(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_SKX
+#  define CV_TRY_AVX512_SKX 1
+#  define CV_CPU_FORCE_AVX512_SKX 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_SKX 1
+#  define CV_CPU_CALL_AVX512_SKX(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_SKX_(fn, args) return (opt_AVX512_SKX::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_SKX
+#  define CV_TRY_AVX512_SKX 1
+#  define CV_CPU_FORCE_AVX512_SKX 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_SKX (cv::checkHardwareSupport(CV_CPU_AVX512_SKX))
+#  define CV_CPU_CALL_AVX512_SKX(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_SKX) return (opt_AVX512_SKX::fn args)
+#  define CV_CPU_CALL_AVX512_SKX_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_SKX) return (opt_AVX512_SKX::fn args)
+#else
+#  define CV_TRY_AVX512_SKX 0
+#  define CV_CPU_FORCE_AVX512_SKX 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_SKX 0
+#  define CV_CPU_CALL_AVX512_SKX(fn, args)
+#  define CV_CPU_CALL_AVX512_SKX_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_SKX(fn, args, mode, ...)  CV_CPU_CALL_AVX512_SKX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_CNL
+#  define CV_TRY_AVX512_CNL 1
+#  define CV_CPU_FORCE_AVX512_CNL 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_CNL 1
+#  define CV_CPU_CALL_AVX512_CNL(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_CNL_(fn, args) return (opt_AVX512_CNL::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_CNL
+#  define CV_TRY_AVX512_CNL 1
+#  define CV_CPU_FORCE_AVX512_CNL 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_CNL (cv::checkHardwareSupport(CV_CPU_AVX512_CNL))
+#  define CV_CPU_CALL_AVX512_CNL(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CNL) return (opt_AVX512_CNL::fn args)
+#  define CV_CPU_CALL_AVX512_CNL_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CNL) return (opt_AVX512_CNL::fn args)
+#else
+#  define CV_TRY_AVX512_CNL 0
+#  define CV_CPU_FORCE_AVX512_CNL 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_CNL 0
+#  define CV_CPU_CALL_AVX512_CNL(fn, args)
+#  define CV_CPU_CALL_AVX512_CNL_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_CNL(fn, args, mode, ...)  CV_CPU_CALL_AVX512_CNL(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_CLX
+#  define CV_TRY_AVX512_CLX 1
+#  define CV_CPU_FORCE_AVX512_CLX 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_CLX 1
+#  define CV_CPU_CALL_AVX512_CLX(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_CLX_(fn, args) return (opt_AVX512_CLX::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_CLX
+#  define CV_TRY_AVX512_CLX 1
+#  define CV_CPU_FORCE_AVX512_CLX 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_CLX (cv::checkHardwareSupport(CV_CPU_AVX512_CLX))
+#  define CV_CPU_CALL_AVX512_CLX(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CLX) return (opt_AVX512_CLX::fn args)
+#  define CV_CPU_CALL_AVX512_CLX_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CLX) return (opt_AVX512_CLX::fn args)
+#else
+#  define CV_TRY_AVX512_CLX 0
+#  define CV_CPU_FORCE_AVX512_CLX 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_CLX 0
+#  define CV_CPU_CALL_AVX512_CLX(fn, args)
+#  define CV_CPU_CALL_AVX512_CLX_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_CLX(fn, args, mode, ...)  CV_CPU_CALL_AVX512_CLX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_ICL
+#  define CV_TRY_AVX512_ICL 1
+#  define CV_CPU_FORCE_AVX512_ICL 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_ICL 1
+#  define CV_CPU_CALL_AVX512_ICL(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_ICL_(fn, args) return (opt_AVX512_ICL::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_ICL
+#  define CV_TRY_AVX512_ICL 1
+#  define CV_CPU_FORCE_AVX512_ICL 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_ICL (cv::checkHardwareSupport(CV_CPU_AVX512_ICL))
+#  define CV_CPU_CALL_AVX512_ICL(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_ICL) return (opt_AVX512_ICL::fn args)
+#  define CV_CPU_CALL_AVX512_ICL_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_ICL) return (opt_AVX512_ICL::fn args)
+#else
+#  define CV_TRY_AVX512_ICL 0
+#  define CV_CPU_FORCE_AVX512_ICL 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_ICL 0
+#  define CV_CPU_CALL_AVX512_ICL(fn, args)
+#  define CV_CPU_CALL_AVX512_ICL_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_ICL(fn, args, mode, ...)  CV_CPU_CALL_AVX512_ICL(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_NEON
+#  define CV_TRY_NEON 1
+#  define CV_CPU_FORCE_NEON 1
+#  define CV_CPU_HAS_SUPPORT_NEON 1
+#  define CV_CPU_CALL_NEON(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_NEON_(fn, args) return (opt_NEON::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_NEON
+#  define CV_TRY_NEON 1
+#  define CV_CPU_FORCE_NEON 0
+#  define CV_CPU_HAS_SUPPORT_NEON (cv::checkHardwareSupport(CV_CPU_NEON))
+#  define CV_CPU_CALL_NEON(fn, args) if (CV_CPU_HAS_SUPPORT_NEON) return (opt_NEON::fn args)
+#  define CV_CPU_CALL_NEON_(fn, args) if (CV_CPU_HAS_SUPPORT_NEON) return (opt_NEON::fn args)
+#else
+#  define CV_TRY_NEON 0
+#  define CV_CPU_FORCE_NEON 0
+#  define CV_CPU_HAS_SUPPORT_NEON 0
+#  define CV_CPU_CALL_NEON(fn, args)
+#  define CV_CPU_CALL_NEON_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_NEON(fn, args, mode, ...)  CV_CPU_CALL_NEON(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_NEON_DOTPROD
+#  define CV_TRY_NEON_DOTPROD 1
+#  define CV_CPU_FORCE_NEON_DOTPROD 1
+#  define CV_CPU_HAS_SUPPORT_NEON_DOTPROD 1
+#  define CV_CPU_CALL_NEON_DOTPROD(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_NEON_DOTPROD_(fn, args) return (opt_NEON_DOTPROD::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_NEON_DOTPROD
+#  define CV_TRY_NEON_DOTPROD 1
+#  define CV_CPU_FORCE_NEON_DOTPROD 0
+#  define CV_CPU_HAS_SUPPORT_NEON_DOTPROD (cv::checkHardwareSupport(CV_CPU_NEON_DOTPROD))
+#  define CV_CPU_CALL_NEON_DOTPROD(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_DOTPROD) return (opt_NEON_DOTPROD::fn args)
+#  define CV_CPU_CALL_NEON_DOTPROD_(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_DOTPROD) return (opt_NEON_DOTPROD::fn args)
+#else
+#  define CV_TRY_NEON_DOTPROD 0
+#  define CV_CPU_FORCE_NEON_DOTPROD 0
+#  define CV_CPU_HAS_SUPPORT_NEON_DOTPROD 0
+#  define CV_CPU_CALL_NEON_DOTPROD(fn, args)
+#  define CV_CPU_CALL_NEON_DOTPROD_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_NEON_DOTPROD(fn, args, mode, ...)  CV_CPU_CALL_NEON_DOTPROD(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_NEON_FP16
+#  define CV_TRY_NEON_FP16 1
+#  define CV_CPU_FORCE_NEON_FP16 1
+#  define CV_CPU_HAS_SUPPORT_NEON_FP16 1
+#  define CV_CPU_CALL_NEON_FP16(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_NEON_FP16_(fn, args) return (opt_NEON_FP16::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_NEON_FP16
+#  define CV_TRY_NEON_FP16 1
+#  define CV_CPU_FORCE_NEON_FP16 0
+#  define CV_CPU_HAS_SUPPORT_NEON_FP16 (cv::checkHardwareSupport(CV_CPU_NEON_FP16))
+#  define CV_CPU_CALL_NEON_FP16(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_FP16) return (opt_NEON_FP16::fn args)
+#  define CV_CPU_CALL_NEON_FP16_(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_FP16) return (opt_NEON_FP16::fn args)
+#else
+#  define CV_TRY_NEON_FP16 0
+#  define CV_CPU_FORCE_NEON_FP16 0
+#  define CV_CPU_HAS_SUPPORT_NEON_FP16 0
+#  define CV_CPU_CALL_NEON_FP16(fn, args)
+#  define CV_CPU_CALL_NEON_FP16_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_NEON_FP16(fn, args, mode, ...)  CV_CPU_CALL_NEON_FP16(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_NEON_BF16
+#  define CV_TRY_NEON_BF16 1
+#  define CV_CPU_FORCE_NEON_BF16 1
+#  define CV_CPU_HAS_SUPPORT_NEON_BF16 1
+#  define CV_CPU_CALL_NEON_BF16(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_NEON_BF16_(fn, args) return (opt_NEON_BF16::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_NEON_BF16
+#  define CV_TRY_NEON_BF16 1
+#  define CV_CPU_FORCE_NEON_BF16 0
+#  define CV_CPU_HAS_SUPPORT_NEON_BF16 (cv::checkHardwareSupport(CV_CPU_NEON_BF16))
+#  define CV_CPU_CALL_NEON_BF16(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_BF16) return (opt_NEON_BF16::fn args)
+#  define CV_CPU_CALL_NEON_BF16_(fn, args) if (CV_CPU_HAS_SUPPORT_NEON_BF16) return (opt_NEON_BF16::fn args)
+#else
+#  define CV_TRY_NEON_BF16 0
+#  define CV_CPU_FORCE_NEON_BF16 0
+#  define CV_CPU_HAS_SUPPORT_NEON_BF16 0
+#  define CV_CPU_CALL_NEON_BF16(fn, args)
+#  define CV_CPU_CALL_NEON_BF16_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_NEON_BF16(fn, args, mode, ...)  CV_CPU_CALL_NEON_BF16(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_MSA
+#  define CV_TRY_MSA 1
+#  define CV_CPU_FORCE_MSA 1
+#  define CV_CPU_HAS_SUPPORT_MSA 1
+#  define CV_CPU_CALL_MSA(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_MSA_(fn, args) return (opt_MSA::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_MSA
+#  define CV_TRY_MSA 1
+#  define CV_CPU_FORCE_MSA 0
+#  define CV_CPU_HAS_SUPPORT_MSA (cv::checkHardwareSupport(CV_CPU_MSA))
+#  define CV_CPU_CALL_MSA(fn, args) if (CV_CPU_HAS_SUPPORT_MSA) return (opt_MSA::fn args)
+#  define CV_CPU_CALL_MSA_(fn, args) if (CV_CPU_HAS_SUPPORT_MSA) return (opt_MSA::fn args)
+#else
+#  define CV_TRY_MSA 0
+#  define CV_CPU_FORCE_MSA 0
+#  define CV_CPU_HAS_SUPPORT_MSA 0
+#  define CV_CPU_CALL_MSA(fn, args)
+#  define CV_CPU_CALL_MSA_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_MSA(fn, args, mode, ...)  CV_CPU_CALL_MSA(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_VSX
+#  define CV_TRY_VSX 1
+#  define CV_CPU_FORCE_VSX 1
+#  define CV_CPU_HAS_SUPPORT_VSX 1
+#  define CV_CPU_CALL_VSX(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_VSX_(fn, args) return (opt_VSX::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_VSX
+#  define CV_TRY_VSX 1
+#  define CV_CPU_FORCE_VSX 0
+#  define CV_CPU_HAS_SUPPORT_VSX (cv::checkHardwareSupport(CV_CPU_VSX))
+#  define CV_CPU_CALL_VSX(fn, args) if (CV_CPU_HAS_SUPPORT_VSX) return (opt_VSX::fn args)
+#  define CV_CPU_CALL_VSX_(fn, args) if (CV_CPU_HAS_SUPPORT_VSX) return (opt_VSX::fn args)
+#else
+#  define CV_TRY_VSX 0
+#  define CV_CPU_FORCE_VSX 0
+#  define CV_CPU_HAS_SUPPORT_VSX 0
+#  define CV_CPU_CALL_VSX(fn, args)
+#  define CV_CPU_CALL_VSX_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_VSX(fn, args, mode, ...)  CV_CPU_CALL_VSX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_VSX3
+#  define CV_TRY_VSX3 1
+#  define CV_CPU_FORCE_VSX3 1
+#  define CV_CPU_HAS_SUPPORT_VSX3 1
+#  define CV_CPU_CALL_VSX3(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_VSX3_(fn, args) return (opt_VSX3::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_VSX3
+#  define CV_TRY_VSX3 1
+#  define CV_CPU_FORCE_VSX3 0
+#  define CV_CPU_HAS_SUPPORT_VSX3 (cv::checkHardwareSupport(CV_CPU_VSX3))
+#  define CV_CPU_CALL_VSX3(fn, args) if (CV_CPU_HAS_SUPPORT_VSX3) return (opt_VSX3::fn args)
+#  define CV_CPU_CALL_VSX3_(fn, args) if (CV_CPU_HAS_SUPPORT_VSX3) return (opt_VSX3::fn args)
+#else
+#  define CV_TRY_VSX3 0
+#  define CV_CPU_FORCE_VSX3 0
+#  define CV_CPU_HAS_SUPPORT_VSX3 0
+#  define CV_CPU_CALL_VSX3(fn, args)
+#  define CV_CPU_CALL_VSX3_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_VSX3(fn, args, mode, ...)  CV_CPU_CALL_VSX3(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_RVV
+#  define CV_TRY_RVV 1
+#  define CV_CPU_FORCE_RVV 1
+#  define CV_CPU_HAS_SUPPORT_RVV 1
+#  define CV_CPU_CALL_RVV(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_RVV_(fn, args) return (opt_RVV::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_RVV
+#  define CV_TRY_RVV 1
+#  define CV_CPU_FORCE_RVV 0
+#  define CV_CPU_HAS_SUPPORT_RVV (cv::checkHardwareSupport(CV_CPU_RVV))
+#  define CV_CPU_CALL_RVV(fn, args) if (CV_CPU_HAS_SUPPORT_RVV) return (opt_RVV::fn args)
+#  define CV_CPU_CALL_RVV_(fn, args) if (CV_CPU_HAS_SUPPORT_RVV) return (opt_RVV::fn args)
+#else
+#  define CV_TRY_RVV 0
+#  define CV_CPU_FORCE_RVV 0
+#  define CV_CPU_HAS_SUPPORT_RVV 0
+#  define CV_CPU_CALL_RVV(fn, args)
+#  define CV_CPU_CALL_RVV_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_RVV(fn, args, mode, ...)  CV_CPU_CALL_RVV(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_LSX
+#  define CV_TRY_LSX 1
+#  define CV_CPU_FORCE_LSX 1
+#  define CV_CPU_HAS_SUPPORT_LSX 1
+#  define CV_CPU_CALL_LSX(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_LSX_(fn, args) return (opt_LSX::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_LSX
+#  define CV_TRY_LSX 1
+#  define CV_CPU_FORCE_LSX 0
+#  define CV_CPU_HAS_SUPPORT_LSX (cv::checkHardwareSupport(CV_CPU_LSX))
+#  define CV_CPU_CALL_LSX(fn, args) if (CV_CPU_HAS_SUPPORT_LSX) return (opt_LSX::fn args)
+#  define CV_CPU_CALL_LSX_(fn, args) if (CV_CPU_HAS_SUPPORT_LSX) return (opt_LSX::fn args)
+#else
+#  define CV_TRY_LSX 0
+#  define CV_CPU_FORCE_LSX 0
+#  define CV_CPU_HAS_SUPPORT_LSX 0
+#  define CV_CPU_CALL_LSX(fn, args)
+#  define CV_CPU_CALL_LSX_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_LSX(fn, args, mode, ...)  CV_CPU_CALL_LSX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_LASX
+#  define CV_TRY_LASX 1
+#  define CV_CPU_FORCE_LASX 1
+#  define CV_CPU_HAS_SUPPORT_LASX 1
+#  define CV_CPU_CALL_LASX(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_LASX_(fn, args) return (opt_LASX::fn args)
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_LASX
+#  define CV_TRY_LASX 1
+#  define CV_CPU_FORCE_LASX 0
+#  define CV_CPU_HAS_SUPPORT_LASX (cv::checkHardwareSupport(CV_CPU_LASX))
+#  define CV_CPU_CALL_LASX(fn, args) if (CV_CPU_HAS_SUPPORT_LASX) return (opt_LASX::fn args)
+#  define CV_CPU_CALL_LASX_(fn, args) if (CV_CPU_HAS_SUPPORT_LASX) return (opt_LASX::fn args)
+#else
+#  define CV_TRY_LASX 0
+#  define CV_CPU_FORCE_LASX 0
+#  define CV_CPU_HAS_SUPPORT_LASX 0
+#  define CV_CPU_CALL_LASX(fn, args)
+#  define CV_CPU_CALL_LASX_(fn, args)
+#endif
+#define __CV_CPU_DISPATCH_CHAIN_LASX(fn, args, mode, ...)  CV_CPU_CALL_LASX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+
+#define CV_CPU_CALL_BASELINE(fn, args) return (cpu_baseline::fn args)
+#define __CV_CPU_DISPATCH_CHAIN_BASELINE(fn, args, mode, ...)  CV_CPU_CALL_BASELINE(fn, args) /* last in sequence */

GameAssist/GameAssist/include/cv2/opencv2/core/cvdef.h

@@ -0,0 +1,948 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_CVDEF_H
+#define OPENCV_CORE_CVDEF_H
+
+#include "opencv2/core/version.hpp"
+
+//! @addtogroup core_utils
+//! @{
+
+#ifdef OPENCV_INCLUDE_PORT_FILE  // User-provided header file with custom platform configuration
+#include OPENCV_INCLUDE_PORT_FILE
+#endif
+
+#if !defined CV_DOXYGEN && !defined CV_IGNORE_DEBUG_BUILD_GUARD
+#if (defined(_MSC_VER) && (defined(DEBUG) || defined(_DEBUG))) || \
+    (defined(_GLIBCXX_DEBUG) || defined(_GLIBCXX_DEBUG_PEDANTIC))
+// Guard to prevent using of binary incompatible binaries / runtimes
+// https://github.com/opencv/opencv/pull/9161
+#define CV__DEBUG_NS_BEGIN namespace debug_build_guard {
+#define CV__DEBUG_NS_END }
+namespace cv { namespace debug_build_guard { } using namespace debug_build_guard; }
+#endif
+#endif
+
+#ifndef CV__DEBUG_NS_BEGIN
+#define CV__DEBUG_NS_BEGIN
+#define CV__DEBUG_NS_END
+#endif
+
+
+#ifdef __OPENCV_BUILD
+#include "cvconfig.h"
+#endif
+
+#ifndef __CV_EXPAND
+#define __CV_EXPAND(x) x
+#endif
+
+#ifndef __CV_CAT
+#define __CV_CAT__(x, y) x ## y
+#define __CV_CAT_(x, y) __CV_CAT__(x, y)
+#define __CV_CAT(x, y) __CV_CAT_(x, y)
+#endif
+
+#define __CV_VA_NUM_ARGS_HELPER(_1, _2, _3, _4, _5, _6, _7, _8, _9, _10, N, ...) N
+#define __CV_VA_NUM_ARGS(...) __CV_EXPAND(__CV_VA_NUM_ARGS_HELPER(__VA_ARGS__, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0))
+
+#ifdef CV_Func
+// keep current value (through OpenCV port file)
+#elif defined __GNUC__ || (defined (__cpluscplus) && (__cpluscplus >= 201103))
+#define CV_Func __func__
+#elif defined __clang__ && (__clang_minor__ * 100 + __clang_major__ >= 305)
+#define CV_Func __func__
+#elif defined(__STDC_VERSION__) && (__STDC_VERSION >= 199901)
+#define CV_Func __func__
+#elif defined _MSC_VER
+#define CV_Func __FUNCTION__
+#elif defined(__INTEL_COMPILER) && (_INTEL_COMPILER >= 600)
+#define CV_Func __FUNCTION__
+#elif defined __IBMCPP__ && __IBMCPP__ >=500
+#define CV_Func __FUNCTION__
+#elif defined __BORLAND__ && (__BORLANDC__ >= 0x550)
+#define CV_Func __FUNC__
+#else
+#define CV_Func "<unknown>"
+#endif
+
+//! @cond IGNORED
+
+//////////////// static assert /////////////////
+#define CVAUX_CONCAT_EXP(a, b) a##b
+#define CVAUX_CONCAT(a, b) CVAUX_CONCAT_EXP(a,b)
+
+#if defined(__clang__)
+#  ifndef __has_extension
+#    define __has_extension __has_feature /* compatibility, for older versions of clang */
+#  endif
+#  if __has_extension(cxx_static_assert)
+#    define CV_StaticAssert(condition, reason)    static_assert((condition), reason " " #condition)
+#  elif __has_extension(c_static_assert)
+#    define CV_StaticAssert(condition, reason)    _Static_assert((condition), reason " " #condition)
+#  endif
+#elif defined(__GNUC__)
+#  if (defined(__GXX_EXPERIMENTAL_CXX0X__) || __cplusplus >= 201103L)
+#    define CV_StaticAssert(condition, reason)    static_assert((condition), reason " " #condition)
+#  endif
+#elif defined(_MSC_VER)
+#  if _MSC_VER >= 1600 /* MSVC 10 */
+#    define CV_StaticAssert(condition, reason)    static_assert((condition), reason " " #condition)
+#  endif
+#endif
+#ifndef CV_StaticAssert
+#  if !defined(__clang__) && defined(__GNUC__) && (__GNUC__*100 + __GNUC_MINOR__ > 302)
+#    define CV_StaticAssert(condition, reason) ({ extern int __attribute__((error("CV_StaticAssert: " reason " " #condition))) CV_StaticAssert(); ((condition) ? 0 : CV_StaticAssert()); })
+#  else
+namespace cv {
+     template <bool x> struct CV_StaticAssert_failed;
+     template <> struct CV_StaticAssert_failed<true> { enum { val = 1 }; };
+     template<int x> struct CV_StaticAssert_test {};
+}
+#    define CV_StaticAssert(condition, reason)\
+       typedef cv::CV_StaticAssert_test< sizeof(cv::CV_StaticAssert_failed< static_cast<bool>(condition) >) > CVAUX_CONCAT(CV_StaticAssert_failed_at_, __LINE__)
+#  endif
+#endif
+
+// Suppress warning "-Wdeprecated-declarations" / C4996
+#if defined(_MSC_VER)
+    #define CV_DO_PRAGMA(x) __pragma(x)
+#elif defined(__GNUC__)
+    #define CV_DO_PRAGMA(x) _Pragma (#x)
+#else
+    #define CV_DO_PRAGMA(x)
+#endif
+
+#ifdef _MSC_VER
+#define CV_SUPPRESS_DEPRECATED_START \
+    CV_DO_PRAGMA(warning(push)) \
+    CV_DO_PRAGMA(warning(disable: 4996))
+#define CV_SUPPRESS_DEPRECATED_END CV_DO_PRAGMA(warning(pop))
+#elif defined (__clang__) || ((__GNUC__)  && (__GNUC__*100 + __GNUC_MINOR__ > 405))
+#define CV_SUPPRESS_DEPRECATED_START \
+    CV_DO_PRAGMA(GCC diagnostic push) \
+    CV_DO_PRAGMA(GCC diagnostic ignored "-Wdeprecated-declarations")
+#define CV_SUPPRESS_DEPRECATED_END CV_DO_PRAGMA(GCC diagnostic pop)
+#else
+#define CV_SUPPRESS_DEPRECATED_START
+#define CV_SUPPRESS_DEPRECATED_END
+#endif
+
+#define CV_UNUSED(name) (void)name
+
+//! @endcond
+
+// undef problematic defines sometimes defined by system headers (windows.h in particular)
+#undef small
+#undef min
+#undef max
+#undef abs
+#undef Complex
+
+#if defined __cplusplus
+#include <limits>
+#else
+#include <limits.h>
+#endif
+
+#include "opencv2/core/hal/interface.h"
+
+#if defined __ICL
+#  define CV_ICC   __ICL
+#elif defined __ICC
+#  define CV_ICC   __ICC
+#elif defined __ECL
+#  define CV_ICC   __ECL
+#elif defined __ECC
+#  define CV_ICC   __ECC
+#elif defined __INTEL_COMPILER
+#  define CV_ICC   __INTEL_COMPILER
+#endif
+
+#if defined _WIN32
+#  define CV_CDECL __cdecl
+#  define CV_STDCALL __stdcall
+#else
+#  define CV_CDECL
+#  define CV_STDCALL
+#endif
+
+#ifndef CV_INLINE
+#  if defined __cplusplus
+#    define CV_INLINE static inline
+#  elif defined _MSC_VER
+#    define CV_INLINE __inline
+#  else
+#    define CV_INLINE static
+#  endif
+#endif
+
+#ifndef CV_ALWAYS_INLINE
+#if defined(__GNUC__) && (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 1))
+#define CV_ALWAYS_INLINE inline __attribute__((always_inline))
+#elif defined(_MSC_VER)
+#define CV_ALWAYS_INLINE __forceinline
+#else
+#define CV_ALWAYS_INLINE inline
+#endif
+#endif
+
+#if defined CV_DISABLE_OPTIMIZATION || (defined CV_ICC && !defined CV_ENABLE_UNROLLED)
+#  define CV_ENABLE_UNROLLED 0
+#else
+#  define CV_ENABLE_UNROLLED 1
+#endif
+
+#ifdef __GNUC__
+#  define CV_DECL_ALIGNED(x) __attribute__ ((aligned (x)))
+#elif defined _MSC_VER
+#  define CV_DECL_ALIGNED(x) __declspec(align(x))
+#else
+#  define CV_DECL_ALIGNED(x)
+#endif
+
+/* CPU features and intrinsics support */
+#define CV_CPU_NONE             0
+#define CV_CPU_MMX              1
+#define CV_CPU_SSE              2
+#define CV_CPU_SSE2             3
+#define CV_CPU_SSE3             4
+#define CV_CPU_SSSE3            5
+#define CV_CPU_SSE4_1           6
+#define CV_CPU_SSE4_2           7
+#define CV_CPU_POPCNT           8
+#define CV_CPU_FP16             9
+#define CV_CPU_AVX              10
+#define CV_CPU_AVX2             11
+#define CV_CPU_FMA3             12
+
+#define CV_CPU_AVX_512F         13
+#define CV_CPU_AVX_512BW        14
+#define CV_CPU_AVX_512CD        15
+#define CV_CPU_AVX_512DQ        16
+#define CV_CPU_AVX_512ER        17
+#define CV_CPU_AVX_512IFMA512   18 // deprecated
+#define CV_CPU_AVX_512IFMA      18
+#define CV_CPU_AVX_512PF        19
+#define CV_CPU_AVX_512VBMI      20
+#define CV_CPU_AVX_512VL        21
+#define CV_CPU_AVX_512VBMI2     22
+#define CV_CPU_AVX_512VNNI      23
+#define CV_CPU_AVX_512BITALG    24
+#define CV_CPU_AVX_512VPOPCNTDQ 25
+#define CV_CPU_AVX_5124VNNIW    26
+#define CV_CPU_AVX_5124FMAPS    27
+
+#define CV_CPU_NEON             100
+#define CV_CPU_NEON_DOTPROD     101
+#define CV_CPU_NEON_FP16        102
+#define CV_CPU_NEON_BF16        103
+
+#define CV_CPU_MSA              150
+
+#define CV_CPU_RISCVV           170
+
+#define CV_CPU_VSX              200
+#define CV_CPU_VSX3             201
+
+#define CV_CPU_RVV              210
+
+#define CV_CPU_LSX              230
+#define CV_CPU_LASX             231
+
+// CPU features groups
+#define CV_CPU_AVX512_SKX       256
+#define CV_CPU_AVX512_COMMON    257
+#define CV_CPU_AVX512_KNL       258
+#define CV_CPU_AVX512_KNM       259
+#define CV_CPU_AVX512_CNL       260
+#define CV_CPU_AVX512_CLX       261
+#define CV_CPU_AVX512_ICL       262
+
+// when adding to this list remember to update the following enum
+#define CV_HARDWARE_MAX_FEATURE 512
+
+/** @brief Available CPU features.
+*/
+enum CpuFeatures {
+    CPU_MMX             = 1,
+    CPU_SSE             = 2,
+    CPU_SSE2            = 3,
+    CPU_SSE3            = 4,
+    CPU_SSSE3           = 5,
+    CPU_SSE4_1          = 6,
+    CPU_SSE4_2          = 7,
+    CPU_POPCNT          = 8,
+    CPU_FP16            = 9,
+    CPU_AVX             = 10,
+    CPU_AVX2            = 11,
+    CPU_FMA3            = 12,
+
+    CPU_AVX_512F        = 13,
+    CPU_AVX_512BW       = 14,
+    CPU_AVX_512CD       = 15,
+    CPU_AVX_512DQ       = 16,
+    CPU_AVX_512ER       = 17,
+    CPU_AVX_512IFMA512  = 18, // deprecated
+    CPU_AVX_512IFMA     = 18,
+    CPU_AVX_512PF       = 19,
+    CPU_AVX_512VBMI     = 20,
+    CPU_AVX_512VL       = 21,
+    CPU_AVX_512VBMI2    = 22,
+    CPU_AVX_512VNNI     = 23,
+    CPU_AVX_512BITALG   = 24,
+    CPU_AVX_512VPOPCNTDQ= 25,
+    CPU_AVX_5124VNNIW   = 26,
+    CPU_AVX_5124FMAPS   = 27,
+
+    CPU_NEON            = 100,
+    CPU_NEON_DOTPROD    = 101,
+    CPU_NEON_FP16       = 102,
+    CPU_NEON_BF16       = 103,
+
+    CPU_MSA             = 150,
+
+    CPU_RISCVV          = 170,
+
+    CPU_VSX             = 200,
+    CPU_VSX3            = 201,
+
+    CPU_RVV             = 210,
+
+    CPU_LSX             = 230,
+    CPU_LASX            = 231,
+
+    CPU_AVX512_SKX      = 256, //!< Skylake-X with AVX-512F/CD/BW/DQ/VL
+    CPU_AVX512_COMMON   = 257, //!< Common instructions AVX-512F/CD for all CPUs that support AVX-512
+    CPU_AVX512_KNL      = 258, //!< Knights Landing with AVX-512F/CD/ER/PF
+    CPU_AVX512_KNM      = 259, //!< Knights Mill with AVX-512F/CD/ER/PF/4FMAPS/4VNNIW/VPOPCNTDQ
+    CPU_AVX512_CNL      = 260, //!< Cannon Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI
+    CPU_AVX512_CLX      = 261, //!< Cascade Lake with AVX-512F/CD/BW/DQ/VL/VNNI
+    CPU_AVX512_ICL      = 262, //!< Ice Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI/VNNI/VBMI2/BITALG/VPOPCNTDQ
+
+    CPU_MAX_FEATURE     = 512  // see CV_HARDWARE_MAX_FEATURE
+};
+
+
+#include "cv_cpu_dispatch.h"
+
+#if !defined(CV_STRONG_ALIGNMENT) && defined(__arm__) && !(defined(__aarch64__) || defined(_M_ARM64))
+// int*, int64* should be propertly aligned pointers on ARMv7
+#define CV_STRONG_ALIGNMENT 1
+#endif
+#if !defined(CV_STRONG_ALIGNMENT)
+#define CV_STRONG_ALIGNMENT 0
+#endif
+
+/* fundamental constants */
+#define CV_PI   3.1415926535897932384626433832795
+#define CV_2PI  6.283185307179586476925286766559
+#define CV_LOG2 0.69314718055994530941723212145818
+
+#if defined __ARM_FP16_FORMAT_IEEE \
+    && !defined __CUDACC__
+#  define CV_FP16_TYPE 1
+#else
+#  define CV_FP16_TYPE 0
+#endif
+
+typedef union Cv16suf
+{
+    short i;
+    ushort u;
+#if CV_FP16_TYPE
+    __fp16 h;
+#endif
+}
+Cv16suf;
+
+typedef union Cv32suf
+{
+    int i;
+    unsigned u;
+    float f;
+}
+Cv32suf;
+
+typedef union Cv64suf
+{
+    int64 i;
+    uint64 u;
+    double f;
+}
+Cv64suf;
+
+#ifndef OPENCV_ABI_COMPATIBILITY
+#define OPENCV_ABI_COMPATIBILITY 400
+#endif
+
+#ifdef __OPENCV_BUILD
+#  define DISABLE_OPENCV_3_COMPATIBILITY
+#  define OPENCV_DISABLE_DEPRECATED_COMPATIBILITY
+#endif
+
+#ifndef CV_EXPORTS
+# if (defined _WIN32 || defined WINCE || defined __CYGWIN__) && defined(CVAPI_EXPORTS)
+#   define CV_EXPORTS __declspec(dllexport)
+# elif defined __GNUC__ && __GNUC__ >= 4 && (defined(CVAPI_EXPORTS) || defined(__APPLE__))
+#   define CV_EXPORTS __attribute__ ((visibility ("default")))
+# endif
+#endif
+
+#ifndef CV_EXPORTS
+# define CV_EXPORTS
+#endif
+
+#ifdef _MSC_VER
+#   define CV_EXPORTS_TEMPLATE
+#else
+#   define CV_EXPORTS_TEMPLATE CV_EXPORTS
+#endif
+
+#ifndef CV_DEPRECATED
+#  if defined(__GNUC__)
+#    define CV_DEPRECATED __attribute__ ((deprecated))
+#  elif defined(_MSC_VER)
+#    define CV_DEPRECATED __declspec(deprecated)
+#  else
+#    define CV_DEPRECATED
+#  endif
+#endif
+
+#ifndef CV_DEPRECATED_EXTERNAL
+#  if defined(__OPENCV_BUILD)
+#    define CV_DEPRECATED_EXTERNAL /* nothing */
+#  else
+#    define CV_DEPRECATED_EXTERNAL CV_DEPRECATED
+#  endif
+#endif
+
+
+#ifndef CV_EXTERN_C
+#  ifdef __cplusplus
+#    define CV_EXTERN_C extern "C"
+#  else
+#    define CV_EXTERN_C
+#  endif
+#endif
+
+/* special informative macros for wrapper generators */
+#define CV_EXPORTS_W CV_EXPORTS
+#define CV_EXPORTS_W_SIMPLE CV_EXPORTS
+#define CV_EXPORTS_AS(synonym) CV_EXPORTS
+#define CV_EXPORTS_W_MAP CV_EXPORTS
+#define CV_EXPORTS_W_PARAMS CV_EXPORTS
+#define CV_IN_OUT
+#define CV_OUT
+#define CV_PROP
+#define CV_PROP_RW
+#define CV_ND // Indicates that input data should be parsed into Mat without channels
+#define CV_WRAP
+#define CV_WRAP_AS(synonym)
+#define CV_WRAP_MAPPABLE(mappable)
+#define CV_WRAP_PHANTOM(phantom_header)
+#define CV_WRAP_DEFAULT(val)
+/* Indicates that the function parameter has filesystem path semantic */
+#define CV_WRAP_FILE_PATH
+
+/****************************************************************************************\
+*                                  Matrix type (Mat)                                     *
+\****************************************************************************************/
+
+#define CV_MAX_DIM              32
+#define CV_MAT_CN_MASK          ((CV_CN_MAX - 1) << CV_CN_SHIFT)
+#define CV_MAT_CN(flags)        ((((flags) & CV_MAT_CN_MASK) >> CV_CN_SHIFT) + 1)
+#define CV_MAT_TYPE_MASK        (CV_DEPTH_MAX*CV_CN_MAX - 1)
+#define CV_MAT_TYPE(flags)      ((flags) & CV_MAT_TYPE_MASK)
+#define CV_MAT_CONT_FLAG_SHIFT  14
+#define CV_MAT_CONT_FLAG        (1 << CV_MAT_CONT_FLAG_SHIFT)
+#define CV_IS_MAT_CONT(flags)   ((flags) & CV_MAT_CONT_FLAG)
+#define CV_IS_CONT_MAT          CV_IS_MAT_CONT
+#define CV_SUBMAT_FLAG_SHIFT    15
+#define CV_SUBMAT_FLAG          (1 << CV_SUBMAT_FLAG_SHIFT)
+#define CV_IS_SUBMAT(flags)     ((flags) & CV_MAT_SUBMAT_FLAG)
+
+/** Size of each channel item,
+   0x28442211 = 0010 1000 0100 0100 0010 0010 0001 0001 ~ array of sizeof(arr_type_elem) */
+#define CV_ELEM_SIZE1(type) ((0x28442211 >> CV_MAT_DEPTH(type)*4) & 15)
+
+#define CV_ELEM_SIZE(type) (CV_MAT_CN(type)*CV_ELEM_SIZE1(type))
+
+#ifndef MIN
+#  define MIN(a,b)  ((a) > (b) ? (b) : (a))
+#endif
+
+#ifndef MAX
+#  define MAX(a,b)  ((a) < (b) ? (b) : (a))
+#endif
+
+/** min & max without jumps */
+#define CV_IMIN(a, b)  ((a) ^ (((a)^(b)) & (((a) < (b)) - 1)))
+#define CV_IMAX(a, b)  ((a) ^ (((a)^(b)) & (((a) > (b)) - 1)))
+#define CV_SWAP(a,b,t) ((t) = (a), (a) = (b), (b) = (t))
+#define CV_CMP(a,b)    (((a) > (b)) - ((a) < (b)))
+#define CV_SIGN(a)     CV_CMP((a),0)
+
+///////////////////////////////////////// Enum operators ///////////////////////////////////////
+
+/**
+
+Provides compatibility operators for both classical and C++11 enum classes,
+as well as exposing the C++11 enum class members for backwards compatibility
+
+@code
+    // Provides operators required for flag enums
+    CV_ENUM_FLAGS(AccessFlag)
+
+    // Exposes the listed members of the enum class AccessFlag to the current namespace
+    CV_ENUM_CLASS_EXPOSE(AccessFlag, ACCESS_READ [, ACCESS_WRITE [, ...] ]);
+@endcode
+*/
+
+#define __CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST)                                              \
+static const EnumType MEMBER_CONST = EnumType::MEMBER_CONST;                                          \
+
+#define __CV_ENUM_CLASS_EXPOSE_2(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_1(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_CLASS_EXPOSE_3(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_2(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_CLASS_EXPOSE_4(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_3(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_CLASS_EXPOSE_5(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_4(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_CLASS_EXPOSE_6(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_5(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_CLASS_EXPOSE_7(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_6(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_CLASS_EXPOSE_8(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_7(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_CLASS_EXPOSE_9(EnumType, MEMBER_CONST, ...)                                         \
+__CV_ENUM_CLASS_EXPOSE_1(EnumType, MEMBER_CONST);                                                     \
+__CV_EXPAND(__CV_ENUM_CLASS_EXPOSE_8(EnumType, __VA_ARGS__));                                         \
+
+#define __CV_ENUM_FLAGS_LOGICAL_NOT(EnumType)                                                         \
+static inline bool operator!(const EnumType& val)                                                     \
+{                                                                                                     \
+    typedef std::underlying_type<EnumType>::type UnderlyingType;                                      \
+    return !static_cast<UnderlyingType>(val);                                                         \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_LOGICAL_NOT_EQ(Arg1Type, Arg2Type)                                            \
+static inline bool operator!=(const Arg1Type& a, const Arg2Type& b)                                   \
+{                                                                                                     \
+    return static_cast<int>(a) != static_cast<int>(b);                                                \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_LOGICAL_EQ(Arg1Type, Arg2Type)                                                \
+static inline bool operator==(const Arg1Type& a, const Arg2Type& b)                                   \
+{                                                                                                     \
+    return static_cast<int>(a) == static_cast<int>(b);                                                \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_BITWISE_NOT(EnumType)                                                         \
+static inline EnumType operator~(const EnumType& val)                                                 \
+{                                                                                                     \
+    typedef std::underlying_type<EnumType>::type UnderlyingType;                                      \
+    return static_cast<EnumType>(~static_cast<UnderlyingType>(val));                                  \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_BITWISE_OR(EnumType, Arg1Type, Arg2Type)                                      \
+static inline EnumType operator|(const Arg1Type& a, const Arg2Type& b)                                \
+{                                                                                                     \
+    typedef std::underlying_type<EnumType>::type UnderlyingType;                                      \
+    return static_cast<EnumType>(static_cast<UnderlyingType>(a) | static_cast<UnderlyingType>(b));    \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_BITWISE_AND(EnumType, Arg1Type, Arg2Type)                                     \
+static inline EnumType operator&(const Arg1Type& a, const Arg2Type& b)                                \
+{                                                                                                     \
+    typedef std::underlying_type<EnumType>::type UnderlyingType;                                      \
+    return static_cast<EnumType>(static_cast<UnderlyingType>(a) & static_cast<UnderlyingType>(b));    \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_BITWISE_XOR(EnumType, Arg1Type, Arg2Type)                                     \
+static inline EnumType operator^(const Arg1Type& a, const Arg2Type& b)                                \
+{                                                                                                     \
+    typedef std::underlying_type<EnumType>::type UnderlyingType;                                      \
+    return static_cast<EnumType>(static_cast<UnderlyingType>(a) ^ static_cast<UnderlyingType>(b));    \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_BITWISE_OR_EQ(EnumType, Arg1Type)                                             \
+static inline EnumType& operator|=(EnumType& _this, const Arg1Type& val)                              \
+{                                                                                                     \
+    _this = static_cast<EnumType>(static_cast<int>(_this) | static_cast<int>(val));                   \
+    return _this;                                                                                     \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_BITWISE_AND_EQ(EnumType, Arg1Type)                                            \
+static inline EnumType& operator&=(EnumType& _this, const Arg1Type& val)                              \
+{                                                                                                     \
+    _this = static_cast<EnumType>(static_cast<int>(_this) & static_cast<int>(val));                   \
+    return _this;                                                                                     \
+}                                                                                                     \
+
+#define __CV_ENUM_FLAGS_BITWISE_XOR_EQ(EnumType, Arg1Type)                                            \
+static inline EnumType& operator^=(EnumType& _this, const Arg1Type& val)                              \
+{                                                                                                     \
+    _this = static_cast<EnumType>(static_cast<int>(_this) ^ static_cast<int>(val));                   \
+    return _this;                                                                                     \
+}                                                                                                     \
+
+#define CV_ENUM_CLASS_EXPOSE(EnumType, ...)                                                           \
+__CV_EXPAND(__CV_CAT(__CV_ENUM_CLASS_EXPOSE_, __CV_VA_NUM_ARGS(__VA_ARGS__))(EnumType, __VA_ARGS__)); \
+
+#define CV_ENUM_FLAGS(EnumType)                                                                       \
+__CV_ENUM_FLAGS_LOGICAL_NOT      (EnumType)                                                           \
+__CV_ENUM_FLAGS_LOGICAL_EQ       (EnumType, int)                                                      \
+__CV_ENUM_FLAGS_LOGICAL_NOT_EQ   (EnumType, int)                                                      \
+                                                                                                      \
+__CV_ENUM_FLAGS_BITWISE_NOT      (EnumType)                                                           \
+__CV_ENUM_FLAGS_BITWISE_OR       (EnumType, EnumType, EnumType)                                       \
+__CV_ENUM_FLAGS_BITWISE_AND      (EnumType, EnumType, EnumType)                                       \
+__CV_ENUM_FLAGS_BITWISE_XOR      (EnumType, EnumType, EnumType)                                       \
+                                                                                                      \
+__CV_ENUM_FLAGS_BITWISE_OR_EQ    (EnumType, EnumType)                                                 \
+__CV_ENUM_FLAGS_BITWISE_AND_EQ   (EnumType, EnumType)                                                 \
+__CV_ENUM_FLAGS_BITWISE_XOR_EQ   (EnumType, EnumType)                                                 \
+
+/****************************************************************************************\
+*                                    static analysys                                     *
+\****************************************************************************************/
+
+// In practice, some macro are not processed correctly (noreturn is not detected).
+// We need to use simplified definition for them.
+#ifndef CV_STATIC_ANALYSIS
+# if defined(__KLOCWORK__) || defined(__clang_analyzer__) || defined(__COVERITY__)
+#   define CV_STATIC_ANALYSIS 1
+# endif
+#else
+# if defined(CV_STATIC_ANALYSIS) && !(__CV_CAT(1, CV_STATIC_ANALYSIS) == 1)  // defined and not empty
+#   if 0 == CV_STATIC_ANALYSIS
+#     undef CV_STATIC_ANALYSIS
+#   endif
+# endif
+#endif
+
+/****************************************************************************************\
+*                                    Thread sanitizer                                    *
+\****************************************************************************************/
+#ifndef CV_THREAD_SANITIZER
+# if defined(__has_feature)
+#   if __has_feature(thread_sanitizer)
+#     define CV_THREAD_SANITIZER
+#   endif
+# endif
+#endif
+
+/****************************************************************************************\
+*          exchange-add operation for atomic operations on reference counters            *
+\****************************************************************************************/
+
+#ifdef CV_XADD
+  // allow to use user-defined macro
+#elif defined __GNUC__ || defined __clang__
+#  if defined __clang__ && __clang_major__ >= 3 && !defined __ANDROID__ && !defined __EMSCRIPTEN__ && !defined(__CUDACC__)  && !defined __INTEL_COMPILER
+#    ifdef __ATOMIC_ACQ_REL
+#      define CV_XADD(addr, delta) __c11_atomic_fetch_add((_Atomic(int)*)(addr), delta, __ATOMIC_ACQ_REL)
+#    else
+#      define CV_XADD(addr, delta) __atomic_fetch_add((_Atomic(int)*)(addr), delta, 4)
+#    endif
+#  else
+#    if defined __ATOMIC_ACQ_REL && !defined __clang__
+       // version for gcc >= 4.7
+#      define CV_XADD(addr, delta) (int)__atomic_fetch_add((unsigned*)(addr), (unsigned)(delta), __ATOMIC_ACQ_REL)
+#    else
+#      define CV_XADD(addr, delta) (int)__sync_fetch_and_add((unsigned*)(addr), (unsigned)(delta))
+#    endif
+#  endif
+#elif defined _MSC_VER && !defined RC_INVOKED
+#  include <intrin.h>
+#  define CV_XADD(addr, delta) (int)_InterlockedExchangeAdd((long volatile*)addr, delta)
+#else
+  #ifdef OPENCV_FORCE_UNSAFE_XADD
+    CV_INLINE int CV_XADD(int* addr, int delta) { int tmp = *addr; *addr += delta; return tmp; }
+  #else
+    #error "OpenCV: can't define safe CV_XADD macro for current platform (unsupported). Define CV_XADD macro through custom port header (see OPENCV_INCLUDE_PORT_FILE)"
+  #endif
+#endif
+
+
+/****************************************************************************************\
+*                                  CV_NORETURN attribute                                 *
+\****************************************************************************************/
+
+#ifndef CV_NORETURN
+#  if defined(__GNUC__)
+#    define CV_NORETURN __attribute__((__noreturn__))
+#  elif defined(_MSC_VER) && (_MSC_VER >= 1300)
+#    define CV_NORETURN __declspec(noreturn)
+#  else
+#    define CV_NORETURN /* nothing by default */
+#  endif
+#endif
+
+/****************************************************************************************\
+*                       CV_NODISCARD_STD attribute (C++17)                               *
+* encourages the compiler to issue a warning if the return value is discarded            *
+\****************************************************************************************/
+#ifndef CV_NODISCARD_STD
+#  ifndef __has_cpp_attribute
+//   workaround preprocessor non-compliance https://reviews.llvm.org/D57851
+#    define __has_cpp_attribute(__x) 0
+#  endif
+#  if __has_cpp_attribute(nodiscard)
+#    if defined(__NVCC__) && __CUDACC_VER_MAJOR__ < 12
+#       define CV_NODISCARD_STD
+#    else
+#       define CV_NODISCARD_STD [[nodiscard]]
+#    endif
+#  elif __cplusplus >= 201703L
+//   available when compiler is C++17 compliant
+#    define CV_NODISCARD_STD [[nodiscard]]
+#  elif defined(__INTEL_COMPILER)
+     // see above, available when C++17 is enabled
+#  elif defined(_MSC_VER) && _MSC_VER >= 1911 && _MSVC_LANG >= 201703L
+//   available with VS2017 v15.3+ with /std:c++17 or higher; works on functions and classes
+#    define CV_NODISCARD_STD [[nodiscard]]
+#  elif defined(__GNUC__) && (((__GNUC__ * 100) + __GNUC_MINOR__) >= 700) && (__cplusplus >= 201103L)
+//   available with GCC 7.0+; works on functions, works or silently fails on classes
+#    define CV_NODISCARD_STD [[nodiscard]]
+#  elif defined(__GNUC__) && (((__GNUC__ * 100) + __GNUC_MINOR__) >= 408) && (__cplusplus >= 201103L)
+//   available with GCC 4.8+ but it usually does nothing and can fail noisily -- therefore not used
+//   define CV_NODISCARD_STD [[gnu::warn_unused_result]]
+#  endif
+#endif
+#ifndef CV_NODISCARD_STD
+#  define CV_NODISCARD_STD /* nothing by default */
+#endif
+
+
+/****************************************************************************************\
+*                                    C++ 11                                              *
+\****************************************************************************************/
+#ifdef __cplusplus
+// MSVC was stuck at __cplusplus == 199711L for a long time, even where it supports C++11,
+// so check _MSC_VER instead. See:
+// <https://devblogs.microsoft.com/cppblog/msvc-now-correctly-reports-__cplusplus>
+#  if defined(_MSC_VER)
+#    if _MSC_VER < 1800
+#      error "OpenCV 4.x+ requires enabled C++11 support"
+#    endif
+#  elif __cplusplus < 201103L
+#    error "OpenCV 4.x+ requires enabled C++11 support"
+#  endif
+#endif
+
+#ifndef CV_CXX11
+#  define CV_CXX11 1
+#endif
+
+#ifndef CV_OVERRIDE
+#  define CV_OVERRIDE override
+#endif
+
+#ifndef CV_FINAL
+#  define CV_FINAL final
+#endif
+
+#ifndef CV_NOEXCEPT
+#  define CV_NOEXCEPT noexcept
+#endif
+
+#ifndef CV_CONSTEXPR
+#  define CV_CONSTEXPR constexpr
+#endif
+
+// Integer types portability
+#ifdef __cplusplus
+#include <cstdint>
+namespace cv {
+using std::int8_t;
+using std::uint8_t;
+using std::int16_t;
+using std::uint16_t;
+using std::int32_t;
+using std::uint32_t;
+using std::int64_t;
+using std::uint64_t;
+}
+#else // pure C
+#include <stdint.h>
+#endif
+
+#ifdef __cplusplus
+namespace cv
+{
+
+class hfloat
+{
+public:
+#if CV_FP16_TYPE
+
+    hfloat() : h(0) {}
+    explicit hfloat(float x) { h = (__fp16)x; }
+    operator float() const { return (float)h; }
+protected:
+    __fp16 h;
+
+#else
+    hfloat() : w(0) {}
+    explicit hfloat(float x)
+    {
+    #if CV_FP16 && CV_AVX2
+        __m128 v = _mm_load_ss(&x);
+        w = (ushort)_mm_cvtsi128_si32(_mm_cvtps_ph(v, 0));
+    #else
+        Cv32suf in;
+        in.f = x;
+        unsigned sign = in.u & 0x80000000;
+        in.u ^= sign;
+
+        if( in.u >= 0x47800000 )
+            w = (ushort)(in.u > 0x7f800000 ? 0x7e00 : 0x7c00);
+        else
+        {
+            if (in.u < 0x38800000)
+            {
+                in.f += 0.5f;
+                w = (ushort)(in.u - 0x3f000000);
+            }
+            else
+            {
+                unsigned t = in.u + 0xc8000fff;
+                w = (ushort)((t + ((in.u >> 13) & 1)) >> 13);
+            }
+        }
+
+        w = (ushort)(w | (sign >> 16));
+    #endif
+    }
+
+    operator float() const
+    {
+    #if CV_FP16 && CV_AVX2
+        float f;
+        _mm_store_ss(&f, _mm_cvtph_ps(_mm_cvtsi32_si128(w)));
+        return f;
+    #else
+        Cv32suf out;
+
+        unsigned t = ((w & 0x7fff) << 13) + 0x38000000;
+        unsigned sign = (w & 0x8000) << 16;
+        unsigned e = w & 0x7c00;
+
+        out.u = t + (1 << 23);
+        out.u = (e >= 0x7c00 ? t + 0x38000000 :
+                 e == 0 ? (static_cast<void>(out.f -= 6.103515625e-05f), out.u) : t) | sign;
+        return out.f;
+    #endif
+    }
+
+protected:
+    ushort w;
+
+#endif
+};
+
+inline hfloat hfloatFromBits(ushort w) {
+#if CV_FP16_TYPE
+    Cv16suf u;
+    u.u = w;
+    hfloat res(float(u.h));
+    return res;
+#else
+    Cv32suf out;
+
+    unsigned t = ((w & 0x7fff) << 13) + 0x38000000;
+    unsigned sign = (w & 0x8000) << 16;
+    unsigned e = w & 0x7c00;
+
+    out.u = t + (1 << 23);
+    out.u = (e >= 0x7c00 ? t + 0x38000000 :
+            e == 0 ? (static_cast<void>(out.f -= 6.103515625e-05f), out.u) : t) | sign;
+    hfloat res(out.f);
+    return res;
+#endif
+}
+
+#if !defined(__OPENCV_BUILD) && !(defined __STDCPP_FLOAT16_T__) && !(defined __ARM_NEON)
+typedef hfloat float16_t;
+#endif
+
+}
+#endif
+
+/** @brief Constructs the 'fourcc' code, used in video codecs and many other places.
+    Simply call it with 4 chars like `CV_FOURCC('I', 'Y', 'U', 'V')`
+*/
+CV_INLINE int CV_FOURCC(char c1, char c2, char c3, char c4)
+{
+    return (c1 & 255) + ((c2 & 255) << 8) + ((c3 & 255) << 16) + ((c4 & 255) << 24);
+}
+
+//! Macro to construct the fourcc code of the codec. Same as CV_FOURCC()
+#define CV_FOURCC_MACRO(c1, c2, c3, c4) (((c1) & 255) + (((c2) & 255) << 8) + (((c3) & 255) << 16) + (((c4) & 255) << 24))
+
+//! @}
+
+#ifndef __cplusplus
+#include "opencv2/core/fast_math.hpp" // define cvRound(double)
+#endif
+
+#endif // OPENCV_CORE_CVDEF_H

GameAssist/GameAssist/include/cv2/opencv2/core/cvstd.hpp

@@ -0,0 +1,189 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_CVSTD_HPP
+#define OPENCV_CORE_CVSTD_HPP
+
+#ifndef __cplusplus
+#  error cvstd.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/core/cvdef.h"
+#include <cstddef>
+#include <cstring>
+#include <cctype>
+
+#include <string>
+
+// import useful primitives from stl
+#  include <algorithm>
+#  include <utility>
+#  include <cstdlib> //for abs(int)
+#  include <cmath>
+
+namespace cv
+{
+    static inline uchar abs(uchar a) { return a; }
+    static inline ushort abs(ushort a) { return a; }
+    static inline unsigned abs(unsigned a) { return a; }
+    static inline uint64 abs(uint64 a) { return a; }
+
+    using std::min;
+    using std::max;
+    using std::abs;
+    using std::swap;
+    using std::sqrt;
+    using std::exp;
+    using std::pow;
+    using std::log;
+}
+
+#include "cvstd_wrapper.hpp"
+
+namespace cv {
+
+//! @addtogroup core_utils
+//! @{
+
+//////////////////////////// memory management functions ////////////////////////////
+
+/** @brief Allocates an aligned memory buffer.
+
+The function allocates the buffer of the specified size and returns it. When the buffer size is 16
+bytes or more, the returned buffer is aligned to 16 bytes.
+@param bufSize Allocated buffer size.
+ */
+CV_EXPORTS void* fastMalloc(size_t bufSize);
+
+/** @brief Deallocates a memory buffer.
+
+The function deallocates the buffer allocated with fastMalloc . If NULL pointer is passed, the
+function does nothing. C version of the function clears the pointer *pptr* to avoid problems with
+double memory deallocation.
+@param ptr Pointer to the allocated buffer.
+ */
+CV_EXPORTS void fastFree(void* ptr);
+
+/*!
+  The STL-compliant memory Allocator based on cv::fastMalloc() and cv::fastFree()
+*/
+template<typename _Tp> class Allocator
+{
+public:
+    typedef _Tp value_type;
+    typedef value_type* pointer;
+    typedef const value_type* const_pointer;
+    typedef value_type& reference;
+    typedef const value_type& const_reference;
+    typedef size_t size_type;
+    typedef ptrdiff_t difference_type;
+    template<typename U> class rebind { typedef Allocator<U> other; };
+
+    explicit Allocator() {}
+    ~Allocator() {}
+    explicit Allocator(Allocator const&) {}
+    template<typename U>
+    explicit Allocator(Allocator<U> const&) {}
+
+    // address
+    pointer address(reference r) { return &r; }
+    const_pointer address(const_reference r) { return &r; }
+
+    pointer allocate(size_type count, const void* =0) { return reinterpret_cast<pointer>(fastMalloc(count * sizeof (_Tp))); }
+    void deallocate(pointer p, size_type) { fastFree(p); }
+
+    void construct(pointer p, const _Tp& v) { new(static_cast<void*>(p)) _Tp(v); }
+    void destroy(pointer p) { p->~_Tp(); }
+
+    size_type max_size() const { return cv::max(static_cast<_Tp>(-1)/sizeof(_Tp), 1); }
+};
+
+//! @} core_utils
+
+
+//! @addtogroup core_basic
+//! @{
+
+//////////////////////////////// string class ////////////////////////////////
+
+class CV_EXPORTS FileNode; //for string constructor from FileNode
+
+typedef std::string String;
+
+#ifndef OPENCV_DISABLE_STRING_LOWER_UPPER_CONVERSIONS
+
+//! @cond IGNORED
+namespace details {
+// std::tolower is int->int
+static inline char char_tolower(char ch)
+{
+    return (char)std::tolower((int)ch);
+}
+// std::toupper is int->int
+static inline char char_toupper(char ch)
+{
+    return (char)std::toupper((int)ch);
+}
+} // namespace details
+//! @endcond
+
+static inline std::string toLowerCase(const std::string& str)
+{
+    std::string result(str);
+    std::transform(result.begin(), result.end(), result.begin(), details::char_tolower);
+    return result;
+}
+
+static inline std::string toUpperCase(const std::string& str)
+{
+    std::string result(str);
+    std::transform(result.begin(), result.end(), result.begin(), details::char_toupper);
+    return result;
+}
+
+#endif // OPENCV_DISABLE_STRING_LOWER_UPPER_CONVERSIONS
+
+//! @} core_basic
+} // cv
+
+#endif //OPENCV_CORE_CVSTD_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cvstd.inl.hpp

@@ -0,0 +1,197 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_CVSTDINL_HPP
+#define OPENCV_CORE_CVSTDINL_HPP
+
+#include <complex>
+#include <ostream>
+#include <sstream>
+
+//! @cond IGNORED
+
+#ifdef _MSC_VER
+#pragma warning( push )
+#pragma warning( disable: 4127 )
+#endif
+
+namespace cv
+{
+
+template<typename _Tp> class DataType< std::complex<_Tp> >
+{
+public:
+    typedef std::complex<_Tp>  value_type;
+    typedef value_type         work_type;
+    typedef _Tp                channel_type;
+
+    enum { generic_type = 0,
+           depth        = DataType<channel_type>::depth,
+           channels     = 2,
+           fmt          = DataType<channel_type>::fmt + ((channels - 1) << 8),
+           type         = CV_MAKETYPE(depth, channels) };
+
+    typedef Vec<channel_type, channels> vec_type;
+};
+
+static inline
+std::ostream& operator << (std::ostream& out, Ptr<Formatted> fmtd)
+{
+    fmtd->reset();
+    for(const char* str = fmtd->next(); str; str = fmtd->next())
+        out << str;
+    return out;
+}
+
+static inline
+std::ostream& operator << (std::ostream& out, const Mat& mtx)
+{
+    return out << Formatter::get()->format(mtx);
+}
+
+static inline
+std::ostream& operator << (std::ostream& out, const UMat& m)
+{
+    return out << m.getMat(ACCESS_READ);
+}
+
+template<typename _Tp> static inline
+std::ostream& operator << (std::ostream& out, const Complex<_Tp>& c)
+{
+    return out << "(" << c.re << "," << c.im << ")";
+}
+
+template<typename _Tp> static inline
+std::ostream& operator << (std::ostream& out, const std::vector<Point_<_Tp> >& vec)
+{
+    return out << Formatter::get()->format(Mat(vec));
+}
+
+
+template<typename _Tp> static inline
+std::ostream& operator << (std::ostream& out, const std::vector<Point3_<_Tp> >& vec)
+{
+    return out << Formatter::get()->format(Mat(vec));
+}
+
+
+template<typename _Tp, int m, int n> static inline
+std::ostream& operator << (std::ostream& out, const Matx<_Tp, m, n>& matx)
+{
+    return out << Formatter::get()->format(Mat(matx));
+}
+
+template<typename _Tp> static inline
+std::ostream& operator << (std::ostream& out, const Point_<_Tp>& p)
+{
+    out << "[" << p.x << ", " << p.y << "]";
+    return out;
+}
+
+template<typename _Tp> static inline
+std::ostream& operator << (std::ostream& out, const Point3_<_Tp>& p)
+{
+    out << "[" << p.x << ", " << p.y << ", " << p.z << "]";
+    return out;
+}
+
+template<typename _Tp, int n> static inline
+std::ostream& operator << (std::ostream& out, const Vec<_Tp, n>& vec)
+{
+    out << "[";
+    if (cv::traits::Depth<_Tp>::value <= CV_32S)
+    {
+        for (int i = 0; i < n - 1; ++i) {
+            out << (int)vec[i] << ", ";
+        }
+        out << (int)vec[n-1] << "]";
+    }
+    else
+    {
+        for (int i = 0; i < n - 1; ++i) {
+            out << vec[i] << ", ";
+        }
+        out << vec[n-1] << "]";
+    }
+
+    return out;
+}
+
+template<typename _Tp> static inline
+std::ostream& operator << (std::ostream& out, const Size_<_Tp>& size)
+{
+    return out << "[" << size.width << " x " << size.height << "]";
+}
+
+template<typename _Tp> static inline
+std::ostream& operator << (std::ostream& out, const Rect_<_Tp>& rect)
+{
+    return out << "[" << rect.width << " x " << rect.height << " from (" << rect.x << ", " << rect.y << ")]";
+}
+
+static inline std::ostream& operator << (std::ostream& out, const MatSize& msize)
+{
+    int i, dims = msize.dims();
+    for( i = 0; i < dims; i++ )
+    {
+        out << msize[i];
+        if( i < dims-1 )
+            out << " x ";
+    }
+    return out;
+}
+
+static inline std::ostream &operator<< (std::ostream &s, cv::Range &r)
+{
+    return s << "[" << r.start << " : " << r.end << ")";
+}
+
+} // cv
+
+#ifdef _MSC_VER
+#pragma warning( pop )
+#endif
+
+//! @endcond
+
+#endif // OPENCV_CORE_CVSTDINL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/cvstd_wrapper.hpp

@@ -0,0 +1,154 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_CVSTD_WRAPPER_HPP
+#define OPENCV_CORE_CVSTD_WRAPPER_HPP
+
+#include "opencv2/core/cvdef.h"
+
+#include <string>
+#include <memory>  // std::shared_ptr
+#include <type_traits>  // std::enable_if
+
+namespace cv {
+
+using std::nullptr_t;
+
+//! @addtogroup core_basic
+//! @{
+
+#ifdef CV_DOXYGEN
+
+template <typename _Tp> using Ptr = std::shared_ptr<_Tp>;  // In ideal world it should look like this, but we need some compatibility workarounds below
+
+template<typename _Tp, typename ... A1> static inline
+Ptr<_Tp> makePtr(const A1&... a1) { return std::make_shared<_Tp>(a1...); }
+
+#else  // cv::Ptr with compatibility workarounds
+
+// It should be defined for C-API types only.
+// C++ types should use regular "delete" operator.
+template<typename Y> struct DefaultDeleter;
+#if 0
+{
+    void operator()(Y* p) const;
+};
+#endif
+
+namespace sfinae {
+template<typename C, typename Ret, typename... Args>
+struct has_parenthesis_operator
+{
+private:
+    template<typename T>
+    static CV_CONSTEXPR std::true_type has_parenthesis_operator_check(typename std::is_same<typename std::decay<decltype(std::declval<T>().operator()(std::declval<Args>()...))>::type, Ret>::type*);
+
+    template<typename> static CV_CONSTEXPR std::false_type has_parenthesis_operator_check(...);
+
+    typedef decltype(has_parenthesis_operator_check<C>(0)) type;
+
+public:
+#if __cplusplus >= 201103L || (defined(_MSC_VER) && _MSC_VER >= 1900/*MSVS 2015*/)
+    static CV_CONSTEXPR bool value = type::value;
+#else
+    // support MSVS 2013
+    static const int value = type::value;
+#endif
+};
+} // namespace sfinae
+
+template <typename T, typename = void>
+struct has_custom_delete
+        : public std::false_type {};
+
+// Force has_custom_delete to std::false_type when NVCC is compiling CUDA source files
+#ifndef __CUDACC__
+template <typename T>
+struct has_custom_delete<T, typename std::enable_if< sfinae::has_parenthesis_operator<DefaultDeleter<T>, void, T*>::value >::type >
+        : public std::true_type {};
+#endif
+
+template<typename T>
+struct Ptr : public std::shared_ptr<T>
+{
+#if 0
+    using std::shared_ptr<T>::shared_ptr;  // GCC 5.x can't handle this
+#else
+    inline Ptr() CV_NOEXCEPT : std::shared_ptr<T>() {}
+    inline Ptr(nullptr_t) CV_NOEXCEPT : std::shared_ptr<T>(nullptr) {}
+    template<typename Y, typename D> inline Ptr(Y* p, D d) : std::shared_ptr<T>(p, d) {}
+    template<typename D> inline Ptr(nullptr_t, D d) : std::shared_ptr<T>(nullptr, d) {}
+
+    template<typename Y> inline Ptr(const Ptr<Y>& r, T* ptr) CV_NOEXCEPT : std::shared_ptr<T>(r, ptr) {}
+
+    inline Ptr(const Ptr<T>& o) CV_NOEXCEPT : std::shared_ptr<T>(o) {}
+    inline Ptr(Ptr<T>&& o) CV_NOEXCEPT : std::shared_ptr<T>(std::move(o)) {}
+
+    template<typename Y> inline Ptr(const Ptr<Y>& o) CV_NOEXCEPT : std::shared_ptr<T>(o) {}
+    template<typename Y> inline Ptr(Ptr<Y>&& o) CV_NOEXCEPT : std::shared_ptr<T>(std::move(o)) {}
+#endif
+    inline Ptr(const std::shared_ptr<T>& o) CV_NOEXCEPT : std::shared_ptr<T>(o) {}
+    inline Ptr(std::shared_ptr<T>&& o) CV_NOEXCEPT : std::shared_ptr<T>(std::move(o)) {}
+
+    // Overload with custom DefaultDeleter: Ptr<IplImage>(...)
+    template<typename Y>
+    inline Ptr(const std::true_type&, Y* ptr) : std::shared_ptr<T>(ptr, DefaultDeleter<Y>()) {}
+
+    // Overload without custom deleter: Ptr<std::string>(...);
+    template<typename Y>
+    inline Ptr(const std::false_type&, Y* ptr) : std::shared_ptr<T>(ptr) {}
+
+    template<typename Y = T>
+    inline Ptr(Y* ptr) : Ptr(has_custom_delete<Y>(), ptr) {}
+
+    // Overload with custom DefaultDeleter: Ptr<IplImage>(...)
+    template<typename Y>
+    inline void reset(const std::true_type&, Y* ptr) { std::shared_ptr<T>::reset(ptr, DefaultDeleter<Y>()); }
+
+    // Overload without custom deleter: Ptr<std::string>(...);
+    template<typename Y>
+    inline void reset(const std::false_type&, Y* ptr) { std::shared_ptr<T>::reset(ptr); }
+
+    template<typename Y>
+    inline void reset(Y* ptr) { Ptr<T>::reset(has_custom_delete<Y>(), ptr); }
+
+    template<class Y, class Deleter>
+    void reset(Y* ptr, Deleter d) { std::shared_ptr<T>::reset(ptr, d); }
+
+    void reset() CV_NOEXCEPT { std::shared_ptr<T>::reset(); }
+
+    Ptr& operator=(const Ptr& o) { std::shared_ptr<T>::operator =(o); return *this; }
+    template<typename Y> inline Ptr& operator=(const Ptr<Y>& o) { std::shared_ptr<T>::operator =(o); return *this; }
+
+    T* operator->() const CV_NOEXCEPT { return std::shared_ptr<T>::get();}
+    typename std::add_lvalue_reference<T>::type operator*() const CV_NOEXCEPT { return *std::shared_ptr<T>::get(); }
+
+    // OpenCV 3.x methods (not a part of standard C++ library)
+    inline void release() { std::shared_ptr<T>::reset(); }
+    inline operator T* () const { return std::shared_ptr<T>::get(); }
+    inline bool empty() const { return std::shared_ptr<T>::get() == nullptr; }
+
+    template<typename Y> inline
+    Ptr<Y> staticCast() const CV_NOEXCEPT { return std::static_pointer_cast<Y>(*this); }
+
+    template<typename Y> inline
+    Ptr<Y> constCast() const CV_NOEXCEPT { return std::const_pointer_cast<Y>(*this); }
+
+    template<typename Y> inline
+    Ptr<Y> dynamicCast() const CV_NOEXCEPT { return std::dynamic_pointer_cast<Y>(*this); }
+};
+
+template<typename _Tp, typename ... A1> static inline
+Ptr<_Tp> makePtr(const A1&... a1)
+{
+    static_assert( !has_custom_delete<_Tp>::value, "Can't use this makePtr with custom DefaultDeleter");
+    return (Ptr<_Tp>)std::make_shared<_Tp>(a1...);
+}
+
+#endif // CV_DOXYGEN
+
+//! @} core_basic
+} // cv
+
+#endif //OPENCV_CORE_CVSTD_WRAPPER_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/detail/async_promise.hpp

@@ -0,0 +1,69 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_ASYNC_PROMISE_HPP
+#define OPENCV_CORE_ASYNC_PROMISE_HPP
+
+#include "../async.hpp"
+
+#include "exception_ptr.hpp"
+
+namespace cv {
+
+/** @addtogroup core_async
+@{
+*/
+
+
+/** @brief Provides result of asynchronous operations
+
+*/
+class CV_EXPORTS AsyncPromise
+{
+public:
+    ~AsyncPromise() CV_NOEXCEPT;
+    AsyncPromise() CV_NOEXCEPT;
+    explicit AsyncPromise(const AsyncPromise& o) CV_NOEXCEPT;
+    AsyncPromise& operator=(const AsyncPromise& o) CV_NOEXCEPT;
+    void release() CV_NOEXCEPT;
+
+    /** Returns associated AsyncArray
+    @note Can be called once
+    */
+    AsyncArray getArrayResult();
+
+    /** Stores asynchronous result.
+    @param[in] value result
+    */
+    void setValue(InputArray value);
+
+    // TODO "move" setters
+
+#if CV__EXCEPTION_PTR
+    /** Stores exception.
+    @param[in] exception exception to be raised in AsyncArray
+    */
+    void setException(std::exception_ptr exception);
+#endif
+
+    /** Stores exception.
+    @param[in] exception exception to be raised in AsyncArray
+    */
+    void setException(const cv::Exception& exception);
+
+    explicit AsyncPromise(AsyncPromise&& o) { p = o.p; o.p = NULL; }
+    AsyncPromise& operator=(AsyncPromise&& o) CV_NOEXCEPT { std::swap(p, o.p); return *this; }
+
+
+    // PImpl
+    typedef struct AsyncArray::Impl Impl; friend struct AsyncArray::Impl;
+    inline void* _getImpl() const CV_NOEXCEPT { return p; }
+protected:
+    Impl* p;
+};
+
+
+//! @}
+} // namespace
+#endif // OPENCV_CORE_ASYNC_PROMISE_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/detail/dispatch_helper.impl.hpp

@@ -0,0 +1,49 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_DETAIL_DISPATCH_HELPER_IMPL_HPP
+#define OPENCV_CORE_DETAIL_DISPATCH_HELPER_IMPL_HPP
+
+//! @cond IGNORED
+
+namespace cv {
+namespace detail {
+
+template<template<typename> class Functor, typename... Args>
+static inline void depthDispatch(const int depth, Args&&... args)
+{
+    switch (depth)
+    {
+        case CV_8U:
+            Functor<uint8_t>{}(std::forward<Args>(args)...);
+            break;
+        case CV_8S:
+            Functor<int8_t>{}(std::forward<Args>(args)...);
+            break;
+        case CV_16U:
+            Functor<uint16_t>{}(std::forward<Args>(args)...);
+            break;
+        case CV_16S:
+            Functor<int16_t>{}(std::forward<Args>(args)...);
+            break;
+        case CV_32S:
+            Functor<int32_t>{}(std::forward<Args>(args)...);
+            break;
+        case CV_32F:
+            Functor<float>{}(std::forward<Args>(args)...);
+            break;
+        case CV_64F:
+            Functor<double>{}(std::forward<Args>(args)...);
+            break;
+        case CV_16F:
+        default:
+            CV_Error(cv::Error::BadDepth, "Unsupported matrix type.");
+    };
+}
+
+}}
+
+//! @endcond
+
+#endif //OPENCV_CORE_DETAIL_DISPATCH_HELPER_IMPL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/detail/exception_ptr.hpp

@@ -0,0 +1,21 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_DETAILS_EXCEPTION_PTR_H
+#define OPENCV_CORE_DETAILS_EXCEPTION_PTR_H
+
+#ifndef CV__EXCEPTION_PTR
+#  if defined(__ANDROID__) && defined(ATOMIC_INT_LOCK_FREE) && ATOMIC_INT_LOCK_FREE < 2
+#    define CV__EXCEPTION_PTR 0  // Not supported, details: https://gcc.gnu.org/bugzilla/show_bug.cgi?id=58938
+#  else
+#    define CV__EXCEPTION_PTR 1
+#  endif
+#endif
+#ifndef CV__EXCEPTION_PTR
+#  define CV__EXCEPTION_PTR 0
+#elif CV__EXCEPTION_PTR
+#  include <exception>  // std::exception_ptr
+#endif
+
+#endif // OPENCV_CORE_DETAILS_EXCEPTION_PTR_H

GameAssist/GameAssist/include/cv2/opencv2/core/directx.hpp

@@ -0,0 +1,184 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors as is and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the copyright holders or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_DIRECTX_HPP
+#define OPENCV_CORE_DIRECTX_HPP
+
+#include "mat.hpp"
+#include "ocl.hpp"
+
+#if !defined(__d3d11_h__)
+struct ID3D11Device;
+struct ID3D11Texture2D;
+#endif
+
+#if !defined(__d3d10_h__)
+struct ID3D10Device;
+struct ID3D10Texture2D;
+#endif
+
+#if !defined(_D3D9_H_)
+struct IDirect3DDevice9;
+struct IDirect3DDevice9Ex;
+struct IDirect3DSurface9;
+#endif
+
+
+namespace cv { namespace directx {
+
+namespace ocl {
+using namespace cv::ocl;
+
+//! @addtogroup core_directx
+// This section describes OpenCL and DirectX interoperability.
+//
+// To enable DirectX support, configure OpenCV using CMake with WITH_DIRECTX=ON . Note, DirectX is
+// supported only on Windows.
+//
+// To use OpenCL functionality you should first initialize OpenCL context from DirectX resource.
+//
+//! @{
+
+// TODO static functions in the Context class
+//! @brief Creates OpenCL context from D3D11 device
+//
+//! @param pD3D11Device - pointer to D3D11 device
+//! @return Returns reference to OpenCL Context
+CV_EXPORTS Context& initializeContextFromD3D11Device(ID3D11Device* pD3D11Device);
+
+//! @brief Creates OpenCL context from D3D10 device
+//
+//! @param pD3D10Device - pointer to D3D10 device
+//! @return Returns reference to OpenCL Context
+CV_EXPORTS Context& initializeContextFromD3D10Device(ID3D10Device* pD3D10Device);
+
+//! @brief Creates OpenCL context from Direct3DDevice9Ex device
+//
+//! @param pDirect3DDevice9Ex - pointer to Direct3DDevice9Ex device
+//! @return Returns reference to OpenCL Context
+CV_EXPORTS Context& initializeContextFromDirect3DDevice9Ex(IDirect3DDevice9Ex* pDirect3DDevice9Ex);
+
+//! @brief Creates OpenCL context from Direct3DDevice9 device
+//
+//! @param pDirect3DDevice9 - pointer to Direct3Device9 device
+//! @return Returns reference to OpenCL Context
+CV_EXPORTS Context& initializeContextFromDirect3DDevice9(IDirect3DDevice9* pDirect3DDevice9);
+
+//! @}
+
+} // namespace cv::directx::ocl
+
+//! @addtogroup core_directx
+//! @{
+
+//! @brief Converts InputArray to ID3D11Texture2D. If destination texture format is DXGI_FORMAT_NV12 then
+//!        input UMat expected to be in BGR format and data will be downsampled and color-converted to NV12.
+//
+//! @note Note: Destination texture must be allocated by application. Function does memory copy from src to
+//!             pD3D11Texture2D
+//
+//! @param src - source InputArray
+//! @param pD3D11Texture2D - destination D3D11 texture
+CV_EXPORTS void convertToD3D11Texture2D(InputArray src, ID3D11Texture2D* pD3D11Texture2D);
+
+//! @brief Converts ID3D11Texture2D to OutputArray. If input texture format is DXGI_FORMAT_NV12 then
+//!        data will be upsampled and color-converted to BGR format.
+//
+//! @note Note: Destination matrix will be re-allocated if it has not enough memory to match texture size.
+//!             function does memory copy from pD3D11Texture2D to dst
+//
+//! @param pD3D11Texture2D - source D3D11 texture
+//! @param dst             - destination OutputArray
+CV_EXPORTS void convertFromD3D11Texture2D(ID3D11Texture2D* pD3D11Texture2D, OutputArray dst);
+
+//! @brief Converts InputArray to ID3D10Texture2D
+//
+//! @note Note: function does memory copy from src to
+//!             pD3D10Texture2D
+//
+//! @param src             - source InputArray
+//! @param pD3D10Texture2D - destination D3D10 texture
+CV_EXPORTS void convertToD3D10Texture2D(InputArray src, ID3D10Texture2D* pD3D10Texture2D);
+
+//! @brief Converts ID3D10Texture2D to OutputArray
+//
+//! @note Note: function does memory copy from pD3D10Texture2D
+//!             to dst
+//
+//! @param pD3D10Texture2D - source D3D10 texture
+//! @param dst             - destination OutputArray
+CV_EXPORTS void convertFromD3D10Texture2D(ID3D10Texture2D* pD3D10Texture2D, OutputArray dst);
+
+//! @brief Converts InputArray to IDirect3DSurface9
+//
+//! @note Note: function does memory copy from src to
+//!             pDirect3DSurface9
+//
+//! @param src                 - source InputArray
+//! @param pDirect3DSurface9   - destination D3D10 texture
+//! @param surfaceSharedHandle - shared handle
+CV_EXPORTS void convertToDirect3DSurface9(InputArray src, IDirect3DSurface9* pDirect3DSurface9, void* surfaceSharedHandle = NULL);
+
+//! @brief Converts IDirect3DSurface9 to OutputArray
+//
+//! @note Note: function does memory copy from pDirect3DSurface9
+//!             to dst
+//
+//! @param pDirect3DSurface9   - source D3D10 texture
+//! @param dst                 - destination OutputArray
+//! @param surfaceSharedHandle - shared handle
+CV_EXPORTS void convertFromDirect3DSurface9(IDirect3DSurface9* pDirect3DSurface9, OutputArray dst, void* surfaceSharedHandle = NULL);
+
+//! @brief Get OpenCV type from DirectX type
+//! @param iDXGI_FORMAT - enum DXGI_FORMAT for D3D10/D3D11
+//! @return OpenCV type or -1 if there is no equivalent
+CV_EXPORTS int getTypeFromDXGI_FORMAT(const int iDXGI_FORMAT); // enum DXGI_FORMAT for D3D10/D3D11
+
+//! @brief Get OpenCV type from DirectX type
+//! @param iD3DFORMAT - enum D3DTYPE for D3D9
+//! @return OpenCV type or -1 if there is no equivalent
+CV_EXPORTS int getTypeFromD3DFORMAT(const int iD3DFORMAT); // enum D3DTYPE for D3D9
+
+//! @}
+
+} } // namespace cv::directx
+
+#endif // OPENCV_CORE_DIRECTX_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/dualquaternion.hpp

@@ -0,0 +1,979 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2020, Huawei Technologies Co., Ltd. All rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//       http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+// Author: Liangqian Kong <kongliangqian@huawei.com>
+//         Longbu Wang <wanglongbu@huawei.com>
+#ifndef OPENCV_CORE_DUALQUATERNION_HPP
+#define OPENCV_CORE_DUALQUATERNION_HPP
+
+#include <opencv2/core/quaternion.hpp>
+#include <opencv2/core/affine.hpp>
+
+namespace cv{
+//! @addtogroup core_quaternion
+//! @{
+
+template <typename _Tp> class DualQuat;
+template <typename _Tp> std::ostream& operator<<(std::ostream&, const DualQuat<_Tp>&);
+
+/**
+ * Dual quaternions were introduced to describe rotation together with translation while ordinary
+ * quaternions can only describe rotation. It can be used for shortest path pose interpolation,
+ * local pose optimization or volumetric deformation. More details can be found
+ * - https://en.wikipedia.org/wiki/Dual_quaternion
+ * - ["A beginners guide to dual-quaternions: what they are, how they work, and how to use them for 3D character hierarchies", Ben Kenwright, 2012](https://borodust.org/public/shared/beginner_dual_quats.pdf)
+ * - ["Dual Quaternions", Yan-Bin Jia, 2013](http://web.cs.iastate.edu/~cs577/handouts/dual-quaternion.pdf)
+ * - ["Geometric Skinning with Approximate Dual Quaternion Blending", Kavan, 2008](https://www.cs.utah.edu/~ladislav/kavan08geometric/kavan08geometric)
+ * - http://rodolphe-vaillant.fr/?e=29
+ *
+ * A unit dual quaternion can be classically represented as:
+ * \f[
+ * \begin{equation}
+ * \begin{split}
+ * \sigma &= \left(r+\frac{\epsilon}{2}tr\right)\\
+ * &= [w, x, y, z, w\_, x\_, y\_, z\_]
+ * \end{split}
+ * \end{equation}
+ * \f]
+ * where \f$r, t\f$ represents the rotation (ordinary unit quaternion) and translation (pure ordinary quaternion) respectively.
+ *
+ * A general dual quaternions which consist of two quaternions is usually represented in form of:
+ * \f[
+ * \sigma = p + \epsilon q
+ * \f]
+ * where the introduced dual unit \f$\epsilon\f$ satisfies \f$\epsilon^2 = \epsilon^3 =...=0\f$, and \f$p, q\f$ are quaternions.
+ *
+ * Alternatively, dual quaternions can also be interpreted as four components which are all [dual numbers](https://www.cs.utah.edu/~ladislav/kavan08geometric/kavan08geometric):
+ * \f[
+ * \sigma = \hat{q}_w + \hat{q}_xi + \hat{q}_yj + \hat{q}_zk
+ * \f]
+ * If we set \f$\hat{q}_x, \hat{q}_y\f$ and \f$\hat{q}_z\f$ equal to 0, a dual quaternion is transformed to a dual number. see normalize().
+ *
+ * If you want to create a dual quaternion, you can use:
+ *
+ * ```
+ * using namespace cv;
+ * double angle = CV_PI;
+ *
+ * // create from eight number
+ * DualQuatd dq1(1, 2, 3, 4, 5, 6, 7, 8); //p = [1,2,3,4]. q=[5,6,7,8]
+ *
+ * // create from Vec
+ * Vec<double, 8> v{1,2,3,4,5,6,7,8};
+ * DualQuatd dq_v{v};
+ *
+ * // create from two quaternion
+ * Quatd p(1, 2, 3, 4);
+ * Quatd q(5, 6, 7, 8);
+ * DualQuatd dq2 = DualQuatd::createFromQuat(p, q);
+ *
+ * // create from an angle, an axis and a translation
+ * Vec3d axis{0, 0, 1};
+ * Vec3d trans{3, 4, 5};
+ * DualQuatd dq3 = DualQuatd::createFromAngleAxisTrans(angle, axis, trans);
+ *
+ * // If you already have an instance of class Affine3, then you can use
+ * Affine3d R = dq3.toAffine3();
+ * DualQuatd dq4 = DualQuatd::createFromAffine3(R);
+ *
+ * // or create directly by affine transformation matrix Rt
+ * // see createFromMat() in detail for the form of Rt
+ * Matx44d Rt = dq3.toMat();
+ * DualQuatd dq5 = DualQuatd::createFromMat(Rt);
+ *
+ * // Any rotation + translation movement can
+ * // be expressed as a rotation + translation around the same line in space (expressed by Plucker
+ * // coords), and here's a way to represent it this way.
+ * Vec3d axis{1, 1, 1}; // axis will be normalized in createFromPitch
+ * Vec3d trans{3, 4 ,5};
+ * axis = axis / std::sqrt(axis.dot(axis));// The formula for computing moment that I use below requires a normalized axis
+ * Vec3d moment = 1.0 / 2 * (trans.cross(axis) + axis.cross(trans.cross(axis)) *
+ *                            std::cos(rotation_angle / 2) / std::sin(rotation_angle / 2));
+ * double d = trans.dot(qaxis);
+ * DualQuatd dq6 = DualQuatd::createFromPitch(angle, d, axis, moment);
+ * ```
+ *
+ * A point \f$v=(x, y, z)\f$ in form of dual quaternion is \f$[1+\epsilon v]=[1,0,0,0,0,x,y,z]\f$.
+ * The transformation of a point \f$v_1\f$ to another point \f$v_2\f$ under the dual quaternion \f$\sigma\f$ is
+ * \f[
+ * 1 + \epsilon v_2 = \sigma * (1 + \epsilon v_1) * \sigma^{\star}
+ * \f]
+ * where \f$\sigma^{\star}=p^*-\epsilon q^*.\f$
+ *
+ * A line in the \f$Pl\ddot{u}cker\f$ coordinates \f$(\hat{l}, m)\f$ defined by the dual quaternion \f$l=\hat{l}+\epsilon m\f$.
+ * To transform a line, \f[l_2 = \sigma * l_1 * \sigma^*,\f] where \f$\sigma=r+\frac{\epsilon}{2}rt\f$ and
+ * \f$\sigma^*=p^*+\epsilon q^*\f$.
+ *
+ * To extract the Vec<double, 8> or Vec<float, 8>, see toVec();
+ *
+ * To extract the affine transformation matrix, see toMat();
+ *
+ * To extract the instance of Affine3, see toAffine3();
+ *
+ * If two quaternions \f$q_0, q_1\f$ are needed to be interpolated, you can use sclerp()
+ * ```
+ * DualQuatd::sclerp(q0, q1, t)
+ * ```
+ * or dqblend().
+ * ```
+ * DualQuatd::dqblend(q0, q1, t)
+ * ```
+ * With more than two dual quaternions to be blended, you can use generalize linear dual quaternion blending
+ * with the corresponding weights, i.e. gdqblend().
+ *
+ */
+template <typename _Tp>
+class CV_EXPORTS DualQuat{
+    static_assert(std::is_floating_point<_Tp>::value, "Dual quaternion only make sense with type of float or double");
+    using value_type = _Tp;
+
+public:
+    static constexpr _Tp CV_DUAL_QUAT_EPS = (_Tp)1.e-6;
+
+    DualQuat();
+
+    /**
+     * @brief create from eight same type numbers.
+     */
+    DualQuat(const _Tp w, const _Tp x, const _Tp y, const _Tp z, const _Tp w_, const _Tp x_, const _Tp y_, const _Tp z_);
+
+    /**
+     * @brief create from a double or float vector.
+     */
+    DualQuat(const Vec<_Tp, 8> &q);
+
+    _Tp w, x, y, z, w_, x_, y_, z_;
+
+    /**
+     * @brief create Dual Quaternion from two same type quaternions p and q.
+     * A Dual Quaternion \f$\sigma\f$ has the form:
+     * \f[\sigma = p + \epsilon q\f]
+     * where p and q are defined as follows:
+     * \f[\begin{equation}
+     *    \begin{split}
+     *    p &= w + x\boldsymbol{i} + y\boldsymbol{j} + z\boldsymbol{k}\\
+     *    q &= w\_ + x\_\boldsymbol{i} + y\_\boldsymbol{j} + z\_\boldsymbol{k}.
+     *    \end{split}
+     *   \end{equation}
+     * \f]
+     * The p and q are the real part and dual part respectively.
+     * @param realPart a quaternion, real part of dual quaternion.
+     * @param dualPart a quaternion, dual part of dual quaternion.
+     * @sa Quat
+    */
+    static DualQuat<_Tp> createFromQuat(const Quat<_Tp> &realPart, const Quat<_Tp> &dualPart);
+
+    /**
+     * @brief create a dual quaternion from a rotation angle \f$\theta\f$, a rotation axis
+     * \f$\boldsymbol{u}\f$ and a translation \f$\boldsymbol{t}\f$.
+     * It generates a dual quaternion \f$\sigma\f$ in the form of
+     * \f[\begin{equation}
+     *    \begin{split}
+     *    \sigma &= r + \frac{\epsilon}{2}\boldsymbol{t}r \\
+     *           &= [\cos(\frac{\theta}{2}), \boldsymbol{u}\sin(\frac{\theta}{2})]
+     *           + \frac{\epsilon}{2}[0, \boldsymbol{t}][[\cos(\frac{\theta}{2}),
+     *           \boldsymbol{u}\sin(\frac{\theta}{2})]]\\
+     *           &= \cos(\frac{\theta}{2}) + \boldsymbol{u}\sin(\frac{\theta}{2})
+     *           + \frac{\epsilon}{2}(-(\boldsymbol{t} \cdot \boldsymbol{u})\sin(\frac{\theta}{2})
+     *           + \boldsymbol{t}\cos(\frac{\theta}{2}) + \boldsymbol{u} \times \boldsymbol{t} \sin(\frac{\theta}{2})).
+     *    \end{split}
+     *    \end{equation}\f]
+     * @param angle rotation angle.
+     * @param axis rotation axis.
+     * @param translation a vector of length 3.
+     * @note Axis will be normalized in this function. And translation is applied
+     * after the rotation. Use @ref createFromQuat(r, r * t / 2) to create a dual quaternion
+     * which translation is applied before rotation.
+     * @sa Quat
+     */
+    static DualQuat<_Tp> createFromAngleAxisTrans(const _Tp angle, const Vec<_Tp, 3> &axis, const Vec<_Tp, 3> &translation);
+
+    /**
+     * @brief Transform this dual quaternion to an affine transformation matrix \f$M\f$.
+     * Dual quaternion consists of a rotation \f$r=[a,b,c,d]\f$ and a translation \f$t=[\Delta x,\Delta y,\Delta z]\f$. The
+     * affine transformation matrix \f$M\f$ has the form
+     * \f[
+     * \begin{bmatrix}
+     * 1-2(e_2^2 +e_3^2) &2(e_1e_2-e_0e_3) &2(e_0e_2+e_1e_3) &\Delta x\\
+     * 2(e_0e_3+e_1e_2)  &1-2(e_1^2+e_3^2) &2(e_2e_3-e_0e_1) &\Delta y\\
+     * 2(e_1e_3-e_0e_2)  &2(e_0e_1+e_2e_3) &1-2(e_1^2-e_2^2) &\Delta z\\
+     * 0&0&0&1
+     * \end{bmatrix}
+     * \f]
+     *  if A is a matrix consisting of  n points to be transformed, this could be achieved by
+     * \f[
+     *  new\_A = M * A
+     * \f]
+     * where A has the form
+     * \f[
+     * \begin{bmatrix}
+     * x_0& x_1& x_2&...&x_n\\
+     * y_0& y_1& y_2&...&y_n\\
+     * z_0& z_1& z_2&...&z_n\\
+     * 1&1&1&...&1
+     * \end{bmatrix}
+     * \f]
+     * where the same subscript represent the same point. The size of A should be \f$[4,n]\f$.
+     * and the same size for matrix new_A.
+     * @param _R 4x4 matrix that represents rotations and translation.
+     * @note Translation is applied after the rotation. Use createFromQuat(r, r * t / 2) to create
+     * a dual quaternion which translation is applied before rotation.
+     */
+    static DualQuat<_Tp> createFromMat(InputArray _R);
+
+    /**
+     * @brief create dual quaternion from an affine matrix. The definition of affine matrix can refer to  createFromMat()
+     */
+    static DualQuat<_Tp> createFromAffine3(const Affine3<_Tp> &R);
+
+    /**
+     * @brief A dual quaternion is a vector in form of
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * \sigma &=\boldsymbol{p} + \epsilon \boldsymbol{q}\\
+     * &= \cos\hat{\frac{\theta}{2}}+\overline{\hat{l}}\sin\frac{\hat{\theta}}{2}
+     * \end{split}
+     * \end{equation}
+     * \f]
+     * where \f$\hat{\theta}\f$ is dual angle and \f$\overline{\hat{l}}\f$ is dual axis:
+     * \f[
+     * \hat{\theta}=\theta + \epsilon d,\\
+     * \overline{\hat{l}}= \hat{l} +\epsilon m.
+     * \f]
+     * In this representation, \f$\theta\f$ is rotation angle and \f$(\hat{l},m)\f$ is the screw axis, d is the translation distance along the axis.
+     *
+     * @param angle rotation angle.
+     * @param d translation along the rotation axis.
+     * @param axis rotation axis represented by quaternion with w = 0.
+     * @param moment the moment of line, and it should be orthogonal to axis.
+     * @note Translation is applied after the rotation. Use createFromQuat(r, r * t / 2) to create
+     * a dual quaternion which translation is applied before rotation.
+     */
+    static DualQuat<_Tp> createFromPitch(const _Tp angle, const _Tp d, const Vec<_Tp, 3> &axis, const Vec<_Tp, 3> &moment);
+
+    /**
+     * @brief return a quaternion which represent the real part of dual quaternion.
+     * The definition of real part is in createFromQuat().
+     * @sa createFromQuat, getDualPart
+     */
+    Quat<_Tp> getRealPart() const;
+
+    /**
+     * @brief return a quaternion which represent the dual part of dual quaternion.
+     * The definition of dual part is in createFromQuat().
+     * @sa createFromQuat, getRealPart
+     */
+    Quat<_Tp> getDualPart() const;
+
+    /**
+     * @brief return the conjugate of a dual quaternion.
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * \sigma^* &= (p + \epsilon q)^*
+     *          &= (p^* + \epsilon q^*)
+     * \end{split}
+     * \end{equation}
+     * \f]
+     * @param dq a dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> conjugate(const DualQuat<T> &dq);
+
+    /**
+     * @brief return the conjugate of a dual quaternion.
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * \sigma^* &= (p + \epsilon q)^*
+     *          &= (p^* + \epsilon q^*)
+     * \end{split}
+     * \end{equation}
+     * \f]
+     */
+    DualQuat<_Tp> conjugate() const;
+
+    /**
+     * @brief return the rotation in quaternion form.
+     */
+    Quat<_Tp> getRotation(QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+     * @brief return the translation vector.
+     * The rotation \f$r\f$ in this dual quaternion \f$\sigma\f$ is applied before translation \f$t\f$.
+     * The dual quaternion \f$\sigma\f$ is defined as
+     * \f[\begin{equation}
+     * \begin{split}
+     * \sigma &= p + \epsilon q \\
+     *        &= r + \frac{\epsilon}{2}{t}r.
+     * \end{split}
+     * \end{equation}\f]
+     * Thus, the translation can be obtained as follows
+     * \f[t = 2qp^*.\f]
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, this dual quaternion assume to be a unit dual quaternion
+     * and this function will save some computations.
+     * @note This dual quaternion's translation is applied after the rotation.
+     */
+    Vec<_Tp, 3> getTranslation(QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+     * @brief return the norm \f$||\sigma||\f$ of dual quaternion \f$\sigma = p + \epsilon q\f$.
+     * \f[
+     *  \begin{equation}
+     *  \begin{split}
+     *  ||\sigma|| &= \sqrt{\sigma * \sigma^*} \\
+     *        &= ||p|| + \epsilon \frac{p \cdot q}{||p||}.
+     *  \end{split}
+     *  \end{equation}
+     *  \f]
+     * Generally speaking, the norm of a not unit dual
+     * quaternion is a dual number. For convenience, we return it in the form of a dual quaternion
+     * , i.e.
+     * \f[ ||\sigma|| = [||p||, 0, 0, 0, \frac{p \cdot q}{||p||}, 0, 0, 0].\f]
+     *
+     * @note The data type of dual number is dual quaternion.
+     */
+    DualQuat<_Tp> norm() const;
+
+    /**
+     * @brief return a normalized dual quaternion.
+     * A dual quaternion can be expressed as
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * \sigma &= p + \epsilon q\\
+     * &=||\sigma||\left(r+\frac{1}{2}tr\right)
+     * \end{split}
+     * \end{equation}
+     * \f]
+     * where \f$r, t\f$ represents the rotation (ordinary quaternion) and translation (pure ordinary quaternion) respectively,
+     * and \f$||\sigma||\f$ is the norm of dual quaternion(a dual number).
+     * A dual quaternion is unit if and only if
+     * \f[
+     * ||p||=1, p \cdot q=0
+     * \f]
+     * where \f$\cdot\f$ means dot product.
+     * The process of normalization is
+     * \f[
+     * \sigma_{u}=\frac{\sigma}{||\sigma||}
+     * \f]
+     * Next, we simply proof \f$\sigma_u\f$ is a unit dual quaternion:
+     * \f[
+     * \renewcommand{\Im}{\operatorname{Im}}
+     * \begin{equation}
+     * \begin{split}
+     * \sigma_{u}=\frac{\sigma}{||\sigma||}&=\frac{p + \epsilon q}{||p||+\epsilon\frac{p\cdot q}{||p||}}\\
+     * &=\frac{p}{||p||}+\epsilon\left(\frac{q}{||p||}-p\frac{p\cdot q}{||p||^3}\right)\\
+     * &=\frac{p}{||p||}+\epsilon\frac{1}{||p||^2}\left(qp^{*}-p\cdot q\right)\frac{p}{||p||}\\
+     * &=\frac{p}{||p||}+\epsilon\frac{1}{||p||^2}\Im(qp^*)\frac{p}{||p||}.\\
+     * \end{split}
+     * \end{equation}
+     * \f]
+     * As expected, the real part is a rotation and dual part is a pure quaternion.
+     */
+    DualQuat<_Tp> normalize() const;
+
+    /**
+     * @brief if \f$\sigma = p + \epsilon q\f$ is a dual quaternion, p is not zero,
+     * the inverse dual quaternion is
+     * \f[\sigma^{-1} = \frac{\sigma^*}{||\sigma||^2}, \f]
+     * or equivalentlly,
+     * \f[\sigma^{-1} = p^{-1} - \epsilon p^{-1}qp^{-1}.\f]
+     * @param dq a dual quaternion.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, dual quaternion dq assume to be a unit dual quaternion
+     * and this function will save some computations.
+     */
+    template <typename T>
+    friend DualQuat<T> inv(const DualQuat<T> &dq, QuatAssumeType assumeUnit);
+
+    /**
+     * @brief if \f$\sigma = p + \epsilon q\f$ is a dual quaternion, p is not zero,
+     * the inverse dual quaternion is
+     * \f[\sigma^{-1} = \frac{\sigma^*}{||\sigma||^2}, \f]
+     * or equivalentlly,
+     * \f[\sigma^{-1} = p^{-1} - \epsilon p^{-1}qp^{-1}.\f]
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, this dual quaternion assume to be a unit dual quaternion
+     * and this function will save some computations.
+     */
+    DualQuat<_Tp> inv(QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+     * @brief return the dot product of two dual quaternion.
+     * @param p other dual quaternion.
+     */
+    _Tp dot(DualQuat<_Tp> p) const;
+
+    /**
+     ** @brief return the value of \f$p^t\f$ where p is a dual quaternion.
+     * This could be calculated as:
+     * \f[
+     * p^t = \exp(t\ln p)
+     * \f]
+     * @param dq a dual quaternion.
+     * @param t index of power function.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, dual quaternion dq assume to be a unit dual quaternion
+     * and this function will save some computations.
+     */
+    template <typename T>
+    friend DualQuat<T> power(const DualQuat<T> &dq, const T t, QuatAssumeType assumeUnit);
+
+    /**
+     ** @brief return the value of \f$p^t\f$ where p is a dual quaternion.
+     * This could be calculated as:
+     * \f[
+     * p^t = \exp(t\ln p)
+     * \f]
+     *
+     * @param t index of power function.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, this dual quaternion assume to be a unit dual quaternion
+     * and this function will save some computations.
+     */
+    DualQuat<_Tp> power(const _Tp t, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+     * @brief return the value of \f$p^q\f$ where p and q are dual quaternions.
+     * This could be calculated as:
+     * \f[
+     * p^q = \exp(q\ln p)
+     * \f]
+     * @param p a dual quaternion.
+     * @param q a dual quaternion.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, dual quaternion p assume to be a dual unit quaternion
+     * and this function will save some computations.
+     */
+    template <typename T>
+    friend DualQuat<T> power(const DualQuat<T>& p, const DualQuat<T>& q, QuatAssumeType assumeUnit);
+
+    /**
+     * @brief return the value of \f$p^q\f$ where p and q are dual quaternions.
+     * This could be calculated as:
+     * \f[
+     * p^q = \exp(q\ln p)
+     * \f]
+     *
+     * @param q a dual quaternion
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, this dual quaternion assume to be a dual unit quaternion
+     * and this function will save some computations.
+     */
+    DualQuat<_Tp> power(const DualQuat<_Tp>& q, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+     * @brief return the value of exponential function value
+     * @param dq a dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> exp(const DualQuat<T> &dq);
+
+    /**
+     * @brief return the value of exponential function value
+     */
+    DualQuat<_Tp> exp() const;
+
+    /**
+     * @brief return the value of logarithm function value
+     *
+     * @param dq a dual quaternion.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, dual quaternion dq assume to be a unit dual quaternion
+     * and this function will save some computations.
+     */
+    template <typename T>
+    friend DualQuat<T> log(const DualQuat<T> &dq, QuatAssumeType assumeUnit);
+
+    /**
+     * @brief return the value of logarithm function value
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, this dual quaternion assume to be a unit dual quaternion
+     * and this function will save some computations.
+     */
+    DualQuat<_Tp> log(QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+     * @brief Transform this dual quaternion to a vector.
+     */
+    Vec<_Tp, 8> toVec() const;
+
+    /**
+     * @brief Transform this dual quaternion to a affine transformation matrix
+     * the form of matrix, see createFromMat().
+     */
+    Matx<_Tp, 4, 4> toMat(QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+      * @brief Transform this dual quaternion to a instance of Affine3.
+      */
+    Affine3<_Tp> toAffine3(QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT) const;
+
+    /**
+     * @brief The screw linear interpolation(ScLERP) is an extension of spherical linear interpolation of dual quaternion.
+     * If \f$\sigma_1\f$ and \f$\sigma_2\f$ are two dual quaternions representing the initial and final pose.
+     * The interpolation of ScLERP function can be defined as:
+     * \f[
+     * ScLERP(t;\sigma_1,\sigma_2) = \sigma_1 * (\sigma_1^{-1} * \sigma_2)^t, t\in[0,1]
+     * \f]
+     *
+     * @param q1 a dual quaternion represents a initial pose.
+     * @param q2 a dual quaternion represents a final pose.
+     * @param t interpolation parameter
+     * @param directChange if true, it always return the shortest path.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, this dual quaternion assume to be a unit dual quaternion
+     * and this function will save some computations.
+     *
+     * For example
+     * ```
+     * double angle1 = CV_PI / 2;
+     * Vec3d axis{0, 0, 1};
+     * Vec3d t(0, 0, 3);
+     * DualQuatd initial = DualQuatd::createFromAngleAxisTrans(angle1, axis, t);
+     * double angle2 = CV_PI;
+     * DualQuatd final = DualQuatd::createFromAngleAxisTrans(angle2, axis, t);
+     * DualQuatd inter = DualQuatd::sclerp(initial, final, 0.5);
+     * ```
+     */
+    static DualQuat<_Tp> sclerp(const DualQuat<_Tp> &q1, const DualQuat<_Tp> &q2, const _Tp t,
+                                bool directChange=true, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT);
+    /**
+     * @brief The method of Dual Quaternion linear Blending(DQB) is to compute a transformation between dual quaternion
+     * \f$q_1\f$ and \f$q_2\f$ and can be defined as:
+     * \f[
+     * DQB(t;{\boldsymbol{q}}_1,{\boldsymbol{q}}_2)=
+     * \frac{(1-t){\boldsymbol{q}}_1+t{\boldsymbol{q}}_2}{||(1-t){\boldsymbol{q}}_1+t{\boldsymbol{q}}_2||}.
+     * \f]
+     * where \f$q_1\f$ and \f$q_2\f$ are unit dual quaternions representing the input transformations.
+     * If you want to use DQB that works for more than two rigid transformations, see @ref gdqblend
+     *
+     * @param q1 a unit dual quaternion representing the input transformations.
+     * @param q2 a unit dual quaternion representing the input transformations.
+     * @param t parameter \f$t\in[0,1]\f$.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, this dual quaternion assume to be a unit dual quaternion
+     * and this function will save some computations.
+     *
+     * @sa gdqblend
+     */
+    static DualQuat<_Tp> dqblend(const DualQuat<_Tp> &q1, const DualQuat<_Tp> &q2, const _Tp t,
+                                   QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT);
+
+    /**
+     * @brief The generalized Dual Quaternion linear Blending works for more than two rigid transformations.
+     * If these transformations are expressed as unit dual quaternions \f$q_1,...,q_n\f$ with convex weights
+     * \f$w = (w_1,...,w_n)\f$, the generalized DQB is simply
+     * \f[
+     * gDQB(\boldsymbol{w};{\boldsymbol{q}}_1,...,{\boldsymbol{q}}_n)=\frac{w_1{\boldsymbol{q}}_1+...+w_n{\boldsymbol{q}}_n}
+     * {||w_1{\boldsymbol{q}}_1+...+w_n{\boldsymbol{q}}_n||}.
+     * \f]
+     * @param dualquat vector of dual quaternions
+     * @param weights vector of weights, the size of weights should be the same as dualquat, and the weights should
+     * satisfy \f$\sum_0^n w_{i} = 1\f$ and \f$w_i>0\f$.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, these dual quaternions assume to be unit quaternions
+     * and this function will save some computations.
+     * @note the type of weights' element should be the same as the date type of dual quaternion inside the dualquat.
+     */
+    template <int cn>
+    static DualQuat<_Tp> gdqblend(const Vec<DualQuat<_Tp>, cn> &dualquat, InputArray weights,
+                                QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT);
+
+    /**
+     * @brief The generalized Dual Quaternion linear Blending works for more than two rigid transformations.
+     * If these transformations are expressed as unit dual quaternions \f$q_1,...,q_n\f$ with convex weights
+     * \f$w = (w_1,...,w_n)\f$, the generalized DQB is simply
+     * \f[
+     * gDQB(\boldsymbol{w};{\boldsymbol{q}}_1,...,{\boldsymbol{q}}_n)=\frac{w_1{\boldsymbol{q}}_1+...+w_n{\boldsymbol{q}}_n}
+     * {||w_1{\boldsymbol{q}}_1+...+w_n{\boldsymbol{q}}_n||}.
+     * \f]
+     * @param dualquat The dual quaternions which have 8 channels and 1 row or 1 col.
+     * @param weights vector of weights, the size of weights should be the same as dualquat, and the weights should
+     * satisfy \f$\sum_0^n w_{i} = 1\f$ and \f$w_i>0\f$.
+     * @param assumeUnit if @ref QUAT_ASSUME_UNIT, these dual quaternions assume to be unit quaternions
+     * and this function will save some computations.
+     * @note the type of weights' element should be the same as the date type of dual quaternion inside the dualquat.
+     */
+    static DualQuat<_Tp> gdqblend(InputArray dualquat, InputArray weights,
+                                QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT);
+
+    /**
+     * @brief Return opposite dual quaternion \f$-p\f$
+     * which satisfies \f$p + (-p) = 0.\f$
+     *
+     * For example
+     * ```
+     * DualQuatd q{1, 2, 3, 4, 5, 6, 7, 8};
+     * std::cout << -q << std::endl; // [-1, -2, -3, -4, -5, -6, -7, -8]
+     * ```
+     */
+    DualQuat<_Tp> operator-() const;
+
+    /**
+     * @brief return true if two dual quaternions p and q are nearly equal, i.e. when the absolute
+     * value of each \f$p_i\f$ and \f$q_i\f$ is less than CV_DUAL_QUAT_EPS.
+     */
+    bool operator==(const DualQuat<_Tp>&) const;
+
+    /**
+     * @brief Subtraction operator of two dual quaternions p and q.
+     * It returns a new dual quaternion that each value is the sum of \f$p_i\f$ and \f$-q_i\f$.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * std::cout << p - q << std::endl; //[-4, -4, -4, -4, 4, -4, -4, -4]
+     * ```
+     */
+    DualQuat<_Tp> operator-(const DualQuat<_Tp>&) const;
+
+    /**
+     * @brief Subtraction assignment operator of two dual quaternions p and q.
+     * It subtracts right operand from the left operand and assign the result to left operand.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * p -= q; // equivalent to p = p - q
+     * std::cout << p << std::endl; //[-4, -4, -4, -4, 4, -4, -4, -4]
+     *
+     * ```
+     */
+    DualQuat<_Tp>& operator-=(const DualQuat<_Tp>&);
+
+    /**
+     * @brief Addition operator of two dual quaternions p and q.
+     * It returns a new dual quaternion that each value is the sum of \f$p_i\f$ and \f$q_i\f$.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * std::cout << p + q << std::endl; //[6, 8, 10, 12, 14, 16, 18, 20]
+     * ```
+     */
+    DualQuat<_Tp> operator+(const DualQuat<_Tp>&) const;
+
+    /**
+     * @brief Addition assignment operator of two dual quaternions p and q.
+     * It adds right operand to the left operand and assign the result to left operand.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * p += q; // equivalent to p = p + q
+     * std::cout << p << std::endl; //[6, 8, 10, 12, 14, 16, 18, 20]
+     *
+     * ```
+     */
+    DualQuat<_Tp>& operator+=(const DualQuat<_Tp>&);
+
+    /**
+     * @brief Multiplication assignment operator of two quaternions.
+     * It multiplies right operand with the left operand and assign the result to left operand.
+     *
+     * Rule of dual quaternion multiplication:
+     * The dual quaternion can be written as an ordered pair of quaternions [A, B]. Thus
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p * q &= [A, B][C, D]\\
+     * &=[AC, AD + BC]
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * p *= q;
+     * std::cout << p << std::endl; //[-60, 12, 30, 24, -216, 80, 124, 120]
+     * ```
+     */
+    DualQuat<_Tp>& operator*=(const DualQuat<_Tp>&);
+
+    /**
+     * @brief Multiplication assignment operator of a quaternions and a scalar.
+     * It multiplies right operand with the left operand and assign the result to left operand.
+     *
+     * Rule of dual quaternion multiplication with a scalar:
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p * s &= [w, x, y, z, w\_, x\_, y\_, z\_] * s\\
+     *  &=[w   s, x   s, y   s, z   s, w\_  \space  s, x\_  \space  s, y\_ \space  s, z\_ \space  s].
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double s = 2.0;
+     * p *= s;
+     * std::cout << p << std::endl; //[2, 4, 6, 8, 10, 12, 14, 16]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    DualQuat<_Tp> operator*=(const _Tp s);
+
+
+    /**
+     * @brief Multiplication operator of two dual quaternions q and p.
+     * Multiplies values on either side of the operator.
+     *
+     * Rule of dual quaternion multiplication:
+     * The dual quaternion can be written as an ordered pair of quaternions [A, B]. Thus
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p * q &= [A, B][C, D]\\
+     * &=[AC, AD + BC]
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * std::cout << p * q << std::endl; //[-60, 12, 30, 24, -216, 80, 124, 120]
+     * ```
+     */
+    DualQuat<_Tp> operator*(const DualQuat<_Tp>&) const;
+
+    /**
+     * @brief Division operator of a dual quaternions and a scalar.
+     * It divides left operand with the right operand and assign the result to left operand.
+     *
+     * Rule of dual quaternion division with a scalar:
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p / s &= [w, x, y, z, w\_, x\_, y\_, z\_] / s\\
+     * &=[w/s, x/s, y/s, z/s, w\_/s, x\_/s, y\_/s, z\_/s].
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double s = 2.0;
+     * p /= s; // equivalent to p = p / s
+     * std::cout << p << std::endl; //[0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4]
+     * ```
+     * @note the type of scalar should be equal to this dual quaternion.
+     */
+    DualQuat<_Tp> operator/(const _Tp s) const;
+
+    /**
+     * @brief Division operator of two dual quaternions p and q.
+     * Divides left hand operand by right hand operand.
+     *
+     * Rule of dual quaternion division with a dual quaternion:
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p / q &= p * q.inv()\\
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * std::cout << p / q << std::endl; // equivalent to p * q.inv()
+     * ```
+     */
+    DualQuat<_Tp> operator/(const DualQuat<_Tp>&) const;
+
+    /**
+     * @brief Division assignment operator of two dual quaternions p and q;
+     * It divides left operand with the right operand and assign the result to left operand.
+     *
+     * Rule of dual quaternion division with a quaternion:
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p / q&= p * q.inv()\\
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * DualQuatd q{5, 6, 7, 8, 9, 10, 11, 12};
+     * p /= q; // equivalent to p = p * q.inv()
+     * std::cout << p << std::endl;
+     * ```
+     */
+    DualQuat<_Tp>& operator/=(const DualQuat<_Tp>&);
+
+    /**
+     * @brief Division assignment operator of a dual quaternions and a scalar.
+     * It divides left operand with the right operand and assign the result to left operand.
+     *
+     * Rule of dual quaternion division with a scalar:
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p / s &= [w, x, y, z, w\_, x\_, y\_ ,z\_] / s\\
+     * &=[w / s, x / s, y / s, z / s, w\_ / \space s, x\_ / \space s, y\_ / \space s, z\_ / \space s].
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double s = 2.0;;
+     * p /= s; // equivalent to p = p / s
+     * std::cout << p << std::endl; //[0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    Quat<_Tp>& operator/=(const _Tp s);
+
+    /**
+     * @brief Addition operator of a scalar and a dual quaternions.
+     * Adds right hand operand from left hand operand.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double scalar = 2.0;
+     * std::cout << scalar + p << std::endl; //[3.0, 2, 3, 4, 5, 6, 7, 8]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> cv::operator+(const T s, const DualQuat<T>&);
+
+    /**
+     * @brief Addition operator of a dual quaternions and a scalar.
+     * Adds right hand operand from left hand operand.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double scalar = 2.0;
+     * std::cout << p + scalar << std::endl; //[3.0, 2, 3, 4, 5, 6, 7, 8]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> cv::operator+(const DualQuat<T>&, const T s);
+
+    /**
+     * @brief Multiplication operator of a scalar and a dual quaternions.
+     * It multiplies right operand with the left operand and assign the result to left operand.
+     *
+     * Rule of dual quaternion multiplication with a scalar:
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p * s &= [w, x, y, z, w\_, x\_, y\_, z\_] * s\\
+     * &=[w s, x s, y s, z s, w\_ \space s, x\_ \space s, y\_ \space s, z\_ \space s].
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double s = 2.0;
+     * std::cout << s * p << std::endl; //[2, 4, 6, 8, 10, 12, 14, 16]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> cv::operator*(const T s, const DualQuat<T>&);
+
+    /**
+     * @brief Subtraction operator of a dual quaternion and a scalar.
+     * Subtracts right hand operand from left hand operand.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double scalar = 2.0;
+     * std::cout << p - scalar << std::endl; //[-1, 2, 3, 4, 5, 6, 7, 8]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> cv::operator-(const DualQuat<T>&, const T s);
+
+    /**
+     * @brief Subtraction operator of a scalar and a dual quaternions.
+     * Subtracts right hand operand from left hand operand.
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double scalar = 2.0;
+     * std::cout << scalar - p << std::endl; //[1.0, -2, -3, -4, -5, -6, -7, -8]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> cv::operator-(const T s, const DualQuat<T>&);
+
+    /**
+     * @brief Multiplication operator of a dual quaternions and a scalar.
+     * It multiplies right operand with the left operand and assign the result to left operand.
+     *
+     * Rule of dual quaternion multiplication with a scalar:
+     * \f[
+     * \begin{equation}
+     * \begin{split}
+     * p * s &= [w, x, y, z, w\_, x\_, y\_, z\_] * s\\
+     * &=[w s, x s, y s, z s, w\_ \space s, x\_ \space s, y\_ \space s, z\_ \space s].
+     * \end{split}
+     * \end{equation}
+     * \f]
+     *
+     * For example
+     * ```
+     * DualQuatd p{1, 2, 3, 4, 5, 6, 7, 8};
+     * double s = 2.0;
+     * std::cout << p * s << std::endl; //[2, 4, 6, 8, 10, 12, 14, 16]
+     * ```
+     * @note the type of scalar should be equal to the dual quaternion.
+     */
+    template <typename T>
+    friend DualQuat<T> cv::operator*(const DualQuat<T>&, const T s);
+
+    template <typename S>
+    friend std::ostream& cv::operator<<(std::ostream&, const DualQuat<S>&);
+
+};
+
+using DualQuatd = DualQuat<double>;
+using DualQuatf = DualQuat<float>;
+
+//! @} core
+}//namespace
+
+#include "dualquaternion.inl.hpp"
+
+#endif /* OPENCV_CORE_QUATERNION_HPP */

GameAssist/GameAssist/include/cv2/opencv2/core/dualquaternion.inl.hpp

@@ -0,0 +1,487 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2020, Huawei Technologies Co., Ltd. All rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//       http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+// Author: Liangqian Kong <kongliangqian@huawei.com>
+//         Longbu Wang <wanglongbu@huawei.com>
+
+#ifndef OPENCV_CORE_DUALQUATERNION_INL_HPP
+#define OPENCV_CORE_DUALQUATERNION_INL_HPP
+
+#ifndef OPENCV_CORE_DUALQUATERNION_HPP
+#error This is not a standalone header. Include dualquaternion.hpp instead.
+#endif
+
+///////////////////////////////////////////////////////////////////////////////////////
+//Implementation
+namespace cv {
+
+template <typename T>
+DualQuat<T>::DualQuat():w(0), x(0), y(0), z(0), w_(0), x_(0), y_(0), z_(0){}
+
+template <typename T>
+DualQuat<T>::DualQuat(const T vw, const T vx, const T vy, const T vz, const T _w, const T _x, const T _y, const T _z):
+                      w(vw), x(vx), y(vy), z(vz), w_(_w), x_(_x), y_(_y), z_(_z){}
+
+template <typename T>
+DualQuat<T>::DualQuat(const Vec<T, 8> &q):w(q[0]), x(q[1]), y(q[2]), z(q[3]),
+                                          w_(q[4]), x_(q[5]), y_(q[6]), z_(q[7]){}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::createFromQuat(const Quat<T> &realPart, const Quat<T> &dualPart)
+{
+    T w = realPart.w;
+    T x = realPart.x;
+    T y = realPart.y;
+    T z = realPart.z;
+    T w_ = dualPart.w;
+    T x_ = dualPart.x;
+    T y_ = dualPart.y;
+    T z_ = dualPart.z;
+    return DualQuat<T>(w, x, y, z, w_, x_, y_, z_);
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::createFromAngleAxisTrans(const T angle, const Vec<T, 3> &axis, const Vec<T, 3> &trans)
+{
+    Quat<T> r = Quat<T>::createFromAngleAxis(angle, axis);
+    Quat<T> t{0, trans[0], trans[1], trans[2]};
+    return createFromQuat(r, t * r * T(0.5));
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::createFromMat(InputArray _R)
+{
+    CV_CheckTypeEQ(_R.type(), cv::traits::Type<T>::value, "");
+    if (_R.size() != Size(4, 4))
+    {
+        CV_Error(Error::StsBadArg, "The input matrix must have 4 columns and 4 rows");
+    }
+    Mat R = _R.getMat();
+    Quat<T> r = Quat<T>::createFromRotMat(R.colRange(0, 3).rowRange(0, 3));
+    Quat<T> trans(0, R.at<T>(0, 3), R.at<T>(1, 3), R.at<T>(2, 3));
+    return createFromQuat(r, trans * r * T(0.5));
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::createFromAffine3(const Affine3<T> &R)
+{
+    return createFromMat(R.matrix);
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::createFromPitch(const T angle, const T d, const Vec<T, 3> &axis, const Vec<T, 3> &moment)
+{
+    T half_angle = angle * T(0.5), half_d = d * T(0.5);
+    Quat<T> qaxis = Quat<T>(0, axis[0], axis[1], axis[2]).normalize();
+    Quat<T> qmoment = Quat<T>(0, moment[0], moment[1], moment[2]);
+    qmoment -= qaxis * axis.dot(moment);
+    Quat<T> dual = -half_d * std::sin(half_angle) + std::sin(half_angle) * qmoment +
+        half_d * std::cos(half_angle) * qaxis;
+    return createFromQuat(Quat<T>::createFromAngleAxis(angle, axis), dual);
+}
+
+template <typename T>
+inline bool DualQuat<T>::operator==(const DualQuat<T> &q) const
+{
+    return (abs(w - q.w) < CV_DUAL_QUAT_EPS && abs(x - q.x) < CV_DUAL_QUAT_EPS &&
+            abs(y - q.y) < CV_DUAL_QUAT_EPS && abs(z - q.z) < CV_DUAL_QUAT_EPS &&
+            abs(w_ - q.w_) < CV_DUAL_QUAT_EPS && abs(x_ - q.x_) < CV_DUAL_QUAT_EPS &&
+            abs(y_ - q.y_) < CV_DUAL_QUAT_EPS && abs(z_ - q.z_) < CV_DUAL_QUAT_EPS);
+}
+
+template <typename T>
+inline Quat<T> DualQuat<T>::getRealPart() const
+{
+    return Quat<T>(w, x, y, z);
+}
+
+template <typename T>
+inline Quat<T> DualQuat<T>::getDualPart() const
+{
+    return Quat<T>(w_, x_, y_, z_);
+}
+
+template <typename T>
+inline DualQuat<T> conjugate(const DualQuat<T> &dq)
+{
+    return dq.conjugate();
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::conjugate() const
+{
+    return DualQuat<T>(w, -x, -y, -z, w_, -x_, -y_, -z_);
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::norm() const
+{
+    Quat<T> real = getRealPart();
+    T realNorm = real.norm();
+    Quat<T> dual = getDualPart();
+    if (realNorm < CV_DUAL_QUAT_EPS){
+        return DualQuat<T>(0, 0, 0, 0, 0, 0, 0, 0);
+    }
+    return DualQuat<T>(realNorm, 0, 0, 0, real.dot(dual) / realNorm, 0, 0, 0);
+}
+
+template <typename T>
+inline Quat<T> DualQuat<T>::getRotation(QuatAssumeType assumeUnit) const
+{
+    if (assumeUnit)
+    {
+        return getRealPart();
+    }
+    return getRealPart().normalize();
+}
+
+template <typename T>
+inline Vec<T, 3> DualQuat<T>::getTranslation(QuatAssumeType assumeUnit) const
+{
+    Quat<T> trans = T(2.0) * (getDualPart() * getRealPart().inv(assumeUnit));
+    return Vec<T, 3>{trans[1], trans[2], trans[3]};
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::normalize() const
+{
+    Quat<T> p = getRealPart();
+    Quat<T> q = getDualPart();
+    T p_norm = p.norm();
+    if (p_norm < CV_DUAL_QUAT_EPS)
+    {
+        CV_Error(Error::StsBadArg, "Cannot normalize this dual quaternion: the norm is too small.");
+    }
+    Quat<T> p_nr = p / p_norm;
+    Quat<T> q_nr = q / p_norm;
+    return createFromQuat(p_nr, q_nr - p_nr * p_nr.dot(q_nr));
+}
+
+template <typename T>
+inline T DualQuat<T>::dot(DualQuat<T> q) const
+{
+    return q.w * w + q.x * x + q.y * y + q.z * z + q.w_ * w_ + q.x_ * x_ + q.y_ * y_ + q.z_ * z_;
+}
+
+template <typename T>
+inline DualQuat<T> inv(const DualQuat<T> &dq, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
+{
+    return dq.inv(assumeUnit);
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::inv(QuatAssumeType assumeUnit) const
+{
+    Quat<T> real = getRealPart();
+    Quat<T> dual = getDualPart();
+    return createFromQuat(real.inv(assumeUnit), -real.inv(assumeUnit) * dual * real.inv(assumeUnit));
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::operator-(const DualQuat<T> &q) const
+{
+    return DualQuat<T>(w - q.w, x - q.x, y - q.y, z - q.z, w_ - q.w_, x_ - q.x_, y_ - q.y_, z_ - q.z_);
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::operator-() const
+{
+    return DualQuat<T>(-w, -x, -y, -z, -w_, -x_, -y_, -z_);
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::operator+(const DualQuat<T> &q) const
+{
+    return DualQuat<T>(w + q.w, x + q.x, y + q.y, z + q.z, w_ + q.w_, x_ + q.x_, y_ + q.y_, z_ + q.z_);
+}
+
+template <typename T>
+inline DualQuat<T>& DualQuat<T>::operator+=(const DualQuat<T> &q)
+{
+    *this = *this + q;
+    return *this;
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::operator*(const DualQuat<T> &q) const
+{
+    Quat<T> A = getRealPart();
+    Quat<T> B = getDualPart();
+    Quat<T> C = q.getRealPart();
+    Quat<T> D = q.getDualPart();
+    return DualQuat<T>::createFromQuat(A * C, A * D + B * C);
+}
+
+template <typename T>
+inline DualQuat<T>& DualQuat<T>::operator*=(const DualQuat<T> &q)
+{
+    *this = *this * q;
+    return *this;
+}
+
+template <typename T>
+inline DualQuat<T> operator+(const T a, const DualQuat<T> &q)
+{
+    return DualQuat<T>(a + q.w, q.x, q.y, q.z, q.w_, q.x_, q.y_, q.z_);
+}
+
+template <typename T>
+inline DualQuat<T> operator+(const DualQuat<T> &q, const T a)
+{
+    return DualQuat<T>(a + q.w, q.x, q.y, q.z, q.w_, q.x_, q.y_, q.z_);
+}
+
+template <typename T>
+inline DualQuat<T> operator-(const DualQuat<T> &q, const T a)
+{
+    return DualQuat<T>(q.w - a, q.x, q.y, q.z, q.w_, q.x_, q.y_, q.z_);
+}
+
+template <typename T>
+inline DualQuat<T>& DualQuat<T>::operator-=(const DualQuat<T> &q)
+{
+    *this = *this - q;
+    return *this;
+}
+
+template <typename T>
+inline DualQuat<T> operator-(const T a, const DualQuat<T> &q)
+{
+    return DualQuat<T>(a - q.w, -q.x, -q.y, -q.z, -q.w_, -q.x_, -q.y_, -q.z_);
+}
+
+template <typename T>
+inline DualQuat<T> operator*(const T a, const DualQuat<T> &q)
+{
+    return DualQuat<T>(q.w * a, q.x * a, q.y * a, q.z * a, q.w_ * a, q.x_ * a, q.y_ * a, q.z_ * a);
+}
+
+template <typename T>
+inline DualQuat<T> operator*(const DualQuat<T> &q, const T a)
+{
+    return DualQuat<T>(q.w * a, q.x * a, q.y * a, q.z * a, q.w_ * a, q.x_ * a, q.y_ * a, q.z_ * a);
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::operator/(const T a) const
+{
+    return DualQuat<T>(w / a, x / a, y / a, z / a, w_ / a, x_ / a, y_ / a, z_ / a);
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::operator/(const DualQuat<T> &q) const
+{
+    return *this * q.inv();
+}
+
+template <typename T>
+inline DualQuat<T>& DualQuat<T>::operator/=(const DualQuat<T> &q)
+{
+    *this = *this / q;
+    return *this;
+}
+
+template <typename T>
+std::ostream & operator<<(std::ostream &os, const DualQuat<T> &q)
+{
+    os << "DualQuat " << Vec<T, 8>{q.w, q.x, q.y, q.z, q.w_, q.x_, q.y_, q.z_};
+    return os;
+}
+
+template <typename T>
+inline DualQuat<T> exp(const DualQuat<T> &dq)
+{
+    return dq.exp();
+}
+
+namespace detail {
+
+template <typename _Tp>
+Matx<_Tp, 4, 4> jacob_exp(const Quat<_Tp> &q)
+{
+    _Tp nv = std::sqrt(q.x * q.x + q.y * q.y + q.z * q.z);
+    _Tp sinc_nv = abs(nv) < cv::DualQuat<_Tp>::CV_DUAL_QUAT_EPS ? _Tp(1.0) - nv * nv * _Tp(1.0/6.0) : std::sin(nv) / nv;
+    _Tp csiii_nv = abs(nv) < cv::DualQuat<_Tp>::CV_DUAL_QUAT_EPS ? -_Tp(1.0/3.0) : (std::cos(nv) - sinc_nv) / nv / nv;
+    Matx<_Tp, 4, 4> J_exp_quat {
+        std::cos(nv), -sinc_nv * q.x,  -sinc_nv * q.y,  -sinc_nv * q.z,
+        sinc_nv * q.x, csiii_nv * q.x * q.x + sinc_nv, csiii_nv * q.x * q.y, csiii_nv * q.x * q.z,
+        sinc_nv * q.y, csiii_nv * q.y * q.x, csiii_nv * q.y * q.y + sinc_nv, csiii_nv * q.y * q.z,
+        sinc_nv * q.z, csiii_nv * q.z * q.x, csiii_nv * q.z * q.y, csiii_nv * q.z * q.z + sinc_nv
+    };
+    return std::exp(q.w) * J_exp_quat;
+}
+
+} // namespace detail
+
+template <typename T>
+DualQuat<T> DualQuat<T>::exp() const
+{
+    Quat<T> real = getRealPart();
+    return createFromQuat(real.exp(), Quat<T>(detail::jacob_exp(real) * getDualPart().toVec()));
+}
+
+template <typename T>
+DualQuat<T> log(const DualQuat<T> &dq, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
+{
+    return dq.log(assumeUnit);
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::log(QuatAssumeType assumeUnit) const
+{
+    Quat<T> plog = getRealPart().log(assumeUnit);
+    Matx<T, 4, 4> jacob = detail::jacob_exp(plog);
+    return createFromQuat(plog, Quat<T>(jacob.inv() * getDualPart().toVec()));
+}
+
+template <typename T>
+inline DualQuat<T> power(const DualQuat<T> &dq, const T t, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
+{
+    return dq.power(t, assumeUnit);
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::power(const T t, QuatAssumeType assumeUnit) const
+{
+    return (t * log(assumeUnit)).exp();
+}
+
+template <typename T>
+inline DualQuat<T> power(const DualQuat<T> &p, const DualQuat<T> &q, QuatAssumeType assumeUnit=QUAT_ASSUME_NOT_UNIT)
+{
+    return p.power(q, assumeUnit);
+}
+
+template <typename T>
+inline DualQuat<T> DualQuat<T>::power(const DualQuat<T> &q, QuatAssumeType assumeUnit) const
+{
+    return (q * log(assumeUnit)).exp();
+}
+
+template <typename T>
+inline Vec<T, 8> DualQuat<T>::toVec() const
+{
+   return Vec<T, 8>(w, x, y, z, w_, x_, y_, z_);
+}
+
+template <typename T>
+Affine3<T> DualQuat<T>::toAffine3(QuatAssumeType assumeUnit) const
+{
+    return Affine3<T>(toMat(assumeUnit));
+}
+
+template <typename T>
+Matx<T, 4, 4> DualQuat<T>::toMat(QuatAssumeType assumeUnit) const
+{
+    Matx<T, 4, 4> rot44 = getRotation(assumeUnit).toRotMat4x4();
+    Vec<T, 3> translation = getTranslation(assumeUnit);
+    rot44(0, 3) = translation[0];
+    rot44(1, 3) = translation[1];
+    rot44(2, 3) = translation[2];
+    return rot44;
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::sclerp(const DualQuat<T> &q0, const DualQuat<T> &q1, const T t, bool directChange, QuatAssumeType assumeUnit)
+{
+    DualQuat<T> v0(q0), v1(q1);
+    if (!assumeUnit)
+    {
+        v0 = v0.normalize();
+        v1 = v1.normalize();
+    }
+    Quat<T> v0Real = v0.getRealPart();
+    Quat<T> v1Real = v1.getRealPart();
+    if (directChange && v1Real.dot(v0Real) < 0)
+    {
+        v0 = -v0;
+    }
+    DualQuat<T> v0inv1 = v0.inv() * v1;
+    return v0 * v0inv1.power(t, QUAT_ASSUME_UNIT);
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::dqblend(const DualQuat<T> &q1, const DualQuat<T> &q2, const T t, QuatAssumeType assumeUnit)
+{
+    DualQuat<T> v1(q1), v2(q2);
+    if (!assumeUnit)
+    {
+        v1 = v1.normalize();
+        v2 = v2.normalize();
+    }
+    if (v1.getRotation(assumeUnit).dot(v2.getRotation(assumeUnit)) < 0)
+    {
+        return ((1 - t) * v1 - t * v2).normalize();
+    }
+    return ((1 - t) * v1 + t * v2).normalize();
+}
+
+template <typename T>
+DualQuat<T> DualQuat<T>::gdqblend(InputArray _dualquat, InputArray _weight, QuatAssumeType assumeUnit)
+{
+    CV_CheckTypeEQ(_weight.type(), cv::traits::Type<T>::value, "");
+    CV_CheckTypeEQ(_dualquat.type(), CV_MAKETYPE(CV_MAT_DEPTH(cv::traits::Type<T>::value), 8), "");
+    Size dq_s = _dualquat.size();
+    if (dq_s != _weight.size() || (dq_s.height != 1 && dq_s.width != 1))
+    {
+        CV_Error(Error::StsBadArg, "The size of weight must be the same as dualquat, both of them should be (1, n) or (n, 1)");
+    }
+    Mat dualquat = _dualquat.getMat(), weight = _weight.getMat();
+    const int cn = std::max(dq_s.width, dq_s.height);
+    if (!assumeUnit)
+    {
+        for (int i = 0; i < cn; ++i)
+        {
+            dualquat.at<Vec<T, 8>>(i) = DualQuat<T>{dualquat.at<Vec<T, 8>>(i)}.normalize().toVec();
+        }
+    }
+    Vec<T, 8> dq_blend = dualquat.at<Vec<T, 8>>(0) * weight.at<T>(0);
+    Quat<T> q0 = DualQuat<T> {dualquat.at<Vec<T, 8>>(0)}.getRotation(assumeUnit);
+    for (int i = 1; i < cn; ++i)
+    {
+        T k = q0.dot(DualQuat<T>{dualquat.at<Vec<T, 8>>(i)}.getRotation(assumeUnit)) < 0 ? -1: 1;
+        dq_blend = dq_blend + dualquat.at<Vec<T, 8>>(i) * k * weight.at<T>(i);
+    }
+    return DualQuat<T>{dq_blend}.normalize();
+}
+
+template <typename T>
+template <int cn>
+DualQuat<T> DualQuat<T>::gdqblend(const Vec<DualQuat<T>, cn> &_dualquat, InputArray _weight, QuatAssumeType assumeUnit)
+{
+    Vec<DualQuat<T>, cn> dualquat(_dualquat);
+    if (cn == 0)
+    {
+        return DualQuat<T>(1, 0, 0, 0, 0, 0, 0, 0);
+    }
+    Mat dualquat_mat(cn, 1, CV_64FC(8));
+    for (int i = 0; i < cn ; ++i)
+    {
+        dualquat_mat.at<Vec<T, 8>>(i) = dualquat[i].toVec();
+    }
+    return gdqblend(dualquat_mat, _weight, assumeUnit);
+}
+
+} //namespace cv
+
+#endif /*OPENCV_CORE_DUALQUATERNION_INL_HPP*/

GameAssist/GameAssist/include/cv2/opencv2/core/eigen.hpp

@@ -0,0 +1,425 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+
+#ifndef OPENCV_CORE_EIGEN_HPP
+#define OPENCV_CORE_EIGEN_HPP
+
+#ifndef EIGEN_WORLD_VERSION
+#error "Wrong usage of OpenCV's Eigen utility header. Include Eigen's headers first. See https://github.com/opencv/opencv/issues/17366"
+#endif
+
+#include "opencv2/core.hpp"
+
+#if defined _MSC_VER && _MSC_VER >= 1200
+#ifndef NOMINMAX
+#define NOMINMAX // fix https://github.com/opencv/opencv/issues/17548
+#endif
+#pragma warning( disable: 4714 ) //__forceinline is not inlined
+#pragma warning( disable: 4127 ) //conditional expression is constant
+#pragma warning( disable: 4244 ) //conversion from '__int64' to 'int', possible loss of data
+#endif
+
+#if !defined(OPENCV_DISABLE_EIGEN_TENSOR_SUPPORT)
+#if EIGEN_WORLD_VERSION == 3 && EIGEN_MAJOR_VERSION >= 3
+#include <unsupported/Eigen/CXX11/Tensor>
+#define OPENCV_EIGEN_TENSOR_SUPPORT 1
+#endif  // EIGEN_WORLD_VERSION == 3 && EIGEN_MAJOR_VERSION >= 3
+#endif  // !defined(OPENCV_DISABLE_EIGEN_TENSOR_SUPPORT)
+
+namespace cv
+{
+
+/** @addtogroup core_eigen
+These functions are provided for OpenCV-Eigen interoperability. They convert `Mat`
+objects to corresponding `Eigen::Matrix` objects and vice-versa. Consult the [Eigen
+documentation](https://eigen.tuxfamily.org/dox/group__TutorialMatrixClass.html) for
+information about the `Matrix` template type.
+
+@note Using these functions requires the `Eigen/Dense` or similar header to be
+included before this header.
+*/
+//! @{
+
+#if defined(OPENCV_EIGEN_TENSOR_SUPPORT) || defined(CV_DOXYGEN)
+/** @brief Converts an Eigen::Tensor to a cv::Mat.
+
+The method converts an Eigen::Tensor with shape (H x W x C) to a cv::Mat where:
+ H = number of rows
+ W = number of columns
+ C = number of channels
+
+Usage:
+\code
+Eigen::Tensor<float, 3, Eigen::RowMajor> a_tensor(...);
+// populate tensor with values
+Mat a_mat;
+eigen2cv(a_tensor, a_mat);
+\endcode
+*/
+template <typename _Tp, int _layout> static inline
+void eigen2cv( const Eigen::Tensor<_Tp, 3, _layout> &src, OutputArray dst )
+{
+    if( !(_layout & Eigen::RowMajorBit) )
+    {
+        const std::array<int, 3> shuffle{2, 1, 0};
+        Eigen::Tensor<_Tp, 3, !_layout> row_major_tensor = src.swap_layout().shuffle(shuffle);
+        Mat _src(src.dimension(0), src.dimension(1), CV_MAKETYPE(DataType<_Tp>::type, src.dimension(2)), row_major_tensor.data());
+        _src.copyTo(dst);
+    }
+    else
+    {
+        Mat _src(src.dimension(0), src.dimension(1), CV_MAKETYPE(DataType<_Tp>::type, src.dimension(2)), (void *)src.data());
+        _src.copyTo(dst);
+    }
+}
+
+/** @brief Converts a cv::Mat to an Eigen::Tensor.
+
+The method converts a cv::Mat to an Eigen Tensor with shape (H x W x C) where:
+ H = number of rows
+ W = number of columns
+ C = number of channels
+
+Usage:
+\code
+Mat a_mat(...);
+// populate Mat with values
+Eigen::Tensor<float, 3, Eigen::RowMajor> a_tensor(...);
+cv2eigen(a_mat, a_tensor);
+\endcode
+*/
+template <typename _Tp, int _layout> static inline
+void cv2eigen( const Mat &src, Eigen::Tensor<_Tp, 3, _layout> &dst )
+{
+    if( !(_layout & Eigen::RowMajorBit) )
+    {
+        Eigen::Tensor<_Tp, 3, !_layout> row_major_tensor(src.rows, src.cols, src.channels());
+        Mat _dst(src.rows, src.cols, CV_MAKETYPE(DataType<_Tp>::type, src.channels()), row_major_tensor.data());
+        if (src.type() == _dst.type())
+            src.copyTo(_dst);
+        else
+            src.convertTo(_dst, _dst.type());
+        const std::array<int, 3> shuffle{2, 1, 0};
+        dst = row_major_tensor.swap_layout().shuffle(shuffle);
+    }
+    else
+    {
+        dst.resize(src.rows, src.cols, src.channels());
+        Mat _dst(src.rows, src.cols, CV_MAKETYPE(DataType<_Tp>::type, src.channels()), dst.data());
+        if (src.type() == _dst.type())
+            src.copyTo(_dst);
+        else
+            src.convertTo(_dst, _dst.type());
+    }
+}
+
+/** @brief Maps cv::Mat data to an Eigen::TensorMap.
+
+The method wraps an existing Mat data array with an Eigen TensorMap of shape (H x W x C) where:
+ H = number of rows
+ W = number of columns
+ C = number of channels
+
+Explicit instantiation of the return type is required.
+
+@note Caller should be aware of the lifetime of the cv::Mat instance and take appropriate safety measures.
+The cv::Mat instance will retain ownership of the data and the Eigen::TensorMap will lose access when the cv::Mat data is deallocated.
+
+The example below initializes a cv::Mat and produces an Eigen::TensorMap:
+\code
+float arr[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11};
+Mat a_mat(2, 2, CV_32FC3, arr);
+Eigen::TensorMap<Eigen::Tensor<float, 3, Eigen::RowMajor>> a_tensormap = cv2eigen_tensormap<float>(a_mat);
+\endcode
+*/
+template <typename _Tp> static inline
+Eigen::TensorMap<Eigen::Tensor<_Tp, 3, Eigen::RowMajor>> cv2eigen_tensormap(InputArray src)
+{
+    Mat mat = src.getMat();
+    CV_CheckTypeEQ(mat.type(), CV_MAKETYPE(traits::Type<_Tp>::value, mat.channels()), "");
+    return Eigen::TensorMap<Eigen::Tensor<_Tp, 3, Eigen::RowMajor>>((_Tp *)mat.data, mat.rows, mat.cols, mat.channels());
+}
+#endif // OPENCV_EIGEN_TENSOR_SUPPORT
+
+template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
+void eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src, OutputArray dst )
+{
+    if( !(src.Flags & Eigen::RowMajorBit) )
+    {
+        Mat _src(src.cols(), src.rows(), traits::Type<_Tp>::value,
+              (void*)src.data(), src.outerStride()*sizeof(_Tp));
+        transpose(_src, dst);
+    }
+    else
+    {
+        Mat _src(src.rows(), src.cols(), traits::Type<_Tp>::value,
+                 (void*)src.data(), src.outerStride()*sizeof(_Tp));
+        _src.copyTo(dst);
+    }
+}
+
+// Matx case
+template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
+void eigen2cv( const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& src,
+               Matx<_Tp, _rows, _cols>& dst )
+{
+    if( !(src.Flags & Eigen::RowMajorBit) )
+    {
+        dst = Matx<_Tp, _cols, _rows>(static_cast<const _Tp*>(src.data())).t();
+    }
+    else
+    {
+        dst = Matx<_Tp, _rows, _cols>(static_cast<const _Tp*>(src.data()));
+    }
+}
+
+template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
+void cv2eigen( const Mat& src,
+               Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst )
+{
+    CV_DbgAssert(src.rows == _rows && src.cols == _cols);
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        if( src.type() == _dst.type() )
+            transpose(src, _dst);
+        else if( src.cols == src.rows )
+        {
+            src.convertTo(_dst, _dst.type());
+            transpose(_dst, _dst);
+        }
+        else
+            Mat(src.t()).convertTo(_dst, _dst.type());
+    }
+    else
+    {
+        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        src.convertTo(_dst, _dst.type());
+    }
+}
+
+// Matx case
+template<typename _Tp, int _rows, int _cols, int _options, int _maxRows, int _maxCols> static inline
+void cv2eigen( const Matx<_Tp, _rows, _cols>& src,
+               Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols>& dst )
+{
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(_cols, _rows, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        transpose(src, _dst);
+    }
+    else
+    {
+        const Mat _dst(_rows, _cols, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        Mat(src).copyTo(_dst);
+    }
+}
+
+template<typename _Tp>  static inline
+void cv2eigen( const Mat& src,
+               Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst )
+{
+    dst.resize(src.rows, src.cols);
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,
+             dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        if( src.type() == _dst.type() )
+            transpose(src, _dst);
+        else if( src.cols == src.rows )
+        {
+            src.convertTo(_dst, _dst.type());
+            transpose(_dst, _dst);
+        }
+        else
+            Mat(src.t()).convertTo(_dst, _dst.type());
+    }
+    else
+    {
+        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        src.convertTo(_dst, _dst.type());
+    }
+}
+
+template<typename _Tp>  static inline
+void cv2eigen( const Mat& src,
+               Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>& dst )
+{
+    CV_CheckEQ(src.dims, 2, "");
+    dst.resize(src.rows, src.cols);
+    const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,
+             dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+    src.convertTo(_dst, _dst.type());
+}
+
+// Matx case
+template<typename _Tp, int _rows, int _cols> static inline
+void cv2eigen( const Matx<_Tp, _rows, _cols>& src,
+               Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic>& dst )
+{
+    dst.resize(_rows, _cols);
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(_cols, _rows, traits::Type<_Tp>::value,
+             dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        transpose(src, _dst);
+    }
+    else
+    {
+        const Mat _dst(_rows, _cols, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        Mat(src).copyTo(_dst);
+    }
+}
+
+template<typename _Tp, int _rows, int _cols> static inline
+void cv2eigen( const Matx<_Tp, _rows, _cols>& src,
+               Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>& dst )
+{
+    CV_CheckEQ(src.dims, 2, "");
+    dst.resize(_rows, _cols);
+    const Mat _dst(_rows, _cols, traits::Type<_Tp>::value,
+                   dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+    Mat(src).copyTo(_dst);
+}
+
+template<typename _Tp> static inline
+void cv2eigen( const Mat& src,
+               Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst )
+{
+    CV_Assert(src.cols == 1);
+    dst.resize(src.rows);
+
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        if( src.type() == _dst.type() )
+            transpose(src, _dst);
+        else
+            Mat(src.t()).convertTo(_dst, _dst.type());
+    }
+    else
+    {
+        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        src.convertTo(_dst, _dst.type());
+    }
+}
+
+// Matx case
+template<typename _Tp, int _rows> static inline
+void cv2eigen( const Matx<_Tp, _rows, 1>& src,
+               Eigen::Matrix<_Tp, Eigen::Dynamic, 1>& dst )
+{
+    dst.resize(_rows);
+
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(1, _rows, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        transpose(src, _dst);
+    }
+    else
+    {
+        const Mat _dst(_rows, 1, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        src.copyTo(_dst);
+    }
+}
+
+
+template<typename _Tp> static inline
+void cv2eigen( const Mat& src,
+               Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst )
+{
+    CV_Assert(src.rows == 1);
+    dst.resize(src.cols);
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        if( src.type() == _dst.type() )
+            transpose(src, _dst);
+        else
+            Mat(src.t()).convertTo(_dst, _dst.type());
+    }
+    else
+    {
+        const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        src.convertTo(_dst, _dst.type());
+    }
+}
+
+//Matx
+template<typename _Tp, int _cols> static inline
+void cv2eigen( const Matx<_Tp, 1, _cols>& src,
+               Eigen::Matrix<_Tp, 1, Eigen::Dynamic>& dst )
+{
+    dst.resize(_cols);
+    if( !(dst.Flags & Eigen::RowMajorBit) )
+    {
+        const Mat _dst(_cols, 1, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        transpose(src, _dst);
+    }
+    else
+    {
+        const Mat _dst(1, _cols, traits::Type<_Tp>::value,
+                 dst.data(), (size_t)(dst.outerStride()*sizeof(_Tp)));
+        Mat(src).copyTo(_dst);
+    }
+}
+
+//! @}
+
+} // cv
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/fast_math.hpp

@@ -0,0 +1,433 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_FAST_MATH_HPP
+#define OPENCV_CORE_FAST_MATH_HPP
+
+#include "opencv2/core/cvdef.h"
+
+//! @addtogroup core_utils
+//! @{
+
+/****************************************************************************************\
+*                                      fast math                                         *
+\****************************************************************************************/
+
+#ifdef __cplusplus
+#  include <cmath>
+#else
+#  ifdef __BORLANDC__
+#    include <fastmath.h>
+#  else
+#    include <math.h>
+#  endif
+#endif
+
+#if defined(__CUDACC__)
+  // nothing, intrinsics/asm code is not supported
+#else
+  #if ((defined _MSC_VER && defined _M_X64) \
+      || (defined __GNUC__ && defined __SSE2__)) \
+      && !defined(OPENCV_SKIP_INCLUDE_EMMINTRIN_H)
+    #include <emmintrin.h>
+  #endif
+
+  #if defined __PPC64__ && defined __GNUC__ && defined _ARCH_PWR8 \
+      && !defined(OPENCV_SKIP_INCLUDE_ALTIVEC_H)
+    #include <altivec.h>
+    #undef vector
+    #undef bool
+    #undef pixel
+  #endif
+
+  #if defined(CV_INLINE_ROUND_FLT)
+    // user-specified version
+    // CV_INLINE_ROUND_DBL should be defined too
+  #elif defined __GNUC__ && defined __arm__ && (defined __ARM_PCS_VFP || defined __ARM_VFPV3__ || defined __ARM_NEON) && !defined __SOFTFP__
+    // 1. general scheme
+    #define ARM_ROUND(_value, _asm_string) \
+        int res; \
+        float temp; \
+        CV_UNUSED(temp); \
+        __asm__(_asm_string : [res] "=r" (res), [temp] "=w" (temp) : [value] "w" (_value)); \
+        return res
+    // 2. version for double
+    #ifdef __clang__
+        #define CV_INLINE_ROUND_DBL(value) ARM_ROUND(value, "vcvtr.s32.f64 %[temp], %[value] \n vmov %[res], %[temp]")
+    #else
+        #define CV_INLINE_ROUND_DBL(value) ARM_ROUND(value, "vcvtr.s32.f64 %[temp], %P[value] \n vmov %[res], %[temp]")
+    #endif
+    // 3. version for float
+    #define CV_INLINE_ROUND_FLT(value) ARM_ROUND(value, "vcvtr.s32.f32 %[temp], %[value]\n vmov %[res], %[temp]")
+  #elif defined __PPC64__ && defined __GNUC__ && defined _ARCH_PWR8
+    // P8 and newer machines can convert fp32/64 to int quickly.
+    #define CV_INLINE_ROUND_DBL(value) \
+        int out; \
+        double temp; \
+        __asm__( "fctiw %[temp],%[in]\n\tmfvsrwz %[out],%[temp]\n\t" : [out] "=r" (out), [temp] "=d" (temp) : [in] "d" ((double)(value)) : ); \
+        return out;
+
+    // FP32 also works with FP64 routine above
+    #define CV_INLINE_ROUND_FLT(value) CV_INLINE_ROUND_DBL(value)
+  #endif
+
+  #ifdef CV_INLINE_ISINF_FLT
+    // user-specified version
+    // CV_INLINE_ISINF_DBL should be defined too
+  #elif defined __PPC64__ && defined _ARCH_PWR9 && defined(scalar_test_data_class)
+    #define CV_INLINE_ISINF_DBL(value) return scalar_test_data_class(value, 0x30);
+    #define CV_INLINE_ISINF_FLT(value) CV_INLINE_ISINF_DBL(value)
+  #endif
+
+  #ifdef CV_INLINE_ISNAN_FLT
+    // user-specified version
+    // CV_INLINE_ISNAN_DBL should be defined too
+  #elif defined __PPC64__ && defined _ARCH_PWR9 && defined(scalar_test_data_class)
+    #define CV_INLINE_ISNAN_DBL(value) return scalar_test_data_class(value, 0x40);
+    #define CV_INLINE_ISNAN_FLT(value) CV_INLINE_ISNAN_DBL(value)
+  #endif
+
+  #if !defined(OPENCV_USE_FASTMATH_BUILTINS) \
+    && ( \
+        defined(__x86_64__) || defined(__i686__) \
+        || defined(__arm__) \
+        || defined(__PPC64__) \
+    )
+    /* Let builtin C math functions when available. Dedicated hardware is available to
+       round and convert FP values. */
+    #define OPENCV_USE_FASTMATH_BUILTINS 1
+  #endif
+
+  /* Enable builtin math functions if possible, desired, and available.
+     Note, not all math functions inline equally. E.g lrint will not inline
+     without the -fno-math-errno option. */
+  #if defined(CV_ICC)
+    // nothing
+  #elif defined(OPENCV_USE_FASTMATH_BUILTINS) && OPENCV_USE_FASTMATH_BUILTINS
+    #if defined(__clang__)
+      #define CV__FASTMATH_ENABLE_CLANG_MATH_BUILTINS
+      #if !defined(CV_INLINE_ISNAN_DBL) && __has_builtin(__builtin_isnan)
+        #define CV_INLINE_ISNAN_DBL(value) return __builtin_isnan(value);
+      #endif
+      #if !defined(CV_INLINE_ISNAN_FLT) && __has_builtin(__builtin_isnan)
+        #define CV_INLINE_ISNAN_FLT(value) return __builtin_isnan(value);
+      #endif
+      #if !defined(CV_INLINE_ISINF_DBL) && __has_builtin(__builtin_isinf)
+        #define CV_INLINE_ISINF_DBL(value) return __builtin_isinf(value);
+      #endif
+      #if !defined(CV_INLINE_ISINF_FLT) && __has_builtin(__builtin_isinf)
+        #define CV_INLINE_ISINF_FLT(value) return __builtin_isinf(value);
+      #endif
+    #elif defined(__GNUC__)
+      #define CV__FASTMATH_ENABLE_GCC_MATH_BUILTINS
+      #if !defined(CV_INLINE_ISNAN_DBL)
+        #define CV_INLINE_ISNAN_DBL(value) return __builtin_isnan(value);
+      #endif
+      #if !defined(CV_INLINE_ISNAN_FLT)
+        #define CV_INLINE_ISNAN_FLT(value) return __builtin_isnanf(value);
+      #endif
+      #if !defined(CV_INLINE_ISINF_DBL)
+        #define CV_INLINE_ISINF_DBL(value) return __builtin_isinf(value);
+      #endif
+      #if !defined(CV_INLINE_ISINF_FLT)
+        #define CV_INLINE_ISINF_FLT(value) return __builtin_isinff(value);
+      #endif
+    #elif defined(_MSC_VER)
+      #if !defined(CV_INLINE_ISNAN_DBL)
+        #define CV_INLINE_ISNAN_DBL(value) return isnan(value);
+      #endif
+      #if !defined(CV_INLINE_ISNAN_FLT)
+        #define CV_INLINE_ISNAN_FLT(value) return isnan(value);
+      #endif
+      #if !defined(CV_INLINE_ISINF_DBL)
+        #define CV_INLINE_ISINF_DBL(value) return isinf(value);
+      #endif
+      #if !defined(CV_INLINE_ISINF_FLT)
+        #define CV_INLINE_ISINF_FLT(value) return isinf(value);
+      #endif
+    #endif
+  #endif
+
+#endif // defined(__CUDACC__)
+
+/** @brief Rounds floating-point number to the nearest integer
+
+ @param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the
+ result is not defined.
+ */
+CV_INLINE int
+cvRound( double value )
+{
+#if defined CV_INLINE_ROUND_DBL
+    CV_INLINE_ROUND_DBL(value);
+#elif ((defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __SSE2__)) && !defined(__CUDACC__)
+    __m128d t = _mm_set_sd( value );
+    return _mm_cvtsd_si32(t);
+#elif defined _MSC_VER && defined _M_IX86
+    int t;
+    __asm
+    {
+        fld value;
+        fistp t;
+    }
+    return t;
+#elif defined CV__FASTMATH_ENABLE_GCC_MATH_BUILTINS || \
+      defined CV__FASTMATH_ENABLE_CLANG_MATH_BUILTINS
+    return (int)__builtin_lrint(value);
+#else
+    return (int)lrint(value);
+#endif
+}
+
+
+/** @brief Rounds floating-point number to the nearest integer not larger than the original.
+
+ The function computes an integer i such that:
+ \f[i \le \texttt{value} < i+1\f]
+ @param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the
+ result is not defined.
+ */
+CV_INLINE int cvFloor( double value )
+{
+#if defined CV__FASTMATH_ENABLE_GCC_MATH_BUILTINS || \
+    defined CV__FASTMATH_ENABLE_CLANG_MATH_BUILTINS
+    return (int)__builtin_floor(value);
+#elif defined __loongarch64
+    int i;
+    double tmp;
+    __asm__ ("ftintrm.l.d     %[tmp],    %[in]       \n\t"
+             "movfr2gr.d      %[i],      %[tmp]      \n\t"
+             : [i] "=r" (i), [tmp] "=f" (tmp)
+             : [in] "f" (value)
+             :);
+    return i;
+#else
+    int i = (int)value;
+    return i - (i > value);
+#endif
+}
+
+/** @brief Rounds floating-point number to the nearest integer not smaller than the original.
+
+ The function computes an integer i such that:
+ \f[i \le \texttt{value} < i+1\f]
+ @param value floating-point number. If the value is outside of INT_MIN ... INT_MAX range, the
+ result is not defined.
+ */
+CV_INLINE int cvCeil( double value )
+{
+#if defined CV__FASTMATH_ENABLE_GCC_MATH_BUILTINS || \
+    defined CV__FASTMATH_ENABLE_CLANG_MATH_BUILTINS
+    return (int)__builtin_ceil(value);
+#elif defined __loongarch64
+    int i;
+    double tmp;
+    __asm__ ("ftintrp.l.d     %[tmp],    %[in]       \n\t"
+             "movfr2gr.d      %[i],      %[tmp]      \n\t"
+             : [i] "=r" (i), [tmp] "=f" (tmp)
+             : [in] "f" (value)
+             :);
+    return i;
+#else
+    int i = (int)value;
+    return i + (i < value);
+#endif
+}
+
+/** @brief Determines if the argument is Not A Number.
+
+ @param value The input floating-point value
+
+ The function returns 1 if the argument is Not A Number (as defined by IEEE754 standard), 0
+ otherwise. */
+CV_INLINE int cvIsNaN( double value )
+{
+#if defined CV_INLINE_ISNAN_DBL
+    CV_INLINE_ISNAN_DBL(value);
+#else
+    Cv64suf ieee754;
+    ieee754.f = value;
+    return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) +
+           ((unsigned)ieee754.u != 0) > 0x7ff00000;
+#endif
+}
+
+/** @brief Determines if the argument is Infinity.
+
+ @param value The input floating-point value
+
+ The function returns 1 if the argument is a plus or minus infinity (as defined by IEEE754 standard)
+ and 0 otherwise. */
+CV_INLINE int cvIsInf( double value )
+{
+#if defined CV_INLINE_ISINF_DBL
+    CV_INLINE_ISINF_DBL(value);
+#elif defined(__x86_64__) || defined(_M_X64) || defined(__aarch64__) || defined(_M_ARM64) || defined(__PPC64__) || defined(__loongarch64)
+    Cv64suf ieee754;
+    ieee754.f = value;
+    return (ieee754.u & 0x7fffffffffffffff) ==
+                        0x7ff0000000000000;
+#else
+    Cv64suf ieee754;
+    ieee754.f = value;
+    return ((unsigned)(ieee754.u >> 32) & 0x7fffffff) == 0x7ff00000 &&
+            (unsigned)ieee754.u == 0;
+#endif
+}
+
+#ifdef __cplusplus
+
+/** @overload */
+CV_INLINE int cvRound(float value)
+{
+#if defined CV_INLINE_ROUND_FLT
+    CV_INLINE_ROUND_FLT(value);
+#elif ((defined _MSC_VER && defined _M_X64) || (defined __GNUC__ && defined __SSE2__)) && !defined(__CUDACC__)
+    __m128 t = _mm_set_ss( value );
+    return _mm_cvtss_si32(t);
+#elif defined _MSC_VER && defined _M_IX86
+    int t;
+    __asm
+    {
+        fld value;
+        fistp t;
+    }
+    return t;
+#elif defined CV__FASTMATH_ENABLE_GCC_MATH_BUILTINS || \
+      defined CV__FASTMATH_ENABLE_CLANG_MATH_BUILTINS
+    return (int)__builtin_lrintf(value);
+#else
+    return (int)lrintf(value);
+#endif
+}
+
+/** @overload */
+CV_INLINE int cvRound( int value )
+{
+    return value;
+}
+
+/** @overload */
+CV_INLINE int cvFloor( float value )
+{
+#if defined CV__FASTMATH_ENABLE_GCC_MATH_BUILTINS || \
+    defined CV__FASTMATH_ENABLE_CLANG_MATH_BUILTINS
+    return (int)__builtin_floorf(value);
+#elif defined __loongarch__
+    int i;
+    float tmp;
+    __asm__ ("ftintrm.w.s     %[tmp],    %[in]       \n\t"
+             "movfr2gr.s      %[i],      %[tmp]      \n\t"
+             : [i] "=r" (i), [tmp] "=f" (tmp)
+             : [in] "f" (value)
+             :);
+    return i;
+#else
+    int i = (int)value;
+    return i - (i > value);
+#endif
+}
+
+/** @overload */
+CV_INLINE int cvFloor( int value )
+{
+    return value;
+}
+
+/** @overload */
+CV_INLINE int cvCeil( float value )
+{
+#if defined CV__FASTMATH_ENABLE_GCC_MATH_BUILTINS || \
+    defined CV__FASTMATH_ENABLE_CLANG_MATH_BUILTINS
+    return (int)__builtin_ceilf(value);
+#elif defined __loongarch__
+    int i;
+    float tmp;
+    __asm__ ("ftintrp.w.s     %[tmp],    %[in]       \n\t"
+             "movfr2gr.s      %[i],      %[tmp]      \n\t"
+             : [i] "=r" (i), [tmp] "=f" (tmp)
+             : [in] "f" (value)
+             :);
+    return i;
+#else
+    int i = (int)value;
+    return i + (i < value);
+#endif
+}
+
+/** @overload */
+CV_INLINE int cvCeil( int value )
+{
+    return value;
+}
+
+/** @overload */
+CV_INLINE int cvIsNaN( float value )
+{
+#if defined CV_INLINE_ISNAN_FLT
+    CV_INLINE_ISNAN_FLT(value);
+#else
+    Cv32suf ieee754;
+    ieee754.f = value;
+    return (ieee754.u & 0x7fffffff) > 0x7f800000;
+#endif
+}
+
+/** @overload */
+CV_INLINE int cvIsInf( float value )
+{
+#if defined CV_INLINE_ISINF_FLT
+    CV_INLINE_ISINF_FLT(value);
+#else
+    Cv32suf ieee754;
+    ieee754.f = value;
+    return (ieee754.u & 0x7fffffff) == 0x7f800000;
+#endif
+}
+
+#endif // __cplusplus
+
+//! @} core_utils
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/hal.hpp

@@ -0,0 +1,260 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_HAL_HPP
+#define OPENCV_HAL_HPP
+
+#include "opencv2/core/cvdef.h"
+#include "opencv2/core/cvstd.hpp"
+#include "opencv2/core/hal/interface.h"
+
+namespace cv { namespace hal {
+
+//! @addtogroup core_hal_functions
+//! @{
+
+CV_EXPORTS int normHamming(const uchar* a, int n);
+CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n);
+
+CV_EXPORTS int normHamming(const uchar* a, int n, int cellSize);
+CV_EXPORTS int normHamming(const uchar* a, const uchar* b, int n, int cellSize);
+
+CV_EXPORTS int LU32f(float* A, size_t astep, int m, float* b, size_t bstep, int n);
+CV_EXPORTS int LU64f(double* A, size_t astep, int m, double* b, size_t bstep, int n);
+CV_EXPORTS bool Cholesky32f(float* A, size_t astep, int m, float* b, size_t bstep, int n);
+CV_EXPORTS bool Cholesky64f(double* A, size_t astep, int m, double* b, size_t bstep, int n);
+CV_EXPORTS void SVD32f(float* At, size_t astep, float* W, float* U, size_t ustep, float* Vt, size_t vstep, int m, int n, int flags);
+CV_EXPORTS void SVD64f(double* At, size_t astep, double* W, double* U, size_t ustep, double* Vt, size_t vstep, int m, int n, int flags);
+CV_EXPORTS int QR32f(float* A, size_t astep, int m, int n, int k, float* b, size_t bstep, float* hFactors);
+CV_EXPORTS int QR64f(double* A, size_t astep, int m, int n, int k, double* b, size_t bstep, double* hFactors);
+
+CV_EXPORTS void gemm32f(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
+                        float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
+                        int m_a, int n_a, int n_d, int flags);
+CV_EXPORTS void gemm64f(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
+                        double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
+                        int m_a, int n_a, int n_d, int flags);
+CV_EXPORTS void gemm32fc(const float* src1, size_t src1_step, const float* src2, size_t src2_step,
+                        float alpha, const float* src3, size_t src3_step, float beta, float* dst, size_t dst_step,
+                        int m_a, int n_a, int n_d, int flags);
+CV_EXPORTS void gemm64fc(const double* src1, size_t src1_step, const double* src2, size_t src2_step,
+                        double alpha, const double* src3, size_t src3_step, double beta, double* dst, size_t dst_step,
+                        int m_a, int n_a, int n_d, int flags);
+
+CV_EXPORTS int normL1_(const uchar* a, const uchar* b, int n);
+CV_EXPORTS float normL1_(const float* a, const float* b, int n);
+CV_EXPORTS float normL2Sqr_(const float* a, const float* b, int n);
+
+CV_EXPORTS void exp32f(const float* src, float* dst, int n);
+CV_EXPORTS void exp64f(const double* src, double* dst, int n);
+CV_EXPORTS void log32f(const float* src, float* dst, int n);
+CV_EXPORTS void log64f(const double* src, double* dst, int n);
+
+CV_EXPORTS void cartToPolar32f(const float* x, const float* y, float* mag, float* angle, int n, bool angleInDegrees);
+CV_EXPORTS void cartToPolar64f(const double* x, const double* y, double* mag, double* angle, int n, bool angleInDegrees);
+CV_EXPORTS void fastAtan32f(const float* y, const float* x, float* dst, int n, bool angleInDegrees);
+CV_EXPORTS void fastAtan64f(const double* y, const double* x, double* dst, int n, bool angleInDegrees);
+CV_EXPORTS void magnitude32f(const float* x, const float* y, float* dst, int n);
+CV_EXPORTS void magnitude64f(const double* x, const double* y, double* dst, int n);
+CV_EXPORTS void polarToCart32f(const float* mag, const float* angle, float* x, float* y, int n, bool angleInDegrees);
+CV_EXPORTS void polarToCart64f(const double* mag, const double* angle, double* x, double* y, int n, bool angleInDegrees);
+CV_EXPORTS void sqrt32f(const float* src, float* dst, int len);
+CV_EXPORTS void sqrt64f(const double* src, double* dst, int len);
+CV_EXPORTS void invSqrt32f(const float* src, float* dst, int len);
+CV_EXPORTS void invSqrt64f(const double* src, double* dst, int len);
+
+CV_EXPORTS void split8u(const uchar* src, uchar** dst, int len, int cn );
+CV_EXPORTS void split16u(const ushort* src, ushort** dst, int len, int cn );
+CV_EXPORTS void split32s(const int* src, int** dst, int len, int cn );
+CV_EXPORTS void split64s(const int64* src, int64** dst, int len, int cn );
+
+CV_EXPORTS void merge8u(const uchar** src, uchar* dst, int len, int cn );
+CV_EXPORTS void merge16u(const ushort** src, ushort* dst, int len, int cn );
+CV_EXPORTS void merge32s(const int** src, int* dst, int len, int cn );
+CV_EXPORTS void merge64s(const int64** src, int64* dst, int len, int cn );
+
+CV_EXPORTS void add8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void add8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void add16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void add16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void add32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void add32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void add64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
+
+CV_EXPORTS void sub8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void sub8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void sub16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void sub16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void sub32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void sub32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void sub64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
+
+CV_EXPORTS void max8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void max8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void max16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void max16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void max32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void max32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void max64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
+
+CV_EXPORTS void min8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void min8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void min16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void min16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void min32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void min32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void min64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
+
+CV_EXPORTS void absdiff8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void absdiff8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void absdiff16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void absdiff16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void absdiff32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void absdiff32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void absdiff64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* );
+
+CV_EXPORTS void and8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void or8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void xor8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+CV_EXPORTS void not8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* );
+
+CV_EXPORTS void cmp8u(const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
+CV_EXPORTS void cmp8s(const schar* src1, size_t step1, const schar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
+CV_EXPORTS void cmp16u(const ushort* src1, size_t step1, const ushort* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
+CV_EXPORTS void cmp16s(const short* src1, size_t step1, const short* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
+CV_EXPORTS void cmp32s(const int* src1, size_t step1, const int* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
+CV_EXPORTS void cmp32f(const float* src1, size_t step1, const float* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
+CV_EXPORTS void cmp64f(const double* src1, size_t step1, const double* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _cmpop);
+
+CV_EXPORTS void mul8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void mul8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void mul16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void mul16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void mul32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void mul32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void mul64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scale);
+
+CV_EXPORTS void div8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void div8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void div16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void div16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void div32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void div32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void div64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scale);
+
+CV_EXPORTS void recip8u( const uchar *, size_t, const uchar * src2, size_t step2, uchar* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void recip8s( const schar *, size_t, const schar * src2, size_t step2, schar* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void recip16u( const ushort *, size_t, const ushort * src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void recip16s( const short *, size_t, const short * src2, size_t step2, short* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void recip32s( const int *, size_t, const int * src2, size_t step2, int* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void recip32f( const float *, size_t, const float * src2, size_t step2, float* dst, size_t step, int width, int height, void* scale);
+CV_EXPORTS void recip64f( const double *, size_t, const double * src2, size_t step2, double* dst, size_t step, int width, int height, void* scale);
+
+CV_EXPORTS void addWeighted8u( const uchar* src1, size_t step1, const uchar* src2, size_t step2, uchar* dst, size_t step, int width, int height, void* _scalars );
+CV_EXPORTS void addWeighted8s( const schar* src1, size_t step1, const schar* src2, size_t step2, schar* dst, size_t step, int width, int height, void* scalars );
+CV_EXPORTS void addWeighted16u( const ushort* src1, size_t step1, const ushort* src2, size_t step2, ushort* dst, size_t step, int width, int height, void* scalars );
+CV_EXPORTS void addWeighted16s( const short* src1, size_t step1, const short* src2, size_t step2, short* dst, size_t step, int width, int height, void* scalars );
+CV_EXPORTS void addWeighted32s( const int* src1, size_t step1, const int* src2, size_t step2, int* dst, size_t step, int width, int height, void* scalars );
+CV_EXPORTS void addWeighted32f( const float* src1, size_t step1, const float* src2, size_t step2, float* dst, size_t step, int width, int height, void* scalars );
+CV_EXPORTS void addWeighted64f( const double* src1, size_t step1, const double* src2, size_t step2, double* dst, size_t step, int width, int height, void* scalars );
+
+CV_EXPORTS void cvt16f32f( const hfloat* src, float* dst, int len );
+CV_EXPORTS void cvt32f16f( const float* src, hfloat* dst, int len );
+
+CV_EXPORTS void addRNGBias32f( float* arr, const float* scaleBiasPairs, int len );
+CV_EXPORTS void addRNGBias64f( double* arr, const double* scaleBiasPairs, int len );
+
+struct CV_EXPORTS DFT1D
+{
+    static Ptr<DFT1D> create(int len, int count, int depth, int flags, bool * useBuffer = 0);
+    virtual void apply(const uchar *src, uchar *dst) = 0;
+    virtual ~DFT1D() {}
+};
+
+struct CV_EXPORTS DFT2D
+{
+    static Ptr<DFT2D> create(int width, int height, int depth,
+                             int src_channels, int dst_channels,
+                             int flags, int nonzero_rows = 0);
+    virtual void apply(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step) = 0;
+    virtual ~DFT2D() {}
+};
+
+struct CV_EXPORTS DCT2D
+{
+    static Ptr<DCT2D> create(int width, int height, int depth, int flags);
+    virtual void apply(const uchar *src_data, size_t src_step, uchar *dst_data, size_t dst_step) = 0;
+    virtual ~DCT2D() {}
+};
+
+//! @} core_hal
+
+//=============================================================================
+// for binary compatibility with 3.0
+
+//! @cond IGNORED
+
+CV_EXPORTS int LU(float* A, size_t astep, int m, float* b, size_t bstep, int n);
+CV_EXPORTS int LU(double* A, size_t astep, int m, double* b, size_t bstep, int n);
+CV_EXPORTS bool Cholesky(float* A, size_t astep, int m, float* b, size_t bstep, int n);
+CV_EXPORTS bool Cholesky(double* A, size_t astep, int m, double* b, size_t bstep, int n);
+
+CV_EXPORTS void exp(const float* src, float* dst, int n);
+CV_EXPORTS void exp(const double* src, double* dst, int n);
+CV_EXPORTS void log(const float* src, float* dst, int n);
+CV_EXPORTS void log(const double* src, double* dst, int n);
+
+CV_EXPORTS void fastAtan2(const float* y, const float* x, float* dst, int n, bool angleInDegrees);
+CV_EXPORTS void magnitude(const float* x, const float* y, float* dst, int n);
+CV_EXPORTS void magnitude(const double* x, const double* y, double* dst, int n);
+CV_EXPORTS void sqrt(const float* src, float* dst, int len);
+CV_EXPORTS void sqrt(const double* src, double* dst, int len);
+CV_EXPORTS void invSqrt(const float* src, float* dst, int len);
+CV_EXPORTS void invSqrt(const double* src, double* dst, int len);
+
+//! @endcond
+
+}} //cv::hal
+
+#endif //OPENCV_HAL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/interface.h

@@ -0,0 +1,190 @@
+#ifndef OPENCV_CORE_HAL_INTERFACE_H
+#define OPENCV_CORE_HAL_INTERFACE_H
+
+//! @addtogroup core_hal_interface
+//! @{
+
+//! @name Return codes
+//! @{
+#define CV_HAL_ERROR_OK 0
+#define CV_HAL_ERROR_NOT_IMPLEMENTED 1
+#define CV_HAL_ERROR_UNKNOWN -1
+//! @}
+
+#ifdef __cplusplus
+#include <cstddef>
+#else
+#include <stddef.h>
+#include <stdbool.h>
+#endif
+
+//! @name Data types
+//! primitive types
+//! - schar  - signed 1 byte integer
+//! - uchar  - unsigned 1 byte integer
+//! - short  - signed 2 byte integer
+//! - ushort - unsigned 2 byte integer
+//! - int    - signed 4 byte integer
+//! - uint   - unsigned 4 byte integer
+//! - int64  - signed 8 byte integer
+//! - uint64 - unsigned 8 byte integer
+//! @{
+#if !defined _MSC_VER && !defined __BORLANDC__
+#  if defined __cplusplus && __cplusplus >= 201103L && !defined __APPLE__
+#    include <cstdint>
+#    ifdef __NEWLIB__
+        typedef unsigned int uint;
+#    else
+        typedef std::uint32_t uint;
+#    endif
+#  else
+#    include <stdint.h>
+     typedef uint32_t uint;
+#  endif
+#else
+   typedef unsigned uint;
+#endif
+
+typedef signed char schar;
+
+#ifndef __IPL_H__
+   typedef unsigned char uchar;
+   typedef unsigned short ushort;
+#endif
+
+#if defined _MSC_VER || defined __BORLANDC__
+   typedef __int64 int64;
+   typedef unsigned __int64 uint64;
+#  define CV_BIG_INT(n)   n##I64
+#  define CV_BIG_UINT(n)  n##UI64
+#else
+   typedef int64_t int64;
+   typedef uint64_t uint64;
+#  define CV_BIG_INT(n)   n##LL
+#  define CV_BIG_UINT(n)  n##ULL
+#endif
+
+#define CV_USRTYPE1 (void)"CV_USRTYPE1 support has been dropped in OpenCV 4.0"
+
+#define CV_CN_MAX     512
+#define CV_CN_SHIFT   3
+#define CV_DEPTH_MAX  (1 << CV_CN_SHIFT)
+
+#define CV_8U   0
+#define CV_8S   1
+#define CV_16U  2
+#define CV_16S  3
+#define CV_32S  4
+#define CV_32F  5
+#define CV_64F  6
+#define CV_16F  7
+
+#define CV_MAT_DEPTH_MASK       (CV_DEPTH_MAX - 1)
+#define CV_MAT_DEPTH(flags)     ((flags) & CV_MAT_DEPTH_MASK)
+
+#define CV_MAKETYPE(depth,cn) (CV_MAT_DEPTH(depth) + (((cn)-1) << CV_CN_SHIFT))
+#define CV_MAKE_TYPE CV_MAKETYPE
+
+#define CV_8UC1 CV_MAKETYPE(CV_8U,1)
+#define CV_8UC2 CV_MAKETYPE(CV_8U,2)
+#define CV_8UC3 CV_MAKETYPE(CV_8U,3)
+#define CV_8UC4 CV_MAKETYPE(CV_8U,4)
+#define CV_8UC(n) CV_MAKETYPE(CV_8U,(n))
+
+#define CV_8SC1 CV_MAKETYPE(CV_8S,1)
+#define CV_8SC2 CV_MAKETYPE(CV_8S,2)
+#define CV_8SC3 CV_MAKETYPE(CV_8S,3)
+#define CV_8SC4 CV_MAKETYPE(CV_8S,4)
+#define CV_8SC(n) CV_MAKETYPE(CV_8S,(n))
+
+#define CV_16UC1 CV_MAKETYPE(CV_16U,1)
+#define CV_16UC2 CV_MAKETYPE(CV_16U,2)
+#define CV_16UC3 CV_MAKETYPE(CV_16U,3)
+#define CV_16UC4 CV_MAKETYPE(CV_16U,4)
+#define CV_16UC(n) CV_MAKETYPE(CV_16U,(n))
+
+#define CV_16SC1 CV_MAKETYPE(CV_16S,1)
+#define CV_16SC2 CV_MAKETYPE(CV_16S,2)
+#define CV_16SC3 CV_MAKETYPE(CV_16S,3)
+#define CV_16SC4 CV_MAKETYPE(CV_16S,4)
+#define CV_16SC(n) CV_MAKETYPE(CV_16S,(n))
+
+#define CV_32SC1 CV_MAKETYPE(CV_32S,1)
+#define CV_32SC2 CV_MAKETYPE(CV_32S,2)
+#define CV_32SC3 CV_MAKETYPE(CV_32S,3)
+#define CV_32SC4 CV_MAKETYPE(CV_32S,4)
+#define CV_32SC(n) CV_MAKETYPE(CV_32S,(n))
+
+#define CV_32FC1 CV_MAKETYPE(CV_32F,1)
+#define CV_32FC2 CV_MAKETYPE(CV_32F,2)
+#define CV_32FC3 CV_MAKETYPE(CV_32F,3)
+#define CV_32FC4 CV_MAKETYPE(CV_32F,4)
+#define CV_32FC(n) CV_MAKETYPE(CV_32F,(n))
+
+#define CV_64FC1 CV_MAKETYPE(CV_64F,1)
+#define CV_64FC2 CV_MAKETYPE(CV_64F,2)
+#define CV_64FC3 CV_MAKETYPE(CV_64F,3)
+#define CV_64FC4 CV_MAKETYPE(CV_64F,4)
+#define CV_64FC(n) CV_MAKETYPE(CV_64F,(n))
+
+#define CV_16FC1 CV_MAKETYPE(CV_16F,1)
+#define CV_16FC2 CV_MAKETYPE(CV_16F,2)
+#define CV_16FC3 CV_MAKETYPE(CV_16F,3)
+#define CV_16FC4 CV_MAKETYPE(CV_16F,4)
+#define CV_16FC(n) CV_MAKETYPE(CV_16F,(n))
+//! @}
+
+//! @name Comparison operation
+//! @sa cv::CmpTypes
+//! @{
+#define CV_HAL_CMP_EQ 0
+#define CV_HAL_CMP_GT 1
+#define CV_HAL_CMP_GE 2
+#define CV_HAL_CMP_LT 3
+#define CV_HAL_CMP_LE 4
+#define CV_HAL_CMP_NE 5
+//! @}
+
+//! @name Border processing modes
+//! @sa cv::BorderTypes
+//! @{
+#define CV_HAL_BORDER_CONSTANT 0
+#define CV_HAL_BORDER_REPLICATE 1
+#define CV_HAL_BORDER_REFLECT 2
+#define CV_HAL_BORDER_WRAP 3
+#define CV_HAL_BORDER_REFLECT_101 4
+#define CV_HAL_BORDER_TRANSPARENT 5
+#define CV_HAL_BORDER_ISOLATED 16
+//! @}
+
+//! @name DFT flags
+//! @{
+#define CV_HAL_DFT_INVERSE        1
+#define CV_HAL_DFT_SCALE          2
+#define CV_HAL_DFT_ROWS           4
+#define CV_HAL_DFT_COMPLEX_OUTPUT 16
+#define CV_HAL_DFT_REAL_OUTPUT    32
+#define CV_HAL_DFT_TWO_STAGE      64
+#define CV_HAL_DFT_STAGE_COLS    128
+#define CV_HAL_DFT_IS_CONTINUOUS 512
+#define CV_HAL_DFT_IS_INPLACE 1024
+//! @}
+
+//! @name SVD flags
+//! @{
+#define CV_HAL_SVD_NO_UV    1
+#define CV_HAL_SVD_SHORT_UV 2
+#define CV_HAL_SVD_MODIFY_A 4
+#define CV_HAL_SVD_FULL_UV  8
+//! @}
+
+//! @name Gemm flags
+//! @{
+#define CV_HAL_GEMM_1_T 1
+#define CV_HAL_GEMM_2_T 2
+#define CV_HAL_GEMM_3_T 4
+//! @}
+
+//! @}
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin.hpp

@@ -0,0 +1,988 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_HAL_INTRIN_HPP
+#define OPENCV_HAL_INTRIN_HPP
+
+#include <cmath>
+#include <float.h>
+#include <stdlib.h>
+#include "opencv2/core/cvdef.h"
+
+#if defined(__GNUC__) && __GNUC__ == 12
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wuninitialized"
+#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
+#endif
+
+#define OPENCV_HAL_ADD(a, b) ((a) + (b))
+#define OPENCV_HAL_AND(a, b) ((a) & (b))
+#define OPENCV_HAL_NOP(a) (a)
+#define OPENCV_HAL_1ST(a, b) (a)
+
+namespace {
+inline unsigned int trailingZeros32(unsigned int value) {
+#if defined(_MSC_VER)
+#if (_MSC_VER < 1700) || defined(_M_ARM) || defined(_M_ARM64) || defined(_M_ARM64EC)
+    unsigned long index = 0;
+    _BitScanForward(&index, value);
+    return (unsigned int)index;
+#elif defined(__clang__)
+    // clang-cl doesn't export _tzcnt_u32 for non BMI systems
+    return value ? __builtin_ctz(value) : 32;
+#else
+    return _tzcnt_u32(value);
+#endif
+#elif defined(__GNUC__) || defined(__GNUG__)
+    return __builtin_ctz(value);
+#elif defined(__ICC) || defined(__INTEL_COMPILER)
+    return _bit_scan_forward(value);
+#elif defined(__clang__)
+    return llvm.cttz.i32(value, true);
+#else
+    static const int MultiplyDeBruijnBitPosition[32] = {
+        0, 1, 28, 2, 29, 14, 24, 3, 30, 22, 20, 15, 25, 17, 4, 8,
+        31, 27, 13, 23, 21, 19, 16, 7, 26, 12, 18, 6, 11, 5, 10, 9 };
+    return MultiplyDeBruijnBitPosition[((uint32_t)((value & -value) * 0x077CB531U)) >> 27];
+#endif
+}
+}
+
+// unlike HAL API, which is in cv::hal,
+// we put intrinsics into cv namespace to make its
+// access from within opencv code more accessible
+namespace cv {
+
+namespace hal {
+
+enum StoreMode
+{
+    STORE_UNALIGNED = 0,
+    STORE_ALIGNED = 1,
+    STORE_ALIGNED_NOCACHE = 2
+};
+
+}
+
+// TODO FIXIT: Don't use "God" traits. Split on separate cases.
+template<typename _Tp> struct V_TypeTraits
+{
+};
+
+#define CV_INTRIN_DEF_TYPE_TRAITS(type, int_type_, uint_type_, abs_type_, w_type_, q_type_, sum_type_) \
+    template<> struct V_TypeTraits<type> \
+    { \
+        typedef type value_type; \
+        typedef int_type_ int_type; \
+        typedef abs_type_ abs_type; \
+        typedef uint_type_ uint_type; \
+        typedef w_type_ w_type; \
+        typedef q_type_ q_type; \
+        typedef sum_type_ sum_type; \
+    \
+        static inline int_type reinterpret_int(type x) \
+        { \
+            union { type l; int_type i; } v; \
+            v.l = x; \
+            return v.i; \
+        } \
+    \
+        static inline type reinterpret_from_int(int_type x) \
+        { \
+            union { type l; int_type i; } v; \
+            v.i = x; \
+            return v.l; \
+        } \
+    }
+
+#define CV_INTRIN_DEF_TYPE_TRAITS_NO_Q_TYPE(type, int_type_, uint_type_, abs_type_, w_type_, sum_type_) \
+    template<> struct V_TypeTraits<type> \
+    { \
+        typedef type value_type; \
+        typedef int_type_ int_type; \
+        typedef abs_type_ abs_type; \
+        typedef uint_type_ uint_type; \
+        typedef w_type_ w_type; \
+        typedef sum_type_ sum_type; \
+    \
+        static inline int_type reinterpret_int(type x) \
+        { \
+            union { type l; int_type i; } v; \
+            v.l = x; \
+            return v.i; \
+        } \
+    \
+        static inline type reinterpret_from_int(int_type x) \
+        { \
+            union { type l; int_type i; } v; \
+            v.i = x; \
+            return v.l; \
+        } \
+    }
+
+CV_INTRIN_DEF_TYPE_TRAITS(uchar, schar, uchar, uchar, ushort, unsigned, unsigned);
+CV_INTRIN_DEF_TYPE_TRAITS(schar, schar, uchar, uchar, short, int, int);
+CV_INTRIN_DEF_TYPE_TRAITS(ushort, short, ushort, ushort, unsigned, uint64, unsigned);
+CV_INTRIN_DEF_TYPE_TRAITS(short, short, ushort, ushort, int, int64, int);
+CV_INTRIN_DEF_TYPE_TRAITS_NO_Q_TYPE(unsigned, int, unsigned, unsigned, uint64, unsigned);
+CV_INTRIN_DEF_TYPE_TRAITS_NO_Q_TYPE(int, int, unsigned, unsigned, int64, int);
+CV_INTRIN_DEF_TYPE_TRAITS_NO_Q_TYPE(float, int, unsigned, float, double, float);
+CV_INTRIN_DEF_TYPE_TRAITS_NO_Q_TYPE(uint64, int64, uint64, uint64, void, uint64);
+CV_INTRIN_DEF_TYPE_TRAITS_NO_Q_TYPE(int64, int64, uint64, uint64, void, int64);
+CV_INTRIN_DEF_TYPE_TRAITS_NO_Q_TYPE(double, int64, uint64, double, void, double);
+
+#ifndef CV_DOXYGEN
+
+#ifndef CV_CPU_OPTIMIZATION_HAL_NAMESPACE
+#ifdef CV_FORCE_SIMD128_CPP
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE hal_EMULATOR_CPP
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN namespace hal_EMULATOR_CPP {
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END }
+#elif defined(CV_CPU_DISPATCH_MODE)
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE __CV_CAT(hal_, CV_CPU_DISPATCH_MODE)
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN namespace __CV_CAT(hal_, CV_CPU_DISPATCH_MODE) {
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END }
+#else
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE hal_baseline
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN namespace hal_baseline {
+    #define CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END }
+#endif
+#endif // CV_CPU_OPTIMIZATION_HAL_NAMESPACE
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+template <typename _VecTp> inline _VecTp v_setzero_();
+template <typename _VecTp> inline _VecTp v_setall_(uchar);
+template <typename _VecTp> inline _VecTp v_setall_(schar);
+template <typename _VecTp> inline _VecTp v_setall_(ushort);
+template <typename _VecTp> inline _VecTp v_setall_(short);
+template <typename _VecTp> inline _VecTp v_setall_(unsigned);
+template <typename _VecTp> inline _VecTp v_setall_(int);
+template <typename _VecTp> inline _VecTp v_setall_(uint64);
+template <typename _VecTp> inline _VecTp v_setall_(int64);
+template <typename _VecTp> inline _VecTp v_setall_(float);
+template <typename _VecTp> inline _VecTp v_setall_(double);
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+using namespace CV_CPU_OPTIMIZATION_HAL_NAMESPACE;
+#endif
+}
+
+#ifdef CV_DOXYGEN
+#   undef CV_AVX2
+#   undef CV_SSE2
+#   undef CV_NEON
+#   undef CV_VSX
+#   undef CV_FP16
+#   undef CV_MSA
+#   undef CV_RVV
+#endif
+
+#if (CV_SSE2 || CV_NEON || CV_VSX || CV_MSA || CV_WASM_SIMD || CV_RVV071 || CV_LSX) && !defined(CV_FORCE_SIMD128_CPP)
+#define CV__SIMD_FORWARD 128
+#include "opencv2/core/hal/intrin_forward.hpp"
+#endif
+
+#if CV_SSE2 && !defined(CV_FORCE_SIMD128_CPP)
+
+#include "opencv2/core/hal/intrin_sse_em.hpp"
+#include "opencv2/core/hal/intrin_sse.hpp"
+
+#elif CV_NEON && !defined(CV_FORCE_SIMD128_CPP)
+
+#include "opencv2/core/hal/intrin_neon.hpp"
+
+#elif CV_RVV071 && !defined(CV_FORCE_SIMD128_CPP)
+#define CV_SIMD128_CPP 0
+#include "opencv2/core/hal/intrin_rvv071.hpp"
+
+#elif CV_VSX && !defined(CV_FORCE_SIMD128_CPP)
+
+#include "opencv2/core/hal/intrin_vsx.hpp"
+
+#elif CV_MSA && !defined(CV_FORCE_SIMD128_CPP)
+
+#include "opencv2/core/hal/intrin_msa.hpp"
+
+#elif CV_WASM_SIMD && !defined(CV_FORCE_SIMD128_CPP)
+#include "opencv2/core/hal/intrin_wasm.hpp"
+
+#elif CV_RVV && !defined(CV_FORCE_SIMD128_CPP)
+#include "opencv2/core/hal/intrin_rvv_scalable.hpp"
+
+#elif CV_LSX && !defined(CV_FORCE_SIMD128_CPP)
+
+#include "opencv2/core/hal/intrin_lsx.hpp"
+
+#else
+
+#include "opencv2/core/hal/intrin_cpp.hpp"
+
+#endif
+
+// AVX2 can be used together with SSE2, so
+// we define those two sets of intrinsics at once.
+// Most of the intrinsics do not conflict (the proper overloaded variant is
+// resolved by the argument types, e.g. v_float32x4 ~ SSE2, v_float32x8 ~ AVX2),
+// but some of AVX2 intrinsics get v256_ prefix instead of v_, e.g. v256_load() vs v_load().
+// Correspondingly, the wide intrinsics (which are mapped to the "widest"
+// available instruction set) will get vx_ prefix
+// (and will be mapped to v256_ counterparts) (e.g. vx_load() => v256_load())
+#if CV_AVX2
+
+#define CV__SIMD_FORWARD 256
+#include "opencv2/core/hal/intrin_forward.hpp"
+#include "opencv2/core/hal/intrin_avx.hpp"
+
+#endif
+
+// AVX512 can be used together with SSE2 and AVX2, so
+// we define those sets of intrinsics at once.
+// For some of AVX512 intrinsics get v512_ prefix instead of v_, e.g. v512_load() vs v_load().
+// Wide intrinsics will be mapped to v512_ counterparts in this case(e.g. vx_load() => v512_load())
+#if CV_AVX512_SKX
+
+#define CV__SIMD_FORWARD 512
+#include "opencv2/core/hal/intrin_forward.hpp"
+#include "opencv2/core/hal/intrin_avx512.hpp"
+
+#endif
+
+#if CV_LASX
+
+#define CV__SIMD_FORWARD 256
+#include "opencv2/core/hal/intrin_forward.hpp"
+#include "opencv2/core/hal/intrin_lasx.hpp"
+
+#endif
+
+//! @cond IGNORED
+
+namespace cv {
+
+#ifndef CV_DOXYGEN
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+#endif
+
+#ifndef CV_SIMD128
+#define CV_SIMD128 0
+#endif
+
+#ifndef CV_SIMD128_CPP
+#define CV_SIMD128_CPP 0
+#endif
+
+#ifndef CV_SIMD128_64F
+#define CV_SIMD128_64F 0
+#endif
+
+#ifndef CV_SIMD256
+#define CV_SIMD256 0
+#endif
+
+#ifndef CV_SIMD256_64F
+#define CV_SIMD256_64F 0
+#endif
+
+#ifndef CV_SIMD512
+#define CV_SIMD512 0
+#endif
+
+#ifndef CV_SIMD512_64F
+#define CV_SIMD512_64F 0
+#endif
+
+#ifndef CV_SIMD128_FP16
+#define CV_SIMD128_FP16 0
+#endif
+
+#ifndef CV_SIMD256_FP16
+#define CV_SIMD256_FP16 0
+#endif
+
+#ifndef CV_SIMD512_FP16
+#define CV_SIMD512_FP16 0
+#endif
+
+#ifndef CV_SIMD_SCALABLE
+#define CV_SIMD_SCALABLE 0
+#endif
+
+#ifndef CV_SIMD_SCALABLE_64F
+#define CV_SIMD_SCALABLE_64F 0
+#endif
+
+//==================================================================================================
+
+template<typename _Tp> struct V_RegTraits
+{
+};
+
+#define CV_DEF_REG_TRAITS(prefix, _reg, lane_type, suffix, _u_reg, _w_reg, _q_reg, _int_reg, _round_reg) \
+    template<> struct V_RegTraits<_reg> \
+    { \
+        typedef _reg reg; \
+        typedef _u_reg u_reg; \
+        typedef _w_reg w_reg; \
+        typedef _q_reg q_reg; \
+        typedef _int_reg int_reg; \
+        typedef _round_reg round_reg; \
+    }
+
+#if CV_SIMD128 || CV_SIMD128_CPP
+    CV_DEF_REG_TRAITS(v, v_uint8x16, uchar, u8, v_uint8x16, v_uint16x8, v_uint32x4, v_int8x16, void);
+    CV_DEF_REG_TRAITS(v, v_int8x16, schar, s8, v_uint8x16, v_int16x8, v_int32x4, v_int8x16, void);
+    CV_DEF_REG_TRAITS(v, v_uint16x8, ushort, u16, v_uint16x8, v_uint32x4, v_uint64x2, v_int16x8, void);
+    CV_DEF_REG_TRAITS(v, v_int16x8, short, s16, v_uint16x8, v_int32x4, v_int64x2, v_int16x8, void);
+    CV_DEF_REG_TRAITS(v, v_uint32x4, unsigned, u32, v_uint32x4, v_uint64x2, void, v_int32x4, void);
+    CV_DEF_REG_TRAITS(v, v_int32x4, int, s32, v_uint32x4, v_int64x2, void, v_int32x4, void);
+#if CV_SIMD128_64F || CV_SIMD128_CPP
+    CV_DEF_REG_TRAITS(v, v_float32x4, float, f32, v_float32x4, v_float64x2, void, v_int32x4, v_int32x4);
+#else
+    CV_DEF_REG_TRAITS(v, v_float32x4, float, f32, v_float32x4, void, void, v_int32x4, v_int32x4);
+#endif
+    CV_DEF_REG_TRAITS(v, v_uint64x2, uint64, u64, v_uint64x2, void, void, v_int64x2, void);
+    CV_DEF_REG_TRAITS(v, v_int64x2, int64, s64, v_uint64x2, void, void, v_int64x2, void);
+#if CV_SIMD128_64F
+    CV_DEF_REG_TRAITS(v, v_float64x2, double, f64, v_float64x2, void, void, v_int64x2, v_int32x4);
+#endif
+#endif
+
+#if CV_SIMD256
+    CV_DEF_REG_TRAITS(v256, v_uint8x32, uchar, u8, v_uint8x32, v_uint16x16, v_uint32x8, v_int8x32, void);
+    CV_DEF_REG_TRAITS(v256, v_int8x32, schar, s8, v_uint8x32, v_int16x16, v_int32x8, v_int8x32, void);
+    CV_DEF_REG_TRAITS(v256, v_uint16x16, ushort, u16, v_uint16x16, v_uint32x8, v_uint64x4, v_int16x16, void);
+    CV_DEF_REG_TRAITS(v256, v_int16x16, short, s16, v_uint16x16, v_int32x8, v_int64x4, v_int16x16, void);
+    CV_DEF_REG_TRAITS(v256, v_uint32x8, unsigned, u32, v_uint32x8, v_uint64x4, void, v_int32x8, void);
+    CV_DEF_REG_TRAITS(v256, v_int32x8, int, s32, v_uint32x8, v_int64x4, void, v_int32x8, void);
+    CV_DEF_REG_TRAITS(v256, v_float32x8, float, f32, v_float32x8, v_float64x4, void, v_int32x8, v_int32x8);
+    CV_DEF_REG_TRAITS(v256, v_uint64x4, uint64, u64, v_uint64x4, void, void, v_int64x4, void);
+    CV_DEF_REG_TRAITS(v256, v_int64x4, int64, s64, v_uint64x4, void, void, v_int64x4, void);
+    CV_DEF_REG_TRAITS(v256, v_float64x4, double, f64, v_float64x4, void, void, v_int64x4, v_int32x8);
+#endif
+
+#if CV_SIMD512
+    CV_DEF_REG_TRAITS(v512, v_uint8x64, uchar, u8, v_uint8x64, v_uint16x32, v_uint32x16, v_int8x64, void);
+    CV_DEF_REG_TRAITS(v512, v_int8x64, schar, s8, v_uint8x64, v_int16x32, v_int32x16, v_int8x64, void);
+    CV_DEF_REG_TRAITS(v512, v_uint16x32, ushort, u16, v_uint16x32, v_uint32x16, v_uint64x8, v_int16x32, void);
+    CV_DEF_REG_TRAITS(v512, v_int16x32, short, s16, v_uint16x32, v_int32x16, v_int64x8, v_int16x32, void);
+    CV_DEF_REG_TRAITS(v512, v_uint32x16, unsigned, u32, v_uint32x16, v_uint64x8, void, v_int32x16, void);
+    CV_DEF_REG_TRAITS(v512, v_int32x16, int, s32, v_uint32x16, v_int64x8, void, v_int32x16, void);
+    CV_DEF_REG_TRAITS(v512, v_float32x16, float, f32, v_float32x16, v_float64x8, void, v_int32x16, v_int32x16);
+    CV_DEF_REG_TRAITS(v512, v_uint64x8, uint64, u64, v_uint64x8, void, void, v_int64x8, void);
+    CV_DEF_REG_TRAITS(v512, v_int64x8, int64, s64, v_uint64x8, void, void, v_int64x8, void);
+    CV_DEF_REG_TRAITS(v512, v_float64x8, double, f64, v_float64x8, void, void, v_int64x8, v_int32x16);
+#endif
+#if CV_SIMD_SCALABLE
+    CV_DEF_REG_TRAITS(v, v_uint8, uchar, u8, v_uint8, v_uint16, v_uint32, v_int8, void);
+    CV_DEF_REG_TRAITS(v, v_int8, schar, s8, v_uint8, v_int16, v_int32, v_int8, void);
+    CV_DEF_REG_TRAITS(v, v_uint16, ushort, u16, v_uint16, v_uint32, v_uint64, v_int16, void);
+    CV_DEF_REG_TRAITS(v, v_int16, short, s16, v_uint16, v_int32, v_int64, v_int16, void);
+    CV_DEF_REG_TRAITS(v, v_uint32, unsigned, u32, v_uint32, v_uint64, void, v_int32, void);
+    CV_DEF_REG_TRAITS(v, v_int32, int, s32, v_uint32, v_int64, void, v_int32, void);
+    CV_DEF_REG_TRAITS(v, v_float32, float, f32, v_float32, v_float64, void, v_int32, v_int32);
+    CV_DEF_REG_TRAITS(v, v_uint64, uint64, u64, v_uint64, void, void, v_int64, void);
+    CV_DEF_REG_TRAITS(v, v_int64, int64, s64, v_uint64, void, void, v_int64, void);
+    CV_DEF_REG_TRAITS(v, v_float64, double, f64, v_float64, void, void, v_int64, v_int32);
+#endif
+//! @endcond
+
+#if CV_SIMD512 && (!defined(CV__SIMD_FORCE_WIDTH) || CV__SIMD_FORCE_WIDTH == 512)
+#define CV__SIMD_NAMESPACE simd512
+namespace CV__SIMD_NAMESPACE {
+    #define CV_SIMD 1
+    #define CV_SIMD_64F CV_SIMD512_64F
+    #define CV_SIMD_FP16 CV_SIMD512_FP16
+    #define CV_SIMD_WIDTH 64
+//! @addtogroup core_hal_intrin
+//! @{
+    //! @brief Maximum available vector register capacity 8-bit unsigned integer values
+    typedef v_uint8x64    v_uint8;
+    //! @brief Maximum available vector register capacity 8-bit signed integer values
+    typedef v_int8x64     v_int8;
+    //! @brief Maximum available vector register capacity 16-bit unsigned integer values
+    typedef v_uint16x32   v_uint16;
+    //! @brief Maximum available vector register capacity 16-bit signed integer values
+    typedef v_int16x32    v_int16;
+    //! @brief Maximum available vector register capacity 32-bit unsigned integer values
+    typedef v_uint32x16   v_uint32;
+    //! @brief Maximum available vector register capacity 32-bit signed integer values
+    typedef v_int32x16    v_int32;
+    //! @brief Maximum available vector register capacity 64-bit unsigned integer values
+    typedef v_uint64x8    v_uint64;
+    //! @brief Maximum available vector register capacity 64-bit signed integer values
+    typedef v_int64x8     v_int64;
+    //! @brief Maximum available vector register capacity 32-bit floating point values (single precision)
+    typedef v_float32x16  v_float32;
+    #if CV_SIMD512_64F
+    //! @brief Maximum available vector register capacity 64-bit floating point values (double precision)
+    typedef v_float64x8   v_float64;
+    #endif
+//! @}
+
+    #define VXPREFIX(func) v512##func
+} // namespace
+using namespace CV__SIMD_NAMESPACE;
+#elif CV_SIMD256 && (!defined(CV__SIMD_FORCE_WIDTH) || CV__SIMD_FORCE_WIDTH == 256)
+#define CV__SIMD_NAMESPACE simd256
+namespace CV__SIMD_NAMESPACE {
+    #define CV_SIMD 1
+    #define CV_SIMD_64F CV_SIMD256_64F
+    #define CV_SIMD_FP16 CV_SIMD256_FP16
+    #define CV_SIMD_WIDTH 32
+//! @addtogroup core_hal_intrin
+//! @{
+    //! @brief Maximum available vector register capacity 8-bit unsigned integer values
+    typedef v_uint8x32   v_uint8;
+    //! @brief Maximum available vector register capacity 8-bit signed integer values
+    typedef v_int8x32    v_int8;
+    //! @brief Maximum available vector register capacity 16-bit unsigned integer values
+    typedef v_uint16x16  v_uint16;
+    //! @brief Maximum available vector register capacity 16-bit signed integer values
+    typedef v_int16x16   v_int16;
+    //! @brief Maximum available vector register capacity 32-bit unsigned integer values
+    typedef v_uint32x8   v_uint32;
+    //! @brief Maximum available vector register capacity 32-bit signed integer values
+    typedef v_int32x8    v_int32;
+    //! @brief Maximum available vector register capacity 64-bit unsigned integer values
+    typedef v_uint64x4   v_uint64;
+    //! @brief Maximum available vector register capacity 64-bit signed integer values
+    typedef v_int64x4    v_int64;
+    //! @brief Maximum available vector register capacity 32-bit floating point values (single precision)
+    typedef v_float32x8  v_float32;
+    #if CV_SIMD256_64F
+    //! @brief Maximum available vector register capacity 64-bit floating point values (double precision)
+    typedef v_float64x4  v_float64;
+    #endif
+//! @}
+
+    #define VXPREFIX(func) v256##func
+} // namespace
+using namespace CV__SIMD_NAMESPACE;
+#elif (CV_SIMD128 || CV_SIMD128_CPP) && (!defined(CV__SIMD_FORCE_WIDTH) || CV__SIMD_FORCE_WIDTH == 128)
+#if defined CV_SIMD128_CPP
+#define CV__SIMD_NAMESPACE simd128_cpp
+#else
+#define CV__SIMD_NAMESPACE simd128
+#endif
+namespace CV__SIMD_NAMESPACE {
+    #define CV_SIMD CV_SIMD128
+    #define CV_SIMD_64F CV_SIMD128_64F
+    #define CV_SIMD_WIDTH 16
+//! @addtogroup core_hal_intrin
+//! @{
+    //! @brief Maximum available vector register capacity 8-bit unsigned integer values
+    typedef v_uint8x16  v_uint8;
+    //! @brief Maximum available vector register capacity 8-bit signed integer values
+    typedef v_int8x16   v_int8;
+    //! @brief Maximum available vector register capacity 16-bit unsigned integer values
+    typedef v_uint16x8  v_uint16;
+    //! @brief Maximum available vector register capacity 16-bit signed integer values
+    typedef v_int16x8   v_int16;
+    //! @brief Maximum available vector register capacity 32-bit unsigned integer values
+    typedef v_uint32x4  v_uint32;
+    //! @brief Maximum available vector register capacity 32-bit signed integer values
+    typedef v_int32x4   v_int32;
+    //! @brief Maximum available vector register capacity 64-bit unsigned integer values
+    typedef v_uint64x2  v_uint64;
+    //! @brief Maximum available vector register capacity 64-bit signed integer values
+    typedef v_int64x2   v_int64;
+    //! @brief Maximum available vector register capacity 32-bit floating point values (single precision)
+    typedef v_float32x4 v_float32;
+    #if CV_SIMD128_64F
+    //! @brief Maximum available vector register capacity 64-bit floating point values (double precision)
+    typedef v_float64x2 v_float64;
+    #endif
+//! @}
+
+    #define VXPREFIX(func) v##func
+} // namespace
+using namespace CV__SIMD_NAMESPACE;
+
+#elif CV_SIMD_SCALABLE
+#define CV__SIMD_NAMESPACE simd
+namespace CV__SIMD_NAMESPACE {
+    #define CV_SIMD 0
+    #define CV_SIMD_WIDTH 128  /* 1024/8 */
+
+    #define VXPREFIX(func) v##func
+} // namespace
+using namespace CV__SIMD_NAMESPACE;
+
+#endif
+
+//! @cond IGNORED
+#ifndef CV_SIMD_64F
+#define CV_SIMD_64F 0
+#endif
+
+namespace CV__SIMD_NAMESPACE {
+//! @addtogroup core_hal_intrin
+//! @{
+    //! @name Wide init with value
+    //! @{
+    //! @brief Create maximum available capacity vector with elements set to a specific value
+    inline v_uint8 vx_setall_u8(uchar v) { return VXPREFIX(_setall_u8)(v); }
+    inline v_int8 vx_setall_s8(schar v) { return VXPREFIX(_setall_s8)(v); }
+    inline v_uint16 vx_setall_u16(ushort v) { return VXPREFIX(_setall_u16)(v); }
+    inline v_int16 vx_setall_s16(short v) { return VXPREFIX(_setall_s16)(v); }
+    inline v_int32 vx_setall_s32(int v) { return VXPREFIX(_setall_s32)(v); }
+    inline v_uint32 vx_setall_u32(unsigned v) { return VXPREFIX(_setall_u32)(v); }
+    inline v_float32 vx_setall_f32(float v) { return VXPREFIX(_setall_f32)(v); }
+    inline v_int64 vx_setall_s64(int64 v) { return VXPREFIX(_setall_s64)(v); }
+    inline v_uint64 vx_setall_u64(uint64 v) { return VXPREFIX(_setall_u64)(v); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_setall_f64(double v) { return VXPREFIX(_setall_f64)(v); }
+#endif
+    //! @}
+
+    //! @name Wide init with zero
+    //! @{
+    //! @brief Create maximum available capacity vector with elements set to zero
+    inline v_uint8 vx_setzero_u8() { return VXPREFIX(_setzero_u8)(); }
+    inline v_int8 vx_setzero_s8() { return VXPREFIX(_setzero_s8)(); }
+    inline v_uint16 vx_setzero_u16() { return VXPREFIX(_setzero_u16)(); }
+    inline v_int16 vx_setzero_s16() { return VXPREFIX(_setzero_s16)(); }
+    inline v_int32 vx_setzero_s32() { return VXPREFIX(_setzero_s32)(); }
+    inline v_uint32 vx_setzero_u32() { return VXPREFIX(_setzero_u32)(); }
+    inline v_float32 vx_setzero_f32() { return VXPREFIX(_setzero_f32)(); }
+    inline v_int64 vx_setzero_s64() { return VXPREFIX(_setzero_s64)(); }
+    inline v_uint64 vx_setzero_u64() { return VXPREFIX(_setzero_u64)(); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_setzero_f64() { return VXPREFIX(_setzero_f64)(); }
+#endif
+    //! @}
+
+    //! @name Wide load from memory
+    //! @{
+    //! @brief Load maximum available capacity register contents from memory
+    inline v_uint8 vx_load(const uchar * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_int8 vx_load(const schar * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_uint16 vx_load(const ushort * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_int16 vx_load(const short * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_int32 vx_load(const int * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_uint32 vx_load(const unsigned * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_float32 vx_load(const float * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_int64 vx_load(const int64 * ptr) { return VXPREFIX(_load)(ptr); }
+    inline v_uint64 vx_load(const uint64 * ptr) { return VXPREFIX(_load)(ptr); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_load(const double * ptr) { return VXPREFIX(_load)(ptr); }
+#endif
+    //! @}
+
+    //! @name Wide load from memory(aligned)
+    //! @{
+    //! @brief Load maximum available capacity register contents from memory(aligned)
+    inline v_uint8 vx_load_aligned(const uchar * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_int8 vx_load_aligned(const schar * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_uint16 vx_load_aligned(const ushort * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_int16 vx_load_aligned(const short * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_int32 vx_load_aligned(const int * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_uint32 vx_load_aligned(const unsigned * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_float32 vx_load_aligned(const float * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_int64 vx_load_aligned(const int64 * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+    inline v_uint64 vx_load_aligned(const uint64 * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_load_aligned(const double * ptr) { return VXPREFIX(_load_aligned)(ptr); }
+#endif
+    //! @}
+
+    //! @name Wide load lower half from memory
+    //! @{
+    //! @brief Load lower half of maximum available capacity register from memory
+    inline v_uint8 vx_load_low(const uchar * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_int8 vx_load_low(const schar * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_uint16 vx_load_low(const ushort * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_int16 vx_load_low(const short * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_int32 vx_load_low(const int * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_uint32 vx_load_low(const unsigned * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_float32 vx_load_low(const float * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_int64 vx_load_low(const int64 * ptr) { return VXPREFIX(_load_low)(ptr); }
+    inline v_uint64 vx_load_low(const uint64 * ptr) { return VXPREFIX(_load_low)(ptr); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_load_low(const double * ptr) { return VXPREFIX(_load_low)(ptr); }
+#endif
+    //! @}
+
+    //! @name Wide load halfs from memory
+    //! @{
+    //! @brief Load maximum available capacity register contents from two memory blocks
+    inline v_uint8 vx_load_halves(const uchar * ptr0, const uchar * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_int8 vx_load_halves(const schar * ptr0, const schar * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_uint16 vx_load_halves(const ushort * ptr0, const ushort * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_int16 vx_load_halves(const short * ptr0, const short * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_int32 vx_load_halves(const int * ptr0, const int * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_uint32 vx_load_halves(const unsigned * ptr0, const unsigned * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_float32 vx_load_halves(const float * ptr0, const float * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_int64 vx_load_halves(const int64 * ptr0, const int64 * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+    inline v_uint64 vx_load_halves(const uint64 * ptr0, const uint64 * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_load_halves(const double * ptr0, const double * ptr1) { return VXPREFIX(_load_halves)(ptr0, ptr1); }
+#endif
+    //! @}
+
+    //! @name Wide LUT of elements
+    //! @{
+    //! @brief Load maximum available capacity register contents with array elements by provided indexes
+    inline v_uint8 vx_lut(const uchar * ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_int8 vx_lut(const schar * ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_uint16 vx_lut(const ushort * ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_int16 vx_lut(const short* ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_int32 vx_lut(const int* ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_uint32 vx_lut(const unsigned* ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_float32 vx_lut(const float* ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_int64 vx_lut(const int64 * ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+    inline v_uint64 vx_lut(const uint64 * ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_lut(const double* ptr, const int* idx) { return VXPREFIX(_lut)(ptr, idx); }
+#endif
+    //! @}
+
+    //! @name Wide LUT of element pairs
+    //! @{
+    //! @brief Load maximum available capacity register contents with array element pairs by provided indexes
+    inline v_uint8 vx_lut_pairs(const uchar * ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_int8 vx_lut_pairs(const schar * ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_uint16 vx_lut_pairs(const ushort * ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_int16 vx_lut_pairs(const short* ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_int32 vx_lut_pairs(const int* ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_uint32 vx_lut_pairs(const unsigned* ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_float32 vx_lut_pairs(const float* ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_int64 vx_lut_pairs(const int64 * ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+    inline v_uint64 vx_lut_pairs(const uint64 * ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
+    inline v_float64 vx_lut_pairs(const double* ptr, const int* idx) { return VXPREFIX(_lut_pairs)(ptr, idx); }
+#endif
+    //! @}
+
+    //! @name Wide LUT of element quads
+    //! @{
+    //! @brief Load maximum available capacity register contents with array element quads by provided indexes
+    inline v_uint8 vx_lut_quads(const uchar* ptr, const int* idx) { return VXPREFIX(_lut_quads)(ptr, idx); }
+    inline v_int8 vx_lut_quads(const schar* ptr, const int* idx) { return VXPREFIX(_lut_quads)(ptr, idx); }
+    inline v_uint16 vx_lut_quads(const ushort* ptr, const int* idx) { return VXPREFIX(_lut_quads)(ptr, idx); }
+    inline v_int16 vx_lut_quads(const short* ptr, const int* idx) { return VXPREFIX(_lut_quads)(ptr, idx); }
+    inline v_int32 vx_lut_quads(const int* ptr, const int* idx) { return VXPREFIX(_lut_quads)(ptr, idx); }
+    inline v_uint32 vx_lut_quads(const unsigned* ptr, const int* idx) { return VXPREFIX(_lut_quads)(ptr, idx); }
+    inline v_float32 vx_lut_quads(const float* ptr, const int* idx) { return VXPREFIX(_lut_quads)(ptr, idx); }
+    //! @}
+
+    //! @name Wide load with double expansion
+    //! @{
+    //! @brief Load maximum available capacity register contents from memory with double expand
+    inline v_uint16 vx_load_expand(const uchar * ptr) { return VXPREFIX(_load_expand)(ptr); }
+    inline v_int16 vx_load_expand(const schar * ptr) { return VXPREFIX(_load_expand)(ptr); }
+    inline v_uint32 vx_load_expand(const ushort * ptr) { return VXPREFIX(_load_expand)(ptr); }
+    inline v_int32 vx_load_expand(const short* ptr) { return VXPREFIX(_load_expand)(ptr); }
+    inline v_int64 vx_load_expand(const int* ptr) { return VXPREFIX(_load_expand)(ptr); }
+    inline v_uint64 vx_load_expand(const unsigned* ptr) { return VXPREFIX(_load_expand)(ptr); }
+    inline v_float32 vx_load_expand(const hfloat * ptr) { return VXPREFIX(_load_expand)(ptr); }
+    //! @}
+
+    //! @name Wide load with quad expansion
+    //! @{
+    //! @brief Load maximum available capacity register contents from memory with quad expand
+    inline v_uint32 vx_load_expand_q(const uchar * ptr) { return VXPREFIX(_load_expand_q)(ptr); }
+    inline v_int32 vx_load_expand_q(const schar * ptr) { return VXPREFIX(_load_expand_q)(ptr); }
+    //! @}
+
+    /** @brief SIMD processing state cleanup call */
+    inline void vx_cleanup() { VXPREFIX(_cleanup)(); }
+
+#if !CV_SIMD_SCALABLE
+    // Compatibility layer
+#if !(CV_NEON && !defined(CV_FORCE_SIMD128_CPP))
+    template<typename T> struct VTraits {
+        static inline int vlanes() { return T::nlanes; }
+        enum { nlanes = T::nlanes, max_nlanes = T::nlanes };
+        using lane_type = typename T::lane_type;
+    };
+
+    //////////// get0 ////////////
+    #define OPENCV_HAL_WRAP_GRT0(_Tpvec) \
+    inline typename VTraits<_Tpvec>::lane_type v_get0(const _Tpvec& v) \
+    { \
+        return v.get0(); \
+    }
+
+    OPENCV_HAL_WRAP_GRT0(v_uint8)
+    OPENCV_HAL_WRAP_GRT0(v_int8)
+    OPENCV_HAL_WRAP_GRT0(v_uint16)
+    OPENCV_HAL_WRAP_GRT0(v_int16)
+    OPENCV_HAL_WRAP_GRT0(v_uint32)
+    OPENCV_HAL_WRAP_GRT0(v_int32)
+    OPENCV_HAL_WRAP_GRT0(v_uint64)
+    OPENCV_HAL_WRAP_GRT0(v_int64)
+    OPENCV_HAL_WRAP_GRT0(v_float32)
+    #if CV_SIMD_64F
+    OPENCV_HAL_WRAP_GRT0(v_float64)
+    #endif
+    #if CV_SIMD_WIDTH != 16/*128*/ && CV_SIMD128
+        OPENCV_HAL_WRAP_GRT0(v_uint8x16)
+        OPENCV_HAL_WRAP_GRT0(v_uint16x8)
+        OPENCV_HAL_WRAP_GRT0(v_uint32x4)
+        OPENCV_HAL_WRAP_GRT0(v_uint64x2)
+        OPENCV_HAL_WRAP_GRT0(v_int8x16)
+        OPENCV_HAL_WRAP_GRT0(v_int16x8)
+        OPENCV_HAL_WRAP_GRT0(v_int32x4)
+        OPENCV_HAL_WRAP_GRT0(v_int64x2)
+        OPENCV_HAL_WRAP_GRT0(v_float32x4)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_GRT0(v_float64x2)
+        #endif
+    #endif
+    #if CV_SIMD_WIDTH != 32/*256*/ && CV_SIMD256
+        OPENCV_HAL_WRAP_GRT0(v_uint8x32)
+        OPENCV_HAL_WRAP_GRT0(v_uint16x16)
+        OPENCV_HAL_WRAP_GRT0(v_uint32x8)
+        OPENCV_HAL_WRAP_GRT0(v_uint64x4)
+        OPENCV_HAL_WRAP_GRT0(v_int8x32)
+        OPENCV_HAL_WRAP_GRT0(v_int16x16)
+        OPENCV_HAL_WRAP_GRT0(v_int32x8)
+        OPENCV_HAL_WRAP_GRT0(v_int64x4)
+        OPENCV_HAL_WRAP_GRT0(v_float32x8)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_GRT0(v_float64x4)
+        #endif
+    #endif
+#endif
+
+    #define OPENCV_HAL_WRAP_BIN_OP_ADDSUB(_Tpvec) \
+    template<typename... Args> \
+    inline _Tpvec v_add(const _Tpvec& f1, const _Tpvec& f2, const _Tpvec& f3, const Args&... vf) { \
+        return v_add(v_add(f1, f2), f3, vf...); \
+    }
+
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint8)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint16)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint32)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint64)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int8)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int16)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int32)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int64)
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_float32)
+    #if CV_SIMD_64F
+    OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_float64)
+    #endif
+    #if CV_SIMD_WIDTH != 16/*128*/ && CV_SIMD128
+    // when we use CV_SIMD128 with 256/512 bit SIMD (e.g. AVX2 or AVX512)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint8x16)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint16x8)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint32x4)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint64x2)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int8x16)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int16x8)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int32x4)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int64x2)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_float32x4)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_float64x2)
+        #endif
+    #endif
+    #if CV_SIMD_WIDTH != 32/*256*/ && CV_SIMD256
+    // when we use CV_SIMD256 with 512 bit SIMD (e.g. AVX512)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint8x32)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint16x16)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint32x8)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_uint64x4)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int8x32)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int16x16)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int32x8)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_int64x4)
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_float32x8)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_BIN_OP_ADDSUB(v_float64x4)
+        #endif
+    #endif
+
+    #define OPENCV_HAL_WRAP_BIN_OP_MUL(_Tpvec) \
+    template<typename... Args> \
+    inline _Tpvec v_mul(const _Tpvec& f1, const _Tpvec& f2, const _Tpvec& f3, const Args&... vf) { \
+        return v_mul(v_mul(f1, f2), f3, vf...); \
+    }
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint8)
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_int8)
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint16)
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint32)
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_int16)
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_int32)
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_float32)
+    #if CV_SIMD_64F
+    OPENCV_HAL_WRAP_BIN_OP_MUL(v_float64)
+    #endif
+    #if CV_SIMD_WIDTH != 16/*128*/ && CV_SIMD128
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint8x16)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint16x8)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint32x4)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_int8x16)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_int16x8)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_int32x4)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_float32x4)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_float64x2)
+        #endif
+    #endif
+    #if CV_SIMD_WIDTH != 32/*256*/ && CV_SIMD256
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint8x32)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint16x16)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_uint32x8)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_int8x32)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_int16x16)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_int32x8)
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_float32x8)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_BIN_OP_MUL(v_float64x4)
+        #endif
+    #endif
+
+    #define OPENCV_HAL_WRAP_EXTRACT(_Tpvec) \
+    inline typename VTraits<_Tpvec>::lane_type v_extract_highest(const _Tpvec& v) \
+    { \
+        return v_extract_n<VTraits<_Tpvec>::nlanes-1>(v); \
+    }
+
+    OPENCV_HAL_WRAP_EXTRACT(v_uint8)
+    OPENCV_HAL_WRAP_EXTRACT(v_int8)
+    OPENCV_HAL_WRAP_EXTRACT(v_uint16)
+    OPENCV_HAL_WRAP_EXTRACT(v_int16)
+    OPENCV_HAL_WRAP_EXTRACT(v_uint32)
+    OPENCV_HAL_WRAP_EXTRACT(v_int32)
+    OPENCV_HAL_WRAP_EXTRACT(v_uint64)
+    OPENCV_HAL_WRAP_EXTRACT(v_int64)
+    OPENCV_HAL_WRAP_EXTRACT(v_float32)
+    #if CV_SIMD_64F
+    OPENCV_HAL_WRAP_EXTRACT(v_float64)
+    #endif
+    #if CV_SIMD_WIDTH != 16/*128*/ && CV_SIMD128
+        OPENCV_HAL_WRAP_EXTRACT(v_uint8x16)
+        OPENCV_HAL_WRAP_EXTRACT(v_uint16x8)
+        OPENCV_HAL_WRAP_EXTRACT(v_uint32x4)
+        OPENCV_HAL_WRAP_EXTRACT(v_uint64x2)
+        OPENCV_HAL_WRAP_EXTRACT(v_int8x16)
+        OPENCV_HAL_WRAP_EXTRACT(v_int16x8)
+        OPENCV_HAL_WRAP_EXTRACT(v_int32x4)
+        OPENCV_HAL_WRAP_EXTRACT(v_int64x2)
+        OPENCV_HAL_WRAP_EXTRACT(v_float32x4)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_EXTRACT(v_float64x2)
+        #endif
+    #endif
+    #if CV_SIMD_WIDTH != 32/*256*/ && CV_SIMD256
+        OPENCV_HAL_WRAP_EXTRACT(v_uint8x32)
+        OPENCV_HAL_WRAP_EXTRACT(v_uint16x16)
+        OPENCV_HAL_WRAP_EXTRACT(v_uint32x8)
+        OPENCV_HAL_WRAP_EXTRACT(v_uint64x4)
+        OPENCV_HAL_WRAP_EXTRACT(v_int8x32)
+        OPENCV_HAL_WRAP_EXTRACT(v_int16x16)
+        OPENCV_HAL_WRAP_EXTRACT(v_int32x8)
+        OPENCV_HAL_WRAP_EXTRACT(v_int64x4)
+        OPENCV_HAL_WRAP_EXTRACT(v_float32x8)
+        #if CV_SIMD_64F
+        OPENCV_HAL_WRAP_EXTRACT(v_float64x4)
+        #endif
+    #endif
+
+    #define OPENCV_HAL_WRAP_BROADCAST(_Tpvec) \
+    inline _Tpvec v_broadcast_highest(const _Tpvec& v) \
+    { \
+        return v_broadcast_element<VTraits<_Tpvec>::nlanes-1>(v); \
+    }
+
+    OPENCV_HAL_WRAP_BROADCAST(v_uint32)
+    OPENCV_HAL_WRAP_BROADCAST(v_int32)
+    OPENCV_HAL_WRAP_BROADCAST(v_float32)
+    #if CV_SIMD_WIDTH != 16/*128*/ && CV_SIMD128
+        OPENCV_HAL_WRAP_BROADCAST(v_uint32x4)
+        OPENCV_HAL_WRAP_BROADCAST(v_int32x4)
+        OPENCV_HAL_WRAP_BROADCAST(v_float32x4)
+    #endif
+    #if CV_SIMD_WIDTH != 32/*256*/ && CV_SIMD256
+        OPENCV_HAL_WRAP_BROADCAST(v_uint32x8)
+        OPENCV_HAL_WRAP_BROADCAST(v_int32x8)
+        OPENCV_HAL_WRAP_BROADCAST(v_float32x8)
+    #endif
+
+#endif //!CV_SIMD_SCALABLE
+
+//! @cond IGNORED
+
+    // backward compatibility
+    template<typename _Tp, typename _Tvec> static inline
+    void vx_store(_Tp* dst, const _Tvec& v) { return v_store(dst, v); }
+    // backward compatibility
+    template<typename _Tp, typename _Tvec> static inline
+    void vx_store_aligned(_Tp* dst, const _Tvec& v) { return v_store_aligned(dst, v); }
+
+//! @endcond
+
+
+//! @}
+    #undef VXPREFIX
+} // namespace
+
+
+#ifndef CV_SIMD_FP16
+#define CV_SIMD_FP16 0  //!< Defined to 1 on native support of operations with float16x8_t / float16x16_t (SIMD256) types
+#endif
+
+#ifndef CV_SIMD
+#define CV_SIMD 0
+#endif
+
+#include "simd_utils.impl.hpp"
+
+#ifndef CV_DOXYGEN
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+#endif
+
+} // cv::
+
+//! @endcond
+
+#if defined(__GNUC__) && __GNUC__ == 12
+#pragma GCC diagnostic pop
+#endif
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_avx.hpp

@@ -0,0 +1,3189 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+#ifndef OPENCV_HAL_INTRIN_AVX_HPP
+#define OPENCV_HAL_INTRIN_AVX_HPP
+
+#define CV_SIMD256 1
+#define CV_SIMD256_64F 1
+#define CV_SIMD256_FP16 0  // no native operations with FP16 type. Only load/store from float32x8 are available (if CV_FP16 == 1)
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+///////// Utils ////////////
+
+inline __m256i _v256_combine(const __m128i& lo, const __m128i& hi)
+{ return _mm256_inserti128_si256(_mm256_castsi128_si256(lo), hi, 1); }
+
+inline __m256 _v256_combine(const __m128& lo, const __m128& hi)
+{ return _mm256_insertf128_ps(_mm256_castps128_ps256(lo), hi, 1); }
+
+inline __m256d _v256_combine(const __m128d& lo, const __m128d& hi)
+{ return _mm256_insertf128_pd(_mm256_castpd128_pd256(lo), hi, 1); }
+
+inline int _v_cvtsi256_si32(const __m256i& a)
+{ return _mm_cvtsi128_si32(_mm256_castsi256_si128(a)); }
+
+inline __m256i _v256_shuffle_odd_64(const __m256i& v)
+{ return _mm256_permute4x64_epi64(v, _MM_SHUFFLE(3, 1, 2, 0)); }
+
+inline __m256d _v256_shuffle_odd_64(const __m256d& v)
+{ return _mm256_permute4x64_pd(v, _MM_SHUFFLE(3, 1, 2, 0)); }
+
+template<int imm>
+inline __m256i _v256_permute2x128(const __m256i& a, const __m256i& b)
+{ return _mm256_permute2x128_si256(a, b, imm); }
+
+template<int imm>
+inline __m256 _v256_permute2x128(const __m256& a, const __m256& b)
+{ return _mm256_permute2f128_ps(a, b, imm); }
+
+template<int imm>
+inline __m256d _v256_permute2x128(const __m256d& a, const __m256d& b)
+{ return _mm256_permute2f128_pd(a, b, imm); }
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v256_permute2x128(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(_v256_permute2x128<imm>(a.val, b.val)); }
+
+template<int imm>
+inline __m256i _v256_permute4x64(const __m256i& a)
+{ return _mm256_permute4x64_epi64(a, imm); }
+
+template<int imm>
+inline __m256d _v256_permute4x64(const __m256d& a)
+{ return _mm256_permute4x64_pd(a, imm); }
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v256_permute4x64(const _Tpvec& a)
+{ return _Tpvec(_v256_permute4x64<imm>(a.val)); }
+
+inline __m128i _v256_extract_high(const __m256i& v)
+{ return _mm256_extracti128_si256(v, 1); }
+
+inline __m128  _v256_extract_high(const __m256& v)
+{ return _mm256_extractf128_ps(v, 1); }
+
+inline __m128d _v256_extract_high(const __m256d& v)
+{ return _mm256_extractf128_pd(v, 1); }
+
+inline __m128i _v256_extract_low(const __m256i& v)
+{ return _mm256_castsi256_si128(v); }
+
+inline __m128  _v256_extract_low(const __m256& v)
+{ return _mm256_castps256_ps128(v); }
+
+inline __m128d _v256_extract_low(const __m256d& v)
+{ return _mm256_castpd256_pd128(v); }
+
+inline __m256i _v256_packs_epu32(const __m256i& a, const __m256i& b)
+{
+    const __m256i m = _mm256_set1_epi32(65535);
+    __m256i am = _mm256_min_epu32(a, m);
+    __m256i bm = _mm256_min_epu32(b, m);
+    return _mm256_packus_epi32(am, bm);
+}
+
+template<int i>
+inline int _v256_extract_epi8(const __m256i& a)
+{
+#if defined(CV__SIMD_HAVE_mm256_extract_epi8) || (CV_AVX2 && (!defined(_MSC_VER) || _MSC_VER >= 1910/*MSVS 2017*/))
+    return _mm256_extract_epi8(a, i);
+#else
+    __m128i b = _mm256_extractf128_si256(a, ((i) >> 4));
+    return _mm_extract_epi8(b, i & 15);  // SSE4.1
+#endif
+}
+
+template<int i>
+inline int _v256_extract_epi16(const __m256i& a)
+{
+#if defined(CV__SIMD_HAVE_mm256_extract_epi8) || (CV_AVX2 && (!defined(_MSC_VER) || _MSC_VER >= 1910/*MSVS 2017*/))
+    return _mm256_extract_epi16(a, i);
+#else
+    __m128i b = _mm256_extractf128_si256(a, ((i) >> 3));
+    return _mm_extract_epi16(b, i & 7);  // SSE2
+#endif
+}
+
+template<int i>
+inline int _v256_extract_epi32(const __m256i& a)
+{
+#if defined(CV__SIMD_HAVE_mm256_extract_epi8) || (CV_AVX2 && (!defined(_MSC_VER) || _MSC_VER >= 1910/*MSVS 2017*/))
+    return _mm256_extract_epi32(a, i);
+#else
+    __m128i b = _mm256_extractf128_si256(a, ((i) >> 2));
+    return _mm_extract_epi32(b, i & 3);  // SSE4.1
+#endif
+}
+
+template<int i>
+inline int64 _v256_extract_epi64(const __m256i& a)
+{
+#if defined(CV__SIMD_HAVE_mm256_extract_epi8) || (CV_AVX2 && (!defined(_MSC_VER) || _MSC_VER >= 1910/*MSVS 2017*/))
+    return _mm256_extract_epi64(a, i);
+#else
+    __m128i b = _mm256_extractf128_si256(a, ((i) >> 1));
+    return _mm_extract_epi64(b, i & 1);  // SSE4.1
+#endif
+}
+
+///////// Types ////////////
+
+struct v_uint8x32
+{
+    typedef uchar lane_type;
+    enum { nlanes = 32 };
+    __m256i val;
+
+    explicit v_uint8x32(__m256i v) : val(v) {}
+    v_uint8x32(uchar v0,  uchar v1,  uchar v2,  uchar v3,
+               uchar v4,  uchar v5,  uchar v6,  uchar v7,
+               uchar v8,  uchar v9,  uchar v10, uchar v11,
+               uchar v12, uchar v13, uchar v14, uchar v15,
+               uchar v16, uchar v17, uchar v18, uchar v19,
+               uchar v20, uchar v21, uchar v22, uchar v23,
+               uchar v24, uchar v25, uchar v26, uchar v27,
+               uchar v28, uchar v29, uchar v30, uchar v31)
+    {
+        val = _mm256_setr_epi8((char)v0, (char)v1, (char)v2, (char)v3,
+            (char)v4,  (char)v5,  (char)v6 , (char)v7,  (char)v8,  (char)v9,
+            (char)v10, (char)v11, (char)v12, (char)v13, (char)v14, (char)v15,
+            (char)v16, (char)v17, (char)v18, (char)v19, (char)v20, (char)v21,
+            (char)v22, (char)v23, (char)v24, (char)v25, (char)v26, (char)v27,
+            (char)v28, (char)v29, (char)v30, (char)v31);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint8x32() {}
+
+    uchar get0() const { return (uchar)_v_cvtsi256_si32(val); }
+};
+
+struct v_int8x32
+{
+    typedef schar lane_type;
+    enum { nlanes = 32 };
+    __m256i val;
+
+    explicit v_int8x32(__m256i v) : val(v) {}
+    v_int8x32(schar v0,  schar v1,  schar v2,  schar v3,
+              schar v4,  schar v5,  schar v6,  schar v7,
+              schar v8,  schar v9,  schar v10, schar v11,
+              schar v12, schar v13, schar v14, schar v15,
+              schar v16, schar v17, schar v18, schar v19,
+              schar v20, schar v21, schar v22, schar v23,
+              schar v24, schar v25, schar v26, schar v27,
+              schar v28, schar v29, schar v30, schar v31)
+    {
+        val = _mm256_setr_epi8(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9,
+            v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20,
+            v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int8x32() {}
+
+    schar get0() const { return (schar)_v_cvtsi256_si32(val); }
+};
+
+struct v_uint16x16
+{
+    typedef ushort lane_type;
+    enum { nlanes = 16 };
+    __m256i val;
+
+    explicit v_uint16x16(__m256i v) : val(v) {}
+    v_uint16x16(ushort v0,  ushort v1,  ushort v2,  ushort v3,
+                ushort v4,  ushort v5,  ushort v6,  ushort v7,
+                ushort v8,  ushort v9,  ushort v10, ushort v11,
+                ushort v12, ushort v13, ushort v14, ushort v15)
+    {
+        val = _mm256_setr_epi16((short)v0, (short)v1, (short)v2, (short)v3,
+            (short)v4,  (short)v5,  (short)v6,  (short)v7,  (short)v8,  (short)v9,
+            (short)v10, (short)v11, (short)v12, (short)v13, (short)v14, (short)v15);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint16x16() {}
+
+    ushort get0() const { return (ushort)_v_cvtsi256_si32(val); }
+};
+
+struct v_int16x16
+{
+    typedef short lane_type;
+    enum { nlanes = 16 };
+    __m256i val;
+
+    explicit v_int16x16(__m256i v) : val(v) {}
+    v_int16x16(short v0,  short v1,  short v2,  short v3,
+               short v4,  short v5,  short v6,  short v7,
+               short v8,  short v9,  short v10, short v11,
+               short v12, short v13, short v14, short v15)
+    {
+        val = _mm256_setr_epi16(v0, v1, v2, v3, v4, v5, v6, v7,
+            v8, v9, v10, v11, v12, v13, v14, v15);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int16x16() {}
+
+    short get0() const { return (short)_v_cvtsi256_si32(val); }
+};
+
+struct v_uint32x8
+{
+    typedef unsigned lane_type;
+    enum { nlanes = 8 };
+    __m256i val;
+
+    explicit v_uint32x8(__m256i v) : val(v) {}
+    v_uint32x8(unsigned v0, unsigned v1, unsigned v2, unsigned v3,
+               unsigned v4, unsigned v5, unsigned v6, unsigned v7)
+    {
+        val = _mm256_setr_epi32((unsigned)v0, (unsigned)v1, (unsigned)v2,
+            (unsigned)v3, (unsigned)v4, (unsigned)v5, (unsigned)v6, (unsigned)v7);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint32x8() {}
+
+    unsigned get0() const { return (unsigned)_v_cvtsi256_si32(val); }
+};
+
+struct v_int32x8
+{
+    typedef int lane_type;
+    enum { nlanes = 8 };
+    __m256i val;
+
+    explicit v_int32x8(__m256i v) : val(v) {}
+    v_int32x8(int v0, int v1, int v2, int v3,
+              int v4, int v5, int v6, int v7)
+    {
+        val = _mm256_setr_epi32(v0, v1, v2, v3, v4, v5, v6, v7);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int32x8() {}
+
+    int get0() const { return _v_cvtsi256_si32(val); }
+};
+
+struct v_float32x8
+{
+    typedef float lane_type;
+    enum { nlanes = 8 };
+    __m256 val;
+
+    explicit v_float32x8(__m256 v) : val(v) {}
+    v_float32x8(float v0, float v1, float v2, float v3,
+                float v4, float v5, float v6, float v7)
+    {
+        val = _mm256_setr_ps(v0, v1, v2, v3, v4, v5, v6, v7);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_float32x8() {}
+
+    float get0() const { return _mm_cvtss_f32(_mm256_castps256_ps128(val)); }
+};
+
+struct v_uint64x4
+{
+    typedef uint64 lane_type;
+    enum { nlanes = 4 };
+    __m256i val;
+
+    explicit v_uint64x4(__m256i v) : val(v) {}
+    v_uint64x4(uint64 v0, uint64 v1, uint64 v2, uint64 v3)
+    { val = _mm256_setr_epi64x((int64)v0, (int64)v1, (int64)v2, (int64)v3); }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint64x4() {}
+
+    uint64 get0() const
+    {
+    #if defined __x86_64__ || defined _M_X64
+        return (uint64)_mm_cvtsi128_si64(_mm256_castsi256_si128(val));
+    #else
+        int a = _mm_cvtsi128_si32(_mm256_castsi256_si128(val));
+        int b = _mm_cvtsi128_si32(_mm256_castsi256_si128(_mm256_srli_epi64(val, 32)));
+        return (unsigned)a | ((uint64)(unsigned)b << 32);
+    #endif
+    }
+};
+
+struct v_int64x4
+{
+    typedef int64 lane_type;
+    enum { nlanes = 4 };
+    __m256i val;
+
+    explicit v_int64x4(__m256i v) : val(v) {}
+    v_int64x4(int64 v0, int64 v1, int64 v2, int64 v3)
+    { val = _mm256_setr_epi64x(v0, v1, v2, v3); }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int64x4() {}
+
+    int64 get0() const
+    {
+    #if defined __x86_64__ || defined _M_X64
+        return (int64)_mm_cvtsi128_si64(_mm256_castsi256_si128(val));
+    #else
+        int a = _mm_cvtsi128_si32(_mm256_castsi256_si128(val));
+        int b = _mm_cvtsi128_si32(_mm256_castsi256_si128(_mm256_srli_epi64(val, 32)));
+        return (int64)((unsigned)a | ((uint64)(unsigned)b << 32));
+    #endif
+    }
+};
+
+struct v_float64x4
+{
+    typedef double lane_type;
+    enum { nlanes = 4 };
+    __m256d val;
+
+    explicit v_float64x4(__m256d v) : val(v) {}
+    v_float64x4(double v0, double v1, double v2, double v3)
+    { val = _mm256_setr_pd(v0, v1, v2, v3); }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_float64x4() {}
+
+    double get0() const { return _mm_cvtsd_f64(_mm256_castpd256_pd128(val)); }
+};
+
+//////////////// Load and store operations ///////////////
+
+#define OPENCV_HAL_IMPL_AVX_LOADSTORE(_Tpvec, _Tp)                    \
+    inline _Tpvec v256_load(const _Tp* ptr)                           \
+    { return _Tpvec(_mm256_loadu_si256((const __m256i*)ptr)); }       \
+    inline _Tpvec v256_load_aligned(const _Tp* ptr)                   \
+    { return _Tpvec(_mm256_load_si256((const __m256i*)ptr)); }        \
+    inline _Tpvec v256_load_low(const _Tp* ptr)                       \
+    {                                                                 \
+        __m128i v128 = _mm_loadu_si128((const __m128i*)ptr);          \
+        return _Tpvec(_mm256_castsi128_si256(v128));                  \
+    }                                                                 \
+    inline _Tpvec v256_load_halves(const _Tp* ptr0, const _Tp* ptr1)  \
+    {                                                                 \
+        __m128i vlo = _mm_loadu_si128((const __m128i*)ptr0);          \
+        __m128i vhi = _mm_loadu_si128((const __m128i*)ptr1);          \
+        return _Tpvec(_v256_combine(vlo, vhi));                       \
+    }                                                                 \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                    \
+    { _mm256_storeu_si256((__m256i*)ptr, a.val); }                    \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)            \
+    { _mm256_store_si256((__m256i*)ptr, a.val); }                     \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)    \
+    { _mm256_stream_si256((__m256i*)ptr, a.val); }                    \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+    { \
+        if( mode == hal::STORE_UNALIGNED ) \
+            _mm256_storeu_si256((__m256i*)ptr, a.val); \
+        else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+            _mm256_stream_si256((__m256i*)ptr, a.val); \
+        else \
+            _mm256_store_si256((__m256i*)ptr, a.val); \
+    } \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                \
+    { _mm_storeu_si128((__m128i*)ptr, _v256_extract_low(a.val)); }    \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)               \
+    { _mm_storeu_si128((__m128i*)ptr, _v256_extract_high(a.val)); }
+
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint8x32,  uchar)
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int8x32,   schar)
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint16x16, ushort)
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int16x16,  short)
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint32x8,  unsigned)
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int32x8,   int)
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_uint64x4,  uint64)
+OPENCV_HAL_IMPL_AVX_LOADSTORE(v_int64x4,   int64)
+
+#define OPENCV_HAL_IMPL_AVX_LOADSTORE_FLT(_Tpvec, _Tp, suffix, halfreg)   \
+    inline _Tpvec v256_load(const _Tp* ptr)                               \
+    { return _Tpvec(_mm256_loadu_##suffix(ptr)); }                        \
+    inline _Tpvec v256_load_aligned(const _Tp* ptr)                       \
+    { return _Tpvec(_mm256_load_##suffix(ptr)); }                         \
+    inline _Tpvec v256_load_low(const _Tp* ptr)                           \
+    {                                                                     \
+        return _Tpvec(_mm256_cast##suffix##128_##suffix##256              \
+                     (_mm_loadu_##suffix(ptr)));                          \
+    }                                                                     \
+    inline _Tpvec v256_load_halves(const _Tp* ptr0, const _Tp* ptr1)      \
+    {                                                                     \
+        halfreg vlo = _mm_loadu_##suffix(ptr0);                           \
+        halfreg vhi = _mm_loadu_##suffix(ptr1);                           \
+        return _Tpvec(_v256_combine(vlo, vhi));                           \
+    }                                                                     \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                        \
+    { _mm256_storeu_##suffix(ptr, a.val); }                               \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)                \
+    { _mm256_store_##suffix(ptr, a.val); }                                \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)        \
+    { _mm256_stream_##suffix(ptr, a.val); }                               \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+    { \
+        if( mode == hal::STORE_UNALIGNED ) \
+            _mm256_storeu_##suffix(ptr, a.val); \
+        else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+            _mm256_stream_##suffix(ptr, a.val); \
+        else \
+            _mm256_store_##suffix(ptr, a.val); \
+    } \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                    \
+    { _mm_storeu_##suffix(ptr, _v256_extract_low(a.val)); }               \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)                   \
+    { _mm_storeu_##suffix(ptr, _v256_extract_high(a.val)); }
+
+OPENCV_HAL_IMPL_AVX_LOADSTORE_FLT(v_float32x8, float,  ps, __m128)
+OPENCV_HAL_IMPL_AVX_LOADSTORE_FLT(v_float64x4, double, pd, __m128d)
+
+#define OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, _Tpvecf, suffix, cast) \
+    inline _Tpvec v_reinterpret_as_##suffix(const _Tpvecf& a)   \
+    { return _Tpvec(cast(a.val)); }
+
+#define OPENCV_HAL_IMPL_AVX_INIT(_Tpvec, _Tp, suffix, ssuffix, ctype_s)          \
+    inline _Tpvec v256_setzero_##suffix()                                        \
+    { return _Tpvec(_mm256_setzero_si256()); }                                   \
+    inline _Tpvec v256_setall_##suffix(_Tp v)                                    \
+    { return _Tpvec(_mm256_set1_##ssuffix((ctype_s)v)); }                        \
+    template <> inline _Tpvec v_setzero_()                                       \
+    { return v256_setzero_##suffix(); }                                          \
+    template <> inline _Tpvec v_setall_(_Tp v)                                   \
+    { return v256_setall_##suffix(v); }                                          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint8x32,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int8x32,   suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint16x16, suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int16x16,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint32x8,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int32x8,   suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint64x4,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int64x4,   suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_float32x8, suffix, _mm256_castps_si256)   \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_float64x4, suffix, _mm256_castpd_si256)
+
+OPENCV_HAL_IMPL_AVX_INIT(v_uint8x32,  uchar,    u8,  epi8,   char)
+OPENCV_HAL_IMPL_AVX_INIT(v_int8x32,   schar,    s8,  epi8,   char)
+OPENCV_HAL_IMPL_AVX_INIT(v_uint16x16, ushort,   u16, epi16,  short)
+OPENCV_HAL_IMPL_AVX_INIT(v_int16x16,  short,    s16, epi16,  short)
+OPENCV_HAL_IMPL_AVX_INIT(v_uint32x8,  unsigned, u32, epi32,  int)
+OPENCV_HAL_IMPL_AVX_INIT(v_int32x8,   int,      s32, epi32,  int)
+OPENCV_HAL_IMPL_AVX_INIT(v_uint64x4,  uint64,   u64, epi64x, int64)
+OPENCV_HAL_IMPL_AVX_INIT(v_int64x4,   int64,    s64, epi64x, int64)
+
+#define OPENCV_HAL_IMPL_AVX_INIT_FLT(_Tpvec, _Tp, suffix, zsuffix, cast) \
+    inline _Tpvec v256_setzero_##suffix()                                \
+    { return _Tpvec(_mm256_setzero_##zsuffix()); }                       \
+    inline _Tpvec v256_setall_##suffix(_Tp v)                            \
+    { return _Tpvec(_mm256_set1_##zsuffix(v)); }                         \
+    template <> inline _Tpvec v_setzero_()                               \
+    { return v256_setzero_##suffix(); }                                  \
+    template <> inline _Tpvec v_setall_(_Tp v)                           \
+    { return v256_setall_##suffix(v); }                                  \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint8x32,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int8x32,   suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint16x16, suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int16x16,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint32x8,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int32x8,   suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_uint64x4,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX_CAST(_Tpvec, v_int64x4,   suffix, cast)
+
+OPENCV_HAL_IMPL_AVX_INIT_FLT(v_float32x8, float,  f32, ps, _mm256_castsi256_ps)
+OPENCV_HAL_IMPL_AVX_INIT_FLT(v_float64x4, double, f64, pd, _mm256_castsi256_pd)
+
+inline v_float32x8 v_reinterpret_as_f32(const v_float32x8& a)
+{ return a; }
+inline v_float32x8 v_reinterpret_as_f32(const v_float64x4& a)
+{ return v_float32x8(_mm256_castpd_ps(a.val)); }
+
+inline v_float64x4 v_reinterpret_as_f64(const v_float64x4& a)
+{ return a; }
+inline v_float64x4 v_reinterpret_as_f64(const v_float32x8& a)
+{ return v_float64x4(_mm256_castps_pd(a.val)); }
+
+/* Recombine */
+/*#define OPENCV_HAL_IMPL_AVX_COMBINE(_Tpvec, perm)                    \
+    inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b)    \
+    { return _Tpvec(perm(a.val, b.val, 0x20)); }                     \
+    inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b)   \
+    { return _Tpvec(perm(a.val, b.val, 0x31)); }                     \
+    inline void v_recombine(const _Tpvec& a, const _Tpvec& b,        \
+                             _Tpvec& c, _Tpvec& d)                   \
+    { c = v_combine_low(a, b); d = v_combine_high(a, b); }
+
+#define OPENCV_HAL_IMPL_AVX_UNPACKS(_Tpvec, suffix)                  \
+    OPENCV_HAL_IMPL_AVX_COMBINE(_Tpvec, _mm256_permute2x128_si256)   \
+    inline void v_zip(const _Tpvec& a0, const _Tpvec& a1,            \
+                             _Tpvec& b0, _Tpvec& b1)                 \
+    {                                                                \
+        __m256i v0 = _v256_shuffle_odd_64(a0.val);                   \
+        __m256i v1 = _v256_shuffle_odd_64(a1.val);                   \
+        b0.val = _mm256_unpacklo_##suffix(v0, v1);                   \
+        b1.val = _mm256_unpackhi_##suffix(v0, v1);                   \
+    }
+
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint8x32,  epi8)
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_int8x32,   epi8)
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint16x16, epi16)
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_int16x16,  epi16)
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint32x8,  epi32)
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_int32x8,   epi32)
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_uint64x4,  epi64)
+OPENCV_HAL_IMPL_AVX_UNPACKS(v_int64x4,   epi64)
+OPENCV_HAL_IMPL_AVX_COMBINE(v_float32x8, _mm256_permute2f128_ps)
+OPENCV_HAL_IMPL_AVX_COMBINE(v_float64x4, _mm256_permute2f128_pd)
+
+inline void v_zip(const v_float32x8& a0, const v_float32x8& a1, v_float32x8& b0, v_float32x8& b1)
+{
+    __m256 v0 = _mm256_unpacklo_ps(a0.val, a1.val);
+    __m256 v1 = _mm256_unpackhi_ps(a0.val, a1.val);
+    v_recombine(v_float32x8(v0), v_float32x8(v1), b0, b1);
+}
+
+inline void v_zip(const v_float64x4& a0, const v_float64x4& a1, v_float64x4& b0, v_float64x4& b1)
+{
+    __m256d v0 = _v_shuffle_odd_64(a0.val);
+    __m256d v1 = _v_shuffle_odd_64(a1.val);
+    b0.val = _mm256_unpacklo_pd(v0, v1);
+    b1.val = _mm256_unpackhi_pd(v0, v1);
+}*/
+
+//////////////// Variant Value reordering ///////////////
+
+// unpacks
+#define OPENCV_HAL_IMPL_AVX_UNPACK(_Tpvec, suffix)                 \
+    inline _Tpvec v256_unpacklo(const _Tpvec& a, const _Tpvec& b)  \
+    { return _Tpvec(_mm256_unpacklo_##suffix(a.val, b.val)); }     \
+    inline _Tpvec v256_unpackhi(const _Tpvec& a, const _Tpvec& b)  \
+    { return _Tpvec(_mm256_unpackhi_##suffix(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_AVX_UNPACK(v_uint8x32,  epi8)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_int8x32,   epi8)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_uint16x16, epi16)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_int16x16,  epi16)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_uint32x8,  epi32)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_int32x8,   epi32)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_uint64x4,  epi64)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_int64x4,   epi64)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_float32x8, ps)
+OPENCV_HAL_IMPL_AVX_UNPACK(v_float64x4, pd)
+
+// blend
+#define OPENCV_HAL_IMPL_AVX_BLEND(_Tpvec, suffix)               \
+    template<int m>                                             \
+    inline _Tpvec v256_blend(const _Tpvec& a, const _Tpvec& b)  \
+    { return _Tpvec(_mm256_blend_##suffix(a.val, b.val, m)); }
+
+OPENCV_HAL_IMPL_AVX_BLEND(v_uint16x16, epi16)
+OPENCV_HAL_IMPL_AVX_BLEND(v_int16x16,  epi16)
+OPENCV_HAL_IMPL_AVX_BLEND(v_uint32x8,  epi32)
+OPENCV_HAL_IMPL_AVX_BLEND(v_int32x8,   epi32)
+OPENCV_HAL_IMPL_AVX_BLEND(v_float32x8, ps)
+OPENCV_HAL_IMPL_AVX_BLEND(v_float64x4, pd)
+
+template<int m>
+inline v_uint64x4 v256_blend(const v_uint64x4& a, const v_uint64x4& b)
+{
+    enum {M0 = m};
+    enum {M1 = (M0 | (M0 << 2)) & 0x33};
+    enum {M2 = (M1 | (M1 << 1)) & 0x55};
+    enum {MM =  M2 | (M2 << 1)};
+    return v_uint64x4(_mm256_blend_epi32(a.val, b.val, MM));
+}
+template<int m>
+inline v_int64x4 v256_blend(const v_int64x4& a, const v_int64x4& b)
+{ return v_int64x4(v256_blend<m>(v_uint64x4(a.val), v_uint64x4(b.val)).val); }
+
+// shuffle
+// todo: emulate 64bit
+#define OPENCV_HAL_IMPL_AVX_SHUFFLE(_Tpvec, intrin)  \
+    template<int m>                                  \
+    inline _Tpvec v256_shuffle(const _Tpvec& a)      \
+    { return _Tpvec(_mm256_##intrin(a.val, m)); }
+
+OPENCV_HAL_IMPL_AVX_SHUFFLE(v_uint32x8,  shuffle_epi32)
+OPENCV_HAL_IMPL_AVX_SHUFFLE(v_int32x8,   shuffle_epi32)
+OPENCV_HAL_IMPL_AVX_SHUFFLE(v_float32x8, permute_ps)
+OPENCV_HAL_IMPL_AVX_SHUFFLE(v_float64x4, permute_pd)
+
+template<typename _Tpvec>
+inline void v256_zip(const _Tpvec& a, const _Tpvec& b, _Tpvec& ab0, _Tpvec& ab1)
+{
+    ab0 = v256_unpacklo(a, b);
+    ab1 = v256_unpackhi(a, b);
+}
+
+template<typename _Tpvec>
+inline _Tpvec v256_combine_diagonal(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(_mm256_blend_epi32(a.val, b.val, 0xf0)); }
+
+inline v_float32x8 v256_combine_diagonal(const v_float32x8& a, const v_float32x8& b)
+{ return v256_blend<0xf0>(a, b); }
+
+inline v_float64x4 v256_combine_diagonal(const v_float64x4& a, const v_float64x4& b)
+{ return v256_blend<0xc>(a, b); }
+
+template<typename _Tpvec>
+inline _Tpvec v256_alignr_128(const _Tpvec& a, const _Tpvec& b)
+{ return v256_permute2x128<0x21>(a, b); }
+
+template<typename _Tpvec>
+inline _Tpvec v256_alignr_64(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(_mm256_alignr_epi8(a.val, b.val, 8)); }
+inline v_float64x4 v256_alignr_64(const v_float64x4& a, const v_float64x4& b)
+{ return v_float64x4(_mm256_shuffle_pd(b.val, a.val, _MM_SHUFFLE(0, 0, 1, 1))); }
+// todo: emulate float32
+
+template<typename _Tpvec>
+inline _Tpvec v256_swap_halves(const _Tpvec& a)
+{ return v256_permute2x128<1>(a, a); }
+
+template<typename _Tpvec>
+inline _Tpvec v256_reverse_64(const _Tpvec& a)
+{ return v256_permute4x64<_MM_SHUFFLE(0, 1, 2, 3)>(a); }
+
+// ZIP
+#define OPENCV_HAL_IMPL_AVX_ZIP(_Tpvec)                              \
+    inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b)    \
+    { return v256_permute2x128<0x20>(a, b); }                        \
+    inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b)   \
+    { return v256_permute2x128<0x31>(a, b); }                        \
+    inline void v_recombine(const _Tpvec& a, const _Tpvec& b,        \
+                             _Tpvec& c, _Tpvec& d)                   \
+    {                                                                \
+        _Tpvec a1b0 = v256_alignr_128(a, b);                         \
+        c = v256_combine_diagonal(a, a1b0);                          \
+        d = v256_combine_diagonal(a1b0, b);                          \
+    }                                                                \
+    inline void v_zip(const _Tpvec& a, const _Tpvec& b,              \
+                      _Tpvec& ab0, _Tpvec& ab1)                      \
+    {                                                                \
+        _Tpvec ab0ab2, ab1ab3;                                       \
+        v256_zip(a, b, ab0ab2, ab1ab3);                              \
+        v_recombine(ab0ab2, ab1ab3, ab0, ab1);                       \
+    }
+
+OPENCV_HAL_IMPL_AVX_ZIP(v_uint8x32)
+OPENCV_HAL_IMPL_AVX_ZIP(v_int8x32)
+OPENCV_HAL_IMPL_AVX_ZIP(v_uint16x16)
+OPENCV_HAL_IMPL_AVX_ZIP(v_int16x16)
+OPENCV_HAL_IMPL_AVX_ZIP(v_uint32x8)
+OPENCV_HAL_IMPL_AVX_ZIP(v_int32x8)
+OPENCV_HAL_IMPL_AVX_ZIP(v_uint64x4)
+OPENCV_HAL_IMPL_AVX_ZIP(v_int64x4)
+OPENCV_HAL_IMPL_AVX_ZIP(v_float32x8)
+OPENCV_HAL_IMPL_AVX_ZIP(v_float64x4)
+
+////////// Arithmetic, bitwise and comparison operations /////////
+
+/* Element-wise binary and unary operations */
+
+/** Arithmetics **/
+#define OPENCV_HAL_IMPL_AVX_BIN_OP(bin_op, _Tpvec, intrin)            \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)            \
+    { return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_uint8x32,  _mm256_adds_epu8)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_uint8x32,  _mm256_subs_epu8)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_int8x32,   _mm256_adds_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_int8x32,   _mm256_subs_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_uint16x16, _mm256_adds_epu16)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_uint16x16, _mm256_subs_epu16)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_int16x16,  _mm256_adds_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_int16x16,  _mm256_subs_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_uint32x8,  _mm256_add_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_uint32x8,  _mm256_sub_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_mul, v_uint32x8,  _mm256_mullo_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_int32x8,   _mm256_add_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_int32x8,   _mm256_sub_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_mul, v_int32x8,   _mm256_mullo_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_uint64x4,  _mm256_add_epi64)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_uint64x4,  _mm256_sub_epi64)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_int64x4,   _mm256_add_epi64)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_int64x4,   _mm256_sub_epi64)
+
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_float32x8, _mm256_add_ps)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_float32x8, _mm256_sub_ps)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_mul, v_float32x8, _mm256_mul_ps)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_div, v_float32x8, _mm256_div_ps)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_add, v_float64x4, _mm256_add_pd)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_sub, v_float64x4, _mm256_sub_pd)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_mul, v_float64x4, _mm256_mul_pd)
+OPENCV_HAL_IMPL_AVX_BIN_OP(v_div, v_float64x4, _mm256_div_pd)
+
+// saturating multiply 8-bit, 16-bit
+inline v_uint8x32 v_mul(const v_uint8x32& a, const v_uint8x32& b)
+{
+    v_uint16x16 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_int8x32 v_mul(const v_int8x32& a, const v_int8x32& b)
+{
+    v_int16x16 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_uint16x16 v_mul(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i pl = _mm256_mullo_epi16(a.val, b.val);
+    __m256i ph = _mm256_mulhi_epu16(a.val, b.val);
+    __m256i p0 = _mm256_unpacklo_epi16(pl, ph);
+    __m256i p1 = _mm256_unpackhi_epi16(pl, ph);
+    return v_uint16x16(_v256_packs_epu32(p0, p1));
+}
+inline v_int16x16 v_mul(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i pl = _mm256_mullo_epi16(a.val, b.val);
+    __m256i ph = _mm256_mulhi_epi16(a.val, b.val);
+    __m256i p0 = _mm256_unpacklo_epi16(pl, ph);
+    __m256i p1 = _mm256_unpackhi_epi16(pl, ph);
+    return v_int16x16(_mm256_packs_epi32(p0, p1));
+}
+
+/** Non-saturating arithmetics **/
+#define OPENCV_HAL_IMPL_AVX_BIN_FUNC(func, _Tpvec, intrin) \
+    inline _Tpvec func(const _Tpvec& a, const _Tpvec& b)   \
+    { return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_uint8x32,  _mm256_add_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_int8x32,   _mm256_add_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_uint16x16, _mm256_add_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_add_wrap, v_int16x16,  _mm256_add_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_uint8x32,  _mm256_sub_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_int8x32,   _mm256_sub_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_uint16x16, _mm256_sub_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_sub_wrap, v_int16x16,  _mm256_sub_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_mul_wrap, v_uint16x16, _mm256_mullo_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_mul_wrap, v_int16x16,  _mm256_mullo_epi16)
+
+inline v_uint8x32 v_mul_wrap(const v_uint8x32& a, const v_uint8x32& b)
+{
+    __m256i ad = _mm256_srai_epi16(a.val, 8);
+    __m256i bd = _mm256_srai_epi16(b.val, 8);
+    __m256i p0 = _mm256_mullo_epi16(a.val, b.val); // even
+    __m256i p1 = _mm256_slli_epi16(_mm256_mullo_epi16(ad, bd), 8); // odd
+
+    const __m256i b01 = _mm256_set1_epi32(0xFF00FF00);
+    return v_uint8x32(_mm256_blendv_epi8(p0, p1, b01));
+}
+inline v_int8x32 v_mul_wrap(const v_int8x32& a, const v_int8x32& b)
+{
+    return v_reinterpret_as_s8(v_mul_wrap(v_reinterpret_as_u8(a), v_reinterpret_as_u8(b)));
+}
+
+//  Multiply and expand
+inline void v_mul_expand(const v_uint8x32& a, const v_uint8x32& b,
+                         v_uint16x16& c, v_uint16x16& d)
+{
+    v_uint16x16 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int8x32& a, const v_int8x32& b,
+                         v_int16x16& c, v_int16x16& d)
+{
+    v_int16x16 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int16x16& a, const v_int16x16& b,
+                         v_int32x8& c, v_int32x8& d)
+{
+    v_int16x16 vhi = v_int16x16(_mm256_mulhi_epi16(a.val, b.val));
+
+    v_int16x16 v0, v1;
+    v_zip(v_mul_wrap(a, b), vhi, v0, v1);
+
+    c = v_reinterpret_as_s32(v0);
+    d = v_reinterpret_as_s32(v1);
+}
+
+inline void v_mul_expand(const v_uint16x16& a, const v_uint16x16& b,
+                         v_uint32x8& c, v_uint32x8& d)
+{
+    v_uint16x16 vhi = v_uint16x16(_mm256_mulhi_epu16(a.val, b.val));
+
+    v_uint16x16 v0, v1;
+    v_zip(v_mul_wrap(a, b), vhi, v0, v1);
+
+    c = v_reinterpret_as_u32(v0);
+    d = v_reinterpret_as_u32(v1);
+}
+
+inline void v_mul_expand(const v_uint32x8& a, const v_uint32x8& b,
+                         v_uint64x4& c, v_uint64x4& d)
+{
+    __m256i v0 = _mm256_mul_epu32(a.val, b.val);
+    __m256i v1 = _mm256_mul_epu32(_mm256_srli_epi64(a.val, 32), _mm256_srli_epi64(b.val, 32));
+    v_zip(v_uint64x4(v0), v_uint64x4(v1), c, d);
+}
+
+inline v_int16x16 v_mul_hi(const v_int16x16& a, const v_int16x16& b) { return v_int16x16(_mm256_mulhi_epi16(a.val, b.val)); }
+inline v_uint16x16 v_mul_hi(const v_uint16x16& a, const v_uint16x16& b) { return v_uint16x16(_mm256_mulhi_epu16(a.val, b.val)); }
+
+/** Bitwise shifts **/
+#define OPENCV_HAL_IMPL_AVX_SHIFT_OP(_Tpuvec, _Tpsvec, suffix, srai)  \
+    inline _Tpuvec v_shl(const _Tpuvec& a, int imm)                   \
+    { return _Tpuvec(_mm256_slli_##suffix(a.val, imm)); }             \
+    inline _Tpsvec v_shl(const _Tpsvec& a, int imm)                   \
+    { return _Tpsvec(_mm256_slli_##suffix(a.val, imm)); }             \
+    inline _Tpuvec v_shr(const _Tpuvec& a, int imm)                   \
+    { return _Tpuvec(_mm256_srli_##suffix(a.val, imm)); }             \
+    inline _Tpsvec v_shr(const _Tpsvec& a, int imm)                   \
+    { return _Tpsvec(srai(a.val, imm)); }                             \
+    template<int imm>                                                 \
+    inline _Tpuvec v_shl(const _Tpuvec& a)                            \
+    { return _Tpuvec(_mm256_slli_##suffix(a.val, imm)); }             \
+    template<int imm>                                                 \
+    inline _Tpsvec v_shl(const _Tpsvec& a)                            \
+    { return _Tpsvec(_mm256_slli_##suffix(a.val, imm)); }             \
+    template<int imm>                                                 \
+    inline _Tpuvec v_shr(const _Tpuvec& a)                            \
+    { return _Tpuvec(_mm256_srli_##suffix(a.val, imm)); }             \
+    template<int imm>                                                 \
+    inline _Tpsvec v_shr(const _Tpsvec& a)                            \
+    { return _Tpsvec(srai(a.val, imm)); }
+
+OPENCV_HAL_IMPL_AVX_SHIFT_OP(v_uint16x16, v_int16x16, epi16, _mm256_srai_epi16)
+OPENCV_HAL_IMPL_AVX_SHIFT_OP(v_uint32x8,  v_int32x8,  epi32, _mm256_srai_epi32)
+
+inline __m256i _mm256_srai_epi64xx(const __m256i a, int imm)
+{
+    __m256i d = _mm256_set1_epi64x((int64)1 << 63);
+    __m256i r = _mm256_srli_epi64(_mm256_add_epi64(a, d), imm);
+    return _mm256_sub_epi64(r, _mm256_srli_epi64(d, imm));
+}
+OPENCV_HAL_IMPL_AVX_SHIFT_OP(v_uint64x4,  v_int64x4,  epi64, _mm256_srai_epi64xx)
+
+
+/** Bitwise logic **/
+#define OPENCV_HAL_IMPL_AVX_LOGIC_OP(_Tpvec, suffix, not_const)     \
+    OPENCV_HAL_IMPL_AVX_BIN_OP(v_and, _Tpvec, _mm256_and_##suffix)  \
+    OPENCV_HAL_IMPL_AVX_BIN_OP(v_or, _Tpvec, _mm256_or_##suffix)    \
+    OPENCV_HAL_IMPL_AVX_BIN_OP(v_xor, _Tpvec, _mm256_xor_##suffix)  \
+    inline _Tpvec v_not(const _Tpvec& a)                            \
+    { return _Tpvec(_mm256_xor_##suffix(a.val, not_const)); }
+
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint8x32,   si256, _mm256_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int8x32,    si256, _mm256_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint16x16,  si256, _mm256_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int16x16,   si256, _mm256_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint32x8,   si256, _mm256_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int32x8,    si256, _mm256_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_uint64x4,   si256, _mm256_set1_epi64x(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_int64x4,    si256, _mm256_set1_epi64x(-1))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_float32x8,  ps,    _mm256_castsi256_ps(_mm256_set1_epi32(-1)))
+OPENCV_HAL_IMPL_AVX_LOGIC_OP(v_float64x4,  pd,    _mm256_castsi256_pd(_mm256_set1_epi32(-1)))
+
+/** Select **/
+#define OPENCV_HAL_IMPL_AVX_SELECT(_Tpvec, suffix)                               \
+    inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+    { return _Tpvec(_mm256_blendv_##suffix(b.val, a.val, mask.val)); }
+
+OPENCV_HAL_IMPL_AVX_SELECT(v_uint8x32,  epi8)
+OPENCV_HAL_IMPL_AVX_SELECT(v_int8x32,   epi8)
+OPENCV_HAL_IMPL_AVX_SELECT(v_uint16x16, epi8)
+OPENCV_HAL_IMPL_AVX_SELECT(v_int16x16,  epi8)
+OPENCV_HAL_IMPL_AVX_SELECT(v_uint32x8,  epi8)
+OPENCV_HAL_IMPL_AVX_SELECT(v_int32x8,   epi8)
+OPENCV_HAL_IMPL_AVX_SELECT(v_float32x8, ps)
+OPENCV_HAL_IMPL_AVX_SELECT(v_float64x4, pd)
+
+/** Comparison **/
+#define OPENCV_HAL_IMPL_AVX_CMP_OP_OV(_Tpvec)                            \
+    inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_not(v_eq(a, b)); }                                        \
+    inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_gt(b, a); }                                               \
+    inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_not(v_lt(a, b)); }                                        \
+    inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_ge(b, a); }
+
+#define OPENCV_HAL_IMPL_AVX_CMP_OP_INT(_Tpuvec, _Tpsvec, suffix, sbit)   \
+    inline _Tpuvec v_eq(const _Tpuvec& a, const _Tpuvec& b)              \
+    { return _Tpuvec(_mm256_cmpeq_##suffix(a.val, b.val)); }             \
+    inline _Tpuvec v_gt(const _Tpuvec& a, const _Tpuvec& b)              \
+    {                                                                    \
+        __m256i smask = _mm256_set1_##suffix(sbit);                      \
+        return _Tpuvec(_mm256_cmpgt_##suffix(                            \
+                       _mm256_xor_si256(a.val, smask),                   \
+                       _mm256_xor_si256(b.val, smask)));                 \
+    }                                                                    \
+    inline _Tpsvec v_eq(const _Tpsvec& a, const _Tpsvec& b)              \
+    { return _Tpsvec(_mm256_cmpeq_##suffix(a.val, b.val)); }             \
+    inline _Tpsvec v_gt(const _Tpsvec& a, const _Tpsvec& b)              \
+    { return _Tpsvec(_mm256_cmpgt_##suffix(a.val, b.val)); }             \
+    OPENCV_HAL_IMPL_AVX_CMP_OP_OV(_Tpuvec)                               \
+    OPENCV_HAL_IMPL_AVX_CMP_OP_OV(_Tpsvec)
+
+OPENCV_HAL_IMPL_AVX_CMP_OP_INT(v_uint8x32,  v_int8x32,  epi8,  (char)-128)
+OPENCV_HAL_IMPL_AVX_CMP_OP_INT(v_uint16x16, v_int16x16, epi16, (short)-32768)
+OPENCV_HAL_IMPL_AVX_CMP_OP_INT(v_uint32x8,  v_int32x8,  epi32, (int)0x80000000)
+
+#define OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(_Tpvec)                 \
+    inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b)         \
+    { return _Tpvec(_mm256_cmpeq_epi64(a.val, b.val)); }         \
+    inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b)         \
+    { return v_not(v_eq(a, b)); }
+
+OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(v_uint64x4)
+OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(v_int64x4)
+
+#define OPENCV_HAL_IMPL_AVX_CMP_FLT(bin_op, imm8, _Tpvec, suffix)    \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)           \
+    { return _Tpvec(_mm256_cmp_##suffix(a.val, b.val, imm8)); }
+
+#define OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(_Tpvec, suffix)               \
+    OPENCV_HAL_IMPL_AVX_CMP_FLT(v_eq, _CMP_EQ_OQ,  _Tpvec, suffix)   \
+    OPENCV_HAL_IMPL_AVX_CMP_FLT(v_ne, _CMP_NEQ_OQ, _Tpvec, suffix)   \
+    OPENCV_HAL_IMPL_AVX_CMP_FLT(v_lt,  _CMP_LT_OQ,  _Tpvec, suffix)  \
+    OPENCV_HAL_IMPL_AVX_CMP_FLT(v_gt,  _CMP_GT_OQ,  _Tpvec, suffix)  \
+    OPENCV_HAL_IMPL_AVX_CMP_FLT(v_le, _CMP_LE_OQ,  _Tpvec, suffix)   \
+    OPENCV_HAL_IMPL_AVX_CMP_FLT(v_ge, _CMP_GE_OQ,  _Tpvec, suffix)
+
+OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float32x8, ps)
+OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float64x4, pd)
+
+inline v_float32x8 v_not_nan(const v_float32x8& a)
+{ return v_float32x8(_mm256_cmp_ps(a.val, a.val, _CMP_ORD_Q)); }
+inline v_float64x4 v_not_nan(const v_float64x4& a)
+{ return v_float64x4(_mm256_cmp_pd(a.val, a.val, _CMP_ORD_Q)); }
+
+/** min/max **/
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint8x32,  _mm256_min_epu8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint8x32,  _mm256_max_epu8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_int8x32,   _mm256_min_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_int8x32,   _mm256_max_epi8)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint16x16, _mm256_min_epu16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint16x16, _mm256_max_epu16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_int16x16,  _mm256_min_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_int16x16,  _mm256_max_epi16)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint32x8,  _mm256_min_epu32)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint32x8,  _mm256_max_epu32)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_int32x8,   _mm256_min_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_int32x8,   _mm256_max_epi32)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_float32x8, _mm256_min_ps)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_float32x8, _mm256_max_ps)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_float64x4, _mm256_min_pd)
+OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_float64x4, _mm256_max_pd)
+
+/** Rotate **/
+template<int imm>
+inline v_uint8x32 v_rotate_left(const v_uint8x32& a, const v_uint8x32& b)
+{
+    enum {IMM_R = (16 - imm) & 0xFF};
+    enum {IMM_R2 = (32 - imm) & 0xFF};
+
+    if (imm == 0)  return a;
+    if (imm == 32) return b;
+    if (imm > 32)  return v_uint8x32();
+
+    __m256i swap = _mm256_permute2x128_si256(a.val, b.val, 0x03);
+    if (imm == 16) return v_uint8x32(swap);
+    if (imm < 16)  return v_uint8x32(_mm256_alignr_epi8(a.val, swap, IMM_R));
+    return v_uint8x32(_mm256_alignr_epi8(swap, b.val, IMM_R2)); // imm < 32
+}
+
+template<int imm>
+inline v_uint8x32 v_rotate_right(const v_uint8x32& a, const v_uint8x32& b)
+{
+    enum {IMM_L = (imm - 16) & 0xFF};
+
+    if (imm == 0)  return a;
+    if (imm == 32) return b;
+    if (imm > 32)  return v_uint8x32();
+
+    __m256i swap = _mm256_permute2x128_si256(a.val, b.val, 0x21);
+    if (imm == 16) return v_uint8x32(swap);
+    if (imm < 16)  return v_uint8x32(_mm256_alignr_epi8(swap, a.val, imm));
+    return v_uint8x32(_mm256_alignr_epi8(b.val, swap, IMM_L));
+}
+
+template<int imm>
+inline v_uint8x32 v_rotate_left(const v_uint8x32& a)
+{
+    enum {IMM_L = (imm - 16) & 0xFF};
+    enum {IMM_R = (16 - imm) & 0xFF};
+
+    if (imm == 0) return a;
+    if (imm > 32) return v_uint8x32();
+
+    // ESAC control[3] ? [127:0] = 0
+    __m256i swapz = _mm256_permute2x128_si256(a.val, a.val, _MM_SHUFFLE(0, 0, 2, 0));
+    if (imm == 16) return v_uint8x32(swapz);
+    if (imm < 16)  return v_uint8x32(_mm256_alignr_epi8(a.val, swapz, IMM_R));
+    return v_uint8x32(_mm256_slli_si256(swapz, IMM_L));
+}
+
+template<int imm>
+inline v_uint8x32 v_rotate_right(const v_uint8x32& a)
+{
+    enum {IMM_L = (imm - 16) & 0xFF};
+
+    if (imm == 0) return a;
+    if (imm > 32) return v_uint8x32();
+
+    // ESAC control[3] ? [127:0] = 0
+    __m256i swapz = _mm256_permute2x128_si256(a.val, a.val, _MM_SHUFFLE(2, 0, 0, 1));
+    if (imm == 16) return v_uint8x32(swapz);
+    if (imm < 16)  return v_uint8x32(_mm256_alignr_epi8(swapz, a.val, imm));
+    return v_uint8x32(_mm256_srli_si256(swapz, IMM_L));
+}
+
+#define OPENCV_HAL_IMPL_AVX_ROTATE_CAST(intrin, _Tpvec, cast)     \
+    template<int imm>                                             \
+    inline _Tpvec intrin(const _Tpvec& a, const _Tpvec& b)        \
+    {                                                             \
+        enum {IMMxW = imm * sizeof(typename _Tpvec::lane_type)};  \
+        v_uint8x32 ret = intrin<IMMxW>(v_reinterpret_as_u8(a),    \
+                                       v_reinterpret_as_u8(b));   \
+        return _Tpvec(cast(ret.val));                             \
+    }                                                             \
+    template<int imm>                                             \
+    inline _Tpvec intrin(const _Tpvec& a)                         \
+    {                                                             \
+        enum {IMMxW = imm * sizeof(typename _Tpvec::lane_type)};  \
+        v_uint8x32 ret = intrin<IMMxW>(v_reinterpret_as_u8(a));   \
+        return _Tpvec(cast(ret.val));                             \
+    }
+
+#define OPENCV_HAL_IMPL_AVX_ROTATE(_Tpvec)                                  \
+    OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_left,  _Tpvec, OPENCV_HAL_NOP) \
+    OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_right, _Tpvec, OPENCV_HAL_NOP)
+
+OPENCV_HAL_IMPL_AVX_ROTATE(v_int8x32)
+OPENCV_HAL_IMPL_AVX_ROTATE(v_uint16x16)
+OPENCV_HAL_IMPL_AVX_ROTATE(v_int16x16)
+OPENCV_HAL_IMPL_AVX_ROTATE(v_uint32x8)
+OPENCV_HAL_IMPL_AVX_ROTATE(v_int32x8)
+OPENCV_HAL_IMPL_AVX_ROTATE(v_uint64x4)
+OPENCV_HAL_IMPL_AVX_ROTATE(v_int64x4)
+
+OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_left,  v_float32x8, _mm256_castsi256_ps)
+OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_right, v_float32x8, _mm256_castsi256_ps)
+OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_left,  v_float64x4, _mm256_castsi256_pd)
+OPENCV_HAL_IMPL_AVX_ROTATE_CAST(v_rotate_right, v_float64x4, _mm256_castsi256_pd)
+
+/** Reverse **/
+inline v_uint8x32 v_reverse(const v_uint8x32 &a)
+{
+    static const __m256i perm = _mm256_setr_epi8(
+            15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0,
+            15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0);
+    __m256i vec = _mm256_shuffle_epi8(a.val, perm);
+    return v_uint8x32(_mm256_permute2x128_si256(vec, vec, 1));
+}
+
+inline v_int8x32 v_reverse(const v_int8x32 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x16 v_reverse(const v_uint16x16 &a)
+{
+    static const __m256i perm = _mm256_setr_epi8(
+            14, 15, 12, 13, 10, 11, 8, 9, 6, 7, 4, 5, 2, 3, 0, 1,
+            14, 15, 12, 13, 10, 11, 8, 9, 6, 7, 4, 5, 2, 3, 0, 1);
+    __m256i vec = _mm256_shuffle_epi8(a.val, perm);
+    return v_uint16x16(_mm256_permute2x128_si256(vec, vec, 1));
+}
+
+inline v_int16x16 v_reverse(const v_int16x16 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x8 v_reverse(const v_uint32x8 &a)
+{
+    static const __m256i perm = _mm256_setr_epi32(7, 6, 5, 4, 3, 2, 1, 0);
+    return v_uint32x8(_mm256_permutevar8x32_epi32(a.val, perm));
+}
+
+inline v_int32x8 v_reverse(const v_int32x8 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x8 v_reverse(const v_float32x8 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x4 v_reverse(const v_uint64x4 &a)
+{
+    return v_uint64x4(_mm256_permute4x64_epi64(a.val, _MM_SHUFFLE(0, 1, 2, 3)));
+}
+
+inline v_int64x4 v_reverse(const v_int64x4 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+inline v_float64x4 v_reverse(const v_float64x4 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+////////// Reduce and mask /////////
+
+/** Reduce **/
+inline unsigned v_reduce_sum(const v_uint8x32& a)
+{
+    __m256i half = _mm256_sad_epu8(a.val, _mm256_setzero_si256());
+    __m128i quarter = _mm_add_epi32(_v256_extract_low(half), _v256_extract_high(half));
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(quarter, _mm_unpackhi_epi64(quarter, quarter)));
+}
+inline int v_reduce_sum(const v_int8x32& a)
+{
+    __m256i half = _mm256_sad_epu8(_mm256_xor_si256(a.val, _mm256_set1_epi8((schar)-128)), _mm256_setzero_si256());
+    __m128i quarter = _mm_add_epi32(_v256_extract_low(half), _v256_extract_high(half));
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(quarter, _mm_unpackhi_epi64(quarter, quarter))) - 4096;
+}
+#define OPENCV_HAL_IMPL_AVX_REDUCE_32(_Tpvec, sctype, func, intrin) \
+    inline sctype v_reduce_##func(const _Tpvec& a) \
+    { \
+        __m128i val = intrin(_v256_extract_low(a.val), _v256_extract_high(a.val)); \
+        val = intrin(val, _mm_srli_si128(val,8)); \
+        val = intrin(val, _mm_srli_si128(val,4)); \
+        val = intrin(val, _mm_srli_si128(val,2)); \
+        val = intrin(val, _mm_srli_si128(val,1)); \
+        return (sctype)_mm_cvtsi128_si32(val); \
+    }
+
+OPENCV_HAL_IMPL_AVX_REDUCE_32(v_uint8x32, uchar, min, _mm_min_epu8)
+OPENCV_HAL_IMPL_AVX_REDUCE_32(v_int8x32,  schar, min, _mm_min_epi8)
+OPENCV_HAL_IMPL_AVX_REDUCE_32(v_uint8x32, uchar, max, _mm_max_epu8)
+OPENCV_HAL_IMPL_AVX_REDUCE_32(v_int8x32,  schar, max, _mm_max_epi8)
+
+#define OPENCV_HAL_IMPL_AVX_REDUCE_16(_Tpvec, sctype, func, intrin) \
+    inline sctype v_reduce_##func(const _Tpvec& a)                  \
+    {                                                               \
+        __m128i v0 = _v256_extract_low(a.val);                      \
+        __m128i v1 = _v256_extract_high(a.val);                     \
+        v0 = intrin(v0, v1);                                        \
+        v0 = intrin(v0, _mm_srli_si128(v0, 8));                     \
+        v0 = intrin(v0, _mm_srli_si128(v0, 4));                     \
+        v0 = intrin(v0, _mm_srli_si128(v0, 2));                     \
+        return (sctype) _mm_cvtsi128_si32(v0);                      \
+    }
+
+OPENCV_HAL_IMPL_AVX_REDUCE_16(v_uint16x16, ushort, min, _mm_min_epu16)
+OPENCV_HAL_IMPL_AVX_REDUCE_16(v_int16x16,  short,  min, _mm_min_epi16)
+OPENCV_HAL_IMPL_AVX_REDUCE_16(v_uint16x16, ushort, max, _mm_max_epu16)
+OPENCV_HAL_IMPL_AVX_REDUCE_16(v_int16x16,  short,  max, _mm_max_epi16)
+
+#define OPENCV_HAL_IMPL_AVX_REDUCE_8(_Tpvec, sctype, func, intrin) \
+    inline sctype v_reduce_##func(const _Tpvec& a)                 \
+    {                                                              \
+        __m128i v0 = _v256_extract_low(a.val);                     \
+        __m128i v1 = _v256_extract_high(a.val);                    \
+        v0 = intrin(v0, v1);                                       \
+        v0 = intrin(v0, _mm_srli_si128(v0, 8));                    \
+        v0 = intrin(v0, _mm_srli_si128(v0, 4));                    \
+        return (sctype) _mm_cvtsi128_si32(v0);                     \
+    }
+
+OPENCV_HAL_IMPL_AVX_REDUCE_8(v_uint32x8, unsigned, min, _mm_min_epu32)
+OPENCV_HAL_IMPL_AVX_REDUCE_8(v_int32x8,  int,      min, _mm_min_epi32)
+OPENCV_HAL_IMPL_AVX_REDUCE_8(v_uint32x8, unsigned, max, _mm_max_epu32)
+OPENCV_HAL_IMPL_AVX_REDUCE_8(v_int32x8,  int,      max, _mm_max_epi32)
+
+#define OPENCV_HAL_IMPL_AVX_REDUCE_FLT(func, intrin)                  \
+    inline float v_reduce_##func(const v_float32x8& a)                \
+    {                                                                 \
+        __m128 v0 = _v256_extract_low(a.val);                         \
+        __m128 v1 = _v256_extract_high(a.val);                        \
+        v0 = intrin(v0, v1);                                          \
+        v0 = intrin(v0, _mm_permute_ps(v0, _MM_SHUFFLE(0, 0, 3, 2))); \
+        v0 = intrin(v0, _mm_permute_ps(v0, _MM_SHUFFLE(0, 0, 0, 1))); \
+        return _mm_cvtss_f32(v0);                                     \
+    }
+
+OPENCV_HAL_IMPL_AVX_REDUCE_FLT(min, _mm_min_ps)
+OPENCV_HAL_IMPL_AVX_REDUCE_FLT(max, _mm_max_ps)
+
+inline int v_reduce_sum(const v_int32x8& a)
+{
+    __m256i s0 = _mm256_hadd_epi32(a.val, a.val);
+            s0 = _mm256_hadd_epi32(s0, s0);
+
+    __m128i s1 = _v256_extract_high(s0);
+            s1 = _mm_add_epi32(_v256_extract_low(s0), s1);
+
+    return _mm_cvtsi128_si32(s1);
+}
+
+inline unsigned v_reduce_sum(const v_uint32x8& a)
+{ return v_reduce_sum(v_reinterpret_as_s32(a)); }
+
+inline int v_reduce_sum(const v_int16x16& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+inline unsigned v_reduce_sum(const v_uint16x16& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+
+inline float v_reduce_sum(const v_float32x8& a)
+{
+    __m256 s0 = _mm256_hadd_ps(a.val, a.val);
+           s0 = _mm256_hadd_ps(s0, s0);
+
+    __m128 s1 = _v256_extract_high(s0);
+           s1 = _mm_add_ps(_v256_extract_low(s0), s1);
+
+    return _mm_cvtss_f32(s1);
+}
+
+inline uint64 v_reduce_sum(const v_uint64x4& a)
+{
+    uint64 CV_DECL_ALIGNED(32) idx[2];
+    _mm_store_si128((__m128i*)idx, _mm_add_epi64(_v256_extract_low(a.val), _v256_extract_high(a.val)));
+    return idx[0] + idx[1];
+}
+inline int64 v_reduce_sum(const v_int64x4& a)
+{
+    int64 CV_DECL_ALIGNED(32) idx[2];
+    _mm_store_si128((__m128i*)idx, _mm_add_epi64(_v256_extract_low(a.val), _v256_extract_high(a.val)));
+    return idx[0] + idx[1];
+}
+inline double v_reduce_sum(const v_float64x4& a)
+{
+    __m256d s0 = _mm256_hadd_pd(a.val, a.val);
+    return _mm_cvtsd_f64(_mm_add_pd(_v256_extract_low(s0), _v256_extract_high(s0)));
+}
+
+inline v_float32x8 v_reduce_sum4(const v_float32x8& a, const v_float32x8& b,
+                                 const v_float32x8& c, const v_float32x8& d)
+{
+    __m256 ab = _mm256_hadd_ps(a.val, b.val);
+    __m256 cd = _mm256_hadd_ps(c.val, d.val);
+    return v_float32x8(_mm256_hadd_ps(ab, cd));
+}
+
+inline unsigned v_reduce_sad(const v_uint8x32& a, const v_uint8x32& b)
+{
+    __m256i half = _mm256_sad_epu8(a.val, b.val);
+    __m128i quarter = _mm_add_epi32(_v256_extract_low(half), _v256_extract_high(half));
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(quarter, _mm_unpackhi_epi64(quarter, quarter)));
+}
+inline unsigned v_reduce_sad(const v_int8x32& a, const v_int8x32& b)
+{
+    __m256i half = _mm256_set1_epi8(0x7f);
+    half = _mm256_sad_epu8(_mm256_add_epi8(a.val, half), _mm256_add_epi8(b.val, half));
+    __m128i quarter = _mm_add_epi32(_v256_extract_low(half), _v256_extract_high(half));
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(quarter, _mm_unpackhi_epi64(quarter, quarter)));
+}
+inline unsigned v_reduce_sad(const v_uint16x16& a, const v_uint16x16& b)
+{
+    v_uint32x8 l, h;
+    v_expand(v_add_wrap(v_sub(a, b), v_sub(b, a)), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_int16x16& a, const v_int16x16& b)
+{
+    v_uint32x8 l, h;
+    v_expand(v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_uint32x8& a, const v_uint32x8& b)
+{
+    return v_reduce_sum(v_sub(v_max(a, b), v_min(a, b)));
+}
+inline unsigned v_reduce_sad(const v_int32x8& a, const v_int32x8& b)
+{
+    v_int32x8 m = v_lt(a, b);
+    return v_reduce_sum(v_reinterpret_as_u32(v_sub(v_xor(v_sub(a, b), m), m)));
+}
+inline float v_reduce_sad(const v_float32x8& a, const v_float32x8& b)
+{
+    return v_reduce_sum(v_and(v_sub(a, b), v_float32x8(_mm256_castsi256_ps(_mm256_set1_epi32(0x7fffffff)))));
+}
+
+/** Popcount **/
+inline v_uint8x32 v_popcount(const v_uint8x32& a)
+{
+    __m256i _popcnt_table = _mm256_setr_epi8(0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
+                                             0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4);
+    __m256i _popcnt_mask = _mm256_set1_epi8(0x0F);
+    return v_uint8x32(_mm256_add_epi8(_mm256_shuffle_epi8(_popcnt_table, _mm256_and_si256(                  a.val    , _popcnt_mask)),
+                                      _mm256_shuffle_epi8(_popcnt_table, _mm256_and_si256(_mm256_srli_epi16(a.val, 4), _popcnt_mask))));
+}
+inline v_uint16x16 v_popcount(const v_uint16x16& a)
+{
+    v_uint8x32 p = v_popcount(v_reinterpret_as_u8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    return v_and(v_reinterpret_as_u16(p), v256_setall_u16(0x00ff));
+}
+inline v_uint32x8 v_popcount(const v_uint32x8& a)
+{
+    v_uint8x32 p = v_popcount(v_reinterpret_as_u8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    p = v_add(p, v_rotate_right<2>(p));
+    return v_and(v_reinterpret_as_u32(p), v256_setall_u32(0x000000ff));
+}
+inline v_uint64x4 v_popcount(const v_uint64x4& a)
+{
+    return v_uint64x4(_mm256_sad_epu8(v_popcount(v_reinterpret_as_u8(a)).val, _mm256_setzero_si256()));
+}
+inline v_uint8x32 v_popcount(const v_int8x32& a)
+{ return v_popcount(v_reinterpret_as_u8(a)); }
+inline v_uint16x16 v_popcount(const v_int16x16& a)
+{ return v_popcount(v_reinterpret_as_u16(a)); }
+inline v_uint32x8 v_popcount(const v_int32x8& a)
+{ return v_popcount(v_reinterpret_as_u32(a)); }
+inline v_uint64x4 v_popcount(const v_int64x4& a)
+{ return v_popcount(v_reinterpret_as_u64(a)); }
+
+/** Mask **/
+inline int v_signmask(const v_int8x32& a)
+{ return _mm256_movemask_epi8(a.val); }
+inline int v_signmask(const v_uint8x32& a)
+{ return v_signmask(v_reinterpret_as_s8(a)); }
+
+inline int v_signmask(const v_int16x16& a)
+{ return v_signmask(v_pack(a, a)) & 0xFFFF; }
+inline int v_signmask(const v_uint16x16& a)
+{ return v_signmask(v_reinterpret_as_s16(a)); }
+
+inline int v_signmask(const v_float32x8& a)
+{ return _mm256_movemask_ps(a.val); }
+inline int v_signmask(const v_float64x4& a)
+{ return _mm256_movemask_pd(a.val); }
+
+inline int v_signmask(const v_int32x8& a)
+{ return v_signmask(v_reinterpret_as_f32(a)); }
+inline int v_signmask(const v_uint32x8& a)
+{ return v_signmask(v_reinterpret_as_f32(a)); }
+
+inline int v_signmask(const v_int64x4& a)
+{ return v_signmask(v_reinterpret_as_f64(a)); }
+inline int v_signmask(const v_uint64x4& a)
+{ return v_signmask(v_reinterpret_as_f64(a)); }
+
+inline int v_scan_forward(const v_int8x32& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_uint8x32& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_int16x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_uint16x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_int32x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_uint32x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_float32x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_int64x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_uint64x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_float64x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+
+/** Checks **/
+#define OPENCV_HAL_IMPL_AVX_CHECK(_Tpvec, allmask) \
+    inline bool v_check_all(const _Tpvec& a) { return v_signmask(a) == allmask; } \
+    inline bool v_check_any(const _Tpvec& a) { return v_signmask(a) != 0; }
+OPENCV_HAL_IMPL_AVX_CHECK(v_uint8x32, -1)
+OPENCV_HAL_IMPL_AVX_CHECK(v_int8x32, -1)
+OPENCV_HAL_IMPL_AVX_CHECK(v_uint32x8, 255)
+OPENCV_HAL_IMPL_AVX_CHECK(v_int32x8, 255)
+OPENCV_HAL_IMPL_AVX_CHECK(v_uint64x4, 15)
+OPENCV_HAL_IMPL_AVX_CHECK(v_int64x4, 15)
+OPENCV_HAL_IMPL_AVX_CHECK(v_float32x8, 255)
+OPENCV_HAL_IMPL_AVX_CHECK(v_float64x4, 15)
+
+#define OPENCV_HAL_IMPL_AVX_CHECK_SHORT(_Tpvec)  \
+    inline bool v_check_all(const _Tpvec& a) { return (v_signmask(v_reinterpret_as_s8(a)) & 0xaaaaaaaa) == 0xaaaaaaaa; } \
+    inline bool v_check_any(const _Tpvec& a) { return (v_signmask(v_reinterpret_as_s8(a)) & 0xaaaaaaaa) != 0; }
+OPENCV_HAL_IMPL_AVX_CHECK_SHORT(v_uint16x16)
+OPENCV_HAL_IMPL_AVX_CHECK_SHORT(v_int16x16)
+
+////////// Other math /////////
+
+/** Some frequent operations **/
+#if CV_FMA3
+#define OPENCV_HAL_IMPL_AVX_MULADD(_Tpvec, suffix)                            \
+    inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)    \
+    { return _Tpvec(_mm256_fmadd_##suffix(a.val, b.val, c.val)); }            \
+    inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \
+    { return _Tpvec(_mm256_fmadd_##suffix(a.val, b.val, c.val)); }
+#else
+#define OPENCV_HAL_IMPL_AVX_MULADD(_Tpvec, suffix)                                    \
+    inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)            \
+    { return _Tpvec(_mm256_add_##suffix(_mm256_mul_##suffix(a.val, b.val), c.val)); } \
+    inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)         \
+    { return _Tpvec(_mm256_add_##suffix(_mm256_mul_##suffix(a.val, b.val), c.val)); }
+#endif
+
+#define OPENCV_HAL_IMPL_AVX_MISC(_Tpvec, suffix)                              \
+    inline _Tpvec v_sqrt(const _Tpvec& x)                                     \
+    { return _Tpvec(_mm256_sqrt_##suffix(x.val)); }                           \
+    inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b)           \
+    { return v_fma(a, a, v_mul(b, b)); }                                      \
+    inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b)               \
+    { return v_sqrt(v_fma(a, a, v_mul(b, b))); }
+
+OPENCV_HAL_IMPL_AVX_MULADD(v_float32x8, ps)
+OPENCV_HAL_IMPL_AVX_MULADD(v_float64x4, pd)
+OPENCV_HAL_IMPL_AVX_MISC(v_float32x8, ps)
+OPENCV_HAL_IMPL_AVX_MISC(v_float64x4, pd)
+
+inline v_int32x8 v_fma(const v_int32x8& a, const v_int32x8& b, const v_int32x8& c)
+{
+    return v_add(v_mul(a, b), c);
+}
+
+inline v_int32x8 v_muladd(const v_int32x8& a, const v_int32x8& b, const v_int32x8& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_float32x8 v_invsqrt(const v_float32x8& x)
+{
+    v_float32x8 half = v_mul(x, v256_setall_f32(0.5));
+    v_float32x8 t  = v_float32x8(_mm256_rsqrt_ps(x.val));
+    // todo: _mm256_fnmsub_ps
+    t = v_mul(t, v_sub(v256_setall_f32(1.5), v_mul(v_mul(t, t), half)));
+    return t;
+}
+
+inline v_float64x4 v_invsqrt(const v_float64x4& x)
+{
+    return v_div(v256_setall_f64(1.), v_sqrt(x));
+}
+
+/** Absolute values **/
+#define OPENCV_HAL_IMPL_AVX_ABS(_Tpvec, suffix)         \
+    inline v_u##_Tpvec v_abs(const v_##_Tpvec& x)       \
+    { return v_u##_Tpvec(_mm256_abs_##suffix(x.val)); }
+
+OPENCV_HAL_IMPL_AVX_ABS(int8x32,  epi8)
+OPENCV_HAL_IMPL_AVX_ABS(int16x16, epi16)
+OPENCV_HAL_IMPL_AVX_ABS(int32x8,  epi32)
+
+inline v_float32x8 v_abs(const v_float32x8& x)
+{ return v_and(x, v_float32x8(_mm256_castsi256_ps(_mm256_set1_epi32(0x7fffffff)))); }
+inline v_float64x4 v_abs(const v_float64x4& x)
+{ return v_and(x, v_float64x4(_mm256_castsi256_pd(_mm256_srli_epi64(_mm256_set1_epi64x(-1), 1)))); }
+
+/** Absolute difference **/
+inline v_uint8x32 v_absdiff(const v_uint8x32& a, const v_uint8x32& b)
+{ return v_add_wrap(v_sub(a, b), v_sub(b, a)); }
+inline v_uint16x16 v_absdiff(const v_uint16x16& a, const v_uint16x16& b)
+{ return v_add_wrap(v_sub(a, b), v_sub(b, a)); }
+inline v_uint32x8 v_absdiff(const v_uint32x8& a, const v_uint32x8& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+inline v_uint8x32 v_absdiff(const v_int8x32& a, const v_int8x32& b)
+{
+    v_int8x32 d = v_sub_wrap(a, b);
+    v_int8x32 m = v_lt(a, b);
+    return v_reinterpret_as_u8(v_sub_wrap(v_xor(d, m), m));
+}
+
+inline v_uint16x16 v_absdiff(const v_int16x16& a, const v_int16x16& b)
+{ return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))); }
+
+inline v_uint32x8 v_absdiff(const v_int32x8& a, const v_int32x8& b)
+{
+    v_int32x8 d = v_sub(a, b);
+    v_int32x8 m = v_lt(a, b);
+    return v_reinterpret_as_u32(v_sub(v_xor(d, m), m));
+}
+
+inline v_float32x8 v_absdiff(const v_float32x8& a, const v_float32x8& b)
+{ return v_abs(v_sub(a, b)); }
+
+inline v_float64x4 v_absdiff(const v_float64x4& a, const v_float64x4& b)
+{ return v_abs(v_sub(a, b)); }
+
+/** Saturating absolute difference **/
+inline v_int8x32 v_absdiffs(const v_int8x32& a, const v_int8x32& b)
+{
+    v_int8x32 d = v_sub(a, b);
+    v_int8x32 m = v_lt(a, b);
+    return v_sub(v_xor(d, m), m);
+}
+inline v_int16x16 v_absdiffs(const v_int16x16& a, const v_int16x16& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+////////// Conversions /////////
+
+/** Rounding **/
+inline v_int32x8 v_round(const v_float32x8& a)
+{ return v_int32x8(_mm256_cvtps_epi32(a.val)); }
+
+inline v_int32x8 v_round(const v_float64x4& a)
+{ return v_int32x8(_mm256_castsi128_si256(_mm256_cvtpd_epi32(a.val))); }
+
+inline v_int32x8 v_round(const v_float64x4& a, const v_float64x4& b)
+{
+    __m128i ai = _mm256_cvtpd_epi32(a.val), bi = _mm256_cvtpd_epi32(b.val);
+    return v_int32x8(_v256_combine(ai, bi));
+}
+
+inline v_int32x8 v_trunc(const v_float32x8& a)
+{ return v_int32x8(_mm256_cvttps_epi32(a.val)); }
+
+inline v_int32x8 v_trunc(const v_float64x4& a)
+{ return v_int32x8(_mm256_castsi128_si256(_mm256_cvttpd_epi32(a.val))); }
+
+inline v_int32x8 v_floor(const v_float32x8& a)
+{ return v_int32x8(_mm256_cvttps_epi32(_mm256_floor_ps(a.val))); }
+
+inline v_int32x8 v_floor(const v_float64x4& a)
+{ return v_trunc(v_float64x4(_mm256_floor_pd(a.val))); }
+
+inline v_int32x8 v_ceil(const v_float32x8& a)
+{ return v_int32x8(_mm256_cvttps_epi32(_mm256_ceil_ps(a.val))); }
+
+inline v_int32x8 v_ceil(const v_float64x4& a)
+{ return v_trunc(v_float64x4(_mm256_ceil_pd(a.val))); }
+
+/** To float **/
+inline v_float32x8 v_cvt_f32(const v_int32x8& a)
+{ return v_float32x8(_mm256_cvtepi32_ps(a.val)); }
+
+inline v_float32x8 v_cvt_f32(const v_float64x4& a)
+{ return v_float32x8(_mm256_castps128_ps256(_mm256_cvtpd_ps(a.val))); }
+
+inline v_float32x8 v_cvt_f32(const v_float64x4& a, const v_float64x4& b)
+{
+    __m128 af = _mm256_cvtpd_ps(a.val), bf = _mm256_cvtpd_ps(b.val);
+    return v_float32x8(_v256_combine(af, bf));
+}
+
+inline v_float64x4 v_cvt_f64(const v_int32x8& a)
+{ return v_float64x4(_mm256_cvtepi32_pd(_v256_extract_low(a.val))); }
+
+inline v_float64x4 v_cvt_f64_high(const v_int32x8& a)
+{ return v_float64x4(_mm256_cvtepi32_pd(_v256_extract_high(a.val))); }
+
+inline v_float64x4 v_cvt_f64(const v_float32x8& a)
+{ return v_float64x4(_mm256_cvtps_pd(_v256_extract_low(a.val))); }
+
+inline v_float64x4 v_cvt_f64_high(const v_float32x8& a)
+{ return v_float64x4(_mm256_cvtps_pd(_v256_extract_high(a.val))); }
+
+// from (Mysticial and wim) https://stackoverflow.com/q/41144668
+inline v_float64x4 v_cvt_f64(const v_int64x4& v)
+{
+    // constants encoded as floating-point
+    __m256i magic_i_lo   = _mm256_set1_epi64x(0x4330000000000000); // 2^52
+    __m256i magic_i_hi32 = _mm256_set1_epi64x(0x4530000080000000); // 2^84 + 2^63
+    __m256i magic_i_all  = _mm256_set1_epi64x(0x4530000080100000); // 2^84 + 2^63 + 2^52
+    __m256d magic_d_all  = _mm256_castsi256_pd(magic_i_all);
+
+    // Blend the 32 lowest significant bits of v with magic_int_lo
+    __m256i v_lo         = _mm256_blend_epi32(magic_i_lo, v.val, 0x55);
+    // Extract the 32 most significant bits of v
+    __m256i v_hi         = _mm256_srli_epi64(v.val, 32);
+    // Flip the msb of v_hi and blend with 0x45300000
+            v_hi         = _mm256_xor_si256(v_hi, magic_i_hi32);
+    // Compute in double precision
+    __m256d v_hi_dbl     = _mm256_sub_pd(_mm256_castsi256_pd(v_hi), magic_d_all);
+    // (v_hi - magic_d_all) + v_lo  Do not assume associativity of floating point addition
+    __m256d result       = _mm256_add_pd(v_hi_dbl, _mm256_castsi256_pd(v_lo));
+    return v_float64x4(result);
+}
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x32 v256_lut(const schar* tab, const int* idx)
+{
+    return v_int8x32(_mm256_setr_epi8(tab[idx[ 0]], tab[idx[ 1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]],
+                                      tab[idx[ 8]], tab[idx[ 9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]],
+                                      tab[idx[16]], tab[idx[17]], tab[idx[18]], tab[idx[19]], tab[idx[20]], tab[idx[21]], tab[idx[22]], tab[idx[23]],
+                                      tab[idx[24]], tab[idx[25]], tab[idx[26]], tab[idx[27]], tab[idx[28]], tab[idx[29]], tab[idx[30]], tab[idx[31]]));
+}
+inline v_int8x32 v256_lut_pairs(const schar* tab, const int* idx)
+{
+    return v_int8x32(_mm256_setr_epi16(*(const short*)(tab + idx[ 0]), *(const short*)(tab + idx[ 1]), *(const short*)(tab + idx[ 2]), *(const short*)(tab + idx[ 3]),
+                                       *(const short*)(tab + idx[ 4]), *(const short*)(tab + idx[ 5]), *(const short*)(tab + idx[ 6]), *(const short*)(tab + idx[ 7]),
+                                       *(const short*)(tab + idx[ 8]), *(const short*)(tab + idx[ 9]), *(const short*)(tab + idx[10]), *(const short*)(tab + idx[11]),
+                                       *(const short*)(tab + idx[12]), *(const short*)(tab + idx[13]), *(const short*)(tab + idx[14]), *(const short*)(tab + idx[15])));
+}
+inline v_int8x32 v256_lut_quads(const schar* tab, const int* idx)
+{
+    return v_int8x32(_mm256_i32gather_epi32((const int*)tab, _mm256_loadu_si256((const __m256i*)idx), 1));
+}
+inline v_uint8x32 v256_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut((const schar *)tab, idx)); }
+inline v_uint8x32 v256_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut_pairs((const schar *)tab, idx)); }
+inline v_uint8x32 v256_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut_quads((const schar *)tab, idx)); }
+
+inline v_int16x16 v256_lut(const short* tab, const int* idx)
+{
+    return v_int16x16(_mm256_setr_epi16(tab[idx[0]], tab[idx[1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]],
+                                        tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]]));
+}
+inline v_int16x16 v256_lut_pairs(const short* tab, const int* idx)
+{
+    return v_int16x16(_mm256_i32gather_epi32((const int*)tab, _mm256_loadu_si256((const __m256i*)idx), 2));
+}
+inline v_int16x16 v256_lut_quads(const short* tab, const int* idx)
+{
+#if defined(__GNUC__)
+    return v_int16x16(_mm256_i32gather_epi64((const long long int*)tab, _mm_loadu_si128((const __m128i*)idx), 2));//Looks like intrinsic has wrong definition
+#else
+    return v_int16x16(_mm256_i32gather_epi64((const int64*)tab, _mm_loadu_si128((const __m128i*)idx), 2));
+#endif
+}
+inline v_uint16x16 v256_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut((const short *)tab, idx)); }
+inline v_uint16x16 v256_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut_pairs((const short *)tab, idx)); }
+inline v_uint16x16 v256_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut_quads((const short *)tab, idx)); }
+
+inline v_int32x8 v256_lut(const int* tab, const int* idx)
+{
+    return v_int32x8(_mm256_i32gather_epi32(tab, _mm256_loadu_si256((const __m256i*)idx), 4));
+}
+inline v_int32x8 v256_lut_pairs(const int* tab, const int* idx)
+{
+#if defined(__GNUC__)
+    return v_int32x8(_mm256_i32gather_epi64((const long long int*)tab, _mm_loadu_si128((const __m128i*)idx), 4));
+#else
+    return v_int32x8(_mm256_i32gather_epi64((const int64*)tab, _mm_loadu_si128((const __m128i*)idx), 4));
+#endif
+}
+inline v_int32x8 v256_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x8(_v256_combine(_mm_loadu_si128((const __m128i*)(tab + idx[0])), _mm_loadu_si128((const __m128i*)(tab + idx[1]))));
+}
+inline v_uint32x8 v256_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut((const int *)tab, idx)); }
+inline v_uint32x8 v256_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut_pairs((const int *)tab, idx)); }
+inline v_uint32x8 v256_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut_quads((const int *)tab, idx)); }
+
+inline v_int64x4 v256_lut(const int64* tab, const int* idx)
+{
+#if defined(__GNUC__)
+    return v_int64x4(_mm256_i32gather_epi64((const long long int*)tab, _mm_loadu_si128((const __m128i*)idx), 8));
+#else
+    return v_int64x4(_mm256_i32gather_epi64(tab, _mm_loadu_si128((const __m128i*)idx), 8));
+#endif
+}
+inline v_int64x4 v256_lut_pairs(const int64* tab, const int* idx)
+{
+    return v_int64x4(_v256_combine(_mm_loadu_si128((const __m128i*)(tab + idx[0])), _mm_loadu_si128((const __m128i*)(tab + idx[1]))));
+}
+inline v_uint64x4 v256_lut(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v256_lut((const int64 *)tab, idx)); }
+inline v_uint64x4 v256_lut_pairs(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v256_lut_pairs((const int64 *)tab, idx)); }
+
+inline v_float32x8 v256_lut(const float* tab, const int* idx)
+{
+    return v_float32x8(_mm256_i32gather_ps(tab, _mm256_loadu_si256((const __m256i*)idx), 4));
+}
+inline v_float32x8 v256_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v256_lut_pairs((const int *)tab, idx)); }
+inline v_float32x8 v256_lut_quads(const float* tab, const int* idx) { return v_reinterpret_as_f32(v256_lut_quads((const int *)tab, idx)); }
+
+inline v_float64x4 v256_lut(const double* tab, const int* idx)
+{
+    return v_float64x4(_mm256_i32gather_pd(tab, _mm_loadu_si128((const __m128i*)idx), 8));
+}
+inline v_float64x4 v256_lut_pairs(const double* tab, const int* idx) { return v_float64x4(_v256_combine(_mm_loadu_pd(tab + idx[0]), _mm_loadu_pd(tab + idx[1]))); }
+
+inline v_int32x8 v_lut(const int* tab, const v_int32x8& idxvec)
+{
+    return v_int32x8(_mm256_i32gather_epi32(tab, idxvec.val, 4));
+}
+
+inline v_uint32x8 v_lut(const unsigned* tab, const v_int32x8& idxvec)
+{
+    return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec));
+}
+
+inline v_float32x8 v_lut(const float* tab, const v_int32x8& idxvec)
+{
+    return v_float32x8(_mm256_i32gather_ps(tab, idxvec.val, 4));
+}
+
+inline v_float64x4 v_lut(const double* tab, const v_int32x8& idxvec)
+{
+    return v_float64x4(_mm256_i32gather_pd(tab, _mm256_castsi256_si128(idxvec.val), 8));
+}
+
+inline void v_lut_deinterleave(const float* tab, const v_int32x8& idxvec, v_float32x8& x, v_float32x8& y)
+{
+    int CV_DECL_ALIGNED(32) idx[8];
+    v_store_aligned(idx, idxvec);
+    __m128 z = _mm_setzero_ps();
+    __m128 xy01, xy45, xy23, xy67;
+    xy01 = _mm_loadl_pi(z, (const __m64*)(tab + idx[0]));
+    xy01 = _mm_loadh_pi(xy01, (const __m64*)(tab + idx[1]));
+    xy45 = _mm_loadl_pi(z, (const __m64*)(tab + idx[4]));
+    xy45 = _mm_loadh_pi(xy45, (const __m64*)(tab + idx[5]));
+    __m256 xy0145 = _v256_combine(xy01, xy45);
+    xy23 = _mm_loadl_pi(z, (const __m64*)(tab + idx[2]));
+    xy23 = _mm_loadh_pi(xy23, (const __m64*)(tab + idx[3]));
+    xy67 = _mm_loadl_pi(z, (const __m64*)(tab + idx[6]));
+    xy67 = _mm_loadh_pi(xy67, (const __m64*)(tab + idx[7]));
+    __m256 xy2367 = _v256_combine(xy23, xy67);
+
+    __m256 xxyy0145 = _mm256_unpacklo_ps(xy0145, xy2367);
+    __m256 xxyy2367 = _mm256_unpackhi_ps(xy0145, xy2367);
+
+    x = v_float32x8(_mm256_unpacklo_ps(xxyy0145, xxyy2367));
+    y = v_float32x8(_mm256_unpackhi_ps(xxyy0145, xxyy2367));
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x8& idxvec, v_float64x4& x, v_float64x4& y)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_low(idx, idxvec);
+    __m128d xy0 = _mm_loadu_pd(tab + idx[0]);
+    __m128d xy2 = _mm_loadu_pd(tab + idx[2]);
+    __m128d xy1 = _mm_loadu_pd(tab + idx[1]);
+    __m128d xy3 = _mm_loadu_pd(tab + idx[3]);
+    __m256d xy02 = _v256_combine(xy0, xy2);
+    __m256d xy13 = _v256_combine(xy1, xy3);
+
+    x = v_float64x4(_mm256_unpacklo_pd(xy02, xy13));
+    y = v_float64x4(_mm256_unpackhi_pd(xy02, xy13));
+}
+
+inline v_int8x32 v_interleave_pairs(const v_int8x32& vec)
+{
+    return v_int8x32(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0d0e0c0b090a08, 0x0705060403010200, 0x0f0d0e0c0b090a08, 0x0705060403010200)));
+}
+inline v_uint8x32 v_interleave_pairs(const v_uint8x32& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x32 v_interleave_quads(const v_int8x32& vec)
+{
+    return v_int8x32(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0b0e0a0d090c08, 0x0703060205010400, 0x0f0b0e0a0d090c08, 0x0703060205010400)));
+}
+inline v_uint8x32 v_interleave_quads(const v_uint8x32& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x16 v_interleave_pairs(const v_int16x16& vec)
+{
+    return v_int16x16(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0e0b0a0d0c0908, 0x0706030205040100, 0x0f0e0b0a0d0c0908, 0x0706030205040100)));
+}
+inline v_uint16x16 v_interleave_pairs(const v_uint16x16& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x16 v_interleave_quads(const v_int16x16& vec)
+{
+    return v_int16x16(_mm256_shuffle_epi8(vec.val, _mm256_set_epi64x(0x0f0e07060d0c0504, 0x0b0a030209080100, 0x0f0e07060d0c0504, 0x0b0a030209080100)));
+}
+inline v_uint16x16 v_interleave_quads(const v_uint16x16& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x8 v_interleave_pairs(const v_int32x8& vec)
+{
+    return v_int32x8(_mm256_shuffle_epi32(vec.val, _MM_SHUFFLE(3, 1, 2, 0)));
+}
+inline v_uint32x8 v_interleave_pairs(const v_uint32x8& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x8 v_interleave_pairs(const v_float32x8& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x32 v_pack_triplets(const v_int8x32& vec)
+{
+    return v_int8x32(_mm256_permutevar8x32_epi32(_mm256_shuffle_epi8(vec.val, _mm256_broadcastsi128_si256(_mm_set_epi64x(0xffffff0f0e0d0c0a, 0x0908060504020100))),
+                                                 _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+inline v_uint8x32 v_pack_triplets(const v_uint8x32& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x16 v_pack_triplets(const v_int16x16& vec)
+{
+    return v_int16x16(_mm256_permutevar8x32_epi32(_mm256_shuffle_epi8(vec.val, _mm256_broadcastsi128_si256(_mm_set_epi64x(0xffff0f0e0d0c0b0a, 0x0908050403020100))),
+                                                  _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+inline v_uint16x16 v_pack_triplets(const v_uint16x16& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x8 v_pack_triplets(const v_int32x8& vec)
+{
+    return v_int32x8(_mm256_permutevar8x32_epi32(vec.val, _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+inline v_uint32x8 v_pack_triplets(const v_uint32x8& vec) { return v_reinterpret_as_u32(v_pack_triplets(v_reinterpret_as_s32(vec))); }
+inline v_float32x8 v_pack_triplets(const v_float32x8& vec)
+{
+    return v_float32x8(_mm256_permutevar8x32_ps(vec.val, _mm256_set_epi64x(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+
+////////// Matrix operations /////////
+
+//////// Dot Product ////////
+
+// 16 >> 32
+inline v_int32x8 v_dotprod(const v_int16x16& a, const v_int16x16& b)
+{ return v_int32x8(_mm256_madd_epi16(a.val, b.val)); }
+inline v_int32x8 v_dotprod(const v_int16x16& a, const v_int16x16& b, const v_int32x8& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 32 >> 64
+inline v_int64x4 v_dotprod(const v_int32x8& a, const v_int32x8& b)
+{
+    __m256i even = _mm256_mul_epi32(a.val, b.val);
+    __m256i odd = _mm256_mul_epi32(_mm256_srli_epi64(a.val, 32), _mm256_srli_epi64(b.val, 32));
+    return v_int64x4(_mm256_add_epi64(even, odd));
+}
+inline v_int64x4 v_dotprod(const v_int32x8& a, const v_int32x8& b, const v_int64x4& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 8 >> 32
+inline v_uint32x8 v_dotprod_expand(const v_uint8x32& a, const v_uint8x32& b)
+{
+    __m256i even_m = _mm256_set1_epi32(0xFF00FF00);
+    __m256i even_a = _mm256_blendv_epi8(a.val, _mm256_setzero_si256(), even_m);
+    __m256i odd_a  = _mm256_srli_epi16(a.val, 8);
+
+    __m256i even_b = _mm256_blendv_epi8(b.val, _mm256_setzero_si256(), even_m);
+    __m256i odd_b  = _mm256_srli_epi16(b.val, 8);
+
+    __m256i prod0  = _mm256_madd_epi16(even_a, even_b);
+    __m256i prod1  = _mm256_madd_epi16(odd_a, odd_b);
+    return v_uint32x8(_mm256_add_epi32(prod0, prod1));
+}
+inline v_uint32x8 v_dotprod_expand(const v_uint8x32& a, const v_uint8x32& b, const v_uint32x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int32x8 v_dotprod_expand(const v_int8x32& a, const v_int8x32& b)
+{
+    __m256i even_a = _mm256_srai_epi16(_mm256_bslli_epi128(a.val, 1), 8);
+    __m256i odd_a  = _mm256_srai_epi16(a.val, 8);
+
+    __m256i even_b = _mm256_srai_epi16(_mm256_bslli_epi128(b.val, 1), 8);
+    __m256i odd_b  = _mm256_srai_epi16(b.val, 8);
+
+    __m256i prod0  = _mm256_madd_epi16(even_a, even_b);
+    __m256i prod1  = _mm256_madd_epi16(odd_a, odd_b);
+    return v_int32x8(_mm256_add_epi32(prod0, prod1));
+}
+inline v_int32x8 v_dotprod_expand(const v_int8x32& a, const v_int8x32& b, const v_int32x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x4 v_dotprod_expand(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i mullo = _mm256_mullo_epi16(a.val, b.val);
+    __m256i mulhi = _mm256_mulhi_epu16(a.val, b.val);
+    __m256i mul0  = _mm256_unpacklo_epi16(mullo, mulhi);
+    __m256i mul1  = _mm256_unpackhi_epi16(mullo, mulhi);
+
+    __m256i p02   = _mm256_blend_epi32(mul0, _mm256_setzero_si256(), 0xAA);
+    __m256i p13   = _mm256_srli_epi64(mul0, 32);
+    __m256i p46   = _mm256_blend_epi32(mul1, _mm256_setzero_si256(), 0xAA);
+    __m256i p57   = _mm256_srli_epi64(mul1, 32);
+
+    __m256i p15_  = _mm256_add_epi64(p02, p13);
+    __m256i p9d_  = _mm256_add_epi64(p46, p57);
+
+    return v_uint64x4(_mm256_add_epi64(
+        _mm256_unpacklo_epi64(p15_, p9d_),
+        _mm256_unpackhi_epi64(p15_, p9d_)
+    ));
+}
+inline v_uint64x4 v_dotprod_expand(const v_uint16x16& a, const v_uint16x16& b, const v_uint64x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x4 v_dotprod_expand(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i prod = _mm256_madd_epi16(a.val, b.val);
+    __m256i sign = _mm256_srai_epi32(prod, 31);
+
+    __m256i lo = _mm256_unpacklo_epi32(prod, sign);
+    __m256i hi = _mm256_unpackhi_epi32(prod, sign);
+
+    return v_int64x4(_mm256_add_epi64(
+        _mm256_unpacklo_epi64(lo, hi),
+        _mm256_unpackhi_epi64(lo, hi)
+    ));
+}
+inline v_int64x4 v_dotprod_expand(const v_int16x16& a, const v_int16x16& b, const v_int64x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x4 v_dotprod_expand(const v_int32x8& a, const v_int32x8& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x4 v_dotprod_expand(const v_int32x8& a, const v_int32x8& b, const v_float64x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x8 v_dotprod_fast(const v_int16x16& a, const v_int16x16& b)
+{ return v_dotprod(a, b); }
+inline v_int32x8 v_dotprod_fast(const v_int16x16& a, const v_int16x16& b, const v_int32x8& c)
+{ return v_dotprod(a, b, c); }
+
+// 32 >> 64
+inline v_int64x4 v_dotprod_fast(const v_int32x8& a, const v_int32x8& b)
+{ return v_dotprod(a, b); }
+inline v_int64x4 v_dotprod_fast(const v_int32x8& a, const v_int32x8& b, const v_int64x4& c)
+{ return v_dotprod(a, b, c); }
+
+// 8 >> 32
+inline v_uint32x8 v_dotprod_expand_fast(const v_uint8x32& a, const v_uint8x32& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint32x8 v_dotprod_expand_fast(const v_uint8x32& a, const v_uint8x32& b, const v_uint32x8& c)
+{ return v_dotprod_expand(a, b, c); }
+
+inline v_int32x8 v_dotprod_expand_fast(const v_int8x32& a, const v_int8x32& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int32x8 v_dotprod_expand_fast(const v_int8x32& a, const v_int8x32& b, const v_int32x8& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 16 >> 64
+inline v_uint64x4 v_dotprod_expand_fast(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i mullo = _mm256_mullo_epi16(a.val, b.val);
+    __m256i mulhi = _mm256_mulhi_epu16(a.val, b.val);
+    __m256i mul0  = _mm256_unpacklo_epi16(mullo, mulhi);
+    __m256i mul1  = _mm256_unpackhi_epi16(mullo, mulhi);
+
+    __m256i p02   = _mm256_blend_epi32(mul0, _mm256_setzero_si256(), 0xAA);
+    __m256i p13   = _mm256_srli_epi64(mul0, 32);
+    __m256i p46   = _mm256_blend_epi32(mul1, _mm256_setzero_si256(), 0xAA);
+    __m256i p57   = _mm256_srli_epi64(mul1, 32);
+
+    __m256i p15_  = _mm256_add_epi64(p02, p13);
+    __m256i p9d_  = _mm256_add_epi64(p46, p57);
+
+    return v_uint64x4(_mm256_add_epi64(p15_, p9d_));
+}
+inline v_uint64x4 v_dotprod_expand_fast(const v_uint16x16& a, const v_uint16x16& b, const v_uint64x4& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+inline v_int64x4 v_dotprod_expand_fast(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i prod = _mm256_madd_epi16(a.val, b.val);
+    __m256i sign = _mm256_srai_epi32(prod, 31);
+    __m256i lo = _mm256_unpacklo_epi32(prod, sign);
+    __m256i hi = _mm256_unpackhi_epi32(prod, sign);
+    return v_int64x4(_mm256_add_epi64(lo, hi));
+}
+inline v_int64x4 v_dotprod_expand_fast(const v_int16x16& a, const v_int16x16& b, const v_int64x4& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x4 v_dotprod_expand_fast(const v_int32x8& a, const v_int32x8& b)
+{ return v_dotprod_expand(a, b); }
+inline v_float64x4 v_dotprod_expand_fast(const v_int32x8& a, const v_int32x8& b, const v_float64x4& c)
+{ return v_dotprod_expand(a, b, c); }
+
+#define OPENCV_HAL_AVX_SPLAT2_PS(a, im) \
+    v_float32x8(_mm256_permute_ps(a.val, _MM_SHUFFLE(im, im, im, im)))
+
+inline v_float32x8 v_matmul(const v_float32x8& v, const v_float32x8& m0,
+                            const v_float32x8& m1, const v_float32x8& m2,
+                            const v_float32x8& m3)
+{
+    v_float32x8 v04 = OPENCV_HAL_AVX_SPLAT2_PS(v, 0);
+    v_float32x8 v15 = OPENCV_HAL_AVX_SPLAT2_PS(v, 1);
+    v_float32x8 v26 = OPENCV_HAL_AVX_SPLAT2_PS(v, 2);
+    v_float32x8 v37 = OPENCV_HAL_AVX_SPLAT2_PS(v, 3);
+    return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, v_mul(v37, m3))));
+}
+
+inline v_float32x8 v_matmuladd(const v_float32x8& v, const v_float32x8& m0,
+                               const v_float32x8& m1, const v_float32x8& m2,
+                               const v_float32x8& a)
+{
+    v_float32x8 v04 = OPENCV_HAL_AVX_SPLAT2_PS(v, 0);
+    v_float32x8 v15 = OPENCV_HAL_AVX_SPLAT2_PS(v, 1);
+    v_float32x8 v26 = OPENCV_HAL_AVX_SPLAT2_PS(v, 2);
+    return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, a)));
+}
+
+#define OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(_Tpvec, suffix, cast_from, cast_to)    \
+    inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1,              \
+                               const _Tpvec& a2, const _Tpvec& a3,              \
+                               _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3)  \
+    {                                                                           \
+        __m256i t0 = cast_from(_mm256_unpacklo_##suffix(a0.val, a1.val));       \
+        __m256i t1 = cast_from(_mm256_unpacklo_##suffix(a2.val, a3.val));       \
+        __m256i t2 = cast_from(_mm256_unpackhi_##suffix(a0.val, a1.val));       \
+        __m256i t3 = cast_from(_mm256_unpackhi_##suffix(a2.val, a3.val));       \
+        b0.val = cast_to(_mm256_unpacklo_epi64(t0, t1));                        \
+        b1.val = cast_to(_mm256_unpackhi_epi64(t0, t1));                        \
+        b2.val = cast_to(_mm256_unpacklo_epi64(t2, t3));                        \
+        b3.val = cast_to(_mm256_unpackhi_epi64(t2, t3));                        \
+    }
+
+OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(v_uint32x8,  epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(v_int32x8,   epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_AVX_TRANSPOSE4x4(v_float32x8, ps, _mm256_castps_si256, _mm256_castsi256_ps)
+
+//////////////// Value reordering ///////////////
+
+/* Expand */
+#define OPENCV_HAL_IMPL_AVX_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin)    \
+    inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
+    {                                                               \
+        b0.val = intrin(_v256_extract_low(a.val));                  \
+        b1.val = intrin(_v256_extract_high(a.val));                 \
+    }                                                               \
+    inline _Tpwvec v_expand_low(const _Tpvec& a)                    \
+    { return _Tpwvec(intrin(_v256_extract_low(a.val))); }           \
+    inline _Tpwvec v_expand_high(const _Tpvec& a)                   \
+    { return _Tpwvec(intrin(_v256_extract_high(a.val))); }          \
+    inline _Tpwvec v256_load_expand(const _Tp* ptr)                 \
+    {                                                               \
+        __m128i a = _mm_loadu_si128((const __m128i*)ptr);           \
+        return _Tpwvec(intrin(a));                                  \
+    }
+
+OPENCV_HAL_IMPL_AVX_EXPAND(v_uint8x32,  v_uint16x16, uchar,    _mm256_cvtepu8_epi16)
+OPENCV_HAL_IMPL_AVX_EXPAND(v_int8x32,   v_int16x16,  schar,    _mm256_cvtepi8_epi16)
+OPENCV_HAL_IMPL_AVX_EXPAND(v_uint16x16, v_uint32x8,  ushort,   _mm256_cvtepu16_epi32)
+OPENCV_HAL_IMPL_AVX_EXPAND(v_int16x16,  v_int32x8,   short,    _mm256_cvtepi16_epi32)
+OPENCV_HAL_IMPL_AVX_EXPAND(v_uint32x8,  v_uint64x4,  unsigned, _mm256_cvtepu32_epi64)
+OPENCV_HAL_IMPL_AVX_EXPAND(v_int32x8,   v_int64x4,   int,      _mm256_cvtepi32_epi64)
+
+#define OPENCV_HAL_IMPL_AVX_EXPAND_Q(_Tpvec, _Tp, intrin)   \
+    inline _Tpvec v256_load_expand_q(const _Tp* ptr)        \
+    {                                                       \
+        __m128i a = _mm_loadl_epi64((const __m128i*)ptr);   \
+        return _Tpvec(intrin(a));                           \
+    }
+
+OPENCV_HAL_IMPL_AVX_EXPAND_Q(v_uint32x8, uchar, _mm256_cvtepu8_epi32)
+OPENCV_HAL_IMPL_AVX_EXPAND_Q(v_int32x8,  schar, _mm256_cvtepi8_epi32)
+
+/* pack */
+// 16
+inline v_int8x32 v_pack(const v_int16x16& a, const v_int16x16& b)
+{ return v_int8x32(_v256_shuffle_odd_64(_mm256_packs_epi16(a.val, b.val))); }
+
+inline v_uint8x32 v_pack(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i t = _mm256_set1_epi16(255);
+    __m256i a1 = _mm256_min_epu16(a.val, t);
+    __m256i b1 = _mm256_min_epu16(b.val, t);
+    return v_uint8x32(_v256_shuffle_odd_64(_mm256_packus_epi16(a1, b1)));
+}
+
+inline v_uint8x32 v_pack_u(const v_int16x16& a, const v_int16x16& b)
+{
+    return v_uint8x32(_v256_shuffle_odd_64(_mm256_packus_epi16(a.val, b.val)));
+}
+
+inline void v_pack_store(schar* ptr, const v_int16x16& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(uchar* ptr, const v_uint16x16& a)
+{
+    const __m256i m = _mm256_set1_epi16(255);
+    __m256i am = _mm256_min_epu16(a.val, m);
+            am =  _v256_shuffle_odd_64(_mm256_packus_epi16(am, am));
+    v_store_low(ptr, v_uint8x32(am));
+}
+
+inline void v_pack_u_store(uchar* ptr, const v_int16x16& a)
+{ v_store_low(ptr, v_pack_u(a, a)); }
+
+template<int n> inline
+v_uint8x32 v_rshr_pack(const v_uint16x16& a, const v_uint16x16& b)
+{
+    // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers.
+    v_uint16x16 delta = v256_setall_u16((short)(1 << (n-1)));
+    return v_pack_u(v_reinterpret_as_s16(v_shr(v_add(a, delta), n)),
+                    v_reinterpret_as_s16(v_shr(v_add(b, delta), n)));
+}
+
+template<int n> inline
+void v_rshr_pack_store(uchar* ptr, const v_uint16x16& a)
+{
+    v_uint16x16 delta = v256_setall_u16((short)(1 << (n-1)));
+    v_pack_u_store(ptr, v_reinterpret_as_s16(v_shr(v_add(a, delta), n)));
+}
+
+template<int n> inline
+v_uint8x32 v_rshr_pack_u(const v_int16x16& a, const v_int16x16& b)
+{
+    v_int16x16 delta = v256_setall_s16((short)(1 << (n-1)));
+    return v_pack_u(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_u_store(uchar* ptr, const v_int16x16& a)
+{
+    v_int16x16 delta = v256_setall_s16((short)(1 << (n-1)));
+    v_pack_u_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+template<int n> inline
+v_int8x32 v_rshr_pack(const v_int16x16& a, const v_int16x16& b)
+{
+    v_int16x16 delta = v256_setall_s16((short)(1 << (n-1)));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(schar* ptr, const v_int16x16& a)
+{
+    v_int16x16 delta = v256_setall_s16((short)(1 << (n-1)));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+// 32
+inline v_int16x16 v_pack(const v_int32x8& a, const v_int32x8& b)
+{ return v_int16x16(_v256_shuffle_odd_64(_mm256_packs_epi32(a.val, b.val))); }
+
+inline v_uint16x16 v_pack(const v_uint32x8& a, const v_uint32x8& b)
+{ return v_uint16x16(_v256_shuffle_odd_64(_v256_packs_epu32(a.val, b.val))); }
+
+inline v_uint16x16 v_pack_u(const v_int32x8& a, const v_int32x8& b)
+{ return v_uint16x16(_v256_shuffle_odd_64(_mm256_packus_epi32(a.val, b.val))); }
+
+inline void v_pack_store(short* ptr, const v_int32x8& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(ushort* ptr, const v_uint32x8& a)
+{
+    const __m256i m = _mm256_set1_epi32(65535);
+    __m256i am = _mm256_min_epu32(a.val, m);
+            am = _v256_shuffle_odd_64(_mm256_packus_epi32(am, am));
+    v_store_low(ptr, v_uint16x16(am));
+}
+
+inline void v_pack_u_store(ushort* ptr, const v_int32x8& a)
+{ v_store_low(ptr, v_pack_u(a, a)); }
+
+
+template<int n> inline
+v_uint16x16 v_rshr_pack(const v_uint32x8& a, const v_uint32x8& b)
+{
+    // we assume that n > 0, and so the shifted 32-bit values can be treated as signed numbers.
+    v_uint32x8 delta = v256_setall_u32(1 << (n-1));
+    return v_pack_u(v_reinterpret_as_s32(v_shr(v_add(a, delta), n)),
+                    v_reinterpret_as_s32(v_shr(v_add(b, delta), n)));
+}
+
+template<int n> inline
+void v_rshr_pack_store(ushort* ptr, const v_uint32x8& a)
+{
+    v_uint32x8 delta = v256_setall_u32(1 << (n-1));
+    v_pack_u_store(ptr, v_reinterpret_as_s32(v_shr(v_add(a, delta), n)));
+}
+
+template<int n> inline
+v_uint16x16 v_rshr_pack_u(const v_int32x8& a, const v_int32x8& b)
+{
+    v_int32x8 delta = v256_setall_s32(1 << (n-1));
+    return v_pack_u(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_u_store(ushort* ptr, const v_int32x8& a)
+{
+    v_int32x8 delta = v256_setall_s32(1 << (n-1));
+    v_pack_u_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+template<int n> inline
+v_int16x16 v_rshr_pack(const v_int32x8& a, const v_int32x8& b)
+{
+    v_int32x8 delta = v256_setall_s32(1 << (n-1));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(short* ptr, const v_int32x8& a)
+{
+    v_int32x8 delta = v256_setall_s32(1 << (n-1));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+// 64
+// Non-saturating pack
+inline v_uint32x8 v_pack(const v_uint64x4& a, const v_uint64x4& b)
+{
+    __m256i a0 = _mm256_shuffle_epi32(a.val, _MM_SHUFFLE(0, 0, 2, 0));
+    __m256i b0 = _mm256_shuffle_epi32(b.val, _MM_SHUFFLE(0, 0, 2, 0));
+    __m256i ab = _mm256_unpacklo_epi64(a0, b0); // a0, a1, b0, b1, a2, a3, b2, b3
+    return v_uint32x8(_v256_shuffle_odd_64(ab));
+}
+
+inline v_int32x8 v_pack(const v_int64x4& a, const v_int64x4& b)
+{ return v_reinterpret_as_s32(v_pack(v_reinterpret_as_u64(a), v_reinterpret_as_u64(b))); }
+
+inline void v_pack_store(unsigned* ptr, const v_uint64x4& a)
+{
+    __m256i a0 = _mm256_shuffle_epi32(a.val, _MM_SHUFFLE(0, 0, 2, 0));
+    v_store_low(ptr, v_uint32x8(_v256_shuffle_odd_64(a0)));
+}
+
+inline void v_pack_store(int* ptr, const v_int64x4& b)
+{ v_pack_store((unsigned*)ptr, v_reinterpret_as_u64(b)); }
+
+template<int n> inline
+v_uint32x8 v_rshr_pack(const v_uint64x4& a, const v_uint64x4& b)
+{
+    v_uint64x4 delta = v256_setall_u64((uint64)1 << (n-1));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(unsigned* ptr, const v_uint64x4& a)
+{
+    v_uint64x4 delta = v256_setall_u64((uint64)1 << (n-1));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+template<int n> inline
+v_int32x8 v_rshr_pack(const v_int64x4& a, const v_int64x4& b)
+{
+    v_int64x4 delta = v256_setall_s64((int64)1 << (n-1));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(int* ptr, const v_int64x4& a)
+{
+    v_int64x4 delta = v256_setall_s64((int64)1 << (n-1));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+// pack boolean
+inline v_uint8x32 v_pack_b(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i ab = _mm256_packs_epi16(a.val, b.val);
+    return v_uint8x32(_v256_shuffle_odd_64(ab));
+}
+
+inline v_uint8x32 v_pack_b(const v_uint32x8& a, const v_uint32x8& b,
+                           const v_uint32x8& c, const v_uint32x8& d)
+{
+    __m256i ab = _mm256_packs_epi32(a.val, b.val);
+    __m256i cd = _mm256_packs_epi32(c.val, d.val);
+
+    __m256i abcd = _v256_shuffle_odd_64(_mm256_packs_epi16(ab, cd));
+    return v_uint8x32(_mm256_shuffle_epi32(abcd, _MM_SHUFFLE(3, 1, 2, 0)));
+}
+
+inline v_uint8x32 v_pack_b(const v_uint64x4& a, const v_uint64x4& b, const v_uint64x4& c,
+                           const v_uint64x4& d, const v_uint64x4& e, const v_uint64x4& f,
+                           const v_uint64x4& g, const v_uint64x4& h)
+{
+    __m256i ab = _mm256_packs_epi32(a.val, b.val);
+    __m256i cd = _mm256_packs_epi32(c.val, d.val);
+    __m256i ef = _mm256_packs_epi32(e.val, f.val);
+    __m256i gh = _mm256_packs_epi32(g.val, h.val);
+
+    __m256i abcd = _mm256_packs_epi32(ab, cd);
+    __m256i efgh = _mm256_packs_epi32(ef, gh);
+    __m256i pkall = _v256_shuffle_odd_64(_mm256_packs_epi16(abcd, efgh));
+
+    __m256i rev = _mm256_alignr_epi8(pkall, pkall, 8);
+    return v_uint8x32(_mm256_unpacklo_epi16(pkall, rev));
+}
+
+/* Recombine */
+// its up there with load and store operations
+
+/* Extract */
+#define OPENCV_HAL_IMPL_AVX_EXTRACT(_Tpvec)                    \
+    template<int s>                                            \
+    inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b)  \
+    { return v_rotate_right<s>(a, b); }
+
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint8x32)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_int8x32)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint16x16)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_int16x16)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint32x8)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_int32x8)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_uint64x4)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_int64x4)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_float32x8)
+OPENCV_HAL_IMPL_AVX_EXTRACT(v_float64x4)
+
+template<int i>
+inline uchar v_extract_n(v_uint8x32 a)
+{
+    return (uchar)_v256_extract_epi8<i>(a.val);
+}
+
+template<int i>
+inline schar v_extract_n(v_int8x32 a)
+{
+    return (schar)v_extract_n<i>(v_reinterpret_as_u8(a));
+}
+
+template<int i>
+inline ushort v_extract_n(v_uint16x16 a)
+{
+    return (ushort)_v256_extract_epi16<i>(a.val);
+}
+
+template<int i>
+inline short v_extract_n(v_int16x16 a)
+{
+    return (short)v_extract_n<i>(v_reinterpret_as_u16(a));
+}
+
+template<int i>
+inline uint v_extract_n(v_uint32x8 a)
+{
+    return (uint)_v256_extract_epi32<i>(a.val);
+}
+
+template<int i>
+inline int v_extract_n(v_int32x8 a)
+{
+    return (int)v_extract_n<i>(v_reinterpret_as_u32(a));
+}
+
+template<int i>
+inline uint64 v_extract_n(v_uint64x4 a)
+{
+    return (uint64)_v256_extract_epi64<i>(a.val);
+}
+
+template<int i>
+inline int64 v_extract_n(v_int64x4 v)
+{
+    return (int64)v_extract_n<i>(v_reinterpret_as_u64(v));
+}
+
+template<int i>
+inline float v_extract_n(v_float32x8 v)
+{
+    union { uint iv; float fv; } d;
+    d.iv = v_extract_n<i>(v_reinterpret_as_u32(v));
+    return d.fv;
+}
+
+template<int i>
+inline double v_extract_n(v_float64x4 v)
+{
+    union { uint64 iv; double dv; } d;
+    d.iv = v_extract_n<i>(v_reinterpret_as_u64(v));
+    return d.dv;
+}
+
+template<int i>
+inline v_uint32x8 v_broadcast_element(v_uint32x8 a)
+{
+    static const __m256i perm = _mm256_set1_epi32((char)i);
+    return v_uint32x8(_mm256_permutevar8x32_epi32(a.val, perm));
+}
+
+template<int i>
+inline v_int32x8 v_broadcast_element(const v_int32x8 &a)
+{ return v_reinterpret_as_s32(v_broadcast_element<i>(v_reinterpret_as_u32(a))); }
+
+template<int i>
+inline v_float32x8 v_broadcast_element(const v_float32x8 &a)
+{ return v_reinterpret_as_f32(v_broadcast_element<i>(v_reinterpret_as_u32(a))); }
+
+
+///////////////////// load deinterleave /////////////////////////////
+
+inline void v_load_deinterleave( const uchar* ptr, v_uint8x32& a, v_uint8x32& b )
+{
+    __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 32));
+
+    const __m256i sh = _mm256_setr_epi8(0, 2, 4, 6, 8, 10, 12, 14, 1, 3, 5, 7, 9, 11, 13, 15,
+                                               0, 2, 4, 6, 8, 10, 12, 14, 1, 3, 5, 7, 9, 11, 13, 15);
+    __m256i p0 = _mm256_shuffle_epi8(ab0, sh);
+    __m256i p1 = _mm256_shuffle_epi8(ab1, sh);
+    __m256i pl = _mm256_permute2x128_si256(p0, p1, 0 + 2*16);
+    __m256i ph = _mm256_permute2x128_si256(p0, p1, 1 + 3*16);
+    __m256i a0 = _mm256_unpacklo_epi64(pl, ph);
+    __m256i b0 = _mm256_unpackhi_epi64(pl, ph);
+    a = v_uint8x32(a0);
+    b = v_uint8x32(b0);
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b )
+{
+    __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 16));
+
+    const __m256i sh = _mm256_setr_epi8(0, 1, 4, 5, 8, 9, 12, 13, 2, 3, 6, 7, 10, 11, 14, 15,
+                                               0, 1, 4, 5, 8, 9, 12, 13, 2, 3, 6, 7, 10, 11, 14, 15);
+    __m256i p0 = _mm256_shuffle_epi8(ab0, sh);
+    __m256i p1 = _mm256_shuffle_epi8(ab1, sh);
+    __m256i pl = _mm256_permute2x128_si256(p0, p1, 0 + 2*16);
+    __m256i ph = _mm256_permute2x128_si256(p0, p1, 1 + 3*16);
+    __m256i a0 = _mm256_unpacklo_epi64(pl, ph);
+    __m256i b0 = _mm256_unpackhi_epi64(pl, ph);
+    a = v_uint16x16(a0);
+    b = v_uint16x16(b0);
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b )
+{
+    __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 8));
+
+    enum { sh = 0+2*4+1*16+3*64 };
+    __m256i p0 = _mm256_shuffle_epi32(ab0, sh);
+    __m256i p1 = _mm256_shuffle_epi32(ab1, sh);
+    __m256i pl = _mm256_permute2x128_si256(p0, p1, 0 + 2*16);
+    __m256i ph = _mm256_permute2x128_si256(p0, p1, 1 + 3*16);
+    __m256i a0 = _mm256_unpacklo_epi64(pl, ph);
+    __m256i b0 = _mm256_unpackhi_epi64(pl, ph);
+    a = v_uint32x8(a0);
+    b = v_uint32x8(b0);
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b )
+{
+    __m256i ab0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i ab1 = _mm256_loadu_si256((const __m256i*)(ptr + 4));
+
+    __m256i pl = _mm256_permute2x128_si256(ab0, ab1, 0 + 2*16);
+    __m256i ph = _mm256_permute2x128_si256(ab0, ab1, 1 + 3*16);
+    __m256i a0 = _mm256_unpacklo_epi64(pl, ph);
+    __m256i b0 = _mm256_unpackhi_epi64(pl, ph);
+    a = v_uint64x4(a0);
+    b = v_uint64x4(b0);
+}
+
+inline void v_load_deinterleave( const uchar* ptr, v_uint8x32& a, v_uint8x32& b, v_uint8x32& c )
+{
+    __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 32));
+    __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 64));
+
+    __m256i s02_low = _mm256_permute2x128_si256(bgr0, bgr2, 0 + 2*16);
+    __m256i s02_high = _mm256_permute2x128_si256(bgr0, bgr2, 1 + 3*16);
+
+    const __m256i m0 = _mm256_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0,
+                                               0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0);
+    const __m256i m1 = _mm256_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0,
+                                               -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1);
+
+    __m256i b0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_low, s02_high, m0), bgr1, m1);
+    __m256i g0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_high, s02_low, m1), bgr1, m0);
+    __m256i r0 = _mm256_blendv_epi8(_mm256_blendv_epi8(bgr1, s02_low, m0), s02_high, m1);
+
+    const __m256i
+    sh_b = _mm256_setr_epi8(0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13,
+                            0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13),
+    sh_g = _mm256_setr_epi8(1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14,
+                            1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14),
+    sh_r = _mm256_setr_epi8(2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15,
+                            2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15);
+    b0 = _mm256_shuffle_epi8(b0, sh_b);
+    g0 = _mm256_shuffle_epi8(g0, sh_g);
+    r0 = _mm256_shuffle_epi8(r0, sh_r);
+
+    a = v_uint8x32(b0);
+    b = v_uint8x32(g0);
+    c = v_uint8x32(r0);
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b, v_uint16x16& c )
+{
+    __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 16));
+    __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 32));
+
+    __m256i s02_low = _mm256_permute2x128_si256(bgr0, bgr2, 0 + 2*16);
+    __m256i s02_high = _mm256_permute2x128_si256(bgr0, bgr2, 1 + 3*16);
+
+    const __m256i m0 = _mm256_setr_epi8(0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1,
+                                               0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0);
+    const __m256i m1 = _mm256_setr_epi8(0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0,
+                                               -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0);
+    __m256i b0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_low, s02_high, m0), bgr1, m1);
+    __m256i g0 = _mm256_blendv_epi8(_mm256_blendv_epi8(bgr1, s02_low, m0), s02_high, m1);
+    __m256i r0 = _mm256_blendv_epi8(_mm256_blendv_epi8(s02_high, s02_low, m1), bgr1, m0);
+    const __m256i sh_b = _mm256_setr_epi8(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11,
+                                                 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11);
+    const __m256i sh_g = _mm256_setr_epi8(2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13,
+                                                 2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13);
+    const __m256i sh_r = _mm256_setr_epi8(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15,
+                                                 4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15);
+    b0 = _mm256_shuffle_epi8(b0, sh_b);
+    g0 = _mm256_shuffle_epi8(g0, sh_g);
+    r0 = _mm256_shuffle_epi8(r0, sh_r);
+
+    a = v_uint16x16(b0);
+    b = v_uint16x16(g0);
+    c = v_uint16x16(r0);
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b, v_uint32x8& c )
+{
+    __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 8));
+    __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 16));
+
+    __m256i s02_low = _mm256_permute2x128_si256(bgr0, bgr2, 0 + 2*16);
+    __m256i s02_high = _mm256_permute2x128_si256(bgr0, bgr2, 1 + 3*16);
+
+    __m256i b0 = _mm256_blend_epi32(_mm256_blend_epi32(s02_low, s02_high, 0x24), bgr1, 0x92);
+    __m256i g0 = _mm256_blend_epi32(_mm256_blend_epi32(s02_high, s02_low, 0x92), bgr1, 0x24);
+    __m256i r0 = _mm256_blend_epi32(_mm256_blend_epi32(bgr1, s02_low, 0x24), s02_high, 0x92);
+
+    b0 = _mm256_shuffle_epi32(b0, 0x6c);
+    g0 = _mm256_shuffle_epi32(g0, 0xb1);
+    r0 = _mm256_shuffle_epi32(r0, 0xc6);
+
+    a = v_uint32x8(b0);
+    b = v_uint32x8(g0);
+    c = v_uint32x8(r0);
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b, v_uint64x4& c )
+{
+    __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 4));
+    __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 8));
+
+    __m256i s01 = _mm256_blend_epi32(bgr0, bgr1, 0xf0);
+    __m256i s12 = _mm256_blend_epi32(bgr1, bgr2, 0xf0);
+    __m256i s20r = _mm256_permute4x64_epi64(_mm256_blend_epi32(bgr2, bgr0, 0xf0), 0x1b);
+    __m256i b0 = _mm256_unpacklo_epi64(s01, s20r);
+    __m256i g0 = _mm256_alignr_epi8(s12, s01, 8);
+    __m256i r0 = _mm256_unpackhi_epi64(s20r, s12);
+
+    a = v_uint64x4(b0);
+    b = v_uint64x4(g0);
+    c = v_uint64x4(r0);
+}
+
+inline void v_load_deinterleave( const uchar* ptr, v_uint8x32& a, v_uint8x32& b, v_uint8x32& c, v_uint8x32& d )
+{
+    __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 32));
+    __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 64));
+    __m256i bgr3 = _mm256_loadu_si256((const __m256i*)(ptr + 96));
+    const __m256i sh = _mm256_setr_epi8(0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15,
+                                               0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15);
+
+    __m256i p0 = _mm256_shuffle_epi8(bgr0, sh);
+    __m256i p1 = _mm256_shuffle_epi8(bgr1, sh);
+    __m256i p2 = _mm256_shuffle_epi8(bgr2, sh);
+    __m256i p3 = _mm256_shuffle_epi8(bgr3, sh);
+
+    __m256i p01l = _mm256_unpacklo_epi32(p0, p1);
+    __m256i p01h = _mm256_unpackhi_epi32(p0, p1);
+    __m256i p23l = _mm256_unpacklo_epi32(p2, p3);
+    __m256i p23h = _mm256_unpackhi_epi32(p2, p3);
+
+    __m256i pll = _mm256_permute2x128_si256(p01l, p23l, 0 + 2*16);
+    __m256i plh = _mm256_permute2x128_si256(p01l, p23l, 1 + 3*16);
+    __m256i phl = _mm256_permute2x128_si256(p01h, p23h, 0 + 2*16);
+    __m256i phh = _mm256_permute2x128_si256(p01h, p23h, 1 + 3*16);
+
+    __m256i b0 = _mm256_unpacklo_epi32(pll, plh);
+    __m256i g0 = _mm256_unpackhi_epi32(pll, plh);
+    __m256i r0 = _mm256_unpacklo_epi32(phl, phh);
+    __m256i a0 = _mm256_unpackhi_epi32(phl, phh);
+
+    a = v_uint8x32(b0);
+    b = v_uint8x32(g0);
+    c = v_uint8x32(r0);
+    d = v_uint8x32(a0);
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b, v_uint16x16& c, v_uint16x16& d )
+{
+    __m256i bgr0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i bgr1 = _mm256_loadu_si256((const __m256i*)(ptr + 16));
+    __m256i bgr2 = _mm256_loadu_si256((const __m256i*)(ptr + 32));
+    __m256i bgr3 = _mm256_loadu_si256((const __m256i*)(ptr + 48));
+    const __m256i sh = _mm256_setr_epi8(0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15,
+                                               0, 1, 8, 9, 2, 3, 10, 11, 4, 5, 12, 13, 6, 7, 14, 15);
+    __m256i p0 = _mm256_shuffle_epi8(bgr0, sh);
+    __m256i p1 = _mm256_shuffle_epi8(bgr1, sh);
+    __m256i p2 = _mm256_shuffle_epi8(bgr2, sh);
+    __m256i p3 = _mm256_shuffle_epi8(bgr3, sh);
+
+    __m256i p01l = _mm256_unpacklo_epi32(p0, p1);
+    __m256i p01h = _mm256_unpackhi_epi32(p0, p1);
+    __m256i p23l = _mm256_unpacklo_epi32(p2, p3);
+    __m256i p23h = _mm256_unpackhi_epi32(p2, p3);
+
+    __m256i pll = _mm256_permute2x128_si256(p01l, p23l, 0 + 2*16);
+    __m256i plh = _mm256_permute2x128_si256(p01l, p23l, 1 + 3*16);
+    __m256i phl = _mm256_permute2x128_si256(p01h, p23h, 0 + 2*16);
+    __m256i phh = _mm256_permute2x128_si256(p01h, p23h, 1 + 3*16);
+
+    __m256i b0 = _mm256_unpacklo_epi32(pll, plh);
+    __m256i g0 = _mm256_unpackhi_epi32(pll, plh);
+    __m256i r0 = _mm256_unpacklo_epi32(phl, phh);
+    __m256i a0 = _mm256_unpackhi_epi32(phl, phh);
+
+    a = v_uint16x16(b0);
+    b = v_uint16x16(g0);
+    c = v_uint16x16(r0);
+    d = v_uint16x16(a0);
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b, v_uint32x8& c, v_uint32x8& d )
+{
+    __m256i p0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i p1 = _mm256_loadu_si256((const __m256i*)(ptr + 8));
+    __m256i p2 = _mm256_loadu_si256((const __m256i*)(ptr + 16));
+    __m256i p3 = _mm256_loadu_si256((const __m256i*)(ptr + 24));
+
+    __m256i p01l = _mm256_unpacklo_epi32(p0, p1);
+    __m256i p01h = _mm256_unpackhi_epi32(p0, p1);
+    __m256i p23l = _mm256_unpacklo_epi32(p2, p3);
+    __m256i p23h = _mm256_unpackhi_epi32(p2, p3);
+
+    __m256i pll = _mm256_permute2x128_si256(p01l, p23l, 0 + 2*16);
+    __m256i plh = _mm256_permute2x128_si256(p01l, p23l, 1 + 3*16);
+    __m256i phl = _mm256_permute2x128_si256(p01h, p23h, 0 + 2*16);
+    __m256i phh = _mm256_permute2x128_si256(p01h, p23h, 1 + 3*16);
+
+    __m256i b0 = _mm256_unpacklo_epi32(pll, plh);
+    __m256i g0 = _mm256_unpackhi_epi32(pll, plh);
+    __m256i r0 = _mm256_unpacklo_epi32(phl, phh);
+    __m256i a0 = _mm256_unpackhi_epi32(phl, phh);
+
+    a = v_uint32x8(b0);
+    b = v_uint32x8(g0);
+    c = v_uint32x8(r0);
+    d = v_uint32x8(a0);
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b, v_uint64x4& c, v_uint64x4& d )
+{
+    __m256i bgra0 = _mm256_loadu_si256((const __m256i*)ptr);
+    __m256i bgra1 = _mm256_loadu_si256((const __m256i*)(ptr + 4));
+    __m256i bgra2 = _mm256_loadu_si256((const __m256i*)(ptr + 8));
+    __m256i bgra3 = _mm256_loadu_si256((const __m256i*)(ptr + 12));
+
+    __m256i l02 = _mm256_permute2x128_si256(bgra0, bgra2, 0 + 2*16);
+    __m256i h02 = _mm256_permute2x128_si256(bgra0, bgra2, 1 + 3*16);
+    __m256i l13 = _mm256_permute2x128_si256(bgra1, bgra3, 0 + 2*16);
+    __m256i h13 = _mm256_permute2x128_si256(bgra1, bgra3, 1 + 3*16);
+
+    __m256i b0 = _mm256_unpacklo_epi64(l02, l13);
+    __m256i g0 = _mm256_unpackhi_epi64(l02, l13);
+    __m256i r0 = _mm256_unpacklo_epi64(h02, h13);
+    __m256i a0 = _mm256_unpackhi_epi64(h02, h13);
+
+    a = v_uint64x4(b0);
+    b = v_uint64x4(g0);
+    c = v_uint64x4(r0);
+    d = v_uint64x4(a0);
+}
+
+///////////////////////////// store interleave /////////////////////////////////////
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x32& x, const v_uint8x32& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = _mm256_unpacklo_epi8(x.val, y.val);
+    __m256i xy_h = _mm256_unpackhi_epi8(x.val, y.val);
+
+    __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16);
+    __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, xy0);
+        _mm256_stream_si256((__m256i*)(ptr + 32), xy1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, xy0);
+        _mm256_store_si256((__m256i*)(ptr + 32), xy1);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, xy0);
+        _mm256_storeu_si256((__m256i*)(ptr + 32), xy1);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x16& x, const v_uint16x16& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = _mm256_unpacklo_epi16(x.val, y.val);
+    __m256i xy_h = _mm256_unpackhi_epi16(x.val, y.val);
+
+    __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16);
+    __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, xy0);
+        _mm256_stream_si256((__m256i*)(ptr + 16), xy1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, xy0);
+        _mm256_store_si256((__m256i*)(ptr + 16), xy1);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, xy0);
+        _mm256_storeu_si256((__m256i*)(ptr + 16), xy1);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x8& x, const v_uint32x8& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = _mm256_unpacklo_epi32(x.val, y.val);
+    __m256i xy_h = _mm256_unpackhi_epi32(x.val, y.val);
+
+    __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16);
+    __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, xy0);
+        _mm256_stream_si256((__m256i*)(ptr + 8), xy1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, xy0);
+        _mm256_store_si256((__m256i*)(ptr + 8), xy1);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, xy0);
+        _mm256_storeu_si256((__m256i*)(ptr + 8), xy1);
+    }
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x4& x, const v_uint64x4& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = _mm256_unpacklo_epi64(x.val, y.val);
+    __m256i xy_h = _mm256_unpackhi_epi64(x.val, y.val);
+
+    __m256i xy0 = _mm256_permute2x128_si256(xy_l, xy_h, 0 + 2*16);
+    __m256i xy1 = _mm256_permute2x128_si256(xy_l, xy_h, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, xy0);
+        _mm256_stream_si256((__m256i*)(ptr + 4), xy1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, xy0);
+        _mm256_store_si256((__m256i*)(ptr + 4), xy1);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, xy0);
+        _mm256_storeu_si256((__m256i*)(ptr + 4), xy1);
+    }
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x32& a, const v_uint8x32& b, const v_uint8x32& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    const __m256i sh_b = _mm256_setr_epi8(
+            0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5,
+            0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5);
+    const __m256i sh_g = _mm256_setr_epi8(
+            5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10,
+            5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10);
+    const __m256i sh_r = _mm256_setr_epi8(
+            10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15,
+            10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15);
+
+    __m256i b0 = _mm256_shuffle_epi8(a.val, sh_b);
+    __m256i g0 = _mm256_shuffle_epi8(b.val, sh_g);
+    __m256i r0 = _mm256_shuffle_epi8(c.val, sh_r);
+
+    const __m256i m0 = _mm256_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0,
+                                               0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0);
+    const __m256i m1 = _mm256_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0,
+                                               0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0);
+
+    __m256i p0 = _mm256_blendv_epi8(_mm256_blendv_epi8(b0, g0, m0), r0, m1);
+    __m256i p1 = _mm256_blendv_epi8(_mm256_blendv_epi8(g0, r0, m0), b0, m1);
+    __m256i p2 = _mm256_blendv_epi8(_mm256_blendv_epi8(r0, b0, m0), g0, m1);
+
+    __m256i bgr0 = _mm256_permute2x128_si256(p0, p1, 0 + 2*16);
+    __m256i bgr1 = _mm256_permute2x128_si256(p2, p0, 0 + 3*16);
+    __m256i bgr2 = _mm256_permute2x128_si256(p1, p2, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgr0);
+        _mm256_stream_si256((__m256i*)(ptr + 32), bgr1);
+        _mm256_stream_si256((__m256i*)(ptr + 64), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgr0);
+        _mm256_store_si256((__m256i*)(ptr + 32), bgr1);
+        _mm256_store_si256((__m256i*)(ptr + 64), bgr2);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgr0);
+        _mm256_storeu_si256((__m256i*)(ptr + 32), bgr1);
+        _mm256_storeu_si256((__m256i*)(ptr + 64), bgr2);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x16& a, const v_uint16x16& b, const v_uint16x16& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    const __m256i sh_b = _mm256_setr_epi8(
+         0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11,
+         0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11);
+    const __m256i sh_g = _mm256_setr_epi8(
+         10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5,
+         10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5);
+    const __m256i sh_r = _mm256_setr_epi8(
+         4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15,
+         4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15);
+
+    __m256i b0 = _mm256_shuffle_epi8(a.val, sh_b);
+    __m256i g0 = _mm256_shuffle_epi8(b.val, sh_g);
+    __m256i r0 = _mm256_shuffle_epi8(c.val, sh_r);
+
+    const __m256i m0 = _mm256_setr_epi8(0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1,
+                                               0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0);
+    const __m256i m1 = _mm256_setr_epi8(0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0,
+                                               -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0);
+
+    __m256i p0 = _mm256_blendv_epi8(_mm256_blendv_epi8(b0, g0, m0), r0, m1);
+    __m256i p1 = _mm256_blendv_epi8(_mm256_blendv_epi8(g0, r0, m0), b0, m1);
+    __m256i p2 = _mm256_blendv_epi8(_mm256_blendv_epi8(r0, b0, m0), g0, m1);
+
+    __m256i bgr0 = _mm256_permute2x128_si256(p0, p2, 0 + 2*16);
+    //__m256i bgr1 = p1;
+    __m256i bgr2 = _mm256_permute2x128_si256(p0, p2, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgr0);
+        _mm256_stream_si256((__m256i*)(ptr + 16), p1);
+        _mm256_stream_si256((__m256i*)(ptr + 32), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgr0);
+        _mm256_store_si256((__m256i*)(ptr + 16), p1);
+        _mm256_store_si256((__m256i*)(ptr + 32), bgr2);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgr0);
+        _mm256_storeu_si256((__m256i*)(ptr + 16), p1);
+        _mm256_storeu_si256((__m256i*)(ptr + 32), bgr2);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x8& a, const v_uint32x8& b, const v_uint32x8& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i b0 = _mm256_shuffle_epi32(a.val, 0x6c);
+    __m256i g0 = _mm256_shuffle_epi32(b.val, 0xb1);
+    __m256i r0 = _mm256_shuffle_epi32(c.val, 0xc6);
+
+    __m256i p0 = _mm256_blend_epi32(_mm256_blend_epi32(b0, g0, 0x92), r0, 0x24);
+    __m256i p1 = _mm256_blend_epi32(_mm256_blend_epi32(g0, r0, 0x92), b0, 0x24);
+    __m256i p2 = _mm256_blend_epi32(_mm256_blend_epi32(r0, b0, 0x92), g0, 0x24);
+
+    __m256i bgr0 = _mm256_permute2x128_si256(p0, p1, 0 + 2*16);
+    //__m256i bgr1 = p2;
+    __m256i bgr2 = _mm256_permute2x128_si256(p0, p1, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgr0);
+        _mm256_stream_si256((__m256i*)(ptr + 8), p2);
+        _mm256_stream_si256((__m256i*)(ptr + 16), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgr0);
+        _mm256_store_si256((__m256i*)(ptr + 8), p2);
+        _mm256_store_si256((__m256i*)(ptr + 16), bgr2);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgr0);
+        _mm256_storeu_si256((__m256i*)(ptr + 8), p2);
+        _mm256_storeu_si256((__m256i*)(ptr + 16), bgr2);
+    }
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x4& a, const v_uint64x4& b, const v_uint64x4& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i s01 = _mm256_unpacklo_epi64(a.val, b.val);
+    __m256i s12 = _mm256_unpackhi_epi64(b.val, c.val);
+    __m256i s20 = _mm256_blend_epi32(c.val, a.val, 0xcc);
+
+    __m256i bgr0 = _mm256_permute2x128_si256(s01, s20, 0 + 2*16);
+    __m256i bgr1 = _mm256_blend_epi32(s01, s12, 0x0f);
+    __m256i bgr2 = _mm256_permute2x128_si256(s20, s12, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgr0);
+        _mm256_stream_si256((__m256i*)(ptr + 4), bgr1);
+        _mm256_stream_si256((__m256i*)(ptr + 8), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgr0);
+        _mm256_store_si256((__m256i*)(ptr + 4), bgr1);
+        _mm256_store_si256((__m256i*)(ptr + 8), bgr2);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgr0);
+        _mm256_storeu_si256((__m256i*)(ptr + 4), bgr1);
+        _mm256_storeu_si256((__m256i*)(ptr + 8), bgr2);
+    }
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x32& a, const v_uint8x32& b,
+                                const v_uint8x32& c, const v_uint8x32& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = _mm256_unpacklo_epi8(a.val, b.val);
+    __m256i bg1 = _mm256_unpackhi_epi8(a.val, b.val);
+    __m256i ra0 = _mm256_unpacklo_epi8(c.val, d.val);
+    __m256i ra1 = _mm256_unpackhi_epi8(c.val, d.val);
+
+    __m256i bgra0_ = _mm256_unpacklo_epi16(bg0, ra0);
+    __m256i bgra1_ = _mm256_unpackhi_epi16(bg0, ra0);
+    __m256i bgra2_ = _mm256_unpacklo_epi16(bg1, ra1);
+    __m256i bgra3_ = _mm256_unpackhi_epi16(bg1, ra1);
+
+    __m256i bgra0 = _mm256_permute2x128_si256(bgra0_, bgra1_, 0 + 2*16);
+    __m256i bgra2 = _mm256_permute2x128_si256(bgra0_, bgra1_, 1 + 3*16);
+    __m256i bgra1 = _mm256_permute2x128_si256(bgra2_, bgra3_, 0 + 2*16);
+    __m256i bgra3 = _mm256_permute2x128_si256(bgra2_, bgra3_, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgra0);
+        _mm256_stream_si256((__m256i*)(ptr + 32), bgra1);
+        _mm256_stream_si256((__m256i*)(ptr + 64), bgra2);
+        _mm256_stream_si256((__m256i*)(ptr + 96), bgra3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgra0);
+        _mm256_store_si256((__m256i*)(ptr + 32), bgra1);
+        _mm256_store_si256((__m256i*)(ptr + 64), bgra2);
+        _mm256_store_si256((__m256i*)(ptr + 96), bgra3);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgra0);
+        _mm256_storeu_si256((__m256i*)(ptr + 32), bgra1);
+        _mm256_storeu_si256((__m256i*)(ptr + 64), bgra2);
+        _mm256_storeu_si256((__m256i*)(ptr + 96), bgra3);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x16& a, const v_uint16x16& b,
+                                const v_uint16x16& c, const v_uint16x16& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = _mm256_unpacklo_epi16(a.val, b.val);
+    __m256i bg1 = _mm256_unpackhi_epi16(a.val, b.val);
+    __m256i ra0 = _mm256_unpacklo_epi16(c.val, d.val);
+    __m256i ra1 = _mm256_unpackhi_epi16(c.val, d.val);
+
+    __m256i bgra0_ = _mm256_unpacklo_epi32(bg0, ra0);
+    __m256i bgra1_ = _mm256_unpackhi_epi32(bg0, ra0);
+    __m256i bgra2_ = _mm256_unpacklo_epi32(bg1, ra1);
+    __m256i bgra3_ = _mm256_unpackhi_epi32(bg1, ra1);
+
+    __m256i bgra0 = _mm256_permute2x128_si256(bgra0_, bgra1_, 0 + 2*16);
+    __m256i bgra2 = _mm256_permute2x128_si256(bgra0_, bgra1_, 1 + 3*16);
+    __m256i bgra1 = _mm256_permute2x128_si256(bgra2_, bgra3_, 0 + 2*16);
+    __m256i bgra3 = _mm256_permute2x128_si256(bgra2_, bgra3_, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgra0);
+        _mm256_stream_si256((__m256i*)(ptr + 16), bgra1);
+        _mm256_stream_si256((__m256i*)(ptr + 32), bgra2);
+        _mm256_stream_si256((__m256i*)(ptr + 48), bgra3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgra0);
+        _mm256_store_si256((__m256i*)(ptr + 16), bgra1);
+        _mm256_store_si256((__m256i*)(ptr + 32), bgra2);
+        _mm256_store_si256((__m256i*)(ptr + 48), bgra3);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgra0);
+        _mm256_storeu_si256((__m256i*)(ptr + 16), bgra1);
+        _mm256_storeu_si256((__m256i*)(ptr + 32), bgra2);
+        _mm256_storeu_si256((__m256i*)(ptr + 48), bgra3);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x8& a, const v_uint32x8& b,
+                                const v_uint32x8& c, const v_uint32x8& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = _mm256_unpacklo_epi32(a.val, b.val);
+    __m256i bg1 = _mm256_unpackhi_epi32(a.val, b.val);
+    __m256i ra0 = _mm256_unpacklo_epi32(c.val, d.val);
+    __m256i ra1 = _mm256_unpackhi_epi32(c.val, d.val);
+
+    __m256i bgra0_ = _mm256_unpacklo_epi64(bg0, ra0);
+    __m256i bgra1_ = _mm256_unpackhi_epi64(bg0, ra0);
+    __m256i bgra2_ = _mm256_unpacklo_epi64(bg1, ra1);
+    __m256i bgra3_ = _mm256_unpackhi_epi64(bg1, ra1);
+
+    __m256i bgra0 = _mm256_permute2x128_si256(bgra0_, bgra1_, 0 + 2*16);
+    __m256i bgra2 = _mm256_permute2x128_si256(bgra0_, bgra1_, 1 + 3*16);
+    __m256i bgra1 = _mm256_permute2x128_si256(bgra2_, bgra3_, 0 + 2*16);
+    __m256i bgra3 = _mm256_permute2x128_si256(bgra2_, bgra3_, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgra0);
+        _mm256_stream_si256((__m256i*)(ptr + 8), bgra1);
+        _mm256_stream_si256((__m256i*)(ptr + 16), bgra2);
+        _mm256_stream_si256((__m256i*)(ptr + 24), bgra3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgra0);
+        _mm256_store_si256((__m256i*)(ptr + 8), bgra1);
+        _mm256_store_si256((__m256i*)(ptr + 16), bgra2);
+        _mm256_store_si256((__m256i*)(ptr + 24), bgra3);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgra0);
+        _mm256_storeu_si256((__m256i*)(ptr + 8), bgra1);
+        _mm256_storeu_si256((__m256i*)(ptr + 16), bgra2);
+        _mm256_storeu_si256((__m256i*)(ptr + 24), bgra3);
+    }
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x4& a, const v_uint64x4& b,
+                                const v_uint64x4& c, const v_uint64x4& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = _mm256_unpacklo_epi64(a.val, b.val);
+    __m256i bg1 = _mm256_unpackhi_epi64(a.val, b.val);
+    __m256i ra0 = _mm256_unpacklo_epi64(c.val, d.val);
+    __m256i ra1 = _mm256_unpackhi_epi64(c.val, d.val);
+
+    __m256i bgra0 = _mm256_permute2x128_si256(bg0, ra0, 0 + 2*16);
+    __m256i bgra1 = _mm256_permute2x128_si256(bg1, ra1, 0 + 2*16);
+    __m256i bgra2 = _mm256_permute2x128_si256(bg0, ra0, 1 + 3*16);
+    __m256i bgra3 = _mm256_permute2x128_si256(bg1, ra1, 1 + 3*16);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm256_stream_si256((__m256i*)ptr, bgra0);
+        _mm256_stream_si256((__m256i*)(ptr + 4), bgra1);
+        _mm256_stream_si256((__m256i*)(ptr + 8), bgra2);
+        _mm256_stream_si256((__m256i*)(ptr + 12), bgra3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm256_store_si256((__m256i*)ptr, bgra0);
+        _mm256_store_si256((__m256i*)(ptr + 4), bgra1);
+        _mm256_store_si256((__m256i*)(ptr + 8), bgra2);
+        _mm256_store_si256((__m256i*)(ptr + 12), bgra3);
+    }
+    else
+    {
+        _mm256_storeu_si256((__m256i*)ptr, bgra0);
+        _mm256_storeu_si256((__m256i*)(ptr + 4), bgra1);
+        _mm256_storeu_si256((__m256i*)(ptr + 8), bgra2);
+        _mm256_storeu_si256((__m256i*)(ptr + 12), bgra3);
+    }
+}
+
+#define OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1) \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0 ) \
+{ \
+    _Tpvec1 a1, b1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0 ) \
+{ \
+    _Tpvec1 a1, b1, c1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0, _Tpvec0& d0 ) \
+{ \
+    _Tpvec1 a1, b1, c1, d1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+    d0 = v_reinterpret_as_##suffix0(d1); \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                hal::StoreMode mode=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, mode);      \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, const _Tpvec0& c0, \
+                                hal::StoreMode mode=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, mode);  \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                const _Tpvec0& c0, const _Tpvec0& d0, \
+                                hal::StoreMode mode=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1, mode); \
+}
+
+OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int8x32, schar, s8, v_uint8x32, uchar, u8)
+OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int16x16, short, s16, v_uint16x16, ushort, u16)
+OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int32x8, int, s32, v_uint32x8, unsigned, u32)
+OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_float32x8, float, f32, v_uint32x8, unsigned, u32)
+OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_int64x4, int64, s64, v_uint64x4, uint64, u64)
+OPENCV_HAL_IMPL_AVX_LOADSTORE_INTERLEAVE(v_float64x4, double, f64, v_uint64x4, uint64, u64)
+
+//
+// FP16
+//
+
+inline v_float32x8 v256_load_expand(const hfloat* ptr)
+{
+#if CV_FP16
+    return v_float32x8(_mm256_cvtph_ps(_mm_loadu_si128((const __m128i*)ptr)));
+#else
+    float CV_DECL_ALIGNED(32) buf[8];
+    for (int i = 0; i < 8; i++)
+        buf[i] = (float)ptr[i];
+    return v256_load_aligned(buf);
+#endif
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x8& a)
+{
+#if CV_FP16
+    __m128i ah = _mm256_cvtps_ph(a.val, 0);
+    _mm_storeu_si128((__m128i*)ptr, ah);
+#else
+    float CV_DECL_ALIGNED(32) buf[8];
+    v_store_aligned(buf, a);
+    for (int i = 0; i < 8; i++)
+        ptr[i] = hfloat(buf[i]);
+#endif
+}
+
+//
+// end of FP16
+//
+
+inline void v256_cleanup() { _mm256_zeroall(); }
+
+#include "intrin_math.hpp"
+inline v_float32x8 v_exp(const v_float32x8& x) { return v_exp_default_32f<v_float32x8, v_int32x8>(x); }
+inline v_float32x8 v_log(const v_float32x8& x) { return v_log_default_32f<v_float32x8, v_int32x8>(x); }
+inline void v_sincos(const v_float32x8& x, v_float32x8& s, v_float32x8& c) { v_sincos_default_32f<v_float32x8, v_int32x8>(x, s, c); }
+inline v_float32x8 v_sin(const v_float32x8& x) { return v_sin_default_32f<v_float32x8, v_int32x8>(x); }
+inline v_float32x8 v_cos(const v_float32x8& x) { return v_cos_default_32f<v_float32x8, v_int32x8>(x); }
+inline v_float32x8 v_erf(const v_float32x8& x) { return v_erf_default_32f<v_float32x8, v_int32x8>(x); }
+
+inline v_float64x4 v_exp(const v_float64x4& x) { return v_exp_default_64f<v_float64x4, v_int64x4>(x); }
+inline v_float64x4 v_log(const v_float64x4& x) { return v_log_default_64f<v_float64x4, v_int64x4>(x); }
+inline void v_sincos(const v_float64x4& x, v_float64x4& s, v_float64x4& c) { v_sincos_default_64f<v_float64x4, v_int64x4>(x, s, c); }
+inline v_float64x4 v_sin(const v_float64x4& x) { return v_sin_default_64f<v_float64x4, v_int64x4>(x); }
+inline v_float64x4 v_cos(const v_float64x4& x) { return v_cos_default_64f<v_float64x4, v_int64x4>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+} // cv::
+
+#endif // OPENCV_HAL_INTRIN_AVX_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_avx512.hpp

@@ -0,0 +1,3101 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+#ifndef OPENCV_HAL_INTRIN_AVX512_HPP
+#define OPENCV_HAL_INTRIN_AVX512_HPP
+
+#if defined(_MSC_VER) && (_MSC_VER < 1920/*MSVS2019*/)
+# pragma warning(disable:4146)  // unary minus operator applied to unsigned type, result still unsigned
+# pragma warning(disable:4309)  // 'argument': truncation of constant value
+# pragma warning(disable:4310)  // cast truncates constant value
+#endif
+
+#define CVT_ROUND_MODES_IMPLEMENTED 0
+
+#define CV_SIMD512 1
+#define CV_SIMD512_64F 1
+#define CV_SIMD512_FP16 0  // no native operations with FP16 type. Only load/store from float32x8 are available (if CV_FP16 == 1)
+
+#define _v512_set_epu64(a7, a6, a5, a4, a3, a2, a1, a0) _mm512_set_epi64((int64)(a7),(int64)(a6),(int64)(a5),(int64)(a4),(int64)(a3),(int64)(a2),(int64)(a1),(int64)(a0))
+#define _v512_set_epu32(a15, a14, a13, a12, a11, a10,  a9,  a8,  a7,  a6,  a5,  a4,  a3,  a2,  a1,  a0) \
+        _mm512_set_epi64(((int64)(a15)<<32)|(int64)(a14), ((int64)(a13)<<32)|(int64)(a12), ((int64)(a11)<<32)|(int64)(a10), ((int64)( a9)<<32)|(int64)( a8), \
+                         ((int64)( a7)<<32)|(int64)( a6), ((int64)( a5)<<32)|(int64)( a4), ((int64)( a3)<<32)|(int64)( a2), ((int64)( a1)<<32)|(int64)( a0))
+#define _v512_set_epu16(a31, a30, a29, a28, a27, a26, a25, a24, a23, a22, a21, a20, a19, a18, a17, a16, \
+                        a15, a14, a13, a12, a11, a10,  a9,  a8,  a7,  a6,  a5,  a4,  a3,  a2,  a1,  a0) \
+        _v512_set_epu32(((unsigned)(a31)<<16)|(unsigned)(a30), ((unsigned)(a29)<<16)|(unsigned)(a28), ((unsigned)(a27)<<16)|(unsigned)(a26), ((unsigned)(a25)<<16)|(unsigned)(a24), \
+                        ((unsigned)(a23)<<16)|(unsigned)(a22), ((unsigned)(a21)<<16)|(unsigned)(a20), ((unsigned)(a19)<<16)|(unsigned)(a18), ((unsigned)(a17)<<16)|(unsigned)(a16), \
+                        ((unsigned)(a15)<<16)|(unsigned)(a14), ((unsigned)(a13)<<16)|(unsigned)(a12), ((unsigned)(a11)<<16)|(unsigned)(a10), ((unsigned)( a9)<<16)|(unsigned)( a8), \
+                        ((unsigned)( a7)<<16)|(unsigned)( a6), ((unsigned)( a5)<<16)|(unsigned)( a4), ((unsigned)( a3)<<16)|(unsigned)( a2), ((unsigned)( a1)<<16)|(unsigned)( a0))
+#define _v512_set_epu8(a63, a62, a61, a60, a59, a58, a57, a56, a55, a54, a53, a52, a51, a50, a49, a48, \
+                       a47, a46, a45, a44, a43, a42, a41, a40, a39, a38, a37, a36, a35, a34, a33, a32, \
+                       a31, a30, a29, a28, a27, a26, a25, a24, a23, a22, a21, a20, a19, a18, a17, a16, \
+                       a15, a14, a13, a12, a11, a10,  a9,  a8,  a7,  a6,  a5,  a4,  a3,  a2,  a1,  a0) \
+        _v512_set_epu32(((unsigned)(a63)<<24)|((unsigned)(a62)<<16)|((unsigned)(a61)<<8)|(unsigned)(a60),((unsigned)(a59)<<24)|((unsigned)(a58)<<16)|((unsigned)(a57)<<8)|(unsigned)(a56), \
+                        ((unsigned)(a55)<<24)|((unsigned)(a54)<<16)|((unsigned)(a53)<<8)|(unsigned)(a52),((unsigned)(a51)<<24)|((unsigned)(a50)<<16)|((unsigned)(a49)<<8)|(unsigned)(a48), \
+                        ((unsigned)(a47)<<24)|((unsigned)(a46)<<16)|((unsigned)(a45)<<8)|(unsigned)(a44),((unsigned)(a43)<<24)|((unsigned)(a42)<<16)|((unsigned)(a41)<<8)|(unsigned)(a40), \
+                        ((unsigned)(a39)<<24)|((unsigned)(a38)<<16)|((unsigned)(a37)<<8)|(unsigned)(a36),((unsigned)(a35)<<24)|((unsigned)(a34)<<16)|((unsigned)(a33)<<8)|(unsigned)(a32), \
+                        ((unsigned)(a31)<<24)|((unsigned)(a30)<<16)|((unsigned)(a29)<<8)|(unsigned)(a28),((unsigned)(a27)<<24)|((unsigned)(a26)<<16)|((unsigned)(a25)<<8)|(unsigned)(a24), \
+                        ((unsigned)(a23)<<24)|((unsigned)(a22)<<16)|((unsigned)(a21)<<8)|(unsigned)(a20),((unsigned)(a19)<<24)|((unsigned)(a18)<<16)|((unsigned)(a17)<<8)|(unsigned)(a16), \
+                        ((unsigned)(a15)<<24)|((unsigned)(a14)<<16)|((unsigned)(a13)<<8)|(unsigned)(a12),((unsigned)(a11)<<24)|((unsigned)(a10)<<16)|((unsigned)( a9)<<8)|(unsigned)( a8), \
+                        ((unsigned)( a7)<<24)|((unsigned)( a6)<<16)|((unsigned)( a5)<<8)|(unsigned)( a4),((unsigned)( a3)<<24)|((unsigned)( a2)<<16)|((unsigned)( a1)<<8)|(unsigned)( a0))
+#define _v512_set_epi8(a63, a62, a61, a60, a59, a58, a57, a56, a55, a54, a53, a52, a51, a50, a49, a48, \
+                       a47, a46, a45, a44, a43, a42, a41, a40, a39, a38, a37, a36, a35, a34, a33, a32, \
+                       a31, a30, a29, a28, a27, a26, a25, a24, a23, a22, a21, a20, a19, a18, a17, a16, \
+                       a15, a14, a13, a12, a11, a10,  a9,  a8,  a7,  a6,  a5,  a4,  a3,  a2,  a1,  a0) \
+        _v512_set_epu8((uchar)(a63), (uchar)(a62), (uchar)(a61), (uchar)(a60), (uchar)(a59), (uchar)(a58), (uchar)(a57), (uchar)(a56), \
+                       (uchar)(a55), (uchar)(a54), (uchar)(a53), (uchar)(a52), (uchar)(a51), (uchar)(a50), (uchar)(a49), (uchar)(a48), \
+                       (uchar)(a47), (uchar)(a46), (uchar)(a45), (uchar)(a44), (uchar)(a43), (uchar)(a42), (uchar)(a41), (uchar)(a40), \
+                       (uchar)(a39), (uchar)(a38), (uchar)(a37), (uchar)(a36), (uchar)(a35), (uchar)(a34), (uchar)(a33), (uchar)(a32), \
+                       (uchar)(a31), (uchar)(a30), (uchar)(a29), (uchar)(a28), (uchar)(a27), (uchar)(a26), (uchar)(a25), (uchar)(a24), \
+                       (uchar)(a23), (uchar)(a22), (uchar)(a21), (uchar)(a20), (uchar)(a19), (uchar)(a18), (uchar)(a17), (uchar)(a16), \
+                       (uchar)(a15), (uchar)(a14), (uchar)(a13), (uchar)(a12), (uchar)(a11), (uchar)(a10), (uchar)( a9), (uchar)( a8), \
+                       (uchar)( a7), (uchar)( a6), (uchar)( a5), (uchar)( a4), (uchar)( a3), (uchar)( a2), (uchar)( a1), (uchar)( a0))
+
+#ifndef _mm512_cvtpd_pslo
+#ifdef _mm512_zextsi256_si512
+#define _mm512_cvtpd_pslo(a) _mm512_zextps256_ps512(_mm512_cvtpd_ps(a))
+#else
+//if preferred way to extend with zeros is unavailable
+#define _mm512_cvtpd_pslo(a) _mm512_castps256_ps512(_mm512_cvtpd_ps(a))
+#endif
+#endif
+///////// Utils ////////////
+
+namespace
+{
+
+inline __m512i _v512_combine(const __m256i& lo, const __m256i& hi)
+{ return _mm512_inserti32x8(_mm512_castsi256_si512(lo), hi, 1); }
+
+inline __m512 _v512_combine(const __m256& lo, const __m256& hi)
+{ return _mm512_insertf32x8(_mm512_castps256_ps512(lo), hi, 1); }
+
+inline __m512d _v512_combine(const __m256d& lo, const __m256d& hi)
+{ return _mm512_insertf64x4(_mm512_castpd256_pd512(lo), hi, 1); }
+
+inline int _v_cvtsi512_si32(const __m512i& a)
+{ return _mm_cvtsi128_si32(_mm512_castsi512_si128(a)); }
+
+inline __m256i _v512_extract_high(const __m512i& v)
+{ return _mm512_extracti32x8_epi32(v, 1); }
+
+inline __m256  _v512_extract_high(const __m512& v)
+{ return _mm512_extractf32x8_ps(v, 1); }
+
+inline __m256d _v512_extract_high(const __m512d& v)
+{ return _mm512_extractf64x4_pd(v, 1); }
+
+inline __m256i _v512_extract_low(const __m512i& v)
+{ return _mm512_castsi512_si256(v); }
+
+inline __m256  _v512_extract_low(const __m512& v)
+{ return _mm512_castps512_ps256(v); }
+
+inline __m256d _v512_extract_low(const __m512d& v)
+{ return _mm512_castpd512_pd256(v); }
+
+inline __m512i _v512_insert(const __m512i& a, const __m256i& b)
+{ return _mm512_inserti32x8(a, b, 0); }
+
+inline __m512 _v512_insert(const __m512& a, const __m256& b)
+{ return _mm512_insertf32x8(a, b, 0); }
+
+inline __m512d _v512_insert(const __m512d& a, const __m256d& b)
+{ return _mm512_insertf64x4(a, b, 0); }
+
+}
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+///////// Types ////////////
+
+struct v_uint8x64
+{
+    typedef uchar lane_type;
+    enum { nlanes = 64 };
+    __m512i val;
+
+    explicit v_uint8x64(__m512i v) : val(v) {}
+    v_uint8x64(uchar v0,  uchar v1,  uchar v2,  uchar v3,
+               uchar v4,  uchar v5,  uchar v6,  uchar v7,
+               uchar v8,  uchar v9,  uchar v10, uchar v11,
+               uchar v12, uchar v13, uchar v14, uchar v15,
+               uchar v16, uchar v17, uchar v18, uchar v19,
+               uchar v20, uchar v21, uchar v22, uchar v23,
+               uchar v24, uchar v25, uchar v26, uchar v27,
+               uchar v28, uchar v29, uchar v30, uchar v31,
+               uchar v32, uchar v33, uchar v34, uchar v35,
+               uchar v36, uchar v37, uchar v38, uchar v39,
+               uchar v40, uchar v41, uchar v42, uchar v43,
+               uchar v44, uchar v45, uchar v46, uchar v47,
+               uchar v48, uchar v49, uchar v50, uchar v51,
+               uchar v52, uchar v53, uchar v54, uchar v55,
+               uchar v56, uchar v57, uchar v58, uchar v59,
+               uchar v60, uchar v61, uchar v62, uchar v63)
+    {
+        val = _v512_set_epu8(v63, v62, v61, v60, v59, v58, v57, v56, v55, v54, v53, v52, v51, v50, v49, v48,
+                             v47, v46, v45, v44, v43, v42, v41, v40, v39, v38, v37, v36, v35, v34, v33, v32,
+                             v31, v30, v29, v28, v27, v26, v25, v24, v23, v22, v21, v20, v19, v18, v17, v16,
+                             v15, v14, v13, v12, v11, v10, v9,  v8,  v7,  v6,  v5,  v4,  v3,  v2,  v1,  v0);
+    }
+    v_uint8x64() {}
+
+    static inline v_uint8x64 zero() { return v_uint8x64(_mm512_setzero_si512()); }
+
+    uchar get0() const { return (uchar)_v_cvtsi512_si32(val); }
+};
+
+struct v_int8x64
+{
+    typedef schar lane_type;
+    enum { nlanes = 64 };
+    __m512i val;
+
+    explicit v_int8x64(__m512i v) : val(v) {}
+    v_int8x64(schar v0,  schar v1,  schar v2,  schar v3,
+              schar v4,  schar v5,  schar v6,  schar v7,
+              schar v8,  schar v9,  schar v10, schar v11,
+              schar v12, schar v13, schar v14, schar v15,
+              schar v16, schar v17, schar v18, schar v19,
+              schar v20, schar v21, schar v22, schar v23,
+              schar v24, schar v25, schar v26, schar v27,
+              schar v28, schar v29, schar v30, schar v31,
+              schar v32, schar v33, schar v34, schar v35,
+              schar v36, schar v37, schar v38, schar v39,
+              schar v40, schar v41, schar v42, schar v43,
+              schar v44, schar v45, schar v46, schar v47,
+              schar v48, schar v49, schar v50, schar v51,
+              schar v52, schar v53, schar v54, schar v55,
+              schar v56, schar v57, schar v58, schar v59,
+              schar v60, schar v61, schar v62, schar v63)
+    {
+        val = _v512_set_epi8(v63, v62, v61, v60, v59, v58, v57, v56, v55, v54, v53, v52, v51, v50, v49, v48,
+                             v47, v46, v45, v44, v43, v42, v41, v40, v39, v38, v37, v36, v35, v34, v33, v32,
+                             v31, v30, v29, v28, v27, v26, v25, v24, v23, v22, v21, v20, v19, v18, v17, v16,
+                             v15, v14, v13, v12, v11, v10, v9,  v8,  v7,  v6,  v5,  v4,  v3,  v2,  v1,  v0);
+    }
+    v_int8x64() {}
+
+    static inline v_int8x64 zero() { return v_int8x64(_mm512_setzero_si512()); }
+
+    schar get0() const { return (schar)_v_cvtsi512_si32(val); }
+};
+
+struct v_uint16x32
+{
+    typedef ushort lane_type;
+    enum { nlanes = 32 };
+    __m512i val;
+
+    explicit v_uint16x32(__m512i v) : val(v) {}
+    v_uint16x32(ushort v0,  ushort v1,  ushort v2,  ushort v3,
+                ushort v4,  ushort v5,  ushort v6,  ushort v7,
+                ushort v8,  ushort v9,  ushort v10, ushort v11,
+                ushort v12, ushort v13, ushort v14, ushort v15,
+                ushort v16, ushort v17, ushort v18, ushort v19,
+                ushort v20, ushort v21, ushort v22, ushort v23,
+                ushort v24, ushort v25, ushort v26, ushort v27,
+                ushort v28, ushort v29, ushort v30, ushort v31)
+    {
+        val = _v512_set_epu16(v31, v30, v29, v28, v27, v26, v25, v24, v23, v22, v21, v20, v19, v18, v17, v16,
+                              v15, v14, v13, v12, v11, v10, v9,  v8,  v7,  v6,  v5,  v4,  v3,  v2,  v1,  v0);
+    }
+    v_uint16x32() {}
+
+    static inline v_uint16x32 zero() { return v_uint16x32(_mm512_setzero_si512()); }
+
+    ushort get0() const { return (ushort)_v_cvtsi512_si32(val); }
+};
+
+struct v_int16x32
+{
+    typedef short lane_type;
+    enum { nlanes = 32 };
+    __m512i val;
+
+    explicit v_int16x32(__m512i v) : val(v) {}
+    v_int16x32(short v0,  short v1,  short v2,  short v3,  short v4,  short v5,  short v6,  short v7,
+               short v8,  short v9,  short v10, short v11, short v12, short v13, short v14, short v15,
+               short v16, short v17, short v18, short v19, short v20, short v21, short v22, short v23,
+               short v24, short v25, short v26, short v27, short v28, short v29, short v30, short v31)
+    {
+        val = _v512_set_epu16((ushort)v31, (ushort)v30, (ushort)v29, (ushort)v28, (ushort)v27, (ushort)v26, (ushort)v25, (ushort)v24,
+                              (ushort)v23, (ushort)v22, (ushort)v21, (ushort)v20, (ushort)v19, (ushort)v18, (ushort)v17, (ushort)v16,
+                              (ushort)v15, (ushort)v14, (ushort)v13, (ushort)v12, (ushort)v11, (ushort)v10, (ushort)v9 , (ushort)v8,
+                              (ushort)v7 , (ushort)v6 , (ushort)v5 , (ushort)v4 , (ushort)v3 , (ushort)v2 , (ushort)v1 , (ushort)v0);
+    }
+    v_int16x32() {}
+
+    static inline v_int16x32 zero() { return v_int16x32(_mm512_setzero_si512()); }
+
+    short get0() const { return (short)_v_cvtsi512_si32(val); }
+};
+
+struct v_uint32x16
+{
+    typedef unsigned lane_type;
+    enum { nlanes = 16 };
+    __m512i val;
+
+    explicit v_uint32x16(__m512i v) : val(v) {}
+    v_uint32x16(unsigned v0,  unsigned v1,  unsigned v2,  unsigned v3,
+                unsigned v4,  unsigned v5,  unsigned v6,  unsigned v7,
+                unsigned v8,  unsigned v9,  unsigned v10, unsigned v11,
+                unsigned v12, unsigned v13, unsigned v14, unsigned v15)
+    {
+        val = _mm512_setr_epi32((int)v0,  (int)v1,  (int)v2,  (int)v3, (int)v4,  (int)v5,  (int)v6,  (int)v7,
+                                (int)v8,  (int)v9,  (int)v10, (int)v11, (int)v12, (int)v13, (int)v14, (int)v15);
+    }
+    v_uint32x16() {}
+
+    static inline v_uint32x16 zero() { return v_uint32x16(_mm512_setzero_si512()); }
+
+    unsigned get0() const { return (unsigned)_v_cvtsi512_si32(val); }
+};
+
+struct v_int32x16
+{
+    typedef int lane_type;
+    enum { nlanes = 16 };
+    __m512i val;
+
+    explicit v_int32x16(__m512i v) : val(v) {}
+    v_int32x16(int v0, int v1, int v2,  int v3,  int v4,  int v5,  int v6,  int v7,
+               int v8, int v9, int v10, int v11, int v12, int v13, int v14, int v15)
+    {
+        val = _mm512_setr_epi32(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15);
+    }
+    v_int32x16() {}
+
+    static inline v_int32x16 zero() { return v_int32x16(_mm512_setzero_si512()); }
+
+    int get0() const { return _v_cvtsi512_si32(val); }
+};
+
+struct v_float32x16
+{
+    typedef float lane_type;
+    enum { nlanes = 16 };
+    __m512 val;
+
+    explicit v_float32x16(__m512 v) : val(v) {}
+    v_float32x16(float v0, float v1, float v2,  float v3,  float v4,  float v5,  float v6,  float v7,
+                 float v8, float v9, float v10, float v11, float v12, float v13, float v14, float v15)
+    {
+        val = _mm512_setr_ps(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15);
+    }
+    v_float32x16() {}
+
+    static inline v_float32x16 zero() { return v_float32x16(_mm512_setzero_ps()); }
+
+    float get0() const { return _mm_cvtss_f32(_mm512_castps512_ps128(val)); }
+};
+
+struct v_uint64x8
+{
+    typedef uint64 lane_type;
+    enum { nlanes = 8 };
+    __m512i val;
+
+    explicit v_uint64x8(__m512i v) : val(v) {}
+    v_uint64x8(uint64 v0, uint64 v1, uint64 v2, uint64 v3, uint64 v4, uint64 v5, uint64 v6, uint64 v7)
+    { val = _mm512_setr_epi64((int64)v0, (int64)v1, (int64)v2, (int64)v3, (int64)v4, (int64)v5, (int64)v6, (int64)v7); }
+    v_uint64x8() {}
+
+    static inline v_uint64x8 zero() { return v_uint64x8(_mm512_setzero_si512()); }
+
+    uint64 get0() const
+    {
+    #if defined __x86_64__ || defined _M_X64
+        return (uint64)_mm_cvtsi128_si64(_mm512_castsi512_si128(val));
+    #else
+        int a = _mm_cvtsi128_si32(_mm512_castsi512_si128(val));
+        int b = _mm_cvtsi128_si32(_mm512_castsi512_si128(_mm512_srli_epi64(val, 32)));
+        return (unsigned)a | ((uint64)(unsigned)b << 32);
+    #endif
+    }
+};
+
+struct v_int64x8
+{
+    typedef int64 lane_type;
+    enum { nlanes = 8 };
+    __m512i val;
+
+    explicit v_int64x8(__m512i v) : val(v) {}
+    v_int64x8(int64 v0, int64 v1, int64 v2, int64 v3, int64 v4, int64 v5, int64 v6, int64 v7)
+    { val = _mm512_setr_epi64(v0, v1, v2, v3, v4, v5, v6, v7); }
+    v_int64x8() {}
+
+    static inline v_int64x8 zero() { return v_int64x8(_mm512_setzero_si512()); }
+
+    int64 get0() const
+    {
+    #if defined __x86_64__ || defined _M_X64
+        return (int64)_mm_cvtsi128_si64(_mm512_castsi512_si128(val));
+    #else
+        int a = _mm_cvtsi128_si32(_mm512_castsi512_si128(val));
+        int b = _mm_cvtsi128_si32(_mm512_castsi512_si128(_mm512_srli_epi64(val, 32)));
+        return (int64)((unsigned)a | ((uint64)(unsigned)b << 32));
+    #endif
+    }
+};
+
+struct v_float64x8
+{
+    typedef double lane_type;
+    enum { nlanes = 8 };
+    __m512d val;
+
+    explicit v_float64x8(__m512d v) : val(v) {}
+    v_float64x8(double v0, double v1, double v2, double v3, double v4, double v5, double v6, double v7)
+    { val = _mm512_setr_pd(v0, v1, v2, v3, v4, v5, v6, v7); }
+    v_float64x8() {}
+
+    static inline v_float64x8 zero() { return v_float64x8(_mm512_setzero_pd()); }
+
+    double get0() const { return _mm_cvtsd_f64(_mm512_castpd512_pd128(val)); }
+};
+
+//////////////// Load and store operations ///////////////
+
+#define OPENCV_HAL_IMPL_AVX512_LOADSTORE(_Tpvec, _Tp)                    \
+    inline _Tpvec v512_load(const _Tp* ptr)                           \
+    { return _Tpvec(_mm512_loadu_si512((const __m512i*)ptr)); }       \
+    inline _Tpvec v512_load_aligned(const _Tp* ptr)                   \
+    { return _Tpvec(_mm512_load_si512((const __m512i*)ptr)); }        \
+    inline _Tpvec v512_load_low(const _Tp* ptr)                       \
+    {                                                                 \
+        __m256i v256 = _mm256_loadu_si256((const __m256i*)ptr);       \
+        return _Tpvec(_mm512_castsi256_si512(v256));                  \
+    }                                                                 \
+    inline _Tpvec v512_load_halves(const _Tp* ptr0, const _Tp* ptr1)  \
+    {                                                                 \
+        __m256i vlo = _mm256_loadu_si256((const __m256i*)ptr0);       \
+        __m256i vhi = _mm256_loadu_si256((const __m256i*)ptr1);       \
+        return _Tpvec(_v512_combine(vlo, vhi));                       \
+    }                                                                 \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                    \
+    { _mm512_storeu_si512((__m512i*)ptr, a.val); }                    \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)            \
+    { _mm512_store_si512((__m512i*)ptr, a.val); }                     \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)    \
+    { _mm512_stream_si512((__m512i*)ptr, a.val); }                    \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+    { \
+        if( mode == hal::STORE_UNALIGNED ) \
+            _mm512_storeu_si512((__m512i*)ptr, a.val); \
+        else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+            _mm512_stream_si512((__m512i*)ptr, a.val); \
+        else \
+            _mm512_store_si512((__m512i*)ptr, a.val); \
+    } \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                \
+    { _mm256_storeu_si256((__m256i*)ptr, _v512_extract_low(a.val)); }    \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)               \
+    { _mm256_storeu_si256((__m256i*)ptr, _v512_extract_high(a.val)); }
+
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_uint8x64,  uchar)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_int8x64,   schar)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_uint16x32, ushort)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_int16x32,  short)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_uint32x16,  unsigned)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_int32x16,   int)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_uint64x8,  uint64)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE(v_int64x8,   int64)
+
+#define OPENCV_HAL_IMPL_AVX512_LOADSTORE_FLT(_Tpvec, _Tp, suffix, halfreg)   \
+    inline _Tpvec v512_load(const _Tp* ptr)                               \
+    { return _Tpvec(_mm512_loadu_##suffix(ptr)); }                        \
+    inline _Tpvec v512_load_aligned(const _Tp* ptr)                       \
+    { return _Tpvec(_mm512_load_##suffix(ptr)); }                         \
+    inline _Tpvec v512_load_low(const _Tp* ptr)                           \
+    {                                                                     \
+        return _Tpvec(_mm512_cast##suffix##256_##suffix##512              \
+                     (_mm256_loadu_##suffix(ptr)));                       \
+    }                                                                     \
+    inline _Tpvec v512_load_halves(const _Tp* ptr0, const _Tp* ptr1)      \
+    {                                                                     \
+        halfreg vlo = _mm256_loadu_##suffix(ptr0);                        \
+        halfreg vhi = _mm256_loadu_##suffix(ptr1);                        \
+        return _Tpvec(_v512_combine(vlo, vhi));                           \
+    }                                                                     \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                        \
+    { _mm512_storeu_##suffix(ptr, a.val); }                               \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)                \
+    { _mm512_store_##suffix(ptr, a.val); }                                \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)        \
+    { _mm512_stream_##suffix(ptr, a.val); }                               \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+    { \
+        if( mode == hal::STORE_UNALIGNED ) \
+            _mm512_storeu_##suffix(ptr, a.val); \
+        else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+            _mm512_stream_##suffix(ptr, a.val); \
+        else \
+            _mm512_store_##suffix(ptr, a.val); \
+    } \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                    \
+    { _mm256_storeu_##suffix(ptr, _v512_extract_low(a.val)); }            \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)                   \
+    { _mm256_storeu_##suffix(ptr, _v512_extract_high(a.val)); }
+
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_FLT(v_float32x16, float,  ps, __m256)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_FLT(v_float64x8, double, pd, __m256d)
+
+#define OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, _Tpvecf, suffix, cast) \
+    inline _Tpvec v_reinterpret_as_##suffix(const _Tpvecf& a)   \
+    { return _Tpvec(cast(a.val)); }
+
+#define OPENCV_HAL_IMPL_AVX512_INIT(_Tpvec, _Tp, suffix, ssuffix, ctype_s)         \
+    inline _Tpvec v512_setzero_##suffix()                                          \
+    { return _Tpvec(_mm512_setzero_si512()); }                                     \
+    inline _Tpvec v512_setall_##suffix(_Tp v)                                      \
+    { return _Tpvec(_mm512_set1_##ssuffix((ctype_s)v)); }                          \
+    template <> inline _Tpvec v_setzero_()                                         \
+    { return v512_setzero_##suffix(); }                                            \
+    template <> inline _Tpvec v_setall_(_Tp v)                                     \
+    { return v512_setall_##suffix(v); }                                            \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint8x64,   suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int8x64,    suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint16x32,  suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int16x32,   suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint32x16,  suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int32x16,   suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint64x8,   suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int64x8,    suffix, OPENCV_HAL_NOP)      \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_float32x16, suffix, _mm512_castps_si512) \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_float64x8,  suffix, _mm512_castpd_si512)
+
+OPENCV_HAL_IMPL_AVX512_INIT(v_uint8x64,  uchar,    u8,  epi8,   char)
+OPENCV_HAL_IMPL_AVX512_INIT(v_int8x64,   schar,    s8,  epi8,   char)
+OPENCV_HAL_IMPL_AVX512_INIT(v_uint16x32, ushort,   u16, epi16,  short)
+OPENCV_HAL_IMPL_AVX512_INIT(v_int16x32,  short,    s16, epi16,  short)
+OPENCV_HAL_IMPL_AVX512_INIT(v_uint32x16, unsigned, u32, epi32,  int)
+OPENCV_HAL_IMPL_AVX512_INIT(v_int32x16,  int,      s32, epi32,  int)
+OPENCV_HAL_IMPL_AVX512_INIT(v_uint64x8,  uint64,   u64, epi64,  int64)
+OPENCV_HAL_IMPL_AVX512_INIT(v_int64x8,   int64,    s64, epi64,  int64)
+
+#define OPENCV_HAL_IMPL_AVX512_INIT_FLT(_Tpvec, _Tp, suffix, zsuffix, cast) \
+    inline _Tpvec v512_setzero_##suffix()                                   \
+    { return _Tpvec(_mm512_setzero_##zsuffix()); }                          \
+    inline _Tpvec v512_setall_##suffix(_Tp v)                               \
+    { return _Tpvec(_mm512_set1_##zsuffix(v)); }                            \
+    template <> inline _Tpvec v_setzero_()                                  \
+    { return v512_setzero_##suffix(); }                                     \
+    template <> inline _Tpvec v_setall_(_Tp v)                              \
+    { return v512_setall_##suffix(v); }                                     \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint8x64,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int8x64,   suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint16x32, suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int16x32,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint32x16, suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int32x16,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_uint64x8,  suffix, cast)          \
+    OPENCV_HAL_IMPL_AVX512_CAST(_Tpvec, v_int64x8,   suffix, cast)
+
+OPENCV_HAL_IMPL_AVX512_INIT_FLT(v_float32x16, float,  f32, ps, _mm512_castsi512_ps)
+OPENCV_HAL_IMPL_AVX512_INIT_FLT(v_float64x8,  double, f64, pd, _mm512_castsi512_pd)
+
+inline v_float32x16 v_reinterpret_as_f32(const v_float32x16& a)
+{ return a; }
+inline v_float32x16 v_reinterpret_as_f32(const v_float64x8& a)
+{ return v_float32x16(_mm512_castpd_ps(a.val)); }
+
+inline v_float64x8 v_reinterpret_as_f64(const v_float64x8& a)
+{ return a; }
+inline v_float64x8 v_reinterpret_as_f64(const v_float32x16& a)
+{ return v_float64x8(_mm512_castps_pd(a.val)); }
+
+// FP16
+inline v_float32x16 v512_load_expand(const hfloat* ptr)
+{
+    return v_float32x16(_mm512_cvtph_ps(_mm256_loadu_si256((const __m256i*)ptr)));
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x16& a)
+{
+    __m256i ah = _mm512_cvtps_ph(a.val, 0);
+    _mm256_storeu_si256((__m256i*)ptr, ah);
+}
+
+/* Recombine & ZIP */
+inline void v_zip(const v_int8x64& a, const v_int8x64& b, v_int8x64& ab0, v_int8x64& ab1)
+{
+#if CV_AVX_512VBMI
+    __m512i mask0 = _v512_set_epu8( 95,  31,  94,  30,  93,  29,  92,  28,  91,  27,  90,  26,  89,  25,  88,  24,
+                                    87,  23,  86,  22,  85,  21,  84,  20,  83,  19,  82,  18,  81,  17,  80,  16,
+                                    79,  15,  78,  14,  77,  13,  76,  12,  75,  11,  74,  10,  73,   9,  72,   8,
+                                    71,   7,  70,   6,  69,   5,  68,   4,  67,   3,  66,   2,  65,   1,  64,   0);
+    ab0 = v_int8x64(_mm512_permutex2var_epi8(a.val, mask0, b.val));
+    __m512i mask1 = _v512_set_epu8(127,  63, 126,  62, 125,  61, 124,  60, 123,  59, 122,  58, 121,  57, 120,  56,
+                                   119,  55, 118,  54, 117,  53, 116,  52, 115,  51, 114,  50, 113,  49, 112,  48,
+                                   111,  47, 110,  46, 109,  45, 108,  44, 107,  43, 106,  42, 105,  41, 104,  40,
+                                   103,  39, 102,  38, 101,  37, 100,  36,  99,  35,  98,  34,  97,  33,  96,  32);
+    ab1 = v_int8x64(_mm512_permutex2var_epi8(a.val, mask1, b.val));
+#else
+    __m512i low  = _mm512_unpacklo_epi8(a.val, b.val);
+    __m512i high = _mm512_unpackhi_epi8(a.val, b.val);
+    ab0 = v_int8x64(_mm512_permutex2var_epi64(low, _v512_set_epu64(11, 10, 3, 2,  9,  8, 1, 0), high));
+    ab1 = v_int8x64(_mm512_permutex2var_epi64(low, _v512_set_epu64(15, 14, 7, 6, 13, 12, 5, 4), high));
+#endif
+}
+inline void v_zip(const v_int16x32& a, const v_int16x32& b, v_int16x32& ab0, v_int16x32& ab1)
+{
+    __m512i mask0 = _v512_set_epu16(47, 15, 46, 14, 45, 13, 44, 12, 43, 11, 42, 10, 41,  9, 40,  8,
+                                    39,  7, 38,  6, 37,  5, 36,  4, 35,  3, 34,  2, 33,  1, 32,  0);
+    ab0 = v_int16x32(_mm512_permutex2var_epi16(a.val, mask0, b.val));
+    __m512i mask1 = _v512_set_epu16(63, 31, 62, 30, 61, 29, 60, 28, 59, 27, 58, 26, 57, 25, 56, 24,
+                                    55, 23, 54, 22, 53, 21, 52, 20, 51, 19, 50, 18, 49, 17, 48, 16);
+    ab1 = v_int16x32(_mm512_permutex2var_epi16(a.val, mask1, b.val));
+}
+inline void v_zip(const v_int32x16& a, const v_int32x16& b, v_int32x16& ab0, v_int32x16& ab1)
+{
+    __m512i mask0 = _v512_set_epu32(23,  7, 22,  6, 21,  5, 20,  4, 19,  3, 18,  2, 17, 1, 16, 0);
+    ab0 = v_int32x16(_mm512_permutex2var_epi32(a.val, mask0, b.val));
+    __m512i mask1 = _v512_set_epu32(31, 15, 30, 14, 29, 13, 28, 12, 27, 11, 26, 10, 25, 9, 24, 8);
+    ab1 = v_int32x16(_mm512_permutex2var_epi32(a.val, mask1, b.val));
+}
+inline void v_zip(const v_int64x8& a, const v_int64x8& b, v_int64x8& ab0, v_int64x8& ab1)
+{
+    __m512i mask0 = _v512_set_epu64(11, 3, 10, 2,  9, 1,  8, 0);
+    ab0 = v_int64x8(_mm512_permutex2var_epi64(a.val, mask0, b.val));
+    __m512i mask1 = _v512_set_epu64(15, 7, 14, 6, 13, 5, 12, 4);
+    ab1 = v_int64x8(_mm512_permutex2var_epi64(a.val, mask1, b.val));
+}
+
+inline void v_zip(const v_uint8x64&  a, const v_uint8x64&  b, v_uint8x64& ab0, v_uint8x64& ab1)
+{
+    v_int8x64 i0, i1;
+    v_zip(v_reinterpret_as_s8(a), v_reinterpret_as_s8(b), i0, i1);
+    ab0 = v_reinterpret_as_u8(i0);
+    ab1 = v_reinterpret_as_u8(i1);
+}
+inline void v_zip(const v_uint16x32&  a, const v_uint16x32&  b, v_uint16x32& ab0, v_uint16x32& ab1)
+{
+    v_int16x32 i0, i1;
+    v_zip(v_reinterpret_as_s16(a), v_reinterpret_as_s16(b), i0, i1);
+    ab0 = v_reinterpret_as_u16(i0);
+    ab1 = v_reinterpret_as_u16(i1);
+}
+inline void v_zip(const v_uint32x16&  a, const v_uint32x16&  b, v_uint32x16& ab0, v_uint32x16& ab1)
+{
+    v_int32x16 i0, i1;
+    v_zip(v_reinterpret_as_s32(a), v_reinterpret_as_s32(b), i0, i1);
+    ab0 = v_reinterpret_as_u32(i0);
+    ab1 = v_reinterpret_as_u32(i1);
+}
+inline void v_zip(const v_uint64x8&  a, const v_uint64x8&  b, v_uint64x8& ab0, v_uint64x8& ab1)
+{
+    v_int64x8 i0, i1;
+    v_zip(v_reinterpret_as_s64(a), v_reinterpret_as_s64(b), i0, i1);
+    ab0 = v_reinterpret_as_u64(i0);
+    ab1 = v_reinterpret_as_u64(i1);
+}
+inline void v_zip(const v_float32x16&  a, const v_float32x16&  b, v_float32x16& ab0, v_float32x16& ab1)
+{
+    v_int32x16 i0, i1;
+    v_zip(v_reinterpret_as_s32(a), v_reinterpret_as_s32(b), i0, i1);
+    ab0 = v_reinterpret_as_f32(i0);
+    ab1 = v_reinterpret_as_f32(i1);
+}
+inline void v_zip(const v_float64x8&  a, const v_float64x8&  b, v_float64x8& ab0, v_float64x8& ab1)
+{
+    v_int64x8 i0, i1;
+    v_zip(v_reinterpret_as_s64(a), v_reinterpret_as_s64(b), i0, i1);
+    ab0 = v_reinterpret_as_f64(i0);
+    ab1 = v_reinterpret_as_f64(i1);
+}
+
+#define OPENCV_HAL_IMPL_AVX512_COMBINE(_Tpvec, suffix)                                    \
+    inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b)                         \
+    { return _Tpvec(_v512_combine(_v512_extract_low(a.val), _v512_extract_low(b.val))); } \
+    inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b)                        \
+    { return _Tpvec(_v512_insert(b.val, _v512_extract_high(a.val))); }                    \
+    inline void v_recombine(const _Tpvec& a, const _Tpvec& b,                             \
+                                  _Tpvec& c, _Tpvec& d)                                   \
+    {                                                                                     \
+        c.val = _v512_combine(_v512_extract_low(a.val),_v512_extract_low(b.val));         \
+        d.val = _v512_insert(b.val,_v512_extract_high(a.val));                            \
+    }
+
+
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_uint8x64,   epi8)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_int8x64,    epi8)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_uint16x32,  epi16)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_int16x32,   epi16)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_uint32x16,  epi32)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_int32x16,   epi32)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_uint64x8,   epi64)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_int64x8,    epi64)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_float32x16, ps)
+OPENCV_HAL_IMPL_AVX512_COMBINE(v_float64x8,  pd)
+
+////////// Arithmetic, bitwise and comparison operations /////////
+
+/* Element-wise binary and unary operations */
+
+/** Non-saturating arithmetics **/
+#define OPENCV_HAL_IMPL_AVX512_BIN_FUNC(func, _Tpvec, intrin) \
+    inline _Tpvec func(const _Tpvec& a, const _Tpvec& b)      \
+    { return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_add_wrap, v_uint8x64, _mm512_add_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_add_wrap, v_int8x64, _mm512_add_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_add_wrap, v_uint16x32, _mm512_add_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_add_wrap, v_int16x32, _mm512_add_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_sub_wrap, v_uint8x64, _mm512_sub_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_sub_wrap, v_int8x64, _mm512_sub_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_sub_wrap, v_uint16x32, _mm512_sub_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_sub_wrap, v_int16x32, _mm512_sub_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_mul_wrap, v_uint16x32, _mm512_mullo_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_mul_wrap, v_int16x32, _mm512_mullo_epi16)
+
+inline v_uint8x64 v_mul_wrap(const v_uint8x64& a, const v_uint8x64& b)
+{
+    __m512i ad = _mm512_srai_epi16(a.val, 8);
+    __m512i bd = _mm512_srai_epi16(b.val, 8);
+    __m512i p0 = _mm512_mullo_epi16(a.val, b.val); // even
+    __m512i p1 = _mm512_slli_epi16(_mm512_mullo_epi16(ad, bd), 8); // odd
+    return v_uint8x64(_mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, p0, p1));
+}
+inline v_int8x64 v_mul_wrap(const v_int8x64& a, const v_int8x64& b)
+{
+    return v_reinterpret_as_s8(v_mul_wrap(v_reinterpret_as_u8(a), v_reinterpret_as_u8(b)));
+}
+
+#define OPENCV_HAL_IMPL_AVX512_BIN_OP(bin_op, _Tpvec, intrin)            \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)               \
+    { return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_uint32x16, _mm512_add_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_uint32x16, _mm512_sub_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_int32x16, _mm512_add_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_int32x16, _mm512_sub_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_uint64x8, _mm512_add_epi64)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_uint64x8, _mm512_sub_epi64)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_int64x8, _mm512_add_epi64)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_int64x8, _mm512_sub_epi64)
+
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_mul, v_uint32x16, _mm512_mullo_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_mul, v_int32x16, _mm512_mullo_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_mul, v_uint64x8, _mm512_mullo_epi64)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_mul, v_int64x8, _mm512_mullo_epi64)
+
+/** Saturating arithmetics **/
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_uint8x64,  _mm512_adds_epu8)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_uint8x64,  _mm512_subs_epu8)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_int8x64,   _mm512_adds_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_int8x64,   _mm512_subs_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_uint16x32, _mm512_adds_epu16)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_uint16x32, _mm512_subs_epu16)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_int16x32,  _mm512_adds_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_int16x32,  _mm512_subs_epi16)
+
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_float32x16, _mm512_add_ps)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_float32x16, _mm512_sub_ps)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_mul, v_float32x16, _mm512_mul_ps)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_div, v_float32x16, _mm512_div_ps)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_add, v_float64x8, _mm512_add_pd)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_sub, v_float64x8, _mm512_sub_pd)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_mul, v_float64x8, _mm512_mul_pd)
+OPENCV_HAL_IMPL_AVX512_BIN_OP(v_div, v_float64x8, _mm512_div_pd)
+
+// saturating multiply
+inline v_uint8x64 v_mul(const v_uint8x64& a, const v_uint8x64& b)
+{
+    v_uint16x32 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_int8x64 v_mul(const v_int8x64& a, const v_int8x64& b)
+{
+    v_int16x32 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_uint16x32 v_mul(const v_uint16x32& a, const v_uint16x32& b)
+{
+    __m512i pl = _mm512_mullo_epi16(a.val, b.val);
+    __m512i ph = _mm512_mulhi_epu16(a.val, b.val);
+    __m512i p0 = _mm512_unpacklo_epi16(pl, ph);
+    __m512i p1 = _mm512_unpackhi_epi16(pl, ph);
+
+    const __m512i m = _mm512_set1_epi32(65535);
+    return v_uint16x32(_mm512_packus_epi32(_mm512_min_epu32(p0, m), _mm512_min_epu32(p1, m)));
+}
+inline v_int16x32 v_mul(const v_int16x32& a, const v_int16x32& b)
+{
+    __m512i pl = _mm512_mullo_epi16(a.val, b.val);
+    __m512i ph = _mm512_mulhi_epi16(a.val, b.val);
+    __m512i p0 = _mm512_unpacklo_epi16(pl, ph);
+    __m512i p1 = _mm512_unpackhi_epi16(pl, ph);
+    return v_int16x32(_mm512_packs_epi32(p0, p1));
+}
+
+inline v_int16x32 v_mul_hi(const v_int16x32& a, const v_int16x32& b) { return v_int16x32(_mm512_mulhi_epi16(a.val, b.val)); }
+inline v_uint16x32 v_mul_hi(const v_uint16x32& a, const v_uint16x32& b) { return v_uint16x32(_mm512_mulhi_epu16(a.val, b.val)); }
+
+//  Multiply and expand
+inline void v_mul_expand(const v_uint8x64& a, const v_uint8x64& b,
+                         v_uint16x32& c, v_uint16x32& d)
+{
+    v_uint16x32 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int8x64& a, const v_int8x64& b,
+                         v_int16x32& c, v_int16x32& d)
+{
+    v_int16x32 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int16x32& a, const v_int16x32& b,
+                         v_int32x16& c, v_int32x16& d)
+{
+    v_int16x32 v0, v1;
+    v_zip(v_mul_wrap(a, b), v_mul_hi(a, b), v0, v1);
+
+    c = v_reinterpret_as_s32(v0);
+    d = v_reinterpret_as_s32(v1);
+}
+
+inline void v_mul_expand(const v_uint16x32& a, const v_uint16x32& b,
+                         v_uint32x16& c, v_uint32x16& d)
+{
+    v_uint16x32 v0, v1;
+    v_zip(v_mul_wrap(a, b), v_mul_hi(a, b), v0, v1);
+
+    c = v_reinterpret_as_u32(v0);
+    d = v_reinterpret_as_u32(v1);
+}
+
+inline void v_mul_expand(const v_uint32x16& a, const v_uint32x16& b,
+                         v_uint64x8& c, v_uint64x8& d)
+{
+    v_zip(v_uint64x8(_mm512_mul_epu32(a.val, b.val)),
+          v_uint64x8(_mm512_mul_epu32(_mm512_srli_epi64(a.val, 32), _mm512_srli_epi64(b.val, 32))), c, d);
+}
+
+inline void v_mul_expand(const v_int32x16& a, const v_int32x16& b,
+    v_int64x8& c, v_int64x8& d)
+{
+    v_zip(v_int64x8(_mm512_mul_epi32(a.val, b.val)),
+          v_int64x8(_mm512_mul_epi32(_mm512_srli_epi64(a.val, 32), _mm512_srli_epi64(b.val, 32))), c, d);
+}
+
+/** Bitwise shifts **/
+#define OPENCV_HAL_IMPL_AVX512_SHIFT_OP(_Tpuvec, _Tpsvec, suffix) \
+    inline _Tpuvec v_shl(const _Tpuvec& a, int imm)               \
+    { return _Tpuvec(_mm512_slli_##suffix(a.val, imm)); }         \
+    inline _Tpsvec v_shl(const _Tpsvec& a, int imm)               \
+    { return _Tpsvec(_mm512_slli_##suffix(a.val, imm)); }         \
+    inline _Tpuvec v_shr(const _Tpuvec& a, int imm)               \
+    { return _Tpuvec(_mm512_srli_##suffix(a.val, imm)); }         \
+    inline _Tpsvec v_shr(const _Tpsvec& a, int imm)               \
+    { return _Tpsvec(_mm512_srai_##suffix(a.val, imm)); }         \
+    template<int imm>                                             \
+    inline _Tpuvec v_shl(const _Tpuvec& a)                        \
+    { return _Tpuvec(_mm512_slli_##suffix(a.val, imm)); }         \
+    template<int imm>                                             \
+    inline _Tpsvec v_shl(const _Tpsvec& a)                        \
+    { return _Tpsvec(_mm512_slli_##suffix(a.val, imm)); }         \
+    template<int imm>                                             \
+    inline _Tpuvec v_shr(const _Tpuvec& a)                        \
+    { return _Tpuvec(_mm512_srli_##suffix(a.val, imm)); }         \
+    template<int imm>                                             \
+    inline _Tpsvec v_shr(const _Tpsvec& a)                        \
+    { return _Tpsvec(_mm512_srai_##suffix(a.val, imm)); }
+
+OPENCV_HAL_IMPL_AVX512_SHIFT_OP(v_uint16x32, v_int16x32, epi16)
+OPENCV_HAL_IMPL_AVX512_SHIFT_OP(v_uint32x16, v_int32x16, epi32)
+OPENCV_HAL_IMPL_AVX512_SHIFT_OP(v_uint64x8,  v_int64x8,  epi64)
+
+
+/** Bitwise logic **/
+#define OPENCV_HAL_IMPL_AVX512_LOGIC_OP(_Tpvec, suffix, not_const) \
+    OPENCV_HAL_IMPL_AVX512_BIN_OP(v_and, _Tpvec, _mm512_and_##suffix)  \
+    OPENCV_HAL_IMPL_AVX512_BIN_OP(v_or, _Tpvec, _mm512_or_##suffix)    \
+    OPENCV_HAL_IMPL_AVX512_BIN_OP(v_xor, _Tpvec, _mm512_xor_##suffix)  \
+    inline _Tpvec v_not(const _Tpvec& a)                               \
+    { return _Tpvec(_mm512_xor_##suffix(a.val, not_const)); }
+
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_uint8x64,   si512, _mm512_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_int8x64,    si512, _mm512_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_uint16x32,  si512, _mm512_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_int16x32,   si512, _mm512_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_uint32x16,  si512, _mm512_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_int32x16,   si512, _mm512_set1_epi32(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_uint64x8,   si512, _mm512_set1_epi64(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_int64x8,    si512, _mm512_set1_epi64(-1))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_float32x16, ps,    _mm512_castsi512_ps(_mm512_set1_epi32(-1)))
+OPENCV_HAL_IMPL_AVX512_LOGIC_OP(v_float64x8,  pd,    _mm512_castsi512_pd(_mm512_set1_epi32(-1)))
+
+/** Select **/
+#define OPENCV_HAL_IMPL_AVX512_SELECT(_Tpvec, suffix, zsuf)                      \
+    inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+    { return _Tpvec(_mm512_mask_blend_##suffix(_mm512_cmp_##suffix##_mask(mask.val, _mm512_setzero_##zsuf(), _MM_CMPINT_EQ), a.val, b.val)); }
+
+OPENCV_HAL_IMPL_AVX512_SELECT(v_uint8x64,   epi8, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_int8x64,    epi8, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_uint16x32, epi16, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_int16x32,  epi16, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_uint32x16, epi32, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_int32x16,  epi32, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_uint64x8,  epi64, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_int64x8,   epi64, si512)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_float32x16,   ps,    ps)
+OPENCV_HAL_IMPL_AVX512_SELECT(v_float64x8,    pd,    pd)
+
+/** Comparison **/
+#define OPENCV_HAL_IMPL_AVX512_CMP_INT(bin_op, imm8, _Tpvec, sufcmp, sufset, tval) \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)                         \
+    { return _Tpvec(_mm512_maskz_set1_##sufset(_mm512_cmp_##sufcmp##_mask(a.val, b.val, imm8), tval)); }
+
+#define OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(_Tpvec, sufcmp, sufset, tval)              \
+    OPENCV_HAL_IMPL_AVX512_CMP_INT(v_eq, _MM_CMPINT_EQ,  _Tpvec, sufcmp, sufset, tval)  \
+    OPENCV_HAL_IMPL_AVX512_CMP_INT(v_ne, _MM_CMPINT_NE,  _Tpvec, sufcmp, sufset, tval)  \
+    OPENCV_HAL_IMPL_AVX512_CMP_INT(v_lt,  _MM_CMPINT_LT,  _Tpvec, sufcmp, sufset, tval) \
+    OPENCV_HAL_IMPL_AVX512_CMP_INT(v_gt,  _MM_CMPINT_NLE, _Tpvec, sufcmp, sufset, tval) \
+    OPENCV_HAL_IMPL_AVX512_CMP_INT(v_le, _MM_CMPINT_LE,  _Tpvec, sufcmp, sufset, tval)  \
+    OPENCV_HAL_IMPL_AVX512_CMP_INT(v_ge, _MM_CMPINT_NLT, _Tpvec, sufcmp, sufset, tval)
+
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_uint8x64,   epu8,  epi8, (char)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_int8x64,    epi8,  epi8, (char)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_uint16x32, epu16, epi16, (short)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_int16x32,  epi16, epi16, (short)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_uint32x16, epu32, epi32, (int)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_int32x16,  epi32, epi32, (int)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_uint64x8,  epu64, epi64, (int64)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_INT(v_int64x8,   epi64, epi64, (int64)-1)
+
+#define OPENCV_HAL_IMPL_AVX512_CMP_FLT(bin_op, imm8, _Tpvec, sufcmp, sufset, tval) \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)                        \
+    { return _Tpvec(_mm512_castsi512_##sufcmp(_mm512_maskz_set1_##sufset(_mm512_cmp_##sufcmp##_mask(a.val, b.val, imm8), tval))); }
+
+#define OPENCV_HAL_IMPL_AVX512_CMP_OP_FLT(_Tpvec, sufcmp, sufset, tval)           \
+    OPENCV_HAL_IMPL_AVX512_CMP_FLT(v_eq, _CMP_EQ_OQ,  _Tpvec, sufcmp, sufset, tval)  \
+    OPENCV_HAL_IMPL_AVX512_CMP_FLT(v_ne, _CMP_NEQ_OQ, _Tpvec, sufcmp, sufset, tval)  \
+    OPENCV_HAL_IMPL_AVX512_CMP_FLT(v_lt,  _CMP_LT_OQ,  _Tpvec, sufcmp, sufset, tval) \
+    OPENCV_HAL_IMPL_AVX512_CMP_FLT(v_gt,  _CMP_GT_OQ,  _Tpvec, sufcmp, sufset, tval) \
+    OPENCV_HAL_IMPL_AVX512_CMP_FLT(v_le, _CMP_LE_OQ,  _Tpvec, sufcmp, sufset, tval)  \
+    OPENCV_HAL_IMPL_AVX512_CMP_FLT(v_ge, _CMP_GE_OQ,  _Tpvec, sufcmp, sufset, tval)
+
+OPENCV_HAL_IMPL_AVX512_CMP_OP_FLT(v_float32x16, ps, epi32, (int)-1)
+OPENCV_HAL_IMPL_AVX512_CMP_OP_FLT(v_float64x8,  pd, epi64, (int64)-1)
+
+inline v_float32x16 v_not_nan(const v_float32x16& a)
+{ return v_float32x16(_mm512_castsi512_ps(_mm512_maskz_set1_epi32(_mm512_cmp_ps_mask(a.val, a.val, _CMP_ORD_Q), (int)-1))); }
+inline v_float64x8 v_not_nan(const v_float64x8& a)
+{ return v_float64x8(_mm512_castsi512_pd(_mm512_maskz_set1_epi64(_mm512_cmp_pd_mask(a.val, a.val, _CMP_ORD_Q), (int64)-1))); }
+
+/** min/max **/
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_uint8x64,   _mm512_min_epu8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_uint8x64,   _mm512_max_epu8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_int8x64,    _mm512_min_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_int8x64,    _mm512_max_epi8)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_uint16x32,  _mm512_min_epu16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_uint16x32,  _mm512_max_epu16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_int16x32,   _mm512_min_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_int16x32,   _mm512_max_epi16)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_uint32x16,  _mm512_min_epu32)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_uint32x16,  _mm512_max_epu32)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_int32x16,   _mm512_min_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_int32x16,   _mm512_max_epi32)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_uint64x8,   _mm512_min_epu64)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_uint64x8,   _mm512_max_epu64)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_int64x8,    _mm512_min_epi64)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_int64x8,    _mm512_max_epi64)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_float32x16, _mm512_min_ps)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_float32x16, _mm512_max_ps)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_min, v_float64x8,  _mm512_min_pd)
+OPENCV_HAL_IMPL_AVX512_BIN_FUNC(v_max, v_float64x8,  _mm512_max_pd)
+
+/** Rotate **/
+namespace {
+    template<bool prec, int imm4, bool part, int imm32>
+    struct _v_rotate_right { static inline v_int8x64 eval(const v_int8x64&, const v_int8x64&) { return v_int8x64(); }};
+    template<int imm4, int imm32>
+    struct _v_rotate_right<true, imm4, false, imm32> { static inline v_int8x64 eval(const v_int8x64& a, const v_int8x64& b)
+    {
+        return v_int8x64(_mm512_or_si512(_mm512_srli_epi32(_mm512_alignr_epi32(b.val, a.val, imm32    ),    imm4 *8),
+                                         _mm512_slli_epi32(_mm512_alignr_epi32(b.val, a.val, imm32 + 1), (4-imm4)*8)));
+    }};
+    template<int imm4>
+    struct _v_rotate_right<true, imm4, false, 15> { static inline v_int8x64 eval(const v_int8x64& a, const v_int8x64& b)
+    {
+        return v_int8x64(_mm512_or_si512(_mm512_srli_epi32(_mm512_alignr_epi32(b.val, a.val, 15),    imm4 *8),
+                                         _mm512_slli_epi32(                                b.val, (4-imm4)*8)));
+    }};
+    template<int imm4, int imm32>
+    struct _v_rotate_right<true, imm4, true, imm32> { static inline v_int8x64 eval(const v_int8x64&, const v_int8x64& b)
+    {
+        return v_int8x64(_mm512_or_si512(_mm512_srli_epi32(_mm512_alignr_epi32(_mm512_setzero_si512(), b.val, imm32 - 16),    imm4 *8),
+                                         _mm512_slli_epi32(_mm512_alignr_epi32(_mm512_setzero_si512(), b.val, imm32 - 15), (4-imm4)*8)));
+    }};
+    template<int imm4>
+    struct _v_rotate_right<true, imm4, true, 31> { static inline v_int8x64 eval(const v_int8x64&, const v_int8x64& b)
+    { return v_int8x64(_mm512_srli_epi32(_mm512_alignr_epi32(_mm512_setzero_si512(), b.val, 15), imm4*8)); }};
+    template<int imm32>
+    struct _v_rotate_right<false, 0, false, imm32> { static inline v_int8x64 eval(const v_int8x64& a, const v_int8x64& b)
+    { return v_int8x64(_mm512_alignr_epi32(b.val, a.val, imm32)); }};
+    template<>
+    struct _v_rotate_right<false, 0, false, 0> { static inline v_int8x64 eval(const v_int8x64& a, const v_int8x64&) { return a; }};
+    template<int imm32>
+    struct _v_rotate_right<false, 0, true, imm32> { static inline v_int8x64 eval(const v_int8x64&, const v_int8x64& b)
+    { return v_int8x64(_mm512_alignr_epi32(_mm512_setzero_si512(), b.val, imm32 - 16)); }};
+    template<>
+    struct _v_rotate_right<false, 0, true, 16> { static inline v_int8x64 eval(const v_int8x64&, const v_int8x64& b) { return b; }};
+    template<>
+    struct _v_rotate_right<false, 0, true, 32> { static inline v_int8x64 eval(const v_int8x64&, const v_int8x64&) { return v_int8x64(); }};
+}
+template<int imm> inline v_int8x64 v_rotate_right(const v_int8x64& a, const v_int8x64& b)
+{
+    return imm >= 128 ? v_int8x64() :
+#if CV_AVX_512VBMI
+    v_int8x64(_mm512_permutex2var_epi8(a.val,
+    _v512_set_epu8(0x3f + imm, 0x3e + imm, 0x3d + imm, 0x3c + imm, 0x3b + imm, 0x3a + imm, 0x39 + imm, 0x38 + imm,
+                   0x37 + imm, 0x36 + imm, 0x35 + imm, 0x34 + imm, 0x33 + imm, 0x32 + imm, 0x31 + imm, 0x30 + imm,
+                   0x2f + imm, 0x2e + imm, 0x2d + imm, 0x2c + imm, 0x2b + imm, 0x2a + imm, 0x29 + imm, 0x28 + imm,
+                   0x27 + imm, 0x26 + imm, 0x25 + imm, 0x24 + imm, 0x23 + imm, 0x22 + imm, 0x21 + imm, 0x20 + imm,
+                   0x1f + imm, 0x1e + imm, 0x1d + imm, 0x1c + imm, 0x1b + imm, 0x1a + imm, 0x19 + imm, 0x18 + imm,
+                   0x17 + imm, 0x16 + imm, 0x15 + imm, 0x14 + imm, 0x13 + imm, 0x12 + imm, 0x11 + imm, 0x10 + imm,
+                   0x0f + imm, 0x0e + imm, 0x0d + imm, 0x0c + imm, 0x0b + imm, 0x0a + imm, 0x09 + imm, 0x08 + imm,
+                   0x07 + imm, 0x06 + imm, 0x05 + imm, 0x04 + imm, 0x03 + imm, 0x02 + imm, 0x01 + imm, 0x00 + imm), b.val));
+#else
+    _v_rotate_right<imm%4!=0, imm%4, (imm/4 > 15), imm/4>::eval(a, b);
+#endif
+}
+template<int imm>
+inline v_int8x64 v_rotate_left(const v_int8x64& a, const v_int8x64& b)
+{
+    if (imm == 0) return a;
+    if (imm == 64) return b;
+    if (imm >= 128) return v_int8x64();
+#if CV_AVX_512VBMI
+    return v_int8x64(_mm512_permutex2var_epi8(b.val,
+           _v512_set_epi8(0x7f - imm,0x7e - imm,0x7d - imm,0x7c - imm,0x7b - imm,0x7a - imm,0x79 - imm,0x78 - imm,
+                          0x77 - imm,0x76 - imm,0x75 - imm,0x74 - imm,0x73 - imm,0x72 - imm,0x71 - imm,0x70 - imm,
+                          0x6f - imm,0x6e - imm,0x6d - imm,0x6c - imm,0x6b - imm,0x6a - imm,0x69 - imm,0x68 - imm,
+                          0x67 - imm,0x66 - imm,0x65 - imm,0x64 - imm,0x63 - imm,0x62 - imm,0x61 - imm,0x60 - imm,
+                          0x5f - imm,0x5e - imm,0x5d - imm,0x5c - imm,0x5b - imm,0x5a - imm,0x59 - imm,0x58 - imm,
+                          0x57 - imm,0x56 - imm,0x55 - imm,0x54 - imm,0x53 - imm,0x52 - imm,0x51 - imm,0x50 - imm,
+                          0x4f - imm,0x4e - imm,0x4d - imm,0x4c - imm,0x4b - imm,0x4a - imm,0x49 - imm,0x48 - imm,
+                          0x47 - imm,0x46 - imm,0x45 - imm,0x44 - imm,0x43 - imm,0x42 - imm,0x41 - imm,0x40 - imm), a.val));
+#else
+    return imm < 64 ? v_rotate_right<64 - imm>(b, a) : v_rotate_right<128 - imm>(v512_setzero_s8(), b);
+#endif
+}
+template<int imm>
+inline v_int8x64 v_rotate_right(const v_int8x64& a)
+{
+    if (imm == 0) return a;
+    if (imm >= 64) return v_int8x64();
+#if CV_AVX_512VBMI
+    return v_int8x64(_mm512_maskz_permutexvar_epi8(0xFFFFFFFFFFFFFFFF >> imm,
+           _v512_set_epu8(0x3f + imm,0x3e + imm,0x3d + imm,0x3c + imm,0x3b + imm,0x3a + imm,0x39 + imm,0x38 + imm,
+                          0x37 + imm,0x36 + imm,0x35 + imm,0x34 + imm,0x33 + imm,0x32 + imm,0x31 + imm,0x30 + imm,
+                          0x2f + imm,0x2e + imm,0x2d + imm,0x2c + imm,0x2b + imm,0x2a + imm,0x29 + imm,0x28 + imm,
+                          0x27 + imm,0x26 + imm,0x25 + imm,0x24 + imm,0x23 + imm,0x22 + imm,0x21 + imm,0x20 + imm,
+                          0x1f + imm,0x1e + imm,0x1d + imm,0x1c + imm,0x1b + imm,0x1a + imm,0x19 + imm,0x18 + imm,
+                          0x17 + imm,0x16 + imm,0x15 + imm,0x14 + imm,0x13 + imm,0x12 + imm,0x11 + imm,0x10 + imm,
+                          0x0f + imm,0x0e + imm,0x0d + imm,0x0c + imm,0x0b + imm,0x0a + imm,0x09 + imm,0x08 + imm,
+                          0x07 + imm,0x06 + imm,0x05 + imm,0x04 + imm,0x03 + imm,0x02 + imm,0x01 + imm,0x00 + imm), a.val));
+#else
+    return v_rotate_right<imm>(a, v512_setzero_s8());
+#endif
+}
+template<int imm>
+inline v_int8x64 v_rotate_left(const v_int8x64& a)
+{
+    if (imm == 0) return a;
+    if (imm >= 64) return v_int8x64();
+#if CV_AVX_512VBMI
+    return v_int8x64(_mm512_maskz_permutexvar_epi8(0xFFFFFFFFFFFFFFFF << imm,
+           _v512_set_epi8(0x3f - imm,0x3e - imm,0x3d - imm,0x3c - imm,0x3b - imm,0x3a - imm,0x39 - imm,0x38 - imm,
+                          0x37 - imm,0x36 - imm,0x35 - imm,0x34 - imm,0x33 - imm,0x32 - imm,0x31 - imm,0x30 - imm,
+                          0x2f - imm,0x2e - imm,0x2d - imm,0x2c - imm,0x2b - imm,0x2a - imm,0x29 - imm,0x28 - imm,
+                          0x27 - imm,0x26 - imm,0x25 - imm,0x24 - imm,0x23 - imm,0x22 - imm,0x21 - imm,0x20 - imm,
+                          0x1f - imm,0x1e - imm,0x1d - imm,0x1c - imm,0x1b - imm,0x1a - imm,0x19 - imm,0x18 - imm,
+                          0x17 - imm,0x16 - imm,0x15 - imm,0x14 - imm,0x13 - imm,0x12 - imm,0x11 - imm,0x10 - imm,
+                          0x0f - imm,0x0e - imm,0x0d - imm,0x0c - imm,0x0b - imm,0x0a - imm,0x09 - imm,0x08 - imm,
+                          0x07 - imm,0x06 - imm,0x05 - imm,0x04 - imm,0x03 - imm,0x02 - imm,0x01 - imm,0x00 - imm), a.val));
+#else
+    return v_rotate_right<64 - imm>(v512_setzero_s8(), a);
+#endif
+}
+
+#define OPENCV_HAL_IMPL_AVX512_ROTATE_PM(_Tpvec, suffix)                                                                                   \
+template<int imm> inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b)                                                            \
+{ return v_reinterpret_as_##suffix(v_rotate_left<imm * sizeof(_Tpvec::lane_type)>(v_reinterpret_as_s8(a), v_reinterpret_as_s8(b))); }      \
+template<int imm> inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b)                                                           \
+{ return v_reinterpret_as_##suffix(v_rotate_right<imm * sizeof(_Tpvec::lane_type)>(v_reinterpret_as_s8(a), v_reinterpret_as_s8(b))); }     \
+template<int imm> inline _Tpvec v_rotate_left(const _Tpvec& a)                                                                             \
+{ return v_reinterpret_as_##suffix(v_rotate_left<imm * sizeof(_Tpvec::lane_type)>(v_reinterpret_as_s8(a))); }                              \
+template<int imm> inline _Tpvec v_rotate_right(const _Tpvec& a)                                                                            \
+{ return v_reinterpret_as_##suffix(v_rotate_right<imm * sizeof(_Tpvec::lane_type)>(v_reinterpret_as_s8(a))); }
+
+#define OPENCV_HAL_IMPL_AVX512_ROTATE_EC(_Tpvec, suffix)                                                                                   \
+template<int imm>                                                                                                                          \
+inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b)                                                                              \
+{                                                                                                                                          \
+    enum { SHIFT2 = (_Tpvec::nlanes - imm) };                                                                                              \
+    enum { MASK = ((1 << _Tpvec::nlanes) - 1) };                                                                                           \
+    if (imm == 0) return a;                                                                                                                \
+    if (imm == _Tpvec::nlanes) return b;                                                                                                   \
+    if (imm >= 2*_Tpvec::nlanes) return _Tpvec::zero();                                                                                    \
+    return _Tpvec(_mm512_mask_expand_##suffix(_mm512_maskz_compress_##suffix((MASK << SHIFT2)&MASK, b.val), (MASK << (imm))&MASK, a.val)); \
+}                                                                                                                                          \
+template<int imm>                                                                                                                          \
+inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b)                                                                             \
+{                                                                                                                                          \
+    enum { SHIFT2 = (_Tpvec::nlanes - imm) };                                                                                              \
+    enum { MASK = ((1 << _Tpvec::nlanes) - 1) };                                                                                           \
+    if (imm == 0) return a;                                                                                                                \
+    if (imm == _Tpvec::nlanes) return b;                                                                                                   \
+    if (imm >= 2*_Tpvec::nlanes) return _Tpvec::zero();                                                                                    \
+    return _Tpvec(_mm512_mask_expand_##suffix(_mm512_maskz_compress_##suffix((MASK << (imm))&MASK, a.val), (MASK << SHIFT2)&MASK, b.val)); \
+}                                                                                                                                          \
+template<int imm>                                                                                                                          \
+inline _Tpvec v_rotate_left(const _Tpvec& a)                                                                                               \
+{                                                                                                                                          \
+    if (imm == 0) return a;                                                                                                                \
+    if (imm >= _Tpvec::nlanes) return _Tpvec::zero();                                                                                      \
+    return _Tpvec(_mm512_maskz_expand_##suffix((1 << _Tpvec::nlanes) - (1 << (imm)), a.val));                                              \
+}                                                                                                                                          \
+template<int imm>                                                                                                                          \
+inline _Tpvec v_rotate_right(const _Tpvec& a)                                                                                              \
+{                                                                                                                                          \
+    if (imm == 0) return a;                                                                                                                \
+    if (imm >= _Tpvec::nlanes) return _Tpvec::zero();                                                                                      \
+    return _Tpvec(_mm512_maskz_compress_##suffix((1 << _Tpvec::nlanes) - (1 << (imm)), a.val));                                            \
+}
+
+OPENCV_HAL_IMPL_AVX512_ROTATE_PM(v_uint8x64,   u8)
+OPENCV_HAL_IMPL_AVX512_ROTATE_PM(v_uint16x32,  u16)
+OPENCV_HAL_IMPL_AVX512_ROTATE_PM(v_int16x32,   s16)
+OPENCV_HAL_IMPL_AVX512_ROTATE_EC(v_uint32x16,  epi32)
+OPENCV_HAL_IMPL_AVX512_ROTATE_EC(v_int32x16,   epi32)
+OPENCV_HAL_IMPL_AVX512_ROTATE_EC(v_uint64x8,   epi64)
+OPENCV_HAL_IMPL_AVX512_ROTATE_EC(v_int64x8,    epi64)
+OPENCV_HAL_IMPL_AVX512_ROTATE_EC(v_float32x16, ps)
+OPENCV_HAL_IMPL_AVX512_ROTATE_EC(v_float64x8,  pd)
+
+/** Reverse **/
+inline v_uint8x64 v_reverse(const v_uint8x64 &a)
+{
+#if CV_AVX_512VBMI
+    static const __m512i perm = _mm512_set_epi32(
+            0x00010203, 0x04050607, 0x08090a0b, 0x0c0d0e0f,
+            0x10111213, 0x14151617, 0x18191a1b, 0x1c1d1e1f,
+            0x20212223, 0x24252627, 0x28292a2b, 0x2c2d2e2f,
+            0x30313233, 0x34353637, 0x38393a3b, 0x3c3d3e3f);
+    return v_uint8x64(_mm512_permutexvar_epi8(perm, a.val));
+#else
+    static const __m512i shuf = _mm512_set_epi32(
+            0x00010203, 0x04050607, 0x08090a0b, 0x0c0d0e0f,
+            0x00010203, 0x04050607, 0x08090a0b, 0x0c0d0e0f,
+            0x00010203, 0x04050607, 0x08090a0b, 0x0c0d0e0f,
+            0x00010203, 0x04050607, 0x08090a0b, 0x0c0d0e0f);
+    static const __m512i perm = _mm512_set_epi64(1, 0, 3, 2, 5, 4, 7, 6);
+    __m512i vec = _mm512_shuffle_epi8(a.val, shuf);
+    return v_uint8x64(_mm512_permutexvar_epi64(perm, vec));
+#endif
+}
+
+inline v_int8x64 v_reverse(const v_int8x64 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x32 v_reverse(const v_uint16x32 &a)
+{
+#if CV_AVX_512VBMI
+    static const __m512i perm = _mm512_set_epi32(
+            0x00000001, 0x00020003, 0x00040005, 0x00060007,
+            0x00080009, 0x000a000b, 0x000c000d, 0x000e000f,
+            0x00100011, 0x00120013, 0x00140015, 0x00160017,
+            0x00180019, 0x001a001b, 0x001c001d, 0x001e001f);
+    return v_uint16x32(_mm512_permutexvar_epi16(perm, a.val));
+#else
+    static const __m512i shuf = _mm512_set_epi32(
+            0x01000302, 0x05040706, 0x09080b0a, 0x0d0c0f0e,
+            0x01000302, 0x05040706, 0x09080b0a, 0x0d0c0f0e,
+            0x01000302, 0x05040706, 0x09080b0a, 0x0d0c0f0e,
+            0x01000302, 0x05040706, 0x09080b0a, 0x0d0c0f0e);
+    static const __m512i perm = _mm512_set_epi64(1, 0, 3, 2, 5, 4, 7, 6);
+    __m512i vec = _mm512_shuffle_epi8(a.val, shuf);
+    return v_uint16x32(_mm512_permutexvar_epi64(perm, vec));
+#endif
+}
+
+inline v_int16x32 v_reverse(const v_int16x32 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x16 v_reverse(const v_uint32x16 &a)
+{
+    static const __m512i perm = _mm512_set_epi32(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15);
+    return v_uint32x16(_mm512_permutexvar_epi32(perm, a.val));
+}
+
+inline v_int32x16 v_reverse(const v_int32x16 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x16 v_reverse(const v_float32x16 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x8 v_reverse(const v_uint64x8 &a)
+{
+    static const __m512i perm = _mm512_set_epi64(0, 1, 2, 3, 4, 5, 6, 7);
+    return v_uint64x8(_mm512_permutexvar_epi64(perm, a.val));
+}
+
+inline v_int64x8 v_reverse(const v_int64x8 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+inline v_float64x8 v_reverse(const v_float64x8 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+////////// Reduce /////////
+
+/** Reduce **/
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_ADD64(a, b) a + b
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_8(sctype, func, _Tpvec, ifunc, scop)                                          \
+    inline sctype v_reduce_##func(const _Tpvec& a)                                                                  \
+    { __m256i half = _mm256_##ifunc(_v512_extract_low(a.val), _v512_extract_high(a.val));                           \
+      sctype CV_DECL_ALIGNED(64) idx[2];                                                                            \
+      _mm_store_si128((__m128i*)idx, _mm_##ifunc(_mm256_castsi256_si128(half), _mm256_extracti128_si256(half, 1))); \
+      return scop(idx[0], idx[1]); }
+OPENCV_HAL_IMPL_AVX512_REDUCE_8(uint64, min, v_uint64x8, min_epu64, min)
+OPENCV_HAL_IMPL_AVX512_REDUCE_8(uint64, max, v_uint64x8, max_epu64, max)
+OPENCV_HAL_IMPL_AVX512_REDUCE_8(uint64, sum, v_uint64x8, add_epi64, OPENCV_HAL_IMPL_AVX512_REDUCE_ADD64)
+OPENCV_HAL_IMPL_AVX512_REDUCE_8(int64,  min, v_int64x8,  min_epi64, min)
+OPENCV_HAL_IMPL_AVX512_REDUCE_8(int64,  max, v_int64x8,  max_epi64, max)
+OPENCV_HAL_IMPL_AVX512_REDUCE_8(int64,  sum, v_int64x8,  add_epi64, OPENCV_HAL_IMPL_AVX512_REDUCE_ADD64)
+
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_8F(func, ifunc, scop)                                         \
+    inline double v_reduce_##func(const v_float64x8& a)                                             \
+    { __m256d half = _mm256_##ifunc(_v512_extract_low(a.val), _v512_extract_high(a.val));           \
+      double CV_DECL_ALIGNED(64) idx[2];                                                            \
+      _mm_store_pd(idx, _mm_##ifunc(_mm256_castpd256_pd128(half), _mm256_extractf128_pd(half, 1))); \
+      return scop(idx[0], idx[1]); }
+OPENCV_HAL_IMPL_AVX512_REDUCE_8F(min, min_pd, min)
+OPENCV_HAL_IMPL_AVX512_REDUCE_8F(max, max_pd, max)
+OPENCV_HAL_IMPL_AVX512_REDUCE_8F(sum, add_pd, OPENCV_HAL_IMPL_AVX512_REDUCE_ADD64)
+
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_16(sctype, func, _Tpvec, ifunc)                                 \
+    inline sctype v_reduce_##func(const _Tpvec& a)                                                    \
+    { __m256i half = _mm256_##ifunc(_v512_extract_low(a.val), _v512_extract_high(a.val));             \
+      __m128i quarter = _mm_##ifunc(_mm256_castsi256_si128(half), _mm256_extracti128_si256(half, 1)); \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 8));                                     \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 4));                                     \
+      return (sctype)_mm_cvtsi128_si32(quarter); }
+OPENCV_HAL_IMPL_AVX512_REDUCE_16(uint, min, v_uint32x16, min_epu32)
+OPENCV_HAL_IMPL_AVX512_REDUCE_16(uint, max, v_uint32x16, max_epu32)
+OPENCV_HAL_IMPL_AVX512_REDUCE_16(int,  min, v_int32x16,  min_epi32)
+OPENCV_HAL_IMPL_AVX512_REDUCE_16(int,  max, v_int32x16,  max_epi32)
+
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_16F(func, ifunc)                                            \
+    inline float v_reduce_##func(const v_float32x16& a)                                           \
+    { __m256 half = _mm256_##ifunc(_v512_extract_low(a.val), _v512_extract_high(a.val));          \
+      __m128 quarter = _mm_##ifunc(_mm256_castps256_ps128(half), _mm256_extractf128_ps(half, 1)); \
+      quarter = _mm_##ifunc(quarter, _mm_permute_ps(quarter, _MM_SHUFFLE(0, 0, 3, 2)));           \
+      quarter = _mm_##ifunc(quarter, _mm_permute_ps(quarter, _MM_SHUFFLE(0, 0, 0, 1)));           \
+      return _mm_cvtss_f32(quarter); }
+OPENCV_HAL_IMPL_AVX512_REDUCE_16F(min, min_ps)
+OPENCV_HAL_IMPL_AVX512_REDUCE_16F(max, max_ps)
+
+inline float v_reduce_sum(const v_float32x16& a)
+{
+    __m256 half = _mm256_add_ps(_v512_extract_low(a.val), _v512_extract_high(a.val));
+    __m128 quarter = _mm_add_ps(_mm256_castps256_ps128(half), _mm256_extractf128_ps(half, 1));
+    quarter = _mm_hadd_ps(quarter, quarter);
+    return _mm_cvtss_f32(_mm_hadd_ps(quarter, quarter));
+}
+inline int v_reduce_sum(const v_int32x16& a)
+{
+    __m256i half = _mm256_add_epi32(_v512_extract_low(a.val), _v512_extract_high(a.val));
+    __m128i quarter = _mm_add_epi32(_mm256_castsi256_si128(half), _mm256_extracti128_si256(half, 1));
+    quarter = _mm_hadd_epi32(quarter, quarter);
+    return _mm_cvtsi128_si32(_mm_hadd_epi32(quarter, quarter));
+}
+inline uint v_reduce_sum(const v_uint32x16& a)
+{ return (uint)v_reduce_sum(v_reinterpret_as_s32(a)); }
+
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_32(sctype, func, _Tpvec, ifunc)                                 \
+    inline sctype v_reduce_##func(const _Tpvec& a)                                                    \
+    { __m256i half = _mm256_##ifunc(_v512_extract_low(a.val), _v512_extract_high(a.val));             \
+      __m128i quarter = _mm_##ifunc(_mm256_castsi256_si128(half), _mm256_extracti128_si256(half, 1)); \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 8));                                     \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 4));                                     \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 2));                                     \
+      return (sctype)_mm_cvtsi128_si32(quarter); }
+OPENCV_HAL_IMPL_AVX512_REDUCE_32(ushort, min, v_uint16x32, min_epu16)
+OPENCV_HAL_IMPL_AVX512_REDUCE_32(ushort, max, v_uint16x32, max_epu16)
+OPENCV_HAL_IMPL_AVX512_REDUCE_32(short,  min, v_int16x32,  min_epi16)
+OPENCV_HAL_IMPL_AVX512_REDUCE_32(short,  max, v_int16x32,  max_epi16)
+
+inline int v_reduce_sum(const v_int16x32& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+inline uint v_reduce_sum(const v_uint16x32& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_64(sctype, func, _Tpvec, ifunc)                                 \
+    inline sctype v_reduce_##func(const _Tpvec& a)                                                    \
+    { __m256i half = _mm256_##ifunc(_v512_extract_low(a.val), _v512_extract_high(a.val));             \
+      __m128i quarter = _mm_##ifunc(_mm256_castsi256_si128(half), _mm256_extracti128_si256(half, 1)); \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 8));                                     \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 4));                                     \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 2));                                     \
+      quarter = _mm_##ifunc(quarter, _mm_srli_si128(quarter, 1));                                     \
+      return (sctype)_mm_cvtsi128_si32(quarter); }
+OPENCV_HAL_IMPL_AVX512_REDUCE_64(uchar, min, v_uint8x64, min_epu8)
+OPENCV_HAL_IMPL_AVX512_REDUCE_64(uchar, max, v_uint8x64, max_epu8)
+OPENCV_HAL_IMPL_AVX512_REDUCE_64(schar, min, v_int8x64,  min_epi8)
+OPENCV_HAL_IMPL_AVX512_REDUCE_64(schar, max, v_int8x64,  max_epi8)
+
+#define OPENCV_HAL_IMPL_AVX512_REDUCE_64_SUM(sctype, _Tpvec, suffix)                                    \
+    inline sctype v_reduce_sum(const _Tpvec& a)                                                         \
+    {   __m512i a16 = _mm512_add_epi16(_mm512_cvt##suffix##_epi16(_v512_extract_low(a.val)),            \
+                                       _mm512_cvt##suffix##_epi16(_v512_extract_high(a.val)));          \
+        a16 = _mm512_cvtepi16_epi32(_mm256_add_epi16(_v512_extract_low(a16), _v512_extract_high(a16))); \
+        __m256i a8 = _mm256_add_epi32(_v512_extract_low(a16), _v512_extract_high(a16));                 \
+        __m128i a4 = _mm_add_epi32(_mm256_castsi256_si128(a8), _mm256_extracti128_si256(a8, 1));        \
+        a4 = _mm_hadd_epi32(a4, a4);                                                                    \
+        return (sctype)_mm_cvtsi128_si32(_mm_hadd_epi32(a4, a4)); }
+OPENCV_HAL_IMPL_AVX512_REDUCE_64_SUM(uint, v_uint8x64, epu8)
+OPENCV_HAL_IMPL_AVX512_REDUCE_64_SUM(int,  v_int8x64,  epi8)
+
+inline v_float32x16 v_reduce_sum4(const v_float32x16& a, const v_float32x16& b,
+                                  const v_float32x16& c, const v_float32x16& d)
+{
+    __m256 abl = _mm256_hadd_ps(_v512_extract_low(a.val), _v512_extract_low(b.val));
+    __m256 abh = _mm256_hadd_ps(_v512_extract_high(a.val), _v512_extract_high(b.val));
+    __m256 cdl = _mm256_hadd_ps(_v512_extract_low(c.val), _v512_extract_low(d.val));
+    __m256 cdh = _mm256_hadd_ps(_v512_extract_high(c.val), _v512_extract_high(d.val));
+    return v_float32x16(_v512_combine(_mm256_hadd_ps(abl, cdl), _mm256_hadd_ps(abh, cdh)));
+}
+
+inline unsigned v_reduce_sad(const v_uint8x64& a, const v_uint8x64& b)
+{
+    __m512i val = _mm512_sad_epu8(a.val, b.val);
+    __m256i half = _mm256_add_epi32(_v512_extract_low(val), _v512_extract_high(val));
+    __m128i quarter = _mm_add_epi32(_mm256_castsi256_si128(half), _mm256_extracti128_si256(half, 1));
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(quarter, _mm_unpackhi_epi64(quarter, quarter)));
+}
+inline unsigned v_reduce_sad(const v_int8x64& a, const v_int8x64& b)
+{
+    __m512i val = _mm512_set1_epi8(-128);
+    val = _mm512_sad_epu8(_mm512_add_epi8(a.val, val), _mm512_add_epi8(b.val, val));
+    __m256i half = _mm256_add_epi32(_v512_extract_low(val), _v512_extract_high(val));
+    __m128i quarter = _mm_add_epi32(_mm256_castsi256_si128(half), _mm256_extracti128_si256(half, 1));
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(quarter, _mm_unpackhi_epi64(quarter, quarter)));
+}
+inline unsigned v_reduce_sad(const v_uint16x32& a, const v_uint16x32& b)
+{ return v_reduce_sum(v_add_wrap(v_sub(a, b), v_sub(b, a))); }
+inline unsigned v_reduce_sad(const v_int16x32& a, const v_int16x32& b)
+{ return v_reduce_sum(v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b)))); }
+inline unsigned v_reduce_sad(const v_uint32x16& a, const v_uint32x16& b)
+{ return v_reduce_sum(v_sub(v_max(a, b), v_min(a, b))); }
+inline unsigned v_reduce_sad(const v_int32x16& a, const v_int32x16& b)
+{ return v_reduce_sum(v_reinterpret_as_u32(v_sub(v_max(a, b), v_min(a, b)))); }
+inline float v_reduce_sad(const v_float32x16& a, const v_float32x16& b)
+{ return v_reduce_sum(v_and(v_sub(a, b), v_float32x16(_mm512_castsi512_ps(_mm512_set1_epi32(0x7fffffff))))); }
+inline double v_reduce_sad(const v_float64x8& a, const v_float64x8& b)
+{ return v_reduce_sum(v_and(v_sub(a, b), v_float64x8(_mm512_castsi512_pd(_mm512_set1_epi64(0x7fffffffffffffff))))); }
+
+/** Popcount **/
+inline v_uint8x64 v_popcount(const v_int8x64& a)
+{
+#if CV_AVX_512BITALG
+    return v_uint8x64(_mm512_popcnt_epi8(a.val));
+#elif CV_AVX_512VBMI
+    __m512i _popcnt_table0 = _v512_set_epu8(7, 6, 6, 5, 6, 5, 5, 4, 6, 5, 5, 4, 5, 4, 4, 3,
+                                            5, 4, 4, 3, 4, 3, 3, 2, 4, 3, 3, 2, 3, 2, 2, 1,
+                                            5, 4, 4, 3, 4, 3, 3, 2, 4, 3, 3, 2, 3, 2, 2, 1,
+                                            4, 3, 3, 2, 3, 2, 2, 1, 3, 2, 2, 1, 2, 1, 1, 0);
+    __m512i _popcnt_table1 = _v512_set_epu8(7, 6, 6, 5, 6, 5, 5, 4, 6, 5, 5, 4, 5, 4, 4, 3,
+                                            6, 5, 5, 4, 5, 4, 4, 3, 5, 4, 4, 3, 4, 3, 3, 2,
+                                            6, 5, 5, 4, 5, 4, 4, 3, 5, 4, 4, 3, 4, 3, 3, 2,
+                                            5, 4, 4, 3, 4, 3, 3, 2, 4, 3, 3, 2, 3, 2, 2, 1);
+    return v_uint8x64(_mm512_sub_epi8(_mm512_permutex2var_epi8(_popcnt_table0, a.val, _popcnt_table1), _mm512_movm_epi8(_mm512_movepi8_mask(a.val))));
+#else
+    __m512i _popcnt_table = _mm512_set4_epi32(0x04030302, 0x03020201, 0x03020201, 0x02010100);
+    __m512i _popcnt_mask = _mm512_set1_epi8(0x0F);
+
+    return v_uint8x64(_mm512_add_epi8(_mm512_shuffle_epi8(_popcnt_table, _mm512_and_si512(                  a.val,     _popcnt_mask)),
+                                      _mm512_shuffle_epi8(_popcnt_table, _mm512_and_si512(_mm512_srli_epi16(a.val, 4), _popcnt_mask))));
+#endif
+}
+inline v_uint16x32 v_popcount(const v_int16x32& a)
+{
+#if CV_AVX_512BITALG
+    return v_uint16x32(_mm512_popcnt_epi16(a.val));
+#elif CV_AVX_512VPOPCNTDQ
+    __m512i zero = _mm512_setzero_si512();
+    return v_uint16x32(_mm512_packs_epi32(_mm512_popcnt_epi32(_mm512_unpacklo_epi16(a.val, zero)),
+                                          _mm512_popcnt_epi32(_mm512_unpackhi_epi16(a.val, zero))));
+#else
+    v_uint8x64 p = v_popcount(v_reinterpret_as_s8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    return v_and(v_reinterpret_as_u16(p), v512_setall_u16(0x00ff));
+#endif
+}
+inline v_uint32x16 v_popcount(const v_int32x16& a)
+{
+#if CV_AVX_512VPOPCNTDQ
+    return v_uint32x16(_mm512_popcnt_epi32(a.val));
+#else
+    v_uint8x64 p = v_popcount(v_reinterpret_as_s8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    p = v_add(p, v_rotate_right<2>(p));
+    return v_and(v_reinterpret_as_u32(p), v512_setall_u32(0x000000ff));
+#endif
+}
+inline v_uint64x8 v_popcount(const v_int64x8& a)
+{
+#if CV_AVX_512VPOPCNTDQ
+    return v_uint64x8(_mm512_popcnt_epi64(a.val));
+#else
+    return v_uint64x8(_mm512_sad_epu8(v_popcount(v_reinterpret_as_s8(a)).val, _mm512_setzero_si512()));
+#endif
+}
+
+
+inline v_uint8x64  v_popcount(const v_uint8x64&  a) { return v_popcount(v_reinterpret_as_s8 (a)); }
+inline v_uint16x32 v_popcount(const v_uint16x32& a) { return v_popcount(v_reinterpret_as_s16(a)); }
+inline v_uint32x16 v_popcount(const v_uint32x16& a) { return v_popcount(v_reinterpret_as_s32(a)); }
+inline v_uint64x8  v_popcount(const v_uint64x8&  a) { return v_popcount(v_reinterpret_as_s64(a)); }
+
+
+////////// Other math /////////
+
+/** Some frequent operations **/
+#if CV_FMA3
+#define OPENCV_HAL_IMPL_AVX512_MULADD(_Tpvec, suffix)                         \
+    inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)    \
+    { return _Tpvec(_mm512_fmadd_##suffix(a.val, b.val, c.val)); }            \
+    inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \
+    { return _Tpvec(_mm512_fmadd_##suffix(a.val, b.val, c.val)); }
+#else
+#define OPENCV_HAL_IMPL_AVX512_MULADD(_Tpvec, suffix)                                 \
+    inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)            \
+    { return _Tpvec(_mm512_add_##suffix(_mm512_mul_##suffix(a.val, b.val), c.val)); } \
+    inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)         \
+    { return _Tpvec(_mm512_add_##suffix(_mm512_mul_##suffix(a.val, b.val), c.val)); }
+#endif
+
+#define OPENCV_HAL_IMPL_AVX512_MISC(_Tpvec, suffix)                           \
+    inline _Tpvec v_sqrt(const _Tpvec& x)                                     \
+    { return _Tpvec(_mm512_sqrt_##suffix(x.val)); }                           \
+    inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b)           \
+    { return v_fma(a, a, v_mul(b, b)); }                                      \
+    inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b)               \
+    { return v_sqrt(v_fma(a, a, v_mul(b, b))); }
+
+OPENCV_HAL_IMPL_AVX512_MULADD(v_float32x16, ps)
+OPENCV_HAL_IMPL_AVX512_MULADD(v_float64x8,  pd)
+OPENCV_HAL_IMPL_AVX512_MISC(v_float32x16, ps)
+OPENCV_HAL_IMPL_AVX512_MISC(v_float64x8,  pd)
+
+inline v_int32x16 v_fma(const v_int32x16& a, const v_int32x16& b, const v_int32x16& c)
+{ return v_add(v_mul(a, b), c); }
+inline v_int32x16 v_muladd(const v_int32x16& a, const v_int32x16& b, const v_int32x16& c)
+{ return v_fma(a, b, c); }
+
+inline v_float32x16 v_invsqrt(const v_float32x16& x)
+{
+#if CV_AVX_512ER
+    return v_float32x16(_mm512_rsqrt28_ps(x.val));
+#else
+    v_float32x16 half = v_mul(x, v512_setall_f32(0.5));
+    v_float32x16 t  = v_float32x16(_mm512_rsqrt14_ps(x.val));
+    t = v_mul(t, v_sub(v512_setall_f32(1.5), v_mul(v_mul(t, t), half)));
+    return t;
+#endif
+}
+
+inline v_float64x8 v_invsqrt(const v_float64x8& x)
+{
+#if CV_AVX_512ER
+    return v_float64x8(_mm512_rsqrt28_pd(x.val));
+#else
+    return v_div(v512_setall_f64(1.), v_sqrt(x));
+//    v_float64x8 half = x * v512_setall_f64(0.5);
+//    v_float64x8 t = v_float64x8(_mm512_rsqrt14_pd(x.val));
+//    t *= v512_setall_f64(1.5) - ((t * t) * half);
+//    t *= v512_setall_f64(1.5) - ((t * t) * half);
+//    return t;
+#endif
+}
+
+/** Absolute values **/
+#define OPENCV_HAL_IMPL_AVX512_ABS(_Tpvec, _Tpuvec, suffix) \
+    inline _Tpuvec v_abs(const _Tpvec& x)                   \
+    { return _Tpuvec(_mm512_abs_##suffix(x.val)); }
+
+OPENCV_HAL_IMPL_AVX512_ABS(v_int8x64,    v_uint8x64,    epi8)
+OPENCV_HAL_IMPL_AVX512_ABS(v_int16x32,   v_uint16x32,  epi16)
+OPENCV_HAL_IMPL_AVX512_ABS(v_int32x16,   v_uint32x16,  epi32)
+OPENCV_HAL_IMPL_AVX512_ABS(v_int64x8,    v_uint64x8,   epi64)
+
+inline v_float32x16 v_abs(const v_float32x16& x)
+{
+#ifdef _mm512_abs_pd
+    return v_float32x16(_mm512_abs_ps(x.val));
+#else
+    return v_float32x16(_mm512_castsi512_ps(_mm512_and_si512(_mm512_castps_si512(x.val),
+                        _v512_set_epu64(0x7FFFFFFF7FFFFFFF, 0x7FFFFFFF7FFFFFFF, 0x7FFFFFFF7FFFFFFF, 0x7FFFFFFF7FFFFFFF,
+                                        0x7FFFFFFF7FFFFFFF, 0x7FFFFFFF7FFFFFFF, 0x7FFFFFFF7FFFFFFF, 0x7FFFFFFF7FFFFFFF))));
+#endif
+}
+
+inline v_float64x8 v_abs(const v_float64x8& x)
+{
+#ifdef _mm512_abs_pd
+    #if defined __GNUC__ && (__GNUC__ < 7 || (__GNUC__ == 7 && __GNUC_MINOR__ <= 3) || (__GNUC__ == 8 && __GNUC_MINOR__ <= 2))
+        // Workaround for https://gcc.gnu.org/bugzilla/show_bug.cgi?id=87476
+        return v_float64x8(_mm512_abs_pd(_mm512_castpd_ps(x.val)));
+    #else
+        return v_float64x8(_mm512_abs_pd(x.val));
+    #endif
+#else
+    return v_float64x8(_mm512_castsi512_pd(_mm512_and_si512(_mm512_castpd_si512(x.val),
+                       _v512_set_epu64(0x7FFFFFFFFFFFFFFF, 0x7FFFFFFFFFFFFFFF, 0x7FFFFFFFFFFFFFFF, 0x7FFFFFFFFFFFFFFF,
+                                       0x7FFFFFFFFFFFFFFF, 0x7FFFFFFFFFFFFFFF, 0x7FFFFFFFFFFFFFFF, 0x7FFFFFFFFFFFFFFF))));
+#endif
+}
+
+/** Absolute difference **/
+inline v_uint8x64 v_absdiff(const v_uint8x64& a, const v_uint8x64& b)
+{ return v_add_wrap(v_sub(a, b), v_sub(b, a)); }
+inline v_uint16x32 v_absdiff(const v_uint16x32& a, const v_uint16x32& b)
+{ return v_add_wrap(v_sub(a, b), v_sub(b, a)); }
+inline v_uint32x16 v_absdiff(const v_uint32x16& a, const v_uint32x16& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+inline v_uint8x64 v_absdiff(const v_int8x64& a, const v_int8x64& b)
+{
+    v_int8x64 d = v_sub_wrap(a, b);
+    v_int8x64 m = v_lt(a, b);
+    return v_reinterpret_as_u8(v_sub_wrap(v_xor(d, m), m));
+}
+
+inline v_uint16x32 v_absdiff(const v_int16x32& a, const v_int16x32& b)
+{ return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))); }
+
+inline v_uint32x16 v_absdiff(const v_int32x16& a, const v_int32x16& b)
+{
+    v_int32x16 d = v_sub(a, b);
+    v_int32x16 m = v_lt(a, b);
+    return v_reinterpret_as_u32(v_sub(v_xor(d, m), m));
+}
+
+inline v_float32x16 v_absdiff(const v_float32x16& a, const v_float32x16& b)
+{ return v_abs(v_sub(a, b)); }
+
+inline v_float64x8 v_absdiff(const v_float64x8& a, const v_float64x8& b)
+{ return v_abs(v_sub(a, b)); }
+
+/** Saturating absolute difference **/
+inline v_int8x64 v_absdiffs(const v_int8x64& a, const v_int8x64& b)
+{
+    v_int8x64 d = v_sub(a, b);
+    v_int8x64 m = v_lt(a, b);
+    return v_sub(v_xor(d, m), m);
+}
+inline v_int16x32 v_absdiffs(const v_int16x32& a, const v_int16x32& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+////////// Conversions /////////
+
+/** Rounding **/
+inline v_int32x16 v_round(const v_float32x16& a)
+{ return v_int32x16(_mm512_cvtps_epi32(a.val)); }
+
+inline v_int32x16 v_round(const v_float64x8& a)
+{ return v_int32x16(_mm512_castsi256_si512(_mm512_cvtpd_epi32(a.val))); }
+
+inline v_int32x16 v_round(const v_float64x8& a, const v_float64x8& b)
+{ return v_int32x16(_v512_combine(_mm512_cvtpd_epi32(a.val), _mm512_cvtpd_epi32(b.val))); }
+
+inline v_int32x16 v_trunc(const v_float32x16& a)
+{ return v_int32x16(_mm512_cvttps_epi32(a.val)); }
+
+inline v_int32x16 v_trunc(const v_float64x8& a)
+{ return v_int32x16(_mm512_castsi256_si512(_mm512_cvttpd_epi32(a.val))); }
+
+#if CVT_ROUND_MODES_IMPLEMENTED
+inline v_int32x16 v_floor(const v_float32x16& a)
+{ return v_int32x16(_mm512_cvt_roundps_epi32(a.val, _MM_FROUND_TO_NEG_INF | _MM_FROUND_NO_EXC)); }
+
+inline v_int32x16 v_floor(const v_float64x8& a)
+{ return v_int32x16(_mm512_castsi256_si512(_mm512_cvt_roundpd_epi32(a.val, _MM_FROUND_TO_NEG_INF | _MM_FROUND_NO_EXC))); }
+
+inline v_int32x16 v_ceil(const v_float32x16& a)
+{ return v_int32x16(_mm512_cvt_roundps_epi32(a.val, _MM_FROUND_TO_POS_INF | _MM_FROUND_NO_EXC)); }
+
+inline v_int32x16 v_ceil(const v_float64x8& a)
+{ return v_int32x16(_mm512_castsi256_si512(_mm512_cvt_roundpd_epi32(a.val, _MM_FROUND_TO_POS_INF | _MM_FROUND_NO_EXC))); }
+#else
+inline v_int32x16 v_floor(const v_float32x16& a)
+{ return v_int32x16(_mm512_cvtps_epi32(_mm512_roundscale_ps(a.val, 1))); }
+
+inline v_int32x16 v_floor(const v_float64x8& a)
+{ return v_int32x16(_mm512_castsi256_si512(_mm512_cvtpd_epi32(_mm512_roundscale_pd(a.val, 1)))); }
+
+inline v_int32x16 v_ceil(const v_float32x16& a)
+{ return v_int32x16(_mm512_cvtps_epi32(_mm512_roundscale_ps(a.val, 2))); }
+
+inline v_int32x16 v_ceil(const v_float64x8& a)
+{ return v_int32x16(_mm512_castsi256_si512(_mm512_cvtpd_epi32(_mm512_roundscale_pd(a.val, 2)))); }
+#endif
+
+/** To float **/
+inline v_float32x16 v_cvt_f32(const v_int32x16& a)
+{ return v_float32x16(_mm512_cvtepi32_ps(a.val)); }
+
+inline v_float32x16 v_cvt_f32(const v_float64x8& a)
+{ return v_float32x16(_mm512_cvtpd_pslo(a.val)); }
+
+inline v_float32x16 v_cvt_f32(const v_float64x8& a, const v_float64x8& b)
+{ return v_float32x16(_v512_combine(_mm512_cvtpd_ps(a.val), _mm512_cvtpd_ps(b.val))); }
+
+inline v_float64x8 v_cvt_f64(const v_int32x16& a)
+{ return v_float64x8(_mm512_cvtepi32_pd(_v512_extract_low(a.val))); }
+
+inline v_float64x8 v_cvt_f64_high(const v_int32x16& a)
+{ return v_float64x8(_mm512_cvtepi32_pd(_v512_extract_high(a.val))); }
+
+inline v_float64x8 v_cvt_f64(const v_float32x16& a)
+{ return v_float64x8(_mm512_cvtps_pd(_v512_extract_low(a.val))); }
+
+inline v_float64x8 v_cvt_f64_high(const v_float32x16& a)
+{ return v_float64x8(_mm512_cvtps_pd(_v512_extract_high(a.val))); }
+
+// from (Mysticial and wim) https://stackoverflow.com/q/41144668
+inline v_float64x8 v_cvt_f64(const v_int64x8& v)
+{
+#if CV_AVX_512DQ
+    return v_float64x8(_mm512_cvtepi64_pd(v.val));
+#else
+    // constants encoded as floating-point
+    __m512i magic_i_lo   = _mm512_set1_epi64(0x4330000000000000); // 2^52
+    __m512i magic_i_hi32 = _mm512_set1_epi64(0x4530000080000000); // 2^84 + 2^63
+    __m512i magic_i_all  = _mm512_set1_epi64(0x4530000080100000); // 2^84 + 2^63 + 2^52
+    __m512d magic_d_all  = _mm512_castsi512_pd(magic_i_all);
+
+    // Blend the 32 lowest significant bits of v with magic_int_lo
+    __m512i v_lo         = _mm512_mask_blend_epi32(0x5555, magic_i_lo, v.val);
+    // Extract the 32 most significant bits of v
+    __m512i v_hi         = _mm512_srli_epi64(v.val, 32);
+    // Flip the msb of v_hi and blend with 0x45300000
+            v_hi         = _mm512_xor_si512(v_hi, magic_i_hi32);
+    // Compute in double precision
+    __m512d v_hi_dbl     = _mm512_sub_pd(_mm512_castsi512_pd(v_hi), magic_d_all);
+    // (v_hi - magic_d_all) + v_lo  Do not assume associativity of floating point addition
+    __m512d result       = _mm512_add_pd(v_hi_dbl, _mm512_castsi512_pd(v_lo));
+    return v_float64x8(result);
+#endif
+}
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x64 v512_lut(const schar* tab, const int* idx)
+{
+    __m128i p0 = _mm512_cvtepi32_epi8(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx    ), (const int *)tab, 1));
+    __m128i p1 = _mm512_cvtepi32_epi8(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx + 1), (const int *)tab, 1));
+    __m128i p2 = _mm512_cvtepi32_epi8(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx + 2), (const int *)tab, 1));
+    __m128i p3 = _mm512_cvtepi32_epi8(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx + 3), (const int *)tab, 1));
+    return v_int8x64(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_castsi128_si512(p0), p1, 1), p2, 2), p3, 3));
+}
+inline v_int8x64 v512_lut_pairs(const schar* tab, const int* idx)
+{
+    __m256i p0 = _mm512_cvtepi32_epi16(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx    ), (const int *)tab, 1));
+    __m256i p1 = _mm512_cvtepi32_epi16(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx + 1), (const int *)tab, 1));
+    return v_int8x64(_v512_combine(p0, p1));
+}
+inline v_int8x64 v512_lut_quads(const schar* tab, const int* idx)
+{
+    return v_int8x64(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx), (const int *)tab, 1));
+}
+inline v_uint8x64 v512_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v512_lut((const schar *)tab, idx)); }
+inline v_uint8x64 v512_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v512_lut_pairs((const schar *)tab, idx)); }
+inline v_uint8x64 v512_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v512_lut_quads((const schar *)tab, idx)); }
+
+inline v_int16x32 v512_lut(const short* tab, const int* idx)
+{
+    __m256i p0 = _mm512_cvtepi32_epi16(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx    ), (const int *)tab, 2));
+    __m256i p1 = _mm512_cvtepi32_epi16(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx + 1), (const int *)tab, 2));
+    return v_int16x32(_v512_combine(p0, p1));
+}
+inline v_int16x32 v512_lut_pairs(const short* tab, const int* idx)
+{
+    return v_int16x32(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx), (const int *)tab, 2));
+}
+inline v_int16x32 v512_lut_quads(const short* tab, const int* idx)
+{
+#if defined(__GNUC__)
+    return v_int16x32(_mm512_i32gather_epi64(_mm256_loadu_si256((const __m256i*)idx), (const long long int*)tab, 2));
+#else
+    return v_int16x32(_mm512_i32gather_epi64(_mm256_loadu_si256((const __m256i*)idx), (const int64*)tab, 2));
+#endif
+}
+inline v_uint16x32 v512_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v512_lut((const short *)tab, idx)); }
+inline v_uint16x32 v512_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v512_lut_pairs((const short *)tab, idx)); }
+inline v_uint16x32 v512_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v512_lut_quads((const short *)tab, idx)); }
+
+inline v_int32x16 v512_lut(const int* tab, const int* idx)
+{
+    return v_int32x16(_mm512_i32gather_epi32(_mm512_loadu_si512((const __m512i*)idx), tab, 4));
+}
+inline v_int32x16 v512_lut_pairs(const int* tab, const int* idx)
+{
+#if defined(__GNUC__)
+    return v_int32x16(_mm512_i32gather_epi64(_mm256_loadu_si256((const __m256i*)idx), (const long long int*)tab, 4));
+#else
+    return v_int32x16(_mm512_i32gather_epi64(_mm256_loadu_si256((const __m256i*)idx), (const int64*)tab, 4));
+#endif
+}
+inline v_int32x16 v512_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x16(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_castsi128_si512(
+                          _mm_loadu_si128((const __m128i*)(tab + idx[0]))),
+                          _mm_loadu_si128((const __m128i*)(tab + idx[1])), 1),
+                          _mm_loadu_si128((const __m128i*)(tab + idx[2])), 2),
+                          _mm_loadu_si128((const __m128i*)(tab + idx[3])), 3));
+}
+inline v_uint32x16 v512_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v512_lut((const int *)tab, idx)); }
+inline v_uint32x16 v512_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v512_lut_pairs((const int *)tab, idx)); }
+inline v_uint32x16 v512_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v512_lut_quads((const int *)tab, idx)); }
+
+inline v_int64x8 v512_lut(const int64* tab, const int* idx)
+{
+#if defined(__GNUC__)
+    return v_int64x8(_mm512_i32gather_epi64(_mm256_loadu_si256((const __m256i*)idx), (const long long int*)tab, 8));
+#else
+    return v_int64x8(_mm512_i32gather_epi64(_mm256_loadu_si256((const __m256i*)idx), tab , 8));
+#endif
+}
+inline v_int64x8 v512_lut_pairs(const int64* tab, const int* idx)
+{
+    return v_int64x8(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_castsi128_si512(
+                         _mm_loadu_si128((const __m128i*)(tab + idx[0]))),
+                         _mm_loadu_si128((const __m128i*)(tab + idx[1])), 1),
+                         _mm_loadu_si128((const __m128i*)(tab + idx[2])), 2),
+                         _mm_loadu_si128((const __m128i*)(tab + idx[3])), 3));
+}
+inline v_uint64x8 v512_lut(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v512_lut((const int64 *)tab, idx)); }
+inline v_uint64x8 v512_lut_pairs(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v512_lut_pairs((const int64 *)tab, idx)); }
+
+inline v_float32x16 v512_lut(const float* tab, const int* idx)
+{
+    return v_float32x16(_mm512_i32gather_ps(_mm512_loadu_si512((const __m512i*)idx), tab, 4));
+}
+inline v_float32x16 v512_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v512_lut_pairs((const int *)tab, idx)); }
+inline v_float32x16 v512_lut_quads(const float* tab, const int* idx) { return v_reinterpret_as_f32(v512_lut_quads((const int *)tab, idx)); }
+
+inline v_float64x8 v512_lut(const double* tab, const int* idx)
+{
+    return v_float64x8(_mm512_i32gather_pd(_mm256_loadu_si256((const __m256i*)idx), tab, 8));
+}
+inline v_float64x8 v512_lut_pairs(const double* tab, const int* idx)
+{
+        return v_float64x8(_mm512_insertf64x2(_mm512_insertf64x2(_mm512_insertf64x2(_mm512_castpd128_pd512(
+                               _mm_loadu_pd(tab + idx[0])),
+                               _mm_loadu_pd(tab + idx[1]), 1),
+                               _mm_loadu_pd(tab + idx[2]), 2),
+                               _mm_loadu_pd(tab + idx[3]), 3));
+}
+
+inline v_int32x16 v_lut(const int* tab, const v_int32x16& idxvec)
+{
+    return v_int32x16(_mm512_i32gather_epi32(idxvec.val, tab, 4));
+}
+
+inline v_uint32x16 v_lut(const unsigned* tab, const v_int32x16& idxvec)
+{
+    return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec));
+}
+
+inline v_float32x16 v_lut(const float* tab, const v_int32x16& idxvec)
+{
+    return v_float32x16(_mm512_i32gather_ps(idxvec.val, tab, 4));
+}
+
+inline v_float64x8 v_lut(const double* tab, const v_int32x16& idxvec)
+{
+    return v_float64x8(_mm512_i32gather_pd(_v512_extract_low(idxvec.val), tab, 8));
+}
+
+inline void v_lut_deinterleave(const float* tab, const v_int32x16& idxvec, v_float32x16& x, v_float32x16& y)
+{
+    x.val = _mm512_i32gather_ps(idxvec.val, tab, 4);
+    y.val = _mm512_i32gather_ps(idxvec.val, &tab[1], 4);
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x16& idxvec, v_float64x8& x, v_float64x8& y)
+{
+    x.val = _mm512_i32gather_pd(_v512_extract_low(idxvec.val), tab, 8);
+    y.val = _mm512_i32gather_pd(_v512_extract_low(idxvec.val), &tab[1], 8);
+}
+
+inline v_int8x64 v_interleave_pairs(const v_int8x64& vec)
+{
+    return v_int8x64(_mm512_shuffle_epi8(vec.val, _mm512_set4_epi32(0x0f0d0e0c, 0x0b090a08, 0x07050604, 0x03010200)));
+}
+inline v_uint8x64 v_interleave_pairs(const v_uint8x64& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x64 v_interleave_quads(const v_int8x64& vec)
+{
+    return v_int8x64(_mm512_shuffle_epi8(vec.val, _mm512_set4_epi32(0x0f0b0e0a, 0x0d090c08, 0x07030602, 0x05010400)));
+}
+inline v_uint8x64 v_interleave_quads(const v_uint8x64& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x32 v_interleave_pairs(const v_int16x32& vec)
+{
+    return v_int16x32(_mm512_shuffle_epi8(vec.val, _mm512_set4_epi32(0x0f0e0b0a, 0x0d0c0908, 0x07060302, 0x05040100)));
+}
+inline v_uint16x32 v_interleave_pairs(const v_uint16x32& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x32 v_interleave_quads(const v_int16x32& vec)
+{
+    return v_int16x32(_mm512_shuffle_epi8(vec.val, _mm512_set4_epi32(0x0f0e0706, 0x0d0c0504, 0x0b0a0302, 0x09080100)));
+}
+inline v_uint16x32 v_interleave_quads(const v_uint16x32& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x16 v_interleave_pairs(const v_int32x16& vec)
+{
+    return v_int32x16(_mm512_shuffle_epi32(vec.val, _MM_PERM_ACBD));
+}
+inline v_uint32x16 v_interleave_pairs(const v_uint32x16& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x16 v_interleave_pairs(const v_float32x16& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x64 v_pack_triplets(const v_int8x64& vec)
+{
+    return v_int8x64(_mm512_permutexvar_epi32(_v512_set_epu64(0x0000000f0000000f, 0x0000000f0000000f, 0x0000000e0000000d, 0x0000000c0000000a,
+                                                              0x0000000900000008, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000),
+                                              _mm512_shuffle_epi8(vec.val, _mm512_set4_epi32(0xffffff0f, 0x0e0d0c0a, 0x09080605, 0x04020100))));
+}
+inline v_uint8x64 v_pack_triplets(const v_uint8x64& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x32 v_pack_triplets(const v_int16x32& vec)
+{
+    return v_int16x32(_mm512_permutexvar_epi16(_v512_set_epu64(0x001f001f001f001f, 0x001f001f001f001f, 0x001e001d001c001a, 0x0019001800160015,
+                                                               0x0014001200110010, 0x000e000d000c000a, 0x0009000800060005, 0x0004000200010000), vec.val));
+}
+inline v_uint16x32 v_pack_triplets(const v_uint16x32& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x16 v_pack_triplets(const v_int32x16& vec)
+{
+    return v_int32x16(_mm512_permutexvar_epi32(_v512_set_epu64(0x0000000f0000000f, 0x0000000f0000000f, 0x0000000e0000000d, 0x0000000c0000000a,
+                                                               0x0000000900000008, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000), vec.val));
+}
+inline v_uint32x16 v_pack_triplets(const v_uint32x16& vec) { return v_reinterpret_as_u32(v_pack_triplets(v_reinterpret_as_s32(vec))); }
+inline v_float32x16 v_pack_triplets(const v_float32x16& vec)
+{
+    return v_float32x16(_mm512_permutexvar_ps(_v512_set_epu64(0x0000000f0000000f, 0x0000000f0000000f, 0x0000000e0000000d, 0x0000000c0000000a,
+                                                              0x0000000900000008, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000), vec.val));
+}
+
+////////// Matrix operations /////////
+
+//////// Dot Product ////////
+
+// 16 >> 32
+inline v_int32x16 v_dotprod(const v_int16x32& a, const v_int16x32& b)
+{ return v_int32x16(_mm512_madd_epi16(a.val, b.val)); }
+inline v_int32x16 v_dotprod(const v_int16x32& a, const v_int16x32& b, const v_int32x16& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 32 >> 64
+inline v_int64x8 v_dotprod(const v_int32x16& a, const v_int32x16& b)
+{
+    __m512i even = _mm512_mul_epi32(a.val, b.val);
+    __m512i odd = _mm512_mul_epi32(_mm512_srli_epi64(a.val, 32), _mm512_srli_epi64(b.val, 32));
+    return v_int64x8(_mm512_add_epi64(even, odd));
+}
+inline v_int64x8 v_dotprod(const v_int32x16& a, const v_int32x16& b, const v_int64x8& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 8 >> 32
+inline v_uint32x16 v_dotprod_expand(const v_uint8x64& a, const v_uint8x64& b)
+{
+    __m512i even_a = _mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, a.val, _mm512_setzero_si512());
+    __m512i odd_a  = _mm512_srli_epi16(a.val, 8);
+
+    __m512i even_b = _mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, b.val, _mm512_setzero_si512());
+    __m512i odd_b  = _mm512_srli_epi16(b.val, 8);
+
+    __m512i prod0  = _mm512_madd_epi16(even_a, even_b);
+    __m512i prod1  = _mm512_madd_epi16(odd_a, odd_b);
+    return v_uint32x16(_mm512_add_epi32(prod0, prod1));
+}
+inline v_uint32x16 v_dotprod_expand(const v_uint8x64& a, const v_uint8x64& b, const v_uint32x16& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int32x16 v_dotprod_expand(const v_int8x64& a, const v_int8x64& b)
+{
+    __m512i even_a = _mm512_srai_epi16(_mm512_bslli_epi128(a.val, 1), 8);
+    __m512i odd_a  = _mm512_srai_epi16(a.val, 8);
+
+    __m512i even_b = _mm512_srai_epi16(_mm512_bslli_epi128(b.val, 1), 8);
+    __m512i odd_b  = _mm512_srai_epi16(b.val, 8);
+
+    __m512i prod0  = _mm512_madd_epi16(even_a, even_b);
+    __m512i prod1  = _mm512_madd_epi16(odd_a, odd_b);
+    return v_int32x16(_mm512_add_epi32(prod0, prod1));
+}
+inline v_int32x16 v_dotprod_expand(const v_int8x64& a, const v_int8x64& b, const v_int32x16& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x8 v_dotprod_expand(const v_uint16x32& a, const v_uint16x32& b)
+{
+    __m512i mullo = _mm512_mullo_epi16(a.val, b.val);
+    __m512i mulhi = _mm512_mulhi_epu16(a.val, b.val);
+    __m512i mul0  = _mm512_unpacklo_epi16(mullo, mulhi);
+    __m512i mul1  = _mm512_unpackhi_epi16(mullo, mulhi);
+
+    __m512i p02   = _mm512_mask_blend_epi32(0xAAAA, mul0, _mm512_setzero_si512());
+    __m512i p13   = _mm512_srli_epi64(mul0, 32);
+    __m512i p46   = _mm512_mask_blend_epi32(0xAAAA, mul1, _mm512_setzero_si512());
+    __m512i p57   = _mm512_srli_epi64(mul1, 32);
+
+    __m512i p15_  = _mm512_add_epi64(p02, p13);
+    __m512i p9d_  = _mm512_add_epi64(p46, p57);
+
+    return v_uint64x8(_mm512_add_epi64(
+        _mm512_unpacklo_epi64(p15_, p9d_),
+        _mm512_unpackhi_epi64(p15_, p9d_)
+    ));
+}
+inline v_uint64x8 v_dotprod_expand(const v_uint16x32& a, const v_uint16x32& b, const v_uint64x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x8 v_dotprod_expand(const v_int16x32& a, const v_int16x32& b)
+{
+    __m512i prod = _mm512_madd_epi16(a.val, b.val);
+    __m512i even = _mm512_srai_epi64(_mm512_bslli_epi128(prod, 4), 32);
+    __m512i odd  = _mm512_srai_epi64(prod, 32);
+    return v_int64x8(_mm512_add_epi64(even, odd));
+}
+inline v_int64x8 v_dotprod_expand(const v_int16x32& a, const v_int16x32& b, const v_int64x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x8 v_dotprod_expand(const v_int32x16& a, const v_int32x16& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x8 v_dotprod_expand(const v_int32x16& a, const v_int32x16& b, const v_float64x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x16 v_dotprod_fast(const v_int16x32& a, const v_int16x32& b)
+{ return v_dotprod(a, b); }
+inline v_int32x16 v_dotprod_fast(const v_int16x32& a, const v_int16x32& b, const v_int32x16& c)
+{ return v_dotprod(a, b, c); }
+
+// 32 >> 64
+inline v_int64x8 v_dotprod_fast(const v_int32x16& a, const v_int32x16& b)
+{ return v_dotprod(a, b); }
+inline v_int64x8 v_dotprod_fast(const v_int32x16& a, const v_int32x16& b, const v_int64x8& c)
+{ return v_dotprod(a, b, c); }
+
+// 8 >> 32
+inline v_uint32x16 v_dotprod_expand_fast(const v_uint8x64& a, const v_uint8x64& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint32x16 v_dotprod_expand_fast(const v_uint8x64& a, const v_uint8x64& b, const v_uint32x16& c)
+{ return v_dotprod_expand(a, b, c); }
+
+inline v_int32x16 v_dotprod_expand_fast(const v_int8x64& a, const v_int8x64& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int32x16 v_dotprod_expand_fast(const v_int8x64& a, const v_int8x64& b, const v_int32x16& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 16 >> 64
+inline v_uint64x8 v_dotprod_expand_fast(const v_uint16x32& a, const v_uint16x32& b)
+{
+    __m512i mullo = _mm512_mullo_epi16(a.val, b.val);
+    __m512i mulhi = _mm512_mulhi_epu16(a.val, b.val);
+    __m512i mul0  = _mm512_unpacklo_epi16(mullo, mulhi);
+    __m512i mul1  = _mm512_unpackhi_epi16(mullo, mulhi);
+
+    __m512i p02   = _mm512_mask_blend_epi32(0xAAAA, mul0, _mm512_setzero_si512());
+    __m512i p13   = _mm512_srli_epi64(mul0, 32);
+    __m512i p46   = _mm512_mask_blend_epi32(0xAAAA, mul1, _mm512_setzero_si512());
+    __m512i p57   = _mm512_srli_epi64(mul1, 32);
+
+    __m512i p15_  = _mm512_add_epi64(p02, p13);
+    __m512i p9d_  = _mm512_add_epi64(p46, p57);
+    return v_uint64x8(_mm512_add_epi64(p15_, p9d_));
+}
+inline v_uint64x8 v_dotprod_expand_fast(const v_uint16x32& a, const v_uint16x32& b, const v_uint64x8& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+inline v_int64x8 v_dotprod_expand_fast(const v_int16x32& a, const v_int16x32& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int64x8 v_dotprod_expand_fast(const v_int16x32& a, const v_int16x32& b, const v_int64x8& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 32 >> 64f
+inline v_float64x8 v_dotprod_expand_fast(const v_int32x16& a, const v_int32x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_float64x8 v_dotprod_expand_fast(const v_int32x16& a, const v_int32x16& b, const v_float64x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+
+#define OPENCV_HAL_AVX512_SPLAT2_PS(a, im) \
+    v_float32x16(_mm512_permute_ps(a.val, _MM_SHUFFLE(im, im, im, im)))
+
+inline v_float32x16 v_matmul(const v_float32x16& v,
+                             const v_float32x16& m0, const v_float32x16& m1,
+                             const v_float32x16& m2, const v_float32x16& m3)
+{
+    v_float32x16 v04 = OPENCV_HAL_AVX512_SPLAT2_PS(v, 0);
+    v_float32x16 v15 = OPENCV_HAL_AVX512_SPLAT2_PS(v, 1);
+    v_float32x16 v26 = OPENCV_HAL_AVX512_SPLAT2_PS(v, 2);
+    v_float32x16 v37 = OPENCV_HAL_AVX512_SPLAT2_PS(v, 3);
+    return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, v_mul(v37, m3))));
+}
+
+inline v_float32x16 v_matmuladd(const v_float32x16& v,
+                                const v_float32x16& m0, const v_float32x16& m1,
+                                const v_float32x16& m2, const v_float32x16& a)
+{
+    v_float32x16 v04 = OPENCV_HAL_AVX512_SPLAT2_PS(v, 0);
+    v_float32x16 v15 = OPENCV_HAL_AVX512_SPLAT2_PS(v, 1);
+    v_float32x16 v26 = OPENCV_HAL_AVX512_SPLAT2_PS(v, 2);
+    return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, a)));
+}
+
+#define OPENCV_HAL_IMPL_AVX512_TRANSPOSE4x4(_Tpvec, suffix, cast_from, cast_to) \
+    inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1,              \
+                               const _Tpvec& a2, const _Tpvec& a3,              \
+                               _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3)  \
+    {                                                                           \
+        __m512i t0 = cast_from(_mm512_unpacklo_##suffix(a0.val, a1.val));       \
+        __m512i t1 = cast_from(_mm512_unpacklo_##suffix(a2.val, a3.val));       \
+        __m512i t2 = cast_from(_mm512_unpackhi_##suffix(a0.val, a1.val));       \
+        __m512i t3 = cast_from(_mm512_unpackhi_##suffix(a2.val, a3.val));       \
+        b0.val = cast_to(_mm512_unpacklo_epi64(t0, t1));                        \
+        b1.val = cast_to(_mm512_unpackhi_epi64(t0, t1));                        \
+        b2.val = cast_to(_mm512_unpacklo_epi64(t2, t3));                        \
+        b3.val = cast_to(_mm512_unpackhi_epi64(t2, t3));                        \
+    }
+
+OPENCV_HAL_IMPL_AVX512_TRANSPOSE4x4(v_uint32x16,  epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_AVX512_TRANSPOSE4x4(v_int32x16,   epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_AVX512_TRANSPOSE4x4(v_float32x16, ps, _mm512_castps_si512, _mm512_castsi512_ps)
+
+//////////////// Value reordering ///////////////
+
+/* Expand */
+#define OPENCV_HAL_IMPL_AVX512_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin) \
+    inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
+    {                                                               \
+        b0.val = intrin(_v512_extract_low(a.val));                  \
+        b1.val = intrin(_v512_extract_high(a.val));                 \
+    }                                                               \
+    inline _Tpwvec v_expand_low(const _Tpvec& a)                    \
+    { return _Tpwvec(intrin(_v512_extract_low(a.val))); }           \
+    inline _Tpwvec v_expand_high(const _Tpvec& a)                   \
+    { return _Tpwvec(intrin(_v512_extract_high(a.val))); }          \
+    inline _Tpwvec v512_load_expand(const _Tp* ptr)                 \
+    {                                                               \
+        __m256i a = _mm256_loadu_si256((const __m256i*)ptr);        \
+        return _Tpwvec(intrin(a));                                  \
+    }
+
+OPENCV_HAL_IMPL_AVX512_EXPAND(v_uint8x64,  v_uint16x32, uchar,    _mm512_cvtepu8_epi16)
+OPENCV_HAL_IMPL_AVX512_EXPAND(v_int8x64,   v_int16x32,  schar,    _mm512_cvtepi8_epi16)
+OPENCV_HAL_IMPL_AVX512_EXPAND(v_uint16x32, v_uint32x16, ushort,   _mm512_cvtepu16_epi32)
+OPENCV_HAL_IMPL_AVX512_EXPAND(v_int16x32,  v_int32x16,  short,    _mm512_cvtepi16_epi32)
+OPENCV_HAL_IMPL_AVX512_EXPAND(v_uint32x16, v_uint64x8,  unsigned, _mm512_cvtepu32_epi64)
+OPENCV_HAL_IMPL_AVX512_EXPAND(v_int32x16,  v_int64x8,   int,      _mm512_cvtepi32_epi64)
+
+#define OPENCV_HAL_IMPL_AVX512_EXPAND_Q(_Tpvec, _Tp, intrin) \
+    inline _Tpvec v512_load_expand_q(const _Tp* ptr)         \
+    {                                                        \
+        __m128i a = _mm_loadu_si128((const __m128i*)ptr);    \
+        return _Tpvec(intrin(a));                            \
+    }
+
+OPENCV_HAL_IMPL_AVX512_EXPAND_Q(v_uint32x16, uchar, _mm512_cvtepu8_epi32)
+OPENCV_HAL_IMPL_AVX512_EXPAND_Q(v_int32x16,  schar, _mm512_cvtepi8_epi32)
+
+/* pack */
+// 16
+inline v_int8x64 v_pack(const v_int16x32& a, const v_int16x32& b)
+{ return v_int8x64(_mm512_permutexvar_epi64(_v512_set_epu64(7, 5, 3, 1, 6, 4, 2, 0), _mm512_packs_epi16(a.val, b.val))); }
+
+inline v_uint8x64 v_pack(const v_uint16x32& a, const v_uint16x32& b)
+{
+    const __m512i t = _mm512_set1_epi16(255);
+    return v_uint8x64(_v512_combine(_mm512_cvtepi16_epi8(_mm512_min_epu16(a.val, t)), _mm512_cvtepi16_epi8(_mm512_min_epu16(b.val, t))));
+}
+
+inline v_uint8x64 v_pack_u(const v_int16x32& a, const v_int16x32& b)
+{
+    return v_uint8x64(_mm512_permutexvar_epi64(_v512_set_epu64(7, 5, 3, 1, 6, 4, 2, 0), _mm512_packus_epi16(a.val, b.val)));
+}
+
+inline void v_pack_store(schar* ptr, const v_int16x32& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(uchar* ptr, const v_uint16x32& a)
+{
+    const __m512i m = _mm512_set1_epi16(255);
+    _mm256_storeu_si256((__m256i*)ptr, _mm512_cvtepi16_epi8(_mm512_min_epu16(a.val, m)));
+}
+
+inline void v_pack_u_store(uchar* ptr, const v_int16x32& a)
+{ v_store_low(ptr, v_pack_u(a, a)); }
+
+template<int n> inline
+v_uint8x64 v_rshr_pack(const v_uint16x32& a, const v_uint16x32& b)
+{
+    // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers.
+    v_uint16x32 delta = v512_setall_u16((short)(1 << (n-1)));
+    return v_pack_u(v_reinterpret_as_s16(v_shr(v_add(a, delta), n)),
+                    v_reinterpret_as_s16(v_shr(v_add(b, delta), n)));
+}
+
+template<int n> inline
+void v_rshr_pack_store(uchar* ptr, const v_uint16x32& a)
+{
+    v_uint16x32 delta = v512_setall_u16((short)(1 << (n-1)));
+    v_pack_u_store(ptr, v_reinterpret_as_s16(v_shr(v_add(a, delta), n)));
+}
+
+template<int n> inline
+v_uint8x64 v_rshr_pack_u(const v_int16x32& a, const v_int16x32& b)
+{
+    v_int16x32 delta = v512_setall_s16((short)(1 << (n-1)));
+    return v_pack_u(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_u_store(uchar* ptr, const v_int16x32& a)
+{
+    v_int16x32 delta = v512_setall_s16((short)(1 << (n-1)));
+    v_pack_u_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+template<int n> inline
+v_int8x64 v_rshr_pack(const v_int16x32& a, const v_int16x32& b)
+{
+    v_int16x32 delta = v512_setall_s16((short)(1 << (n-1)));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(schar* ptr, const v_int16x32& a)
+{
+    v_int16x32 delta = v512_setall_s16((short)(1 << (n-1)));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+// 32
+inline v_int16x32 v_pack(const v_int32x16& a, const v_int32x16& b)
+{ return v_int16x32(_mm512_permutexvar_epi64(_v512_set_epu64(7, 5, 3, 1, 6, 4, 2, 0), _mm512_packs_epi32(a.val, b.val))); }
+
+inline v_uint16x32 v_pack(const v_uint32x16& a, const v_uint32x16& b)
+{
+    const __m512i m = _mm512_set1_epi32(65535);
+    return v_uint16x32(_v512_combine(_mm512_cvtepi32_epi16(_mm512_min_epu32(a.val, m)), _mm512_cvtepi32_epi16(_mm512_min_epu32(b.val, m))));
+}
+
+inline v_uint16x32 v_pack_u(const v_int32x16& a, const v_int32x16& b)
+{ return v_uint16x32(_mm512_permutexvar_epi64(_v512_set_epu64(7, 5, 3, 1, 6, 4, 2, 0), _mm512_packus_epi32(a.val, b.val))); }
+
+inline void v_pack_store(short* ptr, const v_int32x16& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(ushort* ptr, const v_uint32x16& a)
+{
+    const __m512i m = _mm512_set1_epi32(65535);
+    _mm256_storeu_si256((__m256i*)ptr, _mm512_cvtepi32_epi16(_mm512_min_epu32(a.val, m)));
+}
+
+inline void v_pack_u_store(ushort* ptr, const v_int32x16& a)
+{ v_store_low(ptr, v_pack_u(a, a)); }
+
+
+template<int n> inline
+v_uint16x32 v_rshr_pack(const v_uint32x16& a, const v_uint32x16& b)
+{
+    v_uint32x16 delta = v512_setall_u32(1 << (n-1));
+    return v_pack_u(v_reinterpret_as_s32(v_shr(v_add(a, delta), n)),
+                    v_reinterpret_as_s32(v_shr(v_add(b, delta), n)));
+}
+
+template<int n> inline
+void v_rshr_pack_store(ushort* ptr, const v_uint32x16& a)
+{
+    v_uint32x16 delta = v512_setall_u32(1 << (n-1));
+    v_pack_u_store(ptr, v_reinterpret_as_s32(v_shr(v_add(a, delta), n)));
+}
+
+template<int n> inline
+v_uint16x32 v_rshr_pack_u(const v_int32x16& a, const v_int32x16& b)
+{
+    v_int32x16 delta = v512_setall_s32(1 << (n-1));
+    return v_pack_u(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_u_store(ushort* ptr, const v_int32x16& a)
+{
+    v_int32x16 delta = v512_setall_s32(1 << (n-1));
+    v_pack_u_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+template<int n> inline
+v_int16x32 v_rshr_pack(const v_int32x16& a, const v_int32x16& b)
+{
+    v_int32x16 delta = v512_setall_s32(1 << (n-1));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(short* ptr, const v_int32x16& a)
+{
+    v_int32x16 delta = v512_setall_s32(1 << (n-1));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+// 64
+// Non-saturating pack
+inline v_uint32x16 v_pack(const v_uint64x8& a, const v_uint64x8& b)
+{ return v_uint32x16(_v512_combine(_mm512_cvtepi64_epi32(a.val), _mm512_cvtepi64_epi32(b.val))); }
+
+inline v_int32x16 v_pack(const v_int64x8& a, const v_int64x8& b)
+{ return v_reinterpret_as_s32(v_pack(v_reinterpret_as_u64(a), v_reinterpret_as_u64(b))); }
+
+inline void v_pack_store(unsigned* ptr, const v_uint64x8& a)
+{ _mm256_storeu_si256((__m256i*)ptr, _mm512_cvtepi64_epi32(a.val)); }
+
+inline void v_pack_store(int* ptr, const v_int64x8& b)
+{ v_pack_store((unsigned*)ptr, v_reinterpret_as_u64(b)); }
+
+template<int n> inline
+v_uint32x16 v_rshr_pack(const v_uint64x8& a, const v_uint64x8& b)
+{
+    v_uint64x8 delta = v512_setall_u64((uint64)1 << (n-1));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(unsigned* ptr, const v_uint64x8& a)
+{
+    v_uint64x8 delta = v512_setall_u64((uint64)1 << (n-1));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+template<int n> inline
+v_int32x16 v_rshr_pack(const v_int64x8& a, const v_int64x8& b)
+{
+    v_int64x8 delta = v512_setall_s64((int64)1 << (n-1));
+    return v_pack(v_shr(v_add(a, delta), n), v_shr(v_add(b, delta), n));
+}
+
+template<int n> inline
+void v_rshr_pack_store(int* ptr, const v_int64x8& a)
+{
+    v_int64x8 delta = v512_setall_s64((int64)1 << (n-1));
+    v_pack_store(ptr, v_shr(v_add(a, delta), n));
+}
+
+// pack boolean
+inline v_uint8x64 v_pack_b(const v_uint16x32& a, const v_uint16x32& b)
+{ return v_uint8x64(_mm512_permutexvar_epi64(_v512_set_epu64(7, 5, 3, 1, 6, 4, 2, 0), _mm512_packs_epi16(a.val, b.val))); }
+
+inline v_uint8x64 v_pack_b(const v_uint32x16& a, const v_uint32x16& b,
+                           const v_uint32x16& c, const v_uint32x16& d)
+{
+    __m512i ab = _mm512_packs_epi32(a.val, b.val);
+    __m512i cd = _mm512_packs_epi32(c.val, d.val);
+
+    return v_uint8x64(_mm512_permutexvar_epi32(_v512_set_epu32(15, 11, 7, 3, 14, 10, 6, 2, 13, 9, 5, 1, 12, 8, 4, 0), _mm512_packs_epi16(ab, cd)));
+}
+
+inline v_uint8x64 v_pack_b(const v_uint64x8& a, const v_uint64x8& b, const v_uint64x8& c,
+                           const v_uint64x8& d, const v_uint64x8& e, const v_uint64x8& f,
+                           const v_uint64x8& g, const v_uint64x8& h)
+{
+    __m512i ab = _mm512_packs_epi32(a.val, b.val);
+    __m512i cd = _mm512_packs_epi32(c.val, d.val);
+    __m512i ef = _mm512_packs_epi32(e.val, f.val);
+    __m512i gh = _mm512_packs_epi32(g.val, h.val);
+
+    __m512i abcd = _mm512_packs_epi32(ab, cd);
+    __m512i efgh = _mm512_packs_epi32(ef, gh);
+
+    return v_uint8x64(_mm512_permutexvar_epi16(_v512_set_epu16(31, 23, 15, 7, 30, 22, 14, 6, 29, 21, 13, 5, 28, 20, 12, 4,
+                                                               27, 19, 11, 3, 26, 18, 10, 2, 25, 17,  9, 1, 24, 16,  8, 0), _mm512_packs_epi16(abcd, efgh)));
+}
+
+/* Recombine */
+// its up there with load and store operations
+
+/* Extract */
+#define OPENCV_HAL_IMPL_AVX512_EXTRACT(_Tpvec)                \
+    template<int s>                                           \
+    inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b) \
+    { return v_rotate_right<s>(a, b); }
+
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_uint8x64)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_int8x64)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_uint16x32)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_int16x32)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_uint32x16)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_int32x16)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_uint64x8)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_int64x8)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_float32x16)
+OPENCV_HAL_IMPL_AVX512_EXTRACT(v_float64x8)
+
+#define OPENCV_HAL_IMPL_AVX512_EXTRACT_N(_Tpvec, _Tp) \
+template<int i> inline _Tp v_extract_n(_Tpvec v) { return v_rotate_right<i>(v).get0(); }
+
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_uint8x64, uchar)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_int8x64, schar)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_uint16x32, ushort)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_int16x32, short)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_uint32x16, uint)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_int32x16, int)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_uint64x8, uint64)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_int64x8, int64)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_float32x16, float)
+OPENCV_HAL_IMPL_AVX512_EXTRACT_N(v_float64x8, double)
+
+template<int i>
+inline v_uint32x16 v_broadcast_element(v_uint32x16 a)
+{
+    static const __m512i perm = _mm512_set1_epi32((char)i);
+    return v_uint32x16(_mm512_permutexvar_epi32(perm, a.val));
+}
+
+template<int i>
+inline v_int32x16 v_broadcast_element(const v_int32x16 &a)
+{ return v_reinterpret_as_s32(v_broadcast_element<i>(v_reinterpret_as_u32(a))); }
+
+template<int i>
+inline v_float32x16 v_broadcast_element(const v_float32x16 &a)
+{ return v_reinterpret_as_f32(v_broadcast_element<i>(v_reinterpret_as_u32(a))); }
+
+
+///////////////////// load deinterleave /////////////////////////////
+
+inline void v_load_deinterleave( const uchar* ptr, v_uint8x64& a, v_uint8x64& b )
+{
+    __m512i ab0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i ab1 = _mm512_loadu_si512((const __m512i*)(ptr + 64));
+#if CV_AVX_512VBMI
+    __m512i mask0 = _v512_set_epu8(126, 124, 122, 120, 118, 116, 114, 112, 110, 108, 106, 104, 102, 100, 98, 96,
+                                    94,  92,  90,  88,  86,  84,  82,  80,  78,  76,  74,  72,  70,  68, 66, 64,
+                                    62,  60,  58,  56,  54,  52,  50,  48,  46,  44,  42,  40,  38,  36, 34, 32,
+                                    30,  28,  26,  24,  22,  20,  18,  16,  14,  12,  10,   8,   6,   4,  2,  0);
+    __m512i mask1 = _v512_set_epu8(127, 125, 123, 121, 119, 117, 115, 113, 111, 109, 107, 105, 103, 101, 99, 97,
+                                    95,  93,  91,  89,  87,  85,  83,  81,  79,  77,  75,  73,  71,  69, 67, 65,
+                                    63,  61,  59,  57,  55,  53,  51,  49,  47,  45,  43,  41,  39,  37, 35, 33,
+                                    31,  29,  27,  25,  23,  21,  19,  17,  15,  13,  11,   9,   7,   5,  3,  1);
+    a = v_uint8x64(_mm512_permutex2var_epi8(ab0, mask0, ab1));
+    b = v_uint8x64(_mm512_permutex2var_epi8(ab0, mask1, ab1));
+#else
+    __m512i mask0 = _mm512_set4_epi32(0x0f0d0b09, 0x07050301, 0x0e0c0a08, 0x06040200);
+    __m512i a0b0 = _mm512_shuffle_epi8(ab0, mask0);
+    __m512i a1b1 = _mm512_shuffle_epi8(ab1, mask0);
+    __m512i mask1 = _v512_set_epu64(14, 12, 10, 8, 6, 4, 2, 0);
+    __m512i mask2 = _v512_set_epu64(15, 13, 11, 9, 7, 5, 3, 1);
+    a = v_uint8x64(_mm512_permutex2var_epi64(a0b0, mask1, a1b1));
+    b = v_uint8x64(_mm512_permutex2var_epi64(a0b0, mask2, a1b1));
+#endif
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x32& a, v_uint16x32& b )
+{
+    __m512i ab0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i ab1 = _mm512_loadu_si512((const __m512i*)(ptr + 32));
+    __m512i mask0 = _v512_set_epu16(62, 60, 58, 56, 54, 52, 50, 48, 46, 44, 42, 40, 38, 36, 34, 32,
+                                    30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10,  8,  6,  4,  2,  0);
+    __m512i mask1 = _v512_set_epu16(63, 61, 59, 57, 55, 53, 51, 49, 47, 45, 43, 41, 39, 37, 35, 33,
+                                    31, 29, 27, 25, 23, 21, 19, 17, 15, 13, 11,  9,  7,  5,  3,  1);
+    a = v_uint16x32(_mm512_permutex2var_epi16(ab0, mask0, ab1));
+    b = v_uint16x32(_mm512_permutex2var_epi16(ab0, mask1, ab1));
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x16& a, v_uint32x16& b )
+{
+    __m512i ab0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i ab1 = _mm512_loadu_si512((const __m512i*)(ptr + 16));
+    __m512i mask0 = _v512_set_epu32(30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0);
+    __m512i mask1 = _v512_set_epu32(31, 29, 27, 25, 23, 21, 19, 17, 15, 13, 11, 9, 7, 5, 3, 1);
+    a = v_uint32x16(_mm512_permutex2var_epi32(ab0, mask0, ab1));
+    b = v_uint32x16(_mm512_permutex2var_epi32(ab0, mask1, ab1));
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x8& a, v_uint64x8& b )
+{
+    __m512i ab0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i ab1 = _mm512_loadu_si512((const __m512i*)(ptr + 8));
+    __m512i mask0 = _v512_set_epu64(14, 12, 10, 8, 6, 4, 2, 0);
+    __m512i mask1 = _v512_set_epu64(15, 13, 11, 9, 7, 5, 3, 1);
+    a = v_uint64x8(_mm512_permutex2var_epi64(ab0, mask0, ab1));
+    b = v_uint64x8(_mm512_permutex2var_epi64(ab0, mask1, ab1));
+}
+
+inline void v_load_deinterleave( const uchar* ptr, v_uint8x64& a, v_uint8x64& b, v_uint8x64& c )
+{
+    __m512i bgr0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgr1 = _mm512_loadu_si512((const __m512i*)(ptr + 64));
+    __m512i bgr2 = _mm512_loadu_si512((const __m512i*)(ptr + 128));
+
+#if CV_AVX_512VBMI2
+    __m512i mask0 = _v512_set_epu8(126, 123, 120, 117, 114, 111, 108, 105, 102,  99,  96,  93,  90,  87,  84, 81,
+                                    78,  75,  72,  69,  66,  63,  60,  57,  54,  51,  48,  45,  42,  39,  36, 33,
+                                    30,  27,  24,  21,  18,  15,  12,   9,   6,   3,   0,  62,  59,  56,  53, 50,
+                                    47,  44,  41,  38,  35,  32,  29,  26,  23,  20,  17,  14,  11,   8,   5,  2);
+    __m512i r0b01 = _mm512_permutex2var_epi8(bgr0, mask0, bgr1);
+    __m512i b1g12 = _mm512_permutex2var_epi8(bgr1, mask0, bgr2);
+    __m512i r12b2 = _mm512_permutex2var_epi8(bgr1,
+                    _v512_set_epu8(125, 122, 119, 116, 113, 110, 107, 104, 101,  98,  95,  92,  89,  86,  83, 80,
+                                    77,  74,  71,  68,  65, 127, 124, 121, 118, 115, 112, 109, 106, 103, 100, 97,
+                                    94,  91,  88,  85,  82,  79,  76,  73,  70,  67,  64,  61,  58,  55,  52, 49,
+                                    46,  43,  40,  37,  34,  31,  28,  25,  22,  19,  16,  13,  10,   7,   4,  1), bgr2);
+    a = v_uint8x64(_mm512_mask_compress_epi8(r12b2, 0xffffffffffe00000, r0b01));
+    b = v_uint8x64(_mm512_mask_compress_epi8(b1g12, 0x2492492492492492, bgr0));
+    c = v_uint8x64(_mm512_mask_expand_epi8(r0b01, 0xffffffffffe00000, r12b2));
+#elif CV_AVX_512VBMI
+    __m512i b0g0b1 = _mm512_mask_blend_epi8(0xb6db6db6db6db6db, bgr1, bgr0);
+    __m512i g1r1g2 = _mm512_mask_blend_epi8(0xb6db6db6db6db6db, bgr2, bgr1);
+    __m512i r2b2r0 = _mm512_mask_blend_epi8(0xb6db6db6db6db6db, bgr0, bgr2);
+    a = v_uint8x64(_mm512_permutex2var_epi8(b0g0b1, _v512_set_epu8(125, 122, 119, 116, 113, 110, 107, 104, 101,  98,  95,  92,  89,  86,  83,  80,
+                                                                    77,  74,  71,  68,  65,  63,  61,  60,  58,  57,  55,  54,  52,  51,  49,  48,
+                                                                    46,  45,  43,  42,  40,  39,  37,  36,  34,  33,  31,  30,  28,  27,  25,  24,
+                                                                    23,  21,  20,  18,  17,  15,  14,  12,  11,   9,   8,   6,   5,   3,   2,   0), bgr2));
+    b = v_uint8x64(_mm512_permutex2var_epi8(g1r1g2, _v512_set_epu8( 63,  61,  60,  58,  57,  55,  54,  52,  51,  49,  48,  46,  45,  43,  42,  40,
+                                                                    39,  37,  36,  34,  33,  31,  30,  28,  27,  25,  24,  23,  21,  20,  18,  17,
+                                                                    15,  14,  12,  11,   9,   8,   6,   5,   3,   2,   0, 126, 123, 120, 117, 114,
+                                                                   111, 108, 105, 102,  99,  96,  93,  90,  87,  84,  81,  78,  75,  72,  69,  66), bgr0));
+    c = v_uint8x64(_mm512_permutex2var_epi8(r2b2r0, _v512_set_epu8( 63,  60,  57,  54,  51,  48,  45,  42,  39,  36,  33,  30,  27,  24,  21,  18,
+                                                                    15,  12,   9,   6,   3,   0, 125, 122, 119, 116, 113, 110, 107, 104, 101,  98,
+                                                                    95,  92,  89,  86,  83,  80,  77,  74,  71,  68,  65,  62,  59,  56,  53,  50,
+                                                                    47,  44,  41,  38,  35,  32,  29,  26,  23,  20,  17,  14,  11,   8,   5,   2), bgr1));
+#else
+    __m512i mask0 = _v512_set_epu16(61, 58, 55, 52, 49, 46, 43, 40, 37, 34, 63, 60, 57, 54, 51, 48,
+                                    45, 42, 39, 36, 33, 30, 27, 24, 21, 18, 15, 12,  9,  6,  3,  0);
+    __m512i b01g1 = _mm512_permutex2var_epi16(bgr0, mask0, bgr1);
+    __m512i r12b2 = _mm512_permutex2var_epi16(bgr1, mask0, bgr2);
+    __m512i g20r0 = _mm512_permutex2var_epi16(bgr2, mask0, bgr0);
+
+    __m512i b0g0 = _mm512_mask_blend_epi32(0xf800, b01g1, r12b2);
+    __m512i r0b1 = _mm512_permutex2var_epi16(bgr1, _v512_set_epu16(42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 29, 26, 23, 20, 17,
+                                                                   14, 11,  8,  5,  2, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43), g20r0);
+    __m512i g1r1 = _mm512_alignr_epi32(r12b2, g20r0, 11);
+    a = v_uint8x64(_mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, b0g0, r0b1));
+    c = v_uint8x64(_mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, r0b1, g1r1));
+    b = v_uint8x64(_mm512_shuffle_epi8(_mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, g1r1, b0g0), _mm512_set4_epi32(0x0e0f0c0d, 0x0a0b0809, 0x06070405, 0x02030001)));
+#endif
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x32& a, v_uint16x32& b, v_uint16x32& c )
+{
+    __m512i bgr0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgr1 = _mm512_loadu_si512((const __m512i*)(ptr + 32));
+    __m512i bgr2 = _mm512_loadu_si512((const __m512i*)(ptr + 64));
+
+    __m512i mask0 = _v512_set_epu16(61, 58, 55, 52, 49, 46, 43, 40, 37, 34, 63, 60, 57, 54, 51, 48,
+                                    45, 42, 39, 36, 33, 30, 27, 24, 21, 18, 15, 12,  9,  6,  3,  0);
+    __m512i b01g1 = _mm512_permutex2var_epi16(bgr0, mask0, bgr1);
+    __m512i r12b2 = _mm512_permutex2var_epi16(bgr1, mask0, bgr2);
+    __m512i g20r0 = _mm512_permutex2var_epi16(bgr2, mask0, bgr0);
+
+    a = v_uint16x32(_mm512_mask_blend_epi32(0xf800, b01g1, r12b2));
+    b = v_uint16x32(_mm512_permutex2var_epi16(bgr1, _v512_set_epu16(42, 41, 40, 39, 38, 37, 36, 35, 34, 33, 32, 29, 26, 23, 20, 17,
+                                                                    14, 11,  8,  5,  2, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43), g20r0));
+    c = v_uint16x32(_mm512_alignr_epi32(r12b2, g20r0, 11));
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x16& a, v_uint32x16& b, v_uint32x16& c )
+{
+    __m512i bgr0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgr1 = _mm512_loadu_si512((const __m512i*)(ptr + 16));
+    __m512i bgr2 = _mm512_loadu_si512((const __m512i*)(ptr + 32));
+
+    __m512i mask0 = _v512_set_epu32(29, 26, 23, 20, 17, 30, 27, 24, 21, 18, 15, 12, 9, 6, 3, 0);
+    __m512i b01r1 = _mm512_permutex2var_epi32(bgr0, mask0, bgr1);
+    __m512i g12b2 = _mm512_permutex2var_epi32(bgr1, mask0, bgr2);
+    __m512i r20g0 = _mm512_permutex2var_epi32(bgr2, mask0, bgr0);
+
+    a = v_uint32x16(_mm512_mask_blend_epi32(0xf800, b01r1, g12b2));
+    b = v_uint32x16(_mm512_alignr_epi32(g12b2, r20g0, 11));
+    c = v_uint32x16(_mm512_permutex2var_epi32(bgr1, _v512_set_epu32(21, 20, 19, 18, 17, 16, 13, 10, 7, 4, 1, 26, 25, 24, 23, 22), r20g0));
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x8& a, v_uint64x8& b, v_uint64x8& c )
+{
+    __m512i bgr0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgr1 = _mm512_loadu_si512((const __m512i*)(ptr + 8));
+    __m512i bgr2 = _mm512_loadu_si512((const __m512i*)(ptr + 16));
+
+    __m512i mask0 = _v512_set_epu64(13, 10, 15, 12, 9, 6, 3, 0);
+    __m512i b01g1 = _mm512_permutex2var_epi64(bgr0, mask0, bgr1);
+    __m512i r12b2 = _mm512_permutex2var_epi64(bgr1, mask0, bgr2);
+    __m512i g20r0 = _mm512_permutex2var_epi64(bgr2, mask0, bgr0);
+
+    a = v_uint64x8(_mm512_mask_blend_epi64(0xc0, b01g1, r12b2));
+    c = v_uint64x8(_mm512_alignr_epi64(r12b2, g20r0, 6));
+    b = v_uint64x8(_mm512_permutex2var_epi64(bgr1, _v512_set_epu64(10, 9, 8, 5, 2, 13, 12, 11), g20r0));
+}
+
+inline void v_load_deinterleave( const uchar* ptr, v_uint8x64& a, v_uint8x64& b, v_uint8x64& c, v_uint8x64& d )
+{
+    __m512i bgra0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgra1 = _mm512_loadu_si512((const __m512i*)(ptr + 64));
+    __m512i bgra2 = _mm512_loadu_si512((const __m512i*)(ptr + 128));
+    __m512i bgra3 = _mm512_loadu_si512((const __m512i*)(ptr + 192));
+
+#if CV_AVX_512VBMI
+    __m512i mask0 = _v512_set_epu8(126, 124, 122, 120, 118, 116, 114, 112, 110, 108, 106, 104, 102, 100, 98, 96,
+                                    94,  92,  90,  88,  86,  84,  82,  80,  78,  76,  74,  72,  70,  68, 66, 64,
+                                    62,  60,  58,  56,  54,  52,  50,  48,  46,  44,  42,  40,  38,  36, 34, 32,
+                                    30,  28,  26,  24,  22,  20,  18,  16,  14,  12,  10,   8,   6,   4,  2,  0);
+    __m512i mask1 = _v512_set_epu8(127, 125, 123, 121, 119, 117, 115, 113, 111, 109, 107, 105, 103, 101, 99, 97,
+                                    95,  93,  91,  89,  87,  85,  83,  81,  79,  77,  75,  73,  71,  69, 67, 65,
+                                    63,  61,  59,  57,  55,  53,  51,  49,  47,  45,  43,  41,  39,  37, 35, 33,
+                                    31,  29,  27,  25,  23,  21,  19,  17,  15,  13,  11,   9,   7,   5,  3,  1);
+
+    __m512i br01 = _mm512_permutex2var_epi8(bgra0, mask0, bgra1);
+    __m512i ga01 = _mm512_permutex2var_epi8(bgra0, mask1, bgra1);
+    __m512i br23 = _mm512_permutex2var_epi8(bgra2, mask0, bgra3);
+    __m512i ga23 = _mm512_permutex2var_epi8(bgra2, mask1, bgra3);
+
+    a = v_uint8x64(_mm512_permutex2var_epi8(br01, mask0, br23));
+    c = v_uint8x64(_mm512_permutex2var_epi8(br01, mask1, br23));
+    b = v_uint8x64(_mm512_permutex2var_epi8(ga01, mask0, ga23));
+    d = v_uint8x64(_mm512_permutex2var_epi8(ga01, mask1, ga23));
+#else
+    __m512i mask = _mm512_set4_epi32(0x0f0b0703, 0x0e0a0602, 0x0d090501, 0x0c080400);
+    __m512i b0g0r0a0 = _mm512_shuffle_epi8(bgra0, mask);
+    __m512i b1g1r1a1 = _mm512_shuffle_epi8(bgra1, mask);
+    __m512i b2g2r2a2 = _mm512_shuffle_epi8(bgra2, mask);
+    __m512i b3g3r3a3 = _mm512_shuffle_epi8(bgra3, mask);
+
+    __m512i mask0 = _v512_set_epu32(30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0);
+    __m512i mask1 = _v512_set_epu32(31, 29, 27, 25, 23, 21, 19, 17, 15, 13, 11, 9, 7, 5, 3, 1);
+
+    __m512i br01 = _mm512_permutex2var_epi32(b0g0r0a0, mask0, b1g1r1a1);
+    __m512i ga01 = _mm512_permutex2var_epi32(b0g0r0a0, mask1, b1g1r1a1);
+    __m512i br23 = _mm512_permutex2var_epi32(b2g2r2a2, mask0, b3g3r3a3);
+    __m512i ga23 = _mm512_permutex2var_epi32(b2g2r2a2, mask1, b3g3r3a3);
+
+    a = v_uint8x64(_mm512_permutex2var_epi32(br01, mask0, br23));
+    c = v_uint8x64(_mm512_permutex2var_epi32(br01, mask1, br23));
+    b = v_uint8x64(_mm512_permutex2var_epi32(ga01, mask0, ga23));
+    d = v_uint8x64(_mm512_permutex2var_epi32(ga01, mask1, ga23));
+#endif
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x32& a, v_uint16x32& b, v_uint16x32& c, v_uint16x32& d )
+{
+    __m512i bgra0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgra1 = _mm512_loadu_si512((const __m512i*)(ptr + 32));
+    __m512i bgra2 = _mm512_loadu_si512((const __m512i*)(ptr + 64));
+    __m512i bgra3 = _mm512_loadu_si512((const __m512i*)(ptr + 96));
+
+    __m512i mask0 = _v512_set_epu16(62, 60, 58, 56, 54, 52, 50, 48, 46, 44, 42, 40, 38, 36, 34, 32,
+                                    30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10,  8,  6,  4,  2,  0);
+    __m512i mask1 = _v512_set_epu16(63, 61, 59, 57, 55, 53, 51, 49, 47, 45, 43, 41, 39, 37, 35, 33,
+                                    31, 29, 27, 25, 23, 21, 19, 17, 15, 13, 11,  9,  7,  5,  3,  1);
+
+    __m512i br01 = _mm512_permutex2var_epi16(bgra0, mask0, bgra1);
+    __m512i ga01 = _mm512_permutex2var_epi16(bgra0, mask1, bgra1);
+    __m512i br23 = _mm512_permutex2var_epi16(bgra2, mask0, bgra3);
+    __m512i ga23 = _mm512_permutex2var_epi16(bgra2, mask1, bgra3);
+
+    a = v_uint16x32(_mm512_permutex2var_epi16(br01, mask0, br23));
+    c = v_uint16x32(_mm512_permutex2var_epi16(br01, mask1, br23));
+    b = v_uint16x32(_mm512_permutex2var_epi16(ga01, mask0, ga23));
+    d = v_uint16x32(_mm512_permutex2var_epi16(ga01, mask1, ga23));
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x16& a, v_uint32x16& b, v_uint32x16& c, v_uint32x16& d )
+{
+    __m512i bgra0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgra1 = _mm512_loadu_si512((const __m512i*)(ptr + 16));
+    __m512i bgra2 = _mm512_loadu_si512((const __m512i*)(ptr + 32));
+    __m512i bgra3 = _mm512_loadu_si512((const __m512i*)(ptr + 48));
+
+    __m512i mask0 = _v512_set_epu32(30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0);
+    __m512i mask1 = _v512_set_epu32(31, 29, 27, 25, 23, 21, 19, 17, 15, 13, 11, 9, 7, 5, 3, 1);
+
+    __m512i br01 = _mm512_permutex2var_epi32(bgra0, mask0, bgra1);
+    __m512i ga01 = _mm512_permutex2var_epi32(bgra0, mask1, bgra1);
+    __m512i br23 = _mm512_permutex2var_epi32(bgra2, mask0, bgra3);
+    __m512i ga23 = _mm512_permutex2var_epi32(bgra2, mask1, bgra3);
+
+    a = v_uint32x16(_mm512_permutex2var_epi32(br01, mask0, br23));
+    c = v_uint32x16(_mm512_permutex2var_epi32(br01, mask1, br23));
+    b = v_uint32x16(_mm512_permutex2var_epi32(ga01, mask0, ga23));
+    d = v_uint32x16(_mm512_permutex2var_epi32(ga01, mask1, ga23));
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x8& a, v_uint64x8& b, v_uint64x8& c, v_uint64x8& d )
+{
+    __m512i bgra0 = _mm512_loadu_si512((const __m512i*)ptr);
+    __m512i bgra1 = _mm512_loadu_si512((const __m512i*)(ptr + 8));
+    __m512i bgra2 = _mm512_loadu_si512((const __m512i*)(ptr + 16));
+    __m512i bgra3 = _mm512_loadu_si512((const __m512i*)(ptr + 24));
+
+    __m512i mask0 = _v512_set_epu64(14, 12, 10, 8, 6, 4, 2, 0);
+    __m512i mask1 = _v512_set_epu64(15, 13, 11, 9, 7, 5, 3, 1);
+
+    __m512i br01 = _mm512_permutex2var_epi64(bgra0, mask0, bgra1);
+    __m512i ga01 = _mm512_permutex2var_epi64(bgra0, mask1, bgra1);
+    __m512i br23 = _mm512_permutex2var_epi64(bgra2, mask0, bgra3);
+    __m512i ga23 = _mm512_permutex2var_epi64(bgra2, mask1, bgra3);
+
+    a = v_uint64x8(_mm512_permutex2var_epi64(br01, mask0, br23));
+    c = v_uint64x8(_mm512_permutex2var_epi64(br01, mask1, br23));
+    b = v_uint64x8(_mm512_permutex2var_epi64(ga01, mask0, ga23));
+    d = v_uint64x8(_mm512_permutex2var_epi64(ga01, mask1, ga23));
+}
+
+///////////////////////////// store interleave /////////////////////////////////////
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x64& x, const v_uint8x64& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint8x64 low, high;
+    v_zip(x, y, low, high);
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, low.val);
+        _mm512_stream_si512((__m512i*)(ptr + 64), high.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, low.val);
+        _mm512_store_si512((__m512i*)(ptr + 64), high.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, low.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 64), high.val);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x32& x, const v_uint16x32& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint16x32 low, high;
+    v_zip(x, y, low, high);
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, low.val);
+        _mm512_stream_si512((__m512i*)(ptr + 32), high.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, low.val);
+        _mm512_store_si512((__m512i*)(ptr + 32), high.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, low.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 32), high.val);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x16& x, const v_uint32x16& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint32x16 low, high;
+    v_zip(x, y, low, high);
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, low.val);
+        _mm512_stream_si512((__m512i*)(ptr + 16), high.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, low.val);
+        _mm512_store_si512((__m512i*)(ptr + 16), high.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, low.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 16), high.val);
+    }
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x8& x, const v_uint64x8& y,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint64x8 low, high;
+    v_zip(x, y, low, high);
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, low.val);
+        _mm512_stream_si512((__m512i*)(ptr + 8), high.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, low.val);
+        _mm512_store_si512((__m512i*)(ptr + 8), high.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, low.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 8), high.val);
+    }
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x64& a, const v_uint8x64& b, const v_uint8x64& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+#if CV_AVX_512VBMI
+    __m512i mask0 = _v512_set_epu8(127,  84,  20, 126,  83,  19, 125,  82,  18, 124,  81,  17, 123,  80,  16, 122,
+                                    79,  15, 121,  78,  14, 120,  77,  13, 119,  76,  12, 118,  75,  11, 117,  74,
+                                    10, 116,  73,   9, 115,  72,   8, 114,  71,   7, 113,  70,   6, 112,  69,   5,
+                                   111,  68,   4, 110,  67,   3, 109,  66,   2, 108,  65,   1, 107,  64,   0, 106);
+    __m512i mask1 = _v512_set_epu8( 21,  42, 105,  20,  41, 104,  19,  40, 103,  18,  39, 102,  17,  38, 101,  16,
+                                    37, 100,  15,  36,  99,  14,  35,  98,  13,  34,  97,  12,  33,  96,  11,  32,
+                                    95,  10,  31,  94,   9,  30,  93,   8,  29,  92,   7,  28,  91,   6,  27,  90,
+                                     5,  26,  89,   4,  25,  88,   3,  24,  87,   2,  23,  86,   1,  22,  85,   0);
+    __m512i mask2 = _v512_set_epu8(106, 127,  63, 105, 126,  62, 104, 125,  61, 103, 124,  60, 102, 123,  59, 101,
+                                   122,  58, 100, 121,  57,  99, 120,  56,  98, 119,  55,  97, 118,  54,  96, 117,
+                                    53,  95, 116,  52,  94, 115,  51,  93, 114,  50,  92, 113,  49,  91, 112,  48,
+                                    90, 111,  47,  89, 110,  46,  88, 109,  45,  87, 108,  44,  86, 107,  43,  85);
+    __m512i r2g0r0 = _mm512_permutex2var_epi8(b.val, mask0, c.val);
+    __m512i b0r1b1 = _mm512_permutex2var_epi8(a.val, mask1, c.val);
+    __m512i g1b2g2 = _mm512_permutex2var_epi8(a.val, mask2, b.val);
+
+    __m512i bgr0 = _mm512_mask_blend_epi8(0x9249249249249249, r2g0r0, b0r1b1);
+    __m512i bgr1 = _mm512_mask_blend_epi8(0x9249249249249249, b0r1b1, g1b2g2);
+    __m512i bgr2 = _mm512_mask_blend_epi8(0x9249249249249249, g1b2g2, r2g0r0);
+#else
+    __m512i g1g0 = _mm512_shuffle_epi8(b.val, _mm512_set4_epi32(0x0e0f0c0d, 0x0a0b0809, 0x06070405, 0x02030001));
+    __m512i b0g0 = _mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, a.val, g1g0);
+    __m512i r0b1 = _mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, c.val, a.val);
+    __m512i g1r1 = _mm512_mask_blend_epi8(0xAAAAAAAAAAAAAAAA, g1g0, c.val);
+
+    __m512i mask0 = _v512_set_epu16(42, 10, 31, 41,  9, 30, 40,  8, 29, 39,  7, 28, 38,  6, 27, 37,
+                                     5, 26, 36,  4, 25, 35,  3, 24, 34,  2, 23, 33,  1, 22, 32,  0);
+    __m512i mask1 = _v512_set_epu16(21, 52, 41, 20, 51, 40, 19, 50, 39, 18, 49, 38, 17, 48, 37, 16,
+                                    47, 36, 15, 46, 35, 14, 45, 34, 13, 44, 33, 12, 43, 32, 11, 42);
+    __m512i mask2 = _v512_set_epu16(63, 31, 20, 62, 30, 19, 61, 29, 18, 60, 28, 17, 59, 27, 16, 58,
+                                    26, 15, 57, 25, 14, 56, 24, 13, 55, 23, 12, 54, 22, 11, 53, 21);
+    __m512i b0g0b2 = _mm512_permutex2var_epi16(b0g0, mask0, r0b1);
+    __m512i r1b1r0 = _mm512_permutex2var_epi16(b0g0, mask1, g1r1);
+    __m512i g2r2g1 = _mm512_permutex2var_epi16(r0b1, mask2, g1r1);
+
+    __m512i bgr0 = _mm512_mask_blend_epi16(0x24924924, b0g0b2, r1b1r0);
+    __m512i bgr1 = _mm512_mask_blend_epi16(0x24924924, r1b1r0, g2r2g1);
+    __m512i bgr2 = _mm512_mask_blend_epi16(0x24924924, g2r2g1, b0g0b2);
+#endif
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgr0);
+        _mm512_stream_si512((__m512i*)(ptr + 64), bgr1);
+        _mm512_stream_si512((__m512i*)(ptr + 128), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgr0);
+        _mm512_store_si512((__m512i*)(ptr + 64), bgr1);
+        _mm512_store_si512((__m512i*)(ptr + 128), bgr2);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgr0);
+        _mm512_storeu_si512((__m512i*)(ptr + 64), bgr1);
+        _mm512_storeu_si512((__m512i*)(ptr + 128), bgr2);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x32& a, const v_uint16x32& b, const v_uint16x32& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m512i mask0 = _v512_set_epu16(42, 10, 31, 41,  9, 30, 40,  8, 29, 39,  7, 28, 38,  6, 27, 37,
+                                     5, 26, 36,  4, 25, 35,  3, 24, 34,  2, 23, 33,  1, 22, 32,  0);
+    __m512i mask1 = _v512_set_epu16(21, 52, 41, 20, 51, 40, 19, 50, 39, 18, 49, 38, 17, 48, 37, 16,
+                                    47, 36, 15, 46, 35, 14, 45, 34, 13, 44, 33, 12, 43, 32, 11, 42);
+    __m512i mask2 = _v512_set_epu16(63, 31, 20, 62, 30, 19, 61, 29, 18, 60, 28, 17, 59, 27, 16, 58,
+                                    26, 15, 57, 25, 14, 56, 24, 13, 55, 23, 12, 54, 22, 11, 53, 21);
+    __m512i b0g0b2 = _mm512_permutex2var_epi16(a.val, mask0, b.val);
+    __m512i r1b1r0 = _mm512_permutex2var_epi16(a.val, mask1, c.val);
+    __m512i g2r2g1 = _mm512_permutex2var_epi16(b.val, mask2, c.val);
+
+    __m512i bgr0 = _mm512_mask_blend_epi16(0x24924924, b0g0b2, r1b1r0);
+    __m512i bgr1 = _mm512_mask_blend_epi16(0x24924924, r1b1r0, g2r2g1);
+    __m512i bgr2 = _mm512_mask_blend_epi16(0x24924924, g2r2g1, b0g0b2);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgr0);
+        _mm512_stream_si512((__m512i*)(ptr + 32), bgr1);
+        _mm512_stream_si512((__m512i*)(ptr + 64), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgr0);
+        _mm512_store_si512((__m512i*)(ptr + 32), bgr1);
+        _mm512_store_si512((__m512i*)(ptr + 64), bgr2);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgr0);
+        _mm512_storeu_si512((__m512i*)(ptr + 32), bgr1);
+        _mm512_storeu_si512((__m512i*)(ptr + 64), bgr2);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x16& a, const v_uint32x16& b, const v_uint32x16& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m512i mask0 = _v512_set_epu32(26, 31, 15, 25, 30, 14, 24, 29, 13, 23, 28, 12, 22, 27, 11, 21);
+    __m512i mask1 = _v512_set_epu32(31, 10, 25, 30,  9, 24, 29,  8, 23, 28,  7, 22, 27,  6, 21, 26);
+    __m512i g1b2g2 = _mm512_permutex2var_epi32(a.val, mask0, b.val);
+    __m512i r2r1b1 = _mm512_permutex2var_epi32(a.val, mask1, c.val);
+
+    __m512i bgr0 = _mm512_mask_expand_epi32(_mm512_mask_expand_epi32(_mm512_maskz_expand_epi32(0x9249, a.val), 0x2492, b.val), 0x4924, c.val);
+    __m512i bgr1 = _mm512_mask_blend_epi32(0x9249, r2r1b1, g1b2g2);
+    __m512i bgr2 = _mm512_mask_blend_epi32(0x9249, g1b2g2, r2r1b1);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgr0);
+        _mm512_stream_si512((__m512i*)(ptr + 16), bgr1);
+        _mm512_stream_si512((__m512i*)(ptr + 32), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgr0);
+        _mm512_store_si512((__m512i*)(ptr + 16), bgr1);
+        _mm512_store_si512((__m512i*)(ptr + 32), bgr2);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgr0);
+        _mm512_storeu_si512((__m512i*)(ptr + 16), bgr1);
+        _mm512_storeu_si512((__m512i*)(ptr + 32), bgr2);
+    }
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x8& a, const v_uint64x8& b, const v_uint64x8& c,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    __m512i mask0 = _v512_set_epu64( 5, 12,  7,  4, 11,  6,  3, 10);
+    __m512i mask1 = _v512_set_epu64(15,  7,  4, 14,  6,  3, 13,  5);
+    __m512i r1b1b2 = _mm512_permutex2var_epi64(a.val, mask0, c.val);
+    __m512i g2r2g1 = _mm512_permutex2var_epi64(b.val, mask1, c.val);
+
+    __m512i bgr0 = _mm512_mask_expand_epi64(_mm512_mask_expand_epi64(_mm512_maskz_expand_epi64(0x49, a.val), 0x92, b.val), 0x24, c.val);
+    __m512i bgr1 = _mm512_mask_blend_epi64(0xdb, g2r2g1, r1b1b2);
+    __m512i bgr2 = _mm512_mask_blend_epi64(0xdb, r1b1b2, g2r2g1);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgr0);
+        _mm512_stream_si512((__m512i*)(ptr + 8), bgr1);
+        _mm512_stream_si512((__m512i*)(ptr + 16), bgr2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgr0);
+        _mm512_store_si512((__m512i*)(ptr + 8), bgr1);
+        _mm512_store_si512((__m512i*)(ptr + 16), bgr2);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgr0);
+        _mm512_storeu_si512((__m512i*)(ptr + 8), bgr1);
+        _mm512_storeu_si512((__m512i*)(ptr + 16), bgr2);
+    }
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x64& a, const v_uint8x64& b,
+                                const v_uint8x64& c, const v_uint8x64& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint8x64 br01, br23, ga01, ga23;
+    v_zip(a, c, br01, br23);
+    v_zip(b, d, ga01, ga23);
+    v_uint8x64 bgra0, bgra1, bgra2, bgra3;
+    v_zip(br01, ga01, bgra0, bgra1);
+    v_zip(br23, ga23, bgra2, bgra3);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgra0.val);
+        _mm512_stream_si512((__m512i*)(ptr + 64), bgra1.val);
+        _mm512_stream_si512((__m512i*)(ptr + 128), bgra2.val);
+        _mm512_stream_si512((__m512i*)(ptr + 192), bgra3.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgra0.val);
+        _mm512_store_si512((__m512i*)(ptr + 64), bgra1.val);
+        _mm512_store_si512((__m512i*)(ptr + 128), bgra2.val);
+        _mm512_store_si512((__m512i*)(ptr + 192), bgra3.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgra0.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 64), bgra1.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 128), bgra2.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 192), bgra3.val);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x32& a, const v_uint16x32& b,
+                                const v_uint16x32& c, const v_uint16x32& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint16x32 br01, br23, ga01, ga23;
+    v_zip(a, c, br01, br23);
+    v_zip(b, d, ga01, ga23);
+    v_uint16x32 bgra0, bgra1, bgra2, bgra3;
+    v_zip(br01, ga01, bgra0, bgra1);
+    v_zip(br23, ga23, bgra2, bgra3);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgra0.val);
+        _mm512_stream_si512((__m512i*)(ptr + 32), bgra1.val);
+        _mm512_stream_si512((__m512i*)(ptr + 64), bgra2.val);
+        _mm512_stream_si512((__m512i*)(ptr + 96), bgra3.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgra0.val);
+        _mm512_store_si512((__m512i*)(ptr + 32), bgra1.val);
+        _mm512_store_si512((__m512i*)(ptr + 64), bgra2.val);
+        _mm512_store_si512((__m512i*)(ptr + 96), bgra3.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgra0.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 32), bgra1.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 64), bgra2.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 96), bgra3.val);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x16& a, const v_uint32x16& b,
+                                const v_uint32x16& c, const v_uint32x16& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint32x16 br01, br23, ga01, ga23;
+    v_zip(a, c, br01, br23);
+    v_zip(b, d, ga01, ga23);
+    v_uint32x16 bgra0, bgra1, bgra2, bgra3;
+    v_zip(br01, ga01, bgra0, bgra1);
+    v_zip(br23, ga23, bgra2, bgra3);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgra0.val);
+        _mm512_stream_si512((__m512i*)(ptr + 16), bgra1.val);
+        _mm512_stream_si512((__m512i*)(ptr + 32), bgra2.val);
+        _mm512_stream_si512((__m512i*)(ptr + 48), bgra3.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgra0.val);
+        _mm512_store_si512((__m512i*)(ptr + 16), bgra1.val);
+        _mm512_store_si512((__m512i*)(ptr + 32), bgra2.val);
+        _mm512_store_si512((__m512i*)(ptr + 48), bgra3.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgra0.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 16), bgra1.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 32), bgra2.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 48), bgra3.val);
+    }
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x8& a, const v_uint64x8& b,
+                                const v_uint64x8& c, const v_uint64x8& d,
+                                hal::StoreMode mode=hal::STORE_UNALIGNED )
+{
+    v_uint64x8 br01, br23, ga01, ga23;
+    v_zip(a, c, br01, br23);
+    v_zip(b, d, ga01, ga23);
+    v_uint64x8 bgra0, bgra1, bgra2, bgra3;
+    v_zip(br01, ga01, bgra0, bgra1);
+    v_zip(br23, ga23, bgra2, bgra3);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm512_stream_si512((__m512i*)ptr, bgra0.val);
+        _mm512_stream_si512((__m512i*)(ptr + 8), bgra1.val);
+        _mm512_stream_si512((__m512i*)(ptr + 16), bgra2.val);
+        _mm512_stream_si512((__m512i*)(ptr + 24), bgra3.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm512_store_si512((__m512i*)ptr, bgra0.val);
+        _mm512_store_si512((__m512i*)(ptr + 8), bgra1.val);
+        _mm512_store_si512((__m512i*)(ptr + 16), bgra2.val);
+        _mm512_store_si512((__m512i*)(ptr + 24), bgra3.val);
+    }
+    else
+    {
+        _mm512_storeu_si512((__m512i*)ptr, bgra0.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 8), bgra1.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 16), bgra2.val);
+        _mm512_storeu_si512((__m512i*)(ptr + 24), bgra3.val);
+    }
+}
+
+#define OPENCV_HAL_IMPL_AVX512_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1) \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0 ) \
+{ \
+    _Tpvec1 a1, b1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0 ) \
+{ \
+    _Tpvec1 a1, b1, c1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0, _Tpvec0& d0 ) \
+{ \
+    _Tpvec1 a1, b1, c1, d1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+    d0 = v_reinterpret_as_##suffix0(d1); \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                hal::StoreMode mode=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, mode);      \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, const _Tpvec0& c0, \
+                                hal::StoreMode mode=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, mode);  \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                const _Tpvec0& c0, const _Tpvec0& d0, \
+                                hal::StoreMode mode=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1, mode); \
+}
+
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_INTERLEAVE(v_int8x64, schar, s8, v_uint8x64, uchar, u8)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_INTERLEAVE(v_int16x32, short, s16, v_uint16x32, ushort, u16)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_INTERLEAVE(v_int32x16, int, s32, v_uint32x16, unsigned, u32)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_INTERLEAVE(v_float32x16, float, f32, v_uint32x16, unsigned, u32)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_INTERLEAVE(v_int64x8, int64, s64, v_uint64x8, uint64, u64)
+OPENCV_HAL_IMPL_AVX512_LOADSTORE_INTERLEAVE(v_float64x8, double, f64, v_uint64x8, uint64, u64)
+
+////////// Mask and checks /////////
+
+/** Mask **/
+inline int64 v_signmask(const v_int8x64& a) { return (int64)_mm512_movepi8_mask(a.val); }
+inline int v_signmask(const v_int16x32& a) { return (int)_mm512_cmp_epi16_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_LT); }
+inline int v_signmask(const v_int32x16& a) { return (int)_mm512_cmp_epi32_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_LT); }
+inline int v_signmask(const v_int64x8& a) { return (int)_mm512_cmp_epi64_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_LT); }
+
+inline int64 v_signmask(const v_uint8x64& a) { return v_signmask(v_reinterpret_as_s8(a)); }
+inline int v_signmask(const v_uint16x32& a) { return v_signmask(v_reinterpret_as_s16(a)); }
+inline int v_signmask(const v_uint32x16& a) { return v_signmask(v_reinterpret_as_s32(a)); }
+inline int v_signmask(const v_uint64x8& a) { return v_signmask(v_reinterpret_as_s64(a)); }
+inline int v_signmask(const v_float32x16& a) { return v_signmask(v_reinterpret_as_s32(a)); }
+inline int v_signmask(const v_float64x8& a) { return v_signmask(v_reinterpret_as_s64(a)); }
+
+/** Checks **/
+inline bool v_check_all(const v_int8x64& a) { return !(bool)_mm512_cmp_epi8_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_NLT); }
+inline bool v_check_any(const v_int8x64& a) { return (bool)_mm512_movepi8_mask(a.val); }
+inline bool v_check_all(const v_int16x32& a) { return !(bool)_mm512_cmp_epi16_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_NLT); }
+inline bool v_check_any(const v_int16x32& a) { return (bool)_mm512_cmp_epi16_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_LT); }
+inline bool v_check_all(const v_int32x16& a) { return !(bool)_mm512_cmp_epi32_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_NLT); }
+inline bool v_check_any(const v_int32x16& a) { return (bool)_mm512_cmp_epi32_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_LT); }
+inline bool v_check_all(const v_int64x8& a) { return !(bool)_mm512_cmp_epi64_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_NLT); }
+inline bool v_check_any(const v_int64x8& a) { return (bool)_mm512_cmp_epi64_mask(a.val, _mm512_setzero_si512(), _MM_CMPINT_LT); }
+
+inline bool v_check_all(const v_float32x16& a) { return v_check_all(v_reinterpret_as_s32(a)); }
+inline bool v_check_any(const v_float32x16& a) { return v_check_any(v_reinterpret_as_s32(a)); }
+inline bool v_check_all(const v_float64x8& a) { return v_check_all(v_reinterpret_as_s64(a)); }
+inline bool v_check_any(const v_float64x8& a) { return v_check_any(v_reinterpret_as_s64(a)); }
+inline bool v_check_all(const v_uint8x64& a) { return v_check_all(v_reinterpret_as_s8(a)); }
+inline bool v_check_all(const v_uint16x32& a) { return v_check_all(v_reinterpret_as_s16(a)); }
+inline bool v_check_all(const v_uint32x16& a) { return v_check_all(v_reinterpret_as_s32(a)); }
+inline bool v_check_all(const v_uint64x8& a) { return v_check_all(v_reinterpret_as_s64(a)); }
+inline bool v_check_any(const v_uint8x64& a) { return v_check_any(v_reinterpret_as_s8(a)); }
+inline bool v_check_any(const v_uint16x32& a) { return v_check_any(v_reinterpret_as_s16(a)); }
+inline bool v_check_any(const v_uint32x16& a) { return v_check_any(v_reinterpret_as_s32(a)); }
+inline bool v_check_any(const v_uint64x8& a) { return v_check_any(v_reinterpret_as_s64(a)); }
+
+inline int v_scan_forward(const v_int8x64& a)
+{
+    int64 mask = _mm512_movepi8_mask(a.val);
+    int mask32 = (int)mask;
+    return mask != 0 ? mask32 != 0 ? trailingZeros32(mask32) : 32 + trailingZeros32((int)(mask >> 32)) : 0;
+}
+inline int v_scan_forward(const v_uint8x64& a) { return v_scan_forward(v_reinterpret_as_s8(a)); }
+inline int v_scan_forward(const v_int16x32& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))); }
+inline int v_scan_forward(const v_uint16x32& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))); }
+inline int v_scan_forward(const v_int32x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))) / 2; }
+inline int v_scan_forward(const v_uint32x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))) / 2; }
+inline int v_scan_forward(const v_float32x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))) / 2; }
+inline int v_scan_forward(const v_int64x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))) / 4; }
+inline int v_scan_forward(const v_uint64x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))) / 4; }
+inline int v_scan_forward(const v_float64x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s16(a))) / 4; }
+
+inline void v512_cleanup() { _mm256_zeroall(); }
+
+#include "intrin_math.hpp"
+inline v_float32x16 v_exp(const v_float32x16& x) { return v_exp_default_32f<v_float32x16, v_int32x16>(x); }
+inline v_float32x16 v_log(const v_float32x16& x) { return v_log_default_32f<v_float32x16, v_int32x16>(x); }
+inline void v_sincos(const v_float32x16& x, v_float32x16& s, v_float32x16& c) { v_sincos_default_32f<v_float32x16, v_int32x16>(x, s, c); }
+inline v_float32x16 v_sin(const v_float32x16& x) { return v_sin_default_32f<v_float32x16, v_int32x16>(x); }
+inline v_float32x16 v_cos(const v_float32x16& x) { return v_cos_default_32f<v_float32x16, v_int32x16>(x); }
+inline v_float32x16 v_erf(const v_float32x16& x) { return v_erf_default_32f<v_float32x16, v_int32x16>(x); }
+
+inline v_float64x8 v_exp(const v_float64x8& x) { return v_exp_default_64f<v_float64x8, v_int64x8>(x); }
+inline v_float64x8 v_log(const v_float64x8& x) { return v_log_default_64f<v_float64x8, v_int64x8>(x); }
+inline void v_sincos(const v_float64x8& x, v_float64x8& s, v_float64x8& c) { v_sincos_default_64f<v_float64x8, v_int64x8>(x, s, c); }
+inline v_float64x8 v_sin(const v_float64x8& x) { return v_sin_default_64f<v_float64x8, v_int64x8>(x); }
+inline v_float64x8 v_cos(const v_float64x8& x) { return v_cos_default_64f<v_float64x8, v_int64x8>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+} // cv::
+
+#endif // OPENCV_HAL_INTRIN_AVX_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_cpp.hpp

@@ -0,0 +1,3373 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_HAL_INTRIN_CPP_HPP
+#define OPENCV_HAL_INTRIN_CPP_HPP
+
+#include <limits>
+#include <cstring>
+#include <algorithm>
+#include "opencv2/core/utility.hpp"
+#include "opencv2/core/saturate.hpp"
+
+//! @cond IGNORED
+#define CV_SIMD128_CPP 1
+#if defined(CV_FORCE_SIMD128_CPP)
+#define CV_SIMD128 1
+#define CV_SIMD128_64F 1
+#endif
+#if defined(CV_DOXYGEN)
+#define CV_SIMD128 1
+#define CV_SIMD128_64F 1
+#define CV_SIMD256 1
+#define CV_SIMD256_64F 1
+#define CV_SIMD512 1
+#define CV_SIMD512_64F 1
+#else
+#define CV_SIMD256 0 // Explicitly disable SIMD256 and SIMD512 support for scalar intrinsic implementation
+#define CV_SIMD512 0 // to avoid warnings during compilation
+#endif
+//! @endcond
+
+namespace cv
+{
+
+#ifndef CV_DOXYGEN
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+#endif
+
+/** @addtogroup core_hal_intrin
+
+"Universal intrinsics" is a types and functions set intended to simplify vectorization of code on
+different platforms. Currently a few different SIMD extensions on different architectures are supported.
+128 bit registers of various types support is implemented for a wide range of architectures
+including x86(__SSE/SSE2/SSE4.2__), ARM(__NEON__), PowerPC(__VSX__), MIPS(__MSA__).
+256 bit long registers are supported on x86(__AVX2__) and 512 bit long registers are supported on x86(__AVX512__).
+In case when there is no SIMD extension available during compilation, fallback C++ implementation of intrinsics
+will be chosen and code will work as expected although it could be slower.
+
+### Types
+
+There are several types representing packed values vector registers, each type is
+implemented as a structure based on a one SIMD register.
+
+- cv::v_uint8 and cv::v_int8: 8-bit integer values (unsigned/signed) - char
+- cv::v_uint16 and cv::v_int16: 16-bit integer values (unsigned/signed) - short
+- cv::v_uint32 and cv::v_int32: 32-bit integer values (unsigned/signed) - int
+- cv::v_uint64 and cv::v_int64: 64-bit integer values (unsigned/signed) - int64
+- cv::v_float32: 32-bit floating point values (signed) - float
+- cv::v_float64: 64-bit floating point values (signed) - double
+
+Exact bit length(and value quantity) of listed types is compile time deduced and depends on architecture SIMD
+capabilities chosen as available during compilation of the library. All the types contains __nlanes__ enumeration
+to check for exact value quantity of the type.
+
+In case the exact bit length of the type is important it is possible to use specific fixed length register types.
+
+There are several types representing 128-bit registers.
+
+- cv::v_uint8x16 and cv::v_int8x16: sixteen 8-bit integer values (unsigned/signed) - char
+- cv::v_uint16x8 and cv::v_int16x8: eight 16-bit integer values (unsigned/signed) - short
+- cv::v_uint32x4 and cv::v_int32x4: four 32-bit integer values (unsigned/signed) - int
+- cv::v_uint64x2 and cv::v_int64x2: two 64-bit integer values (unsigned/signed) - int64
+- cv::v_float32x4: four 32-bit floating point values (signed) - float
+- cv::v_float64x2: two 64-bit floating point values (signed) - double
+
+There are several types representing 256-bit registers.
+
+- cv::v_uint8x32 and cv::v_int8x32: thirty two 8-bit integer values (unsigned/signed) - char
+- cv::v_uint16x16 and cv::v_int16x16: sixteen 16-bit integer values (unsigned/signed) - short
+- cv::v_uint32x8 and cv::v_int32x8: eight 32-bit integer values (unsigned/signed) - int
+- cv::v_uint64x4 and cv::v_int64x4: four 64-bit integer values (unsigned/signed) - int64
+- cv::v_float32x8: eight 32-bit floating point values (signed) - float
+- cv::v_float64x4: four 64-bit floating point values (signed) - double
+
+@note
+256 bit registers at the moment implemented for AVX2 SIMD extension only, if you want to use this type directly,
+don't forget to check the CV_SIMD256 preprocessor definition:
+@code
+#if CV_SIMD256
+//...
+#endif
+@endcode
+
+There are several types representing 512-bit registers.
+
+- cv::v_uint8x64 and cv::v_int8x64: sixty four 8-bit integer values (unsigned/signed) - char
+- cv::v_uint16x32 and cv::v_int16x32: thirty two 16-bit integer values (unsigned/signed) - short
+- cv::v_uint32x16 and cv::v_int32x16: sixteen 32-bit integer values (unsigned/signed) - int
+- cv::v_uint64x8 and cv::v_int64x8: eight 64-bit integer values (unsigned/signed) - int64
+- cv::v_float32x16: sixteen 32-bit floating point values (signed) - float
+- cv::v_float64x8: eight 64-bit floating point values (signed) - double
+@note
+512 bit registers at the moment implemented for AVX512 SIMD extension only, if you want to use this type directly,
+don't forget to check the CV_SIMD512 preprocessor definition.
+
+@note
+cv::v_float64x2 is not implemented in NEON variant, if you want to use this type, don't forget to
+check the CV_SIMD128_64F preprocessor definition.
+
+### Load and store operations
+
+These operations allow to set contents of the register explicitly or by loading it from some memory
+block and to save contents of the register to memory block.
+
+There are variable size register load operations that provide result of maximum available size
+depending on chosen platform capabilities.
+- Constructors:
+@ref v_reg::v_reg(const _Tp *ptr) "from memory",
+- Other create methods:
+vx_setall_s8, vx_setall_u8, ...,
+vx_setzero_u8, vx_setzero_s8, ...
+- Memory load operations:
+vx_load, vx_load_aligned, vx_load_low, vx_load_halves,
+- Memory operations with expansion of values:
+vx_load_expand, vx_load_expand_q
+
+Also there are fixed size register load/store operations.
+
+For 128 bit registers
+- Constructors:
+@ref v_reg::v_reg(const _Tp *ptr) "from memory",
+@ref v_reg::v_reg(_Tp s0, _Tp s1) "from two values", ...
+- Other create methods:
+@ref v_setall_s8, @ref v_setall_u8, ...,
+@ref v_setzero_u8, @ref v_setzero_s8, ...
+- Memory load operations:
+@ref v_load, @ref v_load_aligned, @ref v_load_low, @ref v_load_halves,
+- Memory operations with expansion of values:
+@ref v_load_expand, @ref v_load_expand_q
+
+For 256 bit registers(check CV_SIMD256 preprocessor definition)
+- Constructors:
+@ref v_reg::v_reg(const _Tp *ptr) "from memory",
+@ref v_reg::v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3) "from four values", ...
+- Other create methods:
+@ref v256_setall_s8, @ref v256_setall_u8, ...,
+@ref v256_setzero_u8, @ref v256_setzero_s8, ...
+- Memory load operations:
+@ref v256_load, @ref v256_load_aligned, @ref v256_load_low, @ref v256_load_halves,
+- Memory operations with expansion of values:
+@ref v256_load_expand, @ref v256_load_expand_q
+
+For 512 bit registers(check CV_SIMD512 preprocessor definition)
+- Constructors:
+@ref v_reg::v_reg(const _Tp *ptr) "from memory",
+@ref v_reg::v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3, _Tp s4, _Tp s5, _Tp s6, _Tp s7) "from eight values", ...
+- Other create methods:
+@ref v512_setall_s8, @ref v512_setall_u8, ...,
+@ref v512_setzero_u8, @ref v512_setzero_s8, ...
+- Memory load operations:
+@ref v512_load, @ref v512_load_aligned, @ref v512_load_low, @ref v512_load_halves,
+- Memory operations with expansion of values:
+@ref v512_load_expand, @ref v512_load_expand_q
+
+Store to memory operations are similar across different platform capabilities:
+@ref v_store, @ref v_store_aligned,
+@ref v_store_high, @ref v_store_low
+
+### Value reordering
+
+These operations allow to reorder or recombine elements in one or multiple vectors.
+
+- Interleave, deinterleave (2, 3 and 4 channels): @ref v_load_deinterleave, @ref v_store_interleave
+- Expand: @ref v_expand, @ref v_expand_low, @ref v_expand_high
+- Pack: @ref v_pack, @ref v_pack_u, @ref v_pack_b, @ref v_rshr_pack, @ref v_rshr_pack_u,
+@ref v_pack_store, @ref v_pack_u_store, @ref v_rshr_pack_store, @ref v_rshr_pack_u_store
+- Recombine: @ref v_zip, @ref v_recombine, @ref v_combine_low, @ref v_combine_high
+- Reverse: @ref v_reverse
+- Extract: @ref v_extract
+
+
+### Arithmetic, bitwise and comparison operations
+
+Element-wise binary and unary operations.
+
+- Arithmetics:
+@ref v_add(const v_reg &a, const v_reg &b) "+",
+@ref v_sub(const v_reg &a, const v_reg &b) "-",
+@ref v_mul(const v_reg &a, const v_reg &b) "*",
+@ref v_div(const v_reg &a, const v_reg &b) "/",
+@ref v_mul_expand
+
+- Non-saturating arithmetics: @ref v_add_wrap, @ref v_sub_wrap
+
+- Bitwise shifts:
+@ref v_shl(const v_reg &a, int s) "<<",
+@ref v_shr(const v_reg &a, int s) ">>",
+@ref v_shl, @ref v_shr
+
+- Bitwise logic:
+@ref v_and(const v_reg &a, const v_reg &b) "&",
+@ref v_or(const v_reg &a, const v_reg &b) "|",
+@ref v_xor(const v_reg &a, const v_reg &b) "^",
+@ref v_not(const v_reg &a) "~"
+
+- Comparison:
+@ref v_gt(const v_reg &a, const v_reg &b) ">",
+@ref v_ge(const v_reg &a, const v_reg &b) ">=",
+@ref v_lt(const v_reg &a, const v_reg &b) "<",
+@ref v_le(const v_reg &a, const v_reg &b) "<=",
+@ref v_eq(const v_reg &a, const v_reg &b) "==",
+@ref v_ne(const v_reg &a, const v_reg &b) "!="
+
+- min/max: @ref v_min, @ref v_max
+
+### Reduce and mask
+
+Most of these operations return only one value.
+
+- Reduce: @ref v_reduce_min, @ref v_reduce_max, @ref v_reduce_sum, @ref v_popcount
+- Mask: @ref v_signmask, @ref v_check_all, @ref v_check_any, @ref v_select
+
+### Other math
+
+- Some frequent operations: @ref v_sqrt, @ref v_invsqrt, @ref v_magnitude, @ref v_sqr_magnitude, @ref v_exp, @ref v_log,
+                            @ref v_erf, @ref v_sin, @ref v_cos
+- Absolute values: @ref v_abs, @ref v_absdiff, @ref v_absdiffs
+
+### Conversions
+
+Different type conversions and casts:
+
+- Rounding: @ref v_round, @ref v_floor, @ref v_ceil, @ref v_trunc,
+- To float: @ref v_cvt_f32, @ref v_cvt_f64
+- Reinterpret: @ref v_reinterpret_as_u8, @ref v_reinterpret_as_s8, ...
+
+### Matrix operations
+
+In these operations vectors represent matrix rows/columns: @ref v_dotprod, @ref v_dotprod_fast,
+@ref v_dotprod_expand, @ref v_dotprod_expand_fast, @ref v_matmul, @ref v_transpose4x4
+
+### Usability
+
+Most operations are implemented only for some subset of the available types, following matrices
+shows the applicability of different operations to the types.
+
+Regular integers:
+
+| Operations\\Types | uint 8 | int 8 | uint 16 | int 16 | uint 32 | int 32 |
+|-------------------|:-:|:-:|:-:|:-:|:-:|:-:|
+|load, store        | x | x | x | x | x | x |
+|interleave         | x | x | x | x | x | x |
+|expand             | x | x | x | x | x | x |
+|expand_low         | x | x | x | x | x | x |
+|expand_high        | x | x | x | x | x | x |
+|expand_q           | x | x |   |   |   |   |
+|add, sub           | x | x | x | x | x | x |
+|add_wrap, sub_wrap | x | x | x | x |   |   |
+|mul_wrap           | x | x | x | x |   |   |
+|mul                | x | x | x | x | x | x |
+|mul_expand         | x | x | x | x | x |   |
+|compare            | x | x | x | x | x | x |
+|shift              |   |   | x | x | x | x |
+|dotprod            |   |   |   | x |   | x |
+|dotprod_fast       |   |   |   | x |   | x |
+|dotprod_expand     | x | x | x | x |   | x |
+|dotprod_expand_fast| x | x | x | x |   | x |
+|logical            | x | x | x | x | x | x |
+|min, max           | x | x | x | x | x | x |
+|absdiff            | x | x | x | x | x | x |
+|absdiffs           |   | x |   | x |   |   |
+|reduce             | x | x | x | x | x | x |
+|mask               | x | x | x | x | x | x |
+|pack               | x | x | x | x | x | x |
+|pack_u             | x |   | x |   |   |   |
+|pack_b             | x |   |   |   |   |   |
+|unpack             | x | x | x | x | x | x |
+|extract            | x | x | x | x | x | x |
+|rotate (lanes)     | x | x | x | x | x | x |
+|cvt_flt32          |   |   |   |   |   | x |
+|cvt_flt64          |   |   |   |   |   | x |
+|transpose4x4       |   |   |   |   | x | x |
+|reverse            | x | x | x | x | x | x |
+|extract_n          | x | x | x | x | x | x |
+|broadcast_element  |   |   |   |   | x | x |
+
+Big integers:
+
+| Operations\\Types | uint 64 | int 64 |
+|-------------------|:-:|:-:|
+|load, store        | x | x |
+|add, sub           | x | x |
+|shift              | x | x |
+|logical            | x | x |
+|reverse            | x | x |
+|extract            | x | x |
+|rotate (lanes)     | x | x |
+|cvt_flt64          |   | x |
+|extract_n          | x | x |
+
+Floating point:
+
+| Operations\\Types | float 32 | float 64 |
+|-------------------|:-:|:-:|
+|load, store        | x | x |
+|interleave         | x |   |
+|add, sub           | x | x |
+|mul                | x | x |
+|div                | x | x |
+|compare            | x | x |
+|min, max           | x | x |
+|absdiff            | x | x |
+|reduce             | x |   |
+|mask               | x | x |
+|unpack             | x | x |
+|cvt_flt32          |   | x |
+|cvt_flt64          | x |   |
+|sqrt, abs          | x | x |
+|float math         | x | x |
+|transpose4x4       | x |   |
+|extract            | x | x |
+|rotate (lanes)     | x | x |
+|reverse            | x | x |
+|extract_n          | x | x |
+|broadcast_element  | x |   |
+|exp                | x | x |
+|log                | x | x |
+|sin, cos           | x | x |
+
+ @{ */
+
+template<typename _Tp, int n> struct v_reg
+{
+//! @cond IGNORED
+    typedef _Tp lane_type;
+    enum { nlanes = n };
+// !@endcond
+
+    /** @brief Constructor
+
+    Initializes register with data from memory
+    @param ptr pointer to memory block with data for register */
+    explicit v_reg(const _Tp* ptr) { for( int i = 0; i < n; i++ ) s[i] = ptr[i]; }
+
+    /** @brief Constructor
+
+    Initializes register with two 64-bit values */
+    v_reg(_Tp s0, _Tp s1) { s[0] = s0; s[1] = s1; }
+
+    /** @brief Constructor
+
+    Initializes register with four 32-bit values */
+    v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3) { s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3; }
+
+    /** @brief Constructor
+
+    Initializes register with eight 16-bit values */
+    v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3,
+           _Tp s4, _Tp s5, _Tp s6, _Tp s7)
+    {
+        s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3;
+        s[4] = s4; s[5] = s5; s[6] = s6; s[7] = s7;
+    }
+
+    /** @brief Constructor
+
+    Initializes register with sixteen 8-bit values */
+    v_reg(_Tp s0, _Tp s1, _Tp s2, _Tp s3,
+           _Tp s4, _Tp s5, _Tp s6, _Tp s7,
+           _Tp s8, _Tp s9, _Tp s10, _Tp s11,
+           _Tp s12, _Tp s13, _Tp s14, _Tp s15)
+    {
+        s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3;
+        s[4] = s4; s[5] = s5; s[6] = s6; s[7] = s7;
+        s[8] = s8; s[9] = s9; s[10] = s10; s[11] = s11;
+        s[12] = s12; s[13] = s13; s[14] = s14; s[15] = s15;
+    }
+
+    /** @brief Default constructor
+
+    Does not initialize anything*/
+    v_reg() {}
+
+    /** @brief Copy constructor */
+    v_reg(const v_reg<_Tp, n> & r)
+    {
+        for( int i = 0; i < n; i++ )
+            s[i] = r.s[i];
+    }
+    /** @brief Access first value
+
+    Returns value of the first lane according to register type, for example:
+    @code{.cpp}
+    v_int32x4 r(1, 2, 3, 4);
+    int v = r.get0(); // returns 1
+    v_uint64x2 r(1, 2);
+    uint64_t v = r.get0(); // returns 1
+    @endcode
+    */
+    _Tp get0() const { return s[0]; }
+
+//! @cond IGNORED
+    _Tp get(const int i) const { return s[i]; }
+    v_reg<_Tp, n> high() const
+    {
+        v_reg<_Tp, n> c;
+        int i;
+        for( i = 0; i < n/2; i++ )
+        {
+            c.s[i] = s[i+(n/2)];
+            c.s[i+(n/2)] = 0;
+        }
+        return c;
+    }
+
+    static v_reg<_Tp, n> zero()
+    {
+        v_reg<_Tp, n> c;
+        for( int i = 0; i < n; i++ )
+            c.s[i] = (_Tp)0;
+        return c;
+    }
+
+    static v_reg<_Tp, n> all(_Tp s)
+    {
+        v_reg<_Tp, n> c;
+        for( int i = 0; i < n; i++ )
+            c.s[i] = s;
+        return c;
+    }
+
+    template<typename _Tp2, int n2> v_reg<_Tp2, n2> reinterpret_as() const
+    {
+        size_t bytes = std::min(sizeof(_Tp2)*n2, sizeof(_Tp)*n);
+        v_reg<_Tp2, n2> c;
+        std::memcpy(&c.s[0], &s[0], bytes);
+        return c;
+    }
+
+    v_reg& operator=(const v_reg<_Tp, n> & r)
+    {
+        for( int i = 0; i < n; i++ )
+            s[i] = r.s[i];
+        return *this;
+    }
+
+    _Tp s[n];
+//! @endcond
+};
+
+/** @brief Sixteen 8-bit unsigned integer values */
+typedef v_reg<uchar, 16> v_uint8x16;
+/** @brief Sixteen 8-bit signed integer values */
+typedef v_reg<schar, 16> v_int8x16;
+/** @brief Eight 16-bit unsigned integer values */
+typedef v_reg<ushort, 8> v_uint16x8;
+/** @brief Eight 16-bit signed integer values */
+typedef v_reg<short, 8> v_int16x8;
+/** @brief Four 32-bit unsigned integer values */
+typedef v_reg<unsigned, 4> v_uint32x4;
+/** @brief Four 32-bit signed integer values */
+typedef v_reg<int, 4> v_int32x4;
+/** @brief Four 32-bit floating point values (single precision) */
+typedef v_reg<float, 4> v_float32x4;
+/** @brief Two 64-bit floating point values (double precision) */
+typedef v_reg<double, 2> v_float64x2;
+/** @brief Two 64-bit unsigned integer values */
+typedef v_reg<uint64, 2> v_uint64x2;
+/** @brief Two 64-bit signed integer values */
+typedef v_reg<int64, 2> v_int64x2;
+
+#if CV_SIMD256
+/** @brief Thirty two 8-bit unsigned integer values */
+typedef v_reg<uchar, 32> v_uint8x32;
+/** @brief Thirty two 8-bit signed integer values */
+typedef v_reg<schar, 32> v_int8x32;
+/** @brief Sixteen 16-bit unsigned integer values */
+typedef v_reg<ushort, 16> v_uint16x16;
+/** @brief Sixteen 16-bit signed integer values */
+typedef v_reg<short, 16> v_int16x16;
+/** @brief Eight 32-bit unsigned integer values */
+typedef v_reg<unsigned, 8> v_uint32x8;
+/** @brief Eight 32-bit signed integer values */
+typedef v_reg<int, 8> v_int32x8;
+/** @brief Eight 32-bit floating point values (single precision) */
+typedef v_reg<float, 8> v_float32x8;
+/** @brief Four 64-bit floating point values (double precision) */
+typedef v_reg<double, 4> v_float64x4;
+/** @brief Four 64-bit unsigned integer values */
+typedef v_reg<uint64, 4> v_uint64x4;
+/** @brief Four 64-bit signed integer values */
+typedef v_reg<int64, 4> v_int64x4;
+#endif
+
+#if CV_SIMD512
+/** @brief Sixty four 8-bit unsigned integer values */
+typedef v_reg<uchar, 64> v_uint8x64;
+/** @brief Sixty four 8-bit signed integer values */
+typedef v_reg<schar, 64> v_int8x64;
+/** @brief Thirty two 16-bit unsigned integer values */
+typedef v_reg<ushort, 32> v_uint16x32;
+/** @brief Thirty two 16-bit signed integer values */
+typedef v_reg<short, 32> v_int16x32;
+/** @brief Sixteen 32-bit unsigned integer values */
+typedef v_reg<unsigned, 16> v_uint32x16;
+/** @brief Sixteen 32-bit signed integer values */
+typedef v_reg<int, 16> v_int32x16;
+/** @brief Sixteen 32-bit floating point values (single precision) */
+typedef v_reg<float, 16> v_float32x16;
+/** @brief Eight 64-bit floating point values (double precision) */
+typedef v_reg<double, 8> v_float64x8;
+/** @brief Eight 64-bit unsigned integer values */
+typedef v_reg<uint64, 8> v_uint64x8;
+/** @brief Eight 64-bit signed integer values */
+typedef v_reg<int64, 8> v_int64x8;
+#endif
+
+enum {
+    simd128_width = 16,
+#if CV_SIMD256
+    simd256_width = 32,
+#endif
+#if CV_SIMD512
+    simd512_width = 64,
+    simdmax_width = simd512_width
+#elif CV_SIMD256
+    simdmax_width = simd256_width
+#else
+    simdmax_width = simd128_width
+#endif
+};
+
+/** @brief Add values
+
+For all types. */
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_add(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
+
+/** @brief Subtract values
+
+For all types. */
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_sub(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
+
+/** @brief Multiply values
+
+For 16- and 32-bit integer types and floating types. */
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_mul(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
+
+/** @brief Divide values
+
+For floating types only. */
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_div(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
+
+
+/** @brief Bitwise AND
+
+Only for integer types. */
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_and(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
+
+/** @brief Bitwise OR
+
+Only for integer types. */
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_or(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
+
+/** @brief Bitwise XOR
+
+Only for integer types.*/
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_xor(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b);
+
+/** @brief Bitwise NOT
+
+Only for integer types.*/
+template<typename _Tp, int n> CV_INLINE v_reg<_Tp, n> v_not(const v_reg<_Tp, n>& a);
+
+
+#ifndef CV_DOXYGEN
+
+#define CV__HAL_INTRIN_EXPAND_WITH_INTEGER_TYPES(macro_name, ...) \
+__CV_EXPAND(macro_name(uchar, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(schar, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(ushort, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(short, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(unsigned, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(int, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(uint64, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(int64, __VA_ARGS__)) \
+
+#define CV__HAL_INTRIN_EXPAND_WITH_FP_TYPES(macro_name, ...) \
+__CV_EXPAND(macro_name(float, __VA_ARGS__)) \
+__CV_EXPAND(macro_name(double, __VA_ARGS__)) \
+
+#define CV__HAL_INTRIN_EXPAND_WITH_ALL_TYPES(macro_name, ...) \
+CV__HAL_INTRIN_EXPAND_WITH_INTEGER_TYPES(macro_name, __VA_ARGS__) \
+CV__HAL_INTRIN_EXPAND_WITH_FP_TYPES(macro_name, __VA_ARGS__) \
+
+#define CV__HAL_INTRIN_IMPL_BIN_OP_(_Tp, bin_op, func) \
+template<int n> inline \
+v_reg<_Tp, n> func(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    v_reg<_Tp, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = saturate_cast<_Tp>(a.s[i] bin_op b.s[i]); \
+    return c; \
+}
+
+#define CV__HAL_INTRIN_IMPL_BIN_OP(bin_op, func) CV__HAL_INTRIN_EXPAND_WITH_ALL_TYPES(CV__HAL_INTRIN_IMPL_BIN_OP_, bin_op, func)
+
+CV__HAL_INTRIN_IMPL_BIN_OP(+, v_add)
+CV__HAL_INTRIN_IMPL_BIN_OP(-, v_sub)
+CV__HAL_INTRIN_IMPL_BIN_OP(*, v_mul)
+CV__HAL_INTRIN_EXPAND_WITH_FP_TYPES(CV__HAL_INTRIN_IMPL_BIN_OP_, /, v_div)
+
+#define CV__HAL_INTRIN_IMPL_BIT_OP_(_Tp, bit_op, func) \
+template<int n> CV_INLINE \
+v_reg<_Tp, n> func(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    v_reg<_Tp, n> c; \
+    typedef typename V_TypeTraits<_Tp>::int_type itype; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = V_TypeTraits<_Tp>::reinterpret_from_int((itype)(V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) bit_op \
+                                                        V_TypeTraits<_Tp>::reinterpret_int(b.s[i]))); \
+    return c; \
+}
+
+#define CV__HAL_INTRIN_IMPL_BIT_OP(bit_op, func) \
+CV__HAL_INTRIN_EXPAND_WITH_INTEGER_TYPES(CV__HAL_INTRIN_IMPL_BIT_OP_, bit_op, func) \
+CV__HAL_INTRIN_EXPAND_WITH_FP_TYPES(CV__HAL_INTRIN_IMPL_BIT_OP_, bit_op, func) /* TODO: FIXIT remove this after masks refactoring */
+
+
+CV__HAL_INTRIN_IMPL_BIT_OP(&, v_and)
+CV__HAL_INTRIN_IMPL_BIT_OP(|, v_or)
+CV__HAL_INTRIN_IMPL_BIT_OP(^, v_xor)
+
+#define CV__HAL_INTRIN_IMPL_BITWISE_NOT_(_Tp, dummy, dummy2) \
+template<int n> CV_INLINE \
+v_reg<_Tp, n> v_not(const v_reg<_Tp, n>& a) \
+{ \
+    v_reg<_Tp, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = V_TypeTraits<_Tp>::reinterpret_from_int(~V_TypeTraits<_Tp>::reinterpret_int(a.s[i])); \
+    return c; \
+} \
+
+CV__HAL_INTRIN_EXPAND_WITH_INTEGER_TYPES(CV__HAL_INTRIN_IMPL_BITWISE_NOT_, ~, v_not)
+
+#endif  // !CV_DOXYGEN
+
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_MATH_FUNC(func, cfunc, _Tp2) \
+template<typename _Tp, int n> inline v_reg<_Tp2, n> func(const v_reg<_Tp, n>& a) \
+{ \
+    v_reg<_Tp2, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = cfunc(a.s[i]); \
+    return c; \
+}
+
+/** @brief Square root of elements
+
+Only for floating point types.*/
+OPENCV_HAL_IMPL_MATH_FUNC(v_sqrt, std::sqrt, _Tp)
+
+/**
+ * @brief Exponential \f$ e^x \f$ of elements
+ *
+ * Only for floating point types. Core implementation steps:
+ * 1. Decompose Input: Convert the input to \f$ 2^{x \cdot \log_2e} \f$ and split its exponential into integer and fractional parts:
+ *    \f$ x \cdot \log_2e = n + f \f$, where \f$ n \f$ is the integer part and \f$ f \f$ is the fractional part.
+ * 2. Compute \f$ 2^n \f$: Calculated by shifting the bits.
+ * 3. Adjust Fractional Part: Compute \f$ f \cdot \ln2 \f$ to convert the fractional part to base \f$ e \f$.
+ *    \f$ C1 \f$ and \f$ C2 \f$ are used to adjust the fractional part.
+ * 4. Polynomial Approximation for \f$ e^{f \cdot \ln2} \f$: The closer the fractional part is to 0, the more accurate the result.
+ *    - For float16 and float32, use a Taylor Series with 6 terms.
+ *    - For float64, use Pade Polynomials Approximation with 4 terms.
+ * 5. Combine Results: Multiply the two parts together to get the final result:
+ *    \f$ e^x = 2^n \cdot e^{f \cdot \ln2} \f$.
+ *
+ * @note The precision of the calculation depends on the implementation and the data type of the input vector.
+ */
+OPENCV_HAL_IMPL_MATH_FUNC(v_exp, std::exp, _Tp)
+#define OPENCV_HAL_MATH_HAVE_EXP 1
+
+/**
+ * @brief Natural logarithm \f$ \log(x) \f$ of elements
+ *
+ * Only for floating point types. Core implementation steps:
+ * 1. Decompose Input: Use binary representation to decompose the input into mantissa part \f$ m \f$ and exponent part \f$ e \f$. Such that \f$ \log(x) = \log(m \cdot 2^e) = \log(m) + e \cdot \ln(2) \f$.
+ * 2. Adjust Mantissa and Exponent Parts: If the mantissa is less than \f$ \sqrt{0.5} \f$, adjust the exponent and mantissa to ensure the mantissa is in the range \f$ (\sqrt{0.5}, \sqrt{2}) \f$ for better approximation.
+ * 3. Polynomial Approximation for \f$ \log(m) \f$: The closer the \f$ m \f$ is to 1, the more accurate the result.
+ *    - For float16 and float32, use a Taylor Series with 9 terms.
+ *    - For float64, use Pade Polynomials Approximation with 6 terms.
+ * 4. Combine Results: Add the two parts together to get the final result.
+ *
+ * @note The precision of the calculation depends on the implementation and the data type of the input.
+ *
+ * @note Similar to the behavior of std::log(), \f$ \ln(0) = -\infty \f$.
+ */
+OPENCV_HAL_IMPL_MATH_FUNC(v_log, std::log, _Tp)
+
+/**
+ * @brief Error function.
+ *
+ * @note Support FP32 precision for now.
+ */
+OPENCV_HAL_IMPL_MATH_FUNC(v_erf, std::erf, _Tp)
+
+/**
+ * @brief Compute sine \f$ sin(x) \f$ and cosine \f$ cos(x) \f$ of elements at the same time
+ *
+ * Only for floating point types. Core implementation steps:
+ * 1. Input Normalization: Scale the periodicity from 2π to 4 and reduce the angle to the range \f$ [0, \frac{\pi}{4}] \f$ using periodicity and trigonometric identities.
+ * 2. Polynomial Approximation for \f$ sin(x) \f$ and \f$ cos(x) \f$:
+ *   - For float16 and float32, use a Taylor series with 4 terms for sine and 5 terms for cosine.
+ *   - For float64, use a Taylor series with 7 terms for sine and 8 terms for cosine.
+ * 3. Select Results: select and convert the final sine and cosine values for the original input angle.
+ *
+ * @note The precision of the calculation depends on the implementation and the data type of the input vector.
+ */
+template<typename _Tp, int n>
+inline void v_sincos(const v_reg<_Tp, n>& x, v_reg<_Tp, n>& s, v_reg<_Tp, n>& c)
+{
+    for( int i = 0; i < n; i++ )
+    {
+        s.s[i] = std::sin(x.s[i]);
+        c.s[i] = std::cos(x.s[i]);
+    }
+}
+
+/**
+ * @brief Sine \f$ sin(x) \f$ of elements
+ *
+ * Only for floating point types. Core implementation the same as @ref v_sincos.
+ */
+OPENCV_HAL_IMPL_MATH_FUNC(v_sin, std::sin, _Tp)
+
+/**
+ * @brief Cosine \f$ cos(x) \f$ of elements
+ *
+ * Only for floating point types. Core implementation the same as @ref v_sincos.
+ */
+OPENCV_HAL_IMPL_MATH_FUNC(v_cos, std::cos, _Tp)
+
+/** @brief Absolute value of elements
+
+Only for floating point types.*/
+OPENCV_HAL_IMPL_MATH_FUNC(v_abs, (typename V_TypeTraits<_Tp>::abs_type)std::abs,
+                          typename V_TypeTraits<_Tp>::abs_type)
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_MINMAX_FUNC(func, cfunc) \
+template<typename _Tp, int n> inline v_reg<_Tp, n> func(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    v_reg<_Tp, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = cfunc(a.s[i], b.s[i]); \
+    return c; \
+}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_REDUCE_MINMAX_FUNC(func, cfunc) \
+template<typename _Tp, int n> inline _Tp func(const v_reg<_Tp, n>& a) \
+{ \
+    _Tp c = a.s[0]; \
+    for( int i = 1; i < n; i++ ) \
+        c = cfunc(c, a.s[i]); \
+    return c; \
+}
+
+/** @brief Choose min values for each pair
+
+Scheme:
+@code
+{A1 A2 ...}
+{B1 B2 ...}
+--------------
+{min(A1,B1) min(A2,B2) ...}
+@endcode
+For all types except 64-bit integer. */
+OPENCV_HAL_IMPL_MINMAX_FUNC(v_min, std::min)
+
+/** @brief Choose max values for each pair
+
+Scheme:
+@code
+{A1 A2 ...}
+{B1 B2 ...}
+--------------
+{max(A1,B1) max(A2,B2) ...}
+@endcode
+For all types except 64-bit integer. */
+OPENCV_HAL_IMPL_MINMAX_FUNC(v_max, std::max)
+
+/** @brief Find one min value
+
+Scheme:
+@code
+{A1 A2 A3 ...} => min(A1,A2,A3,...)
+@endcode
+For all types except 64-bit integer and 64-bit floating point types. */
+OPENCV_HAL_IMPL_REDUCE_MINMAX_FUNC(v_reduce_min, std::min)
+
+/** @brief Find one max value
+
+Scheme:
+@code
+{A1 A2 A3 ...} => max(A1,A2,A3,...)
+@endcode
+For all types except 64-bit integer and 64-bit floating point types. */
+OPENCV_HAL_IMPL_REDUCE_MINMAX_FUNC(v_reduce_max, std::max)
+
+static const unsigned char popCountTable[] =
+{
+    0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8,
+};
+/** @brief Count the 1 bits in the vector lanes and return result as corresponding unsigned type
+
+Scheme:
+@code
+{A1 A2 A3 ...} => {popcount(A1), popcount(A2), popcount(A3), ...}
+@endcode
+For all integer types. */
+template<typename _Tp, int n>
+inline v_reg<typename V_TypeTraits<_Tp>::abs_type, n> v_popcount(const v_reg<_Tp, n>& a)
+{
+    v_reg<typename V_TypeTraits<_Tp>::abs_type, n> b = v_reg<typename V_TypeTraits<_Tp>::abs_type, n>::zero();
+    for (int i = 0; i < n*(int)sizeof(_Tp); i++)
+        b.s[i/sizeof(_Tp)] += popCountTable[v_reinterpret_as_u8(a).s[i]];
+    return b;
+}
+
+
+//! @cond IGNORED
+template<typename _Tp, int n>
+inline void v_minmax( const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+                      v_reg<_Tp, n>& minval, v_reg<_Tp, n>& maxval )
+{
+    for( int i = 0; i < n; i++ )
+    {
+        minval.s[i] = std::min(a.s[i], b.s[i]);
+        maxval.s[i] = std::max(a.s[i], b.s[i]);
+    }
+}
+//! @endcond
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_CMP_OP(cmp_op, func) \
+template<typename _Tp, int n> \
+inline v_reg<_Tp, n> func(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    typedef typename V_TypeTraits<_Tp>::int_type itype; \
+    v_reg<_Tp, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = V_TypeTraits<_Tp>::reinterpret_from_int((itype)-(int)(a.s[i] cmp_op b.s[i])); \
+    return c; \
+}
+
+/** @brief Less-than comparison
+
+For all types except 64-bit integer values. */
+OPENCV_HAL_IMPL_CMP_OP(<, v_lt)
+
+/** @brief Greater-than comparison
+
+For all types except 64-bit integer values. */
+OPENCV_HAL_IMPL_CMP_OP(>, v_gt)
+
+/** @brief Less-than or equal comparison
+
+For all types except 64-bit integer values. */
+OPENCV_HAL_IMPL_CMP_OP(<=, v_le)
+
+/** @brief Greater-than or equal comparison
+
+For all types except 64-bit integer values. */
+OPENCV_HAL_IMPL_CMP_OP(>=, v_ge)
+
+/** @brief Equal comparison */
+OPENCV_HAL_IMPL_CMP_OP(==, v_eq)
+
+/** @brief Not equal comparison */
+OPENCV_HAL_IMPL_CMP_OP(!=, v_ne)
+
+template<int n>
+inline v_reg<float, n> v_not_nan(const v_reg<float, n>& a)
+{
+    typedef typename V_TypeTraits<float>::int_type itype;
+    v_reg<float, n> c;
+    for (int i = 0; i < n; i++)
+        c.s[i] = V_TypeTraits<float>::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i]));
+    return c;
+}
+template<int n>
+inline v_reg<double, n> v_not_nan(const v_reg<double, n>& a)
+{
+    typedef typename V_TypeTraits<double>::int_type itype;
+    v_reg<double, n> c;
+    for (int i = 0; i < n; i++)
+        c.s[i] = V_TypeTraits<double>::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i]));
+    return c;
+}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_ARITHM_OP(func, bin_op, cast_op, _Tp2) \
+template<typename _Tp, int n> \
+inline v_reg<_Tp2, n> func(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    typedef _Tp2 rtype; \
+    v_reg<rtype, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = cast_op(a.s[i] bin_op b.s[i]); \
+    return c; \
+}
+
+/** @brief Add values without saturation
+
+For 8- and 16-bit integer values. */
+OPENCV_HAL_IMPL_ARITHM_OP(v_add_wrap, +, (_Tp), _Tp)
+
+/** @brief Subtract values without saturation
+
+For 8- and 16-bit integer values. */
+OPENCV_HAL_IMPL_ARITHM_OP(v_sub_wrap, -, (_Tp), _Tp)
+
+/** @brief Multiply values without saturation
+
+For 8- and 16-bit integer values. */
+OPENCV_HAL_IMPL_ARITHM_OP(v_mul_wrap, *, (_Tp), _Tp)
+
+//! @cond IGNORED
+template<typename T> inline T _absdiff(T a, T b)
+{
+    return a > b ? a - b : b - a;
+}
+//! @endcond
+
+/** @brief Absolute difference
+
+Returns \f$ |a - b| \f$ converted to corresponding unsigned type.
+Example:
+@code{.cpp}
+v_int32x4 a, b; // {1, 2, 3, 4} and {4, 3, 2, 1}
+v_uint32x4 c = v_absdiff(a, b); // result is {3, 1, 1, 3}
+@endcode
+For 8-, 16-, 32-bit integer source types. */
+template<typename _Tp, int n>
+inline v_reg<typename V_TypeTraits<_Tp>::abs_type, n> v_absdiff(const v_reg<_Tp, n>& a, const v_reg<_Tp, n> & b)
+{
+    typedef typename V_TypeTraits<_Tp>::abs_type rtype;
+    v_reg<rtype, n> c;
+    const rtype mask = (rtype)(std::numeric_limits<_Tp>::is_signed ? (1 << (sizeof(rtype)*8 - 1)) : 0);
+    for( int i = 0; i < n; i++ )
+    {
+        rtype ua = a.s[i] ^ mask;
+        rtype ub = b.s[i] ^ mask;
+        c.s[i] = _absdiff(ua, ub);
+    }
+    return c;
+}
+
+/** @overload
+
+For 32-bit floating point values */
+template<int n> inline v_reg<float, n> v_absdiff(const v_reg<float, n>& a, const v_reg<float, n>& b)
+{
+    v_reg<float, n> c;
+    for( int i = 0; i < c.nlanes; i++ )
+        c.s[i] = _absdiff(a.s[i], b.s[i]);
+    return c;
+}
+
+/** @overload
+
+For 64-bit floating point values */
+template<int n> inline v_reg<double, n> v_absdiff(const v_reg<double, n>& a, const v_reg<double, n>& b)
+{
+    v_reg<double, n> c;
+    for( int i = 0; i < c.nlanes; i++ )
+        c.s[i] = _absdiff(a.s[i], b.s[i]);
+    return c;
+}
+
+/** @brief Saturating absolute difference
+
+Returns \f$ saturate(|a - b|) \f$ .
+For 8-, 16-bit signed integer source types. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_absdiffs(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < n; i++)
+        c.s[i] = saturate_cast<_Tp>(std::abs(a.s[i] - b.s[i]));
+    return c;
+}
+
+/** @brief Inversed square root
+
+Returns \f$ 1/sqrt(a) \f$
+For floating point types only. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_invsqrt(const v_reg<_Tp, n>& a)
+{
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = 1.f/std::sqrt(a.s[i]);
+    return c;
+}
+
+/** @brief Magnitude
+
+Returns \f$ sqrt(a^2 + b^2) \f$
+For floating point types only. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_magnitude(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = std::sqrt(a.s[i]*a.s[i] + b.s[i]*b.s[i]);
+    return c;
+}
+
+/** @brief Square of the magnitude
+
+Returns \f$ a^2 + b^2 \f$
+For floating point types only. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_sqr_magnitude(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = a.s[i]*a.s[i] + b.s[i]*b.s[i];
+    return c;
+}
+
+/** @brief Multiply and add
+
+ Returns \f$ a*b + c \f$
+ For floating point types and signed 32bit int only. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_fma(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+                           const v_reg<_Tp, n>& c)
+{
+    v_reg<_Tp, n> d;
+    for( int i = 0; i < n; i++ )
+        d.s[i] = a.s[i]*b.s[i] + c.s[i];
+    return d;
+}
+
+/** @brief A synonym for v_fma */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_muladd(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+                              const v_reg<_Tp, n>& c)
+{
+    return v_fma(a, b, c);
+}
+
+/** @brief Dot product of elements
+
+Multiply values in two registers and sum adjacent result pairs.
+
+Scheme:
+@code
+  {A1 A2 ...} // 16-bit
+x {B1 B2 ...} // 16-bit
+-------------
+{A1B1+A2B2 ...} // 32-bit
+
+@endcode
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>
+v_dotprod(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    v_reg<w_type, n/2> c;
+    for( int i = 0; i < (n/2); i++ )
+        c.s[i] = (w_type)a.s[i*2]*b.s[i*2] + (w_type)a.s[i*2+1]*b.s[i*2+1];
+    return c;
+}
+
+/** @brief Dot product of elements
+
+Same as cv::v_dotprod, but add a third element to the sum of adjacent pairs.
+Scheme:
+@code
+  {A1 A2 ...} // 16-bit
+x {B1 B2 ...} // 16-bit
+-------------
+  {A1B1+A2B2+C1 ...} // 32-bit
+@endcode
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>
+v_dotprod(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+          const v_reg<typename V_TypeTraits<_Tp>::w_type, n / 2>& c)
+{
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    v_reg<w_type, n/2> s;
+    for( int i = 0; i < (n/2); i++ )
+        s.s[i] = (w_type)a.s[i*2]*b.s[i*2] + (w_type)a.s[i*2+1]*b.s[i*2+1] + c.s[i];
+    return s;
+}
+
+/** @brief Fast Dot product of elements
+
+Same as cv::v_dotprod, but it may perform unorder sum between result pairs in some platforms,
+this intrinsic can be used if the sum among all lanes is only matters
+and also it should be yielding better performance on the affected platforms.
+
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>
+v_dotprod_fast(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{ return v_dotprod(a, b); }
+
+/** @brief Fast Dot product of elements
+
+Same as cv::v_dotprod_fast, but add a third element to the sum of adjacent pairs.
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>
+v_dotprod_fast(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+               const v_reg<typename V_TypeTraits<_Tp>::w_type, n / 2>& c)
+{ return v_dotprod(a, b, c); }
+
+/** @brief Dot product of elements and expand
+
+Multiply values in two registers and expand the sum of adjacent result pairs.
+
+Scheme:
+@code
+  {A1 A2 A3 A4 ...} // 8-bit
+x {B1 B2 B3 B4 ...} // 8-bit
+-------------
+  {A1B1+A2B2+A3B3+A4B4 ...} // 32-bit
+
+@endcode
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::q_type, n/4>
+v_dotprod_expand(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    typedef typename V_TypeTraits<_Tp>::q_type q_type;
+    v_reg<q_type, n/4> s;
+    for( int i = 0; i < (n/4); i++ )
+        s.s[i] = (q_type)a.s[i*4    ]*b.s[i*4    ] + (q_type)a.s[i*4 + 1]*b.s[i*4 + 1] +
+                 (q_type)a.s[i*4 + 2]*b.s[i*4 + 2] + (q_type)a.s[i*4 + 3]*b.s[i*4 + 3];
+    return s;
+}
+
+/** @brief Dot product of elements
+
+Same as cv::v_dotprod_expand, but add a third element to the sum of adjacent pairs.
+Scheme:
+@code
+  {A1 A2 A3 A4 ...} // 8-bit
+x {B1 B2 B3 B4 ...} // 8-bit
+-------------
+  {A1B1+A2B2+A3B3+A4B4+C1 ...} // 32-bit
+@endcode
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::q_type, n/4>
+v_dotprod_expand(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+                 const v_reg<typename V_TypeTraits<_Tp>::q_type, n / 4>& c)
+{
+    typedef typename V_TypeTraits<_Tp>::q_type q_type;
+    v_reg<q_type, n/4> s;
+    for( int i = 0; i < (n/4); i++ )
+        s.s[i] = (q_type)a.s[i*4    ]*b.s[i*4    ] + (q_type)a.s[i*4 + 1]*b.s[i*4 + 1] +
+                 (q_type)a.s[i*4 + 2]*b.s[i*4 + 2] + (q_type)a.s[i*4 + 3]*b.s[i*4 + 3] + c.s[i];
+    return s;
+}
+
+/** @brief Fast Dot product of elements and expand
+
+Multiply values in two registers and expand the sum of adjacent result pairs.
+
+Same as cv::v_dotprod_expand, but it may perform unorder sum between result pairs in some platforms,
+this intrinsic can be used if the sum among all lanes is only matters
+and also it should be yielding better performance on the affected platforms.
+
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::q_type, n/4>
+v_dotprod_expand_fast(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{ return v_dotprod_expand(a, b); }
+
+/** @brief Fast Dot product of elements
+
+Same as cv::v_dotprod_expand_fast, but add a third element to the sum of adjacent pairs.
+*/
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::q_type, n/4>
+v_dotprod_expand_fast(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+                      const v_reg<typename V_TypeTraits<_Tp>::q_type, n / 4>& c)
+{ return v_dotprod_expand(a, b, c); }
+
+/** @brief Multiply and expand
+
+Multiply values two registers and store results in two registers with wider pack type.
+Scheme:
+@code
+  {A B C D} // 32-bit
+x {E F G H} // 32-bit
+---------------
+{AE BF}         // 64-bit
+        {CG DH} // 64-bit
+@endcode
+Example:
+@code{.cpp}
+v_uint32x4 a, b; // {1,2,3,4} and {2,2,2,2}
+v_uint64x2 c, d; // results
+v_mul_expand(a, b, c, d); // c, d = {2,4}, {6, 8}
+@endcode
+Implemented only for 16- and unsigned 32-bit source types (v_int16x8, v_uint16x8, v_uint32x4).
+*/
+template<typename _Tp, int n> inline void v_mul_expand(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+                                                       v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>& c,
+                                                       v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>& d)
+{
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    for( int i = 0; i < (n/2); i++ )
+    {
+        c.s[i] = (w_type)a.s[i]*b.s[i];
+        d.s[i] = (w_type)a.s[i+(n/2)]*b.s[i+(n/2)];
+    }
+}
+
+/** @brief Multiply and extract high part
+
+Multiply values two registers and store high part of the results.
+Implemented only for 16-bit source types (v_int16x8, v_uint16x8). Returns \f$ a*b >> 16 \f$
+*/
+template<typename _Tp, int n> inline v_reg<_Tp, n> v_mul_hi(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    v_reg<_Tp, n> c;
+    for (int i = 0; i < n; i++)
+        c.s[i] = (_Tp)(((w_type)a.s[i] * b.s[i]) >> sizeof(_Tp)*8);
+    return c;
+}
+
+//! @cond IGNORED
+template<typename _Tp, int n> inline void v_hsum(const v_reg<_Tp, n>& a,
+                                                 v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>& c)
+{
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    for( int i = 0; i < (n/2); i++ )
+    {
+        c.s[i] = (w_type)a.s[i*2] + a.s[i*2+1];
+    }
+}
+//! @endcond
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_SHIFT_OP(shift_op, func) \
+template<typename _Tp, int n> inline v_reg<_Tp, n> func(const v_reg<_Tp, n>& a, int imm) \
+{ \
+    v_reg<_Tp, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = (_Tp)(a.s[i] shift_op imm); \
+    return c; \
+}
+
+/** @brief Bitwise shift left
+
+For 16-, 32- and 64-bit integer values. */
+OPENCV_HAL_IMPL_SHIFT_OP(<<, v_shl)
+
+/** @brief Bitwise shift right
+
+For 16-, 32- and 64-bit integer values. */
+OPENCV_HAL_IMPL_SHIFT_OP(>>, v_shr)
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_ROTATE_SHIFT_OP(suffix,opA,opB) \
+template<int imm, typename _Tp, int n> inline v_reg<_Tp, n> v_rotate_##suffix(const v_reg<_Tp, n>& a) \
+{ \
+    v_reg<_Tp, n> b; \
+    for (int i = 0; i < n; i++) \
+    { \
+        int sIndex = i opA imm; \
+        if (0 <= sIndex && sIndex < n) \
+        { \
+            b.s[i] = a.s[sIndex]; \
+        } \
+        else \
+        { \
+            b.s[i] = 0; \
+        } \
+    } \
+    return b; \
+} \
+template<int imm, typename _Tp, int n> inline v_reg<_Tp, n> v_rotate_##suffix(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    v_reg<_Tp, n> c; \
+    for (int i = 0; i < n; i++) \
+    { \
+        int aIndex = i opA imm; \
+        int bIndex = i opA imm opB n; \
+        if (0 <= bIndex && bIndex < n) \
+        { \
+            c.s[i] = b.s[bIndex]; \
+        } \
+        else if (0 <= aIndex && aIndex < n) \
+        { \
+            c.s[i] = a.s[aIndex]; \
+        } \
+        else \
+        { \
+            c.s[i] = 0; \
+        } \
+    } \
+    return c; \
+}
+
+/** @brief Element shift left among vector
+
+For all type */
+OPENCV_HAL_IMPL_ROTATE_SHIFT_OP(left,  -, +)
+
+/** @brief Element shift right among vector
+
+For all type */
+OPENCV_HAL_IMPL_ROTATE_SHIFT_OP(right, +, -)
+
+/** @brief Sum packed values
+
+Scheme:
+@code
+{A1 A2 A3 ...} => sum{A1,A2,A3,...}
+@endcode
+*/
+template<typename _Tp, int n> inline typename V_TypeTraits<_Tp>::sum_type v_reduce_sum(const v_reg<_Tp, n>& a)
+{
+    typename V_TypeTraits<_Tp>::sum_type c = a.s[0];
+    for( int i = 1; i < n; i++ )
+        c += a.s[i];
+    return c;
+}
+
+/** @brief Sums all elements of each input vector, returns the vector of sums
+
+ Scheme:
+ @code
+ result[0] = a[0] + a[1] + a[2] + a[3]
+ result[1] = b[0] + b[1] + b[2] + b[3]
+ result[2] = c[0] + c[1] + c[2] + c[3]
+ result[3] = d[0] + d[1] + d[2] + d[3]
+ @endcode
+*/
+template<int n> inline v_reg<float, n> v_reduce_sum4(const v_reg<float, n>& a, const v_reg<float, n>& b,
+    const v_reg<float, n>& c, const v_reg<float, n>& d)
+{
+    v_reg<float, n> r;
+    for(int i = 0; i < (n/4); i++)
+    {
+        r.s[i*4 + 0] = a.s[i*4 + 0] + a.s[i*4 + 1] + a.s[i*4 + 2] + a.s[i*4 + 3];
+        r.s[i*4 + 1] = b.s[i*4 + 0] + b.s[i*4 + 1] + b.s[i*4 + 2] + b.s[i*4 + 3];
+        r.s[i*4 + 2] = c.s[i*4 + 0] + c.s[i*4 + 1] + c.s[i*4 + 2] + c.s[i*4 + 3];
+        r.s[i*4 + 3] = d.s[i*4 + 0] + d.s[i*4 + 1] + d.s[i*4 + 2] + d.s[i*4 + 3];
+    }
+    return r;
+}
+
+/** @brief Sum absolute differences of values
+
+Scheme:
+@code
+{A1 A2 A3 ...} {B1 B2 B3 ...} => sum{ABS(A1-B1),abs(A2-B2),abs(A3-B3),...}
+@endcode
+For all types except 64-bit types.*/
+template<typename _Tp, int n> inline typename V_TypeTraits< typename V_TypeTraits<_Tp>::abs_type >::sum_type v_reduce_sad(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    typename V_TypeTraits< typename V_TypeTraits<_Tp>::abs_type >::sum_type c = _absdiff(a.s[0], b.s[0]);
+    for (int i = 1; i < n; i++)
+        c += _absdiff(a.s[i], b.s[i]);
+    return c;
+}
+
+/** @brief Get negative values mask
+@deprecated v_signmask depends on a lane count heavily and therefore isn't universal enough
+
+Returned value is a bit mask with bits set to 1 on places corresponding to negative packed values indexes.
+Example:
+@code{.cpp}
+v_int32x4 r; // set to {-1, -1, 1, 1}
+int mask = v_signmask(r); // mask = 3 <== 00000000 00000000 00000000 00000011
+@endcode
+*/
+template<typename _Tp, int n> inline int v_signmask(const v_reg<_Tp, n>& a)
+{
+    int mask = 0;
+    for( int i = 0; i < n; i++ )
+        mask |= (V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) < 0) << i;
+    return mask;
+}
+
+/** @brief Get first negative lane index
+
+Returned value is an index of first negative lane (undefined for input of all positive values)
+Example:
+@code{.cpp}
+v_int32x4 r; // set to {0, 0, -1, -1}
+int idx = v_heading_zeros(r); // idx = 2
+@endcode
+*/
+template <typename _Tp, int n> inline int v_scan_forward(const v_reg<_Tp, n>& a)
+{
+    for (int i = 0; i < n; i++)
+        if(V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) < 0)
+            return i;
+    return 0;
+}
+
+/** @brief Check if all packed values are less than zero
+
+Unsigned values will be casted to signed: `uchar 254 => char -2`.
+*/
+template<typename _Tp, int n> inline bool v_check_all(const v_reg<_Tp, n>& a)
+{
+    for( int i = 0; i < n; i++ )
+        if( V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) >= 0 )
+            return false;
+    return true;
+}
+
+/** @brief Check if any of packed values is less than zero
+
+Unsigned values will be casted to signed: `uchar 254 => char -2`.
+*/
+template<typename _Tp, int n> inline bool v_check_any(const v_reg<_Tp, n>& a)
+{
+    for( int i = 0; i < n; i++ )
+        if( V_TypeTraits<_Tp>::reinterpret_int(a.s[i]) < 0 )
+            return true;
+    return false;
+}
+
+/** @brief Per-element select (blend operation)
+
+Return value will be built by combining values _a_ and _b_ using the following scheme:
+    result[i] = mask[i] ? a[i] : b[i];
+
+@note: _mask_ element values are restricted to these values:
+- 0: select element from _b_
+- 0xff/0xffff/etc: select element from _a_
+(fully compatible with bitwise-based operator)
+*/
+template<typename _Tp, int n> inline v_reg<_Tp, n> v_select(const v_reg<_Tp, n>& mask,
+                                                           const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    typedef V_TypeTraits<_Tp> Traits;
+    typedef typename Traits::int_type int_type;
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < n; i++ )
+    {
+        int_type m = Traits::reinterpret_int(mask.s[i]);
+        CV_DbgAssert(m == 0 || m == (~(int_type)0));  // restrict mask values: 0 or 0xff/0xffff/etc
+        c.s[i] = m ? a.s[i] : b.s[i];
+    }
+    return c;
+}
+
+/** @brief Expand values to the wider pack type
+
+Copy contents of register to two registers with 2x wider pack type.
+Scheme:
+@code
+ int32x4     int64x2 int64x2
+{A B C D} ==> {A B} , {C D}
+@endcode */
+template<typename _Tp, int n> inline void v_expand(const v_reg<_Tp, n>& a,
+                            v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>& b0,
+                            v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>& b1)
+{
+    for( int i = 0; i < (n/2); i++ )
+    {
+        b0.s[i] = a.s[i];
+        b1.s[i] = a.s[i+(n/2)];
+    }
+}
+
+/** @brief Expand lower values to the wider pack type
+
+Same as cv::v_expand, but return lower half of the vector.
+
+Scheme:
+@code
+ int32x4     int64x2
+{A B C D} ==> {A B}
+@endcode */
+template<typename _Tp, int n>
+inline v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>
+v_expand_low(const v_reg<_Tp, n>& a)
+{
+    v_reg<typename V_TypeTraits<_Tp>::w_type, n/2> b;
+    for( int i = 0; i < (n/2); i++ )
+        b.s[i] = a.s[i];
+    return b;
+}
+
+/** @brief Expand higher values to the wider pack type
+
+Same as cv::v_expand_low, but expand higher half of the vector instead.
+
+Scheme:
+@code
+ int32x4     int64x2
+{A B C D} ==> {C D}
+@endcode */
+template<typename _Tp, int n>
+inline v_reg<typename V_TypeTraits<_Tp>::w_type, n/2>
+v_expand_high(const v_reg<_Tp, n>& a)
+{
+    v_reg<typename V_TypeTraits<_Tp>::w_type, n/2> b;
+    for( int i = 0; i < (n/2); i++ )
+        b.s[i] = a.s[i+(n/2)];
+    return b;
+}
+
+//! @cond IGNORED
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::int_type, n>
+    v_reinterpret_as_int(const v_reg<_Tp, n>& a)
+{
+    v_reg<typename V_TypeTraits<_Tp>::int_type, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = V_TypeTraits<_Tp>::reinterpret_int(a.s[i]);
+    return c;
+}
+
+template<typename _Tp, int n> inline v_reg<typename V_TypeTraits<_Tp>::uint_type, n>
+    v_reinterpret_as_uint(const v_reg<_Tp, n>& a)
+{
+    v_reg<typename V_TypeTraits<_Tp>::uint_type, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = V_TypeTraits<_Tp>::reinterpret_uint(a.s[i]);
+    return c;
+}
+//! @endcond
+
+/** @brief Interleave two vectors
+
+Scheme:
+@code
+  {A1 A2 A3 A4}
+  {B1 B2 B3 B4}
+---------------
+  {A1 B1 A2 B2} and {A3 B3 A4 B4}
+@endcode
+For all types except 64-bit.
+*/
+template<typename _Tp, int n> inline void v_zip( const v_reg<_Tp, n>& a0, const v_reg<_Tp, n>& a1,
+                                               v_reg<_Tp, n>& b0, v_reg<_Tp, n>& b1 )
+{
+    int i;
+    for( i = 0; i < n/2; i++ )
+    {
+        b0.s[i*2] = a0.s[i];
+        b0.s[i*2+1] = a1.s[i];
+    }
+    for( ; i < n; i++ )
+    {
+        b1.s[i*2-n] = a0.s[i];
+        b1.s[i*2-n+1] = a1.s[i];
+    }
+}
+
+/** @brief Load register contents from memory
+
+@param ptr pointer to memory block with data
+@return register object
+
+@note Returned type will be detected from passed pointer type, for example uchar ==> cv::v_uint8x16, int ==> cv::v_int32x4, etc.
+
+@note Use vx_load version to get maximum available register length result
+
+@note Alignment requirement:
+if CV_STRONG_ALIGNMENT=1 then passed pointer must be aligned (`sizeof(lane type)` should be enough).
+Do not cast pointer types without runtime check for pointer alignment (like `uchar*` => `int*`).
+ */
+template<typename _Tp>
+inline v_reg<_Tp, simd128_width / sizeof(_Tp)> v_load(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    return v_reg<_Tp, simd128_width / sizeof(_Tp)>(ptr);
+}
+
+#if CV_SIMD256
+/** @brief Load 256-bit length register contents from memory
+
+@param ptr pointer to memory block with data
+@return register object
+
+@note Returned type will be detected from passed pointer type, for example uchar ==> cv::v_uint8x32, int ==> cv::v_int32x8, etc.
+
+@note Check CV_SIMD256 preprocessor definition prior to use.
+Use vx_load version to get maximum available register length result
+
+@note Alignment requirement:
+if CV_STRONG_ALIGNMENT=1 then passed pointer must be aligned (`sizeof(lane type)` should be enough).
+Do not cast pointer types without runtime check for pointer alignment (like `uchar*` => `int*`).
+ */
+template<typename _Tp>
+inline v_reg<_Tp, simd256_width / sizeof(_Tp)> v256_load(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    return v_reg<_Tp, simd256_width / sizeof(_Tp)>(ptr);
+}
+#endif
+
+#if CV_SIMD512
+/** @brief Load 512-bit length register contents from memory
+
+@param ptr pointer to memory block with data
+@return register object
+
+@note Returned type will be detected from passed pointer type, for example uchar ==> cv::v_uint8x64, int ==> cv::v_int32x16, etc.
+
+@note Check CV_SIMD512 preprocessor definition prior to use.
+Use vx_load version to get maximum available register length result
+
+@note Alignment requirement:
+if CV_STRONG_ALIGNMENT=1 then passed pointer must be aligned (`sizeof(lane type)` should be enough).
+Do not cast pointer types without runtime check for pointer alignment (like `uchar*` => `int*`).
+ */
+template<typename _Tp>
+inline v_reg<_Tp, simd512_width / sizeof(_Tp)> v512_load(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    return v_reg<_Tp, simd512_width / sizeof(_Tp)>(ptr);
+}
+#endif
+
+/** @brief Load register contents from memory (aligned)
+
+similar to cv::v_load, but source memory block should be aligned (to 16-byte boundary in case of SIMD128, 32-byte - SIMD256, etc)
+
+@note Use vx_load_aligned version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd128_width / sizeof(_Tp)> v_load_aligned(const _Tp* ptr)
+{
+    CV_Assert(isAligned<sizeof(v_reg<_Tp, simd128_width / sizeof(_Tp)>)>(ptr));
+    return v_reg<_Tp, simd128_width / sizeof(_Tp)>(ptr);
+}
+
+#if CV_SIMD256
+/** @brief Load register contents from memory (aligned)
+
+similar to cv::v256_load, but source memory block should be aligned (to 32-byte boundary in case of SIMD256, 64-byte - SIMD512, etc)
+
+@note Check CV_SIMD256 preprocessor definition prior to use.
+Use vx_load_aligned version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd256_width / sizeof(_Tp)> v256_load_aligned(const _Tp* ptr)
+{
+    CV_Assert(isAligned<sizeof(v_reg<_Tp, simd256_width / sizeof(_Tp)>)>(ptr));
+    return v_reg<_Tp, simd256_width / sizeof(_Tp)>(ptr);
+}
+#endif
+
+#if CV_SIMD512
+/** @brief Load register contents from memory (aligned)
+
+similar to cv::v512_load, but source memory block should be aligned (to 64-byte boundary in case of SIMD512, etc)
+
+@note Check CV_SIMD512 preprocessor definition prior to use.
+Use vx_load_aligned version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd512_width / sizeof(_Tp)> v512_load_aligned(const _Tp* ptr)
+{
+    CV_Assert(isAligned<sizeof(v_reg<_Tp, simd512_width / sizeof(_Tp)>)>(ptr));
+    return v_reg<_Tp, simd512_width / sizeof(_Tp)>(ptr);
+}
+#endif
+
+/** @brief Load 64-bits of data to lower part (high part is undefined).
+
+@param ptr memory block containing data for first half (0..n/2)
+
+@code{.cpp}
+int lo[2] = { 1, 2 };
+v_int32x4 r = v_load_low(lo);
+@endcode
+
+@note Use vx_load_low version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd128_width / sizeof(_Tp)> v_load_low(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    v_reg<_Tp, simd128_width / sizeof(_Tp)> c;
+    for( int i = 0; i < c.nlanes/2; i++ )
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+
+#if CV_SIMD256
+/** @brief Load 128-bits of data to lower part (high part is undefined).
+
+@param ptr memory block containing data for first half (0..n/2)
+
+@code{.cpp}
+int lo[4] = { 1, 2, 3, 4 };
+v_int32x8 r = v256_load_low(lo);
+@endcode
+
+@note Check CV_SIMD256 preprocessor definition prior to use.
+Use vx_load_low version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd256_width / sizeof(_Tp)> v256_load_low(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    v_reg<_Tp, simd256_width / sizeof(_Tp)> c;
+    for (int i = 0; i < c.nlanes / 2; i++)
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+#endif
+
+#if CV_SIMD512
+/** @brief Load 256-bits of data to lower part (high part is undefined).
+
+@param ptr memory block containing data for first half (0..n/2)
+
+@code{.cpp}
+int lo[8] = { 1, 2, 3, 4, 5, 6, 7, 8 };
+v_int32x16 r = v512_load_low(lo);
+@endcode
+
+@note Check CV_SIMD512 preprocessor definition prior to use.
+Use vx_load_low version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd512_width / sizeof(_Tp)> v512_load_low(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    v_reg<_Tp, simd512_width / sizeof(_Tp)> c;
+    for (int i = 0; i < c.nlanes / 2; i++)
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+#endif
+
+/** @brief Load register contents from two memory blocks
+
+@param loptr memory block containing data for first half (0..n/2)
+@param hiptr memory block containing data for second half (n/2..n)
+
+@code{.cpp}
+int lo[2] = { 1, 2 }, hi[2] = { 3, 4 };
+v_int32x4 r = v_load_halves(lo, hi);
+@endcode
+
+@note Use vx_load_halves version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd128_width / sizeof(_Tp)> v_load_halves(const _Tp* loptr, const _Tp* hiptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(loptr));
+    CV_Assert(isAligned<sizeof(_Tp)>(hiptr));
+#endif
+    v_reg<_Tp, simd128_width / sizeof(_Tp)> c;
+    for( int i = 0; i < c.nlanes/2; i++ )
+    {
+        c.s[i] = loptr[i];
+        c.s[i+c.nlanes/2] = hiptr[i];
+    }
+    return c;
+}
+
+#if CV_SIMD256
+/** @brief Load register contents from two memory blocks
+
+@param loptr memory block containing data for first half (0..n/2)
+@param hiptr memory block containing data for second half (n/2..n)
+
+@code{.cpp}
+int lo[4] = { 1, 2, 3, 4 }, hi[4] = { 5, 6, 7, 8 };
+v_int32x8 r = v256_load_halves(lo, hi);
+@endcode
+
+@note Check CV_SIMD256 preprocessor definition prior to use.
+Use vx_load_halves version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd256_width / sizeof(_Tp)> v256_load_halves(const _Tp* loptr, const _Tp* hiptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(loptr));
+    CV_Assert(isAligned<sizeof(_Tp)>(hiptr));
+#endif
+    v_reg<_Tp, simd256_width / sizeof(_Tp)> c;
+    for (int i = 0; i < c.nlanes / 2; i++)
+    {
+        c.s[i] = loptr[i];
+        c.s[i + c.nlanes / 2] = hiptr[i];
+    }
+    return c;
+}
+#endif
+
+#if CV_SIMD512
+/** @brief Load register contents from two memory blocks
+
+@param loptr memory block containing data for first half (0..n/2)
+@param hiptr memory block containing data for second half (n/2..n)
+
+@code{.cpp}
+int lo[4] = { 1, 2, 3, 4, 5, 6, 7, 8 }, hi[4] = { 9, 10, 11, 12, 13, 14, 15, 16 };
+v_int32x16 r = v512_load_halves(lo, hi);
+@endcode
+
+@note Check CV_SIMD512 preprocessor definition prior to use.
+Use vx_load_halves version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<_Tp, simd512_width / sizeof(_Tp)> v512_load_halves(const _Tp* loptr, const _Tp* hiptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(loptr));
+    CV_Assert(isAligned<sizeof(_Tp)>(hiptr));
+#endif
+    v_reg<_Tp, simd512_width / sizeof(_Tp)> c;
+    for (int i = 0; i < c.nlanes / 2; i++)
+    {
+        c.s[i] = loptr[i];
+        c.s[i + c.nlanes / 2] = hiptr[i];
+    }
+    return c;
+}
+#endif
+
+/** @brief Load register contents from memory with double expand
+
+Same as cv::v_load, but result pack type will be 2x wider than memory type.
+
+@code{.cpp}
+short buf[4] = {1, 2, 3, 4}; // type is int16
+v_int32x4 r = v_load_expand(buf); // r = {1, 2, 3, 4} - type is int32
+@endcode
+For 8-, 16-, 32-bit integer source types.
+
+@note Use vx_load_expand version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<typename V_TypeTraits<_Tp>::w_type, simd128_width / sizeof(typename V_TypeTraits<_Tp>::w_type)>
+v_load_expand(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    v_reg<w_type, simd128_width / sizeof(w_type)> c;
+    for( int i = 0; i < c.nlanes; i++ )
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+
+#if CV_SIMD256
+/** @brief Load register contents from memory with double expand
+
+Same as cv::v256_load, but result pack type will be 2x wider than memory type.
+
+@code{.cpp}
+short buf[8] = {1, 2, 3, 4, 5, 6, 7, 8}; // type is int16
+v_int32x8 r = v256_load_expand(buf); // r = {1, 2, 3, 4, 5, 6, 7, 8} - type is int32
+@endcode
+For 8-, 16-, 32-bit integer source types.
+
+@note Check CV_SIMD256 preprocessor definition prior to use.
+Use vx_load_expand version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<typename V_TypeTraits<_Tp>::w_type, simd256_width / sizeof(typename V_TypeTraits<_Tp>::w_type)>
+v256_load_expand(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    v_reg<w_type, simd256_width / sizeof(w_type)> c;
+    for (int i = 0; i < c.nlanes; i++)
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+#endif
+
+#if CV_SIMD512
+/** @brief Load register contents from memory with double expand
+
+Same as cv::v512_load, but result pack type will be 2x wider than memory type.
+
+@code{.cpp}
+short buf[8] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}; // type is int16
+v_int32x16 r = v512_load_expand(buf); // r = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16} - type is int32
+@endcode
+For 8-, 16-, 32-bit integer source types.
+
+@note Check CV_SIMD512 preprocessor definition prior to use.
+Use vx_load_expand version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<typename V_TypeTraits<_Tp>::w_type, simd512_width / sizeof(typename V_TypeTraits<_Tp>::w_type)>
+v512_load_expand(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    typedef typename V_TypeTraits<_Tp>::w_type w_type;
+    v_reg<w_type, simd512_width / sizeof(w_type)> c;
+    for (int i = 0; i < c.nlanes; i++)
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+#endif
+
+/** @brief Load register contents from memory with quad expand
+
+Same as cv::v_load_expand, but result type is 4 times wider than source.
+@code{.cpp}
+char buf[4] = {1, 2, 3, 4}; // type is int8
+v_int32x4 r = v_load_expand_q(buf); // r = {1, 2, 3, 4} - type is int32
+@endcode
+For 8-bit integer source types.
+
+@note Use vx_load_expand_q version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<typename V_TypeTraits<_Tp>::q_type, simd128_width / sizeof(typename V_TypeTraits<_Tp>::q_type)>
+v_load_expand_q(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    typedef typename V_TypeTraits<_Tp>::q_type q_type;
+    v_reg<q_type, simd128_width / sizeof(q_type)> c;
+    for( int i = 0; i < c.nlanes; i++ )
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+
+#if CV_SIMD256
+/** @brief Load register contents from memory with quad expand
+
+Same as cv::v256_load_expand, but result type is 4 times wider than source.
+@code{.cpp}
+char buf[8] = {1, 2, 3, 4, 5, 6, 7, 8}; // type is int8
+v_int32x8 r = v256_load_expand_q(buf); // r = {1, 2, 3, 4, 5, 6, 7, 8} - type is int32
+@endcode
+For 8-bit integer source types.
+
+@note Check CV_SIMD256 preprocessor definition prior to use.
+Use vx_load_expand_q version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<typename V_TypeTraits<_Tp>::q_type, simd256_width / sizeof(typename V_TypeTraits<_Tp>::q_type)>
+v256_load_expand_q(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    typedef typename V_TypeTraits<_Tp>::q_type q_type;
+    v_reg<q_type, simd256_width / sizeof(q_type)> c;
+    for (int i = 0; i < c.nlanes; i++)
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+#endif
+
+#if CV_SIMD512
+/** @brief Load register contents from memory with quad expand
+
+Same as cv::v512_load_expand, but result type is 4 times wider than source.
+@code{.cpp}
+char buf[16] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}; // type is int8
+v_int32x16 r = v512_load_expand_q(buf); // r = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16} - type is int32
+@endcode
+For 8-bit integer source types.
+
+@note Check CV_SIMD512 preprocessor definition prior to use.
+Use vx_load_expand_q version to get maximum available register length result
+*/
+template<typename _Tp>
+inline v_reg<typename V_TypeTraits<_Tp>::q_type, simd512_width / sizeof(typename V_TypeTraits<_Tp>::q_type)>
+v512_load_expand_q(const _Tp* ptr)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    typedef typename V_TypeTraits<_Tp>::q_type q_type;
+    v_reg<q_type, simd512_width / sizeof(q_type)> c;
+    for (int i = 0; i < c.nlanes; i++)
+    {
+        c.s[i] = ptr[i];
+    }
+    return c;
+}
+#endif
+
+/** @brief Load and deinterleave (2 channels)
+
+Load data from memory deinterleave and store to 2 registers.
+Scheme:
+@code
+{A1 B1 A2 B2 ...} ==> {A1 A2 ...}, {B1 B2 ...}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n> inline void v_load_deinterleave(const _Tp* ptr, v_reg<_Tp, n>& a,
+                                                            v_reg<_Tp, n>& b)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    int i, i2;
+    for( i = i2 = 0; i < n; i++, i2 += 2 )
+    {
+        a.s[i] = ptr[i2];
+        b.s[i] = ptr[i2+1];
+    }
+}
+
+/** @brief Load and deinterleave (3 channels)
+
+Load data from memory deinterleave and store to 3 registers.
+Scheme:
+@code
+{A1 B1 C1 A2 B2 C2 ...} ==> {A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n> inline void v_load_deinterleave(const _Tp* ptr, v_reg<_Tp, n>& a,
+                                                            v_reg<_Tp, n>& b, v_reg<_Tp, n>& c)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    int i, i3;
+    for( i = i3 = 0; i < n; i++, i3 += 3 )
+    {
+        a.s[i] = ptr[i3];
+        b.s[i] = ptr[i3+1];
+        c.s[i] = ptr[i3+2];
+    }
+}
+
+/** @brief Load and deinterleave (4 channels)
+
+Load data from memory deinterleave and store to 4 registers.
+Scheme:
+@code
+{A1 B1 C1 D1 A2 B2 C2 D2 ...} ==> {A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...}, {D1 D2 ...}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n>
+inline void v_load_deinterleave(const _Tp* ptr, v_reg<_Tp, n>& a,
+                                v_reg<_Tp, n>& b, v_reg<_Tp, n>& c,
+                                v_reg<_Tp, n>& d)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    int i, i4;
+    for( i = i4 = 0; i < n; i++, i4 += 4 )
+    {
+        a.s[i] = ptr[i4];
+        b.s[i] = ptr[i4+1];
+        c.s[i] = ptr[i4+2];
+        d.s[i] = ptr[i4+3];
+    }
+}
+
+/** @brief Interleave and store (2 channels)
+
+Interleave and store data from 2 registers to memory.
+Scheme:
+@code
+{A1 A2 ...}, {B1 B2 ...} ==> {A1 B1 A2 B2 ...}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n>
+inline void v_store_interleave( _Tp* ptr, const v_reg<_Tp, n>& a,
+                               const v_reg<_Tp, n>& b,
+                               hal::StoreMode /*mode*/=hal::STORE_UNALIGNED)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    int i, i2;
+    for( i = i2 = 0; i < n; i++, i2 += 2 )
+    {
+        ptr[i2] = a.s[i];
+        ptr[i2+1] = b.s[i];
+    }
+}
+
+/** @brief Interleave and store (3 channels)
+
+Interleave and store data from 3 registers to memory.
+Scheme:
+@code
+{A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...} ==> {A1 B1 C1 A2 B2 C2 ...}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n>
+inline void v_store_interleave( _Tp* ptr, const v_reg<_Tp, n>& a,
+                                const v_reg<_Tp, n>& b, const v_reg<_Tp, n>& c,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    int i, i3;
+    for( i = i3 = 0; i < n; i++, i3 += 3 )
+    {
+        ptr[i3] = a.s[i];
+        ptr[i3+1] = b.s[i];
+        ptr[i3+2] = c.s[i];
+    }
+}
+
+/** @brief Interleave and store (4 channels)
+
+Interleave and store data from 4 registers to memory.
+Scheme:
+@code
+{A1 A2 ...}, {B1 B2 ...}, {C1 C2 ...}, {D1 D2 ...} ==> {A1 B1 C1 D1 A2 B2 C2 D2 ...}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n> inline void v_store_interleave( _Tp* ptr, const v_reg<_Tp, n>& a,
+                                                            const v_reg<_Tp, n>& b, const v_reg<_Tp, n>& c,
+                                                            const v_reg<_Tp, n>& d,
+                                                            hal::StoreMode /*mode*/=hal::STORE_UNALIGNED)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    int i, i4;
+    for( i = i4 = 0; i < n; i++, i4 += 4 )
+    {
+        ptr[i4] = a.s[i];
+        ptr[i4+1] = b.s[i];
+        ptr[i4+2] = c.s[i];
+        ptr[i4+3] = d.s[i];
+    }
+}
+
+/** @brief Store data to memory
+
+Store register contents to memory.
+Scheme:
+@code
+  REG {A B C D} ==> MEM {A B C D}
+@endcode
+Pointer can be unaligned. */
+template<typename _Tp, int n>
+inline void v_store(_Tp* ptr, const v_reg<_Tp, n>& a)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    for( int i = 0; i < n; i++ )
+        ptr[i] = a.s[i];
+}
+
+template<typename _Tp, int n>
+inline void v_store(_Tp* ptr, const v_reg<_Tp, n>& a, hal::StoreMode /*mode*/)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    v_store(ptr, a);
+}
+
+/** @brief Store data to memory (lower half)
+
+Store lower half of register contents to memory.
+Scheme:
+@code
+  REG {A B C D} ==> MEM {A B}
+@endcode */
+template<typename _Tp, int n>
+inline void v_store_low(_Tp* ptr, const v_reg<_Tp, n>& a)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    for( int i = 0; i < (n/2); i++ )
+        ptr[i] = a.s[i];
+}
+
+/** @brief Store data to memory (higher half)
+
+Store higher half of register contents to memory.
+Scheme:
+@code
+  REG {A B C D} ==> MEM {C D}
+@endcode */
+template<typename _Tp, int n>
+inline void v_store_high(_Tp* ptr, const v_reg<_Tp, n>& a)
+{
+#if CV_STRONG_ALIGNMENT
+    CV_Assert(isAligned<sizeof(_Tp)>(ptr));
+#endif
+    for( int i = 0; i < (n/2); i++ )
+        ptr[i] = a.s[i+(n/2)];
+}
+
+/** @brief Store data to memory (aligned)
+
+Store register contents to memory.
+Scheme:
+@code
+  REG {A B C D} ==> MEM {A B C D}
+@endcode
+Pointer __should__ be aligned by 16-byte boundary. */
+template<typename _Tp, int n>
+inline void v_store_aligned(_Tp* ptr, const v_reg<_Tp, n>& a)
+{
+    CV_Assert(isAligned<sizeof(v_reg<_Tp, n>)>(ptr));
+    v_store(ptr, a);
+}
+
+template<typename _Tp, int n>
+inline void v_store_aligned_nocache(_Tp* ptr, const v_reg<_Tp, n>& a)
+{
+    CV_Assert(isAligned<sizeof(v_reg<_Tp, n>)>(ptr));
+    v_store(ptr, a);
+}
+
+template<typename _Tp, int n>
+inline void v_store_aligned(_Tp* ptr, const v_reg<_Tp, n>& a, hal::StoreMode /*mode*/)
+{
+    CV_Assert(isAligned<sizeof(v_reg<_Tp, n>)>(ptr));
+    v_store(ptr, a);
+}
+
+/** @brief Combine vector from first elements of two vectors
+
+Scheme:
+@code
+  {A1 A2 A3 A4}
+  {B1 B2 B3 B4}
+---------------
+  {A1 A2 B1 B2}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_combine_low(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < (n/2); i++ )
+    {
+        c.s[i] = a.s[i];
+        c.s[i+(n/2)] = b.s[i];
+    }
+    return c;
+}
+
+/** @brief Combine vector from last elements of two vectors
+
+Scheme:
+@code
+  {A1 A2 A3 A4}
+  {B1 B2 B3 B4}
+---------------
+  {A3 A4 B3 B4}
+@endcode
+For all types except 64-bit. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_combine_high(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < (n/2); i++ )
+    {
+        c.s[i] = a.s[i+(n/2)];
+        c.s[i+(n/2)] = b.s[i+(n/2)];
+    }
+    return c;
+}
+
+/** @brief Combine two vectors from lower and higher parts of two other vectors
+
+@code{.cpp}
+low = cv::v_combine_low(a, b);
+high = cv::v_combine_high(a, b);
+@endcode */
+template<typename _Tp, int n>
+inline void v_recombine(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b,
+                        v_reg<_Tp, n>& low, v_reg<_Tp, n>& high)
+{
+    for( int i = 0; i < (n/2); i++ )
+    {
+        low.s[i] = a.s[i];
+        low.s[i+(n/2)] = b.s[i];
+        high.s[i] = a.s[i+(n/2)];
+        high.s[i+(n/2)] = b.s[i+(n/2)];
+    }
+}
+
+/** @brief Vector reverse order
+
+Reverse the order of the vector
+Scheme:
+@code
+  REG {A1 ... An} ==> REG {An ... A1}
+@endcode
+For all types. */
+template<typename _Tp, int n>
+inline v_reg<_Tp, n> v_reverse(const v_reg<_Tp, n>& a)
+{
+    v_reg<_Tp, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = a.s[n-i-1];
+    return c;
+}
+
+/** @brief Vector extract
+
+Scheme:
+@code
+  {A1 A2 A3 A4}
+  {B1 B2 B3 B4}
+========================
+shift = 1  {A2 A3 A4 B1}
+shift = 2  {A3 A4 B1 B2}
+shift = 3  {A4 B1 B2 B3}
+@endcode
+Restriction: 0 <= shift < nlanes
+
+Usage:
+@code
+v_int32x4 a, b, c;
+c = v_extract<2>(a, b);
+@endcode
+For all types. */
+template<int s, typename _Tp, int n>
+inline v_reg<_Tp, n> v_extract(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    v_reg<_Tp, n> r;
+    const int shift = n - s;
+    int i = 0;
+    for (; i < shift; ++i)
+        r.s[i] = a.s[i+s];
+    for (; i < n; ++i)
+        r.s[i] = b.s[i-shift];
+    return r;
+}
+
+/** @brief Vector extract
+
+Scheme:
+Return the s-th element of v.
+Restriction: 0 <= s < nlanes
+
+Usage:
+@code
+v_int32x4 a;
+int r;
+r = v_extract_n<2>(a);
+@endcode
+For all types. */
+template<int s, typename _Tp, int n>
+inline _Tp v_extract_n(const v_reg<_Tp, n>& v)
+{
+    CV_DbgAssert(s >= 0 && s < n);
+    return v.s[s];
+}
+
+/** @brief Broadcast i-th element of vector
+
+Scheme:
+@code
+{ v[0] v[1] v[2] ... v[SZ] } => { v[i], v[i], v[i] ... v[i] }
+@endcode
+Restriction: 0 <= i < nlanes
+Supported types: 32-bit integers and floats (s32/u32/f32)
+ */
+template<int i, typename _Tp, int n>
+inline v_reg<_Tp, n> v_broadcast_element(const v_reg<_Tp, n>& a)
+{
+    CV_DbgAssert(i >= 0 && i < n);
+    return v_reg<_Tp, n>::all(a.s[i]);
+}
+
+/** @brief Round elements
+
+Rounds each value. Input type is float vector ==> output type is int vector.
+@note Only for floating point types.
+*/
+template<int n> inline v_reg<int, n> v_round(const v_reg<float, n>& a)
+{
+    v_reg<int, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = cvRound(a.s[i]);
+    return c;
+}
+
+/** @overload */
+template<int n> inline v_reg<int, n*2> v_round(const v_reg<double, n>& a, const v_reg<double, n>& b)
+{
+    v_reg<int, n*2> c;
+    for( int i = 0; i < n; i++ )
+    {
+        c.s[i] = cvRound(a.s[i]);
+        c.s[i+n] = cvRound(b.s[i]);
+    }
+    return c;
+}
+
+/** @brief Floor elements
+
+Floor each value. Input type is float vector ==> output type is int vector.
+@note Only for floating point types.
+*/
+template<int n> inline v_reg<int, n> v_floor(const v_reg<float, n>& a)
+{
+    v_reg<int, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = cvFloor(a.s[i]);
+    return c;
+}
+
+/** @brief Ceil elements
+
+Ceil each value. Input type is float vector ==> output type is int vector.
+@note Only for floating point types.
+*/
+template<int n> inline v_reg<int, n> v_ceil(const v_reg<float, n>& a)
+{
+    v_reg<int, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = cvCeil(a.s[i]);
+    return c;
+}
+
+/** @brief Truncate elements
+
+Truncate each value. Input type is float vector ==> output type is int vector.
+@note Only for floating point types.
+*/
+template<int n> inline v_reg<int, n> v_trunc(const v_reg<float, n>& a)
+{
+    v_reg<int, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = (int)(a.s[i]);
+    return c;
+}
+
+/** @overload */
+template<int n> inline v_reg<int, n*2> v_round(const v_reg<double, n>& a)
+{
+    v_reg<int, n*2> c;
+    for( int i = 0; i < n; i++ )
+    {
+        c.s[i] = cvRound(a.s[i]);
+        c.s[i+n] = 0;
+    }
+    return c;
+}
+
+/** @overload */
+template<int n> inline v_reg<int, n*2> v_floor(const v_reg<double, n>& a)
+{
+    v_reg<int, n*2> c;
+    for( int i = 0; i < n; i++ )
+    {
+        c.s[i] = cvFloor(a.s[i]);
+        c.s[i+n] = 0;
+    }
+    return c;
+}
+
+/** @overload */
+template<int n> inline v_reg<int, n*2> v_ceil(const v_reg<double, n>& a)
+{
+    v_reg<int, n*2> c;
+    for( int i = 0; i < n; i++ )
+    {
+        c.s[i] = cvCeil(a.s[i]);
+        c.s[i+n] = 0;
+    }
+    return c;
+}
+
+/** @overload */
+template<int n> inline v_reg<int, n*2> v_trunc(const v_reg<double, n>& a)
+{
+    v_reg<int, n*2> c;
+    for( int i = 0; i < n; i++ )
+    {
+        c.s[i] = (int)(a.s[i]);
+        c.s[i+n] = 0;
+    }
+    return c;
+}
+
+/** @brief Convert to float
+
+Supported input type is cv::v_int32. */
+template<int n> inline v_reg<float, n> v_cvt_f32(const v_reg<int, n>& a)
+{
+    v_reg<float, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = (float)a.s[i];
+    return c;
+}
+
+/** @brief Convert lower half to float
+
+Supported input type is cv::v_float64. */
+template<int n> inline v_reg<float, n*2> v_cvt_f32(const v_reg<double, n>& a)
+{
+    v_reg<float, n*2> c;
+    for( int i = 0; i < n; i++ )
+    {
+        c.s[i] = (float)a.s[i];
+        c.s[i+n] = 0;
+    }
+    return c;
+}
+
+/** @brief Convert to float
+
+Supported input type is cv::v_float64. */
+template<int n> inline v_reg<float, n*2> v_cvt_f32(const v_reg<double, n>& a, const v_reg<double, n>& b)
+{
+    v_reg<float, n*2> c;
+    for( int i = 0; i < n; i++ )
+    {
+        c.s[i] = (float)a.s[i];
+        c.s[i+n] = (float)b.s[i];
+    }
+    return c;
+}
+
+/** @brief Convert lower half to double
+
+Supported input type is cv::v_int32. */
+template<int n> CV_INLINE v_reg<double, n/2> v_cvt_f64(const v_reg<int, n>& a)
+{
+    v_reg<double, (n/2)> c;
+    for( int i = 0; i < (n/2); i++ )
+        c.s[i] = (double)a.s[i];
+    return c;
+}
+
+/** @brief Convert to double high part of vector
+
+Supported input type is cv::v_int32. */
+template<int n> CV_INLINE v_reg<double, (n/2)> v_cvt_f64_high(const v_reg<int, n>& a)
+{
+    v_reg<double, (n/2)> c;
+    for( int i = 0; i < (n/2); i++ )
+        c.s[i] = (double)a.s[i + (n/2)];
+    return c;
+}
+
+/** @brief Convert lower half to double
+
+Supported input type is cv::v_float32. */
+template<int n> CV_INLINE v_reg<double, (n/2)> v_cvt_f64(const v_reg<float, n>& a)
+{
+    v_reg<double, (n/2)> c;
+    for( int i = 0; i < (n/2); i++ )
+        c.s[i] = (double)a.s[i];
+    return c;
+}
+
+/** @brief Convert to double high part of vector
+
+Supported input type is cv::v_float32. */
+template<int n> CV_INLINE v_reg<double, (n/2)> v_cvt_f64_high(const v_reg<float, n>& a)
+{
+    v_reg<double, (n/2)> c;
+    for( int i = 0; i < (n/2); i++ )
+        c.s[i] = (double)a.s[i + (n/2)];
+    return c;
+}
+
+/** @brief Convert to double
+
+Supported input type is cv::v_int64. */
+template<int n> CV_INLINE v_reg<double, n> v_cvt_f64(const v_reg<int64, n>& a)
+{
+    v_reg<double, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = (double)a.s[i];
+    return c;
+}
+
+
+template<typename _Tp> inline v_reg<_Tp, simd128_width / sizeof(_Tp)> v_lut(const _Tp* tab, const int* idx)
+{
+    v_reg<_Tp, simd128_width / sizeof(_Tp)> c;
+    for (int i = 0; i < c.nlanes; i++)
+        c.s[i] = tab[idx[i]];
+    return c;
+}
+template<typename _Tp> inline v_reg<_Tp, simd128_width / sizeof(_Tp)> v_lut_pairs(const _Tp* tab, const int* idx)
+{
+    v_reg<_Tp, simd128_width / sizeof(_Tp)> c;
+    for (int i = 0; i < c.nlanes; i++)
+        c.s[i] = tab[idx[i / 2] + i % 2];
+    return c;
+}
+template<typename _Tp> inline v_reg<_Tp, simd128_width / sizeof(_Tp)> v_lut_quads(const _Tp* tab, const int* idx)
+{
+    v_reg<_Tp, simd128_width / sizeof(_Tp)> c;
+    for (int i = 0; i < c.nlanes; i++)
+        c.s[i] = tab[idx[i / 4] + i % 4];
+    return c;
+}
+
+template<int n> inline v_reg<int, n> v_lut(const int* tab, const v_reg<int, n>& idx)
+{
+    v_reg<int, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = tab[idx.s[i]];
+    return c;
+}
+
+template<int n> inline v_reg<unsigned, n> v_lut(const unsigned* tab, const v_reg<int, n>& idx)
+{
+    v_reg<int, n> c;
+    for (int i = 0; i < n; i++)
+        c.s[i] = tab[idx.s[i]];
+    return c;
+}
+
+template<int n> inline v_reg<float, n> v_lut(const float* tab, const v_reg<int, n>& idx)
+{
+    v_reg<float, n> c;
+    for( int i = 0; i < n; i++ )
+        c.s[i] = tab[idx.s[i]];
+    return c;
+}
+
+template<int n> inline v_reg<double, n/2> v_lut(const double* tab, const v_reg<int, n>& idx)
+{
+    v_reg<double, n/2> c;
+    for( int i = 0; i < n/2; i++ )
+        c.s[i] = tab[idx.s[i]];
+    return c;
+}
+
+
+template<int n> inline void v_lut_deinterleave(const float* tab, const v_reg<int, n>& idx,
+                                               v_reg<float, n>& x, v_reg<float, n>& y)
+{
+    for( int i = 0; i < n; i++ )
+    {
+        int j = idx.s[i];
+        x.s[i] = tab[j];
+        y.s[i] = tab[j+1];
+    }
+}
+
+template<int n> inline void v_lut_deinterleave(const double* tab, const v_reg<int, n*2>& idx,
+                                               v_reg<double, n>& x, v_reg<double, n>& y)
+{
+    for( int i = 0; i < n; i++ )
+    {
+        int j = idx.s[i];
+        x.s[i] = tab[j];
+        y.s[i] = tab[j+1];
+    }
+}
+
+template<typename _Tp, int n> inline v_reg<_Tp, n> v_interleave_pairs(const v_reg<_Tp, n>& vec)
+{
+    v_reg<_Tp, n> c;
+    for (int i = 0; i < n/4; i++)
+    {
+        c.s[4*i  ] = vec.s[4*i  ];
+        c.s[4*i+1] = vec.s[4*i+2];
+        c.s[4*i+2] = vec.s[4*i+1];
+        c.s[4*i+3] = vec.s[4*i+3];
+    }
+    return c;
+}
+
+template<typename _Tp, int n> inline v_reg<_Tp, n> v_interleave_quads(const v_reg<_Tp, n>& vec)
+{
+    v_reg<_Tp, n> c;
+    for (int i = 0; i < n/8; i++)
+    {
+        c.s[8*i  ] = vec.s[8*i  ];
+        c.s[8*i+1] = vec.s[8*i+4];
+        c.s[8*i+2] = vec.s[8*i+1];
+        c.s[8*i+3] = vec.s[8*i+5];
+        c.s[8*i+4] = vec.s[8*i+2];
+        c.s[8*i+5] = vec.s[8*i+6];
+        c.s[8*i+6] = vec.s[8*i+3];
+        c.s[8*i+7] = vec.s[8*i+7];
+    }
+    return c;
+}
+
+template<typename _Tp, int n> inline v_reg<_Tp, n> v_pack_triplets(const v_reg<_Tp, n>& vec)
+{
+    v_reg<_Tp, n> c;
+    for (int i = 0; i < n/4; i++)
+    {
+        c.s[3*i  ] = vec.s[4*i  ];
+        c.s[3*i+1] = vec.s[4*i+1];
+        c.s[3*i+2] = vec.s[4*i+2];
+    }
+    return c;
+}
+
+/** @brief Transpose 4x4 matrix
+
+Scheme:
+@code
+a0  {A1 A2 A3 A4}
+a1  {B1 B2 B3 B4}
+a2  {C1 C2 C3 C4}
+a3  {D1 D2 D3 D4}
+===============
+b0  {A1 B1 C1 D1}
+b1  {A2 B2 C2 D2}
+b2  {A3 B3 C3 D3}
+b3  {A4 B4 C4 D4}
+@endcode
+*/
+template<typename _Tp, int n>
+inline void v_transpose4x4( v_reg<_Tp, n>& a0, const v_reg<_Tp, n>& a1,
+                            const v_reg<_Tp, n>& a2, const v_reg<_Tp, n>& a3,
+                            v_reg<_Tp, n>& b0, v_reg<_Tp, n>& b1,
+                            v_reg<_Tp, n>& b2, v_reg<_Tp, n>& b3 )
+{
+    for (int i = 0; i < n / 4; i++)
+    {
+        b0.s[0 + i*4] = a0.s[0 + i*4]; b0.s[1 + i*4] = a1.s[0 + i*4];
+        b0.s[2 + i*4] = a2.s[0 + i*4]; b0.s[3 + i*4] = a3.s[0 + i*4];
+        b1.s[0 + i*4] = a0.s[1 + i*4]; b1.s[1 + i*4] = a1.s[1 + i*4];
+        b1.s[2 + i*4] = a2.s[1 + i*4]; b1.s[3 + i*4] = a3.s[1 + i*4];
+        b2.s[0 + i*4] = a0.s[2 + i*4]; b2.s[1 + i*4] = a1.s[2 + i*4];
+        b2.s[2 + i*4] = a2.s[2 + i*4]; b2.s[3 + i*4] = a3.s[2 + i*4];
+        b3.s[0 + i*4] = a0.s[3 + i*4]; b3.s[1 + i*4] = a1.s[3 + i*4];
+        b3.s[2 + i*4] = a2.s[3 + i*4]; b3.s[3 + i*4] = a3.s[3 + i*4];
+    }
+}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_INIT_ZERO(_Tpvec, prefix, suffix) \
+inline _Tpvec prefix##_setzero_##suffix() { return _Tpvec::zero(); } \
+template <> inline _Tpvec v_setzero_() { return _Tpvec::zero(); }
+
+//! @name Init with zero
+//! @{
+//! @brief Create new vector with zero elements
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint8x16, v, u8)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int8x16, v, s8)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint16x8, v, u16)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int16x8, v, s16)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint32x4, v, u32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int32x4, v, s32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_float32x4, v, f32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_float64x2, v, f64)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint64x2, v, u64)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int64x2, v, s64)
+
+#if CV_SIMD256
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint8x32, v256, u8)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int8x32, v256, s8)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint16x16, v256, u16)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int16x16, v256, s16)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint32x8, v256, u32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int32x8, v256, s32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_float32x8, v256, f32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_float64x4, v256, f64)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint64x4, v256, u64)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int64x4, v256, s64)
+#endif
+
+#if CV_SIMD512
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint8x64, v512, u8)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int8x64, v512, s8)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint16x32, v512, u16)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int16x32, v512, s16)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint32x16, v512, u32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int32x16, v512, s32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_float32x16, v512, f32)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_float64x8, v512, f64)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_uint64x8, v512, u64)
+OPENCV_HAL_IMPL_C_INIT_ZERO(v_int64x8, v512, s64)
+#endif
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_INIT_VAL(_Tpvec, _Tp, prefix, suffix) \
+inline _Tpvec prefix##_setall_##suffix(_Tp val) { return _Tpvec::all(val); } \
+template <> inline _Tpvec v_setall_(_Tp val) { return _Tpvec::all(val); }
+
+//! @name Init with value
+//! @{
+//! @brief Create new vector with elements set to a specific value
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint8x16, uchar, v, u8)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int8x16, schar, v, s8)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint16x8, ushort, v, u16)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int16x8, short, v, s16)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint32x4, unsigned, v, u32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int32x4, int, v, s32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_float32x4, float, v, f32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_float64x2, double, v, f64)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint64x2, uint64, v, u64)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int64x2, int64, v, s64)
+
+#if CV_SIMD256
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint8x32, uchar, v256, u8)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int8x32, schar, v256, s8)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint16x16, ushort, v256, u16)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int16x16, short, v256, s16)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint32x8, unsigned, v256, u32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int32x8, int, v256, s32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_float32x8, float, v256, f32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_float64x4, double, v256, f64)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint64x4, uint64, v256, u64)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int64x4, int64, v256, s64)
+#endif
+
+#if CV_SIMD512
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint8x64, uchar, v512, u8)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int8x64, schar, v512, s8)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint16x32, ushort, v512, u16)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int16x32, short, v512, s16)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint32x16, unsigned, v512, u32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int32x16, int, v512, s32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_float32x16, float, v512, f32)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_float64x8, double, v512, f64)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_uint64x8, uint64, v512, u64)
+OPENCV_HAL_IMPL_C_INIT_VAL(v_int64x8, int64, v512, s64)
+#endif
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_REINTERPRET(_Tp, suffix) \
+template<typename _Tp0, int n0> inline v_reg<_Tp, n0*sizeof(_Tp0)/sizeof(_Tp)> \
+    v_reinterpret_as_##suffix(const v_reg<_Tp0, n0>& a) \
+{ return a.template reinterpret_as<_Tp, n0*sizeof(_Tp0)/sizeof(_Tp)>(); }
+
+//! @name Reinterpret
+//! @{
+//! @brief Convert vector to different type without modifying underlying data.
+OPENCV_HAL_IMPL_C_REINTERPRET(uchar, u8)
+OPENCV_HAL_IMPL_C_REINTERPRET(schar, s8)
+OPENCV_HAL_IMPL_C_REINTERPRET(ushort, u16)
+OPENCV_HAL_IMPL_C_REINTERPRET(short, s16)
+OPENCV_HAL_IMPL_C_REINTERPRET(unsigned, u32)
+OPENCV_HAL_IMPL_C_REINTERPRET(int, s32)
+OPENCV_HAL_IMPL_C_REINTERPRET(float, f32)
+OPENCV_HAL_IMPL_C_REINTERPRET(double, f64)
+OPENCV_HAL_IMPL_C_REINTERPRET(uint64, u64)
+OPENCV_HAL_IMPL_C_REINTERPRET(int64, s64)
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_SHIFTL(_Tp) \
+template<int shift, int n> inline v_reg<_Tp, n> v_shl(const v_reg<_Tp, n>& a) \
+{ return v_shl(a, shift); }
+
+//! @name Left shift
+//! @{
+//! @brief Shift left
+OPENCV_HAL_IMPL_C_SHIFTL(ushort)
+OPENCV_HAL_IMPL_C_SHIFTL(short)
+OPENCV_HAL_IMPL_C_SHIFTL(unsigned)
+OPENCV_HAL_IMPL_C_SHIFTL(int)
+OPENCV_HAL_IMPL_C_SHIFTL(uint64)
+OPENCV_HAL_IMPL_C_SHIFTL(int64)
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_SHIFTR(_Tp) \
+template<int shift, int n> inline v_reg<_Tp, n> v_shr(const v_reg<_Tp, n>& a) \
+{ return v_shr(a, shift); }
+
+//! @name Right shift
+//! @{
+//! @brief Shift right
+OPENCV_HAL_IMPL_C_SHIFTR(ushort)
+OPENCV_HAL_IMPL_C_SHIFTR(short)
+OPENCV_HAL_IMPL_C_SHIFTR(unsigned)
+OPENCV_HAL_IMPL_C_SHIFTR(int)
+OPENCV_HAL_IMPL_C_SHIFTR(uint64)
+OPENCV_HAL_IMPL_C_SHIFTR(int64)
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_RSHIFTR(_Tp) \
+template<int shift, int n> inline v_reg<_Tp, n> v_rshr(const v_reg<_Tp, n>& a) \
+{ \
+    v_reg<_Tp, n> c; \
+    for( int i = 0; i < n; i++ ) \
+        c.s[i] = (_Tp)((a.s[i] + ((_Tp)1 << (shift - 1))) >> shift); \
+    return c; \
+}
+
+//! @name Rounding shift
+//! @{
+//! @brief Rounding shift right
+OPENCV_HAL_IMPL_C_RSHIFTR(ushort)
+OPENCV_HAL_IMPL_C_RSHIFTR(short)
+OPENCV_HAL_IMPL_C_RSHIFTR(unsigned)
+OPENCV_HAL_IMPL_C_RSHIFTR(int)
+OPENCV_HAL_IMPL_C_RSHIFTR(uint64)
+OPENCV_HAL_IMPL_C_RSHIFTR(int64)
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_PACK(_Tp, _Tpn, pack_suffix, cast) \
+template<int n> inline v_reg<_Tpn, 2*n> v_##pack_suffix(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    v_reg<_Tpn, 2*n> c; \
+    for( int i = 0; i < n; i++ ) \
+    { \
+        c.s[i] = cast<_Tpn>(a.s[i]); \
+        c.s[i+n] = cast<_Tpn>(b.s[i]); \
+    } \
+    return c; \
+}
+
+//! @name Pack
+//! @{
+//! @brief Pack values from two vectors to one
+//!
+//! Return vector type have twice more elements than input vector types. Variant with _u_ suffix also
+//! converts to corresponding unsigned type.
+//!
+//! - pack: for 16-, 32- and 64-bit integer input types
+//! - pack_u: for 16- and 32-bit signed integer input types
+//!
+//! @note All variants except 64-bit use saturation.
+OPENCV_HAL_IMPL_C_PACK(ushort, uchar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK(short, schar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK(unsigned, ushort, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK(int, short, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK(uint64, unsigned, pack, static_cast)
+OPENCV_HAL_IMPL_C_PACK(int64, int, pack, static_cast)
+OPENCV_HAL_IMPL_C_PACK(short, uchar, pack_u, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK(int, ushort, pack_u, saturate_cast)
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_RSHR_PACK(_Tp, _Tpn, pack_suffix, cast) \
+template<int shift, int n> inline v_reg<_Tpn, 2*n> v_rshr_##pack_suffix(const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b) \
+{ \
+    v_reg<_Tpn, 2*n> c; \
+    for( int i = 0; i < n; i++ ) \
+    { \
+        c.s[i] = cast<_Tpn>((a.s[i] + ((_Tp)1 << (shift - 1))) >> shift); \
+        c.s[i+n] = cast<_Tpn>((b.s[i] + ((_Tp)1 << (shift - 1))) >> shift); \
+    } \
+    return c; \
+}
+
+//! @name Pack with rounding shift
+//! @{
+//! @brief Pack values from two vectors to one with rounding shift
+//!
+//! Values from the input vectors will be shifted right by _n_ bits with rounding, converted to narrower
+//! type and returned in the result vector. Variant with _u_ suffix converts to unsigned type.
+//!
+//! - pack: for 16-, 32- and 64-bit integer input types
+//! - pack_u: for 16- and 32-bit signed integer input types
+//!
+//! @note All variants except 64-bit use saturation.
+OPENCV_HAL_IMPL_C_RSHR_PACK(ushort, uchar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK(short, schar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK(unsigned, ushort, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK(int, short, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK(uint64, unsigned, pack, static_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK(int64, int, pack, static_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK(short, uchar, pack_u, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK(int, ushort, pack_u, saturate_cast)
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_PACK_STORE(_Tp, _Tpn, pack_suffix, cast) \
+template<int n> inline void v_##pack_suffix##_store(_Tpn* ptr, const v_reg<_Tp, n>& a) \
+{ \
+    for( int i = 0; i < n; i++ ) \
+        ptr[i] = cast<_Tpn>(a.s[i]); \
+}
+
+//! @name Pack and store
+//! @{
+//! @brief Store values from the input vector into memory with pack
+//!
+//! Values will be stored into memory with conversion to narrower type.
+//! Variant with _u_ suffix converts to corresponding unsigned type.
+//!
+//! - pack: for 16-, 32- and 64-bit integer input types
+//! - pack_u: for 16- and 32-bit signed integer input types
+//!
+//! @note All variants except 64-bit use saturation.
+OPENCV_HAL_IMPL_C_PACK_STORE(ushort, uchar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK_STORE(short, schar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK_STORE(unsigned, ushort, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK_STORE(int, short, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK_STORE(uint64, unsigned, pack, static_cast)
+OPENCV_HAL_IMPL_C_PACK_STORE(int64, int, pack, static_cast)
+OPENCV_HAL_IMPL_C_PACK_STORE(short, uchar, pack_u, saturate_cast)
+OPENCV_HAL_IMPL_C_PACK_STORE(int, ushort, pack_u, saturate_cast)
+//! @}
+
+//! @brief Helper macro
+//! @ingroup core_hal_intrin_impl
+#define OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(_Tp, _Tpn, pack_suffix, cast) \
+template<int shift, int n> inline void v_rshr_##pack_suffix##_store(_Tpn* ptr, const v_reg<_Tp, n>& a) \
+{ \
+    for( int i = 0; i < n; i++ ) \
+        ptr[i] = cast<_Tpn>((a.s[i] + ((_Tp)1 << (shift - 1))) >> shift); \
+}
+
+//! @name Pack and store with rounding shift
+//! @{
+//! @brief Store values from the input vector into memory with pack
+//!
+//! Values will be shifted _n_ bits right with rounding, converted to narrower type and stored into
+//! memory. Variant with _u_ suffix converts to unsigned type.
+//!
+//! - pack: for 16-, 32- and 64-bit integer input types
+//! - pack_u: for 16- and 32-bit signed integer input types
+//!
+//! @note All variants except 64-bit use saturation.
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(ushort, uchar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(short, schar, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(unsigned, ushort, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(int, short, pack, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(uint64, unsigned, pack, static_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(int64, int, pack, static_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(short, uchar, pack_u, saturate_cast)
+OPENCV_HAL_IMPL_C_RSHR_PACK_STORE(int, ushort, pack_u, saturate_cast)
+//! @}
+
+//! @cond IGNORED
+template<typename _Tpm, typename _Tp, int n>
+inline void _pack_b(_Tpm* mptr, const v_reg<_Tp, n>& a, const v_reg<_Tp, n>& b)
+{
+    for (int i = 0; i < n; ++i)
+    {
+        mptr[i] = (_Tpm)a.s[i];
+        mptr[i + n] = (_Tpm)b.s[i];
+    }
+}
+//! @endcond
+
+//! @name Pack boolean values
+//! @{
+//! @brief Pack boolean values from multiple vectors to one unsigned 8-bit integer vector
+//!
+//! @note Must provide valid boolean values to guarantee same result for all architectures.
+
+/** @brief
+//! For 16-bit boolean values
+
+Scheme:
+@code
+a  {0xFFFF 0 0 0xFFFF 0 0xFFFF 0xFFFF 0}
+b  {0xFFFF 0 0xFFFF 0 0 0xFFFF 0 0xFFFF}
+===============
+{
+   0xFF 0 0 0xFF 0 0xFF 0xFF 0
+   0xFF 0 0xFF 0 0 0xFF 0 0xFF
+}
+@endcode */
+
+template<int n> inline v_reg<uchar, 2*n> v_pack_b(const v_reg<ushort, n>& a, const v_reg<ushort, n>& b)
+{
+    v_reg<uchar, 2*n> mask;
+    _pack_b(mask.s, a, b);
+    return mask;
+}
+
+/** @overload
+For 32-bit boolean values
+
+Scheme:
+@code
+a  {0xFFFF.. 0 0 0xFFFF..}
+b  {0 0xFFFF.. 0xFFFF.. 0}
+c  {0xFFFF.. 0 0xFFFF.. 0}
+d  {0 0xFFFF.. 0 0xFFFF..}
+===============
+{
+   0xFF 0 0 0xFF 0 0xFF 0xFF 0
+   0xFF 0 0xFF 0 0 0xFF 0 0xFF
+}
+@endcode */
+
+template<int n> inline v_reg<uchar, 4*n> v_pack_b(const v_reg<unsigned, n>& a, const v_reg<unsigned, n>& b,
+                                                  const v_reg<unsigned, n>& c, const v_reg<unsigned, n>& d)
+{
+    v_reg<uchar, 4*n> mask;
+    _pack_b(mask.s, a, b);
+    _pack_b(mask.s + 2*n, c, d);
+    return mask;
+}
+
+/** @overload
+For 64-bit boolean values
+
+Scheme:
+@code
+a  {0xFFFF.. 0}
+b  {0 0xFFFF..}
+c  {0xFFFF.. 0}
+d  {0 0xFFFF..}
+
+e  {0xFFFF.. 0}
+f  {0xFFFF.. 0}
+g  {0 0xFFFF..}
+h  {0 0xFFFF..}
+===============
+{
+   0xFF 0 0 0xFF 0xFF 0 0 0xFF
+   0xFF 0 0xFF 0 0 0xFF 0 0xFF
+}
+@endcode */
+template<int n> inline v_reg<uchar, 8*n> v_pack_b(const v_reg<uint64, n>& a, const v_reg<uint64, n>& b,
+                                                  const v_reg<uint64, n>& c, const v_reg<uint64, n>& d,
+                                                  const v_reg<uint64, n>& e, const v_reg<uint64, n>& f,
+                                                  const v_reg<uint64, n>& g, const v_reg<uint64, n>& h)
+{
+    v_reg<uchar, 8*n> mask;
+    _pack_b(mask.s, a, b);
+    _pack_b(mask.s + 2*n, c, d);
+    _pack_b(mask.s + 4*n, e, f);
+    _pack_b(mask.s + 6*n, g, h);
+    return mask;
+}
+//! @}
+
+/** @brief Matrix multiplication
+
+Scheme:
+@code
+{A0 A1 A2 A3}   |V0|
+{B0 B1 B2 B3}   |V1|
+{C0 C1 C2 C3}   |V2|
+{D0 D1 D2 D3} x |V3|
+====================
+{R0 R1 R2 R3}, where:
+R0 = A0V0 + B0V1 + C0V2 + D0V3,
+R1 = A1V0 + B1V1 + C1V2 + D1V3
+...
+@endcode
+*/
+template<int n>
+inline v_reg<float, n> v_matmul(const v_reg<float, n>& v,
+                                const v_reg<float, n>& a, const v_reg<float, n>& b,
+                                const v_reg<float, n>& c, const v_reg<float, n>& d)
+{
+    v_reg<float, n> res;
+    for (int i = 0; i < n / 4; i++)
+    {
+        res.s[0 + i*4] = v.s[0 + i*4] * a.s[0 + i*4] + v.s[1 + i*4] * b.s[0 + i*4] + v.s[2 + i*4] * c.s[0 + i*4] + v.s[3 + i*4] * d.s[0 + i*4];
+        res.s[1 + i*4] = v.s[0 + i*4] * a.s[1 + i*4] + v.s[1 + i*4] * b.s[1 + i*4] + v.s[2 + i*4] * c.s[1 + i*4] + v.s[3 + i*4] * d.s[1 + i*4];
+        res.s[2 + i*4] = v.s[0 + i*4] * a.s[2 + i*4] + v.s[1 + i*4] * b.s[2 + i*4] + v.s[2 + i*4] * c.s[2 + i*4] + v.s[3 + i*4] * d.s[2 + i*4];
+        res.s[3 + i*4] = v.s[0 + i*4] * a.s[3 + i*4] + v.s[1 + i*4] * b.s[3 + i*4] + v.s[2 + i*4] * c.s[3 + i*4] + v.s[3 + i*4] * d.s[3 + i*4];
+    }
+    return res;
+}
+
+/** @brief Matrix multiplication and add
+
+Scheme:
+@code
+{A0 A1 A2 A3}   |V0|   |D0|
+{B0 B1 B2 B3}   |V1|   |D1|
+{C0 C1 C2 C3} x |V2| + |D2|
+====================   |D3|
+{R0 R1 R2 R3}, where:
+R0 = A0V0 + B0V1 + C0V2 + D0,
+R1 = A1V0 + B1V1 + C1V2 + D1
+...
+@endcode
+*/
+template<int n>
+inline v_reg<float, n> v_matmuladd(const v_reg<float, n>& v,
+                                   const v_reg<float, n>& a, const v_reg<float, n>& b,
+                                   const v_reg<float, n>& c, const v_reg<float, n>& d)
+{
+    v_reg<float, n> res;
+    for (int i = 0; i < n / 4; i++)
+    {
+        res.s[0 + i * 4] = v.s[0 + i * 4] * a.s[0 + i * 4] + v.s[1 + i * 4] * b.s[0 + i * 4] + v.s[2 + i * 4] * c.s[0 + i * 4] + d.s[0 + i * 4];
+        res.s[1 + i * 4] = v.s[0 + i * 4] * a.s[1 + i * 4] + v.s[1 + i * 4] * b.s[1 + i * 4] + v.s[2 + i * 4] * c.s[1 + i * 4] + d.s[1 + i * 4];
+        res.s[2 + i * 4] = v.s[0 + i * 4] * a.s[2 + i * 4] + v.s[1 + i * 4] * b.s[2 + i * 4] + v.s[2 + i * 4] * c.s[2 + i * 4] + d.s[2 + i * 4];
+        res.s[3 + i * 4] = v.s[0 + i * 4] * a.s[3 + i * 4] + v.s[1 + i * 4] * b.s[3 + i * 4] + v.s[2 + i * 4] * c.s[3 + i * 4] + d.s[3 + i * 4];
+    }
+    return res;
+}
+
+
+template<int n> inline v_reg<double, n/2> v_dotprod_expand(const v_reg<int, n>& a, const v_reg<int, n>& b)
+{ return v_fma(v_cvt_f64(a), v_cvt_f64(b), v_mul(v_cvt_f64_high(a), v_cvt_f64_high(b))); }
+template<int n> inline v_reg<double, n/2> v_dotprod_expand(const v_reg<int, n>& a, const v_reg<int, n>& b,
+                                                           const v_reg<double, n/2>& c)
+{ return v_fma(v_cvt_f64(a), v_cvt_f64(b), v_fma(v_cvt_f64_high(a), v_cvt_f64_high(b), c)); }
+
+template<int n> inline v_reg<double, n/2> v_dotprod_expand_fast(const v_reg<int, n>& a, const v_reg<int, n>& b)
+{ return v_dotprod_expand(a, b); }
+template<int n> inline v_reg<double, n/2> v_dotprod_expand_fast(const v_reg<int, n>& a, const v_reg<int, n>& b,
+                                                                const v_reg<double, n/2>& c)
+{ return v_dotprod_expand(a, b, c); }
+
+////// FP16 support ///////
+
+inline v_reg<float, simd128_width / sizeof(float)>
+v_load_expand(const hfloat* ptr)
+{
+    v_reg<float, simd128_width / sizeof(float)> v;
+    for( int i = 0; i < v.nlanes; i++ )
+    {
+        v.s[i] = ptr[i];
+    }
+    return v;
+}
+#if CV_SIMD256
+inline v_reg<float, simd256_width / sizeof(float)>
+v256_load_expand(const hfloat* ptr)
+{
+    v_reg<float, simd256_width / sizeof(float)> v;
+    for (int i = 0; i < v.nlanes; i++)
+    {
+        v.s[i] = ptr[i];
+    }
+    return v;
+}
+#endif
+#if CV_SIMD512
+inline v_reg<float, simd512_width / sizeof(float)>
+v512_load_expand(const hfloat* ptr)
+{
+    v_reg<float, simd512_width / sizeof(float)> v;
+    for (int i = 0; i < v.nlanes; i++)
+    {
+        v.s[i] = ptr[i];
+    }
+    return v;
+}
+#endif
+
+template<int n> inline void
+v_pack_store(hfloat* ptr, const v_reg<float, n>& v)
+{
+    for( int i = 0; i < v.nlanes; i++ )
+    {
+        ptr[i] = hfloat(v.s[i]);
+    }
+}
+
+inline void v_cleanup() {}
+#if CV_SIMD256
+inline void v256_cleanup() {}
+#endif
+#if CV_SIMD512
+inline void v512_cleanup() {}
+#endif
+
+//! @}
+
+#ifndef CV_DOXYGEN
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+#endif
+}
+
+#if !defined(CV_DOXYGEN)
+#undef CV_SIMD256
+#undef CV_SIMD512
+#endif
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_forward.hpp

@@ -0,0 +1,191 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+#ifndef CV__SIMD_FORWARD
+#error "Need to pre-define forward width"
+#endif
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+/** Types **/
+#if CV__SIMD_FORWARD == 1024
+// [todo] 1024
+#error "1024-long ops not implemented yet"
+#elif CV__SIMD_FORWARD == 512
+// 512
+#define __CV_VX(fun)   v512_##fun
+#define __CV_V_UINT8   v_uint8x64
+#define __CV_V_INT8    v_int8x64
+#define __CV_V_UINT16  v_uint16x32
+#define __CV_V_INT16   v_int16x32
+#define __CV_V_UINT32  v_uint32x16
+#define __CV_V_INT32   v_int32x16
+#define __CV_V_UINT64  v_uint64x8
+#define __CV_V_INT64   v_int64x8
+#define __CV_V_FLOAT32 v_float32x16
+#define __CV_V_FLOAT64 v_float64x8
+struct v_uint8x64;
+struct v_int8x64;
+struct v_uint16x32;
+struct v_int16x32;
+struct v_uint32x16;
+struct v_int32x16;
+struct v_uint64x8;
+struct v_int64x8;
+struct v_float32x16;
+struct v_float64x8;
+#elif CV__SIMD_FORWARD == 256
+// 256
+#define __CV_VX(fun)   v256_##fun
+#define __CV_V_UINT8   v_uint8x32
+#define __CV_V_INT8    v_int8x32
+#define __CV_V_UINT16  v_uint16x16
+#define __CV_V_INT16   v_int16x16
+#define __CV_V_UINT32  v_uint32x8
+#define __CV_V_INT32   v_int32x8
+#define __CV_V_UINT64  v_uint64x4
+#define __CV_V_INT64   v_int64x4
+#define __CV_V_FLOAT32 v_float32x8
+#define __CV_V_FLOAT64 v_float64x4
+struct v_uint8x32;
+struct v_int8x32;
+struct v_uint16x16;
+struct v_int16x16;
+struct v_uint32x8;
+struct v_int32x8;
+struct v_uint64x4;
+struct v_int64x4;
+struct v_float32x8;
+struct v_float64x4;
+#else
+// 128
+#define __CV_VX(fun)   v_##fun
+#define __CV_V_UINT8   v_uint8x16
+#define __CV_V_INT8    v_int8x16
+#define __CV_V_UINT16  v_uint16x8
+#define __CV_V_INT16   v_int16x8
+#define __CV_V_UINT32  v_uint32x4
+#define __CV_V_INT32   v_int32x4
+#define __CV_V_UINT64  v_uint64x2
+#define __CV_V_INT64   v_int64x2
+#define __CV_V_FLOAT32 v_float32x4
+#define __CV_V_FLOAT64 v_float64x2
+struct v_uint8x16;
+struct v_int8x16;
+struct v_uint16x8;
+struct v_int16x8;
+struct v_uint32x4;
+struct v_int32x4;
+struct v_uint64x2;
+struct v_int64x2;
+struct v_float32x4;
+struct v_float64x2;
+#endif
+
+/** Value reordering **/
+
+// Expansion
+void v_expand(const __CV_V_UINT8&,  __CV_V_UINT16&, __CV_V_UINT16&);
+void v_expand(const __CV_V_INT8&,   __CV_V_INT16&,  __CV_V_INT16&);
+void v_expand(const __CV_V_UINT16&, __CV_V_UINT32&, __CV_V_UINT32&);
+void v_expand(const __CV_V_INT16&,  __CV_V_INT32&,  __CV_V_INT32&);
+void v_expand(const __CV_V_UINT32&, __CV_V_UINT64&, __CV_V_UINT64&);
+void v_expand(const __CV_V_INT32&,  __CV_V_INT64&,  __CV_V_INT64&);
+// Low Expansion
+__CV_V_UINT16 v_expand_low(const __CV_V_UINT8&);
+__CV_V_INT16  v_expand_low(const __CV_V_INT8&);
+__CV_V_UINT32 v_expand_low(const __CV_V_UINT16&);
+__CV_V_INT32  v_expand_low(const __CV_V_INT16&);
+__CV_V_UINT64 v_expand_low(const __CV_V_UINT32&);
+__CV_V_INT64  v_expand_low(const __CV_V_INT32&);
+// High Expansion
+__CV_V_UINT16 v_expand_high(const __CV_V_UINT8&);
+__CV_V_INT16  v_expand_high(const __CV_V_INT8&);
+__CV_V_UINT32 v_expand_high(const __CV_V_UINT16&);
+__CV_V_INT32  v_expand_high(const __CV_V_INT16&);
+__CV_V_UINT64 v_expand_high(const __CV_V_UINT32&);
+__CV_V_INT64  v_expand_high(const __CV_V_INT32&);
+// Load & Low Expansion
+__CV_V_UINT16 __CV_VX(load_expand)(const uchar*);
+__CV_V_INT16  __CV_VX(load_expand)(const schar*);
+__CV_V_UINT32 __CV_VX(load_expand)(const ushort*);
+__CV_V_INT32  __CV_VX(load_expand)(const short*);
+__CV_V_UINT64 __CV_VX(load_expand)(const uint*);
+__CV_V_INT64  __CV_VX(load_expand)(const int*);
+// Load lower 8-bit and expand into 32-bit
+__CV_V_UINT32 __CV_VX(load_expand_q)(const uchar*);
+__CV_V_INT32  __CV_VX(load_expand_q)(const schar*);
+
+// Saturating Pack
+__CV_V_UINT8  v_pack(const __CV_V_UINT16&, const __CV_V_UINT16&);
+__CV_V_INT8   v_pack(const __CV_V_INT16&,  const __CV_V_INT16&);
+__CV_V_UINT16 v_pack(const __CV_V_UINT32&, const __CV_V_UINT32&);
+__CV_V_INT16  v_pack(const __CV_V_INT32&,  const __CV_V_INT32&);
+// Non-saturating Pack
+__CV_V_UINT32 v_pack(const __CV_V_UINT64&, const __CV_V_UINT64&);
+__CV_V_INT32  v_pack(const __CV_V_INT64&,  const __CV_V_INT64&);
+// Pack signed integers with unsigned saturation
+__CV_V_UINT8  v_pack_u(const __CV_V_INT16&, const __CV_V_INT16&);
+__CV_V_UINT16 v_pack_u(const __CV_V_INT32&, const __CV_V_INT32&);
+
+/** Arithmetic, bitwise and comparison operations **/
+
+// Non-saturating multiply
+#if CV_VSX
+template<typename Tvec>
+Tvec v_mul_wrap(const Tvec& a, const Tvec& b);
+#else
+__CV_V_UINT8  v_mul_wrap(const __CV_V_UINT8&,  const __CV_V_UINT8&);
+__CV_V_INT8   v_mul_wrap(const __CV_V_INT8&,   const __CV_V_INT8&);
+__CV_V_UINT16 v_mul_wrap(const __CV_V_UINT16&, const __CV_V_UINT16&);
+__CV_V_INT16  v_mul_wrap(const __CV_V_INT16&,  const __CV_V_INT16&);
+#endif
+
+//  Multiply and expand
+#if CV_VSX
+template<typename Tvec, typename Twvec>
+void v_mul_expand(const Tvec& a, const Tvec& b, Twvec& c, Twvec& d);
+#else
+void v_mul_expand(const __CV_V_UINT8&,  const __CV_V_UINT8&,  __CV_V_UINT16&, __CV_V_UINT16&);
+void v_mul_expand(const __CV_V_INT8&,   const __CV_V_INT8&,   __CV_V_INT16&,  __CV_V_INT16&);
+void v_mul_expand(const __CV_V_UINT16&, const __CV_V_UINT16&, __CV_V_UINT32&, __CV_V_UINT32&);
+void v_mul_expand(const __CV_V_INT16&,  const __CV_V_INT16&,  __CV_V_INT32&,  __CV_V_INT32&);
+void v_mul_expand(const __CV_V_UINT32&, const __CV_V_UINT32&, __CV_V_UINT64&, __CV_V_UINT64&);
+void v_mul_expand(const __CV_V_INT32&,  const __CV_V_INT32&,  __CV_V_INT64&,  __CV_V_INT64&);
+#endif
+
+// Conversions
+__CV_V_FLOAT32 v_cvt_f32(const __CV_V_INT32& a);
+__CV_V_FLOAT32 v_cvt_f32(const __CV_V_FLOAT64& a);
+__CV_V_FLOAT32 v_cvt_f32(const __CV_V_FLOAT64& a, const __CV_V_FLOAT64& b);
+__CV_V_FLOAT64 v_cvt_f64(const __CV_V_INT32& a);
+__CV_V_FLOAT64 v_cvt_f64_high(const __CV_V_INT32& a);
+__CV_V_FLOAT64 v_cvt_f64(const __CV_V_FLOAT32& a);
+__CV_V_FLOAT64 v_cvt_f64_high(const __CV_V_FLOAT32& a);
+__CV_V_FLOAT64 v_cvt_f64(const __CV_V_INT64& a);
+
+/** Cleanup **/
+#undef CV__SIMD_FORWARD
+#undef __CV_VX
+#undef __CV_V_UINT8
+#undef __CV_V_INT8
+#undef __CV_V_UINT16
+#undef __CV_V_INT16
+#undef __CV_V_UINT32
+#undef __CV_V_INT32
+#undef __CV_V_UINT64
+#undef __CV_V_INT64
+#undef __CV_V_FLOAT32
+#undef __CV_V_FLOAT64
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+} // cv::

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_lasx.hpp

@@ -0,0 +1,3036 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+#ifndef OPENCV_HAL_INTRIN_LASX_HPP
+#define OPENCV_HAL_INTRIN_LASX_HPP
+
+#include <lsxintrin.h>
+#include <lasxintrin.h>
+
+#define CV_SIMD256 1
+#define CV_SIMD256_64F 1
+#define CV_SIMD256_FP16 0
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+///////// Utils ////////////
+
+inline __m256i _v256_setr_b(char v0, char v1, char v2, char v3, char v4, char v5, char v6, char v7, char v8,  char v9,
+                    char v10, char v11, char v12, char v13, char v14, char v15, char v16, char v17, char v18, char v19,
+                    char v20, char v21, char v22, char v23, char v24, char v25, char v26, char v27, char v28, char v29,
+                    char v30, char v31)
+{
+    return (__m256i)v32i8{ v0, v1, v2, v3, v4, v5, v6, v7, v8, v9,
+                           v10, v11, v12, v13, v14, v15, v16, v17, v18, v19,
+                           v20, v21, v22, v23, v24, v25, v26, v27, v28, v29,
+                           v30, v31 };
+}
+
+inline __m256i _v256_set_b(char v0, char v1, char v2, char v3, char v4, char v5, char v6, char v7, char v8,  char v9,
+                   char v10, char v11, char v12, char v13, char v14, char v15, char v16, char v17, char v18, char v19,
+                   char v20, char v21, char v22, char v23, char v24, char v25, char v26, char v27, char v28, char v29,
+                   char v30, char v31)
+{
+    return (__m256i)v32i8{ v31, v30,
+                           v29, v28, v27, v26, v25, v24, v23, v22, v21, v20,
+                           v19, v18, v17, v16, v15, v14, v13, v12, v11, v10,
+                           v9, v8, v7, v6, v5, v4, v3, v2, v1, v0 };
+}
+
+inline __m256i _v256_setr_h(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7,
+                            short v8,  short v9, short v10, short v11, short v12, short v13, short v14, short v15)
+{
+    return (__m256i)v16i16{ v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15 };
+}
+
+inline __m256i _v256_setr_w(int v0, int v1, int v2, int v3, int v4, int v5, int v6, int v7)
+{
+    return (__m256i)v8i32{ v0, v1, v2, v3, v4, v5, v6, v7 };
+}
+
+inline __m256i _v256_set_w(int v0, int v1, int v2, int v3, int v4, int v5, int v6, int v7)
+{
+    return (__m256i)v8i32{ v7, v6, v5, v4, v3, v2, v1, v0 };
+}
+
+inline __m256i _v256_setall_w(int v0)
+{
+    return (__m256i)v8i32{ v0, v0, v0, v0, v0, v0, v0, v0 };
+}
+
+inline __m256i _v256_setr_d(int64 v0, int64 v1, int64 v2, int64 v3)
+{
+    return (__m256i)v4i64{ v0, v1, v2, v3 };
+}
+
+inline __m256i _v256_set_d(int64 v0, int64 v1, int64 v2, int64 v3)
+{
+    return (__m256i)v4i64{ v3, v2, v1, v0 };
+}
+
+inline __m256 _v256_setr_ps(float v0, float v1, float v2, float v3, float v4, float v5, float v6, float v7)
+{
+    return (__m256)v8f32{ v0, v1, v2, v3, v4, v5, v6, v7 };
+}
+
+inline __m256 _v256_setall_ps(float f32)
+{
+    return (__m256)v8f32{ f32, f32, f32, f32, f32, f32, f32, f32 };
+}
+
+inline __m256d _v256_setr_pd(double v0, double v1, double v2, double v3)
+{
+    return (__m256d)v4f64{ v0, v1, v2, v3 };
+}
+
+inline __m256d _v256_setall_pd(double f64)
+{
+    return (__m256d)v4f64{ f64, f64, f64, f64 };
+}
+
+inline __m256i _lasx_packus_h(const __m256i& a, const __m256i& b)
+{
+    return __lasx_xvssrarni_bu_h(b, a, 0);
+}
+
+inline __m256i _lasx_packs_h(const __m256i& a, const __m256i& b)
+{
+    return __lasx_xvssrarni_b_h(b, a, 0);
+}
+
+inline __m256i _lasx_packus_w(const __m256i& a, const __m256i& b)
+{
+    return __lasx_xvssrarni_hu_w(b, a, 0);
+}
+
+inline __m256i _lasx_packs_w(const __m256i& a, const __m256i& b)
+{
+    return __lasx_xvssrarni_h_w(b, a, 0);
+}
+
+inline __m256i _v256_combine(const __m128i& lo, const __m128i& hi)
+{ return __lasx_xvpermi_q(*((__m256i*)&lo), *((__m256i*)&hi), 0x02); }
+
+inline __m256 _v256_combine(const __m128& lo, const __m128& hi)
+{ return __m256(__lasx_xvpermi_q(*((__m256i*)&lo), *((__m256i*)&hi), 0x02)); }
+
+inline __m256d _v256_combine(const __m128d& lo, const __m128d& hi)
+{ return __m256d(__lasx_xvpermi_q(*((__m256i*)&lo), *((__m256i*)&hi), 0x02)); }
+
+inline __m256i _v256_shuffle_odd_64(const __m256i& v)
+{ return __lasx_xvpermi_d(v, 0xd8); }
+
+inline __m256d _v256_shuffle_odd_64(const __m256d& v)
+{ return __m256d(__lasx_xvpermi_d(*((__m256i*)&v), 0xd8)); }
+
+//LASX: only use for permute WITHOUT zero clearing
+template<int imm>
+inline __m256i _v256_permute2x128(const __m256i& a, const __m256i& b)
+{ return __lasx_xvpermi_q(a, b, imm); }
+
+template<int imm>
+inline __m256 _v256_permute2x128(const __m256& a, const __m256& b)
+{ return __m256(__lasx_xvpermi_q(*((__m256i*)&a), *((__m256i*)&b), imm)); }
+
+template<int imm>
+inline __m256d _v256_permute2x128(const __m256d& a, const __m256d& b)
+{ return __m256d(__lasx_xvpermi_q(*((__m256i*)&a), *((__m256i*)&b), imm)); }
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v256_permute2x128(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(_v256_permute2x128<imm>(a.val, b.val)); }
+
+template<int imm>
+inline __m256i _v256_permute4x64(const __m256i& a)
+{ return __lasx_xvpermi_d(a, imm); }
+
+template<int imm>
+inline __m256d _v256_permute4x64(const __m256d& a)
+{ return __m256d(__lasx_xvpermi_d(*((__m256i*)&a), imm)); }
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v256_permute4x64(const _Tpvec& a)
+{ return _Tpvec(_v256_permute4x64<imm>(a.val)); }
+
+inline __m128i _v256_extract_high(const __m256i& v)
+{ __m256i temp256i = __lasx_xvpermi_d(v, 0x4E);
+  return *((__m128i*)&temp256i); }
+
+inline __m128  _v256_extract_high(const __m256& v)
+{ return __m128(_v256_extract_high(*((__m256i*)&v))); }
+
+inline __m128d _v256_extract_high(const __m256d& v)
+{ return __m128d(_v256_extract_high(*((__m256i*)&v))); }
+
+inline __m128i _v256_extract_low(const __m256i& v)
+{ return *((__m128i*)&v); }
+
+inline __m128  _v256_extract_low(const __m256& v)
+{ return __m128(_v256_extract_low(*((__m256i*)&v))); }
+
+inline __m128d _v256_extract_low(const __m256d& v)
+{ return __m128d(_v256_extract_low(*((__m256i*)&v))); }
+
+inline __m256i _v256_packs_epu32(const __m256i& a, const __m256i& b)
+{
+    return __lasx_xvssrlrni_hu_w(b, a, 0);
+}
+
+template<int i>
+inline int _v256_extract_b(const __m256i& a)
+{
+    int des[1] = {0};
+    __lasx_xvstelm_b(a, des, 0, i);
+    return des[0];
+}
+
+template<int i>
+inline int _v256_extract_h(const __m256i& a)
+{
+    int des[1] = {0};
+    __lasx_xvstelm_h(a, des, 0, i);
+    return des[0];
+}
+
+template<int i>
+inline int _v256_extract_w(const __m256i& a)
+{
+    return __lasx_xvpickve2gr_w(a, i);
+}
+
+template<int i>
+inline int64 _v256_extract_d(const __m256i& a)
+{
+    return __lasx_xvpickve2gr_d(a, i);
+}
+
+///////// Types ////////////
+
+struct v_uint8x32
+{
+    typedef uchar lane_type;
+    enum { nlanes = 32 };
+    __m256i val;
+
+    explicit v_uint8x32(__m256i v) : val(v) {}
+    v_uint8x32(uchar v0,  uchar v1,  uchar v2,  uchar v3,
+               uchar v4,  uchar v5,  uchar v6,  uchar v7,
+               uchar v8,  uchar v9,  uchar v10, uchar v11,
+               uchar v12, uchar v13, uchar v14, uchar v15,
+               uchar v16, uchar v17, uchar v18, uchar v19,
+               uchar v20, uchar v21, uchar v22, uchar v23,
+               uchar v24, uchar v25, uchar v26, uchar v27,
+               uchar v28, uchar v29, uchar v30, uchar v31)
+    {
+        val = _v256_setr_b((char)v0, (char)v1, (char)v2, (char)v3,
+            (char)v4,  (char)v5,  (char)v6 , (char)v7,  (char)v8,  (char)v9,
+            (char)v10, (char)v11, (char)v12, (char)v13, (char)v14, (char)v15,
+            (char)v16, (char)v17, (char)v18, (char)v19, (char)v20, (char)v21,
+            (char)v22, (char)v23, (char)v24, (char)v25, (char)v26, (char)v27,
+            (char)v28, (char)v29, (char)v30, (char)v31);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint8x32() {}
+
+    uchar get0() const {
+        uchar des[1] = {0};
+        __lasx_xvstelm_b(val, des, 0, 0);
+        return des[0];
+    }
+};
+
+struct v_int8x32
+{
+    typedef schar lane_type;
+    enum { nlanes = 32 };
+    __m256i val;
+
+    explicit v_int8x32(__m256i v) : val(v) {}
+    v_int8x32(schar v0,  schar v1,  schar v2,  schar v3,
+              schar v4,  schar v5,  schar v6,  schar v7,
+              schar v8,  schar v9,  schar v10, schar v11,
+              schar v12, schar v13, schar v14, schar v15,
+              schar v16, schar v17, schar v18, schar v19,
+              schar v20, schar v21, schar v22, schar v23,
+              schar v24, schar v25, schar v26, schar v27,
+              schar v28, schar v29, schar v30, schar v31)
+    {
+        val = _v256_setr_b(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9,
+            v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20,
+            v21, v22, v23, v24, v25, v26, v27, v28, v29, v30, v31);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int8x32() {}
+
+    schar get0() const {
+        schar des[1] = {0};
+        __lasx_xvstelm_b(val, des, 0, 0);
+        return des[0];
+    }
+};
+
+struct v_uint16x16
+{
+    typedef ushort lane_type;
+    enum { nlanes = 16 };
+    __m256i val;
+
+    explicit v_uint16x16(__m256i v) : val(v) {}
+    v_uint16x16(ushort v0,  ushort v1,  ushort v2,  ushort v3,
+                ushort v4,  ushort v5,  ushort v6,  ushort v7,
+                ushort v8,  ushort v9,  ushort v10, ushort v11,
+                ushort v12, ushort v13, ushort v14, ushort v15)
+    {
+        val = _v256_setr_h((short)v0, (short)v1, (short)v2, (short)v3,
+            (short)v4,  (short)v5,  (short)v6,  (short)v7,  (short)v8,  (short)v9,
+            (short)v10, (short)v11, (short)v12, (short)v13, (short)v14, (short)v15);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint16x16() {}
+
+    ushort get0() const {
+        ushort des[1] = {0};
+        __lasx_xvstelm_h(val, des, 0, 0);
+        return des[0];
+    }
+};
+
+struct v_int16x16
+{
+    typedef short lane_type;
+    enum { nlanes = 16 };
+    __m256i val;
+
+    explicit v_int16x16(__m256i v) : val(v) {}
+    v_int16x16(short v0,  short v1,  short v2,  short v3,
+               short v4,  short v5,  short v6,  short v7,
+               short v8,  short v9,  short v10, short v11,
+               short v12, short v13, short v14, short v15)
+    {
+        val = _v256_setr_h(v0, v1, v2, v3, v4, v5, v6, v7,
+            v8, v9, v10, v11, v12, v13, v14, v15);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int16x16() {}
+
+    short get0() const {
+        short des[1] = {0};
+        __lasx_xvstelm_h(val, des, 0, 0);
+        return des[0];
+    }
+};
+
+struct v_uint32x8
+{
+    typedef unsigned lane_type;
+    enum { nlanes = 8 };
+    __m256i val;
+
+    explicit v_uint32x8(__m256i v) : val(v) {}
+    v_uint32x8(unsigned v0, unsigned v1, unsigned v2, unsigned v3,
+               unsigned v4, unsigned v5, unsigned v6, unsigned v7)
+    {
+        val = _v256_setr_w((unsigned)v0, (unsigned)v1, (unsigned)v2,
+            (unsigned)v3, (unsigned)v4, (unsigned)v5, (unsigned)v6, (unsigned)v7);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint32x8() {}
+
+    unsigned get0() const { return __lasx_xvpickve2gr_wu(val, 0); }
+};
+
+struct v_int32x8
+{
+    typedef int lane_type;
+    enum { nlanes = 8 };
+    __m256i val;
+
+    explicit v_int32x8(__m256i v) : val(v) {}
+    v_int32x8(int v0, int v1, int v2, int v3,
+              int v4, int v5, int v6, int v7)
+    {
+        val = _v256_setr_w(v0, v1, v2, v3, v4, v5, v6, v7);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int32x8() {}
+
+    int get0() const { return __lasx_xvpickve2gr_w(val, 0); }
+};
+
+struct v_float32x8
+{
+    typedef float lane_type;
+    enum { nlanes = 8 };
+    __m256 val;
+
+    explicit v_float32x8(__m256 v) : val(v) {}
+    explicit v_float32x8(__m256i v) { val = *((__m256*)&v); }
+    v_float32x8(float v0, float v1, float v2, float v3,
+                float v4, float v5, float v6, float v7)
+    {
+        val = _v256_setr_ps(v0, v1, v2, v3, v4, v5, v6, v7);
+    }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_float32x8() {}
+
+    float get0() const {
+        float des[1] = {0};
+        __lasx_xvstelm_w(*((__m256i*)&val), des, 0, 0);
+        return des[0];
+    }
+
+    int get0toint() const {
+        int des[1] = {0};
+        __lasx_xvstelm_w(*((__m256i*)&val), des, 0, 0);
+        return des[0];
+    }
+};
+
+struct v_uint64x4
+{
+    typedef uint64 lane_type;
+    enum { nlanes = 4 };
+    __m256i val;
+
+    explicit v_uint64x4(__m256i v) : val(v) {}
+    v_uint64x4(uint64 v0, uint64 v1, uint64 v2, uint64 v3)
+    { val = _v256_setr_d((int64)v0, (int64)v1, (int64)v2, (int64)v3); }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint64x4() {}
+
+    uint64 get0() const
+    {
+        return __lasx_xvpickve2gr_du(val, 0);
+    }
+};
+
+struct v_int64x4
+{
+    typedef int64 lane_type;
+    enum { nlanes = 4 };
+    __m256i val;
+
+    explicit v_int64x4(__m256i v) : val(v) {}
+    v_int64x4(int64 v0, int64 v1, int64 v2, int64 v3)
+    { val = _v256_setr_d(v0, v1, v2, v3); }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int64x4() {}
+
+    int64 get0() const
+    {
+        return __lasx_xvpickve2gr_d(val, 0);
+    }
+};
+
+struct v_float64x4
+{
+    typedef double lane_type;
+    enum { nlanes = 4 };
+    __m256d val;
+
+    explicit v_float64x4(__m256d v) : val(v) {}
+    explicit v_float64x4(__m256i v) { val = *((__m256d*)&v); }
+    v_float64x4(double v0, double v1, double v2, double v3)
+    { val = _v256_setr_pd(v0, v1, v2, v3); }
+    /* coverity[uninit_ctor]: suppress warning */
+    v_float64x4() {}
+
+    double get0() const {
+        double des[1] = {0};
+        __lasx_xvstelm_d(*((__m256i*)&val), des, 0, 0);
+        return des[0];
+    }
+
+    int64 get0toint64() const {
+        int64 des[1] = {0};
+        __lasx_xvstelm_d(*((__m256i*)&val), des, 0, 0);
+        return des[0];
+    }
+};
+
+//////////////// Load and store operations ///////////////
+
+#define OPENCV_HAL_IMPL_LASX_LOADSTORE(_Tpvec, _Tp)                   \
+    inline _Tpvec v256_load(const _Tp* ptr)                           \
+    { return _Tpvec(__lasx_xvld(ptr, 0)); }                           \
+    inline _Tpvec v256_load_aligned(const _Tp* ptr)                   \
+    { return _Tpvec(__lasx_xvld(ptr, 0)); }                           \
+    inline _Tpvec v256_load_low(const _Tp* ptr)                       \
+    {                                                                 \
+        __m128i v128 = __lsx_vld(ptr, 0);                             \
+        return _Tpvec(*((__m256i*)&v128));                            \
+    }                                                                 \
+    inline _Tpvec v256_load_halves(const _Tp* ptr0, const _Tp* ptr1)  \
+    {                                                                 \
+        __m128i vlo = __lsx_vld(ptr0, 0);                             \
+        __m128i vhi = __lsx_vld(ptr1, 0);                             \
+        return _Tpvec(_v256_combine(vlo, vhi));                       \
+    }                                                                 \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                    \
+    { __lasx_xvst(a.val, ptr, 0); }                                   \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)            \
+    { __lasx_xvst(a.val, ptr, 0); }                                   \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)    \
+    { __lasx_xvst(a.val, ptr, 0); }                                   \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+    { \
+        if( mode == hal::STORE_UNALIGNED ) \
+            __lasx_xvst(a.val, ptr, 0); \
+        else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+            __lasx_xvst(a.val, ptr, 0); \
+        else \
+            __lasx_xvst(a.val, ptr, 0); \
+    } \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                \
+    { __lsx_vst(_v256_extract_low(a.val), ptr, 0); }                  \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)               \
+    { __lsx_vst(_v256_extract_high(a.val), ptr, 0); }
+
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_uint8x32,  uchar)
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_int8x32,   schar)
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_uint16x16, ushort)
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_int16x16,  short)
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_uint32x8,  unsigned)
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_int32x8,   int)
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_uint64x4,  uint64)
+OPENCV_HAL_IMPL_LASX_LOADSTORE(v_int64x4,   int64)
+
+
+#define OPENCV_HAL_IMPL_LASX_LOADSTORE_FLT(_Tpvec, _Tp, halfreg)          \
+    inline _Tpvec v256_load(const _Tp* ptr)                               \
+    { return _Tpvec(__lasx_xvld(ptr, 0)); }                               \
+    inline _Tpvec v256_load_aligned(const _Tp* ptr)                       \
+    { return _Tpvec(__lasx_xvld(ptr, 0)); }                               \
+    inline _Tpvec v256_load_low(const _Tp* ptr)                           \
+    {                                                                     \
+        __m128i v128 = __lsx_vld(ptr, 0);                                 \
+        return _Tpvec(*((__m256i*)&v128));                                \
+    }                                                                     \
+    inline _Tpvec v256_load_halves(const _Tp* ptr0, const _Tp* ptr1)      \
+    {                                                                     \
+        halfreg vlo = __lsx_vld(ptr0, 0);                                 \
+        halfreg vhi = __lsx_vld(ptr1, 0);                                 \
+        return _Tpvec(_v256_combine(vlo, vhi));                           \
+    }                                                                     \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                        \
+    { __lasx_xvst(a.val, ptr, 0); }                                       \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)                \
+    { __lasx_xvst(a.val, ptr, 0); }                                       \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)        \
+    { __lasx_xvst(a.val, ptr, 0); }                                       \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+    { \
+        if( mode == hal::STORE_UNALIGNED ) \
+            __lasx_xvst(a.val, ptr, 0); \
+        else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+            __lasx_xvst(a.val, ptr, 0); \
+        else \
+            __lasx_xvst(a.val, ptr, 0); \
+    } \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                    \
+    { __lsx_vst(_v256_extract_low(a.val), ptr, 0); }                      \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)                   \
+    { __lsx_vst(_v256_extract_high(a.val), ptr, 0); }
+
+OPENCV_HAL_IMPL_LASX_LOADSTORE_FLT(v_float32x8, float, __m128i)
+OPENCV_HAL_IMPL_LASX_LOADSTORE_FLT(v_float64x4, double, __m128i)
+
+
+inline __m256i _lasx_256_castps_si256(const __m256& v)
+{ return __m256i(v); }
+
+inline __m256i _lasx_256_castpd_si256(const __m256d& v)
+{ return __m256i(v); }
+
+#define OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, _Tpvecf, suffix, cast) \
+    inline _Tpvec v_reinterpret_as_##suffix(const _Tpvecf& a)   \
+    { return _Tpvec(cast(a.val)); }
+
+#define OPENCV_HAL_IMPL_LASX_INIT(_Tpvec, _Tp, suffix, ssuffix, ctype_s)          \
+    inline _Tpvec v256_setzero_##suffix()                                         \
+    { return _Tpvec(__lasx_xvreplgr2vr_d(0)); }                                   \
+    inline _Tpvec v256_setall_##suffix(_Tp v)                                     \
+    { return _Tpvec(__lasx_xvreplgr2vr_##ssuffix((ctype_s)v)); }                  \
+    template <> inline _Tpvec v_setzero_()                                        \
+    { return v256_setzero_##suffix(); }                                           \
+    template <> inline _Tpvec v_setall_(_Tp v)                                    \
+    { return v256_setall_##suffix(v); }                                           \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint8x32,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int8x32,   suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint16x16, suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int16x16,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint32x8,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int32x8,   suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint64x4,  suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int64x4,   suffix, OPENCV_HAL_NOP)        \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_float32x8, suffix, _lasx_256_castps_si256) \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_float64x4, suffix, _lasx_256_castpd_si256)
+
+OPENCV_HAL_IMPL_LASX_INIT(v_uint8x32,  uchar,    u8,  b,   int)
+OPENCV_HAL_IMPL_LASX_INIT(v_int8x32,   schar,    s8,  b,   int)
+OPENCV_HAL_IMPL_LASX_INIT(v_uint16x16, ushort,   u16, h,  int)
+OPENCV_HAL_IMPL_LASX_INIT(v_int16x16,  short,    s16, h,  int)
+OPENCV_HAL_IMPL_LASX_INIT(v_uint32x8,  unsigned, u32, w,  int)
+OPENCV_HAL_IMPL_LASX_INIT(v_int32x8,   int,      s32, w,  int)
+OPENCV_HAL_IMPL_LASX_INIT(v_uint64x4,  uint64,   u64, d, long int)
+OPENCV_HAL_IMPL_LASX_INIT(v_int64x4,   int64,    s64, d, long int)
+
+
+inline __m256 _lasx_256_castsi256_ps(const __m256i &v)
+{ return __m256(v); }
+
+inline __m256d _lasx_256_castsi256_pd(const __m256i &v)
+{ return __m256d(v); }
+
+#define OPENCV_HAL_IMPL_LASX_INIT_FLT(_Tpvec, _Tp, suffix, zsuffix, cast) \
+    inline _Tpvec v256_setzero_##suffix()                                 \
+    { return _Tpvec(__lasx_xvreplgr2vr_d(0)); }                           \
+    inline _Tpvec v256_setall_##suffix(_Tp v)                             \
+    { return _Tpvec(_v256_setall_##zsuffix(v)); }                         \
+    template <> inline _Tpvec v_setzero_()                                \
+    { return v256_setzero_##suffix(); }                                   \
+    template <> inline _Tpvec v_setall_(_Tp v)                            \
+    { return v256_setall_##suffix(v); }                                   \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint8x32,  suffix, cast)          \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int8x32,   suffix, cast)          \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint16x16, suffix, cast)          \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int16x16,  suffix, cast)          \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint32x8,  suffix, cast)          \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int32x8,   suffix, cast)          \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_uint64x4,  suffix, cast)          \
+    OPENCV_HAL_IMPL_LASX_CAST(_Tpvec, v_int64x4,   suffix, cast)
+
+OPENCV_HAL_IMPL_LASX_INIT_FLT(v_float32x8, float,  f32, ps, _lasx_256_castsi256_ps)
+OPENCV_HAL_IMPL_LASX_INIT_FLT(v_float64x4, double, f64, pd, _lasx_256_castsi256_pd)
+
+inline v_float32x8 v_reinterpret_as_f32(const v_float32x8& a)
+{ return a; }
+inline v_float32x8 v_reinterpret_as_f32(const v_float64x4& a)
+{ return v_float32x8(_lasx_256_castps_si256(__m256(a.val))); }
+
+inline v_float64x4 v_reinterpret_as_f64(const v_float64x4& a)
+{ return a; }
+inline v_float64x4 v_reinterpret_as_f64(const v_float32x8& a)
+{ return v_float64x4(_lasx_256_castpd_si256(__m256d(a.val))); }
+
+
+//////////////// Variant Value reordering ///////////////
+
+// unpacks
+#define OPENCV_HAL_IMPL_LASX_UNPACK(_Tpvec, suffix)                 \
+    inline _Tpvec v256_unpacklo(const _Tpvec& a, const _Tpvec& b)   \
+    { return _Tpvec(__lasx_xvilvl_##suffix(__m256i(b.val), __m256i(a.val))); }        \
+    inline _Tpvec v256_unpackhi(const _Tpvec& a, const _Tpvec& b)   \
+    { return _Tpvec(__lasx_xvilvh_##suffix(__m256i(b.val), __m256i(a.val))); }
+
+OPENCV_HAL_IMPL_LASX_UNPACK(v_uint8x32,  b)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_int8x32,   b)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_uint16x16, h)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_int16x16,  h)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_uint32x8,  w)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_int32x8,   w)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_uint64x4,  d)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_int64x4,   d)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_float32x8, w)
+OPENCV_HAL_IMPL_LASX_UNPACK(v_float64x4, d)
+
+
+// shuffle
+// todo: emulate 64bit
+#define OPENCV_HAL_IMPL_LASX_SHUFFLE(_Tpvec, intrin)  \
+    template<int m>                                  \
+    inline _Tpvec v256_shuffle(const _Tpvec& a)      \
+    { return _Tpvec(__lasx_xvshuf4i_##intrin(a.val, m)); }
+
+OPENCV_HAL_IMPL_LASX_SHUFFLE(v_uint32x8,  w)
+OPENCV_HAL_IMPL_LASX_SHUFFLE(v_int32x8,   w)
+
+template<int m>
+inline v_float32x8 v256_shuffle(const v_float32x8 &a)
+{ return v_float32x8(__lasx_xvshuf4i_w(*((__m256i*)&a.val), m)); }
+
+template<int m>
+inline v_float64x4 v256_shuffle(const v_float64x4 &a)
+{
+    const int m1 = m & 0b1;
+    const int m2 = m & 0b10;
+    const int m3 = m & 0b100;
+    const int m4 = m & 0b1000;
+    const int m5 = m2 << 1;
+    const int m6 = m3 << 2;
+    const int m7 = m4 << 3;
+    const int m8 = m1 & m5 & m6 & m7;
+
+    return v_float64x4(__lasx_xvshuf4i_d(*((__m256i*)&a.val), *((__m256i*)&a.val), m8));
+}
+
+template<typename _Tpvec>
+inline void v256_zip(const _Tpvec& a, const _Tpvec& b, _Tpvec& ab0, _Tpvec& ab1)
+{
+    ab0 = v256_unpacklo(a, b);
+    ab1 = v256_unpackhi(a, b);
+}
+
+template<typename _Tpvec>
+inline _Tpvec v256_combine_diagonal(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(__lasx_xvpermi_q(a.val, b.val, 0x12)); }
+
+inline v_float32x8 v256_combine_diagonal(const v_float32x8& a, const v_float32x8& b)
+{ return v_float32x8(__lasx_xvpermi_q(a.val, b.val, 0x12)); }
+
+inline v_float64x4 v256_combine_diagonal(const v_float64x4& a, const v_float64x4& b)
+{ return v_float64x4(__lasx_xvpermi_q(a.val, b.val, 0x12)); }
+
+template<typename _Tpvec>
+inline _Tpvec v256_alignr_128(const _Tpvec& a, const _Tpvec& b)
+{ return v256_permute2x128<0x03>(a, b); }
+
+inline __m256i _v256_alignr_b(const __m256i &a, const __m256i &b, const int imm)
+{
+    if (imm == 8) {
+        return __lasx_xvshuf4i_d(b, a, 0x9); // b.d1 a.d0 b.d3 a.d2
+    } else {
+        __m256i byteIndex = _v256_setr_b(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
+                                         0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15);
+        return __lasx_xvshuf_b(a, b, __lasx_xvadd_b(__lasx_xvreplgr2vr_b(imm), byteIndex));
+    }
+}
+
+template<typename _Tpvec>
+inline _Tpvec v256_alignr_64(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(_v256_alignr_b(a.val, b.val, 8)); }
+inline v_float64x4 v256_alignr_64(const v_float64x4& a, const v_float64x4& b)
+{ return v_float64x4(__lasx_xvshuf4i_d(b.val, a.val, 0x9)); } // b.d1 a.d0 b.d3 a.d2
+// todo: emulate float32
+
+template<typename _Tpvec>
+inline _Tpvec v256_swap_halves(const _Tpvec& a)
+{ return v256_permute2x128<1>(a, a); }
+
+template<typename _Tpvec>
+inline _Tpvec v256_reverse_64(const _Tpvec& a)
+{ return v256_permute4x64<0x1b>(a); }
+
+
+// ZIP
+#define OPENCV_HAL_IMPL_LASX_ZIP(_Tpvec)                             \
+    inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b)    \
+    { return v256_permute2x128<0x02>(a, b); }                        \
+    inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b)   \
+    { return v256_permute2x128<0x13>(a, b); }                        \
+    inline void v_recombine(const _Tpvec& a, const _Tpvec& b,        \
+                             _Tpvec& c, _Tpvec& d)                   \
+    {                                                                \
+        _Tpvec a1b0 = v256_alignr_128(a, b);                         \
+        c = v256_combine_diagonal(a, a1b0);                          \
+        d = v256_combine_diagonal(a1b0, b);                          \
+    }                                                                \
+    inline void v_zip(const _Tpvec& a, const _Tpvec& b,              \
+                      _Tpvec& ab0, _Tpvec& ab1)                      \
+    {                                                                \
+        _Tpvec ab0ab2, ab1ab3;                                       \
+        v256_zip(a, b, ab0ab2, ab1ab3);                              \
+        v_recombine(ab0ab2, ab1ab3, ab0, ab1);                       \
+    }
+
+OPENCV_HAL_IMPL_LASX_ZIP(v_uint8x32)
+OPENCV_HAL_IMPL_LASX_ZIP(v_int8x32)
+OPENCV_HAL_IMPL_LASX_ZIP(v_uint16x16)
+OPENCV_HAL_IMPL_LASX_ZIP(v_int16x16)
+OPENCV_HAL_IMPL_LASX_ZIP(v_uint32x8)
+OPENCV_HAL_IMPL_LASX_ZIP(v_int32x8)
+OPENCV_HAL_IMPL_LASX_ZIP(v_uint64x4)
+OPENCV_HAL_IMPL_LASX_ZIP(v_int64x4)
+OPENCV_HAL_IMPL_LASX_ZIP(v_float32x8)
+OPENCV_HAL_IMPL_LASX_ZIP(v_float64x4)
+
+////////// Arithmetic, bitwise and comparison operations /////////
+
+/** Arithmetics **/
+#define OPENCV_HAL_IMPL_LASX_BIN_OP(bin_op, _Tpvec, intrin)           \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)            \
+    { return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_uint8x32,  __lasx_xvsadd_bu)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_uint8x32,  __lasx_xvssub_bu)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_int8x32,   __lasx_xvsadd_b)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_int8x32,   __lasx_xvssub_b)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_uint16x16, __lasx_xvsadd_hu)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_uint16x16, __lasx_xvssub_hu)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_int16x16,  __lasx_xvsadd_h)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_int16x16,  __lasx_xvssub_h)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_uint32x8,  __lasx_xvadd_w)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_uint32x8,  __lasx_xvsub_w)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_mul, v_uint32x8,  __lasx_xvmul_w)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_int32x8,   __lasx_xvadd_w)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_int32x8,   __lasx_xvsub_w)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_mul, v_int32x8,   __lasx_xvmul_w)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_uint64x4,  __lasx_xvadd_d)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_uint64x4,  __lasx_xvsub_d)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_int64x4,   __lasx_xvadd_d)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_int64x4,   __lasx_xvsub_d)
+
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_float32x8, __lasx_xvfadd_s)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_float32x8, __lasx_xvfsub_s)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_mul, v_float32x8, __lasx_xvfmul_s)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_div, v_float32x8, __lasx_xvfdiv_s)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_add, v_float64x4, __lasx_xvfadd_d)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_sub, v_float64x4, __lasx_xvfsub_d)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_mul, v_float64x4, __lasx_xvfmul_d)
+OPENCV_HAL_IMPL_LASX_BIN_OP(v_div, v_float64x4, __lasx_xvfdiv_d)
+
+// saturating multiply 8-bit, 16-bit
+inline v_uint8x32 v_mul(const v_uint8x32& a, const v_uint8x32& b)
+{
+    v_uint16x16 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_int8x32 v_mul(const v_int8x32& a, const v_int8x32& b)
+{
+    v_int16x16 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_uint16x16 v_mul(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i pl = __lasx_xvmul_h(a.val, b.val);
+    __m256i ph = __lasx_xvmuh_hu(a.val, b.val);
+    __m256i p0 = __lasx_xvilvl_h(ph, pl);
+    __m256i p1 = __lasx_xvilvh_h(ph, pl);
+    return v_uint16x16(_v256_packs_epu32(p0, p1));
+}
+inline v_int16x16 v_mul(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i pl = __lasx_xvmul_h(a.val, b.val);
+    __m256i ph = __lasx_xvmuh_h(a.val, b.val);
+    __m256i p0 = __lasx_xvilvl_h(ph, pl);
+    __m256i p1 = __lasx_xvilvh_h(ph, pl);
+    return v_int16x16(_lasx_packs_w(p0, p1));
+}
+
+/** Non-saturating arithmetics **/
+
+#define OPENCV_HAL_IMPL_LASX_BIN_FUNC(func, _Tpvec, intrin) \
+    inline _Tpvec func(const _Tpvec& a, const _Tpvec& b)    \
+    { return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_add_wrap, v_uint8x32,  __lasx_xvadd_b)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_add_wrap, v_int8x32,   __lasx_xvadd_b)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_add_wrap, v_uint16x16, __lasx_xvadd_h)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_add_wrap, v_int16x16,  __lasx_xvadd_h)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_sub_wrap, v_uint8x32,  __lasx_xvsub_b)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_sub_wrap, v_int8x32,   __lasx_xvsub_b)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_sub_wrap, v_uint16x16, __lasx_xvsub_h)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_sub_wrap, v_int16x16,  __lasx_xvsub_h)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_mul_wrap, v_uint16x16, __lasx_xvmul_h)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_mul_wrap, v_int16x16,  __lasx_xvmul_h)
+
+inline v_uint8x32 v_mul_wrap(const v_uint8x32& a, const v_uint8x32& b)
+{
+    __m256i p0 = __lasx_xvmulwev_h_bu(a.val, b.val);
+    __m256i p1 = __lasx_xvmulwod_h_bu(a.val, b.val);
+    return v_uint8x32(__lasx_xvpackev_b(p1, p0));
+}
+
+inline v_int8x32 v_mul_wrap(const v_int8x32& a, const v_int8x32& b)
+{
+    return v_reinterpret_as_s8(v_mul_wrap(v_reinterpret_as_u8(a), v_reinterpret_as_u8(b)));
+}
+
+//  Multiply and expand
+inline void v_mul_expand(const v_uint8x32& a, const v_uint8x32& b,
+                         v_uint16x16& c, v_uint16x16& d)
+{
+    v_uint16x16 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int8x32& a, const v_int8x32& b,
+                         v_int16x16& c, v_int16x16& d)
+{
+    v_int16x16 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int16x16& a, const v_int16x16& b,
+                         v_int32x8& c, v_int32x8& d)
+{
+    v_int16x16 vhi = v_int16x16(__lasx_xvmuh_h(a.val, b.val));
+
+    v_int16x16 v0, v1;
+    v_zip(v_mul_wrap(a, b), vhi, v0, v1);
+
+    c = v_reinterpret_as_s32(v0);
+    d = v_reinterpret_as_s32(v1);
+}
+
+inline void v_mul_expand(const v_uint16x16& a, const v_uint16x16& b,
+                         v_uint32x8& c, v_uint32x8& d)
+{
+    v_uint16x16 vhi = v_uint16x16(__lasx_xvmuh_hu(a.val, b.val));
+
+    v_uint16x16 v0, v1;
+    v_zip(v_mul_wrap(a, b), vhi, v0, v1);
+
+    c = v_reinterpret_as_u32(v0);
+    d = v_reinterpret_as_u32(v1);
+}
+
+inline void v_mul_expand(const v_uint32x8& a, const v_uint32x8& b,
+                         v_uint64x4& c, v_uint64x4& d)
+{
+    __m256i v0 = __lasx_xvmulwev_d_wu(a.val, b.val);
+    __m256i v1 = __lasx_xvmulwod_d_wu(a.val, b.val);
+    v_zip(v_uint64x4(v0), v_uint64x4(v1), c, d);
+}
+
+inline v_int16x16 v_mul_hi(const v_int16x16& a, const v_int16x16& b) { return v_int16x16(__lasx_xvmuh_h(a.val, b.val)); }
+inline v_uint16x16 v_mul_hi(const v_uint16x16& a, const v_uint16x16& b) { return v_uint16x16(__lasx_xvmuh_hu(a.val, b.val)); }
+
+/** Bitwise shifts **/
+#define OPENCV_HAL_IMPL_LASX_SHIFT_OP(_Tpuvec, _Tpsvec, suffix, srai)                             \
+    inline _Tpuvec v_shl(const _Tpuvec& a, int imm)                                               \
+    { return _Tpuvec(__lasx_xvsll_##suffix(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }           \
+    inline _Tpsvec v_shl(const _Tpsvec& a, int imm)                                               \
+    { return _Tpsvec(__lasx_xvsll_##suffix(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }           \
+    inline _Tpuvec v_shr(const _Tpuvec& a, int imm)                                               \
+    { return _Tpuvec(__lasx_xvsrl_##suffix(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }           \
+    inline _Tpsvec v_shr(const _Tpsvec& a, int imm)                                               \
+    { return _Tpsvec(srai(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }                            \
+    template<int imm>                                                                             \
+    inline _Tpuvec v_shl(const _Tpuvec& a)                                                        \
+    { return _Tpuvec(__lasx_xvsll_##suffix(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }           \
+    template<int imm>                                                                             \
+    inline _Tpsvec v_shl(const _Tpsvec& a)                                                        \
+    { return _Tpsvec(__lasx_xvsll_##suffix(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }           \
+    template<int imm>                                                                             \
+    inline _Tpuvec v_shr(const _Tpuvec& a)                                                        \
+    { return _Tpuvec(__lasx_xvsrl_##suffix(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }           \
+    template<int imm>                                                                             \
+    inline _Tpsvec v_shr(const _Tpsvec& a)                                                        \
+    { return _Tpsvec(srai(a.val, __lasx_xvreplgr2vr_##suffix(imm))); }
+
+OPENCV_HAL_IMPL_LASX_SHIFT_OP(v_uint16x16, v_int16x16, h, __lasx_xvsra_h)
+OPENCV_HAL_IMPL_LASX_SHIFT_OP(v_uint32x8,  v_int32x8,  w, __lasx_xvsra_w)
+OPENCV_HAL_IMPL_LASX_SHIFT_OP(v_uint64x4,  v_int64x4,  d, __lasx_xvsra_d)
+
+
+/** Bitwise logic **/
+#define OPENCV_HAL_IMPL_LASX_LOGIC_OP(_Tpvec, suffix, not_const)    \
+    OPENCV_HAL_IMPL_LASX_BIN_OP(v_and, _Tpvec, __lasx_xvand_##suffix)  \
+    OPENCV_HAL_IMPL_LASX_BIN_OP(v_or, _Tpvec, __lasx_xvor_##suffix)    \
+    OPENCV_HAL_IMPL_LASX_BIN_OP(v_xor, _Tpvec, __lasx_xvxor_##suffix)  \
+    inline _Tpvec v_not(const _Tpvec& a)                               \
+    { return _Tpvec(__lasx_xvnori_b(a.val, 0)); }
+
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_uint8x32,   v, __lasx_xvreplgr2vr_w(-1))
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_int8x32,    v, __lasx_xvreplgr2vr_w(-1))
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_uint16x16,  v, __lasx_xvreplgr2vr_w(-1))
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_int16x16,   v, __lasx_xvreplgr2vr_w(-1))
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_uint32x8,   v, __lasx_xvreplgr2vr_w(-1))
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_int32x8,    v, __lasx_xvreplgr2vr_w(-1))
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_uint64x4,   v, __lasx_xvreplgr2vr_d(-1))
+OPENCV_HAL_IMPL_LASX_LOGIC_OP(v_int64x4,    v, __lasx_xvreplgr2vr_d(-1))
+
+#define OPENCV_HAL_IMPL_LASX_FLOAT_BIN_OP(bin_op, _Tpvec, intrin, cast)                         \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)                                      \
+    { return _Tpvec(intrin(*((__m256i*)(&a.val)), *((__m256i*)(&b.val)))); }
+
+#define OPENCV_HAL_IMPL_LASX_FLOAT_LOGIC_OP(_Tpvec, suffix, not_const, cast)       \
+    OPENCV_HAL_IMPL_LASX_FLOAT_BIN_OP(v_and, _Tpvec, __lasx_xvand_##suffix, cast)  \
+    OPENCV_HAL_IMPL_LASX_FLOAT_BIN_OP(v_or, _Tpvec, __lasx_xvor_##suffix, cast)    \
+    OPENCV_HAL_IMPL_LASX_FLOAT_BIN_OP(v_xor, _Tpvec, __lasx_xvxor_##suffix, cast)  \
+    inline _Tpvec v_not(const _Tpvec& a)                                           \
+    { return _Tpvec(__lasx_xvxor_##suffix(*((__m256i*)(&a.val)), not_const)); }
+
+OPENCV_HAL_IMPL_LASX_FLOAT_LOGIC_OP(v_float32x8,  v, __lasx_xvreplgr2vr_w(-1), _lasx_256_castsi256_ps)
+OPENCV_HAL_IMPL_LASX_FLOAT_LOGIC_OP(v_float64x4,  v, __lasx_xvreplgr2vr_d(-1), _lasx_256_castsi256_pd)
+
+/** Select **/
+#define OPENCV_HAL_IMPL_LASX_SELECT(_Tpvec)                                      \
+    inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+    { return _Tpvec(__lasx_xvbitsel_v(b.val, a.val, mask.val)); }
+
+OPENCV_HAL_IMPL_LASX_SELECT(v_uint8x32)
+OPENCV_HAL_IMPL_LASX_SELECT(v_int8x32)
+OPENCV_HAL_IMPL_LASX_SELECT(v_uint16x16)
+OPENCV_HAL_IMPL_LASX_SELECT(v_int16x16)
+OPENCV_HAL_IMPL_LASX_SELECT(v_uint32x8)
+OPENCV_HAL_IMPL_LASX_SELECT(v_int32x8)
+
+inline v_float32x8 v_select(const v_float32x8 &mask, const v_float32x8 &a, const v_float32x8 &b)
+{ return v_float32x8(__lasx_xvbitsel_v(*((__m256i*)&b.val), *((__m256i*)&a.val), *((__m256i*)&mask.val))); }
+
+inline v_float64x4 v_select(const v_float64x4 &mask, const v_float64x4 &a, const v_float64x4 &b)
+{ return v_float64x4(__lasx_xvbitsel_v(*((__m256i*)&b.val), *((__m256i*)&a.val), *((__m256i*)&mask.val))); }
+
+/** Comparison **/
+#define OPENCV_HAL_IMPL_LASX_CMP_OP_OV(_Tpvec)                     \
+    inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b)           \
+    { return v_not(v_eq(a, b)); }                                  \
+    inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b)           \
+    { return v_gt(b, a); }                                         \
+    inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b)           \
+    { return v_not(v_lt(a, b)); }                                  \
+    inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b)           \
+    { return v_ge(b, a); }
+
+#define OPENCV_HAL_IMPL_LASX_CMP_OP_INT(_Tpuvec, _Tpsvec, suffix, usuffix)   \
+    inline _Tpuvec v_eq(const _Tpuvec& a, const _Tpuvec& b)                  \
+    { return _Tpuvec(__lasx_xvseq_##suffix(a.val, b.val)); }                 \
+    inline _Tpuvec v_gt(const _Tpuvec& a, const _Tpuvec& b)                  \
+    {                                                                        \
+        return _Tpuvec(__lasx_xvslt_##usuffix(b.val, a.val));                \
+    }                                                                        \
+    inline _Tpsvec v_eq(const _Tpsvec& a, const _Tpsvec& b)                  \
+    { return _Tpsvec(__lasx_xvseq_##suffix(a.val, b.val)); }                 \
+    inline _Tpsvec v_gt(const _Tpsvec& a, const _Tpsvec& b)                  \
+    { return _Tpsvec(__lasx_xvslt_##suffix(b.val, a.val)); }                 \
+    OPENCV_HAL_IMPL_LASX_CMP_OP_OV(_Tpuvec)                                  \
+    OPENCV_HAL_IMPL_LASX_CMP_OP_OV(_Tpsvec)
+
+OPENCV_HAL_IMPL_LASX_CMP_OP_INT(v_uint8x32,  v_int8x32,  b, bu)
+OPENCV_HAL_IMPL_LASX_CMP_OP_INT(v_uint16x16, v_int16x16, h, hu)
+OPENCV_HAL_IMPL_LASX_CMP_OP_INT(v_uint32x8,  v_int32x8,  w, wu)
+
+#define OPENCV_HAL_IMPL_LASX_CMP_OP_64BIT(_Tpvec, suffix)         \
+    inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b)          \
+    { return _Tpvec(__lasx_xvseq_##suffix(a.val, b.val)); }       \
+    inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b)          \
+    { return v_not(v_eq(a, b)); }
+
+OPENCV_HAL_IMPL_LASX_CMP_OP_64BIT(v_uint64x4, d)
+OPENCV_HAL_IMPL_LASX_CMP_OP_64BIT(v_int64x4, d)
+
+#define OPENCV_HAL_IMPL_LASX_CMP_FLT(bin_op, suffix, _Tpvec, ssuffix)    \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)               \
+    { return _Tpvec(__lasx_##suffix##_##ssuffix(a.val, b.val)); }
+
+#define OPENCV_HAL_IMPL_LASX_CMP_OP_FLT(_Tpvec, ssuffix)              \
+    OPENCV_HAL_IMPL_LASX_CMP_FLT(v_eq, xvfcmp_ceq, _Tpvec, ssuffix)   \
+    OPENCV_HAL_IMPL_LASX_CMP_FLT(v_ne, xvfcmp_cne, _Tpvec, ssuffix)   \
+    OPENCV_HAL_IMPL_LASX_CMP_FLT(v_lt,  xvfcmp_clt, _Tpvec, ssuffix)  \
+    OPENCV_HAL_IMPL_LASX_CMP_FLT(v_le, xvfcmp_cle, _Tpvec, ssuffix)
+
+OPENCV_HAL_IMPL_LASX_CMP_OP_FLT(v_float32x8, s)
+OPENCV_HAL_IMPL_LASX_CMP_OP_FLT(v_float64x4, d)
+
+inline v_float32x8 v_gt(const v_float32x8 &a, const v_float32x8 &b)
+{ return v_float32x8(__lasx_xvfcmp_clt_s(b.val, a.val)); }
+
+inline v_float32x8 v_ge(const v_float32x8 &a, const v_float32x8 &b)
+{ return v_float32x8(__lasx_xvfcmp_cle_s(b.val, a.val)); }
+
+inline v_float64x4 v_gt(const v_float64x4 &a, const v_float64x4 &b)
+{ return v_float64x4(__lasx_xvfcmp_clt_d(b.val, a.val)); }
+
+inline v_float64x4 v_ge(const v_float64x4 &a, const v_float64x4 &b)
+{ return v_float64x4(__lasx_xvfcmp_cle_d(b.val, a.val)); }
+
+inline v_float32x8 v_not_nan(const v_float32x8& a)
+{ return v_float32x8(__lasx_xvfcmp_cor_s(a.val, a.val)); }
+inline v_float64x4 v_not_nan(const v_float64x4& a)
+{ return v_float64x4(__lasx_xvfcmp_cor_d(a.val, a.val)); }
+
+/** min/max **/
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_uint8x32,  __lasx_xvmin_bu)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_uint8x32,  __lasx_xvmax_bu)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_int8x32,   __lasx_xvmin_b)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_int8x32,   __lasx_xvmax_b)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_uint16x16, __lasx_xvmin_hu)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_uint16x16, __lasx_xvmax_hu)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_int16x16,  __lasx_xvmin_h)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_int16x16,  __lasx_xvmax_h)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_uint32x8,  __lasx_xvmin_wu)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_uint32x8,  __lasx_xvmax_wu)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_int32x8,   __lasx_xvmin_w)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_int32x8,   __lasx_xvmax_w)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_float32x8, __lasx_xvfmin_s)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_float32x8, __lasx_xvfmax_s)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_min, v_float64x4, __lasx_xvfmin_d)
+OPENCV_HAL_IMPL_LASX_BIN_FUNC(v_max, v_float64x4, __lasx_xvfmax_d)
+
+/** Rotate **/
+template<int imm>
+inline v_uint8x32 v_rotate_left(const v_uint8x32& a, const v_uint8x32& b)
+{
+    enum {IMM_R = (16 - imm) & 0xFF};
+    enum {IMM_R2 = (32 - imm) & 0xFF};
+
+    if (imm == 0)  return a;
+    if (imm == 32) return b;
+    if (imm > 32)  return v_uint8x32();
+
+    __m256i swap = _v256_permute2x128<0x21>(a.val, b.val);
+    if (imm == 16) return v_uint8x32(swap);
+    if (imm < 16)  return v_uint8x32(_v256_alignr_b(a.val, swap, IMM_R));
+    return v_uint8x32(_v256_alignr_b(swap, b.val, IMM_R2)); // imm < 32
+}
+
+template<int imm>
+inline v_uint8x32 v_rotate_right(const v_uint8x32& a, const v_uint8x32& b)
+{
+    enum {IMM_L = (imm - 16) & 0xFF};
+
+    if (imm == 0)  return a;
+    if (imm == 32) return b;
+    if (imm > 32)  return v_uint8x32();
+
+    __m256i swap = _v256_permute2x128<0x03>(a.val, b.val);
+    if (imm == 16) return v_uint8x32(swap);
+    if (imm < 16)  return v_uint8x32(_v256_alignr_b(swap, a.val, imm));
+    return v_uint8x32(_v256_alignr_b(b.val, swap, IMM_L));
+}
+
+template<int imm>
+inline v_uint8x32 v_rotate_left(const v_uint8x32& a)
+{
+    enum {IMM_L = ((imm - 16) & 0xFF) > 31 ? 31 : ((imm - 16) & 0xFF)};
+    enum {IMM_R = (16 - imm) & 0xFF};
+
+    if (imm == 0) return a;
+    if (imm > 32) return v_uint8x32();
+
+    // ESAC control[3] ? [127:0] = 0
+    __m256i vzero = __lasx_xvreplgr2vr_w(0);
+    __m256i swapz = __lasx_xvpermi_q(a.val, vzero, 0x20);;
+    if (imm == 16) return v_uint8x32(swapz);
+    if (imm < 16)  return v_uint8x32(_v256_alignr_b(a.val, swapz, IMM_R));
+    return v_uint8x32(__lasx_xvbsll_v(swapz, IMM_L));
+}
+
+template<int imm>
+inline v_uint8x32 v_rotate_right(const v_uint8x32& a)
+{
+    enum {IMM_L = ((imm - 16) & 0xFF) > 31 ? 31 : ((imm - 16) & 0xFF)};
+
+    if (imm == 0) return a;
+    if (imm > 32) return v_uint8x32();
+
+    // ESAC control[3] ? [127:0] = 0
+    __m256i vzero = __lasx_xvreplgr2vr_w(0);
+    __m256i swapz = __lasx_xvpermi_q(vzero, a.val, 0x21);;
+    if (imm == 16) return v_uint8x32(swapz);
+    if (imm < 16)  return v_uint8x32(_v256_alignr_b(swapz, a.val, imm));
+    return v_uint8x32(__lasx_xvbsrl_v(swapz, IMM_L));
+}
+
+#define OPENCV_HAL_IMPL_LASX_ROTATE_CAST(intrin, _Tpvec, cast)    \
+    template<int imm>                                             \
+    inline _Tpvec intrin(const _Tpvec& a, const _Tpvec& b)        \
+    {                                                             \
+        enum {IMMxW = imm * sizeof(typename _Tpvec::lane_type)};  \
+        v_uint8x32 ret = intrin<IMMxW>(v_reinterpret_as_u8(a),    \
+                                       v_reinterpret_as_u8(b));   \
+        return _Tpvec(cast(ret.val));                             \
+    }                                                             \
+    template<int imm>                                             \
+    inline _Tpvec intrin(const _Tpvec& a)                         \
+    {                                                             \
+        enum {IMMxW = imm * sizeof(typename _Tpvec::lane_type)};  \
+        v_uint8x32 ret = intrin<IMMxW>(v_reinterpret_as_u8(a));   \
+        return _Tpvec(cast(ret.val));                             \
+    }
+
+#define OPENCV_HAL_IMPL_LASX_ROTATE(_Tpvec)                                  \
+    OPENCV_HAL_IMPL_LASX_ROTATE_CAST(v_rotate_left,  _Tpvec, OPENCV_HAL_NOP) \
+    OPENCV_HAL_IMPL_LASX_ROTATE_CAST(v_rotate_right, _Tpvec, OPENCV_HAL_NOP)
+
+OPENCV_HAL_IMPL_LASX_ROTATE(v_int8x32)
+OPENCV_HAL_IMPL_LASX_ROTATE(v_uint16x16)
+OPENCV_HAL_IMPL_LASX_ROTATE(v_int16x16)
+OPENCV_HAL_IMPL_LASX_ROTATE(v_uint32x8)
+OPENCV_HAL_IMPL_LASX_ROTATE(v_int32x8)
+OPENCV_HAL_IMPL_LASX_ROTATE(v_uint64x4)
+OPENCV_HAL_IMPL_LASX_ROTATE(v_int64x4)
+
+OPENCV_HAL_IMPL_LASX_ROTATE_CAST(v_rotate_left,  v_float32x8, _lasx_256_castsi256_ps)
+OPENCV_HAL_IMPL_LASX_ROTATE_CAST(v_rotate_right, v_float32x8, _lasx_256_castsi256_ps)
+OPENCV_HAL_IMPL_LASX_ROTATE_CAST(v_rotate_left,  v_float64x4, _lasx_256_castsi256_pd)
+OPENCV_HAL_IMPL_LASX_ROTATE_CAST(v_rotate_right, v_float64x4, _lasx_256_castsi256_pd)
+
+/** Reverse **/
+inline v_uint8x32 v_reverse(const v_uint8x32 &a)
+{
+    static const __m256i perm = _v256_setr_b(
+            15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0,
+            15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0);
+    __m256i vec = __lasx_xvshuf_b(a.val, a.val, perm);
+    return v_uint8x32(__lasx_xvpermi_q(vec, vec, 1));
+}
+
+inline v_int8x32 v_reverse(const v_int8x32 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x16 v_reverse(const v_uint16x16 &a)
+{
+    __m256i vec = __lasx_xvshuf4i_h(a.val, 0x1B);
+    vec = __lasx_xvshuf4i_w(vec, 0x4E);
+    return v_uint16x16(__lasx_xvpermi_d(vec, 0x4E));
+}
+
+inline v_int16x16 v_reverse(const v_int16x16 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x8 v_reverse(const v_uint32x8 &a)
+{
+    __m256i vec = __lasx_xvshuf4i_w(a.val, 0x1B);
+    return v_uint32x8(__lasx_xvpermi_d(vec, 0x4E));
+}
+
+inline v_int32x8 v_reverse(const v_int32x8 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x8 v_reverse(const v_float32x8 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x4 v_reverse(const v_uint64x4 &a)
+{
+    return v_uint64x4(__lasx_xvpermi_d(a.val, 0x1b));
+}
+
+inline v_int64x4 v_reverse(const v_int64x4 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+inline v_float64x4 v_reverse(const v_float64x4 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+////////// Reduce and mask /////////
+
+/** Reduce **/
+// this function is return a[0]+a[1]+...+a[31]
+inline unsigned v_reduce_sum(const v_uint8x32& a)
+{
+    __m256i t1 = __lasx_xvhaddw_hu_bu(a.val, a.val);
+    __m256i t2 = __lasx_xvhaddw_wu_hu(t1, t1);
+    __m256i t3 = __lasx_xvhaddw_du_wu(t2, t2);
+    __m256i t4 = __lasx_xvhaddw_qu_du(t3, t3);
+    return (unsigned)(((v8u32)t4)[0]+((v8u32)t4)[4]);
+}
+
+inline int v_reduce_sum(const v_int8x32& a)
+{
+    __m256i t1 = __lasx_xvhaddw_h_b(a.val, a.val);
+    __m256i t2 = __lasx_xvhaddw_w_h(t1, t1);
+    __m256i t3 = __lasx_xvhaddw_d_w(t2, t2);
+    __m256i t4 = __lasx_xvhaddw_q_d(t3, t3);
+    return (int)(((v8i32)t4)[0]+((v8i32)t4)[4]);
+}
+
+#define OPENCV_HAL_IMPL_LASX_REDUCE_32(_Tpvec, sctype, func, intrin) \
+    inline sctype v_reduce_##func(const _Tpvec& a) \
+    { \
+        __m128i val = intrin(_v256_extract_low(a.val), _v256_extract_high(a.val)); \
+        val = intrin(val, __lsx_vbsrl_v(val,8));    \
+        val = intrin(val, __lsx_vbsrl_v(val,4));    \
+        val = intrin(val, __lsx_vbsrl_v(val,2));    \
+        val = intrin(val, __lsx_vbsrl_v(val,1));    \
+        return (sctype)__lsx_vpickve2gr_w(val, 0);  \
+    }
+
+OPENCV_HAL_IMPL_LASX_REDUCE_32(v_uint8x32, uchar, min, __lsx_vmin_bu)
+OPENCV_HAL_IMPL_LASX_REDUCE_32(v_int8x32,  schar, min, __lsx_vmin_b)
+OPENCV_HAL_IMPL_LASX_REDUCE_32(v_uint8x32, uchar, max, __lsx_vmax_bu)
+OPENCV_HAL_IMPL_LASX_REDUCE_32(v_int8x32,  schar, max, __lsx_vmax_b)
+
+#define OPENCV_HAL_IMPL_LASX_REDUCE_16(_Tpvec, sctype, func, intrin) \
+    inline sctype v_reduce_##func(const _Tpvec& a)                   \
+    {                                                                \
+        __m128i v0 = _v256_extract_low(a.val);                       \
+        __m128i v1 = _v256_extract_high(a.val);                      \
+        v0 = intrin(v0, v1);                                         \
+        v0 = intrin(v0, __lsx_vbsrl_v(v0, 8));                       \
+        v0 = intrin(v0, __lsx_vbsrl_v(v0, 4));                       \
+        v0 = intrin(v0, __lsx_vbsrl_v(v0, 2));                       \
+        return (sctype) __lsx_vpickve2gr_w(v0, 0);                   \
+    }
+
+OPENCV_HAL_IMPL_LASX_REDUCE_16(v_uint16x16, ushort, min, __lsx_vmin_hu)
+OPENCV_HAL_IMPL_LASX_REDUCE_16(v_int16x16,  short,  min, __lsx_vmin_h)
+OPENCV_HAL_IMPL_LASX_REDUCE_16(v_uint16x16, ushort, max, __lsx_vmax_hu)
+OPENCV_HAL_IMPL_LASX_REDUCE_16(v_int16x16,  short,  max, __lsx_vmax_h)
+
+#define OPENCV_HAL_IMPL_LASX_REDUCE_8(_Tpvec, sctype, func, intrin) \
+    inline sctype v_reduce_##func(const _Tpvec& a)                  \
+    {                                                               \
+        __m128i v0 = _v256_extract_low(a.val);                      \
+        __m128i v1 = _v256_extract_high(a.val);                     \
+        v0 = intrin(v0, v1);                                        \
+        v0 = intrin(v0, __lsx_vbsrl_v(v0, 8));                      \
+        v0 = intrin(v0, __lsx_vbsrl_v(v0, 4));                      \
+        return (sctype) __lsx_vpickve2gr_w(v0, 0);                  \
+    }
+
+OPENCV_HAL_IMPL_LASX_REDUCE_8(v_uint32x8, unsigned, min, __lsx_vmin_wu)
+OPENCV_HAL_IMPL_LASX_REDUCE_8(v_int32x8,  int,      min, __lsx_vmin_w)
+OPENCV_HAL_IMPL_LASX_REDUCE_8(v_uint32x8, unsigned, max, __lsx_vmax_wu)
+OPENCV_HAL_IMPL_LASX_REDUCE_8(v_int32x8,  int,      max, __lsx_vmax_w)
+
+#define OPENCV_HAL_IMPL_LASX_REDUCE_FLT(func, intrin)                 \
+    inline float v_reduce_##func(const v_float32x8& a)                \
+    {                                                                 \
+        __m128 v0 = _v256_extract_low(a.val);                         \
+        __m128 v1 = _v256_extract_high(a.val);                        \
+        v0 = intrin(v0, v1);                                          \
+        v0 = intrin(v0, __m128(__lsx_vpermi_w(*((__m128i*)&v0), *((__m128i*)&v0), 0x0e))); \
+        v0 = intrin(v0, __m128(__lsx_vpermi_w(*((__m128i*)&v0), *((__m128i*)&v0), 0x01))); \
+        float *fvalue = (float*)&v0;                                  \
+        return fvalue[0];                                             \
+    }
+
+OPENCV_HAL_IMPL_LASX_REDUCE_FLT(min, __lsx_vfmin_s)
+OPENCV_HAL_IMPL_LASX_REDUCE_FLT(max, __lsx_vfmax_s)
+
+inline int v_reduce_sum(const v_int32x8& a)
+{
+    __m256i t1 = __lasx_xvhaddw_d_w(a.val, a.val);
+    __m256i t2 = __lasx_xvhaddw_q_d(t1, t1);
+    return (int)(((v8i32)t2)[0]+((v8i32)t2)[4]);
+}
+
+inline unsigned v_reduce_sum(const v_uint32x8& a)
+{ return v_reduce_sum(v_reinterpret_as_s32(a)); }
+
+inline int v_reduce_sum(const v_int16x16& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+inline unsigned v_reduce_sum(const v_uint16x16& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+
+inline float v_reduce_sum(const v_float32x8& a)
+{
+    float result = 0;
+    float *pa = (float*)&a;
+    for (int i = 0; i < 2; ++i) {
+        result += pa[i*4] + pa[i*4+1] + pa[i*4+2] + pa[i*4+3];
+    }
+    return result;
+}
+
+inline uint64 v_reduce_sum(const v_uint64x4& a)
+{
+    __m256i t0 = __lasx_xvhaddw_qu_du(a.val, a.val);
+    return (uint64)(((v4u64)t0)[0] + ((v4u64)t0)[2]);
+}
+inline int64 v_reduce_sum(const v_int64x4& a)
+{
+    __m256i t0 = __lasx_xvhaddw_q_d(a.val, a.val);
+    return (int64)(((v4i64)t0)[0] + ((v4i64)t0)[2]);
+}
+inline double v_reduce_sum(const v_float64x4& a)
+{
+    double *pa = (double*)&a;
+    return pa[0] + pa[1] + pa[2] + pa[3];
+}
+
+inline v_float32x8 v_reduce_sum4(const v_float32x8& a, const v_float32x8& b,
+                                 const v_float32x8& c, const v_float32x8& d)
+{
+    float *pa = (float*)&a;
+    float *pb = (float*)&b;
+    float *pc = (float*)&c;
+    float *pd = (float*)&d;
+
+    float v0 = pa[0] + pa[1] + pa[2] + pa[3];
+    float v1 = pb[0] + pb[1] + pb[2] + pb[3];
+    float v2 = pc[0] + pc[1] + pc[2] + pc[3];
+    float v3 = pd[0] + pd[1] + pd[2] + pd[3];
+    float v4 = pa[4] + pa[5] + pa[6] + pa[7];
+    float v5 = pb[4] + pb[5] + pb[6] + pb[7];
+    float v6 = pc[4] + pc[5] + pc[6] + pc[7];
+    float v7 = pd[4] + pd[5] + pd[6] + pd[7];
+    return v_float32x8(v0, v1, v2, v3, v4, v5, v6, v7);
+}
+
+inline unsigned v_reduce_sad(const v_uint8x32& a, const v_uint8x32& b)
+{
+    __m256i t0 = __lasx_xvabsd_bu(a.val, b.val);
+    __m256i t1 = __lasx_xvhaddw_hu_bu(t0, t0);
+    __m256i t2 = __lasx_xvhaddw_wu_hu(t1, t1);
+    __m256i t3 = __lasx_xvhaddw_du_wu(t2, t2);
+    __m256i t4 = __lasx_xvhaddw_qu_du(t3, t3);
+    return (unsigned)(((v8u32)t4)[0]+((v8u32)t4)[4]);
+}
+inline unsigned v_reduce_sad(const v_int8x32& a, const v_int8x32& b)
+{
+    __m256i t0 = __lasx_xvabsd_b(a.val, b.val);
+    __m256i t1 = __lasx_xvhaddw_hu_bu(t0, t0);
+    __m256i t2 = __lasx_xvhaddw_wu_hu(t1, t1);
+    __m256i t3 = __lasx_xvhaddw_du_wu(t2, t2);
+    __m256i t4 = __lasx_xvhaddw_qu_du(t3, t3);
+    return (unsigned)(((v8u32)t4)[0]+((v8u32)t4)[4]);
+}
+inline unsigned v_reduce_sad(const v_uint16x16& a, const v_uint16x16& b)
+{
+    v_uint32x8 l, h;
+    v_expand(v_add_wrap(v_sub(a, b), v_sub(b, a)), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_int16x16& a, const v_int16x16& b)
+{
+    v_uint32x8 l, h;
+    v_expand(v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_uint32x8& a, const v_uint32x8& b)
+{
+    return v_reduce_sum(v_sub(v_max(a, b), v_min(a, b)));
+}
+inline unsigned v_reduce_sad(const v_int32x8& a, const v_int32x8& b)
+{
+    v_int32x8 m = v_lt(a, b);
+    return v_reduce_sum(v_reinterpret_as_u32(v_sub(v_xor(v_sub(a, b), m), m)));
+}
+inline float v_reduce_sad(const v_float32x8& a, const v_float32x8& b)
+{
+    v_float32x8 a_b = v_sub(a, b);
+    return v_reduce_sum(v_float32x8(*((__m256i*)&a_b.val) & __lasx_xvreplgr2vr_w(0x7fffffff)));
+}
+
+/** Popcount **/
+inline v_uint8x32 v_popcount(const v_uint8x32& a)
+{ return v_uint8x32(__lasx_xvpcnt_b(a.val)); }
+inline v_uint16x16 v_popcount(const v_uint16x16& a)
+{ return v_uint16x16(__lasx_xvpcnt_h(a.val)); }
+inline v_uint32x8 v_popcount(const v_uint32x8& a)
+{ return v_uint32x8(__lasx_xvpcnt_w(a.val)); }
+inline v_uint64x4 v_popcount(const v_uint64x4& a)
+{ return v_uint64x4(__lasx_xvpcnt_d(a.val)); }
+inline v_uint8x32 v_popcount(const v_int8x32& a)
+{ return v_popcount(v_reinterpret_as_u8(a)); }
+inline v_uint16x16 v_popcount(const v_int16x16& a)
+{ return v_popcount(v_reinterpret_as_u16(a)); }
+inline v_uint32x8 v_popcount(const v_int32x8& a)
+{ return v_popcount(v_reinterpret_as_u32(a)); }
+inline v_uint64x4 v_popcount(const v_int64x4& a)
+{ return v_popcount(v_reinterpret_as_u64(a)); }
+
+inline int v_signmask(const v_int8x32& a)
+{
+    __m256i result = __lasx_xvmskltz_b(a.val);
+    int mask = __lasx_xvpickve2gr_w(result, 0);
+    mask |= (__lasx_xvpickve2gr_w(result, 4) << 16);
+    return mask;
+}
+inline int v_signmask(const v_uint8x32& a)
+{ return v_signmask(v_reinterpret_as_s8(a)); }
+
+inline int v_signmask(const v_int16x16& a)
+{ return v_signmask(v_pack(a, a)) & 0xFFFF; }
+inline int v_signmask(const v_uint16x16& a)
+{ return v_signmask(v_reinterpret_as_s16(a)); }
+
+inline int v_signmask(const v_int32x8& a)
+{
+    __m256i result = __lasx_xvmskltz_w(a.val);
+    int mask = __lasx_xvpickve2gr_w(result, 0);
+    mask |= (__lasx_xvpickve2gr_w(result, 4) << 4);
+    return mask;
+}
+inline int v_signmask(const v_uint32x8& a)
+{ return v_signmask(*(v_int32x8*)(&a)); }
+
+inline int v_signmask(const v_int64x4& a)
+{
+    __m256i result = __lasx_xvmskltz_d(a.val);
+    int mask = __lasx_xvpickve2gr_d(result, 0);
+    mask |= (__lasx_xvpickve2gr_w(result, 4) << 2);
+    return mask;
+}
+inline int v_signmask(const v_uint64x4& a)
+{ return v_signmask(v_reinterpret_as_s64(a)); }
+
+inline int v_signmask(const v_float32x8& a)
+{ return v_signmask(*(v_int32x8*)(&a)); }
+
+inline int v_signmask(const v_float64x4& a)
+{ return v_signmask(*(v_int64x4*)(&a)); }
+
+inline int v_scan_forward(const v_int8x32& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_uint8x32& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_int16x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_uint16x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_int32x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_uint32x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_float32x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_int64x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_uint64x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_float64x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+
+/** Checks **/
+#define OPENCV_HAL_IMPL_LASX_CHECK(_Tpvec, allmask) \
+    inline bool v_check_all(const _Tpvec& a) { return v_signmask(a) == allmask; } \
+    inline bool v_check_any(const _Tpvec& a) { return v_signmask(a) != 0; }
+OPENCV_HAL_IMPL_LASX_CHECK(v_uint8x32, -1)
+OPENCV_HAL_IMPL_LASX_CHECK(v_int8x32, -1)
+OPENCV_HAL_IMPL_LASX_CHECK(v_uint32x8, 255)
+OPENCV_HAL_IMPL_LASX_CHECK(v_int32x8, 255)
+OPENCV_HAL_IMPL_LASX_CHECK(v_uint64x4, 15)
+OPENCV_HAL_IMPL_LASX_CHECK(v_int64x4, 15)
+OPENCV_HAL_IMPL_LASX_CHECK(v_float32x8, 255)
+OPENCV_HAL_IMPL_LASX_CHECK(v_float64x4, 15)
+
+#define OPENCV_HAL_IMPL_LASX_CHECK_SHORT(_Tpvec)  \
+    inline bool v_check_all(const _Tpvec& a) { return (v_signmask(v_reinterpret_as_s8(a)) & 0xaaaaaaaa) == 0xaaaaaaaa; } \
+    inline bool v_check_any(const _Tpvec& a) { return (v_signmask(v_reinterpret_as_s8(a)) & 0xaaaaaaaa) != 0; }
+OPENCV_HAL_IMPL_LASX_CHECK_SHORT(v_uint16x16)
+OPENCV_HAL_IMPL_LASX_CHECK_SHORT(v_int16x16)
+
+////////// Other math /////////
+
+/** Some frequent operations **/
+#define OPENCV_HAL_IMPL_LASX_MULADD(_Tpvec, suffix)                            \
+    inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)     \
+    { return _Tpvec(__lasx_xvfmadd_##suffix(a.val, b.val, c.val)); }           \
+    inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)  \
+    { return _Tpvec(__lasx_xvfmadd_##suffix(a.val, b.val, c.val)); }           \
+    inline _Tpvec v_sqrt(const _Tpvec& x)                                      \
+    { return _Tpvec(__lasx_xvfsqrt_##suffix(x.val)); }                         \
+    inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b)            \
+    { return v_fma(a, a, v_mul(b, b)); }                                       \
+    inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b)                \
+    { return v_sqrt(v_fma(a, a, v_mul(b, b))); }
+
+OPENCV_HAL_IMPL_LASX_MULADD(v_float32x8, s)
+OPENCV_HAL_IMPL_LASX_MULADD(v_float64x4, d)
+
+inline v_int32x8 v_fma(const v_int32x8& a, const v_int32x8& b, const v_int32x8& c)
+{
+    return v_int32x8(__lasx_xvmadd_w(c.val, a.val, b.val));
+}
+
+inline v_int32x8 v_muladd(const v_int32x8& a, const v_int32x8& b, const v_int32x8& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_float32x8 v_invsqrt(const v_float32x8& x)
+{ return v_float32x8(__lasx_xvfrsqrt_s(x.val)); }
+
+inline v_float64x4 v_invsqrt(const v_float64x4& x)
+{ return v_float64x4(__lasx_xvfrsqrt_d(x.val)); }
+
+/** Absolute values **/
+#define OPENCV_HAL_IMPL_LASX_ABS(_Tpvec, suffix)         \
+    inline v_u##_Tpvec v_abs(const v_##_Tpvec& x)        \
+    { return v_u##_Tpvec(__lasx_xvabsd_##suffix(x.val, __lasx_xvreplgr2vr_w(0))); }
+
+OPENCV_HAL_IMPL_LASX_ABS(int8x32,  b)
+OPENCV_HAL_IMPL_LASX_ABS(int16x16, h)
+OPENCV_HAL_IMPL_LASX_ABS(int32x8,  w)
+
+inline v_float32x8 v_abs(const v_float32x8& x)
+{ return v_float32x8(*((__m256i*)&x) & __lasx_xvreplgr2vr_w(0x7fffffff)); }
+inline v_float64x4 v_abs(const v_float64x4& x)
+{ return v_float64x4(*((__m256i*)&x) & __lasx_xvreplgr2vr_d(0x7fffffffffffffff)); }
+
+/** Absolute difference **/
+inline v_uint8x32 v_absdiff(const v_uint8x32& a, const v_uint8x32& b)
+{ return (v_uint8x32)__lasx_xvabsd_bu(a.val, b.val); }
+inline v_uint16x16 v_absdiff(const v_uint16x16& a, const v_uint16x16& b)
+{ return (v_uint16x16)__lasx_xvabsd_hu(a.val, b.val); }
+inline v_uint32x8 v_absdiff(const v_uint32x8& a, const v_uint32x8& b)
+{ return (v_uint32x8)__lasx_xvabsd_wu(a.val, b.val); }
+
+inline v_uint8x32 v_absdiff(const v_int8x32& a, const v_int8x32& b)
+{ return (v_uint8x32)__lasx_xvabsd_b(a.val, b.val); }
+inline v_uint16x16 v_absdiff(const v_int16x16& a, const v_int16x16& b)
+{ return (v_uint16x16)__lasx_xvabsd_h(a.val, b.val); }
+inline v_uint32x8 v_absdiff(const v_int32x8& a, const v_int32x8& b)
+{ return (v_uint32x8)__lasx_xvabsd_w(a.val, b.val); }
+
+inline v_float32x8 v_absdiff(const v_float32x8& a, const v_float32x8& b)
+{ return v_abs(v_sub(a, b)); }
+
+inline v_float64x4 v_absdiff(const v_float64x4& a, const v_float64x4& b)
+{ return v_abs(v_sub(a, b)); }
+
+/** Saturating absolute difference **/
+inline v_int8x32 v_absdiffs(const v_int8x32& a, const v_int8x32& b)
+{
+    v_int8x32 d = v_sub(a, b);
+    v_int8x32 m = v_lt(a, b);
+    return v_sub(v_xor(d, m), m);
+}
+inline v_int16x16 v_absdiffs(const v_int16x16& a, const v_int16x16& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+////////// Conversions /////////
+
+/** Rounding **/
+inline v_int32x8 v_round(const v_float32x8& a)
+{ return v_int32x8(__lasx_xvftint_w_s(a.val)); }
+
+inline v_int32x8 v_round(const v_float64x4& a)
+{ __m256i t = __lasx_xvftint_w_d(a.val, a.val);
+  return v_int32x8(__lasx_xvpermi_d(t, 0x88)); }
+
+inline v_int32x8 v_round(const v_float64x4& a, const v_float64x4& b)
+{
+    __m256i abi = __lasx_xvftint_w_d(b.val, a.val);
+    return v_int32x8(__lasx_xvpermi_d(abi, 0b11011000)); //3120
+}
+
+inline v_int32x8 v_trunc(const v_float32x8& a)
+{ return v_int32x8(__lasx_xvftintrz_w_s(a.val)); }
+
+inline v_int32x8 v_trunc(const v_float64x4& a)
+{ __m256i t = __lasx_xvftintrz_w_d(a.val, a.val);
+  return v_int32x8(__lasx_xvpermi_d(t, 0x88)); }
+
+inline v_int32x8 v_floor(const v_float32x8& a)
+{ return v_int32x8(__lasx_xvftintrz_w_s(__m256(__lasx_xvfrintrm_s(a.val)))); }
+
+inline v_int32x8 v_floor(const v_float64x4& a)
+{ return v_trunc(v_float64x4(__lasx_xvfrintrm_d(a.val))); }
+
+inline v_int32x8 v_ceil(const v_float32x8& a)
+{ return v_int32x8(__lasx_xvftintrz_w_s(__m256(__lasx_xvfrintrp_s(a.val)))); }
+
+inline v_int32x8 v_ceil(const v_float64x4& a)
+{ return v_trunc(v_float64x4(__lasx_xvfrintrp_d(a.val))); }
+
+/** To float **/
+inline v_float32x8 v_cvt_f32(const v_int32x8& a)
+{ return v_float32x8(__lasx_xvffint_s_w(a.val)); }
+
+inline v_float32x8 v_cvt_f32(const v_float64x4& a)
+{ return v_float32x8(__lasx_xvpermi_d(__lasx_xvfcvt_s_d(a.val, a.val), 0x88)); }
+
+inline v_float32x8 v_cvt_f32(const v_float64x4& a, const v_float64x4& b)
+{
+    __m256 abf = __lasx_xvfcvt_s_d(a.val, b.val);  //warnning: order of a,b is diff from instruction xvfcvt.s.d
+    return v_float32x8(__lasx_xvpermi_d(abf, 0x8D));
+}
+
+inline v_float64x4 v_cvt_f64(const v_int32x8& a)
+{
+    __m256i alow = __lasx_xvpermi_d(a.val, 0x10);
+    return v_float64x4(__lasx_xvffintl_d_w(alow));
+}
+
+inline v_float64x4 v_cvt_f64_high(const v_int32x8& a)
+{
+    __m256i ahigh = __lasx_xvpermi_d(a.val, 0x32);
+    return v_float64x4(__lasx_xvffintl_d_w(ahigh));
+}
+
+inline v_float64x4 v_cvt_f64(const v_float32x8& a)
+{
+    __m256i alow = __lasx_xvpermi_d(a.val, 0x10);
+    return v_float64x4(__lasx_xvfcvtl_d_s((__m256)alow));
+}
+
+inline v_float64x4 v_cvt_f64_high(const v_float32x8& a)
+{
+    __m256i ahigh = __lasx_xvpermi_d(a.val, 0x32);
+    return v_float64x4(__lasx_xvfcvtl_d_s((__m256)ahigh));
+}
+
+inline v_float64x4 v_cvt_f64(const v_int64x4& v)
+{ return v_float64x4(__lasx_xvffint_d_l(v.val)); }
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x32 v256_lut(const schar* tab, const int* idx)
+{
+    return v_int8x32(_v256_setr_b(tab[idx[ 0]], tab[idx[ 1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]],
+                                  tab[idx[ 6]], tab[idx[ 7]], tab[idx[ 8]], tab[idx[ 9]], tab[idx[10]], tab[idx[11]],
+                                  tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]], tab[idx[16]], tab[idx[17]],
+                                  tab[idx[18]], tab[idx[19]], tab[idx[20]], tab[idx[21]], tab[idx[22]], tab[idx[23]],
+                                  tab[idx[24]], tab[idx[25]], tab[idx[26]], tab[idx[27]], tab[idx[28]], tab[idx[29]],
+                                  tab[idx[30]], tab[idx[31]]));
+}
+inline v_int8x32 v256_lut_pairs(const schar* tab, const int* idx)
+{
+    return v_int8x32(_v256_setr_h(*(const short*)(tab + idx[ 0]), *(const short*)(tab + idx[ 1]), *(const short*)(tab + idx[ 2]),
+                                  *(const short*)(tab + idx[ 3]), *(const short*)(tab + idx[ 4]), *(const short*)(tab + idx[ 5]),
+                                  *(const short*)(tab + idx[ 6]), *(const short*)(tab + idx[ 7]), *(const short*)(tab + idx[ 8]),
+                                  *(const short*)(tab + idx[ 9]), *(const short*)(tab + idx[10]), *(const short*)(tab + idx[11]),
+                                  *(const short*)(tab + idx[12]), *(const short*)(tab + idx[13]), *(const short*)(tab + idx[14]),
+                                  *(const short*)(tab + idx[15])));
+}
+inline v_int8x32 v256_lut_quads(const schar* tab, const int* idx)
+{
+    return v_int8x32(_v256_setr_w(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]),
+                                  *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]),
+                                  *(const int*)(tab + idx[4]), *(const int*)(tab + idx[5]),
+                                  *(const int*)(tab + idx[6]), *(const int*)(tab + idx[7])));
+}
+inline v_uint8x32 v256_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut((const schar *)tab, idx)); }
+inline v_uint8x32 v256_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut_pairs((const schar *)tab, idx)); }
+inline v_uint8x32 v256_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v256_lut_quads((const schar *)tab, idx)); }
+
+inline v_int16x16 v256_lut(const short* tab, const int* idx)
+{
+    return v_int16x16(_v256_setr_h(tab[idx[ 0]], tab[idx[ 1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]],
+                                   tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]], tab[idx[ 8]], tab[idx[ 9]],
+                                   tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]],
+                                   tab[idx[15]]));
+}
+inline v_int16x16 v256_lut_pairs(const short* tab, const int* idx)
+{
+    return v_int16x16(_v256_setr_w(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]),
+                                   *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]),
+                                   *(const int*)(tab + idx[4]), *(const int*)(tab + idx[5]),
+                                   *(const int*)(tab + idx[6]), *(const int*)(tab + idx[7]) ));
+}
+inline v_int16x16 v256_lut_quads(const short* tab, const int* idx)
+{
+    return v_int16x16(_v256_setr_d(*(const long long int*)(tab + idx[0]), *(const long long int*)(tab + idx[1]),
+                                   *(const long long int*)(tab + idx[2]), *(const long long int*)(tab + idx[3]) ));
+
+}
+inline v_uint16x16 v256_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut((const short *)tab, idx)); }
+inline v_uint16x16 v256_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut_pairs((const short *)tab, idx)); }
+inline v_uint16x16 v256_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v256_lut_quads((const short *)tab, idx)); }
+
+inline v_int32x8 v256_lut(const int* tab, const int* idx)
+{
+    return v_int32x8(_v256_setr_w(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]),
+                                  *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]),
+                                  *(const int*)(tab + idx[4]), *(const int*)(tab + idx[5]),
+                                  *(const int*)(tab + idx[6]), *(const int*)(tab + idx[7]) ));
+}
+inline v_int32x8 v256_lut_pairs(const int* tab, const int* idx)
+{
+    return v_int32x8(_v256_setr_d(*(const long long int*)(tab + idx[0]), *(const long long int*)(tab + idx[1]),
+                                  *(const long long int*)(tab + idx[2]), *(const long long int*)(tab + idx[3]) ));
+}
+inline v_int32x8 v256_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x8(_v256_combine(__lsx_vld(tab + idx[0], 0), __lsx_vld(tab + idx[1], 0)));
+}
+inline v_uint32x8 v256_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut((const int *)tab, idx)); }
+inline v_uint32x8 v256_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut_pairs((const int *)tab, idx)); }
+inline v_uint32x8 v256_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v256_lut_quads((const int *)tab, idx)); }
+
+inline v_int64x4 v256_lut(const int64* tab, const int* idx)
+{
+    return v_int64x4(_v256_setr_d(*(const long long int*)(tab + idx[0]), *(const long long int*)(tab + idx[1]),
+                                  *(const long long int*)(tab + idx[2]), *(const long long int*)(tab + idx[3]) ));
+}
+inline v_int64x4 v256_lut_pairs(const int64* tab, const int* idx)
+{
+    return v_int64x4(_v256_combine(__lsx_vld(tab + idx[0], 0), __lsx_vld(tab + idx[1], 0)));
+}
+inline v_uint64x4 v256_lut(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v256_lut((const int64 *)tab, idx)); }
+inline v_uint64x4 v256_lut_pairs(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v256_lut_pairs((const int64 *)tab, idx)); }
+
+inline v_float32x8 v256_lut(const float* tab, const int* idx)
+{
+    return v_float32x8(_v256_setr_ps(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]],
+                                     tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]));
+}
+inline v_float32x8 v256_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v256_lut_pairs((const int *)tab, idx)); }
+inline v_float32x8 v256_lut_quads(const float* tab, const int* idx) { return v_reinterpret_as_f32(v256_lut_quads((const int *)tab, idx)); }
+
+inline v_float64x4 v256_lut(const double* tab, const int* idx)
+{
+    return v_float64x4(_v256_setr_pd(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]));
+}
+inline v_float64x4 v256_lut_pairs(const double* tab, const int* idx)
+{ return v_float64x4(_v256_combine(__lsx_vld(tab + idx[0], 0), __lsx_vld(tab + idx[1], 0))); }
+
+inline v_int32x8 v_lut(const int* tab, const v_int32x8& idxvec)
+{
+    int *idx = (int*)&idxvec.val;
+    return v256_lut(tab, idx);
+}
+
+inline v_uint32x8 v_lut(const unsigned* tab, const v_int32x8& idxvec)
+{
+    return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec));
+}
+
+inline v_float32x8 v_lut(const float* tab, const v_int32x8& idxvec)
+{
+    const int *idx = (const int*)&idxvec.val;
+    return v256_lut(tab, idx);
+}
+
+inline v_float64x4 v_lut(const double* tab, const v_int32x8& idxvec)
+{
+    const int *idx = (const int*)&idxvec.val;
+    return v256_lut(tab, idx);
+}
+
+inline void v_lut_deinterleave(const float* tab, const v_int32x8& idxvec, v_float32x8& x, v_float32x8& y)
+{
+    const int *idx = (const int*)&idxvec.val;
+    __m128i xy01, xy45, xy23, xy67;
+    xy01 = __lsx_vld(tab + idx[0], 0);
+    xy01 = __lsx_vextrins_d(xy01, __lsx_vld(tab + idx[1], 0), 0x10);
+    xy45 = __lsx_vld(tab + idx[4], 0);
+    xy45 = __lsx_vextrins_d(xy45, __lsx_vld(tab + idx[5], 0), 0x10);
+    __m256i xy0145 = _v256_combine(xy01, xy45);
+    xy23 = __lsx_vld(tab + idx[2], 0);
+    xy23 = __lsx_vextrins_d(xy23, __lsx_vld(tab + idx[3], 0), 0x10);
+    xy67 = __lsx_vld(tab + idx[6], 0);
+    xy67 = __lsx_vextrins_d(xy67, __lsx_vld(tab + idx[7], 0), 0x10);
+    __m256i xy2367 = _v256_combine(xy23, xy67);
+
+    __m256i xxyy0145 = __lasx_xvilvl_w(xy2367, xy0145);
+    __m256i xxyy2367 = __lasx_xvilvh_w(xy2367, xy0145);
+
+    x = v_float32x8(__lasx_xvilvl_w(xxyy2367, xxyy0145));
+    y = v_float32x8(__lasx_xvilvh_w(xxyy2367, xxyy0145));
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x8& idxvec, v_float64x4& x, v_float64x4& y)
+{
+    //int CV_DECL_ALIGNED(32) idx[4];
+    const int *idx = (const int*)&idxvec.val;
+    __m128i xy0 = __lsx_vld(tab + idx[0], 0);
+    __m128i xy2 = __lsx_vld(tab + idx[2], 0);
+    __m128i xy1 = __lsx_vld(tab + idx[1], 0);
+    __m128i xy3 = __lsx_vld(tab + idx[3], 0);
+    __m256i xy02 = _v256_combine(xy0, xy2);
+    __m256i xy13 = _v256_combine(xy1, xy3);
+
+    x = v_float64x4(__lasx_xvilvl_d(xy13, xy02));
+    y = v_float64x4(__lasx_xvilvh_d(xy13, xy02));
+}
+
+inline v_int8x32 v_interleave_pairs(const v_int8x32& vec)
+{
+    return v_int8x32(__lasx_xvshuf_b(vec.val, vec.val,
+                       _v256_set_d(0x0f0d0e0c0b090a08, 0x0705060403010200, 0x0f0d0e0c0b090a08, 0x0705060403010200)));
+}
+inline v_uint8x32 v_interleave_pairs(const v_uint8x32& vec)
+{ return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x32 v_interleave_quads(const v_int8x32& vec)
+{
+    return v_int8x32(__lasx_xvshuf_b(vec.val, vec.val,
+                       _v256_set_d(0x0f0b0e0a0d090c08, 0x0703060205010400, 0x0f0b0e0a0d090c08, 0x0703060205010400)));
+}
+inline v_uint8x32 v_interleave_quads(const v_uint8x32& vec)
+{ return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x16 v_interleave_pairs(const v_int16x16& vec)
+{
+    return v_int16x16(__lasx_xvshuf_b(vec.val, vec.val,
+                        _v256_set_d(0x0f0e0b0a0d0c0908, 0x0706030205040100, 0x0f0e0b0a0d0c0908, 0x0706030205040100)));
+}
+inline v_uint16x16 v_interleave_pairs(const v_uint16x16& vec)
+{ return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x16 v_interleave_quads(const v_int16x16& vec)
+{
+    return v_int16x16(__lasx_xvshuf_b(vec.val, vec.val,
+                        _v256_set_d(0x0f0e07060d0c0504, 0x0b0a030209080100, 0x0f0e07060d0c0504, 0x0b0a030209080100)));
+}
+inline v_uint16x16 v_interleave_quads(const v_uint16x16& vec)
+{ return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x8 v_interleave_pairs(const v_int32x8& vec)
+{
+    return v_int32x8(__lasx_xvshuf4i_w(vec.val, 0xd8));
+}
+inline v_uint32x8 v_interleave_pairs(const v_uint32x8& vec)
+{ return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x8 v_interleave_pairs(const v_float32x8& vec)
+{ return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x32 v_pack_triplets(const v_int8x32& vec)
+{
+    __m256i vzero = __lasx_xvreplgr2vr_w(0);
+    __m256i t1 = __lasx_xvshuf_b(vzero, vec.val,
+                   _v256_set_d(0x1211100f0e0d0c0a, 0x0908060504020100, 0x1211100f0e0d0c0a, 0x0908060504020100));
+    return v_int8x32(__lasx_xvperm_w(t1,
+                       _v256_set_d(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+inline v_uint8x32 v_pack_triplets(const v_uint8x32& vec)
+{ return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x16 v_pack_triplets(const v_int16x16& vec)
+{
+    __m256i vzero = __lasx_xvreplgr2vr_w(0);
+    __m256i t1 = __lasx_xvshuf_b(vzero, vec.val,
+                   _v256_set_d(0x11100f0e0d0c0b0a, 0x0908050403020100, 0x11100f0e0d0c0b0a, 0x0908050403020100));
+    return v_int16x16(__lasx_xvperm_w(t1,
+                        _v256_set_d(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+inline v_uint16x16 v_pack_triplets(const v_uint16x16& vec)
+{ return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x8 v_pack_triplets(const v_int32x8& vec)
+{
+    return v_int32x8(__lasx_xvperm_w(vec.val,
+                       _v256_set_d(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+inline v_uint32x8 v_pack_triplets(const v_uint32x8& vec)
+{ return v_reinterpret_as_u32(v_pack_triplets(v_reinterpret_as_s32(vec))); }
+inline v_float32x8 v_pack_triplets(const v_float32x8& vec)
+{
+    return v_float32x8(__lasx_xvperm_w(*(__m256i*)(&vec.val),
+                         _v256_set_d(0x0000000700000007, 0x0000000600000005, 0x0000000400000002, 0x0000000100000000)));
+}
+
+////////// Matrix operations /////////
+
+//////// Dot Product ////////
+
+// 16 >> 32
+inline v_int32x8 v_dotprod(const v_int16x16& a, const v_int16x16& b)
+{ return v_int32x8(__lasx_xvadd_w(__lasx_xvmulwev_w_h(a.val, b.val), __lasx_xvmulwod_w_h(a.val, b.val))); }
+
+inline v_int32x8 v_dotprod(const v_int16x16& a, const v_int16x16& b, const v_int32x8& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 32 >> 64
+inline v_int64x4 v_dotprod(const v_int32x8& a, const v_int32x8& b)
+{
+    __m256i even = __lasx_xvmulwev_d_w(a.val, b.val);
+    return v_int64x4(__lasx_xvmaddwod_d_w(even, a.val, b.val));
+}
+inline v_int64x4 v_dotprod(const v_int32x8& a, const v_int32x8& b, const v_int64x4& c)
+{
+    __m256i even = __lasx_xvmaddwev_d_w(c.val, a.val, b.val);
+    return v_int64x4(__lasx_xvmaddwod_d_w(even, a.val, b.val));
+}
+
+// 8 >> 32
+inline v_uint32x8 v_dotprod_expand(const v_uint8x32& a, const v_uint8x32& b)
+{
+    __m256i even  = __lasx_xvmulwev_h_bu(a.val, b.val);
+    __m256i odd   = __lasx_xvmulwod_h_bu(a.val, b.val);
+    __m256i prod0 = __lasx_xvhaddw_wu_hu(even, even);
+    __m256i prod1 = __lasx_xvhaddw_wu_hu(odd, odd);
+    return v_uint32x8(__lasx_xvadd_w(prod0, prod1));
+}
+inline v_uint32x8 v_dotprod_expand(const v_uint8x32& a, const v_uint8x32& b, const v_uint32x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int32x8 v_dotprod_expand(const v_int8x32& a, const v_int8x32& b)
+{
+    __m256i even  = __lasx_xvmulwev_h_b(a.val, b.val);
+    __m256i odd   = __lasx_xvmulwod_h_b(a.val, b.val);
+    __m256i prod0 = __lasx_xvhaddw_w_h(even, even);
+    __m256i prod1 = __lasx_xvhaddw_w_h(odd, odd);
+    return v_int32x8(__lasx_xvadd_w(prod0, prod1));
+}
+inline v_int32x8 v_dotprod_expand(const v_int8x32& a, const v_int8x32& b, const v_int32x8& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x4 v_dotprod_expand(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i even  = __lasx_xvmulwev_w_hu(a.val, b.val);
+    __m256i odd   = __lasx_xvmulwod_w_hu(a.val, b.val);
+    __m256i prod0 = __lasx_xvhaddw_du_wu(even, even);
+    __m256i prod1 = __lasx_xvhaddw_du_wu(odd, odd);
+    return v_uint64x4(__lasx_xvadd_d(prod0, prod1));
+}
+inline v_uint64x4 v_dotprod_expand(const v_uint16x16& a, const v_uint16x16& b, const v_uint64x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x4 v_dotprod_expand(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i even  = __lasx_xvmulwev_w_h(a.val, b.val);
+    __m256i odd   = __lasx_xvmulwod_w_h(a.val, b.val);
+    __m256i prod0 = __lasx_xvhaddw_d_w(even, even);
+    __m256i prod1 = __lasx_xvhaddw_d_w(odd, odd);
+    return v_int64x4(__lasx_xvadd_d(prod0, prod1));
+}
+
+inline v_int64x4 v_dotprod_expand(const v_int16x16& a, const v_int16x16& b, const v_int64x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x4 v_dotprod_expand(const v_int32x8& a, const v_int32x8& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x4 v_dotprod_expand(const v_int32x8& a, const v_int32x8& b, const v_float64x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x8 v_dotprod_fast(const v_int16x16& a, const v_int16x16& b)
+{ return v_dotprod(a, b); }
+inline v_int32x8 v_dotprod_fast(const v_int16x16& a, const v_int16x16& b, const v_int32x8& c)
+{ return v_dotprod(a, b, c); }
+
+// 32 >> 64
+inline v_int64x4 v_dotprod_fast(const v_int32x8& a, const v_int32x8& b)
+{ return v_dotprod(a, b); }
+inline v_int64x4 v_dotprod_fast(const v_int32x8& a, const v_int32x8& b, const v_int64x4& c)
+{ return v_dotprod(a, b, c); }
+
+// 8 >> 32
+inline v_uint32x8 v_dotprod_expand_fast(const v_uint8x32& a, const v_uint8x32& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint32x8 v_dotprod_expand_fast(const v_uint8x32& a, const v_uint8x32& b, const v_uint32x8& c)
+{ return v_dotprod_expand(a, b, c); }
+
+inline v_int32x8 v_dotprod_expand_fast(const v_int8x32& a, const v_int8x32& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int32x8 v_dotprod_expand_fast(const v_int8x32& a, const v_int8x32& b, const v_int32x8& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 16 >> 64
+inline v_uint64x4 v_dotprod_expand_fast(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i even  = __lasx_xvmulwev_w_hu(a.val, b.val);
+    __m256i odd   = __lasx_xvmulwod_w_hu(a.val, b.val);
+    __m256i prod0 = __lasx_xvhaddw_du_wu(even, even);
+    __m256i prod1 = __lasx_xvhaddw_du_wu(odd, odd);
+    return v_uint64x4(__lasx_xvadd_d(__lasx_xvilvl_d(prod1, prod0), __lasx_xvilvh_d(prod1, prod0)));
+}
+inline v_uint64x4 v_dotprod_expand_fast(const v_uint16x16& a, const v_uint16x16& b, const v_uint64x4& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+inline v_int64x4 v_dotprod_expand_fast(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i prod = __lasx_xvadd_w(__lasx_xvmulwev_w_h(a.val, b.val), __lasx_xvmulwod_w_h(a.val, b.val));
+    __m256i sign = __lasx_xvsrai_w(prod, 31);
+    __m256i lo = __lasx_xvilvl_w(sign, prod);
+    __m256i hi = __lasx_xvilvh_w(sign, prod);
+    return v_int64x4(__lasx_xvadd_d(lo, hi));
+}
+inline v_int64x4 v_dotprod_expand_fast(const v_int16x16& a, const v_int16x16& b, const v_int64x4& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x4 v_dotprod_expand_fast(const v_int32x8& a, const v_int32x8& b)
+{ return v_dotprod_expand(a, b); }
+inline v_float64x4 v_dotprod_expand_fast(const v_int32x8& a, const v_int32x8& b, const v_float64x4& c)
+{ return v_dotprod_expand(a, b, c); }
+
+
+#define OPENCV_HAL_LASX_SPLAT2_PS(a, im) \
+    v_float32x8(__lasx_xvpermi_w(a.val, a.val, im))
+
+inline v_float32x8 v_matmul(const v_float32x8& v, const v_float32x8& m0,
+                            const v_float32x8& m1, const v_float32x8& m2,
+                            const v_float32x8& m3)
+{
+    v_float32x8 v04 = OPENCV_HAL_LASX_SPLAT2_PS(v, 0);
+    v_float32x8 v15 = OPENCV_HAL_LASX_SPLAT2_PS(v, 0x55);
+    v_float32x8 v26 = OPENCV_HAL_LASX_SPLAT2_PS(v, 0xAA);
+    v_float32x8 v37 = OPENCV_HAL_LASX_SPLAT2_PS(v, 0xFF);
+    return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, v_mul(v37, m3))));
+}
+
+inline v_float32x8 v_matmuladd(const v_float32x8& v, const v_float32x8& m0,
+                               const v_float32x8& m1, const v_float32x8& m2,
+                               const v_float32x8& a)
+{
+    v_float32x8 v04 = OPENCV_HAL_LASX_SPLAT2_PS(v, 0);
+    v_float32x8 v15 = OPENCV_HAL_LASX_SPLAT2_PS(v, 0x55);
+    v_float32x8 v26 = OPENCV_HAL_LASX_SPLAT2_PS(v, 0xAA);
+    return v_fma(v04, m0, v_fma(v15, m1, v_fma(v26, m2, a)));
+}
+
+
+#define OPENCV_HAL_IMPL_LASX_TRANSPOSE4x4(_Tpvec, cast_from, cast_to)           \
+    inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1,              \
+                               const _Tpvec& a2, const _Tpvec& a3,              \
+                               _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3)  \
+    {                                                                           \
+        __m256i t0 = cast_from(__lasx_xvilvl_w(a1.val, a0.val));                \
+        __m256i t1 = cast_from(__lasx_xvilvl_w(a3.val, a2.val));                \
+        __m256i t2 = cast_from(__lasx_xvilvh_w(a1.val, a0.val));                \
+        __m256i t3 = cast_from(__lasx_xvilvh_w(a3.val, a2.val));                \
+        b0.val = cast_to(__lasx_xvilvl_d(t1, t0));                              \
+        b1.val = cast_to(__lasx_xvilvh_d(t1, t0));                              \
+        b2.val = cast_to(__lasx_xvilvl_d(t3, t2));                              \
+        b3.val = cast_to(__lasx_xvilvh_d(t3, t2));                              \
+    }
+
+OPENCV_HAL_IMPL_LASX_TRANSPOSE4x4(v_uint32x8, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_LASX_TRANSPOSE4x4(v_int32x8,  OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+
+inline void v_transpose4x4(const v_float32x8 &a0, const v_float32x8 &a1,
+                           const v_float32x8 &a2, const v_float32x8 &a3,
+                           v_float32x8 &b0, v_float32x8 &b1, v_float32x8 &b2, v_float32x8 &b3)
+{
+    __m256i t0 = __lasx_xvilvl_w(__m256i(a1.val), __m256i(a0.val));
+    __m256i t1 = __lasx_xvilvl_w(__m256i(a3.val), __m256i(a2.val));
+    __m256i t2 = __lasx_xvilvh_w(__m256i(a1.val), __m256i(a0.val));
+    __m256i t3 = __lasx_xvilvh_w(__m256i(a3.val), __m256i(a2.val));
+    b0.val = __m256(__lasx_xvilvl_d(t1, t0));
+    b1.val = __m256(__lasx_xvilvh_d(t1, t0));
+    b2.val = __m256(__lasx_xvilvl_d(t3, t2));
+    b3.val = __m256(__lasx_xvilvh_d(t3, t2));
+}
+
+//////////////// Value reordering ///////////////
+
+/* Expand */
+#define OPENCV_HAL_IMPL_LASX_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin)     \
+    inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1)   \
+    {                                                                 \
+        b0.val = intrin(a.val);                                       \
+        b1.val = intrin(__lasx_xvpermi_q(a.val, a.val, 0x11));        \
+    }                                                                 \
+    inline _Tpwvec v_expand_low(const _Tpvec& a)                      \
+    { return _Tpwvec(intrin(a.val)); }                                \
+    inline _Tpwvec v_expand_high(const _Tpvec& a)                     \
+    { return _Tpwvec(intrin(__lasx_xvpermi_q(a.val, a.val, 0x11))); } \
+    inline _Tpwvec v256_load_expand(const _Tp* ptr)                   \
+    {                                                                 \
+        __m128i a = __lsx_vld(ptr, 0);                                \
+        return _Tpwvec(intrin(*((__m256i*)&a)));                      \
+    }
+
+OPENCV_HAL_IMPL_LASX_EXPAND(v_uint8x32,  v_uint16x16, uchar,    __lasx_vext2xv_hu_bu)
+OPENCV_HAL_IMPL_LASX_EXPAND(v_int8x32,   v_int16x16,  schar,    __lasx_vext2xv_h_b)
+OPENCV_HAL_IMPL_LASX_EXPAND(v_uint16x16, v_uint32x8,  ushort,   __lasx_vext2xv_wu_hu)
+OPENCV_HAL_IMPL_LASX_EXPAND(v_int16x16,  v_int32x8,   short,    __lasx_vext2xv_w_h)
+OPENCV_HAL_IMPL_LASX_EXPAND(v_uint32x8,  v_uint64x4,  unsigned, __lasx_vext2xv_du_wu)
+OPENCV_HAL_IMPL_LASX_EXPAND(v_int32x8,   v_int64x4,   int,      __lasx_vext2xv_d_w)
+
+#define OPENCV_HAL_IMPL_LASX_EXPAND_Q(_Tpvec, _Tp, intrin)   \
+    inline _Tpvec v256_load_expand_q(const _Tp* ptr)         \
+    {                                                        \
+        __m128i a = __lsx_vld(ptr, 0);                       \
+        return _Tpvec(intrin(*((__m256i*)&a)));              \
+    }
+
+OPENCV_HAL_IMPL_LASX_EXPAND_Q(v_uint32x8, uchar, __lasx_vext2xv_wu_bu)
+OPENCV_HAL_IMPL_LASX_EXPAND_Q(v_int32x8,  schar, __lasx_vext2xv_w_b)
+
+/* pack */
+// 16
+inline v_int8x32 v_pack(const v_int16x16& a, const v_int16x16& b)
+{ return v_int8x32(_v256_shuffle_odd_64(_lasx_packs_h(a.val, b.val))); }
+
+inline v_uint8x32 v_pack(const v_uint16x16& a, const v_uint16x16& b)
+{ return v_uint8x32(_v256_shuffle_odd_64(__lasx_xvssrlrni_bu_h(b.val, a.val, 0))); }
+
+inline v_uint8x32 v_pack_u(const v_int16x16& a, const v_int16x16& b)
+{
+    return v_uint8x32(_v256_shuffle_odd_64(_lasx_packus_h(a.val, b.val)));
+}
+
+inline void v_pack_store(schar* ptr, const v_int16x16& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(uchar *ptr, const v_uint16x16& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_u_store(uchar* ptr, const v_int16x16& a)
+{ v_store_low(ptr, v_pack_u(a, a)); }
+
+template<int n> inline
+v_uint8x32 v_rshr_pack(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i res = __lasx_xvssrlrni_bu_h(b.val, a.val, n);
+    return v_uint8x32(_v256_shuffle_odd_64(res));
+}
+
+template<int n> inline
+void v_rshr_pack_store(uchar* ptr, const v_uint16x16& a)
+{
+    __m256i res = __lasx_xvssrlrni_bu_h(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+template<int n> inline
+v_uint8x32 v_rshr_pack_u(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i res = __lasx_xvssrarni_bu_h(b.val, a.val, n);
+    return v_uint8x32(_v256_shuffle_odd_64(res));
+}
+
+template<int n> inline
+void v_rshr_pack_u_store(uchar* ptr, const v_int16x16& a)
+{
+    __m256i res = __lasx_xvssrarni_bu_h(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+template<int n> inline
+v_int8x32 v_rshr_pack(const v_int16x16& a, const v_int16x16& b)
+{
+    __m256i res = __lasx_xvssrarni_b_h(b.val, a.val, n);
+    return v_int8x32(_v256_shuffle_odd_64(res));
+}
+
+template<int n> inline
+void v_rshr_pack_store(schar* ptr, const v_int16x16& a)
+{
+    __m256i res = __lasx_xvssrarni_b_h(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+// 32
+inline v_int16x16 v_pack(const v_int32x8& a, const v_int32x8& b)
+{ return v_int16x16(_v256_shuffle_odd_64(_lasx_packs_w(a.val, b.val))); }
+
+inline v_uint16x16 v_pack(const v_uint32x8& a, const v_uint32x8& b)
+{ return v_uint16x16(_v256_shuffle_odd_64(_v256_packs_epu32(a.val, b.val))); }
+
+inline v_uint16x16 v_pack_u(const v_int32x8& a, const v_int32x8& b)
+{ return v_uint16x16(_v256_shuffle_odd_64(_lasx_packus_w(a.val, b.val))); }
+
+inline void v_pack_store(short* ptr, const v_int32x8& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(ushort* ptr, const v_uint32x8& a)
+{
+    __m256i res = __lasx_xvssrlrni_hu_w(a.val, a.val, 0);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+inline void v_pack_u_store(ushort* ptr, const v_int32x8& a)
+{ v_store_low(ptr, v_pack_u(a, a)); }
+
+template<int n> inline
+v_uint16x16 v_rshr_pack(const v_uint32x8& a, const v_uint32x8& b)
+{ return v_uint16x16(_v256_shuffle_odd_64(__lasx_xvssrlrni_hu_w(b.val, a.val, n))); }
+
+template<int n> inline
+void v_rshr_pack_store(ushort* ptr, const v_uint32x8& a)
+{
+    __m256i res = __lasx_xvssrlrni_hu_w(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+template<int n> inline
+v_uint16x16 v_rshr_pack_u(const v_int32x8& a, const v_int32x8& b)
+{ return v_uint16x16(_v256_shuffle_odd_64(__lasx_xvssrarni_hu_w(b.val, a.val, n))); }
+
+template<int n> inline
+void v_rshr_pack_u_store(ushort* ptr, const v_int32x8& a)
+{
+    __m256i res = __lasx_xvssrarni_hu_w(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+template<int n> inline
+v_int16x16 v_rshr_pack(const v_int32x8& a, const v_int32x8& b)
+{ return v_int16x16(_v256_shuffle_odd_64(__lasx_xvssrarni_h_w(b.val, a.val, n))); }
+
+template<int n> inline
+void v_rshr_pack_store(short* ptr, const v_int32x8& a)
+{
+    __m256i res = __lasx_xvssrarni_h_w(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+// 64
+// Non-saturating pack
+inline v_uint32x8 v_pack(const v_uint64x4& a, const v_uint64x4& b)
+{
+    __m256i ab = __lasx_xvpickev_w(b.val, a.val);
+    return v_uint32x8(_v256_shuffle_odd_64(ab));
+}
+
+inline v_int32x8 v_pack(const v_int64x4& a, const v_int64x4& b)
+{ return v_reinterpret_as_s32(v_pack(v_reinterpret_as_u64(a), v_reinterpret_as_u64(b))); }
+
+inline void v_pack_store(unsigned* ptr, const v_uint64x4& a)
+{
+    __m256i a0 = __lasx_xvshuf4i_w(a.val, 0x08);
+    v_store_low(ptr, v_uint32x8(_v256_shuffle_odd_64(a0)));
+}
+
+inline void v_pack_store(int* ptr, const v_int64x4& b)
+{ v_pack_store((unsigned*)ptr, v_reinterpret_as_u64(b)); }
+
+template<int n> inline
+v_uint32x8 v_rshr_pack(const v_uint64x4& a, const v_uint64x4& b)
+{ return v_uint32x8(_v256_shuffle_odd_64(__lasx_xvsrlrni_w_d(b.val, a.val, n))); }
+
+template<int n> inline
+void v_rshr_pack_store(unsigned* ptr, const v_uint64x4& a)
+{
+    __m256i res = __lasx_xvsrlrni_w_d(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+template<int n> inline
+v_int32x8 v_rshr_pack(const v_int64x4& a, const v_int64x4& b)
+{ return v_int32x8(_v256_shuffle_odd_64(__lasx_xvsrarni_w_d(b.val, a.val, n))); }
+
+template<int n> inline
+void v_rshr_pack_store(int* ptr, const v_int64x4& a)
+{
+    __m256i res = __lasx_xvsrarni_w_d(a.val, a.val, n);
+    __lasx_xvstelm_d(res, ptr, 0, 0);
+    __lasx_xvstelm_d(res, ptr, 8, 2);
+}
+
+// pack boolean
+inline v_uint8x32 v_pack_b(const v_uint16x16& a, const v_uint16x16& b)
+{
+    __m256i ab = _lasx_packs_h(a.val, b.val);
+    return v_uint8x32(_v256_shuffle_odd_64(ab));
+}
+
+inline v_uint8x32 v_pack_b(const v_uint32x8& a, const v_uint32x8& b,
+                           const v_uint32x8& c, const v_uint32x8& d)
+{
+    __m256i ab = _lasx_packs_w(a.val, b.val);
+    __m256i cd = _lasx_packs_w(c.val, d.val);
+
+    __m256i abcd = _v256_shuffle_odd_64(_lasx_packs_h(ab, cd));
+    return v_uint8x32(__lasx_xvshuf4i_w(abcd, 0xd8));
+}
+
+inline v_uint8x32 v_pack_b(const v_uint64x4& a, const v_uint64x4& b, const v_uint64x4& c,
+                           const v_uint64x4& d, const v_uint64x4& e, const v_uint64x4& f,
+                           const v_uint64x4& g, const v_uint64x4& h)
+{
+    __m256i ab = _lasx_packs_w(a.val, b.val);
+    __m256i cd = _lasx_packs_w(c.val, d.val);
+    __m256i ef = _lasx_packs_w(e.val, f.val);
+    __m256i gh = _lasx_packs_w(g.val, h.val);
+
+    __m256i abcd = _lasx_packs_w(ab, cd);
+    __m256i efgh = _lasx_packs_w(ef, gh);
+    __m256i pkall = _v256_shuffle_odd_64(_lasx_packs_h(abcd, efgh));
+
+    __m256i rev = _v256_alignr_b(pkall, pkall, 8);
+    return v_uint8x32(__lasx_xvilvl_h(rev, pkall));
+}
+
+/* Recombine */
+// its up there with load and store operations
+
+/* Extract */
+#define OPENCV_HAL_IMPL_LASX_EXTRACT(_Tpvec)                    \
+    template<int s>                                             \
+    inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b)   \
+    { return v_rotate_right<s>(a, b); }
+
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_uint8x32)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_int8x32)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_uint16x16)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_int16x16)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_uint32x8)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_int32x8)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_uint64x4)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_int64x4)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_float32x8)
+OPENCV_HAL_IMPL_LASX_EXTRACT(v_float64x4)
+
+template<int i>
+inline uchar v_extract_n(v_uint8x32 a)
+{
+    return (uchar)_v256_extract_b<i>(a.val);
+}
+
+template<int i>
+inline schar v_extract_n(v_int8x32 a)
+{
+    return (schar)v_extract_n<i>(v_reinterpret_as_u8(a));
+}
+
+template<int i>
+inline ushort v_extract_n(v_uint16x16 a)
+{
+    return (ushort)_v256_extract_h<i>(a.val);
+}
+
+template<int i>
+inline short v_extract_n(v_int16x16 a)
+{
+    return (short)v_extract_n<i>(v_reinterpret_as_u16(a));
+}
+
+template<int i>
+inline uint v_extract_n(v_uint32x8 a)
+{
+    return (uint)_v256_extract_w<i>(a.val);
+}
+
+template<int i>
+inline int v_extract_n(v_int32x8 a)
+{
+    return (int)v_extract_n<i>(v_reinterpret_as_u32(a));
+}
+
+template<int i>
+inline uint64 v_extract_n(v_uint64x4 a)
+{
+    return (uint64)_v256_extract_d<i>(a.val);
+}
+
+template<int i>
+inline int64 v_extract_n(v_int64x4 v)
+{
+    return (int64)v_extract_n<i>(v_reinterpret_as_u64(v));
+}
+
+template<int i>
+inline float v_extract_n(v_float32x8 v)
+{
+    union { uint iv; float fv; } d;
+    d.iv = v_extract_n<i>(v_reinterpret_as_u32(v));
+    return d.fv;
+}
+
+template<int i>
+inline double v_extract_n(v_float64x4 v)
+{
+    union { uint64 iv; double dv; } d;
+    d.iv = v_extract_n<i>(v_reinterpret_as_u64(v));
+    return d.dv;
+}
+
+template<int i>
+inline v_uint32x8 v_broadcast_element(v_uint32x8 a)
+{
+    static const __m256i perm = __lasx_xvreplgr2vr_w((char)i);
+    return v_uint32x8(__lasx_xvperm_w(a.val, perm));
+}
+
+template<int i>
+inline v_int32x8 v_broadcast_element(const v_int32x8 &a)
+{ return v_reinterpret_as_s32(v_broadcast_element<i>(v_reinterpret_as_u32(a))); }
+
+template<int i>
+inline v_float32x8 v_broadcast_element(const v_float32x8 &a)
+{ return v_reinterpret_as_f32(v_broadcast_element<i>(v_reinterpret_as_u32(a))); }
+
+///////////////////// load deinterleave /////////////////////////////
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x32& a, v_uint8x32& b)
+{
+    __m256i t0 = __lasx_xvld(ptr, 0);
+    __m256i t1 = __lasx_xvld(ptr, 32);
+
+    __m256i p0 = __lasx_xvpickev_b(t1, t0);
+    __m256i p1 = __lasx_xvpickod_b(t1, t0);
+
+    a.val = __lasx_xvpermi_d(p0, 0xd8);
+    b.val = __lasx_xvpermi_d(p1, 0xd8);
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b )
+{
+    __m256i t0 = __lasx_xvld(ptr, 0);
+    __m256i t1 = __lasx_xvld(ptr, 32);
+
+    __m256i p0 = __lasx_xvpickev_h(t1, t0);
+    __m256i p1 = __lasx_xvpickod_h(t1, t0);
+
+    a.val = __lasx_xvpermi_d(p0, 0xd8);
+    b.val = __lasx_xvpermi_d(p1, 0xd8);
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b )
+{
+    __m256i t0 = __lasx_xvld(ptr, 0);
+    __m256i t1 = __lasx_xvld(ptr, 32);
+
+    __m256i p0 = __lasx_xvpickev_w(t1, t0);
+    __m256i p1 = __lasx_xvpickod_w(t1, t0);
+
+    a.val = __lasx_xvpermi_d(p0, 0xd8);
+    b.val = __lasx_xvpermi_d(p1, 0xd8);
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b )
+{
+    __m256i ab0 = __lasx_xvld(ptr, 0);
+    __m256i ab1 = __lasx_xvld(ptr, 32);
+
+    __m256i pl = __lasx_xvpermi_q(ab0, ab1, 0x02);
+    __m256i ph = __lasx_xvpermi_q(ab0, ab1, 0x13);
+    __m256i a0 = __lasx_xvilvl_d(ph, pl);
+    __m256i b0 = __lasx_xvilvh_d(ph, pl);
+    a = v_uint64x4(a0);
+    b = v_uint64x4(b0);
+}
+
+inline void v_load_deinterleave( const uchar* ptr, v_uint8x32& a, v_uint8x32& b, v_uint8x32& c )
+{
+    __m256i bgr0 = __lasx_xvld(ptr, 0);
+    __m256i bgr1 = __lasx_xvld(ptr, 32);
+    __m256i bgr2 = __lasx_xvld(ptr, 64);
+
+    __m256i s02_low = __lasx_xvpermi_q(bgr0, bgr2, 0x02);
+    __m256i s02_high = __lasx_xvpermi_q(bgr0, bgr2, 0x13);
+
+    const __m256i m0 = _v256_setr_b(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0,
+                                    0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0);
+    const __m256i m1 = _v256_setr_b(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0,
+                                    -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1);
+
+    __m256i b0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(s02_low, s02_high, m0), bgr1, m1);
+    __m256i g0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(s02_high, s02_low, m1), bgr1, m0);
+    __m256i r0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(bgr1, s02_low, m0), s02_high, m1);
+
+    const __m256i
+    sh_b = _v256_setr_b(0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13,
+                        0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13),
+    sh_g = _v256_setr_b(1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14,
+                        1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14),
+    sh_r = _v256_setr_b(2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15,
+                        2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15);
+    b0 = __lasx_xvshuf_b(b0, b0, sh_b);
+    g0 = __lasx_xvshuf_b(g0, g0, sh_g);
+    r0 = __lasx_xvshuf_b(r0, r0, sh_r);
+
+    a = v_uint8x32(b0);
+    b = v_uint8x32(g0);
+    c = v_uint8x32(r0);
+}
+
+inline void v_load_deinterleave( const ushort* ptr, v_uint16x16& a, v_uint16x16& b, v_uint16x16& c )
+{
+    __m256i bgr0 = __lasx_xvld(ptr, 0);
+    __m256i bgr1 = __lasx_xvld(ptr, 32);
+    __m256i bgr2 = __lasx_xvld(ptr, 64);
+
+    __m256i s02_low = __lasx_xvpermi_q(bgr0, bgr2, 0x02);
+    __m256i s02_high = __lasx_xvpermi_q(bgr0, bgr2, 0x13);
+
+    const __m256i m0 = _v256_setr_b(0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1,
+                                    0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0);
+    const __m256i m1 = _v256_setr_b(0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0,
+                                    -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0);
+    __m256i b0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(s02_low, s02_high, m0), bgr1, m1);
+    __m256i g0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(bgr1, s02_low, m0), s02_high, m1);
+    __m256i r0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(s02_high, s02_low, m1), bgr1, m0);
+    const __m256i sh_b = _v256_setr_b(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11,
+                                      0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11);
+    const __m256i sh_g = _v256_setr_b(2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13,
+                                      2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13);
+    const __m256i sh_r = _v256_setr_b(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15,
+                                      4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15);
+    b0 = __lasx_xvshuf_b(b0, b0, sh_b);
+    g0 = __lasx_xvshuf_b(g0, g0, sh_g);
+    r0 = __lasx_xvshuf_b(r0, r0, sh_r);
+
+    a = v_uint16x16(b0);
+    b = v_uint16x16(g0);
+    c = v_uint16x16(r0);
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b, v_uint32x8& c )
+{
+    __m256i bgr0 = __lasx_xvld(ptr, 0);
+    __m256i bgr1 = __lasx_xvld(ptr, 32);
+    __m256i bgr2 = __lasx_xvld(ptr, 64);
+
+    __m256i s02_low = __lasx_xvpermi_q(bgr0, bgr2, 0x02);
+    __m256i s02_high = __lasx_xvpermi_q(bgr0, bgr2, 0x13);
+
+    __m256i m24 = _v256_set_w(0, 0, -1, 0, 0, -1, 0, 0);
+    __m256i m92 = _v256_set_w(-1, 0, 0, -1, 0, 0, -1, 0);
+    __m256i b0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(s02_low, s02_high, m24), bgr1, m92);
+    __m256i g0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(s02_high, s02_low, m92), bgr1, m24);
+    __m256i r0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(bgr1, s02_low, m24), s02_high, m92);
+
+    b0 = __lasx_xvshuf4i_w(b0, 0x6c);
+    g0 = __lasx_xvshuf4i_w(g0, 0xb1);
+    r0 = __lasx_xvshuf4i_w(r0, 0xc6);
+
+    a = v_uint32x8(b0);
+    b = v_uint32x8(g0);
+    c = v_uint32x8(r0);
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b, v_uint64x4& c )
+{
+    __m256i bgr0 = __lasx_xvld(ptr, 0);
+    __m256i bgr1 = __lasx_xvld(ptr, 32);
+    __m256i bgr2 = __lasx_xvld(ptr, 64);
+
+    __m256i s01 = __lasx_xvpermi_q(bgr0, bgr1, 0x12); // get bgr0 low 128 and bgr1 high 128
+    __m256i s12 = __lasx_xvpermi_q(bgr1, bgr2, 0x12);
+    __m256i s20r = __lasx_xvpermi_d(__lasx_xvpermi_q(bgr2, bgr0, 0x12), 0x1b);
+    __m256i b0 = __lasx_xvilvl_d(s20r, s01);
+    __m256i g0 = _v256_alignr_b(s12, s01, 8);
+    __m256i r0 = __lasx_xvilvh_d(s12, s20r);
+
+    a = v_uint64x4(b0);
+    b = v_uint64x4(g0);
+    c = v_uint64x4(r0);
+}
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x32& a, v_uint8x32& b, v_uint8x32& c, v_uint8x32& d)
+{
+    __m256i t0 = __lasx_xvld(ptr, 0);
+    __m256i t1 = __lasx_xvld(ptr, 32);
+    __m256i t2 = __lasx_xvld(ptr, 64);
+    __m256i t3 = __lasx_xvld(ptr, 96);
+
+    const __m256i sh = _v256_setr_w(0, 4, 1, 5, 2, 6, 3, 7);
+    __m256i ac_lo = __lasx_xvpickev_b(t1, t0);
+    __m256i bd_lo = __lasx_xvpickod_b(t1, t0);
+    __m256i ac_hi = __lasx_xvpickev_b(t3, t2);
+    __m256i bd_hi = __lasx_xvpickod_b(t3, t2);
+
+    __m256i a_pre = __lasx_xvpickev_b(ac_hi, ac_lo);
+    __m256i c_pre = __lasx_xvpickod_b(ac_hi, ac_lo);
+    __m256i b_pre = __lasx_xvpickev_b(bd_hi, bd_lo);
+    __m256i d_pre = __lasx_xvpickod_b(bd_hi, bd_lo);
+
+    a.val = __lasx_xvperm_w(a_pre, sh);
+    b.val = __lasx_xvperm_w(b_pre, sh);
+    c.val = __lasx_xvperm_w(c_pre, sh);
+    d.val = __lasx_xvperm_w(d_pre, sh);
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x16& a, v_uint16x16& b, v_uint16x16& c, v_uint16x16& d)
+{
+    __m256i t0 = __lasx_xvld(ptr, 0);
+    __m256i t1 = __lasx_xvld(ptr, 32);
+    __m256i t2 = __lasx_xvld(ptr, 64);
+    __m256i t3 = __lasx_xvld(ptr, 96);
+
+    const __m256i sh = _v256_setr_w(0, 4, 1, 5, 2, 6, 3, 7);
+    __m256i ac_lo = __lasx_xvpickev_h(t1, t0);
+    __m256i bd_lo = __lasx_xvpickod_h(t1, t0);
+    __m256i ac_hi = __lasx_xvpickev_h(t3, t2);
+    __m256i bd_hi = __lasx_xvpickod_h(t3, t2);
+
+    __m256i a_pre = __lasx_xvpickev_h(ac_hi, ac_lo);
+    __m256i c_pre = __lasx_xvpickod_h(ac_hi, ac_lo);
+    __m256i b_pre = __lasx_xvpickev_h(bd_hi, bd_lo);
+    __m256i d_pre = __lasx_xvpickod_h(bd_hi, bd_lo);
+
+    a.val = __lasx_xvperm_w(a_pre, sh);
+    b.val = __lasx_xvperm_w(b_pre, sh);
+    c.val = __lasx_xvperm_w(c_pre, sh);
+    d.val = __lasx_xvperm_w(d_pre, sh);
+}
+
+inline void v_load_deinterleave( const unsigned* ptr, v_uint32x8& a, v_uint32x8& b, v_uint32x8& c, v_uint32x8& d )
+{
+    __m256i p0 = __lasx_xvld(ptr, 0);
+    __m256i p1 = __lasx_xvld(ptr, 32);
+    __m256i p2 = __lasx_xvld(ptr, 64);
+    __m256i p3 = __lasx_xvld(ptr, 96);
+
+    __m256i p01l = __lasx_xvilvl_w(p1, p0);
+    __m256i p01h = __lasx_xvilvh_w(p1, p0);
+    __m256i p23l = __lasx_xvilvl_w(p3, p2);
+    __m256i p23h = __lasx_xvilvh_w(p3, p2);
+
+    __m256i pll = __lasx_xvpermi_q(p01l, p23l, 0x02);
+    __m256i plh = __lasx_xvpermi_q(p01l, p23l, 0x13);
+    __m256i phl = __lasx_xvpermi_q(p01h, p23h, 0x02);
+    __m256i phh = __lasx_xvpermi_q(p01h, p23h, 0x13);
+
+    __m256i b0 = __lasx_xvilvl_w(plh, pll);
+    __m256i g0 = __lasx_xvilvh_w(plh, pll);
+    __m256i r0 = __lasx_xvilvl_w(phh, phl);
+    __m256i a0 = __lasx_xvilvh_w(phh, phl);
+
+    a = v_uint32x8(b0);
+    b = v_uint32x8(g0);
+    c = v_uint32x8(r0);
+    d = v_uint32x8(a0);
+}
+
+inline void v_load_deinterleave( const uint64* ptr, v_uint64x4& a, v_uint64x4& b, v_uint64x4& c, v_uint64x4& d )
+{
+    __m256i bgra0 = __lasx_xvld(ptr, 0);
+    __m256i bgra1 = __lasx_xvld(ptr, 32);
+    __m256i bgra2 = __lasx_xvld(ptr, 64);
+    __m256i bgra3 = __lasx_xvld(ptr, 96);
+
+    __m256i l02 = __lasx_xvpermi_q(bgra0, bgra2, 0x02);
+    __m256i h02 = __lasx_xvpermi_q(bgra0, bgra2, 0x13);
+    __m256i l13 = __lasx_xvpermi_q(bgra1, bgra3, 0x02);
+    __m256i h13 = __lasx_xvpermi_q(bgra1, bgra3, 0x13);
+
+    __m256i b0 = __lasx_xvilvl_d(l13, l02);
+    __m256i g0 = __lasx_xvilvh_d(l13, l02);
+    __m256i r0 = __lasx_xvilvl_d(h13, h02);
+    __m256i a0 = __lasx_xvilvh_d(h13, h02);
+
+    a = v_uint64x4(b0);
+    b = v_uint64x4(g0);
+    c = v_uint64x4(r0);
+    d = v_uint64x4(a0);
+}
+
+///////////////////////////// store interleave /////////////////////////////////////
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x32& x, const v_uint8x32& y,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = __lasx_xvilvl_b(y.val, x.val);
+    __m256i xy_h = __lasx_xvilvh_b(y.val, x.val);
+
+    __m256i xy0 = __lasx_xvpermi_q(xy_h, xy_l, 0 + 2*16);
+    __m256i xy1 = __lasx_xvpermi_q(xy_h, xy_l, 1 + 3*16);
+
+    __lasx_xvst(xy0, (__m256i*)ptr, 0);
+    __lasx_xvst(xy1, (__m256i*)ptr, 32*1);
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x16& x, const v_uint16x16& y,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = __lasx_xvilvl_h(y.val, x.val);
+    __m256i xy_h = __lasx_xvilvh_h(y.val, x.val);
+
+    __m256i xy0 = __lasx_xvpermi_q(xy_h, xy_l, 0 + 2*16);
+    __m256i xy1 = __lasx_xvpermi_q(xy_h, xy_l, 1 + 3*16);
+
+    __lasx_xvst(xy0, (__m256i*)ptr, 0);
+    __lasx_xvst(xy1, (__m256i*)ptr, 16*2);
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x8& x, const v_uint32x8& y,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = __lasx_xvilvl_w(y.val, x.val);
+    __m256i xy_h = __lasx_xvilvh_w(y.val, x.val);
+
+    __m256i xy0 = __lasx_xvpermi_q(xy_h, xy_l, 0 + 2*16);
+    __m256i xy1 = __lasx_xvpermi_q(xy_h, xy_l, 1 + 3*16);
+
+    __lasx_xvst(xy0, (__m256i*)ptr, 0);
+    __lasx_xvst(xy1, (__m256i*)ptr, 8*4);
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x4& x, const v_uint64x4& y,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i xy_l = __lasx_xvilvl_d(y.val, x.val);
+    __m256i xy_h = __lasx_xvilvh_d(y.val, x.val);
+
+    __m256i xy0 = __lasx_xvpermi_q(xy_h, xy_l, 0 + 2*16);
+    __m256i xy1 = __lasx_xvpermi_q(xy_h, xy_l, 1 + 3*16);
+
+    __lasx_xvst(xy0, (__m256i*)ptr, 0);
+    __lasx_xvst(xy1, (__m256i*)ptr, 4*8);
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x32& a, const v_uint8x32& b, const v_uint8x32& c,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    const __m256i sh_b = _v256_setr_b(
+            0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5,
+            0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5);
+    const __m256i sh_g = _v256_setr_b(
+            5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10,
+            5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10);
+    const __m256i sh_r = _v256_setr_b(
+            10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15,
+            10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15);
+
+    __m256i b0 = __lasx_xvshuf_b(a.val, a.val, sh_b);
+    __m256i g0 = __lasx_xvshuf_b(b.val, b.val, sh_g);
+    __m256i r0 = __lasx_xvshuf_b(c.val, c.val, sh_r);
+
+    const __m256i m0 = _v256_setr_b(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0,
+                                    0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0);
+    const __m256i m1 = _v256_setr_b(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0,
+                                    0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0);
+
+    __m256i p0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(b0, g0, m0), r0, m1);
+    __m256i p1 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(g0, r0, m0), b0, m1);
+    __m256i p2 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(r0, b0, m0), g0, m1);
+
+    __m256i bgr0 = __lasx_xvpermi_q(p1, p0, 0 + 2*16);
+    __m256i bgr1 = __lasx_xvpermi_q(p0, p2, 0 + 3*16);
+    __m256i bgr2 = __lasx_xvpermi_q(p2, p1, 1 + 3*16);
+
+    __lasx_xvst(bgr0, (__m256i*)ptr, 0);
+    __lasx_xvst(bgr1, (__m256i*)ptr, 32);
+    __lasx_xvst(bgr2, (__m256i*)ptr, 64);
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x16& a, const v_uint16x16& b, const v_uint16x16& c,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    const __m256i sh_b = _v256_setr_b(
+         0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11,
+         0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11);
+    const __m256i sh_g = _v256_setr_b(
+         10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5,
+         10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5);
+    const __m256i sh_r = _v256_setr_b(
+         4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15,
+         4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15);
+
+    __m256i b0 = __lasx_xvshuf_b(a.val, a.val, sh_b);
+    __m256i g0 = __lasx_xvshuf_b(b.val, b.val, sh_g);
+    __m256i r0 = __lasx_xvshuf_b(c.val, c.val, sh_r);
+
+    const __m256i m0 = _v256_setr_b(0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1,
+                                    0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0);
+    const __m256i m1 = _v256_setr_b(0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0,
+                                    -1, -1, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, -1, -1, 0, 0);
+
+    __m256i p0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(b0, g0, m0), r0, m1);
+    __m256i p1 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(g0, r0, m0), b0, m1);
+    __m256i p2 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(r0, b0, m0), g0, m1);
+
+    __m256i bgr0 = __lasx_xvpermi_q(p2, p0, 0 + 2*16);
+    __m256i bgr2 = __lasx_xvpermi_q(p2, p0, 1 + 3*16);
+
+    __lasx_xvst(bgr0, (__m256i*)ptr, 0);
+    __lasx_xvst(p1,   (__m256i*)ptr, 16*2);
+    __lasx_xvst(bgr2, (__m256i*)ptr, 32*2);
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x8& a, const v_uint32x8& b, const v_uint32x8& c,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i b0 = __lasx_xvshuf4i_w(a.val, 0x6c);
+    __m256i g0 = __lasx_xvshuf4i_w(b.val, 0xb1);
+    __m256i r0 = __lasx_xvshuf4i_w(c.val, 0xc6);
+
+    __m256i bitmask_1 = _v256_set_w(-1, 0, 0, -1, 0, 0, -1, 0);
+    __m256i bitmask_2 = _v256_set_w(0, 0, -1, 0, 0, -1, 0, 0);
+
+    __m256i p0 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(b0, g0, bitmask_1), r0, bitmask_2);
+    __m256i p1 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(g0, r0, bitmask_1), b0, bitmask_2);
+    __m256i p2 = __lasx_xvbitsel_v(__lasx_xvbitsel_v(r0, b0, bitmask_1), g0, bitmask_2);
+
+    __m256i bgr0 = __lasx_xvpermi_q(p1, p0, 0 + 2*16);
+    __m256i bgr2 = __lasx_xvpermi_q(p1, p0, 1 + 3*16);
+
+    __lasx_xvst(bgr0, (__m256i*)ptr, 0);
+    __lasx_xvst(p2,   (__m256i*)ptr, 8*4);
+    __lasx_xvst(bgr2, (__m256i*)ptr, 16*4);
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x4& a, const v_uint64x4& b, const v_uint64x4& c,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i s01 = __lasx_xvilvl_d(b.val, a.val);
+    __m256i s12 = __lasx_xvilvh_d(c.val, b.val);
+    __m256i s20 = __lasx_xvpermi_w(a.val, c.val, 0xe4);
+
+    __m256i bgr0 = __lasx_xvpermi_q(s20, s01, 0 + 2*16);
+    __m256i bgr1 = __lasx_xvpermi_q(s01, s12, 0x30);
+    __m256i bgr2 = __lasx_xvpermi_q(s12, s20, 1 + 3*16);
+
+    __lasx_xvst(bgr0, (__m256i*)ptr, 0);
+    __lasx_xvst(bgr1, (__m256i*)ptr, 4*8);
+    __lasx_xvst(bgr2, (__m256i*)ptr, 8*8);
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x32& a, const v_uint8x32& b,
+                                const v_uint8x32& c, const v_uint8x32& d,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = __lasx_xvilvl_b(b.val, a.val);
+    __m256i bg1 = __lasx_xvilvh_b(b.val, a.val);
+    __m256i ra0 = __lasx_xvilvl_b(d.val, c.val);
+    __m256i ra1 = __lasx_xvilvh_b(d.val, c.val);
+
+    __m256i bgra0_ = __lasx_xvilvl_h(ra0, bg0);
+    __m256i bgra1_ = __lasx_xvilvh_h(ra0, bg0);
+    __m256i bgra2_ = __lasx_xvilvl_h(ra1, bg1);
+    __m256i bgra3_ = __lasx_xvilvh_h(ra1, bg1);
+
+    __m256i bgra0 = __lasx_xvpermi_q(bgra1_, bgra0_, 0 + 2*16);
+    __m256i bgra2 = __lasx_xvpermi_q(bgra1_, bgra0_, 1 + 3*16);
+    __m256i bgra1 = __lasx_xvpermi_q(bgra3_, bgra2_, 0 + 2*16);
+    __m256i bgra3 = __lasx_xvpermi_q(bgra3_, bgra2_, 1 + 3*16);
+
+    __lasx_xvst(bgra0, (__m256i*)ptr, 0);
+    __lasx_xvst(bgra1, (__m256i*)ptr, 32);
+    __lasx_xvst(bgra2, (__m256i*)ptr, 64);
+    __lasx_xvst(bgra3, (__m256i*)ptr, 96);
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x16& a, const v_uint16x16& b,
+                                const v_uint16x16& c, const v_uint16x16& d,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = __lasx_xvilvl_h(b.val, a.val);
+    __m256i bg1 = __lasx_xvilvh_h(b.val, a.val);
+    __m256i ra0 = __lasx_xvilvl_h(d.val, c.val);
+    __m256i ra1 = __lasx_xvilvh_h(d.val, c.val);
+
+    __m256i bgra0_ = __lasx_xvilvl_w(ra0, bg0);
+    __m256i bgra1_ = __lasx_xvilvh_w(ra0, bg0);
+    __m256i bgra2_ = __lasx_xvilvl_w(ra1, bg1);
+    __m256i bgra3_ = __lasx_xvilvh_w(ra1, bg1);
+
+    __m256i bgra0 = __lasx_xvpermi_q(bgra1_, bgra0_, 0 + 2*16);
+    __m256i bgra2 = __lasx_xvpermi_q(bgra1_, bgra0_, 1 + 3*16);
+    __m256i bgra1 = __lasx_xvpermi_q(bgra3_, bgra2_, 0 + 2*16);
+    __m256i bgra3 = __lasx_xvpermi_q(bgra3_, bgra2_, 1 + 3*16);
+
+    __lasx_xvst(bgra0, (__m256i*)ptr, 0);
+    __lasx_xvst(bgra1, (__m256i*)ptr, 16*2);
+    __lasx_xvst(bgra2, (__m256i*)ptr, 32*2);
+    __lasx_xvst(bgra3, (__m256i*)ptr, 48*2);
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x8& a, const v_uint32x8& b,
+                                const v_uint32x8& c, const v_uint32x8& d,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = __lasx_xvilvl_w(b.val, a.val);
+    __m256i bg1 = __lasx_xvilvh_w(b.val, a.val);
+    __m256i ra0 = __lasx_xvilvl_w(d.val, c.val);
+    __m256i ra1 = __lasx_xvilvh_w(d.val, c.val);
+
+    __m256i bgra0_ = __lasx_xvilvl_d(ra0, bg0);
+    __m256i bgra1_ = __lasx_xvilvh_d(ra0, bg0);
+    __m256i bgra2_ = __lasx_xvilvl_d(ra1, bg1);
+    __m256i bgra3_ = __lasx_xvilvh_d(ra1, bg1);
+
+    __m256i bgra0 = __lasx_xvpermi_q(bgra1_, bgra0_, 0 + 2*16);
+    __m256i bgra2 = __lasx_xvpermi_q(bgra1_, bgra0_, 1 + 3*16);
+    __m256i bgra1 = __lasx_xvpermi_q(bgra3_, bgra2_, 0 + 2*16);
+    __m256i bgra3 = __lasx_xvpermi_q(bgra3_, bgra2_, 1 + 3*16);
+
+    __lasx_xvst(bgra0, (__m256i*)ptr, 0);
+    __lasx_xvst(bgra1, (__m256i*)ptr, 8*4);
+    __lasx_xvst(bgra2, (__m256i*)ptr, 16*4);
+    __lasx_xvst(bgra3, (__m256i*)ptr, 24*4);
+}
+
+inline void v_store_interleave( uint64* ptr, const v_uint64x4& a, const v_uint64x4& b,
+                                const v_uint64x4& c, const v_uint64x4& d,
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED )
+{
+    __m256i bg0 = __lasx_xvilvl_d(b.val, a.val);
+    __m256i bg1 = __lasx_xvilvh_d(b.val, a.val);
+    __m256i ra0 = __lasx_xvilvl_d(d.val, c.val);
+    __m256i ra1 = __lasx_xvilvh_d(d.val, c.val);
+
+    __m256i bgra0 = __lasx_xvpermi_q(ra0, bg0, 0 + 2*16);
+    __m256i bgra1 = __lasx_xvpermi_q(ra1, bg1, 0 + 2*16);
+    __m256i bgra2 = __lasx_xvpermi_q(ra0, bg0, 1 + 3*16);
+    __m256i bgra3 = __lasx_xvpermi_q(ra1, bg1, 1 + 3*16);
+
+    __lasx_xvst(bgra0, (__m256i*)ptr, 0);
+    __lasx_xvst(bgra1, (__m256i*)(ptr), 4*8);
+    __lasx_xvst(bgra2, (__m256i*)(ptr), 8*8);
+    __lasx_xvst(bgra3, (__m256i*)(ptr), 12*8);
+}
+
+
+#define OPENCV_HAL_IMPL_LASX_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1) \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0 ) \
+{ \
+    _Tpvec1 a1, b1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0 ) \
+{ \
+    _Tpvec1 a1, b1, c1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0, _Tpvec0& d0 ) \
+{ \
+    _Tpvec1 a1, b1, c1, d1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+    d0 = v_reinterpret_as_##suffix0(d1); \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1/*, mode*/);      \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, const _Tpvec0& c0, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1/*, mode*/);  \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                const _Tpvec0& c0, const _Tpvec0& d0, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1/*, mode*/); \
+}
+
+OPENCV_HAL_IMPL_LASX_LOADSTORE_INTERLEAVE(v_int8x32, schar, s8, v_uint8x32, uchar, u8)
+OPENCV_HAL_IMPL_LASX_LOADSTORE_INTERLEAVE(v_int16x16, short, s16, v_uint16x16, ushort, u16)
+OPENCV_HAL_IMPL_LASX_LOADSTORE_INTERLEAVE(v_int32x8, int, s32, v_uint32x8, unsigned, u32)
+OPENCV_HAL_IMPL_LASX_LOADSTORE_INTERLEAVE(v_float32x8, float, f32, v_uint32x8, unsigned, u32)
+OPENCV_HAL_IMPL_LASX_LOADSTORE_INTERLEAVE(v_int64x4, int64, s64, v_uint64x4, uint64, u64)
+OPENCV_HAL_IMPL_LASX_LOADSTORE_INTERLEAVE(v_float64x4, double, f64, v_uint64x4, uint64, u64)
+
+//
+// FP16
+//
+
+inline v_float32x8 v256_load_expand(const hfloat* ptr)
+{
+#if CV_FP16
+    //1-load128, 2-permi, 3-cvt
+   return v_float32x8(__lasx_xvfcvtl_s_h(__lasx_xvpermi_d(__lsx_vld((const __m128i*)ptr, 0), 0x10)));
+#else
+    float CV_DECL_ALIGNED(32) buf[8];
+    for (int i = 0; i < 8; i++)
+        buf[i] = (float)ptr[i];
+    return v256_load_aligned(buf);
+#endif
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x8& a)
+{
+#if CV_FP16
+    __m256i ah = __lasx_xvfcvt_h_s(a.val, a.val);
+    __lsx_vst((_m128i)ah, ptr, 0);
+#else
+    float CV_DECL_ALIGNED(32) buf[8];
+    v_store_aligned(buf, a);
+    for (int i = 0; i < 8; i++)
+        ptr[i] = hfloat(buf[i]);
+#endif
+}
+
+//
+// end of FP16
+//
+
+inline void v256_cleanup() {}
+
+#include "intrin_math.hpp"
+inline v_float32x8 v_exp(const v_float32x8& x) { return v_exp_default_32f<v_float32x8, v_int32x8>(x); }
+inline v_float32x8 v_log(const v_float32x8& x) { return v_log_default_32f<v_float32x8, v_int32x8>(x); }
+inline void v_sincos(const v_float32x8& x, v_float32x8& s, v_float32x8& c) { v_sincos_default_32f<v_float32x8, v_int32x8>(x, s, c); }
+inline v_float32x8 v_sin(const v_float32x8& x) { return v_sin_default_32f<v_float32x8, v_int32x8>(x); }
+inline v_float32x8 v_cos(const v_float32x8& x) { return v_cos_default_32f<v_float32x8, v_int32x8>(x); }
+inline v_float32x8 v_erf(const v_float32x8& x) { return v_erf_default_32f<v_float32x8, v_int32x8>(x); }
+
+inline v_float64x4 v_exp(const v_float64x4& x) { return v_exp_default_64f<v_float64x4, v_int64x4>(x); }
+inline v_float64x4 v_log(const v_float64x4& x) { return v_log_default_64f<v_float64x4, v_int64x4>(x); }
+inline void v_sincos(const v_float64x4& x, v_float64x4& s, v_float64x4& c) { v_sincos_default_64f<v_float64x4, v_int64x4>(x, s, c); }
+inline v_float64x4 v_sin(const v_float64x4& x) { return v_sin_default_64f<v_float64x4, v_int64x4>(x); }
+inline v_float64x4 v_cos(const v_float64x4& x) { return v_cos_default_64f<v_float64x4, v_int64x4>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+} // cv::
+
+#endif // OPENCV_HAL_INTRIN_LASX_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_lsx.hpp

@@ -0,0 +1,2546 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+#ifndef OPENCV_HAL_INTRIN_LSX_HPP
+#define OPENCV_HAL_INTRIN_LSX_HPP
+
+#include <lsxintrin.h>
+
+#define CV_SIMD128 1
+#define CV_SIMD128_64F 1
+#define CV_SIMD128_FP16 0
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+/////////// Utils ////////
+
+inline __m128i _v128_setr_b(char v0, char v1, char v2, char v3, char v4, char v5, char v6,
+        char v7, char v8, char v9, char v10, char v11, char v12, char v13, char v14, char v15)
+{
+    return (__m128i)v16i8{ v0, v1, v2, v3, v4, v5, v6, v7,
+                           v8, v9, v10, v11, v12, v13, v14, v15 };
+}
+
+inline __m128i _v128_set_b(char v0, char v1, char v2, char v3, char v4, char v5, char v6,
+        char v7, char v8, char v9, char v10, char v11, char v12, char v13, char v14, char v15)
+{
+    return (__m128i)v16i8{ v15, v14, v13, v12, v11, v10, v9, v8,
+                           v7, v6, v5, v4, v3, v2, v1, v0 };
+}
+
+inline __m128i _v128_setr_h(short v0, short v1, short v2, short v3, short v4, short v5,
+       short v6, short v7)
+{
+    return (__m128i)v8i16{ v0, v1, v2, v3, v4, v5, v6, v7 };
+}
+
+inline __m128i _v128_setr_w(int v0, int v1, int v2, int v3)
+{
+    return (__m128i)v4i32{ v0, v1, v2, v3 };
+}
+
+inline __m128i _v128_set_w(int v0, int v1, int v2, int v3)
+{
+    return (__m128i)v4i32{ v3, v2, v1, v0 };
+}
+
+inline __m128i _v128_setall_w(int v0)
+{
+    return __lsx_vreplgr2vr_w(v0);
+}
+
+inline __m128i _v128_setr_d(int64 v0, int64 v1)
+{
+    return (__m128i)v2i64{ v0, v1 };
+}
+
+inline __m128i _v128_set_d(int64 v0, int64 v1)
+{
+    return (__m128i)v2i64{ v1, v0 };
+}
+
+inline __m128 _v128_setr_ps(float v0, float v1, float v2, float v3)
+{
+    return (__m128)v4f32{ v0, v1, v2, v3 };
+}
+
+inline __m128 _v128_setall_ps(float v0)
+{
+    return (__m128)v4f32{ v0, v0, v0, v0 };
+}
+
+inline __m128d _v128_setr_pd(double v0, double v1)
+{
+    return (__m128d)v2f64{ v0, v1 };
+}
+
+inline __m128d _v128_setall_pd(double v0)
+{
+    return (__m128d)v2f64{ v0, v0 };
+}
+
+inline __m128i _lsx_packus_h(const __m128i& a, const __m128i& b)
+{
+    return __lsx_vssrarni_bu_h(b, a, 0);
+}
+
+inline __m128i _lsx_packs_h(const __m128i& a, const __m128i& b)
+{
+    return __lsx_vssrarni_b_h(b, a, 0);
+}
+
+inline __m128i _lsx_packus_w(const __m128i& a, const __m128i& b)
+{
+    return __lsx_vssrarni_hu_w(b, a, 0);
+}
+
+/////// Types ///////
+
+struct v_uint8x16
+{
+    typedef uchar lane_type;
+    enum { nlanes = 16};
+
+    v_uint8x16() {}
+    explicit v_uint8x16(__m128i v): val(v) {}
+    v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
+             uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
+    {
+        val = _v128_setr_b(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15);
+    }
+
+    uchar get0() const
+    {
+        return (uchar)__lsx_vpickve2gr_bu(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_int8x16
+{
+    typedef schar lane_type;
+    enum { nlanes = 16 };
+
+    v_int8x16() {}
+    explicit v_int8x16(__m128i v) : val(v) {}
+    v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
+            schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
+    {
+        val = _v128_setr_b(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15);
+    }
+
+    schar get0() const
+    {
+        return (schar)__lsx_vpickve2gr_b(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_uint16x8
+{
+    typedef ushort lane_type;
+    enum { nlanes = 8 };
+
+    v_uint16x8() {}
+    explicit v_uint16x8(__m128i v) : val(v) {}
+    v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
+    {
+        val = _v128_setr_h(v0, v1, v2, v3, v4, v5, v6, v7);
+    }
+
+    ushort get0() const
+    {
+        return (ushort)__lsx_vpickve2gr_hu(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_int16x8
+{
+    typedef short lane_type;
+    enum { nlanes = 8 };
+
+    v_int16x8() {}
+    explicit v_int16x8(__m128i v) : val(v) {}
+    v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
+    {
+        val = _v128_setr_h(v0, v1, v2, v3, v4, v5, v6, v7);
+    }
+
+    short get0() const
+    {
+        return (short)__lsx_vpickve2gr_h(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_uint32x4
+{
+    typedef unsigned lane_type;
+    enum { nlanes = 4 };
+
+    v_uint32x4() {}
+    explicit v_uint32x4(__m128i v) : val(v) {}
+    v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3)
+    {
+        val = _v128_setr_w(v0, v1, v2, v3);
+    }
+
+    unsigned get0() const
+    {
+        return (unsigned)__lsx_vpickve2gr_wu(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_int32x4
+{
+    typedef int lane_type;
+    enum { nlanes = 4 };
+
+    v_int32x4() {}
+    explicit v_int32x4(__m128i v) : val(v) {}
+    v_int32x4(int v0, int v1, int v2, int v3)
+    {
+        val = _v128_setr_w(v0, v1, v2, v3);
+    }
+
+    int get0() const
+    {
+        return (int)__lsx_vpickve2gr_w(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_float32x4
+{
+    typedef float lane_type;
+    enum { nlanes = 4};
+
+    v_float32x4() {}
+    explicit v_float32x4(__m128 v) : val(v) {}
+    explicit v_float32x4(__m128i v) { val = *((__m128*)&v); }
+    v_float32x4(float v0, float v1, float v2, float v3)
+    {
+        val = _v128_setr_ps(v0, v1, v2, v3);
+    }
+
+    float get0() const
+    {
+        union { int iv; float fv; } d;
+        d.iv = __lsx_vpickve2gr_w(val, 0);
+        return d.fv;
+    }
+
+    int get0toint() const
+    {
+        __m128i result = __lsx_vftintrz_w_s(val);
+        return (int)__lsx_vpickve2gr_w(result, 0);
+    }
+
+    __m128 val;
+};
+
+struct v_uint64x2
+{
+    typedef uint64 lane_type;
+    enum { nlanes = 2};
+
+    v_uint64x2() {}
+    explicit v_uint64x2(__m128i v) : val(v) {}
+    v_uint64x2(uint64 v0, uint64 v1)
+    {
+        val = _v128_setr_d(v0, v1);
+    }
+
+    uint64 get0() const
+    {
+        return __lsx_vpickve2gr_du(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_int64x2
+{
+    typedef int64 lane_type;
+    enum { nlanes = 2};
+
+    v_int64x2() {}
+    explicit v_int64x2(__m128i v) : val(v) {}
+    v_int64x2(int64 v0, int64 v1)
+    {
+        val = _v128_setr_d(v0, v1);
+    }
+
+    uint64 get0() const
+    {
+        return __lsx_vpickve2gr_d(val, 0);
+    }
+
+    __m128i val;
+};
+
+struct v_float64x2
+{
+    typedef double lane_type;
+    enum { nlanes = 2};
+
+    v_float64x2() {}
+    explicit v_float64x2(__m128d v) : val(v) {}
+    explicit v_float64x2(__m128i v) { val = *((__m128d*)&v); }
+    v_float64x2(double v0, double v1)
+    {
+        val = _v128_setr_pd(v0, v1);
+    }
+
+    double get0() const
+    {
+        union { int64 iv; double fv; } d;
+        d.iv = __lsx_vpickve2gr_d(val, 0);
+        return d.fv;
+    }
+
+    int64 get0toint64() const
+    {
+        __m128i result = __lsx_vftintrz_l_d(val);
+        return (int64)__lsx_vpickve2gr_d(result, 0);
+    }
+
+    __m128d val;
+};
+
+////////////// Load and store operations /////////
+
+#define OPENCV_HAL_IMPL_LSX_LOADSTORE(_Tpvec, _Tp)                     \
+    inline _Tpvec v_load(const _Tp* ptr)                               \
+    { return _Tpvec(__lsx_vld(ptr, 0)); }                              \
+    inline _Tpvec v_load_aligned(const _Tp* ptr)                       \
+    { return _Tpvec(__lsx_vld(ptr, 0)); }                              \
+    inline _Tpvec v_load_low(const _Tp* ptr)                           \
+    { return _Tpvec(__lsx_vldrepl_d(ptr, 0)); }                        \
+    inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1)      \
+    {                                                                  \
+        __m128i vl = __lsx_vldrepl_d(ptr0, 0);                         \
+        __m128i vh = __lsx_vldrepl_d(ptr1, 0);                         \
+        return _Tpvec(__lsx_vilvl_d(vh, vl));                          \
+    }                                                                  \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                     \
+    { __lsx_vst(a.val, ptr, 0); }                                      \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)             \
+    { __lsx_vst(a.val, ptr, 0); }                                      \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)     \
+    { __lsx_vst(a.val, ptr, 0); }                                      \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode)\
+    {                                                                  \
+        if ( mode == hal::STORE_UNALIGNED)                             \
+            __lsx_vst(a.val, ptr, 0);                                  \
+        else if ( mode == hal::STORE_ALIGNED_NOCACHE)                  \
+            __lsx_vst(a.val, ptr, 0);                                  \
+        else                                                           \
+            __lsx_vst(a.val, ptr, 0);                                  \
+    }                                                                  \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                 \
+    {  __lsx_vstelm_d(a.val, ptr, 0, 0); }                             \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)                \
+    {  __lsx_vstelm_d(a.val, ptr, 0, 1); }                             \
+
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_uint8x16,  uchar)
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_int8x16,   schar)
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_uint16x8, ushort)
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_int16x8,  short)
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_uint32x4,  unsigned)
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_int32x4,   int)
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_uint64x2,  uint64)
+OPENCV_HAL_IMPL_LSX_LOADSTORE(v_int64x2,   int64)
+
+#define OPENCV_HAL_IMPL_LSX_LOADSTORE_FLT(_Tpvec, _Tp, halfreg)        \
+    inline _Tpvec v_load(const _Tp* ptr)                               \
+    { return _Tpvec((halfreg)__lsx_vld(ptr, 0)); }                     \
+    inline _Tpvec v_load_aligned(const _Tp* ptr)                       \
+    { return _Tpvec((halfreg)__lsx_vld(ptr, 0)); }                     \
+    inline _Tpvec v_load_low(const _Tp* ptr)                           \
+    { return _Tpvec((halfreg)__lsx_vldrepl_d(ptr, 0)); }               \
+    inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1)      \
+    {                                                                  \
+        __m128i vl = __lsx_vldrepl_d(ptr0, 0);                         \
+        __m128i vh = __lsx_vldrepl_d(ptr1, 0);                         \
+        return _Tpvec((halfreg)__lsx_vilvl_d(vh, vl));                 \
+    }                                                                  \
+    inline void v_store(_Tp* ptr, const _Tpvec& a)                     \
+    {  __lsx_vst((__m128i)a.val, ptr, 0); }                            \
+    inline void v_store_aligned(_Tp* ptr, const _Tpvec& a)             \
+    {  __lsx_vst((__m128i)a.val, ptr, 0); }                            \
+    inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a)     \
+    {  __lsx_vst((__m128i)a.val, ptr, 0); }                            \
+    inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode)\
+    {                                                                  \
+        if( mode == hal::STORE_UNALIGNED)                              \
+            __lsx_vst((__m128i)a.val, ptr, 0);                         \
+        else if( mode == hal::STORE_ALIGNED_NOCACHE)                   \
+            __lsx_vst((__m128i)a.val, ptr, 0);                         \
+        else                                                           \
+            __lsx_vst((__m128i)a.val, ptr, 0);                         \
+    }                                                                  \
+    inline void v_store_low(_Tp* ptr, const _Tpvec& a)                 \
+    {  __lsx_vstelm_d((__m128i)a.val, ptr, 0, 0); }                    \
+    inline void v_store_high(_Tp* ptr, const _Tpvec& a)                \
+    {  __lsx_vstelm_d((__m128i)a.val, ptr, 0, 1); }                    \
+
+OPENCV_HAL_IMPL_LSX_LOADSTORE_FLT(v_float32x4, float, __m128)
+OPENCV_HAL_IMPL_LSX_LOADSTORE_FLT(v_float64x2, double, __m128d)
+
+inline __m128i _lsx_128_castps_si128(const __m128& v)
+{ return __m128i(v); }
+
+inline __m128i _lsx_128_castpd_si128(const __m128d& v)
+{ return __m128i(v); }
+
+#define OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, _Tpvecf, suffix, cast)  \
+    inline _Tpvec v_reinterpret_as_##suffix(const _Tpvecf& a)    \
+    { return _Tpvec(cast(a.val)); }
+
+#define OPENCV_HAL_IMPL_LSX_INIT(_Tpvec, _Tp, suffix, ssuffix, ctype_s)           \
+    inline _Tpvec v_setzero_##suffix()                                            \
+    { return _Tpvec(__lsx_vldi(0)); }                                             \
+    inline _Tpvec v_setall_##suffix(_Tp v)                                        \
+    { return _Tpvec(__lsx_vreplgr2vr_##ssuffix((ctype_s)v)); }                    \
+    template <> inline _Tpvec v_setzero_()                                        \
+    { return v_setzero_##suffix(); }                                              \
+    template <> inline _Tpvec v_setall_(_Tp v)                                    \
+    { return v_setall_##suffix(v); }                                              \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint8x16,  suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int8x16,   suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint16x8,  suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int16x8,   suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint32x4,  suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int32x4,   suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint64x2,  suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int64x2,   suffix, OPENCV_HAL_NOP)         \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_float32x4, suffix, _lsx_128_castps_si128)  \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_float64x2, suffix, _lsx_128_castpd_si128)  \
+
+OPENCV_HAL_IMPL_LSX_INIT(v_uint8x16,  uchar,    u8,   b,  int)
+OPENCV_HAL_IMPL_LSX_INIT(v_int8x16,   schar,    s8,   b,  int)
+OPENCV_HAL_IMPL_LSX_INIT(v_uint16x8,  ushort,   u16,  h,  int)
+OPENCV_HAL_IMPL_LSX_INIT(v_int16x8,   short,    s16,  h,  int)
+OPENCV_HAL_IMPL_LSX_INIT(v_uint32x4,  unsigned, u32,  w,  int)
+OPENCV_HAL_IMPL_LSX_INIT(v_int32x4,   int,      s32,  w,  int)
+OPENCV_HAL_IMPL_LSX_INIT(v_uint64x2,  uint64,   u64,  d,  long int)
+OPENCV_HAL_IMPL_LSX_INIT(v_int64x2,   int64,    s64,  d,  long int)
+
+inline __m128 _lsx_128_castsi128_ps(const __m128i &v)
+{ return __m128(v); }
+
+inline __m128d _lsx_128_castsi128_pd(const __m128i &v)
+{ return __m128d(v); }
+
+#define OPENCV_HAL_IMPL_LSX_INIT_FLT(_Tpvec, _Tp, suffix, zsuffix, cast)    \
+    inline _Tpvec v_setzero_##suffix()                                      \
+    { return _Tpvec(__lsx_vldi(0)); }                                       \
+    inline _Tpvec v_setall_##suffix(_Tp v)                                  \
+    { return _Tpvec(_v128_setall_##zsuffix(v)); }                           \
+    template <> inline _Tpvec v_setzero_()                                  \
+    { return v_setzero_##suffix(); }                                        \
+    template <> inline _Tpvec v_setall_(_Tp v)                              \
+    { return v_setall_##suffix(v); }                                        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint8x16,     suffix,   cast)        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int8x16,      suffix,   cast)        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint16x8,     suffix,   cast)        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int16x8,      suffix,   cast)        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint32x4,     suffix,   cast)        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int32x4,      suffix,   cast)        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_uint64x2,     suffix,   cast)        \
+    OPENCV_HAL_IMPL_LSX_CAST(_Tpvec, v_int64x2,      suffix,   cast)        \
+
+OPENCV_HAL_IMPL_LSX_INIT_FLT(v_float32x4, float,  f32, ps, _lsx_128_castsi128_ps)
+OPENCV_HAL_IMPL_LSX_INIT_FLT(v_float64x2, double, f64, pd, _lsx_128_castsi128_pd)
+
+inline v_float32x4 v_reinterpret_as_f32(const v_float32x4& a)
+{ return a; }
+inline v_float32x4 v_reinterpret_as_f32(const v_float64x2& a)
+{ return v_float32x4(_lsx_128_castps_si128(__m128(a.val))); }
+
+inline v_float64x2 v_reinterpret_as_f64(const v_float64x2& a)
+{ return a; }
+inline v_float64x2 v_reinterpret_as_f64(const v_float32x4& a)
+{ return v_float64x2(_lsx_128_castpd_si128(__m128d(a.val))); }
+
+//////////////// Variant Value reordering ///////////////
+
+// unpacks
+#define OPENCV_HAL_IMPL_LSX_UNPACK(_Tpvec, suffix)                            \
+    inline _Tpvec v128_unpacklo(const _Tpvec& a, const _Tpvec& b)             \
+    { return _Tpvec(__lsx_vilvl_##suffix(__m128i(b.val), __m128i(a.val))); }  \
+    inline _Tpvec v128_unpackhi(const _Tpvec& a, const _Tpvec& b)             \
+    { return _Tpvec(__lsx_vilvh_##suffix(__m128i(b.val), __m128i(a.val))); }  \
+
+OPENCV_HAL_IMPL_LSX_UNPACK(v_uint8x16,  b)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_int8x16,   b)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_uint16x8,  h)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_int16x8,   h)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_uint32x4,  w)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_int32x4,   w)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_uint64x2,  d)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_int64x2,   d)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_float32x4, w)
+OPENCV_HAL_IMPL_LSX_UNPACK(v_float64x2, d)
+
+//ZIP
+#define OPENCV_HAL_IMPL_LSX_ZIP(_Tpvec)                               \
+    inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b)     \
+    { return (_Tpvec)__lsx_vilvl_d((__m128i)b.val, (__m128i)a.val); } \
+    inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b)    \
+    { return (_Tpvec)__lsx_vilvh_d((__m128i)b.val, (__m128i)a.val); } \
+    inline void v_recombine(const _Tpvec& a, const _Tpvec& b,         \
+                            _Tpvec& c, _Tpvec& d)                     \
+    {                                                                 \
+        __m128i a1 = (__m128i)a.val,  b1 = (__m128i)b.val;            \
+        c = _Tpvec(__lsx_vilvl_d(b1, a1));                            \
+        d = _Tpvec(__lsx_vilvh_d(b1, a1));                            \
+    }                                                                 \
+    inline void v_zip(const _Tpvec& a, const _Tpvec& b,               \
+                      _Tpvec& ab0, _Tpvec& ab1)                       \
+    {                                                                 \
+        ab0 = v128_unpacklo(a, b);                                    \
+        ab1 = v128_unpackhi(a, b);                                    \
+    }
+
+OPENCV_HAL_IMPL_LSX_ZIP(v_uint8x16)
+OPENCV_HAL_IMPL_LSX_ZIP(v_int8x16)
+OPENCV_HAL_IMPL_LSX_ZIP(v_uint16x8)
+OPENCV_HAL_IMPL_LSX_ZIP(v_int16x8)
+OPENCV_HAL_IMPL_LSX_ZIP(v_uint32x4)
+OPENCV_HAL_IMPL_LSX_ZIP(v_int32x4)
+OPENCV_HAL_IMPL_LSX_ZIP(v_uint64x2)
+OPENCV_HAL_IMPL_LSX_ZIP(v_int64x2)
+OPENCV_HAL_IMPL_LSX_ZIP(v_float32x4)
+OPENCV_HAL_IMPL_LSX_ZIP(v_float64x2)
+
+////////// Arithmetic, bitwise and comparison operations /////////
+
+/** Arithmetics **/
+#define OPENCV_HAL_IMPL_LSX_BIN_OP(bin_op, _Tpvec, intrin)           \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)  \
+    { return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_uint8x16,  __lsx_vsadd_bu)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_uint8x16,  __lsx_vssub_bu)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_int8x16,   __lsx_vsadd_b)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_int8x16,   __lsx_vssub_b)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_uint16x8,  __lsx_vsadd_hu)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_uint16x8,  __lsx_vssub_hu)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_int16x8,   __lsx_vsadd_h)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_int16x8,   __lsx_vssub_h)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_uint32x4,  __lsx_vadd_w)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_uint32x4,  __lsx_vsub_w)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_mul, v_uint32x4,  __lsx_vmul_w)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_int32x4,   __lsx_vadd_w)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_int32x4,   __lsx_vsub_w)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_mul, v_int32x4,   __lsx_vmul_w)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_uint64x2,  __lsx_vadd_d)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_uint64x2,  __lsx_vsub_d)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_int64x2,   __lsx_vadd_d)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_int64x2,   __lsx_vsub_d)
+
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_float32x4, __lsx_vfadd_s)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_float32x4, __lsx_vfsub_s)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_mul, v_float32x4, __lsx_vfmul_s)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_div, v_float32x4, __lsx_vfdiv_s)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_add, v_float64x2, __lsx_vfadd_d)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_sub, v_float64x2, __lsx_vfsub_d)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_mul, v_float64x2, __lsx_vfmul_d)
+OPENCV_HAL_IMPL_LSX_BIN_OP(v_div, v_float64x2, __lsx_vfdiv_d)
+
+// saturating multiply 8-bit, 16-bit
+inline v_uint8x16 v_mul(const v_uint8x16& a, const v_uint8x16& b)
+{
+    v_uint16x8 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_int8x16 v_mul(const v_int8x16& a, const v_int8x16& b)
+{
+    v_int16x8 c, d;
+    v_mul_expand(a, b, c, d);
+    return v_pack(c, d);
+}
+inline v_uint16x8 v_mul(const v_uint16x8& a, const v_uint16x8& b)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i pev = __lsx_vmulwev_w_hu(a0, b0);
+    __m128i pod = __lsx_vmulwod_w_hu(a0, b0);
+    __m128i pl  = __lsx_vilvl_w(pod, pev);
+    __m128i ph  = __lsx_vilvh_w(pod, pev);
+    return (v_uint16x8)__lsx_vssrlrni_hu_w(ph, pl, 0);
+}
+inline v_int16x8 v_mul(const v_int16x8& a, const v_int16x8& b)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i pev = __lsx_vmulwev_w_h(a0, b0);
+    __m128i pod = __lsx_vmulwod_w_h(a0, b0);
+    __m128i pl  = __lsx_vilvl_w(pod, pev);
+    __m128i ph  = __lsx_vilvh_w(pod, pev);
+    return (v_int16x8)__lsx_vssrarni_h_w(ph, pl, 0);
+}
+
+/** Non-saturating arithmetics **/
+
+#define OPENCV_HAL_IMPL_LSX_BIN_FUNC(func, _Tpvec, intrin)         \
+    inline _Tpvec func(const _Tpvec& a, const _Tpvec& b)           \
+    { return _Tpvec(intrin(a.val, b.val)); }                       \
+
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_add_wrap, v_uint8x16,  __lsx_vadd_b)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_add_wrap, v_int8x16,   __lsx_vadd_b)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_add_wrap, v_uint16x8,  __lsx_vadd_h)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_add_wrap, v_int16x8,   __lsx_vadd_h)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_sub_wrap, v_uint8x16,  __lsx_vsub_b)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_sub_wrap, v_int8x16,   __lsx_vsub_b)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_sub_wrap, v_uint16x8,  __lsx_vsub_h)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_sub_wrap, v_int16x8,   __lsx_vsub_h)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_mul_wrap, v_uint16x8,  __lsx_vmul_h)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_mul_wrap, v_int16x8,   __lsx_vmul_h)
+
+inline v_uint8x16 v_mul_wrap(const v_uint8x16& a, const v_uint8x16& b)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i p0 = __lsx_vmulwev_h_bu(a0, b0);
+    __m128i p1 = __lsx_vmulwod_h_bu(a0, b0);
+    return v_uint8x16(__lsx_vpackev_b(p1, p0));
+}
+
+inline v_int8x16 v_mul_wrap(const v_int8x16& a, const v_int8x16& b)
+{
+    return v_reinterpret_as_s8(v_mul_wrap(v_reinterpret_as_u8(a), v_reinterpret_as_u8(b)));
+}
+
+// Multiply and expand
+inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b,
+                         v_uint16x8& c, v_uint16x8& d)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i p0 = __lsx_vmulwev_h_bu(a0, b0);
+    __m128i p1 = __lsx_vmulwod_h_bu(a0, b0);
+    c.val = __lsx_vilvl_h(p1, p0);
+    d.val = __lsx_vilvh_h(p1, p0);
+}
+inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b,
+                         v_int16x8& c, v_int16x8& d)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i p0 = __lsx_vmulwev_h_b(a0, b0);
+    __m128i p1 = __lsx_vmulwod_h_b(a0, b0);
+    c.val = __lsx_vilvl_h(p1, p0);
+    d.val = __lsx_vilvh_h(p1, p0);
+}
+inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b,
+                         v_int32x4& c, v_int32x4& d)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i p0 = __lsx_vmulwev_w_h(a0, b0);
+    __m128i p1 = __lsx_vmulwod_w_h(a0, b0);
+    c.val = __lsx_vilvl_w(p1, p0);
+    d.val = __lsx_vilvh_w(p1, p0);
+}
+inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b,
+                         v_uint32x4& c, v_uint32x4& d)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i p0 = __lsx_vmulwev_w_hu(a0, b0);
+    __m128i p1 = __lsx_vmulwod_w_hu(a0, b0);
+    c.val = __lsx_vilvl_w(p1, p0);
+    d.val = __lsx_vilvh_w(p1, p0);
+}
+inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b,
+                         v_uint64x2& c, v_uint64x2& d)
+{
+    __m128i a0 = a.val, b0 = b.val;
+    __m128i p0 = __lsx_vmulwev_d_wu(a0, b0);
+    __m128i p1 = __lsx_vmulwod_d_wu(a0, b0);
+    c.val = __lsx_vilvl_d(p1, p0);
+    d.val = __lsx_vilvh_d(p1, p0);
+}
+inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b)
+{ return v_int16x8(__lsx_vmuh_h(a.val, b.val)); }
+inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_uint16x8(__lsx_vmuh_hu(a.val, b.val)); }
+
+/** Bitwise shifts **/
+#define OPENCV_HAL_IMPL_LSX_SHIFT_OP(_Tpuvec, _Tpsvec, suffix, srai)                 \
+    inline _Tpuvec v_shl(const _Tpuvec& a, int imm)                                  \
+    { return _Tpuvec(__lsx_vsll_##suffix(a.val, __lsx_vreplgr2vr_##suffix(imm))); }  \
+    inline _Tpsvec v_shl(const _Tpsvec& a, int imm)                                  \
+    { return _Tpsvec(__lsx_vsll_##suffix(a.val, __lsx_vreplgr2vr_##suffix(imm))); }  \
+    inline _Tpuvec v_shr(const _Tpuvec& a, int imm)                                  \
+    { return _Tpuvec(__lsx_vsrl_##suffix(a.val, __lsx_vreplgr2vr_##suffix(imm))); }  \
+    inline _Tpsvec v_shr(const _Tpsvec& a, int imm)                                  \
+    { return _Tpsvec(srai(a.val, __lsx_vreplgr2vr_##suffix(imm))); }                 \
+    template<int imm>                                                                \
+    inline _Tpuvec v_shl(const _Tpuvec& a)                                           \
+    { return _Tpuvec(__lsx_vslli_##suffix(a.val, imm)); }                            \
+    template<int imm>                                                                \
+    inline _Tpsvec v_shl(const _Tpsvec& a)                                           \
+    { return _Tpsvec(__lsx_vslli_##suffix(a.val, imm)); }                            \
+    template<int imm>                                                                \
+    inline _Tpuvec v_shr(const _Tpuvec& a)                                           \
+    { return _Tpuvec(__lsx_vsrli_##suffix(a.val, imm)); }                            \
+    template<int imm>                                                                \
+    inline _Tpsvec v_shr(const _Tpsvec& a)                                           \
+    { return _Tpsvec(__lsx_vsrai_##suffix(a.val, imm)); }                            \
+
+OPENCV_HAL_IMPL_LSX_SHIFT_OP(v_uint16x8, v_int16x8, h, __lsx_vsra_h)
+OPENCV_HAL_IMPL_LSX_SHIFT_OP(v_uint32x4, v_int32x4, w, __lsx_vsra_w)
+OPENCV_HAL_IMPL_LSX_SHIFT_OP(v_uint64x2, v_int64x2, d, __lsx_vsra_d)
+
+/** Bitwise logic **/
+#define OPENCV_HAL_IMPL_LSX_LOGIC_OP(_Tpvec, suffix)                                 \
+    OPENCV_HAL_IMPL_LSX_BIN_OP(v_and, _Tpvec, __lsx_vand_##suffix)                   \
+    OPENCV_HAL_IMPL_LSX_BIN_OP(v_or, _Tpvec, __lsx_vor_##suffix)                     \
+    OPENCV_HAL_IMPL_LSX_BIN_OP(v_xor, _Tpvec, __lsx_vxor_##suffix)                   \
+    inline _Tpvec v_not(const _Tpvec& a)                                             \
+    { return _Tpvec(__lsx_vnori_b(a.val, 0)); }                                      \
+
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_uint8x16,   v)
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_int8x16,    v)
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_uint16x8,   v)
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_int16x8,    v)
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_uint32x4,   v)
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_int32x4,    v)
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_uint64x2,   v)
+OPENCV_HAL_IMPL_LSX_LOGIC_OP(v_int64x2,    v)
+
+#define OPENCV_HAL_IMPL_LSX_FLOAT_BIN_OP(bin_op, _Tpvec, intrin, cast)               \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)                           \
+    { return _Tpvec(intrin((__m128i)(a.val), (__m128i)(b.val))); }
+
+#define OPENCV_HAL_IMPL_LSX_FLOAT_LOGIC_OP(_Tpvec, cast)                             \
+    OPENCV_HAL_IMPL_LSX_FLOAT_BIN_OP(v_and, _Tpvec, __lsx_vand_v, cast)              \
+    OPENCV_HAL_IMPL_LSX_FLOAT_BIN_OP(v_or, _Tpvec, __lsx_vor_v, cast)                \
+    OPENCV_HAL_IMPL_LSX_FLOAT_BIN_OP(v_xor, _Tpvec, __lsx_vxor_v, cast)              \
+    inline _Tpvec v_not(const _Tpvec& a)                                             \
+    { return _Tpvec(__lsx_vnori_b((__m128i)(a.val), 0)); }                           \
+
+OPENCV_HAL_IMPL_LSX_FLOAT_LOGIC_OP(v_float32x4, _lsx_128_castsi128_ps)
+OPENCV_HAL_IMPL_LSX_FLOAT_LOGIC_OP(v_float64x2, _lsx_128_castsi128_pd)
+
+/** Select **/
+#define OPENCV_HAL_IMPL_LSX_SELECT(_Tpvec)                                           \
+    inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b)     \
+    { return _Tpvec(__lsx_vbitsel_v(b.val, a.val, mask.val)); }                      \
+
+OPENCV_HAL_IMPL_LSX_SELECT(v_uint8x16)
+OPENCV_HAL_IMPL_LSX_SELECT(v_int8x16)
+OPENCV_HAL_IMPL_LSX_SELECT(v_uint16x8)
+OPENCV_HAL_IMPL_LSX_SELECT(v_int16x8)
+OPENCV_HAL_IMPL_LSX_SELECT(v_uint32x4)
+OPENCV_HAL_IMPL_LSX_SELECT(v_int32x4)
+
+inline v_float32x4 v_select(const v_float32x4 &mask, const v_float32x4 &a, const v_float32x4 &b)
+{ return v_float32x4(__lsx_vbitsel_v((__m128i)b.val, (__m128i)a.val, (__m128i)mask.val)); }
+inline v_float64x2 v_select(const v_float64x2 &mask, const v_float64x2 &a, const v_float64x2 &b)
+{ return v_float64x2(__lsx_vbitsel_v((__m128i)b.val, (__m128i)a.val, (__m128i)mask.val)); }
+
+/** Comparison **/
+#define OPENCV_HAL_IMPL_LSX_CMP_OP_OV(_Tpvec)                            \
+    inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_not(v_eq(a, b)); }                                        \
+    inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_gt(b, a); }                                               \
+    inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_not(v_lt(a, b)); }                                        \
+    inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_ge(b, a); }                                               \
+
+#define OPENCV_HAL_IMPL_LSX_CMP_OP_INT(_Tpuvec, _Tpsvec, suffix, usuffix)    \
+    inline _Tpuvec v_eq(const _Tpuvec& a, const _Tpuvec& b)                  \
+    { return _Tpuvec(__lsx_vseq_##suffix(a.val, b.val)); }                   \
+    inline _Tpuvec v_gt(const _Tpuvec& a, const _Tpuvec& b)                  \
+    { return _Tpuvec(__lsx_vslt_##usuffix(b.val, a.val)); }                  \
+    inline _Tpsvec v_eq(const _Tpsvec& a, const _Tpsvec& b)                  \
+    { return _Tpsvec(__lsx_vseq_##suffix(a.val, b.val)); }                   \
+    inline _Tpsvec v_gt(const _Tpsvec& a, const _Tpsvec& b)                  \
+    { return _Tpsvec(__lsx_vslt_##suffix(b.val, a.val)); }                   \
+    OPENCV_HAL_IMPL_LSX_CMP_OP_OV(_Tpuvec)                                   \
+    OPENCV_HAL_IMPL_LSX_CMP_OP_OV(_Tpsvec)
+
+OPENCV_HAL_IMPL_LSX_CMP_OP_INT(v_uint8x16,  v_int8x16,  b, bu)
+OPENCV_HAL_IMPL_LSX_CMP_OP_INT(v_uint16x8,  v_int16x8,  h, hu)
+OPENCV_HAL_IMPL_LSX_CMP_OP_INT(v_uint32x4,  v_int32x4,  w, wu)
+
+#define OPENCV_HAL_IMPL_LSX_CMP_OP_64BIT(_Tpvec, suffix)          \
+    inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b)          \
+    { return _Tpvec(__lsx_vseq_##suffix(a.val, b.val)); }         \
+    inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b)          \
+    { return v_not(v_eq(a, b)); }
+
+OPENCV_HAL_IMPL_LSX_CMP_OP_64BIT(v_uint64x2, d)
+OPENCV_HAL_IMPL_LSX_CMP_OP_64BIT(v_int64x2, d)
+
+#define OPENCV_HAL_IMPL_LSX_CMP_FLT(bin_op, suffix, _Tpvec, ssuffix)       \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b)                 \
+    { return _Tpvec(__lsx_##suffix##_##ssuffix(a.val, b.val)); }           \
+
+#define OPENCV_HAL_IMPL_LSX_CMP_OP_FLT(_Tpvec, ssuffix)                    \
+    OPENCV_HAL_IMPL_LSX_CMP_FLT(v_eq, vfcmp_ceq, _Tpvec, ssuffix)          \
+    OPENCV_HAL_IMPL_LSX_CMP_FLT(v_ne, vfcmp_cne, _Tpvec, ssuffix)          \
+    OPENCV_HAL_IMPL_LSX_CMP_FLT(v_lt,  vfcmp_clt, _Tpvec, ssuffix)         \
+    OPENCV_HAL_IMPL_LSX_CMP_FLT(v_le, vfcmp_cle, _Tpvec, ssuffix)          \
+
+OPENCV_HAL_IMPL_LSX_CMP_OP_FLT(v_float32x4, s)
+OPENCV_HAL_IMPL_LSX_CMP_OP_FLT(v_float64x2, d)
+
+inline v_float32x4 v_gt(const v_float32x4 &a, const v_float32x4 &b)
+{ return v_float32x4(__lsx_vfcmp_clt_s(b.val, a.val)); }
+
+inline v_float32x4 v_ge(const v_float32x4 &a, const v_float32x4 &b)
+{ return v_float32x4(__lsx_vfcmp_cle_s(b.val, a.val)); }
+
+inline v_float64x2 v_gt(const v_float64x2 &a, const v_float64x2 &b)
+{ return v_float64x2(__lsx_vfcmp_clt_d(b.val, a.val)); }
+
+inline v_float64x2 v_ge(const v_float64x2 &a, const v_float64x2 &b)
+{ return v_float64x2(__lsx_vfcmp_cle_d(b.val, a.val)); }
+
+inline v_float32x4 v_not_nan(const v_float32x4& a)
+{ return v_float32x4(__lsx_vfcmp_cor_s(a.val, a.val)); }
+
+inline v_float64x2 v_not_nan(const v_float64x2& a)
+{ return v_float64x2(__lsx_vfcmp_cor_d(a.val, a.val)); }
+
+/** min/max **/
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_uint8x16,  __lsx_vmin_bu)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_uint8x16,  __lsx_vmax_bu)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_int8x16,   __lsx_vmin_b)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_int8x16,   __lsx_vmax_b)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_uint16x8,  __lsx_vmin_hu)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_uint16x8,  __lsx_vmax_hu)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_int16x8,   __lsx_vmin_h)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_int16x8,   __lsx_vmax_h)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_uint32x4,  __lsx_vmin_wu)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_uint32x4,  __lsx_vmax_wu)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_int32x4,   __lsx_vmin_w)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_int32x4,   __lsx_vmax_w)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_float32x4, __lsx_vfmin_s)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_float32x4, __lsx_vfmax_s)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_min, v_float64x2, __lsx_vfmin_d)
+OPENCV_HAL_IMPL_LSX_BIN_FUNC(v_max, v_float64x2, __lsx_vfmax_d)
+
+template <int imm,
+    bool is_invalid = ((imm < 0) || (imm > 16)),
+    bool is_first = (imm == 0),
+    bool is_half = (imm == 8),
+    bool is_second = (imm == 16),
+    bool is_other = (((imm > 0) && (imm < 8)) || ((imm > 8) && (imm < 16)))>
+class v_lsx_palignr_u8_class;
+
+template <int imm>
+class v_lsx_palignr_u8_class<imm, true, false, false, false, false>;
+
+template <int imm>
+class v_lsx_palignr_u8_class<imm, false, true, false, false, false>
+{
+public:
+    inline __m128i operator()(const __m128i& a, const __m128i& b) const
+    {
+        CV_UNUSED(b);
+        return a;
+    }
+};
+
+template <int imm>
+class v_lsx_palignr_u8_class<imm, false, false, true, false, false>
+{
+public:
+    inline __m128i operator()(const __m128i& a, const __m128i& b) const
+    {
+        return __lsx_vshuf4i_d(a, b, 0x9);
+    }
+};
+
+template <int imm>
+class v_lsx_palignr_u8_class<imm, false, false, false, true, false>
+{
+public:
+    inline __m128i operator()(const __m128i& a, const __m128i& b) const
+    {
+        CV_UNUSED(a);
+        return b;
+    }
+};
+
+template <int imm>
+class v_lsx_palignr_u8_class<imm, false, false, false, false, true>
+{
+public:
+    inline __m128i operator()(const __m128i& a, const __m128i& b) const
+    {
+        enum { imm2 = (sizeof(__m128i) - imm) };
+        return __lsx_vor_v(__lsx_vbsrl_v(a, imm), __lsx_vbsll_v(b, imm2));
+    }
+};
+
+template <int imm>
+inline __m128i v_lsx_palignr_u8(const __m128i& a, const __m128i& b)
+{
+    CV_StaticAssert((imm >= 0) && (imm <= 16), "Invalid imm for v_lsx_palignr_u8");
+    return v_lsx_palignr_u8_class<imm>()(a, b);
+}
+/** Rotate **/
+#define OPENCV_HAL_IMPL_LSX_ROTATE_CAST(_Tpvec, cast)                                   \
+    template<int imm>                                                                   \
+    inline _Tpvec v_rotate_right(const _Tpvec &a)                                       \
+    {                                                                                   \
+        enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type))};                      \
+        __m128i ret = __lsx_vbsrl_v((__m128i)a.val, imm2);                              \
+        return _Tpvec(cast(ret));                                                       \
+    }                                                                                   \
+    template<int imm>                                                                   \
+    inline _Tpvec v_rotate_left(const _Tpvec &a)                                        \
+    {                                                                                   \
+        enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type))};                      \
+        __m128i ret = __lsx_vbsll_v((__m128i)a.val, imm2);                              \
+        return _Tpvec(cast(ret));                                                       \
+    }                                                                                   \
+    template<int imm>                                                                   \
+    inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b)                      \
+    {                                                                                   \
+        enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type))};                      \
+        return _Tpvec(cast(v_lsx_palignr_u8<imm2>((__m128i)a.val, (__m128i)b.val)));    \
+    }                                                                                   \
+    template<int imm>                                                                   \
+    inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b)                       \
+    {                                                                                   \
+        enum { imm2 = ((_Tpvec::nlanes - imm) * sizeof(typename _Tpvec::lane_type))};   \
+        return _Tpvec(cast(v_lsx_palignr_u8<imm2>((__m128i)b.val, (__m128i)a.val)));    \
+    }
+
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_uint8x16, OPENCV_HAL_NOP)                             \
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_int8x16,  OPENCV_HAL_NOP)                             \
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_uint16x8, OPENCV_HAL_NOP)                             \
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_int16x8,  OPENCV_HAL_NOP)                             \
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_uint32x4, OPENCV_HAL_NOP)                             \
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_int32x4,  OPENCV_HAL_NOP)                             \
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_uint64x2, OPENCV_HAL_NOP)                             \
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_int64x2,  OPENCV_HAL_NOP)                             \
+
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_float32x4, _lsx_128_castsi128_ps)
+OPENCV_HAL_IMPL_LSX_ROTATE_CAST(v_float64x2, _lsx_128_castsi128_pd)
+
+/** Rverse **/
+inline v_uint8x16 v_reverse(const v_uint8x16 &a)
+{
+    __m128i vec = __lsx_vshuf4i_b(a.val, 0x1B);
+    return v_uint8x16(__lsx_vshuf4i_w(vec, 0x1B));
+}
+
+inline v_int8x16 v_reverse(const v_int8x16 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x8 v_reverse(const v_uint16x8 &a)
+{
+    __m128i vec = __lsx_vshuf4i_h(a.val, 0x1B);
+    return v_uint16x8(__lsx_vshuf4i_w(vec, 0x4E));
+}
+
+inline v_int16x8 v_reverse(const v_int16x8 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x4 v_reverse(const v_uint32x4 &a)
+{ return v_uint32x4(__lsx_vshuf4i_w(a.val, 0x1B)); }
+
+inline v_int32x4 v_reverse(const v_int32x4 &a)
+{ return v_int32x4(__lsx_vshuf4i_w(a.val, 0x1B)); }
+
+inline v_uint64x2 v_reverse(const v_uint64x2 &a)
+{ return v_uint64x2(__lsx_vshuf4i_w(a.val, 0x4E)); }
+
+inline v_int64x2 v_reverse(const v_int64x2 &a)
+{ return v_int64x2(__lsx_vshuf4i_w(a.val, 0x4E)); }
+
+inline v_float32x4 v_reverse(const v_float32x4 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float64x2 v_reverse(const v_float64x2 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+////////////// Reduce and mask ////////////
+
+/** Reduce **/
+// this function is return a[0]+a[1]+...+a[31]
+inline unsigned v_reduce_sum(const v_uint8x16& a)
+{
+    __m128i t1 = __lsx_vhaddw_hu_bu(a.val, a.val);
+    __m128i t2 = __lsx_vhaddw_wu_hu(t1, t1);
+    __m128i t3 = __lsx_vhaddw_du_wu(t2, t2);
+    __m128i t4 = __lsx_vhaddw_qu_du(t3, t3);
+    return (unsigned)__lsx_vpickve2gr_w(t4, 0);
+}
+
+inline int v_reduce_sum(const v_int8x16 &a)
+{
+    __m128i t1 = __lsx_vhaddw_h_b(a.val, a.val);
+    __m128i t2 = __lsx_vhaddw_w_h(t1, t1);
+    __m128i t3 = __lsx_vhaddw_d_w(t2, t2);
+    __m128i t4 = __lsx_vhaddw_q_d(t3, t3);
+    return (int)__lsx_vpickve2gr_w(t4, 0);
+}
+
+#define OPENCV_HAL_IMPL_LSX_REDUCE_16(_Tpvec, sctype, func, intrin)            \
+    inline sctype v_reduce_##func(const _Tpvec& a)                             \
+    {                                                                          \
+        __m128i val = intrin(a.val, __lsx_vbsrl_v(a.val, 8));                  \
+        val = intrin(val, __lsx_vbsrl_v(val, 4));                              \
+        val = intrin(val, __lsx_vbsrl_v(val, 2));                              \
+        val = intrin(val, __lsx_vbsrl_v(val, 1));                              \
+        return (sctype)__lsx_vpickve2gr_b(val, 0);                             \
+    }
+
+OPENCV_HAL_IMPL_LSX_REDUCE_16(v_uint8x16, uchar, min, __lsx_vmin_bu)
+OPENCV_HAL_IMPL_LSX_REDUCE_16(v_uint8x16, uchar, max, __lsx_vmax_bu)
+OPENCV_HAL_IMPL_LSX_REDUCE_16(v_int8x16,  schar, min, __lsx_vmin_b)
+OPENCV_HAL_IMPL_LSX_REDUCE_16(v_int8x16,  schar, max, __lsx_vmax_b)
+
+#define OPENCV_HAL_IMPL_LSX_REDUCE_8(_Tpvec, sctype, func, intrin)             \
+    inline sctype v_reduce_##func(const _Tpvec &a)                             \
+    {                                                                          \
+        __m128i val = intrin(a.val, __lsx_vbsrl_v(a.val, 8));                  \
+        val = intrin(val, __lsx_vbsrl_v(val, 4));                              \
+        val = intrin(val, __lsx_vbsrl_v(val, 2));                              \
+        return (sctype)__lsx_vpickve2gr_h(val, 0);                             \
+    }
+
+OPENCV_HAL_IMPL_LSX_REDUCE_8(v_uint16x8, ushort, min, __lsx_vmin_hu)
+OPENCV_HAL_IMPL_LSX_REDUCE_8(v_uint16x8, ushort, max, __lsx_vmax_hu)
+OPENCV_HAL_IMPL_LSX_REDUCE_8(v_int16x8,  short,  min, __lsx_vmin_h)
+OPENCV_HAL_IMPL_LSX_REDUCE_8(v_int16x8,  short,  max, __lsx_vmax_h)
+
+#define OPENCV_HAL_IMPL_LSX_REDUCE_4(_Tpvec, sctype, func, intrin)             \
+    inline sctype v_reduce_##func(const _Tpvec &a)                             \
+    {                                                                          \
+        __m128i val = intrin(a.val, __lsx_vbsrl_v(a.val, 8));                  \
+        val = intrin(val, __lsx_vbsrl_v(val, 4));                              \
+        return (sctype)__lsx_vpickve2gr_w(val, 0);                             \
+    }
+
+OPENCV_HAL_IMPL_LSX_REDUCE_4(v_uint32x4, unsigned, min, __lsx_vmin_wu)
+OPENCV_HAL_IMPL_LSX_REDUCE_4(v_uint32x4, unsigned, max, __lsx_vmax_wu)
+OPENCV_HAL_IMPL_LSX_REDUCE_4(v_int32x4,  int,      min, __lsx_vmin_w)
+OPENCV_HAL_IMPL_LSX_REDUCE_4(v_int32x4,  int,      max, __lsx_vmax_w)
+
+#define OPENCV_HAL_IMPL_LSX_REDUCE_FLT(func, intrin)                           \
+    inline float v_reduce_##func(const v_float32x4 &a)                         \
+    {                                                                          \
+        __m128 val   = a.val;                                                  \
+        val = intrin(val, (__m128)__lsx_vbsrl_v((__m128i)val, 8));             \
+        val = intrin(val, (__m128)__lsx_vbsrl_v((__m128i)val, 4));             \
+        float *fval = (float*)&val;                                            \
+        return fval[0];                                                        \
+    }
+
+OPENCV_HAL_IMPL_LSX_REDUCE_FLT(min, __lsx_vfmin_s)
+OPENCV_HAL_IMPL_LSX_REDUCE_FLT(max, __lsx_vfmax_s)
+
+inline int v_reduce_sum(const v_int32x4 &a)
+{
+    __m128i t1 = __lsx_vhaddw_d_w(a.val, a.val);
+    __m128i t2 = __lsx_vhaddw_q_d(t1, t1);
+    return (int)__lsx_vpickve2gr_w(t2, 0);
+}
+
+inline unsigned v_reduce_sum(const v_uint32x4 &a)
+{
+    __m128i t1 = __lsx_vhaddw_du_wu(a.val, a.val);
+    __m128i t2 = __lsx_vhaddw_qu_du(t1, t1);
+    return (int)__lsx_vpickve2gr_w(t2, 0);
+}
+
+inline int v_reduce_sum(const v_int16x8 &a)
+{
+    __m128i t1 = __lsx_vhaddw_w_h(a.val, a.val);
+    __m128i t2 = __lsx_vhaddw_d_w(t1, t1);
+    __m128i t3 = __lsx_vhaddw_q_d(t2, t2);
+    return (int)__lsx_vpickve2gr_w(t3, 0);
+}
+
+inline unsigned v_reduce_sum(const v_uint16x8 &a)
+{
+    __m128i t1 = __lsx_vhaddw_wu_hu(a.val, a.val);
+    __m128i t2 = __lsx_vhaddw_du_wu(t1, t1);
+    __m128i t3 = __lsx_vhaddw_qu_du(t2, t2);
+    return (int)__lsx_vpickve2gr_w(t3, 0);
+}
+
+inline float v_reduce_sum(const v_float32x4 &a)
+{
+    __m128i val = (__m128i)a.val;
+    val = __lsx_vbsrl_v(val, 8);
+    __m128 result = __lsx_vfadd_s(a.val, (__m128)val);
+    float *pa = (float*)&result;
+    return (float)(pa[0] + pa[1]);
+}
+
+inline uint64 v_reduce_sum(const v_uint64x2 &a)
+{
+    __m128i t0 = __lsx_vhaddw_qu_du(a.val, a.val);
+    return (uint64)__lsx_vpickve2gr_du(t0, 0);
+}
+
+inline int64 v_reduce_sum(const v_int64x2 &a)
+{
+    __m128i t0 = __lsx_vhaddw_q_d(a.val, a.val);
+    return (int64)__lsx_vpickve2gr_d(t0, 0);
+}
+
+inline double v_reduce_sum(const v_float64x2 &a)
+{
+    double *pa = (double*)&a;
+    return pa[0] + pa[1];
+}
+
+inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b,
+                                 const v_float32x4& c, const v_float32x4& d)
+{
+    __m128i a0 = (__m128i)a.val;
+    __m128i b0 = (__m128i)b.val;
+    __m128i c0 = (__m128i)c.val;
+    __m128i d0 = (__m128i)d.val;
+    __m128i ac_l = __lsx_vilvl_w(c0, a0);
+    __m128i ac_h = __lsx_vilvh_w(c0, a0);
+    __m128i bd_l = __lsx_vilvl_w(d0, b0);
+    __m128i bd_h = __lsx_vilvh_w(d0, b0);
+    __m128  ac   = __lsx_vfadd_s((__m128)ac_l, (__m128)ac_h);
+    __m128  bd   = __lsx_vfadd_s((__m128)bd_l, (__m128)bd_h);
+    return v_float32x4(__lsx_vfadd_s((__m128)__lsx_vilvl_w((__m128i)bd, (__m128i)ac),
+                       (__m128)__lsx_vilvh_w((__m128i)bd, (__m128i)ac)));
+}
+
+inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b)
+{
+    __m128i t0 = __lsx_vabsd_b(a.val, b.val);
+    __m128i t1 = __lsx_vhaddw_hu_bu(t0, t0);
+    __m128i t2 = __lsx_vhaddw_wu_hu(t1, t1);
+    __m128i t3 = __lsx_vhaddw_du_wu(t2, t2);
+    __m128i t4 = __lsx_vhaddw_qu_du(t3, t3);
+    return (unsigned)__lsx_vpickve2gr_w(t4, 0);
+}
+
+inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b)
+{
+    __m128i t0 = __lsx_vabsd_bu(a.val, b.val);
+    __m128i t1 = __lsx_vhaddw_hu_bu(t0, t0);
+    __m128i t2 = __lsx_vhaddw_wu_hu(t1, t1);
+    __m128i t3 = __lsx_vhaddw_du_wu(t2, t2);
+    __m128i t4 = __lsx_vhaddw_qu_du(t3, t3);
+    return (unsigned)__lsx_vpickve2gr_w(t4, 0);
+}
+
+inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b)
+{
+    __m128i t0 = __lsx_vabsd_hu(a.val, b.val);
+    __m128i t1 = __lsx_vhaddw_wu_hu(t0, t0);
+    __m128i t2 = __lsx_vhaddw_du_wu(t1, t1);
+    __m128i t3 = __lsx_vhaddw_qu_du(t2, t2);
+    return (unsigned)__lsx_vpickve2gr_w(t3, 0);
+}
+
+inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b)
+{
+    __m128i t0 = __lsx_vabsd_h(a.val, b.val);
+    __m128i t1 = __lsx_vhaddw_wu_hu(t0, t0);
+    __m128i t2 = __lsx_vhaddw_du_wu(t1, t1);
+    __m128i t3 = __lsx_vhaddw_qu_du(t2, t2);
+    return (unsigned)__lsx_vpickve2gr_w(t3, 0);
+}
+
+inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b)
+{
+    __m128i t0 = __lsx_vabsd_wu(a.val, b.val);
+    __m128i t1 = __lsx_vhaddw_du_wu(t0, t0);
+    __m128i t2 = __lsx_vhaddw_qu_du(t1, t1);
+    return (unsigned)__lsx_vpickve2gr_w(t2, 0);
+}
+
+inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b)
+{
+    __m128i t0 = __lsx_vabsd_w(a.val, b.val);
+    __m128i t1 = __lsx_vhaddw_du_wu(t0, t0);
+    __m128i t2 = __lsx_vhaddw_qu_du(t1, t1);
+    return (unsigned)__lsx_vpickve2gr_w(t2, 0);
+}
+
+inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b)
+{
+    v_float32x4 a_b = v_sub(a, b);
+    return v_reduce_sum(v_float32x4((__m128i)a_b.val & __lsx_vreplgr2vr_w(0x7fffffff)));
+}
+
+/** Popcount **/
+#define OPENCV_HAL_IMPL_LSX_POPCOUNT(_Tpvec, _Tp, suffix)                  \
+inline _Tpvec v_popcount(const _Tp& a)                                     \
+{ return _Tpvec(__lsx_vpcnt_##suffix(a.val)); }
+
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint8x16,  v_uint8x16,  b);
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint8x16,  v_int8x16,   b);
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint16x8,  v_uint16x8,  h);
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint16x8,  v_int16x8,   h);
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint32x4,  v_uint32x4,  w);
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint32x4,  v_int32x4,   w);
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint64x2,  v_uint64x2,  d);
+OPENCV_HAL_IMPL_LSX_POPCOUNT(v_uint64x2,  v_int64x2,   d);
+
+/** Mask **/
+#define OPENCV_HAL_IMPL_REINTERPRET_INT(ft, tt)              \
+inline tt reinterpret_int(ft x) { union {ft l; tt i;} v; v.l = x; return v.i; }
+OPENCV_HAL_IMPL_REINTERPRET_INT(uchar, schar)
+OPENCV_HAL_IMPL_REINTERPRET_INT(schar, schar)
+OPENCV_HAL_IMPL_REINTERPRET_INT(ushort, short)
+OPENCV_HAL_IMPL_REINTERPRET_INT(short, short)
+OPENCV_HAL_IMPL_REINTERPRET_INT(unsigned, int)
+OPENCV_HAL_IMPL_REINTERPRET_INT(int, int)
+OPENCV_HAL_IMPL_REINTERPRET_INT(float, int)
+OPENCV_HAL_IMPL_REINTERPRET_INT(uint64, int64)
+OPENCV_HAL_IMPL_REINTERPRET_INT(int64, int64)
+OPENCV_HAL_IMPL_REINTERPRET_INT(double, int64)
+
+inline int v_signmask(const v_int8x16& a)
+{
+    __m128i result = __lsx_vmskltz_b(a.val);
+    return __lsx_vpickve2gr_w(result, 0);
+}
+inline int v_signmask(const v_uint8x16& a)
+{ return v_signmask(v_reinterpret_as_s8(a)) ;}
+
+inline int v_signmask(const v_int16x8 &a)
+{
+    __m128i result = __lsx_vmskltz_h(a.val);
+    return __lsx_vpickve2gr_w(result, 0);
+}
+inline int v_signmask(const v_uint16x8 &a)
+{ return v_signmask(v_reinterpret_as_s16(a)); }
+
+inline int v_signmask(const v_uint32x4& a)
+{
+    __m128i result = __lsx_vmskltz_w(a.val);
+    return __lsx_vpickve2gr_w(result, 0);
+}
+inline int v_signmask(const v_int32x4& a)
+{ return v_signmask(v_reinterpret_as_u32(a)); }
+
+inline int v_signmask(const v_uint64x2& a)
+{
+    __m128i result = __lsx_vmskltz_d(a.val);
+    return __lsx_vpickve2gr_w(result, 0);
+}
+inline int v_signmask(const v_int64x2& a)
+{ return v_signmask(v_reinterpret_as_u64(a)); }
+
+inline int v_signmask(const v_float32x4& a)
+{ return v_signmask(*(v_int32x4*)(&a)); }
+
+inline int v_signmask(const v_float64x2& a)
+{ return v_signmask(*(v_int64x2*)(&a)); }
+
+inline int v_scan_forward(const v_int8x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_uint8x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_int16x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_uint16x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_int32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_uint32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_float32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_int64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_uint64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_float64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+
+/** Checks **/
+#define OPENCV_HAL_IMPL_LSX_CHECK(_Tpvec, allmask) \
+    inline bool v_check_all(const _Tpvec& a) { return v_signmask(a) == allmask; } \
+    inline bool v_check_any(const _Tpvec& a) { return v_signmask(a) != 0; }
+OPENCV_HAL_IMPL_LSX_CHECK(v_uint8x16, 65535)
+OPENCV_HAL_IMPL_LSX_CHECK(v_int8x16, 65535)
+OPENCV_HAL_IMPL_LSX_CHECK(v_uint16x8, 255);
+OPENCV_HAL_IMPL_LSX_CHECK(v_int16x8, 255);
+OPENCV_HAL_IMPL_LSX_CHECK(v_uint32x4, 15)
+OPENCV_HAL_IMPL_LSX_CHECK(v_int32x4, 15)
+OPENCV_HAL_IMPL_LSX_CHECK(v_uint64x2, 3)
+OPENCV_HAL_IMPL_LSX_CHECK(v_int64x2, 3)
+OPENCV_HAL_IMPL_LSX_CHECK(v_float32x4, 15)
+OPENCV_HAL_IMPL_LSX_CHECK(v_float64x2, 3)
+
+///////////// Other math /////////////
+
+/** Some frequent operations **/
+#define OPENCV_HAL_IMPL_LSX_MULADD(_Tpvec, suffix)                              \
+    inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)      \
+    { return _Tpvec(__lsx_vfmadd_##suffix(a.val, b.val, c.val)); }              \
+    inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec &b, const _Tpvec& c)   \
+    { return _Tpvec(__lsx_vfmadd_##suffix(a.val, b.val, c.val)); }              \
+    inline _Tpvec v_sqrt(const _Tpvec& x)                                       \
+    { return _Tpvec(__lsx_vfsqrt_##suffix(x.val)); }                            \
+    inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b)             \
+    { return v_fma(a, a, v_mul(b, b)); }                                        \
+    inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b)                 \
+    { return v_sqrt(v_fma(a, a, v_mul(b, b))); }
+
+OPENCV_HAL_IMPL_LSX_MULADD(v_float32x4, s)
+OPENCV_HAL_IMPL_LSX_MULADD(v_float64x2, d)
+
+inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{ return v_int32x4(__lsx_vmadd_w(c.val, a.val, b.val)); }
+
+inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{ return v_fma(a, b, c); }
+
+inline v_float32x4 v_invsqrt(const v_float32x4& x)
+{
+    return v_float32x4(__lsx_vfrsqrt_s(x.val));
+}
+
+inline v_float64x2 v_invsqrt(const v_float64x2& x)
+{
+    return v_float64x2(__lsx_vfrsqrt_d(x.val));
+}
+
+/** Absolute values **/
+#define OPENCV_HAL_IMPL_LSX_ABS(_Tpvec, suffix)                          \
+    inline v_u##_Tpvec v_abs(const v_##_Tpvec& x)                        \
+    { return v_u##_Tpvec(__lsx_vabsd_##suffix(x.val, __lsx_vldi(0))); }
+
+OPENCV_HAL_IMPL_LSX_ABS(int8x16, b)
+OPENCV_HAL_IMPL_LSX_ABS(int16x8, h)
+OPENCV_HAL_IMPL_LSX_ABS(int32x4, w)
+
+inline v_float32x4 v_abs(const v_float32x4& x)
+{ return v_float32x4(*((__m128i*)&x) & __lsx_vreplgr2vr_w(0x7fffffff)); }
+inline v_float64x2 v_abs(const v_float64x2& x)
+{ return v_float64x2(*((__m128i*)&x) & __lsx_vreplgr2vr_d(0x7fffffffffffffff)); }
+
+/** Absolute difference **/
+
+inline v_uint8x16 v_absdiff(const v_uint8x16& a, const v_uint8x16& b)
+{ return (v_uint8x16)__lsx_vabsd_bu(a.val, b.val); }
+inline v_uint16x8 v_absdiff(const v_uint16x8& a, const v_uint16x8& b)
+{ return (v_uint16x8)__lsx_vabsd_hu(a.val, b.val); }
+inline v_uint32x4 v_absdiff(const v_uint32x4& a, const v_uint32x4& b)
+{ return (v_uint32x4)__lsx_vabsd_wu(a.val, b.val); }
+
+inline v_uint8x16 v_absdiff(const v_int8x16& a, const v_int8x16& b)
+{ return (v_uint8x16)__lsx_vabsd_b(a.val, b.val); }
+inline v_uint16x8 v_absdiff(const v_int16x8& a, const v_int16x8& b)
+{ return (v_uint16x8)__lsx_vabsd_h(a.val, b.val); }
+inline v_uint32x4 v_absdiff(const v_int32x4& a, const v_int32x4& b)
+{ return (v_uint32x4)__lsx_vabsd_w(a.val, b.val); }
+
+inline v_float32x4 v_absdiff(const v_float32x4& a, const v_float32x4& b)
+{ return v_abs(v_sub(a, b)); }
+
+inline v_float64x2 v_absdiff(const v_float64x2& a, const v_float64x2& b)
+{ return v_abs(v_sub(a, b)); }
+
+/** Saturating absolute difference **/
+inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b)
+{
+    v_int8x16 d = v_sub(a, b);
+    v_int8x16 m = v_lt(a, b);
+    return v_sub(v_xor(d, m), m);
+}
+inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+///////// Conversions /////////
+
+/** Rounding **/
+inline v_int32x4 v_round(const v_float32x4& a)
+{ return v_int32x4(__lsx_vftint_w_s(a.val)); }
+
+inline v_int32x4 v_round(const v_float64x2& a)
+{ return v_int32x4(__lsx_vftint_w_d(a.val, a.val)); }
+
+inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b)
+{ return v_int32x4(__lsx_vftint_w_d(b.val, a.val)); }
+
+inline v_int32x4 v_trunc(const v_float32x4& a)
+{ return v_int32x4(__lsx_vftintrz_w_s(a.val)); }
+
+inline v_int32x4 v_trunc(const v_float64x2& a)
+{ return v_int32x4(__lsx_vftintrz_w_d(a.val, a.val)); }
+
+inline v_int32x4 v_floor(const v_float32x4& a)
+{ return v_int32x4(__lsx_vftintrz_w_s(__m128(__lsx_vfrintrm_s(a.val)))); }
+
+inline v_int32x4 v_floor(const v_float64x2& a)
+{ return v_trunc(v_float64x2(__lsx_vfrintrm_d(a.val))); }
+
+inline v_int32x4 v_ceil(const v_float32x4& a)
+{ return v_int32x4(__lsx_vftintrz_w_s(__m128(__lsx_vfrintrp_s(a.val)))); }
+
+inline v_int32x4 v_ceil(const v_float64x2& a)
+{ return v_trunc(v_float64x2(__lsx_vfrintrp_d(a.val))); }
+
+/** To float **/
+inline v_float32x4 v_cvt_f32(const v_int32x4& a)
+{ return v_float32x4(__lsx_vffint_s_w(a.val)); }
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a)
+{ return v_float32x4(__lsx_vfcvt_s_d(a.val, a.val)); }
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b)
+{ return v_float32x4(__lsx_vfcvt_s_d(b.val, a.val)); }
+
+inline v_float64x2 v_cvt_f64(const v_int32x4& a)
+{ return v_float64x2(__lsx_vffintl_d_w(a.val)); }
+
+inline v_float64x2 v_cvt_f64_high(const v_int32x4& a)
+{ return v_float64x2(__lsx_vffinth_d_w(a.val)); }
+
+inline v_float64x2 v_cvt_f64(const v_float32x4& a)
+{ return v_float64x2(__lsx_vfcvtl_d_s(a.val)); }
+
+inline v_float64x2 v_cvt_f64_high(const v_float32x4& a)
+{ return v_float64x2(__lsx_vfcvth_d_s(a.val)); }
+
+inline v_float64x2 v_cvt_f64(const v_int64x2& v)
+{ return v_float64x2(__lsx_vffint_d_l(v.val)); }
+
+
+//////////////// Lookup table access ////////////////
+inline v_int8x16 v_lut(const schar* tab, const int* idx)
+{
+    return v_int8x16(_v128_setr_b(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]],
+                     tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]], tab[idx[8]],
+                     tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]],
+                     tab[idx[14]], tab[idx[15]]));
+}
+
+inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx)
+{
+    return v_int8x16(_v128_setr_h(*(const short*)(tab + idx[0]), *(const short*)(tab + idx[1]),
+           *(const short*)(tab + idx[2]), *(const short*)(tab + idx[3]), *(const short*)(tab + idx[4]),
+           *(const short*)(tab + idx[5]), *(const short*)(tab + idx[6]), *(const short*)(tab + idx[7])));
+}
+
+inline v_int8x16 v_lut_quads(const schar* tab, const int* idx)
+{
+    return v_int8x16(_v128_setr_w(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]),
+                *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3])));
+}
+
+inline v_uint8x16 v_lut(const uchar* tab, const int* idx)
+{ return v_reinterpret_as_u8(v_lut((const schar*)tab, idx)); }
+inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx)
+{ return v_reinterpret_as_u8(v_lut_pairs((const schar*)tab, idx)); }
+inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx)
+{ return v_reinterpret_as_u8(v_lut_quads((const schar*)tab, idx)); }
+
+inline v_int16x8 v_lut(const short* tab, const int* idx)
+{
+    return v_int16x8(_v128_setr_h(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]],
+                     tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]));
+}
+inline v_int16x8 v_lut_pairs(const short* tab, const int* idx)
+{
+    return v_int16x8(_v128_setr_w(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]),
+                *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3])));
+}
+inline v_int16x8 v_lut_quads(const short* tab, const int* idx)
+{
+    return v_int16x8(_v128_setr_d(*(const int64_t*)(tab + idx[0]), *(const int64_t*)(tab + idx[1])));
+}
+
+inline v_uint16x8 v_lut(const ushort* tab, const int* idx)
+{ return v_reinterpret_as_u16(v_lut((const short *)tab, idx)); }
+inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx)
+{ return v_reinterpret_as_u16(v_lut_pairs((const short *)tab, idx)); }
+inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx)
+{ return v_reinterpret_as_u16(v_lut_quads((const short *)tab, idx)); }
+
+inline v_int32x4 v_lut(const int* tab, const int* idx)
+{
+    return v_int32x4(_v128_setr_w(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]));
+}
+inline v_int32x4 v_lut_pairs(const int *tab, const int* idx)
+{
+    return v_int32x4(_v128_setr_d(*(const int64_t*)(tab + idx[0]), *(const int64_t*)(tab + idx[1])));
+}
+inline v_int32x4 v_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x4(__lsx_vld(tab + idx[0], 0));
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((const int *)tab, idx)); }
+inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((const int *)tab, idx)); }
+inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((const int *)tab, idx)); }
+
+inline v_int64x2 v_lut(const int64_t* tab, const int *idx)
+{
+    return v_int64x2(_v128_setr_d(tab[idx[0]], tab[idx[1]]));
+}
+inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(__lsx_vld(tab + idx[0], 0));
+}
+
+inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); }
+inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); }
+
+inline v_float32x4 v_lut(const float* tab, const int* idx)
+{
+    return v_float32x4(_v128_setr_ps(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]));
+}
+inline v_float32x4 v_lut_pairs(const float* tab, const int* idx)
+{
+    return v_float32x4((__m128)_v128_setr_pd(*(const double*)(tab + idx[0]), *(const double*)(tab + idx[1])));
+}
+inline v_float32x4 v_lut_quads(const float* tab, const int* idx)
+{
+    return v_float32x4((__m128)__lsx_vld(tab + idx[0], 0));
+}
+
+inline v_float64x2 v_lut(const double* tab, const int* idx)
+{
+    return v_float64x2(_v128_setr_pd(tab[idx[0]], tab[idx[1]]));
+}
+inline v_float64x2 v_lut_pairs(const double* tab, const int* idx)
+{
+    return v_float64x2((__m128d)__lsx_vld(tab + idx[0], 0));
+}
+
+inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec)
+{
+    int *idx = (int*)&idxvec.val;
+    return v_lut(tab, idx);
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec)
+{
+    return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec));
+}
+
+inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec)
+{
+    const int *idx = (const int*)&idxvec.val;
+    return v_lut(tab, idx);
+}
+
+inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec)
+{
+    const int *idx = (const int*)&idxvec.val;
+    return v_lut(tab, idx);
+}
+
+inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y)
+{
+    const int *idx = (const int*)&idxvec.val;
+    __m128i xy0  = __lsx_vld(tab + idx[0], 0);
+    __m128i xy1  = __lsx_vld(tab + idx[1], 0);
+    __m128i xy2  = __lsx_vld(tab + idx[2], 0);
+    __m128i xy3  = __lsx_vld(tab + idx[3], 0);
+    __m128i xy01 = __lsx_vilvl_d(xy1, xy0);
+    __m128i xy23 = __lsx_vilvl_d(xy3, xy2);
+    __m128i xxyy02 = __lsx_vilvl_w(xy23, xy01);
+    __m128i xxyy13 = __lsx_vilvh_w(xy23, xy01);
+    x = v_float32x4((__m128)__lsx_vilvl_w(xxyy13, xxyy02));
+    y = v_float32x4((__m128)__lsx_vilvh_w(xxyy13, xxyy02));
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y)
+{
+    const int* idx = (const int*)&idxvec.val;
+    __m128i xy0 = __lsx_vld(tab + idx[0], 0);
+    __m128i xy1 = __lsx_vld(tab + idx[1], 0);
+    x = v_float64x2((__m128d)__lsx_vilvl_d(xy1, xy0));
+    y = v_float64x2((__m128d)__lsx_vilvh_d(xy1, xy0));
+}
+
+inline v_int8x16 v_interleave_pairs(const v_int8x16& vec)
+{
+    return v_int8x16(__lsx_vshuf_b(vec.val, vec.val,
+                _v128_setr_d(0x0705060403010200, 0x0f0d0e0c0b090a08)));
+}
+inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec)
+{ return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x16 v_interleave_quads(const v_int8x16& vec)
+{
+    return v_int8x16(__lsx_vshuf_b(vec.val, vec.val,
+                _v128_setr_d(0x0703060205010400, 0x0f0b0e0a0d090c08)));
+}
+inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec)
+{ return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_interleave_pairs(const v_int16x8& vec)
+{
+    return v_int16x8(__lsx_vshuf_b(vec.val, vec.val,
+                _v128_setr_d(0x0706030205040100, 0x0f0e0b0a0d0c0908)));
+}
+inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec)
+{ return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x8 v_interleave_quads(const v_int16x8& vec)
+{
+    return v_int16x8(__lsx_vshuf_b(vec.val, vec.val,
+                _v128_setr_d(0x0b0a030209080100, 0x0f0e07060d0c0504)));
+}
+inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec)
+{ return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_interleave_pairs(const v_int32x4& vec)
+{
+    return v_int32x4(__lsx_vshuf4i_w(vec.val, 0xd8));
+}
+inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec)
+{ return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_float32x4 v_interleave_pairs(const v_float32x4& vec)
+{ return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x16 v_pack_triplets(const v_int8x16& vec)
+{
+    __m128i zero = __lsx_vldi(0);
+    return v_int8x16(__lsx_vshuf_b(zero, vec.val,
+           _v128_set_d(0x1211100f0e0d0c0a, 0x0908060504020100)));
+}
+inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec)
+{ return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_pack_triplets(const v_int16x8& vec)
+{
+    __m128i zero = __lsx_vldi(0);
+    return v_int16x8(__lsx_vshuf_b(zero, vec.val,
+           _v128_set_d(0x11100f0e0d0c0b0a, 0x0908050403020100)));
+}
+inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec)
+{ return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; }
+inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; }
+inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; }
+
+//////////// Matrix operations /////////
+
+/////////// Dot Product /////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
+{
+    __m128i x = a.val, y = b.val;
+    return v_int32x4(__lsx_vmaddwod_w_h(__lsx_vmulwev_w_h(x, y), x, y));
+}
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{
+    __m128i x = a.val, y = b.val, z = c.val;
+    __m128i t = __lsx_vmaddwev_w_h(z, x, y);
+    return v_int32x4(__lsx_vmaddwod_w_h(t, x, y));
+}
+
+// 32 >> 64
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b)
+{
+    __m128i x = a.val, y = b.val;
+    return v_int64x2(__lsx_vmaddwod_d_w(__lsx_vmulwev_d_w(x, y), x, y));
+}
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{
+    __m128i x = a.val, y = b.val, z = c.val;
+    __m128i t = __lsx_vmaddwev_d_w(z, x, y);
+    return v_int64x2(__lsx_vmaddwod_d_w(t, x, y));
+}
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
+{
+    __m128i x = a.val, y = b.val;
+    __m128i even  = __lsx_vmulwev_h_bu(x, y);
+    __m128i odd   = __lsx_vmulwod_h_bu(x, y);
+    __m128i prod0 = __lsx_vhaddw_wu_hu(even, even);
+    __m128i prod1 = __lsx_vhaddw_wu_hu(odd, odd);
+    return v_uint32x4(__lsx_vadd_w(prod0, prod1));
+}
+
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_add(v_dotprod_expand(a, b), c) ;}
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
+{
+    __m128i x = a.val, y = b.val;
+    __m128i even  = __lsx_vmulwev_h_b(x, y);
+    __m128i odd   = __lsx_vmulwod_h_b(x, y);
+    __m128i prod0 = __lsx_vhaddw_w_h(even, even);
+    __m128i prod1 = __lsx_vhaddw_w_h(odd, odd);
+    return v_int32x4(__lsx_vadd_w(prod0, prod1));
+}
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
+{
+    __m128i x = a.val, y = b.val;
+    __m128i even  = __lsx_vmulwev_w_hu(x, y);
+    __m128i odd   = __lsx_vmulwod_w_hu(x, y);
+    __m128i prod0 = __lsx_vhaddw_du_wu(even, even);
+    __m128i prod1 = __lsx_vhaddw_du_wu(odd, odd);
+    return v_uint64x2(__lsx_vadd_d(prod0, prod1));
+}
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b)
+{
+    __m128i x = a.val, y = b.val;
+    __m128i even  = __lsx_vmulwev_w_h(x, y);
+    __m128i odd   = __lsx_vmulwod_w_h(x, y);
+    __m128i prod0 = __lsx_vhaddw_d_w(even, even);
+    __m128i prod1 = __lsx_vhaddw_d_w(odd, odd);
+    return v_int64x2(__lsx_vadd_d(prod0, prod1));
+}
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+//32 >> 64f
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+
+///////// Fast Dot Product //////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b)
+{ return v_dotprod(a, b); }
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_dotprod(a, b, c); }
+
+// 32 >> 64
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod(a, b); }
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_dotprod(a, b, c); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_dotprod_expand(a, b, c); }
+
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
+{
+    __m128i x = a.val, y = b.val;
+    __m128i even  = __lsx_vmulwev_w_hu(x, y);
+    __m128i odd   = __lsx_vmulwod_w_hu(x, y);
+    __m128i prod0 = __lsx_vhaddw_du_wu(even, even);
+    __m128i prod1 = __lsx_vhaddw_du_wu(odd, odd);
+    return v_uint64x2(__lsx_vilvl_d(__lsx_vhaddw_qu_du(prod0, prod0), __lsx_vhaddw_qu_du(prod1, prod1)));
+}
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b)
+{
+    __m128i x = a.val, y = b.val;
+    __m128i prod = __lsx_vmaddwod_w_h(__lsx_vmulwev_w_h(x, y), x, y);
+    __m128i sign = __lsx_vsrai_w(prod, 31);
+    __m128i lo   = __lsx_vilvl_w(sign, prod);
+    __m128i hi   = __lsx_vilvh_w(sign, prod);
+    return v_int64x2(__lsx_vadd_d(lo, hi));
+}
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod_expand(a, b); }
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+
+inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
+                            const v_float32x4& m1, const v_float32x4& m2, const v_float32x4& m3)
+{
+    __m128i x = (__m128i)v.val;
+    __m128 v0 = __lsx_vfmul_s((__m128)__lsx_vshuf4i_w(x, 0x0), m0.val);
+    __m128 v1 = __lsx_vfmul_s((__m128)__lsx_vshuf4i_w(x, 0x55), m1.val);
+    __m128 v2 = __lsx_vfmul_s((__m128)__lsx_vshuf4i_w(x, 0xAA), m2.val);
+    __m128 v3 = __lsx_vfmul_s((__m128)__lsx_vshuf4i_w(x, 0xFF), m3.val);
+
+    return v_float32x4(__lsx_vfadd_s(__lsx_vfadd_s(v0, v1), __lsx_vfadd_s(v2, v3)));
+}
+
+inline v_float32x4 v_matmuladd(const v_float32x4& v, const  v_float32x4& m0,
+                               const v_float32x4& m1, const v_float32x4& m2, const v_float32x4& a)
+{
+    __m128i x = (__m128i)v.val;
+    __m128 v0 = __lsx_vfmul_s((__m128)__lsx_vshuf4i_w(x, 0x0), m0.val);
+    __m128 v1 = __lsx_vfmul_s((__m128)__lsx_vshuf4i_w(x, 0x55), m1.val);
+    __m128 v2 = __lsx_vfmadd_s((__m128)__lsx_vshuf4i_w(x, 0xAA), m2.val, a.val);
+
+    return v_float32x4(__lsx_vfadd_s(__lsx_vfadd_s(v0, v1), v2));
+}
+
+#define OPENCV_HAL_IMPL_LSX_TRANSPOSE4X4(_Tpvec, cast_from, cast_to)                          \
+    inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1,                            \
+                               const _Tpvec& a2, const _Tpvec& a3,                            \
+                               _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3)                \
+   {                                                                                          \
+       __m128i t0 = cast_from(__lsx_vilvl_w(a1.val, a0.val));                                 \
+       __m128i t1 = cast_from(__lsx_vilvl_w(a3.val, a2.val));                                 \
+       __m128i t2 = cast_from(__lsx_vilvh_w(a1.val, a0.val));                                 \
+       __m128i t3 = cast_from(__lsx_vilvh_w(a3.val, a2.val));                                 \
+       b0.val = cast_to(__lsx_vilvl_d(t1, t0));                                               \
+       b1.val = cast_to(__lsx_vilvh_d(t1, t0));                                               \
+       b2.val = cast_to(__lsx_vilvl_d(t3, t2));                                               \
+       b3.val = cast_to(__lsx_vilvh_d(t3, t2));                                               \
+   }
+
+OPENCV_HAL_IMPL_LSX_TRANSPOSE4X4(v_uint32x4, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_LSX_TRANSPOSE4X4(v_int32x4, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+
+inline void v_transpose4x4(const v_float32x4& a0, const v_float32x4& a1,
+                           const v_float32x4& a2, const v_float32x4& a3,
+                           v_float32x4& b0, v_float32x4& b1, v_float32x4& b2, v_float32x4& b3)
+{
+    __m128i vec0 = (__m128i)a0.val, vec1 = (__m128i)a1.val;
+    __m128i vec2 = (__m128i)a2.val, vec3 = (__m128i)a3.val;
+    __m128i t0 = __lsx_vilvl_w(vec1, vec0);
+    __m128i t1 = __lsx_vilvl_w(vec3, vec2);
+    __m128i t2 = __lsx_vilvh_w(vec1, vec0);
+    __m128i t3 = __lsx_vilvh_w(vec3, vec2);
+    b0.val = __m128(__lsx_vilvl_d(t1, t0));
+    b1.val = __m128(__lsx_vilvh_d(t1, t0));
+    b2.val = __m128(__lsx_vilvl_d(t3, t2));
+    b3.val = __m128(__lsx_vilvh_d(t3, t2));
+}
+
+////////////////// Value reordering ////////////////
+
+/* Expand */
+#define OPENCV_HAL_IMPL_LSX_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin_lo, intrin_hi)     \
+    inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1)                \
+    {                                                                              \
+        b0.val = intrin_lo(a.val, 0);                                              \
+        b1.val = intrin_hi(a.val);                                                 \
+    }                                                                              \
+    inline _Tpwvec v_expand_low(const _Tpvec& a)                                   \
+    { return _Tpwvec(intrin_lo(a.val, 0)); }                                       \
+    inline _Tpwvec v_expand_high(const _Tpvec& a)                                  \
+    { return _Tpwvec(intrin_hi(a.val)); }                                          \
+    inline _Tpwvec v_load_expand(const _Tp* ptr)                                   \
+    {                                                                              \
+        __m128i a = __lsx_vld(ptr, 0);                                             \
+        return _Tpwvec(intrin_lo(a, 0));                                           \
+    }
+
+OPENCV_HAL_IMPL_LSX_EXPAND(v_uint8x16, v_uint16x8, uchar,     __lsx_vsllwil_hu_bu, __lsx_vexth_hu_bu)
+OPENCV_HAL_IMPL_LSX_EXPAND(v_int8x16,  v_int16x8,  schar,     __lsx_vsllwil_h_b,   __lsx_vexth_h_b)
+OPENCV_HAL_IMPL_LSX_EXPAND(v_uint16x8, v_uint32x4, ushort,    __lsx_vsllwil_wu_hu, __lsx_vexth_wu_hu)
+OPENCV_HAL_IMPL_LSX_EXPAND(v_int16x8,  v_int32x4,  short,     __lsx_vsllwil_w_h,   __lsx_vexth_w_h)
+OPENCV_HAL_IMPL_LSX_EXPAND(v_uint32x4, v_uint64x2, unsigned,  __lsx_vsllwil_du_wu, __lsx_vexth_du_wu)
+OPENCV_HAL_IMPL_LSX_EXPAND(v_int32x4,  v_int64x2,  int,       __lsx_vsllwil_d_w,   __lsx_vexth_d_w)
+
+#define OPENCV_HAL_IMPL_LSX_EXPAND_Q(_Tpvec, _Tp, intrin_lo, intrin_hi)          \
+    inline _Tpvec v_load_expand_q(const _Tp* ptr)                                \
+    {                                                                            \
+        __m128i a = __lsx_vld(ptr, 0);                                           \
+        __m128i b = intrin_lo(a, 0);                                             \
+        return _Tpvec(intrin_hi(b, 0));                                          \
+    }
+
+OPENCV_HAL_IMPL_LSX_EXPAND_Q(v_uint32x4, uchar, __lsx_vsllwil_hu_bu, __lsx_vsllwil_wu_hu)
+OPENCV_HAL_IMPL_LSX_EXPAND_Q(v_int32x4,  schar, __lsx_vsllwil_h_b,   __lsx_vsllwil_w_h)
+
+/* pack */
+// 16
+inline v_int8x16 v_pack(const v_int16x8& a, const v_int16x8& b)
+{ return v_int8x16(_lsx_packs_h(a.val, b.val)); }
+
+inline v_uint8x16 v_pack(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_uint8x16(__lsx_vssrlrni_bu_h(b.val, a.val, 0)); }
+
+inline v_uint8x16 v_pack_u(const v_int16x8& a, const v_int16x8& b)
+{ return v_uint8x16(_lsx_packus_h(a.val, b.val)); }
+
+inline void v_pack_store(schar* ptr, const v_int16x8& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(uchar* ptr, const v_uint16x8& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_u_store(uchar* ptr, const v_int16x8& a)
+{ v_store_low(ptr, v_pack_u(a, a)); }
+
+template<int n> inline
+v_uint8x16 v_rshr_pack(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_uint8x16(__lsx_vssrlrni_bu_h(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_store(uchar* ptr, const v_uint16x8& a)
+{ __lsx_vstelm_d(__lsx_vssrlrni_bu_h(a.val, a.val, n), ptr, 0, 0); }
+
+template<int n> inline
+v_uint8x16 v_rshr_pack_u(const v_int16x8& a, const v_int16x8& b)
+{ return v_uint8x16(__lsx_vssrarni_bu_h(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_u_store(uchar* ptr, const v_int16x8& a)
+{ __lsx_vstelm_d(__lsx_vssrarni_bu_h(a.val, a.val, n), ptr, 0, 0); }
+
+template<int n> inline
+v_int8x16 v_rshr_pack(const v_int16x8& a, const v_int16x8& b)
+{ return v_int8x16(__lsx_vssrarni_b_h(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_store(schar* ptr, const v_int16x8& a)
+{ __lsx_vstelm_d(__lsx_vssrarni_b_h(a.val, a.val, n), ptr, 0, 0); }
+
+//32
+inline v_int16x8 v_pack(const v_int32x4& a, const v_int32x4& b)
+{ return v_int16x8(__lsx_vssrarni_h_w(b.val, a.val, 0)); }
+
+inline v_uint16x8 v_pack(const v_uint32x4& a, const v_uint32x4& b)
+{ return v_uint16x8(__lsx_vssrlrni_hu_w(b.val, a.val, 0)); }
+
+inline v_uint16x8 v_pack_u(const v_int32x4& a, const v_int32x4& b)
+{ return v_uint16x8(__lsx_vssrarni_hu_w(b.val, a.val, 0)); }
+
+inline void v_pack_store(short* ptr, const v_int32x4& a)
+{ v_store_low(ptr, v_pack(a, a)); }
+
+inline void v_pack_store(ushort *ptr, const v_uint32x4& a)
+{ __lsx_vstelm_d(__lsx_vssrlrni_hu_w(a.val, a.val, 0), ptr,  0, 0); }
+
+inline void v_pack_u_store(ushort* ptr, const v_int32x4& a)
+{ __lsx_vstelm_d(__lsx_vssrarni_hu_w(a.val, a.val, 0), ptr, 0, 0); }
+
+template<int n> inline
+v_uint16x8 v_rshr_pack(const v_uint32x4& a, const v_uint32x4& b)
+{ return v_uint16x8(__lsx_vssrlrni_hu_w(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_store(ushort* ptr, const v_uint32x4& a)
+{ __lsx_vstelm_d(__lsx_vssrlrni_hu_w(a.val, a.val, n), ptr, 0, 0); }
+
+template<int n> inline
+v_uint16x8 v_rshr_pack_u(const v_int32x4& a, const v_int32x4& b)
+{ return v_uint16x8(__lsx_vssrarni_hu_w(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_u_store(ushort* ptr, const v_int32x4& a)
+{ __lsx_vstelm_d(__lsx_vssrarni_hu_w(a.val, a.val, n), ptr, 0, 0); }
+
+template<int n> inline
+v_int16x8 v_rshr_pack(const v_int32x4& a, const v_int32x4& b)
+{ return v_int16x8(__lsx_vssrarni_h_w(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_store(short* ptr, const v_int32x4& a)
+{ __lsx_vstelm_d(__lsx_vssrarni_h_w(a.val, a.val, n), ptr, 0, 0); }
+
+// 64
+// Non-saturaing pack
+inline v_uint32x4 v_pack(const v_uint64x2& a, const v_uint64x2& b)
+{ return v_uint32x4(__lsx_vpickev_w(b.val, a.val)); }
+
+inline v_int32x4 v_pack(const v_int64x2& a, const v_int64x2& b)
+{ return v_reinterpret_as_s32(v_pack(v_reinterpret_as_u64(a), v_reinterpret_as_u64(b))); }
+
+inline void v_pack_store(unsigned* ptr, const v_uint64x2& a)
+{ __lsx_vstelm_d(__lsx_vshuf4i_w(a.val, 0x08), ptr, 0, 0); }
+
+inline void v_pack_store(int *ptr, const v_int64x2& a)
+{ v_pack_store((unsigned*)ptr, v_reinterpret_as_u64(a)); }
+
+template<int n> inline
+v_uint32x4 v_rshr_pack(const v_uint64x2& a, const v_uint64x2& b)
+{ return v_uint32x4(__lsx_vsrlrni_w_d(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_store(unsigned* ptr, const v_uint64x2& a)
+{ __lsx_vstelm_d(__lsx_vsrlrni_w_d(a.val, a.val, n), ptr, 0, 0); }
+
+template<int n> inline
+v_int32x4 v_rshr_pack(const v_int64x2& a, const v_int64x2& b)
+{ return v_int32x4(__lsx_vsrarni_w_d(b.val, a.val, n)); }
+
+template<int n> inline
+void v_rshr_pack_store(int* ptr, const v_int64x2& a)
+{ __lsx_vstelm_d(__lsx_vsrarni_w_d(a.val, a.val, n), ptr, 0, 0); }
+
+// pack boolean
+inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_uint8x16(__lsx_vssrarni_b_h(b.val, a.val, 0)); }
+
+inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b,
+                           const v_uint32x4& c, const v_uint32x4& d)
+{
+    __m128i ab = __lsx_vssrarni_h_w(b.val, a.val, 0);
+    __m128i cd = __lsx_vssrarni_h_w(d.val, c.val, 0);
+    return v_uint8x16(__lsx_vssrarni_b_h(cd, ab, 0));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                           const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f,
+                           const v_uint64x2& g, const v_uint64x2& h)
+{
+    __m128i ab = __lsx_vssrarni_w_d(b.val, a.val, 0);
+    __m128i cd = __lsx_vssrarni_w_d(d.val, c.val, 0);
+    __m128i ef = __lsx_vssrarni_w_d(f.val, e.val, 0);
+    __m128i gh = __lsx_vssrarni_w_d(h.val, g.val, 0);
+
+    __m128i abcd = __lsx_vssrarni_h_w(cd, ab, 0);
+    __m128i efgh = __lsx_vssrarni_h_w(gh, ef, 0);
+    return v_uint8x16(__lsx_vssrarni_b_h(efgh, abcd, 0));
+}
+
+/* Recombine */
+// its up there with load and store operations
+
+/* Extract */
+#define OPENCV_HAL_IMPL_LSX_EXTRACT(_Tpvec)                    \
+    template<int s>                                            \
+    inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b)  \
+    { return v_rotate_right<s>(a, b); }
+
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_uint8x16)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_int8x16)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_uint16x8)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_int16x8)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_uint32x4)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_int32x4)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_uint64x2)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_int64x2)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_float32x4)
+OPENCV_HAL_IMPL_LSX_EXTRACT(v_float64x2)
+
+#define OPENCV_HAL_IMPL_LSX_EXTRACT_N(_Tpvec, _Twvec, intrin)             \
+template<int i>                                                           \
+inline _Twvec v_extract_n(const _Tpvec& a)                                \
+{ return (_Twvec)intrin(a.val, i); }
+
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_uint8x16, uchar,   __lsx_vpickve2gr_b)
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_int8x16,  schar,   __lsx_vpickve2gr_b)
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_uint16x8, ushort,  __lsx_vpickve2gr_h)
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_int16x8,  short,   __lsx_vpickve2gr_h)
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_uint32x4, uint,    __lsx_vpickve2gr_w)
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_int32x4,  int,     __lsx_vpickve2gr_w)
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_uint64x2, uint64,  __lsx_vpickve2gr_d)
+OPENCV_HAL_IMPL_LSX_EXTRACT_N(v_int64x2,  int64,   __lsx_vpickve2gr_d)
+
+template<int i>
+inline float v_extract_n(const v_float32x4& v)
+{
+    union { uint iv; float fv; } d;
+    d.iv = __lsx_vpickve2gr_w(v.val, i);
+    return d.fv;
+}
+
+template<int i>
+inline double v_extract_n(const v_float64x2& v)
+{
+    union { uint64 iv; double dv; } d;
+    d.iv = __lsx_vpickve2gr_d(v.val, i);
+    return d.dv;
+}
+
+template<int i>
+inline v_uint32x4 v_broadcast_element(const v_uint32x4& a)
+{ return v_uint32x4(__lsx_vreplvei_w(a.val, i)); }
+
+template<int i>
+inline v_int32x4 v_broadcast_element(const v_int32x4& a)
+{ return v_int32x4(__lsx_vreplvei_w(a.val, i)); }
+
+template<int i>
+inline v_float32x4 v_broadcast_element(const v_float32x4& a)
+{ return v_float32x4((__m128)__lsx_vreplvei_w((__m128i)a.val, i)); }
+
+/////////////////// load deinterleave //////////////////////////////
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+
+    a.val = __lsx_vpickev_b(t1, t0);
+    b.val = __lsx_vpickod_b(t1, t0);
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    a.val = __lsx_vpickev_h(t1, t0);
+    b.val = __lsx_vpickod_h(t1, t0);
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    a.val = __lsx_vpickev_w(t1, t0);
+    b.val = __lsx_vpickod_w(t1, t0);
+}
+
+inline void v_load_deinterleave(const uint64* ptr, v_uint64x2& a, v_uint64x2& b)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    a.val = __lsx_vilvl_d(t1, t0);
+    b.val = __lsx_vilvh_d(t1, t0);
+}
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    __m128i t2 = __lsx_vld(ptr, 32);
+    const __m128i shuff0 = _v128_setr_b(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0);
+    const __m128i shuff1 = _v128_setr_b(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0);
+    __m128i a0 = __lsx_vbitsel_v(t0, t1, shuff0);
+    __m128i b0 = __lsx_vbitsel_v(t1, t0, shuff1);
+    __m128i c0 = __lsx_vbitsel_v(t1, t0, shuff0);
+    const __m128i shuff_a = _v128_setr_b(0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 17, 20, 23, 26, 29);
+    const __m128i shuff_b = _v128_setr_b(1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30);
+    const __m128i shuff_c = _v128_setr_b(2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 16, 19, 22, 25, 28, 31);
+
+    a.val = __lsx_vshuf_b(t2, a0, shuff_a);
+    b.val = __lsx_vshuf_b(t2, b0, shuff_b);
+    c.val = __lsx_vshuf_b(t2, c0, shuff_c);
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    __m128i t2 = __lsx_vld(ptr, 32);
+    const __m128i shuff0 = _v128_setr_h(0, 0, -1, 0, 0, -1, 0, 0);
+    const __m128i shuff1 = _v128_setr_h(0, -1, 0, 0, -1, 0, 0, -1);
+
+    __m128i a0 = __lsx_vbitsel_v(t0, t1, shuff1);
+    __m128i b0 = __lsx_vbitsel_v(t0, t1, shuff0);
+    __m128i c0 = __lsx_vbitsel_v(t1, t0, shuff0);
+
+    const __m128i shuff_a = _v128_setr_b(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 20, 21, 26, 27);
+    const __m128i shuff_b = _v128_setr_b(2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 16, 17, 22, 23, 28, 29);
+    const __m128i shuff_c = _v128_setr_b(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 18, 19, 24, 25, 30, 31);
+
+    a.val = __lsx_vshuf_b(t2, a0, shuff_a);
+    b.val = __lsx_vshuf_b(t2, b0, shuff_b);
+    c.val = __lsx_vshuf_b(t2, c0, shuff_c);
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    __m128i t2 = __lsx_vld(ptr, 32);
+
+    __m128i a0 = __lsx_vpermi_w(t1, t0, 0xAC);
+    __m128i b0 = __lsx_vpermi_w(t1, t0, 0xC5);
+    __m128i c0 = __lsx_vpermi_w(t1, t0, 0x5A);
+
+    a.val = __lsx_vextrins_w(a0, t2, 0x31);
+    b0    = __lsx_vshuf4i_w(b0, 0x38);
+    c0    = __lsx_vshuf4i_w(c0, 0x8);
+    b.val = __lsx_vextrins_w(b0, t2, 0x32);
+    c.val = __lsx_vpermi_w(t2, c0, 0xC4);
+}
+
+inline void v_load_deinterleave(const uint64* ptr, v_uint64x2& a, v_uint64x2& b, v_uint64x2& c)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    __m128i t2 = __lsx_vld(ptr, 32);
+
+    a.val = __lsx_vshuf4i_d(t0, t1, 0xC);
+    b.val = __lsx_vshuf4i_d(t0, t2, 0x9);
+    c.val = __lsx_vshuf4i_d(t1, t2, 0xC);
+}
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c, v_uint8x16& d)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    __m128i t2 = __lsx_vld(ptr, 32);
+    __m128i t3 = __lsx_vld(ptr, 48);
+
+    __m128i ac_lo = __lsx_vpickev_b(t1, t0);
+    __m128i bd_lo = __lsx_vpickod_b(t1, t0);
+    __m128i ac_hi = __lsx_vpickev_b(t3, t2);
+    __m128i bd_hi = __lsx_vpickod_b(t3, t2);
+
+    a.val = __lsx_vpickev_b(ac_hi, ac_lo);
+    c.val = __lsx_vpickod_b(ac_hi, ac_lo);
+    b.val = __lsx_vpickev_b(bd_hi, bd_lo);
+    d.val = __lsx_vpickod_b(bd_hi, bd_lo);
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c, v_uint16x8& d)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    __m128i t2 = __lsx_vld(ptr, 32);
+    __m128i t3 = __lsx_vld(ptr, 48);
+
+    __m128i ac_lo = __lsx_vpickev_h(t1, t0);
+    __m128i bd_lo = __lsx_vpickod_h(t1, t0);
+    __m128i ac_hi = __lsx_vpickev_h(t3, t2);
+    __m128i bd_hi = __lsx_vpickod_h(t3, t2);
+
+    a.val = __lsx_vpickev_h(ac_hi, ac_lo);
+    c.val = __lsx_vpickod_h(ac_hi, ac_lo);
+    b.val = __lsx_vpickev_h(bd_hi, bd_lo);
+    d.val = __lsx_vpickod_h(bd_hi, bd_lo);
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c, v_uint32x4& d)
+{
+    __m128i p0 = __lsx_vld(ptr, 0);
+    __m128i p1 = __lsx_vld(ptr, 16);
+    __m128i p2 = __lsx_vld(ptr, 32);
+    __m128i p3 = __lsx_vld(ptr, 48);
+
+    __m128i t0 = __lsx_vilvl_w(p1, p0);
+    __m128i t1 = __lsx_vilvl_w(p3, p2);
+    __m128i t2 = __lsx_vilvh_w(p1, p0);
+    __m128i t3 = __lsx_vilvh_w(p3, p2);
+    a.val = __lsx_vilvl_d(t1, t0);
+    b.val = __lsx_vilvh_d(t1, t0);
+    c.val = __lsx_vilvl_d(t3, t2);
+    d.val = __lsx_vilvh_d(t3, t2);
+}
+
+inline void v_load_deinterleave(const uint64* ptr, v_uint64x2& a, v_uint64x2& b, v_uint64x2& c, v_uint64x2& d)
+{
+    __m128i t0 = __lsx_vld(ptr, 0);
+    __m128i t1 = __lsx_vld(ptr, 16);
+    __m128i t2 = __lsx_vld(ptr, 32);
+    __m128i t3 = __lsx_vld(ptr, 48);
+
+    a.val = __lsx_vilvl_d(t2, t0);
+    b.val = __lsx_vilvh_d(t2, t0);
+    c.val = __lsx_vilvl_d(t3, t1);
+    d.val = __lsx_vilvh_d(t3, t1);
+}
+
+////////////////////////// store interleave ////////////////////////////////
+
+inline void v_store_interleave(uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = __lsx_vilvl_b(b.val, a.val);
+    __m128i v1 = __lsx_vilvh_b(b.val, a.val);
+
+    __lsx_vst(v0, ptr, 0);
+    __lsx_vst(v1, ptr, 16);
+}
+
+inline void v_store_interleave(ushort* ptr, const v_uint16x8& a, const v_uint16x8& b,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = __lsx_vilvl_h(b.val, a.val);
+    __m128i v1 = __lsx_vilvh_h(b.val, a.val);
+
+    __lsx_vst(v0, ptr, 0);
+    __lsx_vst(v1, ptr, 16);
+}
+
+inline void v_store_interleave(unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = __lsx_vilvl_w(b.val, a.val);
+    __m128i v1 = __lsx_vilvh_w(b.val, a.val);
+
+    __lsx_vst(v0, ptr, 0);
+    __lsx_vst(v1, ptr, 16);
+}
+
+inline void v_store_interleave(uint64* ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = __lsx_vilvl_d(b.val, a.val);
+    __m128i v1 = __lsx_vilvh_d(b.val, a.val);
+
+    __lsx_vst(v0, ptr, 0);
+    __lsx_vst(v1, ptr, 16);
+}
+
+inline void v_store_interleave(uchar* ptr, const v_uint8x16& a, const v_uint8x16& b, const v_uint8x16& c,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i ab_lo = __lsx_vilvl_b(b.val, a.val);
+    __m128i ab_hi = __lsx_vilvh_b(b.val, a.val);
+    __m128i v_c = c.val;
+    const __m128i shuff0 = _v128_setr_b(0, 1, 16, 2, 3, 17, 4, 5, 18, 6, 7, 19, 8, 9, 20, 10);
+    const __m128i shuff1 = _v128_setr_b(11, 21, 12, 13, 22, 14, 15, 23, 0, 0, 0, 0, 0, 0, 0, 0);
+    const __m128i shuff2 = _v128_setr_b(0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 24, 18, 19, 25, 20, 21);
+    const __m128i shuff3 = _v128_setr_b(26, 6, 7, 27, 8, 9, 28, 10, 11, 29, 12, 13, 30, 14, 15, 31);
+    __m128i abc = __lsx_vpermi_w(v_c, ab_hi, 0xE4);
+
+    __m128i dst0 = __lsx_vshuf_b(v_c, ab_lo, shuff0);
+    __m128i dst1 = __lsx_vshuf_b(v_c, ab_lo, shuff1);
+    __m128i dst2 = __lsx_vshuf_b(v_c, ab_hi, shuff3);
+    dst1 = __lsx_vshuf_b(abc, dst1, shuff2);
+
+    __lsx_vst(dst0, ptr, 0);
+    __lsx_vst(dst1, ptr, 16);
+    __lsx_vst(dst2, ptr, 32);
+}
+
+inline void v_store_interleave(ushort* ptr, const v_uint16x8& a, const v_uint16x8& b, const v_uint16x8& c,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i ab_lo = __lsx_vilvl_h(b.val, a.val);
+    __m128i ab_hi = __lsx_vilvh_h(b.val, a.val);
+    __m128i v_c = c.val;
+    const __m128i shuff0 = _v128_setr_b(0, 1, 2, 3, 16, 17, 4, 5, 6, 7, 18, 19, 8, 9, 10, 11);
+    const __m128i shuff1 = _v128_setr_b(20, 21, 12, 13, 14, 15, 22, 23, 0, 0, 0, 0, 0, 0, 0, 0);
+    const __m128i shuff2 = _v128_setr_b(0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19, 24, 25, 20, 21);
+    const __m128i shuff3 = _v128_setr_b(6, 7, 26, 27, 8, 9, 10, 11, 28, 29, 12, 13, 14, 15, 30, 31);
+    __m128i abc = __lsx_vpermi_w(v_c, ab_hi, 0xE4);
+
+    __m128i dst0 = __lsx_vshuf_b(v_c, ab_lo, shuff0);
+    __m128i dst1 = __lsx_vshuf_b(v_c, ab_lo, shuff1);
+    __m128i dst2 = __lsx_vshuf_b(v_c, ab_hi, shuff3);
+    dst1 = __lsx_vshuf_b(abc, dst1, shuff2);
+
+    __lsx_vst(dst0, ptr, 0);
+    __lsx_vst(dst1, ptr, 16);
+    __lsx_vst(dst2, ptr, 32);
+}
+
+inline void v_store_interleave(unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b, const v_uint32x4& c,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i v_c = c.val;
+    __m128i ab_lo = __lsx_vilvl_w(b.val, a.val);  //a0 b0 a1 b1
+    __m128i ab_hi = __lsx_vilvh_w(b.val, a.val);  //a2 b2 a3 b3
+    __m128i bc_od = __lsx_vpackod_w(v_c, b.val); // b1 c1 b3 c3
+
+    __m128i dst0 = __lsx_vshuf4i_w(ab_lo, 0xB4);  //a0 b0 b1 a1
+    __m128i dst1 = __lsx_vilvl_d(ab_hi, bc_od); //b1 c1 a2 b2
+    __m128i dst2 = __lsx_vpermi_w(bc_od, ab_hi, 0xE8); //a2, a3, b3, c3
+
+    dst0 = __lsx_vextrins_w(dst0, v_c, 0x20);
+    dst2 = __lsx_vextrins_w(dst2, v_c, 0x2);
+    __lsx_vst(dst0, ptr, 0);  //a0 b0 c0 a1
+    __lsx_vst(dst1, ptr, 16); //b1 c1 a2 b2
+    __lsx_vst(dst2, ptr, 32); //c2 a3 b3 c3
+}
+
+inline void v_store_interleave(uint64* ptr, const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i dst0 = __lsx_vilvl_d(b.val, a.val);
+    __m128i dst1 = __lsx_vpermi_w(a.val, c.val, 0xE4);
+    __m128i dst2 = __lsx_vilvh_d(c.val, b.val);
+
+    __lsx_vst(dst0, ptr, 0);
+    __lsx_vst(dst1, ptr, 16);
+    __lsx_vst(dst2, ptr, 32);
+}
+
+inline void v_store_interleave(uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                               const v_uint8x16& c, const v_uint8x16& d,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i ab_lo = __lsx_vilvl_b(b.val, a.val);
+    __m128i ab_hi = __lsx_vilvh_b(b.val, a.val);
+    __m128i cd_lo = __lsx_vilvl_b(d.val, c.val);
+    __m128i cd_hi = __lsx_vilvh_b(d.val, c.val);
+
+    __m128i dst0 = __lsx_vilvl_h(cd_lo, ab_lo);
+    __m128i dst1 = __lsx_vilvh_h(cd_lo, ab_lo);
+    __m128i dst2 = __lsx_vilvl_h(cd_hi, ab_hi);
+    __m128i dst3 = __lsx_vilvh_h(cd_hi, ab_hi);
+
+    __lsx_vst(dst0, ptr, 0);
+    __lsx_vst(dst1, ptr, 16);
+    __lsx_vst(dst2, ptr, 32);
+    __lsx_vst(dst3, ptr, 48);
+}
+
+inline void v_store_interleave(ushort* ptr, const v_uint16x8& a, const v_uint16x8& b,
+                               const v_uint16x8& c, const v_uint16x8& d,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i ab_lo = __lsx_vilvl_h(b.val, a.val);
+    __m128i ab_hi = __lsx_vilvh_h(b.val, a.val);
+    __m128i cd_lo = __lsx_vilvl_h(d.val, c.val);
+    __m128i cd_hi = __lsx_vilvh_h(d.val, c.val);
+
+    __m128i dst0 = __lsx_vilvl_w(cd_lo, ab_lo);
+    __m128i dst1 = __lsx_vilvh_w(cd_lo, ab_lo);
+    __m128i dst2 = __lsx_vilvl_w(cd_hi, ab_hi);
+    __m128i dst3 = __lsx_vilvh_w(cd_hi, ab_hi);
+
+    __lsx_vst(dst0, ptr, 0);
+    __lsx_vst(dst1, ptr, 16);
+    __lsx_vst(dst2, ptr, 32);
+    __lsx_vst(dst3, ptr, 48);
+}
+
+inline void v_store_interleave(unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                               const v_uint32x4& c, const v_uint32x4& d,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i ab_lo = __lsx_vilvl_w(b.val, a.val);
+    __m128i ab_hi = __lsx_vilvh_w(b.val, a.val);
+    __m128i cd_lo = __lsx_vilvl_w(d.val, c.val);
+    __m128i cd_hi = __lsx_vilvh_w(d.val, c.val);
+
+    __m128i dst0 = __lsx_vilvl_d(cd_lo, ab_lo);
+    __m128i dst1 = __lsx_vilvh_d(cd_lo, ab_lo);
+    __m128i dst2 = __lsx_vilvl_d(cd_hi, ab_hi);
+    __m128i dst3 = __lsx_vilvh_d(cd_hi, ab_hi);
+
+    __lsx_vst(dst0, ptr, 0);
+    __lsx_vst(dst1, ptr, 16);
+    __lsx_vst(dst2, ptr, 32);
+    __lsx_vst(dst3, ptr, 48);
+}
+
+inline void v_store_interleave(uint64* ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               const v_uint64x2& c, const v_uint64x2& d,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    __m128i dst0 = __lsx_vilvl_d(b.val, a.val);
+    __m128i dst2 = __lsx_vilvh_d(b.val, a.val);
+    __m128i dst1 = __lsx_vilvl_d(d.val, c.val);
+    __m128i dst3 = __lsx_vilvh_d(d.val, c.val);
+
+    __lsx_vst(dst0, ptr, 0);
+    __lsx_vst(dst1, ptr, 16);
+    __lsx_vst(dst2, ptr, 32);
+    __lsx_vst(dst3, ptr, 48);
+}
+
+#define OPENCV_HAL_IMPL_LSX_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1)  \
+inline void v_load_deinterleave(const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0)                        \
+{                                                                                                 \
+    _Tpvec1 a1, b1;                                                                               \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1);                                                \
+    a0 = v_reinterpret_as_##suffix0(a1);                                                          \
+    b0 = v_reinterpret_as_##suffix0(b1);                                                          \
+}                                                                                                 \
+inline void v_load_deinterleave(const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0)           \
+{                                                                                                 \
+    _Tpvec1 a1, b1, c1;                                                                           \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1);                                            \
+    a0 = v_reinterpret_as_##suffix0(a1);                                                          \
+    b0 = v_reinterpret_as_##suffix0(b1);                                                          \
+    c0 = v_reinterpret_as_##suffix0(c1);                                                          \
+}                                                                                                 \
+inline void v_load_deinterleave(const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0,                        \
+                                _Tpvec0& c0, _Tpvec0& d0)                                         \
+{                                                                                                 \
+    _Tpvec1 a1, b1, c1, d1;                                                                       \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1);                                        \
+    a0 = v_reinterpret_as_##suffix0(a1);                                                          \
+    b0 = v_reinterpret_as_##suffix0(b1);                                                          \
+    c0 = v_reinterpret_as_##suffix0(c1);                                                          \
+    d0 = v_reinterpret_as_##suffix0(d1);                                                          \
+}                                                                                                 \
+inline void v_store_interleave(_Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0,                   \
+                               hal::StoreMode /*mode*/=hal::STORE_UNALIGNED)                      \
+{                                                                                                 \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0);                                                  \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0);                                                  \
+    v_store_interleave((_Tp1*)ptr, a1, b1);                                                     \
+}                                                                                                 \
+inline void v_store_interleave(_Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, const _Tpvec0& c0,\
+                               hal::StoreMode /*mode*/=hal::STORE_UNALIGNED)                      \
+{                                                                                                 \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0);                                                  \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0);                                                  \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0);                                                  \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1);                                                 \
+}                                                                                                 \
+inline void v_store_interleave(_Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0,                   \
+                               const _Tpvec0& c0, const _Tpvec0& d0,                              \
+                               hal::StoreMode /*mode*/=hal::STORE_UNALIGNED)                      \
+{                                                                                                 \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0);                                                  \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0);                                                  \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0);                                                  \
+    _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0);                                                  \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1);                                             \
+}
+
+OPENCV_HAL_IMPL_LSX_LOADSTORE_INTERLEAVE(v_int8x16, schar, s8, v_uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_LSX_LOADSTORE_INTERLEAVE(v_int16x8, short, s16, v_uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_LSX_LOADSTORE_INTERLEAVE(v_int32x4, int, s32, v_uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_LSX_LOADSTORE_INTERLEAVE(v_float32x4, float, f32, v_uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_LSX_LOADSTORE_INTERLEAVE(v_int64x2, int64, s64, v_uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_LSX_LOADSTORE_INTERLEAVE(v_float64x2, double, f64, v_uint64x2, uint64, u64)
+
+//
+// FP16
+//
+
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+#if CV_FP16
+    return v_float32x4(__lsx_vfcvtl_s_h((__m128)__lsx_vld(ptr, 0)));
+#else
+    float CV_DECL_ALIGNED(32) buf[4];
+    for (int i = 0; i < 4; i++)
+        buf[i] = (float)ptr[i];
+    return v_float32x4((__m128)__lsx_vld(buf, 0));
+#endif
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& a)
+{
+#if CV_FP16
+    __m128i res = (__m218i)__lsx_vfcvt_h_s(a.val, a.val);
+    __lsx_vstelm_d(res, ptr, 0, 0);
+#else
+    float CV_DECL_ALIGNED(32) buf[4];
+    v_store_aligned(buf, a);
+    for (int i = 0; i < 4; i++)
+        ptr[i] = hfloat(buf[i]);
+#endif
+}
+
+//
+// end of FP16
+//
+
+inline void v_cleanup() {}
+
+#include "intrin_math.hpp"
+inline v_float32x4 v_exp(const v_float32x4& x) { return v_exp_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_log(const v_float32x4& x) { return v_log_default_32f<v_float32x4, v_int32x4>(x); }
+inline void v_sincos(const v_float32x4& x, v_float32x4& s, v_float32x4& c) { v_sincos_default_32f<v_float32x4, v_int32x4>(x, s, c); }
+inline v_float32x4 v_sin(const v_float32x4& x) { return v_sin_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_cos(const v_float32x4& x) { return v_cos_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_erf(const v_float32x4& x) { return v_erf_default_32f<v_float32x4, v_int32x4>(x); }
+
+inline v_float64x2 v_exp(const v_float64x2& x) { return v_exp_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_log(const v_float64x2& x) { return v_log_default_64f<v_float64x2, v_int64x2>(x); }
+inline void v_sincos(const v_float64x2& x, v_float64x2& s, v_float64x2& c) { v_sincos_default_64f<v_float64x2, v_int64x2>(x, s, c); }
+inline v_float64x2 v_sin(const v_float64x2& x) { return v_sin_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_cos(const v_float64x2& x) { return v_cos_default_64f<v_float64x2, v_int64x2>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+} // cv::
+
+#endif // OPENCV_HAL_INTRIN_LSX_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_math.hpp

@@ -0,0 +1,687 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+
+/* Universal Intrinsics implementation of sin, cos, exp and log
+
+   Inspired by Intel Approximate Math library, and based on the
+   corresponding algorithms of the cephes math library
+*/
+
+/* Copyright (C) 2010,2011  RJVB - extensions */
+/* Copyright (C) 2011  Julien Pommier
+
+  This software is provided 'as-is', without any express or implied
+  warranty.  In no event will the authors be held liable for any damages
+  arising from the use of this software.
+
+  Permission is granted to anyone to use this software for any purpose,
+  including commercial applications, and to alter it and redistribute it
+  freely, subject to the following restrictions:
+
+  1. The origin of this software must not be misrepresented; you must not
+     claim that you wrote the original software. If you use this software
+     in a product, an acknowledgment in the product documentation would be
+     appreciated but is not required.
+  2. Altered source versions must be plainly marked as such, and must not be
+     misrepresented as being the original software.
+  3. This notice may not be removed or altered from any source distribution.
+
+  (this is the zlib license)
+*/
+#ifndef OPENCV_HAL_INTRIN_MATH_HPP
+#define OPENCV_HAL_INTRIN_MATH_HPP
+
+//! @name Exponential
+//! @{
+// Implementation is the same as float32 vector.
+template<typename _TpVec16F, typename _TpVec16S>
+inline _TpVec16F v_exp_default_16f(const _TpVec16F &x) {
+    const _TpVec16F _vexp_lo_f16 = v_setall_<_TpVec16F>(-10.7421875f);
+    const _TpVec16F _vexp_hi_f16 = v_setall_<_TpVec16F>(11.f);
+    const _TpVec16F _vexp_half_fp16 = v_setall_<_TpVec16F>(0.5f);
+    const _TpVec16F _vexp_one_fp16 = v_setall_<_TpVec16F>(1.f);
+    const _TpVec16F _vexp_LOG2EF_f16 = v_setall_<_TpVec16F>(1.44269504088896341f);
+    const _TpVec16F _vexp_C1_f16 = v_setall_<_TpVec16F>(-6.93359375E-1f);
+    const _TpVec16F _vexp_C2_f16 = v_setall_<_TpVec16F>(2.12194440E-4f);
+    const _TpVec16F _vexp_p0_f16 = v_setall_<_TpVec16F>(1.9875691500E-4f);
+    const _TpVec16F _vexp_p1_f16 = v_setall_<_TpVec16F>(1.3981999507E-3f);
+    const _TpVec16F _vexp_p2_f16 = v_setall_<_TpVec16F>(8.3334519073E-3f);
+    const _TpVec16F _vexp_p3_f16 = v_setall_<_TpVec16F>(4.1665795894E-2f);
+    const _TpVec16F _vexp_p4_f16 = v_setall_<_TpVec16F>(1.6666665459E-1f);
+    const _TpVec16F _vexp_p5_f16 = v_setall_<_TpVec16F>(5.0000001201E-1f);
+
+    _TpVec16F _vexp_, _vexp_x, _vexp_y, _vexp_xx;
+    _TpVec16S _vexp_mm;
+    const _TpVec16S _vexp_bias_s16 = v_setall_<_TpVec16S>((short)0xf);
+
+    // compute exponential of x
+    _vexp_x = v_max(x, _vexp_lo_f16);
+    _vexp_x = v_min(_vexp_x, _vexp_hi_f16);
+
+    _vexp_ = v_fma(_vexp_x, _vexp_LOG2EF_f16, _vexp_half_fp16);
+    _vexp_mm = v_floor(_vexp_);
+    _vexp_ = v_cvt_f16(_vexp_mm);
+    _vexp_mm = v_add(_vexp_mm, _vexp_bias_s16);
+    _vexp_mm = v_shl(_vexp_mm, 10);
+
+    _vexp_x = v_fma(_vexp_, _vexp_C1_f16, _vexp_x);
+    _vexp_x = v_fma(_vexp_, _vexp_C2_f16, _vexp_x);
+    _vexp_xx = v_mul(_vexp_x, _vexp_x);
+
+    _vexp_y = v_fma(_vexp_x, _vexp_p0_f16, _vexp_p1_f16);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p2_f16);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p3_f16);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p4_f16);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p5_f16);
+
+    _vexp_y = v_fma(_vexp_y, _vexp_xx, _vexp_x);
+    _vexp_y = v_add(_vexp_y, _vexp_one_fp16);
+    _vexp_y = v_mul(_vexp_y, v_reinterpret_as_f16(_vexp_mm));
+
+    // exp(NAN) -> NAN
+    _TpVec16F mask_not_nan = v_not_nan(x);
+    return v_select(mask_not_nan, _vexp_y, v_reinterpret_as_f16(v_setall_<_TpVec16S>((short)0x7e00)));
+}
+
+template<typename _TpVec32F, typename _TpVec32S>
+inline _TpVec32F v_exp_default_32f(const _TpVec32F &x) {
+    const _TpVec32F _vexp_lo_f32 = v_setall_<_TpVec32F>(-88.3762626647949f);
+    const _TpVec32F _vexp_hi_f32 = v_setall_<_TpVec32F>(89.f);
+    const _TpVec32F _vexp_half_fp32 = v_setall_<_TpVec32F>(0.5f);
+    const _TpVec32F _vexp_one_fp32 = v_setall_<_TpVec32F>(1.f);
+    const _TpVec32F _vexp_LOG2EF_f32 = v_setall_<_TpVec32F>(1.44269504088896341f);
+    const _TpVec32F _vexp_C1_f32 = v_setall_<_TpVec32F>(-6.93359375E-1f);
+    const _TpVec32F _vexp_C2_f32 = v_setall_<_TpVec32F>(2.12194440E-4f);
+    const _TpVec32F _vexp_p0_f32 = v_setall_<_TpVec32F>(1.9875691500E-4f);
+    const _TpVec32F _vexp_p1_f32 = v_setall_<_TpVec32F>(1.3981999507E-3f);
+    const _TpVec32F _vexp_p2_f32 = v_setall_<_TpVec32F>(8.3334519073E-3f);
+    const _TpVec32F _vexp_p3_f32 = v_setall_<_TpVec32F>(4.1665795894E-2f);
+    const _TpVec32F _vexp_p4_f32 = v_setall_<_TpVec32F>(1.6666665459E-1f);
+    const _TpVec32F _vexp_p5_f32 = v_setall_<_TpVec32F>(5.0000001201E-1f);
+
+    _TpVec32F _vexp_, _vexp_x, _vexp_y, _vexp_xx;
+    _TpVec32S _vexp_mm;
+    const _TpVec32S _vexp_bias_s32 = v_setall_<_TpVec32S>((int)0x7f);
+
+    // compute exponential of x
+    _vexp_x = v_max(x, _vexp_lo_f32);
+    _vexp_x = v_min(_vexp_x, _vexp_hi_f32);
+
+    _vexp_ = v_fma(_vexp_x, _vexp_LOG2EF_f32, _vexp_half_fp32);
+    _vexp_mm = v_floor(_vexp_);
+    _vexp_ = v_cvt_f32(_vexp_mm);
+    _vexp_mm = v_add(_vexp_mm, _vexp_bias_s32);
+    _vexp_mm = v_shl(_vexp_mm, 23);
+
+    _vexp_x = v_fma(_vexp_, _vexp_C1_f32, _vexp_x);
+    _vexp_x = v_fma(_vexp_, _vexp_C2_f32, _vexp_x);
+    _vexp_xx = v_mul(_vexp_x, _vexp_x);
+
+    _vexp_y = v_fma(_vexp_x, _vexp_p0_f32, _vexp_p1_f32);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p2_f32);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p3_f32);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p4_f32);
+    _vexp_y = v_fma(_vexp_y, _vexp_x, _vexp_p5_f32);
+
+    _vexp_y = v_fma(_vexp_y, _vexp_xx, _vexp_x);
+    _vexp_y = v_add(_vexp_y, _vexp_one_fp32);
+    _vexp_y = v_mul(_vexp_y, v_reinterpret_as_f32(_vexp_mm));
+
+    // exp(NAN) -> NAN
+    _TpVec32F mask_not_nan = v_not_nan(x);
+    return v_select(mask_not_nan, _vexp_y, v_reinterpret_as_f32(v_setall_<_TpVec32S>((int)0x7fc00000)));
+}
+
+template<typename _TpVec64F, typename _TpVec64S>
+inline _TpVec64F v_exp_default_64f(const _TpVec64F &x) {
+    const _TpVec64F _vexp_lo_f64 = v_setall_<_TpVec64F>(-709.43613930310391424428);
+    const _TpVec64F _vexp_hi_f64 = v_setall_<_TpVec64F>(710.);
+    const _TpVec64F _vexp_half_f64 = v_setall_<_TpVec64F>(0.5);
+    const _TpVec64F _vexp_one_f64 = v_setall_<_TpVec64F>(1.0);
+    const _TpVec64F _vexp_two_f64 = v_setall_<_TpVec64F>(2.0);
+    const _TpVec64F _vexp_LOG2EF_f64 = v_setall_<_TpVec64F>(1.44269504088896340736);
+    const _TpVec64F _vexp_C1_f64 = v_setall_<_TpVec64F>(-6.93145751953125E-1);
+    const _TpVec64F _vexp_C2_f64 = v_setall_<_TpVec64F>(-1.42860682030941723212E-6);
+    const _TpVec64F _vexp_p0_f64 = v_setall_<_TpVec64F>(1.26177193074810590878E-4);
+    const _TpVec64F _vexp_p1_f64 = v_setall_<_TpVec64F>(3.02994407707441961300E-2);
+    const _TpVec64F _vexp_p2_f64 = v_setall_<_TpVec64F>(9.99999999999999999910E-1);
+    const _TpVec64F _vexp_q0_f64 = v_setall_<_TpVec64F>(3.00198505138664455042E-6);
+    const _TpVec64F _vexp_q1_f64 = v_setall_<_TpVec64F>(2.52448340349684104192E-3);
+    const _TpVec64F _vexp_q2_f64 = v_setall_<_TpVec64F>(2.27265548208155028766E-1);
+    const _TpVec64F _vexp_q3_f64 = v_setall_<_TpVec64F>(2.00000000000000000009E0);
+
+    _TpVec64F _vexp_, _vexp_x, _vexp_y, _vexp_z, _vexp_xx;
+    _TpVec64S _vexp_mm;
+    const _TpVec64S _vexp_bias_s64 = v_setall_<_TpVec64S>((int64)0x3ff);
+
+    // compute exponential of x
+    _vexp_x = v_max(x, _vexp_lo_f64);
+    _vexp_x = v_min(_vexp_x, _vexp_hi_f64);
+
+    _vexp_ = v_fma(_vexp_x, _vexp_LOG2EF_f64, _vexp_half_f64);
+    _vexp_mm = v_expand_low(v_floor(_vexp_));
+    _vexp_ = v_cvt_f64(_vexp_mm);
+    _vexp_mm = v_add(_vexp_mm, _vexp_bias_s64);
+    _vexp_mm = v_shl(_vexp_mm, 52);
+
+    _vexp_x = v_fma(_vexp_, _vexp_C1_f64, _vexp_x);
+    _vexp_x = v_fma(_vexp_, _vexp_C2_f64, _vexp_x);
+    _vexp_xx = v_mul(_vexp_x, _vexp_x);
+
+    _vexp_y = v_fma(_vexp_xx, _vexp_p0_f64, _vexp_p1_f64);
+    _vexp_y = v_fma(_vexp_y, _vexp_xx, _vexp_p2_f64);
+    _vexp_y = v_mul(_vexp_y, _vexp_x);
+
+    _vexp_z = v_fma(_vexp_xx, _vexp_q0_f64, _vexp_q1_f64);
+    _vexp_z = v_fma(_vexp_xx, _vexp_z, _vexp_q2_f64);
+    _vexp_z = v_fma(_vexp_xx, _vexp_z, _vexp_q3_f64);
+
+    _vexp_z = v_div(_vexp_y, v_sub(_vexp_z, _vexp_y));
+    _vexp_z = v_fma(_vexp_two_f64, _vexp_z, _vexp_one_f64);
+    _vexp_z = v_mul(_vexp_z, v_reinterpret_as_f64(_vexp_mm));
+
+    // exp(NAN) -> NAN
+    _TpVec64F mask_not_nan = v_not_nan(x);
+    return v_select(mask_not_nan, _vexp_z, v_reinterpret_as_f64(v_setall_<_TpVec64S>((int64)0x7FF8000000000000)));
+}
+//! @}
+
+//! @name Natural Logarithm
+//! @{
+template<typename _TpVec16F, typename _TpVec16S>
+inline _TpVec16F v_log_default_16f(const _TpVec16F &x) {
+    const _TpVec16F _vlog_one_fp16 = v_setall_<_TpVec16F>(1.0f);
+    const _TpVec16F _vlog_SQRTHF_fp16 = v_setall_<_TpVec16F>(0.707106781186547524f);
+    const _TpVec16F _vlog_q1_fp16 = v_setall_<_TpVec16F>(-2.12194440E-4f);
+    const _TpVec16F _vlog_q2_fp16 = v_setall_<_TpVec16F>(0.693359375f);
+    const _TpVec16F _vlog_p0_fp16 = v_setall_<_TpVec16F>(7.0376836292E-2f);
+    const _TpVec16F _vlog_p1_fp16 = v_setall_<_TpVec16F>(-1.1514610310E-1f);
+    const _TpVec16F _vlog_p2_fp16 = v_setall_<_TpVec16F>(1.1676998740E-1f);
+    const _TpVec16F _vlog_p3_fp16 = v_setall_<_TpVec16F>(-1.2420140846E-1f);
+    const _TpVec16F _vlog_p4_fp16 = v_setall_<_TpVec16F>(1.4249322787E-1f);
+    const _TpVec16F _vlog_p5_fp16 = v_setall_<_TpVec16F>(-1.6668057665E-1f);
+    const _TpVec16F _vlog_p6_fp16 = v_setall_<_TpVec16F>(2.0000714765E-1f);
+    const _TpVec16F _vlog_p7_fp16 = v_setall_<_TpVec16F>(-2.4999993993E-1f);
+    const _TpVec16F _vlog_p8_fp16 = v_setall_<_TpVec16F>(3.3333331174E-1f);
+
+    _TpVec16F _vlog_x, _vlog_e, _vlog_y, _vlog_z, _vlog_tmp;
+    _TpVec16S _vlog_ux, _vlog_emm0;
+    const _TpVec16S _vlog_inv_mant_mask_s16 = v_setall_<_TpVec16S>((short)~0x7c00);
+
+    _vlog_ux = v_reinterpret_as_s16(x);
+    _vlog_emm0 = v_shr(_vlog_ux, 10);
+
+    _vlog_ux = v_and(_vlog_ux, _vlog_inv_mant_mask_s16);
+    _vlog_ux = v_or(_vlog_ux, v_reinterpret_as_s16(v_setall_<_TpVec16F>(0.5f)));
+    _vlog_x = v_reinterpret_as_f16(_vlog_ux);
+
+    _vlog_emm0 = v_sub(_vlog_emm0, v_setall_<_TpVec16S>((short)0xf));
+    _vlog_e = v_cvt_f16(_vlog_emm0);
+
+    _vlog_e = v_add(_vlog_e, _vlog_one_fp16);
+
+    _TpVec16F _vlog_mask = v_lt(_vlog_x, _vlog_SQRTHF_fp16);
+    _vlog_tmp = v_and(_vlog_x, _vlog_mask);
+    _vlog_x = v_sub(_vlog_x, _vlog_one_fp16);
+    _vlog_e = v_sub(_vlog_e, v_and(_vlog_one_fp16, _vlog_mask));
+    _vlog_x = v_add(_vlog_x, _vlog_tmp);
+
+    _vlog_z = v_mul(_vlog_x, _vlog_x);
+
+    _vlog_y = v_fma(_vlog_p0_fp16, _vlog_x, _vlog_p1_fp16);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p2_fp16);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p3_fp16);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p4_fp16);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p5_fp16);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p6_fp16);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p7_fp16);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p8_fp16);
+    _vlog_y = v_mul(_vlog_y, _vlog_x);
+    _vlog_y = v_mul(_vlog_y, _vlog_z);
+
+    _vlog_y = v_fma(_vlog_e, _vlog_q1_fp16, _vlog_y);
+
+    _vlog_y = v_sub(_vlog_y, v_mul(_vlog_z, v_setall_<_TpVec16F>(0.5f)));
+
+    _vlog_x = v_add(_vlog_x, _vlog_y);
+    _vlog_x = v_fma(_vlog_e, _vlog_q2_fp16, _vlog_x);
+    // log(0) -> -INF
+    _TpVec16F mask_zero = v_eq(x, v_setzero_<_TpVec16F>());
+    _vlog_x = v_select(mask_zero, v_reinterpret_as_f16(v_setall_<_TpVec16S>((short)0xfc00)), _vlog_x);
+    // log(NEG), log(NAN) -> NAN
+    _TpVec16F mask_not_nan = v_ge(x, v_setzero_<_TpVec16F>());
+    _vlog_x = v_select(mask_not_nan, _vlog_x, v_reinterpret_as_f16(v_setall_<_TpVec16S>((short)0x7e00)));
+    // log(INF) -> INF
+    _TpVec16F mask_inf = v_eq(x, v_reinterpret_as_f16(v_setall_<_TpVec16S>((short)0x7c00)));
+    _vlog_x = v_select(mask_inf, x, _vlog_x);
+    return _vlog_x;
+}
+
+template<typename _TpVec32F, typename _TpVec32S>
+inline _TpVec32F v_log_default_32f(const _TpVec32F &x) {
+    const _TpVec32F _vlog_one_fp32 = v_setall_<_TpVec32F>(1.0f);
+    const _TpVec32F _vlog_SQRTHF_fp32 = v_setall_<_TpVec32F>(0.707106781186547524f);
+    const _TpVec32F _vlog_q1_fp32 = v_setall_<_TpVec32F>(-2.12194440E-4f);
+    const _TpVec32F _vlog_q2_fp32 = v_setall_<_TpVec32F>(0.693359375f);
+    const _TpVec32F _vlog_p0_fp32 = v_setall_<_TpVec32F>(7.0376836292E-2f);
+    const _TpVec32F _vlog_p1_fp32 = v_setall_<_TpVec32F>(-1.1514610310E-1f);
+    const _TpVec32F _vlog_p2_fp32 = v_setall_<_TpVec32F>(1.1676998740E-1f);
+    const _TpVec32F _vlog_p3_fp32 = v_setall_<_TpVec32F>(-1.2420140846E-1f);
+    const _TpVec32F _vlog_p4_fp32 = v_setall_<_TpVec32F>(1.4249322787E-1f);
+    const _TpVec32F _vlog_p5_fp32 = v_setall_<_TpVec32F>(-1.6668057665E-1f);
+    const _TpVec32F _vlog_p6_fp32 = v_setall_<_TpVec32F>(2.0000714765E-1f);
+    const _TpVec32F _vlog_p7_fp32 = v_setall_<_TpVec32F>(-2.4999993993E-1f);
+    const _TpVec32F _vlog_p8_fp32 = v_setall_<_TpVec32F>(3.3333331174E-1f);
+
+    _TpVec32F _vlog_x, _vlog_e, _vlog_y, _vlog_z, _vlog_tmp;
+    _TpVec32S _vlog_ux, _vlog_emm0;
+    const _TpVec32S _vlog_inv_mant_mask_s32 = v_setall_<_TpVec32S>((int)~0x7f800000);
+
+    _vlog_ux = v_reinterpret_as_s32(x);
+    _vlog_emm0 = v_shr(_vlog_ux, 23);
+
+    _vlog_ux = v_and(_vlog_ux, _vlog_inv_mant_mask_s32);
+    _vlog_ux = v_or(_vlog_ux, v_reinterpret_as_s32(v_setall_<_TpVec32F>(0.5f)));
+    _vlog_x = v_reinterpret_as_f32(_vlog_ux);
+
+    _vlog_emm0 = v_sub(_vlog_emm0, v_setall_<_TpVec32S>((int)0x7f));
+    _vlog_e = v_cvt_f32(_vlog_emm0);
+
+    _vlog_e = v_add(_vlog_e, _vlog_one_fp32);
+
+    _TpVec32F _vlog_mask = v_lt(_vlog_x, _vlog_SQRTHF_fp32);
+    _vlog_tmp = v_and(_vlog_x, _vlog_mask);
+    _vlog_x = v_sub(_vlog_x, _vlog_one_fp32);
+    _vlog_e = v_sub(_vlog_e, v_and(_vlog_one_fp32, _vlog_mask));
+    _vlog_x = v_add(_vlog_x, _vlog_tmp);
+
+    _vlog_z = v_mul(_vlog_x, _vlog_x);
+
+    _vlog_y = v_fma(_vlog_p0_fp32, _vlog_x, _vlog_p1_fp32);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p2_fp32);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p3_fp32);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p4_fp32);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p5_fp32);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p6_fp32);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p7_fp32);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p8_fp32);
+    _vlog_y = v_mul(_vlog_y, _vlog_x);
+    _vlog_y = v_mul(_vlog_y, _vlog_z);
+
+    _vlog_y = v_fma(_vlog_e, _vlog_q1_fp32, _vlog_y);
+
+    _vlog_y = v_sub(_vlog_y, v_mul(_vlog_z, v_setall_<_TpVec32F>(0.5f)));
+
+    _vlog_x = v_add(_vlog_x, _vlog_y);
+    _vlog_x = v_fma(_vlog_e, _vlog_q2_fp32, _vlog_x);
+    // log(0) -> -INF
+    _TpVec32F mask_zero = v_eq(x, v_setzero_<_TpVec32F>());
+    _vlog_x = v_select(mask_zero, v_reinterpret_as_f32(v_setall_<_TpVec32S>((int)0xff800000)), _vlog_x);
+    // log(NEG), log(NAN) -> NAN
+    _TpVec32F mask_not_nan = v_ge(x, v_setzero_<_TpVec32F>());
+    _vlog_x = v_select(mask_not_nan, _vlog_x, v_reinterpret_as_f32(v_setall_<_TpVec32S>((int)0x7fc00000)));
+    // log(INF) -> INF
+    _TpVec32F mask_inf = v_eq(x, v_reinterpret_as_f32(v_setall_<_TpVec32S>((int)0x7f800000)));
+    _vlog_x = v_select(mask_inf, x, _vlog_x);
+    return _vlog_x;
+}
+
+template<typename _TpVec64F, typename _TpVec64S>
+inline _TpVec64F v_log_default_64f(const _TpVec64F &x) {
+    const _TpVec64F _vlog_one_fp64 = v_setall_<_TpVec64F>(1.0);
+    const _TpVec64F _vlog_SQRTHF_fp64 = v_setall_<_TpVec64F>(0.7071067811865475244);
+    const _TpVec64F _vlog_p0_fp64 = v_setall_<_TpVec64F>(1.01875663804580931796E-4);
+    const _TpVec64F _vlog_p1_fp64 = v_setall_<_TpVec64F>(4.97494994976747001425E-1);
+    const _TpVec64F _vlog_p2_fp64 = v_setall_<_TpVec64F>(4.70579119878881725854);
+    const _TpVec64F _vlog_p3_fp64 = v_setall_<_TpVec64F>(1.44989225341610930846E1);
+    const _TpVec64F _vlog_p4_fp64 = v_setall_<_TpVec64F>(1.79368678507819816313E1);
+    const _TpVec64F _vlog_p5_fp64 = v_setall_<_TpVec64F>(7.70838733755885391666);
+    const _TpVec64F _vlog_q0_fp64 = v_setall_<_TpVec64F>(1.12873587189167450590E1);
+    const _TpVec64F _vlog_q1_fp64 = v_setall_<_TpVec64F>(4.52279145837532221105E1);
+    const _TpVec64F _vlog_q2_fp64 = v_setall_<_TpVec64F>(8.29875266912776603211E1);
+    const _TpVec64F _vlog_q3_fp64 = v_setall_<_TpVec64F>(7.11544750618563894466E1);
+    const _TpVec64F _vlog_q4_fp64 = v_setall_<_TpVec64F>(2.31251620126765340583E1);
+
+    const _TpVec64F _vlog_C0_fp64 = v_setall_<_TpVec64F>(2.121944400546905827679e-4);
+    const _TpVec64F _vlog_C1_fp64 = v_setall_<_TpVec64F>(0.693359375);
+
+    _TpVec64F _vlog_x, _vlog_e, _vlog_y, _vlog_z, _vlog_tmp, _vlog_xx;
+    _TpVec64S _vlog_ux, _vlog_emm0;
+    const _TpVec64S _vlog_inv_mant_mask_s64 = v_setall_<_TpVec64S>((int64)~0x7ff0000000000000);
+
+    _vlog_ux = v_reinterpret_as_s64(x);
+    _vlog_emm0 = v_shr(_vlog_ux, 52);
+
+    _vlog_ux = v_and(_vlog_ux, _vlog_inv_mant_mask_s64);
+    _vlog_ux = v_or(_vlog_ux, v_reinterpret_as_s64(v_setall_<_TpVec64F>(0.5)));
+    _vlog_x = v_reinterpret_as_f64(_vlog_ux);
+
+    _vlog_emm0 = v_sub(_vlog_emm0, v_setall_<_TpVec64S>((int64)0x3ff));
+    _vlog_e = v_cvt_f64(_vlog_emm0);
+
+    _vlog_e = v_add(_vlog_e, _vlog_one_fp64);
+
+    _TpVec64F _vlog_mask = v_lt(_vlog_x, _vlog_SQRTHF_fp64);
+    _vlog_tmp = v_and(_vlog_x, _vlog_mask);
+    _vlog_x = v_sub(_vlog_x, _vlog_one_fp64);
+    _vlog_e = v_sub(_vlog_e, v_and(_vlog_one_fp64, _vlog_mask));
+    _vlog_x = v_add(_vlog_x, _vlog_tmp);
+
+    _vlog_xx = v_mul(_vlog_x, _vlog_x);
+
+    _vlog_y = v_fma(_vlog_p0_fp64, _vlog_x, _vlog_p1_fp64);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p2_fp64);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p3_fp64);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p4_fp64);
+    _vlog_y = v_fma(_vlog_y, _vlog_x, _vlog_p5_fp64);
+    _vlog_y = v_mul(_vlog_y, _vlog_x);
+    _vlog_y = v_mul(_vlog_y, _vlog_xx);
+
+    _vlog_z = v_add(_vlog_x, _vlog_q0_fp64);
+    _vlog_z = v_fma(_vlog_z, _vlog_x, _vlog_q1_fp64);
+    _vlog_z = v_fma(_vlog_z, _vlog_x, _vlog_q2_fp64);
+    _vlog_z = v_fma(_vlog_z, _vlog_x, _vlog_q3_fp64);
+    _vlog_z = v_fma(_vlog_z, _vlog_x, _vlog_q4_fp64);
+
+    _vlog_z = v_div(_vlog_y, _vlog_z);
+    _vlog_z = v_sub(_vlog_z, v_mul(_vlog_e, _vlog_C0_fp64));
+    _vlog_z = v_sub(_vlog_z, v_mul(_vlog_xx, v_setall_<_TpVec64F>(0.5)));
+
+    _vlog_z = v_add(_vlog_z, _vlog_x);
+    _vlog_z = v_fma(_vlog_e, _vlog_C1_fp64, _vlog_z);
+
+    // log(0) -> -INF
+    _TpVec64F mask_zero = v_eq(x, v_setzero_<_TpVec64F>());
+    _vlog_z = v_select(mask_zero, v_reinterpret_as_f64(v_setall_<_TpVec64S>((int64)0xfff0000000000000)), _vlog_z);
+    // log(NEG), log(NAN) -> NAN
+    _TpVec64F mask_not_nan = v_ge(x, v_setzero_<_TpVec64F>());
+    _vlog_z = v_select(mask_not_nan, _vlog_z, v_reinterpret_as_f64(v_setall_<_TpVec64S>((int64)0x7ff8000000000000)));
+    // log(INF) -> INF
+    _TpVec64F mask_inf = v_eq(x, v_reinterpret_as_f64(v_setall_<_TpVec64S>((int64)0x7ff0000000000000)));
+    _vlog_z = v_select(mask_inf, x, _vlog_z);
+    return _vlog_z;
+}
+//! @}
+
+//! @name Sine and Cosine
+//! @{
+template<typename _TpVec16F, typename _TpVec16S>
+inline void v_sincos_default_16f(const _TpVec16F &x, _TpVec16F &ysin, _TpVec16F &ycos) {
+    const _TpVec16F v_cephes_FOPI = v_setall_<_TpVec16F>(hfloat(1.27323954473516f)); // 4 / M_PI
+    const _TpVec16F v_minus_DP1 = v_setall_<_TpVec16F>(hfloat(-0.78515625f));
+    const _TpVec16F v_minus_DP2 = v_setall_<_TpVec16F>(hfloat(-2.4187564849853515625E-4f));
+    const _TpVec16F v_minus_DP3 = v_setall_<_TpVec16F>(hfloat(-3.77489497744594108E-8f));
+    const _TpVec16F v_sincof_p0 = v_setall_<_TpVec16F>(hfloat(-1.9515295891E-4f));
+    const _TpVec16F v_sincof_p1 = v_setall_<_TpVec16F>(hfloat(8.3321608736E-3f));
+    const _TpVec16F v_sincof_p2 = v_setall_<_TpVec16F>(hfloat(-1.6666654611E-1f));
+    const _TpVec16F v_coscof_p0 = v_setall_<_TpVec16F>(hfloat(2.443315711809948E-5f));
+    const _TpVec16F v_coscof_p1 = v_setall_<_TpVec16F>(hfloat(-1.388731625493765E-3f));
+    const _TpVec16F v_coscof_p2 = v_setall_<_TpVec16F>(hfloat(4.166664568298827E-2f));
+    const _TpVec16F v_nan = v_reinterpret_as_f16(v_setall_<_TpVec16S>((short)0x7e00));
+    const _TpVec16F v_neg_zero = v_setall_<_TpVec16F>(hfloat(-0.f));
+
+    _TpVec16F _vx, _vy, sign_mask_sin, sign_mask_cos;
+    _TpVec16S emm2;
+
+    sign_mask_sin = v_lt(x, v_setzero_<_TpVec16F>());
+    _vx = v_abs(x);
+    _vy = v_mul(_vx, v_cephes_FOPI);
+
+    emm2 = v_trunc(_vy);
+    emm2 = v_add(emm2, v_setall_<_TpVec16S>((short)1));
+    emm2 = v_and(emm2, v_setall_<_TpVec16S>((short)~1));
+    _vy = v_cvt_f16(emm2);
+
+    _TpVec16F poly_mask = v_reinterpret_as_f16(v_eq(v_and(emm2, v_setall_<_TpVec16S>((short)2)), v_setall_<_TpVec16S>((short)0)));
+
+    _vx = v_fma(_vy, v_minus_DP1, _vx);
+    _vx = v_fma(_vy, v_minus_DP2, _vx);
+    _vx = v_fma(_vy, v_minus_DP3, _vx);
+
+    sign_mask_sin = v_xor(sign_mask_sin, v_reinterpret_as_f16(v_eq(v_and(emm2, v_setall_<_TpVec16S>((short)4)), v_setall_<_TpVec16S>((short)0))));
+    sign_mask_cos = v_reinterpret_as_f16(v_eq(v_and(v_sub(emm2, v_setall_<_TpVec16S>((short)2)), v_setall_<_TpVec16S>((short)4)), v_setall_<_TpVec16S>((short)0)));
+
+    _TpVec16F _vxx = v_mul(_vx, _vx);
+    _TpVec16F y1, y2;
+
+    y1 = v_fma(v_coscof_p0, _vxx, v_coscof_p1);
+    y1 = v_fma(y1, _vxx, v_coscof_p2);
+    y1 = v_fma(y1, _vxx, v_setall_<_TpVec16F>(hfloat(-0.5f)));
+    y1 = v_fma(y1, _vxx, v_setall_<_TpVec16F>(hfloat(1.f)));
+
+    y2 = v_fma(v_sincof_p0, _vxx, v_sincof_p1);
+    y2 = v_fma(y2, _vxx, v_sincof_p2);
+    y2 = v_mul(y2, _vxx);
+    y2 = v_fma(y2, _vx, _vx);
+
+    ysin = v_select(poly_mask, y2, y1);
+    ycos = v_select(poly_mask, y1, y2);
+    ysin = v_select(sign_mask_sin, ysin, v_xor(v_neg_zero, ysin));
+    ycos = v_select(sign_mask_cos, v_xor(v_neg_zero, ycos), ycos);
+
+    // sincos(NAN) -> NAN, sincos(±INF) -> NAN
+    _TpVec16F mask_inf = v_eq(_vx, v_reinterpret_as_f16(v_setall_<_TpVec16S>((short)0x7c00)));
+    _TpVec16F mask_nan = v_or(mask_inf, v_ne(x, x));
+    ysin = v_select(mask_nan, v_nan, ysin);
+    ycos = v_select(mask_nan, v_nan, ycos);
+}
+
+template<typename _TpVec16F, typename _TpVec16S>
+inline _TpVec16F v_sin_default_16f(const _TpVec16F &x) {
+    _TpVec16F ysin, ycos;
+    v_sincos_default_16f<_TpVec16F, _TpVec16S>(x, ysin, ycos);
+    return ysin;
+}
+
+template<typename _TpVec16F, typename _TpVec16S>
+inline _TpVec16F v_cos_default_16f(const _TpVec16F &x) {
+    _TpVec16F ysin, ycos;
+    v_sincos_default_16f<_TpVec16F, _TpVec16S>(x, ysin, ycos);
+    return ycos;
+}
+
+
+template<typename _TpVec32F, typename _TpVec32S>
+inline void v_sincos_default_32f(const _TpVec32F &x, _TpVec32F &ysin, _TpVec32F &ycos) {
+    const _TpVec32F v_cephes_FOPI = v_setall_<_TpVec32F>(1.27323954473516f); // 4 / M_PI
+    const _TpVec32F v_minus_DP1 = v_setall_<_TpVec32F>(-0.78515625f);
+    const _TpVec32F v_minus_DP2 = v_setall_<_TpVec32F>(-2.4187564849853515625E-4f);
+    const _TpVec32F v_minus_DP3 = v_setall_<_TpVec32F>(-3.77489497744594108E-8f);
+    const _TpVec32F v_sincof_p0 = v_setall_<_TpVec32F>(-1.9515295891E-4f);
+    const _TpVec32F v_sincof_p1 = v_setall_<_TpVec32F>(8.3321608736E-3f);
+    const _TpVec32F v_sincof_p2 = v_setall_<_TpVec32F>(-1.6666654611E-1f);
+    const _TpVec32F v_coscof_p0 = v_setall_<_TpVec32F>(2.443315711809948E-5f);
+    const _TpVec32F v_coscof_p1 = v_setall_<_TpVec32F>(-1.388731625493765E-3f);
+    const _TpVec32F v_coscof_p2 = v_setall_<_TpVec32F>(4.166664568298827E-2f);
+    const _TpVec32F v_nan = v_reinterpret_as_f32(v_setall_<_TpVec32S>((int)0x7fc00000));
+    const _TpVec32F v_neg_zero = v_setall_<_TpVec32F>(-0.f);
+
+    _TpVec32F _vx, _vy, sign_mask_sin, sign_mask_cos;
+    _TpVec32S emm2;
+
+    sign_mask_sin = v_lt(x, v_setzero_<_TpVec32F>());
+    _vx = v_abs(x);
+    _vy = v_mul(_vx, v_cephes_FOPI);
+
+    emm2 = v_trunc(_vy);
+    emm2 = v_add(emm2, v_setall_<_TpVec32S>(1));
+    emm2 = v_and(emm2, v_setall_<_TpVec32S>(~1));
+    _vy = v_cvt_f32(emm2);
+
+    _TpVec32F poly_mask = v_reinterpret_as_f32(v_eq(v_and(emm2, v_setall_<_TpVec32S>(2)), v_setall_<_TpVec32S>(0)));
+
+    _vx = v_fma(_vy, v_minus_DP1, _vx);
+    _vx = v_fma(_vy, v_minus_DP2, _vx);
+    _vx = v_fma(_vy, v_minus_DP3, _vx);
+
+    sign_mask_sin = v_xor(sign_mask_sin, v_reinterpret_as_f32(v_eq(v_and(emm2, v_setall_<_TpVec32S>(4)), v_setall_<_TpVec32S>(0))));
+    sign_mask_cos = v_reinterpret_as_f32(v_eq(v_and(v_sub(emm2, v_setall_<_TpVec32S>(2)), v_setall_<_TpVec32S>(4)), v_setall_<_TpVec32S>(0)));
+
+    _TpVec32F _vxx = v_mul(_vx, _vx);
+    _TpVec32F y1, y2;
+
+    y1 = v_fma(v_coscof_p0, _vxx, v_coscof_p1);
+    y1 = v_fma(y1, _vxx, v_coscof_p2);
+    y1 = v_fma(y1, _vxx, v_setall_<_TpVec32F>(-0.5f));
+    y1 = v_fma(y1, _vxx, v_setall_<_TpVec32F>(1.f));
+
+    y2 = v_fma(v_sincof_p0, _vxx, v_sincof_p1);
+    y2 = v_fma(y2, _vxx, v_sincof_p2);
+    y2 = v_mul(y2, _vxx);
+    y2 = v_fma(y2, _vx, _vx);
+
+    ysin = v_select(poly_mask, y2, y1);
+    ycos = v_select(poly_mask, y1, y2);
+    ysin = v_select(sign_mask_sin, ysin, v_xor(v_neg_zero, ysin));
+    ycos = v_select(sign_mask_cos, v_xor(v_neg_zero, ycos), ycos);
+
+    // sincos(NAN) -> NAN, sincos(±INF) -> NAN
+    _TpVec32F mask_inf = v_eq(_vx, v_reinterpret_as_f32(v_setall_<_TpVec32S>((int)0x7f800000)));
+    _TpVec32F mask_nan = v_or(mask_inf, v_ne(x, x));
+    ysin = v_select(mask_nan, v_nan, ysin);
+    ycos = v_select(mask_nan, v_nan, ycos);
+}
+
+template<typename _TpVec32F, typename _TpVec32S>
+inline _TpVec32F v_sin_default_32f(const _TpVec32F &x) {
+    _TpVec32F ysin, ycos;
+    v_sincos_default_32f<_TpVec32F, _TpVec32S>(x, ysin, ycos);
+    return ysin;
+}
+
+template<typename _TpVec32F, typename _TpVec32S>
+inline _TpVec32F v_cos_default_32f(const _TpVec32F &x) {
+    _TpVec32F ysin, ycos;
+    v_sincos_default_32f<_TpVec32F, _TpVec32S>(x, ysin, ycos);
+    return ycos;
+}
+
+template<typename _TpVec64F, typename _TpVec64S>
+inline void v_sincos_default_64f(const _TpVec64F &x, _TpVec64F &ysin, _TpVec64F &ycos) {
+    const _TpVec64F v_cephes_FOPI = v_setall_<_TpVec64F>(1.2732395447351626861510701069801148); // 4 / M_PI
+    const _TpVec64F v_minus_DP1 = v_setall_<_TpVec64F>(-7.853981554508209228515625E-1);
+    const _TpVec64F v_minus_DP2 = v_setall_<_TpVec64F>(-7.94662735614792836714E-9);
+    const _TpVec64F v_minus_DP3 = v_setall_<_TpVec64F>(-3.06161699786838294307E-17);
+    const _TpVec64F v_sin_C1 = v_setall_<_TpVec64F>(1.58962301576546568060E-10);
+    const _TpVec64F v_sin_C2 = v_setall_<_TpVec64F>(-2.50507477628578072866E-8);
+    const _TpVec64F v_sin_C3 = v_setall_<_TpVec64F>(2.75573136213857245213E-6);
+    const _TpVec64F v_sin_C4 = v_setall_<_TpVec64F>(-1.98412698295895385996E-4);
+    const _TpVec64F v_sin_C5 = v_setall_<_TpVec64F>(8.33333333332211858878E-3);
+    const _TpVec64F v_sin_C6 = v_setall_<_TpVec64F>(-1.66666666666666307295E-1);
+    const _TpVec64F v_cos_C1 = v_setall_<_TpVec64F>(-1.13585365213876817300E-11);
+    const _TpVec64F v_cos_C2 = v_setall_<_TpVec64F>(2.08757008419747316778E-9);
+    const _TpVec64F v_cos_C3 = v_setall_<_TpVec64F>(-2.75573141792967388112E-7);
+    const _TpVec64F v_cos_C4 = v_setall_<_TpVec64F>(2.48015872888517045348E-5);
+    const _TpVec64F v_cos_C5 = v_setall_<_TpVec64F>(-1.38888888888730564116E-3);
+    const _TpVec64F v_cos_C6 = v_setall_<_TpVec64F>(4.16666666666665929218E-2);
+    const _TpVec64F v_nan = v_reinterpret_as_f64(v_setall_<_TpVec64S>((int64)0x7ff8000000000000));
+    const _TpVec64F v_neg_zero = v_setall_<_TpVec64F>(-0.0);
+
+    _TpVec64F _vx, _vy, sign_mask_sin, sign_mask_cos;
+    _TpVec64S emm2;
+
+    sign_mask_sin = v_lt(x, v_setzero_<_TpVec64F>());
+    _vx = v_abs(x);
+    _vy = v_mul(_vx, v_cephes_FOPI);
+
+    emm2 = v_expand_low(v_trunc(_vy));
+    emm2 = v_add(emm2, v_setall_<_TpVec64S>((int64)1));
+    emm2 = v_and(emm2, v_setall_<_TpVec64S>((int64)~1));
+    _vy = v_cvt_f64(emm2);
+
+    _TpVec64F poly_mask = v_reinterpret_as_f64(v_eq(v_and(emm2, v_setall_<_TpVec64S>((int64)2)), v_setall_<_TpVec64S>((int64)0)));
+
+    _vx = v_fma(_vy, v_minus_DP1, _vx);
+    _vx = v_fma(_vy, v_minus_DP2, _vx);
+    _vx = v_fma(_vy, v_minus_DP3, _vx);
+
+    sign_mask_sin = v_xor(sign_mask_sin, v_reinterpret_as_f64(v_eq(v_and(emm2, v_setall_<_TpVec64S>((int64)4)), v_setall_<_TpVec64S>((int64)0))));
+    sign_mask_cos = v_reinterpret_as_f64(v_eq(v_and(v_sub(emm2, v_setall_<_TpVec64S>((int64)2)), v_setall_<_TpVec64S>((int64)4)), v_setall_<_TpVec64S>((int64)0)));
+
+    _TpVec64F _vxx = v_mul(_vx, _vx);
+    _TpVec64F y1, y2;
+
+    y1 = v_fma(v_cos_C1, _vxx, v_cos_C2);
+    y1 = v_fma(y1, _vxx, v_cos_C3);
+    y1 = v_fma(y1, _vxx, v_cos_C4);
+    y1 = v_fma(y1, _vxx, v_cos_C5);
+    y1 = v_fma(y1, _vxx, v_cos_C6);
+    y1 = v_fma(y1, _vxx, v_setall_<_TpVec64F>(-0.5));
+    y1 = v_fma(y1, _vxx, v_setall_<_TpVec64F>(1.0));
+
+    y2 = v_fma(v_sin_C1, _vxx, v_sin_C2);
+    y2 = v_fma(y2, _vxx, v_sin_C3);
+    y2 = v_fma(y2, _vxx, v_sin_C4);
+    y2 = v_fma(y2, _vxx, v_sin_C5);
+    y2 = v_fma(y2, _vxx, v_sin_C6);
+    y2 = v_mul(y2, _vxx);
+    y2 = v_fma(y2, _vx, _vx);
+
+    ysin = v_select(poly_mask, y2, y1);
+    ycos = v_select(poly_mask, y1, y2);
+    ysin = v_select(sign_mask_sin, ysin, v_xor(v_neg_zero, ysin));
+    ycos = v_select(sign_mask_cos, v_xor(v_neg_zero, ycos), ycos);
+
+    // sincos(NAN) -> NAN, sincos(±INF) -> NAN
+    _TpVec64F mask_inf = v_eq(_vx, v_reinterpret_as_f64(v_setall_<_TpVec64S>((int64)0x7ff0000000000000)));
+    _TpVec64F mask_nan = v_or(mask_inf, v_ne(x, x));
+    ysin = v_select(mask_nan, v_nan, ysin);
+    ycos = v_select(mask_nan, v_nan, ycos);
+}
+
+template<typename _TpVec64F, typename _TpVec64S>
+inline _TpVec64F v_sin_default_64f(const _TpVec64F &x) {
+    _TpVec64F ysin, ycos;
+    v_sincos_default_64f<_TpVec64F, _TpVec64S>(x, ysin, ycos);
+    return ysin;
+}
+
+template<typename _TpVec64F, typename _TpVec64S>
+inline _TpVec64F v_cos_default_64f(const _TpVec64F &x) {
+    _TpVec64F ysin, ycos;
+    v_sincos_default_64f<_TpVec64F, _TpVec64S>(x, ysin, ycos);
+    return ycos;
+}
+//! @}
+
+
+/* This implementation is derived from the approximation approach of Error Function (Erf) from PyTorch
+   https://github.com/pytorch/pytorch/blob/9c50ecc84b9a6e699a7f058891b889aafbf976c7/aten/src/ATen/cpu/vec/vec512/vec512_float.h#L189-L220
+*/
+
+//! @name Error Function
+//! @{
+template<typename _TpVec32F, typename _TpVec32S>
+inline _TpVec32F v_erf_default_32f(const _TpVec32F &v) {
+    const _TpVec32F coef0 = v_setall_<_TpVec32F>(0.3275911f),
+            coef1 = v_setall_<_TpVec32F>(1.061405429f),
+            coef2 = v_setall_<_TpVec32F>(-1.453152027f),
+            coef3 = v_setall_<_TpVec32F>(1.421413741f),
+            coef4 = v_setall_<_TpVec32F>(-0.284496736f),
+            coef5 = v_setall_<_TpVec32F>(0.254829592f),
+            ones = v_setall_<_TpVec32F>(1.0f),
+            neg_zeros = v_setall_<_TpVec32F>(-0.f);
+    _TpVec32F t = v_abs(v);
+    // sign(v)
+    _TpVec32F sign_mask = v_and(neg_zeros, v);
+
+    t = v_div(ones, v_fma(coef0, t, ones));
+    _TpVec32F r = v_fma(coef1, t, coef2);
+    r = v_fma(r, t, coef3);
+    r = v_fma(r, t, coef4);
+    r = v_fma(r, t, coef5);
+    // - v * v
+    _TpVec32F v2 = v_mul(v, v);
+    _TpVec32F mv2 = v_xor(neg_zeros, v2);
+    // - exp(- v * v)
+    _TpVec32F exp = v_exp_default_32f<_TpVec32F, _TpVec32S>(mv2);
+    _TpVec32F neg_exp = v_xor(neg_zeros, exp);
+    _TpVec32F res = v_mul(t, neg_exp);
+    res = v_fma(r, res, ones);
+    return v_xor(sign_mask, res);
+}
+//! @}
+
+#endif // OPENCV_HAL_INTRIN_MATH_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_msa.hpp

@@ -0,0 +1,1886 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_HAL_INTRIN_MSA_HPP
+#define OPENCV_HAL_INTRIN_MSA_HPP
+
+#include <algorithm>
+#include "opencv2/core/utility.hpp"
+
+namespace cv
+{
+
+//! @cond IGNORED
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+#define CV_SIMD128 1
+
+//MSA implements 128-bit wide vector registers shared with the 64-bit wide floating-point unit registers.
+//MSA and FPU can not be both present, unless the FPU has 64-bit floating-point registers.
+#define CV_SIMD128_64F 1
+
+struct v_uint8x16
+{
+    typedef uchar lane_type;
+    enum { nlanes = 16 };
+
+    v_uint8x16() {}
+    explicit v_uint8x16(v16u8 v) : val(v) {}
+    v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
+               uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
+    {
+        uchar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = msa_ld1q_u8(v);
+    }
+
+    uchar get0() const
+    {
+        return msa_getq_lane_u8(val, 0);
+    }
+
+    v16u8 val;
+};
+
+struct v_int8x16
+{
+    typedef schar lane_type;
+    enum { nlanes = 16 };
+
+    v_int8x16() {}
+    explicit v_int8x16(v16i8 v) : val(v) {}
+    v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
+               schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
+    {
+        schar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = msa_ld1q_s8(v);
+    }
+
+    schar get0() const
+    {
+        return msa_getq_lane_s8(val, 0);
+    }
+
+    v16i8 val;
+};
+
+struct v_uint16x8
+{
+    typedef ushort lane_type;
+    enum { nlanes = 8 };
+
+    v_uint16x8() {}
+    explicit v_uint16x8(v8u16 v) : val(v) {}
+    v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
+    {
+        ushort v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = msa_ld1q_u16(v);
+    }
+
+    ushort get0() const
+    {
+        return msa_getq_lane_u16(val, 0);
+    }
+
+    v8u16 val;
+};
+
+struct v_int16x8
+{
+    typedef short lane_type;
+    enum { nlanes = 8 };
+
+    v_int16x8() {}
+    explicit v_int16x8(v8i16 v) : val(v) {}
+    v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
+    {
+        short v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = msa_ld1q_s16(v);
+    }
+
+    short get0() const
+    {
+        return msa_getq_lane_s16(val, 0);
+    }
+
+    v8i16 val;
+};
+
+struct v_uint32x4
+{
+    typedef unsigned int lane_type;
+    enum { nlanes = 4 };
+
+    v_uint32x4() {}
+    explicit v_uint32x4(v4u32 v) : val(v) {}
+    v_uint32x4(unsigned int v0, unsigned int v1, unsigned int v2, unsigned int v3)
+    {
+        unsigned int v[] = {v0, v1, v2, v3};
+        val = msa_ld1q_u32(v);
+    }
+
+    unsigned int get0() const
+    {
+        return msa_getq_lane_u32(val, 0);
+    }
+
+    v4u32 val;
+};
+
+struct v_int32x4
+{
+    typedef int lane_type;
+    enum { nlanes = 4 };
+
+    v_int32x4() {}
+    explicit v_int32x4(v4i32 v) : val(v) {}
+    v_int32x4(int v0, int v1, int v2, int v3)
+    {
+        int v[] = {v0, v1, v2, v3};
+        val = msa_ld1q_s32(v);
+    }
+
+    int get0() const
+    {
+        return msa_getq_lane_s32(val, 0);
+    }
+
+    v4i32 val;
+};
+
+struct v_float32x4
+{
+    typedef float lane_type;
+    enum { nlanes = 4 };
+
+    v_float32x4() {}
+    explicit v_float32x4(v4f32 v) : val(v) {}
+    v_float32x4(float v0, float v1, float v2, float v3)
+    {
+        float v[] = {v0, v1, v2, v3};
+        val = msa_ld1q_f32(v);
+    }
+
+    float get0() const
+    {
+        return msa_getq_lane_f32(val, 0);
+    }
+
+    v4f32 val;
+};
+
+struct v_uint64x2
+{
+    typedef uint64 lane_type;
+    enum { nlanes = 2 };
+
+    v_uint64x2() {}
+    explicit v_uint64x2(v2u64 v) : val(v) {}
+    v_uint64x2(uint64 v0, uint64 v1)
+    {
+        uint64 v[] = {v0, v1};
+        val = msa_ld1q_u64(v);
+    }
+
+    uint64 get0() const
+    {
+        return msa_getq_lane_u64(val, 0);
+    }
+
+    v2u64 val;
+};
+
+struct v_int64x2
+{
+    typedef int64 lane_type;
+    enum { nlanes = 2 };
+
+    v_int64x2() {}
+    explicit v_int64x2(v2i64 v) : val(v) {}
+    v_int64x2(int64 v0, int64 v1)
+    {
+        int64 v[] = {v0, v1};
+        val = msa_ld1q_s64(v);
+    }
+
+    int64 get0() const
+    {
+        return msa_getq_lane_s64(val, 0);
+    }
+
+    v2i64 val;
+};
+
+struct v_float64x2
+{
+    typedef double lane_type;
+    enum { nlanes = 2 };
+
+    v_float64x2() {}
+    explicit v_float64x2(v2f64 v) : val(v) {}
+    v_float64x2(double v0, double v1)
+    {
+        double v[] = {v0, v1};
+        val = msa_ld1q_f64(v);
+    }
+
+    double get0() const
+    {
+        return msa_getq_lane_f64(val, 0);
+    }
+
+    v2f64 val;
+};
+
+#define OPENCV_HAL_IMPL_MSA_INIT(_Tpv, _Tp, suffix) \
+inline v_##_Tpv v_setzero_##suffix() { return v_##_Tpv(msa_dupq_n_##suffix((_Tp)0)); } \
+inline v_##_Tpv v_setall_##suffix(_Tp v) { return v_##_Tpv(msa_dupq_n_##suffix(v)); } \
+template <> inline v_##_Tpv v_setzero_() { return v_setzero_##suffix(); } \
+template <> inline v_##_Tpv v_setall_(_Tp v) { return v_setall_##suffix(v); } \
+inline v_uint8x16 v_reinterpret_as_u8(const v_##_Tpv& v) { return v_uint8x16(MSA_TPV_REINTERPRET(v16u8, v.val)); } \
+inline v_int8x16 v_reinterpret_as_s8(const v_##_Tpv& v) { return v_int8x16(MSA_TPV_REINTERPRET(v16i8, v.val)); } \
+inline v_uint16x8 v_reinterpret_as_u16(const v_##_Tpv& v) { return v_uint16x8(MSA_TPV_REINTERPRET(v8u16, v.val)); } \
+inline v_int16x8 v_reinterpret_as_s16(const v_##_Tpv& v) { return v_int16x8(MSA_TPV_REINTERPRET(v8i16, v.val)); } \
+inline v_uint32x4 v_reinterpret_as_u32(const v_##_Tpv& v) { return v_uint32x4(MSA_TPV_REINTERPRET(v4u32, v.val)); } \
+inline v_int32x4 v_reinterpret_as_s32(const v_##_Tpv& v) { return v_int32x4(MSA_TPV_REINTERPRET(v4i32, v.val)); } \
+inline v_uint64x2 v_reinterpret_as_u64(const v_##_Tpv& v) { return v_uint64x2(MSA_TPV_REINTERPRET(v2u64, v.val)); } \
+inline v_int64x2 v_reinterpret_as_s64(const v_##_Tpv& v) { return v_int64x2(MSA_TPV_REINTERPRET(v2i64, v.val)); } \
+inline v_float32x4 v_reinterpret_as_f32(const v_##_Tpv& v) { return v_float32x4(MSA_TPV_REINTERPRET(v4f32, v.val)); } \
+inline v_float64x2 v_reinterpret_as_f64(const v_##_Tpv& v) { return v_float64x2(MSA_TPV_REINTERPRET(v2f64, v.val)); }
+
+OPENCV_HAL_IMPL_MSA_INIT(uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_MSA_INIT(int8x16, schar, s8)
+OPENCV_HAL_IMPL_MSA_INIT(uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_MSA_INIT(int16x8, short, s16)
+OPENCV_HAL_IMPL_MSA_INIT(uint32x4, unsigned int, u32)
+OPENCV_HAL_IMPL_MSA_INIT(int32x4, int, s32)
+OPENCV_HAL_IMPL_MSA_INIT(uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_MSA_INIT(int64x2, int64, s64)
+OPENCV_HAL_IMPL_MSA_INIT(float32x4, float, f32)
+OPENCV_HAL_IMPL_MSA_INIT(float64x2, double, f64)
+
+#define OPENCV_HAL_IMPL_MSA_PACK(_Tpvec, _Tpwvec, pack, mov, rshr) \
+inline _Tpvec v_##pack(const _Tpwvec& a, const _Tpwvec& b) \
+{ \
+    return _Tpvec(mov(a.val, b.val)); \
+} \
+template<int n> inline \
+_Tpvec v_rshr_##pack(const _Tpwvec& a, const _Tpwvec& b) \
+{ \
+    return _Tpvec(rshr(a.val, b.val, n)); \
+}
+
+OPENCV_HAL_IMPL_MSA_PACK(v_uint8x16, v_uint16x8, pack, msa_qpack_u16, msa_qrpackr_u16)
+OPENCV_HAL_IMPL_MSA_PACK(v_int8x16, v_int16x8, pack, msa_qpack_s16, msa_qrpackr_s16)
+OPENCV_HAL_IMPL_MSA_PACK(v_uint16x8, v_uint32x4, pack, msa_qpack_u32, msa_qrpackr_u32)
+OPENCV_HAL_IMPL_MSA_PACK(v_int16x8, v_int32x4, pack, msa_qpack_s32, msa_qrpackr_s32)
+OPENCV_HAL_IMPL_MSA_PACK(v_uint32x4, v_uint64x2, pack, msa_pack_u64, msa_rpackr_u64)
+OPENCV_HAL_IMPL_MSA_PACK(v_int32x4, v_int64x2, pack, msa_pack_s64, msa_rpackr_s64)
+OPENCV_HAL_IMPL_MSA_PACK(v_uint8x16, v_int16x8, pack_u, msa_qpacku_s16, msa_qrpackru_s16)
+OPENCV_HAL_IMPL_MSA_PACK(v_uint16x8, v_int32x4, pack_u, msa_qpacku_s32, msa_qrpackru_s32)
+
+#define OPENCV_HAL_IMPL_MSA_PACK_STORE(_Tpvec, _Tp, hreg, suffix, _Tpwvec, pack, mov, rshr) \
+inline void v_##pack##_store(_Tp* ptr, const _Tpwvec& a) \
+{ \
+    hreg a1 = mov(a.val); \
+    msa_st1_##suffix(ptr, a1); \
+} \
+template<int n> inline \
+void v_rshr_##pack##_store(_Tp* ptr, const _Tpwvec& a) \
+{ \
+    hreg a1 = rshr(a.val, n); \
+    msa_st1_##suffix(ptr, a1); \
+}
+
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_uint8x16, uchar, v8u8, u8, v_uint16x8, pack, msa_qmovn_u16, msa_qrshrn_n_u16)
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_int8x16, schar, v8i8, s8, v_int16x8, pack, msa_qmovn_s16, msa_qrshrn_n_s16)
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_uint16x8, ushort, v4u16, u16, v_uint32x4, pack, msa_qmovn_u32, msa_qrshrn_n_u32)
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_int16x8, short, v4i16, s16, v_int32x4, pack, msa_qmovn_s32, msa_qrshrn_n_s32)
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_uint32x4, unsigned, v2u32, u32, v_uint64x2, pack, msa_movn_u64, msa_rshrn_n_u64)
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_int32x4, int, v2i32, s32, v_int64x2, pack, msa_movn_s64, msa_rshrn_n_s64)
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_uint8x16, uchar, v8u8, u8, v_int16x8, pack_u, msa_qmovun_s16, msa_qrshrun_n_s16)
+OPENCV_HAL_IMPL_MSA_PACK_STORE(v_uint16x8, ushort, v4u16, u16, v_int32x4, pack_u, msa_qmovun_s32, msa_qrshrun_n_s32)
+
+// pack boolean
+inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b)
+{
+    return v_uint8x16(msa_pack_u16(a.val, b.val));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b,
+                           const v_uint32x4& c, const v_uint32x4& d)
+{
+    return v_uint8x16(msa_pack_u16(msa_pack_u32(a.val, b.val), msa_pack_u32(c.val, d.val)));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                           const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f,
+                           const v_uint64x2& g, const v_uint64x2& h)
+{
+    v8u16 abcd = msa_pack_u32(msa_pack_u64(a.val, b.val), msa_pack_u64(c.val, d.val));
+    v8u16 efgh = msa_pack_u32(msa_pack_u64(e.val, f.val), msa_pack_u64(g.val, h.val));
+    return v_uint8x16(msa_pack_u16(abcd, efgh));
+}
+
+inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
+                            const v_float32x4& m1, const v_float32x4& m2,
+                            const v_float32x4& m3)
+{
+    v4f32 v0 = v.val;
+    v4f32 res = msa_mulq_lane_f32(m0.val, v0, 0);
+    res = msa_mlaq_lane_f32(res, m1.val, v0, 1);
+    res = msa_mlaq_lane_f32(res, m2.val, v0, 2);
+    res = msa_mlaq_lane_f32(res, m3.val, v0, 3);
+    return v_float32x4(res);
+}
+
+inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0,
+                               const v_float32x4& m1, const v_float32x4& m2,
+                               const v_float32x4& a)
+{
+    v4f32 v0 = v.val;
+    v4f32 res = msa_mulq_lane_f32(m0.val, v0, 0);
+    res = msa_mlaq_lane_f32(res, m1.val, v0, 1);
+    res = msa_mlaq_lane_f32(res, m2.val, v0, 2);
+    res = msa_addq_f32(res, a.val);
+    return v_float32x4(res);
+}
+
+#define OPENCV_HAL_IMPL_MSA_BIN_OP(bin_op, _Tpvec, intrin) \
+inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_uint8x16, msa_qaddq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_uint8x16, msa_qsubq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_int8x16, msa_qaddq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_int8x16, msa_qsubq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_uint16x8, msa_qaddq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_uint16x8, msa_qsubq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_int16x8, msa_qaddq_s16)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_int16x8, msa_qsubq_s16)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_int32x4, msa_addq_s32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_int32x4, msa_subq_s32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_mul, v_int32x4, msa_mulq_s32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_uint32x4, msa_addq_u32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_uint32x4, msa_subq_u32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_mul, v_uint32x4, msa_mulq_u32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_float32x4, msa_addq_f32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_float32x4, msa_subq_f32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_mul, v_float32x4, msa_mulq_f32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_int64x2, msa_addq_s64)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_int64x2, msa_subq_s64)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_uint64x2, msa_addq_u64)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_uint64x2, msa_subq_u64)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_div, v_float32x4, msa_divq_f32)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_add, v_float64x2, msa_addq_f64)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_sub, v_float64x2, msa_subq_f64)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_mul, v_float64x2, msa_mulq_f64)
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_div, v_float64x2, msa_divq_f64)
+
+// saturating multiply 8-bit, 16-bit
+#define OPENCV_HAL_IMPL_MSA_MUL_SAT(_Tpvec, _Tpwvec)         \
+inline _Tpvec v_mul(const _Tpvec& a, const _Tpvec& b)  \
+{                                                            \
+    _Tpwvec c, d;                                            \
+    v_mul_expand(a, b, c, d);                                \
+    return v_pack(c, d);                                     \
+}
+
+OPENCV_HAL_IMPL_MSA_MUL_SAT(v_int8x16,  v_int16x8)
+OPENCV_HAL_IMPL_MSA_MUL_SAT(v_uint8x16, v_uint16x8)
+OPENCV_HAL_IMPL_MSA_MUL_SAT(v_int16x8,  v_int32x4)
+OPENCV_HAL_IMPL_MSA_MUL_SAT(v_uint16x8, v_uint32x4)
+
+//  Multiply and expand
+inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b,
+                         v_int16x8& c, v_int16x8& d)
+{
+    v16i8 a_lo, a_hi, b_lo, b_hi;
+
+    ILVRL_B2_SB(a.val, msa_dupq_n_s8(0), a_lo, a_hi);
+    ILVRL_B2_SB(b.val, msa_dupq_n_s8(0), b_lo, b_hi);
+    c.val = msa_mulq_s16(msa_paddlq_s8(a_lo), msa_paddlq_s8(b_lo));
+    d.val = msa_mulq_s16(msa_paddlq_s8(a_hi), msa_paddlq_s8(b_hi));
+}
+
+inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b,
+                         v_uint16x8& c, v_uint16x8& d)
+{
+    v16u8 a_lo, a_hi, b_lo, b_hi;
+
+    ILVRL_B2_UB(a.val, msa_dupq_n_u8(0), a_lo, a_hi);
+    ILVRL_B2_UB(b.val, msa_dupq_n_u8(0), b_lo, b_hi);
+    c.val = msa_mulq_u16(msa_paddlq_u8(a_lo), msa_paddlq_u8(b_lo));
+    d.val = msa_mulq_u16(msa_paddlq_u8(a_hi), msa_paddlq_u8(b_hi));
+}
+
+inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b,
+                         v_int32x4& c, v_int32x4& d)
+{
+    v8i16 a_lo, a_hi, b_lo, b_hi;
+
+    ILVRL_H2_SH(a.val, msa_dupq_n_s16(0), a_lo, a_hi);
+    ILVRL_H2_SH(b.val, msa_dupq_n_s16(0), b_lo, b_hi);
+    c.val = msa_mulq_s32(msa_paddlq_s16(a_lo), msa_paddlq_s16(b_lo));
+    d.val = msa_mulq_s32(msa_paddlq_s16(a_hi), msa_paddlq_s16(b_hi));
+}
+
+inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b,
+                         v_uint32x4& c, v_uint32x4& d)
+{
+    v8u16 a_lo, a_hi, b_lo, b_hi;
+
+    ILVRL_H2_UH(a.val, msa_dupq_n_u16(0), a_lo, a_hi);
+    ILVRL_H2_UH(b.val, msa_dupq_n_u16(0), b_lo, b_hi);
+    c.val = msa_mulq_u32(msa_paddlq_u16(a_lo), msa_paddlq_u16(b_lo));
+    d.val = msa_mulq_u32(msa_paddlq_u16(a_hi), msa_paddlq_u16(b_hi));
+}
+
+inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b,
+                         v_uint64x2& c, v_uint64x2& d)
+{
+    v4u32 a_lo, a_hi, b_lo, b_hi;
+
+    ILVRL_W2_UW(a.val, msa_dupq_n_u32(0), a_lo, a_hi);
+    ILVRL_W2_UW(b.val, msa_dupq_n_u32(0), b_lo, b_hi);
+    c.val = msa_mulq_u64(msa_paddlq_u32(a_lo), msa_paddlq_u32(b_lo));
+    d.val = msa_mulq_u64(msa_paddlq_u32(a_hi), msa_paddlq_u32(b_hi));
+}
+
+inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b)
+{
+    v8i16 a_lo, a_hi, b_lo, b_hi;
+
+    ILVRL_H2_SH(a.val, msa_dupq_n_s16(0), a_lo, a_hi);
+    ILVRL_H2_SH(b.val, msa_dupq_n_s16(0), b_lo, b_hi);
+
+    return v_int16x8(msa_packr_s32(msa_mulq_s32(msa_paddlq_s16(a_lo), msa_paddlq_s16(b_lo)),
+                                   msa_mulq_s32(msa_paddlq_s16(a_hi), msa_paddlq_s16(b_hi)), 16));
+}
+
+inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v8u16 a_lo, a_hi, b_lo, b_hi;
+
+    ILVRL_H2_UH(a.val, msa_dupq_n_u16(0), a_lo, a_hi);
+    ILVRL_H2_UH(b.val, msa_dupq_n_u16(0), b_lo, b_hi);
+
+    return v_uint16x8(msa_packr_u32(msa_mulq_u32(msa_paddlq_u16(a_lo), msa_paddlq_u16(b_lo)),
+                                    msa_mulq_u32(msa_paddlq_u16(a_hi), msa_paddlq_u16(b_hi)), 16));
+}
+
+//////// Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
+{ return v_int32x4(msa_dotp_s_w(a.val, b.val)); }
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_int32x4(msa_dpadd_s_w(c.val , a.val, b.val)); }
+
+// 32 >> 64
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b)
+{ return v_int64x2(msa_dotp_s_d(a.val, b.val)); }
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_int64x2(msa_dpadd_s_d(c.val , a.val, b.val)); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
+{
+    v8u16 even_a = msa_shrq_n_u16(msa_shlq_n_u16(MSA_TPV_REINTERPRET(v8u16, a.val), 8), 8);
+    v8u16 odd_a  = msa_shrq_n_u16(MSA_TPV_REINTERPRET(v8u16, a.val), 8);
+    v8u16 even_b = msa_shrq_n_u16(msa_shlq_n_u16(MSA_TPV_REINTERPRET(v8u16, b.val), 8), 8);
+    v8u16 odd_b  = msa_shrq_n_u16(MSA_TPV_REINTERPRET(v8u16, b.val), 8);
+    v4u32 prod   = msa_dotp_u_w(even_a, even_b);
+    return v_uint32x4(msa_dpadd_u_w(prod, odd_a, odd_b));
+}
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{
+    v8u16 even_a = msa_shrq_n_u16(msa_shlq_n_u16(MSA_TPV_REINTERPRET(v8u16, a.val), 8), 8);
+    v8u16 odd_a  = msa_shrq_n_u16(MSA_TPV_REINTERPRET(v8u16, a.val), 8);
+    v8u16 even_b = msa_shrq_n_u16(msa_shlq_n_u16(MSA_TPV_REINTERPRET(v8u16, b.val), 8), 8);
+    v8u16 odd_b  = msa_shrq_n_u16(MSA_TPV_REINTERPRET(v8u16, b.val), 8);
+    v4u32 prod   = msa_dpadd_u_w(c.val, even_a, even_b);
+    return v_uint32x4(msa_dpadd_u_w(prod, odd_a, odd_b));
+}
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
+{
+    v8i16 prod = msa_dotp_s_h(a.val, b.val);
+    return v_int32x4(msa_hadd_s32(prod, prod));
+}
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b,
+                                  const v_int32x4& c)
+{ return v_dotprod_expand(a, b) + c; }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v4u32 even_a = msa_shrq_n_u32(msa_shlq_n_u32(MSA_TPV_REINTERPRET(v4u32, a.val), 16), 16);
+    v4u32 odd_a  = msa_shrq_n_u32(MSA_TPV_REINTERPRET(v4u32, a.val), 16);
+    v4u32 even_b = msa_shrq_n_u32(msa_shlq_n_u32(MSA_TPV_REINTERPRET(v4u32, b.val), 16), 16);
+    v4u32 odd_b  = msa_shrq_n_u32(MSA_TPV_REINTERPRET(v4u32, b.val), 16);
+    v2u64 prod   = msa_dotp_u_d(even_a, even_b);
+    return v_uint64x2(msa_dpadd_u_d(prod, odd_a, odd_b));
+}
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b,
+                                   const v_uint64x2& c)
+{
+    v4u32 even_a = msa_shrq_n_u32(msa_shlq_n_u32(MSA_TPV_REINTERPRET(v4u32, a.val), 16), 16);
+    v4u32 odd_a  = msa_shrq_n_u32(MSA_TPV_REINTERPRET(v4u32, a.val), 16);
+    v4u32 even_b = msa_shrq_n_u32(msa_shlq_n_u32(MSA_TPV_REINTERPRET(v4u32, b.val), 16), 16);
+    v4u32 odd_b  = msa_shrq_n_u32(MSA_TPV_REINTERPRET(v4u32, b.val), 16);
+    v2u64 prod   = msa_dpadd_u_d(c.val, even_a, even_b);
+    return v_uint64x2(msa_dpadd_u_d(prod, odd_a, odd_b));
+}
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b)
+{
+    v4i32 prod = msa_dotp_s_w(a.val, b.val);
+    return v_int64x2(msa_hadd_s64(prod, prod));
+}
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b)
+{ return v_dotprod(a, b); }
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_dotprod(a, b, c); }
+
+// 32 >> 64
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod(a, b); }
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_dotprod(a, b, c); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_dotprod_expand(a, b, c); }
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod_expand(a, b); }
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+
+#define OPENCV_HAL_IMPL_MSA_LOGIC_OP(_Tpvec, _Tpv, suffix) \
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_and, _Tpvec, msa_andq_##suffix)   \
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_or, _Tpvec, msa_orrq_##suffix)    \
+OPENCV_HAL_IMPL_MSA_BIN_OP(v_xor, _Tpvec, msa_eorq_##suffix)   \
+inline _Tpvec v_not(const _Tpvec& a) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_mvnq_u8(MSA_TPV_REINTERPRET(v16u8, a.val)))); \
+}
+
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_uint8x16, v16u8, u8)
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_int8x16, v16i8, s8)
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_uint16x8, v8u16, u16)
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_int16x8, v8i16, s16)
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_uint32x4, v4u32, u32)
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_int32x4, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_uint64x2, v2u64, u64)
+OPENCV_HAL_IMPL_MSA_LOGIC_OP(v_int64x2, v2i64, s64)
+
+#define OPENCV_HAL_IMPL_MSA_FLT_BIT_OP(bin_op, intrin) \
+inline v_float32x4 bin_op(const v_float32x4& a, const v_float32x4& b) \
+{ \
+    return v_float32x4(MSA_TPV_REINTERPRET(v4f32, intrin(MSA_TPV_REINTERPRET(v4i32, a.val), MSA_TPV_REINTERPRET(v4i32, b.val)))); \
+}
+
+OPENCV_HAL_IMPL_MSA_FLT_BIT_OP(v_and, msa_andq_s32)
+OPENCV_HAL_IMPL_MSA_FLT_BIT_OP(v_or, msa_orrq_s32)
+OPENCV_HAL_IMPL_MSA_FLT_BIT_OP(v_xor, msa_eorq_s32)
+
+inline v_float32x4 v_not(const v_float32x4& a)
+{
+    return v_float32x4(MSA_TPV_REINTERPRET(v4f32, msa_mvnq_s32(MSA_TPV_REINTERPRET(v4i32, a.val))));
+}
+
+/* v_abs */
+#define OPENCV_HAL_IMPL_MSA_ABS(_Tpuvec, _Tpsvec, usuffix, ssuffix) \
+inline _Tpuvec v_abs(const _Tpsvec& a) \
+{ \
+    return v_reinterpret_as_##usuffix(_Tpsvec(msa_absq_##ssuffix(a.val))); \
+}
+
+OPENCV_HAL_IMPL_MSA_ABS(v_uint8x16, v_int8x16, u8, s8)
+OPENCV_HAL_IMPL_MSA_ABS(v_uint16x8, v_int16x8, u16, s16)
+OPENCV_HAL_IMPL_MSA_ABS(v_uint32x4, v_int32x4, u32, s32)
+
+/* v_abs(float), v_sqrt, v_invsqrt */
+#define OPENCV_HAL_IMPL_MSA_BASIC_FUNC(_Tpvec, func, intrin) \
+inline _Tpvec func(const _Tpvec& a) \
+{ \
+    return _Tpvec(intrin(a.val)); \
+}
+
+OPENCV_HAL_IMPL_MSA_BASIC_FUNC(v_float32x4, v_abs, msa_absq_f32)
+OPENCV_HAL_IMPL_MSA_BASIC_FUNC(v_float64x2, v_abs, msa_absq_f64)
+OPENCV_HAL_IMPL_MSA_BASIC_FUNC(v_float32x4, v_sqrt, msa_sqrtq_f32)
+OPENCV_HAL_IMPL_MSA_BASIC_FUNC(v_float32x4, v_invsqrt, msa_rsqrtq_f32)
+OPENCV_HAL_IMPL_MSA_BASIC_FUNC(v_float64x2, v_sqrt, msa_sqrtq_f64)
+OPENCV_HAL_IMPL_MSA_BASIC_FUNC(v_float64x2, v_invsqrt, msa_rsqrtq_f64)
+
+#define OPENCV_HAL_IMPL_MSA_DBL_BIT_OP(bin_op, intrin) \
+inline v_float64x2 bin_op(const v_float64x2& a, const v_float64x2& b) \
+{ \
+    return v_float64x2(MSA_TPV_REINTERPRET(v2f64, intrin(MSA_TPV_REINTERPRET(v2i64, a.val), MSA_TPV_REINTERPRET(v2i64, b.val)))); \
+}
+
+OPENCV_HAL_IMPL_MSA_DBL_BIT_OP(v_and, msa_andq_s64)
+OPENCV_HAL_IMPL_MSA_DBL_BIT_OP(v_or, msa_orrq_s64)
+OPENCV_HAL_IMPL_MSA_DBL_BIT_OP(v_xor, msa_eorq_s64)
+
+inline v_float64x2 v_not(const v_float64x2& a)
+{
+    return v_float64x2(MSA_TPV_REINTERPRET(v2f64, msa_mvnq_s32(MSA_TPV_REINTERPRET(v4i32, a.val))));
+}
+
+// TODO: exp, log, sin, cos
+
+#define OPENCV_HAL_IMPL_MSA_BIN_FUNC(_Tpvec, func, intrin) \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint8x16, v_min, msa_minq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint8x16, v_max, msa_maxq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int8x16, v_min, msa_minq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int8x16, v_max, msa_maxq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint16x8, v_min, msa_minq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint16x8, v_max, msa_maxq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int16x8, v_min, msa_minq_s16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int16x8, v_max, msa_maxq_s16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint32x4, v_min, msa_minq_u32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint32x4, v_max, msa_maxq_u32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int32x4, v_min, msa_minq_s32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int32x4, v_max, msa_maxq_s32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_float32x4, v_min, msa_minq_f32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_float32x4, v_max, msa_maxq_f32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_float64x2, v_min, msa_minq_f64)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_float64x2, v_max, msa_maxq_f64)
+
+#define OPENCV_HAL_IMPL_MSA_INT_CMP_OP(_Tpvec, _Tpv, suffix, not_suffix) \
+inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_ceqq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_mvnq_##not_suffix(msa_ceqq_##suffix(a.val, b.val)))); } \
+inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_cltq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_gt(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_cgtq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_cleq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_cgeq_##suffix(a.val, b.val))); }
+
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_uint8x16, v16u8, u8, u8)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_int8x16, v16i8, s8, u8)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_uint16x8, v8u16, u16, u16)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_int16x8, v8i16, s16, u16)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_uint32x4, v4u32, u32, u32)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_int32x4, v4i32, s32, u32)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_float32x4, v4f32, f32, u32)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_uint64x2, v2u64, u64, u64)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_int64x2, v2i64, s64, u64)
+OPENCV_HAL_IMPL_MSA_INT_CMP_OP(v_float64x2, v2f64, f64, u64)
+
+inline v_float32x4 v_not_nan(const v_float32x4& a)
+{ return v_float32x4(MSA_TPV_REINTERPRET(v4f32, msa_ceqq_f32(a.val, a.val))); }
+inline v_float64x2 v_not_nan(const v_float64x2& a)
+{ return v_float64x2(MSA_TPV_REINTERPRET(v2f64, msa_ceqq_f64(a.val, a.val))); }
+
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint8x16, v_add_wrap, msa_addq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int8x16, v_add_wrap, msa_addq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint16x8, v_add_wrap, msa_addq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int16x8, v_add_wrap, msa_addq_s16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint8x16, v_sub_wrap, msa_subq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int8x16, v_sub_wrap, msa_subq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint16x8, v_sub_wrap, msa_subq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int16x8, v_sub_wrap, msa_subq_s16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint8x16, v_mul_wrap, msa_mulq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int8x16, v_mul_wrap, msa_mulq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint16x8, v_mul_wrap, msa_mulq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int16x8, v_mul_wrap, msa_mulq_s16)
+
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint8x16, v_absdiff, msa_abdq_u8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint16x8, v_absdiff, msa_abdq_u16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_uint32x4, v_absdiff, msa_abdq_u32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_float32x4, v_absdiff, msa_abdq_f32)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_float64x2, v_absdiff, msa_abdq_f64)
+
+/** Saturating absolute difference **/
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int8x16, v_absdiffs, msa_qabdq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC(v_int16x8, v_absdiffs, msa_qabdq_s16)
+
+#define OPENCV_HAL_IMPL_MSA_BIN_FUNC2(_Tpvec, _Tpvec2, _Tpv, func, intrin) \
+inline _Tpvec2 func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec2(MSA_TPV_REINTERPRET(_Tpv, intrin(a.val, b.val))); \
+}
+
+OPENCV_HAL_IMPL_MSA_BIN_FUNC2(v_int8x16, v_uint8x16, v16u8, v_absdiff, msa_abdq_s8)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC2(v_int16x8, v_uint16x8, v8u16, v_absdiff, msa_abdq_s16)
+OPENCV_HAL_IMPL_MSA_BIN_FUNC2(v_int32x4, v_uint32x4, v4u32, v_absdiff, msa_abdq_s32)
+
+/* v_magnitude, v_sqr_magnitude, v_fma, v_muladd */
+inline v_float32x4 v_magnitude(const v_float32x4& a, const v_float32x4& b)
+{
+    v_float32x4 x(msa_mlaq_f32(msa_mulq_f32(a.val, a.val), b.val, b.val));
+    return v_sqrt(x);
+}
+
+inline v_float32x4 v_sqr_magnitude(const v_float32x4& a, const v_float32x4& b)
+{
+    return v_float32x4(msa_mlaq_f32(msa_mulq_f32(a.val, a.val), b.val, b.val));
+}
+
+inline v_float32x4 v_fma(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+    return v_float32x4(msa_mlaq_f32(c.val, a.val, b.val));
+}
+
+inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_int32x4(msa_mlaq_s32(c.val, a.val, b.val));
+}
+
+inline v_float32x4 v_muladd(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_float64x2 v_magnitude(const v_float64x2& a, const v_float64x2& b)
+{
+    v_float64x2 x(msa_mlaq_f64(msa_mulq_f64(a.val, a.val), b.val, b.val));
+    return v_sqrt(x);
+}
+
+inline v_float64x2 v_sqr_magnitude(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float64x2(msa_mlaq_f64(msa_mulq_f64(a.val, a.val), b.val, b.val));
+}
+
+inline v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+    return v_float64x2(msa_mlaq_f64(c.val, a.val, b.val));
+}
+
+inline v_float64x2 v_muladd(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+    return v_fma(a, b, c);
+}
+
+// trade efficiency for convenience
+#define OPENCV_HAL_IMPL_MSA_SHIFT_OP(_Tpvec, suffix, _Tps, ssuffix) \
+inline _Tpvec v_shl(const _Tpvec& a, int n) \
+{ return _Tpvec(msa_shlq_##suffix(a.val, msa_dupq_n_##ssuffix((_Tps)n))); } \
+inline _Tpvec v_shr(const _Tpvec& a, int n) \
+{ return _Tpvec(msa_shrq_##suffix(a.val, msa_dupq_n_##ssuffix((_Tps)n))); } \
+template<int n> inline _Tpvec v_shl(const _Tpvec& a) \
+{ return _Tpvec(msa_shlq_n_##suffix(a.val, n)); } \
+template<int n> inline _Tpvec v_shr(const _Tpvec& a) \
+{ return _Tpvec(msa_shrq_n_##suffix(a.val, n)); } \
+template<int n> inline _Tpvec v_rshr(const _Tpvec& a) \
+{ return _Tpvec(msa_rshrq_n_##suffix(a.val, n)); }
+
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_uint8x16, u8, schar, s8)
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_int8x16, s8, schar, s8)
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_uint16x8, u16, short, s16)
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_int16x8, s16, short, s16)
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_uint32x4, u32, int, s32)
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_int32x4, s32, int, s32)
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_uint64x2, u64, int64, s64)
+OPENCV_HAL_IMPL_MSA_SHIFT_OP(v_int64x2, s64, int64, s64)
+
+/* v_rotate_right, v_rotate_left */
+#define OPENCV_HAL_IMPL_MSA_ROTATE_OP(_Tpvec, _Tpv, _Tpvs, suffix) \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_extq_##suffix(MSA_TPV_REINTERPRET(_Tpvs, a.val), msa_dupq_n_##suffix(0), n))); \
+} \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_extq_##suffix(msa_dupq_n_##suffix(0), MSA_TPV_REINTERPRET(_Tpvs, a.val), _Tpvec::nlanes - n))); \
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a) \
+{ \
+    return a; \
+} \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_extq_##suffix(MSA_TPV_REINTERPRET(_Tpvs, a.val), MSA_TPV_REINTERPRET(_Tpvs, b.val), n))); \
+} \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_extq_##suffix(MSA_TPV_REINTERPRET(_Tpvs, b.val), MSA_TPV_REINTERPRET(_Tpvs, a.val), _Tpvec::nlanes - n))); \
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    CV_UNUSED(b); \
+    return a; \
+}
+
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_uint8x16, v16u8, v16i8, s8)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_int8x16, v16i8, v16i8, s8)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_uint16x8, v8u16, v8i16, s16)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_int16x8, v8i16, v8i16, s16)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_uint32x4, v4u32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_int32x4, v4i32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_float32x4, v4f32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_uint64x2, v2u64, v2i64, s64)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_int64x2, v2i64, v2i64, s64)
+OPENCV_HAL_IMPL_MSA_ROTATE_OP(v_float64x2, v2f64, v2i64, s64)
+
+#define OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(_Tpvec, _Tp, suffix) \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec(msa_ld1q_##suffix(ptr)); } \
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(msa_ld1q_##suffix(ptr)); } \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ return _Tpvec(msa_combine_##suffix(msa_ld1_##suffix(ptr), msa_dup_n_##suffix((_Tp)0))); } \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ return _Tpvec(msa_combine_##suffix(msa_ld1_##suffix(ptr0), msa_ld1_##suffix(ptr1))); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ msa_st1q_##suffix(ptr, a.val); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ msa_st1q_##suffix(ptr, a.val); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ msa_st1q_##suffix(ptr, a.val); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \
+{ msa_st1q_##suffix(ptr, a.val); } \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ \
+    int n  = _Tpvec::nlanes; \
+    for( int i = 0; i < (n/2); i++ ) \
+        ptr[i] = a.val[i]; \
+} \
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ \
+    int n  = _Tpvec::nlanes; \
+    for( int i = 0; i < (n/2); i++ ) \
+        ptr[i] = a.val[i+(n/2)]; \
+}
+
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_int8x16, schar, s8)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_int16x8, short, s16)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_int32x4, int, s32)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_int64x2, int64, s64)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_float32x4, float, f32)
+OPENCV_HAL_IMPL_MSA_LOADSTORE_OP(v_float64x2, double, f64)
+
+
+/** Reverse **/
+inline v_uint8x16 v_reverse(const v_uint8x16 &a)
+{
+    v_uint8x16 c = v_uint8x16((v16u8)__builtin_msa_vshf_b((v16i8)((v2i64){0x08090A0B0C0D0E0F, 0x0001020304050607}), msa_dupq_n_s8(0), (v16i8)a.val));
+    return c;
+}
+
+inline v_int8x16 v_reverse(const v_int8x16 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x8 v_reverse(const v_uint16x8 &a)
+{
+    v_uint16x8 c = v_uint16x8((v8u16)__builtin_msa_vshf_h((v8i16)((v2i64){0x0004000500060007, 0x0000000100020003}), msa_dupq_n_s16(0), (v8i16)a.val));
+    return c;
+}
+
+inline v_int16x8 v_reverse(const v_int16x8 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x4 v_reverse(const v_uint32x4 &a)
+{
+    v_uint32x4 c;
+    c.val[0] = a.val[3];
+    c.val[1] = a.val[2];
+    c.val[2] = a.val[1];
+    c.val[3] = a.val[0];
+    return c;
+}
+
+inline v_int32x4 v_reverse(const v_int32x4 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x4 v_reverse(const v_float32x4 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x2 v_reverse(const v_uint64x2 &a)
+{
+    v_uint64x2 c;
+    c.val[0] = a.val[1];
+    c.val[1] = a.val[0];
+    return c;
+}
+
+inline v_int64x2 v_reverse(const v_int64x2 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+inline v_float64x2 v_reverse(const v_float64x2 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+
+#define OPENCV_HAL_IMPL_MSA_REDUCE_OP_8U(func, cfunc) \
+inline unsigned short v_reduce_##func(const v_uint16x8& a) \
+{ \
+    v8u16 a_lo, a_hi; \
+    ILVRL_H2_UH(a.val, msa_dupq_n_u16(0), a_lo, a_hi); \
+    v4u32 b = msa_##func##q_u32(msa_paddlq_u16(a_lo), msa_paddlq_u16(a_hi)); \
+    v4u32 b_lo, b_hi; \
+    ILVRL_W2_UW(b, msa_dupq_n_u32(0), b_lo, b_hi); \
+    v2u64 c = msa_##func##q_u64(msa_paddlq_u32(b_lo), msa_paddlq_u32(b_hi)); \
+    return (unsigned short)cfunc(c[0], c[1]); \
+}
+
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_8U(max, std::max)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_8U(min, std::min)
+
+#define OPENCV_HAL_IMPL_MSA_REDUCE_OP_8S(func, cfunc) \
+inline short v_reduce_##func(const v_int16x8& a) \
+{ \
+    v8i16 a_lo, a_hi; \
+    ILVRL_H2_SH(a.val, msa_dupq_n_s16(0), a_lo, a_hi); \
+    v4i32 b = msa_##func##q_s32(msa_paddlq_s16(a_lo), msa_paddlq_s16(a_hi)); \
+    v4i32 b_lo, b_hi; \
+    ILVRL_W2_SW(b, msa_dupq_n_s32(0), b_lo, b_hi); \
+    v2i64 c = msa_##func##q_s64(msa_paddlq_s32(b_lo), msa_paddlq_s32(b_hi)); \
+    return (short)cfunc(c[0], c[1]); \
+}
+
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_8S(max, std::max)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_8S(min, std::min)
+
+#define OPENCV_HAL_IMPL_MSA_REDUCE_OP_4(_Tpvec, scalartype, func, cfunc) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    return (scalartype)cfunc(cfunc(a.val[0], a.val[1]), cfunc(a.val[2], a.val[3])); \
+}
+
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_4(v_uint32x4, unsigned, max, std::max)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_4(v_uint32x4, unsigned, min, std::min)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_4(v_int32x4, int, max, std::max)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_4(v_int32x4, int, min, std::min)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_4(v_float32x4, float, max, std::max)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_4(v_float32x4, float, min, std::min)
+
+
+#define OPENCV_HAL_IMPL_MSA_REDUCE_OP_16(_Tpvec, scalartype, _Tpvec2, func) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    _Tpvec2 a1, a2; \
+    v_expand(a, a1, a2); \
+    return (scalartype)v_reduce_##func(v_##func(a1, a2)); \
+}
+
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_16(v_uint8x16, uchar, v_uint16x8, min)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_16(v_uint8x16, uchar, v_uint16x8, max)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_16(v_int8x16, char, v_int16x8, min)
+OPENCV_HAL_IMPL_MSA_REDUCE_OP_16(v_int8x16, char, v_int16x8, max)
+
+
+
+#define OPENCV_HAL_IMPL_MSA_REDUCE_SUM(_Tpvec, scalartype, suffix) \
+inline scalartype v_reduce_sum(const _Tpvec& a) \
+{ \
+    return (scalartype)msa_sum_##suffix(a.val); \
+}
+
+OPENCV_HAL_IMPL_MSA_REDUCE_SUM(v_uint8x16, unsigned short, u8)
+OPENCV_HAL_IMPL_MSA_REDUCE_SUM(v_int8x16, short, s8)
+OPENCV_HAL_IMPL_MSA_REDUCE_SUM(v_uint16x8, unsigned, u16)
+OPENCV_HAL_IMPL_MSA_REDUCE_SUM(v_int16x8, int, s16)
+OPENCV_HAL_IMPL_MSA_REDUCE_SUM(v_uint32x4, uint64_t, u32)
+OPENCV_HAL_IMPL_MSA_REDUCE_SUM(v_int32x4, int64_t, s32)
+OPENCV_HAL_IMPL_MSA_REDUCE_SUM(v_float32x4, float, f32)
+
+inline uint64 v_reduce_sum(const v_uint64x2& a)
+{ return (uint64)(msa_getq_lane_u64(a.val, 0) + msa_getq_lane_u64(a.val, 1)); }
+inline int64 v_reduce_sum(const v_int64x2& a)
+{ return (int64)(msa_getq_lane_s64(a.val, 0) + msa_getq_lane_s64(a.val, 1)); }
+inline double v_reduce_sum(const v_float64x2& a)
+{
+    return msa_getq_lane_f64(a.val, 0) + msa_getq_lane_f64(a.val, 1);
+}
+
+/* v_reduce_sum4, v_reduce_sad */
+inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b,
+                                 const v_float32x4& c, const v_float32x4& d)
+{
+    v4f32 u0 = msa_addq_f32(MSA_TPV_REINTERPRET(v4f32, msa_ilvevq_s32(MSA_TPV_REINTERPRET(v4i32, b.val), MSA_TPV_REINTERPRET(v4i32, a.val))),
+                            MSA_TPV_REINTERPRET(v4f32, msa_ilvodq_s32(MSA_TPV_REINTERPRET(v4i32, b.val), MSA_TPV_REINTERPRET(v4i32, a.val)))); // a0+a1 b0+b1 a2+a3 b2+b3
+    v4f32 u1 = msa_addq_f32(MSA_TPV_REINTERPRET(v4f32, msa_ilvevq_s32(MSA_TPV_REINTERPRET(v4i32, d.val), MSA_TPV_REINTERPRET(v4i32, c.val))),
+                            MSA_TPV_REINTERPRET(v4f32, msa_ilvodq_s32(MSA_TPV_REINTERPRET(v4i32, d.val), MSA_TPV_REINTERPRET(v4i32, c.val)))); // c0+c1 d0+d1 c2+c3 d2+d3
+
+    return v_float32x4(msa_addq_f32(MSA_TPV_REINTERPRET(v4f32, msa_ilvrq_s64(MSA_TPV_REINTERPRET(v2i64, u1), MSA_TPV_REINTERPRET(v2i64, u0))),
+                                    MSA_TPV_REINTERPRET(v4f32, msa_ilvlq_s64(MSA_TPV_REINTERPRET(v2i64, u1), MSA_TPV_REINTERPRET(v2i64, u0)))));
+}
+
+inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b)
+{
+    v16u8 t0 = msa_abdq_u8(a.val, b.val);
+    v8u16 t1 = msa_paddlq_u8(t0);
+    v4u32 t2 = msa_paddlq_u16(t1);
+    return msa_sum_u32(t2);
+}
+inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b)
+{
+    v16u8 t0 = MSA_TPV_REINTERPRET(v16u8, msa_abdq_s8(a.val, b.val));
+    v8u16 t1 = msa_paddlq_u8(t0);
+    v4u32 t2 = msa_paddlq_u16(t1);
+    return msa_sum_u32(t2);
+}
+inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v8u16 t0 = msa_abdq_u16(a.val, b.val);
+    v4u32 t1 = msa_paddlq_u16(t0);
+    return msa_sum_u32(t1);
+}
+inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b)
+{
+    v8u16 t0 = MSA_TPV_REINTERPRET(v8u16, msa_abdq_s16(a.val, b.val));
+    v4u32 t1 = msa_paddlq_u16(t0);
+    return msa_sum_u32(t1);
+}
+inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b)
+{
+    v4u32 t0 = msa_abdq_u32(a.val, b.val);
+    return msa_sum_u32(t0);
+}
+inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b)
+{
+    v4u32 t0 = MSA_TPV_REINTERPRET(v4u32, msa_abdq_s32(a.val, b.val));
+    return msa_sum_u32(t0);
+}
+inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b)
+{
+    v4f32 t0 = msa_abdq_f32(a.val, b.val);
+    return msa_sum_f32(t0);
+}
+
+/* v_popcount */
+#define OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE8(_Tpvec) \
+inline v_uint8x16 v_popcount(const _Tpvec& a) \
+{ \
+    v16u8 t = MSA_TPV_REINTERPRET(v16u8, msa_cntq_s8(MSA_TPV_REINTERPRET(v16i8, a.val))); \
+    return v_uint8x16(t); \
+}
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE8(v_uint8x16)
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE8(v_int8x16)
+
+#define OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE16(_Tpvec) \
+inline v_uint16x8 v_popcount(const _Tpvec& a) \
+{ \
+    v8u16 t = MSA_TPV_REINTERPRET(v8u16, msa_cntq_s16(MSA_TPV_REINTERPRET(v8i16, a.val))); \
+    return v_uint16x8(t); \
+}
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE16(v_uint16x8)
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE16(v_int16x8)
+
+#define OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE32(_Tpvec) \
+inline v_uint32x4 v_popcount(const _Tpvec& a) \
+{ \
+    v4u32 t = MSA_TPV_REINTERPRET(v4u32, msa_cntq_s32(MSA_TPV_REINTERPRET(v4i32, a.val))); \
+    return v_uint32x4(t); \
+}
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE32(v_uint32x4)
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE32(v_int32x4)
+
+#define OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE64(_Tpvec) \
+inline v_uint64x2 v_popcount(const _Tpvec& a) \
+{ \
+    v2u64 t = MSA_TPV_REINTERPRET(v2u64, msa_cntq_s64(MSA_TPV_REINTERPRET(v2i64, a.val))); \
+    return v_uint64x2(t); \
+}
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE64(v_uint64x2)
+OPENCV_HAL_IMPL_MSA_POPCOUNT_SIZE64(v_int64x2)
+
+inline int v_signmask(const v_uint8x16& a)
+{
+    v8i8 m0 = msa_create_s8(CV_BIG_UINT(0x0706050403020100));
+    v16u8 v0 = msa_shlq_u8(msa_shrq_n_u8(a.val, 7), msa_combine_s8(m0, m0));
+    v8u16 v1 = msa_paddlq_u8(v0);
+    v4u32 v2 = msa_paddlq_u16(v1);
+    v2u64 v3 = msa_paddlq_u32(v2);
+    return (int)msa_getq_lane_u64(v3, 0) + ((int)msa_getq_lane_u64(v3, 1) << 8);
+}
+inline int v_signmask(const v_int8x16& a)
+{ return v_signmask(v_reinterpret_as_u8(a)); }
+
+inline int v_signmask(const v_uint16x8& a)
+{
+    v4i16 m0 = msa_create_s16(CV_BIG_UINT(0x0003000200010000));
+    v8u16 v0 = msa_shlq_u16(msa_shrq_n_u16(a.val, 15), msa_combine_s16(m0, m0));
+    v4u32 v1 = msa_paddlq_u16(v0);
+    v2u64 v2 = msa_paddlq_u32(v1);
+    return (int)msa_getq_lane_u64(v2, 0) + ((int)msa_getq_lane_u64(v2, 1) << 4);
+}
+inline int v_signmask(const v_int16x8& a)
+{ return v_signmask(v_reinterpret_as_u16(a)); }
+
+inline int v_signmask(const v_uint32x4& a)
+{
+    v2i32 m0 = msa_create_s32(CV_BIG_UINT(0x0000000100000000));
+    v4u32 v0 = msa_shlq_u32(msa_shrq_n_u32(a.val, 31), msa_combine_s32(m0, m0));
+    v2u64 v1 = msa_paddlq_u32(v0);
+    return (int)msa_getq_lane_u64(v1, 0) + ((int)msa_getq_lane_u64(v1, 1) << 2);
+}
+inline int v_signmask(const v_int32x4& a)
+{ return v_signmask(v_reinterpret_as_u32(a)); }
+inline int v_signmask(const v_float32x4& a)
+{ return v_signmask(v_reinterpret_as_u32(a)); }
+
+inline int v_signmask(const v_uint64x2& a)
+{
+    v2u64 v0 = msa_shrq_n_u64(a.val, 63);
+    return (int)msa_getq_lane_u64(v0, 0) + ((int)msa_getq_lane_u64(v0, 1) << 1);
+}
+inline int v_signmask(const v_int64x2& a)
+{ return v_signmask(v_reinterpret_as_u64(a)); }
+inline int v_signmask(const v_float64x2& a)
+{ return v_signmask(v_reinterpret_as_u64(a)); }
+
+inline int v_scan_forward(const v_int8x16& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint8x16& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int16x8& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint16x8& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_float32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int64x2& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint64x2& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_float64x2& a) { return trailingZeros32(v_signmask(a)); }
+
+#define OPENCV_HAL_IMPL_MSA_CHECK_ALLANY(_Tpvec, _Tpvec2, suffix, shift) \
+inline bool v_check_all(const v_##_Tpvec& a) \
+{ \
+    _Tpvec2 v0 = msa_shrq_n_##suffix(msa_mvnq_##suffix(a.val), shift); \
+    v2u64 v1 = MSA_TPV_REINTERPRET(v2u64, v0); \
+    return (msa_getq_lane_u64(v1, 0) | msa_getq_lane_u64(v1, 1)) == 0; \
+} \
+inline bool v_check_any(const v_##_Tpvec& a) \
+{ \
+    _Tpvec2 v0 = msa_shrq_n_##suffix(a.val, shift); \
+    v2u64 v1 = MSA_TPV_REINTERPRET(v2u64, v0); \
+    return (msa_getq_lane_u64(v1, 0) | msa_getq_lane_u64(v1, 1)) != 0; \
+}
+
+OPENCV_HAL_IMPL_MSA_CHECK_ALLANY(uint8x16, v16u8, u8, 7)
+OPENCV_HAL_IMPL_MSA_CHECK_ALLANY(uint16x8, v8u16, u16, 15)
+OPENCV_HAL_IMPL_MSA_CHECK_ALLANY(uint32x4, v4u32, u32, 31)
+OPENCV_HAL_IMPL_MSA_CHECK_ALLANY(uint64x2, v2u64, u64, 63)
+
+inline bool v_check_all(const v_int8x16& a)
+{ return v_check_all(v_reinterpret_as_u8(a)); }
+inline bool v_check_all(const v_int16x8& a)
+{ return v_check_all(v_reinterpret_as_u16(a)); }
+inline bool v_check_all(const v_int32x4& a)
+{ return v_check_all(v_reinterpret_as_u32(a)); }
+inline bool v_check_all(const v_float32x4& a)
+{ return v_check_all(v_reinterpret_as_u32(a)); }
+
+inline bool v_check_any(const v_int8x16& a)
+{ return v_check_any(v_reinterpret_as_u8(a)); }
+inline bool v_check_any(const v_int16x8& a)
+{ return v_check_any(v_reinterpret_as_u16(a)); }
+inline bool v_check_any(const v_int32x4& a)
+{ return v_check_any(v_reinterpret_as_u32(a)); }
+inline bool v_check_any(const v_float32x4& a)
+{ return v_check_any(v_reinterpret_as_u32(a)); }
+
+inline bool v_check_all(const v_int64x2& a)
+{ return v_check_all(v_reinterpret_as_u64(a)); }
+inline bool v_check_all(const v_float64x2& a)
+{ return v_check_all(v_reinterpret_as_u64(a)); }
+inline bool v_check_any(const v_int64x2& a)
+{ return v_check_any(v_reinterpret_as_u64(a)); }
+inline bool v_check_any(const v_float64x2& a)
+{ return v_check_any(v_reinterpret_as_u64(a)); }
+
+/* v_select */
+#define OPENCV_HAL_IMPL_MSA_SELECT(_Tpvec, _Tpv, _Tpvu) \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_bslq_u8(MSA_TPV_REINTERPRET(_Tpvu, mask.val), \
+                  MSA_TPV_REINTERPRET(_Tpvu, b.val), MSA_TPV_REINTERPRET(_Tpvu, a.val)))); \
+}
+
+OPENCV_HAL_IMPL_MSA_SELECT(v_uint8x16, v16u8, v16u8)
+OPENCV_HAL_IMPL_MSA_SELECT(v_int8x16, v16i8, v16u8)
+OPENCV_HAL_IMPL_MSA_SELECT(v_uint16x8, v8u16, v16u8)
+OPENCV_HAL_IMPL_MSA_SELECT(v_int16x8, v8i16, v16u8)
+OPENCV_HAL_IMPL_MSA_SELECT(v_uint32x4, v4u32, v16u8)
+OPENCV_HAL_IMPL_MSA_SELECT(v_int32x4, v4i32, v16u8)
+OPENCV_HAL_IMPL_MSA_SELECT(v_float32x4, v4f32, v16u8)
+OPENCV_HAL_IMPL_MSA_SELECT(v_float64x2, v2f64, v16u8)
+
+#define OPENCV_HAL_IMPL_MSA_EXPAND(_Tpvec, _Tpwvec, _Tp, suffix, ssuffix, _Tpv, _Tpvs) \
+inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
+{ \
+    _Tpv a_lo = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a.val), msa_dupq_n_##ssuffix(0))); \
+    _Tpv a_hi = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a.val), msa_dupq_n_##ssuffix(0))); \
+    b0.val = msa_paddlq_##suffix(a_lo); \
+    b1.val = msa_paddlq_##suffix(a_hi); \
+} \
+inline _Tpwvec v_expand_low(const _Tpvec& a) \
+{ \
+    _Tpv a_lo = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a.val), msa_dupq_n_##ssuffix(0))); \
+    return _Tpwvec(msa_paddlq_##suffix(a_lo)); \
+} \
+inline _Tpwvec v_expand_high(const _Tpvec& a) \
+{ \
+    _Tpv a_hi = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a.val), msa_dupq_n_##ssuffix(0))); \
+    return _Tpwvec(msa_paddlq_##suffix(a_hi)); \
+} \
+inline _Tpwvec v_load_expand(const _Tp* ptr) \
+{ \
+    return _Tpwvec(msa_movl_##suffix(msa_ld1_##suffix(ptr))); \
+}
+
+OPENCV_HAL_IMPL_MSA_EXPAND(v_uint8x16, v_uint16x8, uchar, u8, s8, v16u8, v16i8)
+OPENCV_HAL_IMPL_MSA_EXPAND(v_int8x16, v_int16x8, schar, s8, s8, v16i8, v16i8)
+OPENCV_HAL_IMPL_MSA_EXPAND(v_uint16x8, v_uint32x4, ushort, u16, s16, v8u16, v8i16)
+OPENCV_HAL_IMPL_MSA_EXPAND(v_int16x8, v_int32x4, short, s16, s16, v8i16, v8i16)
+OPENCV_HAL_IMPL_MSA_EXPAND(v_uint32x4, v_uint64x2, uint, u32, s32, v4u32, v4i32)
+OPENCV_HAL_IMPL_MSA_EXPAND(v_int32x4, v_int64x2, int, s32, s32, v4i32, v4i32)
+
+inline v_uint32x4 v_load_expand_q(const uchar* ptr)
+{
+    return v_uint32x4((v4u32){ptr[0], ptr[1], ptr[2], ptr[3]});
+}
+
+inline v_int32x4 v_load_expand_q(const schar* ptr)
+{
+    return v_int32x4((v4i32){ptr[0], ptr[1], ptr[2], ptr[3]});
+}
+
+/* v_zip, v_combine_low, v_combine_high, v_recombine */
+#define OPENCV_HAL_IMPL_MSA_UNPACKS(_Tpvec, _Tpv, _Tpvs, ssuffix) \
+inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1) \
+{ \
+    b0.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a1.val), MSA_TPV_REINTERPRET(_Tpvs, a0.val))); \
+    b1.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a1.val), MSA_TPV_REINTERPRET(_Tpvs, a0.val))); \
+} \
+inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_s64(MSA_TPV_REINTERPRET(v2i64, b.val), MSA_TPV_REINTERPRET(v2i64, a.val)))); \
+} \
+inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_s64(MSA_TPV_REINTERPRET(v2i64, b.val), MSA_TPV_REINTERPRET(v2i64, a.val)))); \
+} \
+inline void v_recombine(const _Tpvec& a, const _Tpvec& b, _Tpvec& c, _Tpvec& d) \
+{ \
+    c.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_s64(MSA_TPV_REINTERPRET(v2i64, b.val), MSA_TPV_REINTERPRET(v2i64, a.val))); \
+    d.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_s64(MSA_TPV_REINTERPRET(v2i64, b.val), MSA_TPV_REINTERPRET(v2i64, a.val))); \
+}
+
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_uint8x16, v16u8, v16i8, s8)
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_int8x16, v16i8, v16i8, s8)
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_uint16x8, v8u16, v8i16, s16)
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_int16x8, v8i16, v8i16, s16)
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_uint32x4, v4u32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_int32x4, v4i32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_float32x4, v4f32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_UNPACKS(v_float64x2, v2f64, v2i64, s64)
+
+/* v_extract */
+#define OPENCV_HAL_IMPL_MSA_EXTRACT(_Tpvec, _Tpv, _Tpvs, suffix) \
+template <int s> \
+inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(MSA_TPV_REINTERPRET(_Tpv, msa_extq_##suffix(MSA_TPV_REINTERPRET(_Tpvs, a.val), MSA_TPV_REINTERPRET(_Tpvs, b.val), s))); \
+}
+
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_uint8x16, v16u8, v16i8, s8)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_int8x16, v16i8, v16i8, s8)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_uint16x8, v8u16, v8i16, s16)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_int16x8, v8i16, v8i16, s16)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_uint32x4, v4u32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_int32x4, v4i32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_uint64x2, v2u64, v2i64, s64)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_int64x2, v2i64, v2i64, s64)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_float32x4, v4f32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_EXTRACT(v_float64x2, v2f64, v2i64, s64)
+
+/* v_round, v_floor, v_ceil, v_trunc */
+inline v_int32x4 v_round(const v_float32x4& a)
+{
+    return v_int32x4(msa_cvttintq_s32_f32(a.val));
+}
+
+inline v_int32x4 v_floor(const v_float32x4& a)
+{
+    v4i32 a1 = msa_cvttintq_s32_f32(a.val);
+    return v_int32x4(msa_addq_s32(a1, MSA_TPV_REINTERPRET(v4i32, msa_cgtq_f32(msa_cvtfintq_f32_s32(a1), a.val))));
+}
+
+inline v_int32x4 v_ceil(const v_float32x4& a)
+{
+    v4i32 a1 = msa_cvttintq_s32_f32(a.val);
+    return v_int32x4(msa_subq_s32(a1, MSA_TPV_REINTERPRET(v4i32, msa_cgtq_f32(a.val, msa_cvtfintq_f32_s32(a1)))));
+}
+
+inline v_int32x4 v_trunc(const v_float32x4& a)
+{
+    return v_int32x4(msa_cvttruncq_s32_f32(a.val));
+}
+
+inline v_int32x4 v_round(const v_float64x2& a)
+{
+    return v_int32x4(msa_pack_s64(msa_cvttintq_s64_f64(a.val), msa_dupq_n_s64(0)));
+}
+
+inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_int32x4(msa_pack_s64(msa_cvttintq_s64_f64(a.val), msa_cvttintq_s64_f64(b.val)));
+}
+
+inline v_int32x4 v_floor(const v_float64x2& a)
+{
+    v2f64 a1 = msa_cvtrintq_f64(a.val);
+    return v_int32x4(msa_pack_s64(msa_addq_s64(msa_cvttruncq_s64_f64(a1), MSA_TPV_REINTERPRET(v2i64, msa_cgtq_f64(a1, a.val))), msa_dupq_n_s64(0)));
+}
+
+inline v_int32x4 v_ceil(const v_float64x2& a)
+{
+    v2f64 a1 = msa_cvtrintq_f64(a.val);
+    return v_int32x4(msa_pack_s64(msa_subq_s64(msa_cvttruncq_s64_f64(a1), MSA_TPV_REINTERPRET(v2i64, msa_cgtq_f64(a.val, a1))), msa_dupq_n_s64(0)));
+}
+
+inline v_int32x4 v_trunc(const v_float64x2& a)
+{
+    return v_int32x4(msa_pack_s64(msa_cvttruncq_s64_f64(a.val), msa_dupq_n_s64(0)));
+}
+
+#define OPENCV_HAL_IMPL_MSA_TRANSPOSE4x4(_Tpvec, _Tpv, _Tpvs, ssuffix) \
+inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1, \
+                           const _Tpvec& a2, const _Tpvec& a3, \
+                           _Tpvec& b0, _Tpvec& b1, \
+                           _Tpvec& b2, _Tpvec& b3) \
+{ \
+    _Tpv t00 = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a1.val), MSA_TPV_REINTERPRET(_Tpvs, a0.val))); \
+    _Tpv t01 = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a1.val), MSA_TPV_REINTERPRET(_Tpvs, a0.val))); \
+    _Tpv t10 = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a3.val), MSA_TPV_REINTERPRET(_Tpvs, a2.val))); \
+    _Tpv t11 = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_##ssuffix(MSA_TPV_REINTERPRET(_Tpvs, a3.val), MSA_TPV_REINTERPRET(_Tpvs, a2.val))); \
+    b0.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_s64(MSA_TPV_REINTERPRET(v2i64, t10), MSA_TPV_REINTERPRET(v2i64, t00))); \
+    b1.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_s64(MSA_TPV_REINTERPRET(v2i64, t10), MSA_TPV_REINTERPRET(v2i64, t00))); \
+    b2.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvrq_s64(MSA_TPV_REINTERPRET(v2i64, t11), MSA_TPV_REINTERPRET(v2i64, t01))); \
+    b3.val = MSA_TPV_REINTERPRET(_Tpv, msa_ilvlq_s64(MSA_TPV_REINTERPRET(v2i64, t11), MSA_TPV_REINTERPRET(v2i64, t01))); \
+}
+
+OPENCV_HAL_IMPL_MSA_TRANSPOSE4x4(v_uint32x4, v4u32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_TRANSPOSE4x4(v_int32x4, v4i32, v4i32, s32)
+OPENCV_HAL_IMPL_MSA_TRANSPOSE4x4(v_float32x4, v4f32, v4i32, s32)
+
+#define OPENCV_HAL_IMPL_MSA_INTERLEAVED(_Tpvec, _Tp, suffix) \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b) \
+{ \
+    msa_ld2q_##suffix(ptr, &a.val, &b.val); \
+} \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, v_##_Tpvec& c) \
+{ \
+    msa_ld3q_##suffix(ptr, &a.val, &b.val, &c.val); \
+} \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, \
+                                v_##_Tpvec& c, v_##_Tpvec& d) \
+{ \
+    msa_ld4q_##suffix(ptr, &a.val, &b.val, &c.val, &d.val); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    msa_st2q_##suffix(ptr, a.val, b.val); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                const v_##_Tpvec& c, hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    msa_st3q_##suffix(ptr, a.val, b.val, c.val); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                const v_##_Tpvec& c, const v_##_Tpvec& d, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ \
+    msa_st4q_##suffix(ptr, a.val, b.val, c.val, d.val); \
+}
+
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(int8x16, schar, s8)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(int16x8, short, s16)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(int32x4, int, s32)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(float32x4, float, f32)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(int64x2, int64, s64)
+OPENCV_HAL_IMPL_MSA_INTERLEAVED(float64x2, double, f64)
+
+/* v_cvt_f32, v_cvt_f64, v_cvt_f64_high */
+inline v_float32x4 v_cvt_f32(const v_int32x4& a)
+{
+    return v_float32x4(msa_cvtfintq_f32_s32(a.val));
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a)
+{
+    return v_float32x4(msa_cvtfq_f32_f64(a.val, msa_dupq_n_f64(0.0f)));
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float32x4(msa_cvtfq_f32_f64(a.val, b.val));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int32x4& a)
+{
+    return v_float64x2(msa_cvtflq_f64_f32(msa_cvtfintq_f32_s32(a.val)));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_int32x4& a)
+{
+    return v_float64x2(msa_cvtfhq_f64_f32(msa_cvtfintq_f32_s32(a.val)));
+}
+
+inline v_float64x2 v_cvt_f64(const v_float32x4& a)
+{
+    return v_float64x2(msa_cvtflq_f64_f32(a.val));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_float32x4& a)
+{
+    return v_float64x2(msa_cvtfhq_f64_f32(a.val));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int64x2& a)
+{
+    return v_float64x2(msa_cvtfintq_f64_s64(a.val));
+}
+
+////////////// Lookup table access ////////////////////
+inline v_int8x16 v_lut(const schar* tab, const int* idx)
+{
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[ 0]],
+        tab[idx[ 1]],
+        tab[idx[ 2]],
+        tab[idx[ 3]],
+        tab[idx[ 4]],
+        tab[idx[ 5]],
+        tab[idx[ 6]],
+        tab[idx[ 7]],
+        tab[idx[ 8]],
+        tab[idx[ 9]],
+        tab[idx[10]],
+        tab[idx[11]],
+        tab[idx[12]],
+        tab[idx[13]],
+        tab[idx[14]],
+        tab[idx[15]]
+    };
+    return v_int8x16(msa_ld1q_s8(elems));
+}
+inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx)
+{
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[3]],
+        tab[idx[3] + 1],
+        tab[idx[4]],
+        tab[idx[4] + 1],
+        tab[idx[5]],
+        tab[idx[5] + 1],
+        tab[idx[6]],
+        tab[idx[6] + 1],
+        tab[idx[7]],
+        tab[idx[7] + 1]
+    };
+    return v_int8x16(msa_ld1q_s8(elems));
+}
+inline v_int8x16 v_lut_quads(const schar* tab, const int* idx)
+{
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[0] + 2],
+        tab[idx[0] + 3],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[1] + 2],
+        tab[idx[1] + 3],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[2] + 2],
+        tab[idx[2] + 3],
+        tab[idx[3]],
+        tab[idx[3] + 1],
+        tab[idx[3] + 2],
+        tab[idx[3] + 3]
+    };
+    return v_int8x16(msa_ld1q_s8(elems));
+}
+inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((schar*)tab, idx)); }
+inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((schar*)tab, idx)); }
+inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((schar*)tab, idx)); }
+
+
+inline v_int16x8 v_lut(const short* tab, const int* idx)
+{
+    short CV_DECL_ALIGNED(32) elems[8] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]],
+        tab[idx[4]],
+        tab[idx[5]],
+        tab[idx[6]],
+        tab[idx[7]]
+    };
+    return v_int16x8(msa_ld1q_s16(elems));
+}
+inline v_int16x8 v_lut_pairs(const short* tab, const int* idx)
+{
+    short CV_DECL_ALIGNED(32) elems[8] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[3]],
+        tab[idx[3] + 1]
+    };
+    return v_int16x8(msa_ld1q_s16(elems));
+}
+inline v_int16x8 v_lut_quads(const short* tab, const int* idx)
+{
+    return v_int16x8(msa_combine_s16(msa_ld1_s16(tab + idx[0]), msa_ld1_s16(tab + idx[1])));
+}
+inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((short*)tab, idx)); }
+inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((short*)tab, idx)); }
+inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((short*)tab, idx)); }
+
+inline v_int32x4 v_lut(const int* tab, const int* idx)
+{
+    int CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]]
+    };
+    return v_int32x4(msa_ld1q_s32(elems));
+}
+inline v_int32x4 v_lut_pairs(const int* tab, const int* idx)
+{
+    return v_int32x4(msa_combine_s32(msa_ld1_s32(tab + idx[0]), msa_ld1_s32(tab + idx[1])));
+}
+inline v_int32x4 v_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x4(msa_ld1q_s32(tab + idx[0]));
+}
+inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((int*)tab, idx)); }
+inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((int*)tab, idx)); }
+inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((int*)tab, idx)); }
+
+inline v_int64x2 v_lut(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(msa_combine_s64(msa_create_s64(tab[idx[0]]), msa_create_s64(tab[idx[1]])));
+}
+inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(msa_ld1q_s64(tab + idx[0]));
+}
+inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); }
+inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); }
+
+inline v_float32x4 v_lut(const float* tab, const int* idx)
+{
+    float CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]]
+    };
+    return v_float32x4(msa_ld1q_f32(elems));
+}
+inline v_float32x4 v_lut_pairs(const float* tab, const int* idx)
+{
+    uint64 CV_DECL_ALIGNED(32) elems[2] =
+    {
+        *(uint64*)(tab + idx[0]),
+        *(uint64*)(tab + idx[1])
+    };
+    return v_float32x4(MSA_TPV_REINTERPRET(v4f32, msa_ld1q_u64(elems)));
+}
+inline v_float32x4 v_lut_quads(const float* tab, const int* idx)
+{
+    return v_float32x4(msa_ld1q_f32(tab + idx[0]));
+}
+
+inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    return v_int32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec)
+{
+    unsigned CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[msa_getq_lane_s32(idxvec.val, 0)],
+        tab[msa_getq_lane_s32(idxvec.val, 1)],
+        tab[msa_getq_lane_s32(idxvec.val, 2)],
+        tab[msa_getq_lane_s32(idxvec.val, 3)]
+    };
+    return v_uint32x4(msa_ld1q_u32(elems));
+}
+
+inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    return v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+
+inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    v4f32 xy02 = msa_combine_f32(msa_ld1_f32(tab + idx[0]), msa_ld1_f32(tab + idx[2]));
+    v4f32 xy13 = msa_combine_f32(msa_ld1_f32(tab + idx[1]), msa_ld1_f32(tab + idx[3]));
+    x = v_float32x4(MSA_TPV_REINTERPRET(v4f32, msa_ilvevq_s32(MSA_TPV_REINTERPRET(v4i32, xy13), MSA_TPV_REINTERPRET(v4i32, xy02))));
+    y = v_float32x4(MSA_TPV_REINTERPRET(v4f32, msa_ilvodq_s32(MSA_TPV_REINTERPRET(v4i32, xy13), MSA_TPV_REINTERPRET(v4i32, xy02))));
+}
+
+inline v_int8x16 v_interleave_pairs(const v_int8x16& vec)
+{
+    v_int8x16 c = v_int8x16(__builtin_msa_vshf_b((v16i8)((v2i64){0x0705060403010200, 0x0F0D0E0C0B090A08}), msa_dupq_n_s8(0), vec.val));
+    return c;
+}
+inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec)
+{ return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x16 v_interleave_quads(const v_int8x16& vec)
+{
+    v_int8x16 c = v_int8x16(__builtin_msa_vshf_b((v16i8)((v2i64){0x0703060205010400, 0x0F0B0E0A0D090C08}), msa_dupq_n_s8(0), vec.val));
+    return c;
+}
+inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_interleave_pairs(const v_int16x8& vec)
+{
+    v_int16x8 c = v_int16x8(__builtin_msa_vshf_h((v8i16)((v2i64){0x0003000100020000, 0x0007000500060004}), msa_dupq_n_s16(0), vec.val));
+    return c;
+}
+
+inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+
+inline v_int16x8 v_interleave_quads(const v_int16x8& vec)
+{
+    v_int16x8 c = v_int16x8(__builtin_msa_vshf_h((v8i16)((v2i64){0x0005000100040000, 0x0007000300060002}), msa_dupq_n_s16(0), vec.val));
+    return c;
+}
+
+inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_interleave_pairs(const v_int32x4& vec)
+{
+    v_int32x4 c;
+    c.val[0] = vec.val[0];
+    c.val[1] = vec.val[2];
+    c.val[2] = vec.val[1];
+    c.val[3] = vec.val[3];
+    return c;
+}
+
+inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x4 v_interleave_pairs(const v_float32x4& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x16 v_pack_triplets(const v_int8x16& vec)
+{
+    v_int8x16 c = v_int8x16(__builtin_msa_vshf_b((v16i8)((v2i64){0x0908060504020100, 0x131211100E0D0C0A}), msa_dupq_n_s8(0), vec.val));
+    return c;
+}
+
+inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_pack_triplets(const v_int16x8& vec)
+{
+    v_int16x8 c = v_int16x8(__builtin_msa_vshf_h((v8i16)((v2i64){0x0004000200010000, 0x0009000800060005}), msa_dupq_n_s16(0), vec.val));
+    return c;
+}
+
+inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; }
+inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; }
+inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; }
+
+inline v_float64x2 v_lut(const double* tab, const int* idx)
+{
+    double CV_DECL_ALIGNED(32) elems[2] =
+    {
+        tab[idx[0]],
+        tab[idx[1]]
+    };
+    return v_float64x2(msa_ld1q_f64(elems));
+}
+
+inline v_float64x2 v_lut_pairs(const double* tab, const int* idx)
+{
+    return v_float64x2(msa_ld1q_f64(tab + idx[0]));
+}
+
+inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    return v_float64x2(tab[idx[0]], tab[idx[1]]);
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    v2f64 xy0 = msa_ld1q_f64(tab + idx[0]);
+    v2f64 xy1 = msa_ld1q_f64(tab + idx[1]);
+    x = v_float64x2(MSA_TPV_REINTERPRET(v2f64, msa_ilvevq_s64(MSA_TPV_REINTERPRET(v2i64, xy1), MSA_TPV_REINTERPRET(v2i64, xy0))));
+    y = v_float64x2(MSA_TPV_REINTERPRET(v2f64, msa_ilvodq_s64(MSA_TPV_REINTERPRET(v2i64, xy1), MSA_TPV_REINTERPRET(v2i64, xy0))));
+}
+
+template<int i, typename _Tp>
+inline typename _Tp::lane_type v_extract_n(const _Tp& a)
+{
+    return v_rotate_right<i>(a).get0();
+}
+
+template<int i>
+inline v_uint32x4 v_broadcast_element(const v_uint32x4& a)
+{
+    return v_setall_u32(v_extract_n<i>(a));
+}
+template<int i>
+inline v_int32x4 v_broadcast_element(const v_int32x4& a)
+{
+    return v_setall_s32(v_extract_n<i>(a));
+}
+template<int i>
+inline v_float32x4 v_broadcast_element(const v_float32x4& a)
+{
+    return v_setall_f32(v_extract_n<i>(a));
+}
+
+////// FP16 support ///////
+#if CV_FP16
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+#ifndef msa_ld1_f16
+    v4f16 v = (v4f16)msa_ld1_s16((const short*)ptr);
+#else
+    v4f16 v = msa_ld1_f16((const __fp16*)ptr);
+#endif
+    return v_float32x4(msa_cvt_f32_f16(v));
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+    v4f16 hv = msa_cvt_f16_f32(v.val);
+
+#ifndef msa_st1_f16
+    msa_st1_s16((short*)ptr, (int16x4_t)hv);
+#else
+    msa_st1_f16((__fp16*)ptr, hv);
+#endif
+}
+#else
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+    float buf[4];
+    for( int i = 0; i < 4; i++ )
+        buf[i] = (float)ptr[i];
+    return v_load(buf);
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+    float buf[4];
+    v_store(buf, v);
+    for( int i = 0; i < 4; i++ )
+        ptr[i] = (hfloat)buf[i];
+}
+#endif
+
+inline void v_cleanup() {}
+
+#include "intrin_math.hpp"
+inline v_float32x4 v_exp(const v_float32x4& x) { return v_exp_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_log(const v_float32x4& x) { return v_log_default_32f<v_float32x4, v_int32x4>(x); }
+inline void v_sincos(const v_float32x4& x, v_float32x4& s, v_float32x4& c) { v_sincos_default_32f<v_float32x4, v_int32x4>(x, s, c); }
+inline v_float32x4 v_sin(const v_float32x4& x) { return v_sin_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_cos(const v_float32x4& x) { return v_cos_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_erf(const v_float32x4& x) { return v_erf_default_32f<v_float32x4, v_int32x4>(x); }
+
+inline v_float64x2 v_exp(const v_float64x2& x) { return v_exp_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_log(const v_float64x2& x) { return v_log_default_64f<v_float64x2, v_int64x2>(x); }
+inline void v_sincos(const v_float64x2& x, v_float64x2& s, v_float64x2& c) { v_sincos_default_64f<v_float64x2, v_int64x2>(x, s, c); }
+inline v_float64x2 v_sin(const v_float64x2& x) { return v_sin_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_cos(const v_float64x2& x) { return v_cos_default_64f<v_float64x2, v_int64x2>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+}
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_neon.hpp

@@ -0,0 +1,2679 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_HAL_INTRIN_NEON_HPP
+#define OPENCV_HAL_INTRIN_NEON_HPP
+
+#include <algorithm>
+#include "opencv2/core/utility.hpp"
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+#define CV_SIMD128 1
+#if defined(__aarch64__) || defined(_M_ARM64)
+#define CV_SIMD128_64F 1
+#else
+#define CV_SIMD128_64F 0
+#endif
+
+// The following macro checks if the code is being compiled for the
+// AArch64 execution state of Armv8, to enable the 128-bit
+// intrinsics. The macro `__ARM_64BIT_STATE` is the one recommended by
+// the Arm C Language Extension (ACLE) specifications [1] to check the
+// availability of 128-bit intrinsics, and it is supporrted by clang
+// and gcc. The macro `_M_ARM64` is the equivalent one for Microsoft
+// Visual Studio [2] .
+//
+// [1] https://developer.arm.com/documentation/101028/0012/13--Advanced-SIMD--Neon--intrinsics
+// [2] https://docs.microsoft.com/en-us/cpp/preprocessor/predefined-macros
+#if defined(__ARM_64BIT_STATE) || defined(_M_ARM64)
+#define CV_NEON_AARCH64 1
+#else
+#define CV_NEON_AARCH64 0
+#endif
+
+
+//////////// Utils ////////////
+
+#if CV_SIMD128_64F
+#define OPENCV_HAL_IMPL_NEON_UNZIP(_Tpv, _Tpvx2, suffix) \
+    inline void _v128_unzip(const _Tpv& a, const _Tpv& b, _Tpv& c, _Tpv& d) \
+    { c = vuzp1q_##suffix(a, b); d = vuzp2q_##suffix(a, b); }
+#define OPENCV_HAL_IMPL_NEON_UNZIP_L(_Tpv, _Tpvx2, suffix) \
+    inline void _v128_unzip(const _Tpv&a, const _Tpv&b, _Tpv& c, _Tpv& d) \
+    { c = vuzp1_##suffix(a, b); d = vuzp2_##suffix(a, b); }
+#else
+#define OPENCV_HAL_IMPL_NEON_UNZIP(_Tpv, _Tpvx2, suffix) \
+    inline void _v128_unzip(const _Tpv& a, const _Tpv& b, _Tpv& c, _Tpv& d) \
+    { _Tpvx2 ab = vuzpq_##suffix(a, b); c = ab.val[0]; d = ab.val[1]; }
+#define OPENCV_HAL_IMPL_NEON_UNZIP_L(_Tpv, _Tpvx2, suffix) \
+    inline void _v128_unzip(const _Tpv& a, const _Tpv& b, _Tpv& c, _Tpv& d) \
+    { _Tpvx2 ab = vuzp_##suffix(a, b); c = ab.val[0]; d = ab.val[1]; }
+#endif
+
+#if CV_SIMD128_64F
+#define OPENCV_HAL_IMPL_NEON_REINTERPRET(_Tpv, suffix) \
+    template <typename T> static inline \
+    _Tpv vreinterpretq_##suffix##_f64(T a) { return (_Tpv) a; } \
+    template <typename T> static inline \
+    float64x2_t vreinterpretq_f64_##suffix(T a) { return (float64x2_t) a; }
+#else
+#define OPENCV_HAL_IMPL_NEON_REINTERPRET(_Tpv, suffix)
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(_Tpv, _Tpvl, suffix) \
+    OPENCV_HAL_IMPL_NEON_UNZIP(_Tpv##_t, _Tpv##x2_t, suffix) \
+    OPENCV_HAL_IMPL_NEON_UNZIP_L(_Tpvl##_t, _Tpvl##x2_t, suffix) \
+    OPENCV_HAL_IMPL_NEON_REINTERPRET(_Tpv##_t, suffix)
+
+#define OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX_I64(_Tpv, _Tpvl, suffix) \
+    OPENCV_HAL_IMPL_NEON_REINTERPRET(_Tpv##_t, suffix)
+
+#define OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX_F64(_Tpv, _Tpvl, suffix) \
+    OPENCV_HAL_IMPL_NEON_UNZIP(_Tpv##_t, _Tpv##x2_t, suffix)
+
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(uint8x16, uint8x8,  u8)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(int8x16,  int8x8,   s8)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(uint16x8, uint16x4, u16)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(int16x8,  int16x4,  s16)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(uint32x4, uint32x2, u32)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(int32x4,  int32x2,  s32)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX(float32x4, float32x2, f32)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX_I64(uint64x2, uint64x1, u64)
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX_I64(int64x2,  int64x1,  s64)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_UTILS_SUFFIX_F64(float64x2, float64x1,f64)
+#endif
+
+//////////// Compatibility layer ////////////
+template<typename T> struct VTraits {
+        static inline int vlanes() { return T::nlanes; }
+        enum { max_nlanes = T::nlanes, nlanes = T::nlanes };
+        using lane_type = typename T::lane_type;
+};
+
+template<typename T>
+inline typename VTraits<T>::lane_type v_get0(const T& v) \
+{ \
+    return v.get0(); \
+}
+//////////// Types ////////////
+
+struct v_uint8x16
+{
+    v_uint8x16() {}
+    explicit v_uint8x16(uint8x16_t v) : val(v) {}
+    v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
+               uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
+    {
+        uchar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = vld1q_u8(v);
+    }
+    uint8x16_t val;
+
+private:
+    friend struct VTraits<v_uint8x16>;
+    enum { nlanes = 16 };
+    typedef uchar lane_type;
+
+    friend typename VTraits<v_uint8x16>::lane_type v_get0<v_uint8x16>(const v_uint8x16& v);
+    uchar get0() const
+    {
+        return vgetq_lane_u8(val, 0);
+    }
+};
+
+struct v_int8x16
+{
+    v_int8x16() {}
+    explicit v_int8x16(int8x16_t v) : val(v) {}
+    v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
+               schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
+    {
+        schar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = vld1q_s8(v);
+    }
+    int8x16_t val;
+
+private:
+    friend struct VTraits<v_int8x16>;
+    enum { nlanes = 16 };
+    typedef schar lane_type;
+
+    friend typename VTraits<v_int8x16>::lane_type v_get0<v_int8x16>(const v_int8x16& v);
+    schar get0() const
+    {
+        return vgetq_lane_s8(val, 0);
+    }
+};
+
+struct v_uint16x8
+{
+    v_uint16x8() {}
+    explicit v_uint16x8(uint16x8_t v) : val(v) {}
+    v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
+    {
+        ushort v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = vld1q_u16(v);
+    }
+    uint16x8_t val;
+
+private:
+    friend struct VTraits<v_uint16x8>;
+    enum { nlanes = 8 };
+    typedef ushort lane_type;
+
+    friend typename VTraits<v_uint16x8>::lane_type v_get0<v_uint16x8>(const v_uint16x8& v);
+    ushort get0() const
+    {
+        return vgetq_lane_u16(val, 0);
+    }
+};
+
+struct v_int16x8
+{
+    v_int16x8() {}
+    explicit v_int16x8(int16x8_t v) : val(v) {}
+    v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
+    {
+        short v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = vld1q_s16(v);
+    }
+    int16x8_t val;
+
+private:
+    friend struct VTraits<v_int16x8>;
+    enum { nlanes = 8 };
+    typedef short lane_type;
+
+    friend typename VTraits<v_int16x8>::lane_type v_get0<v_int16x8>(const v_int16x8& v);
+    short get0() const
+    {
+        return vgetq_lane_s16(val, 0);
+    }
+};
+
+struct v_uint32x4
+{
+    v_uint32x4() {}
+    explicit v_uint32x4(uint32x4_t v) : val(v) {}
+    v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3)
+    {
+        unsigned v[] = {v0, v1, v2, v3};
+        val = vld1q_u32(v);
+    }
+    uint32x4_t val;
+
+private:
+    friend struct VTraits<v_uint32x4>;
+    enum { nlanes = 4 };
+    typedef unsigned lane_type;
+
+    friend typename VTraits<v_uint32x4>::lane_type v_get0<v_uint32x4>(const v_uint32x4& v);
+    unsigned get0() const
+    {
+        return vgetq_lane_u32(val, 0);
+    }
+};
+
+struct v_int32x4
+{
+    v_int32x4() {}
+    explicit v_int32x4(int32x4_t v) : val(v) {}
+    v_int32x4(int v0, int v1, int v2, int v3)
+    {
+        int v[] = {v0, v1, v2, v3};
+        val = vld1q_s32(v);
+    }
+    int32x4_t val;
+
+private:
+    friend struct VTraits<v_int32x4>;
+    enum { nlanes = 4 };
+    typedef int lane_type;
+
+    friend typename VTraits<v_int32x4>::lane_type v_get0<v_int32x4>(const v_int32x4& v);
+    int get0() const
+    {
+        return vgetq_lane_s32(val, 0);
+    }
+};
+
+struct v_float32x4
+{
+    v_float32x4() {}
+    explicit v_float32x4(float32x4_t v) : val(v) {}
+    v_float32x4(float v0, float v1, float v2, float v3)
+    {
+        float v[] = {v0, v1, v2, v3};
+        val = vld1q_f32(v);
+    }
+    float32x4_t val;
+
+private:
+    friend struct VTraits<v_float32x4>;
+    enum { nlanes = 4 };
+    typedef float lane_type;
+
+    friend typename VTraits<v_float32x4>::lane_type v_get0<v_float32x4>(const v_float32x4& v);
+    float get0() const
+    {
+        return vgetq_lane_f32(val, 0);
+    }
+};
+
+struct v_uint64x2
+{
+    v_uint64x2() {}
+    explicit v_uint64x2(uint64x2_t v) : val(v) {}
+    v_uint64x2(uint64 v0, uint64 v1)
+    {
+        uint64 v[] = {v0, v1};
+        val = vld1q_u64(v);
+    }
+    uint64x2_t val;
+private:
+    friend struct VTraits<v_uint64x2>;
+    enum { nlanes = 2 };
+    typedef uint64 lane_type;
+
+    friend typename VTraits<v_uint64x2>::lane_type v_get0<v_uint64x2>(const v_uint64x2& v);
+    uint64 get0() const
+    {
+        return vgetq_lane_u64(val, 0);
+    }
+};
+
+struct v_int64x2
+{
+    v_int64x2() {}
+    explicit v_int64x2(int64x2_t v) : val(v) {}
+    v_int64x2(int64 v0, int64 v1)
+    {
+        int64 v[] = {v0, v1};
+        val = vld1q_s64(v);
+    }
+    int64x2_t val;
+
+private:
+    friend struct VTraits<v_int64x2>;
+    enum { nlanes = 2 };
+    typedef int64 lane_type;
+
+    friend typename VTraits<v_int64x2>::lane_type v_get0<v_int64x2>(const v_int64x2& v);
+    int64 get0() const
+    {
+        return vgetq_lane_s64(val, 0);
+    }
+};
+
+#if CV_SIMD128_64F
+struct v_float64x2
+{
+    v_float64x2() {}
+    explicit v_float64x2(float64x2_t v) : val(v) {}
+    v_float64x2(double v0, double v1)
+    {
+        double v[] = {v0, v1};
+        val = vld1q_f64(v);
+    }
+
+    float64x2_t val;
+private:
+    friend struct VTraits<v_float64x2>;
+    enum { nlanes = 2 };
+    typedef double lane_type;
+
+    friend typename VTraits<v_float64x2>::lane_type v_get0<v_float64x2>(const v_float64x2& v);
+    double get0() const
+    {
+        return vgetq_lane_f64(val, 0);
+    }
+};
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_INIT(_Tpv, _Tp, suffix) \
+inline v_##_Tpv v_setzero_##suffix() { return v_##_Tpv(vdupq_n_##suffix((_Tp)0)); } \
+inline v_##_Tpv v_setall_##suffix(_Tp v) { return v_##_Tpv(vdupq_n_##suffix(v)); } \
+template <> inline v_##_Tpv v_setzero_() { return v_setzero_##suffix(); } \
+template <> inline v_##_Tpv v_setall_(_Tp v) { return v_setall_##suffix(v); } \
+inline _Tpv##_t vreinterpretq_##suffix##_##suffix(_Tpv##_t v) { return v; } \
+inline v_uint8x16 v_reinterpret_as_u8(const v_##_Tpv& v) { return v_uint8x16(vreinterpretq_u8_##suffix(v.val)); } \
+inline v_int8x16 v_reinterpret_as_s8(const v_##_Tpv& v) { return v_int8x16(vreinterpretq_s8_##suffix(v.val)); } \
+inline v_uint16x8 v_reinterpret_as_u16(const v_##_Tpv& v) { return v_uint16x8(vreinterpretq_u16_##suffix(v.val)); } \
+inline v_int16x8 v_reinterpret_as_s16(const v_##_Tpv& v) { return v_int16x8(vreinterpretq_s16_##suffix(v.val)); } \
+inline v_uint32x4 v_reinterpret_as_u32(const v_##_Tpv& v) { return v_uint32x4(vreinterpretq_u32_##suffix(v.val)); } \
+inline v_int32x4 v_reinterpret_as_s32(const v_##_Tpv& v) { return v_int32x4(vreinterpretq_s32_##suffix(v.val)); } \
+inline v_uint64x2 v_reinterpret_as_u64(const v_##_Tpv& v) { return v_uint64x2(vreinterpretq_u64_##suffix(v.val)); } \
+inline v_int64x2 v_reinterpret_as_s64(const v_##_Tpv& v) { return v_int64x2(vreinterpretq_s64_##suffix(v.val)); } \
+inline v_float32x4 v_reinterpret_as_f32(const v_##_Tpv& v) { return v_float32x4(vreinterpretq_f32_##suffix(v.val)); }
+
+OPENCV_HAL_IMPL_NEON_INIT(uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_NEON_INIT(int8x16, schar, s8)
+OPENCV_HAL_IMPL_NEON_INIT(uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_NEON_INIT(int16x8, short, s16)
+OPENCV_HAL_IMPL_NEON_INIT(uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_NEON_INIT(int32x4, int, s32)
+OPENCV_HAL_IMPL_NEON_INIT(uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_NEON_INIT(int64x2, int64, s64)
+OPENCV_HAL_IMPL_NEON_INIT(float32x4, float, f32)
+#if CV_SIMD128_64F
+#define OPENCV_HAL_IMPL_NEON_INIT_64(_Tpv, suffix) \
+inline v_float64x2 v_reinterpret_as_f64(const v_##_Tpv& v) { return v_float64x2(vreinterpretq_f64_##suffix(v.val)); }
+OPENCV_HAL_IMPL_NEON_INIT(float64x2, double, f64)
+OPENCV_HAL_IMPL_NEON_INIT_64(uint8x16, u8)
+OPENCV_HAL_IMPL_NEON_INIT_64(int8x16, s8)
+OPENCV_HAL_IMPL_NEON_INIT_64(uint16x8, u16)
+OPENCV_HAL_IMPL_NEON_INIT_64(int16x8, s16)
+OPENCV_HAL_IMPL_NEON_INIT_64(uint32x4, u32)
+OPENCV_HAL_IMPL_NEON_INIT_64(int32x4, s32)
+OPENCV_HAL_IMPL_NEON_INIT_64(uint64x2, u64)
+OPENCV_HAL_IMPL_NEON_INIT_64(int64x2, s64)
+OPENCV_HAL_IMPL_NEON_INIT_64(float32x4, f32)
+OPENCV_HAL_IMPL_NEON_INIT_64(float64x2, f64)
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_PACK(_Tpvec, _Tp, hreg, suffix, _Tpwvec, pack, mov, rshr) \
+inline _Tpvec v_##pack(const _Tpwvec& a, const _Tpwvec& b) \
+{ \
+    hreg a1 = mov(a.val), b1 = mov(b.val); \
+    return _Tpvec(vcombine_##suffix(a1, b1)); \
+} \
+inline void v_##pack##_store(_Tp* ptr, const _Tpwvec& a) \
+{ \
+    hreg a1 = mov(a.val); \
+    vst1_##suffix(ptr, a1); \
+} \
+template<int n> inline \
+_Tpvec v_rshr_##pack(const _Tpwvec& a, const _Tpwvec& b) \
+{ \
+    hreg a1 = rshr(a.val, n); \
+    hreg b1 = rshr(b.val, n); \
+    return _Tpvec(vcombine_##suffix(a1, b1)); \
+} \
+template<int n> inline \
+void v_rshr_##pack##_store(_Tp* ptr, const _Tpwvec& a) \
+{ \
+    hreg a1 = rshr(a.val, n); \
+    vst1_##suffix(ptr, a1); \
+}
+
+OPENCV_HAL_IMPL_NEON_PACK(v_uint8x16, uchar, uint8x8_t, u8, v_uint16x8, pack, vqmovn_u16, vqrshrn_n_u16)
+OPENCV_HAL_IMPL_NEON_PACK(v_int8x16, schar, int8x8_t, s8, v_int16x8, pack, vqmovn_s16, vqrshrn_n_s16)
+OPENCV_HAL_IMPL_NEON_PACK(v_uint16x8, ushort, uint16x4_t, u16, v_uint32x4, pack, vqmovn_u32, vqrshrn_n_u32)
+OPENCV_HAL_IMPL_NEON_PACK(v_int16x8, short, int16x4_t, s16, v_int32x4, pack, vqmovn_s32, vqrshrn_n_s32)
+OPENCV_HAL_IMPL_NEON_PACK(v_uint32x4, unsigned, uint32x2_t, u32, v_uint64x2, pack, vmovn_u64, vrshrn_n_u64)
+OPENCV_HAL_IMPL_NEON_PACK(v_int32x4, int, int32x2_t, s32, v_int64x2, pack, vmovn_s64, vrshrn_n_s64)
+
+OPENCV_HAL_IMPL_NEON_PACK(v_uint8x16, uchar, uint8x8_t, u8, v_int16x8, pack_u, vqmovun_s16, vqrshrun_n_s16)
+OPENCV_HAL_IMPL_NEON_PACK(v_uint16x8, ushort, uint16x4_t, u16, v_int32x4, pack_u, vqmovun_s32, vqrshrun_n_s32)
+
+// pack boolean
+inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b)
+{
+    uint8x16_t ab = vcombine_u8(vmovn_u16(a.val), vmovn_u16(b.val));
+    return v_uint8x16(ab);
+}
+
+inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b,
+                           const v_uint32x4& c, const v_uint32x4& d)
+{
+    uint16x8_t nab = vcombine_u16(vmovn_u32(a.val), vmovn_u32(b.val));
+    uint16x8_t ncd = vcombine_u16(vmovn_u32(c.val), vmovn_u32(d.val));
+    return v_uint8x16(vcombine_u8(vmovn_u16(nab), vmovn_u16(ncd)));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                           const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f,
+                           const v_uint64x2& g, const v_uint64x2& h)
+{
+    uint32x4_t ab = vcombine_u32(vmovn_u64(a.val), vmovn_u64(b.val));
+    uint32x4_t cd = vcombine_u32(vmovn_u64(c.val), vmovn_u64(d.val));
+    uint32x4_t ef = vcombine_u32(vmovn_u64(e.val), vmovn_u64(f.val));
+    uint32x4_t gh = vcombine_u32(vmovn_u64(g.val), vmovn_u64(h.val));
+
+    uint16x8_t abcd = vcombine_u16(vmovn_u32(ab), vmovn_u32(cd));
+    uint16x8_t efgh = vcombine_u16(vmovn_u32(ef), vmovn_u32(gh));
+    return v_uint8x16(vcombine_u8(vmovn_u16(abcd), vmovn_u16(efgh)));
+}
+
+inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
+                            const v_float32x4& m1, const v_float32x4& m2,
+                            const v_float32x4& m3)
+{
+    float32x2_t vl = vget_low_f32(v.val), vh = vget_high_f32(v.val);
+    float32x4_t res = vmulq_lane_f32(m0.val, vl, 0);
+    res = vmlaq_lane_f32(res, m1.val, vl, 1);
+    res = vmlaq_lane_f32(res, m2.val, vh, 0);
+    res = vmlaq_lane_f32(res, m3.val, vh, 1);
+    return v_float32x4(res);
+}
+
+inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0,
+                               const v_float32x4& m1, const v_float32x4& m2,
+                               const v_float32x4& a)
+{
+    float32x2_t vl = vget_low_f32(v.val), vh = vget_high_f32(v.val);
+    float32x4_t res = vmulq_lane_f32(m0.val, vl, 0);
+    res = vmlaq_lane_f32(res, m1.val, vl, 1);
+    res = vmlaq_lane_f32(res, m2.val, vh, 0);
+    res = vaddq_f32(res, a.val);
+    return v_float32x4(res);
+}
+
+#define OPENCV_HAL_IMPL_NEON_BIN_OP(bin_op, _Tpvec, intrin) \
+inline _Tpvec bin_op (const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_uint8x16, vqaddq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_uint8x16, vqsubq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_int8x16, vqaddq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_int8x16, vqsubq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_uint16x8, vqaddq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_uint16x8, vqsubq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_int16x8, vqaddq_s16)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_int16x8, vqsubq_s16)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_int32x4, vaddq_s32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_int32x4, vsubq_s32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_mul, v_int32x4, vmulq_s32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_uint32x4, vaddq_u32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_uint32x4, vsubq_u32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_mul, v_uint32x4, vmulq_u32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_float32x4, vaddq_f32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_float32x4, vsubq_f32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_mul, v_float32x4, vmulq_f32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_int64x2, vaddq_s64)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_int64x2, vsubq_s64)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_uint64x2, vaddq_u64)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_uint64x2, vsubq_u64)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_div, v_float32x4, vdivq_f32)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_add, v_float64x2, vaddq_f64)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_sub, v_float64x2, vsubq_f64)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_mul, v_float64x2, vmulq_f64)
+OPENCV_HAL_IMPL_NEON_BIN_OP(v_div, v_float64x2, vdivq_f64)
+#else
+inline v_float32x4 v_div (const v_float32x4& a, const v_float32x4& b)
+{
+    float32x4_t reciprocal = vrecpeq_f32(b.val);
+    reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal);
+    reciprocal = vmulq_f32(vrecpsq_f32(b.val, reciprocal), reciprocal);
+    return v_float32x4(vmulq_f32(a.val, reciprocal));
+}
+#endif
+
+// saturating multiply 8-bit, 16-bit
+#define OPENCV_HAL_IMPL_NEON_MUL_SAT(_Tpvec, _Tpwvec)            \
+    inline _Tpvec v_mul (const _Tpvec& a, const _Tpvec& b)  \
+    {                                                            \
+        _Tpwvec c, d;                                            \
+        v_mul_expand(a, b, c, d);                                \
+        return v_pack(c, d);                                     \
+    }
+
+OPENCV_HAL_IMPL_NEON_MUL_SAT(v_int8x16,  v_int16x8)
+OPENCV_HAL_IMPL_NEON_MUL_SAT(v_uint8x16, v_uint16x8)
+OPENCV_HAL_IMPL_NEON_MUL_SAT(v_int16x8,  v_int32x4)
+OPENCV_HAL_IMPL_NEON_MUL_SAT(v_uint16x8, v_uint32x4)
+
+//  Multiply and expand
+inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b,
+                         v_int16x8& c, v_int16x8& d)
+{
+    c.val = vmull_s8(vget_low_s8(a.val), vget_low_s8(b.val));
+#if CV_NEON_AARCH64
+    d.val = vmull_high_s8(a.val, b.val);
+#else // #if CV_NEON_AARCH64
+    d.val = vmull_s8(vget_high_s8(a.val), vget_high_s8(b.val));
+#endif // #if CV_NEON_AARCH64
+}
+
+inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b,
+                         v_uint16x8& c, v_uint16x8& d)
+{
+    c.val = vmull_u8(vget_low_u8(a.val), vget_low_u8(b.val));
+#if CV_NEON_AARCH64
+    d.val = vmull_high_u8(a.val, b.val);
+#else // #if CV_NEON_AARCH64
+    d.val = vmull_u8(vget_high_u8(a.val), vget_high_u8(b.val));
+#endif // #if CV_NEON_AARCH64
+}
+
+inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b,
+                         v_int32x4& c, v_int32x4& d)
+{
+    c.val = vmull_s16(vget_low_s16(a.val), vget_low_s16(b.val));
+#if CV_NEON_AARCH64
+    d.val = vmull_high_s16(a.val, b.val);
+#else // #if CV_NEON_AARCH64
+    d.val = vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val));
+#endif // #if CV_NEON_AARCH64
+}
+
+inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b,
+                         v_uint32x4& c, v_uint32x4& d)
+{
+    c.val = vmull_u16(vget_low_u16(a.val), vget_low_u16(b.val));
+#if CV_NEON_AARCH64
+    d.val = vmull_high_u16(a.val, b.val);
+#else // #if CV_NEON_AARCH64
+    d.val = vmull_u16(vget_high_u16(a.val), vget_high_u16(b.val));
+#endif // #if CV_NEON_AARCH64
+}
+
+inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b,
+                         v_uint64x2& c, v_uint64x2& d)
+{
+    c.val = vmull_u32(vget_low_u32(a.val), vget_low_u32(b.val));
+#if CV_NEON_AARCH64
+    d.val = vmull_high_u32(a.val, b.val);
+#else // #if CV_NEON_AARCH64
+    d.val = vmull_u32(vget_high_u32(a.val), vget_high_u32(b.val));
+#endif // #if CV_NEON_AARCH64
+}
+
+inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b)
+{
+#if CV_NEON_AARCH64
+    int32x4_t c = vmull_high_s16(a.val, b.val);
+#else // #if CV_NEON_AARCH64
+    int32x4_t c = vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val));
+#endif // #if CV_NEON_AARCH64
+    return v_int16x8(vcombine_s16(
+                                  vshrn_n_s32(vmull_s16( vget_low_s16(a.val),  vget_low_s16(b.val)), 16),
+                                  vshrn_n_s32(c, 16)
+                                 ));
+}
+inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b)
+{
+#if CV_NEON_AARCH64
+    uint32x4_t c = vmull_high_u16(a.val, b.val);
+#else // #if CV_NEON_AARCH64
+    uint32x4_t c = vmull_u16(vget_high_u16(a.val), vget_high_u16(b.val));
+#endif // #if CV_NEON_AARCH64
+    return v_uint16x8(vcombine_u16(
+                                   vshrn_n_u32(vmull_u16( vget_low_u16(a.val),  vget_low_u16(b.val)), 16),
+                                   vshrn_n_u32(c, 16)
+                                  ));
+}
+
+//////// Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
+{
+    int16x8_t uzp1, uzp2;
+    _v128_unzip(a.val, b.val, uzp1, uzp2);
+    int16x4_t a0 = vget_low_s16(uzp1);
+    int16x4_t b0 = vget_high_s16(uzp1);
+    int16x4_t a1 = vget_low_s16(uzp2);
+    int16x4_t b1 = vget_high_s16(uzp2);
+    int32x4_t p = vmull_s16(a0, b0);
+    return v_int32x4(vmlal_s16(p, a1, b1));
+}
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{
+    int16x8_t uzp1, uzp2;
+    _v128_unzip(a.val, b.val, uzp1, uzp2);
+    int16x4_t a0 = vget_low_s16(uzp1);
+    int16x4_t b0 = vget_high_s16(uzp1);
+    int16x4_t a1 = vget_low_s16(uzp2);
+    int16x4_t b1 = vget_high_s16(uzp2);
+    int32x4_t p = vmlal_s16(c.val, a0, b0);
+    return v_int32x4(vmlal_s16(p, a1, b1));
+}
+
+// 32 >> 64
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b)
+{
+    int32x4_t uzp1, uzp2;
+    _v128_unzip(a.val, b.val, uzp1, uzp2);
+    int32x2_t a0 = vget_low_s32(uzp1);
+    int32x2_t b0 = vget_high_s32(uzp1);
+    int32x2_t a1 = vget_low_s32(uzp2);
+    int32x2_t b1 = vget_high_s32(uzp2);
+    int64x2_t p = vmull_s32(a0, b0);
+    return v_int64x2(vmlal_s32(p, a1, b1));
+}
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{
+    int32x4_t uzp1, uzp2;
+    _v128_unzip(a.val, b.val, uzp1, uzp2);
+    int32x2_t a0 = vget_low_s32(uzp1);
+    int32x2_t b0 = vget_high_s32(uzp1);
+    int32x2_t a1 = vget_low_s32(uzp2);
+    int32x2_t b1 = vget_high_s32(uzp2);
+    int64x2_t p = vmlal_s32(c.val, a0, b0);
+    return v_int64x2(vmlal_s32(p, a1, b1));
+}
+
+// 8 >> 32
+#ifdef CV_NEON_DOT
+#define OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_OP(_Tpvec1, _Tpvec2, suffix) \
+inline _Tpvec1 v_dotprod_expand(const _Tpvec2& a, const _Tpvec2& b)   \
+{ \
+    return _Tpvec1(vdotq_##suffix(vdupq_n_##suffix(0), a.val, b.val));\
+} \
+inline _Tpvec1 v_dotprod_expand(const _Tpvec2& a, const _Tpvec2& b, const _Tpvec1& c) \
+{ \
+    return _Tpvec1(vdotq_##suffix(c.val, a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_OP(v_uint32x4, v_uint8x16, u32)
+OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_OP(v_int32x4,  v_int8x16,  s32)
+#else
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
+{
+    const uint8x16_t zero   = vreinterpretq_u8_u32(vdupq_n_u32(0));
+    const uint8x16_t mask   = vreinterpretq_u8_u32(vdupq_n_u32(0x00FF00FF));
+    const uint16x8_t zero32 = vreinterpretq_u16_u32(vdupq_n_u32(0));
+    const uint16x8_t mask32 = vreinterpretq_u16_u32(vdupq_n_u32(0x0000FFFF));
+
+    uint16x8_t even = vmulq_u16(vreinterpretq_u16_u8(vbslq_u8(mask, a.val, zero)),
+                                vreinterpretq_u16_u8(vbslq_u8(mask, b.val, zero)));
+    uint16x8_t odd  = vmulq_u16(vshrq_n_u16(vreinterpretq_u16_u8(a.val), 8),
+                                vshrq_n_u16(vreinterpretq_u16_u8(b.val), 8));
+
+    uint32x4_t s0 = vaddq_u32(vreinterpretq_u32_u16(vbslq_u16(mask32, even, zero32)),
+                              vreinterpretq_u32_u16(vbslq_u16(mask32, odd,  zero32)));
+    uint32x4_t s1 = vaddq_u32(vshrq_n_u32(vreinterpretq_u32_u16(even), 16),
+                              vshrq_n_u32(vreinterpretq_u32_u16(odd),  16));
+    return v_uint32x4(vaddq_u32(s0, s1));
+}
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b,
+                                   const v_uint32x4& c)
+{
+    return v_add(v_dotprod_expand(a, b), c);
+}
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
+{
+    int16x8_t p0  = vmull_s8(vget_low_s8(a.val), vget_low_s8(b.val));
+    int16x8_t p1  = vmull_s8(vget_high_s8(a.val), vget_high_s8(b.val));
+    int16x8_t uzp1, uzp2;
+    _v128_unzip(p0, p1, uzp1, uzp2);
+    int16x8_t sum = vaddq_s16(uzp1, uzp2);
+    int16x4_t uzpl1, uzpl2;
+    _v128_unzip(vget_low_s16(sum), vget_high_s16(sum), uzpl1, uzpl2);
+    return v_int32x4(vaddl_s16(uzpl1, uzpl2));
+}
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b,
+                                  const v_int32x4& c)
+{
+    return v_add(v_dotprod_expand(a, b), c);
+}
+#endif
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
+{
+    const uint16x8_t zero = vreinterpretq_u16_u32(vdupq_n_u32(0));
+    const uint16x8_t mask = vreinterpretq_u16_u32(vdupq_n_u32(0x0000FFFF));
+
+    uint32x4_t even = vmulq_u32(vreinterpretq_u32_u16(vbslq_u16(mask, a.val, zero)),
+                                vreinterpretq_u32_u16(vbslq_u16(mask, b.val, zero)));
+    uint32x4_t odd  = vmulq_u32(vshrq_n_u32(vreinterpretq_u32_u16(a.val), 16),
+                                vshrq_n_u32(vreinterpretq_u32_u16(b.val), 16));
+    uint32x4_t uzp1, uzp2;
+    _v128_unzip(even, odd, uzp1, uzp2);
+    uint64x2_t s0  = vaddl_u32(vget_low_u32(uzp1), vget_high_u32(uzp1));
+    uint64x2_t s1  = vaddl_u32(vget_low_u32(uzp2), vget_high_u32(uzp2));
+    return v_uint64x2(vaddq_u64(s0, s1));
+}
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b)
+{
+    int32x4_t p0  = vmull_s16(vget_low_s16(a.val),  vget_low_s16(b.val));
+    int32x4_t p1  = vmull_s16(vget_high_s16(a.val), vget_high_s16(b.val));
+
+    int32x4_t uzp1, uzp2;
+    _v128_unzip(p0, p1, uzp1, uzp2);
+    int32x4_t sum = vaddq_s32(uzp1, uzp2);
+
+    int32x2_t uzpl1, uzpl2;
+    _v128_unzip(vget_low_s32(sum), vget_high_s32(sum), uzpl1, uzpl2);
+    return v_int64x2(vaddl_s32(uzpl1, uzpl2));
+}
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b,
+                                  const v_int64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+#if CV_SIMD128_64F
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a,   const v_int32x4& b,
+                                    const v_float64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+#endif
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b)
+{
+#if CV_NEON_AARCH64
+    int32x4_t p = vmull_s16(vget_low_s16(a.val), vget_low_s16(b.val));
+    return v_int32x4(vmlal_high_s16(p, a.val, b.val));
+#else
+    int16x4_t a0 = vget_low_s16(a.val);
+    int16x4_t a1 = vget_high_s16(a.val);
+    int16x4_t b0 = vget_low_s16(b.val);
+    int16x4_t b1 = vget_high_s16(b.val);
+    int32x4_t p = vmull_s16(a0, b0);
+    return v_int32x4(vmlal_s16(p, a1, b1));
+#endif
+}
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{
+#if CV_NEON_AARCH64
+    int32x4_t p = vmlal_s16(c.val, vget_low_s16(a.val), vget_low_s16(b.val));
+    return v_int32x4(vmlal_high_s16(p, a.val, b.val));
+#else
+    int16x4_t a0 = vget_low_s16(a.val);
+    int16x4_t a1 = vget_high_s16(a.val);
+    int16x4_t b0 = vget_low_s16(b.val);
+    int16x4_t b1 = vget_high_s16(b.val);
+    int32x4_t p = vmlal_s16(c.val, a0, b0);
+    return v_int32x4(vmlal_s16(p, a1, b1));
+#endif
+}
+
+// 32 >> 64
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_NEON_AARCH64
+    int64x2_t p = vmull_s32(vget_low_s32(a.val), vget_low_s32(b.val));
+    return v_int64x2(vmlal_high_s32(p, a.val, b.val));
+#else
+    int32x2_t a0 = vget_low_s32(a.val);
+    int32x2_t a1 = vget_high_s32(a.val);
+    int32x2_t b0 = vget_low_s32(b.val);
+    int32x2_t b1 = vget_high_s32(b.val);
+    int64x2_t p = vmull_s32(a0, b0);
+    return v_int64x2(vmlal_s32(p, a1, b1));
+#endif
+}
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{
+#if CV_NEON_AARCH64
+    int64x2_t p = vmlal_s32(c.val, vget_low_s32(a.val), vget_low_s32(b.val));
+    return v_int64x2(vmlal_high_s32(p, a.val, b.val));
+#else
+    int32x2_t a0 = vget_low_s32(a.val);
+    int32x2_t a1 = vget_high_s32(a.val);
+    int32x2_t b0 = vget_low_s32(b.val);
+    int32x2_t b1 = vget_high_s32(b.val);
+    int64x2_t p = vmlal_s32(c.val, a0, b0);
+    return v_int64x2(vmlal_s32(p, a1, b1));
+#endif
+}
+
+// 8 >> 32
+#ifdef CV_NEON_DOT
+#define OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_FAST_OP(_Tpvec1, _Tpvec2, suffix) \
+inline _Tpvec1 v_dotprod_expand_fast(const _Tpvec2& a, const _Tpvec2& b)   \
+{ \
+    return v_dotprod_expand(a, b); \
+} \
+inline _Tpvec1 v_dotprod_expand_fast(const _Tpvec2& a, const _Tpvec2& b, const _Tpvec1& c) \
+{ \
+    return v_dotprod_expand(a, b, c); \
+}
+
+OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_FAST_OP(v_uint32x4, v_uint8x16, u32)
+OPENCV_HAL_IMPL_NEON_DOT_PRODUCT_FAST_OP(v_int32x4,  v_int8x16,  s32)
+#else
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
+{
+    uint16x8_t p0 = vmull_u8(vget_low_u8(a.val), vget_low_u8(b.val));
+    uint16x8_t p1 = vmull_u8(vget_high_u8(a.val), vget_high_u8(b.val));
+    uint32x4_t s0 = vaddl_u16(vget_low_u16(p0), vget_low_u16(p1));
+    uint32x4_t s1 = vaddl_u16(vget_high_u16(p0), vget_high_u16(p1));
+    return v_uint32x4(vaddq_u32(s0, s1));
+}
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{
+    return v_add(v_dotprod_expand_fast(a, b), c);
+}
+
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
+{
+    int16x8_t prod = vmull_s8(vget_low_s8(a.val), vget_low_s8(b.val));
+    prod = vmlal_s8(prod, vget_high_s8(a.val), vget_high_s8(b.val));
+    return v_int32x4(vaddl_s16(vget_low_s16(prod), vget_high_s16(prod)));
+}
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{
+    return v_add(v_dotprod_expand_fast(a, b), c);
+}
+#endif
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
+{
+    uint32x4_t p0  = vmull_u16(vget_low_u16(a.val),  vget_low_u16(b.val));
+    uint32x4_t p1  = vmull_u16(vget_high_u16(a.val), vget_high_u16(b.val));
+    uint64x2_t s0  = vaddl_u32(vget_low_u32(p0), vget_high_u32(p0));
+    uint64x2_t s1  = vaddl_u32(vget_low_u32(p1), vget_high_u32(p1));
+    return v_uint64x2(vaddq_u64(s0, s1));
+}
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b)
+{
+    int32x4_t prod = vmull_s16(vget_low_s16(a.val), vget_low_s16(b.val));
+    prod = vmlal_s16(prod, vget_high_s16(a.val), vget_high_s16(b.val));
+    return v_int64x2(vaddl_s32(vget_low_s32(prod), vget_high_s32(prod)));
+}
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 32 >> 64f
+#if CV_SIMD128_64F
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_cvt_f64(v_dotprod_fast(a, b)); }
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+#endif
+
+
+#define OPENCV_HAL_IMPL_NEON_LOGIC_OP(_Tpvec, suffix) \
+    OPENCV_HAL_IMPL_NEON_BIN_OP(v_and, _Tpvec, vandq_##suffix) \
+    OPENCV_HAL_IMPL_NEON_BIN_OP(v_or, _Tpvec, vorrq_##suffix) \
+    OPENCV_HAL_IMPL_NEON_BIN_OP(v_xor, _Tpvec, veorq_##suffix) \
+    inline _Tpvec v_not (const _Tpvec& a) \
+    { \
+        return _Tpvec(vreinterpretq_##suffix##_u8(vmvnq_u8(vreinterpretq_u8_##suffix(a.val)))); \
+    }
+
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint8x16, u8)
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int8x16, s8)
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint16x8, u16)
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int16x8, s16)
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint32x4, u32)
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int32x4, s32)
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_uint64x2, u64)
+OPENCV_HAL_IMPL_NEON_LOGIC_OP(v_int64x2, s64)
+
+#define OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(bin_op, intrin) \
+inline v_float32x4 bin_op (const v_float32x4& a, const v_float32x4& b) \
+{ \
+    return v_float32x4(vreinterpretq_f32_s32(intrin(vreinterpretq_s32_f32(a.val), vreinterpretq_s32_f32(b.val)))); \
+}
+
+OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(v_and, vandq_s32)
+OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(v_or, vorrq_s32)
+OPENCV_HAL_IMPL_NEON_FLT_BIT_OP(v_xor, veorq_s32)
+
+inline v_float32x4 v_not (const v_float32x4& a)
+{
+    return v_float32x4(vreinterpretq_f32_s32(vmvnq_s32(vreinterpretq_s32_f32(a.val))));
+}
+
+#if CV_SIMD128_64F
+inline v_float32x4 v_sqrt(const v_float32x4& x)
+{
+    return v_float32x4(vsqrtq_f32(x.val));
+}
+
+inline v_float32x4 v_invsqrt(const v_float32x4& x)
+{
+    v_float32x4 one = v_setall_f32(1.0f);
+    return v_div(one, v_sqrt(x));
+}
+#else
+inline v_float32x4 v_sqrt(const v_float32x4& x)
+{
+    float32x4_t x1 = vmaxq_f32(x.val, vdupq_n_f32(FLT_MIN));
+    float32x4_t e = vrsqrteq_f32(x1);
+    e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x1, e), e), e);
+    e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x1, e), e), e);
+    return v_float32x4(vmulq_f32(x.val, e));
+}
+
+inline v_float32x4 v_invsqrt(const v_float32x4& x)
+{
+    float32x4_t e = vrsqrteq_f32(x.val);
+    e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x.val, e), e), e);
+    e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(x.val, e), e), e);
+    return v_float32x4(e);
+}
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_ABS(_Tpuvec, _Tpsvec, usuffix, ssuffix) \
+inline _Tpuvec v_abs(const _Tpsvec& a) { return v_reinterpret_as_##usuffix(_Tpsvec(vabsq_##ssuffix(a.val))); }
+
+OPENCV_HAL_IMPL_NEON_ABS(v_uint8x16, v_int8x16, u8, s8)
+OPENCV_HAL_IMPL_NEON_ABS(v_uint16x8, v_int16x8, u16, s16)
+OPENCV_HAL_IMPL_NEON_ABS(v_uint32x4, v_int32x4, u32, s32)
+
+inline v_float32x4 v_abs(v_float32x4 x)
+{ return v_float32x4(vabsq_f32(x.val)); }
+
+#if CV_SIMD128_64F
+#define OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(bin_op, intrin) \
+inline v_float64x2 bin_op (const v_float64x2& a, const v_float64x2& b) \
+{ \
+    return v_float64x2(vreinterpretq_f64_s64(intrin(vreinterpretq_s64_f64(a.val), vreinterpretq_s64_f64(b.val)))); \
+}
+
+OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(v_and, vandq_s64)
+OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(v_or, vorrq_s64)
+OPENCV_HAL_IMPL_NEON_DBL_BIT_OP(v_xor, veorq_s64)
+
+inline v_float64x2 v_not (const v_float64x2& a)
+{
+    return v_float64x2(vreinterpretq_f64_s32(vmvnq_s32(vreinterpretq_s32_f64(a.val))));
+}
+
+inline v_float64x2 v_sqrt(const v_float64x2& x)
+{
+    return v_float64x2(vsqrtq_f64(x.val));
+}
+
+inline v_float64x2 v_invsqrt(const v_float64x2& x)
+{
+    v_float64x2 one = v_setall_f64(1.0f);
+    return v_div(one, v_sqrt(x));
+}
+
+inline v_float64x2 v_abs(v_float64x2 x)
+{ return v_float64x2(vabsq_f64(x.val)); }
+#endif
+
+// TODO: exp, log, sin, cos
+
+#define OPENCV_HAL_IMPL_NEON_BIN_FUNC(_Tpvec, func, intrin) \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_min, vminq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_max, vmaxq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_min, vminq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_max, vmaxq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_min, vminq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_max, vmaxq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_min, vminq_s16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_max, vmaxq_s16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_min, vminq_u32)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_max, vmaxq_u32)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int32x4, v_min, vminq_s32)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int32x4, v_max, vmaxq_s32)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_min, vminq_f32)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_max, vmaxq_f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float64x2, v_min, vminq_f64)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float64x2, v_max, vmaxq_f64)
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_INT_CMP_OP(_Tpvec, cast, suffix, not_suffix) \
+inline _Tpvec v_eq (const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(cast(vceqq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_ne (const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(cast(vmvnq_##not_suffix(vceqq_##suffix(a.val, b.val)))); } \
+inline _Tpvec v_lt (const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(cast(vcltq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_gt (const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(cast(vcgtq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_le (const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(cast(vcleq_##suffix(a.val, b.val))); } \
+inline _Tpvec v_ge (const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(cast(vcgeq_##suffix(a.val, b.val))); }
+
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint8x16, OPENCV_HAL_NOP, u8, u8)
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int8x16, vreinterpretq_s8_u8, s8, u8)
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint16x8, OPENCV_HAL_NOP, u16, u16)
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int16x8, vreinterpretq_s16_u16, s16, u16)
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint32x4, OPENCV_HAL_NOP, u32, u32)
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int32x4, vreinterpretq_s32_u32, s32, u32)
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_float32x4, vreinterpretq_f32_u32, f32, u32)
+#if defined(__aarch64__) || defined(_M_ARM64)
+static inline uint64x2_t vmvnq_u64(uint64x2_t a)
+{
+    uint64x2_t vx = vreinterpretq_u64_u32(vdupq_n_u32(0xFFFFFFFF));
+    return veorq_u64(a, vx);
+}
+//OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_uint64x2, OPENCV_HAL_NOP, u64, u64)
+//OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int64x2, vreinterpretq_s64_u64, s64, u64)
+static inline v_uint64x2 v_eq (const v_uint64x2& a, const v_uint64x2& b)
+{ return v_uint64x2(vceqq_u64(a.val, b.val)); }
+static inline v_uint64x2 v_ne (const v_uint64x2& a, const v_uint64x2& b)
+{ return v_uint64x2(vmvnq_u64(vceqq_u64(a.val, b.val))); }
+static inline v_int64x2 v_eq (const v_int64x2& a, const v_int64x2& b)
+{ return v_int64x2(vreinterpretq_s64_u64(vceqq_s64(a.val, b.val))); }
+static inline v_int64x2 v_ne (const v_int64x2& a, const v_int64x2& b)
+{ return v_int64x2(vreinterpretq_s64_u64(vmvnq_u64(vceqq_s64(a.val, b.val)))); }
+#else
+static inline v_uint64x2 v_eq (const v_uint64x2& a, const v_uint64x2& b)
+{
+    uint32x4_t cmp = vceqq_u32(vreinterpretq_u32_u64(a.val), vreinterpretq_u32_u64(b.val));
+    uint32x4_t swapped = vrev64q_u32(cmp);
+    return v_uint64x2(vreinterpretq_u64_u32(vandq_u32(cmp, swapped)));
+}
+static inline v_uint64x2 v_ne (const v_uint64x2& a, const v_uint64x2& b)
+{
+    uint32x4_t cmp = vceqq_u32(vreinterpretq_u32_u64(a.val), vreinterpretq_u32_u64(b.val));
+    uint32x4_t swapped = vrev64q_u32(cmp);
+    uint64x2_t v_eq = vreinterpretq_u64_u32(vandq_u32(cmp, swapped));
+    uint64x2_t vx = vreinterpretq_u64_u32(vdupq_n_u32(0xFFFFFFFF));
+    return v_uint64x2(veorq_u64(v_eq, vx));
+}
+static inline v_int64x2 v_eq (const v_int64x2& a, const v_int64x2& b)
+{
+    return v_reinterpret_as_s64(v_eq(v_reinterpret_as_u64(a), v_reinterpret_as_u64(b)));
+}
+static inline v_int64x2 v_ne (const v_int64x2& a, const v_int64x2& b)
+{
+    return v_reinterpret_as_s64(v_ne(v_reinterpret_as_u64(a), v_reinterpret_as_u64(b)));
+}
+#endif
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_float64x2, vreinterpretq_f64_u64, f64, u64)
+#endif
+
+inline v_float32x4 v_not_nan(const v_float32x4& a)
+{ return v_float32x4(vreinterpretq_f32_u32(vceqq_f32(a.val, a.val))); }
+#if CV_SIMD128_64F
+inline v_float64x2 v_not_nan(const v_float64x2& a)
+{ return v_float64x2(vreinterpretq_f64_u64(vceqq_f64(a.val, a.val))); }
+#endif
+
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_add_wrap, vaddq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_add_wrap, vaddq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_add_wrap, vaddq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_add_wrap, vaddq_s16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_sub_wrap, vsubq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_sub_wrap, vsubq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_sub_wrap, vsubq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_sub_wrap, vsubq_s16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_mul_wrap, vmulq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_mul_wrap, vmulq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_mul_wrap, vmulq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int16x8, v_mul_wrap, vmulq_s16)
+
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_absdiff, vabdq_u8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_absdiff, vabdq_u16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint32x4, v_absdiff, vabdq_u32)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float32x4, v_absdiff, vabdq_f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_float64x2, v_absdiff, vabdq_f64)
+#endif
+
+/** Saturating absolute difference **/
+inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b)
+{ return v_int8x16(vqabsq_s8(vqsubq_s8(a.val, b.val))); }
+inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b)
+{ return v_int16x8(vqabsq_s16(vqsubq_s16(a.val, b.val))); }
+
+#define OPENCV_HAL_IMPL_NEON_BIN_FUNC2(_Tpvec, _Tpvec2, cast, func, intrin) \
+inline _Tpvec2 func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec2(cast(intrin(a.val, b.val))); \
+}
+
+OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int8x16, v_uint8x16, vreinterpretq_u8_s8, v_absdiff, vabdq_s8)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int16x8, v_uint16x8, vreinterpretq_u16_s16, v_absdiff, vabdq_s16)
+OPENCV_HAL_IMPL_NEON_BIN_FUNC2(v_int32x4, v_uint32x4, vreinterpretq_u32_s32, v_absdiff, vabdq_s32)
+
+inline v_float32x4 v_magnitude(const v_float32x4& a, const v_float32x4& b)
+{
+    v_float32x4 x(vmlaq_f32(vmulq_f32(a.val, a.val), b.val, b.val));
+    return v_sqrt(x);
+}
+
+inline v_float32x4 v_sqr_magnitude(const v_float32x4& a, const v_float32x4& b)
+{
+    return v_float32x4(vmlaq_f32(vmulq_f32(a.val, a.val), b.val, b.val));
+}
+
+inline v_float32x4 v_fma(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+#if CV_SIMD128_64F
+    // ARMv8, which adds support for 64-bit floating-point (so CV_SIMD128_64F is defined),
+    // also adds FMA support both for single- and double-precision floating-point vectors
+    return v_float32x4(vfmaq_f32(c.val, a.val, b.val));
+#else
+    return v_float32x4(vmlaq_f32(c.val, a.val, b.val));
+#endif
+}
+
+inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_int32x4(vmlaq_s32(c.val, a.val, b.val));
+}
+
+inline v_float32x4 v_muladd(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+#if CV_SIMD128_64F
+inline v_float64x2 v_magnitude(const v_float64x2& a, const v_float64x2& b)
+{
+    v_float64x2 x(vaddq_f64(vmulq_f64(a.val, a.val), vmulq_f64(b.val, b.val)));
+    return v_sqrt(x);
+}
+
+inline v_float64x2 v_sqr_magnitude(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float64x2(vaddq_f64(vmulq_f64(a.val, a.val), vmulq_f64(b.val, b.val)));
+}
+
+inline v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+    return v_float64x2(vfmaq_f64(c.val, a.val, b.val));
+}
+
+inline v_float64x2 v_muladd(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+    return v_fma(a, b, c);
+}
+#endif
+
+// trade efficiency for convenience
+#define OPENCV_HAL_IMPL_NEON_SHIFT_OP(_Tpvec, suffix, _Tps, ssuffix) \
+inline _Tpvec v_shl (const _Tpvec& a, int n) \
+{ return _Tpvec(vshlq_##suffix(a.val, vdupq_n_##ssuffix((_Tps)n))); } \
+inline _Tpvec v_shr (const _Tpvec& a, int n) \
+{ return _Tpvec(vshlq_##suffix(a.val, vdupq_n_##ssuffix((_Tps)-n))); } \
+template<int n> inline _Tpvec v_shl(const _Tpvec& a) \
+{ return _Tpvec(vshlq_n_##suffix(a.val, n)); } \
+template<int n> inline _Tpvec v_shr(const _Tpvec& a) \
+{ return _Tpvec(vshrq_n_##suffix(a.val, n)); } \
+template<int n> inline _Tpvec v_rshr(const _Tpvec& a) \
+{ return _Tpvec(vrshrq_n_##suffix(a.val, n)); }
+
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint8x16, u8, schar, s8)
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int8x16, s8, schar, s8)
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint16x8, u16, short, s16)
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int16x8, s16, short, s16)
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint32x4, u32, int, s32)
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int32x4, s32, int, s32)
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_uint64x2, u64, int64, s64)
+OPENCV_HAL_IMPL_NEON_SHIFT_OP(v_int64x2, s64, int64, s64)
+
+#define OPENCV_HAL_IMPL_NEON_ROTATE_OP(_Tpvec, suffix) \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a) \
+{ return _Tpvec(vextq_##suffix(a.val, vdupq_n_##suffix(0), n)); } \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a) \
+{ return _Tpvec(vextq_##suffix(vdupq_n_##suffix(0), a.val, VTraits<_Tpvec>::nlanes - n)); } \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a) \
+{ return a; } \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(vextq_##suffix(a.val, b.val, n)); } \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(vextq_##suffix(b.val, a.val, VTraits<_Tpvec>::nlanes - n)); } \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a, const _Tpvec& b) \
+{ CV_UNUSED(b); return a; }
+
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint8x16, u8)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int8x16, s8)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint16x8, u16)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int16x8, s16)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint32x4, u32)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int32x4, s32)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_float32x4, f32)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_uint64x2, u64)
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_int64x2, s64)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_ROTATE_OP(v_float64x2, f64)
+#endif
+
+#if defined(__clang__) && defined(__aarch64__)
+// avoid LD2 instruction. details: https://github.com/opencv/opencv/issues/14863
+#define OPENCV_HAL_IMPL_NEON_LOAD_LOW_OP(_Tpvec, _Tp, suffix) \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ \
+typedef uint64 CV_DECL_ALIGNED(1) unaligned_uint64; \
+uint64 v = *(unaligned_uint64*)ptr; \
+return _Tpvec(v_reinterpret_as_##suffix(v_uint64x2(v, (uint64)123456))); \
+}
+#else
+#define OPENCV_HAL_IMPL_NEON_LOAD_LOW_OP(_Tpvec, _Tp, suffix) \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ return _Tpvec(vcombine_##suffix(vld1_##suffix(ptr), vdup_n_##suffix((_Tp)0))); }
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(_Tpvec, _Tp, suffix) \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec(vld1q_##suffix(ptr)); } \
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(vld1q_##suffix(ptr)); } \
+OPENCV_HAL_IMPL_NEON_LOAD_LOW_OP(_Tpvec, _Tp, suffix) \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ return _Tpvec(vcombine_##suffix(vld1_##suffix(ptr0), vld1_##suffix(ptr1))); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ vst1q_##suffix(ptr, a.val); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ vst1q_##suffix(ptr, a.val); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ vst1q_##suffix(ptr, a.val); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \
+{ vst1q_##suffix(ptr, a.val); } \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ vst1_##suffix(ptr, vget_low_##suffix(a.val)); } \
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ vst1_##suffix(ptr, vget_high_##suffix(a.val)); }
+
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int8x16, schar, s8)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int16x8, short, s16)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int32x4, int, s32)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_int64x2, int64, s64)
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_float32x4, float, f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_LOADSTORE_OP(v_float64x2, double, f64)
+#endif
+
+inline unsigned v_reduce_sum(const v_uint8x16& a)
+{
+#if CV_NEON_AARCH64
+    uint16_t t0 = vaddlvq_u8(a.val);
+    return t0;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vpaddlq_u16(vpaddlq_u8(a.val));
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline int v_reduce_sum(const v_int8x16& a)
+{
+#if CV_NEON_AARCH64
+    int16_t t0 = vaddlvq_s8(a.val);
+    return t0;
+#else // #if CV_NEON_AARCH64
+    int32x4_t t0 = vpaddlq_s16(vpaddlq_s8(a.val));
+    int32x2_t t1 = vpadd_s32(vget_low_s32(t0), vget_high_s32(t0));
+    return vget_lane_s32(vpadd_s32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline unsigned v_reduce_sum(const v_uint16x8& a)
+{
+#if CV_NEON_AARCH64
+    uint32_t t0 = vaddlvq_u16(a.val);
+    return t0;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vpaddlq_u16(a.val);
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline int v_reduce_sum(const v_int16x8& a)
+{
+#if CV_NEON_AARCH64
+    int32_t t0 = vaddlvq_s16(a.val);
+    return t0;
+#else // #if CV_NEON_AARCH64
+    int32x4_t t0 = vpaddlq_s16(a.val);
+    int32x2_t t1 = vpadd_s32(vget_low_s32(t0), vget_high_s32(t0));
+    return vget_lane_s32(vpadd_s32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+
+#if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_16(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    return v##vectorfunc##vq_##suffix(a.val); \
+}
+#else // #if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_16(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    _Tpnvec##_t a0 = vp##vectorfunc##_##suffix(vget_low_##suffix(a.val), vget_high_##suffix(a.val)); \
+    a0 = vp##vectorfunc##_##suffix(a0, a0); \
+    a0 = vp##vectorfunc##_##suffix(a0, a0); \
+    return (scalartype)vget_lane_##suffix(vp##vectorfunc##_##suffix(a0, a0),0); \
+}
+#endif // #if CV_NEON_AARCH64
+
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_16(v_uint8x16, uint8x8, uchar, max, max, u8)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_16(v_uint8x16, uint8x8, uchar, min, min, u8)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_16(v_int8x16, int8x8, schar, max, max, s8)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_16(v_int8x16, int8x8, schar, min, min, s8)
+
+#if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    return v##vectorfunc##vq_##suffix(a.val); \
+}
+#else // #if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    _Tpnvec##_t a0 = vp##vectorfunc##_##suffix(vget_low_##suffix(a.val), vget_high_##suffix(a.val)); \
+    a0 = vp##vectorfunc##_##suffix(a0, a0); \
+    return (scalartype)vget_lane_##suffix(vp##vectorfunc##_##suffix(a0, a0),0); \
+}
+#endif // #if CV_NEON_AARCH64
+
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_uint16x8, uint16x4, ushort, max, max, u16)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_uint16x8, uint16x4, ushort, min, min, u16)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_int16x8, int16x4, short, max, max, s16)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_8(v_int16x8, int16x4, short, min, min, s16)
+
+#if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    return v##vectorfunc##vq_##suffix(a.val); \
+}
+#else // #if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(_Tpvec, _Tpnvec, scalartype, func, vectorfunc, suffix) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    _Tpnvec##_t a0 = vp##vectorfunc##_##suffix(vget_low_##suffix(a.val), vget_high_##suffix(a.val)); \
+    return (scalartype)vget_lane_##suffix(vp##vectorfunc##_##suffix(a0, vget_high_##suffix(a.val)),0); \
+}
+#endif // #if CV_NEON_AARCH64
+
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, uint32x2, unsigned, sum, add, u32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, uint32x2, unsigned, max, max, u32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_uint32x4, uint32x2, unsigned, min, min, u32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int32x2, int, sum, add, s32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int32x2, int, max, max, s32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_int32x4, int32x2, int, min, min, s32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float32x2, float, sum, add, f32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float32x2, float, max, max, f32)
+OPENCV_HAL_IMPL_NEON_REDUCE_OP_4(v_float32x4, float32x2, float, min, min, f32)
+
+inline uint64 v_reduce_sum(const v_uint64x2& a)
+{
+#if CV_NEON_AARCH64
+    return vaddvq_u64(a.val);
+#else // #if CV_NEON_AARCH64
+    return vget_lane_u64(vadd_u64(vget_low_u64(a.val), vget_high_u64(a.val)),0);
+#endif // #if CV_NEON_AARCH64
+}
+inline int64 v_reduce_sum(const v_int64x2& a)
+{
+#if CV_NEON_AARCH64
+    return vaddvq_s64(a.val);
+#else // #if CV_NEON_AARCH64
+    return vget_lane_s64(vadd_s64(vget_low_s64(a.val), vget_high_s64(a.val)),0);
+#endif // #if CV_NEON_AARCH64
+}
+#if CV_SIMD128_64F
+inline double v_reduce_sum(const v_float64x2& a)
+{
+    return vaddvq_f64(a.val);
+}
+#endif
+
+inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b,
+                                 const v_float32x4& c, const v_float32x4& d)
+{
+#if CV_NEON_AARCH64
+    float32x4_t ab = vpaddq_f32(a.val, b.val); // a0+a1 a2+a3 b0+b1 b2+b3
+    float32x4_t cd = vpaddq_f32(c.val, d.val); // c0+c1 d0+d1 c2+c3 d2+d3
+    return v_float32x4(vpaddq_f32(ab, cd));  // sumA sumB sumC sumD
+#else // #if CV_NEON_AARCH64
+    float32x4x2_t ab = vtrnq_f32(a.val, b.val);
+    float32x4x2_t cd = vtrnq_f32(c.val, d.val);
+
+    float32x4_t u0 = vaddq_f32(ab.val[0], ab.val[1]); // a0+a1 b0+b1 a2+a3 b2+b3
+    float32x4_t u1 = vaddq_f32(cd.val[0], cd.val[1]); // c0+c1 d0+d1 c2+c3 d2+d3
+
+    float32x4_t v0 = vcombine_f32(vget_low_f32(u0), vget_low_f32(u1));
+    float32x4_t v1 = vcombine_f32(vget_high_f32(u0), vget_high_f32(u1));
+
+    return v_float32x4(vaddq_f32(v0, v1));
+#endif // #if CV_NEON_AARCH64
+}
+
+inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b)
+{
+#if CV_NEON_AARCH64
+    uint8x16_t t0 = vabdq_u8(a.val, b.val);
+    uint16_t t1 = vaddlvq_u8(t0);
+    return t1;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vpaddlq_u16(vpaddlq_u8(vabdq_u8(a.val, b.val)));
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b)
+{
+#if CV_NEON_AARCH64
+    uint8x16_t t0 = vreinterpretq_u8_s8(vabdq_s8(a.val, b.val));
+    uint16_t t1 = vaddlvq_u8(t0);
+    return t1;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vpaddlq_u16(vpaddlq_u8(vreinterpretq_u8_s8(vabdq_s8(a.val, b.val))));
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b)
+{
+#if CV_NEON_AARCH64
+    uint16x8_t t0 = vabdq_u16(a.val, b.val);
+    uint32_t t1 = vaddlvq_u16(t0);
+    return t1;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vpaddlq_u16(vabdq_u16(a.val, b.val));
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b)
+{
+#if CV_NEON_AARCH64
+    uint16x8_t t0 = vreinterpretq_u16_s16(vabdq_s16(a.val, b.val));
+    uint32_t t1 = vaddlvq_u16(t0);
+    return t1;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vpaddlq_u16(vreinterpretq_u16_s16(vabdq_s16(a.val, b.val)));
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b)
+{
+#if CV_NEON_AARCH64
+    uint32x4_t t0 = vabdq_u32(a.val, b.val);
+    uint32_t t1 = vaddvq_u32(t0);
+    return t1;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vabdq_u32(a.val, b.val);
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_NEON_AARCH64
+    uint32x4_t t0 = vreinterpretq_u32_s32(vabdq_s32(a.val, b.val));
+    uint32_t t1 = vaddvq_u32(t0);
+    return t1;
+#else // #if CV_NEON_AARCH64
+    uint32x4_t t0 = vreinterpretq_u32_s32(vabdq_s32(a.val, b.val));
+    uint32x2_t t1 = vpadd_u32(vget_low_u32(t0), vget_high_u32(t0));
+    return vget_lane_u32(vpadd_u32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b)
+{
+#if CV_NEON_AARCH64
+    float32x4_t t0 = vabdq_f32(a.val, b.val);
+    return vaddvq_f32(t0);
+#else // #if CV_NEON_AARCH64
+    float32x4_t t0 = vabdq_f32(a.val, b.val);
+    float32x2_t t1 = vpadd_f32(vget_low_f32(t0), vget_high_f32(t0));
+    return vget_lane_f32(vpadd_f32(t1, t1), 0);
+#endif // #if CV_NEON_AARCH64
+}
+
+inline v_uint8x16 v_popcount(const v_uint8x16& a)
+{ return v_uint8x16(vcntq_u8(a.val)); }
+inline v_uint8x16 v_popcount(const v_int8x16& a)
+{ return v_uint8x16(vcntq_u8(vreinterpretq_u8_s8(a.val))); }
+inline v_uint16x8 v_popcount(const v_uint16x8& a)
+{ return v_uint16x8(vpaddlq_u8(vcntq_u8(vreinterpretq_u8_u16(a.val)))); }
+inline v_uint16x8 v_popcount(const v_int16x8& a)
+{ return v_uint16x8(vpaddlq_u8(vcntq_u8(vreinterpretq_u8_s16(a.val)))); }
+inline v_uint32x4 v_popcount(const v_uint32x4& a)
+{ return v_uint32x4(vpaddlq_u16(vpaddlq_u8(vcntq_u8(vreinterpretq_u8_u32(a.val))))); }
+inline v_uint32x4 v_popcount(const v_int32x4& a)
+{ return v_uint32x4(vpaddlq_u16(vpaddlq_u8(vcntq_u8(vreinterpretq_u8_s32(a.val))))); }
+inline v_uint64x2 v_popcount(const v_uint64x2& a)
+{ return v_uint64x2(vpaddlq_u32(vpaddlq_u16(vpaddlq_u8(vcntq_u8(vreinterpretq_u8_u64(a.val)))))); }
+inline v_uint64x2 v_popcount(const v_int64x2& a)
+{ return v_uint64x2(vpaddlq_u32(vpaddlq_u16(vpaddlq_u8(vcntq_u8(vreinterpretq_u8_s64(a.val)))))); }
+
+inline int v_signmask(const v_uint8x16& a)
+{
+#if CV_NEON_AARCH64
+    const int8x16_t signPosition = {0,1,2,3,4,5,6,7,0,1,2,3,4,5,6,7};
+    const uint8x16_t byteOrder = {0,8,1,9,2,10,3,11,4,12,5,13,6,14,7,15};
+    uint8x16_t v0 = vshlq_u8(vshrq_n_u8(a.val, 7), signPosition);
+    uint8x16_t v1 = vqtbl1q_u8(v0, byteOrder);
+    uint32_t t0 = vaddlvq_u16(vreinterpretq_u16_u8(v1));
+    return t0;
+#else // #if CV_NEON_AARCH64
+    int8x8_t m0 = vcreate_s8(CV_BIG_UINT(0x0706050403020100));
+    uint8x16_t v0 = vshlq_u8(vshrq_n_u8(a.val, 7), vcombine_s8(m0, m0));
+    uint64x2_t v1 = vpaddlq_u32(vpaddlq_u16(vpaddlq_u8(v0)));
+    return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 8);
+#endif // #if CV_NEON_AARCH64
+}
+
+inline int v_signmask(const v_int8x16& a)
+{ return v_signmask(v_reinterpret_as_u8(a)); }
+
+inline int v_signmask(const v_uint16x8& a)
+{
+#if CV_NEON_AARCH64
+    const int16x8_t signPosition = {0,1,2,3,4,5,6,7};
+    uint16x8_t v0 = vshlq_u16(vshrq_n_u16(a.val, 15), signPosition);
+    uint32_t t0 = vaddlvq_u16(v0);
+    return t0;
+#else // #if CV_NEON_AARCH64
+    int16x4_t m0 = vcreate_s16(CV_BIG_UINT(0x0003000200010000));
+    uint16x8_t v0 = vshlq_u16(vshrq_n_u16(a.val, 15), vcombine_s16(m0, m0));
+    uint64x2_t v1 = vpaddlq_u32(vpaddlq_u16(v0));
+    return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 4);
+#endif // #if CV_NEON_AARCH64
+}
+inline int v_signmask(const v_int16x8& a)
+{ return v_signmask(v_reinterpret_as_u16(a)); }
+
+inline int v_signmask(const v_uint32x4& a)
+{
+#if CV_NEON_AARCH64
+    const int32x4_t signPosition = {0,1,2,3};
+    uint32x4_t v0 = vshlq_u32(vshrq_n_u32(a.val, 31), signPosition);
+    uint32_t t0 = vaddvq_u32(v0);
+    return t0;
+#else // #if CV_NEON_AARCH64
+    int32x2_t m0 = vcreate_s32(CV_BIG_UINT(0x0000000100000000));
+    uint32x4_t v0 = vshlq_u32(vshrq_n_u32(a.val, 31), vcombine_s32(m0, m0));
+    uint64x2_t v1 = vpaddlq_u32(v0);
+    return (int)vgetq_lane_u64(v1, 0) + ((int)vgetq_lane_u64(v1, 1) << 2);
+#endif // #if CV_NEON_AARCH64
+}
+inline int v_signmask(const v_int32x4& a)
+{ return v_signmask(v_reinterpret_as_u32(a)); }
+inline int v_signmask(const v_float32x4& a)
+{ return v_signmask(v_reinterpret_as_u32(a)); }
+inline int v_signmask(const v_uint64x2& a)
+{
+#if CV_NEON_AARCH64
+    const int64x2_t signPosition = {0,1};
+    uint64x2_t v0 = vshlq_u64(vshrq_n_u64(a.val, 63), signPosition);
+    int t0 = (int)vaddvq_u64(v0);
+    return t0;
+#else // #if CV_NEON_AARCH64
+    int64x1_t m0 = vdup_n_s64(0);
+    uint64x2_t v0 = vshlq_u64(vshrq_n_u64(a.val, 63), vcombine_s64(m0, m0));
+    return (int)vgetq_lane_u64(v0, 0) + ((int)vgetq_lane_u64(v0, 1) << 1);
+#endif // #if CV_NEON_AARCH64
+}
+inline int v_signmask(const v_int64x2& a)
+{ return v_signmask(v_reinterpret_as_u64(a)); }
+#if CV_SIMD128_64F
+inline int v_signmask(const v_float64x2& a)
+{ return v_signmask(v_reinterpret_as_u64(a)); }
+#endif
+
+inline int v_scan_forward(const v_int8x16& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint8x16& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int16x8& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint16x8& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_float32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int64x2& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint64x2& a) { return trailingZeros32(v_signmask(a)); }
+#if CV_SIMD128_64F
+inline int v_scan_forward(const v_float64x2& a) { return trailingZeros32(v_signmask(a)); }
+#endif
+
+#if CV_NEON_AARCH64
+    #define OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(_Tpvec, suffix, shift) \
+    inline bool v_check_all(const v_##_Tpvec& a) \
+    { \
+        return (vminvq_##suffix(a.val) >> shift) != 0; \
+    } \
+    inline bool v_check_any(const v_##_Tpvec& a) \
+    { \
+        return (vmaxvq_##suffix(a.val) >> shift) != 0; \
+    }
+#else // #if CV_NEON_AARCH64
+    #define OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(_Tpvec, suffix, shift) \
+    inline bool v_check_all(const v_##_Tpvec& a) \
+    { \
+        _Tpvec##_t v0 = vshrq_n_##suffix(vmvnq_##suffix(a.val), shift); \
+        uint64x2_t v1 = vreinterpretq_u64_##suffix(v0); \
+        return (vgetq_lane_u64(v1, 0) | vgetq_lane_u64(v1, 1)) == 0; \
+    } \
+    inline bool v_check_any(const v_##_Tpvec& a) \
+    { \
+        _Tpvec##_t v0 = vshrq_n_##suffix(a.val, shift); \
+        uint64x2_t v1 = vreinterpretq_u64_##suffix(v0); \
+        return (vgetq_lane_u64(v1, 0) | vgetq_lane_u64(v1, 1)) != 0; \
+    }
+#endif // #if CV_NEON_AARCH64
+
+OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint8x16, u8, 7)
+OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint16x8, u16, 15)
+OPENCV_HAL_IMPL_NEON_CHECK_ALLANY(uint32x4, u32, 31)
+
+inline bool v_check_all(const v_uint64x2& a)
+{
+    uint64x2_t v0 = vshrq_n_u64(a.val, 63);
+    return (vgetq_lane_u64(v0, 0) & vgetq_lane_u64(v0, 1)) == 1;
+}
+inline bool v_check_any(const v_uint64x2& a)
+{
+    uint64x2_t v0 = vshrq_n_u64(a.val, 63);
+    return (vgetq_lane_u64(v0, 0) | vgetq_lane_u64(v0, 1)) != 0;
+}
+
+inline bool v_check_all(const v_int8x16& a)
+{ return v_check_all(v_reinterpret_as_u8(a)); }
+inline bool v_check_all(const v_int16x8& a)
+{ return v_check_all(v_reinterpret_as_u16(a)); }
+inline bool v_check_all(const v_int32x4& a)
+{ return v_check_all(v_reinterpret_as_u32(a)); }
+inline bool v_check_all(const v_float32x4& a)
+{ return v_check_all(v_reinterpret_as_u32(a)); }
+
+inline bool v_check_any(const v_int8x16& a)
+{ return v_check_any(v_reinterpret_as_u8(a)); }
+inline bool v_check_any(const v_int16x8& a)
+{ return v_check_any(v_reinterpret_as_u16(a)); }
+inline bool v_check_any(const v_int32x4& a)
+{ return v_check_any(v_reinterpret_as_u32(a)); }
+inline bool v_check_any(const v_float32x4& a)
+{ return v_check_any(v_reinterpret_as_u32(a)); }
+
+inline bool v_check_all(const v_int64x2& a)
+{ return v_check_all(v_reinterpret_as_u64(a)); }
+inline bool v_check_any(const v_int64x2& a)
+{ return v_check_any(v_reinterpret_as_u64(a)); }
+#if CV_SIMD128_64F
+inline bool v_check_all(const v_float64x2& a)
+{ return v_check_all(v_reinterpret_as_u64(a)); }
+inline bool v_check_any(const v_float64x2& a)
+{ return v_check_any(v_reinterpret_as_u64(a)); }
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_SELECT(_Tpvec, suffix, usuffix) \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(vbslq_##suffix(vreinterpretq_##usuffix##_##suffix(mask.val), a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_NEON_SELECT(v_uint8x16, u8, u8)
+OPENCV_HAL_IMPL_NEON_SELECT(v_int8x16, s8, u8)
+OPENCV_HAL_IMPL_NEON_SELECT(v_uint16x8, u16, u16)
+OPENCV_HAL_IMPL_NEON_SELECT(v_int16x8, s16, u16)
+OPENCV_HAL_IMPL_NEON_SELECT(v_uint32x4, u32, u32)
+OPENCV_HAL_IMPL_NEON_SELECT(v_int32x4, s32, u32)
+OPENCV_HAL_IMPL_NEON_SELECT(v_float32x4, f32, u32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_SELECT(v_float64x2, f64, u64)
+#endif
+
+#if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_EXPAND(_Tpvec, _Tpwvec, _Tp, suffix) \
+inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
+{ \
+    b0.val = vmovl_##suffix(vget_low_##suffix(a.val)); \
+    b1.val = vmovl_high_##suffix(a.val); \
+} \
+inline _Tpwvec v_expand_low(const _Tpvec& a) \
+{ \
+    return _Tpwvec(vmovl_##suffix(vget_low_##suffix(a.val))); \
+} \
+inline _Tpwvec v_expand_high(const _Tpvec& a) \
+{ \
+    return _Tpwvec(vmovl_high_##suffix(a.val)); \
+} \
+inline _Tpwvec v_load_expand(const _Tp* ptr) \
+{ \
+    return _Tpwvec(vmovl_##suffix(vld1_##suffix(ptr))); \
+}
+#else
+#define OPENCV_HAL_IMPL_NEON_EXPAND(_Tpvec, _Tpwvec, _Tp, suffix) \
+inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
+{ \
+    b0.val = vmovl_##suffix(vget_low_##suffix(a.val)); \
+    b1.val = vmovl_##suffix(vget_high_##suffix(a.val)); \
+} \
+inline _Tpwvec v_expand_low(const _Tpvec& a) \
+{ \
+    return _Tpwvec(vmovl_##suffix(vget_low_##suffix(a.val))); \
+} \
+inline _Tpwvec v_expand_high(const _Tpvec& a) \
+{ \
+    return _Tpwvec(vmovl_##suffix(vget_high_##suffix(a.val))); \
+} \
+inline _Tpwvec v_load_expand(const _Tp* ptr) \
+{ \
+    return _Tpwvec(vmovl_##suffix(vld1_##suffix(ptr))); \
+}
+#endif
+
+OPENCV_HAL_IMPL_NEON_EXPAND(v_uint8x16, v_uint16x8, uchar, u8)
+OPENCV_HAL_IMPL_NEON_EXPAND(v_int8x16, v_int16x8, schar, s8)
+OPENCV_HAL_IMPL_NEON_EXPAND(v_uint16x8, v_uint32x4, ushort, u16)
+OPENCV_HAL_IMPL_NEON_EXPAND(v_int16x8, v_int32x4, short, s16)
+OPENCV_HAL_IMPL_NEON_EXPAND(v_uint32x4, v_uint64x2, uint, u32)
+OPENCV_HAL_IMPL_NEON_EXPAND(v_int32x4, v_int64x2, int, s32)
+
+inline v_uint32x4 v_load_expand_q(const uchar* ptr)
+{
+    typedef unsigned int CV_DECL_ALIGNED(1) unaligned_uint;
+    uint8x8_t v0 = vcreate_u8(*(unaligned_uint*)ptr);
+    uint16x4_t v1 = vget_low_u16(vmovl_u8(v0));
+    return v_uint32x4(vmovl_u16(v1));
+}
+
+inline v_int32x4 v_load_expand_q(const schar* ptr)
+{
+    typedef unsigned int CV_DECL_ALIGNED(1) unaligned_uint;
+    int8x8_t v0 = vcreate_s8(*(unaligned_uint*)ptr);
+    int16x4_t v1 = vget_low_s16(vmovl_s8(v0));
+    return v_int32x4(vmovl_s16(v1));
+}
+
+#if defined(__aarch64__) || defined(_M_ARM64)
+#define OPENCV_HAL_IMPL_NEON_UNPACKS(_Tpvec, suffix) \
+inline void v_zip(const v_##_Tpvec& a0, const v_##_Tpvec& a1, v_##_Tpvec& b0, v_##_Tpvec& b1) \
+{ \
+    b0.val = vzip1q_##suffix(a0.val, a1.val); \
+    b1.val = vzip2q_##suffix(a0.val, a1.val); \
+} \
+inline v_##_Tpvec v_combine_low(const v_##_Tpvec& a, const v_##_Tpvec& b) \
+{ \
+    return v_##_Tpvec(vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val))); \
+} \
+inline v_##_Tpvec v_combine_high(const v_##_Tpvec& a, const v_##_Tpvec& b) \
+{ \
+    return v_##_Tpvec(vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val))); \
+} \
+inline void v_recombine(const v_##_Tpvec& a, const v_##_Tpvec& b, v_##_Tpvec& c, v_##_Tpvec& d) \
+{ \
+    c.val = vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val)); \
+    d.val = vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val)); \
+}
+#else
+#define OPENCV_HAL_IMPL_NEON_UNPACKS(_Tpvec, suffix) \
+inline void v_zip(const v_##_Tpvec& a0, const v_##_Tpvec& a1, v_##_Tpvec& b0, v_##_Tpvec& b1) \
+{ \
+    _Tpvec##x2_t p = vzipq_##suffix(a0.val, a1.val); \
+    b0.val = p.val[0]; \
+    b1.val = p.val[1]; \
+} \
+inline v_##_Tpvec v_combine_low(const v_##_Tpvec& a, const v_##_Tpvec& b) \
+{ \
+    return v_##_Tpvec(vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val))); \
+} \
+inline v_##_Tpvec v_combine_high(const v_##_Tpvec& a, const v_##_Tpvec& b) \
+{ \
+    return v_##_Tpvec(vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val))); \
+} \
+inline void v_recombine(const v_##_Tpvec& a, const v_##_Tpvec& b, v_##_Tpvec& c, v_##_Tpvec& d) \
+{ \
+    c.val = vcombine_##suffix(vget_low_##suffix(a.val), vget_low_##suffix(b.val)); \
+    d.val = vcombine_##suffix(vget_high_##suffix(a.val), vget_high_##suffix(b.val)); \
+}
+#endif
+
+OPENCV_HAL_IMPL_NEON_UNPACKS(uint8x16, u8)
+OPENCV_HAL_IMPL_NEON_UNPACKS(int8x16, s8)
+OPENCV_HAL_IMPL_NEON_UNPACKS(uint16x8, u16)
+OPENCV_HAL_IMPL_NEON_UNPACKS(int16x8, s16)
+OPENCV_HAL_IMPL_NEON_UNPACKS(uint32x4, u32)
+OPENCV_HAL_IMPL_NEON_UNPACKS(int32x4, s32)
+OPENCV_HAL_IMPL_NEON_UNPACKS(float32x4, f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_UNPACKS(float64x2, f64)
+#endif
+
+inline v_uint8x16 v_reverse(const v_uint8x16 &a)
+{
+    uint8x16_t vec = vrev64q_u8(a.val);
+    return v_uint8x16(vextq_u8(vec, vec, 8));
+}
+
+inline v_int8x16 v_reverse(const v_int8x16 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x8 v_reverse(const v_uint16x8 &a)
+{
+    uint16x8_t vec = vrev64q_u16(a.val);
+    return v_uint16x8(vextq_u16(vec, vec, 4));
+}
+
+inline v_int16x8 v_reverse(const v_int16x8 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x4 v_reverse(const v_uint32x4 &a)
+{
+    uint32x4_t vec = vrev64q_u32(a.val);
+    return v_uint32x4(vextq_u32(vec, vec, 2));
+}
+
+inline v_int32x4 v_reverse(const v_int32x4 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x4 v_reverse(const v_float32x4 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x2 v_reverse(const v_uint64x2 &a)
+{
+    uint64x2_t vec = a.val;
+    uint64x1_t vec_lo = vget_low_u64(vec);
+    uint64x1_t vec_hi = vget_high_u64(vec);
+    return v_uint64x2(vcombine_u64(vec_hi, vec_lo));
+}
+
+inline v_int64x2 v_reverse(const v_int64x2 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+#if CV_SIMD128_64F
+inline v_float64x2 v_reverse(const v_float64x2 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_EXTRACT(_Tpvec, suffix) \
+template <int s> \
+inline v_##_Tpvec v_extract(const v_##_Tpvec& a, const v_##_Tpvec& b) \
+{ \
+    return v_##_Tpvec(vextq_##suffix(a.val, b.val, s)); \
+}
+
+OPENCV_HAL_IMPL_NEON_EXTRACT(uint8x16, u8)
+OPENCV_HAL_IMPL_NEON_EXTRACT(int8x16, s8)
+OPENCV_HAL_IMPL_NEON_EXTRACT(uint16x8, u16)
+OPENCV_HAL_IMPL_NEON_EXTRACT(int16x8, s16)
+OPENCV_HAL_IMPL_NEON_EXTRACT(uint32x4, u32)
+OPENCV_HAL_IMPL_NEON_EXTRACT(int32x4, s32)
+OPENCV_HAL_IMPL_NEON_EXTRACT(uint64x2, u64)
+OPENCV_HAL_IMPL_NEON_EXTRACT(int64x2, s64)
+OPENCV_HAL_IMPL_NEON_EXTRACT(float32x4, f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_EXTRACT(float64x2, f64)
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_EXTRACT_N(_Tpvec, _Tp, suffix) \
+template<int i> inline _Tp v_extract_n(_Tpvec v) { return vgetq_lane_##suffix(v.val, i); }
+
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_int8x16, schar, s8)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_int16x8, short, s16)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_uint32x4, uint, u32)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_int32x4, int, s32)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_int64x2, int64, s64)
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_float32x4, float, f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_EXTRACT_N(v_float64x2, double, f64)
+#endif
+
+#define OPENCV_HAL_IMPL_NEON_BROADCAST(_Tpvec, _Tp, suffix) \
+template<int i> inline _Tpvec v_broadcast_element(_Tpvec v) { _Tp t = v_extract_n<i>(v); return v_setall_##suffix(t); }
+
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_int8x16, schar, s8)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_int16x8, short, s16)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_uint32x4, uint, u32)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_int32x4, int, s32)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_int64x2, int64, s64)
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_float32x4, float, f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_BROADCAST(v_float64x2, double, f64)
+#endif
+
+#if CV_SIMD128_64F
+inline v_int32x4 v_round(const v_float32x4& a)
+{
+    float32x4_t a_ = a.val;
+    int32x4_t result;
+#if defined _MSC_VER
+    result = vcvtnq_s32_f32(a_);
+#else
+    __asm__ ("fcvtns %0.4s, %1.4s"
+             : "=w"(result)
+             : "w"(a_)
+             : /* No clobbers */);
+#endif
+    return v_int32x4(result);
+}
+#else
+inline v_int32x4 v_round(const v_float32x4& a)
+{
+    // See https://github.com/opencv/opencv/pull/24271#issuecomment-1867318007
+    float32x4_t delta = vdupq_n_f32(12582912.0f);
+    return v_int32x4(vcvtq_s32_f32(vsubq_f32(vaddq_f32(a.val, delta), delta)));
+}
+#endif
+inline v_int32x4 v_floor(const v_float32x4& a)
+{
+    int32x4_t a1 = vcvtq_s32_f32(a.val);
+    uint32x4_t mask = vcgtq_f32(vcvtq_f32_s32(a1), a.val);
+    return v_int32x4(vaddq_s32(a1, vreinterpretq_s32_u32(mask)));
+}
+
+inline v_int32x4 v_ceil(const v_float32x4& a)
+{
+    int32x4_t a1 = vcvtq_s32_f32(a.val);
+    uint32x4_t mask = vcgtq_f32(a.val, vcvtq_f32_s32(a1));
+    return v_int32x4(vsubq_s32(a1, vreinterpretq_s32_u32(mask)));
+}
+
+inline v_int32x4 v_trunc(const v_float32x4& a)
+{ return v_int32x4(vcvtq_s32_f32(a.val)); }
+
+#if CV_SIMD128_64F
+inline v_int32x4 v_round(const v_float64x2& a)
+{
+    static const int32x2_t zero = vdup_n_s32(0);
+    return v_int32x4(vcombine_s32(vmovn_s64(vcvtnq_s64_f64(a.val)), zero));
+}
+
+inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_int32x4(vcombine_s32(vmovn_s64(vcvtnq_s64_f64(a.val)), vmovn_s64(vcvtnq_s64_f64(b.val))));
+}
+
+inline v_int32x4 v_floor(const v_float64x2& a)
+{
+    static const int32x2_t zero = vdup_n_s32(0);
+    int64x2_t a1 = vcvtq_s64_f64(a.val);
+    uint64x2_t mask = vcgtq_f64(vcvtq_f64_s64(a1), a.val);
+    a1 = vaddq_s64(a1, vreinterpretq_s64_u64(mask));
+    return v_int32x4(vcombine_s32(vmovn_s64(a1), zero));
+}
+
+inline v_int32x4 v_ceil(const v_float64x2& a)
+{
+    static const int32x2_t zero = vdup_n_s32(0);
+    int64x2_t a1 = vcvtq_s64_f64(a.val);
+    uint64x2_t mask = vcgtq_f64(a.val, vcvtq_f64_s64(a1));
+    a1 = vsubq_s64(a1, vreinterpretq_s64_u64(mask));
+    return v_int32x4(vcombine_s32(vmovn_s64(a1), zero));
+}
+
+inline v_int32x4 v_trunc(const v_float64x2& a)
+{
+    static const int32x2_t zero = vdup_n_s32(0);
+    return v_int32x4(vcombine_s32(vmovn_s64(vcvtaq_s64_f64(a.val)), zero));
+}
+#endif
+
+#if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(_Tpvec, suffix) \
+inline void v_transpose4x4(const v_##_Tpvec& a0, const v_##_Tpvec& a1, \
+                         const v_##_Tpvec& a2, const v_##_Tpvec& a3, \
+                         v_##_Tpvec& b0, v_##_Tpvec& b1, \
+                         v_##_Tpvec& b2, v_##_Tpvec& b3) \
+{ \
+    /* -- Pass 1: 64b transpose */ \
+    _Tpvec##_t t0 = vreinterpretq_##suffix##32_##suffix##64( \
+                        vtrn1q_##suffix##64(vreinterpretq_##suffix##64_##suffix##32(a0.val), \
+                                            vreinterpretq_##suffix##64_##suffix##32(a2.val))); \
+    _Tpvec##_t t1 = vreinterpretq_##suffix##32_##suffix##64( \
+                        vtrn1q_##suffix##64(vreinterpretq_##suffix##64_##suffix##32(a1.val), \
+                                            vreinterpretq_##suffix##64_##suffix##32(a3.val))); \
+    _Tpvec##_t t2 = vreinterpretq_##suffix##32_##suffix##64( \
+                        vtrn2q_##suffix##64(vreinterpretq_##suffix##64_##suffix##32(a0.val), \
+                                            vreinterpretq_##suffix##64_##suffix##32(a2.val))); \
+    _Tpvec##_t t3 = vreinterpretq_##suffix##32_##suffix##64( \
+                        vtrn2q_##suffix##64(vreinterpretq_##suffix##64_##suffix##32(a1.val), \
+                                            vreinterpretq_##suffix##64_##suffix##32(a3.val))); \
+    /* -- Pass 2: 32b transpose */ \
+    b0.val = vtrn1q_##suffix##32(t0, t1); \
+    b1.val = vtrn2q_##suffix##32(t0, t1); \
+    b2.val = vtrn1q_##suffix##32(t2, t3); \
+    b3.val = vtrn2q_##suffix##32(t2, t3); \
+}
+
+OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(uint32x4, u)
+OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(int32x4, s)
+OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(float32x4, f)
+#else // #if CV_NEON_AARCH64
+#define OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(_Tpvec, suffix) \
+inline void v_transpose4x4(const v_##_Tpvec& a0, const v_##_Tpvec& a1, \
+                         const v_##_Tpvec& a2, const v_##_Tpvec& a3, \
+                         v_##_Tpvec& b0, v_##_Tpvec& b1, \
+                         v_##_Tpvec& b2, v_##_Tpvec& b3) \
+{ \
+    /* m00 m01 m02 m03 */ \
+    /* m10 m11 m12 m13 */ \
+    /* m20 m21 m22 m23 */ \
+    /* m30 m31 m32 m33 */ \
+    _Tpvec##x2_t t0 = vtrnq_##suffix(a0.val, a1.val); \
+    _Tpvec##x2_t t1 = vtrnq_##suffix(a2.val, a3.val); \
+    /* m00 m10 m02 m12 */ \
+    /* m01 m11 m03 m13 */ \
+    /* m20 m30 m22 m32 */ \
+    /* m21 m31 m23 m33 */ \
+    b0.val = vcombine_##suffix(vget_low_##suffix(t0.val[0]), vget_low_##suffix(t1.val[0])); \
+    b1.val = vcombine_##suffix(vget_low_##suffix(t0.val[1]), vget_low_##suffix(t1.val[1])); \
+    b2.val = vcombine_##suffix(vget_high_##suffix(t0.val[0]), vget_high_##suffix(t1.val[0])); \
+    b3.val = vcombine_##suffix(vget_high_##suffix(t0.val[1]), vget_high_##suffix(t1.val[1])); \
+}
+
+OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(uint32x4, u32)
+OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(int32x4, s32)
+OPENCV_HAL_IMPL_NEON_TRANSPOSE4x4(float32x4, f32)
+#endif // #if CV_NEON_AARCH64
+
+#define OPENCV_HAL_IMPL_NEON_INTERLEAVED(_Tpvec, _Tp, suffix) \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b) \
+{ \
+    _Tpvec##x2_t v = vld2q_##suffix(ptr); \
+    a.val = v.val[0]; \
+    b.val = v.val[1]; \
+} \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, v_##_Tpvec& c) \
+{ \
+    _Tpvec##x3_t v = vld3q_##suffix(ptr); \
+    a.val = v.val[0]; \
+    b.val = v.val[1]; \
+    c.val = v.val[2]; \
+} \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, \
+                                v_##_Tpvec& c, v_##_Tpvec& d) \
+{ \
+    _Tpvec##x4_t v = vld4q_##suffix(ptr); \
+    a.val = v.val[0]; \
+    b.val = v.val[1]; \
+    c.val = v.val[2]; \
+    d.val = v.val[3]; \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    _Tpvec##x2_t v; \
+    v.val[0] = a.val; \
+    v.val[1] = b.val; \
+    vst2q_##suffix(ptr, v); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                const v_##_Tpvec& c, hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    _Tpvec##x3_t v; \
+    v.val[0] = a.val; \
+    v.val[1] = b.val; \
+    v.val[2] = c.val; \
+    vst3q_##suffix(ptr, v); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                const v_##_Tpvec& c, const v_##_Tpvec& d, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec##x4_t v; \
+    v.val[0] = a.val; \
+    v.val[1] = b.val; \
+    v.val[2] = c.val; \
+    v.val[3] = d.val; \
+    vst4q_##suffix(ptr, v); \
+}
+
+#define OPENCV_HAL_IMPL_NEON_INTERLEAVED_INT64(tp, suffix) \
+inline void v_load_deinterleave( const tp* ptr, v_##tp##x2& a, v_##tp##x2& b ) \
+{ \
+    tp##x1_t a0 = vld1_##suffix(ptr); \
+    tp##x1_t b0 = vld1_##suffix(ptr + 1); \
+    tp##x1_t a1 = vld1_##suffix(ptr + 2); \
+    tp##x1_t b1 = vld1_##suffix(ptr + 3); \
+    a = v_##tp##x2(vcombine_##suffix(a0, a1)); \
+    b = v_##tp##x2(vcombine_##suffix(b0, b1)); \
+} \
+ \
+inline void v_load_deinterleave( const tp* ptr, v_##tp##x2& a, \
+                                 v_##tp##x2& b, v_##tp##x2& c ) \
+{ \
+    tp##x1_t a0 = vld1_##suffix(ptr); \
+    tp##x1_t b0 = vld1_##suffix(ptr + 1); \
+    tp##x1_t c0 = vld1_##suffix(ptr + 2); \
+    tp##x1_t a1 = vld1_##suffix(ptr + 3); \
+    tp##x1_t b1 = vld1_##suffix(ptr + 4); \
+    tp##x1_t c1 = vld1_##suffix(ptr + 5); \
+    a = v_##tp##x2(vcombine_##suffix(a0, a1)); \
+    b = v_##tp##x2(vcombine_##suffix(b0, b1)); \
+    c = v_##tp##x2(vcombine_##suffix(c0, c1)); \
+} \
+ \
+inline void v_load_deinterleave( const tp* ptr, v_##tp##x2& a, v_##tp##x2& b, \
+                                 v_##tp##x2& c, v_##tp##x2& d ) \
+{ \
+    tp##x1_t a0 = vld1_##suffix(ptr); \
+    tp##x1_t b0 = vld1_##suffix(ptr + 1); \
+    tp##x1_t c0 = vld1_##suffix(ptr + 2); \
+    tp##x1_t d0 = vld1_##suffix(ptr + 3); \
+    tp##x1_t a1 = vld1_##suffix(ptr + 4); \
+    tp##x1_t b1 = vld1_##suffix(ptr + 5); \
+    tp##x1_t c1 = vld1_##suffix(ptr + 6); \
+    tp##x1_t d1 = vld1_##suffix(ptr + 7); \
+    a = v_##tp##x2(vcombine_##suffix(a0, a1)); \
+    b = v_##tp##x2(vcombine_##suffix(b0, b1)); \
+    c = v_##tp##x2(vcombine_##suffix(c0, c1)); \
+    d = v_##tp##x2(vcombine_##suffix(d0, d1)); \
+} \
+ \
+inline void v_store_interleave( tp* ptr, const v_##tp##x2& a, const v_##tp##x2& b, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    vst1_##suffix(ptr, vget_low_##suffix(a.val)); \
+    vst1_##suffix(ptr + 1, vget_low_##suffix(b.val)); \
+    vst1_##suffix(ptr + 2, vget_high_##suffix(a.val)); \
+    vst1_##suffix(ptr + 3, vget_high_##suffix(b.val)); \
+} \
+ \
+inline void v_store_interleave( tp* ptr, const v_##tp##x2& a, \
+                                const v_##tp##x2& b, const v_##tp##x2& c, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    vst1_##suffix(ptr, vget_low_##suffix(a.val)); \
+    vst1_##suffix(ptr + 1, vget_low_##suffix(b.val)); \
+    vst1_##suffix(ptr + 2, vget_low_##suffix(c.val)); \
+    vst1_##suffix(ptr + 3, vget_high_##suffix(a.val)); \
+    vst1_##suffix(ptr + 4, vget_high_##suffix(b.val)); \
+    vst1_##suffix(ptr + 5, vget_high_##suffix(c.val)); \
+} \
+ \
+inline void v_store_interleave( tp* ptr, const v_##tp##x2& a, const v_##tp##x2& b, \
+                                const v_##tp##x2& c, const v_##tp##x2& d, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    vst1_##suffix(ptr, vget_low_##suffix(a.val)); \
+    vst1_##suffix(ptr + 1, vget_low_##suffix(b.val)); \
+    vst1_##suffix(ptr + 2, vget_low_##suffix(c.val)); \
+    vst1_##suffix(ptr + 3, vget_low_##suffix(d.val)); \
+    vst1_##suffix(ptr + 4, vget_high_##suffix(a.val)); \
+    vst1_##suffix(ptr + 5, vget_high_##suffix(b.val)); \
+    vst1_##suffix(ptr + 6, vget_high_##suffix(c.val)); \
+    vst1_##suffix(ptr + 7, vget_high_##suffix(d.val)); \
+}
+
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(int8x16, schar, s8)
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(int16x8, short, s16)
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(int32x4, int, s32)
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(float32x4, float, f32)
+#if CV_SIMD128_64F
+OPENCV_HAL_IMPL_NEON_INTERLEAVED(float64x2, double, f64)
+#endif
+
+OPENCV_HAL_IMPL_NEON_INTERLEAVED_INT64(int64, s64)
+OPENCV_HAL_IMPL_NEON_INTERLEAVED_INT64(uint64, u64)
+
+inline v_float32x4 v_cvt_f32(const v_int32x4& a)
+{
+    return v_float32x4(vcvtq_f32_s32(a.val));
+}
+
+#if CV_SIMD128_64F
+inline v_float32x4 v_cvt_f32(const v_float64x2& a)
+{
+    float32x2_t zero = vdup_n_f32(0.0f);
+    return v_float32x4(vcombine_f32(vcvt_f32_f64(a.val), zero));
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float32x4(vcombine_f32(vcvt_f32_f64(a.val), vcvt_f32_f64(b.val)));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int32x4& a)
+{
+    return v_float64x2(vcvt_f64_f32(vcvt_f32_s32(vget_low_s32(a.val))));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_int32x4& a)
+{
+    return v_float64x2(vcvt_f64_f32(vcvt_f32_s32(vget_high_s32(a.val))));
+}
+
+inline v_float64x2 v_cvt_f64(const v_float32x4& a)
+{
+    return v_float64x2(vcvt_f64_f32(vget_low_f32(a.val)));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_float32x4& a)
+{
+    return v_float64x2(vcvt_f64_f32(vget_high_f32(a.val)));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int64x2& a)
+{  return v_float64x2(vcvtq_f64_s64(a.val)); }
+
+#endif
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x16 v_lut(const schar* tab, const int* idx)
+{
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[ 0]],
+        tab[idx[ 1]],
+        tab[idx[ 2]],
+        tab[idx[ 3]],
+        tab[idx[ 4]],
+        tab[idx[ 5]],
+        tab[idx[ 6]],
+        tab[idx[ 7]],
+        tab[idx[ 8]],
+        tab[idx[ 9]],
+        tab[idx[10]],
+        tab[idx[11]],
+        tab[idx[12]],
+        tab[idx[13]],
+        tab[idx[14]],
+        tab[idx[15]]
+    };
+    return v_int8x16(vld1q_s8(elems));
+}
+inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx)
+{
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[3]],
+        tab[idx[3] + 1],
+        tab[idx[4]],
+        tab[idx[4] + 1],
+        tab[idx[5]],
+        tab[idx[5] + 1],
+        tab[idx[6]],
+        tab[idx[6] + 1],
+        tab[idx[7]],
+        tab[idx[7] + 1]
+    };
+    return v_int8x16(vld1q_s8(elems));
+}
+inline v_int8x16 v_lut_quads(const schar* tab, const int* idx)
+{
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[0] + 2],
+        tab[idx[0] + 3],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[1] + 2],
+        tab[idx[1] + 3],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[2] + 2],
+        tab[idx[2] + 3],
+        tab[idx[3]],
+        tab[idx[3] + 1],
+        tab[idx[3] + 2],
+        tab[idx[3] + 3]
+    };
+    return v_int8x16(vld1q_s8(elems));
+}
+inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((schar*)tab, idx)); }
+inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((schar*)tab, idx)); }
+inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((schar*)tab, idx)); }
+
+inline v_int16x8 v_lut(const short* tab, const int* idx)
+{
+    short CV_DECL_ALIGNED(32) elems[8] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]],
+        tab[idx[4]],
+        tab[idx[5]],
+        tab[idx[6]],
+        tab[idx[7]]
+    };
+    return v_int16x8(vld1q_s16(elems));
+}
+inline v_int16x8 v_lut_pairs(const short* tab, const int* idx)
+{
+    short CV_DECL_ALIGNED(32) elems[8] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[3]],
+        tab[idx[3] + 1]
+    };
+    return v_int16x8(vld1q_s16(elems));
+}
+inline v_int16x8 v_lut_quads(const short* tab, const int* idx)
+{
+    return v_int16x8(vcombine_s16(vld1_s16(tab + idx[0]), vld1_s16(tab + idx[1])));
+}
+inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((short*)tab, idx)); }
+inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((short*)tab, idx)); }
+inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((short*)tab, idx)); }
+
+inline v_int32x4 v_lut(const int* tab, const int* idx)
+{
+    int CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]]
+    };
+    return v_int32x4(vld1q_s32(elems));
+}
+inline v_int32x4 v_lut_pairs(const int* tab, const int* idx)
+{
+    return v_int32x4(vcombine_s32(vld1_s32(tab + idx[0]), vld1_s32(tab + idx[1])));
+}
+inline v_int32x4 v_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x4(vld1q_s32(tab + idx[0]));
+}
+inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((int*)tab, idx)); }
+inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((int*)tab, idx)); }
+inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((int*)tab, idx)); }
+
+inline v_int64x2 v_lut(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(vcombine_s64(vcreate_s64(tab[idx[0]]), vcreate_s64(tab[idx[1]])));
+}
+inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(vld1q_s64(tab + idx[0]));
+}
+inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); }
+inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); }
+
+inline v_float32x4 v_lut(const float* tab, const int* idx)
+{
+    float CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]]
+    };
+    return v_float32x4(vld1q_f32(elems));
+}
+inline v_float32x4 v_lut_pairs(const float* tab, const int* idx)
+{
+    typedef uint64 CV_DECL_ALIGNED(1) unaligned_uint64;
+
+    uint64 CV_DECL_ALIGNED(32) elems[2] =
+    {
+        *(unaligned_uint64*)(tab + idx[0]),
+        *(unaligned_uint64*)(tab + idx[1])
+    };
+    return v_float32x4(vreinterpretq_f32_u64(vld1q_u64(elems)));
+}
+inline v_float32x4 v_lut_quads(const float* tab, const int* idx)
+{
+    return v_float32x4(vld1q_f32(tab + idx[0]));
+}
+
+inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec)
+{
+    int CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[vgetq_lane_s32(idxvec.val, 0)],
+        tab[vgetq_lane_s32(idxvec.val, 1)],
+        tab[vgetq_lane_s32(idxvec.val, 2)],
+        tab[vgetq_lane_s32(idxvec.val, 3)]
+    };
+    return v_int32x4(vld1q_s32(elems));
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec)
+{
+    unsigned CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[vgetq_lane_s32(idxvec.val, 0)],
+        tab[vgetq_lane_s32(idxvec.val, 1)],
+        tab[vgetq_lane_s32(idxvec.val, 2)],
+        tab[vgetq_lane_s32(idxvec.val, 3)]
+    };
+    return v_uint32x4(vld1q_u32(elems));
+}
+
+inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec)
+{
+    float CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[vgetq_lane_s32(idxvec.val, 0)],
+        tab[vgetq_lane_s32(idxvec.val, 1)],
+        tab[vgetq_lane_s32(idxvec.val, 2)],
+        tab[vgetq_lane_s32(idxvec.val, 3)]
+    };
+    return v_float32x4(vld1q_f32(elems));
+}
+
+inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y)
+{
+    /*int CV_DECL_ALIGNED(32) idx[4];
+    v_store(idx, idxvec);
+
+    float32x4_t xy02 = vcombine_f32(vld1_f32(tab + idx[0]), vld1_f32(tab + idx[2]));
+    float32x4_t xy13 = vcombine_f32(vld1_f32(tab + idx[1]), vld1_f32(tab + idx[3]));
+
+    float32x4x2_t xxyy = vuzpq_f32(xy02, xy13);
+    x = v_float32x4(xxyy.val[0]);
+    y = v_float32x4(xxyy.val[1]);*/
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    x = v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+    y = v_float32x4(tab[idx[0]+1], tab[idx[1]+1], tab[idx[2]+1], tab[idx[3]+1]);
+}
+
+inline v_int8x16 v_interleave_pairs(const v_int8x16& vec)
+{
+    return v_int8x16(vcombine_s8(vtbl1_s8(vget_low_s8(vec.val), vcreate_s8(0x0705060403010200)), vtbl1_s8(vget_high_s8(vec.val), vcreate_s8(0x0705060403010200))));
+}
+inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x16 v_interleave_quads(const v_int8x16& vec)
+{
+    return v_int8x16(vcombine_s8(vtbl1_s8(vget_low_s8(vec.val), vcreate_s8(0x0703060205010400)), vtbl1_s8(vget_high_s8(vec.val), vcreate_s8(0x0703060205010400))));
+}
+inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_interleave_pairs(const v_int16x8& vec)
+{
+    return v_int16x8(vreinterpretq_s16_s8(vcombine_s8(vtbl1_s8(vget_low_s8(vreinterpretq_s8_s16(vec.val)), vcreate_s8(0x0706030205040100)), vtbl1_s8(vget_high_s8(vreinterpretq_s8_s16(vec.val)), vcreate_s8(0x0706030205040100)))));
+}
+inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x8 v_interleave_quads(const v_int16x8& vec)
+{
+    int16x4x2_t res = vzip_s16(vget_low_s16(vec.val), vget_high_s16(vec.val));
+    return v_int16x8(vcombine_s16(res.val[0], res.val[1]));
+}
+inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_interleave_pairs(const v_int32x4& vec)
+{
+    int32x2x2_t res = vzip_s32(vget_low_s32(vec.val), vget_high_s32(vec.val));
+    return v_int32x4(vcombine_s32(res.val[0], res.val[1]));
+}
+inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x4 v_interleave_pairs(const v_float32x4& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x16 v_pack_triplets(const v_int8x16& vec)
+{
+    return v_int8x16(vextq_s8(vcombine_s8(vtbl1_s8(vget_low_s8(vec.val), vcreate_s8(0x0605040201000000)), vtbl1_s8(vget_high_s8(vec.val), vcreate_s8(0x0807060504020100))), vdupq_n_s8(0), 2));
+}
+inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_pack_triplets(const v_int16x8& vec)
+{
+    return v_int16x8(vreinterpretq_s16_s8(vextq_s8(vcombine_s8(vtbl1_s8(vget_low_s8(vreinterpretq_s8_s16(vec.val)), vcreate_s8(0x0504030201000000)), vget_high_s8(vreinterpretq_s8_s16(vec.val))), vdupq_n_s8(0), 2)));
+}
+inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; }
+inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; }
+inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; }
+
+#if CV_SIMD128_64F
+inline v_float64x2 v_lut(const double* tab, const int* idx)
+{
+    double CV_DECL_ALIGNED(32) elems[2] =
+    {
+        tab[idx[0]],
+        tab[idx[1]]
+    };
+    return v_float64x2(vld1q_f64(elems));
+}
+
+inline v_float64x2 v_lut_pairs(const double* tab, const int* idx)
+{
+    return v_float64x2(vld1q_f64(tab + idx[0]));
+}
+
+inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec)
+{
+    double CV_DECL_ALIGNED(32) elems[2] =
+    {
+        tab[vgetq_lane_s32(idxvec.val, 0)],
+        tab[vgetq_lane_s32(idxvec.val, 1)],
+    };
+    return v_float64x2(vld1q_f64(elems));
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    x = v_float64x2(tab[idx[0]], tab[idx[1]]);
+    y = v_float64x2(tab[idx[0]+1], tab[idx[1]+1]);
+}
+#endif
+
+////// FP16 support ///////
+#if CV_FP16
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+    float16x4_t v =
+    #ifndef vld1_f16 // APPLE compiler defines vld1_f16 as macro
+        (float16x4_t)vld1_s16((const short*)ptr);
+    #else
+        vld1_f16((const __fp16*)ptr);
+    #endif
+    return v_float32x4(vcvt_f32_f16(v));
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+    float16x4_t hv = vcvt_f16_f32(v.val);
+
+    #ifndef vst1_f16 // APPLE compiler defines vst1_f16 as macro
+        vst1_s16((short*)ptr, (int16x4_t)hv);
+    #else
+        vst1_f16((__fp16*)ptr, hv);
+    #endif
+}
+#else
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+    const int N = 4;
+    float buf[N];
+    for( int i = 0; i < N; i++ ) buf[i] = (float)ptr[i];
+    return v_load(buf);
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+    const int N = 4;
+    float buf[N];
+    v_store(buf, v);
+    for( int i = 0; i < N; i++ ) ptr[i] = hfloat(buf[i]);
+}
+#endif
+
+inline void v_cleanup() {}
+
+#include "intrin_math.hpp"
+#if defined(CV_SIMD_FP16) && CV_SIMD_FP16
+inline v_float16x8 v_exp(const v_float16x8& x) { return v_exp_default_16f<v_float16x8, v_int16x8>(x); }
+inline v_float16x8 v_log(const v_float16x8& x) { return v_log_default_16f<v_float16x8, v_int16x8>(x); }
+inline void v_sincos(const v_float16x8& x, v_float16x8& s, v_float16x8& c) { v_sincos_default_16f<v_float16x8, v_int16x8>(x, s, c); }
+inline v_float16x8 v_sin(const v_float16x8& x) { return v_sin_default_16f<v_float16x8, v_int16x8>(x); }
+inline v_float16x8 v_cos(const v_float16x8& x) { return v_cos_default_16f<v_float16x8, v_int16x8>(x); }
+#endif
+inline v_float32x4 v_exp(const v_float32x4& x) { return v_exp_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_log(const v_float32x4& x) { return v_log_default_32f<v_float32x4, v_int32x4>(x); }
+inline void v_sincos(const v_float32x4& x, v_float32x4& s, v_float32x4& c) { v_sincos_default_32f<v_float32x4, v_int32x4>(x, s, c); }
+inline v_float32x4 v_sin(const v_float32x4& x) { return v_sin_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_cos(const v_float32x4& x) { return v_cos_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_erf(const v_float32x4& x) { return v_erf_default_32f<v_float32x4, v_int32x4>(x); }
+#if CV_SIMD128_64F
+inline v_float64x2 v_exp(const v_float64x2& x) { return v_exp_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_log(const v_float64x2& x) { return v_log_default_64f<v_float64x2, v_int64x2>(x); }
+inline void v_sincos(const v_float64x2& x, v_float64x2& s, v_float64x2& c) { v_sincos_default_64f<v_float64x2, v_int64x2>(x, s, c); }
+inline v_float64x2 v_sin(const v_float64x2& x) { return v_sin_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_cos(const v_float64x2& x) { return v_cos_default_64f<v_float64x2, v_int64x2>(x); }
+#endif
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+}
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_rvv071.hpp

@@ -0,0 +1,2888 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+// Copyright (C) 2015, PingTouGe Semiconductor Co., Ltd., all rights reserved.
+
+#ifndef OPENCV_HAL_INTRIN_RISCVV_HPP
+#define OPENCV_HAL_INTRIN_RISCVV_HPP
+
+#include <float.h>
+#include <algorithm>
+#include "opencv2/core/utility.hpp"
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+#define CV_SIMD128 1
+#define CV_SIMD128_64F 1
+//////////// Types ////////////
+struct v_uint8x16
+{
+    typedef uchar lane_type;
+    enum { nlanes = 16 };
+
+    v_uint8x16() {}
+    explicit v_uint8x16(vuint8m1_t v) : val(v) {}
+    v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
+               uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
+    {
+        uchar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = (vuint8m1_t)vle8_v_u8m1((unsigned char*)v, 16);
+    }
+    uchar get0() const
+    {
+        return vmv_x_s_u8m1_u8(val);
+    }
+
+    vuint8m1_t val;
+};
+
+struct v_int8x16
+{
+    typedef schar lane_type;
+    enum { nlanes = 16 };
+
+    v_int8x16() {}
+    explicit v_int8x16(vint8m1_t v) : val(v) {}
+    v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
+               schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
+    {
+        schar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = (vint8m1_t)vle8_v_i8m1((schar*)v, 16);
+    }
+    schar get0() const
+    {
+        return vmv_x_s_i8m1_i8(val);
+    }
+
+    vint8m1_t val;
+};
+
+struct v_uint16x8
+{
+    typedef ushort lane_type;
+    enum { nlanes = 8 };
+
+    v_uint16x8() {}
+    explicit v_uint16x8(vuint16m1_t v) : val(v) {}
+    v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
+    {
+        ushort v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = (vuint16m1_t)vle16_v_u16m1((unsigned short*)v, 8);
+    }
+    ushort get0() const
+    {
+        return vmv_x_s_u16m1_u16(val);
+    }
+
+    vuint16m1_t val;
+};
+
+struct v_int16x8
+{
+    typedef short lane_type;
+    enum { nlanes = 8 };
+
+    v_int16x8() {}
+    explicit v_int16x8(vint16m1_t v) : val(v) {}
+    v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
+    {
+        short v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = (vint16m1_t)vle16_v_i16m1((signed short*)v, 8);
+    }
+    short get0() const
+    {
+        return vmv_x_s_i16m1_i16(val);
+    }
+
+    vint16m1_t val;
+};
+
+struct v_uint32x4
+{
+    typedef unsigned lane_type;
+    enum { nlanes = 4 };
+
+    v_uint32x4() {}
+    explicit v_uint32x4(vuint32m1_t v) : val(v) {}
+    v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3)
+    {
+        unsigned v[] = {v0, v1, v2, v3};
+        val = (vuint32m1_t)vle32_v_u32m1((unsigned int*)v, 4);
+    }
+    unsigned get0() const
+    {
+        return vmv_x_s_u32m1_u32(val);
+    }
+
+    vuint32m1_t val;
+};
+
+struct v_int32x4
+{
+    typedef int lane_type;
+    enum { nlanes = 4 };
+
+    v_int32x4() {}
+    explicit v_int32x4(vint32m1_t v) : val(v) {}
+    v_int32x4(int v0, int v1, int v2, int v3)
+    {
+        int v[] = {v0, v1, v2, v3};
+        val = (vint32m1_t)vle32_v_i32m1((signed int*)v, 4);
+    }
+    int get0() const
+    {
+        return vmv_x_s_i32m1_i32(val);
+    }
+    vint32m1_t val;
+};
+
+struct v_float32x4
+{
+    typedef float lane_type;
+    enum { nlanes = 4 };
+
+    v_float32x4() {}
+    explicit v_float32x4(vfloat32m1_t v) : val(v) {}
+    v_float32x4(float v0, float v1, float v2, float v3)
+    {
+        float v[] = {v0, v1, v2, v3};
+        val = (vfloat32m1_t)vle32_v_f32m1((float*)v, 4);
+    }
+    float get0() const
+    {
+        return vfmv_f_s_f32m1_f32(val);
+    }
+    vfloat32m1_t val;
+};
+
+struct v_uint64x2
+{
+    typedef uint64 lane_type;
+    enum { nlanes = 2 };
+
+    v_uint64x2() {}
+    explicit v_uint64x2(vuint64m1_t v) : val(v) {}
+    v_uint64x2(uint64 v0, uint64 v1)
+    {
+        uint64 v[] = {v0, v1};
+        val = (vuint64m1_t)vle64_v_u64m1((unsigned long*)v, 2);
+    }
+    uint64 get0() const
+    {
+        return vmv_x_s_u64m1_u64(val);
+    }
+    vuint64m1_t val;
+};
+
+struct v_int64x2
+{
+    typedef int64 lane_type;
+    enum { nlanes = 2 };
+
+    v_int64x2() {}
+    explicit v_int64x2(vint64m1_t v) : val(v) {}
+    v_int64x2(int64 v0, int64 v1)
+    {
+        int64 v[] = {v0, v1};
+        val = (vint64m1_t)vle64_v_i64m1((long*)v, 2);
+    }
+    int64 get0() const
+    {
+        return vmv_x_s_i64m1_i64(val);
+    }
+    vint64m1_t val;
+};
+
+struct v_float64x2
+{
+    typedef double lane_type;
+    enum { nlanes = 2 };
+
+    v_float64x2() {}
+    explicit v_float64x2(vfloat64m1_t v) : val(v) {}
+    v_float64x2(double v0, double v1)
+    {
+        double v[] = {v0, v1};
+        val = (vfloat64m1_t)vle64_v_f64m1((double*)v, 2);
+    }
+    double get0() const
+    {
+        return vfmv_f_s_f64m1_f64(val);
+    }
+    vfloat64m1_t val;
+};
+/*
+#define OPENCV_HAL_IMPL_RISCVV_INIT(_Tpv, _Tp, suffix) \
+inline _Tp##m1_t vreinterpret_v_##suffix##m1_##suffix##m1(_Tp##m1_t v) { return v; } \
+inline v_uint8x16 v_reinterpret_as_u8(const v_##_Tpv& v) { return v_uint8x16((vuint8m1_t)(v.val)); } \
+inline v_int8x16 v_reinterpret_as_s8(const v_##_Tpv& v) { return v_int8x16((vint8m1_t)(v.val)); } \
+inline v_uint16x8 v_reinterpret_as_u16(const v_##_Tpv& v) { return v_uint16x8((vuint16m1_t)(v.val)); } \
+inline v_int16x8 v_reinterpret_as_s16(const v_##_Tpv& v) { return v_int16x8(vreinterpret_v_i8m1_i16m1(v.val)); } \
+inline v_uint32x4 v_reinterpret_as_u32(const v_##_Tpv& v) { return v_uint32x4((vuint32m1_t)(v.val)); } \
+inline v_int32x4 v_reinterpret_as_s32(const v_##_Tpv& v) { return v_int32x4((vint32m1_t)(v.val)); } \
+inline v_uint64x2 v_reinterpret_as_u64(const v_##_Tpv& v) { return v_uint64x2((vuint64m1_t)(v.val)); } \
+inline v_int64x2 v_reinterpret_as_s64(const v_##_Tpv& v) { return v_int64x2((vint64m1_t)(v.val)); } \
+inline v_float32x4 v_reinterpret_as_f32(const v_##_Tpv& v) { return v_float32x4((vfloat32m1_t)(v.val)); }\
+inline v_float64x2 v_reinterpret_as_f64(const v_##_Tpv& v) { return v_float64x2((vfloat64m1_t)(v.val)); }
+
+
+OPENCV_HAL_IMPL_RISCVV_INIT(uint8x16, vuint8, u8)
+OPENCV_HAL_IMPL_RISCVV_INIT(int8x16, vint8, i8)
+OPENCV_HAL_IMPL_RISCVV_INIT(uint16x8, vuint16, u16)
+OPENCV_HAL_IMPL_RISCVV_INIT(int16x8, vint16, i16)
+OPENCV_HAL_IMPL_RISCVV_INIT(uint32x4, vuint32, u32)
+OPENCV_HAL_IMPL_RISCVV_INIT(int32x4, vint32, i32)
+OPENCV_HAL_IMPL_RISCVV_INIT(uint64x2, vuint64, u64)
+OPENCV_HAL_IMPL_RISCVV_INIT(int64x2, vint64, i64)
+OPENCV_HAL_IMPL_RISCVV_INIT(float64x2, vfloat64, f64)
+OPENCV_HAL_IMPL_RISCVV_INIT(float32x4, vfloat32, f32)
+*/
+inline v_uint8x16 v_reinterpret_as_u8(const v_uint8x16& v) { return v_uint8x16(v.val); }
+inline v_int8x16 v_reinterpret_as_s8(const v_uint8x16& v) { return v_int8x16(vreinterpret_v_u8m1_i8m1(v.val)); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_uint8x16& v) { return v_uint16x8(vreinterpret_v_u8m1_u16m1(v.val)); }
+inline v_int16x8 v_reinterpret_as_s16(const v_uint8x16& v) { return v_int16x8(vreinterpret_v_u16m1_i16m1(vreinterpret_v_u8m1_u16m1(v.val))); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_uint8x16& v) { return v_uint32x4(vreinterpret_v_u8m1_u32m1(v.val)); }
+inline v_int32x4 v_reinterpret_as_s32(const v_uint8x16& v) { return v_int32x4(vreinterpret_v_u32m1_i32m1(vreinterpret_v_u8m1_u32m1(v.val))); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_uint8x16& v) { return v_uint64x2(vreinterpret_v_u8m1_u64m1(v.val)); }
+inline v_int64x2 v_reinterpret_as_s64(const v_uint8x16& v) { return v_int64x2(vreinterpret_v_u64m1_i64m1(vreinterpret_v_u8m1_u64m1(v.val))); }
+inline v_float32x4 v_reinterpret_as_f32(const v_uint8x16& v) { return v_float32x4(vreinterpret_v_u32m1_f32m1(vreinterpret_v_u8m1_u32m1(v.val))); }
+inline v_float64x2 v_reinterpret_as_f64(const v_uint8x16& v) { return v_float64x2(vreinterpret_v_u64m1_f64m1(vreinterpret_v_u8m1_u64m1(v.val))); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_int8x16& v) { return v_uint8x16(vreinterpret_v_i8m1_u8m1(v.val)); }
+inline v_int8x16 v_reinterpret_as_s8(const v_int8x16& v) { return v_int8x16(v.val); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_int8x16& v) { return v_uint16x8(vreinterpret_v_u8m1_u16m1(vreinterpret_v_i8m1_u8m1(v.val))); }
+inline v_int16x8 v_reinterpret_as_s16(const v_int8x16& v) { return v_int16x8(vreinterpret_v_i8m1_i16m1(v.val)); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_int8x16& v) { return v_uint32x4(vreinterpret_v_u8m1_u32m1(vreinterpret_v_i8m1_u8m1(v.val))); }
+inline v_int32x4 v_reinterpret_as_s32(const v_int8x16& v) { return v_int32x4(vreinterpret_v_i8m1_i32m1(v.val)); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_int8x16& v) { return v_uint64x2(vreinterpret_v_u8m1_u64m1(vreinterpret_v_i8m1_u8m1(v.val))); }
+inline v_int64x2 v_reinterpret_as_s64(const v_int8x16& v) { return v_int64x2(vreinterpret_v_i8m1_i64m1(v.val)); }
+inline v_float32x4 v_reinterpret_as_f32(const v_int8x16& v) { return v_float32x4(vreinterpret_v_i32m1_f32m1(vreinterpret_v_i8m1_i32m1(v.val))); }
+inline v_float64x2 v_reinterpret_as_f64(const v_int8x16& v) { return v_float64x2(vreinterpret_v_i64m1_f64m1(vreinterpret_v_i8m1_i64m1(v.val))); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_uint16x8& v) { return v_uint8x16(vreinterpret_v_u16m1_u8m1(v.val)); }
+inline v_int8x16 v_reinterpret_as_s8(const v_uint16x8& v) { return v_int8x16(vreinterpret_v_i16m1_i8m1(vreinterpret_v_u16m1_i16m1(v.val))); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_uint16x8& v) { return v_uint16x8(v.val); }
+inline v_int16x8 v_reinterpret_as_s16(const v_uint16x8& v) { return v_int16x8(vreinterpret_v_u16m1_i16m1(v.val)); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_uint16x8& v) { return v_uint32x4(vreinterpret_v_u16m1_u32m1(v.val)); }
+inline v_int32x4 v_reinterpret_as_s32(const v_uint16x8& v) { return v_int32x4(vreinterpret_v_u32m1_i32m1(vreinterpret_v_u16m1_u32m1(v.val))); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_uint16x8& v) { return v_uint64x2(vreinterpret_v_u16m1_u64m1(v.val)); }
+inline v_int64x2 v_reinterpret_as_s64(const v_uint16x8& v) { return v_int64x2(vreinterpret_v_u64m1_i64m1(vreinterpret_v_u16m1_u64m1(v.val))); }
+inline v_float32x4 v_reinterpret_as_f32(const v_uint16x8& v) { return v_float32x4(vreinterpret_v_u32m1_f32m1(vreinterpret_v_u16m1_u32m1(v.val))); }
+inline v_float64x2 v_reinterpret_as_f64(const v_uint16x8& v) { return v_float64x2(vreinterpret_v_u64m1_f64m1(vreinterpret_v_u16m1_u64m1(v.val))); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_int16x8& v) { return v_uint8x16(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i16m1_i8m1(v.val))); }
+inline v_int8x16 v_reinterpret_as_s8(const v_int16x8& v) { return v_int8x16(vreinterpret_v_i16m1_i8m1(v.val)); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_int16x8& v) { return v_uint16x8(vreinterpret_v_i16m1_u16m1(v.val)); }
+inline v_int16x8 v_reinterpret_as_s16(const v_int16x8& v) { return v_int16x8(v.val); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_int16x8& v) { return v_uint32x4(vreinterpret_v_u16m1_u32m1(vreinterpret_v_i16m1_u16m1(v.val))); }
+inline v_int32x4 v_reinterpret_as_s32(const v_int16x8& v) { return v_int32x4(vreinterpret_v_i16m1_i32m1(v.val)); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_int16x8& v) { return v_uint64x2(vreinterpret_v_u16m1_u64m1(vreinterpret_v_i16m1_u16m1(v.val))); }
+inline v_int64x2 v_reinterpret_as_s64(const v_int16x8& v) { return v_int64x2(vreinterpret_v_i16m1_i64m1(v.val)); }
+inline v_float32x4 v_reinterpret_as_f32(const v_int16x8& v) { return v_float32x4(vreinterpret_v_i32m1_f32m1(vreinterpret_v_i16m1_i32m1(v.val))); }
+inline v_float64x2 v_reinterpret_as_f64(const v_int16x8& v) { return v_float64x2(vreinterpret_v_i64m1_f64m1(vreinterpret_v_i16m1_i64m1(v.val))); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_uint32x4& v) { return v_uint8x16(vreinterpret_v_u32m1_u8m1(v.val)); }
+inline v_int8x16 v_reinterpret_as_s8(const v_uint32x4& v) { return v_int8x16(vreinterpret_v_i32m1_i8m1(vreinterpret_v_u32m1_i32m1(v.val))); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_uint32x4& v) { return v_uint16x8(vreinterpret_v_u32m1_u16m1(v.val)); }
+inline v_int16x8 v_reinterpret_as_s16(const v_uint32x4& v) { return v_int16x8(vreinterpret_v_i32m1_i16m1(vreinterpret_v_u32m1_i32m1(v.val))); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_uint32x4& v) { return v_uint32x4(v.val); }
+inline v_int32x4 v_reinterpret_as_s32(const v_uint32x4& v) { return v_int32x4(vreinterpret_v_u32m1_i32m1(v.val)); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_uint32x4& v) { return v_uint64x2(vreinterpret_v_u32m1_u64m1(v.val)); }
+inline v_int64x2 v_reinterpret_as_s64(const v_uint32x4& v) { return v_int64x2(vreinterpret_v_u64m1_i64m1(vreinterpret_v_u32m1_u64m1(v.val))); }
+inline v_float32x4 v_reinterpret_as_f32(const v_uint32x4& v) { return v_float32x4(vreinterpret_v_u32m1_f32m1(v.val)); }
+inline v_float64x2 v_reinterpret_as_f64(const v_uint32x4& v) { return v_float64x2(vreinterpret_v_u64m1_f64m1(vreinterpret_v_u32m1_u64m1(v.val))); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_int32x4& v) { return v_uint8x16(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i32m1_i8m1(v.val))); }
+inline v_int8x16 v_reinterpret_as_s8(const v_int32x4& v) { return v_int8x16(vreinterpret_v_i32m1_i8m1(v.val)); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_int32x4& v) { return v_uint16x8(vreinterpret_v_u32m1_u16m1(vreinterpret_v_i32m1_u32m1(v.val))); }
+inline v_int16x8 v_reinterpret_as_s16(const v_int32x4& v) { return v_int16x8(vreinterpret_v_i32m1_i16m1(v.val)); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_int32x4& v) { return v_uint32x4(vreinterpret_v_i32m1_u32m1(v.val)); }
+inline v_int32x4 v_reinterpret_as_s32(const v_int32x4& v) { return v_int32x4(v.val); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_int32x4& v) { return v_uint64x2(vreinterpret_v_u32m1_u64m1(vreinterpret_v_i32m1_u32m1(v.val))); }
+inline v_int64x2 v_reinterpret_as_s64(const v_int32x4& v) { return v_int64x2(vreinterpret_v_i32m1_i64m1(v.val)); }
+inline v_float32x4 v_reinterpret_as_f32(const v_int32x4& v) { return v_float32x4(vreinterpret_v_i32m1_f32m1(v.val)); }
+inline v_float64x2 v_reinterpret_as_f64(const v_int32x4& v) { return v_float64x2(vreinterpret_v_i64m1_f64m1(vreinterpret_v_i32m1_i64m1(v.val))); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_uint64x2& v) { return v_uint8x16(vreinterpret_v_u64m1_u8m1(v.val)); }
+inline v_int8x16 v_reinterpret_as_s8(const v_uint64x2& v) { return v_int8x16(vreinterpret_v_i64m1_i8m1(vreinterpret_v_u64m1_i64m1(v.val))); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_uint64x2& v) { return v_uint16x8(vreinterpret_v_u64m1_u16m1(v.val)); }
+inline v_int16x8 v_reinterpret_as_s16(const v_uint64x2& v) { return v_int16x8(vreinterpret_v_i64m1_i16m1(vreinterpret_v_u64m1_i64m1(v.val))); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_uint64x2& v) { return v_uint32x4(vreinterpret_v_u64m1_u32m1(v.val)); }
+inline v_int32x4 v_reinterpret_as_s32(const v_uint64x2& v) { return v_int32x4(vreinterpret_v_i64m1_i32m1(vreinterpret_v_u64m1_i64m1(v.val))); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_uint64x2& v) { return v_uint64x2(v.val); }
+inline v_int64x2 v_reinterpret_as_s64(const v_uint64x2& v) { return v_int64x2(vreinterpret_v_u64m1_i64m1(v.val)); }
+inline v_float32x4 v_reinterpret_as_f32(const v_uint64x2& v) { return v_float32x4(vreinterpret_v_u32m1_f32m1(vreinterpret_v_u64m1_u32m1(v.val))); }
+inline v_float64x2 v_reinterpret_as_f64(const v_uint64x2& v) { return v_float64x2(vreinterpret_v_u64m1_f64m1(v.val)); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_int64x2& v) { return v_uint8x16(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i64m1_i8m1(v.val))); }
+inline v_int8x16 v_reinterpret_as_s8(const v_int64x2& v) { return v_int8x16(vreinterpret_v_i64m1_i8m1(v.val)); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_int64x2& v) { return v_uint16x8(vreinterpret_v_u64m1_u16m1(vreinterpret_v_i64m1_u64m1(v.val))); }
+inline v_int16x8 v_reinterpret_as_s16(const v_int64x2& v) { return v_int16x8(vreinterpret_v_i64m1_i16m1(v.val)); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_int64x2& v) { return v_uint32x4(vreinterpret_v_u64m1_u32m1(vreinterpret_v_i64m1_u64m1(v.val))); }
+inline v_int32x4 v_reinterpret_as_s32(const v_int64x2& v) { return v_int32x4(vreinterpret_v_i64m1_i32m1(v.val)); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_int64x2& v) { return v_uint64x2(vreinterpret_v_i64m1_u64m1(v.val)); }
+inline v_int64x2 v_reinterpret_as_s64(const v_int64x2& v) { return v_int64x2(v.val); }
+inline v_float32x4 v_reinterpret_as_f32(const v_int64x2& v) { return v_float32x4(vreinterpret_v_i32m1_f32m1(vreinterpret_v_i64m1_i32m1(v.val))); }
+inline v_float64x2 v_reinterpret_as_f64(const v_int64x2& v) { return v_float64x2(vreinterpret_v_i64m1_f64m1(v.val)); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_float32x4& v) { return v_uint8x16(vreinterpret_v_u32m1_u8m1(vreinterpret_v_f32m1_u32m1(v.val))); }
+inline v_int8x16 v_reinterpret_as_s8(const v_float32x4& v) { return v_int8x16(vreinterpret_v_i32m1_i8m1(vreinterpret_v_f32m1_i32m1(v.val))); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_float32x4& v) { return v_uint16x8(vreinterpret_v_u32m1_u16m1(vreinterpret_v_f32m1_u32m1(v.val))); }
+inline v_int16x8 v_reinterpret_as_s16(const v_float32x4& v) { return v_int16x8(vreinterpret_v_i32m1_i16m1(vreinterpret_v_f32m1_i32m1(v.val))); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_float32x4& v) { return v_uint32x4(vreinterpret_v_f32m1_u32m1(v.val)); }
+inline v_int32x4 v_reinterpret_as_s32(const v_float32x4& v) { return v_int32x4(vreinterpret_v_f32m1_i32m1(v.val)); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_float32x4& v) { return v_uint64x2(vreinterpret_v_u32m1_u64m1(vreinterpret_v_f32m1_u32m1(v.val))); }
+inline v_int64x2 v_reinterpret_as_s64(const v_float32x4& v) { return v_int64x2(vreinterpret_v_i32m1_i64m1(vreinterpret_v_f32m1_i32m1(v.val))); }
+inline v_float32x4 v_reinterpret_as_f32(const v_float32x4& v) { return v_float32x4(v.val); }
+inline v_float64x2 v_reinterpret_as_f64(const v_float32x4& v) { return v_float64x2(vreinterpret_v_i64m1_f64m1(vreinterpret_v_i32m1_i64m1(vreinterpret_v_f32m1_i32m1(v.val)))); }
+
+inline v_uint8x16 v_reinterpret_as_u8(const v_float64x2& v) { return v_uint8x16(vreinterpret_v_u64m1_u8m1(vreinterpret_v_f64m1_u64m1(v.val))); }
+inline v_int8x16 v_reinterpret_as_s8(const v_float64x2& v) { return v_int8x16(vreinterpret_v_i64m1_i8m1(vreinterpret_v_f64m1_i64m1(v.val))); }
+inline v_uint16x8 v_reinterpret_as_u16(const v_float64x2& v) { return v_uint16x8(vreinterpret_v_u64m1_u16m1(vreinterpret_v_f64m1_u64m1(v.val))); }
+inline v_int16x8 v_reinterpret_as_s16(const v_float64x2& v) { return v_int16x8(vreinterpret_v_i64m1_i16m1(vreinterpret_v_f64m1_i64m1(v.val))); }
+inline v_uint32x4 v_reinterpret_as_u32(const v_float64x2& v) { return v_uint32x4(vreinterpret_v_u64m1_u32m1(vreinterpret_v_f64m1_u64m1(v.val))); }
+inline v_int32x4 v_reinterpret_as_s32(const v_float64x2& v) { return v_int32x4(vreinterpret_v_i64m1_i32m1(vreinterpret_v_f64m1_i64m1(v.val))); }
+inline v_uint64x2 v_reinterpret_as_u64(const v_float64x2& v) { return v_uint64x2(vreinterpret_v_f64m1_u64m1(v.val)); }
+inline v_int64x2 v_reinterpret_as_s64(const v_float64x2& v) { return v_int64x2(vreinterpret_v_f64m1_i64m1(v.val)); }
+inline v_float32x4 v_reinterpret_as_f32(const v_float64x2& v) { return v_float32x4(vreinterpret_v_i32m1_f32m1(vreinterpret_v_i64m1_i32m1(vreinterpret_v_f64m1_i64m1(v.val)))); }
+inline v_float64x2 v_reinterpret_as_f64(const v_float64x2& v) { return v_float64x2(v.val); }
+
+#define OPENCV_HAL_IMPL_RISCVV_INIT_SET(__Tp, _Tp, suffix, len, num) \
+inline v_##_Tp##x##num v_setzero_##suffix() { return v_##_Tp##x##num(vmv_v_x_##len##m1(0, num)); }     \
+inline v_##_Tp##x##num v_setall_##suffix(__Tp v) { return v_##_Tp##x##num(vmv_v_x_##len##m1(v, num)); } \
+template <> inline v_##_Tp##x##num v_setzero_() { return v_setzero_##suffix(); }          \
+template <> inline v_##_Tp##x##num v_setall_(__Tp v) { return v_setall_##suffix(v); }
+
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(uchar, uint8, u8, u8, 16)
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(schar, int8, s8, i8, 16)
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(ushort, uint16, u16, u16, 8)
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(short, int16, s16, i16, 8)
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(unsigned int, uint32, u32, u32, 4)
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(int, int32, s32, i32, 4)
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(unsigned long, uint64, u64, u64, 2)
+OPENCV_HAL_IMPL_RISCVV_INIT_SET(long, int64, s64, i64, 2)
+inline v_float32x4 v_setzero_f32() { return v_float32x4(vfmv_v_f_f32m1(0, 4)); }
+inline v_float32x4 v_setall_f32(float v) { return v_float32x4(vfmv_v_f_f32m1(v, 4)); }
+
+inline v_float64x2 v_setzero_f64() { return v_float64x2(vfmv_v_f_f64m1(0, 2)); }
+inline v_float64x2 v_setall_f64(double v) { return v_float64x2(vfmv_v_f_f64m1(v, 2)); }
+
+template <> inline v_float32x4 v_setzero_() { return v_setzero_f32(); }
+template <> inline v_float32x4 v_setall_(float v) { return v_setall_f32(v); }
+
+template <> inline v_float64x2 v_setzero_() { return v_setzero_f64(); }
+template <> inline v_float64x2 v_setall_(double v) { return v_setall_f64(v); }
+
+#define OPENCV_HAL_IMPL_RISCVV_BIN_OP(bin_op, _Tpvec, intrin) \
+inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_BIN_OPN(bin_op, _Tpvec, intrin, num) \
+inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val, num)); \
+}
+
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_uint8x16, vsaddu_vv_u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_uint8x16, vssubu_vv_u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_int8x16, vsadd_vv_i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_int8x16, vssub_vv_i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_uint16x8, vsaddu_vv_u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_uint16x8, vssubu_vv_u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_int16x8, vsadd_vv_i16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_int16x8, vssub_vv_i16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_int32x4, vadd_vv_i32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_int32x4, vsub_vv_i32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_mul, v_int32x4, vmul_vv_i32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_uint32x4, vadd_vv_u32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_uint32x4, vsub_vv_u32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_mul, v_uint32x4, vmul_vv_u32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_int64x2, vadd_vv_i64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_int64x2, vsub_vv_i64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_uint64x2, vadd_vv_u64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_uint64x2, vsub_vv_u64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_float32x4, vfadd_vv_f32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_float32x4, vfsub_vv_f32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_mul, v_float32x4, vfmul_vv_f32m1, 4)
+inline v_float32x4 v_div(const v_float32x4& a, const v_float32x4& b)
+{
+    return v_float32x4(vfdiv_vv_f32m1(a.val, b.val, 4));
+}
+
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_add, v_float64x2, vfadd_vv_f64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_sub, v_float64x2, vfsub_vv_f64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_mul, v_float64x2, vfmul_vv_f64m1, 2)
+inline v_float64x2 v_div(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float64x2(vfdiv_vv_f64m1(a.val, b.val, 2));
+}
+// TODO: exp, log, sin, cos
+
+#define OPENCV_HAL_IMPL_RISCVV_BIN_FUNC(_Tpvec, func, intrin) \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(_Tpvec, func, intrin, num) \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val, num)); \
+}
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint8x16, v_min, vminu_vv_u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint8x16, v_max, vmaxu_vv_u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int8x16, v_min, vmin_vv_i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int8x16, v_max, vmax_vv_i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint16x8, v_min, vminu_vv_u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint16x8, v_max, vmaxu_vv_u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int16x8, v_min, vmin_vv_i16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int16x8, v_max, vmax_vv_i16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint32x4, v_min, vminu_vv_u32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint32x4, v_max, vmaxu_vv_u32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int32x4, v_min, vmin_vv_i32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int32x4, v_max, vmax_vv_i32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_float32x4, v_min, vfmin_vv_f32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_float32x4, v_max, vfmax_vv_f32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_float64x2, v_min, vfmin_vv_f64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_float64x2, v_max, vfmax_vv_f64m1, 2)
+
+inline v_float32x4 v_sqrt(const v_float32x4& x)
+{
+    return v_float32x4(vfsqrt_v_f32m1(x.val, 4));
+}
+
+inline v_float32x4 v_invsqrt(const v_float32x4& x)
+{
+    return v_float32x4(vfrdiv_vf_f32m1(vfsqrt_v_f32m1(x.val, 4), 1, 4));
+}
+
+inline v_float32x4 v_magnitude(const v_float32x4& a, const v_float32x4& b)
+{
+    v_float32x4 x(vfmacc_vv_f32m1(vfmul_vv_f32m1(a.val, a.val, 4), b.val, b.val, 4));
+    return v_sqrt(x);
+}
+
+inline v_float32x4 v_sqr_magnitude(const v_float32x4& a, const v_float32x4& b)
+{
+    return v_float32x4(vfmacc_vv_f32m1(vfmul_vv_f32m1(a.val, a.val, 4), b.val, b.val, 4));
+}
+
+inline v_float32x4 v_fma(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+    return v_float32x4(vfmadd_vv_f32m1(a.val, b.val, c.val, 4));
+}
+
+inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_int32x4(vmadd_vv_i32m1(a.val, b.val, c.val, 4));
+}
+
+inline v_float32x4 v_muladd(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
+                            const v_float32x4& m1, const v_float32x4& m2,
+                            const v_float32x4& m3)
+{
+    vfloat32m1_t res = vfmul_vv_f32m1(m0.val, vrgather_vx_f32m1(v.val, 0, 4), 4);//vmuli_f32(m0.val, v.val, 0);
+    res = vfmacc_vv_f32m1(res, vrgather_vx_f32m1(v.val, 1, 4), m1.val, 4);//vmulai_f32(res, m1.val, v.val, 1);
+    res = vfmacc_vv_f32m1(res, vrgather_vx_f32m1(v.val, 2, 4), m2.val, 4);//vmulai_f32(res, m1.val, v.val, 1);
+    res = vfmacc_vv_f32m1(res, vrgather_vx_f32m1(v.val, 3, 4), m3.val, 4);//vmulai_f32(res, m1.val, v.val, 1);
+    return v_float32x4(res);
+}
+
+inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0,
+                               const v_float32x4& m1, const v_float32x4& m2,
+                               const v_float32x4& a)
+{
+    vfloat32m1_t res = vfmul_vv_f32m1(m0.val, vrgather_vx_f32m1(v.val, 0, 4), 4);//vmuli_f32(m0.val, v.val, 0);
+    res = vfmacc_vv_f32m1(res, vrgather_vx_f32m1(v.val, 1, 4), m1.val, 4);//vmulai_f32(res, m1.val, v.val, 1);
+    res = vfmacc_vv_f32m1(res, vrgather_vx_f32m1(v.val, 2, 4), m2.val, 4);//vmulai_f32(res, m1.val, v.val, 1);
+    res = vfadd_vv_f32m1(res, a.val, 4);//vmulai_f32(res, m1.val, v.val, 1);
+    return v_float32x4(res);
+}
+
+inline v_float64x2 v_sqrt(const v_float64x2& x)
+{
+    return v_float64x2(vfsqrt_v_f64m1(x.val, 2));
+}
+
+inline v_float64x2 v_invsqrt(const v_float64x2& x)
+{
+    return v_float64x2(vfrdiv_vf_f64m1(vfsqrt_v_f64m1(x.val, 2), 1, 2));
+}
+
+inline v_float64x2 v_magnitude(const v_float64x2& a, const v_float64x2& b)
+{
+    v_float64x2 x(vfmacc_vv_f64m1(vfmul_vv_f64m1(a.val, a.val, 2), b.val, b.val, 2));
+    return v_sqrt(x);
+}
+
+inline v_float64x2 v_sqr_magnitude(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float64x2(vfmacc_vv_f64m1(vfmul_vv_f64m1(a.val, a.val, 2), b.val, b.val, 2));
+}
+
+inline v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+    return v_float64x2(vfmadd_vv_f64m1(a.val, b.val, c.val, 2));
+}
+
+inline v_float64x2 v_muladd(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+    return v_fma(a, b, c);
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(_Tpvec, suffix, num) \
+    OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_and, _Tpvec, vand_vv_##suffix, num) \
+    OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_or, _Tpvec, vor_vv_##suffix, num)   \
+    OPENCV_HAL_IMPL_RISCVV_BIN_OPN(v_xor, _Tpvec, vxor_vv_##suffix, num) \
+    inline _Tpvec v_not(const _Tpvec & a) \
+    { \
+        return _Tpvec(vnot_v_##suffix(a.val, num)); \
+    }
+
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_uint8x16, u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_uint16x8, u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_uint32x4, u32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_uint64x2, u64m1, 2)
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_int8x16,  i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_int16x8,  i16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_int32x4,  i32m1, 4)
+OPENCV_HAL_IMPL_RISCVV_LOGIC_OPN(v_int64x2,  i64m1, 2)
+
+#define OPENCV_HAL_IMPL_RISCVV_FLT_BIT_OP(bin_op, intrin) \
+inline v_float32x4 bin_op(const v_float32x4& a, const v_float32x4& b) \
+{ \
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(intrin(vreinterpret_v_f32m1_i32m1(a.val), vreinterpret_v_f32m1_i32m1(b.val), 4))); \
+}
+
+OPENCV_HAL_IMPL_RISCVV_FLT_BIT_OP(v_and, vand_vv_i32m1)
+OPENCV_HAL_IMPL_RISCVV_FLT_BIT_OP(v_or, vor_vv_i32m1)
+OPENCV_HAL_IMPL_RISCVV_FLT_BIT_OP(v_xor, vxor_vv_i32m1)
+
+inline v_float32x4 v_not(const v_float32x4& a)
+{
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(vnot_v_i32m1(vreinterpret_v_f32m1_i32m1(a.val), 4)));
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_FLT_64BIT_OP(bin_op, intrin) \
+inline v_float64x2 bin_op(const v_float64x2& a, const v_float64x2& b) \
+{ \
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(intrin(vreinterpret_v_f64m1_i64m1(a.val), vreinterpret_v_f64m1_i64m1(b.val), 2))); \
+}
+
+OPENCV_HAL_IMPL_RISCVV_FLT_64BIT_OP(v_and, vand_vv_i64m1)
+OPENCV_HAL_IMPL_RISCVV_FLT_64BIT_OP(v_or, vor_vv_i64m1)
+OPENCV_HAL_IMPL_RISCVV_FLT_64BIT_OP(v_xor, vxor_vv_i64m1)
+
+inline v_float64x2 v_not(const v_float64x2& a)
+{
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(vnot_v_i64m1(vreinterpret_v_f64m1_i64m1(a.val), 2)));
+}
+inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b)
+{
+    return v_int16x8(vmulh_vv_i16m1(a.val, b.val, 8));
+}
+inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b)
+{
+    return v_uint16x8(vmulhu_vv_u16m1(a.val, b.val, 8));
+}
+
+//#define OPENCV_HAL_IMPL_RISCVV_ABS(_Tpuvec, _Tpsvec, usuffix, ssuffix) \
+//inline _Tpuvec v_abs(const _Tpsvec& a) {    \
+//    E##xm1_t mask=vmflt_vf_e32xm1_f32m1(x.val, 0.0, 4);
+
+//OPENCV_HAL_IMPL_RISCVV_ABS(v_uint8x16, v_int8x16, u8, s8)
+//OPENCV_HAL_IMPL_RISCVV_ABS(v_uint16x8, v_int16x8, u16, s16)
+//OPENCV_HAL_IMPL_RISCVV_ABS(v_uint32x4, v_int32x4, u32, s32)
+
+inline v_uint32x4 v_abs(v_int32x4 x)
+{
+    vbool32_t mask=vmslt_vx_i32m1_b32(x.val, 0, 4);
+    return v_uint32x4(vreinterpret_v_i32m1_u32m1(vrsub_vx_i32m1_m(mask, x.val, x.val, 0, 4)));
+}
+
+inline v_uint16x8 v_abs(v_int16x8 x)
+{
+    vbool16_t mask=vmslt_vx_i16m1_b16(x.val, 0, 8);
+    return v_uint16x8(vreinterpret_v_i16m1_u16m1(vrsub_vx_i16m1_m(mask, x.val, x.val, 0, 8)));
+}
+
+inline v_uint8x16 v_abs(v_int8x16 x)
+{
+    vbool8_t mask=vmslt_vx_i8m1_b8(x.val, 0, 16);
+    return v_uint8x16(vreinterpret_v_i8m1_u8m1(vrsub_vx_i8m1_m(mask, x.val, x.val, 0, 16)));
+}
+
+inline v_float32x4 v_abs(v_float32x4 x)
+{
+    return (v_float32x4)vfsgnjx_vv_f32m1(x.val, x.val, 4);
+}
+
+inline v_float64x2 v_abs(v_float64x2 x)
+{
+    return (v_float64x2)vfsgnjx_vv_f64m1(x.val, x.val, 2);
+}
+
+inline v_float32x4 v_absdiff(const v_float32x4& a, const v_float32x4& b)
+{
+    vfloat32m1_t ret = vfsub_vv_f32m1(a.val, b.val, 4);
+    return (v_float32x4)vfsgnjx_vv_f32m1(ret, ret, 4);
+}
+
+inline v_float64x2 v_absdiff(const v_float64x2& a, const v_float64x2& b)
+{
+    vfloat64m1_t ret = vfsub_vv_f64m1(a.val, b.val, 2);
+    return (v_float64x2)vfsgnjx_vv_f64m1(ret, ret, 2);
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_ABSDIFF_U(bit, num) \
+inline v_uint##bit##x##num v_absdiff(v_uint##bit##x##num a, v_uint##bit##x##num b){    \
+    vuint##bit##m1_t vmax = vmaxu_vv_u##bit##m1(a.val, b.val, num);    \
+    vuint##bit##m1_t vmin = vminu_vv_u##bit##m1(a.val, b.val, num);    \
+    return v_uint##bit##x##num(vsub_vv_u##bit##m1(vmax, vmin, num));\
+}
+
+OPENCV_HAL_IMPL_RISCVV_ABSDIFF_U(8, 16)
+OPENCV_HAL_IMPL_RISCVV_ABSDIFF_U(16, 8)
+OPENCV_HAL_IMPL_RISCVV_ABSDIFF_U(32, 4)
+
+/** Saturating absolute difference **/
+inline v_int8x16 v_absdiffs(v_int8x16 a, v_int8x16 b){
+    vint8m1_t vmax = vmax_vv_i8m1(a.val, b.val, 16);
+    vint8m1_t vmin = vmin_vv_i8m1(a.val, b.val, 16);
+    return v_int8x16(vssub_vv_i8m1(vmax, vmin, 16));
+}
+inline v_int16x8 v_absdiffs(v_int16x8 a, v_int16x8 b){
+    vint16m1_t vmax = vmax_vv_i16m1(a.val, b.val, 8);
+    vint16m1_t vmin = vmin_vv_i16m1(a.val, b.val, 8);
+    return v_int16x8(vssub_vv_i16m1(vmax, vmin, 8));
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_ABSDIFF(_Tpvec, _Tpv, num) \
+inline v_uint##_Tpvec v_absdiff(v_int##_Tpvec a, v_int##_Tpvec b){    \
+     vint##_Tpv##_t max = vmax_vv_i##_Tpv(a.val, b.val, num);\
+     vint##_Tpv##_t min = vmin_vv_i##_Tpv(a.val, b.val, num);\
+    return v_uint##_Tpvec(vreinterpret_v_i##_Tpv##_u##_Tpv(vsub_vv_i##_Tpv(max, min, num)));    \
+}
+
+OPENCV_HAL_IMPL_RISCVV_ABSDIFF(8x16, 8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_ABSDIFF(16x8, 16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_ABSDIFF(32x4, 32m1, 4)
+
+//  Multiply and expand
+inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b,
+                         v_int16x8& c, v_int16x8& d)
+{
+    vint16m2_t res = vundefined_i16m2();
+    res = vwmul_vv_i16m2(a.val, b.val, 16);
+    c.val = vget_v_i16m2_i16m1(res, 0);
+    d.val = vget_v_i16m2_i16m1(res, 1);
+}
+
+inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b,
+                         v_uint16x8& c, v_uint16x8& d)
+{
+    vuint16m2_t res = vundefined_u16m2();
+    res = vwmulu_vv_u16m2(a.val, b.val, 16);
+    c.val = vget_v_u16m2_u16m1(res, 0);
+    d.val = vget_v_u16m2_u16m1(res, 1);
+}
+
+inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b,
+                         v_int32x4& c, v_int32x4& d)
+{
+    vint32m2_t res = vundefined_i32m2();
+    res = vwmul_vv_i32m2(a.val, b.val, 8);
+    c.val = vget_v_i32m2_i32m1(res, 0);
+    d.val = vget_v_i32m2_i32m1(res, 1);
+}
+
+inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b,
+                         v_uint32x4& c, v_uint32x4& d)
+{
+    vuint32m2_t res = vundefined_u32m2();
+    res = vwmulu_vv_u32m2(a.val, b.val, 8);
+    c.val = vget_v_u32m2_u32m1(res, 0);
+    d.val = vget_v_u32m2_u32m1(res, 1);
+}
+
+inline void v_mul_expand(const v_int32x4& a, const v_int32x4& b,
+                         v_int64x2& c, v_int64x2& d)
+{
+    vint64m2_t res = vundefined_i64m2();
+    res = vwmul_vv_i64m2(a.val, b.val, 4);
+    c.val = vget_v_i64m2_i64m1(res, 0);
+    d.val = vget_v_i64m2_i64m1(res, 1);
+}
+
+inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b,
+                         v_uint64x2& c, v_uint64x2& d)
+{
+    vuint64m2_t res = vundefined_u64m2();
+    res = vwmulu_vv_u64m2(a.val, b.val, 4);
+    c.val = vget_v_u64m2_u64m1(res, 0);
+    d.val = vget_v_u64m2_u64m1(res, 1);
+}
+
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint8x16, v_add_wrap, vadd_vv_u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int8x16, v_add_wrap, vadd_vv_i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint16x8, v_add_wrap, vadd_vv_u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int16x8, v_add_wrap, vadd_vv_i16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint8x16, v_sub_wrap, vsub_vv_u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int8x16, v_sub_wrap, vsub_vv_i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint16x8, v_sub_wrap, vsub_vv_u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int16x8, v_sub_wrap, vsub_vv_i16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint8x16, v_mul_wrap, vmul_vv_u8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int8x16, v_mul_wrap, vmul_vv_i8m1, 16)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_uint16x8, v_mul_wrap, vmul_vv_u16m1, 8)
+OPENCV_HAL_IMPL_RISCVV_BINN_FUNC(v_int16x8, v_mul_wrap, vmul_vv_i16m1, 8)
+//////// Dot Product ////////
+// 16 >> 32
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
+{
+    vuint32m2_t vindex = vundefined_u32m2();
+    vuint32m1_t vindex0 = vid_v_u32m1(4);
+    vindex0 = vsll_vx_u32m1(vindex0, 1, 4);
+    vindex = vset_v_u32m1_u32m2(vindex, 0, vindex0);
+    vindex = vset_v_u32m1_u32m2(vindex, 1, vadd_vx_u32m1(vindex0, 1, 4));
+    vint32m2_t res = vundefined_i32m2();
+    res = vwmul_vv_i32m2(a.val, b.val, 8);
+    res = vrgather_vv_i32m2(res, vindex, 8);
+    return v_int32x4(vadd_vv_i32m1(vget_v_i32m2_i32m1(res, 0), vget_v_i32m2_i32m1(res, 1), 4));
+}
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{
+    vuint32m2_t vindex = vundefined_u32m2();
+    vuint32m1_t vindex0 = vid_v_u32m1(4);
+    vindex0 = vsll_vx_u32m1(vindex0, 1, 4);
+    vindex = vset_v_u32m1_u32m2(vindex, 0, vindex0);
+    vindex = vset_v_u32m1_u32m2(vindex, 1, vadd_vx_u32m1(vindex0, 1, 4));
+    vint32m2_t res = vundefined_i32m2();
+    res = vwmul_vv_i32m2(a.val, b.val, 8);
+    res = vrgather_vv_i32m2(res, vindex, 8);
+    return v_int32x4(vadd_vv_i32m1(vadd_vv_i32m1(vget_v_i32m2_i32m1(res, 0),vget_v_i32m2_i32m1(res, 1), 4), c.val, 4));
+}
+
+// 32 >> 64
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b)
+{
+    vuint64m2_t vindex = vundefined_u64m2();
+    vuint64m1_t vindex0 = vid_v_u64m1(2);
+    vindex0 = vsll_vx_u64m1(vindex0, 1, 2);
+    vindex = vset_v_u64m1_u64m2(vindex, 0, vindex0);
+    vindex = vset_v_u64m1_u64m2(vindex, 1, vadd_vx_u64m1(vindex0, 1, 2));
+    vint64m2_t res = vundefined_i64m2();
+    res = vwmul_vv_i64m2(a.val, b.val, 4);
+    res = vrgather_vv_i64m2(res, vindex, 4);
+    return v_int64x2(vadd_vv_i64m1(vget_v_i64m2_i64m1(res, 0), vget_v_i64m2_i64m1(res, 1), 2));
+}
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{
+    vuint64m2_t vindex = vundefined_u64m2();
+    vuint64m1_t vindex0 = vid_v_u64m1(2);
+    vindex0 = vsll_vx_u64m1(vindex0, 1, 2);
+    vindex = vset_v_u64m1_u64m2(vindex, 0, vindex0);
+    vindex = vset_v_u64m1_u64m2(vindex, 1, vadd_vx_u64m1(vindex0, 1, 2));
+    vint64m2_t res = vundefined_i64m2();
+    res = vwmul_vv_i64m2(a.val, b.val, 4);
+    res = vrgather_vv_i64m2(res, vindex, 4);
+    return v_int64x2(vadd_vv_i64m1(vadd_vv_i64m1(vget_v_i64m2_i64m1(res, 0), vget_v_i64m2_i64m1(res, 1), 2), c.val, 2));
+}
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
+{
+    vuint32m4_t vindex32 = vundefined_u32m4();
+    vuint32m1_t vindex0 = vid_v_u32m1(4);
+    vindex0 = vsll_vx_u32m1(vindex0, 2, 4);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 0, vindex0);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 1, vadd_vx_u32m1(vindex0, 1, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 2, vadd_vx_u32m1(vindex0, 2, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 3, vadd_vx_u32m1(vindex0, 3, 4));
+    vuint16m2_t vindex = vnsrl_wx_u16m2(vindex32, 0, 16);
+    vuint16m2_t v1 = vundefined_u16m2();
+    vuint32m2_t v2 = vundefined_u32m2();
+    v1 = vwmulu_vv_u16m2(a.val, b.val, 16);
+    v1 = vrgather_vv_u16m2(v1, vindex, 16);
+    v2 = vwaddu_vv_u32m2(vget_v_u16m2_u16m1(v1, 0), vget_v_u16m2_u16m1(v1, 1), 8);
+    return v_uint32x4(vadd_vv_u32m1(vget_v_u32m2_u32m1(v2, 0), vget_v_u32m2_u32m1(v2, 1), 4));
+}
+
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b,
+                                   const v_uint32x4& c)
+{
+    vuint32m4_t vindex32 = vundefined_u32m4();
+    vuint32m1_t vindex0 = vid_v_u32m1(4);
+    vindex0 = vsll_vx_u32m1(vindex0, 2, 4);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 0, vindex0);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 1, vadd_vx_u32m1(vindex0, 1, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 2, vadd_vx_u32m1(vindex0, 2, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 3, vadd_vx_u32m1(vindex0, 3, 4));
+    vuint16m2_t vindex = vnsrl_wx_u16m2(vindex32, 0, 16);
+    vuint16m2_t v1 = vundefined_u16m2();
+    vuint32m2_t v2 = vundefined_u32m2();
+    v1 = vwmulu_vv_u16m2(a.val, b.val, 16);
+    v1 = vrgather_vv_u16m2(v1, vindex, 16);
+    v2 = vwaddu_vv_u32m2(vget_v_u16m2_u16m1(v1, 0), vget_v_u16m2_u16m1(v1, 1), 8);
+    return v_uint32x4(vadd_vv_u32m1(vadd_vv_u32m1(vget_v_u32m2_u32m1(v2, 0), vget_v_u32m2_u32m1(v2, 1), 4), c.val, 4));
+}
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
+{
+    vuint32m4_t vindex32 = vundefined_u32m4();
+    vuint32m1_t vindex0 = vid_v_u32m1(4);
+    vindex0 = vsll_vx_u32m1(vindex0, 2, 4);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 0, vindex0);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 1, vadd_vx_u32m1(vindex0, 1, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 2, vadd_vx_u32m1(vindex0, 2, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 3, vadd_vx_u32m1(vindex0, 3, 4));
+    vuint16m2_t vindex = vnsrl_wx_u16m2(vindex32, 0, 16);
+    vint16m2_t v1 = vundefined_i16m2();
+    vint32m2_t v2 = vundefined_i32m2();
+    v1 = vwmul_vv_i16m2(a.val, b.val, 16);
+    v1 = vrgather_vv_i16m2(v1, vindex, 16);
+    v2 = vwadd_vv_i32m2(vget_v_i16m2_i16m1(v1, 0), vget_v_i16m2_i16m1(v1, 1), 8);
+    return v_int32x4(vadd_vv_i32m1(vget_v_i32m2_i32m1(v2, 0), vget_v_i32m2_i32m1(v2, 1), 4));
+}
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b,
+                                   const v_int32x4& c)
+{
+    vuint32m4_t vindex32 = vundefined_u32m4();
+    vuint32m1_t vindex0 = vid_v_u32m1(4);
+    vindex0 = vsll_vx_u32m1(vindex0, 2, 4);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 0, vindex0);
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 1, vadd_vx_u32m1(vindex0, 1, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 2, vadd_vx_u32m1(vindex0, 2, 4));
+    vindex32 = vset_v_u32m1_u32m4(vindex32, 3, vadd_vx_u32m1(vindex0, 3, 4));
+    vuint16m2_t vindex = vnsrl_wx_u16m2(vindex32, 0, 16);
+    vint16m2_t v1 = vundefined_i16m2();
+    vint32m2_t v2 = vundefined_i32m2();
+    v1 = vwmul_vv_i16m2(a.val, b.val, 16);
+    v1 = vrgather_vv_i16m2(v1, vindex, 16);
+    v2 = vwadd_vv_i32m2(vget_v_i16m2_i16m1(v1, 0), vget_v_i16m2_i16m1(v1, 1), 8);
+    return v_int32x4(vadd_vv_i32m1(vadd_vv_i32m1(vget_v_i32m2_i32m1(v2, 0), vget_v_i32m2_i32m1(v2, 1), 4), c.val, 4));
+}
+
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
+{
+    vuint64m4_t vindex64 = vundefined_u64m4();
+    vuint64m1_t vindex0 = vid_v_u64m1(2);
+    vindex0 = vsll_vx_u64m1(vindex0, 2, 2);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 0, vindex0);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 1, vadd_vx_u64m1(vindex0, 1, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 2, vadd_vx_u64m1(vindex0, 2, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 3, vadd_vx_u64m1(vindex0, 3, 2));
+    vuint32m2_t vindex = vnsrl_wx_u32m2(vindex64, 0, 8);
+    vuint32m2_t v1 = vundefined_u32m2();
+    vuint64m2_t v2 = vundefined_u64m2();
+    v1 = vwmulu_vv_u32m2(a.val, b.val, 8);
+    v1 = vrgather_vv_u32m2(v1, vindex, 8);
+    v2 = vwaddu_vv_u64m2(vget_v_u32m2_u32m1(v1, 0), vget_v_u32m2_u32m1(v1, 1), 4);
+    return v_uint64x2(vadd_vv_u64m1(vget_v_u64m2_u64m1(v2, 0), vget_v_u64m2_u64m1(v2, 1), 2));
+}
+
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b,
+                                   const v_uint64x2& c)
+{
+    vuint64m4_t vindex64 = vundefined_u64m4();
+    vuint64m1_t vindex0 = vid_v_u64m1(2);
+    vindex0 = vsll_vx_u64m1(vindex0, 2, 2);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 0, vindex0);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 1, vadd_vx_u64m1(vindex0, 1, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 2, vadd_vx_u64m1(vindex0, 2, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 3, vadd_vx_u64m1(vindex0, 3, 2));
+    vuint32m2_t vindex = vnsrl_wx_u32m2(vindex64, 0, 8);
+    vuint32m2_t v1 = vundefined_u32m2();
+    vuint64m2_t v2 = vundefined_u64m2();
+    v1 = vwmulu_vv_u32m2(a.val, b.val, 8);
+    v1 = vrgather_vv_u32m2(v1, vindex, 8);
+    v2 = vwaddu_vv_u64m2(vget_v_u32m2_u32m1(v1, 0), vget_v_u32m2_u32m1(v1, 1), 4);
+    return v_uint64x2(vadd_vv_u64m1(vadd_vv_u64m1(vget_v_u64m2_u64m1(v2, 0), vget_v_u64m2_u64m1(v2, 1), 2), c.val, 2));
+}
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b)
+{
+    vuint64m4_t vindex64 = vundefined_u64m4();
+    vuint64m1_t vindex0 = vid_v_u64m1(2);
+    vindex0 = vsll_vx_u64m1(vindex0, 2, 2);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 0, vindex0);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 1, vadd_vx_u64m1(vindex0, 1, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 2, vadd_vx_u64m1(vindex0, 2, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 3, vadd_vx_u64m1(vindex0, 3, 2));
+    vuint32m2_t vindex = vnsrl_wx_u32m2(vindex64, 0, 8);
+    vint32m2_t v1 = vundefined_i32m2();
+    vint64m2_t v2 = vundefined_i64m2();
+    v1 = vwmul_vv_i32m2(a.val, b.val, 8);
+    v1 = vrgather_vv_i32m2(v1, vindex, 8);
+    v2 = vwadd_vv_i64m2(vget_v_i32m2_i32m1(v1, 0), vget_v_i32m2_i32m1(v1, 1), 4);
+    return v_int64x2(vadd_vv_i64m1(vget_v_i64m2_i64m1(v2, 0), vget_v_i64m2_i64m1(v2, 1), 2));
+}
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b,
+                                   const v_int64x2& c)
+{
+    vuint64m4_t vindex64 = vundefined_u64m4();
+    vuint64m1_t vindex0 = vid_v_u64m1(2);
+    vindex0 = vsll_vx_u64m1(vindex0, 2, 2);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 0, vindex0);
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 1, vadd_vx_u64m1(vindex0, 1, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 2, vadd_vx_u64m1(vindex0, 2, 2));
+    vindex64 = vset_v_u64m1_u64m4(vindex64, 3, vadd_vx_u64m1(vindex0, 3, 2));
+    vuint32m2_t vindex = vnsrl_wx_u32m2(vindex64, 0, 8);
+    vint32m2_t v1 = vundefined_i32m2();
+    vint64m2_t v2 = vundefined_i64m2();
+    v1 = vwmul_vv_i32m2(a.val, b.val, 8);
+    v1 = vrgather_vv_i32m2(v1, vindex, 8);
+    v2 = vwadd_vv_i64m2(vget_v_i32m2_i32m1(v1, 0), vget_v_i32m2_i32m1(v1, 1), 4);
+    return v_int64x2(vadd_vv_i64m1(vadd_vv_i64m1(vget_v_i64m2_i64m1(v2, 0), vget_v_i64m2_i64m1(v2, 1), 2), c.val, 2));
+}
+
+//////// Fast Dot Product ////////
+// 16 >> 32
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b)
+{
+    vint32m2_t v1 = vundefined_i32m2();
+    v1 = vwmul_vv_i32m2(a.val, b.val, 8);
+    return v_int32x4(vadd_vv_i32m1(vget_v_i32m2_i32m1(v1, 0), vget_v_i32m2_i32m1(v1, 1), 4));
+}
+
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{
+    vint32m2_t v1 = vundefined_i32m2();
+    v1 = vwmul_vv_i32m2(a.val, b.val, 8);
+    return v_int32x4(vadd_vv_i32m1(vadd_vv_i32m1(vget_v_i32m2_i32m1(v1, 0), vget_v_i32m2_i32m1(v1, 1), 4), c.val, 4));
+}
+
+// 32 >> 64
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b)
+{
+    vint64m2_t v1 = vundefined_i64m2();
+    v1 = vwmul_vv_i64m2(a.val, b.val, 4);
+    return v_int64x2(vadd_vv_i64m1(vget_v_i64m2_i64m1(v1, 0), vget_v_i64m2_i64m1(v1, 1), 2));
+}
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{
+    vint64m2_t v1 = vundefined_i64m2();
+    v1 = vwmul_vv_i64m2(a.val, b.val, 8);
+    return v_int64x2(vadd_vv_i64m1(vadd_vv_i64m1(vget_v_i64m2_i64m1(v1, 0), vget_v_i64m2_i64m1(v1, 1), 4), c.val, 4));
+}
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
+{
+    vuint16m2_t v1 = vundefined_u16m2();
+    vuint32m2_t v2 = vundefined_u32m2();
+    v1 = vwmulu_vv_u16m2(a.val, b.val, 16);
+    v2 = vwaddu_vv_u32m2(vget_v_u16m2_u16m1(v1, 0), vget_v_u16m2_u16m1(v1, 1), 8);
+    return v_uint32x4(vadd_vv_u32m1(vget_v_u32m2_u32m1(v2, 0), vget_v_u32m2_u32m1(v2, 1), 4));
+}
+
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{
+    vuint16m2_t v1 = vundefined_u16m2();
+    vuint32m2_t v2 = vundefined_u32m2();
+    v1 = vwmulu_vv_u16m2(a.val, b.val, 16);
+    v2 = vwaddu_vv_u32m2(vget_v_u16m2_u16m1(v1, 0), vget_v_u16m2_u16m1(v1, 1), 8);
+    return v_uint32x4(vadd_vv_u32m1(vadd_vv_u32m1(vget_v_u32m2_u32m1(v2, 0), vget_v_u32m2_u32m1(v2, 1), 4), c.val, 4));
+}
+
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
+{
+    vint16m2_t v1 = vundefined_i16m2();
+    vint32m2_t v2 = vundefined_i32m2();
+    v1 = vwmul_vv_i16m2(a.val, b.val, 16);
+    v2 = vwadd_vv_i32m2(vget_v_i16m2_i16m1(v1, 0), vget_v_i16m2_i16m1(v1, 1), 8);
+    return v_int32x4(vadd_vv_i32m1(vget_v_i32m2_i32m1(v2, 0), vget_v_i32m2_i32m1(v2, 1), 4));
+}
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{
+    vint16m2_t v1 = vundefined_i16m2();
+    vint32m2_t v2 = vundefined_i32m2();
+    v1 = vwmul_vv_i16m2(a.val, b.val, 16);
+    v2 = vwadd_vv_i32m2(vget_v_i16m2_i16m1(v1, 0), vget_v_i16m2_i16m1(v1, 1), 8);
+    return v_int32x4(vadd_vv_i32m1(vadd_vv_i32m1(vget_v_i32m2_i32m1(v2, 0), vget_v_i32m2_i32m1(v2, 1), 4), c.val, 4));
+}
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
+{
+    vuint32m2_t v1 = vundefined_u32m2();
+    vuint64m2_t v2 = vundefined_u64m2();
+    v1 = vwmulu_vv_u32m2(a.val, b.val, 8);
+    v2 = vwaddu_vv_u64m2(vget_v_u32m2_u32m1(v1, 0), vget_v_u32m2_u32m1(v1, 1), 4);
+    return v_uint64x2(vadd_vv_u64m1(vget_v_u64m2_u64m1(v2, 0), vget_v_u64m2_u64m1(v2, 1), 2));
+}
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{
+    vuint32m2_t v1 = vundefined_u32m2();
+    vuint64m2_t v2 = vundefined_u64m2();
+    v1 = vwmulu_vv_u32m2(a.val, b.val, 8);
+    v2 = vwaddu_vv_u64m2(vget_v_u32m2_u32m1(v1, 0), vget_v_u32m2_u32m1(v1, 1), 4);
+    return v_uint64x2(vadd_vv_u64m1(vadd_vv_u64m1(vget_v_u64m2_u64m1(v2, 0), vget_v_u64m2_u64m1(v2, 1), 2), c.val, 2));
+}
+
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b)
+{
+    vint32m2_t v1 = vundefined_i32m2();
+    vint64m2_t v2 = vundefined_i64m2();
+    v1 = vwmul_vv_i32m2(a.val, b.val, 8);
+    v2 = vwadd_vv_i64m2(vget_v_i32m2_i32m1(v1, 0), vget_v_i32m2_i32m1(v1, 1), 4);
+    return v_int64x2(vadd_vv_i64m1(vget_v_i64m2_i64m1(v2, 0), vget_v_i64m2_i64m1(v2, 1), 2));
+}
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{
+    vint32m2_t v1 = vundefined_i32m2();
+    vint64m2_t v2 = vundefined_i64m2();
+    v1 = vwmul_vv_i32m2(a.val, b.val, 8);
+    v2 = vwadd_vv_i64m2(vget_v_i32m2_i32m1(v1, 0), vget_v_i32m2_i32m1(v1, 1), 4);
+    return v_int64x2(vadd_vv_i64m1(vadd_vv_i64m1(vget_v_i64m2_i64m1(v2, 0), vget_v_i64m2_i64m1(v2, 1), 2), c.val, 2));
+}
+
+
+#define OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_W(_Tpvec, _Tpvec2, len, scalartype, func, intrin, num) \
+inline scalartype v_reduce_##func(const v_##_Tpvec##x##num& a) \
+{\
+    v##_Tpvec2##m1_t val = vmv_v_x_##len##m1(0, num); \
+    val = intrin(val, a.val, val, num);    \
+    return vmv_x_s_##len##m1_##len(val);    \
+}
+
+
+#define OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(_Tpvec, _Tpvec2, scalartype, func, funcu, num, scalerfunc) \
+inline scalartype v_reduce_##func(const v_##_Tpvec##x##num& a) \
+{\
+    v##_Tpvec##m1_t val = vundefined_##_Tpvec2##m1(); \
+    val = v##funcu##_vs_##_Tpvec2##m1_##_Tpvec2##m1(val, a.val, a.val, num);    \
+    return scalerfunc(val);    \
+}
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_W(int8, int16, i16, int, sum, vwredsum_vs_i8m1_i16m1, 16)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_W(int16, int32, i32, int, sum, vwredsum_vs_i16m1_i32m1, 8)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_W(int32, int64, i64, int, sum, vwredsum_vs_i32m1_i64m1, 4)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_W(uint8, uint16, u16, unsigned, sum, vwredsumu_vs_u8m1_u16m1, 16)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_W(uint16, uint32, u32, unsigned, sum, vwredsumu_vs_u16m1_u32m1, 8)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_W(uint32, uint64, u64, unsigned, sum, vwredsumu_vs_u32m1_u64m1, 4)
+inline float v_reduce_sum(const v_float32x4& a) \
+{\
+    vfloat32m1_t val = vfmv_v_f_f32m1(0.0, 4); \
+    val = vfredosum_vs_f32m1_f32m1(val, a.val, val, 4);    \
+    return vfmv_f_s_f32m1_f32(val);    \
+}
+inline double v_reduce_sum(const v_float64x2& a) \
+{\
+    vfloat64m1_t val = vfmv_v_f_f64m1(0.0, 2); \
+    val = vfredosum_vs_f64m1_f64m1(val, a.val, val, 2);    \
+    return vfmv_f_s_f64m1_f64(val);    \
+}
+inline uint64 v_reduce_sum(const v_uint64x2& a)
+{ vuint64m1_t res = vundefined_u64m1(); return vmv_x_s_u64m1_u64(vredsum_vs_u64m1_u64m1(res, a.val, vmv_v_x_u64m1(0, 2), 2)); }
+
+inline int64 v_reduce_sum(const v_int64x2& a)
+{ vint64m1_t res = vundefined_i64m1(); return vmv_x_s_i64m1_i64(vredsum_vs_i64m1_i64m1(res, a.val, vmv_v_x_i64m1(0, 2), 2)); }
+
+#define OPENCV_HAL_IMPL_RISCVV_REDUCE_OP(func)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(int8,  i8, int, func, red##func, 16, vmv_x_s_i8m1_i8)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(int16, i16, int, func, red##func, 8, vmv_x_s_i16m1_i16)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(int32, i32, int, func, red##func, 4, vmv_x_s_i32m1_i32)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(int64, i64, int, func, red##func, 2, vmv_x_s_i64m1_i64)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(uint8,  u8, unsigned, func, red##func##u, 16, vmv_x_s_u8m1_u8)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(uint16, u16, unsigned, func, red##func##u, 8, vmv_x_s_u16m1_u16)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(uint32, u32, unsigned, func, red##func##u, 4, vmv_x_s_u32m1_u32)    \
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP_(float32, f32, float, func, fred##func, 4, vfmv_f_s_f32m1_f32)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP(max)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_OP(min)
+
+inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b,
+                                 const v_float32x4& c, const v_float32x4& d)
+{
+    vfloat32m1_t a0 = vfmv_v_f_f32m1(0.0, 4);
+    vfloat32m1_t b0 = vfmv_v_f_f32m1(0.0, 4);
+    vfloat32m1_t c0 = vfmv_v_f_f32m1(0.0, 4);
+    vfloat32m1_t d0 = vfmv_v_f_f32m1(0.0, 4);
+    a0 = vfredosum_vs_f32m1_f32m1(a0, a.val, a0, 4);
+    b0 = vfredosum_vs_f32m1_f32m1(b0, b.val, b0, 4);
+    c0 = vfredosum_vs_f32m1_f32m1(c0, c.val, c0, 4);
+    d0 = vfredosum_vs_f32m1_f32m1(d0, d.val, d0, 4);
+    vfloat32m1_t res;
+    res = vslideup_vx_f32m1(a0, b0, 1, 4);
+    res = vslideup_vx_f32m1(res, c0, 2, 4);
+    res = vslideup_vx_f32m1(res, d0, 3, 4);
+    return v_float32x4(res);
+}
+
+inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b)
+{
+    vfloat32m1_t a0 = vfmv_v_f_f32m1(0.0, 4);
+    vfloat32m1_t x = vfsub_vv_f32m1(a.val, b.val, 4);
+    vbool32_t mask=vmflt_vf_f32m1_b32(x, 0, 4);
+    vfloat32m1_t val = vfrsub_vf_f32m1_m(mask, x, x, 0, 4);
+    a0 = vfredosum_vs_f32m1_f32m1(a0, val, a0, 4);
+    return vfmv_f_s_f32m1_f32(a0);
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_REDUCE_SAD(_Tpvec, _Tpvec2) \
+inline unsigned v_reduce_sad(const _Tpvec& a, const _Tpvec&b){    \
+    _Tpvec2 x = v_absdiff(a, b);    \
+    return v_reduce_sum(x);    \
+}
+
+OPENCV_HAL_IMPL_RISCVV_REDUCE_SAD(v_int8x16, v_uint8x16)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_SAD(v_uint8x16, v_uint8x16)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_SAD(v_int16x8, v_uint16x8)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_SAD(v_uint16x8, v_uint16x8)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_SAD(v_int32x4, v_uint32x4)
+OPENCV_HAL_IMPL_RISCVV_REDUCE_SAD(v_uint32x4, v_uint32x4)
+
+#define OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(_Tpvec, _Tp, _T, num, uv) \
+inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    vbool##_T##_t mask = vmseq_vv_##_Tp##_b##_T(a.val, b.val, num);    \
+    return _Tpvec(vmerge_vxm_##_Tp(mask, vmv_v_x_##_Tp(0, num), -1, num));    \
+} \
+inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    vbool##_T##_t mask = vmsne_vv_##_Tp##_b##_T(a.val, b.val, num);    \
+    return _Tpvec(vmerge_vxm_##_Tp(mask, vmv_v_x_##_Tp(0, num), -1, num));    \
+} \
+inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    vbool##_T##_t mask = vmslt##uv##_Tp##_b##_T(a.val, b.val, num);    \
+    return _Tpvec(vmerge_vxm_##_Tp(mask, vmv_v_x_##_Tp(0, num), -1, num));    \
+} \
+inline _Tpvec v_gt(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    vbool##_T##_t mask = vmslt##uv##_Tp##_b##_T(b.val, a.val, num);    \
+    return _Tpvec(vmerge_vxm_##_Tp(mask, vmv_v_x_##_Tp(0, num), -1, num));    \
+} \
+inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    vbool##_T##_t mask = vmsle##uv##_Tp##_b##_T(a.val, b.val, num);    \
+    return _Tpvec(vmerge_vxm_##_Tp(mask, vmv_v_x_##_Tp(0, num), -1, num));    \
+} \
+inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    vbool##_T##_t mask = vmsle##uv##_Tp##_b##_T(b.val, a.val, num);    \
+    return _Tpvec(vmerge_vxm_##_Tp(mask, vmv_v_x_##_Tp(0, num), -1, num));    \
+} \
+
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_int8x16, i8m1,  8, 16, _vv_)
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_int16x8, i16m1, 16, 8, _vv_)
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_int32x4, i32m1, 32, 4, _vv_)
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_int64x2, i64m1, 64, 2, _vv_)
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_uint8x16, u8m1, 8, 16, u_vv_)
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_uint16x8, u16m1, 16, 8, u_vv_)
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_uint32x4, u32m1, 32, 4, u_vv_)
+OPENCV_HAL_IMPL_RISCVV_INT_CMP_OP(v_uint64x2, u64m1, 64, 2, u_vv_)
+
+//TODO: ==
+inline v_float32x4 v_eq(const v_float32x4& a, const v_float32x4& b)
+{
+    vbool32_t mask = vmfeq_vv_f32m1_b32(a.val, b.val, 4);
+    vint32m1_t res = vmerge_vxm_i32m1(mask, vmv_v_x_i32m1(0.0, 4), -1, 4);
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(res));
+}
+inline v_float32x4 v_ne(const v_float32x4& a, const v_float32x4& b)
+{
+    vbool32_t mask = vmfne_vv_f32m1_b32(a.val, b.val, 4);
+    vint32m1_t res = vmerge_vxm_i32m1(mask, vmv_v_x_i32m1(0.0, 4), -1, 4);
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(res));
+}
+inline v_float32x4 v_lt(const v_float32x4& a, const v_float32x4& b)
+{
+    vbool32_t mask = vmflt_vv_f32m1_b32(a.val, b.val, 4);
+    vint32m1_t res = vmerge_vxm_i32m1(mask, vmv_v_x_i32m1(0.0, 4), -1, 4);
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(res));
+}
+inline v_float32x4 v_le(const v_float32x4& a, const v_float32x4& b)
+{
+    vbool32_t mask = vmfle_vv_f32m1_b32(a.val, b.val, 4);
+    vint32m1_t res = vmerge_vxm_i32m1(mask, vmv_v_x_i32m1(0.0, 4), -1, 4);
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(res));
+}
+inline v_float32x4 v_gt(const v_float32x4& a, const v_float32x4& b)
+{
+    vbool32_t mask = vmfgt_vv_f32m1_b32(a.val, b.val, 4);
+    vint32m1_t res = vmerge_vxm_i32m1(mask, vmv_v_x_i32m1(0.0, 4), -1, 4);
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(res));
+}
+inline v_float32x4 v_ge(const v_float32x4& a, const v_float32x4& b)
+{
+    vbool32_t mask = vmfge_vv_f32m1_b32(a.val, b.val, 4);
+    vint32m1_t res = vmerge_vxm_i32m1(mask, vmv_v_x_i32m1(0.0, 4), -1, 4);
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(res));
+}/**/
+inline v_float32x4 v_not_nan(const v_float32x4& a)
+{
+    vbool32_t mask = vmfeq_vv_f32m1_b32(a.val, a.val, 4);
+    vint32m1_t res = vmerge_vxm_i32m1(mask, vmv_v_x_i32m1(0.0, 4), -1, 4);
+    return v_float32x4(vreinterpret_v_i32m1_f32m1(res));
+}
+
+//TODO: ==
+inline v_float64x2 v_eq(const v_float64x2& a, const v_float64x2& b)
+{
+    vbool64_t mask = vmfeq_vv_f64m1_b64(a.val, b.val, 2);
+    vint64m1_t res = vmerge_vxm_i64m1(mask, vmv_v_x_i64m1(0.0, 2), -1, 2);
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(res));
+}
+inline v_float64x2 v_ne(const v_float64x2& a, const v_float64x2& b)
+{
+    vbool64_t mask = vmfne_vv_f64m1_b64(a.val, b.val, 2);
+    vint64m1_t res = vmerge_vxm_i64m1(mask, vmv_v_x_i64m1(0.0, 2), -1, 2);
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(res));
+}
+inline v_float64x2 v_lt(const v_float64x2& a, const v_float64x2& b)
+{
+    vbool64_t mask = vmflt_vv_f64m1_b64(a.val, b.val, 2);
+    vint64m1_t res = vmerge_vxm_i64m1(mask, vmv_v_x_i64m1(0.0, 2), -1, 2);
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(res));
+}
+inline v_float64x2 v_le(const v_float64x2& a, const v_float64x2& b)
+{
+    vbool64_t mask = vmfle_vv_f64m1_b64(a.val, b.val, 2);
+    vint64m1_t res = vmerge_vxm_i64m1(mask, vmv_v_x_i64m1(0.0, 2), -1, 2);
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(res));
+}
+inline v_float64x2 v_gt(const v_float64x2& a, const v_float64x2& b)
+{
+    vbool64_t mask = vmfgt_vv_f64m1_b64(a.val, b.val, 2);
+    vint64m1_t res = vmerge_vxm_i64m1(mask, vmv_v_x_i64m1(0.0, 2), -1, 2);
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(res));
+}
+inline v_float64x2 v_ge(const v_float64x2& a, const v_float64x2& b)
+{
+    vbool64_t mask = vmfge_vv_f64m1_b64(a.val, b.val, 2);
+    vint64m1_t res = vmerge_vxm_i64m1(mask, vmv_v_x_i64m1(0.0, 2), -1, 2);
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(res));
+}/**/
+inline v_float64x2 v_not_nan(const v_float64x2& a)
+{
+    vbool64_t mask = vmfeq_vv_f64m1_b64(a.val, a.val, 2);
+    vint64m1_t res = vmerge_vxm_i64m1(mask, vmv_v_x_i64m1(0.0, 2), -1, 2);
+    return v_float64x2(vreinterpret_v_i64m1_f64m1(res));
+}
+#define OPENCV_HAL_IMPL_RISCVV_TRANSPOSE4x4(_Tp, _T) \
+inline void v_transpose4x4(const v_##_Tp##32x4& a0, const v_##_Tp##32x4& a1, \
+                         const v_##_Tp##32x4& a2, const v_##_Tp##32x4& a3, \
+                         v_##_Tp##32x4& b0, v_##_Tp##32x4& b1, \
+                         v_##_Tp##32x4& b2, v_##_Tp##32x4& b3) \
+{ \
+    vuint32m4_t vindex = vundefined_u32m4(); \
+    vuint32m1_t vindex0 = vid_v_u32m1(4); \
+    vindex0 = vsll_vx_u32m1(vindex0, 2, 4); \
+    vindex = vset_v_u32m1_u32m4(vindex, 0, vindex0); \
+    vindex = vset_v_u32m1_u32m4(vindex, 1, vadd_vx_u32m1(vindex0, 1, 4)); \
+    vindex = vset_v_u32m1_u32m4(vindex, 2, vadd_vx_u32m1(vindex0, 2, 4)); \
+    vindex = vset_v_u32m1_u32m4(vindex, 3, vadd_vx_u32m1(vindex0, 3, 4)); \
+    v##_Tp##32m4_t val = vundefined_##_T##m4();    \
+    val = vset_v_##_T##m1_##_T##m4(val, 0, a0.val);    \
+    val = vset_v_##_T##m1_##_T##m4(val, 1, a1.val);    \
+    val = vset_v_##_T##m1_##_T##m4(val, 2, a2.val);    \
+    val = vset_v_##_T##m1_##_T##m4(val, 3, a3.val);   \
+    val = vrgather_vv_##_T##m4(val, vindex, 16);    \
+    b0.val = vget_v_##_T##m4_##_T##m1(val, 0);   \
+    b1.val = vget_v_##_T##m4_##_T##m1(val, 1);   \
+    b2.val = vget_v_##_T##m4_##_T##m1(val, 2);   \
+    b3.val = vget_v_##_T##m4_##_T##m1(val, 3);   \
+}
+OPENCV_HAL_IMPL_RISCVV_TRANSPOSE4x4(uint, u32)
+OPENCV_HAL_IMPL_RISCVV_TRANSPOSE4x4(int, i32)
+OPENCV_HAL_IMPL_RISCVV_TRANSPOSE4x4(float, f32)
+
+
+#define OPENCV_HAL_IMPL_RISCVV_SHIFT_LEFT(_Tpvec, suffix, _T, num) \
+inline _Tpvec v_shl(const _Tpvec& a, int n) \
+{ return _Tpvec((vsll_vx_##_T##m1(a.val, n, num))); } \
+template<int n> inline _Tpvec v_shl(const _Tpvec& a) \
+{ return _Tpvec((vsll_vx_##_T##m1(a.val, n, num))); }
+
+#define OPENCV_HAL_IMPL_RISCVV_SHIFT_RIGHT(_Tpvec, suffix, _T, num, intric) \
+inline _Tpvec v_shr(const _Tpvec& a, int n) \
+{ return _Tpvec((v##intric##_vx_##_T##m1(a.val, n, num))); } \
+template<int n> inline _Tpvec v_shr(const _Tpvec& a) \
+{ return _Tpvec((v##intric##_vx_##_T##m1(a.val, n, num))); }\
+template<int n> inline _Tpvec v_rshr(const _Tpvec& a) \
+{ return _Tpvec((v##intric##_vx_##_T##m1(vadd_vx_##_T##m1(a.val, 1<<(n-1), num), n, num))); }
+
+// trade efficiency for convenience
+#define OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(suffix, _T, num, intrin) \
+OPENCV_HAL_IMPL_RISCVV_SHIFT_LEFT(v_##suffix##x##num, suffix, _T, num) \
+OPENCV_HAL_IMPL_RISCVV_SHIFT_RIGHT(v_##suffix##x##num, suffix, _T, num, intrin)
+
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(uint8, u8, 16, srl)
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(uint16, u16, 8, srl)
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(uint32, u32, 4, srl)
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(uint64, u64, 2, srl)
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(int8, i8, 16, sra)
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(int16, i16, 8, sra)
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(int32, i32, 4, sra)
+OPENCV_HAL_IMPL_RISCVV_SHIFT_OP(int64, i64, 2, sra)
+
+#if 0
+#define VUP4(n) {0, 1, 2, 3}
+#define VUP8(n) {0, 1, 2, 3, 4, 5, 6, 7}
+#define VUP16(n) {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}
+#define VUP2(n) {0, 1}
+#endif
+#define OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(_Tpvec, suffix, _T, num, num2, vmv, len) \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a) \
+{    \
+    suffix##m1_t tmp = vmv##_##_T##m1(0, num);\
+        tmp = vslideup_vx_##_T##m1_m(vmset_m_##len(num), tmp, a.val, n, num);\
+        return _Tpvec(tmp);\
+} \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a) \
+{     \
+        suffix##m1_t res = vundefined_##_T##m1(); \
+        return _Tpvec(vslidedown_vx_##_T##m1(res, a.val, n, num));\
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a) \
+{ return a; } \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    suffix##m2_t tmp = vundefined_##_T##m2();    \
+    suffix##m2_t res = vundefined_##_T##m2();    \
+    tmp = vset_v_##_T##m1_##_T##m2(tmp, 0, a.val);          \
+    tmp = vset_v_##_T##m1_##_T##m2(tmp, 1, b.val);          \
+        res = vslidedown_vx_##_T##m2(res, tmp, n, num2);\
+        return _Tpvec(vget_v_##_T##m2_##_T##m1(res, 0));\
+} \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    suffix##m2_t tmp = vundefined_##_T##m2();    \
+    suffix##m2_t res = vundefined_##_T##m2();    \
+    tmp = vset_v_##_T##m1_##_T##m2(tmp, 0, b.val);    \
+    tmp = vset_v_##_T##m1_##_T##m2(tmp, 1, a.val);    \
+        res = vslideup_vx_##_T##m2(res, tmp, n, num2);\
+        return _Tpvec(vget_v_##_T##m2_##_T##m1(res, 1));\
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    CV_UNUSED(b); return a; \
+}
+
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_uint8x16, vuint8, u8, 16, 32, vmv_v_x, b8)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_int8x16, vint8, i8, 16, 32, vmv_v_x, b8)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_uint16x8, vuint16, u16, 8, 16, vmv_v_x, b16)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_int16x8, vint16, i16, 8, 16, vmv_v_x, b16)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_uint32x4, vuint32, u32, 4, 8, vmv_v_x, b32)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_int32x4, vint32, i32, 4, 8, vmv_v_x, b32)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_uint64x2, vuint64, u64, 2, 4, vmv_v_x, b64)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_int64x2, vint64, i64, 2, 4, vmv_v_x, b64)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_float32x4, vfloat32, f32, 4, 8, vfmv_v_f, b32)
+OPENCV_HAL_IMPL_RISCVV_ROTATE_OP(v_float64x2, vfloat64, f64, 2, 4, vfmv_v_f, b64)
+
+#if 1
+#define vreinterpret_v_i8m1_i8m1
+#define vreinterpret_v_u8m1_u8m1
+#define OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(_Tpvec, _Tp, _Tp2, len, hnum, num, elemsize, ldst_len, ldst_type) \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ \
+  _Tp2##_t res = vundefined_##len(); \
+  _Tp2##_t res1 = vundefined_##len(); \
+  res = vreinterpret_v_##ldst_len##_##len(vle8_v_##ldst_len((ldst_type *)ptr0, 8)); \
+  res1 = vreinterpret_v_##ldst_len##_##len(vle8_v_##ldst_len((ldst_type *)ptr1, 8)); \
+  res = vslideup_vx_##len(res, res1, hnum, num); \
+  return _Tpvec(res); } \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ return _Tpvec(vreinterpret_v_##ldst_len##_##len(vle8_v_##ldst_len((ldst_type *)ptr, 8))); }\
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(vreinterpret_v_##ldst_len##_##len(vle8_v_##ldst_len((ldst_type *)ptr, 16))); } \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec(vle##elemsize##_v_##len(ptr, num)); } \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ vse8_v_##ldst_len((ldst_type *)ptr, vreinterpret_v_##len##_##ldst_len(a.val), 8);}\
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ \
+  _Tp2##_t a0 = vundefined_##len(); \
+  a0 = vslidedown_vx_##len(a0, a.val, hnum, num);    \
+  vse8_v_##ldst_len((ldst_type *)ptr, vreinterpret_v_##len##_##ldst_len(a0), 8);}\
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ vse##elemsize##_v_##len(ptr, a.val, num); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ vse8_v_##ldst_len((ldst_type *)ptr, vreinterpret_v_##len##_##ldst_len(a.val), 16); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ vse8_v_##ldst_len((ldst_type *)ptr, vreinterpret_v_##len##_##ldst_len(a.val), 16); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \
+{ vse8_v_##ldst_len((ldst_type *)ptr, vreinterpret_v_##len##_##ldst_len(a.val), 16); }
+
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint8x16, uchar, vuint8m1, u8m1, 8, 16, 8, u8m1, uchar)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int8x16,  schar, vint8m1, i8m1, 8, 16, 8, i8m1, schar)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint16x8, ushort, vuint16m1, u16m1, 4, 8, 16, u8m1, uchar)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int16x8,  short,  vint16m1, i16m1, 4, 8, 16, i8m1, schar)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint32x4, unsigned, vuint32m1, u32m1, 2, 4, 32, u8m1, uchar)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int32x4,  int,     vint32m1, i32m1, 2, 4, 32, i8m1, schar)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint64x2, unsigned long, vuint64m1, u64m1, 1, 2, 64, u8m1, uchar)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int64x2,  long,     vint64m1, i64m1, 1, 2, 64, i8m1, schar)
+
+#define OPENCV_HAL_IMPL_RISCVV_LOADSTORE_FLOAT_OP(_Tpvec, _Tp, _Tp2, len, hnum, num, elemsize) \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ \
+  _Tp2##_t res = vundefined_##len(); \
+  _Tp2##_t res1 = vundefined_##len(); \
+  res = vreinterpret_v_u##elemsize##m1_##len(vreinterpret_v_u8m1_u##elemsize##m1(vle8_v_u8m1((uchar *)ptr0, 8))); \
+  res1 = vreinterpret_v_u##elemsize##m1_##len(vreinterpret_v_u8m1_u##elemsize##m1(vle8_v_u8m1((uchar *)ptr1, 8))); \
+  res = vslideup_vx_##len(res, res1, hnum, num); \
+  return _Tpvec(res); } \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ return _Tpvec(vreinterpret_v_u##elemsize##m1_##len(vreinterpret_v_u8m1_u##elemsize##m1(vle8_v_u8m1((uchar *)ptr, 8)))); }\
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(vreinterpret_v_u##elemsize##m1_##len(vreinterpret_v_u8m1_u##elemsize##m1(vle8_v_u8m1((uchar *)ptr, 16)))); } \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec(vle##elemsize##_v_##len(ptr, num)); } \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ vse8_v_u8m1((uchar *)ptr, vreinterpret_v_u##elemsize##m1_u8m1(vreinterpret_v_##len##_u##elemsize##m1(a.val)), 8);}\
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ \
+  _Tp2##_t a0 = vundefined_##len(); \
+  a0 = vslidedown_vx_##len(a0, a.val, hnum, num);    \
+  vse8_v_u8m1((uchar *)ptr, vreinterpret_v_u##elemsize##m1_u8m1(vreinterpret_v_##len##_u##elemsize##m1(a0)), 8);}\
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ vse##elemsize##_v_##len(ptr, a.val, num); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ vse8_v_u8m1((uchar *)ptr, vreinterpret_v_u##elemsize##m1_u8m1(vreinterpret_v_##len##_u##elemsize##m1(a.val)), 16); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ vse8_v_u8m1((uchar *)ptr, vreinterpret_v_u##elemsize##m1_u8m1(vreinterpret_v_##len##_u##elemsize##m1(a.val)), 16); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \
+{ vse8_v_u8m1((uchar *)ptr, vreinterpret_v_u##elemsize##m1_u8m1(vreinterpret_v_##len##_u##elemsize##m1(a.val)), 16); }
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_FLOAT_OP(v_float32x4, float, vfloat32m1, f32m1, 2, 4, 32)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_FLOAT_OP(v_float64x2, double, vfloat64m1, f64m1, 1, 2, 64)
+
+#else
+
+#define OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(_Tpvec, _Tp, _Tp2, len, hnum, num, elemsize) \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ \
+  _Tp2##_t res, res1; \
+  res = vle##elemsize##_v_##len(ptr0, hnum); \
+  res1 = vle##elemsize##_v_##len(ptr1, hnum); \
+  res = vslideup_vx_##len(res, res1, hnum, num); \
+  return _Tpvec(res); } \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ return _Tpvec(vle##elemsize##_v_##len(ptr, hnum)); }\
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(vle##elemsize##_v_##len(ptr, num)); } \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec((_Tp2##_t)vle##elemsize##_v_##len((const _Tp *)ptr, num)); } \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ vse##elemsize##_v_##len(ptr, a.val, hnum);}\
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ \
+  _Tp2##_t a0; \
+  a0 = vslidedown_vx_##len(a0, a.val, hnum, num);    \
+  vse##elemsize##_v_##len(ptr, a0, hnum);}\
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ vse##elemsize##_v_##len(ptr, a.val, num); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ vse##elemsize##_v_##len(ptr, a.val, num); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ vse##elemsize##_v_##len(ptr, a.val, num); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \
+{ vse##elemsize##_v_##len(ptr, a.val, num); }
+
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint8x16, uchar, vuint8m1, u8m1, 8, 16, 8)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int8x16,  schar, vint8m1, i8m1, 8, 16, 8)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint16x8, ushort, vuint16m1, u16m1, 4, 8, 16)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int16x8,  short,  vint16m1, i16m1, 4, 8, 16)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint32x4, unsigned, vuint32m1, u32m1, 2, 4, 32)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int32x4,  int,     vint32m1, i32m1, 2, 4, 32)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_uint64x2, unsigned long, vuint64m1, u64m1, 1, 2, 64)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_int64x2,  long,     vint64m1, i64m1, 1, 2, 64)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_float32x4, float, vfloat32m1, f32m1, 2, 4, 32)
+OPENCV_HAL_IMPL_RISCVV_LOADSTORE_OP(v_float64x2, double, vfloat64m1, f64m1, 1, 2, 64)
+
+#endif
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x16 v_lut(const schar* tab, const int* idx)
+{
+#if 0
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[ 0]],
+        tab[idx[ 1]],
+        tab[idx[ 2]],
+        tab[idx[ 3]],
+        tab[idx[ 4]],
+        tab[idx[ 5]],
+        tab[idx[ 6]],
+        tab[idx[ 7]],
+        tab[idx[ 8]],
+        tab[idx[ 9]],
+        tab[idx[10]],
+        tab[idx[11]],
+        tab[idx[12]],
+        tab[idx[13]],
+        tab[idx[14]],
+        tab[idx[15]]
+    };
+    return v_int8x16(vle8_v_i8m1(elems, 16));
+#else
+#if __riscv_v == 7000
+    return v_int8x16(vnclip_wx_i8m1(vnclip_wx_i16m2(vlxb_v_i32m4((const int *)tab, vle32_v_u32m4((unsigned int *)idx, 16), 16), 0, 16), 0, 16));
+#else
+    return v_int8x16(vloxei32_v_i8m1(tab, vle32_v_u32m4((unsigned int *)idx, 16), 16));
+#endif
+#endif
+}
+
+inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx){
+#if 0
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[3]],
+        tab[idx[3] + 1],
+        tab[idx[4]],
+        tab[idx[4] + 1],
+        tab[idx[5]],
+        tab[idx[5] + 1],
+        tab[idx[6]],
+        tab[idx[6] + 1],
+        tab[idx[7]],
+        tab[idx[7] + 1]
+    };
+    return v_int8x16(vle8_v_i8m1(elems, 16));
+#else
+    vuint32m4_t seq, index;
+    vuint32m4_t vidx = vle32_v_u32m4((unsigned int *)idx, 8);
+    seq = vid_v_u32m4(16);
+    index = vsrl_vx_u32m4(seq, 1, 16);
+    vidx = vrgather_vv_u32m4(vidx, index, 16);
+    index = vadd_vv_u32m4(vand_vx_u32m4(seq, 1, 16), vidx, 16);
+#if __riscv_v == 7000
+    return v_int8x16(vnclip_wx_i8m1(vnclip_wx_i16m2(vlxb_v_i32m4((const int *)tab, index, 16), 0, 16), 0, 16));
+#else
+    return v_int8x16(vloxei32_v_i8m1(tab, index, 16));
+#endif
+#endif
+}
+inline v_int8x16 v_lut_quads(const schar* tab, const int* idx)
+{
+#if 0
+    schar CV_DECL_ALIGNED(32) elems[16] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[0] + 2],
+        tab[idx[0] + 3],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[1] + 2],
+        tab[idx[1] + 3],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[2] + 2],
+        tab[idx[2] + 3],
+        tab[idx[3]],
+        tab[idx[3] + 1],
+        tab[idx[3] + 2],
+        tab[idx[3] + 3]
+    };
+    return v_int8x16(vle8_v_i8m1(elems, 16));
+#else
+    vuint32m4_t seq, index;
+    vuint32m4_t vidx = vle32_v_u32m4((unsigned int *)idx, 4);
+    seq = vid_v_u32m4(16);
+    index = vsrl_vx_u32m4(seq, 2, 16);
+    vidx = vrgather_vv_u32m4(vidx, index, 16);
+    seq = vset_v_u32m1_u32m4(seq, 1, vget_v_u32m4_u32m1(seq, 0));
+    seq = vset_v_u32m1_u32m4(seq, 2, vget_v_u32m4_u32m1(seq, 0));
+    seq = vset_v_u32m1_u32m4(seq, 3, vget_v_u32m4_u32m1(seq, 0));
+    index = vadd_vv_u32m4(seq, vidx, 16);
+#if __riscv_v == 7000
+    return v_int8x16(vnclip_wx_i8m1(vnclip_wx_i16m2(vlxb_v_i32m4((const int *)tab, index, 16), 0, 16), 0, 16));
+#else
+    return v_int8x16(vloxei32_v_i8m1(tab, index, 16));
+#endif
+#endif
+}
+
+inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((schar*)tab, idx)); }
+inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((schar*)tab, idx)); }
+inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((schar*)tab, idx)); }
+
+inline v_int16x8 v_lut(const short* tab, const int* idx)
+{
+#if 0
+    short CV_DECL_ALIGNED(32) elems[8] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]],
+        tab[idx[4]],
+        tab[idx[5]],
+        tab[idx[6]],
+        tab[idx[7]]
+    };
+    return v_int16x8(vle16_v_i16m1(elems, 8));
+#else
+#if __riscv_v == 7000
+    return v_int16x8(vnclip_wx_i16m1(vlxh_v_i32m2((const int *)tab, vsll_vx_u32m2(vle32_v_u32m2((unsigned int *)idx, 8), 1, 8), 8), 0, 8));
+#else
+    return v_int16x8(vloxei32_v_i16m1(tab, vsll_vx_u32m2(vle32_v_u32m2((unsigned int *)idx, 8), 1, 8), 8));
+#endif
+#endif
+}
+inline v_int16x8 v_lut_pairs(const short* tab, const int* idx)
+{
+#if 0
+    short CV_DECL_ALIGNED(32) elems[8] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[2]],
+        tab[idx[2] + 1],
+        tab[idx[3]],
+        tab[idx[3] + 1]
+    };
+    return v_int16x8(vle16_v_i16m1(elems, 8));
+#else
+    vuint32m2_t seq, index;
+    vuint32m2_t vidx = vle32_v_u32m2((unsigned int *)idx, 4);
+    seq = vid_v_u32m2(8);
+    index = vsrl_vx_u32m2(seq, 1, 8);
+    vidx = vrgather_vv_u32m2(vidx, index, 8);
+    index = vsll_vx_u32m2(vadd_vv_u32m2(vand_vx_u32m2(seq, 1, 8), vidx, 8), 1, 8);
+#if __riscv_v == 7000
+    return v_int16x8(vnclip_wx_i16m1(vlxh_v_i32m2((const int *)tab, index, 8), 0, 8));
+#else
+    return v_int16x8(vloxei32_v_i16m1(tab, index, 8));
+#endif
+#endif
+}
+inline v_int16x8 v_lut_quads(const short* tab, const int* idx)
+{
+#if 0
+    short CV_DECL_ALIGNED(32) elems[8] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[0] + 2],
+        tab[idx[0] + 3],
+        tab[idx[1]],
+        tab[idx[1] + 1],
+        tab[idx[1] + 2],
+        tab[idx[1] + 3]
+    };
+    return v_int16x8(vle16_v_i16m1(elems, 8));
+#else
+    vuint32m2_t seq, index;
+    vuint32m2_t vidx = vle32_v_u32m2((unsigned int *)idx, 2);
+    seq = vid_v_u32m2(8);
+    index = vsrl_vx_u32m2(seq, 2, 8);
+    vidx = vrgather_vv_u32m2(vidx, index, 8);
+    seq = vset_v_u32m1_u32m2(seq, 1, vget_v_u32m2_u32m1(seq, 0));
+    index = vsll_vx_u32m2(vadd_vv_u32m2(seq, vidx, 8), 1, 8);
+#if __riscv_v == 7000
+    return v_int16x8(vnclip_wx_i16m1(vlxh_v_i32m2((const int *)tab, index, 8), 0, 8));
+#else
+    return v_int16x8(vloxei32_v_i16m1(tab, index, 8));
+#endif
+#endif
+}
+inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((short*)tab, idx)); }
+inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((short*)tab, idx)); }
+inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((short*)tab, idx)); }
+
+inline v_int32x4 v_lut(const int* tab, const int* idx)
+{
+#if 0
+    int CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]]
+    };
+    return v_int32x4(vle32_v_i32m1(elems, 4));
+#else
+    return v_int32x4(vloxei32_v_i32m1(tab, vsll_vx_u32m1(vle32_v_u32m1((unsigned int *)idx, 4), 2, 4), 4));
+#endif
+}
+inline v_int32x4 v_lut_pairs(const int* tab, const int* idx)
+{
+#if 0
+    int CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[0] + 1],
+        tab[idx[1]],
+        tab[idx[1] + 1]
+    };
+    return v_int32x4(vle32_v_i32m1(elems, 4));
+#else
+    vuint32m1_t seq, index;
+    vuint32m1_t vidx = vle32_v_u32m1((unsigned int *)idx, 2);
+    seq = vid_v_u32m1(4);
+    index = vsrl_vx_u32m1(seq, 1, 4);
+    vidx = vrgather_vv_u32m1(vidx, index, 4);
+    index = vsll_vx_u32m1(vadd_vv_u32m1(vand_vx_u32m1(seq, 1, 4), vidx, 4), 2, 4);
+    return v_int32x4(vloxei32_v_i32m1(tab, index, 4));
+#endif
+}
+inline v_int32x4 v_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x4(vle32_v_i32m1(tab+idx[0], 4));
+}
+inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((int*)tab, idx)); }
+inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((int*)tab, idx)); }
+inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((int*)tab, idx)); }
+
+inline v_int64x2 v_lut(const int64_t* tab, const int* idx)
+{
+    //vint64m1_t res = {tab[idx[0]], tab[idx[1]]};
+    return v_int64x2(vloxei64_v_i64m1(tab, vsll_vx_u64m1(vget_v_u64m2_u64m1(vwaddu_vx_u64m2(vle32_v_u32m1((uint32_t*)idx, 2), 0, 2), 0), 3, 2), 2));
+}
+inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(vle64_v_i64m1(tab+idx[0], 2));
+}
+
+inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx)
+{
+    //vuint64m1_t res = {tab[idx[0]], tab[idx[1]]};
+    return v_uint64x2(vloxei64_v_u64m1(tab, vsll_vx_u64m1(vget_v_u64m2_u64m1(vwaddu_vx_u64m2(vle32_v_u32m1((uint32_t*)idx, 2), 0, 2), 0), 3, 2), 2));
+}
+inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx)
+{
+    return v_uint64x2(vle64_v_u64m1(tab+idx[0], 2));
+}
+
+inline v_float32x4 v_lut(const float* tab, const int* idx)
+{
+#if 0
+    float CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[1]],
+        tab[idx[2]],
+        tab[idx[3]]
+    };
+    return v_float32x4(vle32_v_f32m1(elems, 4));
+#else
+    return v_float32x4(vloxei32_v_f32m1(tab, vsll_vx_u32m1(vle32_v_u32m1((unsigned int *)idx, 4), 2, 4), 4));
+#endif
+}
+inline v_float32x4 v_lut_pairs(const float* tab, const int* idx)
+{
+#if 0
+    float CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idx[0]],
+        tab[idx[0]+1],
+        tab[idx[1]],
+        tab[idx[1]+1]
+    };
+    return v_float32x4(vle32_v_f32m1(elems, 4));
+#else
+    vuint32m1_t seq, index;
+    vuint32m1_t vidx = vle32_v_u32m1((unsigned int *)idx, 2);
+    seq = vid_v_u32m1(4);
+    index = vsrl_vx_u32m1(seq, 1, 4);
+    vidx = vrgather_vv_u32m1(vidx, index, 4);
+    index = vsll_vx_u32m1(vadd_vv_u32m1(vand_vx_u32m1(seq, 1, 4), vidx, 4), 2, 4);
+    return v_float32x4(vloxei32_v_f32m1(tab, index, 4));
+#endif
+}
+inline v_float32x4 v_lut_quads(const float* tab, const int* idx)
+{
+    return v_float32x4(vle32_v_f32m1(tab + idx[0], 4));
+}
+inline v_float64x2 v_lut(const double* tab, const int* idx)
+{
+    //vfloat64m1_t res = {tab[idx[0]], tab[idx[1]]};
+    return v_float64x2(vloxei64_v_f64m1(tab, vsll_vx_u64m1(vget_v_u64m2_u64m1(vwaddu_vx_u64m2(vle32_v_u32m1((uint32_t*)idx, 2), 0, 2), 0), 3, 2), 2));
+}
+inline v_float64x2 v_lut_pairs(const double* tab, const int* idx)
+{
+    return v_float64x2(vle64_v_f64m1(tab+idx[0], 2));
+}
+
+inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec)
+{
+    /*int CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idxvec.val[0]],
+        tab[idxvec.val[1]],
+        tab[idxvec.val[2]],
+        tab[idxvec.val[3]]
+    };*/
+    return v_int32x4(vloxei32_v_i32m1(tab, vsll_vx_u32m1(vreinterpret_v_i32m1_u32m1(idxvec.val), 2, 4), 4));
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec)
+{
+    /*unsigned CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idxvec.val[0]],
+        tab[idxvec.val[1]],
+        tab[idxvec.val[2]],
+        tab[idxvec.val[3]]
+    };*/
+    return v_uint32x4(vloxei32_v_u32m1(tab, vsll_vx_u32m1(vreinterpret_v_i32m1_u32m1(idxvec.val), 2, 4), 4));
+}
+
+inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec)
+{
+    /*float CV_DECL_ALIGNED(32) elems[4] =
+    {
+        tab[idxvec.val[0]],
+        tab[idxvec.val[1]],
+        tab[idxvec.val[2]],
+        tab[idxvec.val[3]]
+    };*/
+    return v_float32x4(vloxei32_v_f32m1(tab, vsll_vx_u32m1(vreinterpret_v_i32m1_u32m1(idxvec.val), 2, 4), 4));
+}
+inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec)
+{
+    //vfloat64m1_t res = {tab[idxvec.val[0]], tab[idxvec.val[1]]};
+    return v_float64x2(vloxei64_v_f64m1(tab, vsll_vx_u64m1(vreinterpret_v_i64m1_u64m1(vget_v_i64m2_i64m1(vwadd_vx_i64m2(idxvec.val, 0, 2), 0)), 3, 2), 2));
+}
+inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y)
+{
+    vint32m1_t index = vmul_vx_i32m1(idxvec.val, 4, 4);
+    //vint32m1_t index_y = vadd_vx_i32m1(index_x, 4, 4);
+
+    //x.val = vlxe_v_f32m1(tab, index_x, 4);
+    //y.val = vlxe_v_f32m1(tab, index_y, 4);
+    vloxseg2ei32_v_f32m1(&x.val, &y.val, tab, vreinterpret_v_i32m1_u32m1(index), 4);
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+
+    x = v_float64x2(tab[idx[0]], tab[idx[1]]);
+    y = v_float64x2(tab[idx[0]+1], tab[idx[1]+1]);
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_PACKS(_Tp, _Tp2, _T2, num2, _T1, num, intrin, shr, _Type, elemsize) \
+inline v_##_Tp##x##num v_pack(const v_##_Tp2##x##num2& a, const v_##_Tp2##x##num2& b) \
+{ \
+    v##_Tp2##m2_t  tmp = vundefined_##_T2##m2();    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 0, a.val);    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 1, b.val);    \
+    return v_##_Tp##x##num(shr##_##_T1##m1(tmp, 0, num)); \
+}\
+template<int n> inline \
+v_##_Tp##x##num v_rshr_pack(const v_##_Tp2##x##num2& a, const v_##_Tp2##x##num2& b) \
+{ \
+    v##_Tp2##m2_t  tmp = vundefined_##_T2##m2();    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 0, a.val);    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 1, b.val);    \
+    return v_##_Tp##x##num(intrin##_##_T1##m1(tmp, n, num)); \
+}\
+inline void v_pack_store(_Type* ptr, const v_##_Tp2##x##num2& a) \
+{ \
+    v##_Tp2##m2_t tmp = vundefined_##_T2##m2();    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 0, a.val);    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 1, vmv_v_x_##_T2##m1(0, num2));    \
+    asm("" ::: "memory");                                       \
+    vse##elemsize##_v_##_T1##m1(ptr, shr##_##_T1##m1(tmp, 0, num), num2); \
+}\
+template<int n> inline \
+void v_rshr_pack_store(_Type* ptr, const v_##_Tp2##x##num2& a) \
+{ \
+    v##_Tp2##m2_t tmp = vundefined_##_T2##m2();    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 0, a.val);    \
+    tmp = vset_v_##_T2##m1_##_T2##m2(tmp, 1, vmv_v_x_##_T2##m1(0, num2));    \
+    vse##elemsize##_v_##_T1##m1(ptr, intrin##_##_T1##m1(tmp, n, num), num2); \
+}
+OPENCV_HAL_IMPL_RISCVV_PACKS(int8, int16, i16, 8, i8, 16, vnclip_wx, vnclip_wx, signed char, 8)
+OPENCV_HAL_IMPL_RISCVV_PACKS(int16, int32, i32, 4, i16, 8, vnclip_wx, vnclip_wx, signed short, 16)
+OPENCV_HAL_IMPL_RISCVV_PACKS(int32, int64, i64, 2, i32, 4, vnclip_wx, vnsra_wx, int, 32)
+OPENCV_HAL_IMPL_RISCVV_PACKS(uint8, uint16, u16, 8, u8, 16, vnclipu_wx, vnclipu_wx, unsigned char, 8)
+OPENCV_HAL_IMPL_RISCVV_PACKS(uint16, uint32, u32, 4, u16, 8, vnclipu_wx, vnclipu_wx, unsigned short, 16)
+OPENCV_HAL_IMPL_RISCVV_PACKS(uint32, uint64, u64, 2, u32, 4, vnclipu_wx, vnsrl_wx, unsigned int, 32)
+
+// pack boolean
+inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b)
+{
+    vuint16m2_t tmp = vundefined_u16m2();    \
+    tmp = vset_v_u16m1_u16m2(tmp, 0, a.val);    \
+    tmp = vset_v_u16m1_u16m2(tmp, 1, b.val);    \
+    return v_uint8x16(vnsrl_wx_u8m1(tmp, 0, 16));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b,
+                           const v_uint32x4& c, const v_uint32x4& d)
+{
+    vuint32m4_t vabcd = vundefined_u32m4();    \
+    vuint16m2_t v16 = vundefined_u16m2();    \
+    vabcd = vset_v_u32m1_u32m4(vabcd, 0, a.val);    \
+    vabcd = vset_v_u32m1_u32m4(vabcd, 1, b.val);    \
+    vabcd = vset_v_u32m1_u32m4(vabcd, 2, c.val);    \
+    vabcd = vset_v_u32m1_u32m4(vabcd, 3, d.val);    \
+    v16 = vnsrl_wx_u16m2(vabcd, 0, 16);
+    return v_uint8x16(vnsrl_wx_u8m1(v16, 0, 16));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                           const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f,
+                           const v_uint64x2& g, const v_uint64x2& h)
+{
+    vuint64m8_t v64 = vundefined_u64m8();    \
+    vuint32m4_t v32 = vundefined_u32m4();    \
+    vuint16m2_t v16 = vundefined_u16m2();    \
+    v64 = vset_v_u64m1_u64m8(v64, 0, a.val);    \
+    v64 = vset_v_u64m1_u64m8(v64, 1, b.val);    \
+    v64 = vset_v_u64m1_u64m8(v64, 2, c.val);    \
+    v64 = vset_v_u64m1_u64m8(v64, 3, d.val);    \
+    v64 = vset_v_u64m1_u64m8(v64, 4, e.val);    \
+    v64 = vset_v_u64m1_u64m8(v64, 5, f.val);    \
+    v64 = vset_v_u64m1_u64m8(v64, 6, g.val);    \
+    v64 = vset_v_u64m1_u64m8(v64, 7, h.val);    \
+    v32 = vnsrl_wx_u32m4(v64, 0, 16);
+    v16 = vnsrl_wx_u16m2(v32, 0, 16);
+    return v_uint8x16(vnsrl_wx_u8m1(v16, 0, 16));
+}
+
+//inline v_uint8x16 v_pack_u(const v_int16x8& a, const v_int16x8& b) \
+//{ \
+//    int16xm2_u tmp;    \
+//    tmp.m1[0] = (vint16m1_t)a.val;    \
+//    tmp.m1[1] = (vint16m1_t)b.val;    \
+//    e8xm1_t mask = (e8xm1_t)vmsge_vx_e16xm2_i16m2(tmp.v, 0, 16);\
+//    return v_uint8x16(vnclipuvi_mask_u8m1_u16m2(vmv_v_x_u8m1(0, 16), (vuint16m2_t)tmp.v, 0, mask, 16));
+//}
+
+#define OPENCV_HAL_IMPL_RISCVV_PACK_U(tp1, num1, tp2, num2, _Tp) \
+inline v_uint##tp1##x##num1 v_pack_u(const v_int##tp2##x##num2& a, const v_int##tp2##x##num2& b) \
+{ \
+    vint##tp2##m2_t tmp = vundefined_##i##tp2##m2();    \
+    tmp = vset_v_##i##tp2##m1_##i##tp2##m2(tmp, 0, a.val);    \
+    tmp = vset_v_##i##tp2##m1_##i##tp2##m2(tmp, 1, b.val);    \
+    vint##tp2##m2_t val = vmax_vx_i##tp2##m2(tmp, 0, num1);\
+    return v_uint##tp1##x##num1(vnclipu_wx_u##tp1##m1(vreinterpret_v_i##tp2##m2_u##tp2##m2(val), 0, num1));    \
+} \
+inline void v_pack_u_store(_Tp* ptr, const v_int##tp2##x##num2& a) \
+{ \
+    vint##tp2##m2_t tmp = vundefined_##i##tp2##m2();    \
+    tmp = vset_v_##i##tp2##m1_##i##tp2##m2(tmp, 0, a.val);    \
+    vint##tp2##m2_t val = vmax_vx_i##tp2##m2(tmp, 0, num1);\
+    return vse##tp1##_v_u##tp1##m1(ptr, vnclipu_wx_u##tp1##m1(vreinterpret_v_i##tp2##m2_u##tp2##m2(val), 0, num1), num2);    \
+} \
+template<int n> inline \
+v_uint##tp1##x##num1 v_rshr_pack_u(const v_int##tp2##x##num2& a, const v_int##tp2##x##num2& b) \
+{ \
+    vint##tp2##m2_t tmp = vundefined_##i##tp2##m2();    \
+    tmp = vset_v_##i##tp2##m1_##i##tp2##m2(tmp, 0, a.val);    \
+    tmp = vset_v_##i##tp2##m1_##i##tp2##m2(tmp, 1, b.val);    \
+    vint##tp2##m2_t val = vmax_vx_i##tp2##m2(tmp, 0, num1);\
+    return v_uint##tp1##x##num1(vnclipu_wx_u##tp1##m1(vreinterpret_v_i##tp2##m2_u##tp2##m2(val), n, num1));    \
+} \
+template<int n> inline \
+void v_rshr_pack_u_store(_Tp* ptr, const v_int##tp2##x##num2& a) \
+{ \
+    vint##tp2##m2_t tmp = vundefined_##i##tp2##m2();    \
+    tmp = vset_v_##i##tp2##m1_##i##tp2##m2(tmp, 0, a.val);    \
+    vint##tp2##m2_t val_ = vmax_vx_i##tp2##m2(tmp, 0, num1);\
+    vuint##tp1##m1_t val = vnclipu_wx_u##tp1##m1(vreinterpret_v_i##tp2##m2_u##tp2##m2(val_), n, num1);    \
+    return vse##tp1##_v_u##tp1##m1(ptr, val, num2);\
+}
+OPENCV_HAL_IMPL_RISCVV_PACK_U(8, 16, 16, 8, unsigned char )
+OPENCV_HAL_IMPL_RISCVV_PACK_U(16, 8, 32, 4, unsigned short)
+
+
+// saturating multiply 8-bit, 16-bit
+#define OPENCV_HAL_IMPL_RISCVV_MUL_SAT(_Tpvec, num, mul, cvt)   \
+    inline _Tpvec v_mul(const _Tpvec& a, const _Tpvec& b)       \
+    {                                                           \
+        auto res = mul(a.val, b.val, num);                      \
+        return _Tpvec(cvt(res, 0, num));                        \
+    }
+
+OPENCV_HAL_IMPL_RISCVV_MUL_SAT(v_int8x16,  16, vwmul_vv_i16m2, vnclip_wx_i8m1)
+OPENCV_HAL_IMPL_RISCVV_MUL_SAT(v_uint8x16, 16, vwmulu_vv_u16m2, vnclipu_wx_u8m1)
+OPENCV_HAL_IMPL_RISCVV_MUL_SAT(v_int16x8,  32, vwmul_vv_i32m2, vnclip_wx_i16m1)
+OPENCV_HAL_IMPL_RISCVV_MUL_SAT(v_uint16x8, 32, vwmulu_vv_u32m2, vnclipu_wx_u16m1)
+
+
+static const signed char popCountTable[256] =
+{
+    0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8,
+};
+
+inline vuint8m1_t vcnt_u8(vuint8m1_t val){
+#if __riscv_v == 7000
+    vuint8m1_t v0 = vand_vx_u8m1(val, 1, 16);
+    return vadd_vv_u8m1(vloxei8_v_u8m1((unsigned char*)popCountTable, vsrl_vx_u8m1(val, 1, 16), 16), v0, 16);
+#else
+    return vloxei8_v_u8m1((unsigned char*)popCountTable, val, 16);
+#endif
+}
+
+inline v_uint8x16
+v_popcount(const v_uint8x16& a)
+{
+    return v_uint8x16(vcnt_u8(a.val));
+}
+
+inline v_uint8x16
+v_popcount(const v_int8x16& a)
+{
+    return v_uint8x16(vcnt_u8(vreinterpret_v_i8m1_u8m1(a.val)));
+}
+
+inline v_uint16x8
+v_popcount(const v_uint16x8& a)
+{
+    vuint8m1_t tmp = vcnt_u8(vreinterpret_v_u16m1_u8m1(a.val));
+    vuint8m1_t seq = vid_v_u8m1(8);
+    vuint8m1_t index = vsll_vx_u8m1(seq, 1, 8);
+    return v_uint16x8(vget_v_u16m2_u16m1(vwaddu_vv_u16m2(vrgather_vv_u8m1(tmp, index, 8), vrgather_vv_u8m1(tmp, vadd_vx_u8m1(index, 1, 8), 8), 8), 0));
+}
+
+inline v_uint16x8
+v_popcount(const v_int16x8& a)
+{
+    vuint8m1_t tmp = vcnt_u8(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i16m1_i8m1(a.val)));
+    vuint8m1_t seq = vid_v_u8m1(8);
+    vuint8m1_t index = vsll_vx_u8m1(seq, 1, 8);
+    return v_uint16x8(vget_v_u16m2_u16m1(vwaddu_vv_u16m2(vrgather_vv_u8m1(tmp, index, 8), vrgather_vv_u8m1(tmp, vadd_vx_u8m1(index, 1, 8), 8), 8), 0));
+}
+
+inline v_uint32x4
+v_popcount(const v_uint32x4& a)
+{
+    vuint8m1_t tmp = vcnt_u8(vreinterpret_v_u32m1_u8m1(a.val));
+    vuint8m1_t seq = vid_v_u8m1(8);
+    vuint8m1_t index = vsll_vx_u8m1(seq, 1, 8);
+    vuint8m1_t sum = vadd_vv_u8m1(vrgather_vv_u8m1(tmp, index, 8), vrgather_vv_u8m1(tmp, vadd_vx_u8m1(index, 1, 8), 8), 8);
+    return v_uint32x4(vget_v_u32m4_u32m1(vwaddu_vx_u32m4(vwaddu_vv_u16m2(vrgather_vv_u8m1(sum, index, 4), vrgather_vv_u8m1(sum, vadd_vx_u8m1(index, 1, 4), 4), 4), 0, 4), 0));
+}
+
+inline v_uint32x4
+v_popcount(const v_int32x4& a)
+{
+    vuint8m1_t tmp = vcnt_u8(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i32m1_i8m1(a.val)));
+    vuint8m1_t seq = vid_v_u8m1(8);
+    vuint8m1_t index = vsll_vx_u8m1(seq, 1, 8);
+    vuint8m1_t sum = vadd_vv_u8m1(vrgather_vv_u8m1(tmp, index, 8), vrgather_vv_u8m1(tmp, vadd_vx_u8m1(index, 1, 8), 8), 8);
+    return v_uint32x4(vget_v_u32m4_u32m1(vwaddu_vx_u32m4(vwaddu_vv_u16m2(vrgather_vv_u8m1(sum, index, 4), vrgather_vv_u8m1(sum, vadd_vx_u8m1(index, 1, 4), 4), 4), 0, 4), 0));
+}
+
+inline v_uint64x2
+v_popcount(const v_uint64x2& a)
+{
+    vuint8m1_t tmp = vcnt_u8(vreinterpret_v_u64m1_u8m1(a.val));
+    vuint16m2_t tmp16 = vwaddu_vx_u16m2(tmp, 0, 16);
+    vuint16m1_t res1 = vundefined_u16m1();
+    vuint16m1_t res2 = vundefined_u16m1();
+    res1 = vredsum_vs_u16m1_u16m1(res1, vget_v_u16m2_u16m1(tmp16, 0), vmv_v_x_u16m1(0, 8), 8);
+    res2 = vredsum_vs_u16m1_u16m1(res2, vget_v_u16m2_u16m1(tmp16, 1), vmv_v_x_u16m1(0, 8), 8);
+    return v_uint64x2((unsigned long)vmv_x_s_u16m1_u16(res1), (unsigned long)vmv_x_s_u16m1_u16(res2));
+}
+
+inline v_uint64x2
+v_popcount(const v_int64x2& a)
+{
+    vuint8m1_t tmp = vcnt_u8(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i64m1_i8m1(a.val)));
+    vuint16m2_t tmp16 = vwaddu_vx_u16m2(tmp, 0, 16);
+    vuint16m1_t res1 = vundefined_u16m1(), res2 = vundefined_u16m1();
+    res1 = vredsum_vs_u16m1_u16m1(res1, vget_v_u16m2_u16m1(tmp16, 0), vmv_v_x_u16m1(0, 8), 8);
+    res2 = vredsum_vs_u16m1_u16m1(res2, vget_v_u16m2_u16m1(tmp16, 1), vmv_v_x_u16m1(0, 8), 8);
+    return v_uint64x2((unsigned long)vmv_x_s_u16m1_u16(res1), (unsigned long)vmv_x_s_u16m1_u16(res2));
+}
+
+#define SMASK 1, 2, 4, 8, 16, 32, 64, 128
+inline int v_signmask(const v_uint8x16& a)
+{
+    vuint16m1_t res = vundefined_u16m1();
+    vuint8m1_t id = vid_v_u8m1(16);
+    vuint16m2_t num = vsll_vv_u16m2(vmv_v_x_u16m2(1, 16), vwaddu_vx_u16m2(id, 0, 16), 16);
+    vuint8m1_t t0  = vsrl_vx_u8m1(a.val, 7, 16);
+    vbool8_t mask = vmseq_vx_u8m1_b8(t0, 1, 16);
+    res = vredsum_vs_u16m2_u16m1_m(mask, res, num, vmv_v_x_u16m1(0, 8), 16);
+    return vmv_x_s_u16m1_u16(res);
+}
+inline int v_signmask(const v_int8x16& a)
+{
+    vuint16m1_t res = vundefined_u16m1();
+    vuint8m1_t id = vid_v_u8m1(16);
+    vuint16m2_t num = vsll_vv_u16m2(vmv_v_x_u16m2(1, 16), vwaddu_vx_u16m2(id, 0, 16), 16);
+    vbool8_t mask = vmslt_vx_i8m1_b8(a.val, 0, 16);
+    res = vredsum_vs_u16m2_u16m1_m(mask, res, num, vmv_v_x_u16m1(0, 8), 16);
+    return vmv_x_s_u16m1_u16(res);
+}
+
+inline int v_signmask(const v_int16x8& a)
+{
+    vuint16m1_t res = vundefined_u16m1();
+    vuint16m1_t id = vid_v_u16m1(8);
+    vuint16m1_t num = vsll_vv_u16m1(vmv_v_x_u16m1(1, 8), id, 8);
+    vbool16_t mask = vmslt_vx_i16m1_b16(a.val, 0, 8);
+    res = vredsum_vs_u16m1_u16m1_m(mask, res, num, vmv_v_x_u16m1(0, 8), 16);
+    return vmv_x_s_u16m1_u16(res);
+}
+inline int v_signmask(const v_uint16x8& a)
+{
+    vuint16m1_t res = vundefined_u16m1();
+    vuint16m1_t id = vid_v_u16m1(8);
+    vuint16m1_t num = vsll_vv_u16m1(vmv_v_x_u16m1(1, 8), id, 8);
+    vuint16m1_t t0  = vsrl_vx_u16m1(a.val, 15, 8);
+    vbool16_t mask = vmseq_vx_u16m1_b16(t0, 1, 8);
+    res = vredsum_vs_u16m1_u16m1_m(mask, res, num, vmv_v_x_u16m1(0, 8), 8);
+    return vmv_x_s_u16m1_u16(res);
+}
+inline int v_signmask(const v_int32x4& a)
+{
+    vuint32m1_t res = vundefined_u32m1();
+    vuint32m1_t id = vid_v_u32m1(4);
+    vuint32m1_t num = vsll_vv_u32m1(vmv_v_x_u32m1(1, 4), id, 4);
+    vbool32_t mask = vmslt_vx_i32m1_b32(a.val, 0, 4);
+    res = vredsum_vs_u32m1_u32m1_m(mask, res, num, vmv_v_x_u32m1(0, 4), 4);
+    return vmv_x_s_u32m1_u32(res);
+}
+inline int v_signmask(const v_uint32x4& a)
+{
+    vuint32m1_t res = vundefined_u32m1();
+    vuint32m1_t id = vid_v_u32m1(4);
+    vuint32m1_t num = vsll_vv_u32m1(vmv_v_x_u32m1(1, 4), id, 4);
+    vuint32m1_t t0  = vsrl_vx_u32m1(a.val, 31, 4);
+    vbool32_t mask = vmseq_vx_u32m1_b32(t0, 1, 4);
+    res = vredsum_vs_u32m1_u32m1_m(mask, res, num, vmv_v_x_u32m1(0, 4), 4);
+    return vmv_x_s_u32m1_u32(res);
+}
+inline int v_signmask(const v_uint64x2& a)
+{
+    vuint64m1_t res = vundefined_u64m1();
+    vuint64m1_t id = vid_v_u64m1(2);
+    vuint64m1_t num = vsll_vv_u64m1(vmv_v_x_u64m1(1, 2), id, 2);
+    vuint64m1_t t0  = vsrl_vx_u64m1(a.val, 63, 2);
+    vbool64_t mask = vmseq_vx_u64m1_b64(t0, 1, 2);
+    res = vredsum_vs_u64m1_u64m1_m(mask, res, num, vmv_v_x_u64m1(0, 2), 2);
+    return vmv_x_s_u64m1_u64(res);
+}
+inline int v_signmask(const v_int64x2& a)
+{ return v_signmask(v_reinterpret_as_u64(a)); }
+inline int v_signmask(const v_float64x2& a)
+{ return v_signmask(v_reinterpret_as_u64(a)); }
+inline int v_signmask(const v_float32x4& a)
+{
+    return v_signmask(v_reinterpret_as_u32(a));
+    /*
+    vuint32m1_t res;
+    vuint32m1_t id = vid_v_u32m1(4);
+    vuint32m1_t num = vsll_vv_u32m1(vmv_v_x_u32m1(1, 4), id, 4);
+    vbool32_t mask = vmflt_vf_f32m1_b32(a.val, 0, 4);
+    res = vredsum_vs_u32m1_u32m1_m(mask, res, num, vmv_v_x_u32m1(0, 4), 4);
+    return vmv_x_s_u32m1_u32(res);*/
+}
+
+inline int v_scan_forward(const v_int8x16& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_uint8x16& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_int16x8& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_uint16x8& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_int32x4& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_uint32x4& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_float32x4& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_int64x2& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+inline int v_scan_forward(const v_uint64x2& a) {
+int val = v_signmask(a);
+if(val==0) return 0;
+else return trailingZeros32(val); }
+
+#define OPENCV_HAL_IMPL_RISCVV_CHECK_ALLANY(_Tpvec, suffix, _T, shift, num, mask_b) \
+inline bool v_check_all(const v_##_Tpvec& a) \
+{ \
+    suffix##m1_t v0 = vsrl_vx_##_T(vnot_v_##_T(a.val, num), shift, num); \
+    return (vcpop_m_##mask_b(vmseq_vx_##_T##_##mask_b(v0, 1, num), num)) == 0; \
+} \
+inline bool v_check_any(const v_##_Tpvec& a) \
+{ \
+    suffix##m1_t v0 = vsrl_vx_##_T(a.val, shift, num); \
+    return (vcpop_m_##mask_b(vmseq_vx_##_T##_##mask_b(v0, 1, num), num)) != 0; \
+}
+
+OPENCV_HAL_IMPL_RISCVV_CHECK_ALLANY(uint8x16, vuint8,  u8m1, 7, 16, b8)
+OPENCV_HAL_IMPL_RISCVV_CHECK_ALLANY(uint16x8, vuint16, u16m1, 15, 8, b16)
+OPENCV_HAL_IMPL_RISCVV_CHECK_ALLANY(uint32x4, vuint32, u32m1, 31, 4, b32)
+OPENCV_HAL_IMPL_RISCVV_CHECK_ALLANY(uint64x2, vuint64, u64m1, 63, 2, b64)
+
+inline bool v_check_all(const v_int8x16& a)
+{ return v_check_all(v_reinterpret_as_u8(a)); }
+inline bool v_check_all(const v_int16x8& a)
+{ return v_check_all(v_reinterpret_as_u16(a)); }
+inline bool v_check_all(const v_int32x4& a)
+{ return v_check_all(v_reinterpret_as_u32(a)); }
+inline bool v_check_all(const v_float32x4& a)
+{ return v_check_all(v_reinterpret_as_u32(a)); }
+inline bool v_check_all(const v_int64x2& a)
+{ return v_check_all(v_reinterpret_as_u64(a)); }
+inline bool v_check_all(const v_float64x2& a)
+{ return v_check_all(v_reinterpret_as_u64(a)); }
+
+inline bool v_check_any(const v_int8x16& a)
+{ return v_check_any(v_reinterpret_as_u8(a)); }
+inline bool v_check_any(const v_int16x8& a)
+{ return v_check_any(v_reinterpret_as_u16(a)); }
+inline bool v_check_any(const v_int32x4& a)
+{ return v_check_any(v_reinterpret_as_u32(a)); }
+inline bool v_check_any(const v_float32x4& a)
+{ return v_check_any(v_reinterpret_as_u32(a)); }
+inline bool v_check_any(const v_int64x2& a)
+{ return v_check_any(v_reinterpret_as_u64(a)); }
+inline bool v_check_any(const v_float64x2& a)
+{ return v_check_any(v_reinterpret_as_u64(a)); }
+
+#define OPENCV_HAL_IMPL_RISCVV_SELECT(_Tpvec, suffix, _Tpvec2, num, mask_func) \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(vmerge_vvm_##suffix(mask_func(mask.val, 0, num), b.val, a.val, num)); \
+}
+
+OPENCV_HAL_IMPL_RISCVV_SELECT(v_int8x16,  i8m1, vbool8_t, 16, vmsne_vx_i8m1_b8)
+OPENCV_HAL_IMPL_RISCVV_SELECT(v_int16x8,  i16m1, vbool16_t, 8, vmsne_vx_i16m1_b16)
+OPENCV_HAL_IMPL_RISCVV_SELECT(v_int32x4,  i32m1, vbool32_t, 4, vmsne_vx_i32m1_b32)
+OPENCV_HAL_IMPL_RISCVV_SELECT(v_uint8x16, u8m1, vbool8_t, 16, vmsne_vx_u8m1_b8)
+OPENCV_HAL_IMPL_RISCVV_SELECT(v_uint16x8, u16m1, vbool16_t, 8, vmsne_vx_u16m1_b16)
+OPENCV_HAL_IMPL_RISCVV_SELECT(v_uint32x4, u32m1, vbool32_t, 4, vmsne_vx_u32m1_b32)
+inline v_float32x4 v_select(const v_float32x4& mask, const v_float32x4& a, const v_float32x4& b)
+{
+    return v_float32x4(vmerge_vvm_f32m1(vmfne_vf_f32m1_b32(mask.val, 0, 4), b.val, a.val, 4));
+}
+inline v_float64x2 v_select(const v_float64x2& mask, const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float64x2(vmerge_vvm_f64m1(vmfne_vf_f64m1_b64(mask.val, 0, 2), b.val, a.val, 2));
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_EXPAND(add, _Tpvec, _Tpwvec, _Tp, _Tp1, num1, _Tp2, num2, _T1, _T2, num3) \
+inline void v_expand(const _Tpvec& a, v_##_Tpwvec& b0, v_##_Tpwvec& b1) \
+{ \
+    _T1##_t b = vw##add##_vx_##_Tp2##m2(a.val, 0, num1);    \
+    b0.val = vget_v_##_Tp2##m2_##_Tp2##m1(b, 0);  \
+    b1.val = vget_v_##_Tp2##m2_##_Tp2##m1(b, 1);  \
+} \
+inline v_##_Tpwvec v_expand_low(const _Tpvec& a) \
+{ \
+    _T1##_t b = vw##add##_vx_##_Tp2##m2(a.val, 0, num2);    \
+    return v_##_Tpwvec(vget_v_##_Tp2##m2_##_Tp2##m1(b, 0)); \
+} \
+inline v_##_Tpwvec v_expand_high(const _Tpvec& a) \
+{ \
+    _T1##_t b = vw##add##_vx_##_Tp2##m2(a.val, 0, num1);    \
+    return v_##_Tpwvec(vget_v_##_Tp2##m2_##_Tp2##m1(b, 1)); \
+} \
+inline v_##_Tpwvec v_load_expand(const _Tp* ptr) \
+{ \
+    _T2##_t val = vle##num3##_v_##_Tp1(ptr, num2);    \
+    _T1##_t b = vw##add##_vx_##_Tp2##m2(val, 0, num2);    \
+    return v_##_Tpwvec(vget_v_##_Tp2##m2_##_Tp2##m1(b, 0)); \
+}
+
+OPENCV_HAL_IMPL_RISCVV_EXPAND(addu, v_uint8x16, uint16x8, uchar, u8m1, 16, u16, 8, vuint16m2, vuint8m1, 8)
+OPENCV_HAL_IMPL_RISCVV_EXPAND(addu, v_uint16x8, uint32x4, ushort,  u16m1, 8, u32, 4, vuint32m2, vuint16m1, 16)
+OPENCV_HAL_IMPL_RISCVV_EXPAND(addu, v_uint32x4, uint64x2, uint,  u32m1, 4, u64, 2, vuint64m2, vuint32m1, 32)
+OPENCV_HAL_IMPL_RISCVV_EXPAND(add, v_int8x16, int16x8, schar,  i8m1, 16, i16, 8, vint16m2, vint8m1, 8)
+OPENCV_HAL_IMPL_RISCVV_EXPAND(add, v_int16x8, int32x4, short,  i16m1, 8, i32, 4, vint32m2, vint16m1, 16)
+OPENCV_HAL_IMPL_RISCVV_EXPAND(add, v_int32x4, int64x2, int,  i32m1, 4, i64, 2, vint64m2, vint32m1, 32)
+
+inline v_uint32x4 v_load_expand_q(const uchar* ptr)
+{
+    vuint16m2_t b = vundefined_u16m2();
+    vuint32m2_t c = vundefined_u32m2();
+    vuint8m1_t val = vle8_v_u8m1(ptr, 4);    \
+    b = vwaddu_vv_u16m2(val, vmv_v_x_u8m1(0, 4), 4);    \
+    c = vwaddu_vv_u32m2(vget_v_u16m2_u16m1(b, 0), vmv_v_x_u16m1(0, 4), 4);    \
+    return v_uint32x4(vget_v_u32m2_u32m1(c, 0));
+}
+
+inline v_int32x4 v_load_expand_q(const schar* ptr)
+{
+    vint16m2_t b = vundefined_i16m2();
+    vint32m2_t c = vundefined_i32m2();
+    vint8m1_t val = vle8_v_i8m1(ptr, 4);    \
+    b = vwadd_vv_i16m2(val, vmv_v_x_i8m1(0, 4), 4);    \
+    c = vwadd_vv_i32m2(vget_v_i16m2_i16m1(b, 0), vmv_v_x_i16m1(0, 4), 4);    \
+    return v_int32x4(vget_v_i32m2_i32m1(c, 0));
+}
+#define VITL_16 {0x11011000, 0x13031202, 0x15051404, 0x17071606, 0x19091808, 0x1B0B1A0A, 0x1D0D1C0C, 0x1F0F1E0E}
+#define VITL_8 {0x00080000, 0x00090001, 0x000A0002, 0x000B0003, 0x000C0004, 0x000D0005, 0x000E0006, 0x000F0007}
+#define VITL_4 {0x00000000, 0x00000004, 0x00000001, 0x00000005, 0x00000002, 0x00000006, 0x00000003, 0x00000007}
+#define VITL_2 {0, 0, 2, 0, 1, 0, 3, 0}
+
+#define OPENCV_HAL_IMPL_RISCVV_UNPACKS(_Tpvec, _Tp, _T, _UTp, _UT, num, num2, len, numh, refunc) \
+inline void v_zip(const v_##_Tpvec& a0, const v_##_Tpvec& a1, v_##_Tpvec& b0, v_##_Tpvec& b1) \
+{ \
+    v##_Tp##m2_t tmp = vundefined_##_T##m2();\
+    tmp = vset_v_##_T##m1_##_T##m2(tmp, 0, a0.val); \
+    tmp = vset_v_##_T##m1_##_T##m2(tmp, 1, a1.val); \
+    unsigned mdata[] = VITL_##num; \
+    vuint32m2_t mask = vle32_v_u32m2(mdata, 8);    \
+    tmp = (v##_Tp##m2_t)vrgather_vv_##_T##m2((v##_Tp##m2_t)tmp, refunc(mask), num2);    \
+    b0.val = vget_v_##_T##m2_##_T##m1(tmp, 0); \
+    b1.val = vget_v_##_T##m2_##_T##m1(tmp, 1); \
+} \
+inline v_##_Tpvec v_combine_low(const v_##_Tpvec& a, const v_##_Tpvec& b) \
+{ \
+    v##_Tp##m1_t b0 = vslideup_vx_##_T##m1_m(vmset_m_##len(num), a.val, b.val, numh, num);    \
+    return v_##_Tpvec(b0);\
+} \
+inline v_##_Tpvec v_combine_high(const v_##_Tpvec& a, const v_##_Tpvec& b) \
+{ \
+    v##_Tp##m1_t b0 = vundefined_##_T##m1(); \
+    v##_Tp##m1_t a0 = vundefined_##_T##m1(); \
+    v##_Tp##m1_t b1 = vundefined_##_T##m1(); \
+    b0 = vslidedown_vx_##_T##m1(b0, b.val, numh, num);    \
+    a0 = vslidedown_vx_##_T##m1(a0, a.val, numh, num);    \
+    b1 = vslideup_vx_##_T##m1_m(vmset_m_##len(num), a0, b0, numh, num);    \
+    return v_##_Tpvec(b1);\
+} \
+inline void v_recombine(const v_##_Tpvec& a, const v_##_Tpvec& b, v_##_Tpvec& c, v_##_Tpvec& d) \
+{ \
+    v##_Tp##m1_t b0 = vundefined_##_T##m1(); \
+    v##_Tp##m1_t a0 = vundefined_##_T##m1(); \
+    c.val = vslideup_vx_##_T##m1_m(vmset_m_##len(num), a.val, b.val, numh, num);    \
+    b0 = vslidedown_vx_##_T##m1(b0, b.val, numh, num);    \
+    a0 = vslidedown_vx_##_T##m1(a0, a.val, numh, num);    \
+    d.val = vslideup_vx_##_T##m1_m(vmset_m_##len(num), a0, b0, numh, num);    \
+}
+
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(uint8x16, uint8, u8, uint8, u8, 16, 32, b8, 8, vreinterpret_v_u32m2_u8m2)
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(int8x16, int8, i8, uint8, u8, 16, 32, b8, 8, vreinterpret_v_u32m2_u8m2)
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(uint16x8, uint16, u16, uint16, u16, 8, 16, b16, 4, vreinterpret_v_u32m2_u16m2)
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(int16x8, int16, i16, uint16, u16, 8, 16, b16, 4, vreinterpret_v_u32m2_u16m2)
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(uint32x4, uint32, u32, uint32, u32, 4, 8, b32, 2,)
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(int32x4, int32, i32, uint32, u32, 4, 8, b32, 2,)
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(float32x4, float32, f32, uint32, u32, 4, 8, b32, 2,)
+OPENCV_HAL_IMPL_RISCVV_UNPACKS(float64x2, float64, f64, uint64, u64, 2, 4, b64, 1, vreinterpret_v_u32m2_u64m2)
+
+inline v_uint8x16 v_reverse(const v_uint8x16 &a)
+{
+    return v_uint8x16(vrgather_vv_u8m1(a.val, vrsub_vx_u8m1(vid_v_u8m1(16), 15, 16), 16));
+}
+inline v_int8x16 v_reverse(const v_int8x16 &a)
+{
+    return v_int8x16(vrgather_vv_i8m1(a.val, vrsub_vx_u8m1(vid_v_u8m1(16), 15, 16), 16));
+}
+
+inline v_uint16x8 v_reverse(const v_uint16x8 &a)
+{
+    return v_uint16x8(vrgather_vv_u16m1(a.val, vrsub_vx_u16m1(vid_v_u16m1(8), 7, 8), 8));
+}
+
+inline v_int16x8 v_reverse(const v_int16x8 &a)
+{
+    return v_int16x8(vrgather_vv_i16m1(a.val, vrsub_vx_u16m1(vid_v_u16m1(8), 7, 8), 8));
+}
+inline v_uint32x4 v_reverse(const v_uint32x4 &a)
+{
+    return v_uint32x4(vrgather_vv_u32m1(a.val, vrsub_vx_u32m1(vid_v_u32m1(4), 3, 4), 4));
+}
+
+inline v_int32x4 v_reverse(const v_int32x4 &a)
+{
+    return v_int32x4(vrgather_vv_i32m1(a.val, vrsub_vx_u32m1(vid_v_u32m1(4), 3, 4), 4));
+}
+
+inline v_float32x4 v_reverse(const v_float32x4 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x2 v_reverse(const v_uint64x2 &a)
+{
+    return v_uint64x2(vrgather_vv_u64m1(a.val, vrsub_vx_u64m1(vid_v_u64m1(2), 1, 2), 2));
+}
+
+inline v_int64x2 v_reverse(const v_int64x2 &a)
+{
+    return v_int64x2(vrgather_vv_i64m1(a.val, vrsub_vx_u64m1(vid_v_u64m1(2), 1, 2), 2));
+}
+
+inline v_float64x2 v_reverse(const v_float64x2 &a)
+{
+    return v_float64x2(vrgather_vv_f64m1(a.val, vrsub_vx_u64m1(vid_v_u64m1(2), 1, 2), 2));
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_EXTRACT(_Tpvec, suffix, size) \
+template <int n> \
+inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b) \
+{ return v_rotate_right<n>(a, b);}
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_uint8x16, u8, 0)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_int8x16, s8, 0)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_uint16x8, u16, 1)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_int16x8, s16, 1)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_uint32x4, u32, 2)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_int32x4, s32, 2)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_uint64x2, u64, 3)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_int64x2, s64, 3)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_float32x4, f32, 2)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT(v_float64x2, f64, 3)
+
+
+#define OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(_Tpvec, _Tp, suffix, vtype, _vtype, num, mvfunc) \
+template<int i> inline _Tp v_extract_n(_Tpvec v) { vtype tmp = vundefined_##_vtype(); return mvfunc(vslidedown_vx_##_vtype(tmp, v.val, i, num)); }
+
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_uint8x16, uchar, u8, vuint8m1_t, u8m1, 16, vmv_x_s_u8m1_u8)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_int8x16, schar, s8, vint8m1_t, i8m1, 16, vmv_x_s_i8m1_i8)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_uint16x8, ushort, u16, vuint16m1_t, u16m1, 8, vmv_x_s_u16m1_u16)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_int16x8, short, s16, vint16m1_t, i16m1, 8, vmv_x_s_i16m1_i16)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_uint32x4, uint, u32, vuint32m1_t, u32m1, 4, vmv_x_s_u32m1_u32)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_int32x4, int, s32, vint32m1_t, i32m1, 4, vmv_x_s_i32m1_i32)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_uint64x2, uint64, u64, vuint64m1_t, u64m1, 2, vmv_x_s_u64m1_u64)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_int64x2, int64, s64, vint64m1_t, i64m1, 2, vmv_x_s_i64m1_i64)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_float32x4, float, f32, vfloat32m1_t, f32m1, 4, vfmv_f_s_f32m1_f32)
+OPENCV_HAL_IMPL_RISCVV_EXTRACT_N(v_float64x2, double, f64, vfloat64m1_t, f64m1, 2, vfmv_f_s_f64m1_f64)
+
+#define OPENCV_HAL_IMPL_RISCVV_BROADCAST(_Tpvec, _Tp, num) \
+template<int i> inline _Tpvec v_broadcast_element(_Tpvec v) { return _Tpvec(vrgather_vx_##_Tp##m1(v.val, i, num)); }
+
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_uint8x16, u8, 16)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_int8x16, i8, 16)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_uint16x8, u16, 8)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_int16x8, i16, 8)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_uint32x4, u32, 4)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_int32x4, i32, 4)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_uint64x2, u64, 2)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_int64x2, i64, 2)
+OPENCV_HAL_IMPL_RISCVV_BROADCAST(v_float32x4, f32, 4)
+
+inline void __builtin_riscv_fsrm(int val)
+{
+    asm("csrw frm, %0\n\t"
+        :
+        :"r"(val));
+    return;
+}
+
+inline void barrier1(void *arg) {
+  __asm__ __volatile__("" : : "r" (arg) : "memory");
+}
+
+inline v_int32x4 v_round(const v_float32x4& a)
+{
+    __builtin_riscv_fsrm(0);
+    vint32m1_t nan = vand_vx_i32m1(vreinterpret_v_f32m1_i32m1(a.val), 0x7f800000, 4);
+    barrier1(&nan);
+    vbool32_t mask = vmsne_vx_i32m1_b32(nan, 0x7f800000, 4);
+    vint32m1_t val = vfcvt_x_f_v_i32m1_m(mask, vmv_v_x_i32m1(0, 4), a.val, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+inline v_int32x4 v_floor(const v_float32x4& a)
+{
+    __builtin_riscv_fsrm(2);
+    vint32m1_t nan = vand_vx_i32m1(vreinterpret_v_f32m1_i32m1(a.val), 0x7f800000, 4);
+    barrier1(&nan);
+    vbool32_t mask = vmsne_vx_i32m1_b32(nan, 0x7f800000, 4);
+    vint32m1_t val = vfcvt_x_f_v_i32m1_m(mask, vmv_v_x_i32m1(0, 4), a.val, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+
+inline v_int32x4 v_ceil(const v_float32x4& a)
+{
+    __builtin_riscv_fsrm(3);
+    vint32m1_t nan = vand_vx_i32m1(vreinterpret_v_f32m1_i32m1(a.val), 0x7f800000, 4);
+    barrier1(&nan);
+    vbool32_t mask = vmsne_vx_i32m1_b32(nan, 0x7f800000, 4);
+    vint32m1_t val = vfcvt_x_f_v_i32m1_m(mask, vmv_v_x_i32m1(0, 4), a.val, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+
+inline v_int32x4 v_trunc(const v_float32x4& a)
+{
+    __builtin_riscv_fsrm(1);
+    vint32m1_t nan = vand_vx_i32m1(vreinterpret_v_f32m1_i32m1(a.val), 0x7f800000, 4);
+    barrier1(&nan);
+    vbool32_t mask = vmsne_vx_i32m1_b32(nan, 0x7f800000, 4);
+    vint32m1_t val = vfcvt_x_f_v_i32m1_m(mask, vmv_v_x_i32m1(0, 4), a.val, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+
+inline v_int32x4 v_round(const v_float64x2& a)
+{
+    __builtin_riscv_fsrm(0);
+    vfloat64m2_t _val = vundefined_f64m2();
+    _val = vset_v_f64m1_f64m2(_val, 0, a.val);
+    //_val = vset_f64m2(_val, 1, a.val);
+    _val = vset_v_f64m1_f64m2(_val, 1, vfmv_v_f_f64m1(0, 2));
+    barrier1(&_val);
+    vint32m1_t val = vfncvt_x_f_w_i32m1(_val, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b)
+{
+    __builtin_riscv_fsrm(0);
+    vfloat64m2_t _val = vundefined_f64m2();
+    _val = vset_v_f64m1_f64m2(_val, 0, a.val);
+    _val = vset_v_f64m1_f64m2(_val, 1, b.val);
+    barrier1(&_val);
+    vint32m1_t val = vfncvt_x_f_w_i32m1(_val, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+inline v_int32x4 v_floor(const v_float64x2& a)
+{
+    __builtin_riscv_fsrm(2);
+    vfloat64m2_t _val = vundefined_f64m2();
+    _val = vset_v_f64m1_f64m2(_val, 0, a.val);
+    vfloat32m1_t aval = vfncvt_f_f_w_f32m1(_val, 2);
+    vint32m1_t nan = vand_vx_i32m1(vreinterpret_v_f32m1_i32m1(aval), 0x7f800000, 4);
+    barrier1(&nan);
+    vbool32_t mask = vmsne_vx_i32m1_b32(nan, 0x7f800000, 4);
+    vint32m1_t val = vfcvt_x_f_v_i32m1_m(mask, vmv_v_x_i32m1(0, 4), aval, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+
+inline v_int32x4 v_ceil(const v_float64x2& a)
+{
+    __builtin_riscv_fsrm(3);
+    vfloat64m2_t _val = vundefined_f64m2();
+    _val = vset_v_f64m1_f64m2(_val, 0, a.val);
+    vfloat32m1_t aval = vfncvt_f_f_w_f32m1(_val, 2);
+    vint32m1_t nan = vand_vx_i32m1(vreinterpret_v_f32m1_i32m1(aval), 0x7f800000, 4);
+    barrier1(&nan);
+    vbool32_t mask = vmsne_vx_i32m1_b32(nan, 0x7f800000, 4);
+    vint32m1_t val = vfcvt_x_f_v_i32m1_m(mask, vmv_v_x_i32m1(0, 4), aval, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+
+inline v_int32x4 v_trunc(const v_float64x2& a)
+{
+    __builtin_riscv_fsrm(1);
+    vfloat64m2_t _val = vundefined_f64m2();
+    _val = vset_v_f64m1_f64m2(_val, 0, a.val);
+    vfloat32m1_t aval = vfncvt_f_f_w_f32m1(_val, 2);
+    vint32m1_t nan = vand_vx_i32m1(vreinterpret_v_f32m1_i32m1(aval), 0x7f800000, 4);
+    barrier1(&nan);
+    vbool32_t mask = vmsne_vx_i32m1_b32(nan, 0x7f800000, 4);
+    vint32m1_t val = vfcvt_x_f_v_i32m1_m(mask, vmv_v_x_i32m1(0, 4), aval, 4);
+    __builtin_riscv_fsrm(0);
+    return v_int32x4(val);
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_LOAD_DEINTERLEAVED(intrin, _Tpvec, num, _Tp, _T, elemsize)    \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec##x##num& a, v_##_Tpvec##x##num& b) \
+{ \
+    intrin##2e##elemsize##_v_##_T##m1(&a.val, &b.val, ptr, num); \
+} \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec##x##num& a, v_##_Tpvec##x##num& b, v_##_Tpvec##x##num& c) \
+{ \
+    intrin##3e##elemsize##_v_##_T##m1(&a.val, &b.val, &c.val, ptr, num); \
+}\
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec##x##num& a, v_##_Tpvec##x##num& b, \
+                                v_##_Tpvec##x##num& c, v_##_Tpvec##x##num& d) \
+{ \
+    intrin##4e##elemsize##_v_##_T##m1(&a.val, &b.val, &c.val, &d.val, ptr, num); \
+} \
+
+#define OPENCV_HAL_IMPL_RISCVV_STORE_INTERLEAVED(intrin, _Tpvec, num, _Tp, _T, elemsize)    \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec##x##num& a, const v_##_Tpvec##x##num& b, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    intrin##2e##elemsize##_v_##_T##m1(ptr, a.val, b.val, num); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec##x##num& a, const v_##_Tpvec##x##num& b, \
+                                const v_##_Tpvec##x##num& c, hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    intrin##3e##elemsize##_v_##_T##m1(ptr, a.val, b.val, c.val, num); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec##x##num& a, const v_##_Tpvec##x##num& b, \
+                                const v_##_Tpvec##x##num& c, const v_##_Tpvec##x##num& d, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ \
+    intrin##4e##elemsize##_v_##_T##m1(ptr, a.val, b.val, c.val, d.val, num); \
+}
+
+#define OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(_Tpvec, _Tp, num, ld, st, _T, elemsize) \
+OPENCV_HAL_IMPL_RISCVV_LOAD_DEINTERLEAVED(ld, _Tpvec, num, _Tp, _T, elemsize)    \
+OPENCV_HAL_IMPL_RISCVV_STORE_INTERLEAVED(st, _Tpvec, num, _Tp, _T, elemsize)
+
+//OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(uint8, uchar, )
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(int8, schar, 16, vlseg, vsseg, i8, 8)
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(int16, short, 8, vlseg, vsseg, i16, 16)
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(int32, int, 4, vlseg, vsseg, i32, 32)
+
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(uint8, unsigned char, 16, vlseg, vsseg, u8, 8)
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(uint16, unsigned short, 8, vlseg, vsseg, u16, 16)
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED(uint32, unsigned int, 4, vlseg, vsseg, u32, 32)
+
+#define OPENCV_HAL_IMPL_RISCVV_INTERLEAVED_(_Tpvec, _Tp, num, _T, _esize) \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec##x##num& a, v_##_Tpvec##x##num& b) \
+{ vlseg2e##_esize##_v_##_T##m1(&a.val, &b.val, ptr, num);} \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec##x##num& a, v_##_Tpvec##x##num& b, v_##_Tpvec##x##num& c) \
+{ vlseg3e##_esize##_v_##_T##m1(&a.val, &b.val, &c.val, ptr, num);}\
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec##x##num& a, v_##_Tpvec##x##num& b, \
+                                v_##_Tpvec##x##num& c, v_##_Tpvec##x##num& d) \
+{ vlseg4e##_esize##_v_##_T##m1(&a.val, &b.val, &c.val, &d.val, ptr, num);} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec##x##num& a, const v_##_Tpvec##x##num& b, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ vsseg2e##_esize##_v_##_T##m1(ptr, a.val, b.val, num);} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec##x##num& a, const v_##_Tpvec##x##num& b, \
+                                const v_##_Tpvec##x##num& c, hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ vsseg3e##_esize##_v_##_T##m1(ptr, a.val, b.val, c.val, num);} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec##x##num& a, const v_##_Tpvec##x##num& b, \
+                                const v_##_Tpvec##x##num& c, const v_##_Tpvec##x##num& d, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ vsseg4e##_esize##_v_##_T##m1(ptr, a.val, b.val, c.val, d.val, num);}
+
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED_(float32, float, 4, f32, 32)
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED_(float64, double, 2, f64, 64)
+
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED_(uint64, unsigned long, 2, u64, 64)
+OPENCV_HAL_IMPL_RISCVV_INTERLEAVED_(int64, long, 2, i64, 64)
+
+inline v_float32x4 v_cvt_f32(const v_int32x4& a)
+{
+    return v_float32x4(vfcvt_f_x_v_f32m1(a.val, 4));
+}
+
+#if CV_SIMD128_64F
+inline v_float32x4 v_cvt_f32(const v_float64x2& a)
+{
+    vfloat64m2_t _val = vundefined_f64m2();
+    _val = vset_v_f64m1_f64m2(_val, 0, a.val);
+    vfloat32m1_t aval = vfncvt_f_f_w_f32m1(_val, 2);
+    return v_float32x4(aval);
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b)
+{
+    vfloat64m2_t _val = vundefined_f64m2();
+    _val = vset_v_f64m1_f64m2(_val, 0, a.val);
+    _val = vset_v_f64m1_f64m2(_val, 1, b.val);
+    vfloat32m1_t aval = vfncvt_f_f_w_f32m1(_val, 4);
+    return v_float32x4(aval);
+}
+
+inline v_float64x2 v_cvt_f64(const v_int32x4& a)
+{
+    vfloat32m1_t val = vfcvt_f_x_v_f32m1(a.val, 4);
+    vfloat64m2_t _val = vfwcvt_f_f_v_f64m2(val, 4);
+    return v_float64x2(vget_v_f64m2_f64m1(_val, 0));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_int32x4& a)
+{
+    vfloat32m1_t val = vfcvt_f_x_v_f32m1(a.val, 4);
+    vfloat64m2_t _val = vfwcvt_f_f_v_f64m2(val, 4);
+    return v_float64x2(vget_v_f64m2_f64m1(_val, 1));
+}
+
+inline v_float64x2 v_cvt_f64(const v_float32x4& a)
+{
+    vfloat64m2_t _val  = vfwcvt_f_f_v_f64m2(a.val, 4);
+    return v_float64x2(vget_v_f64m2_f64m1(_val, 0));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_float32x4& a)
+{
+    vfloat64m2_t _val  = vfwcvt_f_f_v_f64m2(a.val, 4);
+    return v_float64x2(vget_v_f64m2_f64m1(_val, 1));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int64x2& a)
+{
+    return v_float64x2(vfcvt_f_x_v_f64m1(a.val, 2));
+}
+
+#endif
+inline v_int8x16 v_interleave_pairs(const v_int8x16& vec)
+{
+    uint64 mdata[2] = {0x0705060403010200, 0x0F0D0E0C0B090A08};
+    vuint64m1_t m0 = vle64_v_u64m1(mdata, 2);
+    return v_int8x16(vrgather_vv_i8m1(vec.val, vreinterpret_v_u64m1_u8m1(m0), 16));
+}
+inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec)
+{
+    return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec)));
+}
+
+inline v_int8x16 v_interleave_quads(const v_int8x16& vec)
+{
+    uint64 mdata[2] = {0x0703060205010400, 0x0F0B0E0A0D090C08};
+    vuint64m1_t m0 = vle64_v_u64m1(mdata, 2);
+    return v_int8x16(vrgather_vv_i8m1(vec.val, vreinterpret_v_u64m1_u8m1(m0), 16));
+}
+inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec)
+{
+    return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec)));
+}
+
+inline v_int16x8 v_interleave_pairs(const v_int16x8& vec)
+{
+    uint64 mdata[2] = {0x0706030205040100, 0x0F0E0B0A0D0C0908};
+    vuint64m1_t m0 = vle64_v_u64m1(mdata, 2);
+    return v_int16x8(vreinterpret_v_i8m1_i16m1(vreinterpret_v_u8m1_i8m1(vrgather_vv_u8m1(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i16m1_i8m1(vec.val)), vreinterpret_v_u64m1_u8m1(m0), 16))));
+}
+inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x8 v_interleave_quads(const v_int16x8& vec)
+{
+    uint64 mdata[2] = {0x0B0A030209080100, 0x0F0E07060D0C0504};
+    vuint64m1_t m0 = vle64_v_u64m1(mdata, 2);
+    return v_int16x8(vreinterpret_v_i8m1_i16m1(vreinterpret_v_u8m1_i8m1(vrgather_vv_u8m1(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i16m1_i8m1(vec.val)), vreinterpret_v_u64m1_u8m1(m0), 16))));
+}
+inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_interleave_pairs(const v_int32x4& vec)
+{
+    uint64 mdata[2] = {0x0B0A090803020100, 0x0F0E0D0C07060504};
+    vuint64m1_t m0 = vle64_v_u64m1(mdata, 2);
+    return v_int32x4(vreinterpret_v_i8m1_i32m1(vreinterpret_v_u8m1_i8m1(vrgather_vv_u8m1(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i32m1_i8m1(vec.val)), vreinterpret_v_u64m1_u8m1(m0), 16))));
+}
+inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x4 v_interleave_pairs(const v_float32x4& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_int8x16 v_pack_triplets(const v_int8x16& vec)
+{
+    uint64 mdata[2] = {0x0908060504020100, 0xFFFFFFFF0E0D0C0A};
+    vuint64m1_t m0 = vle64_v_u64m1(mdata, 2);
+    return v_int8x16(vreinterpret_v_u8m1_i8m1(vrgather_vv_u8m1(vreinterpret_v_i8m1_u8m1(vec.val), vreinterpret_v_u64m1_u8m1(m0), 16)));
+}
+inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_pack_triplets(const v_int16x8& vec)
+{
+    uint64 mdata[2] = {0x0908050403020100, 0xFFFFFFFF0D0C0B0A};
+    vuint64m1_t m0 = vle64_v_u64m1(mdata, 2);
+    return v_int16x8(vreinterpret_v_i8m1_i16m1(vreinterpret_v_u8m1_i8m1(vrgather_vv_u8m1(vreinterpret_v_i8m1_u8m1(vreinterpret_v_i16m1_i8m1(vec.val)), vreinterpret_v_u64m1_u8m1(m0), 16))));
+}
+inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; }
+inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; }
+inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; }
+
+#if CV_SIMD128_64F
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a,   const v_int32x4& b,
+                                    const v_float64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b)
+{
+    vint64m2_t v1 = vwmul_vv_i64m2(a.val, b.val, 4);
+    vfloat64m1_t res = vfcvt_f_x_v_f64m1(vadd_vv_i64m1(vget_v_i64m2_i64m1(v1, 0), vget_v_i64m2_i64m1(v1, 1), 2), 2);
+    return v_float64x2(res);
+}
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ v_float64x2 res = v_dotprod_expand_fast(a, b);
+  return v_add(res, c); }
+#endif
+////// FP16 support ///////
+#if __riscv_v == 7000
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+    vfloat16m1_t v = vle16_v_f16m1((__fp16*)ptr, 4);
+    vfloat32m2_t v32 = vfwcvt_f_f_v_f32m2(v, 4);
+    return v_float32x4(vget_v_f32m2_f32m1(v32, 0));
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+    vfloat32m2_t v32 = vundefined_f32m2();
+    v32 = vset_v_f32m1_f32m2(v32, 0, v.val);
+    vfloat16m1_t hv = vfncvt_f_f_w_f16m1(v32, 4);
+    vse16_v_f16m1((__fp16*)ptr, hv, 4);
+}
+#else
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+    vfloat16mf2_t v = vle16_v_f16mf2((__fp16*)ptr, 4);
+    vfloat32m1_t v32 = vfwcvt_f_f_v_f32m1(v, 4);
+    return v_float32x4(v32);
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+    //vfloat32m2_t v32 = vundefined_f32m2();
+    //v32 = vset_f32m2(v32, 0, v.val);
+    vfloat16mf2_t hv = vfncvt_f_f_w_f16mf2(v.val, 4);
+    vse16_v_f16mf2((__fp16*)ptr, hv, 4);
+}
+#endif
+
+inline void v_cleanup() {}
+
+#include "intrin_math.hpp"
+inline v_float32x4 v_exp(const v_float32x4& x) { return v_exp_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_log(const v_float32x4& x) { return v_log_default_32f<v_float32x4, v_int32x4>(x); }
+inline void v_sincos(const v_float32x4& x, v_float32x4& s, v_float32x4& c) { v_sincos_default_32f<v_float32x4, v_int32x4>(x, s, c); }
+inline v_float32x4 v_sin(const v_float32x4& x) { return v_sin_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_cos(const v_float32x4& x) { return v_cos_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_erf(const v_float32x4& x) { return v_erf_default_32f<v_float32x4, v_int32x4>(x); }
+
+inline v_float64x2 v_exp(const v_float64x2& x) { return v_exp_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_log(const v_float64x2& x) { return v_log_default_64f<v_float64x2, v_int64x2>(x); }
+inline void v_sincos(const v_float64x2& x, v_float64x2& s, v_float64x2& c) { v_sincos_default_64f<v_float64x2, v_int64x2>(x, s, c); }
+inline v_float64x2 v_sin(const v_float64x2& x) { return v_sin_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_cos(const v_float64x2& x) { return v_cos_default_64f<v_float64x2, v_int64x2>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+}
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_rvv_scalable.hpp

@@ -0,0 +1,2153 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+// The original implementation is contributed by HAN Liutong.
+// Copyright (C) 2022, Institute of Software, Chinese Academy of Sciences.
+
+#ifndef OPENCV_HAL_INTRIN_RVV_SCALABLE_HPP
+#define OPENCV_HAL_INTRIN_RVV_SCALABLE_HPP
+
+#include <opencv2/core/check.hpp>
+
+#if defined(__GNUC__) && !defined(__clang__)
+// FIXIT: eliminate massive warnigs from templates
+// GCC from 'rvv-next': riscv64-unknown-linux-gnu-g++ (g42df3464463) 12.0.1 20220505 (prerelease)
+// doesn't work: #pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wignored-attributes"
+#endif
+
+#ifndef CV_RVV_MAX_VLEN
+#define CV_RVV_MAX_VLEN 1024
+#endif
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+#define CV_SIMD_SCALABLE 1
+#define CV_SIMD_SCALABLE_64F 1
+
+using v_uint8 = vuint8m2_t;
+using v_int8 = vint8m2_t;
+using v_uint16 = vuint16m2_t;
+using v_int16 = vint16m2_t;
+using v_uint32 = vuint32m2_t;
+using v_int32 = vint32m2_t;
+using v_uint64 = vuint64m2_t;
+using v_int64 = vint64m2_t;
+
+using v_float32 = vfloat32m2_t;
+#if CV_SIMD_SCALABLE_64F
+using v_float64 = vfloat64m2_t;
+#endif
+
+using uchar = unsigned char;
+using schar = signed char;
+using ushort = unsigned short;
+using uint = unsigned int;
+using uint64 = unsigned long int;
+using int64 = long int;
+
+
+template <class T>
+struct VTraits;
+
+#define OPENCV_HAL_IMPL_RVV_TRAITS(REG, TYP, SUF, SZ) \
+template <> \
+struct VTraits<REG> \
+{ \
+    static inline int vlanes() { return __riscv_vsetvlmax_##SUF(); } \
+    using lane_type = TYP; \
+    static const int max_nlanes = CV_RVV_MAX_VLEN/SZ; \
+};
+
+OPENCV_HAL_IMPL_RVV_TRAITS(vint8m1_t, int8_t, e8m1, 8)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint8m2_t, int8_t, e8m2, 8)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint8m4_t, int8_t, e8m4, 8)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint8m8_t, int8_t, e8m8, 8)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint8m1_t, uint8_t, e8m1, 8)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint8m2_t, uint8_t, e8m2, 8)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint8m4_t, uint8_t, e8m4, 8)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint8m8_t, uint8_t, e8m8, 8)
+
+OPENCV_HAL_IMPL_RVV_TRAITS(vint16m1_t, int16_t, e16m1, 16)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint16m2_t, int16_t, e16m2, 16)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint16m4_t, int16_t, e16m4, 16)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint16m8_t, int16_t, e16m8, 16)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint16m1_t, uint16_t, e16m1, 16)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint16m2_t, uint16_t, e16m2, 16)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint16m4_t, uint16_t, e16m4, 16)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint16m8_t, uint16_t, e16m8, 16)
+
+OPENCV_HAL_IMPL_RVV_TRAITS(vint32m1_t, int32_t, e32m1, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint32m2_t, int32_t, e32m2, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint32m4_t, int32_t, e32m4, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint32m8_t, int32_t, e32m8, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint32m1_t, uint32_t, e32m1, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint32m2_t, uint32_t, e32m2, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint32m4_t, uint32_t, e32m4, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint32m8_t, uint32_t, e32m8, 32)
+
+OPENCV_HAL_IMPL_RVV_TRAITS(vint64m1_t, int64_t, e64m1, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint64m2_t, int64_t, e64m2, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint64m4_t, int64_t, e64m4, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vint64m8_t, int64_t, e64m8, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint64m1_t, uint64_t, e64m1, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint64m2_t, uint64_t, e64m2, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint64m4_t, uint64_t, e64m4, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vuint64m8_t, uint64_t, e64m8, 64)
+
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat32m1_t, float, e32m1, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat32m2_t, float, e32m2, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat32m4_t, float, e32m4, 32)
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat32m8_t, float, e32m8, 32)
+
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat64m1_t, double, e64m1, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat64m2_t, double, e64m2, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat64m4_t, double, e64m4, 64)
+OPENCV_HAL_IMPL_RVV_TRAITS(vfloat64m8_t, double, e64m8, 64)
+#endif
+
+
+// LLVM/Clang defines "overloaded intrinsics" e.g. 'vand(op1, op2)'
+// GCC does not have these functions, so we need to implement them manually
+// We implement only selected subset required to build current state of the code
+// Included inside namespace cv::
+// #ifndef __riscv_v_intrinsic_overloading
+// #include "intrin_rvv_compat_overloaded.hpp"
+// #endif // __riscv_v_intrinsic_overloading
+
+
+//////////// get0 ////////////
+#define OPENCV_HAL_IMPL_RVV_GRT0_INT(_Tpvec, _Tp) \
+inline _Tp v_get0(const v_##_Tpvec& v) \
+{ \
+    return __riscv_vmv_x(v); \
+}
+
+OPENCV_HAL_IMPL_RVV_GRT0_INT(uint8, uchar)
+OPENCV_HAL_IMPL_RVV_GRT0_INT(int8, schar)
+OPENCV_HAL_IMPL_RVV_GRT0_INT(uint16, ushort)
+OPENCV_HAL_IMPL_RVV_GRT0_INT(int16, short)
+OPENCV_HAL_IMPL_RVV_GRT0_INT(uint32, unsigned)
+OPENCV_HAL_IMPL_RVV_GRT0_INT(int32, int)
+OPENCV_HAL_IMPL_RVV_GRT0_INT(uint64, uint64)
+OPENCV_HAL_IMPL_RVV_GRT0_INT(int64, int64)
+
+inline float v_get0(const v_float32& v) \
+{ \
+    return __riscv_vfmv_f(v); \
+}
+#if CV_SIMD_SCALABLE_64F
+inline double v_get0(const v_float64& v) \
+{ \
+    return __riscv_vfmv_f(v); \
+}
+#endif
+
+//////////// Initial ////////////
+
+#define OPENCV_HAL_IMPL_RVV_INIT_INTEGER(_Tpvec, _Tp, suffix1, suffix2, vl) \
+inline v_##_Tpvec v_setzero_##suffix1() \
+{ \
+    return __riscv_vmv_v_x_##suffix2##m2(0, vl); \
+} \
+inline v_##_Tpvec v_setall_##suffix1(_Tp v) \
+{ \
+    return __riscv_vmv_v_x_##suffix2##m2(v, vl); \
+} \
+template <> inline v_##_Tpvec v_setzero_() \
+{ \
+    return v_setzero_##suffix1(); \
+} \
+template <> inline v_##_Tpvec v_setall_(_Tp v) \
+{ \
+    return v_setall_##suffix1(v); \
+}
+
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(uint8, uchar, u8, u8, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(int8, schar, s8, i8, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(uint16, ushort, u16, u16, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(int16, short, s16, i16, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(uint32, uint, u32, u32, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(int32, int, s32, i32, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(uint64, uint64, u64, u64, VTraits<v_uint64>::vlanes())
+OPENCV_HAL_IMPL_RVV_INIT_INTEGER(int64, int64, s64, i64, VTraits<v_int64>::vlanes())
+
+#define OPENCV_HAL_IMPL_RVV_INIT_FP(_Tpv, _Tp, suffix, vl) \
+inline v_##_Tpv v_setzero_##suffix() \
+{ \
+    return __riscv_vfmv_v_f_##suffix##m2(0, vl); \
+} \
+inline v_##_Tpv v_setall_##suffix(_Tp v) \
+{ \
+    return __riscv_vfmv_v_f_##suffix##m2(v, vl); \
+} \
+template <> inline v_##_Tpv v_setzero_() \
+{ \
+    return v_setzero_##suffix(); \
+} \
+template <> inline v_##_Tpv v_setall_(_Tp v) \
+{ \
+    return v_setall_##suffix(v); \
+}
+
+OPENCV_HAL_IMPL_RVV_INIT_FP(float32, float, f32, VTraits<v_float32>::vlanes())
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_INIT_FP(float64, double, f64, VTraits<v_float64>::vlanes())
+#endif
+
+//////////// Reinterpret ////////////
+#define OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(_Tpvec1, suffix1) \
+inline v_##_Tpvec1 v_reinterpret_as_##suffix1(const v_##_Tpvec1& v) \
+{ \
+    return v;\
+}
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(uint8, u8)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(uint16, u16)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(uint32, u32)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(uint64, u64)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(int8, s8)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(int16, s16)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(int32, s32)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(int64, s64)
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(float32, f32)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_NOTHING_REINTERPRET(float64, f64)
+#endif
+// TODO: can be simplified by using overloaded RV intrinsic
+#define OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(_Tpvec1, _Tpvec2, suffix1, suffix2, nsuffix1, nsuffix2) \
+inline v_##_Tpvec1 v_reinterpret_as_##suffix1(const v_##_Tpvec2& v) \
+{ \
+    return v_##_Tpvec1(__riscv_vreinterpret_v_##nsuffix2##m2_##nsuffix1##m2(v));\
+} \
+inline v_##_Tpvec2 v_reinterpret_as_##suffix2(const v_##_Tpvec1& v) \
+{ \
+    return v_##_Tpvec2(__riscv_vreinterpret_v_##nsuffix1##m2_##nsuffix2##m2(v));\
+}
+
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint8, int8, u8, s8, u8, i8)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint16, int16, u16, s16, u16, i16)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint32, int32, u32, s32, u32, i32)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint32, float32, u32, f32, u32, f32)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int32, float32, s32, f32, i32, f32)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint64, int64, u64, s64, u64, i64)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint64, float64, u64, f64, u64, f64)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int64, float64, s64, f64, i64, f64)
+#endif
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint8, uint16, u8, u16, u8, u16)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint8, uint32, u8, u32, u8, u32)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint8, uint64, u8, u64, u8, u64)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint16, uint32, u16, u32, u16, u32)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint16, uint64, u16, u64, u16, u64)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(uint32, uint64, u32, u64, u32, u64)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int8, int16, s8, s16, i8, i16)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int8, int32, s8, s32, i8, i32)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int8, int64, s8, s64, i8, i64)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int16, int32, s16, s32, i16, i32)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int16, int64, s16, s64, i16, i64)
+OPENCV_HAL_IMPL_RVV_NATIVE_REINTERPRET(int32, int64, s32, s64, i32, i64)
+
+
+#define OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(_Tpvec1, _Tpvec2, suffix1, suffix2, nsuffix1, nsuffix2, width1, width2) \
+inline v_##_Tpvec1 v_reinterpret_as_##suffix1(const v_##_Tpvec2& v) \
+{ \
+    return __riscv_vreinterpret_v_##nsuffix1##width2##m2_##nsuffix1##width1##m2(__riscv_vreinterpret_v_##nsuffix2##width2##m2_##nsuffix1##width2##m2(v));\
+} \
+inline v_##_Tpvec2 v_reinterpret_as_##suffix2(const v_##_Tpvec1& v) \
+{ \
+    return __riscv_vreinterpret_v_##nsuffix1##width2##m2_##nsuffix2##width2##m2(__riscv_vreinterpret_v_##nsuffix1##width1##m2_##nsuffix1##width2##m2(v));\
+}
+
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint8, int16, u8, s16, u, i, 8, 16)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint8, int32, u8, s32, u, i, 8, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint8, int64, u8, s64, u, i, 8, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint16, int8, u16, s8, u, i, 16, 8)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint16, int32, u16, s32, u, i, 16, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint16, int64, u16, s64, u, i, 16, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint32, int8, u32, s8, u, i, 32, 8)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint32, int16, u32, s16, u, i, 32, 16)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint32, int64, u32, s64, u, i, 32, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint64, int8, u64, s8, u, i, 64, 8)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint64, int16, u64, s16, u, i, 64, 16)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint64, int32, u64, s32, u, i, 64, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint8, float32, u8, f32, u, f, 8, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint16, float32, u16, f32, u, f, 16, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint64, float32, u64, f32, u, f, 64, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(int8, float32, s8, f32, i, f, 8, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(int16, float32, s16, f32, i, f, 16, 32)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(int64, float32, s64, f32, i, f, 64, 32)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint8, float64, u8, f64, u, f, 8, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint16, float64, u16, f64, u, f, 16, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(uint32, float64, u32, f64, u, f, 32, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(int8, float64, s8, f64, i, f, 8, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(int16, float64, s16, f64, i, f, 16, 64)
+OPENCV_HAL_IMPL_RVV_TWO_TIMES_REINTERPRET(int32, float64, s32, f64, i, f, 32, 64)
+// Three times reinterpret
+inline v_float32 v_reinterpret_as_f32(const v_float64& v) \
+{ \
+    return __riscv_vreinterpret_v_u32m2_f32m2(__riscv_vreinterpret_v_u64m2_u32m2(__riscv_vreinterpret_v_f64m2_u64m2(v)));\
+}
+
+inline v_float64 v_reinterpret_as_f64(const v_float32& v) \
+{ \
+    return __riscv_vreinterpret_v_u64m2_f64m2(__riscv_vreinterpret_v_u32m2_u64m2(__riscv_vreinterpret_v_f32m2_u32m2(v)));\
+}
+#endif
+
+//////////// Extract //////////////
+
+#define OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(_Tpvec, _Tp, vl) \
+template <int s = 0> \
+inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b, int i = s) \
+{ \
+    return __riscv_vslideup(__riscv_vslidedown(a, i, vl), b, VTraits<_Tpvec>::vlanes() - i, vl); \
+} \
+template<int s = 0> inline _Tp v_extract_n(_Tpvec v, int i = s) \
+{ \
+    return __riscv_vmv_x(__riscv_vslidedown(v, i, vl)); \
+}
+
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_uint8, uchar, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_int8, schar, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_uint16, ushort, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_int16, short, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_uint32, unsigned int, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_int32, int, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_uint64, uint64, VTraits<v_uint64>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT_INTEGER(v_int64, int64, VTraits<v_int64>::vlanes())
+
+#define OPENCV_HAL_IMPL_RVV_EXTRACT_FP(_Tpvec, _Tp, vl) \
+template <int s = 0> \
+inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b, int i = s) \
+{ \
+    return __riscv_vslideup(__riscv_vslidedown(a, i, vl), b, VTraits<_Tpvec>::vlanes() - i, vl); \
+} \
+template<int s = 0> inline _Tp v_extract_n(_Tpvec v, int i = s) \
+{ \
+    return __riscv_vfmv_f(__riscv_vslidedown(v, i, vl)); \
+}
+
+OPENCV_HAL_IMPL_RVV_EXTRACT_FP(v_float32, float, VTraits<v_float32>::vlanes())
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_EXTRACT_FP(v_float64, double, VTraits<v_float64>::vlanes())
+#endif
+
+#define OPENCV_HAL_IMPL_RVV_EXTRACT(_Tpvec, _Tp, vl) \
+inline _Tp v_extract_highest(_Tpvec v) \
+{ \
+    return v_extract_n(v, vl-1); \
+}
+
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_uint8, uchar, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_int8, schar, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_uint16, ushort, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_int16, short, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_uint32, unsigned int, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_int32, int, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_uint64, uint64, VTraits<v_uint64>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_int64, int64, VTraits<v_int64>::vlanes())
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_float32, float, VTraits<v_float32>::vlanes())
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_EXTRACT(v_float64, double, VTraits<v_float64>::vlanes())
+#endif
+
+
+////////////// Load/Store //////////////
+#define OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(_Tpvec, _nTpvec, _Tp, hvl, vl, width, suffix) \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ \
+    return __riscv_vle##width##_v_##suffix##m2(ptr, vl); \
+} \
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ \
+    return __riscv_vle##width##_v_##suffix##m2(ptr, vl); \
+} \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \
+{ \
+    __riscv_vse##width##_v_##suffix##m2(ptr, a, vl); \
+} \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ \
+    return __riscv_vle##width##_v_##suffix##m2(ptr, hvl); \
+} \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ \
+    return __riscv_vslideup(__riscv_vle##width##_v_##suffix##m2(ptr0, hvl), __riscv_vle##width##_v_##suffix##m2(ptr1, hvl), hvl, vl); \
+} \
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ \
+    __riscv_vse##width(ptr, a, vl); \
+} \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ \
+    __riscv_vse##width(ptr, a, vl); \
+} \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ \
+    __riscv_vse##width(ptr, a, vl); \
+} \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ \
+    __riscv_vse##width(ptr, a, hvl); \
+} \
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ \
+    __riscv_vse##width(ptr, __riscv_vslidedown_vx_##suffix##m2(a, hvl, vl), hvl); \
+} \
+template<typename... Targs> \
+_Tpvec v_load_##suffix(Targs... nScalars) \
+{ \
+    return v_load({nScalars...}); \
+}
+
+
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_uint8, vuint8m2_t, uchar, VTraits<v_uint8>::vlanes() / 2, VTraits<v_uint8>::vlanes(), 8, u8)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_int8, vint8m2_t, schar, VTraits<v_int8>::vlanes() / 2, VTraits<v_int8>::vlanes(), 8, i8)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_uint16, vuint16m2_t, ushort, VTraits<v_uint16>::vlanes() / 2, VTraits<v_uint16>::vlanes(), 16, u16)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_int16, vint16m2_t, short, VTraits<v_int16>::vlanes() / 2, VTraits<v_int16>::vlanes(), 16, i16)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_uint32, vuint32m2_t, unsigned int, VTraits<v_uint32>::vlanes() / 2, VTraits<v_uint32>::vlanes(), 32, u32)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_int32, vint32m2_t, int, VTraits<v_int32>::vlanes() / 2, VTraits<v_int32>::vlanes(), 32, i32)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_uint64, vuint64m2_t, uint64, VTraits<v_uint64>::vlanes() / 2, VTraits<v_uint64>::vlanes(), 64, u64)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_int64, vint64m2_t, int64, VTraits<v_int64>::vlanes() / 2, VTraits<v_int64>::vlanes(), 64, i64)
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_float32, vfloat32m2_t, float, VTraits<v_float32>::vlanes() /2 , VTraits<v_float32>::vlanes(), 32, f32)
+
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_LOADSTORE_OP(v_float64, vfloat64m2_t, double, VTraits<v_float64>::vlanes() / 2, VTraits<v_float64>::vlanes(), 64, f64)
+#endif
+
+////////////// Lookup table access ////////////////////
+#define OPENCV_HAL_IMPL_RVV_LUT(_Tpvec, _Tp, suffix) \
+inline _Tpvec v_lut(const _Tp* tab, const int* idx) \
+{ \
+    auto vidx = __riscv_vmul(__riscv_vreinterpret_u32##suffix(__riscv_vle32_v_i32##suffix(idx, VTraits<_Tpvec>::vlanes())), sizeof(_Tp), VTraits<_Tpvec>::vlanes()); \
+    return __riscv_vloxei32(tab, vidx, VTraits<_Tpvec>::vlanes()); \
+}
+OPENCV_HAL_IMPL_RVV_LUT(v_int8, schar, m8)
+OPENCV_HAL_IMPL_RVV_LUT(v_int16, short, m4)
+OPENCV_HAL_IMPL_RVV_LUT(v_int32, int, m2)
+OPENCV_HAL_IMPL_RVV_LUT(v_int64, int64_t, m1)
+OPENCV_HAL_IMPL_RVV_LUT(v_float32, float, m2)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_LUT(v_float64, double, m1)
+#endif
+
+#define OPENCV_HAL_IMPL_RVV_LUT_PAIRS(_Tpvec, _Tp, suffix1, suffix2, v_trunc) \
+inline _Tpvec v_lut_pairs(const _Tp* tab, const int* idx) \
+{ \
+    auto v0 = __riscv_vle32_v_u32##suffix1((unsigned*)idx, VTraits<_Tpvec>::vlanes()/2); \
+    auto v1 = __riscv_vadd(v0, 1, VTraits<_Tpvec>::vlanes()/2); \
+    auto w0 = __riscv_vwcvtu_x(v0, VTraits<_Tpvec>::vlanes()/2); \
+    auto w1 = __riscv_vwcvtu_x(v1, VTraits<_Tpvec>::vlanes()/2); \
+    auto sh1 = __riscv_vslide1up(v_trunc(__riscv_vreinterpret_u32##suffix2(w1)),0, VTraits<_Tpvec>::vlanes()); \
+    auto vid = __riscv_vor(sh1, v_trunc(__riscv_vreinterpret_u32##suffix2(w0)), VTraits<_Tpvec>::vlanes()); \
+    auto vidx = __riscv_vmul(vid, sizeof(_Tp), VTraits<_Tpvec>::vlanes()); \
+    return __riscv_vloxei32(tab, vidx, VTraits<_Tpvec>::vlanes()); \
+}
+OPENCV_HAL_IMPL_RVV_LUT_PAIRS(v_int8, schar, m4, m8, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_LUT_PAIRS(v_int16, short, m2, m4, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_LUT_PAIRS(v_int32, int, m1, m2, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_LUT_PAIRS(v_float32, float, m1, m2, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_LUT_PAIRS(v_int64, int64_t, m1, m2, __riscv_vlmul_trunc_u32m1)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_LUT_PAIRS(v_float64, double, m1, m2, __riscv_vlmul_trunc_u32m1)
+#endif
+
+
+#define OPENCV_HAL_IMPL_RVV_LUT_QUADS(_Tpvec, _Tp, suffix0, suffix1, suffix2, v_trunc) \
+inline _Tpvec v_lut_quads(const _Tp* tab, const int* idx) \
+{ \
+    auto v0 = __riscv_vle32_v_u32##suffix0((unsigned*)idx, VTraits<_Tpvec>::vlanes()/4); \
+    auto v1 = __riscv_vadd(v0, 1, VTraits<_Tpvec>::vlanes()/4); \
+    auto v2 = __riscv_vadd(v0, 2, VTraits<_Tpvec>::vlanes()/4); \
+    auto v3 = __riscv_vadd(v0, 3, VTraits<_Tpvec>::vlanes()/4); \
+    auto w0 = __riscv_vwcvtu_x(v0, VTraits<_Tpvec>::vlanes()/4); \
+    auto w1 = __riscv_vwcvtu_x(v1, VTraits<_Tpvec>::vlanes()/4); \
+    auto w2 = __riscv_vwcvtu_x(v2, VTraits<_Tpvec>::vlanes()/4); \
+    auto w3 = __riscv_vwcvtu_x(v3, VTraits<_Tpvec>::vlanes()/4); \
+    auto sh2 = __riscv_vslide1up(__riscv_vreinterpret_u32##suffix1(w2),0, VTraits<_Tpvec>::vlanes()/2); \
+    auto sh3 = __riscv_vslide1up(__riscv_vreinterpret_u32##suffix1(w3),0, VTraits<_Tpvec>::vlanes()/2); \
+    auto vid0 = __riscv_vor(sh2, __riscv_vreinterpret_u32##suffix1(w0), VTraits<_Tpvec>::vlanes()/2); \
+    auto vid1 = __riscv_vor(sh3, __riscv_vreinterpret_u32##suffix1(w1), VTraits<_Tpvec>::vlanes()/2); \
+    auto wid0 = __riscv_vwcvtu_x(v_trunc(vid0), VTraits<_Tpvec>::vlanes()/2); \
+    auto wid1 = __riscv_vwcvtu_x(v_trunc(vid1), VTraits<_Tpvec>::vlanes()/2); \
+    auto shwid1 = __riscv_vslide1up(__riscv_vreinterpret_u32##suffix2(wid1),0, VTraits<_Tpvec>::vlanes()); \
+    auto vid = __riscv_vor(shwid1, __riscv_vreinterpret_u32##suffix2(wid0), VTraits<_Tpvec>::vlanes()); \
+    auto vidx = __riscv_vmul(vid, sizeof(_Tp), VTraits<_Tpvec>::vlanes()); \
+    return __riscv_vloxei32(tab, vidx, VTraits<_Tpvec>::vlanes()); \
+}
+OPENCV_HAL_IMPL_RVV_LUT_QUADS(v_int8, schar, m2, m4, m8, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_LUT_QUADS(v_int16, short, m1 , m2, m4, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_LUT_QUADS(v_int32, int, m1, m2, m2, __riscv_vlmul_trunc_u32m1)
+OPENCV_HAL_IMPL_RVV_LUT_QUADS(v_float32, float, m1, m2, m2, __riscv_vlmul_trunc_u32m1)
+
+#define OPENCV_HAL_IMPL_RVV_LUT_VEC(_Tpvec, _Tp) \
+inline _Tpvec v_lut(const _Tp* tab, const v_int32& vidx) \
+{ \
+    v_uint32 vidx_ = __riscv_vmul(__riscv_vreinterpret_u32m2(vidx), sizeof(_Tp), VTraits<v_int32>::vlanes()); \
+    return __riscv_vloxei32(tab, vidx_, VTraits<_Tpvec>::vlanes()); \
+}
+OPENCV_HAL_IMPL_RVV_LUT_VEC(v_float32, float)
+OPENCV_HAL_IMPL_RVV_LUT_VEC(v_int32, int)
+OPENCV_HAL_IMPL_RVV_LUT_VEC(v_uint32, unsigned)
+
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_lut(const double* tab, const v_int32& vidx) \
+{ \
+    vuint32m1_t vidx_ = __riscv_vmul(__riscv_vlmul_trunc_u32m1(__riscv_vreinterpret_u32m2(vidx)), sizeof(double), VTraits<v_float64>::vlanes()); \
+    return __riscv_vloxei32(tab, vidx_, VTraits<v_float64>::vlanes()); \
+}
+#endif
+
+
+inline v_uint8 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((schar*)tab, idx)); }
+inline v_uint8 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((schar*)tab, idx)); }
+inline v_uint8 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((schar*)tab, idx)); }
+inline v_uint16 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((short*)tab, idx)); }
+inline v_uint16 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((short*)tab, idx)); }
+inline v_uint16 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((short*)tab, idx)); }
+inline v_uint32 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((int*)tab, idx)); }
+inline v_uint32 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((int*)tab, idx)); }
+inline v_uint32 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((int*)tab, idx)); }
+inline v_uint64 v_lut(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); }
+inline v_uint64 v_lut_pairs(const uint64* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); }
+
+////////////// Pack boolean ////////////////////
+inline v_uint8 v_pack_b(const v_uint16& a, const v_uint16& b)
+{
+    return __riscv_vnsrl(__riscv_vset(__riscv_vlmul_ext_v_u16m2_u16m4(a),1,b), 0, VTraits<v_uint8>::vlanes());
+}
+
+inline v_uint8 v_pack_b(const v_uint32& a, const v_uint32& b,
+                           const v_uint32& c, const v_uint32& d)
+{
+
+    return __riscv_vnsrl(__riscv_vnsrl(__riscv_vset(__riscv_vset(__riscv_vset(__riscv_vlmul_ext_u32m8(a),1,b),2,c),3,d), 0, VTraits<v_uint8>::vlanes()), 0, VTraits<v_uint8>::vlanes());
+}
+
+inline v_uint8 v_pack_b(const v_uint64& a, const v_uint64& b, const v_uint64& c,
+                           const v_uint64& d, const v_uint64& e, const v_uint64& f,
+                           const v_uint64& g, const v_uint64& h)
+{
+    vuint8m1_t t0 = __riscv_vnsrl(__riscv_vnsrl(__riscv_vnsrl(__riscv_vset(__riscv_vset(__riscv_vset(__riscv_vlmul_ext_u64m8(a),1,b),2,c),3,d), 0, VTraits<v_uint8>::vlanes()), 0, VTraits<v_uint8>::vlanes()), 0, VTraits<v_uint8>::vlanes());
+    vuint8m1_t t1 = __riscv_vnsrl(__riscv_vnsrl(__riscv_vnsrl(__riscv_vset(__riscv_vset(__riscv_vset(__riscv_vlmul_ext_u64m8(e),1,f),2,g),3,h), 0, VTraits<v_uint8>::vlanes()), 0, VTraits<v_uint8>::vlanes()), 0, VTraits<v_uint8>::vlanes());
+
+    return __riscv_vset(__riscv_vlmul_ext_u8m2(t0), 1, t1);
+}
+
+////////////// Arithmetics //////////////
+#define OPENCV_HAL_IMPL_RVV_BIN_OP(_Tpvec, ocv_intrin, rvv_intrin) \
+inline _Tpvec v_##ocv_intrin(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return rvv_intrin(a, b, VTraits<_Tpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint8, add, __riscv_vsaddu)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint8, sub, __riscv_vssubu)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int8, add, __riscv_vsadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int8, sub, __riscv_vssub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint16, add, __riscv_vsaddu)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint16, sub, __riscv_vssubu)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int16, add, __riscv_vsadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int16, sub, __riscv_vssub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint32, add, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint32, sub, __riscv_vsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint32, mul, __riscv_vmul)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int32, add, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int32, sub, __riscv_vsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int32, mul, __riscv_vmul)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float32, add, __riscv_vfadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float32, sub, __riscv_vfsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float32, mul, __riscv_vfmul)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float32, div, __riscv_vfdiv)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint64, add, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint64, sub, __riscv_vsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int64, add, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int64, sub, __riscv_vsub)
+
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float64, add, __riscv_vfadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float64, sub, __riscv_vfsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float64, mul, __riscv_vfmul)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_float64, div, __riscv_vfdiv)
+#endif
+
+#define OPENCV_HAL_IMPL_RVV_BIN_MADD(_Tpvec, rvv_add) \
+template<typename... Args> \
+inline _Tpvec v_add(const _Tpvec& f1, const _Tpvec& f2, const Args&... vf) { \
+    return v_add(rvv_add(f1, f2, VTraits<_Tpvec>::vlanes()), vf...); \
+}
+#define OPENCV_HAL_IMPL_RVV_BIN_MMUL(_Tpvec, rvv_mul) \
+template<typename... Args> \
+inline _Tpvec v_mul(const _Tpvec& f1, const _Tpvec& f2, const Args&... vf) { \
+    return v_mul(rvv_mul(f1, f2, VTraits<_Tpvec>::vlanes()), vf...); \
+}
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_uint8, __riscv_vsaddu)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_int8, __riscv_vsadd)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_uint16, __riscv_vsaddu)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_int16, __riscv_vsadd)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_uint32, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_int32, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_float32, __riscv_vfadd)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_uint64, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_int64, __riscv_vadd)
+
+OPENCV_HAL_IMPL_RVV_BIN_MMUL(v_uint32, __riscv_vmul)
+OPENCV_HAL_IMPL_RVV_BIN_MMUL(v_int32, __riscv_vmul)
+OPENCV_HAL_IMPL_RVV_BIN_MMUL(v_float32, __riscv_vfmul)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_BIN_MADD(v_float64, __riscv_vfadd)
+OPENCV_HAL_IMPL_RVV_BIN_MMUL(v_float64, __riscv_vfmul)
+#endif
+
+#define OPENCV_HAL_IMPL_RVV_MUL_EXPAND(_Tpvec, _Tpwvec, _TpwvecM2, suffix, wmul) \
+inline void v_mul_expand(const _Tpvec& a, const _Tpvec& b, _Tpwvec& c, _Tpwvec& d) \
+{ \
+    _TpwvecM2 temp = wmul(a, b, VTraits<_Tpvec>::vlanes()); \
+    c = __riscv_vget_##suffix##m2(temp, 0); \
+    d = __riscv_vget_##suffix##m2(temp, 1); \
+}
+
+OPENCV_HAL_IMPL_RVV_MUL_EXPAND(v_uint8, v_uint16, vuint16m4_t, u16, __riscv_vwmulu)
+OPENCV_HAL_IMPL_RVV_MUL_EXPAND(v_int8, v_int16, vint16m4_t, i16, __riscv_vwmul)
+OPENCV_HAL_IMPL_RVV_MUL_EXPAND(v_uint16, v_uint32, vuint32m4_t, u32, __riscv_vwmulu)
+OPENCV_HAL_IMPL_RVV_MUL_EXPAND(v_int16, v_int32, vint32m4_t, i32, __riscv_vwmul)
+OPENCV_HAL_IMPL_RVV_MUL_EXPAND(v_uint32, v_uint64, vuint64m4_t, u64, __riscv_vwmulu)
+
+inline v_int16 v_mul_hi(const v_int16& a, const v_int16& b)
+{
+    return __riscv_vmulh(a, b, VTraits<v_int16>::vlanes());
+}
+inline v_uint16 v_mul_hi(const v_uint16& a, const v_uint16& b)
+{
+    return __riscv_vmulhu(a, b, VTraits<v_uint16>::vlanes());
+}
+
+////////////// Arithmetics (wrap)//////////////
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint8, add_wrap, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int8, add_wrap, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint16, add_wrap, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int16, add_wrap, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint8, sub_wrap, __riscv_vsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int8, sub_wrap, __riscv_vsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint16, sub_wrap, __riscv_vsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int16, sub_wrap, __riscv_vsub)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint8, mul_wrap, __riscv_vmul)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int8, mul_wrap, __riscv_vmul)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_uint16, mul_wrap, __riscv_vmul)
+OPENCV_HAL_IMPL_RVV_BIN_OP(v_int16, mul_wrap, __riscv_vmul)
+
+//////// Saturating Multiply ////////
+#define OPENCV_HAL_IMPL_RVV_MUL_SAT(_Tpvec, _clip, _wmul) \
+inline _Tpvec v_mul(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _clip(_wmul(a, b, VTraits<_Tpvec>::vlanes()), 0, 0, VTraits<_Tpvec>::vlanes()); \
+} \
+template<typename... Args> \
+inline _Tpvec v_mul(const _Tpvec& a1, const _Tpvec& a2, const Args&... va) { \
+    return v_mul(_clip(_wmul(a1, a2, VTraits<_Tpvec>::vlanes()), 0, 0, VTraits<_Tpvec>::vlanes()), va...); \
+}
+
+OPENCV_HAL_IMPL_RVV_MUL_SAT(v_uint8, __riscv_vnclipu, __riscv_vwmulu)
+OPENCV_HAL_IMPL_RVV_MUL_SAT(v_int8, __riscv_vnclip, __riscv_vwmul)
+OPENCV_HAL_IMPL_RVV_MUL_SAT(v_uint16, __riscv_vnclipu, __riscv_vwmulu)
+OPENCV_HAL_IMPL_RVV_MUL_SAT(v_int16, __riscv_vnclip, __riscv_vwmul)
+
+////////////// Bitwise logic //////////////
+
+#define OPENCV_HAL_IMPL_RVV_LOGIC_OP(_Tpvec, vl) \
+inline _Tpvec v_and(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vand(a, b, vl); \
+} \
+inline _Tpvec v_or(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vor(a, b, vl); \
+} \
+inline _Tpvec v_xor(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vxor(a, b, vl); \
+} \
+inline _Tpvec v_not (const _Tpvec& a) \
+{ \
+    return __riscv_vnot(a, vl); \
+}
+
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_uint8, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_int8, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_uint16, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_int16, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_uint32, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_int32, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_uint64, VTraits<v_uint64>::vlanes())
+OPENCV_HAL_IMPL_RVV_LOGIC_OP(v_int64, VTraits<v_int64>::vlanes())
+
+#define OPENCV_HAL_IMPL_RVV_FLT_BIT_OP(intrin) \
+inline v_float32 intrin (const v_float32& a, const v_float32& b) \
+{ \
+    return __riscv_vreinterpret_f32m2(intrin(__riscv_vreinterpret_i32m2(a), __riscv_vreinterpret_i32m2(b))); \
+}
+OPENCV_HAL_IMPL_RVV_FLT_BIT_OP(v_and)
+OPENCV_HAL_IMPL_RVV_FLT_BIT_OP(v_or)
+OPENCV_HAL_IMPL_RVV_FLT_BIT_OP(v_xor)
+
+inline v_float32 v_not (const v_float32& a) \
+{ \
+    return __riscv_vreinterpret_f32m2(v_not(__riscv_vreinterpret_i32m2(a))); \
+}
+
+#if CV_SIMD_SCALABLE_64F
+#define OPENCV_HAL_IMPL_RVV_FLT64_BIT_OP(intrin) \
+inline v_float64 intrin (const v_float64& a, const v_float64& b) \
+{ \
+    return __riscv_vreinterpret_f64m2(intrin(__riscv_vreinterpret_i64m2(a), __riscv_vreinterpret_i64m2(b))); \
+}
+OPENCV_HAL_IMPL_RVV_FLT64_BIT_OP(v_and)
+OPENCV_HAL_IMPL_RVV_FLT64_BIT_OP(v_or)
+OPENCV_HAL_IMPL_RVV_FLT64_BIT_OP(v_xor)
+
+inline v_float64 v_not (const v_float64& a) \
+{ \
+    return __riscv_vreinterpret_f64m2(v_not(__riscv_vreinterpret_i64m2(a))); \
+}
+#endif
+
+
+////////////// Bitwise shifts //////////////
+/*  Usage
+1. v_shl<N>(vec);
+2. v_shl(vec, N); // instead of vec << N, when N is non-constant.
+*/
+
+#define OPENCV_HAL_IMPL_RVV_UNSIGNED_SHIFT_OP(_Tpvec, vl) \
+template<int s = 0> inline _Tpvec v_shl(const _Tpvec& a, int n = s) \
+{ \
+    return _Tpvec(__riscv_vsll(a, uint8_t(n), vl)); \
+} \
+template<int s = 0> inline _Tpvec v_shr(const _Tpvec& a, int n = s) \
+{ \
+    return _Tpvec(__riscv_vsrl(a, uint8_t(n), vl)); \
+}
+
+#define OPENCV_HAL_IMPL_RVV_SIGNED_SHIFT_OP(_Tpvec, vl) \
+template<int s = 0> inline _Tpvec v_shl(const _Tpvec& a, int n = s) \
+{ \
+    return _Tpvec(__riscv_vsll(a, uint8_t(n), vl)); \
+} \
+template<int s = 0> inline _Tpvec v_shr(const _Tpvec& a, int n = s) \
+{ \
+    return _Tpvec(__riscv_vsra(a, uint8_t(n), vl)); \
+}
+
+OPENCV_HAL_IMPL_RVV_UNSIGNED_SHIFT_OP(v_uint16, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_UNSIGNED_SHIFT_OP(v_uint32, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_UNSIGNED_SHIFT_OP(v_uint64, VTraits<v_uint64>::vlanes())
+OPENCV_HAL_IMPL_RVV_SIGNED_SHIFT_OP(v_int16, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_SIGNED_SHIFT_OP(v_int32, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_SIGNED_SHIFT_OP(v_int64, VTraits<v_int64>::vlanes())
+
+////////////// Comparison //////////////
+#define OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, op, intrin, suffix) \
+inline _Tpvec v_##op(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    size_t VLEN = VTraits<_Tpvec>::vlanes(); \
+    uint64_t ones = -1; \
+    return __riscv_vmerge(__riscv_vmv_v_x_##suffix##m2(0, VLEN), ones, intrin(a, b, VLEN), VLEN); \
+}
+
+#define OPENCV_HAL_IMPL_RVV_FLOAT_CMP_OP(_Tpvec, op, intrin, suffix) \
+inline _Tpvec v_##op (const _Tpvec& a, const _Tpvec& b) \
+{ \
+    size_t VLEN = VTraits<_Tpvec>::vlanes(); \
+    union { uint64_t u; VTraits<_Tpvec>::lane_type d; } ones; \
+    ones.u = -1; \
+    auto diff = intrin(a, b, VLEN); \
+    auto z = __riscv_vfmv_v_f_##suffix##m2(0, VLEN); \
+    auto res = __riscv_vfmerge(z, ones.d, diff, VLEN); \
+    return _Tpvec(res); \
+} //TODO
+
+#define OPENCV_HAL_IMPL_RVV_UNSIGNED_CMP(_Tpvec, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, eq, __riscv_vmseq, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, ne, __riscv_vmsne, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, lt, __riscv_vmsltu, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, gt, __riscv_vmsgtu, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, le, __riscv_vmsleu, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, ge, __riscv_vmsgeu, suffix)
+
+#define OPENCV_HAL_IMPL_RVV_SIGNED_CMP(_Tpvec, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, eq, __riscv_vmseq, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, ne, __riscv_vmsne, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, lt, __riscv_vmslt, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, gt, __riscv_vmsgt, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, le, __riscv_vmsle, suffix) \
+OPENCV_HAL_IMPL_RVV_INT_CMP_OP(_Tpvec, ge, __riscv_vmsge, suffix)
+
+#define OPENCV_HAL_IMPL_RVV_FLOAT_CMP(_Tpvec, suffix) \
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP_OP(_Tpvec, eq, __riscv_vmfeq, suffix) \
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP_OP(_Tpvec, ne, __riscv_vmfne, suffix) \
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP_OP(_Tpvec, lt, __riscv_vmflt, suffix) \
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP_OP(_Tpvec, gt, __riscv_vmfgt, suffix) \
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP_OP(_Tpvec, le, __riscv_vmfle, suffix) \
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP_OP(_Tpvec, ge, __riscv_vmfge, suffix)
+
+
+OPENCV_HAL_IMPL_RVV_UNSIGNED_CMP(v_uint8, u8)
+OPENCV_HAL_IMPL_RVV_UNSIGNED_CMP(v_uint16, u16)
+OPENCV_HAL_IMPL_RVV_UNSIGNED_CMP(v_uint32, u32)
+OPENCV_HAL_IMPL_RVV_UNSIGNED_CMP(v_uint64, u64)
+OPENCV_HAL_IMPL_RVV_SIGNED_CMP(v_int8, i8)
+OPENCV_HAL_IMPL_RVV_SIGNED_CMP(v_int16, i16)
+OPENCV_HAL_IMPL_RVV_SIGNED_CMP(v_int32, i32)
+OPENCV_HAL_IMPL_RVV_SIGNED_CMP(v_int64, i64)
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP(v_float32, f32)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_FLOAT_CMP(v_float64, f64)
+#endif
+
+inline v_float32 v_not_nan(const v_float32& a)
+{ return v_eq(a, a); }
+
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_not_nan(const v_float64& a)
+{ return v_eq(a, a); }
+#endif
+
+////////////// Min/Max //////////////
+
+#define OPENCV_HAL_IMPL_RVV_BIN_FUNC(_Tpvec, func, intrin, vl) \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return intrin(a, b, vl); \
+}
+
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_uint8, v_min, __riscv_vminu, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_uint8, v_max, __riscv_vmaxu, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_int8, v_min, __riscv_vmin, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_int8, v_max, __riscv_vmax, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_uint16, v_min, __riscv_vminu, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_uint16, v_max, __riscv_vmaxu, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_int16, v_min, __riscv_vmin, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_int16, v_max, __riscv_vmax, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_uint32, v_min, __riscv_vminu, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_uint32, v_max, __riscv_vmaxu, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_int32, v_min, __riscv_vmin, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_int32, v_max, __riscv_vmax, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_float32, v_min, __riscv_vfmin, VTraits<v_float32>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_float32, v_max, __riscv_vfmax, VTraits<v_float32>::vlanes())
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_float64, v_min, __riscv_vfmin, VTraits<v_float64>::vlanes())
+OPENCV_HAL_IMPL_RVV_BIN_FUNC(v_float64, v_max, __riscv_vfmax, VTraits<v_float64>::vlanes())
+#endif
+
+////////////// Transpose4x4 //////////////
+#define OPENCV_HAL_IMPL_RVV_ZIP4(_Tpvec, _wTpvec, suffix, convert2u, convert) \
+inline void v_zip4(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1) { \
+    int vl = 4; \
+    _wTpvec temp = __riscv_vreinterpret_##suffix##m4(convert2u( \
+        __riscv_vor(__riscv_vzext_vf2(convert(a0), vl), \
+            __riscv_vreinterpret_u64m4(__riscv_vslide1up(__riscv_vreinterpret_u32m4(__riscv_vzext_vf2(convert(a1), vl)), 0, vl*2)), \
+            vl))); \
+    b0 = __riscv_vget_##suffix##m2(temp, 0); \
+    b1 = __riscv_vget_##suffix##m2(__riscv_vrgather(temp, __riscv_vadd(__riscv_vid_v_u32m4(vl), 4, vl)/*{4,5,6,7} */, vl) ,0); \
+}
+
+OPENCV_HAL_IMPL_RVV_ZIP4(v_uint32, vuint32m4_t, u32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_ZIP4(v_int32, vint32m4_t, i32, __riscv_vreinterpret_u32m4, __riscv_vreinterpret_u32m2)
+OPENCV_HAL_IMPL_RVV_ZIP4(v_float32, vfloat32m4_t, f32, __riscv_vreinterpret_u32m4, __riscv_vreinterpret_u32m2)
+
+
+#define OPENCV_HAL_IMPL_RVV_TRANSPOSE4x4(_Tpvec, suffix) \
+inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1, const _Tpvec& a2, const _Tpvec& a3, _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3) { \
+    _Tpvec t0,t1,t2,t3; \
+    v_zip4(a0, a2, t0, t2); \
+    v_zip4(a1, a3, t1, t3); \
+    v_zip4(t0, t1, b0, b1); \
+    v_zip4(t2, t3, b2, b3); \
+}
+
+OPENCV_HAL_IMPL_RVV_TRANSPOSE4x4(v_uint32, u32)
+OPENCV_HAL_IMPL_RVV_TRANSPOSE4x4(v_int32, i32)
+OPENCV_HAL_IMPL_RVV_TRANSPOSE4x4(v_float32, f32)
+
+////////////// Reduce //////////////
+
+#define OPENCV_HAL_IMPL_RVV_REDUCE_SUM(_Tpvec, _wTpvec, _nwTpvec, scalartype, wsuffix, vl, red) \
+inline scalartype v_reduce_sum(const _Tpvec& a)  \
+{ \
+    _nwTpvec zero = __riscv_vmv_v_x_##wsuffix##m1(0, vl); \
+    _nwTpvec res = __riscv_vmv_v_x_##wsuffix##m1(0, vl); \
+    res = __riscv_v##red(a, zero, vl); \
+    return (scalartype)__riscv_vmv_x(res); \
+}
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_uint8, v_uint16, vuint16m1_t, unsigned, u16, VTraits<v_uint8>::vlanes(), wredsumu)
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_int8, v_int16, vint16m1_t, int, i16, VTraits<v_int8>::vlanes(), wredsum)
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_uint16, v_uint32, vuint32m1_t, unsigned, u32, VTraits<v_uint16>::vlanes(), wredsumu)
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_int16, v_int32, vint32m1_t, int, i32, VTraits<v_int16>::vlanes(), wredsum)
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_uint32, v_uint64, vuint64m1_t, unsigned, u64, VTraits<v_uint32>::vlanes(), wredsumu)
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_int32, v_int64, vint64m1_t, int, i64, VTraits<v_int32>::vlanes(), wredsum)
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_uint64, v_uint64, vuint64m1_t, uint64, u64, VTraits<v_uint64>::vlanes(), redsum)
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM(v_int64, v_int64, vint64m1_t, int64, i64, VTraits<v_int64>::vlanes(), redsum)
+
+
+#define OPENCV_HAL_IMPL_RVV_REDUCE_SUM_FP(_Tpvec, _wTpvec, _nwTpvec, scalartype, wsuffix, vl) \
+inline scalartype v_reduce_sum(const _Tpvec& a)  \
+{ \
+    _nwTpvec zero = __riscv_vfmv_v_f_##wsuffix##m1(0, vl); \
+    _nwTpvec res = __riscv_vfmv_v_f_##wsuffix##m1(0, vl); \
+    res = __riscv_vfredusum(a, zero, vl); \
+    return (scalartype)__riscv_vfmv_f(res); \
+}
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM_FP(v_float32, v_float32, vfloat32m1_t, float, f32, VTraits<v_float32>::vlanes())
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_REDUCE_SUM_FP(v_float64, v_float64, vfloat64m1_t, float, f64, VTraits<v_float64>::vlanes())
+#endif
+
+#define OPENCV_HAL_IMPL_RVV_REDUCE(_Tpvec, _nTpvec, func, scalartype, suffix, vl, red) \
+inline scalartype v_reduce_##func(const _Tpvec& a)  \
+{ \
+    _nTpvec narrowM1 = __riscv_vlmul_trunc_##suffix##m1(a); \
+    return (scalartype)__riscv_vmv_x(__riscv_v##red(a, narrowM1, vl)); \
+}
+
+#define OPENCV_HAL_IMPL_RVV_REDUCE_FP(_Tpvec, _nTpvec, func, scalartype, suffix, vl, red) \
+inline scalartype v_reduce_##func(const _Tpvec& a)  \
+{ \
+    _nTpvec narrowM1 = __riscv_vlmul_trunc_##suffix##m1(a); \
+    return (scalartype)__riscv_vfmv_f(__riscv_v##red(a, narrowM1, vl)); \
+}
+
+OPENCV_HAL_IMPL_RVV_REDUCE(v_uint8, vuint8m1_t, min, uchar, u8, VTraits<v_uint8>::vlanes(), redminu)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_int8, vint8m1_t, min, schar, i8, VTraits<v_int8>::vlanes(), redmin)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_uint16, vuint16m1_t, min, ushort, u16, VTraits<v_uint16>::vlanes(), redminu)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_int16, vint16m1_t, min, short, i16, VTraits<v_int16>::vlanes(), redmin)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_uint32, vuint32m1_t, min, unsigned, u32, VTraits<v_uint32>::vlanes(), redminu)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_int32, vint32m1_t, min, int, i32, VTraits<v_int32>::vlanes(), redmin)
+OPENCV_HAL_IMPL_RVV_REDUCE_FP(v_float32, vfloat32m1_t, min, float, f32, VTraits<v_float32>::vlanes(), fredmin)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_uint8,  vuint8m1_t, max, uchar, u8, VTraits<v_uint8>::vlanes(), redmaxu)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_int8,  vint8m1_t, max, schar, i8, VTraits<v_int8>::vlanes(), redmax)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_uint16,  vuint16m1_t, max, ushort, u16, VTraits<v_uint16>::vlanes(), redmaxu)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_int16,  vint16m1_t, max, short, i16, VTraits<v_int16>::vlanes(), redmax)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_uint32,  vuint32m1_t, max, unsigned, u32, VTraits<v_uint32>::vlanes(), redmaxu)
+OPENCV_HAL_IMPL_RVV_REDUCE(v_int32,  vint32m1_t, max, int, i32, VTraits<v_int32>::vlanes(), redmax)
+OPENCV_HAL_IMPL_RVV_REDUCE_FP(v_float32,  vfloat32m1_t, max, float, f32, VTraits<v_float32>::vlanes(), fredmax)
+
+inline v_float32 v_reduce_sum4(const v_float32& a, const v_float32& b,
+                                 const v_float32& c, const v_float32& d)
+{
+    // 0000 1111 2222 3333 ....
+    vuint64m4_t vid1 = __riscv_vid_v_u64m4(VTraits<vuint32m2_t>::vlanes());
+    vuint16m4_t t1 = __riscv_vreinterpret_u16m4(vid1);
+    vuint16m4_t t2 = __riscv_vslide1up(t1, 0, VTraits<vuint8m2_t>::vlanes());
+    vuint16m4_t t3 = __riscv_vslide1up(t2, 0, VTraits<vuint8m2_t>::vlanes());
+    vuint16m4_t t4 = __riscv_vslide1up(t3, 0, VTraits<vuint8m2_t>::vlanes());
+    t1 = __riscv_vor(
+        __riscv_vor(t1, t2, VTraits<vuint8m2_t>::vlanes()),
+        __riscv_vor(t3, t4, VTraits<vuint8m2_t>::vlanes()),
+        VTraits<vuint8m2_t>::vlanes()
+    );
+
+    // index for transpose4X4
+    vuint16m4_t vidx0 = __riscv_vmul(t1, 12, VTraits<vuint8m2_t>::vlanes());
+    vidx0 = __riscv_vadd(vidx0, __riscv_vid_v_u16m4(VTraits<vuint8m2_t>::vlanes()), VTraits<vuint8m2_t>::vlanes());
+    vuint16m4_t vidx1 = __riscv_vadd(vidx0, 4, VTraits<vuint8m2_t>::vlanes());
+    vuint16m4_t vidx2 = __riscv_vadd(vidx0, 8, VTraits<vuint8m2_t>::vlanes());
+    vuint16m4_t vidx3 = __riscv_vadd(vidx0, 12, VTraits<vuint8m2_t>::vlanes());
+
+    // zip
+    vuint32m4_t tempA = __riscv_vreinterpret_u32m4( \
+        __riscv_vor(__riscv_vzext_vf2(__riscv_vreinterpret_u32m2(a), VTraits<vuint16m2_t>::vlanes()), \
+            __riscv_vreinterpret_u64m4(__riscv_vslide1up(__riscv_vreinterpret_u32m4(__riscv_vzext_vf2(__riscv_vreinterpret_u32m2(c), VTraits<vuint16m2_t>::vlanes())), 0, VTraits<vuint16m2_t>::vlanes())), \
+            VTraits<vuint32m2_t>::vlanes())); \
+    vuint32m4_t tempB = __riscv_vreinterpret_u32m4( \
+        __riscv_vor(__riscv_vzext_vf2(__riscv_vreinterpret_u32m2(b), VTraits<vuint16m2_t>::vlanes()), \
+            __riscv_vreinterpret_u64m4(__riscv_vslide1up(__riscv_vreinterpret_u32m4(__riscv_vzext_vf2(__riscv_vreinterpret_u32m2(d), VTraits<vuint16m2_t>::vlanes())), 0, VTraits<vuint16m2_t>::vlanes())), \
+            VTraits<vuint32m2_t>::vlanes())); \
+    vfloat32m8_t temp = __riscv_vreinterpret_f32m8(__riscv_vreinterpret_u32m8( \
+        __riscv_vor(__riscv_vzext_vf2(tempA, VTraits<vuint8m2_t>::vlanes()), \
+            __riscv_vreinterpret_u64m8(__riscv_vslide1up(__riscv_vreinterpret_u32m8(__riscv_vzext_vf2(tempB, VTraits<vuint8m2_t>::vlanes())), 0, VTraits<vuint8m2_t>::vlanes())), \
+            VTraits<vuint16m2_t>::vlanes())));
+
+    // transpose
+    vfloat32m2_t b0 = __riscv_vlmul_trunc_f32m2(__riscv_vrgatherei16(temp, vidx0, VTraits<vuint8m2_t>::vlanes()));
+    vfloat32m2_t b1 = __riscv_vlmul_trunc_f32m2(__riscv_vrgatherei16(temp, vidx1, VTraits<vuint8m2_t>::vlanes()));
+    vfloat32m2_t b2 = __riscv_vlmul_trunc_f32m2(__riscv_vrgatherei16(temp, vidx2, VTraits<vuint8m2_t>::vlanes()));
+    vfloat32m2_t b3 = __riscv_vlmul_trunc_f32m2(__riscv_vrgatherei16(temp, vidx3, VTraits<vuint8m2_t>::vlanes()));
+
+    // vector add
+    v_float32 res = __riscv_vfadd(
+        __riscv_vfadd(b0, b1, VTraits<vfloat32m2_t>::vlanes()),
+        __riscv_vfadd(b2, b3, VTraits<vfloat32m2_t>::vlanes()),
+        VTraits<vfloat32m2_t>::vlanes()
+    );
+    return res;
+}
+
+////////////// Square-Root //////////////
+
+inline v_float32 v_sqrt(const v_float32& x)
+{
+    return __riscv_vfsqrt(x, VTraits<v_float32>::vlanes());
+}
+
+inline v_float32 v_invsqrt(const v_float32& x)
+{
+    v_float32 one = v_setall_f32(1.0f);
+    return v_div(one, v_sqrt(x));
+}
+
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_sqrt(const v_float64& x)
+{
+    return __riscv_vfsqrt(x, VTraits<v_float64>::vlanes());
+}
+
+inline v_float64 v_invsqrt(const v_float64& x)
+{
+    v_float64 one = v_setall_f64(1.0f);
+    return v_div(one, v_sqrt(x));
+}
+#endif
+
+inline v_float32 v_magnitude(const v_float32& a, const v_float32& b)
+{
+    v_float32 x = __riscv_vfmacc(__riscv_vfmul(a, a, VTraits<v_float32>::vlanes()), b, b, VTraits<v_float32>::vlanes());
+    return v_sqrt(x);
+}
+
+inline v_float32 v_sqr_magnitude(const v_float32& a, const v_float32& b)
+{
+    return v_float32(__riscv_vfmacc(__riscv_vfmul(a, a, VTraits<v_float32>::vlanes()), b, b, VTraits<v_float32>::vlanes()));
+}
+
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_magnitude(const v_float64& a, const v_float64& b)
+{
+    v_float64 x = __riscv_vfmacc(__riscv_vfmul(a, a, VTraits<v_float64>::vlanes()), b, b, VTraits<v_float64>::vlanes());
+    return v_sqrt(x);
+}
+
+inline v_float64 v_sqr_magnitude(const v_float64& a, const v_float64& b)
+{
+    return __riscv_vfmacc(__riscv_vfmul(a, a, VTraits<v_float64>::vlanes()), b, b, VTraits<v_float64>::vlanes());
+}
+#endif
+
+////////////// Multiply-Add //////////////
+
+inline v_float32 v_fma(const v_float32& a, const v_float32& b, const v_float32& c)
+{
+    return __riscv_vfmacc(c, a, b, VTraits<v_float32>::vlanes());
+}
+inline v_int32 v_fma(const v_int32& a, const v_int32& b, const v_int32& c)
+{
+    return __riscv_vmacc(c, a, b, VTraits<v_float32>::vlanes());
+}
+
+inline v_float32 v_muladd(const v_float32& a, const v_float32& b, const v_float32& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_int32 v_muladd(const v_int32& a, const v_int32& b, const v_int32& c)
+{
+    return v_fma(a, b, c);
+}
+
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_fma(const v_float64& a, const v_float64& b, const v_float64& c)
+{
+    return __riscv_vfmacc_vv_f64m2(c, a, b, VTraits<v_float64>::vlanes());
+}
+
+inline v_float64 v_muladd(const v_float64& a, const v_float64& b, const v_float64& c)
+{
+    return v_fma(a, b, c);
+}
+#endif
+
+////////////// Check all/any //////////////
+
+#define OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(_Tpvec, vl) \
+inline bool v_check_all(const _Tpvec& a) \
+{ \
+    return (int)__riscv_vcpop(__riscv_vmslt(a, 0, vl), vl) == vl; \
+} \
+inline bool v_check_any(const _Tpvec& a) \
+{ \
+    return (int)__riscv_vcpop(__riscv_vmslt(a, 0, vl), vl) != 0; \
+}
+
+OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_int8, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_int16, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_int32, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_CHECK_ALLANY(v_int64, VTraits<v_int64>::vlanes())
+
+
+inline bool v_check_all(const v_uint8& a)
+{ return v_check_all(v_reinterpret_as_s8(a)); }
+inline bool v_check_any(const v_uint8& a)
+{ return v_check_any(v_reinterpret_as_s8(a)); }
+
+inline bool v_check_all(const v_uint16& a)
+{ return v_check_all(v_reinterpret_as_s16(a)); }
+inline bool v_check_any(const v_uint16& a)
+{ return v_check_any(v_reinterpret_as_s16(a)); }
+
+inline bool v_check_all(const v_uint32& a)
+{ return v_check_all(v_reinterpret_as_s32(a)); }
+inline bool v_check_any(const v_uint32& a)
+{ return v_check_any(v_reinterpret_as_s32(a)); }
+
+inline bool v_check_all(const v_float32& a)
+{ return v_check_all(v_reinterpret_as_s32(a)); }
+inline bool v_check_any(const v_float32& a)
+{ return v_check_any(v_reinterpret_as_s32(a)); }
+
+inline bool v_check_all(const v_uint64& a)
+{ return v_check_all(v_reinterpret_as_s64(a)); }
+inline bool v_check_any(const v_uint64& a)
+{ return v_check_any(v_reinterpret_as_s64(a)); }
+
+#if CV_SIMD_SCALABLE_64F
+inline bool v_check_all(const v_float64& a)
+{ return v_check_all(v_reinterpret_as_s64(a)); }
+inline bool v_check_any(const v_float64& a)
+{ return v_check_any(v_reinterpret_as_s64(a)); }
+#endif
+
+////////////// abs //////////////
+
+#define OPENCV_HAL_IMPL_RVV_ABSDIFF(_Tpvec, abs) \
+inline _Tpvec v_##abs(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return v_sub(v_max(a, b), v_min(a, b)); \
+}
+
+OPENCV_HAL_IMPL_RVV_ABSDIFF(v_uint8, absdiff)
+OPENCV_HAL_IMPL_RVV_ABSDIFF(v_uint16, absdiff)
+OPENCV_HAL_IMPL_RVV_ABSDIFF(v_uint32, absdiff)
+OPENCV_HAL_IMPL_RVV_ABSDIFF(v_float32, absdiff)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_ABSDIFF(v_float64, absdiff)
+#endif
+OPENCV_HAL_IMPL_RVV_ABSDIFF(v_int8, absdiffs)
+OPENCV_HAL_IMPL_RVV_ABSDIFF(v_int16, absdiffs)
+
+#define OPENCV_HAL_IMPL_RVV_ABSDIFF_S(_Tpvec, _rTpvec, width) \
+inline _rTpvec v_absdiff(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vnclipu(__riscv_vreinterpret_u##width##m4(__riscv_vwsub_vv(v_max(a, b), v_min(a, b), VTraits<_Tpvec>::vlanes())), 0, 0, VTraits<_Tpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int8, v_uint8, 16)
+OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int16, v_uint16, 32)
+OPENCV_HAL_IMPL_RVV_ABSDIFF_S(v_int32, v_uint32, 64)
+
+#define OPENCV_HAL_IMPL_RVV_ABS(_Tprvec, _Tpvec, suffix) \
+inline _Tprvec v_abs(const _Tpvec& a) \
+{ \
+    return v_absdiff(a, v_setzero_##suffix()); \
+}
+
+OPENCV_HAL_IMPL_RVV_ABS(v_uint8, v_int8, s8)
+OPENCV_HAL_IMPL_RVV_ABS(v_uint16, v_int16, s16)
+OPENCV_HAL_IMPL_RVV_ABS(v_uint32, v_int32, s32)
+OPENCV_HAL_IMPL_RVV_ABS(v_float32, v_float32, f32)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_ABS(v_float64, v_float64, f64)
+#endif
+
+
+#define OPENCV_HAL_IMPL_RVV_REDUCE_SAD(_Tpvec, scalartype) \
+inline scalartype v_reduce_sad(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return v_reduce_sum(v_absdiff(a, b)); \
+}
+
+OPENCV_HAL_IMPL_RVV_REDUCE_SAD(v_uint8, unsigned)
+OPENCV_HAL_IMPL_RVV_REDUCE_SAD(v_int8, unsigned)
+OPENCV_HAL_IMPL_RVV_REDUCE_SAD(v_uint16, unsigned)
+OPENCV_HAL_IMPL_RVV_REDUCE_SAD(v_int16, unsigned)
+OPENCV_HAL_IMPL_RVV_REDUCE_SAD(v_uint32, unsigned)
+OPENCV_HAL_IMPL_RVV_REDUCE_SAD(v_int32, unsigned)
+OPENCV_HAL_IMPL_RVV_REDUCE_SAD(v_float32, float)
+
+////////////// Select //////////////
+
+#define OPENCV_HAL_IMPL_RVV_SELECT(_Tpvec, vl) \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vmerge(b, a, __riscv_vmsne(mask, 0, vl), vl); \
+}
+
+OPENCV_HAL_IMPL_RVV_SELECT(v_uint8, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_SELECT(v_uint16, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_SELECT(v_uint32, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_SELECT(v_int8, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_SELECT(v_int16, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_SELECT(v_int32, VTraits<v_int32>::vlanes())
+
+inline v_float32 v_select(const v_float32& mask, const v_float32& a, const v_float32& b) \
+{ \
+    return __riscv_vmerge(b, a, __riscv_vmfne(mask, 0, VTraits<v_float32>::vlanes()), VTraits<v_float32>::vlanes()); \
+}
+
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_select(const v_float64& mask, const v_float64& a, const v_float64& b) \
+{ \
+    return __riscv_vmerge(b, a, __riscv_vmfne(mask, 0, VTraits<v_float64>::vlanes()), VTraits<v_float64>::vlanes()); \
+}
+#endif
+
+////////////// Rotate shift //////////////
+
+#define OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(_Tpvec, suffix, vl) \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a) \
+{ \
+    return __riscv_vslidedown(a, n, vl); \
+} \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a) \
+{ \
+    return __riscv_vslideup(__riscv_vmv_v_x_##suffix##m2(0, vl), a, n, vl); \
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a) \
+{ return a; } \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vslideup(__riscv_vslidedown(a, n, vl), b, VTraits<_Tpvec>::vlanes() - n, vl); \
+} \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vslideup(__riscv_vslidedown(b, VTraits<_Tpvec>::vlanes() - n, vl), a, n, vl); \
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a, const _Tpvec& b) \
+{ CV_UNUSED(b); return a; }
+
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_uint8, u8, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_int8, i8, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_uint16, u16, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_int16, i16,  VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_uint32, u32, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_int32, i32, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_uint64, u64, VTraits<v_uint64>::vlanes())
+OPENCV_HAL_IMPL_RVV_ROTATE_INTEGER(v_int64, i64, VTraits<v_int64>::vlanes())
+
+#define OPENCV_HAL_IMPL_RVV_ROTATE_FP(_Tpvec, suffix, vl) \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a) \
+{ \
+    return __riscv_vslidedown(a, n, vl); \
+} \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a) \
+{ \
+    return __riscv_vslideup(__riscv_vfmv_v_f_##suffix##m2(0, vl), a, n, vl); \
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a) \
+{ return a; } \
+template<int n> inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vslideup(__riscv_vslidedown(a, n, vl), b, VTraits<_Tpvec>::vlanes() - n, vl); \
+} \
+template<int n> inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vslideup(__riscv_vslidedown(b, VTraits<_Tpvec>::vlanes() - n, vl), a, n, vl); \
+} \
+template<> inline _Tpvec v_rotate_left<0>(const _Tpvec& a, const _Tpvec& b) \
+{ CV_UNUSED(b); return a; }
+
+OPENCV_HAL_IMPL_RVV_ROTATE_FP(v_float32, f32, VTraits<v_float32>::vlanes())
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_ROTATE_FP(v_float64, f64,  VTraits<v_float64>::vlanes())
+#endif
+
+////////////// Convert to float //////////////
+inline v_float32 v_cvt_f32(const v_int32& a)
+{
+    return __riscv_vfcvt_f_x_v_f32m2(a, VTraits<v_float32>::vlanes());
+}
+
+#if CV_SIMD_SCALABLE_64F
+inline v_float32 v_cvt_f32(const v_float64& a)
+{
+    return __riscv_vfncvt_f(__riscv_vlmul_ext_f64m4(a), VTraits<v_float64>::vlanes());
+}
+
+inline v_float32 v_cvt_f32(const v_float64& a, const v_float64& b)
+{
+    return __riscv_vfncvt_f(__riscv_vset(__riscv_vlmul_ext_f64m4(a),1,b), VTraits<v_float32>::vlanes());
+}
+
+inline v_float64 v_cvt_f64(const v_int32& a)
+{
+    return __riscv_vget_f64m2(__riscv_vfwcvt_f(a, VTraits<v_int32>::vlanes()), 0);
+}
+
+inline v_float64 v_cvt_f64_high(const v_int32& a)
+{
+    return __riscv_vget_f64m2(__riscv_vfwcvt_f(a, VTraits<v_int32>::vlanes()), 1);
+}
+
+inline v_float64 v_cvt_f64(const v_float32& a)
+{
+    return __riscv_vget_f64m2(__riscv_vfwcvt_f(a, VTraits<v_float32>::vlanes()), 0);
+}
+
+inline v_float64 v_cvt_f64_high(const v_float32& a)
+{
+    return __riscv_vget_f64m2(__riscv_vfwcvt_f(a, VTraits<v_float32>::vlanes()), 1);
+}
+
+inline v_float64 v_cvt_f64(const v_int64& a)
+{
+    return __riscv_vfcvt_f(a, VTraits<v_int64>::vlanes());
+}
+#endif
+
+//////////// Broadcast //////////////
+
+#define OPENCV_HAL_IMPL_RVV_BROADCAST(_Tpvec, suffix) \
+template<int s = 0> inline _Tpvec v_broadcast_element(_Tpvec v, int i = s) \
+{ \
+    return v_setall_##suffix(v_extract_n(v, i)); \
+} \
+inline _Tpvec v_broadcast_highest(_Tpvec v) \
+{ \
+    return v_setall_##suffix(v_extract_n(v, VTraits<_Tpvec>::vlanes()-1)); \
+}
+
+OPENCV_HAL_IMPL_RVV_BROADCAST(v_uint32, u32)
+OPENCV_HAL_IMPL_RVV_BROADCAST(v_int32, s32)
+OPENCV_HAL_IMPL_RVV_BROADCAST(v_float32, f32)
+
+
+////////////// Reverse //////////////
+#define OPENCV_HAL_IMPL_RVV_REVERSE(_Tpvec, width) \
+inline _Tpvec v_reverse(const _Tpvec& a)  \
+{ \
+    vuint##width##m2_t vidx = __riscv_vrsub(__riscv_vid_v_u##width##m2(VTraits<_Tpvec>::vlanes()), VTraits<_Tpvec>::vlanes()-1, VTraits<_Tpvec>::vlanes()); \
+    return __riscv_vrgather(a, vidx, VTraits<_Tpvec>::vlanes()); \
+}
+OPENCV_HAL_IMPL_RVV_REVERSE(v_uint8, 8)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_int8, 8)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_uint16, 16)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_int16, 16)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_uint32, 32)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_int32, 32)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_float32, 32)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_uint64, 64)
+OPENCV_HAL_IMPL_RVV_REVERSE(v_int64, 64)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_REVERSE(v_float64, 64)
+#endif
+
+//////////// Value reordering ////////////
+
+#define OPENCV_HAL_IMPL_RVV_EXPAND(_Tp, _Tpwvec, _Tpwvec_m2, _Tpvec, width, suffix, suffix2, cvt) \
+inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
+{ \
+    _Tpwvec_m2 temp = cvt(a, VTraits<_Tpvec>::vlanes()); \
+    b0 = __riscv_vget_##suffix##m2(temp, 0); \
+    b1 = __riscv_vget_##suffix##m2(temp, 1); \
+} \
+inline _Tpwvec v_expand_low(const _Tpvec& a) \
+{ \
+    _Tpwvec_m2 temp = cvt(a, VTraits<_Tpvec>::vlanes()); \
+    return __riscv_vget_##suffix##m2(temp, 0); \
+} \
+inline _Tpwvec v_expand_high(const _Tpvec& a) \
+{ \
+    _Tpwvec_m2 temp = cvt(a, VTraits<_Tpvec>::vlanes()); \
+    return __riscv_vget_##suffix##m2(temp, 1); \
+} \
+inline _Tpwvec v_load_expand(const _Tp* ptr) \
+{ \
+    return cvt(__riscv_vle##width##_v_##suffix2##m1(ptr, VTraits<_Tpvec>::vlanes()), VTraits<_Tpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_EXPAND(uchar, v_uint16, vuint16m4_t, v_uint8, 8, u16, u8, __riscv_vwcvtu_x)
+OPENCV_HAL_IMPL_RVV_EXPAND(schar, v_int16, vint16m4_t, v_int8, 8, i16, i8, __riscv_vwcvt_x)
+OPENCV_HAL_IMPL_RVV_EXPAND(ushort, v_uint32, vuint32m4_t, v_uint16, 16, u32, u16, __riscv_vwcvtu_x)
+OPENCV_HAL_IMPL_RVV_EXPAND(short, v_int32, vint32m4_t, v_int16, 16, i32, i16, __riscv_vwcvt_x)
+OPENCV_HAL_IMPL_RVV_EXPAND(uint, v_uint64, vuint64m4_t, v_uint32, 32, u64, u32, __riscv_vwcvtu_x)
+OPENCV_HAL_IMPL_RVV_EXPAND(int, v_int64, vint64m4_t, v_int32, 32, i64, i32, __riscv_vwcvt_x)
+
+inline v_uint32 v_load_expand_q(const uchar* ptr)
+{
+    return __riscv_vwcvtu_x(__riscv_vwcvtu_x(__riscv_vle8_v_u8mf2(ptr, VTraits<v_uint32>::vlanes()), VTraits<v_uint32>::vlanes()), VTraits<v_uint32>::vlanes());
+}
+
+inline v_int32 v_load_expand_q(const schar* ptr)
+{
+    return __riscv_vwcvt_x(__riscv_vwcvt_x(__riscv_vle8_v_i8mf2(ptr, VTraits<v_int32>::vlanes()), VTraits<v_int32>::vlanes()), VTraits<v_int32>::vlanes());
+}
+
+#define OPENCV_HAL_IMPL_RVV_PACK(_Tpvec, _Tp, _wTpvec, hwidth, hsuffix, suffix, rshr, shr) \
+inline _Tpvec v_pack(const _wTpvec& a, const _wTpvec& b) \
+{ \
+    return shr(__riscv_vset(__riscv_vlmul_ext_##suffix##m4(a), 1, b), 0, 0, VTraits<_Tpvec>::vlanes()); \
+} \
+inline void v_pack_store(_Tp* ptr, const _wTpvec& a) \
+{ \
+    __riscv_vse##hwidth##_v_##hsuffix##m1(ptr, shr(a, 0, 0, VTraits<_Tpvec>::vlanes()), VTraits<_wTpvec>::vlanes()); \
+} \
+template<int n = 0> inline \
+_Tpvec v_rshr_pack(const _wTpvec& a, const _wTpvec& b, int N = n) \
+{ \
+    return rshr(__riscv_vset(__riscv_vlmul_ext_##suffix##m4(a), 1, b), N, 0, VTraits<_Tpvec>::vlanes()); \
+} \
+template<int n = 0> inline \
+void v_rshr_pack_store(_Tp* ptr, const _wTpvec& a, int N = n) \
+{ \
+    __riscv_vse##hwidth##_v_##hsuffix##m1(ptr, rshr(a, N, 0, VTraits<_Tpvec>::vlanes()), VTraits<_wTpvec>::vlanes()); \
+}
+
+#define OPENCV_HAL_IMPL_RVV_PACK_32(_Tpvec, _Tp, _wTpvec, hwidth, hsuffix, suffix, rshr, shr) \
+inline _Tpvec v_pack(const _wTpvec& a, const _wTpvec& b) \
+{ \
+    return shr(__riscv_vset(__riscv_vlmul_ext_##suffix##m4(a), 1, b), 0, VTraits<_Tpvec>::vlanes()); \
+} \
+inline void v_pack_store(_Tp* ptr, const _wTpvec& a) \
+{ \
+    __riscv_vse##hwidth##_v_##hsuffix##m1(ptr, shr(a, 0, VTraits<_Tpvec>::vlanes()), VTraits<_wTpvec>::vlanes()); \
+} \
+template<int n = 0> inline \
+_Tpvec v_rshr_pack(const _wTpvec& a, const _wTpvec& b, int N = n) \
+{ \
+    return rshr(__riscv_vset(__riscv_vlmul_ext_##suffix##m4(a), 1, b), N, 0, VTraits<_Tpvec>::vlanes()); \
+} \
+template<int n = 0> inline \
+void v_rshr_pack_store(_Tp* ptr, const _wTpvec& a, int N = n) \
+{ \
+    __riscv_vse##hwidth##_v_##hsuffix##m1(ptr, rshr(a, N, 0, VTraits<_Tpvec>::vlanes()), VTraits<_wTpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_PACK(v_uint8, uchar, v_uint16, 8, u8, u16, __riscv_vnclipu, __riscv_vnclipu)
+OPENCV_HAL_IMPL_RVV_PACK(v_int8, schar, v_int16, 8,  i8, i16, __riscv_vnclip, __riscv_vnclip)
+OPENCV_HAL_IMPL_RVV_PACK(v_uint16, ushort, v_uint32, 16, u16, u32, __riscv_vnclipu, __riscv_vnclipu)
+OPENCV_HAL_IMPL_RVV_PACK(v_int16, short, v_int32, 16, i16, i32, __riscv_vnclip, __riscv_vnclip)
+OPENCV_HAL_IMPL_RVV_PACK_32(v_uint32, unsigned, v_uint64, 32, u32, u64, __riscv_vnclipu, __riscv_vnsrl)
+OPENCV_HAL_IMPL_RVV_PACK_32(v_int32, int, v_int64, 32, i32, i64, __riscv_vnclip, __riscv_vnsra)
+
+#define OPENCV_HAL_IMPL_RVV_PACK_U(_Tpvec, _Tp, _wTpvec, _wTp, hwidth, width, hsuffix, suffix, cast, hvl, vl) \
+inline _Tpvec v_pack_u(const _wTpvec& a, const _wTpvec& b) \
+{ \
+    return __riscv_vnclipu(cast(__riscv_vmax(__riscv_vset(__riscv_vlmul_ext_##suffix##m4(a), 1, b), 0, vl)), 0, 0, vl); \
+} \
+inline void v_pack_u_store(_Tp* ptr, const _wTpvec& a) \
+{ \
+    __riscv_vse##hwidth##_v_##hsuffix##m1(ptr, __riscv_vnclipu(__riscv_vreinterpret_u##width##m2(__riscv_vmax(a, 0, vl)), 0, 0, vl), hvl); \
+} \
+template<int N = 0> inline \
+_Tpvec v_rshr_pack_u(const _wTpvec& a, const _wTpvec& b, int n = N) \
+{ \
+    return __riscv_vnclipu(cast(__riscv_vmax(__riscv_vset(__riscv_vlmul_ext_##suffix##m4(a), 1, b), 0, vl)), n, 0, vl); \
+} \
+template<int N = 0> inline \
+void v_rshr_pack_u_store(_Tp* ptr, const _wTpvec& a, int n = N) \
+{ \
+    __riscv_vse##hwidth##_v_##hsuffix##m1(ptr, __riscv_vnclipu(__riscv_vreinterpret_u##width##m2(__riscv_vmax(a, 0, vl)), n, 0, vl), hvl); \
+}
+
+OPENCV_HAL_IMPL_RVV_PACK_U(v_uint8, uchar, v_int16, short, 8, 16, u8, i16, __riscv_vreinterpret_v_i16m4_u16m4, VTraits<v_int16>::vlanes(), VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_PACK_U(v_uint16, ushort, v_int32, int, 16, 32, u16, i32,  __riscv_vreinterpret_v_i32m4_u32m4, VTraits<v_int32>::vlanes(), VTraits<v_uint16>::vlanes())
+
+
+/* void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1)
+  a0 = {A1 A2 A3 A4}
+  a1 = {B1 B2 B3 B4}
+---------------
+  {A1 B1 A2 B2} and {A3 B3 A4 B4}
+*/
+
+#define OPENCV_HAL_IMPL_RVV_ZIP(_Tpvec, _wTpvec, suffix, width, width2, convert2um2, convert2um1) \
+inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1) { \
+    _wTpvec temp = __riscv_vreinterpret_##suffix##m4(convert2um2( \
+        __riscv_vor(__riscv_vzext_vf2(convert2um1(a0), VTraits<_Tpvec>::vlanes()*2), \
+            __riscv_vreinterpret_u##width2##m4(__riscv_vslide1up(__riscv_vreinterpret_u##width##m4(__riscv_vzext_vf2(convert2um1(a1), VTraits<_Tpvec>::vlanes()*2)), 0, VTraits<_Tpvec>::vlanes()*2)), \
+            VTraits<_Tpvec>::vlanes()))); \
+    b0 = __riscv_vget_##suffix##m2(temp, 0); \
+    b1 = __riscv_vget_##suffix##m2(temp, 1); \
+}
+OPENCV_HAL_IMPL_RVV_ZIP(v_uint8, vuint8m4_t, u8, 8, 16, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_ZIP(v_int8, vint8m4_t, i8, 8, 16, __riscv_vreinterpret_u8m4, __riscv_vreinterpret_u8m2)
+OPENCV_HAL_IMPL_RVV_ZIP(v_uint16, vuint16m4_t, u16, 16, 32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_ZIP(v_int16, vint16m4_t, i16, 16, 32, __riscv_vreinterpret_u16m4, __riscv_vreinterpret_u16m2)
+OPENCV_HAL_IMPL_RVV_ZIP(v_uint32, vuint32m4_t, u32, 32, 64, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_ZIP(v_int32, vint32m4_t, i32, 32, 64, __riscv_vreinterpret_u32m4, __riscv_vreinterpret_u32m2)
+OPENCV_HAL_IMPL_RVV_ZIP(v_float32, vfloat32m4_t, f32, 32, 64, __riscv_vreinterpret_u32m4, __riscv_vreinterpret_u32m2)
+
+#if CV_SIMD_SCALABLE_64F
+inline void v_zip(const v_float64& a0, const v_float64& a1, v_float64& b0, v_float64& b1) { \
+    vuint16mf2_t idx0 = __riscv_vid_v_u16mf2(VTraits<v_float64>::vlanes());
+    vuint16mf2_t idx1 = __riscv_vadd(idx0, VTraits<v_float64>::vlanes(), VTraits<v_float64>::vlanes());
+    vuint16m1_t idx = __riscv_vreinterpret_u16m1(( \
+        __riscv_vor(__riscv_vzext_vf2(idx0, VTraits<v_float64>::vlanes()), \
+            __riscv_vreinterpret_u32m1(__riscv_vslide1up(__riscv_vreinterpret_u16m1(__riscv_vzext_vf2(idx1, VTraits<v_float64>::vlanes())), 0, VTraits<v_uint32>::vlanes())), \
+            VTraits<v_uint32>::vlanes())));
+#if 0
+    vfloat64m4_t temp = __riscv_vcreate_v_f64m2_f64m4(a0, a1);
+#else // TODO: clean up when RVV Intrinsic is frozen.
+    vfloat64m4_t temp = __riscv_vlmul_ext_f64m4(a0);
+    temp = __riscv_vset(temp, 1, a1);
+#endif
+    temp = __riscv_vrgatherei16(temp, idx, VTraits<v_float64>::vlanes()*2);
+    b0 = __riscv_vget_f64m2(temp, 0); \
+    b1 = __riscv_vget_f64m2(temp, 1); \
+}
+#endif
+
+#define OPENCV_HAL_IMPL_RVV_UNPACKS(_Tpvec, width) \
+inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vslideup(a, b, VTraits<_Tpvec>::vlanes()/2, VTraits<_Tpvec>::vlanes());\
+} \
+inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return __riscv_vslideup( \
+            __riscv_vslidedown(a, VTraits<_Tpvec>::vlanes()/2, VTraits<_Tpvec>::vlanes()), \
+            __riscv_vslidedown(b, VTraits<_Tpvec>::vlanes()/2, VTraits<_Tpvec>::vlanes()), \
+            VTraits<_Tpvec>::vlanes()/2, \
+            VTraits<_Tpvec>::vlanes()); \
+} \
+inline void v_recombine(const _Tpvec& a, const _Tpvec& b, _Tpvec& c, _Tpvec& d) \
+{ \
+    c = v_combine_low(a, b); \
+    d = v_combine_high(a, b); \
+}
+
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_uint8, 8)
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_int8, 8)
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_uint16, 16)
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_int16, 16)
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_uint32, 32)
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_int32, 32)
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_float32, 32)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_UNPACKS(v_float64, 64)
+#endif
+
+#define OPENCV_HAL_IMPL_RVV_INTERLEAVED(_Tpvec, _Tp, suffix, width, hwidth, vl) \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b) \
+{ \
+    a = __riscv_vlse##width##_v_##suffix##m2(ptr  , sizeof(_Tp)*2, VTraits<v_##_Tpvec>::vlanes()); \
+    b = __riscv_vlse##width##_v_##suffix##m2(ptr+1, sizeof(_Tp)*2, VTraits<v_##_Tpvec>::vlanes()); \
+}\
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, v_##_Tpvec& c) \
+{ \
+    a = __riscv_vlse##width##_v_##suffix##m2(ptr  , sizeof(_Tp)*3, VTraits<v_##_Tpvec>::vlanes()); \
+    b = __riscv_vlse##width##_v_##suffix##m2(ptr+1, sizeof(_Tp)*3, VTraits<v_##_Tpvec>::vlanes()); \
+    c = __riscv_vlse##width##_v_##suffix##m2(ptr+2, sizeof(_Tp)*3, VTraits<v_##_Tpvec>::vlanes()); \
+} \
+inline void v_load_deinterleave(const _Tp* ptr, v_##_Tpvec& a, v_##_Tpvec& b, \
+                                v_##_Tpvec& c, v_##_Tpvec& d) \
+{ \
+    \
+    a = __riscv_vlse##width##_v_##suffix##m2(ptr  , sizeof(_Tp)*4, VTraits<v_##_Tpvec>::vlanes()); \
+    b = __riscv_vlse##width##_v_##suffix##m2(ptr+1, sizeof(_Tp)*4, VTraits<v_##_Tpvec>::vlanes()); \
+    c = __riscv_vlse##width##_v_##suffix##m2(ptr+2, sizeof(_Tp)*4, VTraits<v_##_Tpvec>::vlanes()); \
+    d = __riscv_vlse##width##_v_##suffix##m2(ptr+3, sizeof(_Tp)*4, VTraits<v_##_Tpvec>::vlanes()); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    __riscv_vsse##width(ptr, sizeof(_Tp)*2, a, VTraits<v_##_Tpvec>::vlanes()); \
+    __riscv_vsse##width(ptr+1, sizeof(_Tp)*2, b, VTraits<v_##_Tpvec>::vlanes()); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                const v_##_Tpvec& c, hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ \
+    __riscv_vsse##width(ptr, sizeof(_Tp)*3, a, VTraits<v_##_Tpvec>::vlanes()); \
+    __riscv_vsse##width(ptr+1, sizeof(_Tp)*3, b, VTraits<v_##_Tpvec>::vlanes()); \
+    __riscv_vsse##width(ptr+2, sizeof(_Tp)*3, c, VTraits<v_##_Tpvec>::vlanes()); \
+} \
+inline void v_store_interleave( _Tp* ptr, const v_##_Tpvec& a, const v_##_Tpvec& b, \
+                                const v_##_Tpvec& c, const v_##_Tpvec& d, \
+                                hal::StoreMode /*mode*/=hal::STORE_UNALIGNED ) \
+{ \
+    __riscv_vsse##width(ptr, sizeof(_Tp)*4, a, VTraits<v_##_Tpvec>::vlanes()); \
+    __riscv_vsse##width(ptr+1, sizeof(_Tp)*4, b, VTraits<v_##_Tpvec>::vlanes()); \
+    __riscv_vsse##width(ptr+2, sizeof(_Tp)*4, c, VTraits<v_##_Tpvec>::vlanes()); \
+    __riscv_vsse##width(ptr+3, sizeof(_Tp)*4, d, VTraits<v_##_Tpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(uint8, uchar, u8, 8, 4, VTraits<v_uint8>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(int8, schar, i8, 8, 4, VTraits<v_int8>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(uint16, ushort, u16, 16, 8, VTraits<v_uint16>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(int16, short, i16, 16, 8, VTraits<v_int16>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(uint32, unsigned, u32, 32, 16, VTraits<v_uint32>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(int32, int, i32, 32, 16, VTraits<v_int32>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(float32, float, f32, 32, 16, VTraits<v_float32>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(uint64, uint64, u64, 64, 32, VTraits<v_uint64>::vlanes())
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(int64, int64, i64, 64, 32, VTraits<v_int64>::vlanes())
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_INTERLEAVED(float64, double, f64, 64, 32, VTraits<v_float64>::vlanes())
+#endif
+
+static uint64_t idx_interleave_pairs[] = { \
+    0x0705060403010200, 0x0f0d0e0c0b090a08, 0x1715161413111210, 0x1f1d1e1c1b191a18, \
+    0x2725262423212220, 0x2f2d2e2c2b292a28, 0x3735363433313230, 0x3f3d3e3c3b393a38, \
+    0x4745464443414240, 0x4f4d4e4c4b494a48, 0x5755565453515250, 0x5f5d5e5c5b595a58, \
+    0x6765666463616260, 0x6f6d6e6c6b696a68, 0x7775767473717270, 0x7f7d7e7c7b797a78};
+
+static uint64_t idx_interleave_quads[] = { \
+    0x0703060205010400, 0x0f0b0e0a0d090c08, 0x1713161215111410, 0x1f1b1e1a1d191c18, \
+    0x2723262225212420, 0x2f2b2e2a2d292c28, 0x3733363235313430, 0x3f3b3e3a3d393c38, \
+    0x4743464245414440, 0x4f4b4e4a4d494c48, 0x5753565255515450, 0x5f5b5e5a5d595c58, \
+    0x6763666265616460, 0x6f6b6e6a6d696c68, 0x7773767275717470, 0x7f7b7e7a7d797c78};
+
+#define OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ_NOEXPEND(_Tpvec, func) \
+inline _Tpvec v_interleave_##func(const _Tpvec& vec) { \
+    CV_CheckLE(VTraits<_Tpvec>::vlanes(), VTraits<_Tpvec>::max_nlanes, "RVV implementation only supports VLEN in the range [128, 1024]"); \
+    vuint8m2_t vidx = __riscv_vundefined_u8m2();\
+    vidx = __riscv_vreinterpret_u8m2(__riscv_vle64_v_u64m2(idx_interleave_##func, 16)); \
+    return __riscv_vrgather(vec, vidx, VTraits<v_uint8>::vlanes()); \
+}
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ_NOEXPEND(v_uint8, pairs)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ_NOEXPEND(v_int8, pairs)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ_NOEXPEND(v_uint8, quads)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ_NOEXPEND(v_int8, quads)
+
+#define OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(_Tpvec, width, vzext_vfx, func) \
+inline _Tpvec v_interleave_##func(const _Tpvec& vec) { \
+    CV_CheckLE(VTraits<_Tpvec>::vlanes(), VTraits<_Tpvec>::max_nlanes, "RVV implementation only supports VLEN in the range [128, 1024]"); \
+    vuint##width##m2_t vidx = __riscv_vundefined_u##width##m2();\
+    vidx = __riscv_vget_u##width##m2(vzext_vfx(__riscv_vreinterpret_u8m2(__riscv_vle64_v_u64m2(idx_interleave_##func, 16)), VTraits<v_uint8>::vlanes()), 0); \
+    return __riscv_vrgather(vec, vidx, VTraits<_Tpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_uint16, 16, __riscv_vzext_vf2, pairs)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_int16, 16, __riscv_vzext_vf2, pairs)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_uint32, 32, __riscv_vzext_vf4, pairs)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_int32, 32, __riscv_vzext_vf4, pairs)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_float32, 32, __riscv_vzext_vf4, pairs)
+
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_uint16, 16, __riscv_vzext_vf2, quads)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_int16, 16, __riscv_vzext_vf2, quads)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_uint32, 32, __riscv_vzext_vf4, quads)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_int32, 32, __riscv_vzext_vf4, quads)
+OPENCV_HAL_IMPL_RVV_INTERLEAVED_PQ(v_float32, 32, __riscv_vzext_vf4, quads)
+
+//////////// PopCount //////////
+static const unsigned char popCountTable[256] =
+{
+    0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8,
+};
+#define OPENCV_HAL_IMPL_RVV_HADD(_Tpvec, _Tpvec2, _Tm2, width, width2, suffix, add) \
+static inline _Tpvec2 v_hadd(_Tpvec a) { \
+    vuint##width2##m2_t oneX2 = __riscv_vmv_v_x_u##width2##m2(1, VTraits<v_uint##width2>::vlanes()); \
+    vuint##width##m2_t one = __riscv_vreinterpret_u##width##m2(oneX2); \
+    _Tm2 res = add(a, __riscv_vslide1down(a, 0, VTraits<v_uint##width>::vlanes()), VTraits<v_uint##width>::vlanes()); \
+    return __riscv_vget_##suffix##m2(__riscv_vcompress(res, __riscv_vmseq(one, 1, VTraits<v_uint##width>::vlanes()), VTraits<v_uint##width>::vlanes()), 0); \
+}
+OPENCV_HAL_IMPL_RVV_HADD(v_uint8, v_uint16, vuint16m4_t, 8, 16, u16, __riscv_vwaddu_vv)
+OPENCV_HAL_IMPL_RVV_HADD(v_uint16, v_uint32, vuint32m4_t, 16, 32, u32, __riscv_vwaddu_vv)
+OPENCV_HAL_IMPL_RVV_HADD(v_uint32, v_uint64, vuint64m4_t, 32, 64, u64, __riscv_vwaddu_vv)
+OPENCV_HAL_IMPL_RVV_HADD(v_int8, v_int16, vint16m4_t, 8, 16, i16, __riscv_vwadd_vv)
+OPENCV_HAL_IMPL_RVV_HADD(v_int16, v_int32, vint32m4_t, 16, 32, i32, __riscv_vwadd_vv)
+OPENCV_HAL_IMPL_RVV_HADD(v_int32, v_int64, vint64m4_t, 32, 64, i64, __riscv_vwadd_vv)
+
+OPENCV_HAL_IMPL_RVV_HADD(vint32m4_t, v_int32, vint32m4_t, 16, 32, i32, __riscv_vadd)
+OPENCV_HAL_IMPL_RVV_HADD(vint64m4_t, v_int64, vint64m4_t, 32, 64, i64, __riscv_vadd)
+
+inline v_uint8 v_popcount(const v_uint8& a)
+{
+    return __riscv_vloxei8(popCountTable, a, VTraits<v_uint8>::vlanes());
+}
+inline v_uint16 v_popcount(const v_uint16& a)
+{
+    return v_hadd(v_popcount(__riscv_vreinterpret_u8m2(a)));
+}
+inline v_uint32 v_popcount(const v_uint32& a)
+{
+    return v_hadd(v_hadd(v_popcount(__riscv_vreinterpret_u8m2(a))));
+}
+inline v_uint64 v_popcount(const v_uint64& a)
+{
+    return v_hadd(v_hadd(v_hadd(v_popcount(__riscv_vreinterpret_u8m2(a)))));
+}
+
+inline v_uint8 v_popcount(const v_int8& a)
+{
+    return v_popcount(v_abs(a));\
+}
+inline v_uint16 v_popcount(const v_int16& a)
+{
+    return v_popcount(v_abs(a));\
+}
+inline v_uint32 v_popcount(const v_int32& a)
+{
+    return v_popcount(v_abs(a));\
+}
+inline v_uint64 v_popcount(const v_int64& a)
+{
+    // max(0 - a) is used, since v_abs does not support 64-bit integers.
+    return v_popcount(v_reinterpret_as_u64(__riscv_vmax(a, v_sub(v_setzero_s64(), a), VTraits<v_int64>::vlanes())));
+}
+
+
+//////////// SignMask ////////////
+#define OPENCV_HAL_IMPL_RVV_SIGNMASK_OP(_Tpvec) \
+inline int v_signmask(const _Tpvec& a) \
+{ \
+    uint8_t ans[4] = {0}; \
+    __riscv_vsm(ans, __riscv_vmslt(a, 0, VTraits<_Tpvec>::vlanes()), VTraits<_Tpvec>::vlanes()); \
+    return *(reinterpret_cast<int*>(ans)) & (((__int128_t)1 << VTraits<_Tpvec>::vlanes()) - 1); \
+} \
+inline int v_scan_forward(const _Tpvec& a) \
+{ \
+    return (int)__riscv_vfirst(__riscv_vmslt(a, 0, VTraits<_Tpvec>::vlanes()), VTraits<_Tpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_SIGNMASK_OP(v_int8)
+OPENCV_HAL_IMPL_RVV_SIGNMASK_OP(v_int16)
+OPENCV_HAL_IMPL_RVV_SIGNMASK_OP(v_int32)
+OPENCV_HAL_IMPL_RVV_SIGNMASK_OP(v_int64)
+
+inline int64 v_signmask(const v_uint8& a)
+{ return v_signmask(v_reinterpret_as_s8(a)); }
+inline int64 v_signmask(const v_uint16& a)
+{ return v_signmask(v_reinterpret_as_s16(a)); }
+inline int v_signmask(const v_uint32& a)
+{ return v_signmask(v_reinterpret_as_s32(a)); }
+inline int v_signmask(const v_float32& a)
+{ return v_signmask(v_reinterpret_as_s32(a)); }
+inline int v_signmask(const v_uint64& a)
+{ return v_signmask(v_reinterpret_as_s64(a)); }
+#if CV_SIMD_SCALABLE_64F
+inline int v_signmask(const v_float64& a)
+{ return v_signmask(v_reinterpret_as_s64(a)); }
+#endif
+
+//////////// Scan forward ////////////
+inline int v_scan_forward(const v_uint8& a)
+{ return v_scan_forward(v_reinterpret_as_s8(a)); }
+inline int v_scan_forward(const v_uint16& a)
+{ return v_scan_forward(v_reinterpret_as_s16(a)); }
+inline int v_scan_forward(const v_uint32& a)
+{ return v_scan_forward(v_reinterpret_as_s32(a)); }
+inline int v_scan_forward(const v_float32& a)
+{ return v_scan_forward(v_reinterpret_as_s32(a)); }
+inline int v_scan_forward(const v_uint64& a)
+{ return v_scan_forward(v_reinterpret_as_s64(a)); }
+#if CV_SIMD_SCALABLE_64F
+inline int v_scan_forward(const v_float64& a)
+{ return v_scan_forward(v_reinterpret_as_s64(a)); }
+#endif
+
+//////////// Pack triplets ////////////
+// {A0, A1, A2, A3, B0, B1, B2, B3, C0 ...} --> {A0, A1, A2, B0, B1, B2, C0 ...}
+// mask: {0,0,0,1, ...} -> {T,T,T,F, ...}
+#define OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(_Tpvec, v_trunc) \
+inline _Tpvec v_pack_triplets(const _Tpvec& vec) { \
+    size_t vl = VTraits<v_uint8>::vlanes(); \
+    vuint32m2_t one = __riscv_vmv_v_x_u32m2(1, VTraits<v_uint32>::vlanes()); \
+    vuint8m2_t zero = __riscv_vmv_v_x_u8m2(0, vl); \
+    vuint8m2_t mask = __riscv_vreinterpret_u8m2(one); \
+    return __riscv_vcompress(vec, __riscv_vmseq(v_trunc(__riscv_vslideup(zero, mask, 3, vl)), 0, vl), VTraits<_Tpvec>::vlanes()); \
+}
+
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_uint8, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_int8, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_uint16, __riscv_vlmul_trunc_u8m1)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_int16, __riscv_vlmul_trunc_u8m1)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_uint32, __riscv_vlmul_trunc_u8mf2)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_int32, __riscv_vlmul_trunc_u8mf2)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_float32, __riscv_vlmul_trunc_u8mf2)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_uint64, __riscv_vlmul_trunc_u8mf4)
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_int64, __riscv_vlmul_trunc_u8mf4)
+#if CV_SIMD_SCALABLE_64F
+OPENCV_HAL_IMPL_RVV_PACK_TRIPLETS(v_float64, __riscv_vlmul_trunc_u8mf4)
+#endif
+
+
+////// FP16 support ///////
+
+#if defined(__riscv_zfh) && __riscv_zfh
+inline v_float32 v_load_expand(const hfloat* ptr)
+{
+    return __riscv_vfwcvt_f(__riscv_vle16_v_f16m1((_Float16*)ptr, VTraits<v_float32>::vlanes()) ,VTraits<v_float32>::vlanes());;
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32& v)
+{
+    __riscv_vse16_v_f16m1((_Float16*)ptr, __riscv_vfncvt_f_f_w_f16m1(v, VTraits<v_float32>::vlanes()), VTraits<v_float32>::vlanes());
+}
+#else
+inline v_float32 v_load_expand(const hfloat* ptr)
+{
+    float buf[32];
+    for( int i = 0; i < VTraits<v_float32>::vlanes(); i++ ) buf[i] = (float)ptr[i];
+    return v_load(buf);
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32& v)
+{
+    float buf[32];
+    v_store(buf, v);
+    for( int i = 0; i < VTraits<v_float32>::vlanes(); i++ ) ptr[i] = hfloat(buf[i]);
+}
+#endif
+////////////// Rounding //////////////
+inline v_int32 v_round(const v_float32& a)
+{
+    // return vfcvt_x(vfadd(a, 1e-6, VTraits<v_float32>::vlanes()), VTraits<v_float32>::vlanes());
+    return __riscv_vfcvt_x(a, VTraits<v_float32>::vlanes());
+}
+
+inline v_int32 v_floor(const v_float32& a)
+{
+    return __riscv_vfcvt_x(__riscv_vfsub(a, 0.5f - 1e-5, VTraits<v_float32>::vlanes()), VTraits<v_float32>::vlanes());
+    // return vfcvt_x(a, VTraits<v_float32>::vlanes());
+}
+
+inline v_int32 v_ceil(const v_float32& a)
+{
+    return __riscv_vfcvt_x(__riscv_vfadd(a, 0.5f - 1e-5, VTraits<v_float32>::vlanes()), VTraits<v_float32>::vlanes());
+}
+
+inline v_int32 v_trunc(const v_float32& a)
+{
+    return __riscv_vfcvt_rtz_x(a, VTraits<v_float32>::vlanes());
+}
+#if CV_SIMD_SCALABLE_64F
+inline v_int32 v_round(const v_float64& a)
+{
+    return __riscv_vfncvt_x(__riscv_vlmul_ext_f64m4(a), VTraits<v_float32>::vlanes());
+}
+
+inline v_int32 v_round(const v_float64& a, const v_float64& b)
+{
+    // return vfncvt_x(vset(vlmul_ext_f64m2(vfadd(a, 1e-6, VTraits<v_float64>::vlanes())), 1, b), VTraits<v_float32>::vlanes());
+    // Fix https://github.com/opencv/opencv/issues/24746
+    return __riscv_vfncvt_x(__riscv_vset(__riscv_vlmul_ext_f64m4(a), 1, b), VTraits<v_float32>::vlanes());
+}
+
+inline v_int32 v_floor(const v_float64& a)
+{
+    return __riscv_vfncvt_x(__riscv_vlmul_ext_f64m4(__riscv_vfsub(a, 0.5f - 1e-6, VTraits<v_float64>::vlanes())), VTraits<v_float32>::vlanes());
+}
+
+inline v_int32 v_ceil(const v_float64& a)
+{
+    return __riscv_vfncvt_x(__riscv_vlmul_ext_f64m4(__riscv_vfadd(a, 0.5f - 1e-6, VTraits<v_float64>::vlanes())), VTraits<v_float32>::vlanes());
+}
+
+inline v_int32 v_trunc(const v_float64& a)
+{
+    return __riscv_vfncvt_rtz_x(__riscv_vlmul_ext_f64m4(a), VTraits<v_float32>::vlanes());
+}
+#endif
+
+//////// Dot Product ////////
+
+// 16 >> 32
+inline v_int32 v_dotprod(const v_int16& a, const v_int16& b)
+{
+    vint32m4_t temp1 = __riscv_vwmul(a, b, VTraits<v_int16>::vlanes());
+    return v_hadd(temp1);
+}
+
+inline v_int32 v_dotprod(const v_int16& a, const v_int16& b, const v_int32& c)
+{
+    vint32m4_t temp1 = __riscv_vwmul(a, b, VTraits<v_int16>::vlanes());
+    return __riscv_vadd(v_hadd(temp1), c, VTraits<v_int32>::vlanes());
+}
+
+// 32 >> 64
+inline v_int64 v_dotprod(const v_int32& a, const v_int32& b)
+{
+    vuint64m2_t one64 = __riscv_vmv_v_x_u64m2(1, VTraits<v_uint64>::vlanes()); \
+    vuint32m2_t one32 = __riscv_vreinterpret_u32m2(one64); \
+    vbool16_t mask = __riscv_vmseq(one32, 1, VTraits<v_uint32>::vlanes()); \
+    vint64m4_t temp1 = __riscv_vwmul(a, b, VTraits<v_int32>::vlanes()); \
+    vint64m4_t temp2 = __riscv_vslide1down(temp1, 0, VTraits<v_int32>::vlanes());
+    vint64m4_t res = __riscv_vadd(temp1, temp2, VTraits<v_int32>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_int32>::vlanes()); \
+    return __riscv_vlmul_trunc_i64m2(res); \
+}
+inline v_int64 v_dotprod(const v_int32& a, const v_int32& b, const v_int64& c)
+{
+    vuint64m2_t one64 = __riscv_vmv_v_x_u64m2(1, VTraits<v_uint64>::vlanes()); \
+    vuint32m2_t one32 = __riscv_vreinterpret_u32m2(one64); \
+    vbool16_t mask = __riscv_vmseq(one32, 1, VTraits<v_uint32>::vlanes()); \
+    vint64m4_t temp1 = __riscv_vwmul(a, b, VTraits<v_int32>::vlanes()); \
+    vint64m4_t temp2 = __riscv_vslide1down(temp1, 0, VTraits<v_int32>::vlanes());
+    vint64m4_t res = __riscv_vadd(temp1, temp2, VTraits<v_int32>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_int32>::vlanes()); \
+    return __riscv_vadd(__riscv_vlmul_trunc_i64m2(res), c, VTraits<v_int64>::vlanes()); \
+}
+
+// 8 >> 32
+inline v_uint32 v_dotprod_expand(const v_uint8& a, const v_uint8& b)
+{
+    vuint32m2_t one32 = __riscv_vmv_v_x_u32m2(1, VTraits<v_uint32>::vlanes()); \
+    vuint8m2_t one8 = __riscv_vreinterpret_u8m2(one32); \
+    vbool4_t mask = __riscv_vmseq(one8, 1, VTraits<v_uint8>::vlanes()); \
+    vuint16m4_t t0 = __riscv_vwmulu(a, b, VTraits<v_uint8>::vlanes()); \
+    vuint16m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_uint8>::vlanes());
+    vuint16m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_uint8>::vlanes());
+    vuint16m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_uint8>::vlanes());
+    vuint32m8_t res = __riscv_vadd(__riscv_vwaddu_vv(t2, t3, VTraits<v_uint8>::vlanes()), __riscv_vwaddu_vv(t0, t1, VTraits<v_uint8>::vlanes()), VTraits<v_uint8>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_uint8>::vlanes()); \
+    return __riscv_vlmul_trunc_u32m2(res);
+}
+
+inline v_uint32 v_dotprod_expand(const v_uint8& a, const v_uint8& b,
+                                  const v_uint32& c)
+{
+    vuint32m2_t one32 = __riscv_vmv_v_x_u32m2(1, VTraits<v_uint32>::vlanes()); \
+    vuint8m2_t one8 = __riscv_vreinterpret_u8m2(one32); \
+    vbool4_t mask = __riscv_vmseq(one8, 1, VTraits<v_uint8>::vlanes()); \
+    vuint16m4_t t0 = __riscv_vwmulu(a, b, VTraits<v_uint8>::vlanes()); \
+    vuint16m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_uint8>::vlanes());
+    vuint16m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_uint8>::vlanes());
+    vuint16m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_uint8>::vlanes());
+    vuint32m8_t res = __riscv_vadd(__riscv_vwaddu_vv(t2, t3, VTraits<v_uint8>::vlanes()), __riscv_vwaddu_vv(t0, t1, VTraits<v_uint8>::vlanes()), VTraits<v_uint8>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_uint8>::vlanes()); \
+    return __riscv_vadd(__riscv_vlmul_trunc_u32m2(res), c, VTraits<v_uint8>::vlanes());
+}
+
+inline v_int32 v_dotprod_expand(const v_int8& a, const v_int8& b)
+{
+    vuint32m2_t one32 = __riscv_vmv_v_x_u32m2(1, VTraits<v_uint32>::vlanes()); \
+    vuint8m2_t one8 = __riscv_vreinterpret_u8m2(one32); \
+    vbool4_t mask = __riscv_vmseq(one8, 1, VTraits<v_uint8>::vlanes()); \
+    vint16m4_t t0 = __riscv_vwmul(a, b, VTraits<v_int8>::vlanes()); \
+    vint16m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_int8>::vlanes());
+    vint16m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_int8>::vlanes());
+    vint16m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_int8>::vlanes());
+    vint32m8_t res = __riscv_vadd(__riscv_vwadd_vv(t2, t3, VTraits<v_int8>::vlanes()), __riscv_vwadd_vv(t0, t1, VTraits<v_int8>::vlanes()), VTraits<v_int8>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_int8>::vlanes()); \
+    return __riscv_vlmul_trunc_i32m2(res);
+}
+
+inline v_int32 v_dotprod_expand(const v_int8& a, const v_int8& b,
+                                  const v_int32& c)
+{
+    vuint32m2_t one32 = __riscv_vmv_v_x_u32m2(1, VTraits<v_uint32>::vlanes()); \
+    vuint8m2_t one8 = __riscv_vreinterpret_u8m2(one32); \
+    vbool4_t mask = __riscv_vmseq(one8, 1, VTraits<v_uint8>::vlanes()); \
+    vint16m4_t t0 = __riscv_vwmul(a, b, VTraits<v_int8>::vlanes()); \
+    vint16m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_int8>::vlanes());
+    vint16m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_int8>::vlanes());
+    vint16m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_int8>::vlanes());
+    vint32m8_t res = __riscv_vadd(__riscv_vwadd_vv(t2, t3, VTraits<v_int8>::vlanes()), __riscv_vwadd_vv(t0, t1, VTraits<v_int8>::vlanes()), VTraits<v_int8>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_int8>::vlanes()); \
+    return __riscv_vadd(__riscv_vlmul_trunc_i32m2(res), c, VTraits<v_int8>::vlanes());
+}
+
+
+// // 16 >> 64
+inline v_uint64 v_dotprod_expand(const v_uint16& a, const v_uint16& b)
+{
+    vuint64m2_t one64 = __riscv_vmv_v_x_u64m2(1, VTraits<v_uint64>::vlanes()); \
+    vuint16m2_t one16 = __riscv_vreinterpret_u16m2(one64); \
+    vbool8_t mask = __riscv_vmseq(one16, 1, VTraits<v_uint16>::vlanes()); \
+    vuint32m4_t t0 = __riscv_vwmulu(a, b, VTraits<v_uint16>::vlanes()); \
+    vuint32m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_uint16>::vlanes());
+    vuint32m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_uint16>::vlanes());
+    vuint32m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_uint16>::vlanes());
+    vuint64m8_t res = __riscv_vadd(__riscv_vwaddu_vv(t2, t3, VTraits<v_uint16>::vlanes()), __riscv_vwaddu_vv(t0, t1, VTraits<v_uint16>::vlanes()), VTraits<v_uint16>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_uint16>::vlanes()); \
+    return __riscv_vlmul_trunc_u64m2(res);
+}
+inline v_uint64 v_dotprod_expand(const v_uint16& a, const v_uint16& b, const v_uint64& c)
+{
+    vuint64m2_t one64 = __riscv_vmv_v_x_u64m2(1, VTraits<v_uint64>::vlanes()); \
+    vuint16m2_t one16 = __riscv_vreinterpret_u16m2(one64); \
+    vbool8_t mask = __riscv_vmseq(one16, 1, VTraits<v_uint16>::vlanes()); \
+    vuint32m4_t t0 = __riscv_vwmulu(a, b, VTraits<v_uint16>::vlanes()); \
+    vuint32m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_uint16>::vlanes());
+    vuint32m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_uint16>::vlanes());
+    vuint32m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_uint16>::vlanes());
+    vuint64m8_t res = __riscv_vadd(__riscv_vwaddu_vv(t2, t3, VTraits<v_uint16>::vlanes()), __riscv_vwaddu_vv(t0, t1, VTraits<v_uint16>::vlanes()), VTraits<v_uint16>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_uint16>::vlanes()); \
+    return __riscv_vadd(__riscv_vlmul_trunc_u64m2(res), c, VTraits<v_uint16>::vlanes());
+}
+
+inline v_int64 v_dotprod_expand(const v_int16& a, const v_int16& b)
+{
+    vuint64m2_t one64 = __riscv_vmv_v_x_u64m2(1, VTraits<v_uint64>::vlanes()); \
+    vuint16m2_t one16 = __riscv_vreinterpret_u16m2(one64); \
+    vbool8_t mask = __riscv_vmseq(one16, 1, VTraits<v_uint16>::vlanes()); \
+    vint32m4_t t0 = __riscv_vwmul(a, b, VTraits<v_int16>::vlanes()); \
+    vint32m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_int16>::vlanes());
+    vint32m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_int16>::vlanes());
+    vint32m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_int16>::vlanes());
+    vint64m8_t res = __riscv_vadd(__riscv_vwadd_vv(t2, t3, VTraits<v_int16>::vlanes()), __riscv_vwadd_vv(t0, t1, VTraits<v_int16>::vlanes()), VTraits<v_int16>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_int16>::vlanes()); \
+    return __riscv_vlmul_trunc_i64m2(res);
+}
+inline v_int64 v_dotprod_expand(const v_int16& a, const v_int16& b,
+                                  const v_int64& c)
+{
+    vuint64m2_t one64 = __riscv_vmv_v_x_u64m2(1, VTraits<v_uint64>::vlanes()); \
+    vuint16m2_t one16 = __riscv_vreinterpret_u16m2(one64); \
+    vbool8_t mask = __riscv_vmseq(one16, 1, VTraits<v_uint16>::vlanes()); \
+    vint32m4_t t0 = __riscv_vwmul(a, b, VTraits<v_int16>::vlanes()); \
+    vint32m4_t t1= __riscv_vslide1down(t0, 0, VTraits<v_int16>::vlanes());
+    vint32m4_t t2= __riscv_vslide1down(t1, 0, VTraits<v_int16>::vlanes());
+    vint32m4_t t3= __riscv_vslide1down(t2, 0, VTraits<v_int16>::vlanes());
+    vint64m8_t res = __riscv_vadd(__riscv_vwadd_vv(t2, t3, VTraits<v_int16>::vlanes()), __riscv_vwadd_vv(t0, t1, VTraits<v_int16>::vlanes()), VTraits<v_int16>::vlanes());
+    res = __riscv_vcompress(res, mask, VTraits<v_int16>::vlanes()); \
+    return __riscv_vadd(__riscv_vlmul_trunc_i64m2(res), c, VTraits<v_int16>::vlanes());
+}
+
+// // 32 >> 64f
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_dotprod_expand(const v_int32& a, const v_int32& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64 v_dotprod_expand(const v_int32& a,   const v_int32& b,
+                                    const v_float64& c)
+{ return v_add(v_dotprod_expand(a, b) , c); }
+#endif
+
+//////// Fast Dot Product ////////
+// 16 >> 32
+inline v_int32 v_dotprod_fast(const v_int16& a, const v_int16& b)
+{
+    vint32m1_t zero = __riscv_vmv_v_x_i32m1(0, VTraits<vint32m1_t>::vlanes());
+    return __riscv_vset(__riscv_vmv_v_x_i32m2(0, VTraits<v_int32>::vlanes()), 0, __riscv_vredsum_tu(zero, __riscv_vwmul(a, b, VTraits<v_int16>::vlanes()), zero,  VTraits<v_int16>::vlanes()));
+}
+inline v_int32 v_dotprod_fast(const v_int16& a, const v_int16& b, const v_int32& c)
+{
+    vint32m1_t zero = __riscv_vmv_v_x_i32m1(0, VTraits<vint32m1_t>::vlanes());
+    return  __riscv_vadd(c, __riscv_vset(__riscv_vmv_v_x_i32m2(0, VTraits<v_int32>::vlanes()), 0, __riscv_vredsum_tu(zero, __riscv_vwmul(a, b, VTraits<v_int16>::vlanes()), zero,  VTraits<v_int16>::vlanes())), VTraits<v_int32>::vlanes());
+}
+
+// 32 >> 64
+inline v_int64 v_dotprod_fast(const v_int32& a, const v_int32& b)
+{
+    vint64m1_t zero = __riscv_vmv_v_x_i64m1(0, VTraits<vint64m1_t>::vlanes());
+    return __riscv_vset(__riscv_vmv_v_x_i64m2(0, VTraits<v_int64>::vlanes()), 0, __riscv_vredsum_tu(zero, __riscv_vwmul(a, b, VTraits<v_int32>::vlanes()), zero,  VTraits<v_int32>::vlanes()));
+}
+inline v_int64 v_dotprod_fast(const v_int32& a, const v_int32& b, const v_int64& c)
+{
+    vint64m1_t zero = __riscv_vmv_v_x_i64m1(0, VTraits<vint64m1_t>::vlanes());
+    return  __riscv_vadd(c, __riscv_vset(__riscv_vmv_v_x_i64m2(0, VTraits<v_int64>::vlanes()), 0, __riscv_vredsum_tu(zero, __riscv_vwmul(a, b, VTraits<v_int32>::vlanes()), zero,  VTraits<v_int32>::vlanes())), VTraits<v_int64>::vlanes());
+}
+
+
+// 8 >> 32
+inline v_uint32 v_dotprod_expand_fast(const v_uint8& a, const v_uint8& b)
+{
+    vuint32m1_t zero = __riscv_vmv_v_x_u32m1(0, VTraits<vuint32m1_t>::vlanes());
+    auto res = __riscv_vwredsumu_tu(zero, __riscv_vwmulu(a, b, VTraits<v_uint8>::vlanes()), zero,   VTraits<v_uint8>::vlanes());
+    return __riscv_vset(__riscv_vmv_v_x_u32m2(0, VTraits<v_uint32>::vlanes()), 0, res);
+}
+inline v_uint32 v_dotprod_expand_fast(const v_uint8& a, const v_uint8& b, const v_uint32& c)
+{
+    vuint32m1_t zero = __riscv_vmv_v_x_u32m1(0, VTraits<vuint32m1_t>::vlanes());
+    auto res = __riscv_vwredsumu_tu(zero, __riscv_vwmulu(a, b, VTraits<v_uint8>::vlanes()), zero,   VTraits<v_uint8>::vlanes());
+    return __riscv_vadd(c, __riscv_vset(__riscv_vmv_v_x_u32m2(0, VTraits<v_uint32>::vlanes()), 0, res), VTraits<v_uint32>::vlanes());
+}
+inline v_int32 v_dotprod_expand_fast(const v_int8& a, const v_int8& b)
+{
+    vint32m1_t zero = __riscv_vmv_v_x_i32m1(0, VTraits<vint32m1_t>::vlanes());
+    return __riscv_vset(__riscv_vmv_v_x_i32m2(0, VTraits<v_uint32>::vlanes()), 0, __riscv_vwredsum_tu(zero,  __riscv_vwmul(a, b, VTraits<v_int8>::vlanes()), zero,  VTraits<v_int8>::vlanes()));
+}
+inline v_int32 v_dotprod_expand_fast(const v_int8& a, const v_int8& b, const v_int32& c)
+{
+    vint32m1_t zero = __riscv_vmv_v_x_i32m1(0, VTraits<vint32m1_t>::vlanes());
+    return __riscv_vadd(c, __riscv_vset(__riscv_vmv_v_x_i32m2(0, VTraits<v_uint32>::vlanes()), 0, __riscv_vwredsum_tu(zero, __riscv_vwmul(a, b, VTraits<v_int8>::vlanes()), zero,  VTraits<v_int8>::vlanes())), VTraits<v_int32>::vlanes());
+}
+
+// 16 >> 64
+inline v_uint64 v_dotprod_expand_fast(const v_uint16& a, const v_uint16& b)
+{
+    vuint64m1_t zero = __riscv_vmv_v_x_u64m1(0, VTraits<vuint64m1_t>::vlanes());
+    return __riscv_vset(__riscv_vmv_v_x_u64m2(0, VTraits<v_uint64>::vlanes()), 0, __riscv_vwredsumu_tu(zero,  __riscv_vwmulu(a, b, VTraits<v_uint16>::vlanes()), zero,  VTraits<v_uint16>::vlanes()));
+}
+inline v_uint64 v_dotprod_expand_fast(const v_uint16& a, const v_uint16& b, const v_uint64& c)
+{
+    vuint64m1_t zero = __riscv_vmv_v_x_u64m1(0, VTraits<vuint64m1_t>::vlanes());
+    return __riscv_vadd(c, __riscv_vset(__riscv_vmv_v_x_u64m2(0, VTraits<v_uint64>::vlanes()), 0, __riscv_vwredsumu_tu(zero,  __riscv_vwmulu(a, b, VTraits<v_uint16>::vlanes()), zero,  VTraits<v_uint16>::vlanes())), VTraits<v_uint64>::vlanes());
+}
+inline v_int64 v_dotprod_expand_fast(const v_int16& a, const v_int16& b)
+{
+    vint64m1_t zero = __riscv_vmv_v_x_i64m1(0, VTraits<vint64m1_t>::vlanes());
+    return __riscv_vset(__riscv_vmv_v_x_i64m2(0, VTraits<v_int64>::vlanes()), 0, __riscv_vwredsum_tu(zero,  __riscv_vwmul(a, b, VTraits<v_int16>::vlanes()), zero,  VTraits<v_int16>::vlanes()));
+}
+inline v_int64 v_dotprod_expand_fast(const v_int16& a, const v_int16& b, const v_int64& c)
+{
+    vint64m1_t zero = __riscv_vmv_v_x_i64m1(0, VTraits<vint64m1_t>::vlanes());
+    return __riscv_vadd(c, __riscv_vset(__riscv_vmv_v_x_i64m2(0, VTraits<v_int64>::vlanes()), 0, __riscv_vwredsum_tu(zero,  __riscv_vwmul(a, b, VTraits<v_int16>::vlanes()), zero,  VTraits<v_int16>::vlanes())), VTraits<v_int64>::vlanes());
+}
+
+// 32 >> 64f
+#if CV_SIMD_SCALABLE_64F
+inline v_float64 v_dotprod_expand_fast(const v_int32& a, const v_int32& b)
+{ return v_cvt_f64(v_dotprod_fast(a, b)); }
+inline v_float64 v_dotprod_expand_fast(const v_int32& a, const v_int32& b, const v_float64& c)
+{ return v_add(v_dotprod_expand_fast(a, b) , c); }
+#endif
+
+// TODO: only 128 bit now.
+inline v_float32 v_matmul(const v_float32& v, const v_float32& mat0,
+                            const v_float32& mat1, const v_float32& mat2,
+                            const v_float32& mat3)
+{
+    vfloat32m2_t res;
+    res = __riscv_vfmul_vf_f32m2(mat0, v_extract_n(v, 0), VTraits<v_float32>::vlanes());
+    res = __riscv_vfmacc_vf_f32m2(res, v_extract_n(v, 1), mat1, VTraits<v_float32>::vlanes());
+    res = __riscv_vfmacc_vf_f32m2(res, v_extract_n(v, 2), mat2, VTraits<v_float32>::vlanes());
+    res = __riscv_vfmacc_vf_f32m2(res, v_extract_n(v, 3), mat3, VTraits<v_float32>::vlanes());
+    return res;
+}
+
+// TODO: only 128 bit now.
+inline v_float32 v_matmuladd(const v_float32& v, const v_float32& mat0,
+                               const v_float32& mat1, const v_float32& mat2,
+                               const v_float32& a)
+{
+    vfloat32m2_t res = __riscv_vfmul_vf_f32m2(mat0, v_extract_n(v,0), VTraits<v_float32>::vlanes());
+    res = __riscv_vfmacc_vf_f32m2(res, v_extract_n(v,1), mat1, VTraits<v_float32>::vlanes());
+    res = __riscv_vfmacc_vf_f32m2(res, v_extract_n(v,2), mat2, VTraits<v_float32>::vlanes());
+    return __riscv_vfadd(res, a, VTraits<v_float32>::vlanes());
+}
+
+inline void v_cleanup() {}
+
+#include "intrin_math.hpp"
+inline v_float32 v_exp(const v_float32& x) { return v_exp_default_32f<v_float32, v_int32>(x); }
+inline v_float32 v_log(const v_float32& x) { return v_log_default_32f<v_float32, v_int32>(x); }
+inline void v_sincos(const v_float32& x, v_float32& s, v_float32& c) { v_sincos_default_32f<v_float32, v_int32>(x, s, c); }
+inline v_float32 v_sin(const v_float32& x) { return v_sin_default_32f<v_float32, v_int32>(x); }
+inline v_float32 v_cos(const v_float32& x) { return v_cos_default_32f<v_float32, v_int32>(x); }
+inline v_float32 v_erf(const v_float32& x) { return v_erf_default_32f<v_float32, v_int32>(x); }
+
+inline v_float64 v_exp(const v_float64& x) { return v_exp_default_64f<v_float64, v_int64>(x); }
+inline v_float64 v_log(const v_float64& x) { return v_log_default_64f<v_float64, v_int64>(x); }
+inline void v_sincos(const v_float64& x, v_float64& s, v_float64& c) { v_sincos_default_64f<v_float64, v_int64>(x, s, c); }
+inline v_float64 v_sin(const v_float64& x) { return v_sin_default_64f<v_float64, v_int64>(x); }
+inline v_float64 v_cos(const v_float64& x) { return v_cos_default_64f<v_float64, v_int64>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+} //namespace cv
+
+#endif //OPENCV_HAL_INTRIN_RVV_SCALABLE_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_sse.hpp

@@ -0,0 +1,3483 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_HAL_SSE_HPP
+#define OPENCV_HAL_SSE_HPP
+
+#include <algorithm>
+#include "opencv2/core/utility.hpp"
+
+#define CV_SIMD128 1
+#define CV_SIMD128_64F 1
+#define CV_SIMD128_FP16 0  // no native operations with FP16 type.
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+//
+// Compilation troubleshooting:
+// - MSVC: error C2719: 'a': formal parameter with requested alignment of 16 won't be aligned
+//   Replace parameter declaration to const reference:
+//   -v_int32x4 a
+//   +const v_int32x4& a
+//
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+///////// Types ////////////
+
+struct v_uint8x16
+{
+    typedef uchar lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 16 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint8x16() {}
+    explicit v_uint8x16(__m128i v) : val(v) {}
+    v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
+               uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
+    {
+        val = _mm_setr_epi8((char)v0, (char)v1, (char)v2, (char)v3,
+                            (char)v4, (char)v5, (char)v6, (char)v7,
+                            (char)v8, (char)v9, (char)v10, (char)v11,
+                            (char)v12, (char)v13, (char)v14, (char)v15);
+    }
+
+    uchar get0() const
+    {
+        return (uchar)_mm_cvtsi128_si32(val);
+    }
+
+    __m128i val;
+};
+
+struct v_int8x16
+{
+    typedef schar lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 16 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int8x16() {}
+    explicit v_int8x16(__m128i v) : val(v) {}
+    v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
+              schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
+    {
+        val = _mm_setr_epi8((char)v0, (char)v1, (char)v2, (char)v3,
+                            (char)v4, (char)v5, (char)v6, (char)v7,
+                            (char)v8, (char)v9, (char)v10, (char)v11,
+                            (char)v12, (char)v13, (char)v14, (char)v15);
+    }
+
+    schar get0() const
+    {
+        return (schar)_mm_cvtsi128_si32(val);
+    }
+
+    __m128i val;
+};
+
+struct v_uint16x8
+{
+    typedef ushort lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 8 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint16x8() {}
+    explicit v_uint16x8(__m128i v) : val(v) {}
+    v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
+    {
+        val = _mm_setr_epi16((short)v0, (short)v1, (short)v2, (short)v3,
+                             (short)v4, (short)v5, (short)v6, (short)v7);
+    }
+
+    ushort get0() const
+    {
+        return (ushort)_mm_cvtsi128_si32(val);
+    }
+
+    __m128i val;
+};
+
+struct v_int16x8
+{
+    typedef short lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 8 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int16x8() {}
+    explicit v_int16x8(__m128i v) : val(v) {}
+    v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
+    {
+        val = _mm_setr_epi16((short)v0, (short)v1, (short)v2, (short)v3,
+                             (short)v4, (short)v5, (short)v6, (short)v7);
+    }
+
+    short get0() const
+    {
+        return (short)_mm_cvtsi128_si32(val);
+    }
+
+    __m128i val;
+};
+
+struct v_uint32x4
+{
+    typedef unsigned lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 4 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint32x4() {}
+    explicit v_uint32x4(__m128i v) : val(v) {}
+    v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3)
+    {
+        val = _mm_setr_epi32((int)v0, (int)v1, (int)v2, (int)v3);
+    }
+
+    unsigned get0() const
+    {
+        return (unsigned)_mm_cvtsi128_si32(val);
+    }
+
+    __m128i val;
+};
+
+struct v_int32x4
+{
+    typedef int lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 4 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int32x4() {}
+    explicit v_int32x4(__m128i v) : val(v) {}
+    v_int32x4(int v0, int v1, int v2, int v3)
+    {
+        val = _mm_setr_epi32(v0, v1, v2, v3);
+    }
+
+    int get0() const
+    {
+        return _mm_cvtsi128_si32(val);
+    }
+
+    __m128i val;
+};
+
+struct v_float32x4
+{
+    typedef float lane_type;
+    typedef __m128 vector_type;
+    enum { nlanes = 4 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_float32x4() {}
+    explicit v_float32x4(__m128 v) : val(v) {}
+    v_float32x4(float v0, float v1, float v2, float v3)
+    {
+        val = _mm_setr_ps(v0, v1, v2, v3);
+    }
+
+    float get0() const
+    {
+        return _mm_cvtss_f32(val);
+    }
+
+    __m128 val;
+};
+
+struct v_uint64x2
+{
+    typedef uint64 lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 2 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_uint64x2() {}
+    explicit v_uint64x2(__m128i v) : val(v) {}
+    v_uint64x2(uint64 v0, uint64 v1)
+    {
+#if defined(_MSC_VER) && _MSC_VER >= 1920/*MSVS 2019*/ && defined(_M_X64) && !defined(__clang__)
+        val = _mm_setr_epi64x((int64_t)v0, (int64_t)v1);
+#elif defined(__GNUC__)
+        val = _mm_setr_epi64((__m64)v0, (__m64)v1);
+#else
+        val = _mm_setr_epi32((int)v0, (int)(v0 >> 32), (int)v1, (int)(v1 >> 32));
+#endif
+    }
+
+    uint64 get0() const
+    {
+    #if !defined(__x86_64__) && !defined(_M_X64)
+        int a = _mm_cvtsi128_si32(val);
+        int b = _mm_cvtsi128_si32(_mm_srli_epi64(val, 32));
+        return (unsigned)a | ((uint64)(unsigned)b << 32);
+    #else
+        return (uint64)_mm_cvtsi128_si64(val);
+    #endif
+    }
+
+    __m128i val;
+};
+
+struct v_int64x2
+{
+    typedef int64 lane_type;
+    typedef __m128i vector_type;
+    enum { nlanes = 2 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_int64x2() {}
+    explicit v_int64x2(__m128i v) : val(v) {}
+    v_int64x2(int64 v0, int64 v1)
+    {
+#if defined(_MSC_VER) && _MSC_VER >= 1920/*MSVS 2019*/ && defined(_M_X64) && !defined(__clang__)
+        val = _mm_setr_epi64x((int64_t)v0, (int64_t)v1);
+#elif defined(__GNUC__)
+        val = _mm_setr_epi64((__m64)v0, (__m64)v1);
+#else
+        val = _mm_setr_epi32((int)v0, (int)(v0 >> 32), (int)v1, (int)(v1 >> 32));
+#endif
+    }
+
+    int64 get0() const
+    {
+    #if !defined(__x86_64__) && !defined(_M_X64)
+        int a = _mm_cvtsi128_si32(val);
+        int b = _mm_cvtsi128_si32(_mm_srli_epi64(val, 32));
+        return (int64)((unsigned)a | ((uint64)(unsigned)b << 32));
+    #else
+        return _mm_cvtsi128_si64(val);
+    #endif
+    }
+
+    __m128i val;
+};
+
+struct v_float64x2
+{
+    typedef double lane_type;
+    typedef __m128d vector_type;
+    enum { nlanes = 2 };
+
+    /* coverity[uninit_ctor]: suppress warning */
+    v_float64x2() {}
+    explicit v_float64x2(__m128d v) : val(v) {}
+    v_float64x2(double v0, double v1)
+    {
+        val = _mm_setr_pd(v0, v1);
+    }
+
+    double get0() const
+    {
+        return _mm_cvtsd_f64(val);
+    }
+
+    __m128d val;
+};
+
+namespace hal_sse_internal
+{
+    template <typename to_sse_type, typename from_sse_type>
+    to_sse_type v_sse_reinterpret_as(const from_sse_type& val);
+
+#define OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(to_sse_type, from_sse_type, sse_cast_intrin) \
+    template<> inline \
+    to_sse_type v_sse_reinterpret_as(const from_sse_type& a) \
+    { return sse_cast_intrin(a); }
+
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128i, __m128i, OPENCV_HAL_NOP)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128i, __m128, _mm_castps_si128)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128i, __m128d, _mm_castpd_si128)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128, __m128i, _mm_castsi128_ps)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128, __m128, OPENCV_HAL_NOP)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128, __m128d, _mm_castpd_ps)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128d, __m128i, _mm_castsi128_pd)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128d, __m128, _mm_castps_pd)
+    OPENCV_HAL_IMPL_SSE_REINTERPRET_RAW(__m128d, __m128d, OPENCV_HAL_NOP)
+}
+
+#define OPENCV_HAL_IMPL_SSE_INITVEC(_Tpvec, _Tp, suffix, zsuffix, ssuffix, _Tps, cast) \
+inline _Tpvec v_setzero_##suffix() { return _Tpvec(_mm_setzero_##zsuffix()); } \
+inline _Tpvec v_setall_##suffix(_Tp v) { return _Tpvec(_mm_set1_##ssuffix((_Tps)v)); } \
+template <> inline _Tpvec v_setzero_() { return v_setzero_##suffix(); } \
+template <> inline _Tpvec v_setall_(_Tp v) { return v_setall_##suffix(v); } \
+template<typename _Tpvec0> inline _Tpvec v_reinterpret_as_##suffix(const _Tpvec0& a) \
+{ return _Tpvec(cast(a.val)); }
+
+OPENCV_HAL_IMPL_SSE_INITVEC(v_uint8x16, uchar, u8, si128, epi8, schar, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_INITVEC(v_int8x16, schar, s8, si128, epi8, schar, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_INITVEC(v_uint16x8, ushort, u16, si128, epi16, short, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_INITVEC(v_int16x8, short, s16, si128, epi16, short, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_INITVEC(v_uint32x4, unsigned, u32, si128, epi32, int, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_INITVEC(v_int32x4, int, s32, si128, epi32, int, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_INITVEC(v_float32x4, float, f32, ps, ps, float, _mm_castsi128_ps)
+OPENCV_HAL_IMPL_SSE_INITVEC(v_float64x2, double, f64, pd, pd, double, _mm_castsi128_pd)
+
+inline v_uint64x2 v_setzero_u64() { return v_uint64x2(_mm_setzero_si128()); }
+inline v_int64x2 v_setzero_s64() { return v_int64x2(_mm_setzero_si128()); }
+inline v_uint64x2 v_setall_u64(uint64 val) { return v_uint64x2(val, val); }
+inline v_int64x2 v_setall_s64(int64 val) { return v_int64x2(val, val); }
+
+template <> inline v_uint64x2 v_setzero_() { return v_setzero_u64(); }
+template <> inline v_int64x2 v_setzero_() { return v_setzero_s64(); }
+template <> inline v_uint64x2 v_setall_(uint64 val) { return v_setall_u64(val); }
+template <> inline v_int64x2 v_setall_(int64 val) { return v_setall_s64(val); }
+
+template<typename _Tpvec> inline
+v_uint64x2 v_reinterpret_as_u64(const _Tpvec& a) { return v_uint64x2(a.val); }
+template<typename _Tpvec> inline
+v_int64x2 v_reinterpret_as_s64(const _Tpvec& a) { return v_int64x2(a.val); }
+inline v_float32x4 v_reinterpret_as_f32(const v_uint64x2& a)
+{ return v_float32x4(_mm_castsi128_ps(a.val)); }
+inline v_float32x4 v_reinterpret_as_f32(const v_int64x2& a)
+{ return v_float32x4(_mm_castsi128_ps(a.val)); }
+inline v_float64x2 v_reinterpret_as_f64(const v_uint64x2& a)
+{ return v_float64x2(_mm_castsi128_pd(a.val)); }
+inline v_float64x2 v_reinterpret_as_f64(const v_int64x2& a)
+{ return v_float64x2(_mm_castsi128_pd(a.val)); }
+
+#define OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(_Tpvec, suffix) \
+inline _Tpvec v_reinterpret_as_##suffix(const v_float32x4& a) \
+{ return _Tpvec(_mm_castps_si128(a.val)); } \
+inline _Tpvec v_reinterpret_as_##suffix(const v_float64x2& a) \
+{ return _Tpvec(_mm_castpd_si128(a.val)); }
+
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint8x16, u8)
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int8x16, s8)
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint16x8, u16)
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int16x8, s16)
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint32x4, u32)
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int32x4, s32)
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_uint64x2, u64)
+OPENCV_HAL_IMPL_SSE_INIT_FROM_FLT(v_int64x2, s64)
+
+inline v_float32x4 v_reinterpret_as_f32(const v_float32x4& a) {return a; }
+inline v_float64x2 v_reinterpret_as_f64(const v_float64x2& a) {return a; }
+inline v_float32x4 v_reinterpret_as_f32(const v_float64x2& a) {return v_float32x4(_mm_castpd_ps(a.val)); }
+inline v_float64x2 v_reinterpret_as_f64(const v_float32x4& a) {return v_float64x2(_mm_castps_pd(a.val)); }
+
+//////////////// PACK ///////////////
+inline v_uint8x16 v_pack(const v_uint16x8& a, const v_uint16x8& b)
+{
+    __m128i delta = _mm_set1_epi16(255);
+    return v_uint8x16(_mm_packus_epi16(_mm_subs_epu16(a.val, _mm_subs_epu16(a.val, delta)),
+                                       _mm_subs_epu16(b.val, _mm_subs_epu16(b.val, delta))));
+}
+
+inline void v_pack_store(uchar* ptr, const v_uint16x8& a)
+{
+    __m128i delta = _mm_set1_epi16(255);
+    __m128i a1 = _mm_subs_epu16(a.val, _mm_subs_epu16(a.val, delta));
+    _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a1, a1));
+}
+
+inline v_uint8x16 v_pack_u(const v_int16x8& a, const v_int16x8& b)
+{ return v_uint8x16(_mm_packus_epi16(a.val, b.val)); }
+
+inline void v_pack_u_store(uchar* ptr, const v_int16x8& a)
+{ _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a.val, a.val)); }
+
+template<int n> inline
+v_uint8x16 v_rshr_pack(const v_uint16x8& a, const v_uint16x8& b)
+{
+    // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers.
+    __m128i delta = _mm_set1_epi16((short)(1 << (n-1)));
+    return v_uint8x16(_mm_packus_epi16(_mm_srli_epi16(_mm_adds_epu16(a.val, delta), n),
+                                       _mm_srli_epi16(_mm_adds_epu16(b.val, delta), n)));
+}
+
+template<int n> inline
+void v_rshr_pack_store(uchar* ptr, const v_uint16x8& a)
+{
+    __m128i delta = _mm_set1_epi16((short)(1 << (n-1)));
+    __m128i a1 = _mm_srli_epi16(_mm_adds_epu16(a.val, delta), n);
+    _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a1, a1));
+}
+
+template<int n> inline
+v_uint8x16 v_rshr_pack_u(const v_int16x8& a, const v_int16x8& b)
+{
+    __m128i delta = _mm_set1_epi16((short)(1 << (n-1)));
+    return v_uint8x16(_mm_packus_epi16(_mm_srai_epi16(_mm_adds_epi16(a.val, delta), n),
+                                       _mm_srai_epi16(_mm_adds_epi16(b.val, delta), n)));
+}
+
+template<int n> inline
+void v_rshr_pack_u_store(uchar* ptr, const v_int16x8& a)
+{
+    __m128i delta = _mm_set1_epi16((short)(1 << (n-1)));
+    __m128i a1 = _mm_srai_epi16(_mm_adds_epi16(a.val, delta), n);
+    _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi16(a1, a1));
+}
+
+inline v_int8x16 v_pack(const v_int16x8& a, const v_int16x8& b)
+{ return v_int8x16(_mm_packs_epi16(a.val, b.val)); }
+
+inline void v_pack_store(schar* ptr, const v_int16x8& a)
+{ _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi16(a.val, a.val)); }
+
+template<int n> inline
+v_int8x16 v_rshr_pack(const v_int16x8& a, const v_int16x8& b)
+{
+    // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers.
+    __m128i delta = _mm_set1_epi16((short)(1 << (n-1)));
+    return v_int8x16(_mm_packs_epi16(_mm_srai_epi16(_mm_adds_epi16(a.val, delta), n),
+                                     _mm_srai_epi16(_mm_adds_epi16(b.val, delta), n)));
+}
+template<int n> inline
+void v_rshr_pack_store(schar* ptr, const v_int16x8& a)
+{
+    // we assume that n > 0, and so the shifted 16-bit values can be treated as signed numbers.
+    __m128i delta = _mm_set1_epi16((short)(1 << (n-1)));
+    __m128i a1 = _mm_srai_epi16(_mm_adds_epi16(a.val, delta), n);
+    _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi16(a1, a1));
+}
+
+
+// byte-wise "mask ? a : b"
+inline __m128i v_select_si128(__m128i mask, __m128i a, __m128i b)
+{
+#if CV_SSE4_1
+    return _mm_blendv_epi8(b, a, mask);
+#else
+    return _mm_xor_si128(b, _mm_and_si128(_mm_xor_si128(a, b), mask));
+#endif
+}
+
+inline v_uint16x8 v_pack(const v_uint32x4& a, const v_uint32x4& b)
+{ return v_uint16x8(_v128_packs_epu32(a.val, b.val)); }
+
+inline void v_pack_store(ushort* ptr, const v_uint32x4& a)
+{
+    __m128i z = _mm_setzero_si128(), maxval32 = _mm_set1_epi32(65535), delta32 = _mm_set1_epi32(32768);
+    __m128i a1 = _mm_sub_epi32(v_select_si128(_mm_cmpgt_epi32(z, a.val), maxval32, a.val), delta32);
+    __m128i r = _mm_packs_epi32(a1, a1);
+    _mm_storel_epi64((__m128i*)ptr, _mm_sub_epi16(r, _mm_set1_epi16(-32768)));
+}
+
+template<int n> inline
+v_uint16x8 v_rshr_pack(const v_uint32x4& a, const v_uint32x4& b)
+{
+    __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768);
+    __m128i a1 = _mm_sub_epi32(_mm_srli_epi32(_mm_add_epi32(a.val, delta), n), delta32);
+    __m128i b1 = _mm_sub_epi32(_mm_srli_epi32(_mm_add_epi32(b.val, delta), n), delta32);
+    return v_uint16x8(_mm_sub_epi16(_mm_packs_epi32(a1, b1), _mm_set1_epi16(-32768)));
+}
+
+template<int n> inline
+void v_rshr_pack_store(ushort* ptr, const v_uint32x4& a)
+{
+    __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768);
+    __m128i a1 = _mm_sub_epi32(_mm_srli_epi32(_mm_add_epi32(a.val, delta), n), delta32);
+    __m128i a2 = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768));
+    _mm_storel_epi64((__m128i*)ptr, a2);
+}
+
+inline v_uint16x8 v_pack_u(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_SSE4_1
+    return v_uint16x8(_mm_packus_epi32(a.val, b.val));
+#else
+    __m128i delta32 = _mm_set1_epi32(32768);
+
+    // preliminary saturate negative values to zero
+    __m128i a1 = _mm_and_si128(a.val, _mm_cmpgt_epi32(a.val, _mm_set1_epi32(0)));
+    __m128i b1 = _mm_and_si128(b.val, _mm_cmpgt_epi32(b.val, _mm_set1_epi32(0)));
+
+    __m128i r = _mm_packs_epi32(_mm_sub_epi32(a1, delta32), _mm_sub_epi32(b1, delta32));
+    return v_uint16x8(_mm_sub_epi16(r, _mm_set1_epi16(-32768)));
+#endif
+}
+
+inline void v_pack_u_store(ushort* ptr, const v_int32x4& a)
+{
+#if CV_SSE4_1
+    _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi32(a.val, a.val));
+#else
+    __m128i delta32 = _mm_set1_epi32(32768);
+    __m128i a1 = _mm_sub_epi32(a.val, delta32);
+    __m128i r = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768));
+    _mm_storel_epi64((__m128i*)ptr, r);
+#endif
+}
+
+template<int n> inline
+v_uint16x8 v_rshr_pack_u(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_SSE4_1
+    __m128i delta = _mm_set1_epi32(1 << (n - 1));
+    return v_uint16x8(_mm_packus_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n),
+                                       _mm_srai_epi32(_mm_add_epi32(b.val, delta), n)));
+#else
+    __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768);
+    __m128i a1 = _mm_sub_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n), delta32);
+    __m128i a2 = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768));
+    __m128i b1 = _mm_sub_epi32(_mm_srai_epi32(_mm_add_epi32(b.val, delta), n), delta32);
+    __m128i b2 = _mm_sub_epi16(_mm_packs_epi32(b1, b1), _mm_set1_epi16(-32768));
+    return v_uint16x8(_mm_unpacklo_epi64(a2, b2));
+#endif
+}
+
+template<int n> inline
+void v_rshr_pack_u_store(ushort* ptr, const v_int32x4& a)
+{
+#if CV_SSE4_1
+    __m128i delta = _mm_set1_epi32(1 << (n - 1));
+    __m128i a1 = _mm_srai_epi32(_mm_add_epi32(a.val, delta), n);
+    _mm_storel_epi64((__m128i*)ptr, _mm_packus_epi32(a1, a1));
+#else
+    __m128i delta = _mm_set1_epi32(1 << (n-1)), delta32 = _mm_set1_epi32(32768);
+    __m128i a1 = _mm_sub_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n), delta32);
+    __m128i a2 = _mm_sub_epi16(_mm_packs_epi32(a1, a1), _mm_set1_epi16(-32768));
+    _mm_storel_epi64((__m128i*)ptr, a2);
+#endif
+}
+
+inline v_int16x8 v_pack(const v_int32x4& a, const v_int32x4& b)
+{ return v_int16x8(_mm_packs_epi32(a.val, b.val)); }
+
+inline void v_pack_store(short* ptr, const v_int32x4& a)
+{
+    _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi32(a.val, a.val));
+}
+
+template<int n> inline
+v_int16x8 v_rshr_pack(const v_int32x4& a, const v_int32x4& b)
+{
+    __m128i delta = _mm_set1_epi32(1 << (n-1));
+    return v_int16x8(_mm_packs_epi32(_mm_srai_epi32(_mm_add_epi32(a.val, delta), n),
+                                     _mm_srai_epi32(_mm_add_epi32(b.val, delta), n)));
+}
+
+template<int n> inline
+void v_rshr_pack_store(short* ptr, const v_int32x4& a)
+{
+    __m128i delta = _mm_set1_epi32(1 << (n-1));
+    __m128i a1 = _mm_srai_epi32(_mm_add_epi32(a.val, delta), n);
+    _mm_storel_epi64((__m128i*)ptr, _mm_packs_epi32(a1, a1));
+}
+
+
+// [a0 0 | b0 0]  [a1 0 | b1 0]
+inline v_uint32x4 v_pack(const v_uint64x2& a, const v_uint64x2& b)
+{
+    __m128i v0 = _mm_unpacklo_epi32(a.val, b.val); // a0 a1 0 0
+    __m128i v1 = _mm_unpackhi_epi32(a.val, b.val); // b0 b1 0 0
+    return v_uint32x4(_mm_unpacklo_epi32(v0, v1));
+}
+
+inline void v_pack_store(unsigned* ptr, const v_uint64x2& a)
+{
+    __m128i a1 = _mm_shuffle_epi32(a.val, _MM_SHUFFLE(0, 2, 2, 0));
+    _mm_storel_epi64((__m128i*)ptr, a1);
+}
+
+// [a0 0 | b0 0]  [a1 0 | b1 0]
+inline v_int32x4 v_pack(const v_int64x2& a, const v_int64x2& b)
+{
+    __m128i v0 = _mm_unpacklo_epi32(a.val, b.val); // a0 a1 0 0
+    __m128i v1 = _mm_unpackhi_epi32(a.val, b.val); // b0 b1 0 0
+    return v_int32x4(_mm_unpacklo_epi32(v0, v1));
+}
+
+inline void v_pack_store(int* ptr, const v_int64x2& a)
+{
+    __m128i a1 = _mm_shuffle_epi32(a.val, _MM_SHUFFLE(0, 2, 2, 0));
+    _mm_storel_epi64((__m128i*)ptr, a1);
+}
+
+template<int n> inline
+v_uint32x4 v_rshr_pack(const v_uint64x2& a, const v_uint64x2& b)
+{
+    uint64 delta = (uint64)1 << (n-1);
+    v_uint64x2 delta2(delta, delta);
+    __m128i a1 = _mm_srli_epi64(_mm_add_epi64(a.val, delta2.val), n);
+    __m128i b1 = _mm_srli_epi64(_mm_add_epi64(b.val, delta2.val), n);
+    __m128i v0 = _mm_unpacklo_epi32(a1, b1); // a0 a1 0 0
+    __m128i v1 = _mm_unpackhi_epi32(a1, b1); // b0 b1 0 0
+    return v_uint32x4(_mm_unpacklo_epi32(v0, v1));
+}
+
+template<int n> inline
+void v_rshr_pack_store(unsigned* ptr, const v_uint64x2& a)
+{
+    uint64 delta = (uint64)1 << (n-1);
+    v_uint64x2 delta2(delta, delta);
+    __m128i a1 = _mm_srli_epi64(_mm_add_epi64(a.val, delta2.val), n);
+    __m128i a2 = _mm_shuffle_epi32(a1, _MM_SHUFFLE(0, 2, 2, 0));
+    _mm_storel_epi64((__m128i*)ptr, a2);
+}
+
+inline __m128i v_sign_epi64(__m128i a)
+{
+    return _mm_shuffle_epi32(_mm_srai_epi32(a, 31), _MM_SHUFFLE(3, 3, 1, 1)); // x m0 | x m1
+}
+
+inline __m128i v_srai_epi64(__m128i a, int imm)
+{
+    __m128i smask = v_sign_epi64(a);
+    return _mm_xor_si128(_mm_srli_epi64(_mm_xor_si128(a, smask), imm), smask);
+}
+
+template<int n> inline
+v_int32x4 v_rshr_pack(const v_int64x2& a, const v_int64x2& b)
+{
+    int64 delta = (int64)1 << (n-1);
+    v_int64x2 delta2(delta, delta);
+    __m128i a1 = v_srai_epi64(_mm_add_epi64(a.val, delta2.val), n);
+    __m128i b1 = v_srai_epi64(_mm_add_epi64(b.val, delta2.val), n);
+    __m128i v0 = _mm_unpacklo_epi32(a1, b1); // a0 a1 0 0
+    __m128i v1 = _mm_unpackhi_epi32(a1, b1); // b0 b1 0 0
+    return v_int32x4(_mm_unpacklo_epi32(v0, v1));
+}
+
+template<int n> inline
+void v_rshr_pack_store(int* ptr, const v_int64x2& a)
+{
+    int64 delta = (int64)1 << (n-1);
+    v_int64x2 delta2(delta, delta);
+    __m128i a1 = v_srai_epi64(_mm_add_epi64(a.val, delta2.val), n);
+    __m128i a2 = _mm_shuffle_epi32(a1, _MM_SHUFFLE(0, 2, 2, 0));
+    _mm_storel_epi64((__m128i*)ptr, a2);
+}
+
+// pack boolean
+inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b)
+{
+    __m128i ab = _mm_packs_epi16(a.val, b.val);
+    return v_uint8x16(ab);
+}
+
+inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b,
+                           const v_uint32x4& c, const v_uint32x4& d)
+{
+    __m128i ab = _mm_packs_epi32(a.val, b.val);
+    __m128i cd = _mm_packs_epi32(c.val, d.val);
+    return v_uint8x16(_mm_packs_epi16(ab, cd));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                           const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f,
+                           const v_uint64x2& g, const v_uint64x2& h)
+{
+    __m128i ab = _mm_packs_epi32(a.val, b.val);
+    __m128i cd = _mm_packs_epi32(c.val, d.val);
+    __m128i ef = _mm_packs_epi32(e.val, f.val);
+    __m128i gh = _mm_packs_epi32(g.val, h.val);
+
+    __m128i abcd = _mm_packs_epi32(ab, cd);
+    __m128i efgh = _mm_packs_epi32(ef, gh);
+    return v_uint8x16(_mm_packs_epi16(abcd, efgh));
+}
+
+inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
+                            const v_float32x4& m1, const v_float32x4& m2,
+                            const v_float32x4& m3)
+{
+    __m128 v0 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(0, 0, 0, 0)), m0.val);
+    __m128 v1 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(1, 1, 1, 1)), m1.val);
+    __m128 v2 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(2, 2, 2, 2)), m2.val);
+    __m128 v3 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(3, 3, 3, 3)), m3.val);
+
+    return v_float32x4(_mm_add_ps(_mm_add_ps(v0, v1), _mm_add_ps(v2, v3)));
+}
+
+inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0,
+                               const v_float32x4& m1, const v_float32x4& m2,
+                               const v_float32x4& a)
+{
+    __m128 v0 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(0, 0, 0, 0)), m0.val);
+    __m128 v1 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(1, 1, 1, 1)), m1.val);
+    __m128 v2 = _mm_mul_ps(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE(2, 2, 2, 2)), m2.val);
+
+    return v_float32x4(_mm_add_ps(_mm_add_ps(v0, v1), _mm_add_ps(v2, a.val)));
+}
+
+#define OPENCV_HAL_IMPL_SSE_BIN_OP(bin_op, _Tpvec, intrin) \
+    inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b) \
+    { \
+        return _Tpvec(intrin(a.val, b.val)); \
+    }
+
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_uint8x16, _mm_adds_epu8)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_uint8x16, _mm_subs_epu8)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_int8x16, _mm_adds_epi8)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_int8x16, _mm_subs_epi8)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_uint16x8, _mm_adds_epu16)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_uint16x8, _mm_subs_epu16)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_int16x8, _mm_adds_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_int16x8, _mm_subs_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_uint32x4, _mm_add_epi32)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_uint32x4, _mm_sub_epi32)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_mul, v_uint32x4, _v128_mullo_epi32)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_int32x4, _mm_add_epi32)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_int32x4, _mm_sub_epi32)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_mul, v_int32x4, _v128_mullo_epi32)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_float32x4, _mm_add_ps)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_float32x4, _mm_sub_ps)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_mul, v_float32x4, _mm_mul_ps)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_div, v_float32x4, _mm_div_ps)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_float64x2, _mm_add_pd)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_float64x2, _mm_sub_pd)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_mul, v_float64x2, _mm_mul_pd)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_div, v_float64x2, _mm_div_pd)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_uint64x2, _mm_add_epi64)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_uint64x2, _mm_sub_epi64)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_add, v_int64x2, _mm_add_epi64)
+OPENCV_HAL_IMPL_SSE_BIN_OP(v_sub, v_int64x2, _mm_sub_epi64)
+
+// saturating multiply 8-bit, 16-bit
+#define OPENCV_HAL_IMPL_SSE_MUL_SAT(_Tpvec, _Tpwvec)             \
+    inline _Tpvec v_mul(const _Tpvec& a, const _Tpvec& b)        \
+    {                                                            \
+        _Tpwvec c, d;                                            \
+        v_mul_expand(a, b, c, d);                                \
+        return v_pack(c, d);                                     \
+    }
+
+OPENCV_HAL_IMPL_SSE_MUL_SAT(v_uint8x16, v_uint16x8)
+OPENCV_HAL_IMPL_SSE_MUL_SAT(v_int8x16,  v_int16x8)
+OPENCV_HAL_IMPL_SSE_MUL_SAT(v_uint16x8, v_uint32x4)
+OPENCV_HAL_IMPL_SSE_MUL_SAT(v_int16x8,  v_int32x4)
+
+//  Multiply and expand
+inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b,
+                         v_uint16x8& c, v_uint16x8& d)
+{
+    v_uint16x8 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b,
+                         v_int16x8& c, v_int16x8& d)
+{
+    v_int16x8 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b,
+                         v_int32x4& c, v_int32x4& d)
+{
+    __m128i v0 = _mm_mullo_epi16(a.val, b.val);
+    __m128i v1 = _mm_mulhi_epi16(a.val, b.val);
+    c.val = _mm_unpacklo_epi16(v0, v1);
+    d.val = _mm_unpackhi_epi16(v0, v1);
+}
+
+inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b,
+                         v_uint32x4& c, v_uint32x4& d)
+{
+    __m128i v0 = _mm_mullo_epi16(a.val, b.val);
+    __m128i v1 = _mm_mulhi_epu16(a.val, b.val);
+    c.val = _mm_unpacklo_epi16(v0, v1);
+    d.val = _mm_unpackhi_epi16(v0, v1);
+}
+
+inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b,
+                         v_uint64x2& c, v_uint64x2& d)
+{
+    __m128i c0 = _mm_mul_epu32(a.val, b.val);
+    __m128i c1 = _mm_mul_epu32(_mm_srli_epi64(a.val, 32), _mm_srli_epi64(b.val, 32));
+    c.val = _mm_unpacklo_epi64(c0, c1);
+    d.val = _mm_unpackhi_epi64(c0, c1);
+}
+
+inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b) { return v_int16x8(_mm_mulhi_epi16(a.val, b.val)); }
+inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b) { return v_uint16x8(_mm_mulhi_epu16(a.val, b.val)); }
+
+//////// Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
+{ return v_int32x4(_mm_madd_epi16(a.val, b.val)); }
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 32 >> 64
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_SSE4_1
+    __m128i even = _mm_mul_epi32(a.val, b.val);
+    __m128i odd = _mm_mul_epi32(_mm_srli_epi64(a.val, 32), _mm_srli_epi64(b.val, 32));
+    return v_int64x2(_mm_add_epi64(even, odd));
+#else
+    __m128i even_u = _mm_mul_epu32(a.val, b.val);
+    __m128i odd_u = _mm_mul_epu32(_mm_srli_epi64(a.val, 32), _mm_srli_epi64(b.val, 32));
+    // convert unsigned to signed high multiplication (from: Agner Fog(veclib) and H S Warren: Hacker's delight, 2003, p. 132)
+    __m128i a_sign = _mm_srai_epi32(a.val, 31);
+    __m128i b_sign = _mm_srai_epi32(b.val, 31);
+    // |x * sign of x
+    __m128i axb  = _mm_and_si128(a.val, b_sign);
+    __m128i bxa  = _mm_and_si128(b.val, a_sign);
+    // sum of sign corrections
+    __m128i ssum = _mm_add_epi32(bxa, axb);
+    __m128i even_ssum = _mm_slli_epi64(ssum, 32);
+    __m128i odd_ssum = _mm_and_si128(ssum, _mm_set_epi32(-1, 0, -1, 0));
+    // convert to signed and prod
+    return v_int64x2(_mm_add_epi64(_mm_sub_epi64(even_u, even_ssum), _mm_sub_epi64(odd_u, odd_ssum)));
+#endif
+}
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
+{
+    __m128i a0 = _mm_srli_epi16(_mm_slli_si128(a.val, 1), 8); // even
+    __m128i a1 = _mm_srli_epi16(a.val, 8); // odd
+    __m128i b0 = _mm_srli_epi16(_mm_slli_si128(b.val, 1), 8);
+    __m128i b1 = _mm_srli_epi16(b.val, 8);
+    __m128i p0 = _mm_madd_epi16(a0, b0);
+    __m128i p1 = _mm_madd_epi16(a1, b1);
+    return v_uint32x4(_mm_add_epi32(p0, p1));
+}
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
+{
+    __m128i a0 = _mm_srai_epi16(_mm_slli_si128(a.val, 1), 8); // even
+    __m128i a1 = _mm_srai_epi16(a.val, 8); // odd
+    __m128i b0 = _mm_srai_epi16(_mm_slli_si128(b.val, 1), 8);
+    __m128i b1 = _mm_srai_epi16(b.val, 8);
+    __m128i p0 = _mm_madd_epi16(a0, b0);
+    __m128i p1 = _mm_madd_epi16(a1, b1);
+    return v_int32x4(_mm_add_epi32(p0, p1));
+}
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v_uint32x4 c, d;
+    v_mul_expand(a, b, c, d);
+
+    v_uint64x2 c0, c1, d0, d1;
+    v_expand(c, c0, c1);
+    v_expand(d, d0, d1);
+
+    c0 = v_add(c0, c1); d0 = v_add(d0, d1);
+    return v_uint64x2(_mm_add_epi64(
+        _mm_unpacklo_epi64(c0.val, d0.val),
+        _mm_unpackhi_epi64(c0.val, d0.val)
+    ));
+}
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b)
+{
+    v_int32x4 prod = v_dotprod(a, b);
+    v_int64x2 c, d;
+    v_expand(prod, c, d);
+    return v_int64x2(_mm_add_epi64(
+        _mm_unpacklo_epi64(c.val, d.val),
+        _mm_unpackhi_epi64(c.val, d.val)
+    ));
+}
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_SSE4_1
+    return v_cvt_f64(v_dotprod(a, b));
+#else
+    v_float64x2 c = v_mul(v_cvt_f64(a), v_cvt_f64(b));
+    v_float64x2 d = v_mul(v_cvt_f64_high(a), v_cvt_f64_high(b));
+
+    return v_float64x2(_mm_add_pd(
+        _mm_unpacklo_pd(c.val, d.val),
+        _mm_unpackhi_pd(c.val, d.val)
+    ));
+#endif
+}
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b)
+{ return v_dotprod(a, b); }
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 32 >> 64
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod(a, b); }
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_add(v_dotprod_fast(a, b), c); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
+{
+    __m128i a0 = v_expand_low(a).val;
+    __m128i a1 = v_expand_high(a).val;
+    __m128i b0 = v_expand_low(b).val;
+    __m128i b1 = v_expand_high(b).val;
+    __m128i p0 = _mm_madd_epi16(a0, b0);
+    __m128i p1 = _mm_madd_epi16(a1, b1);
+    return v_uint32x4(_mm_add_epi32(p0, p1));
+}
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
+{
+#if CV_SSE4_1
+    __m128i a0 = _mm_cvtepi8_epi16(a.val);
+    __m128i a1 = v_expand_high(a).val;
+    __m128i b0 = _mm_cvtepi8_epi16(b.val);
+    __m128i b1 = v_expand_high(b).val;
+    __m128i p0 = _mm_madd_epi16(a0, b0);
+    __m128i p1 = _mm_madd_epi16(a1, b1);
+    return v_int32x4(_mm_add_epi32(p0, p1));
+#else
+    return v_dotprod_expand(a, b);
+#endif
+}
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v_uint32x4 c, d;
+    v_mul_expand(a, b, c, d);
+
+    v_uint64x2 c0, c1, d0, d1;
+    v_expand(c, c0, c1);
+    v_expand(d, d0, d1);
+
+    c0 = v_add(c0, c1); d0 = v_add(d0, d1);
+    return v_add(c0, d0);
+}
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b)
+{
+    v_int32x4 prod = v_dotprod(a, b);
+    v_int64x2 c, d;
+    v_expand(prod, c, d);
+    return v_add(c, d);
+}
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 32 >> 64f
+v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c);
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_fma(v_cvt_f64(a), v_cvt_f64(b), v_mul(v_cvt_f64_high(a), v_cvt_f64_high(b))); }
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a,   const v_int32x4& b, const v_float64x2& c)
+{ return v_fma(v_cvt_f64(a), v_cvt_f64(b), v_fma(v_cvt_f64_high(a), v_cvt_f64_high(b), c)); }
+
+#define OPENCV_HAL_IMPL_SSE_LOGIC_OP(_Tpvec, suffix, not_const) \
+    OPENCV_HAL_IMPL_SSE_BIN_OP(v_and, _Tpvec, _mm_and_##suffix) \
+    OPENCV_HAL_IMPL_SSE_BIN_OP(v_or, _Tpvec, _mm_or_##suffix)   \
+    OPENCV_HAL_IMPL_SSE_BIN_OP(v_xor, _Tpvec, _mm_xor_##suffix) \
+    inline _Tpvec v_not(const _Tpvec& a) \
+    { \
+        return _Tpvec(_mm_xor_##suffix(a.val, not_const)); \
+    }
+
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint8x16, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int8x16, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint16x8, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int16x8, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint32x4, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int32x4, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_uint64x2, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_int64x2, si128, _mm_set1_epi32(-1))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_float32x4, ps, _mm_castsi128_ps(_mm_set1_epi32(-1)))
+OPENCV_HAL_IMPL_SSE_LOGIC_OP(v_float64x2, pd, _mm_castsi128_pd(_mm_set1_epi32(-1)))
+
+inline v_float32x4 v_sqrt(const v_float32x4& x)
+{ return v_float32x4(_mm_sqrt_ps(x.val)); }
+
+inline v_float32x4 v_invsqrt(const v_float32x4& x)
+{
+    const __m128 _0_5 = _mm_set1_ps(0.5f), _1_5 = _mm_set1_ps(1.5f);
+    __m128 t = x.val;
+    __m128 h = _mm_mul_ps(t, _0_5);
+    t = _mm_rsqrt_ps(t);
+    t = _mm_mul_ps(t, _mm_sub_ps(_1_5, _mm_mul_ps(_mm_mul_ps(t, t), h)));
+    return v_float32x4(t);
+}
+
+inline v_float64x2 v_sqrt(const v_float64x2& x)
+{ return v_float64x2(_mm_sqrt_pd(x.val)); }
+
+inline v_float64x2 v_invsqrt(const v_float64x2& x)
+{
+    const __m128d v_1 = _mm_set1_pd(1.);
+    return v_float64x2(_mm_div_pd(v_1, _mm_sqrt_pd(x.val)));
+}
+
+#define OPENCV_HAL_IMPL_SSE_ABS_INT_FUNC(_Tpuvec, _Tpsvec, func, suffix, subWidth) \
+inline _Tpuvec v_abs(const _Tpsvec& x) \
+{ return _Tpuvec(_mm_##func##_ep##suffix(x.val, _mm_sub_ep##subWidth(_mm_setzero_si128(), x.val))); }
+
+OPENCV_HAL_IMPL_SSE_ABS_INT_FUNC(v_uint8x16, v_int8x16, min, u8, i8)
+OPENCV_HAL_IMPL_SSE_ABS_INT_FUNC(v_uint16x8, v_int16x8, max, i16, i16)
+inline v_uint32x4 v_abs(const v_int32x4& x)
+{
+    __m128i s = _mm_srli_epi32(x.val, 31);
+    __m128i f = _mm_srai_epi32(x.val, 31);
+    return v_uint32x4(_mm_add_epi32(_mm_xor_si128(x.val, f), s));
+}
+inline v_float32x4 v_abs(const v_float32x4& x)
+{ return v_float32x4(_mm_and_ps(x.val, _mm_castsi128_ps(_mm_set1_epi32(0x7fffffff)))); }
+inline v_float64x2 v_abs(const v_float64x2& x)
+{
+    return v_float64x2(_mm_and_pd(x.val,
+        _mm_castsi128_pd(_mm_srli_epi64(_mm_set1_epi32(-1), 1))));
+}
+
+// TODO: exp, log, sin, cos
+
+#define OPENCV_HAL_IMPL_SSE_BIN_FUNC(_Tpvec, func, intrin) \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_min, _mm_min_epu8)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_max, _mm_max_epu8)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_min, _mm_min_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_max, _mm_max_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float32x4, v_min, _mm_min_ps)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float32x4, v_max, _mm_max_ps)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float64x2, v_min, _mm_min_pd)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_float64x2, v_max, _mm_max_pd)
+
+inline v_int8x16 v_min(const v_int8x16& a, const v_int8x16& b)
+{
+#if CV_SSE4_1
+    return v_int8x16(_mm_min_epi8(a.val, b.val));
+#else
+    __m128i delta = _mm_set1_epi8((char)-128);
+    return v_int8x16(_mm_xor_si128(delta, _mm_min_epu8(_mm_xor_si128(a.val, delta),
+                                                       _mm_xor_si128(b.val, delta))));
+#endif
+}
+inline v_int8x16 v_max(const v_int8x16& a, const v_int8x16& b)
+{
+#if CV_SSE4_1
+    return v_int8x16(_mm_max_epi8(a.val, b.val));
+#else
+    __m128i delta = _mm_set1_epi8((char)-128);
+    return v_int8x16(_mm_xor_si128(delta, _mm_max_epu8(_mm_xor_si128(a.val, delta),
+                                                       _mm_xor_si128(b.val, delta))));
+#endif
+}
+inline v_uint16x8 v_min(const v_uint16x8& a, const v_uint16x8& b)
+{
+#if CV_SSE4_1
+    return v_uint16x8(_mm_min_epu16(a.val, b.val));
+#else
+    return v_uint16x8(_mm_subs_epu16(a.val, _mm_subs_epu16(a.val, b.val)));
+#endif
+}
+inline v_uint16x8 v_max(const v_uint16x8& a, const v_uint16x8& b)
+{
+#if CV_SSE4_1
+    return v_uint16x8(_mm_max_epu16(a.val, b.val));
+#else
+    return v_uint16x8(_mm_adds_epu16(_mm_subs_epu16(a.val, b.val), b.val));
+#endif
+}
+inline v_uint32x4 v_min(const v_uint32x4& a, const v_uint32x4& b)
+{
+#if CV_SSE4_1
+    return v_uint32x4(_mm_min_epu32(a.val, b.val));
+#else
+    __m128i delta = _mm_set1_epi32((int)0x80000000);
+    __m128i mask = _mm_cmpgt_epi32(_mm_xor_si128(a.val, delta), _mm_xor_si128(b.val, delta));
+    return v_uint32x4(v_select_si128(mask, b.val, a.val));
+#endif
+}
+inline v_uint32x4 v_max(const v_uint32x4& a, const v_uint32x4& b)
+{
+#if CV_SSE4_1
+    return v_uint32x4(_mm_max_epu32(a.val, b.val));
+#else
+    __m128i delta = _mm_set1_epi32((int)0x80000000);
+    __m128i mask = _mm_cmpgt_epi32(_mm_xor_si128(a.val, delta), _mm_xor_si128(b.val, delta));
+    return v_uint32x4(v_select_si128(mask, a.val, b.val));
+#endif
+}
+inline v_int32x4 v_min(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_SSE4_1
+    return v_int32x4(_mm_min_epi32(a.val, b.val));
+#else
+    return v_int32x4(v_select_si128(_mm_cmpgt_epi32(a.val, b.val), b.val, a.val));
+#endif
+}
+inline v_int32x4 v_max(const v_int32x4& a, const v_int32x4& b)
+{
+#if CV_SSE4_1
+    return v_int32x4(_mm_max_epi32(a.val, b.val));
+#else
+    return v_int32x4(v_select_si128(_mm_cmpgt_epi32(a.val, b.val), a.val, b.val));
+#endif
+}
+
+#define OPENCV_HAL_IMPL_SSE_INT_CMP_OP(_Tpuvec, _Tpsvec, suffix, sbit) \
+inline _Tpuvec v_eq(const _Tpuvec& a, const _Tpuvec& b) \
+{ return _Tpuvec(_mm_cmpeq_##suffix(a.val, b.val)); } \
+inline _Tpuvec v_ne(const _Tpuvec& a, const _Tpuvec& b) \
+{ \
+    __m128i not_mask = _mm_set1_epi32(-1); \
+    return _Tpuvec(_mm_xor_si128(_mm_cmpeq_##suffix(a.val, b.val), not_mask)); \
+} \
+inline _Tpsvec v_eq(const _Tpsvec& a, const _Tpsvec& b) \
+{ return _Tpsvec(_mm_cmpeq_##suffix(a.val, b.val)); } \
+inline _Tpsvec v_ne(const _Tpsvec& a, const _Tpsvec& b) \
+{ \
+    __m128i not_mask = _mm_set1_epi32(-1); \
+    return _Tpsvec(_mm_xor_si128(_mm_cmpeq_##suffix(a.val, b.val), not_mask)); \
+} \
+inline _Tpuvec v_lt(const _Tpuvec& a, const _Tpuvec& b) \
+{ \
+    __m128i smask = _mm_set1_##suffix(sbit); \
+    return _Tpuvec(_mm_cmpgt_##suffix(_mm_xor_si128(b.val, smask), _mm_xor_si128(a.val, smask))); \
+} \
+inline _Tpuvec v_gt(const _Tpuvec& a, const _Tpuvec& b) \
+{ \
+    __m128i smask = _mm_set1_##suffix(sbit); \
+    return _Tpuvec(_mm_cmpgt_##suffix(_mm_xor_si128(a.val, smask), _mm_xor_si128(b.val, smask))); \
+} \
+inline _Tpuvec v_le(const _Tpuvec& a, const _Tpuvec& b) \
+{ \
+    __m128i smask = _mm_set1_##suffix(sbit); \
+    __m128i not_mask = _mm_set1_epi32(-1); \
+    __m128i res = _mm_cmpgt_##suffix(_mm_xor_si128(a.val, smask), _mm_xor_si128(b.val, smask)); \
+    return _Tpuvec(_mm_xor_si128(res, not_mask)); \
+} \
+inline _Tpuvec v_ge(const _Tpuvec& a, const _Tpuvec& b) \
+{ \
+    __m128i smask = _mm_set1_##suffix(sbit); \
+    __m128i not_mask = _mm_set1_epi32(-1); \
+    __m128i res = _mm_cmpgt_##suffix(_mm_xor_si128(b.val, smask), _mm_xor_si128(a.val, smask)); \
+    return _Tpuvec(_mm_xor_si128(res, not_mask)); \
+} \
+inline _Tpsvec v_lt(const _Tpsvec& a, const _Tpsvec& b) \
+{ \
+    return _Tpsvec(_mm_cmpgt_##suffix(b.val, a.val)); \
+} \
+inline _Tpsvec v_gt(const _Tpsvec& a, const _Tpsvec& b) \
+{ \
+    return _Tpsvec(_mm_cmpgt_##suffix(a.val, b.val)); \
+} \
+inline _Tpsvec v_le(const _Tpsvec& a, const _Tpsvec& b) \
+{ \
+    __m128i not_mask = _mm_set1_epi32(-1); \
+    return _Tpsvec(_mm_xor_si128(_mm_cmpgt_##suffix(a.val, b.val), not_mask)); \
+} \
+inline _Tpsvec v_ge(const _Tpsvec& a, const _Tpsvec& b) \
+{ \
+    __m128i not_mask = _mm_set1_epi32(-1); \
+    return _Tpsvec(_mm_xor_si128(_mm_cmpgt_##suffix(b.val, a.val), not_mask)); \
+}
+
+OPENCV_HAL_IMPL_SSE_INT_CMP_OP(v_uint8x16, v_int8x16, epi8, (char)-128)
+OPENCV_HAL_IMPL_SSE_INT_CMP_OP(v_uint16x8, v_int16x8, epi16, (short)-32768)
+OPENCV_HAL_IMPL_SSE_INT_CMP_OP(v_uint32x4, v_int32x4, epi32, (int)0x80000000)
+
+#define OPENCV_HAL_IMPL_SSE_FLT_CMP_OP(_Tpvec, suffix) \
+inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(_mm_cmpeq_##suffix(a.val, b.val)); } \
+inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(_mm_cmpneq_##suffix(a.val, b.val)); } \
+inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(_mm_cmplt_##suffix(a.val, b.val)); } \
+inline _Tpvec v_gt(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(_mm_cmpgt_##suffix(a.val, b.val)); } \
+inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(_mm_cmple_##suffix(a.val, b.val)); } \
+inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(_mm_cmpge_##suffix(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_SSE_FLT_CMP_OP(v_float32x4, ps)
+OPENCV_HAL_IMPL_SSE_FLT_CMP_OP(v_float64x2, pd)
+
+#if CV_SSE4_1
+#define OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(_Tpvec) \
+inline _Tpvec v_eq (const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(_mm_cmpeq_epi64(a.val, b.val)); } \
+inline _Tpvec v_ne (const _Tpvec& a, const _Tpvec& b) \
+{ return v_not(v_eq(a, b)); }
+#else
+#define OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(_Tpvec) \
+inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b) \
+{ __m128i cmp = _mm_cmpeq_epi32(a.val, b.val); \
+  return _Tpvec(_mm_and_si128(cmp, _mm_shuffle_epi32(cmp, _MM_SHUFFLE(2, 3, 0, 1)))); } \
+inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b) \
+{ return v_not(v_eq(a, b)); }
+#endif
+
+OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_uint64x2)
+OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_int64x2)
+
+inline v_float32x4 v_not_nan(const v_float32x4& a)
+{ return v_float32x4(_mm_cmpord_ps(a.val, a.val)); }
+inline v_float64x2 v_not_nan(const v_float64x2& a)
+{ return v_float64x2(_mm_cmpord_pd(a.val, a.val)); }
+
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_add_wrap, _mm_add_epi8)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int8x16, v_add_wrap, _mm_add_epi8)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_add_wrap, _mm_add_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_add_wrap, _mm_add_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_sub_wrap, _mm_sub_epi8)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int8x16, v_sub_wrap, _mm_sub_epi8)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_sub_wrap, _mm_sub_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_sub_wrap, _mm_sub_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_mul_wrap, _mm_mullo_epi16)
+OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int16x8, v_mul_wrap, _mm_mullo_epi16)
+
+inline v_uint8x16 v_mul_wrap(const v_uint8x16& a, const v_uint8x16& b)
+{
+    __m128i ad = _mm_srai_epi16(a.val, 8);
+    __m128i bd = _mm_srai_epi16(b.val, 8);
+    __m128i p0 = _mm_mullo_epi16(a.val, b.val); // even
+    __m128i p1 = _mm_slli_epi16(_mm_mullo_epi16(ad, bd), 8); // odd
+    const __m128i b01 = _mm_set1_epi32(0xFF00FF00);
+    return v_uint8x16(_v128_blendv_epi8(p0, p1, b01));
+}
+inline v_int8x16 v_mul_wrap(const v_int8x16& a, const v_int8x16& b)
+{
+    return v_reinterpret_as_s8(v_mul_wrap(v_reinterpret_as_u8(a), v_reinterpret_as_u8(b)));
+}
+
+/** Absolute difference **/
+
+inline v_uint8x16 v_absdiff(const v_uint8x16& a, const v_uint8x16& b)
+{ return v_add_wrap(v_sub(a, b),  v_sub(b, a)); }
+inline v_uint16x8 v_absdiff(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_add_wrap(v_sub(a, b),  v_sub(b, a)); }
+inline v_uint32x4 v_absdiff(const v_uint32x4& a, const v_uint32x4& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+inline v_uint8x16 v_absdiff(const v_int8x16& a, const v_int8x16& b)
+{
+    v_int8x16 d = v_sub_wrap(a, b);
+    v_int8x16 m = v_lt(a, b);
+    return v_reinterpret_as_u8(v_sub_wrap(v_xor(d, m), m));
+}
+inline v_uint16x8 v_absdiff(const v_int16x8& a, const v_int16x8& b)
+{
+    return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b)));
+}
+inline v_uint32x4 v_absdiff(const v_int32x4& a, const v_int32x4& b)
+{
+    v_int32x4 d = v_sub(a, b);
+    v_int32x4 m = v_lt(a, b);
+    return v_reinterpret_as_u32(v_sub(v_xor(d, m), m));
+}
+
+/** Saturating absolute difference **/
+inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b)
+{
+    v_int8x16 d = v_sub(a, b);
+    v_int8x16 m = v_lt(a, b);
+    return v_sub(v_xor(d, m), m);
+ }
+inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+
+inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_add(v_mul(a, b), c);
+}
+
+inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_float32x4 v_fma(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+#if CV_FMA3
+    return v_float32x4(_mm_fmadd_ps(a.val, b.val, c.val));
+#else
+    return v_float32x4(_mm_add_ps(_mm_mul_ps(a.val, b.val), c.val));
+#endif
+}
+
+inline v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+#if CV_FMA3
+    return v_float64x2(_mm_fmadd_pd(a.val, b.val, c.val));
+#else
+    return v_float64x2(_mm_add_pd(_mm_mul_pd(a.val, b.val), c.val));
+#endif
+}
+
+#define OPENCV_HAL_IMPL_SSE_MISC_FLT_OP(_Tpvec, _Tp, _Tpreg, suffix, absmask_vec) \
+inline _Tpvec v_absdiff(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    _Tpreg absmask = _mm_castsi128_##suffix(absmask_vec); \
+    return _Tpvec(_mm_and_##suffix(_mm_sub_##suffix(a.val, b.val), absmask)); \
+} \
+inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    _Tpvec res = v_fma(a, a, v_mul(b, b)); \
+    return _Tpvec(_mm_sqrt_##suffix(res.val)); \
+} \
+inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return v_fma(a, a, v_mul(b, b)); \
+} \
+inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \
+{ \
+    return v_fma(a, b, c); \
+}
+
+OPENCV_HAL_IMPL_SSE_MISC_FLT_OP(v_float32x4, float, __m128, ps, _mm_set1_epi32((int)0x7fffffff))
+OPENCV_HAL_IMPL_SSE_MISC_FLT_OP(v_float64x2, double, __m128d, pd, _mm_srli_epi64(_mm_set1_epi32(-1), 1))
+
+#define OPENCV_HAL_IMPL_SSE_SHIFT_OP(_Tpuvec, _Tpsvec, suffix, srai) \
+inline _Tpuvec v_shl(const _Tpuvec& a, int imm) \
+{ \
+    return _Tpuvec(_mm_slli_##suffix(a.val, imm)); \
+} \
+inline _Tpsvec v_shl(const _Tpsvec& a, int imm) \
+{ \
+    return _Tpsvec(_mm_slli_##suffix(a.val, imm)); \
+} \
+inline _Tpuvec v_shr(const _Tpuvec& a, int imm) \
+{ \
+    return _Tpuvec(_mm_srli_##suffix(a.val, imm)); \
+} \
+inline _Tpsvec v_shr(const _Tpsvec& a, int imm) \
+{ \
+    return _Tpsvec(srai(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpuvec v_shl(const _Tpuvec& a) \
+{ \
+    return _Tpuvec(_mm_slli_##suffix(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpsvec v_shl(const _Tpsvec& a) \
+{ \
+    return _Tpsvec(_mm_slli_##suffix(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpuvec v_shr(const _Tpuvec& a) \
+{ \
+    return _Tpuvec(_mm_srli_##suffix(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpsvec v_shr(const _Tpsvec& a) \
+{ \
+    return _Tpsvec(srai(a.val, imm)); \
+}
+
+OPENCV_HAL_IMPL_SSE_SHIFT_OP(v_uint16x8, v_int16x8, epi16, _mm_srai_epi16)
+OPENCV_HAL_IMPL_SSE_SHIFT_OP(v_uint32x4, v_int32x4, epi32, _mm_srai_epi32)
+OPENCV_HAL_IMPL_SSE_SHIFT_OP(v_uint64x2, v_int64x2, epi64, v_srai_epi64)
+
+namespace hal_sse_internal
+{
+    template <int imm,
+        bool is_invalid = ((imm < 0) || (imm > 16)),
+        bool is_first = (imm == 0),
+        bool is_half = (imm == 8),
+        bool is_second = (imm == 16),
+        bool is_other = (((imm > 0) && (imm < 8)) || ((imm > 8) && (imm < 16)))>
+    class v_sse_palignr_u8_class;
+
+    template <int imm>
+    class v_sse_palignr_u8_class<imm, true, false, false, false, false>;
+
+    template <int imm>
+    class v_sse_palignr_u8_class<imm, false, true, false, false, false>
+    {
+    public:
+        inline __m128i operator()(const __m128i& a, const __m128i&) const
+        {
+            return a;
+        }
+    };
+
+    template <int imm>
+    class v_sse_palignr_u8_class<imm, false, false, true, false, false>
+    {
+    public:
+        inline __m128i operator()(const __m128i& a, const __m128i& b) const
+        {
+            return _mm_unpacklo_epi64(_mm_unpackhi_epi64(a, a), b);
+        }
+    };
+
+    template <int imm>
+    class v_sse_palignr_u8_class<imm, false, false, false, true, false>
+    {
+    public:
+        inline __m128i operator()(const __m128i&, const __m128i& b) const
+        {
+            return b;
+        }
+    };
+
+    template <int imm>
+    class v_sse_palignr_u8_class<imm, false, false, false, false, true>
+    {
+#if CV_SSSE3
+    public:
+        inline __m128i operator()(const __m128i& a, const __m128i& b) const
+        {
+            return _mm_alignr_epi8(b, a, imm);
+        }
+#else
+    public:
+        inline __m128i operator()(const __m128i& a, const __m128i& b) const
+        {
+            enum { imm2 = (sizeof(__m128i) - imm) };
+            return _mm_or_si128(_mm_srli_si128(a, imm), _mm_slli_si128(b, imm2));
+        }
+#endif
+    };
+
+    template <int imm>
+    inline __m128i v_sse_palignr_u8(const __m128i& a, const __m128i& b)
+    {
+        CV_StaticAssert((imm >= 0) && (imm <= 16), "Invalid imm for v_sse_palignr_u8.");
+        return v_sse_palignr_u8_class<imm>()(a, b);
+    }
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_right(const _Tpvec &a)
+{
+    using namespace hal_sse_internal;
+    enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) };
+    return _Tpvec(v_sse_reinterpret_as<typename _Tpvec::vector_type>(
+        _mm_srli_si128(
+            v_sse_reinterpret_as<__m128i>(a.val), imm2)));
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_left(const _Tpvec &a)
+{
+    using namespace hal_sse_internal;
+    enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) };
+    return _Tpvec(v_sse_reinterpret_as<typename _Tpvec::vector_type>(
+        _mm_slli_si128(
+            v_sse_reinterpret_as<__m128i>(a.val), imm2)));
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_right(const _Tpvec &a, const _Tpvec &b)
+{
+    using namespace hal_sse_internal;
+    enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) };
+    return _Tpvec(v_sse_reinterpret_as<typename _Tpvec::vector_type>(
+        v_sse_palignr_u8<imm2>(
+            v_sse_reinterpret_as<__m128i>(a.val),
+            v_sse_reinterpret_as<__m128i>(b.val))));
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_left(const _Tpvec &a, const _Tpvec &b)
+{
+    using namespace hal_sse_internal;
+    enum { imm2 = ((_Tpvec::nlanes - imm) * sizeof(typename _Tpvec::lane_type)) };
+    return _Tpvec(v_sse_reinterpret_as<typename _Tpvec::vector_type>(
+        v_sse_palignr_u8<imm2>(
+            v_sse_reinterpret_as<__m128i>(b.val),
+            v_sse_reinterpret_as<__m128i>(a.val))));
+}
+
+#define OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(_Tpvec, _Tp) \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec(_mm_loadu_si128((const __m128i*)ptr)); } \
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(_mm_load_si128((const __m128i*)ptr)); } \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ return _Tpvec(_mm_loadl_epi64((const __m128i*)ptr)); } \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ \
+    return _Tpvec(_mm_unpacklo_epi64(_mm_loadl_epi64((const __m128i*)ptr0), \
+                                     _mm_loadl_epi64((const __m128i*)ptr1))); \
+} \
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ _mm_storeu_si128((__m128i*)ptr, a.val); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ _mm_store_si128((__m128i*)ptr, a.val); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ _mm_stream_si128((__m128i*)ptr, a.val); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+{ \
+    if( mode == hal::STORE_UNALIGNED ) \
+        _mm_storeu_si128((__m128i*)ptr, a.val); \
+    else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+        _mm_stream_si128((__m128i*)ptr, a.val); \
+    else \
+        _mm_store_si128((__m128i*)ptr, a.val); \
+} \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ _mm_storel_epi64((__m128i*)ptr, a.val); } \
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ _mm_storel_epi64((__m128i*)ptr, _mm_unpackhi_epi64(a.val, a.val)); }
+
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint8x16, uchar)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int8x16, schar)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint16x8, ushort)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int16x8, short)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint32x4, unsigned)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int32x4, int)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_uint64x2, uint64)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INT_OP(v_int64x2, int64)
+
+#define OPENCV_HAL_IMPL_SSE_LOADSTORE_FLT_OP(_Tpvec, _Tp, suffix) \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec(_mm_loadu_##suffix(ptr)); } \
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(_mm_load_##suffix(ptr)); } \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ return _Tpvec(_mm_castsi128_##suffix(_mm_loadl_epi64((const __m128i*)ptr))); } \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ \
+    return _Tpvec(_mm_castsi128_##suffix( \
+        _mm_unpacklo_epi64(_mm_loadl_epi64((const __m128i*)ptr0), \
+                           _mm_loadl_epi64((const __m128i*)ptr1)))); \
+} \
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ _mm_storeu_##suffix(ptr, a.val); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ _mm_store_##suffix(ptr, a.val); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ _mm_stream_##suffix(ptr, a.val); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode) \
+{ \
+    if( mode == hal::STORE_UNALIGNED ) \
+        _mm_storeu_##suffix(ptr, a.val); \
+    else if( mode == hal::STORE_ALIGNED_NOCACHE )  \
+        _mm_stream_##suffix(ptr, a.val); \
+    else \
+        _mm_store_##suffix(ptr, a.val); \
+} \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ _mm_storel_epi64((__m128i*)ptr, _mm_cast##suffix##_si128(a.val)); } \
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ \
+    __m128i a1 = _mm_cast##suffix##_si128(a.val); \
+    _mm_storel_epi64((__m128i*)ptr, _mm_unpackhi_epi64(a1, a1)); \
+}
+
+OPENCV_HAL_IMPL_SSE_LOADSTORE_FLT_OP(v_float32x4, float, ps)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_FLT_OP(v_float64x2, double, pd)
+
+inline unsigned v_reduce_sum(const v_uint8x16& a)
+{
+    __m128i half = _mm_sad_epu8(a.val, _mm_setzero_si128());
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(half, _mm_unpackhi_epi64(half, half)));
+}
+inline int v_reduce_sum(const v_int8x16& a)
+{
+    __m128i half = _mm_set1_epi8((schar)-128);
+    half = _mm_sad_epu8(_mm_xor_si128(a.val, half), _mm_setzero_si128());
+    return _mm_cvtsi128_si32(_mm_add_epi32(half, _mm_unpackhi_epi64(half, half))) - 2048;
+}
+#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_16(func) \
+inline schar v_reduce_##func(const v_int8x16& a) \
+{ \
+    __m128i val = a.val; \
+    __m128i smask = _mm_set1_epi8((schar)-128); \
+    val = _mm_xor_si128(val, smask); \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,8)); \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,4)); \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,2)); \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,1)); \
+    return (schar)_mm_cvtsi128_si32(val) ^ (schar)-128; \
+} \
+inline uchar v_reduce_##func(const v_uint8x16& a) \
+{ \
+    __m128i val = a.val; \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,8)); \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,4)); \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,2)); \
+    val = _mm_##func##_epu8(val, _mm_srli_si128(val,1)); \
+    return (uchar)_mm_cvtsi128_si32(val); \
+}
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_16(max)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_16(min)
+
+#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_8(_Tpvec, scalartype, func, suffix, sbit) \
+inline scalartype v_reduce_##func(const v_##_Tpvec& a) \
+{ \
+    __m128i val = a.val; \
+    val = _mm_##func##_##suffix(val, _mm_srli_si128(val,8)); \
+    val = _mm_##func##_##suffix(val, _mm_srli_si128(val,4)); \
+    val = _mm_##func##_##suffix(val, _mm_srli_si128(val,2)); \
+    return (scalartype)_mm_cvtsi128_si32(val); \
+} \
+inline unsigned scalartype v_reduce_##func(const v_u##_Tpvec& a) \
+{ \
+    __m128i val = a.val; \
+    __m128i smask = _mm_set1_epi16(sbit); \
+    val = _mm_xor_si128(val, smask); \
+    val = _mm_##func##_##suffix(val, _mm_srli_si128(val,8)); \
+    val = _mm_##func##_##suffix(val, _mm_srli_si128(val,4)); \
+    val = _mm_##func##_##suffix(val, _mm_srli_si128(val,2)); \
+    return (unsigned scalartype)(_mm_cvtsi128_si32(val) ^  sbit); \
+}
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_8(int16x8, short, max, epi16, (short)-32768)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_8(int16x8, short, min, epi16, (short)-32768)
+
+#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(_Tpvec, scalartype, regtype, suffix, cast_from, cast_to, extract) \
+inline scalartype v_reduce_sum(const _Tpvec& a) \
+{ \
+    regtype val = a.val; \
+    val = _mm_add_##suffix(val, cast_to(_mm_srli_si128(cast_from(val), 8))); \
+    val = _mm_add_##suffix(val, cast_to(_mm_srli_si128(cast_from(val), 4))); \
+    return (scalartype)_mm_cvt##extract(val); \
+}
+
+#define OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(_Tpvec, scalartype, func, scalar_func) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    scalartype CV_DECL_ALIGNED(16) buf[4]; \
+    v_store_aligned(buf, a); \
+    scalartype s0 = scalar_func(buf[0], buf[1]); \
+    scalartype s1 = scalar_func(buf[2], buf[3]); \
+    return scalar_func(s0, s1); \
+}
+
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(v_uint32x4, unsigned, __m128i, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP, si128_si32)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(v_int32x4, int, __m128i, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP, si128_si32)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4_SUM(v_float32x4, float, __m128, ps, _mm_castps_si128, _mm_castsi128_ps, ss_f32)
+
+inline int v_reduce_sum(const v_int16x8& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+inline unsigned v_reduce_sum(const v_uint16x8& a)
+{ return v_reduce_sum(v_add(v_expand_low(a), v_expand_high(a))); }
+
+inline uint64 v_reduce_sum(const v_uint64x2& a)
+{
+    uint64 CV_DECL_ALIGNED(32) idx[2];
+    v_store_aligned(idx, a);
+    return idx[0] + idx[1];
+}
+inline int64 v_reduce_sum(const v_int64x2& a)
+{
+    int64 CV_DECL_ALIGNED(32) idx[2];
+    v_store_aligned(idx, a);
+    return idx[0] + idx[1];
+}
+inline double v_reduce_sum(const v_float64x2& a)
+{
+    double CV_DECL_ALIGNED(32) idx[2];
+    v_store_aligned(idx, a);
+    return idx[0] + idx[1];
+}
+
+inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b,
+                                 const v_float32x4& c, const v_float32x4& d)
+{
+#if CV_SSE3
+    __m128 ab = _mm_hadd_ps(a.val, b.val);
+    __m128 cd = _mm_hadd_ps(c.val, d.val);
+    return v_float32x4(_mm_hadd_ps(ab, cd));
+#else
+    __m128 ac = _mm_add_ps(_mm_unpacklo_ps(a.val, c.val), _mm_unpackhi_ps(a.val, c.val));
+    __m128 bd = _mm_add_ps(_mm_unpacklo_ps(b.val, d.val), _mm_unpackhi_ps(b.val, d.val));
+    return v_float32x4(_mm_add_ps(_mm_unpacklo_ps(ac, bd), _mm_unpackhi_ps(ac, bd)));
+#endif
+}
+
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_uint32x4, unsigned, max, std::max)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_uint32x4, unsigned, min, std::min)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_int32x4, int, max, std::max)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_int32x4, int, min, std::min)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_float32x4, float, max, std::max)
+OPENCV_HAL_IMPL_SSE_REDUCE_OP_4(v_float32x4, float, min, std::min)
+
+inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b)
+{
+    __m128i half = _mm_sad_epu8(a.val, b.val);
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(half, _mm_unpackhi_epi64(half, half)));
+}
+inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b)
+{
+    __m128i half = _mm_set1_epi8(0x7f);
+    half = _mm_sad_epu8(_mm_add_epi8(a.val, half), _mm_add_epi8(b.val, half));
+    return (unsigned)_mm_cvtsi128_si32(_mm_add_epi32(half, _mm_unpackhi_epi64(half, half)));
+}
+inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v_uint32x4 l, h;
+    v_expand(v_absdiff(a, b), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b)
+{
+    v_uint32x4 l, h;
+    v_expand(v_absdiff(a, b), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b)
+{
+    return v_reduce_sum(v_absdiff(a, b));
+}
+inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b)
+{
+    return v_reduce_sum(v_absdiff(a, b));
+}
+inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b)
+{
+    return v_reduce_sum(v_absdiff(a, b));
+}
+
+inline v_uint8x16 v_popcount(const v_uint8x16& a)
+{
+    __m128i m1 = _mm_set1_epi32(0x55555555);
+    __m128i m2 = _mm_set1_epi32(0x33333333);
+    __m128i m4 = _mm_set1_epi32(0x0f0f0f0f);
+    __m128i p = a.val;
+    p = _mm_add_epi32(_mm_and_si128(_mm_srli_epi32(p, 1), m1), _mm_and_si128(p, m1));
+    p = _mm_add_epi32(_mm_and_si128(_mm_srli_epi32(p, 2), m2), _mm_and_si128(p, m2));
+    p = _mm_add_epi32(_mm_and_si128(_mm_srli_epi32(p, 4), m4), _mm_and_si128(p, m4));
+    return v_uint8x16(p);
+}
+inline v_uint16x8 v_popcount(const v_uint16x8& a)
+{
+    v_uint8x16 p = v_popcount(v_reinterpret_as_u8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    return v_and(v_reinterpret_as_u16(p), v_setall_u16(0x00ff));
+}
+inline v_uint32x4 v_popcount(const v_uint32x4& a)
+{
+    v_uint8x16 p = v_popcount(v_reinterpret_as_u8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    p = v_add(p, v_rotate_right<2>(p));
+    return v_and(v_reinterpret_as_u32(p), v_setall_u32(0x000000ff));
+}
+inline v_uint64x2 v_popcount(const v_uint64x2& a)
+{
+    return v_uint64x2(_mm_sad_epu8(v_popcount(v_reinterpret_as_u8(a)).val, _mm_setzero_si128()));
+}
+inline v_uint8x16 v_popcount(const v_int8x16& a)
+{ return v_popcount(v_reinterpret_as_u8(a)); }
+inline v_uint16x8 v_popcount(const v_int16x8& a)
+{ return v_popcount(v_reinterpret_as_u16(a)); }
+inline v_uint32x4 v_popcount(const v_int32x4& a)
+{ return v_popcount(v_reinterpret_as_u32(a)); }
+inline v_uint64x2 v_popcount(const v_int64x2& a)
+{ return v_popcount(v_reinterpret_as_u64(a)); }
+
+#define OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(_Tpvec, suffix, cast_op, allmask) \
+inline int v_signmask(const _Tpvec& a)   { return _mm_movemask_##suffix(cast_op(a.val)); } \
+inline bool v_check_all(const _Tpvec& a) { return _mm_movemask_##suffix(cast_op(a.val)) == allmask; } \
+inline bool v_check_any(const _Tpvec& a) { return _mm_movemask_##suffix(cast_op(a.val)) != 0; }
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_uint8x16, epi8, OPENCV_HAL_NOP, 65535)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_int8x16, epi8, OPENCV_HAL_NOP, 65535)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_uint32x4, ps, _mm_castsi128_ps, 15)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_int32x4, ps, _mm_castsi128_ps, 15)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_uint64x2, pd, _mm_castsi128_pd, 3)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_int64x2, pd, _mm_castsi128_pd, 3)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_float32x4, ps, OPENCV_HAL_NOP, 15)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS(v_float64x2, pd, OPENCV_HAL_NOP, 3)
+
+#define OPENCV_HAL_IMPL_SSE_CHECK_SIGNS_SHORT(_Tpvec) \
+inline int v_signmask(const _Tpvec& a) { return _mm_movemask_epi8(_mm_packs_epi16(a.val, a.val)) & 255; } \
+inline bool v_check_all(const _Tpvec& a) { return (_mm_movemask_epi8(a.val) & 0xaaaa) == 0xaaaa; } \
+inline bool v_check_any(const _Tpvec& a) { return (_mm_movemask_epi8(a.val) & 0xaaaa) != 0; }
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS_SHORT(v_uint16x8)
+OPENCV_HAL_IMPL_SSE_CHECK_SIGNS_SHORT(v_int16x8)
+
+inline int v_scan_forward(const v_int8x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_uint8x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_int16x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_uint16x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_int32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_uint32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_float32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_int64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_uint64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_float64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+
+#if CV_SSE4_1
+#define OPENCV_HAL_IMPL_SSE_SELECT(_Tpvec, cast_ret, cast, suffix) \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(cast_ret(_mm_blendv_##suffix(cast(b.val), cast(a.val), cast(mask.val)))); \
+}
+
+OPENCV_HAL_IMPL_SSE_SELECT(v_uint8x16, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8)
+OPENCV_HAL_IMPL_SSE_SELECT(v_int8x16, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8)
+OPENCV_HAL_IMPL_SSE_SELECT(v_uint16x8, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8)
+OPENCV_HAL_IMPL_SSE_SELECT(v_int16x8, OPENCV_HAL_NOP, OPENCV_HAL_NOP, epi8)
+OPENCV_HAL_IMPL_SSE_SELECT(v_uint32x4, _mm_castps_si128, _mm_castsi128_ps, ps)
+OPENCV_HAL_IMPL_SSE_SELECT(v_int32x4, _mm_castps_si128, _mm_castsi128_ps, ps)
+// OPENCV_HAL_IMPL_SSE_SELECT(v_uint64x2, TBD, TBD, pd)
+// OPENCV_HAL_IMPL_SSE_SELECT(v_int64x2, TBD, TBD, ps)
+OPENCV_HAL_IMPL_SSE_SELECT(v_float32x4, OPENCV_HAL_NOP, OPENCV_HAL_NOP, ps)
+OPENCV_HAL_IMPL_SSE_SELECT(v_float64x2, OPENCV_HAL_NOP, OPENCV_HAL_NOP, pd)
+
+#else // CV_SSE4_1
+
+#define OPENCV_HAL_IMPL_SSE_SELECT(_Tpvec, suffix) \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(_mm_xor_##suffix(b.val, _mm_and_##suffix(_mm_xor_##suffix(b.val, a.val), mask.val))); \
+}
+
+OPENCV_HAL_IMPL_SSE_SELECT(v_uint8x16, si128)
+OPENCV_HAL_IMPL_SSE_SELECT(v_int8x16, si128)
+OPENCV_HAL_IMPL_SSE_SELECT(v_uint16x8, si128)
+OPENCV_HAL_IMPL_SSE_SELECT(v_int16x8, si128)
+OPENCV_HAL_IMPL_SSE_SELECT(v_uint32x4, si128)
+OPENCV_HAL_IMPL_SSE_SELECT(v_int32x4, si128)
+// OPENCV_HAL_IMPL_SSE_SELECT(v_uint64x2, si128)
+// OPENCV_HAL_IMPL_SSE_SELECT(v_int64x2, si128)
+OPENCV_HAL_IMPL_SSE_SELECT(v_float32x4, ps)
+OPENCV_HAL_IMPL_SSE_SELECT(v_float64x2, pd)
+#endif
+
+/* Expand */
+#define OPENCV_HAL_IMPL_SSE_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin)    \
+    inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1) \
+    {                                                               \
+        b0.val = intrin(a.val);                                     \
+        b1.val = __CV_CAT(intrin, _high)(a.val);                    \
+    }                                                               \
+    inline _Tpwvec v_expand_low(const _Tpvec& a)                    \
+    { return _Tpwvec(intrin(a.val)); }                              \
+    inline _Tpwvec v_expand_high(const _Tpvec& a)                   \
+    { return _Tpwvec(__CV_CAT(intrin, _high)(a.val)); }             \
+    inline _Tpwvec v_load_expand(const _Tp* ptr)                    \
+    {                                                               \
+        __m128i a = _mm_loadl_epi64((const __m128i*)ptr);           \
+        return _Tpwvec(intrin(a));                                  \
+    }
+
+OPENCV_HAL_IMPL_SSE_EXPAND(v_uint8x16, v_uint16x8,  uchar,    _v128_cvtepu8_epi16)
+OPENCV_HAL_IMPL_SSE_EXPAND(v_int8x16,  v_int16x8,   schar,    _v128_cvtepi8_epi16)
+OPENCV_HAL_IMPL_SSE_EXPAND(v_uint16x8, v_uint32x4,  ushort,   _v128_cvtepu16_epi32)
+OPENCV_HAL_IMPL_SSE_EXPAND(v_int16x8,  v_int32x4,   short,    _v128_cvtepi16_epi32)
+OPENCV_HAL_IMPL_SSE_EXPAND(v_uint32x4, v_uint64x2,  unsigned, _v128_cvtepu32_epi64)
+OPENCV_HAL_IMPL_SSE_EXPAND(v_int32x4,  v_int64x2,   int,      _v128_cvtepi32_epi64)
+
+#define OPENCV_HAL_IMPL_SSE_EXPAND_Q(_Tpvec, _Tp, intrin)          \
+    inline _Tpvec v_load_expand_q(const _Tp* ptr)                  \
+    {                                                              \
+        typedef int CV_DECL_ALIGNED(1) unaligned_int;              \
+        __m128i a = _mm_cvtsi32_si128(*(const unaligned_int*)ptr); \
+        return _Tpvec(intrin(a));                                  \
+    }
+
+OPENCV_HAL_IMPL_SSE_EXPAND_Q(v_uint32x4, uchar, _v128_cvtepu8_epi32)
+OPENCV_HAL_IMPL_SSE_EXPAND_Q(v_int32x4,  schar, _v128_cvtepi8_epi32)
+
+#define OPENCV_HAL_IMPL_SSE_UNPACKS(_Tpvec, suffix, cast_from, cast_to) \
+inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1) \
+{ \
+    b0.val = _mm_unpacklo_##suffix(a0.val, a1.val); \
+    b1.val = _mm_unpackhi_##suffix(a0.val, a1.val); \
+} \
+inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    __m128i a1 = cast_from(a.val), b1 = cast_from(b.val); \
+    return _Tpvec(cast_to(_mm_unpacklo_epi64(a1, b1))); \
+} \
+inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    __m128i a1 = cast_from(a.val), b1 = cast_from(b.val); \
+    return _Tpvec(cast_to(_mm_unpackhi_epi64(a1, b1))); \
+} \
+inline void v_recombine(const _Tpvec& a, const _Tpvec& b, _Tpvec& c, _Tpvec& d) \
+{ \
+    __m128i a1 = cast_from(a.val), b1 = cast_from(b.val); \
+    c.val = cast_to(_mm_unpacklo_epi64(a1, b1)); \
+    d.val = cast_to(_mm_unpackhi_epi64(a1, b1)); \
+}
+
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_uint8x16, epi8, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_int8x16, epi8, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_uint16x8, epi16, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_int16x8, epi16, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_uint32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_int32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_float32x4, ps, _mm_castps_si128, _mm_castsi128_ps)
+OPENCV_HAL_IMPL_SSE_UNPACKS(v_float64x2, pd, _mm_castpd_si128, _mm_castsi128_pd)
+
+inline v_uint8x16 v_reverse(const v_uint8x16 &a)
+{
+#if CV_SSSE3
+    static const __m128i perm = _mm_setr_epi8(15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0);
+    return v_uint8x16(_mm_shuffle_epi8(a.val, perm));
+#else
+    uchar CV_DECL_ALIGNED(32) d[16];
+    v_store_aligned(d, a);
+    return v_uint8x16(d[15], d[14], d[13], d[12], d[11], d[10], d[9], d[8], d[7], d[6], d[5], d[4], d[3], d[2], d[1], d[0]);
+#endif
+}
+
+inline v_int8x16 v_reverse(const v_int8x16 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x8 v_reverse(const v_uint16x8 &a)
+{
+#if CV_SSSE3
+    static const __m128i perm = _mm_setr_epi8(14, 15, 12, 13, 10, 11, 8, 9, 6, 7, 4, 5, 2, 3, 0, 1);
+    return v_uint16x8(_mm_shuffle_epi8(a.val, perm));
+#else
+    __m128i r = _mm_shuffle_epi32(a.val, _MM_SHUFFLE(0, 1, 2, 3));
+    r = _mm_shufflelo_epi16(r, _MM_SHUFFLE(2, 3, 0, 1));
+    r = _mm_shufflehi_epi16(r, _MM_SHUFFLE(2, 3, 0, 1));
+    return v_uint16x8(r);
+#endif
+}
+
+inline v_int16x8 v_reverse(const v_int16x8 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x4 v_reverse(const v_uint32x4 &a)
+{
+    return v_uint32x4(_mm_shuffle_epi32(a.val, _MM_SHUFFLE(0, 1, 2, 3)));
+}
+
+inline v_int32x4 v_reverse(const v_int32x4 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x4 v_reverse(const v_float32x4 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x2 v_reverse(const v_uint64x2 &a)
+{
+    return v_uint64x2(_mm_shuffle_epi32(a.val, _MM_SHUFFLE(1, 0, 3, 2)));
+}
+
+inline v_int64x2 v_reverse(const v_int64x2 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+inline v_float64x2 v_reverse(const v_float64x2 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+template<int s, typename _Tpvec>
+inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b)
+{
+    return v_rotate_right<s>(a, b);
+}
+
+inline v_int32x4 v_round(const v_float32x4& a)
+{ return v_int32x4(_mm_cvtps_epi32(a.val)); }
+
+inline v_int32x4 v_floor(const v_float32x4& a)
+{
+    __m128i a1 = _mm_cvtps_epi32(a.val);
+    __m128i mask = _mm_castps_si128(_mm_cmpgt_ps(_mm_cvtepi32_ps(a1), a.val));
+    return v_int32x4(_mm_add_epi32(a1, mask));
+}
+
+inline v_int32x4 v_ceil(const v_float32x4& a)
+{
+    __m128i a1 = _mm_cvtps_epi32(a.val);
+    __m128i mask = _mm_castps_si128(_mm_cmpgt_ps(a.val, _mm_cvtepi32_ps(a1)));
+    return v_int32x4(_mm_sub_epi32(a1, mask));
+}
+
+inline v_int32x4 v_trunc(const v_float32x4& a)
+{ return v_int32x4(_mm_cvttps_epi32(a.val)); }
+
+inline v_int32x4 v_round(const v_float64x2& a)
+{ return v_int32x4(_mm_cvtpd_epi32(a.val)); }
+
+inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b)
+{
+    __m128i ai = _mm_cvtpd_epi32(a.val), bi = _mm_cvtpd_epi32(b.val);
+    return v_int32x4(_mm_unpacklo_epi64(ai, bi));
+}
+
+inline v_int32x4 v_floor(const v_float64x2& a)
+{
+    __m128i a1 = _mm_cvtpd_epi32(a.val);
+    __m128i mask = _mm_castpd_si128(_mm_cmpgt_pd(_mm_cvtepi32_pd(a1), a.val));
+    mask = _mm_srli_si128(_mm_slli_si128(mask, 4), 8); // m0 m0 m1 m1 => m0 m1 0 0
+    return v_int32x4(_mm_add_epi32(a1, mask));
+}
+
+inline v_int32x4 v_ceil(const v_float64x2& a)
+{
+    __m128i a1 = _mm_cvtpd_epi32(a.val);
+    __m128i mask = _mm_castpd_si128(_mm_cmpgt_pd(a.val, _mm_cvtepi32_pd(a1)));
+    mask = _mm_srli_si128(_mm_slli_si128(mask, 4), 8); // m0 m0 m1 m1 => m0 m1 0 0
+    return v_int32x4(_mm_sub_epi32(a1, mask));
+}
+
+inline v_int32x4 v_trunc(const v_float64x2& a)
+{ return v_int32x4(_mm_cvttpd_epi32(a.val)); }
+
+#define OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(_Tpvec, suffix, cast_from, cast_to) \
+inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1, \
+                           const _Tpvec& a2, const _Tpvec& a3, \
+                           _Tpvec& b0, _Tpvec& b1, \
+                           _Tpvec& b2, _Tpvec& b3) \
+{ \
+    __m128i t0 = cast_from(_mm_unpacklo_##suffix(a0.val, a1.val)); \
+    __m128i t1 = cast_from(_mm_unpacklo_##suffix(a2.val, a3.val)); \
+    __m128i t2 = cast_from(_mm_unpackhi_##suffix(a0.val, a1.val)); \
+    __m128i t3 = cast_from(_mm_unpackhi_##suffix(a2.val, a3.val)); \
+\
+    b0.val = cast_to(_mm_unpacklo_epi64(t0, t1)); \
+    b1.val = cast_to(_mm_unpackhi_epi64(t0, t1)); \
+    b2.val = cast_to(_mm_unpacklo_epi64(t2, t3)); \
+    b3.val = cast_to(_mm_unpackhi_epi64(t2, t3)); \
+}
+
+OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(v_uint32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(v_int32x4, epi32, OPENCV_HAL_NOP, OPENCV_HAL_NOP)
+OPENCV_HAL_IMPL_SSE_TRANSPOSE4x4(v_float32x4, ps, _mm_castps_si128, _mm_castsi128_ps)
+
+// load deinterleave
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b)
+{
+    __m128i t00 = _mm_loadu_si128((const __m128i*)ptr);
+    __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 16));
+
+    __m128i t10 = _mm_unpacklo_epi8(t00, t01);
+    __m128i t11 = _mm_unpackhi_epi8(t00, t01);
+
+    __m128i t20 = _mm_unpacklo_epi8(t10, t11);
+    __m128i t21 = _mm_unpackhi_epi8(t10, t11);
+
+    __m128i t30 = _mm_unpacklo_epi8(t20, t21);
+    __m128i t31 = _mm_unpackhi_epi8(t20, t21);
+
+    a.val = _mm_unpacklo_epi8(t30, t31);
+    b.val = _mm_unpackhi_epi8(t30, t31);
+}
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c)
+{
+#if CV_SSE4_1
+    const __m128i m0 = _mm_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0);
+    const __m128i m1 = _mm_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0);
+    __m128i s0 = _mm_loadu_si128((const __m128i*)ptr);
+    __m128i s1 = _mm_loadu_si128((const __m128i*)(ptr + 16));
+    __m128i s2 = _mm_loadu_si128((const __m128i*)(ptr + 32));
+    __m128i a0 = _mm_blendv_epi8(_mm_blendv_epi8(s0, s1, m0), s2, m1);
+    __m128i b0 = _mm_blendv_epi8(_mm_blendv_epi8(s1, s2, m0), s0, m1);
+    __m128i c0 = _mm_blendv_epi8(_mm_blendv_epi8(s2, s0, m0), s1, m1);
+    const __m128i sh_b = _mm_setr_epi8(0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14, 1, 4, 7, 10, 13);
+    const __m128i sh_g = _mm_setr_epi8(1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15, 2, 5, 8, 11, 14);
+    const __m128i sh_r = _mm_setr_epi8(2, 5, 8, 11, 14, 1, 4, 7, 10, 13, 0, 3, 6, 9, 12, 15);
+    a0 = _mm_shuffle_epi8(a0, sh_b);
+    b0 = _mm_shuffle_epi8(b0, sh_g);
+    c0 = _mm_shuffle_epi8(c0, sh_r);
+    a.val = a0;
+    b.val = b0;
+    c.val = c0;
+#elif CV_SSSE3
+    const __m128i m0 = _mm_setr_epi8(0, 3, 6, 9, 12, 15, 1, 4, 7, 10, 13, 2, 5, 8, 11, 14);
+    const __m128i m1 = _mm_alignr_epi8(m0, m0, 11);
+    const __m128i m2 = _mm_alignr_epi8(m0, m0, 6);
+
+    __m128i t0 = _mm_loadu_si128((const __m128i*)ptr);
+    __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 16));
+    __m128i t2 = _mm_loadu_si128((const __m128i*)(ptr + 32));
+
+    __m128i s0 = _mm_shuffle_epi8(t0, m0);
+    __m128i s1 = _mm_shuffle_epi8(t1, m1);
+    __m128i s2 = _mm_shuffle_epi8(t2, m2);
+
+    t0 = _mm_alignr_epi8(s1, _mm_slli_si128(s0, 10), 5);
+    a.val = _mm_alignr_epi8(s2, t0, 5);
+
+    t1 = _mm_alignr_epi8(_mm_srli_si128(s1, 5), _mm_slli_si128(s0, 5), 6);
+    b.val = _mm_alignr_epi8(_mm_srli_si128(s2, 5), t1, 5);
+
+    t2 = _mm_alignr_epi8(_mm_srli_si128(s2, 10), s1, 11);
+    c.val = _mm_alignr_epi8(t2, s0, 11);
+#else
+    __m128i t00 = _mm_loadu_si128((const __m128i*)ptr);
+    __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 16));
+    __m128i t02 = _mm_loadu_si128((const __m128i*)(ptr + 32));
+
+    __m128i t10 = _mm_unpacklo_epi8(t00, _mm_unpackhi_epi64(t01, t01));
+    __m128i t11 = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t00, t00), t02);
+    __m128i t12 = _mm_unpacklo_epi8(t01, _mm_unpackhi_epi64(t02, t02));
+
+    __m128i t20 = _mm_unpacklo_epi8(t10, _mm_unpackhi_epi64(t11, t11));
+    __m128i t21 = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t10, t10), t12);
+    __m128i t22 = _mm_unpacklo_epi8(t11, _mm_unpackhi_epi64(t12, t12));
+
+    __m128i t30 = _mm_unpacklo_epi8(t20, _mm_unpackhi_epi64(t21, t21));
+    __m128i t31 = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t20, t20), t22);
+    __m128i t32 = _mm_unpacklo_epi8(t21, _mm_unpackhi_epi64(t22, t22));
+
+    a.val = _mm_unpacklo_epi8(t30, _mm_unpackhi_epi64(t31, t31));
+    b.val = _mm_unpacklo_epi8(_mm_unpackhi_epi64(t30, t30), t32);
+    c.val = _mm_unpacklo_epi8(t31, _mm_unpackhi_epi64(t32, t32));
+#endif
+}
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c, v_uint8x16& d)
+{
+    __m128i u0 = _mm_loadu_si128((const __m128i*)ptr); // a0 b0 c0 d0 a1 b1 c1 d1 ...
+    __m128i u1 = _mm_loadu_si128((const __m128i*)(ptr + 16)); // a4 b4 c4 d4 ...
+    __m128i u2 = _mm_loadu_si128((const __m128i*)(ptr + 32)); // a8 b8 c8 d8 ...
+    __m128i u3 = _mm_loadu_si128((const __m128i*)(ptr + 48)); // a12 b12 c12 d12 ...
+
+    __m128i v0 = _mm_unpacklo_epi8(u0, u2); // a0 a8 b0 b8 ...
+    __m128i v1 = _mm_unpackhi_epi8(u0, u2); // a2 a10 b2 b10 ...
+    __m128i v2 = _mm_unpacklo_epi8(u1, u3); // a4 a12 b4 b12 ...
+    __m128i v3 = _mm_unpackhi_epi8(u1, u3); // a6 a14 b6 b14 ...
+
+    u0 = _mm_unpacklo_epi8(v0, v2); // a0 a4 a8 a12 ...
+    u1 = _mm_unpacklo_epi8(v1, v3); // a2 a6 a10 a14 ...
+    u2 = _mm_unpackhi_epi8(v0, v2); // a1 a5 a9 a13 ...
+    u3 = _mm_unpackhi_epi8(v1, v3); // a3 a7 a11 a15 ...
+
+    v0 = _mm_unpacklo_epi8(u0, u1); // a0 a2 a4 a6 ...
+    v1 = _mm_unpacklo_epi8(u2, u3); // a1 a3 a5 a7 ...
+    v2 = _mm_unpackhi_epi8(u0, u1); // c0 c2 c4 c6 ...
+    v3 = _mm_unpackhi_epi8(u2, u3); // c1 c3 c5 c7 ...
+
+    a.val = _mm_unpacklo_epi8(v0, v1);
+    b.val = _mm_unpackhi_epi8(v0, v1);
+    c.val = _mm_unpacklo_epi8(v2, v3);
+    d.val = _mm_unpackhi_epi8(v2, v3);
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b)
+{
+    __m128i v0 = _mm_loadu_si128((__m128i*)(ptr));     // a0 b0 a1 b1 a2 b2 a3 b3
+    __m128i v1 = _mm_loadu_si128((__m128i*)(ptr + 8)); // a4 b4 a5 b5 a6 b6 a7 b7
+
+    __m128i v2 = _mm_unpacklo_epi16(v0, v1); // a0 a4 b0 b4 a1 a5 b1 b5
+    __m128i v3 = _mm_unpackhi_epi16(v0, v1); // a2 a6 b2 b6 a3 a7 b3 b7
+    __m128i v4 = _mm_unpacklo_epi16(v2, v3); // a0 a2 a4 a6 b0 b2 b4 b6
+    __m128i v5 = _mm_unpackhi_epi16(v2, v3); // a1 a3 a5 a7 b1 b3 b5 b7
+
+    a.val = _mm_unpacklo_epi16(v4, v5); // a0 a1 a2 a3 a4 a5 a6 a7
+    b.val = _mm_unpackhi_epi16(v4, v5); // b0 b1 ab b3 b4 b5 b6 b7
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c)
+{
+#if CV_SSE4_1
+    __m128i v0 = _mm_loadu_si128((__m128i*)(ptr));
+    __m128i v1 = _mm_loadu_si128((__m128i*)(ptr + 8));
+    __m128i v2 = _mm_loadu_si128((__m128i*)(ptr + 16));
+    __m128i a0 = _mm_blend_epi16(_mm_blend_epi16(v0, v1, 0x92), v2, 0x24);
+    __m128i b0 = _mm_blend_epi16(_mm_blend_epi16(v2, v0, 0x92), v1, 0x24);
+    __m128i c0 = _mm_blend_epi16(_mm_blend_epi16(v1, v2, 0x92), v0, 0x24);
+
+    const __m128i sh_a = _mm_setr_epi8(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11);
+    const __m128i sh_b = _mm_setr_epi8(2, 3, 8, 9, 14, 15, 4, 5, 10, 11, 0, 1, 6, 7, 12, 13);
+    const __m128i sh_c = _mm_setr_epi8(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15);
+    a0 = _mm_shuffle_epi8(a0, sh_a);
+    b0 = _mm_shuffle_epi8(b0, sh_b);
+    c0 = _mm_shuffle_epi8(c0, sh_c);
+
+    a.val = a0;
+    b.val = b0;
+    c.val = c0;
+#else
+    __m128i t00 = _mm_loadu_si128((const __m128i*)ptr);
+    __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 8));
+    __m128i t02 = _mm_loadu_si128((const __m128i*)(ptr + 16));
+
+    __m128i t10 = _mm_unpacklo_epi16(t00, _mm_unpackhi_epi64(t01, t01));
+    __m128i t11 = _mm_unpacklo_epi16(_mm_unpackhi_epi64(t00, t00), t02);
+    __m128i t12 = _mm_unpacklo_epi16(t01, _mm_unpackhi_epi64(t02, t02));
+
+    __m128i t20 = _mm_unpacklo_epi16(t10, _mm_unpackhi_epi64(t11, t11));
+    __m128i t21 = _mm_unpacklo_epi16(_mm_unpackhi_epi64(t10, t10), t12);
+    __m128i t22 = _mm_unpacklo_epi16(t11, _mm_unpackhi_epi64(t12, t12));
+
+    a.val = _mm_unpacklo_epi16(t20, _mm_unpackhi_epi64(t21, t21));
+    b.val = _mm_unpacklo_epi16(_mm_unpackhi_epi64(t20, t20), t22);
+    c.val = _mm_unpacklo_epi16(t21, _mm_unpackhi_epi64(t22, t22));
+#endif
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c, v_uint16x8& d)
+{
+    __m128i u0 = _mm_loadu_si128((const __m128i*)ptr); // a0 b0 c0 d0 a1 b1 c1 d1
+    __m128i u1 = _mm_loadu_si128((const __m128i*)(ptr + 8)); // a2 b2 c2 d2 ...
+    __m128i u2 = _mm_loadu_si128((const __m128i*)(ptr + 16)); // a4 b4 c4 d4 ...
+    __m128i u3 = _mm_loadu_si128((const __m128i*)(ptr + 24)); // a6 b6 c6 d6 ...
+
+    __m128i v0 = _mm_unpacklo_epi16(u0, u2); // a0 a4 b0 b4 ...
+    __m128i v1 = _mm_unpackhi_epi16(u0, u2); // a1 a5 b1 b5 ...
+    __m128i v2 = _mm_unpacklo_epi16(u1, u3); // a2 a6 b2 b6 ...
+    __m128i v3 = _mm_unpackhi_epi16(u1, u3); // a3 a7 b3 b7 ...
+
+    u0 = _mm_unpacklo_epi16(v0, v2); // a0 a2 a4 a6 ...
+    u1 = _mm_unpacklo_epi16(v1, v3); // a1 a3 a5 a7 ...
+    u2 = _mm_unpackhi_epi16(v0, v2); // c0 c2 c4 c6 ...
+    u3 = _mm_unpackhi_epi16(v1, v3); // c1 c3 c5 c7 ...
+
+    a.val = _mm_unpacklo_epi16(u0, u1);
+    b.val = _mm_unpackhi_epi16(u0, u1);
+    c.val = _mm_unpacklo_epi16(u2, u3);
+    d.val = _mm_unpackhi_epi16(u2, u3);
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b)
+{
+    __m128i v0 = _mm_loadu_si128((__m128i*)(ptr));     // a0 b0 a1 b1
+    __m128i v1 = _mm_loadu_si128((__m128i*)(ptr + 4)); // a2 b2 a3 b3
+
+    __m128i v2 = _mm_unpacklo_epi32(v0, v1); // a0 a2 b0 b2
+    __m128i v3 = _mm_unpackhi_epi32(v0, v1); // a1 a3 b1 b3
+
+    a.val = _mm_unpacklo_epi32(v2, v3); // a0 a1 a2 a3
+    b.val = _mm_unpackhi_epi32(v2, v3); // b0 b1 ab b3
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c)
+{
+    __m128i t00 = _mm_loadu_si128((const __m128i*)ptr);
+    __m128i t01 = _mm_loadu_si128((const __m128i*)(ptr + 4));
+    __m128i t02 = _mm_loadu_si128((const __m128i*)(ptr + 8));
+
+    __m128i t10 = _mm_unpacklo_epi32(t00, _mm_unpackhi_epi64(t01, t01));
+    __m128i t11 = _mm_unpacklo_epi32(_mm_unpackhi_epi64(t00, t00), t02);
+    __m128i t12 = _mm_unpacklo_epi32(t01, _mm_unpackhi_epi64(t02, t02));
+
+    a.val = _mm_unpacklo_epi32(t10, _mm_unpackhi_epi64(t11, t11));
+    b.val = _mm_unpacklo_epi32(_mm_unpackhi_epi64(t10, t10), t12);
+    c.val = _mm_unpacklo_epi32(t11, _mm_unpackhi_epi64(t12, t12));
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c, v_uint32x4& d)
+{
+    v_uint32x4 s0(_mm_loadu_si128((const __m128i*)ptr));        // a0 b0 c0 d0
+    v_uint32x4 s1(_mm_loadu_si128((const __m128i*)(ptr + 4)));  // a1 b1 c1 d1
+    v_uint32x4 s2(_mm_loadu_si128((const __m128i*)(ptr + 8)));  // a2 b2 c2 d2
+    v_uint32x4 s3(_mm_loadu_si128((const __m128i*)(ptr + 12))); // a3 b3 c3 d3
+
+    v_transpose4x4(s0, s1, s2, s3, a, b, c, d);
+}
+
+inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b)
+{
+    __m128 u0 = _mm_loadu_ps(ptr);       // a0 b0 a1 b1
+    __m128 u1 = _mm_loadu_ps((ptr + 4)); // a2 b2 a3 b3
+
+    a.val = _mm_shuffle_ps(u0, u1, _MM_SHUFFLE(2, 0, 2, 0)); // a0 a1 a2 a3
+    b.val = _mm_shuffle_ps(u0, u1, _MM_SHUFFLE(3, 1, 3, 1)); // b0 b1 ab b3
+}
+
+inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b, v_float32x4& c)
+{
+    __m128 t0 = _mm_loadu_ps(ptr + 0);
+    __m128 t1 = _mm_loadu_ps(ptr + 4);
+    __m128 t2 = _mm_loadu_ps(ptr + 8);
+
+    __m128 at12 = _mm_shuffle_ps(t1, t2, _MM_SHUFFLE(0, 1, 0, 2));
+    a.val = _mm_shuffle_ps(t0, at12, _MM_SHUFFLE(2, 0, 3, 0));
+
+    __m128 bt01 = _mm_shuffle_ps(t0, t1, _MM_SHUFFLE(0, 0, 0, 1));
+    __m128 bt12 = _mm_shuffle_ps(t1, t2, _MM_SHUFFLE(0, 2, 0, 3));
+    b.val = _mm_shuffle_ps(bt01, bt12, _MM_SHUFFLE(2, 0, 2, 0));
+
+    __m128 ct01 = _mm_shuffle_ps(t0, t1, _MM_SHUFFLE(0, 1, 0, 2));
+    c.val = _mm_shuffle_ps(ct01, t2, _MM_SHUFFLE(3, 0, 2, 0));
+}
+
+inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b, v_float32x4& c, v_float32x4& d)
+{
+    __m128 t0 = _mm_loadu_ps(ptr +  0);
+    __m128 t1 = _mm_loadu_ps(ptr +  4);
+    __m128 t2 = _mm_loadu_ps(ptr +  8);
+    __m128 t3 = _mm_loadu_ps(ptr + 12);
+    __m128 t02lo = _mm_unpacklo_ps(t0, t2);
+    __m128 t13lo = _mm_unpacklo_ps(t1, t3);
+    __m128 t02hi = _mm_unpackhi_ps(t0, t2);
+    __m128 t13hi = _mm_unpackhi_ps(t1, t3);
+    a.val = _mm_unpacklo_ps(t02lo, t13lo);
+    b.val = _mm_unpackhi_ps(t02lo, t13lo);
+    c.val = _mm_unpacklo_ps(t02hi, t13hi);
+    d.val = _mm_unpackhi_ps(t02hi, t13hi);
+}
+
+inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a, v_uint64x2& b)
+{
+    __m128i t0 = _mm_loadu_si128((const __m128i*)ptr);
+    __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 2));
+
+    a = v_uint64x2(_mm_unpacklo_epi64(t0, t1));
+    b = v_uint64x2(_mm_unpackhi_epi64(t0, t1));
+}
+
+inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a, v_uint64x2& b, v_uint64x2& c)
+{
+    __m128i t0 = _mm_loadu_si128((const __m128i*)ptr); // a0, b0
+    __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 2)); // c0, a1
+    __m128i t2 = _mm_loadu_si128((const __m128i*)(ptr + 4)); // b1, c1
+
+    t1 = _mm_shuffle_epi32(t1, 0x4e); // a1, c0
+
+    a = v_uint64x2(_mm_unpacklo_epi64(t0, t1));
+    b = v_uint64x2(_mm_unpacklo_epi64(_mm_unpackhi_epi64(t0, t0), t2));
+    c = v_uint64x2(_mm_unpackhi_epi64(t1, t2));
+}
+
+inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a,
+                                v_uint64x2& b, v_uint64x2& c, v_uint64x2& d)
+{
+    __m128i t0 = _mm_loadu_si128((const __m128i*)ptr); // a0 b0
+    __m128i t1 = _mm_loadu_si128((const __m128i*)(ptr + 2)); // c0 d0
+    __m128i t2 = _mm_loadu_si128((const __m128i*)(ptr + 4)); // a1 b1
+    __m128i t3 = _mm_loadu_si128((const __m128i*)(ptr + 6)); // c1 d1
+
+    a = v_uint64x2(_mm_unpacklo_epi64(t0, t2));
+    b = v_uint64x2(_mm_unpackhi_epi64(t0, t2));
+    c = v_uint64x2(_mm_unpacklo_epi64(t1, t3));
+    d = v_uint64x2(_mm_unpackhi_epi64(t1, t3));
+}
+
+// store interleave
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                                hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = _mm_unpacklo_epi8(a.val, b.val);
+    __m128i v1 = _mm_unpackhi_epi8(a.val, b.val);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 16), v1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 16), v1);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 16), v1);
+    }
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                                const v_uint8x16& c, hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+#if CV_SSE4_1
+    const __m128i sh_a = _mm_setr_epi8(0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10, 5);
+    const __m128i sh_b = _mm_setr_epi8(5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15, 10);
+    const __m128i sh_c = _mm_setr_epi8(10, 5, 0, 11, 6, 1, 12, 7, 2, 13, 8, 3, 14, 9, 4, 15);
+    __m128i a0 = _mm_shuffle_epi8(a.val, sh_a);
+    __m128i b0 = _mm_shuffle_epi8(b.val, sh_b);
+    __m128i c0 = _mm_shuffle_epi8(c.val, sh_c);
+
+    const __m128i m0 = _mm_setr_epi8(0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0);
+    const __m128i m1 = _mm_setr_epi8(0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0, -1, 0, 0);
+    __m128i v0 = _mm_blendv_epi8(_mm_blendv_epi8(a0, b0, m1), c0, m0);
+    __m128i v1 = _mm_blendv_epi8(_mm_blendv_epi8(b0, c0, m1), a0, m0);
+    __m128i v2 = _mm_blendv_epi8(_mm_blendv_epi8(c0, a0, m1), b0, m0);
+#elif CV_SSSE3
+    const __m128i m0 = _mm_setr_epi8(0, 6, 11, 1, 7, 12, 2, 8, 13, 3, 9, 14, 4, 10, 15, 5);
+    const __m128i m1 = _mm_setr_epi8(5, 11, 0, 6, 12, 1, 7, 13, 2, 8, 14, 3, 9, 15, 4, 10);
+    const __m128i m2 = _mm_setr_epi8(10, 0, 5, 11, 1, 6, 12, 2, 7, 13, 3, 8, 14, 4, 9, 15);
+
+    __m128i t0 = _mm_alignr_epi8(b.val, _mm_slli_si128(a.val, 10), 5);
+    t0 = _mm_alignr_epi8(c.val, t0, 5);
+    __m128i v0 = _mm_shuffle_epi8(t0, m0);
+
+    __m128i t1 = _mm_alignr_epi8(_mm_srli_si128(b.val, 5), _mm_slli_si128(a.val, 5), 6);
+    t1 = _mm_alignr_epi8(_mm_srli_si128(c.val, 5), t1, 5);
+    __m128i v1 = _mm_shuffle_epi8(t1, m1);
+
+    __m128i t2 = _mm_alignr_epi8(_mm_srli_si128(c.val, 10), b.val, 11);
+    t2 = _mm_alignr_epi8(t2, a.val, 11);
+    __m128i v2 = _mm_shuffle_epi8(t2, m2);
+#else
+    __m128i z = _mm_setzero_si128();
+    __m128i ab0 = _mm_unpacklo_epi8(a.val, b.val);
+    __m128i ab1 = _mm_unpackhi_epi8(a.val, b.val);
+    __m128i c0 = _mm_unpacklo_epi8(c.val, z);
+    __m128i c1 = _mm_unpackhi_epi8(c.val, z);
+
+    __m128i p00 = _mm_unpacklo_epi16(ab0, c0);
+    __m128i p01 = _mm_unpackhi_epi16(ab0, c0);
+    __m128i p02 = _mm_unpacklo_epi16(ab1, c1);
+    __m128i p03 = _mm_unpackhi_epi16(ab1, c1);
+
+    __m128i p10 = _mm_unpacklo_epi32(p00, p01);
+    __m128i p11 = _mm_unpackhi_epi32(p00, p01);
+    __m128i p12 = _mm_unpacklo_epi32(p02, p03);
+    __m128i p13 = _mm_unpackhi_epi32(p02, p03);
+
+    __m128i p20 = _mm_unpacklo_epi64(p10, p11);
+    __m128i p21 = _mm_unpackhi_epi64(p10, p11);
+    __m128i p22 = _mm_unpacklo_epi64(p12, p13);
+    __m128i p23 = _mm_unpackhi_epi64(p12, p13);
+
+    p20 = _mm_slli_si128(p20, 1);
+    p22 = _mm_slli_si128(p22, 1);
+
+    __m128i p30 = _mm_slli_epi64(_mm_unpacklo_epi32(p20, p21), 8);
+    __m128i p31 = _mm_srli_epi64(_mm_unpackhi_epi32(p20, p21), 8);
+    __m128i p32 = _mm_slli_epi64(_mm_unpacklo_epi32(p22, p23), 8);
+    __m128i p33 = _mm_srli_epi64(_mm_unpackhi_epi32(p22, p23), 8);
+
+    __m128i p40 = _mm_unpacklo_epi64(p30, p31);
+    __m128i p41 = _mm_unpackhi_epi64(p30, p31);
+    __m128i p42 = _mm_unpacklo_epi64(p32, p33);
+    __m128i p43 = _mm_unpackhi_epi64(p32, p33);
+
+    __m128i v0 = _mm_or_si128(_mm_srli_si128(p40, 2), _mm_slli_si128(p41, 10));
+    __m128i v1 = _mm_or_si128(_mm_srli_si128(p41, 6), _mm_slli_si128(p42, 6));
+    __m128i v2 = _mm_or_si128(_mm_srli_si128(p42, 10), _mm_slli_si128(p43, 2));
+#endif
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 16), v1);
+        _mm_stream_si128((__m128i*)(ptr + 32), v2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 16), v1);
+        _mm_store_si128((__m128i*)(ptr + 32), v2);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 16), v1);
+        _mm_storeu_si128((__m128i*)(ptr + 32), v2);
+    }
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                                const v_uint8x16& c, const v_uint8x16& d,
+                                hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    // a0 a1 a2 a3 ....
+    // b0 b1 b2 b3 ....
+    // c0 c1 c2 c3 ....
+    // d0 d1 d2 d3 ....
+    __m128i u0 = _mm_unpacklo_epi8(a.val, c.val); // a0 c0 a1 c1 ...
+    __m128i u1 = _mm_unpackhi_epi8(a.val, c.val); // a8 c8 a9 c9 ...
+    __m128i u2 = _mm_unpacklo_epi8(b.val, d.val); // b0 d0 b1 d1 ...
+    __m128i u3 = _mm_unpackhi_epi8(b.val, d.val); // b8 d8 b9 d9 ...
+
+    __m128i v0 = _mm_unpacklo_epi8(u0, u2); // a0 b0 c0 d0 ...
+    __m128i v1 = _mm_unpackhi_epi8(u0, u2); // a4 b4 c4 d4 ...
+    __m128i v2 = _mm_unpacklo_epi8(u1, u3); // a8 b8 c8 d8 ...
+    __m128i v3 = _mm_unpackhi_epi8(u1, u3); // a12 b12 c12 d12 ...
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 16), v1);
+        _mm_stream_si128((__m128i*)(ptr + 32), v2);
+        _mm_stream_si128((__m128i*)(ptr + 48), v3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 16), v1);
+        _mm_store_si128((__m128i*)(ptr + 32), v2);
+        _mm_store_si128((__m128i*)(ptr + 48), v3);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 16), v1);
+        _mm_storeu_si128((__m128i*)(ptr + 32), v2);
+        _mm_storeu_si128((__m128i*)(ptr + 48), v3);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x8& a, const v_uint16x8& b,
+                                hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = _mm_unpacklo_epi16(a.val, b.val);
+    __m128i v1 = _mm_unpackhi_epi16(a.val, b.val);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 8), v1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 8), v1);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 8), v1);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x8& a,
+                                const v_uint16x8& b, const v_uint16x8& c,
+                                hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+#if CV_SSE4_1
+    const __m128i sh_a = _mm_setr_epi8(0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5, 10, 11);
+    const __m128i sh_b = _mm_setr_epi8(10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15, 4, 5);
+    const __m128i sh_c = _mm_setr_epi8(4, 5, 10, 11, 0, 1, 6, 7, 12, 13, 2, 3, 8, 9, 14, 15);
+    __m128i a0 = _mm_shuffle_epi8(a.val, sh_a);
+    __m128i b0 = _mm_shuffle_epi8(b.val, sh_b);
+    __m128i c0 = _mm_shuffle_epi8(c.val, sh_c);
+
+    __m128i v0 = _mm_blend_epi16(_mm_blend_epi16(a0, b0, 0x92), c0, 0x24);
+    __m128i v1 = _mm_blend_epi16(_mm_blend_epi16(c0, a0, 0x92), b0, 0x24);
+    __m128i v2 = _mm_blend_epi16(_mm_blend_epi16(b0, c0, 0x92), a0, 0x24);
+#else
+    __m128i z = _mm_setzero_si128();
+    __m128i ab0 = _mm_unpacklo_epi16(a.val, b.val);
+    __m128i ab1 = _mm_unpackhi_epi16(a.val, b.val);
+    __m128i c0 = _mm_unpacklo_epi16(c.val, z);
+    __m128i c1 = _mm_unpackhi_epi16(c.val, z);
+
+    __m128i p10 = _mm_unpacklo_epi32(ab0, c0);
+    __m128i p11 = _mm_unpackhi_epi32(ab0, c0);
+    __m128i p12 = _mm_unpacklo_epi32(ab1, c1);
+    __m128i p13 = _mm_unpackhi_epi32(ab1, c1);
+
+    __m128i p20 = _mm_unpacklo_epi64(p10, p11);
+    __m128i p21 = _mm_unpackhi_epi64(p10, p11);
+    __m128i p22 = _mm_unpacklo_epi64(p12, p13);
+    __m128i p23 = _mm_unpackhi_epi64(p12, p13);
+
+    p20 = _mm_slli_si128(p20, 2);
+    p22 = _mm_slli_si128(p22, 2);
+
+    __m128i p30 = _mm_unpacklo_epi64(p20, p21);
+    __m128i p31 = _mm_unpackhi_epi64(p20, p21);
+    __m128i p32 = _mm_unpacklo_epi64(p22, p23);
+    __m128i p33 = _mm_unpackhi_epi64(p22, p23);
+
+    __m128i v0 = _mm_or_si128(_mm_srli_si128(p30, 2), _mm_slli_si128(p31, 10));
+    __m128i v1 = _mm_or_si128(_mm_srli_si128(p31, 6), _mm_slli_si128(p32, 6));
+    __m128i v2 = _mm_or_si128(_mm_srli_si128(p32, 10), _mm_slli_si128(p33, 2));
+#endif
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 8), v1);
+        _mm_stream_si128((__m128i*)(ptr + 16), v2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 8), v1);
+        _mm_store_si128((__m128i*)(ptr + 16), v2);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 8), v1);
+        _mm_storeu_si128((__m128i*)(ptr + 16), v2);
+    }
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x8& a, const v_uint16x8& b,
+                                const v_uint16x8& c, const v_uint16x8& d,
+                                hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    // a0 a1 a2 a3 ....
+    // b0 b1 b2 b3 ....
+    // c0 c1 c2 c3 ....
+    // d0 d1 d2 d3 ....
+    __m128i u0 = _mm_unpacklo_epi16(a.val, c.val); // a0 c0 a1 c1 ...
+    __m128i u1 = _mm_unpackhi_epi16(a.val, c.val); // a4 c4 a5 c5 ...
+    __m128i u2 = _mm_unpacklo_epi16(b.val, d.val); // b0 d0 b1 d1 ...
+    __m128i u3 = _mm_unpackhi_epi16(b.val, d.val); // b4 d4 b5 d5 ...
+
+    __m128i v0 = _mm_unpacklo_epi16(u0, u2); // a0 b0 c0 d0 ...
+    __m128i v1 = _mm_unpackhi_epi16(u0, u2); // a2 b2 c2 d2 ...
+    __m128i v2 = _mm_unpacklo_epi16(u1, u3); // a4 b4 c4 d4 ...
+    __m128i v3 = _mm_unpackhi_epi16(u1, u3); // a6 b6 c6 d6 ...
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 8), v1);
+        _mm_stream_si128((__m128i*)(ptr + 16), v2);
+        _mm_stream_si128((__m128i*)(ptr + 24), v3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 8), v1);
+        _mm_store_si128((__m128i*)(ptr + 16), v2);
+        _mm_store_si128((__m128i*)(ptr + 24), v3);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 8), v1);
+        _mm_storeu_si128((__m128i*)(ptr + 16), v2);
+        _mm_storeu_si128((__m128i*)(ptr + 24), v3);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                                hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = _mm_unpacklo_epi32(a.val, b.val);
+    __m128i v1 = _mm_unpackhi_epi32(a.val, b.val);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 4), v1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 4), v1);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 4), v1);
+    }
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                                const v_uint32x4& c, hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    v_uint32x4 z = v_setzero_u32(), u0, u1, u2, u3;
+    v_transpose4x4(a, b, c, z, u0, u1, u2, u3);
+
+    __m128i v0 = _mm_or_si128(u0.val, _mm_slli_si128(u1.val, 12));
+    __m128i v1 = _mm_or_si128(_mm_srli_si128(u1.val, 4), _mm_slli_si128(u2.val, 8));
+    __m128i v2 = _mm_or_si128(_mm_srli_si128(u2.val, 8), _mm_slli_si128(u3.val, 4));
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 4), v1);
+        _mm_stream_si128((__m128i*)(ptr + 8), v2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 4), v1);
+        _mm_store_si128((__m128i*)(ptr + 8), v2);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 4), v1);
+        _mm_storeu_si128((__m128i*)(ptr + 8), v2);
+    }
+}
+
+inline void v_store_interleave(unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                               const v_uint32x4& c, const v_uint32x4& d,
+                               hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    v_uint32x4 v0, v1, v2, v3;
+    v_transpose4x4(a, b, c, d, v0, v1, v2, v3);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0.val);
+        _mm_stream_si128((__m128i*)(ptr + 4), v1.val);
+        _mm_stream_si128((__m128i*)(ptr + 8), v2.val);
+        _mm_stream_si128((__m128i*)(ptr + 12), v3.val);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0.val);
+        _mm_store_si128((__m128i*)(ptr + 4), v1.val);
+        _mm_store_si128((__m128i*)(ptr + 8), v2.val);
+        _mm_store_si128((__m128i*)(ptr + 12), v3.val);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0.val);
+        _mm_storeu_si128((__m128i*)(ptr + 4), v1.val);
+        _mm_storeu_si128((__m128i*)(ptr + 8), v2.val);
+        _mm_storeu_si128((__m128i*)(ptr + 12), v3.val);
+    }
+}
+
+// 2-channel, float only
+inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b,
+                               hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128 v0 = _mm_unpacklo_ps(a.val, b.val); // a0 b0 a1 b1
+    __m128 v1 = _mm_unpackhi_ps(a.val, b.val); // a2 b2 a3 b3
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_ps(ptr, v0);
+        _mm_stream_ps(ptr + 4, v1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_ps(ptr, v0);
+        _mm_store_ps(ptr + 4, v1);
+    }
+    else
+    {
+        _mm_storeu_ps(ptr, v0);
+        _mm_storeu_ps(ptr + 4, v1);
+    }
+}
+
+inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b,
+                               const v_float32x4& c, hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128 u0 = _mm_shuffle_ps(a.val, b.val, _MM_SHUFFLE(0, 0, 0, 0));
+    __m128 u1 = _mm_shuffle_ps(c.val, a.val, _MM_SHUFFLE(1, 1, 0, 0));
+    __m128 v0 = _mm_shuffle_ps(u0, u1, _MM_SHUFFLE(2, 0, 2, 0));
+    __m128 u2 = _mm_shuffle_ps(b.val, c.val, _MM_SHUFFLE(1, 1, 1, 1));
+    __m128 u3 = _mm_shuffle_ps(a.val, b.val, _MM_SHUFFLE(2, 2, 2, 2));
+    __m128 v1 = _mm_shuffle_ps(u2, u3, _MM_SHUFFLE(2, 0, 2, 0));
+    __m128 u4 = _mm_shuffle_ps(c.val, a.val, _MM_SHUFFLE(3, 3, 2, 2));
+    __m128 u5 = _mm_shuffle_ps(b.val, c.val, _MM_SHUFFLE(3, 3, 3, 3));
+    __m128 v2 = _mm_shuffle_ps(u4, u5, _MM_SHUFFLE(2, 0, 2, 0));
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_ps(ptr, v0);
+        _mm_stream_ps(ptr + 4, v1);
+        _mm_stream_ps(ptr + 8, v2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_ps(ptr, v0);
+        _mm_store_ps(ptr + 4, v1);
+        _mm_store_ps(ptr + 8, v2);
+    }
+    else
+    {
+        _mm_storeu_ps(ptr, v0);
+        _mm_storeu_ps(ptr + 4, v1);
+        _mm_storeu_ps(ptr + 8, v2);
+    }
+}
+
+inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b,
+                               const v_float32x4& c, const v_float32x4& d,
+                               hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128 u0 = _mm_unpacklo_ps(a.val, c.val);
+    __m128 u1 = _mm_unpacklo_ps(b.val, d.val);
+    __m128 u2 = _mm_unpackhi_ps(a.val, c.val);
+    __m128 u3 = _mm_unpackhi_ps(b.val, d.val);
+    __m128 v0 = _mm_unpacklo_ps(u0, u1);
+    __m128 v2 = _mm_unpacklo_ps(u2, u3);
+    __m128 v1 = _mm_unpackhi_ps(u0, u1);
+    __m128 v3 = _mm_unpackhi_ps(u2, u3);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_ps(ptr, v0);
+        _mm_stream_ps(ptr + 4, v1);
+        _mm_stream_ps(ptr + 8, v2);
+        _mm_stream_ps(ptr + 12, v3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_ps(ptr, v0);
+        _mm_store_ps(ptr + 4, v1);
+        _mm_store_ps(ptr + 8, v2);
+        _mm_store_ps(ptr + 12, v3);
+    }
+    else
+    {
+        _mm_storeu_ps(ptr, v0);
+        _mm_storeu_ps(ptr + 4, v1);
+        _mm_storeu_ps(ptr + 8, v2);
+        _mm_storeu_ps(ptr + 12, v3);
+    }
+}
+
+inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = _mm_unpacklo_epi64(a.val, b.val);
+    __m128i v1 = _mm_unpackhi_epi64(a.val, b.val);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 2), v1);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 2), v1);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 2), v1);
+    }
+}
+
+inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               const v_uint64x2& c, hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = _mm_unpacklo_epi64(a.val, b.val);
+    __m128i v1 = _mm_unpacklo_epi64(c.val, _mm_unpackhi_epi64(a.val, a.val));
+    __m128i v2 = _mm_unpackhi_epi64(b.val, c.val);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 2), v1);
+        _mm_stream_si128((__m128i*)(ptr + 4), v2);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 2), v1);
+        _mm_store_si128((__m128i*)(ptr + 4), v2);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 2), v1);
+        _mm_storeu_si128((__m128i*)(ptr + 4), v2);
+    }
+}
+
+inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               const v_uint64x2& c, const v_uint64x2& d,
+                               hal::StoreMode mode = hal::STORE_UNALIGNED)
+{
+    __m128i v0 = _mm_unpacklo_epi64(a.val, b.val);
+    __m128i v1 = _mm_unpacklo_epi64(c.val, d.val);
+    __m128i v2 = _mm_unpackhi_epi64(a.val, b.val);
+    __m128i v3 = _mm_unpackhi_epi64(c.val, d.val);
+
+    if( mode == hal::STORE_ALIGNED_NOCACHE )
+    {
+        _mm_stream_si128((__m128i*)(ptr), v0);
+        _mm_stream_si128((__m128i*)(ptr + 2), v1);
+        _mm_stream_si128((__m128i*)(ptr + 4), v2);
+        _mm_stream_si128((__m128i*)(ptr + 6), v3);
+    }
+    else if( mode == hal::STORE_ALIGNED )
+    {
+        _mm_store_si128((__m128i*)(ptr), v0);
+        _mm_store_si128((__m128i*)(ptr + 2), v1);
+        _mm_store_si128((__m128i*)(ptr + 4), v2);
+        _mm_store_si128((__m128i*)(ptr + 6), v3);
+    }
+    else
+    {
+        _mm_storeu_si128((__m128i*)(ptr), v0);
+        _mm_storeu_si128((__m128i*)(ptr + 2), v1);
+        _mm_storeu_si128((__m128i*)(ptr + 4), v2);
+        _mm_storeu_si128((__m128i*)(ptr + 6), v3);
+    }
+}
+
+#define OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1) \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0 ) \
+{ \
+    _Tpvec1 a1, b1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0 ) \
+{ \
+    _Tpvec1 a1, b1, c1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0, _Tpvec0& d0 ) \
+{ \
+    _Tpvec1 a1, b1, c1, d1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+    d0 = v_reinterpret_as_##suffix0(d1); \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                hal::StoreMode mode = hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, mode);      \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                const _Tpvec0& c0, hal::StoreMode mode = hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, mode);  \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                const _Tpvec0& c0, const _Tpvec0& d0, \
+                                hal::StoreMode mode = hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1, mode); \
+}
+
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int8x16, schar, s8, v_uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int16x8, short, s16, v_uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int32x4, int, s32, v_uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_int64x2, int64, s64, v_uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_SSE_LOADSTORE_INTERLEAVE(v_float64x2, double, f64, v_uint64x2, uint64, u64)
+
+inline v_float32x4 v_cvt_f32(const v_int32x4& a)
+{
+    return v_float32x4(_mm_cvtepi32_ps(a.val));
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a)
+{
+    return v_float32x4(_mm_cvtpd_ps(a.val));
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b)
+{
+    return v_float32x4(_mm_movelh_ps(_mm_cvtpd_ps(a.val), _mm_cvtpd_ps(b.val)));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int32x4& a)
+{
+    return v_float64x2(_mm_cvtepi32_pd(a.val));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_int32x4& a)
+{
+    return v_float64x2(_mm_cvtepi32_pd(_mm_srli_si128(a.val,8)));
+}
+
+inline v_float64x2 v_cvt_f64(const v_float32x4& a)
+{
+    return v_float64x2(_mm_cvtps_pd(a.val));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_float32x4& a)
+{
+    return v_float64x2(_mm_cvtps_pd(_mm_movehl_ps(a.val, a.val)));
+}
+
+// from (Mysticial and wim) https://stackoverflow.com/q/41144668
+inline v_float64x2 v_cvt_f64(const v_int64x2& v)
+{
+    // constants encoded as floating-point
+    __m128i magic_i_hi32 = _mm_set1_epi64x(0x4530000080000000); // 2^84 + 2^63
+    __m128i magic_i_all  = _mm_set1_epi64x(0x4530000080100000); // 2^84 + 2^63 + 2^52
+    __m128d magic_d_all  = _mm_castsi128_pd(magic_i_all);
+    // Blend the 32 lowest significant bits of v with magic_int_lo
+#if CV_SSE4_1
+    __m128i magic_i_lo   = _mm_set1_epi64x(0x4330000000000000); // 2^52
+    __m128i v_lo         = _mm_blend_epi16(v.val, magic_i_lo, 0xcc);
+#else
+    __m128i magic_i_lo   = _mm_set1_epi32(0x43300000); // 2^52
+    __m128i v_lo         = _mm_unpacklo_epi32(_mm_shuffle_epi32(v.val, _MM_SHUFFLE(0, 0, 2, 0)), magic_i_lo);
+#endif
+    // Extract the 32 most significant bits of v
+    __m128i v_hi         = _mm_srli_epi64(v.val, 32);
+    // Flip the msb of v_hi and blend with 0x45300000
+            v_hi         = _mm_xor_si128(v_hi, magic_i_hi32);
+    // Compute in double precision
+    __m128d v_hi_dbl     = _mm_sub_pd(_mm_castsi128_pd(v_hi), magic_d_all);
+    // (v_hi - magic_d_all) + v_lo  Do not assume associativity of floating point addition
+    __m128d result       = _mm_add_pd(v_hi_dbl, _mm_castsi128_pd(v_lo));
+    return v_float64x2(result);
+}
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x16 v_lut(const schar* tab, const int* idx)
+{
+#if defined(_MSC_VER)
+    return v_int8x16(_mm_setr_epi8(tab[idx[0]], tab[idx[1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]],
+                                   tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]]));
+#else
+    return v_int8x16(_mm_setr_epi64(
+                        _mm_setr_pi8(tab[idx[0]], tab[idx[1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]]),
+                        _mm_setr_pi8(tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]])
+                    ));
+#endif
+}
+inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx)
+{
+#if defined(_MSC_VER)
+    return v_int8x16(_mm_setr_epi16(*(const short*)(tab + idx[0]), *(const short*)(tab + idx[1]), *(const short*)(tab + idx[2]), *(const short*)(tab + idx[3]),
+                                    *(const short*)(tab + idx[4]), *(const short*)(tab + idx[5]), *(const short*)(tab + idx[6]), *(const short*)(tab + idx[7])));
+#else
+    return v_int8x16(_mm_setr_epi64(
+                        _mm_setr_pi16(*(const short*)(tab + idx[0]), *(const short*)(tab + idx[1]), *(const short*)(tab + idx[2]), *(const short*)(tab + idx[3])),
+                        _mm_setr_pi16(*(const short*)(tab + idx[4]), *(const short*)(tab + idx[5]), *(const short*)(tab + idx[6]), *(const short*)(tab + idx[7]))
+                    ));
+#endif
+}
+inline v_int8x16 v_lut_quads(const schar* tab, const int* idx)
+{
+#if defined(_MSC_VER)
+    return v_int8x16(_mm_setr_epi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]),
+                                    *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3])));
+#else
+    return v_int8x16(_mm_setr_epi64(
+                        _mm_setr_pi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1])),
+                        _mm_setr_pi32(*(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]))
+                    ));
+#endif
+}
+inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((const schar *)tab, idx)); }
+inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((const schar *)tab, idx)); }
+inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((const schar *)tab, idx)); }
+
+inline v_int16x8 v_lut(const short* tab, const int* idx)
+{
+#if defined(_MSC_VER)
+    return v_int16x8(_mm_setr_epi16(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]],
+                                    tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]));
+#else
+    return v_int16x8(_mm_setr_epi64(
+                        _mm_setr_pi16(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]),
+                        _mm_setr_pi16(tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]])
+                    ));
+#endif
+}
+inline v_int16x8 v_lut_pairs(const short* tab, const int* idx)
+{
+#if defined(_MSC_VER)
+    return v_int16x8(_mm_setr_epi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]),
+                                    *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3])));
+#else
+    return v_int16x8(_mm_setr_epi64(
+                        _mm_setr_pi32(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1])),
+                        _mm_setr_pi32(*(const int*)(tab + idx[2]), *(const int*)(tab + idx[3]))
+                    ));
+#endif
+}
+inline v_int16x8 v_lut_quads(const short* tab, const int* idx)
+{
+    return v_int16x8(_mm_set_epi64x(*(const int64_t*)(tab + idx[1]), *(const int64_t*)(tab + idx[0])));
+}
+inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((const short *)tab, idx)); }
+inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((const short *)tab, idx)); }
+inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((const short *)tab, idx)); }
+
+inline v_int32x4 v_lut(const int* tab, const int* idx)
+{
+#if defined(_MSC_VER)
+    return v_int32x4(_mm_setr_epi32(tab[idx[0]], tab[idx[1]],
+                                    tab[idx[2]], tab[idx[3]]));
+#else
+    return v_int32x4(_mm_setr_epi64(
+                        _mm_setr_pi32(tab[idx[0]], tab[idx[1]]),
+                        _mm_setr_pi32(tab[idx[2]], tab[idx[3]])
+                    ));
+#endif
+}
+inline v_int32x4 v_lut_pairs(const int* tab, const int* idx)
+{
+    return v_int32x4(_mm_set_epi64x(*(const int64_t*)(tab + idx[1]), *(const int64_t*)(tab + idx[0])));
+}
+inline v_int32x4 v_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x4(_mm_loadu_si128((const __m128i*)(tab + idx[0])));
+}
+inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((const int *)tab, idx)); }
+inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((const int *)tab, idx)); }
+inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((const int *)tab, idx)); }
+
+inline v_int64x2 v_lut(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(_mm_set_epi64x(tab[idx[1]], tab[idx[0]]));
+}
+inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(_mm_loadu_si128((const __m128i*)(tab + idx[0])));
+}
+inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); }
+inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); }
+
+inline v_float32x4 v_lut(const float* tab, const int* idx)
+{
+    return v_float32x4(_mm_setr_ps(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]));
+}
+inline v_float32x4 v_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_pairs((const int *)tab, idx)); }
+inline v_float32x4 v_lut_quads(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_quads((const int *)tab, idx)); }
+
+inline v_float64x2 v_lut(const double* tab, const int* idx)
+{
+    return v_float64x2(_mm_setr_pd(tab[idx[0]], tab[idx[1]]));
+}
+inline v_float64x2 v_lut_pairs(const double* tab, const int* idx) { return v_float64x2(_mm_castsi128_pd(_mm_loadu_si128((const __m128i*)(tab + idx[0])))); }
+
+inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+    return v_int32x4(_mm_setr_epi32(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]));
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec)
+{
+    return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec));
+}
+
+inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+    return v_float32x4(_mm_setr_ps(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]));
+}
+
+inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec)
+{
+    int idx[2];
+    v_store_low(idx, idxvec);
+    return v_float64x2(_mm_setr_pd(tab[idx[0]], tab[idx[1]]));
+}
+
+// loads pairs from the table and deinterleaves them, e.g. returns:
+//   x = (tab[idxvec[0], tab[idxvec[1]], tab[idxvec[2]], tab[idxvec[3]]),
+//   y = (tab[idxvec[0]+1], tab[idxvec[1]+1], tab[idxvec[2]+1], tab[idxvec[3]+1])
+// note that the indices are float's indices, not the float-pair indices.
+// in theory, this function can be used to implement bilinear interpolation,
+// when idxvec are the offsets within the image.
+inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y)
+{
+    int CV_DECL_ALIGNED(32) idx[4];
+    v_store_aligned(idx, idxvec);
+    __m128 z = _mm_setzero_ps();
+    __m128 xy01 = _mm_loadl_pi(z, (__m64*)(tab + idx[0]));
+    __m128 xy23 = _mm_loadl_pi(z, (__m64*)(tab + idx[2]));
+    xy01 = _mm_loadh_pi(xy01, (__m64*)(tab + idx[1]));
+    xy23 = _mm_loadh_pi(xy23, (__m64*)(tab + idx[3]));
+    __m128 xxyy02 = _mm_unpacklo_ps(xy01, xy23);
+    __m128 xxyy13 = _mm_unpackhi_ps(xy01, xy23);
+    x = v_float32x4(_mm_unpacklo_ps(xxyy02, xxyy13));
+    y = v_float32x4(_mm_unpackhi_ps(xxyy02, xxyy13));
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y)
+{
+    int idx[2];
+    v_store_low(idx, idxvec);
+    __m128d xy0 = _mm_loadu_pd(tab + idx[0]);
+    __m128d xy1 = _mm_loadu_pd(tab + idx[1]);
+    x = v_float64x2(_mm_unpacklo_pd(xy0, xy1));
+    y = v_float64x2(_mm_unpackhi_pd(xy0, xy1));
+}
+
+inline v_int8x16 v_interleave_pairs(const v_int8x16& vec)
+{
+#if CV_SSSE3
+    return v_int8x16(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0d0e0c0b090a08, 0x0705060403010200)));
+#else
+    __m128i a = _mm_shufflelo_epi16(vec.val, _MM_SHUFFLE(3, 1, 2, 0));
+    a = _mm_shufflehi_epi16(a, _MM_SHUFFLE(3, 1, 2, 0));
+    a = _mm_shuffle_epi32(a, _MM_SHUFFLE(3, 1, 2, 0));
+    return v_int8x16(_mm_unpacklo_epi8(a, _mm_unpackhi_epi64(a, a)));
+#endif
+}
+inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x16 v_interleave_quads(const v_int8x16& vec)
+{
+#if CV_SSSE3
+    return v_int8x16(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0b0e0a0d090c08, 0x0703060205010400)));
+#else
+    __m128i a = _mm_shuffle_epi32(vec.val, _MM_SHUFFLE(3, 1, 2, 0));
+    return v_int8x16(_mm_unpacklo_epi8(a, _mm_unpackhi_epi64(a, a)));
+#endif
+}
+inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_interleave_pairs(const v_int16x8& vec)
+{
+#if CV_SSSE3
+    return v_int16x8(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0e0b0a0d0c0908, 0x0706030205040100)));
+#else
+    __m128i a = _mm_shufflelo_epi16(vec.val, _MM_SHUFFLE(3, 1, 2, 0));
+    return v_int16x8(_mm_shufflehi_epi16(a, _MM_SHUFFLE(3, 1, 2, 0)));
+#endif
+}
+inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x8 v_interleave_quads(const v_int16x8& vec)
+{
+#if CV_SSSE3
+    return v_int16x8(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0x0f0e07060d0c0504, 0x0b0a030209080100)));
+#else
+    return v_int16x8(_mm_unpacklo_epi16(vec.val, _mm_unpackhi_epi64(vec.val, vec.val)));
+#endif
+}
+inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_interleave_pairs(const v_int32x4& vec)
+{
+    return v_int32x4(_mm_shuffle_epi32(vec.val, _MM_SHUFFLE(3, 1, 2, 0)));
+}
+inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x4 v_interleave_pairs(const v_float32x4& vec) { return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x16 v_pack_triplets(const v_int8x16& vec)
+{
+#if CV_SSSE3
+    return v_int8x16(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0xffffff0f0e0d0c0a, 0x0908060504020100)));
+#else
+    __m128i mask = _mm_set1_epi64x(0x00000000FFFFFFFF);
+    __m128i a = _mm_srli_si128(_mm_or_si128(_mm_andnot_si128(mask, vec.val), _mm_and_si128(mask, _mm_sll_epi32(vec.val, _mm_set_epi64x(0, 8)))), 1);
+    return v_int8x16(_mm_srli_si128(_mm_shufflelo_epi16(a, _MM_SHUFFLE(2, 1, 0, 3)), 2));
+#endif
+}
+inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_pack_triplets(const v_int16x8& vec)
+{
+#if CV_SSSE3
+    return v_int16x8(_mm_shuffle_epi8(vec.val, _mm_set_epi64x(0xffff0f0e0d0c0b0a, 0x0908050403020100)));
+#else
+    return v_int16x8(_mm_srli_si128(_mm_shufflelo_epi16(vec.val, _MM_SHUFFLE(2, 1, 0, 3)), 2));
+#endif
+}
+inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; }
+inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; }
+inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; }
+
+template<int i>
+inline uchar v_extract_n(const v_uint8x16& v)
+{
+#if CV_SSE4_1
+    return (uchar)_mm_extract_epi8(v.val, i);
+#else
+    return v_rotate_right<i>(v).get0();
+#endif
+}
+
+template<int i>
+inline schar v_extract_n(const v_int8x16& v)
+{
+    return (schar)v_extract_n<i>(v_reinterpret_as_u8(v));
+}
+
+template<int i>
+inline ushort v_extract_n(const v_uint16x8& v)
+{
+    return (ushort)_mm_extract_epi16(v.val, i);
+}
+
+template<int i>
+inline short v_extract_n(const v_int16x8& v)
+{
+    return (short)v_extract_n<i>(v_reinterpret_as_u16(v));
+}
+
+template<int i>
+inline uint v_extract_n(const v_uint32x4& v)
+{
+#if CV_SSE4_1
+    return (uint)_mm_extract_epi32(v.val, i);
+#else
+    return v_rotate_right<i>(v).get0();
+#endif
+}
+
+template<int i>
+inline int v_extract_n(const v_int32x4& v)
+{
+    return (int)v_extract_n<i>(v_reinterpret_as_u32(v));
+}
+
+template<int i>
+inline uint64 v_extract_n(const v_uint64x2& v)
+{
+#ifdef CV__SIMD_NATIVE_mm_extract_epi64
+    return (uint64)_v128_extract_epi64<i>(v.val);
+#else
+    return v_rotate_right<i>(v).get0();
+#endif
+}
+
+template<int i>
+inline int64 v_extract_n(const v_int64x2& v)
+{
+    return (int64)v_extract_n<i>(v_reinterpret_as_u64(v));
+}
+
+template<int i>
+inline float v_extract_n(const v_float32x4& v)
+{
+    union { uint iv; float fv; } d;
+    d.iv = v_extract_n<i>(v_reinterpret_as_u32(v));
+    return d.fv;
+}
+
+template<int i>
+inline double v_extract_n(const v_float64x2& v)
+{
+    union { uint64 iv; double dv; } d;
+    d.iv = v_extract_n<i>(v_reinterpret_as_u64(v));
+    return d.dv;
+}
+
+template<int i>
+inline v_int32x4 v_broadcast_element(const v_int32x4& v)
+{
+    return v_int32x4(_mm_shuffle_epi32(v.val, _MM_SHUFFLE(i,i,i,i)));
+}
+
+template<int i>
+inline v_uint32x4 v_broadcast_element(const v_uint32x4& v)
+{
+    return v_uint32x4(_mm_shuffle_epi32(v.val, _MM_SHUFFLE(i,i,i,i)));
+}
+
+template<int i>
+inline v_float32x4 v_broadcast_element(const v_float32x4& v)
+{
+    return v_float32x4(_mm_shuffle_ps(v.val, v.val, _MM_SHUFFLE((char)i,(char)i,(char)i,(char)i)));
+}
+
+////////////// FP16 support ///////////////////////////
+
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+#if CV_FP16
+    return v_float32x4(_mm_cvtph_ps(_mm_loadu_si128((const __m128i*)ptr)));
+#else
+    const __m128i z = _mm_setzero_si128(), delta = _mm_set1_epi32(0x38000000);
+    const __m128i signmask = _mm_set1_epi32(0x80000000), maxexp = _mm_set1_epi32(0x7c000000);
+    const __m128 deltaf = _mm_castsi128_ps(_mm_set1_epi32(0x38800000));
+    __m128i bits = _mm_unpacklo_epi16(z, _mm_loadl_epi64((const __m128i*)ptr)); // h << 16
+    __m128i e = _mm_and_si128(bits, maxexp), sign = _mm_and_si128(bits, signmask);
+    __m128i t = _mm_add_epi32(_mm_srli_epi32(_mm_xor_si128(bits, sign), 3), delta); // ((h & 0x7fff) << 13) + delta
+    __m128i zt = _mm_castps_si128(_mm_sub_ps(_mm_castsi128_ps(_mm_add_epi32(t, _mm_set1_epi32(1 << 23))), deltaf));
+
+    t = _mm_add_epi32(t, _mm_and_si128(delta, _mm_cmpeq_epi32(maxexp, e)));
+    __m128i zmask = _mm_cmpeq_epi32(e, z);
+    __m128i ft = v_select_si128(zmask, zt, t);
+    return v_float32x4(_mm_castsi128_ps(_mm_or_si128(ft, sign)));
+#endif
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+#if CV_FP16
+    __m128i fp16_value = _mm_cvtps_ph(v.val, 0);
+    _mm_storel_epi64((__m128i*)ptr, fp16_value);
+#else
+    const __m128i signmask = _mm_set1_epi32(0x80000000);
+    const __m128i rval = _mm_set1_epi32(0x3f000000);
+
+    __m128i t = _mm_castps_si128(v.val);
+    __m128i sign = _mm_srai_epi32(_mm_and_si128(t, signmask), 16);
+    t = _mm_andnot_si128(signmask, t);
+
+    __m128i finitemask = _mm_cmpgt_epi32(_mm_set1_epi32(0x47800000), t);
+    __m128i isnan = _mm_cmpgt_epi32(t, _mm_set1_epi32(0x7f800000));
+    __m128i naninf = v_select_si128(isnan, _mm_set1_epi32(0x7e00), _mm_set1_epi32(0x7c00));
+    __m128i tinymask = _mm_cmpgt_epi32(_mm_set1_epi32(0x38800000), t);
+    __m128i tt = _mm_castps_si128(_mm_add_ps(_mm_castsi128_ps(t), _mm_castsi128_ps(rval)));
+    tt = _mm_sub_epi32(tt, rval);
+    __m128i odd = _mm_and_si128(_mm_srli_epi32(t, 13), _mm_set1_epi32(1));
+    __m128i nt = _mm_add_epi32(t, _mm_set1_epi32(0xc8000fff));
+    nt = _mm_srli_epi32(_mm_add_epi32(nt, odd), 13);
+    t = v_select_si128(tinymask, tt, nt);
+    t = v_select_si128(finitemask, t, naninf);
+    t = _mm_or_si128(t, sign);
+    t = _mm_packs_epi32(t, t);
+    _mm_storel_epi64((__m128i*)ptr, t);
+#endif
+}
+
+inline void v_cleanup() {}
+
+#include "intrin_math.hpp"
+inline v_float32x4 v_exp(const v_float32x4& x) { return v_exp_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_log(const v_float32x4& x) { return v_log_default_32f<v_float32x4, v_int32x4>(x); }
+inline void v_sincos(const v_float32x4& x, v_float32x4& s, v_float32x4& c) { v_sincos_default_32f<v_float32x4, v_int32x4>(x, s, c); }
+inline v_float32x4 v_sin(const v_float32x4& x) { return v_sin_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_cos(const v_float32x4& x) { return v_cos_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_erf(const v_float32x4& x) { return v_erf_default_32f<v_float32x4, v_int32x4>(x); }
+
+inline v_float64x2 v_exp(const v_float64x2& x) { return v_exp_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_log(const v_float64x2& x) { return v_log_default_64f<v_float64x2, v_int64x2>(x); }
+inline void v_sincos(const v_float64x2& x, v_float64x2& s, v_float64x2& c) { v_sincos_default_64f<v_float64x2, v_int64x2>(x, s, c); }
+inline v_float64x2 v_sin(const v_float64x2& x) { return v_sin_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_cos(const v_float64x2& x) { return v_cos_default_64f<v_float64x2, v_int64x2>(x); }
+
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+}
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_sse_em.hpp

@@ -0,0 +1,180 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+#ifndef OPENCV_HAL_INTRIN_SSE_EM_HPP
+#define OPENCV_HAL_INTRIN_SSE_EM_HPP
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+#define OPENCV_HAL_SSE_WRAP_1(fun, tp) \
+    inline tp _v128_##fun(const tp& a) \
+    { return _mm_##fun(a); }
+
+#define OPENCV_HAL_SSE_WRAP_2(fun, tp) \
+    inline tp _v128_##fun(const tp& a, const tp& b) \
+    { return _mm_##fun(a, b); }
+
+#define OPENCV_HAL_SSE_WRAP_3(fun, tp) \
+    inline tp _v128_##fun(const tp& a, const tp& b, const tp& c) \
+    { return _mm_##fun(a, b, c); }
+
+///////////////////////////// XOP /////////////////////////////
+
+// [todo] define CV_XOP
+#if 1 // CV_XOP
+inline __m128i _v128_comgt_epu32(const __m128i& a, const __m128i& b)
+{
+    const __m128i delta = _mm_set1_epi32((int)0x80000000);
+    return _mm_cmpgt_epi32(_mm_xor_si128(a, delta), _mm_xor_si128(b, delta));
+}
+// wrapping XOP
+#else
+OPENCV_HAL_SSE_WRAP_2(_v128_comgt_epu32, __m128i)
+#endif // !CV_XOP
+
+///////////////////////////// SSE4.1 /////////////////////////////
+
+#if !CV_SSE4_1
+
+/** Swizzle **/
+inline __m128i _v128_blendv_epi8(const __m128i& a, const __m128i& b, const __m128i& mask)
+{ return _mm_xor_si128(a, _mm_and_si128(_mm_xor_si128(b, a), mask)); }
+
+/** Convert **/
+// 8 >> 16
+inline __m128i _v128_cvtepu8_epi16(const __m128i& a)
+{
+    const __m128i z = _mm_setzero_si128();
+    return _mm_unpacklo_epi8(a, z);
+}
+inline __m128i _v128_cvtepi8_epi16(const __m128i& a)
+{ return _mm_srai_epi16(_mm_unpacklo_epi8(a, a), 8); }
+// 8 >> 32
+inline __m128i _v128_cvtepu8_epi32(const __m128i& a)
+{
+    const __m128i z = _mm_setzero_si128();
+    return _mm_unpacklo_epi16(_mm_unpacklo_epi8(a, z), z);
+}
+inline __m128i _v128_cvtepi8_epi32(const __m128i& a)
+{
+    __m128i r = _mm_unpacklo_epi8(a, a);
+    r = _mm_unpacklo_epi8(r, r);
+    return _mm_srai_epi32(r, 24);
+}
+// 16 >> 32
+inline __m128i _v128_cvtepu16_epi32(const __m128i& a)
+{
+    const __m128i z = _mm_setzero_si128();
+    return _mm_unpacklo_epi16(a, z);
+}
+inline __m128i _v128_cvtepi16_epi32(const __m128i& a)
+{ return _mm_srai_epi32(_mm_unpacklo_epi16(a, a), 16); }
+// 32 >> 64
+inline __m128i _v128_cvtepu32_epi64(const __m128i& a)
+{
+    const __m128i z = _mm_setzero_si128();
+    return _mm_unpacklo_epi32(a, z);
+}
+inline __m128i _v128_cvtepi32_epi64(const __m128i& a)
+{ return _mm_unpacklo_epi32(a, _mm_srai_epi32(a, 31)); }
+
+/** Arithmetic **/
+inline __m128i _v128_mullo_epi32(const __m128i& a, const __m128i& b)
+{
+    __m128i c0 = _mm_mul_epu32(a, b);
+    __m128i c1 = _mm_mul_epu32(_mm_srli_epi64(a, 32), _mm_srli_epi64(b, 32));
+    __m128i d0 = _mm_unpacklo_epi32(c0, c1);
+    __m128i d1 = _mm_unpackhi_epi32(c0, c1);
+    return _mm_unpacklo_epi64(d0, d1);
+}
+
+/** Math **/
+inline __m128i _v128_min_epu32(const __m128i& a, const __m128i& b)
+{ return _v128_blendv_epi8(a, b, _v128_comgt_epu32(a, b)); }
+
+// wrapping SSE4.1
+#else
+OPENCV_HAL_SSE_WRAP_1(cvtepu8_epi16, __m128i)
+OPENCV_HAL_SSE_WRAP_1(cvtepi8_epi16, __m128i)
+OPENCV_HAL_SSE_WRAP_1(cvtepu8_epi32, __m128i)
+OPENCV_HAL_SSE_WRAP_1(cvtepi8_epi32, __m128i)
+OPENCV_HAL_SSE_WRAP_1(cvtepu16_epi32, __m128i)
+OPENCV_HAL_SSE_WRAP_1(cvtepi16_epi32, __m128i)
+OPENCV_HAL_SSE_WRAP_1(cvtepu32_epi64, __m128i)
+OPENCV_HAL_SSE_WRAP_1(cvtepi32_epi64, __m128i)
+OPENCV_HAL_SSE_WRAP_2(min_epu32, __m128i)
+OPENCV_HAL_SSE_WRAP_2(mullo_epi32, __m128i)
+OPENCV_HAL_SSE_WRAP_3(blendv_epi8, __m128i)
+#endif // !CV_SSE4_1
+
+///////////////////////////// Revolutionary /////////////////////////////
+
+/** Convert **/
+// 16 << 8
+inline __m128i _v128_cvtepu8_epi16_high(const __m128i& a)
+{
+    const __m128i z = _mm_setzero_si128();
+    return _mm_unpackhi_epi8(a, z);
+}
+inline __m128i _v128_cvtepi8_epi16_high(const __m128i& a)
+{ return _mm_srai_epi16(_mm_unpackhi_epi8(a, a), 8); }
+// 32 << 16
+inline __m128i _v128_cvtepu16_epi32_high(const __m128i& a)
+{
+    const __m128i z = _mm_setzero_si128();
+    return _mm_unpackhi_epi16(a, z);
+}
+inline __m128i _v128_cvtepi16_epi32_high(const __m128i& a)
+{ return _mm_srai_epi32(_mm_unpackhi_epi16(a, a), 16); }
+// 64 << 32
+inline __m128i _v128_cvtepu32_epi64_high(const __m128i& a)
+{
+    const __m128i z = _mm_setzero_si128();
+    return _mm_unpackhi_epi32(a, z);
+}
+inline __m128i _v128_cvtepi32_epi64_high(const __m128i& a)
+{ return _mm_unpackhi_epi32(a, _mm_srai_epi32(a, 31)); }
+
+/** Miscellaneous **/
+inline __m128i _v128_packs_epu32(const __m128i& a, const __m128i& b)
+{
+    const __m128i m = _mm_set1_epi32(65535);
+    __m128i am = _v128_min_epu32(a, m);
+    __m128i bm = _v128_min_epu32(b, m);
+#if CV_SSE4_1
+    return _mm_packus_epi32(am, bm);
+#else
+    const __m128i d = _mm_set1_epi32(32768), nd = _mm_set1_epi16(-32768);
+    am = _mm_sub_epi32(am, d);
+    bm = _mm_sub_epi32(bm, d);
+    am = _mm_packs_epi32(am, bm);
+    return _mm_sub_epi16(am, nd);
+#endif
+}
+
+template<int i>
+inline int64 _v128_extract_epi64(const __m128i& a)
+{
+#if defined(CV__SIMD_HAVE_mm_extract_epi64) || (CV_SSE4_1 && (defined(__x86_64__)/*GCC*/ || defined(_M_X64)/*MSVC*/))
+#define CV__SIMD_NATIVE_mm_extract_epi64 1
+    return _mm_extract_epi64(a, i);
+#else
+    CV_DECL_ALIGNED(16) int64 tmp[2];
+    _mm_store_si128((__m128i*)tmp, a);
+    return tmp[i];
+#endif
+}
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+} // cv::
+
+#endif // OPENCV_HAL_INTRIN_SSE_EM_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_vsx.hpp

@@ -0,0 +1,1619 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+#ifndef OPENCV_HAL_VSX_HPP
+#define OPENCV_HAL_VSX_HPP
+
+#include <algorithm>
+#include "opencv2/core/utility.hpp"
+
+#define CV_SIMD128 1
+#define CV_SIMD128_64F 1
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+///////// Types ////////////
+
+struct v_uint8x16
+{
+    typedef uchar lane_type;
+    enum { nlanes = 16 };
+    vec_uchar16 val;
+
+    explicit v_uint8x16(const vec_uchar16& v) : val(v)
+    {}
+    v_uint8x16()
+    {}
+    v_uint8x16(vec_bchar16 v) : val(vec_uchar16_c(v))
+    {}
+    v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
+               uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
+        : val(vec_uchar16_set(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15))
+    {}
+
+    static inline v_uint8x16 zero() { return v_uint8x16(vec_uchar16_z); }
+
+    uchar get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_int8x16
+{
+    typedef schar lane_type;
+    enum { nlanes = 16 };
+    vec_char16 val;
+
+    explicit v_int8x16(const vec_char16& v) : val(v)
+    {}
+    v_int8x16()
+    {}
+    v_int8x16(vec_bchar16 v) : val(vec_char16_c(v))
+    {}
+    v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
+              schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
+        : val(vec_char16_set(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15))
+    {}
+
+    static inline v_int8x16 zero() { return v_int8x16(vec_char16_z); }
+
+    schar get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_uint16x8
+{
+    typedef ushort lane_type;
+    enum { nlanes = 8 };
+    vec_ushort8 val;
+
+    explicit v_uint16x8(const vec_ushort8& v) : val(v)
+    {}
+    v_uint16x8()
+    {}
+    v_uint16x8(vec_bshort8 v) : val(vec_ushort8_c(v))
+    {}
+    v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
+        : val(vec_ushort8_set(v0, v1, v2, v3, v4, v5, v6, v7))
+    {}
+
+    static inline v_uint16x8 zero() { return v_uint16x8(vec_ushort8_z); }
+
+    ushort get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_int16x8
+{
+    typedef short lane_type;
+    enum { nlanes = 8 };
+    vec_short8 val;
+
+    explicit v_int16x8(const vec_short8& v) : val(v)
+    {}
+    v_int16x8()
+    {}
+    v_int16x8(vec_bshort8 v) : val(vec_short8_c(v))
+    {}
+    v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
+        : val(vec_short8_set(v0, v1, v2, v3, v4, v5, v6, v7))
+    {}
+
+    static inline v_int16x8 zero() { return v_int16x8(vec_short8_z); }
+
+    short get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_uint32x4
+{
+    typedef unsigned lane_type;
+    enum { nlanes = 4 };
+    vec_uint4 val;
+
+    explicit v_uint32x4(const vec_uint4& v) : val(v)
+    {}
+    v_uint32x4()
+    {}
+    v_uint32x4(vec_bint4 v) : val(vec_uint4_c(v))
+    {}
+    v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3) : val(vec_uint4_set(v0, v1, v2, v3))
+    {}
+
+    static inline v_uint32x4 zero() { return v_uint32x4(vec_uint4_z); }
+
+    uint get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_int32x4
+{
+    typedef int lane_type;
+    enum { nlanes = 4 };
+    vec_int4 val;
+
+    explicit v_int32x4(const vec_int4& v) : val(v)
+    {}
+    v_int32x4()
+    {}
+    v_int32x4(vec_bint4 v) : val(vec_int4_c(v))
+    {}
+    v_int32x4(int v0, int v1, int v2, int v3) : val(vec_int4_set(v0, v1, v2, v3))
+    {}
+
+    static inline v_int32x4 zero() { return v_int32x4(vec_int4_z); }
+
+    int get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_float32x4
+{
+    typedef float lane_type;
+    enum { nlanes = 4 };
+    vec_float4 val;
+
+    explicit v_float32x4(const vec_float4& v) : val(v)
+    {}
+    v_float32x4()
+    {}
+    v_float32x4(vec_bint4 v) : val(vec_float4_c(v))
+    {}
+    v_float32x4(float v0, float v1, float v2, float v3) : val(vec_float4_set(v0, v1, v2, v3))
+    {}
+
+    static inline v_float32x4 zero() { return v_float32x4(vec_float4_z); }
+
+    float get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_uint64x2
+{
+    typedef uint64 lane_type;
+    enum { nlanes = 2 };
+    vec_udword2 val;
+
+    explicit v_uint64x2(const vec_udword2& v) : val(v)
+    {}
+    v_uint64x2()
+    {}
+    v_uint64x2(vec_bdword2 v) : val(vec_udword2_c(v))
+    {}
+    v_uint64x2(uint64 v0, uint64 v1) : val(vec_udword2_set(v0, v1))
+    {}
+
+    static inline v_uint64x2 zero() { return v_uint64x2(vec_udword2_z); }
+
+    uint64 get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_int64x2
+{
+    typedef int64 lane_type;
+    enum { nlanes = 2 };
+    vec_dword2 val;
+
+    explicit v_int64x2(const vec_dword2& v) : val(v)
+    {}
+    v_int64x2()
+    {}
+    v_int64x2(vec_bdword2 v) : val(vec_dword2_c(v))
+    {}
+    v_int64x2(int64 v0, int64 v1) : val(vec_dword2_set(v0, v1))
+    {}
+
+    static inline v_int64x2 zero() { return v_int64x2(vec_dword2_z); }
+
+    int64 get0() const
+    { return vec_extract(val, 0); }
+};
+
+struct v_float64x2
+{
+    typedef double lane_type;
+    enum { nlanes = 2 };
+    vec_double2 val;
+
+    explicit v_float64x2(const vec_double2& v) : val(v)
+    {}
+    v_float64x2()
+    {}
+    v_float64x2(vec_bdword2 v) : val(vec_double2_c(v))
+    {}
+    v_float64x2(double v0, double v1) : val(vec_double2_set(v0, v1))
+    {}
+
+    static inline v_float64x2 zero() { return v_float64x2(vec_double2_z); }
+
+    double get0() const
+    { return vec_extract(val, 0); }
+};
+
+#define OPENCV_HAL_IMPL_VSX_EXTRACT_N(_Tpvec, _Tp) \
+template<int i> inline _Tp v_extract_n(VSX_UNUSED(_Tpvec v)) { return vec_extract(v.val, i); }
+
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_uint8x16, uchar)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_int8x16, schar)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_uint16x8, ushort)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_int16x8, short)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_uint32x4, uint)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_int32x4, int)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_uint64x2, uint64)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_int64x2, int64)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_float32x4, float)
+OPENCV_HAL_IMPL_VSX_EXTRACT_N(v_float64x2, double)
+
+//////////////// Load and store operations ///////////////
+
+/*
+ * clang-5 aborted during parse "vec_xxx_c" only if it's
+ * inside a function template which is defined by preprocessor macro.
+ *
+ * if vec_xxx_c defined as C++ cast, clang-5 will pass it
+*/
+#define OPENCV_HAL_IMPL_VSX_INITVEC(_Tpvec, _Tp, suffix, cast)                        \
+inline _Tpvec v_setzero_##suffix() { return _Tpvec(vec_splats((_Tp)0)); }             \
+inline _Tpvec v_setall_##suffix(_Tp v) { return _Tpvec(vec_splats((_Tp)v));}          \
+template <> inline _Tpvec v_setzero_() { return v_setzero_##suffix(); }               \
+template <> inline _Tpvec v_setall_(_Tp v) { return v_setall_##suffix(_Tp v); }       \
+template<typename _Tpvec0> inline _Tpvec v_reinterpret_as_##suffix(const _Tpvec0 &a)  \
+{ return _Tpvec((cast)a.val); }
+
+OPENCV_HAL_IMPL_VSX_INITVEC(v_uint8x16, uchar, u8, vec_uchar16)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_int8x16, schar, s8, vec_char16)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_uint16x8, ushort, u16, vec_ushort8)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_int16x8, short, s16, vec_short8)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_uint32x4, uint, u32, vec_uint4)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_int32x4, int, s32, vec_int4)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_uint64x2, uint64, u64, vec_udword2)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_int64x2, int64, s64, vec_dword2)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_float32x4, float, f32, vec_float4)
+OPENCV_HAL_IMPL_VSX_INITVEC(v_float64x2, double, f64, vec_double2)
+
+#define OPENCV_HAL_IMPL_VSX_LOADSTORE_C(_Tpvec, _Tp, ld, ld_a, st, st_a)    \
+inline _Tpvec v_load(const _Tp* ptr)                                        \
+{ return _Tpvec(ld(0, ptr)); }                                              \
+inline _Tpvec v_load_aligned(VSX_UNUSED(const _Tp* ptr))                    \
+{ return _Tpvec(ld_a(0, ptr)); }                                            \
+inline _Tpvec v_load_low(const _Tp* ptr)                                    \
+{ return _Tpvec(vec_ld_l8(ptr)); }                                          \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1)               \
+{ return _Tpvec(vec_mergesqh(vec_ld_l8(ptr0), vec_ld_l8(ptr1))); }          \
+inline void v_store(_Tp* ptr, const _Tpvec& a)                              \
+{ st(a.val, 0, ptr); }                                                      \
+inline void v_store_aligned(VSX_UNUSED(_Tp* ptr), const _Tpvec& a)          \
+{ st_a(a.val, 0, ptr); }                                                    \
+inline void v_store_aligned_nocache(VSX_UNUSED(_Tp* ptr), const _Tpvec& a)  \
+{ st_a(a.val, 0, ptr); }                                                    \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode mode)         \
+{ if(mode == hal::STORE_UNALIGNED) st(a.val, 0, ptr); else st_a(a.val, 0, ptr); } \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a)                          \
+{ vec_st_l8(a.val, ptr); }                                                  \
+inline void v_store_high(_Tp* ptr, const _Tpvec& a)                         \
+{ vec_st_h8(a.val, ptr); }
+
+// working around gcc bug for aligned ld/st
+// if runtime check for vec_ld/st fail we failback to unaligned ld/st
+// https://github.com/opencv/opencv/issues/13211
+#ifdef CV_COMPILER_VSX_BROKEN_ALIGNED
+    #define OPENCV_HAL_IMPL_VSX_LOADSTORE(_Tpvec, _Tp) \
+    OPENCV_HAL_IMPL_VSX_LOADSTORE_C(_Tpvec, _Tp, vsx_ld, vsx_ld, vsx_st, vsx_st)
+#else
+    #define OPENCV_HAL_IMPL_VSX_LOADSTORE(_Tpvec, _Tp) \
+    OPENCV_HAL_IMPL_VSX_LOADSTORE_C(_Tpvec, _Tp, vsx_ld, vec_ld, vsx_st, vec_st)
+#endif
+
+OPENCV_HAL_IMPL_VSX_LOADSTORE(v_uint8x16,  uchar)
+OPENCV_HAL_IMPL_VSX_LOADSTORE(v_int8x16,   schar)
+OPENCV_HAL_IMPL_VSX_LOADSTORE(v_uint16x8,  ushort)
+OPENCV_HAL_IMPL_VSX_LOADSTORE(v_int16x8,   short)
+OPENCV_HAL_IMPL_VSX_LOADSTORE(v_uint32x4,  uint)
+OPENCV_HAL_IMPL_VSX_LOADSTORE(v_int32x4,   int)
+OPENCV_HAL_IMPL_VSX_LOADSTORE(v_float32x4, float)
+
+OPENCV_HAL_IMPL_VSX_LOADSTORE_C(v_float64x2, double, vsx_ld,  vsx_ld,  vsx_st,  vsx_st)
+OPENCV_HAL_IMPL_VSX_LOADSTORE_C(v_uint64x2,  uint64, vsx_ld2, vsx_ld2, vsx_st2, vsx_st2)
+OPENCV_HAL_IMPL_VSX_LOADSTORE_C(v_int64x2,    int64, vsx_ld2, vsx_ld2, vsx_st2, vsx_st2)
+
+//////////////// Value reordering ///////////////
+
+/* de&interleave */
+#define OPENCV_HAL_IMPL_VSX_INTERLEAVE(_Tp, _Tpvec)                          \
+inline void v_load_deinterleave(const _Tp* ptr, _Tpvec& a, _Tpvec& b)        \
+{ vec_ld_deinterleave(ptr, a.val, b.val);}                                   \
+inline void v_load_deinterleave(const _Tp* ptr, _Tpvec& a,                   \
+                                _Tpvec& b, _Tpvec& c)                        \
+{ vec_ld_deinterleave(ptr, a.val, b.val, c.val); }                           \
+inline void v_load_deinterleave(const _Tp* ptr, _Tpvec& a, _Tpvec& b,        \
+                                                _Tpvec& c, _Tpvec& d)        \
+{ vec_ld_deinterleave(ptr, a.val, b.val, c.val, d.val); }                    \
+inline void v_store_interleave(_Tp* ptr, const _Tpvec& a, const _Tpvec& b,   \
+                               hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ vec_st_interleave(a.val, b.val, ptr); }                                    \
+inline void v_store_interleave(_Tp* ptr, const _Tpvec& a,                    \
+                               const _Tpvec& b, const _Tpvec& c,             \
+                               hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ vec_st_interleave(a.val, b.val, c.val, ptr); }                             \
+inline void v_store_interleave(_Tp* ptr, const _Tpvec& a, const _Tpvec& b,   \
+                                         const _Tpvec& c, const _Tpvec& d,   \
+                               hal::StoreMode /*mode*/=hal::STORE_UNALIGNED) \
+{ vec_st_interleave(a.val, b.val, c.val, d.val, ptr); }
+
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(uchar, v_uint8x16)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(schar, v_int8x16)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(ushort, v_uint16x8)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(short, v_int16x8)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(uint, v_uint32x4)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(int, v_int32x4)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(float, v_float32x4)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(double, v_float64x2)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(int64, v_int64x2)
+OPENCV_HAL_IMPL_VSX_INTERLEAVE(uint64, v_uint64x2)
+
+/* Expand */
+#define OPENCV_HAL_IMPL_VSX_EXPAND(_Tpvec, _Tpwvec, _Tp, fl, fh)  \
+inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1)   \
+{                                                                 \
+    b0.val = fh(a.val);                                           \
+    b1.val = fl(a.val);                                           \
+}                                                                 \
+inline _Tpwvec v_expand_low(const _Tpvec& a)                      \
+{ return _Tpwvec(fh(a.val)); }                                    \
+inline _Tpwvec v_expand_high(const _Tpvec& a)                     \
+{ return _Tpwvec(fl(a.val)); }                                    \
+inline _Tpwvec v_load_expand(const _Tp* ptr)                      \
+{ return _Tpwvec(fh(vec_ld_l8(ptr))); }
+
+OPENCV_HAL_IMPL_VSX_EXPAND(v_uint8x16, v_uint16x8, uchar, vec_unpacklu, vec_unpackhu)
+OPENCV_HAL_IMPL_VSX_EXPAND(v_int8x16, v_int16x8, schar, vec_unpackl, vec_unpackh)
+OPENCV_HAL_IMPL_VSX_EXPAND(v_uint16x8, v_uint32x4, ushort, vec_unpacklu, vec_unpackhu)
+OPENCV_HAL_IMPL_VSX_EXPAND(v_int16x8, v_int32x4, short, vec_unpackl, vec_unpackh)
+OPENCV_HAL_IMPL_VSX_EXPAND(v_uint32x4, v_uint64x2, uint, vec_unpacklu, vec_unpackhu)
+OPENCV_HAL_IMPL_VSX_EXPAND(v_int32x4, v_int64x2, int, vec_unpackl, vec_unpackh)
+
+/* Load and zero expand a 4 byte value into the second dword, first is don't care. */
+#if !defined(CV_COMPILER_VSX_BROKEN_ASM)
+    #define _LXSIWZX(out, ptr, T) __asm__ ("lxsiwzx %x0, 0, %1\r\n" : "=wa"(out) : "r" (ptr) : "memory");
+#else
+    /* This is compiler-agnostic, but will introduce an unneeded splat on the critical path. */
+    #define _LXSIWZX(out, ptr, T) out = (T)vec_udword2_sp(*(uint32_t*)(ptr));
+#endif
+
+inline v_uint32x4 v_load_expand_q(const uchar* ptr)
+{
+    // Zero-extend the extra 24B instead of unpacking. Usually faster in small kernel
+    // Likewise note, value is zero extended and upper 4 bytes are zero'ed.
+    vec_uchar16 pmu = {8, 12, 12, 12, 9, 12, 12, 12, 10, 12, 12, 12, 11, 12, 12, 12};
+    vec_uchar16 out;
+
+    _LXSIWZX(out, ptr, vec_uchar16);
+    out = vec_perm(out, out, pmu);
+    return v_uint32x4((vec_uint4)out);
+}
+
+inline v_int32x4 v_load_expand_q(const schar* ptr)
+{
+    vec_char16 out;
+    vec_short8 outs;
+    vec_int4 outw;
+
+    _LXSIWZX(out, ptr, vec_char16);
+    outs = vec_unpackl(out);
+    outw = vec_unpackh(outs);
+    return v_int32x4(outw);
+}
+
+/* pack */
+#define OPENCV_HAL_IMPL_VSX_PACK(_Tpvec, _Tp, _Tpwvec, _Tpvn, _Tpdel, sfnc, pkfnc, addfnc, pack)    \
+inline _Tpvec v_##pack(const _Tpwvec& a, const _Tpwvec& b)                                          \
+{                                                                                                   \
+    return _Tpvec(pkfnc(a.val, b.val));                                                             \
+}                                                                                                   \
+inline void v_##pack##_store(_Tp* ptr, const _Tpwvec& a)                                            \
+{                                                                                                   \
+    vec_st_l8(pkfnc(a.val, a.val), ptr);                                                            \
+}                                                                                                   \
+template<int n>                                                                                     \
+inline _Tpvec v_rshr_##pack(const _Tpwvec& a, const _Tpwvec& b)                                     \
+{                                                                                                   \
+    const __vector _Tpvn vn = vec_splats((_Tpvn)n);                                                 \
+    const __vector _Tpdel delta = vec_splats((_Tpdel)((_Tpdel)1 << (n-1)));                         \
+    return _Tpvec(pkfnc(sfnc(addfnc(a.val, delta), vn), sfnc(addfnc(b.val, delta), vn)));           \
+}                                                                                                   \
+template<int n>                                                                                     \
+inline void v_rshr_##pack##_store(_Tp* ptr, const _Tpwvec& a)                                       \
+{                                                                                                   \
+    const __vector _Tpvn vn = vec_splats((_Tpvn)n);                                                 \
+    const __vector _Tpdel delta = vec_splats((_Tpdel)((_Tpdel)1 << (n-1)));                         \
+    vec_st_l8(pkfnc(sfnc(addfnc(a.val, delta), vn), delta), ptr);                                   \
+}
+
+OPENCV_HAL_IMPL_VSX_PACK(v_uint8x16, uchar, v_uint16x8, unsigned short, unsigned short,
+                         vec_sr, vec_packs, vec_adds, pack)
+OPENCV_HAL_IMPL_VSX_PACK(v_int8x16, schar, v_int16x8, unsigned short, short,
+                         vec_sra, vec_packs, vec_adds, pack)
+
+OPENCV_HAL_IMPL_VSX_PACK(v_uint16x8, ushort, v_uint32x4, unsigned int, unsigned int,
+                         vec_sr, vec_packs, vec_add, pack)
+OPENCV_HAL_IMPL_VSX_PACK(v_int16x8, short, v_int32x4, unsigned int, int,
+                         vec_sra, vec_packs, vec_add, pack)
+
+OPENCV_HAL_IMPL_VSX_PACK(v_uint32x4, uint, v_uint64x2, unsigned long long, unsigned long long,
+                         vec_sr, vec_pack, vec_add, pack)
+OPENCV_HAL_IMPL_VSX_PACK(v_int32x4, int, v_int64x2, unsigned long long, long long,
+                         vec_sra, vec_pack, vec_add, pack)
+
+OPENCV_HAL_IMPL_VSX_PACK(v_uint8x16, uchar, v_int16x8, unsigned short, short,
+                         vec_sra, vec_packsu, vec_adds, pack_u)
+OPENCV_HAL_IMPL_VSX_PACK(v_uint16x8, ushort, v_int32x4, unsigned int, int,
+                         vec_sra, vec_packsu, vec_add, pack_u)
+// Following variant is not implemented on other platforms:
+//OPENCV_HAL_IMPL_VSX_PACK(v_uint32x4, uint, v_int64x2, unsigned long long, long long,
+//                         vec_sra, vec_packsu, vec_add, pack_u)
+
+// pack boolean
+inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b)
+{
+    vec_uchar16 ab = vec_pack(a.val, b.val);
+    return v_uint8x16(ab);
+}
+
+inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b,
+                           const v_uint32x4& c, const v_uint32x4& d)
+{
+    vec_ushort8 ab = vec_pack(a.val, b.val);
+    vec_ushort8 cd = vec_pack(c.val, d.val);
+    return v_uint8x16(vec_pack(ab, cd));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                           const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f,
+                           const v_uint64x2& g, const v_uint64x2& h)
+{
+    vec_uint4 ab = vec_pack(a.val, b.val);
+    vec_uint4 cd = vec_pack(c.val, d.val);
+    vec_uint4 ef = vec_pack(e.val, f.val);
+    vec_uint4 gh = vec_pack(g.val, h.val);
+
+    vec_ushort8 abcd = vec_pack(ab, cd);
+    vec_ushort8 efgh = vec_pack(ef, gh);
+    return v_uint8x16(vec_pack(abcd, efgh));
+}
+
+/* Recombine */
+template <typename _Tpvec>
+inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1)
+{
+    b0.val = vec_mergeh(a0.val, a1.val);
+    b1.val = vec_mergel(a0.val, a1.val);
+}
+
+template <typename _Tpvec>
+inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(vec_mergesql(a.val, b.val)); }
+
+template <typename _Tpvec>
+inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b)
+{ return _Tpvec(vec_mergesqh(a.val, b.val)); }
+
+template <typename _Tpvec>
+inline void v_recombine(const _Tpvec& a, const _Tpvec& b, _Tpvec& c, _Tpvec& d)
+{
+    c.val = vec_mergesqh(a.val, b.val);
+    d.val = vec_mergesql(a.val, b.val);
+}
+
+////////// Arithmetic, bitwise and comparison operations /////////
+
+/* Element-wise binary and unary operations */
+/** Arithmetics **/
+#define OPENCV_HAL_IMPL_VSX_BIN_OP(bin_op, _Tpvec, intrin)       \
+inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_uint8x16, vec_adds)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_uint8x16, vec_subs)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_int8x16,  vec_adds)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_int8x16, vec_subs)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_uint16x8, vec_adds)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_uint16x8, vec_subs)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_int16x8, vec_adds)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_int16x8, vec_subs)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_uint32x4, vec_add)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_uint32x4, vec_sub)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_mul, v_uint32x4, vec_mul)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_int32x4, vec_add)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_int32x4, vec_sub)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_mul, v_int32x4, vec_mul)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_float32x4, vec_add)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_float32x4, vec_sub)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_mul, v_float32x4, vec_mul)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_div, v_float32x4, vec_div)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_float64x2, vec_add)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_float64x2, vec_sub)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_mul, v_float64x2, vec_mul)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_div, v_float64x2, vec_div)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_uint64x2, vec_add)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_uint64x2, vec_sub)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_add, v_int64x2, vec_add)
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_sub, v_int64x2, vec_sub)
+
+// saturating multiply
+#define OPENCV_HAL_IMPL_VSX_MUL_SAT(_Tpvec, _Tpwvec)             \
+    inline _Tpvec v_mul(const _Tpvec& a, const _Tpvec& b)        \
+    {                                                            \
+        _Tpwvec c, d;                                            \
+        v_mul_expand(a, b, c, d);                                \
+        return v_pack(c, d);                                     \
+    }
+
+OPENCV_HAL_IMPL_VSX_MUL_SAT(v_int8x16,  v_int16x8)
+OPENCV_HAL_IMPL_VSX_MUL_SAT(v_uint8x16, v_uint16x8)
+OPENCV_HAL_IMPL_VSX_MUL_SAT(v_int16x8,  v_int32x4)
+OPENCV_HAL_IMPL_VSX_MUL_SAT(v_uint16x8, v_uint32x4)
+
+template<typename Tvec, typename Twvec>
+inline void v_mul_expand(const Tvec& a, const Tvec& b, Twvec& c, Twvec& d)
+{
+    Twvec p0 = Twvec(vec_mule(a.val, b.val));
+    Twvec p1 = Twvec(vec_mulo(a.val, b.val));
+    v_zip(p0, p1, c, d);
+}
+
+inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b)
+{
+    vec_int4 p0 = vec_mule(a.val, b.val);
+    vec_int4 p1 = vec_mulo(a.val, b.val);
+    static const vec_uchar16 perm = {2, 3, 18, 19, 6, 7, 22, 23, 10, 11, 26, 27, 14, 15, 30, 31};
+    return v_int16x8(vec_perm(vec_short8_c(p0), vec_short8_c(p1), perm));
+}
+inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b)
+{
+    vec_uint4 p0 = vec_mule(a.val, b.val);
+    vec_uint4 p1 = vec_mulo(a.val, b.val);
+    static const vec_uchar16 perm = {2, 3, 18, 19, 6, 7, 22, 23, 10, 11, 26, 27, 14, 15, 30, 31};
+    return v_uint16x8(vec_perm(vec_ushort8_c(p0), vec_ushort8_c(p1), perm));
+}
+
+/** Non-saturating arithmetics **/
+#define OPENCV_HAL_IMPL_VSX_BIN_FUNC(func, intrin)    \
+template<typename _Tpvec>                             \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b)  \
+{ return _Tpvec(intrin(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_add_wrap, vec_add)
+OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_sub_wrap, vec_sub)
+OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_mul_wrap, vec_mul)
+
+/** Bitwise shifts **/
+#define OPENCV_HAL_IMPL_VSX_SHIFT_OP(_Tpvec, shr, splfunc)   \
+inline _Tpvec v_shl(const _Tpvec& a, int imm)                \
+{ return _Tpvec(vec_sl(a.val, splfunc(imm))); }              \
+inline _Tpvec v_shr(const _Tpvec& a, int imm)                \
+{ return _Tpvec(shr(a.val, splfunc(imm))); }                 \
+template<int imm> inline _Tpvec v_shl(const _Tpvec& a)       \
+{ return _Tpvec(vec_sl(a.val, splfunc(imm))); }              \
+template<int imm> inline _Tpvec v_shr(const _Tpvec& a)       \
+{ return _Tpvec(shr(a.val, splfunc(imm))); }
+
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint8x16, vec_sr, vec_uchar16_sp)
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint16x8, vec_sr, vec_ushort8_sp)
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint32x4, vec_sr, vec_uint4_sp)
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_uint64x2, vec_sr, vec_udword2_sp)
+// algebraic right shift
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int8x16, vec_sra, vec_uchar16_sp)
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int16x8, vec_sra, vec_ushort8_sp)
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int32x4, vec_sra, vec_uint4_sp)
+OPENCV_HAL_IMPL_VSX_SHIFT_OP(v_int64x2, vec_sra, vec_udword2_sp)
+
+/** Bitwise logic **/
+#define OPENCV_HAL_IMPL_VSX_LOGIC_OP(_Tpvec)    \
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_and, _Tpvec, vec_and)  \
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_or, _Tpvec, vec_or)    \
+OPENCV_HAL_IMPL_VSX_BIN_OP(v_xor, _Tpvec, vec_xor)  \
+inline _Tpvec v_not(const _Tpvec& a)                \
+{ return _Tpvec(vec_not(a.val)); }
+
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint8x16)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int8x16)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint16x8)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int16x8)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint32x4)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int32x4)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_uint64x2)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_int64x2)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_float32x4)
+OPENCV_HAL_IMPL_VSX_LOGIC_OP(v_float64x2)
+
+/** Bitwise select **/
+#define OPENCV_HAL_IMPL_VSX_SELECT(_Tpvec, cast)                             \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(vec_sel(b.val, a.val, cast(mask.val))); }
+
+OPENCV_HAL_IMPL_VSX_SELECT(v_uint8x16, vec_bchar16_c)
+OPENCV_HAL_IMPL_VSX_SELECT(v_int8x16, vec_bchar16_c)
+OPENCV_HAL_IMPL_VSX_SELECT(v_uint16x8, vec_bshort8_c)
+OPENCV_HAL_IMPL_VSX_SELECT(v_int16x8, vec_bshort8_c)
+OPENCV_HAL_IMPL_VSX_SELECT(v_uint32x4, vec_bint4_c)
+OPENCV_HAL_IMPL_VSX_SELECT(v_int32x4, vec_bint4_c)
+OPENCV_HAL_IMPL_VSX_SELECT(v_float32x4, vec_bint4_c)
+OPENCV_HAL_IMPL_VSX_SELECT(v_float64x2, vec_bdword2_c)
+
+/** Comparison **/
+#define OPENCV_HAL_IMPL_VSX_INT_CMP_OP(_Tpvec)                 \
+inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b)           \
+{ return _Tpvec(vec_cmpeq(a.val, b.val)); }                    \
+inline _Tpvec V_ne(const _Tpvec& a, const _Tpvec& b)           \
+{ return _Tpvec(vec_cmpne(a.val, b.val)); }                    \
+inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b)           \
+{ return _Tpvec(vec_cmplt(a.val, b.val)); }                    \
+inline _Tpvec V_gt(const _Tpvec& a, const _Tpvec& b)           \
+{ return _Tpvec(vec_cmpgt(a.val, b.val)); }                    \
+inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b)           \
+{ return _Tpvec(vec_cmple(a.val, b.val)); }                    \
+inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b)           \
+{ return _Tpvec(vec_cmpge(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint8x16)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int8x16)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint16x8)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int16x8)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint32x4)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int32x4)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_float32x4)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_float64x2)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint64x2)
+OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int64x2)
+
+inline v_float32x4 v_not_nan(const v_float32x4& a)
+{ return v_float32x4(vec_cmpeq(a.val, a.val)); }
+inline v_float64x2 v_not_nan(const v_float64x2& a)
+{ return v_float64x2(vec_cmpeq(a.val, a.val)); }
+
+/** min/max **/
+OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_min, vec_min)
+OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_max, vec_max)
+
+/** Rotate **/
+#define OPENCV_IMPL_VSX_ROTATE(_Tpvec, suffix, shf, cast)                       \
+template<int imm>                                                               \
+inline _Tpvec v_rotate_##suffix(const _Tpvec& a)                                \
+{                                                                               \
+    const int wd = imm * sizeof(typename _Tpvec::lane_type);                    \
+    if (wd > 15)                                                                \
+        return _Tpvec::zero();                                                  \
+    return _Tpvec((cast)shf(vec_uchar16_c(a.val), vec_uchar16_sp(wd << 3)));    \
+}
+
+#define OPENCV_IMPL_VSX_ROTATE_LR(_Tpvec, cast)     \
+OPENCV_IMPL_VSX_ROTATE(_Tpvec, left, vec_slo, cast) \
+OPENCV_IMPL_VSX_ROTATE(_Tpvec, right, vec_sro, cast)
+
+OPENCV_IMPL_VSX_ROTATE_LR(v_uint8x16, vec_uchar16)
+OPENCV_IMPL_VSX_ROTATE_LR(v_int8x16,  vec_char16)
+OPENCV_IMPL_VSX_ROTATE_LR(v_uint16x8, vec_ushort8)
+OPENCV_IMPL_VSX_ROTATE_LR(v_int16x8,  vec_short8)
+OPENCV_IMPL_VSX_ROTATE_LR(v_uint32x4, vec_uint4)
+OPENCV_IMPL_VSX_ROTATE_LR(v_int32x4,  vec_int4)
+OPENCV_IMPL_VSX_ROTATE_LR(v_float32x4, vec_float4)
+OPENCV_IMPL_VSX_ROTATE_LR(v_uint64x2, vec_udword2)
+OPENCV_IMPL_VSX_ROTATE_LR(v_int64x2,  vec_dword2)
+OPENCV_IMPL_VSX_ROTATE_LR(v_float64x2, vec_double2)
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_right(const _Tpvec& a, const _Tpvec& b)
+{
+    enum { CV_SHIFT = 16 - imm * (sizeof(typename _Tpvec::lane_type)) };
+    if (CV_SHIFT == 16)
+        return a;
+#ifdef __IBMCPP__
+    return _Tpvec(vec_sld(b.val, a.val, CV_SHIFT & 15));
+#else
+    return _Tpvec(vec_sld(b.val, a.val, CV_SHIFT));
+#endif
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_left(const _Tpvec& a, const _Tpvec& b)
+{
+    enum { CV_SHIFT = imm * (sizeof(typename _Tpvec::lane_type)) };
+    if (CV_SHIFT == 16)
+        return b;
+    return _Tpvec(vec_sld(a.val, b.val, CV_SHIFT));
+}
+
+#define OPENCV_IMPL_VSX_ROTATE_64_2RG(_Tpvec, suffix, rg1, rg2)   \
+template<int imm>                                                 \
+inline _Tpvec v_rotate_##suffix(const _Tpvec& a, const _Tpvec& b) \
+{                                                                 \
+    if (imm == 1)                                                 \
+        return _Tpvec(vec_permi(rg1.val, rg2.val, 2));            \
+    return imm ? b : a;                                           \
+}
+
+#define OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(_Tpvec)    \
+OPENCV_IMPL_VSX_ROTATE_64_2RG(_Tpvec, left,  b, a)  \
+OPENCV_IMPL_VSX_ROTATE_64_2RG(_Tpvec, right, a, b)
+
+OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(v_float64x2)
+OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(v_uint64x2)
+OPENCV_IMPL_VSX_ROTATE_64_2RG_LR(v_int64x2)
+
+/* Reverse */
+inline v_uint8x16 v_reverse(const v_uint8x16 &a)
+{
+    static const vec_uchar16 perm = {15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0};
+    vec_uchar16 vec = (vec_uchar16)a.val;
+    return v_uint8x16(vec_perm(vec, vec, perm));
+}
+
+inline v_int8x16 v_reverse(const v_int8x16 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x8 v_reverse(const v_uint16x8 &a)
+{
+    static const vec_uchar16 perm = {14, 15, 12, 13, 10, 11, 8, 9, 6, 7, 4, 5, 2, 3, 0, 1};
+    vec_uchar16 vec = (vec_uchar16)a.val;
+    return v_reinterpret_as_u16(v_uint8x16(vec_perm(vec, vec, perm)));
+}
+
+inline v_int16x8 v_reverse(const v_int16x8 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x4 v_reverse(const v_uint32x4 &a)
+{
+    static const vec_uchar16 perm = {12, 13, 14, 15, 8, 9, 10, 11, 4, 5, 6, 7, 0, 1, 2, 3};
+    vec_uchar16 vec = (vec_uchar16)a.val;
+    return v_reinterpret_as_u32(v_uint8x16(vec_perm(vec, vec, perm)));
+}
+
+inline v_int32x4 v_reverse(const v_int32x4 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x4 v_reverse(const v_float32x4 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x2 v_reverse(const v_uint64x2 &a)
+{
+    static const vec_uchar16 perm = {8, 9, 10, 11, 12, 13, 14, 15, 0, 1, 2, 3, 4, 5, 6, 7};
+    vec_uchar16 vec = (vec_uchar16)a.val;
+    return v_reinterpret_as_u64(v_uint8x16(vec_perm(vec, vec, perm)));
+}
+
+inline v_int64x2 v_reverse(const v_int64x2 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+inline v_float64x2 v_reverse(const v_float64x2 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+/* Extract */
+template<int s, typename _Tpvec>
+inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b)
+{ return v_rotate_right<s>(a, b); }
+
+////////// Reduce and mask /////////
+
+/** Reduce **/
+inline uint v_reduce_sum(const v_uint8x16& a)
+{
+    const vec_uint4 zero4 = vec_uint4_z;
+    vec_uint4 sum4 = vec_sum4s(a.val, zero4);
+    return (uint)vec_extract(vec_sums(vec_int4_c(sum4), vec_int4_c(zero4)), 3);
+}
+inline int v_reduce_sum(const v_int8x16& a)
+{
+    const vec_int4 zero4 = vec_int4_z;
+    vec_int4 sum4 = vec_sum4s(a.val, zero4);
+    return (int)vec_extract(vec_sums(sum4, zero4), 3);
+}
+inline int v_reduce_sum(const v_int16x8& a)
+{
+    const vec_int4 zero = vec_int4_z;
+    return saturate_cast<int>(vec_extract(vec_sums(vec_sum4s(a.val, zero), zero), 3));
+}
+inline uint v_reduce_sum(const v_uint16x8& a)
+{
+    const vec_int4 v4 = vec_int4_c(vec_unpackhu(vec_adds(a.val, vec_sld(a.val, a.val, 8))));
+    return saturate_cast<uint>(vec_extract(vec_sums(v4, vec_int4_z), 3));
+}
+
+#define OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(_Tpvec, _Tpvec2, scalartype, suffix, func) \
+inline scalartype v_reduce_##suffix(const _Tpvec& a)                               \
+{                                                                                  \
+    const _Tpvec2 rs = func(a.val, vec_sld(a.val, a.val, 8));                      \
+    return vec_extract(func(rs, vec_sld(rs, rs, 4)), 0);                           \
+}
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_uint32x4, vec_uint4, uint, sum, vec_add)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_uint32x4, vec_uint4, uint, max, vec_max)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_uint32x4, vec_uint4, uint, min, vec_min)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_int32x4, vec_int4, int, sum, vec_add)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_int32x4, vec_int4, int, max, vec_max)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_int32x4, vec_int4, int, min, vec_min)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_float32x4, vec_float4, float, sum, vec_add)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_float32x4, vec_float4, float, max, vec_max)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_4(v_float32x4, vec_float4, float, min, vec_min)
+
+inline uint64 v_reduce_sum(const v_uint64x2& a)
+{
+    return vec_extract(vec_add(a.val, vec_permi(a.val, a.val, 3)), 0);
+}
+inline int64 v_reduce_sum(const v_int64x2& a)
+{
+    return vec_extract(vec_add(a.val, vec_permi(a.val, a.val, 3)), 0);
+}
+inline double v_reduce_sum(const v_float64x2& a)
+{
+    return vec_extract(vec_add(a.val, vec_permi(a.val, a.val, 3)), 0);
+}
+
+#define OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(_Tpvec, _Tpvec2, scalartype, suffix, func) \
+inline scalartype v_reduce_##suffix(const _Tpvec& a)                               \
+{                                                                                  \
+    _Tpvec2 rs = func(a.val, vec_sld(a.val, a.val, 8));                            \
+    rs = func(rs, vec_sld(rs, rs, 4));                                             \
+    return vec_extract(func(rs, vec_sld(rs, rs, 2)), 0);                           \
+}
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_uint16x8, vec_ushort8, ushort, max, vec_max)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_uint16x8, vec_ushort8, ushort, min, vec_min)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_int16x8, vec_short8, short, max, vec_max)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_8(v_int16x8, vec_short8, short, min, vec_min)
+
+#define OPENCV_HAL_IMPL_VSX_REDUCE_OP_16(_Tpvec, _Tpvec2, scalartype, suffix, func) \
+inline scalartype v_reduce_##suffix(const _Tpvec& a)                               \
+{                                                                                  \
+    _Tpvec2 rs = func(a.val, vec_sld(a.val, a.val, 8));                            \
+    rs = func(rs, vec_sld(rs, rs, 4));                                             \
+    rs = func(rs, vec_sld(rs, rs, 2));                                             \
+    return vec_extract(func(rs, vec_sld(rs, rs, 1)), 0);                           \
+}
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_16(v_uint8x16, vec_uchar16, uchar, max, vec_max)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_16(v_uint8x16, vec_uchar16, uchar, min, vec_min)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_16(v_int8x16, vec_char16, schar, max, vec_max)
+OPENCV_HAL_IMPL_VSX_REDUCE_OP_16(v_int8x16, vec_char16, schar, min, vec_min)
+
+inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b,
+                                 const v_float32x4& c, const v_float32x4& d)
+{
+    vec_float4 ac = vec_add(vec_mergel(a.val, c.val), vec_mergeh(a.val, c.val));
+    ac = vec_add(ac, vec_sld(ac, ac, 8));
+
+    vec_float4 bd = vec_add(vec_mergel(b.val, d.val), vec_mergeh(b.val, d.val));
+    bd = vec_add(bd, vec_sld(bd, bd, 8));
+    return v_float32x4(vec_mergeh(ac, bd));
+}
+
+inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b)
+{
+    const vec_uint4 zero4 = vec_uint4_z;
+    vec_uint4 sum4 = vec_sum4s(vec_absd(a.val, b.val), zero4);
+    return (unsigned)vec_extract(vec_sums(vec_int4_c(sum4), vec_int4_c(zero4)), 3);
+}
+inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b)
+{
+    const vec_int4 zero4 = vec_int4_z;
+    vec_char16 ad = vec_abss(vec_subs(a.val, b.val));
+    vec_int4 sum4 = vec_sum4s(ad, zero4);
+    return (unsigned)vec_extract(vec_sums(sum4, zero4), 3);
+}
+inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b)
+{
+    vec_ushort8 ad = vec_absd(a.val, b.val);
+    VSX_UNUSED(vec_int4) sum = vec_sums(vec_int4_c(vec_unpackhu(ad)) + vec_int4_c(vec_unpacklu(ad)), vec_int4_z);
+    return (unsigned)vec_extract(sum, 3);
+}
+inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b)
+{
+    const vec_int4 zero4 = vec_int4_z;
+    vec_short8 ad = vec_abss(vec_subs(a.val, b.val));
+    vec_int4 sum4 = vec_sum4s(ad, zero4);
+    return (unsigned)vec_extract(vec_sums(sum4, zero4), 3);
+}
+inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b)
+{
+    const vec_uint4 ad = vec_absd(a.val, b.val);
+    const vec_uint4 rd = vec_add(ad, vec_sld(ad, ad, 8));
+    return vec_extract(vec_add(rd, vec_sld(rd, rd, 4)), 0);
+}
+inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b)
+{
+    vec_int4 ad = vec_abss(vec_sub(a.val, b.val));
+    return (unsigned)vec_extract(vec_sums(ad, vec_int4_z), 3);
+}
+inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b)
+{
+    const vec_float4 ad = vec_abs(vec_sub(a.val, b.val));
+    const vec_float4 rd = vec_add(ad, vec_sld(ad, ad, 8));
+    return vec_extract(vec_add(rd, vec_sld(rd, rd, 4)), 0);
+}
+
+/** Popcount **/
+inline v_uint8x16 v_popcount(const v_uint8x16& a)
+{ return v_uint8x16(vec_popcntu(a.val)); }
+inline v_uint8x16 v_popcount(const v_int8x16& a)
+{ return v_uint8x16(vec_popcntu(a.val)); }
+inline v_uint16x8 v_popcount(const v_uint16x8& a)
+{ return v_uint16x8(vec_popcntu(a.val)); }
+inline v_uint16x8 v_popcount(const v_int16x8& a)
+{ return v_uint16x8(vec_popcntu(a.val)); }
+inline v_uint32x4 v_popcount(const v_uint32x4& a)
+{ return v_uint32x4(vec_popcntu(a.val)); }
+inline v_uint32x4 v_popcount(const v_int32x4& a)
+{ return v_uint32x4(vec_popcntu(a.val)); }
+inline v_uint64x2 v_popcount(const v_uint64x2& a)
+{ return v_uint64x2(vec_popcntu(a.val)); }
+inline v_uint64x2 v_popcount(const v_int64x2& a)
+{ return v_uint64x2(vec_popcntu(a.val)); }
+
+/** Mask **/
+inline int v_signmask(const v_uint8x16& a)
+{
+    static const vec_uchar16 qperm = {120, 112, 104, 96, 88, 80, 72, 64, 56, 48, 40, 32, 24, 16, 8, 0};
+    return vec_extract((vec_int4)vec_vbpermq(v_reinterpret_as_u8(a).val, qperm), 2);
+}
+inline int v_signmask(const v_int8x16& a)
+{ return v_signmask(v_reinterpret_as_u8(a)); }
+
+inline int v_signmask(const v_int16x8& a)
+{
+    static const vec_uchar16 qperm = {112, 96, 80, 64, 48, 32, 16, 0, 128, 128, 128, 128, 128, 128, 128, 128};
+    return vec_extract((vec_int4)vec_vbpermq(v_reinterpret_as_u8(a).val, qperm), 2);
+}
+inline int v_signmask(const v_uint16x8& a)
+{ return v_signmask(v_reinterpret_as_s16(a)); }
+
+inline int v_signmask(const v_int32x4& a)
+{
+    static const vec_uchar16 qperm = {96, 64, 32, 0, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128};
+    return vec_extract((vec_int4)vec_vbpermq(v_reinterpret_as_u8(a).val, qperm), 2);
+}
+inline int v_signmask(const v_uint32x4& a)
+{ return v_signmask(v_reinterpret_as_s32(a)); }
+inline int v_signmask(const v_float32x4& a)
+{ return v_signmask(v_reinterpret_as_s32(a)); }
+
+inline int v_signmask(const v_int64x2& a)
+{
+    VSX_UNUSED(const vec_dword2) sv = vec_sr(a.val, vec_udword2_sp(63));
+    return (int)vec_extract(sv, 0) | (int)vec_extract(sv, 1) << 1;
+}
+inline int v_signmask(const v_uint64x2& a)
+{ return v_signmask(v_reinterpret_as_s64(a)); }
+inline int v_signmask(const v_float64x2& a)
+{ return v_signmask(v_reinterpret_as_s64(a)); }
+
+inline int v_scan_forward(const v_int8x16& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint8x16& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int16x8& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint16x8& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_float32x4& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_int64x2& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_uint64x2& a) { return trailingZeros32(v_signmask(a)); }
+inline int v_scan_forward(const v_float64x2& a) { return trailingZeros32(v_signmask(a)); }
+
+template<typename _Tpvec>
+inline bool v_check_all(const _Tpvec& a)
+{ return vec_all_lt(a.val, _Tpvec::zero().val); }
+inline bool v_check_all(const v_uint8x16& a)
+{ return v_check_all(v_reinterpret_as_s8(a)); }
+inline bool v_check_all(const v_uint16x8& a)
+{ return v_check_all(v_reinterpret_as_s16(a)); }
+inline bool v_check_all(const v_uint32x4& a)
+{ return v_check_all(v_reinterpret_as_s32(a)); }
+inline bool v_check_all(const v_uint64x2& a)
+{ return v_check_all(v_reinterpret_as_s64(a)); }
+inline bool v_check_all(const v_float32x4& a)
+{ return v_check_all(v_reinterpret_as_s32(a)); }
+inline bool v_check_all(const v_float64x2& a)
+{ return v_check_all(v_reinterpret_as_s64(a)); }
+
+template<typename _Tpvec>
+inline bool v_check_any(const _Tpvec& a)
+{ return vec_any_lt(a.val, _Tpvec::zero().val); }
+inline bool v_check_any(const v_uint8x16& a)
+{ return v_check_any(v_reinterpret_as_s8(a)); }
+inline bool v_check_any(const v_uint16x8& a)
+{ return v_check_any(v_reinterpret_as_s16(a)); }
+inline bool v_check_any(const v_uint32x4& a)
+{ return v_check_any(v_reinterpret_as_s32(a)); }
+inline bool v_check_any(const v_uint64x2& a)
+{ return v_check_any(v_reinterpret_as_s64(a)); }
+inline bool v_check_any(const v_float32x4& a)
+{ return v_check_any(v_reinterpret_as_s32(a)); }
+inline bool v_check_any(const v_float64x2& a)
+{ return v_check_any(v_reinterpret_as_s64(a)); }
+
+////////// Other math /////////
+
+/** Some frequent operations **/
+inline v_float32x4 v_sqrt(const v_float32x4& x)
+{ return v_float32x4(vec_sqrt(x.val)); }
+inline v_float64x2 v_sqrt(const v_float64x2& x)
+{ return v_float64x2(vec_sqrt(x.val)); }
+
+inline v_float32x4 v_invsqrt(const v_float32x4& x)
+{ return v_float32x4(vec_rsqrt(x.val)); }
+inline v_float64x2 v_invsqrt(const v_float64x2& x)
+{ return v_float64x2(vec_rsqrt(x.val)); }
+
+#define OPENCV_HAL_IMPL_VSX_MULADD(_Tpvec)                                  \
+inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b)                 \
+{ return _Tpvec(vec_sqrt(vec_madd(a.val, a.val, vec_mul(b.val, b.val)))); } \
+inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b)             \
+{ return _Tpvec(vec_madd(a.val, a.val, vec_mul(b.val, b.val))); }           \
+inline _Tpvec v_fma(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)      \
+{ return _Tpvec(vec_madd(a.val, b.val, c.val)); }                           \
+inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c)   \
+{ return _Tpvec(vec_madd(a.val, b.val, c.val)); }
+
+OPENCV_HAL_IMPL_VSX_MULADD(v_float32x4)
+OPENCV_HAL_IMPL_VSX_MULADD(v_float64x2)
+
+inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{ return v_add(v_mul(a,  b), c); }
+
+// TODO: exp, log, sin, cos
+
+/** Absolute values **/
+inline v_uint8x16 v_abs(const v_int8x16& x)
+{ return v_uint8x16(vec_uchar16_c(vec_abs(x.val))); }
+
+inline v_uint16x8 v_abs(const v_int16x8& x)
+{ return v_uint16x8(vec_ushort8_c(vec_abs(x.val))); }
+
+inline v_uint32x4 v_abs(const v_int32x4& x)
+{ return v_uint32x4(vec_uint4_c(vec_abs(x.val))); }
+
+inline v_float32x4 v_abs(const v_float32x4& x)
+{ return v_float32x4(vec_abs(x.val)); }
+
+inline v_float64x2 v_abs(const v_float64x2& x)
+{ return v_float64x2(vec_abs(x.val)); }
+
+/** Absolute difference **/
+// unsigned
+OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_absdiff, vec_absd)
+
+inline v_uint8x16 v_absdiff(const v_int8x16& a, const v_int8x16& b)
+{ return v_reinterpret_as_u8(v_sub_wrap(v_max(a, b), v_min(a, b))); }
+inline v_uint16x8 v_absdiff(const v_int16x8& a, const v_int16x8& b)
+{ return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b))); }
+inline v_uint32x4 v_absdiff(const v_int32x4& a, const v_int32x4& b)
+{ return v_reinterpret_as_u32(v_sub(v_max(a, b), v_min(a, b))); }
+
+inline v_float32x4 v_absdiff(const v_float32x4& a, const v_float32x4& b)
+{ return v_abs(v_sub(a, b)); }
+inline v_float64x2 v_absdiff(const v_float64x2& a, const v_float64x2& b)
+{ return v_abs(v_sub(a, b)); }
+
+/** Absolute difference for signed integers **/
+inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b)
+{ return v_int8x16(vec_abss(vec_subs(a.val, b.val))); }
+inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b)
+{ return v_int16x8(vec_abss(vec_subs(a.val, b.val))); }
+
+////////// Conversions /////////
+
+/** Rounding **/
+inline v_int32x4 v_round(const v_float32x4& a)
+{ return v_int32x4(vec_cts(vec_rint(a.val))); }
+
+inline v_int32x4 v_round(const v_float64x2& a)
+{ return v_int32x4(vec_mergesqo(vec_ctso(vec_rint(a.val)), vec_int4_z)); }
+
+inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b)
+{ return v_int32x4(vec_mergesqo(vec_ctso(vec_rint(a.val)), vec_ctso(vec_rint(b.val)))); }
+
+inline v_int32x4 v_floor(const v_float32x4& a)
+{ return v_int32x4(vec_cts(vec_floor(a.val))); }
+
+inline v_int32x4 v_floor(const v_float64x2& a)
+{ return v_int32x4(vec_mergesqo(vec_ctso(vec_floor(a.val)), vec_int4_z)); }
+
+inline v_int32x4 v_ceil(const v_float32x4& a)
+{ return v_int32x4(vec_cts(vec_ceil(a.val))); }
+
+inline v_int32x4 v_ceil(const v_float64x2& a)
+{ return v_int32x4(vec_mergesqo(vec_ctso(vec_ceil(a.val)), vec_int4_z)); }
+
+inline v_int32x4 v_trunc(const v_float32x4& a)
+{ return v_int32x4(vec_cts(a.val)); }
+
+inline v_int32x4 v_trunc(const v_float64x2& a)
+{ return v_int32x4(vec_mergesqo(vec_ctso(a.val), vec_int4_z)); }
+
+/** To float **/
+inline v_float32x4 v_cvt_f32(const v_int32x4& a)
+{ return v_float32x4(vec_ctf(a.val)); }
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a)
+{ return v_float32x4(vec_mergesqo(vec_cvfo(a.val), vec_float4_z)); }
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b)
+{ return v_float32x4(vec_mergesqo(vec_cvfo(a.val), vec_cvfo(b.val))); }
+
+inline v_float64x2 v_cvt_f64(const v_int32x4& a)
+{ return v_float64x2(vec_ctdo(vec_mergeh(a.val, a.val))); }
+
+inline v_float64x2 v_cvt_f64_high(const v_int32x4& a)
+{ return v_float64x2(vec_ctdo(vec_mergel(a.val, a.val))); }
+
+inline v_float64x2 v_cvt_f64(const v_float32x4& a)
+{ return v_float64x2(vec_cvfo(vec_mergeh(a.val, a.val))); }
+
+inline v_float64x2 v_cvt_f64_high(const v_float32x4& a)
+{ return v_float64x2(vec_cvfo(vec_mergel(a.val, a.val))); }
+
+inline v_float64x2 v_cvt_f64(const v_int64x2& a)
+{ return v_float64x2(vec_ctd(a.val)); }
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x16 v_lut(const schar* tab, const int* idx)
+{
+    return v_int8x16(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]], tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]],
+                     tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]]);
+}
+inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx)
+{
+    return v_reinterpret_as_s8(v_int16x8(*(const short*)(tab+idx[0]), *(const short*)(tab+idx[1]), *(const short*)(tab+idx[2]), *(const short*)(tab+idx[3]),
+                                       *(const short*)(tab+idx[4]), *(const short*)(tab+idx[5]), *(const short*)(tab+idx[6]), *(const short*)(tab+idx[7])));
+}
+inline v_int8x16 v_lut_quads(const schar* tab, const int* idx)
+{
+    return v_reinterpret_as_s8(v_int32x4(*(const int*)(tab+idx[0]), *(const int*)(tab+idx[1]), *(const int*)(tab+idx[2]), *(const int*)(tab+idx[3])));
+}
+inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((const schar*)tab, idx)); }
+inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((const schar*)tab, idx)); }
+inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((const schar*)tab, idx)); }
+
+inline v_int16x8 v_lut(const short* tab, const int* idx)
+{
+    return v_int16x8(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]], tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]);
+}
+inline v_int16x8 v_lut_pairs(const short* tab, const int* idx)
+{
+    return v_reinterpret_as_s16(v_int32x4(*(const int*)(tab + idx[0]), *(const int*)(tab + idx[1]), *(const int*)(tab + idx[2]), *(const int*)(tab + idx[3])));
+}
+inline v_int16x8 v_lut_quads(const short* tab, const int* idx)
+{
+    return v_reinterpret_as_s16(v_int64x2(*(const int64*)(tab + idx[0]), *(const int64*)(tab + idx[1])));
+}
+inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((const short*)tab, idx)); }
+inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((const short*)tab, idx)); }
+inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((const short*)tab, idx)); }
+
+inline v_int32x4 v_lut(const int* tab, const int* idx)
+{
+    return v_int32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+inline v_int32x4 v_lut_pairs(const int* tab, const int* idx)
+{
+    return v_reinterpret_as_s32(v_int64x2(*(const int64*)(tab + idx[0]), *(const int64*)(tab + idx[1])));
+}
+inline v_int32x4 v_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x4(vsx_ld(0, tab + idx[0]));
+}
+inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((const int*)tab, idx)); }
+inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((const int*)tab, idx)); }
+inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((const int*)tab, idx)); }
+
+inline v_int64x2 v_lut(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(tab[idx[0]], tab[idx[1]]);
+}
+inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(vsx_ld2(0, tab + idx[0]));
+}
+inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); }
+inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); }
+
+inline v_float32x4 v_lut(const float* tab, const int* idx)
+{
+    return v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+inline v_float32x4 v_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_pairs((const int*)tab, idx)); }
+inline v_float32x4 v_lut_quads(const float* tab, const int* idx) { return v_load(tab + *idx); }
+
+inline v_float64x2 v_lut(const double* tab, const int* idx)
+{
+    return v_float64x2(tab[idx[0]], tab[idx[1]]);
+}
+inline v_float64x2 v_lut_pairs(const double* tab, const int* idx) { return v_load(tab + *idx); }
+
+inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec)
+{
+    const int idx[4] = {
+        vec_extract(idxvec.val, 0),
+        vec_extract(idxvec.val, 1),
+        vec_extract(idxvec.val, 2),
+        vec_extract(idxvec.val, 3)
+    };
+    return v_int32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec)
+{
+    const int idx[4] = {
+        vec_extract(idxvec.val, 0),
+        vec_extract(idxvec.val, 1),
+        vec_extract(idxvec.val, 2),
+        vec_extract(idxvec.val, 3)
+    };
+    return v_uint32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+
+inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec)
+{
+    const int idx[4] = {
+        vec_extract(idxvec.val, 0),
+        vec_extract(idxvec.val, 1),
+        vec_extract(idxvec.val, 2),
+        vec_extract(idxvec.val, 3)
+    };
+    return v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+
+inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec)
+{
+    const int idx[2] = {
+        vec_extract(idxvec.val, 0),
+        vec_extract(idxvec.val, 1)
+    };
+    return v_float64x2(tab[idx[0]], tab[idx[1]]);
+}
+
+inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y)
+{
+    vec_float4 xy0 = vec_ld_l8(tab + vec_extract(idxvec.val, 0));
+    vec_float4 xy1 = vec_ld_l8(tab + vec_extract(idxvec.val, 1));
+    vec_float4 xy2 = vec_ld_l8(tab + vec_extract(idxvec.val, 2));
+    vec_float4 xy3 = vec_ld_l8(tab + vec_extract(idxvec.val, 3));
+    vec_float4 xy02 = vec_mergeh(xy0, xy2); // x0, x2, y0, y2
+    vec_float4 xy13 = vec_mergeh(xy1, xy3); // x1, x3, y1, y3
+    x.val = vec_mergeh(xy02, xy13);
+    y.val = vec_mergel(xy02, xy13);
+}
+inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y)
+{
+    vec_double2 xy0 = vsx_ld(vec_extract(idxvec.val, 0), tab);
+    vec_double2 xy1 = vsx_ld(vec_extract(idxvec.val, 1), tab);
+    x.val = vec_mergeh(xy0, xy1);
+    y.val = vec_mergel(xy0, xy1);
+}
+
+inline v_int8x16 v_interleave_pairs(const v_int8x16& vec)
+{
+    static const vec_uchar16 perm = {0, 2, 1, 3, 4, 6, 5, 7, 8, 10, 9, 11, 12, 14, 13, 15};
+    return v_int8x16(vec_perm(vec.val, vec.val, perm));
+}
+inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec)
+{ return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+
+inline v_int8x16 v_interleave_quads(const v_int8x16& vec)
+{
+    static const vec_uchar16 perm = {0, 4, 1, 5, 2, 6, 3, 7, 8, 12, 9, 13, 10, 14, 11, 15};
+    return v_int8x16(vec_perm(vec.val, vec.val, perm));
+}
+inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec)
+{ return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_interleave_pairs(const v_int16x8& vec)
+{
+    static const vec_uchar16 perm = {0,1, 4,5, 2,3, 6,7, 8,9, 12,13, 10,11, 14,15};
+    return v_int16x8(vec_perm(vec.val, vec.val, perm));
+}
+inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec)
+{ return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+
+inline v_int16x8 v_interleave_quads(const v_int16x8& vec)
+{
+    static const vec_uchar16 perm = {0,1, 8,9, 2,3, 10,11, 4,5, 12,13, 6,7, 14,15};
+    return v_int16x8(vec_perm(vec.val, vec.val, perm));
+}
+inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec)
+{ return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_interleave_pairs(const v_int32x4& vec)
+{
+    static const vec_uchar16 perm = {0,1,2,3, 8,9,10,11, 4,5,6,7, 12,13,14,15};
+    return v_int32x4(vec_perm(vec.val, vec.val, perm));
+}
+inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec)
+{ return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x4 v_interleave_pairs(const v_float32x4& vec)
+{ return v_reinterpret_as_f32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+
+inline v_int8x16 v_pack_triplets(const v_int8x16& vec)
+{
+    static const vec_uchar16 perm = {0, 1, 2, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 15, 15, 15};
+    return v_int8x16(vec_perm(vec.val, vec.val, perm));
+}
+inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec)
+{ return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_pack_triplets(const v_int16x8& vec)
+{
+    static const vec_uchar16 perm = {0,1, 2,3, 4,5, 8,9, 10,11, 12,13, 14,15, 14,15};
+    return v_int16x8(vec_perm(vec.val, vec.val, perm));
+}
+inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec)
+{ return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_pack_triplets(const v_int32x4& vec)
+{ return vec; }
+inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec)
+{ return vec; }
+inline v_float32x4 v_pack_triplets(const v_float32x4& vec)
+{ return vec; }
+
+/////// FP16 support ////////
+
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+    vec_ushort8 vf16 = vec_ld_l8((const ushort*)ptr);
+#if CV_VSX3 && defined(vec_extract_fp_from_shorth)
+    return v_float32x4(vec_extract_fp_from_shorth(vf16));
+#elif CV_VSX3 && !defined(CV_COMPILER_VSX_BROKEN_ASM)
+    vec_float4 vf32;
+    __asm__ __volatile__ ("xvcvhpsp %x0,%x1" : "=wa" (vf32) : "wa" (vec_mergeh(vf16, vf16)));
+    return v_float32x4(vf32);
+#else
+    const vec_int4 z = vec_int4_z, delta = vec_int4_sp(0x38000000);
+    const vec_int4 signmask = vec_int4_sp(0x80000000);
+    const vec_int4 maxexp = vec_int4_sp(0x7c000000);
+    const vec_float4 deltaf = vec_float4_c(vec_int4_sp(0x38800000));
+
+    vec_int4 bits = vec_int4_c(vec_mergeh(vec_short8_c(z), vec_short8_c(vf16)));
+    vec_int4 e = vec_and(bits, maxexp), sign = vec_and(bits, signmask);
+    vec_int4 t = vec_add(vec_sr(vec_xor(bits, sign), vec_uint4_sp(3)), delta); // ((h & 0x7fff) << 13) + delta
+    vec_int4 zt = vec_int4_c(vec_sub(vec_float4_c(vec_add(t, vec_int4_sp(1 << 23))), deltaf));
+
+    t = vec_add(t, vec_and(delta, vec_cmpeq(maxexp, e)));
+    vec_bint4 zmask = vec_cmpeq(e, z);
+    vec_int4 ft = vec_sel(t, zt, zmask);
+    return v_float32x4(vec_float4_c(vec_or(ft, sign)));
+#endif
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+// fixme: Is there any builtin op or intrinsic that cover "xvcvsphp"?
+#if CV_VSX3 && !defined(CV_COMPILER_VSX_BROKEN_ASM)
+    vec_ushort8 vf16;
+    __asm__ __volatile__ ("xvcvsphp %x0,%x1" : "=wa" (vf16) : "wa" (v.val));
+    vec_st_l8(vec_mergesqe(vf16, vf16), ptr);
+#else
+    const vec_int4 signmask = vec_int4_sp(0x80000000);
+    const vec_int4 rval = vec_int4_sp(0x3f000000);
+
+    vec_int4 t = vec_int4_c(v.val);
+    vec_int4 sign = vec_sra(vec_and(t, signmask), vec_uint4_sp(16));
+    t = vec_and(vec_nor(signmask, signmask), t);
+
+    vec_bint4 finitemask = vec_cmpgt(vec_int4_sp(0x47800000), t);
+    vec_bint4 isnan = vec_cmpgt(t, vec_int4_sp(0x7f800000));
+    vec_int4 naninf = vec_sel(vec_int4_sp(0x7c00), vec_int4_sp(0x7e00), isnan);
+    vec_bint4 tinymask = vec_cmpgt(vec_int4_sp(0x38800000), t);
+    vec_int4 tt = vec_int4_c(vec_add(vec_float4_c(t), vec_float4_c(rval)));
+    tt = vec_sub(tt, rval);
+    vec_int4 odd = vec_and(vec_sr(t, vec_uint4_sp(13)), vec_int4_sp(1));
+    vec_int4 nt = vec_add(t, vec_int4_sp(0xc8000fff));
+    nt = vec_sr(vec_add(nt, odd), vec_uint4_sp(13));
+    t = vec_sel(nt, tt, tinymask);
+    t = vec_sel(naninf, t, finitemask);
+    t = vec_or(t, sign);
+    vec_st_l8(vec_packs(t, t), ptr);
+#endif
+}
+
+inline void v_cleanup() {}
+
+
+/** Reinterpret **/
+/** its up there with load and store operations **/
+
+////////// Matrix operations /////////
+
+//////// Dot Product ////////
+// 16 >> 32
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
+{ return v_int32x4(vec_msum(a.val, b.val, vec_int4_z)); }
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_int32x4(vec_msum(a.val, b.val, c.val)); }
+
+// 32 >> 64
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b)
+{
+    vec_dword2 even = vec_mule(a.val, b.val);
+    vec_dword2 odd = vec_mulo(a.val, b.val);
+    return v_int64x2(vec_add(even, odd));
+}
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_uint32x4(vec_msum(a.val, b.val, c.val)); }
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
+{ return v_uint32x4(vec_msum(a.val, b.val, vec_uint4_z)); }
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
+{
+    const vec_ushort8 eight = vec_ushort8_sp(8);
+    vec_short8 a0 = vec_sra((vec_short8)vec_sld(a.val, a.val, 1), eight); // even
+    vec_short8 a1 = vec_sra((vec_short8)a.val, eight); // odd
+    vec_short8 b0 = vec_sra((vec_short8)vec_sld(b.val, b.val, 1), eight);
+    vec_short8 b1 = vec_sra((vec_short8)b.val, eight);
+    return v_int32x4(vec_msum(a0, b0, vec_msum(a1, b1, vec_int4_z)));
+}
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{
+    const vec_ushort8 eight = vec_ushort8_sp(8);
+    vec_short8 a0 = vec_sra((vec_short8)vec_sld(a.val, a.val, 1), eight); // even
+    vec_short8 a1 = vec_sra((vec_short8)a.val, eight); // odd
+    vec_short8 b0 = vec_sra((vec_short8)vec_sld(b.val, b.val, 1), eight);
+    vec_short8 b1 = vec_sra((vec_short8)b.val, eight);
+    return v_int32x4(vec_msum(a0, b0, vec_msum(a1, b1, c.val)));
+}
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
+{
+    const vec_uint4 zero = vec_uint4_z;
+    vec_uint4 even = vec_mule(a.val, b.val);
+    vec_uint4 odd  = vec_mulo(a.val, b.val);
+    vec_udword2 e0 = (vec_udword2)vec_mergee(even, zero);
+    vec_udword2 e1 = (vec_udword2)vec_mergeo(even, zero);
+    vec_udword2 o0 = (vec_udword2)vec_mergee(odd, zero);
+    vec_udword2 o1 = (vec_udword2)vec_mergeo(odd, zero);
+    vec_udword2 s0 = vec_add(e0, o0);
+    vec_udword2 s1 = vec_add(e1, o1);
+    return v_uint64x2(vec_add(s0, s1));
+}
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b)
+{
+    v_int32x4 prod = v_dotprod(a, b);
+    v_int64x2 c, d;
+    v_expand(prod, c, d);
+    return v_int64x2(vec_add(vec_mergeh(c.val, d.val), vec_mergel(c.val, d.val)));
+}
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b)
+{ return v_dotprod(a, b); }
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_int32x4(vec_msum(a.val, b.val, vec_int4_z)) + c; }
+// 32 >> 64
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod(a, b); }
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_dotprod(a, b, c); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_uint32x4(vec_msum(a.val, b.val, vec_uint4_z)) + c; }
+
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
+{
+    vec_short8 a0 = vec_unpackh(a.val);
+    vec_short8 a1 = vec_unpackl(a.val);
+    vec_short8 b0 = vec_unpackh(b.val);
+    vec_short8 b1 = vec_unpackl(b.val);
+    return v_int32x4(vec_msum(a0, b0, vec_msum(a1, b1, vec_int4_z)));
+}
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b)
+{
+    v_int32x4 prod = v_dotprod(a, b);
+    v_int64x2 c, d;
+    v_expand(prod, c, d);
+    return v_add(c, d);
+}
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand_fast(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod_expand(a, b); }
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+
+inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
+                            const v_float32x4& m1, const v_float32x4& m2,
+                            const v_float32x4& m3)
+{
+    const vec_float4 v0 = vec_splat(v.val, 0);
+    const vec_float4 v1 = vec_splat(v.val, 1);
+    const vec_float4 v2 = vec_splat(v.val, 2);
+    VSX_UNUSED(const vec_float4) v3 = vec_splat(v.val, 3);
+    return v_float32x4(vec_madd(v0, m0.val, vec_madd(v1, m1.val, vec_madd(v2, m2.val, vec_mul(v3, m3.val)))));
+}
+
+inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0,
+                               const v_float32x4& m1, const v_float32x4& m2,
+                               const v_float32x4& a)
+{
+    const vec_float4 v0 = vec_splat(v.val, 0);
+    const vec_float4 v1 = vec_splat(v.val, 1);
+    const vec_float4 v2 = vec_splat(v.val, 2);
+    return v_float32x4(vec_madd(v0, m0.val, vec_madd(v1, m1.val, vec_madd(v2, m2.val, a.val))));
+}
+
+#define OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(_Tpvec, _Tpvec2)                        \
+inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1,                   \
+                           const _Tpvec& a2, const _Tpvec& a3,                   \
+                           _Tpvec& b0, _Tpvec& b1, _Tpvec& b2, _Tpvec& b3)       \
+{                                                                                \
+    _Tpvec2 a02 = vec_mergeh(a0.val, a2.val);                                    \
+    _Tpvec2 a13 = vec_mergeh(a1.val, a3.val);                                    \
+    b0.val = vec_mergeh(a02, a13);                                               \
+    b1.val = vec_mergel(a02, a13);                                               \
+    a02 = vec_mergel(a0.val, a2.val);                                            \
+    a13 = vec_mergel(a1.val, a3.val);                                            \
+    b2.val  = vec_mergeh(a02, a13);                                              \
+    b3.val  = vec_mergel(a02, a13);                                              \
+}
+OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(v_uint32x4, vec_uint4)
+OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(v_int32x4, vec_int4)
+OPENCV_HAL_IMPL_VSX_TRANSPOSE4x4(v_float32x4, vec_float4)
+
+template<int i, typename Tvec>
+inline Tvec v_broadcast_element(const Tvec& v)
+{ return Tvec(vec_splat(v.val, i)); }
+
+#include "intrin_math.hpp"
+inline v_float32x4 v_exp(const v_float32x4& x) { return v_exp_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_log(const v_float32x4& x) { return v_log_default_32f<v_float32x4, v_int32x4>(x); }
+inline void v_sincos(const v_float32x4& x, v_float32x4& s, v_float32x4& c) { v_sincos_default_32f<v_float32x4, v_int32x4>(x, s, c); }
+inline v_float32x4 v_sin(const v_float32x4& x) { return v_sin_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_cos(const v_float32x4& x) { return v_cos_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_erf(const v_float32x4& x) { return v_erf_default_32f<v_float32x4, v_int32x4>(x); }
+
+inline v_float64x2 v_exp(const v_float64x2& x) { return v_exp_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_log(const v_float64x2& x) { return v_log_default_64f<v_float64x2, v_int64x2>(x); }
+inline void v_sincos(const v_float64x2& x, v_float64x2& s, v_float64x2& c) { v_sincos_default_64f<v_float64x2, v_int64x2>(x, s, c); }
+inline v_float64x2 v_sin(const v_float64x2& x) { return v_sin_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_cos(const v_float64x2& x) { return v_cos_default_64f<v_float64x2, v_int64x2>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+}
+
+#endif // OPENCV_HAL_VSX_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/hal/intrin_wasm.hpp

@@ -0,0 +1,2801 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_HAL_INTRIN_WASM_HPP
+#define OPENCV_HAL_INTRIN_WASM_HPP
+
+#include <limits>
+#include <cstring>
+#include <algorithm>
+#include "opencv2/core/saturate.hpp"
+
+
+// Emscripten v2.0.13 (latest officially supported, as of 07/30/2024):
+// __EMSCRIPTEN_major__, __EMSCRIPTEN_minor__ and __EMSCRIPTEN_tiny__ are defined via commandline in
+// https://github.com/emscripten-core/emscripten/blob/1690a5802cd1241adc9714fb7fa2f633d38860dc/tools/shared.py#L506-L515
+//
+// See https://github.com/opencv/opencv/pull/25909
+#ifndef __EMSCRIPTEN_major__
+#include <emscripten/version.h>
+#endif
+
+#define CV_SIMD128 1
+#define CV_SIMD128_64F 0 // Now all implementation of f64 use fallback, so disable it.
+#define CV_SIMD128_FP16 0
+
+namespace cv
+{
+
+//! @cond IGNORED
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_BEGIN
+
+#if (__EMSCRIPTEN_major__ * 1000000 + __EMSCRIPTEN_minor__ * 1000 + __EMSCRIPTEN_tiny__) < (1038046)
+// handle renames: https://github.com/emscripten-core/emscripten/pull/9440 (https://github.com/emscripten-core/emscripten/commit/755d5b46cb84d0aa120c10981b11d05646c29673)
+#define wasm_i32x4_trunc_saturate_f32x4 wasm_trunc_saturate_i32x4_f32x4
+#define wasm_u32x4_trunc_saturate_f32x4 wasm_trunc_saturate_u32x4_f32x4
+#define wasm_i64x2_trunc_saturate_f64x2 wasm_trunc_saturate_i64x2_f64x2
+#define wasm_u64x2_trunc_saturate_f64x2 wasm_trunc_saturate_u64x2_f64x2
+#define wasm_f32x4_convert_i32x4 wasm_convert_f32x4_i32x4
+#define wasm_f32x4_convert_u32x4 wasm_convert_f32x4_u32x4
+#define wasm_f64x2_convert_i64x2 wasm_convert_f64x2_i64x2
+#define wasm_f64x2_convert_u64x2 wasm_convert_f64x2_u64x2
+#endif // COMPATIBILITY: <1.38.46
+
+///////// Types ///////////
+
+struct v_uint8x16
+{
+    typedef uchar lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 16 };
+
+    v_uint8x16() {}
+    explicit v_uint8x16(v128_t v) : val(v) {}
+    v_uint8x16(uchar v0, uchar v1, uchar v2, uchar v3, uchar v4, uchar v5, uchar v6, uchar v7,
+            uchar v8, uchar v9, uchar v10, uchar v11, uchar v12, uchar v13, uchar v14, uchar v15)
+    {
+        uchar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = wasm_v128_load(v);
+    }
+
+    uchar get0() const
+    {
+        return (uchar)wasm_i8x16_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_int8x16
+{
+    typedef schar lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 16 };
+
+    v_int8x16() {}
+    explicit v_int8x16(v128_t v) : val(v) {}
+    v_int8x16(schar v0, schar v1, schar v2, schar v3, schar v4, schar v5, schar v6, schar v7,
+            schar v8, schar v9, schar v10, schar v11, schar v12, schar v13, schar v14, schar v15)
+    {
+        schar v[] = {v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15};
+        val = wasm_v128_load(v);
+    }
+
+    schar get0() const
+    {
+        return wasm_i8x16_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_uint16x8
+{
+    typedef ushort lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 8 };
+
+    v_uint16x8() {}
+    explicit v_uint16x8(v128_t v) : val(v) {}
+    v_uint16x8(ushort v0, ushort v1, ushort v2, ushort v3, ushort v4, ushort v5, ushort v6, ushort v7)
+    {
+        ushort v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = wasm_v128_load(v);
+    }
+
+    ushort get0() const
+    {
+        return (ushort)wasm_i16x8_extract_lane(val, 0);    // wasm_u16x8_extract_lane() unimplemented yet
+    }
+
+    v128_t val;
+};
+
+struct v_int16x8
+{
+    typedef short lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 8 };
+
+    v_int16x8() {}
+    explicit v_int16x8(v128_t v) : val(v) {}
+    v_int16x8(short v0, short v1, short v2, short v3, short v4, short v5, short v6, short v7)
+    {
+        short v[] = {v0, v1, v2, v3, v4, v5, v6, v7};
+        val = wasm_v128_load(v);
+    }
+
+    short get0() const
+    {
+        return wasm_i16x8_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_uint32x4
+{
+    typedef unsigned lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 4 };
+
+    v_uint32x4() {}
+    explicit v_uint32x4(v128_t v) : val(v) {}
+    v_uint32x4(unsigned v0, unsigned v1, unsigned v2, unsigned v3)
+    {
+        unsigned v[] = {v0, v1, v2, v3};
+        val = wasm_v128_load(v);
+    }
+
+    unsigned get0() const
+    {
+        return (unsigned)wasm_i32x4_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_int32x4
+{
+    typedef int lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 4 };
+
+    v_int32x4() {}
+    explicit v_int32x4(v128_t v) : val(v) {}
+    v_int32x4(int v0, int v1, int v2, int v3)
+    {
+        int v[] = {v0, v1, v2, v3};
+        val = wasm_v128_load(v);
+    }
+
+    int get0() const
+    {
+        return wasm_i32x4_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_float32x4
+{
+    typedef float lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 4 };
+
+    v_float32x4() {}
+    explicit v_float32x4(v128_t v) : val(v) {}
+    v_float32x4(float v0, float v1, float v2, float v3)
+    {
+        float v[] = {v0, v1, v2, v3};
+        val = wasm_v128_load(v);
+    }
+
+    float get0() const
+    {
+        return wasm_f32x4_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_uint64x2
+{
+    typedef uint64 lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 2 };
+
+    v_uint64x2() {}
+    explicit v_uint64x2(v128_t v) : val(v) {}
+    v_uint64x2(uint64 v0, uint64 v1)
+    {
+        uint64 v[] = {v0, v1};
+        val = wasm_v128_load(v);
+    }
+
+    uint64 get0() const
+    {
+        return (uint64)wasm_i64x2_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_int64x2
+{
+    typedef int64 lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 2 };
+
+    v_int64x2() {}
+    explicit v_int64x2(v128_t v) : val(v) {}
+    v_int64x2(int64 v0, int64 v1)
+    {
+        int64 v[] = {v0, v1};
+        val = wasm_v128_load(v);
+    }
+
+    int64 get0() const
+    {
+        return wasm_i64x2_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+struct v_float64x2
+{
+    typedef double lane_type;
+    typedef v128_t vector_type;
+    enum { nlanes = 2 };
+
+    v_float64x2() {}
+    explicit v_float64x2(v128_t v) : val(v) {}
+    v_float64x2(double v0, double v1)
+    {
+        double v[] = {v0, v1};
+        val = wasm_v128_load(v);
+    }
+
+    double get0() const
+    {
+        return wasm_f64x2_extract_lane(val, 0);
+    }
+
+    v128_t val;
+};
+
+namespace
+{
+#define OPENCV_HAL_IMPL_REINTERPRET_INT(ft, tt) \
+inline tt reinterpret_int(ft x) { union { ft l; tt i; } v; v.l = x; return v.i; }
+OPENCV_HAL_IMPL_REINTERPRET_INT(uchar, schar)
+OPENCV_HAL_IMPL_REINTERPRET_INT(schar, schar)
+OPENCV_HAL_IMPL_REINTERPRET_INT(ushort, short)
+OPENCV_HAL_IMPL_REINTERPRET_INT(short, short)
+OPENCV_HAL_IMPL_REINTERPRET_INT(unsigned, int)
+OPENCV_HAL_IMPL_REINTERPRET_INT(int, int)
+OPENCV_HAL_IMPL_REINTERPRET_INT(float, int)
+OPENCV_HAL_IMPL_REINTERPRET_INT(uint64, int64)
+OPENCV_HAL_IMPL_REINTERPRET_INT(int64, int64)
+OPENCV_HAL_IMPL_REINTERPRET_INT(double, int64)
+
+static const unsigned char popCountTable[] =
+{
+    0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
+    4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8,
+};
+}  // namespace
+
+static v128_t wasm_unpacklo_i8x16(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 0,16,1,17,2,18,3,19,4,20,5,21,6,22,7,23);
+}
+
+static v128_t wasm_unpacklo_i16x8(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 0,1,16,17,2,3,18,19,4,5,20,21,6,7,22,23);
+}
+
+static v128_t wasm_unpacklo_i32x4(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 0,1,2,3,16,17,18,19,4,5,6,7,20,21,22,23);
+}
+
+static v128_t wasm_unpacklo_i64x2(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23);
+}
+
+static v128_t wasm_unpackhi_i8x16(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 8,24,9,25,10,26,11,27,12,28,13,29,14,30,15,31);
+}
+
+static v128_t wasm_unpackhi_i16x8(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 8,9,24,25,10,11,26,27,12,13,28,29,14,15,30,31);
+}
+
+static v128_t wasm_unpackhi_i32x4(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 8,9,10,11,24,25,26,27,12,13,14,15,28,29,30,31);
+}
+
+static v128_t wasm_unpackhi_i64x2(v128_t a, v128_t b) {
+    return wasm_i8x16_shuffle(a, b, 8,9,10,11,12,13,14,15,24,25,26,27,28,29,30,31);
+}
+
+/** Convert **/
+// 8 >> 16
+inline v128_t v128_cvtu8x16_i16x8(const v128_t& a)
+{
+    const v128_t z = wasm_i8x16_splat(0);
+    return wasm_unpacklo_i8x16(a, z);
+}
+inline v128_t v128_cvti8x16_i16x8(const v128_t& a)
+{ return wasm_i16x8_shr(wasm_unpacklo_i8x16(a, a), 8); }
+// 8 >> 32
+inline v128_t v128_cvtu8x16_i32x4(const v128_t& a)
+{
+    const v128_t z = wasm_i8x16_splat(0);
+    return wasm_unpacklo_i16x8(wasm_unpacklo_i8x16(a, z), z);
+}
+inline v128_t v128_cvti8x16_i32x4(const v128_t& a)
+{
+    v128_t r = wasm_unpacklo_i8x16(a, a);
+    r = wasm_unpacklo_i8x16(r, r);
+    return wasm_i32x4_shr(r, 24);
+}
+// 16 >> 32
+inline v128_t v128_cvtu16x8_i32x4(const v128_t& a)
+{
+    const v128_t z = wasm_i8x16_splat(0);
+    return wasm_unpacklo_i16x8(a, z);
+}
+inline v128_t v128_cvti16x8_i32x4(const v128_t& a)
+{ return wasm_i32x4_shr(wasm_unpacklo_i16x8(a, a), 16); }
+// 32 >> 64
+inline v128_t v128_cvtu32x4_i64x2(const v128_t& a)
+{
+    const v128_t z = wasm_i8x16_splat(0);
+    return wasm_unpacklo_i32x4(a, z);
+}
+inline v128_t v128_cvti32x4_i64x2(const v128_t& a)
+{ return wasm_unpacklo_i32x4(a, wasm_i32x4_shr(a, 31)); }
+
+// 16 << 8
+inline v128_t v128_cvtu8x16_i16x8_high(const v128_t& a)
+{
+    const v128_t z = wasm_i8x16_splat(0);
+    return wasm_unpackhi_i8x16(a, z);
+}
+inline v128_t v128_cvti8x16_i16x8_high(const v128_t& a)
+{ return wasm_i16x8_shr(wasm_unpackhi_i8x16(a, a), 8); }
+// 32 << 16
+inline v128_t v128_cvtu16x8_i32x4_high(const v128_t& a)
+{
+    const v128_t z = wasm_i8x16_splat(0);
+    return wasm_unpackhi_i16x8(a, z);
+}
+inline v128_t v128_cvti16x8_i32x4_high(const v128_t& a)
+{ return wasm_i32x4_shr(wasm_unpackhi_i16x8(a, a), 16); }
+// 64 << 32
+inline v128_t v128_cvtu32x4_i64x2_high(const v128_t& a)
+{
+    const v128_t z = wasm_i8x16_splat(0);
+    return wasm_unpackhi_i32x4(a, z);
+}
+inline v128_t v128_cvti32x4_i64x2_high(const v128_t& a)
+{ return wasm_unpackhi_i32x4(a, wasm_i32x4_shr(a, 31)); }
+
+#define OPENCV_HAL_IMPL_WASM_INITVEC(_Tpvec, _Tp, suffix, zsuffix, _Tps) \
+inline _Tpvec v_setzero_##suffix() { return _Tpvec(wasm_##zsuffix##_splat((_Tps)0)); } \
+inline _Tpvec v_setall_##suffix(_Tp v) { return _Tpvec(wasm_##zsuffix##_splat((_Tps)v)); } \
+template <> inline _Tpvec v_setzero_() { return v_setzero_##suffix(); } \
+template <> inline _Tpvec v_setall_(_Tp v) { return v_setall_##suffix(v); } \
+template<typename _Tpvec0> inline _Tpvec v_reinterpret_as_##suffix(const _Tpvec0& a) \
+{ return _Tpvec(a.val); }
+
+OPENCV_HAL_IMPL_WASM_INITVEC(v_uint8x16, uchar, u8, i8x16, schar)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_int8x16, schar, s8, i8x16, schar)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_uint16x8, ushort, u16, i16x8, short)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_int16x8, short, s16, i16x8, short)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_uint32x4, unsigned, u32, i32x4, int)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_int32x4, int, s32, i32x4, int)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_float32x4, float, f32, f32x4, float)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_uint64x2, uint64, u64, i64x2, int64)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_int64x2, int64, s64, i64x2, int64)
+OPENCV_HAL_IMPL_WASM_INITVEC(v_float64x2, double, f64, f64x2, double)
+
+//////////////// PACK ///////////////
+inline v_uint8x16 v_pack(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_u16x8_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_u16x8_gt(b.val, maxval));
+    return v_uint8x16(wasm_i8x16_shuffle(a1, b1, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30));
+}
+inline v_int8x16 v_pack(const v_int16x8& a, const v_int16x8& b)
+{
+    v128_t maxval = wasm_i16x8_splat(127);
+    v128_t minval = wasm_i16x8_splat(-128);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i16x8_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_i16x8_gt(b.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i16x8_lt(a1, minval));
+    v128_t b2 = wasm_v128_bitselect(minval, b1, wasm_i16x8_lt(b1, minval));
+    return v_int8x16(wasm_i8x16_shuffle(a2, b2, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30));
+}
+inline v_uint16x8 v_pack(const v_uint32x4& a, const v_uint32x4& b)
+{
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_u32x4_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_u32x4_gt(b.val, maxval));
+    return v_uint16x8(wasm_i8x16_shuffle(a1, b1, 0,1,4,5,8,9,12,13,16,17,20,21,24,25,28,29));
+}
+inline v_int16x8 v_pack(const v_int32x4& a, const v_int32x4& b)
+{
+    v128_t maxval = wasm_i32x4_splat(32767);
+    v128_t minval = wasm_i32x4_splat(-32768);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i32x4_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_i32x4_gt(b.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i32x4_lt(a1, minval));
+    v128_t b2 = wasm_v128_bitselect(minval, b1, wasm_i32x4_lt(b1, minval));
+    return v_int16x8(wasm_i8x16_shuffle(a2, b2, 0,1,4,5,8,9,12,13,16,17,20,21,24,25,28,29));
+}
+inline v_uint32x4 v_pack(const v_uint64x2& a, const v_uint64x2& b)
+{
+    return v_uint32x4(wasm_i8x16_shuffle(a.val, b.val, 0,1,2,3,8,9,10,11,16,17,18,19,24,25,26,27));
+}
+inline v_int32x4 v_pack(const v_int64x2& a, const v_int64x2& b)
+{
+    return v_int32x4(wasm_i8x16_shuffle(a.val, b.val, 0,1,2,3,8,9,10,11,16,17,18,19,24,25,26,27));
+}
+inline v_uint8x16 v_pack_u(const v_int16x8& a, const v_int16x8& b)
+{
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t minval = wasm_i16x8_splat(0);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i16x8_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_i16x8_gt(b.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i16x8_lt(a1, minval));
+    v128_t b2 = wasm_v128_bitselect(minval, b1, wasm_i16x8_lt(b1, minval));
+    return v_uint8x16(wasm_i8x16_shuffle(a2, b2, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30));
+}
+inline v_uint16x8 v_pack_u(const v_int32x4& a, const v_int32x4& b)
+{
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t minval = wasm_i32x4_splat(0);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i32x4_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_i32x4_gt(b.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i32x4_lt(a1, minval));
+    v128_t b2 = wasm_v128_bitselect(minval, b1, wasm_i32x4_lt(b1, minval));
+    return v_uint16x8(wasm_i8x16_shuffle(a2, b2, 0,1,4,5,8,9,12,13,16,17,20,21,24,25,28,29));
+}
+
+template<int n>
+inline v_uint8x16 v_rshr_pack(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v128_t delta = wasm_i16x8_splat(((short)1 << (n-1)));
+    v128_t a1 = wasm_u16x8_shr(wasm_i16x8_add(a.val, delta), n);
+    v128_t b1 = wasm_u16x8_shr(wasm_i16x8_add(b.val, delta), n);
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_u16x8_gt(a1, maxval));
+    v128_t b2 = wasm_v128_bitselect(maxval, b1, wasm_u16x8_gt(b1, maxval));
+    return v_uint8x16(wasm_i8x16_shuffle(a2, b2, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30));
+}
+template<int n>
+inline v_int8x16 v_rshr_pack(const v_int16x8& a, const v_int16x8& b)
+{
+    v128_t delta = wasm_i16x8_splat(((short)1 << (n-1)));
+    v128_t a1 = wasm_i16x8_shr(wasm_i16x8_add(a.val, delta), n);
+    v128_t b1 = wasm_i16x8_shr(wasm_i16x8_add(b.val, delta), n);
+    v128_t maxval = wasm_i16x8_splat(127);
+    v128_t minval = wasm_i16x8_splat(-128);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i16x8_gt(a1, maxval));
+    v128_t b2 = wasm_v128_bitselect(maxval, b1, wasm_i16x8_gt(b1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i16x8_lt(a1, minval));
+    v128_t b3 = wasm_v128_bitselect(minval, b2, wasm_i16x8_lt(b1, minval));
+    return v_int8x16(wasm_i8x16_shuffle(a3, b3, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30));
+}
+template<int n>
+inline v_uint16x8 v_rshr_pack(const v_uint32x4& a, const v_uint32x4& b)
+{
+    v128_t delta = wasm_i32x4_splat(((int)1 << (n-1)));
+    v128_t a1 = wasm_u32x4_shr(wasm_i32x4_add(a.val, delta), n);
+    v128_t b1 = wasm_u32x4_shr(wasm_i32x4_add(b.val, delta), n);
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_u32x4_gt(a1, maxval));
+    v128_t b2 = wasm_v128_bitselect(maxval, b1, wasm_u32x4_gt(b1, maxval));
+    return v_uint16x8(wasm_i8x16_shuffle(a2, b2, 0,1,4,5,8,9,12,13,16,17,20,21,24,25,28,29));
+}
+template<int n>
+inline v_int16x8 v_rshr_pack(const v_int32x4& a, const v_int32x4& b)
+{
+    v128_t delta = wasm_i32x4_splat(((int)1 << (n-1)));
+    v128_t a1 = wasm_i32x4_shr(wasm_i32x4_add(a.val, delta), n);
+    v128_t b1 = wasm_i32x4_shr(wasm_i32x4_add(b.val, delta), n);
+    v128_t maxval = wasm_i32x4_splat(32767);
+    v128_t minval = wasm_i16x8_splat(-32768);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i32x4_gt(a1, maxval));
+    v128_t b2 = wasm_v128_bitselect(maxval, b1, wasm_i32x4_gt(b1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i32x4_lt(a1, minval));
+    v128_t b3 = wasm_v128_bitselect(minval, b2, wasm_i32x4_lt(b1, minval));
+    return v_int16x8(wasm_i8x16_shuffle(a3, b3, 0,1,4,5,8,9,12,13,16,17,20,21,24,25,28,29));
+}
+template<int n>
+inline v_uint32x4 v_rshr_pack(const v_uint64x2& a, const v_uint64x2& b)
+{
+    v128_t delta = wasm_i64x2_splat(((int64)1 << (n-1)));
+    v128_t a1 = wasm_u64x2_shr(wasm_i64x2_add(a.val, delta), n);
+    v128_t b1 = wasm_u64x2_shr(wasm_i64x2_add(b.val, delta), n);
+    return v_uint32x4(wasm_i8x16_shuffle(a1, b1, 0,1,2,3,8,9,10,11,16,17,18,19,24,25,26,27));
+}
+template<int n>
+inline v_int32x4 v_rshr_pack(const v_int64x2& a, const v_int64x2& b)
+{
+    v128_t delta = wasm_i64x2_splat(((int64)1 << (n-1)));
+    v128_t a1 = wasm_i64x2_shr(wasm_i64x2_add(a.val, delta), n);
+    v128_t b1 = wasm_i64x2_shr(wasm_i64x2_add(b.val, delta), n);
+    return v_int32x4(wasm_i8x16_shuffle(a1, b1, 0,1,2,3,8,9,10,11,16,17,18,19,24,25,26,27));
+}
+template<int n>
+inline v_uint8x16 v_rshr_pack_u(const v_int16x8& a, const v_int16x8& b)
+{
+    v128_t delta = wasm_i16x8_splat(((short)1 << (n-1)));
+    v128_t a1 = wasm_i16x8_shr(wasm_i16x8_add(a.val, delta), n);
+    v128_t b1 = wasm_i16x8_shr(wasm_i16x8_add(b.val, delta), n);
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t minval = wasm_i16x8_splat(0);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i16x8_gt(a1, maxval));
+    v128_t b2 = wasm_v128_bitselect(maxval, b1, wasm_i16x8_gt(b1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i16x8_lt(a1, minval));
+    v128_t b3 = wasm_v128_bitselect(minval, b2, wasm_i16x8_lt(b1, minval));
+    return v_uint8x16(wasm_i8x16_shuffle(a3, b3, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30));
+}
+template<int n>
+inline v_uint16x8 v_rshr_pack_u(const v_int32x4& a, const v_int32x4& b)
+{
+    v128_t delta = wasm_i32x4_splat(((int)1 << (n-1)));
+    v128_t a1 = wasm_i32x4_shr(wasm_i32x4_add(a.val, delta), n);
+    v128_t b1 = wasm_i32x4_shr(wasm_i32x4_add(b.val, delta), n);
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t minval = wasm_i16x8_splat(0);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i32x4_gt(a1, maxval));
+    v128_t b2 = wasm_v128_bitselect(maxval, b1, wasm_i32x4_gt(b1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i32x4_lt(a1, minval));
+    v128_t b3 = wasm_v128_bitselect(minval, b2, wasm_i32x4_lt(b1, minval));
+    return v_uint16x8(wasm_i8x16_shuffle(a3, b3, 0,1,4,5,8,9,12,13,16,17,20,21,24,25,28,29));
+}
+
+inline void v_pack_store(uchar* ptr, const v_uint16x8& a)
+{
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_u16x8_gt(a.val, maxval));
+    v128_t r = wasm_i8x16_shuffle(a1, a1, 0,2,4,6,8,10,12,14,0,2,4,6,8,10,12,14);
+    uchar t_ptr[16];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<8; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+inline void v_pack_store(schar* ptr, const v_int16x8& a)
+{
+    v128_t maxval = wasm_i16x8_splat(127);
+    v128_t minval = wasm_i16x8_splat(-128);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i16x8_gt(a.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i16x8_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a2, a2, 0,2,4,6,8,10,12,14,0,2,4,6,8,10,12,14);
+    schar t_ptr[16];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<8; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+inline void v_pack_store(ushort* ptr, const v_uint32x4& a)
+{
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_u32x4_gt(a.val, maxval));
+    v128_t r = wasm_i8x16_shuffle(a1, a1, 0,1,4,5,8,9,12,13,0,1,4,5,8,9,12,13);
+    ushort t_ptr[8];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<4; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+inline void v_pack_store(short* ptr, const v_int32x4& a)
+{
+    v128_t maxval = wasm_i32x4_splat(32767);
+    v128_t minval = wasm_i32x4_splat(-32768);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i32x4_gt(a.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i32x4_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a2, a2, 0,1,4,5,8,9,12,13,0,1,4,5,8,9,12,13);
+    short t_ptr[8];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<4; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+inline void v_pack_store(unsigned* ptr, const v_uint64x2& a)
+{
+    v128_t r = wasm_i8x16_shuffle(a.val, a.val, 0,1,2,3,8,9,10,11,0,1,2,3,8,9,10,11);
+    unsigned t_ptr[4];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<2; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+inline void v_pack_store(int* ptr, const v_int64x2& a)
+{
+    v128_t r = wasm_i8x16_shuffle(a.val, a.val, 0,1,2,3,8,9,10,11,0,1,2,3,8,9,10,11);
+    int t_ptr[4];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<2; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+inline void v_pack_u_store(uchar* ptr, const v_int16x8& a)
+{
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t minval = wasm_i16x8_splat(0);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i16x8_gt(a.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i16x8_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a2, a2, 0,2,4,6,8,10,12,14,0,2,4,6,8,10,12,14);
+    uchar t_ptr[16];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<8; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+inline void v_pack_u_store(ushort* ptr, const v_int32x4& a)
+{
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t minval = wasm_i32x4_splat(0);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_i32x4_gt(a.val, maxval));
+    v128_t a2 = wasm_v128_bitselect(minval, a1, wasm_i32x4_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a2, a2, 0,1,4,5,8,9,12,13,0,1,4,5,8,9,12,13);
+    ushort t_ptr[8];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<4; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+
+template<int n>
+inline void v_rshr_pack_store(uchar* ptr, const v_uint16x8& a)
+{
+    v128_t delta = wasm_i16x8_splat((short)(1 << (n-1)));
+    v128_t a1 = wasm_u16x8_shr(wasm_i16x8_add(a.val, delta), n);
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_u16x8_gt(a1, maxval));
+    v128_t r = wasm_i8x16_shuffle(a2, a2, 0,2,4,6,8,10,12,14,0,2,4,6,8,10,12,14);
+    uchar t_ptr[16];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<8; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+template<int n>
+inline void v_rshr_pack_store(schar* ptr, const v_int16x8& a)
+{
+    v128_t delta = wasm_i16x8_splat(((short)1 << (n-1)));
+    v128_t a1 = wasm_i16x8_shr(wasm_i16x8_add(a.val, delta), n);
+    v128_t maxval = wasm_i16x8_splat(127);
+    v128_t minval = wasm_i16x8_splat(-128);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i16x8_gt(a1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i16x8_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a3, a3, 0,2,4,6,8,10,12,14,0,2,4,6,8,10,12,14);
+    schar t_ptr[16];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<8; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+template<int n>
+inline void v_rshr_pack_store(ushort* ptr, const v_uint32x4& a)
+{
+    v128_t delta = wasm_i32x4_splat(((int)1 << (n-1)));
+    v128_t a1 = wasm_u32x4_shr(wasm_i32x4_add(a.val, delta), n);
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_u32x4_gt(a1, maxval));
+    v128_t r = wasm_i8x16_shuffle(a2, a2, 0,1,4,5,8,9,12,13,0,1,4,5,8,9,12,13);
+    ushort t_ptr[8];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<4; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+template<int n>
+inline void v_rshr_pack_store(short* ptr, const v_int32x4& a)
+{
+    v128_t delta = wasm_i32x4_splat(((int)1 << (n-1)));
+    v128_t a1 = wasm_i32x4_shr(wasm_i32x4_add(a.val, delta), n);
+    v128_t maxval = wasm_i32x4_splat(32767);
+    v128_t minval = wasm_i32x4_splat(-32768);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i32x4_gt(a1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i32x4_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a3, a3, 0,1,4,5,8,9,12,13,0,1,4,5,8,9,12,13);
+    short t_ptr[8];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<4; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+template<int n>
+inline void v_rshr_pack_store(unsigned* ptr, const v_uint64x2& a)
+{
+    v128_t delta = wasm_i64x2_splat(((int64)1 << (n-1)));
+    v128_t a1 = wasm_u64x2_shr(wasm_i64x2_add(a.val, delta), n);
+    v128_t r = wasm_i8x16_shuffle(a1, a1, 0,1,2,3,8,9,10,11,0,1,2,3,8,9,10,11);
+    unsigned t_ptr[4];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<2; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+template<int n>
+inline void v_rshr_pack_store(int* ptr, const v_int64x2& a)
+{
+    v128_t delta = wasm_i64x2_splat(((int64)1 << (n-1)));
+    v128_t a1 = wasm_i64x2_shr(wasm_i64x2_add(a.val, delta), n);
+    v128_t r = wasm_i8x16_shuffle(a1, a1, 0,1,2,3,8,9,10,11,0,1,2,3,8,9,10,11);
+    int t_ptr[4];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<2; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+template<int n>
+inline void v_rshr_pack_u_store(uchar* ptr, const v_int16x8& a)
+{
+    v128_t delta = wasm_i16x8_splat(((short)1 << (n-1)));
+    v128_t a1 = wasm_i16x8_shr(wasm_i16x8_add(a.val, delta), n);
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t minval = wasm_i16x8_splat(0);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i16x8_gt(a1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i16x8_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a3, a3, 0,2,4,6,8,10,12,14,0,2,4,6,8,10,12,14);
+    uchar t_ptr[16];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<8; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+template<int n>
+inline void v_rshr_pack_u_store(ushort* ptr, const v_int32x4& a)
+{
+    v128_t delta = wasm_i32x4_splat(((int)1 << (n-1)));
+    v128_t a1 = wasm_i32x4_shr(wasm_i32x4_add(a.val, delta), n);
+    v128_t maxval = wasm_i32x4_splat(65535);
+    v128_t minval = wasm_i32x4_splat(0);
+    v128_t a2 = wasm_v128_bitselect(maxval, a1, wasm_i32x4_gt(a1, maxval));
+    v128_t a3 = wasm_v128_bitselect(minval, a2, wasm_i32x4_lt(a1, minval));
+    v128_t r = wasm_i8x16_shuffle(a3, a3, 0,1,4,5,8,9,12,13,0,1,4,5,8,9,12,13);
+    ushort t_ptr[8];
+    wasm_v128_store(t_ptr, r);
+    for (int i=0; i<4; ++i) {
+        ptr[i] = t_ptr[i];
+    }
+}
+
+inline v_uint8x16 v_pack_b(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v128_t maxval = wasm_i16x8_splat(255);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_u16x8_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_u16x8_gt(b.val, maxval));
+    return v_uint8x16(wasm_i8x16_shuffle(a1, b1, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint32x4& a, const v_uint32x4& b,
+                           const v_uint32x4& c, const v_uint32x4& d)
+{
+    v128_t maxval = wasm_i32x4_splat(255);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, wasm_u32x4_gt(a.val, maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, wasm_u32x4_gt(b.val, maxval));
+    v128_t c1 = wasm_v128_bitselect(maxval, c.val, wasm_u32x4_gt(c.val, maxval));
+    v128_t d1 = wasm_v128_bitselect(maxval, d.val, wasm_u32x4_gt(d.val, maxval));
+    v128_t ab = wasm_i8x16_shuffle(a1, b1, 0,4,8,12,16,20,24,28,0,4,8,12,16,20,24,28);
+    v128_t cd = wasm_i8x16_shuffle(c1, d1, 0,4,8,12,16,20,24,28,0,4,8,12,16,20,24,28);
+    return v_uint8x16(wasm_i8x16_shuffle(ab, cd, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23));
+}
+
+inline v_uint8x16 v_pack_b(const v_uint64x2& a, const v_uint64x2& b, const v_uint64x2& c,
+                           const v_uint64x2& d, const v_uint64x2& e, const v_uint64x2& f,
+                           const v_uint64x2& g, const v_uint64x2& h)
+{
+    v128_t maxval = wasm_i32x4_splat(255);
+    v128_t a1 = wasm_v128_bitselect(maxval, a.val, ((__u64x2)(a.val) > (__u64x2)maxval));
+    v128_t b1 = wasm_v128_bitselect(maxval, b.val, ((__u64x2)(b.val) > (__u64x2)maxval));
+    v128_t c1 = wasm_v128_bitselect(maxval, c.val, ((__u64x2)(c.val) > (__u64x2)maxval));
+    v128_t d1 = wasm_v128_bitselect(maxval, d.val, ((__u64x2)(d.val) > (__u64x2)maxval));
+    v128_t e1 = wasm_v128_bitselect(maxval, e.val, ((__u64x2)(e.val) > (__u64x2)maxval));
+    v128_t f1 = wasm_v128_bitselect(maxval, f.val, ((__u64x2)(f.val) > (__u64x2)maxval));
+    v128_t g1 = wasm_v128_bitselect(maxval, g.val, ((__u64x2)(g.val) > (__u64x2)maxval));
+    v128_t h1 = wasm_v128_bitselect(maxval, h.val, ((__u64x2)(h.val) > (__u64x2)maxval));
+    v128_t ab = wasm_i8x16_shuffle(a1, b1, 0,8,16,24,0,8,16,24,0,8,16,24,0,8,16,24);
+    v128_t cd = wasm_i8x16_shuffle(c1, d1, 0,8,16,24,0,8,16,24,0,8,16,24,0,8,16,24);
+    v128_t ef = wasm_i8x16_shuffle(e1, f1, 0,8,16,24,0,8,16,24,0,8,16,24,0,8,16,24);
+    v128_t gh = wasm_i8x16_shuffle(g1, h1, 0,8,16,24,0,8,16,24,0,8,16,24,0,8,16,24);
+    v128_t abcd = wasm_i8x16_shuffle(ab, cd, 0,1,2,3,16,17,18,19,0,1,2,3,16,17,18,19);
+    v128_t efgh = wasm_i8x16_shuffle(ef, gh, 0,1,2,3,16,17,18,19,0,1,2,3,16,17,18,19);
+    return v_uint8x16(wasm_i8x16_shuffle(abcd, efgh, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23));
+}
+
+inline v_float32x4 v_matmul(const v_float32x4& v, const v_float32x4& m0,
+                            const v_float32x4& m1, const v_float32x4& m2,
+                            const v_float32x4& m3)
+{
+    v128_t v0 = wasm_f32x4_splat(wasm_f32x4_extract_lane(v.val, 0));
+    v128_t v1 = wasm_f32x4_splat(wasm_f32x4_extract_lane(v.val, 1));
+    v128_t v2 = wasm_f32x4_splat(wasm_f32x4_extract_lane(v.val, 2));
+    v128_t v3 = wasm_f32x4_splat(wasm_f32x4_extract_lane(v.val, 3));
+    v0 = wasm_f32x4_mul(v0, m0.val);
+    v1 = wasm_f32x4_mul(v1, m1.val);
+    v2 = wasm_f32x4_mul(v2, m2.val);
+    v3 = wasm_f32x4_mul(v3, m3.val);
+
+    return v_float32x4(wasm_f32x4_add(wasm_f32x4_add(v0, v1), wasm_f32x4_add(v2, v3)));
+}
+
+inline v_float32x4 v_matmuladd(const v_float32x4& v, const v_float32x4& m0,
+                               const v_float32x4& m1, const v_float32x4& m2,
+                               const v_float32x4& a)
+{
+    v128_t v0 = wasm_f32x4_splat(wasm_f32x4_extract_lane(v.val, 0));
+    v128_t v1 = wasm_f32x4_splat(wasm_f32x4_extract_lane(v.val, 1));
+    v128_t v2 = wasm_f32x4_splat(wasm_f32x4_extract_lane(v.val, 2));
+    v0 = wasm_f32x4_mul(v0, m0.val);
+    v1 = wasm_f32x4_mul(v1, m1.val);
+    v2 = wasm_f32x4_mul(v2, m2.val);
+
+    return v_float32x4(wasm_f32x4_add(wasm_f32x4_add(v0, v1), wasm_f32x4_add(v2, a.val)));
+}
+
+#define OPENCV_HAL_IMPL_WASM_BIN_OP(bin_op, _Tpvec, intrin) \
+inline _Tpvec bin_op(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_uint8x16, wasm_u8x16_add_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_uint8x16, wasm_u8x16_sub_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_int8x16, wasm_i8x16_add_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_int8x16, wasm_i8x16_sub_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_uint16x8, wasm_u16x8_add_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_uint16x8, wasm_u16x8_sub_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_int16x8, wasm_i16x8_add_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_int16x8, wasm_i16x8_sub_saturate)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_uint32x4, wasm_i32x4_add)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_uint32x4, wasm_i32x4_sub)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_mul, v_uint32x4, wasm_i32x4_mul)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_int32x4, wasm_i32x4_add)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_int32x4, wasm_i32x4_sub)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_mul, v_int32x4, wasm_i32x4_mul)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_float32x4, wasm_f32x4_add)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_float32x4, wasm_f32x4_sub)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_mul, v_float32x4, wasm_f32x4_mul)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_div, v_float32x4, wasm_f32x4_div)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_uint64x2, wasm_i64x2_add)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_uint64x2, wasm_i64x2_sub)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_int64x2, wasm_i64x2_add)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_int64x2, wasm_i64x2_sub)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_add, v_float64x2, wasm_f64x2_add)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_sub, v_float64x2, wasm_f64x2_sub)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_mul, v_float64x2, wasm_f64x2_mul)
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_div, v_float64x2, wasm_f64x2_div)
+
+// saturating multiply 8-bit, 16-bit
+#define OPENCV_HAL_IMPL_WASM_MUL_SAT(_Tpvec, _Tpwvec)        \
+inline _Tpvec v_mul(const _Tpvec& a, const _Tpvec& b)        \
+{                                                            \
+    _Tpwvec c, d;                                            \
+    v_mul_expand(a, b, c, d);                                \
+    return v_pack(c, d);                                     \
+}
+
+OPENCV_HAL_IMPL_WASM_MUL_SAT(v_uint8x16, v_uint16x8)
+OPENCV_HAL_IMPL_WASM_MUL_SAT(v_int8x16,  v_int16x8)
+OPENCV_HAL_IMPL_WASM_MUL_SAT(v_uint16x8, v_uint32x4)
+OPENCV_HAL_IMPL_WASM_MUL_SAT(v_int16x8,  v_int32x4)
+
+//  Multiply and expand
+inline void v_mul_expand(const v_uint8x16& a, const v_uint8x16& b,
+                         v_uint16x8& c, v_uint16x8& d)
+{
+    v_uint16x8 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int8x16& a, const v_int8x16& b,
+                         v_int16x8& c, v_int16x8& d)
+{
+    v_int16x8 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c = v_mul_wrap(a0, b0);
+    d = v_mul_wrap(a1, b1);
+}
+
+inline void v_mul_expand(const v_int16x8& a, const v_int16x8& b,
+                         v_int32x4& c, v_int32x4& d)
+{
+    v_int32x4 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c.val = wasm_i32x4_mul(a0.val, b0.val);
+    d.val = wasm_i32x4_mul(a1.val, b1.val);
+}
+
+inline void v_mul_expand(const v_uint16x8& a, const v_uint16x8& b,
+                         v_uint32x4& c, v_uint32x4& d)
+{
+    v_uint32x4 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c.val = wasm_i32x4_mul(a0.val, b0.val);
+    d.val = wasm_i32x4_mul(a1.val, b1.val);
+}
+
+inline void v_mul_expand(const v_uint32x4& a, const v_uint32x4& b,
+                         v_uint64x2& c, v_uint64x2& d)
+{
+    v_uint64x2 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    c.val = ((__u64x2)(a0.val) * (__u64x2)(b0.val));
+    d.val = ((__u64x2)(a1.val) * (__u64x2)(b1.val));
+}
+
+inline v_int16x8 v_mul_hi(const v_int16x8& a, const v_int16x8& b)
+{
+    v_int32x4 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    v128_t c = wasm_i32x4_mul(a0.val, b0.val);
+    v128_t d = wasm_i32x4_mul(a1.val, b1.val);
+    return v_int16x8(wasm_i8x16_shuffle(c, d, 2,3,6,7,10,11,14,15,18,19,22,23,26,27,30,31));
+}
+inline v_uint16x8 v_mul_hi(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v_uint32x4 a0, a1, b0, b1;
+    v_expand(a, a0, a1);
+    v_expand(b, b0, b1);
+    v128_t c = wasm_i32x4_mul(a0.val, b0.val);
+    v128_t d = wasm_i32x4_mul(a1.val, b1.val);
+    return v_uint16x8(wasm_i8x16_shuffle(c, d, 2,3,6,7,10,11,14,15,18,19,22,23,26,27,30,31));
+}
+
+//////// Dot Product ////////
+
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b)
+{
+    v128_t a0 = wasm_i32x4_shr(wasm_i32x4_shl(a.val, 16), 16);
+    v128_t a1 = wasm_i32x4_shr(a.val, 16);
+    v128_t b0 = wasm_i32x4_shr(wasm_i32x4_shl(b.val, 16), 16);
+    v128_t b1 = wasm_i32x4_shr(b.val, 16);
+    v128_t c = wasm_i32x4_mul(a0, b0);
+    v128_t d = wasm_i32x4_mul(a1, b1);
+    return v_int32x4(wasm_i32x4_add(c, d));
+}
+
+inline v_int32x4 v_dotprod(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_add(v_dotprod(a, b), c); }
+
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b)
+{
+    v128_t a0 = wasm_i64x2_shr(wasm_i64x2_shl(a.val, 32), 32);
+    v128_t a1 = wasm_i64x2_shr(a.val, 32);
+    v128_t b0 = wasm_i64x2_shr(wasm_i64x2_shl(b.val, 32), 32);
+    v128_t b1 = wasm_i64x2_shr(b.val, 32);
+    v128_t c = (v128_t)((__i64x2)a0 * (__i64x2)b0);
+    v128_t d = (v128_t)((__i64x2)a1 * (__i64x2)b1);
+    return v_int64x2(wasm_i64x2_add(c, d));
+}
+inline v_int64x2 v_dotprod(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{
+    return v_add(v_dotprod(a, b), c);
+}
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b)
+{
+    v128_t a0 = wasm_u16x8_shr(wasm_i16x8_shl(a.val, 8), 8);
+    v128_t a1 = wasm_u16x8_shr(a.val, 8);
+    v128_t b0 = wasm_u16x8_shr(wasm_i16x8_shl(b.val, 8), 8);
+    v128_t b1 = wasm_u16x8_shr(b.val, 8);
+    return v_uint32x4((v_add(
+        v_dotprod(v_int16x8(a0), v_int16x8(b0)),
+        v_dotprod(v_int16x8(a1), v_int16x8(b1)))).val
+    );
+}
+inline v_uint32x4 v_dotprod_expand(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b)
+{
+    v128_t a0 = wasm_i16x8_shr(wasm_i16x8_shl(a.val, 8), 8);
+    v128_t a1 = wasm_i16x8_shr(a.val, 8);
+    v128_t b0 = wasm_i16x8_shr(wasm_i16x8_shl(b.val, 8), 8);
+    v128_t b1 = wasm_i16x8_shr(b.val, 8);
+    return v_int32x4(v_add(
+        v_dotprod(v_int16x8(a0), v_int16x8(b0)),
+        v_dotprod(v_int16x8(a1), v_int16x8(b1))
+    ));
+}
+inline v_int32x4 v_dotprod_expand(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v128_t a0 = wasm_u32x4_shr(wasm_i32x4_shl(a.val, 16), 16);
+    v128_t a1 = wasm_u32x4_shr(a.val, 16);
+    v128_t b0 = wasm_u32x4_shr(wasm_i32x4_shl(b.val, 16), 16);
+    v128_t b1 = wasm_u32x4_shr(b.val, 16);
+    return v_uint64x2((v_add(
+        v_dotprod(v_int32x4(a0), v_int32x4(b0)),
+        v_dotprod(v_int32x4(a1), v_int32x4(b1))).val
+    ));
+}
+inline v_uint64x2 v_dotprod_expand(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b)
+{
+    v128_t a0 = wasm_i32x4_shr(wasm_i32x4_shl(a.val, 16), 16);
+    v128_t a1 = wasm_i32x4_shr(a.val, 16);
+    v128_t b0 = wasm_i32x4_shr(wasm_i32x4_shl(b.val, 16), 16);
+    v128_t b1 = wasm_i32x4_shr(b.val, 16);
+    return v_int64x2((v_add(
+        v_dotprod(v_int32x4(a0), v_int32x4(b0)),
+        v_dotprod(v_int32x4(a1), v_int32x4(b1)))
+    ));
+}
+
+inline v_int64x2 v_dotprod_expand(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b)
+{ return v_cvt_f64(v_dotprod(a, b)); }
+inline v_float64x2 v_dotprod_expand(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_add(v_dotprod_expand(a, b), c); }
+
+//////// Fast Dot Product ////////
+
+// 16 >> 32
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b)
+{ return v_dotprod(a, b); }
+inline v_int32x4 v_dotprod_fast(const v_int16x8& a, const v_int16x8& b, const v_int32x4& c)
+{ return v_dotprod(a, b, c); }
+
+// 32 >> 64
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod(a, b); }
+inline v_int64x2 v_dotprod_fast(const v_int32x4& a, const v_int32x4& b, const v_int64x2& c)
+{ return v_dotprod(a, b, c); }
+
+// 8 >> 32
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint32x4 v_dotprod_expand_fast(const v_uint8x16& a, const v_uint8x16& b, const v_uint32x4& c)
+{ return v_dotprod_expand(a, b, c); }
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int32x4 v_dotprod_expand_fast(const v_int8x16& a, const v_int8x16& b, const v_int32x4& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 16 >> 64
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_dotprod_expand(a, b); }
+inline v_uint64x2 v_dotprod_expand_fast(const v_uint16x8& a, const v_uint16x8& b, const v_uint64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b)
+{ return v_dotprod_expand(a, b); }
+inline v_int64x2 v_dotprod_expand_fast(const v_int16x8& a, const v_int16x8& b, const v_int64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+
+// 32 >> 64f
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b)
+{ return v_dotprod_expand(a, b); }
+inline v_float64x2 v_dotprod_expand_fast(const v_int32x4& a, const v_int32x4& b, const v_float64x2& c)
+{ return v_dotprod_expand(a, b, c); }
+
+#define OPENCV_HAL_IMPL_WASM_LOGIC_OP(_Tpvec) \
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_and, _Tpvec, wasm_v128_and) \
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_or, _Tpvec, wasm_v128_or)   \
+OPENCV_HAL_IMPL_WASM_BIN_OP(v_xor, _Tpvec, wasm_v128_xor) \
+inline _Tpvec v_not(const _Tpvec& a) \
+{ \
+    return _Tpvec(wasm_v128_not(a.val)); \
+}
+
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_uint8x16)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_int8x16)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_uint16x8)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_int16x8)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_uint32x4)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_int32x4)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_uint64x2)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_int64x2)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_float32x4)
+OPENCV_HAL_IMPL_WASM_LOGIC_OP(v_float64x2)
+
+inline v_float32x4 v_sqrt(const v_float32x4& x)
+{
+    return v_float32x4(wasm_f32x4_sqrt(x.val));
+}
+
+inline v_float32x4 v_invsqrt(const v_float32x4& x)
+{
+    const v128_t _1_0 = wasm_f32x4_splat(1.0);
+    return v_float32x4(wasm_f32x4_div(_1_0, wasm_f32x4_sqrt(x.val)));
+}
+
+inline v_float64x2 v_sqrt(const v_float64x2& x)
+{
+    return v_float64x2(wasm_f64x2_sqrt(x.val));
+}
+
+inline v_float64x2 v_invsqrt(const v_float64x2& x)
+{
+    const v128_t _1_0 = wasm_f64x2_splat(1.0);
+    return v_float64x2(wasm_f64x2_div(_1_0, wasm_f64x2_sqrt(x.val)));
+}
+
+#define OPENCV_HAL_IMPL_WASM_ABS_INT_FUNC(_Tpuvec, _Tpsvec, suffix, zsuffix, shiftWidth) \
+inline _Tpuvec v_abs(const _Tpsvec& x) \
+{ \
+    v128_t s = wasm_##suffix##_shr(x.val, shiftWidth); \
+    v128_t f = wasm_##zsuffix##_shr(x.val, shiftWidth); \
+    return _Tpuvec(wasm_##zsuffix##_add(wasm_v128_xor(x.val, f), s)); \
+}
+
+OPENCV_HAL_IMPL_WASM_ABS_INT_FUNC(v_uint8x16, v_int8x16, u8x16, i8x16, 7)
+OPENCV_HAL_IMPL_WASM_ABS_INT_FUNC(v_uint16x8, v_int16x8, u16x8, i16x8, 15)
+OPENCV_HAL_IMPL_WASM_ABS_INT_FUNC(v_uint32x4, v_int32x4, u32x4, i32x4, 31)
+
+inline v_float32x4 v_abs(const v_float32x4& x)
+{ return v_float32x4(wasm_f32x4_abs(x.val)); }
+inline v_float64x2 v_abs(const v_float64x2& x)
+{
+    return v_float64x2(wasm_f64x2_abs(x.val));
+}
+
+// TODO: exp, log, sin, cos
+
+#define OPENCV_HAL_IMPL_WASM_BIN_FUNC(_Tpvec, func, intrin) \
+inline _Tpvec func(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(intrin(a.val, b.val)); \
+}
+
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_float32x4, v_min, wasm_f32x4_min)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_float32x4, v_max, wasm_f32x4_max)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_float64x2, v_min, wasm_f64x2_min)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_float64x2, v_max, wasm_f64x2_max)
+
+#define OPENCV_HAL_IMPL_WASM_MINMAX_S_INIT_FUNC(_Tpvec, suffix) \
+inline _Tpvec v_min(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(wasm_v128_bitselect(b.val, a.val, wasm_##suffix##_gt(a.val, b.val))); \
+} \
+inline _Tpvec v_max(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(wasm_v128_bitselect(a.val, b.val, wasm_##suffix##_gt(a.val, b.val))); \
+}
+
+OPENCV_HAL_IMPL_WASM_MINMAX_S_INIT_FUNC(v_int8x16, i8x16)
+OPENCV_HAL_IMPL_WASM_MINMAX_S_INIT_FUNC(v_int16x8, i16x8)
+OPENCV_HAL_IMPL_WASM_MINMAX_S_INIT_FUNC(v_int32x4, i32x4)
+
+#define OPENCV_HAL_IMPL_WASM_MINMAX_U_INIT_FUNC(_Tpvec, suffix, deltaNum) \
+inline _Tpvec v_min(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    v128_t delta = wasm_##suffix##_splat(deltaNum); \
+    v128_t mask = wasm_##suffix##_gt(wasm_v128_xor(a.val, delta), wasm_v128_xor(b.val, delta)); \
+    return _Tpvec(wasm_v128_bitselect(b.val, a.val, mask)); \
+} \
+inline _Tpvec v_max(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    v128_t delta = wasm_##suffix##_splat(deltaNum); \
+    v128_t mask = wasm_##suffix##_gt(wasm_v128_xor(a.val, delta), wasm_v128_xor(b.val, delta)); \
+    return _Tpvec(wasm_v128_bitselect(a.val, b.val, mask)); \
+}
+
+OPENCV_HAL_IMPL_WASM_MINMAX_U_INIT_FUNC(v_uint8x16, i8x16, (schar)0x80)
+OPENCV_HAL_IMPL_WASM_MINMAX_U_INIT_FUNC(v_uint16x8, i16x8, (short)0x8000)
+OPENCV_HAL_IMPL_WASM_MINMAX_U_INIT_FUNC(v_uint32x4, i32x4, (int)0x80000000)
+
+#define OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(_Tpvec, suffix, esuffix) \
+inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b)  \
+{ return _Tpvec(wasm_##esuffix##_eq(a.val, b.val)); } \
+inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b)  \
+{ return _Tpvec(wasm_##esuffix##_ne(a.val, b.val)); } \
+inline _Tpvec v_lt(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(wasm_##suffix##_lt(a.val, b.val)); } \
+inline _Tpvec v_gt(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(wasm_##suffix##_gt(a.val, b.val)); } \
+inline _Tpvec v_le(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(wasm_##suffix##_le(a.val, b.val)); } \
+inline _Tpvec v_ge(const _Tpvec& a, const _Tpvec& b) \
+{ return _Tpvec(wasm_##suffix##_ge(a.val, b.val)); }
+
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_uint8x16, u8x16, i8x16)
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_int8x16, i8x16, i8x16)
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_uint16x8, u16x8, i16x8)
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_int16x8, i16x8, i16x8)
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_uint32x4, u32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_int32x4, i32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_float32x4, f32x4, f32x4)
+OPENCV_HAL_IMPL_WASM_INIT_CMP_OP(v_float64x2, f64x2, f64x2)
+
+#define OPENCV_HAL_IMPL_WASM_64BIT_CMP_OP(_Tpvec, cast) \
+inline _Tpvec v_eq(const _Tpvec& a, const _Tpvec& b) \
+{ return cast(v_eq(v_reinterpret_as_f64(a), v_reinterpret_as_f64(b))); } \
+inline _Tpvec v_ne(const _Tpvec& a, const _Tpvec& b) \
+{ return cast(v_ne(v_reinterpret_as_f64(a), v_reinterpret_as_f64(b))); }
+
+OPENCV_HAL_IMPL_WASM_64BIT_CMP_OP(v_uint64x2, v_reinterpret_as_u64)
+OPENCV_HAL_IMPL_WASM_64BIT_CMP_OP(v_int64x2, v_reinterpret_as_s64)
+
+inline v_float32x4 v_not_nan(const v_float32x4& a)
+{
+    v128_t z = wasm_i32x4_splat(0x7fffffff);
+    v128_t t = wasm_i32x4_splat(0x7f800000);
+    return v_float32x4(wasm_u32x4_lt(wasm_v128_and(a.val, z), t));
+}
+inline v_float64x2 v_not_nan(const v_float64x2& a)
+{
+    v128_t z = wasm_i64x2_splat(0x7fffffffffffffff);
+    v128_t t = wasm_i64x2_splat(0x7ff0000000000000);
+    return v_float64x2((__u64x2)(wasm_v128_and(a.val, z)) < (__u64x2)t);
+}
+
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_uint8x16, v_add_wrap, wasm_i8x16_add)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_int8x16, v_add_wrap, wasm_i8x16_add)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_uint16x8, v_add_wrap, wasm_i16x8_add)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_int16x8, v_add_wrap, wasm_i16x8_add)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_uint8x16, v_sub_wrap, wasm_i8x16_sub)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_int8x16, v_sub_wrap, wasm_i8x16_sub)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_uint16x8, v_sub_wrap, wasm_i16x8_sub)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_int16x8, v_sub_wrap, wasm_i16x8_sub)
+#if (__EMSCRIPTEN_major__ * 1000000 + __EMSCRIPTEN_minor__ * 1000 + __EMSCRIPTEN_tiny__) >= (1039012)
+// details: https://github.com/opencv/opencv/issues/18097 ( https://github.com/emscripten-core/emscripten/issues/12018 )
+// 1.39.12: https://github.com/emscripten-core/emscripten/commit/cd801d0f110facfd694212a3c8b2ed2ffcd630e2
+inline v_uint8x16 v_mul_wrap(const v_uint8x16& a, const v_uint8x16& b)
+{
+    uchar a_[16], b_[16];
+    wasm_v128_store(a_, a.val);
+    wasm_v128_store(b_, b.val);
+    for (int i = 0; i < 16; i++)
+        a_[i] = (uchar)(a_[i] * b_[i]);
+    return v_uint8x16(wasm_v128_load(a_));
+}
+inline v_int8x16 v_mul_wrap(const v_int8x16& a, const v_int8x16& b)
+{
+    schar a_[16], b_[16];
+    wasm_v128_store(a_, a.val);
+    wasm_v128_store(b_, b.val);
+    for (int i = 0; i < 16; i++)
+        a_[i] = (schar)(a_[i] * b_[i]);
+    return v_int8x16(wasm_v128_load(a_));
+}
+#else
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_uint8x16, v_mul_wrap, wasm_i8x16_mul)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_int8x16, v_mul_wrap, wasm_i8x16_mul)
+#endif
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_uint16x8, v_mul_wrap, wasm_i16x8_mul)
+OPENCV_HAL_IMPL_WASM_BIN_FUNC(v_int16x8, v_mul_wrap, wasm_i16x8_mul)
+
+
+/** Absolute difference **/
+
+inline v_uint8x16 v_absdiff(const v_uint8x16& a, const v_uint8x16& b)
+{ return v_add_wrap(v_sub(a, b), v_sub(b, a)); }
+inline v_uint16x8 v_absdiff(const v_uint16x8& a, const v_uint16x8& b)
+{ return v_add_wrap(v_sub(a, b), v_sub(b, a)); }
+inline v_uint32x4 v_absdiff(const v_uint32x4& a, const v_uint32x4& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+inline v_uint8x16 v_absdiff(const v_int8x16& a, const v_int8x16& b)
+{
+    v_int8x16 d = v_sub_wrap(a, b);
+    v_int8x16 m = v_lt(a, b);
+    return v_reinterpret_as_u8(v_sub_wrap(v_xor(d, m), m));
+}
+inline v_uint16x8 v_absdiff(const v_int16x8& a, const v_int16x8& b)
+{
+    return v_reinterpret_as_u16(v_sub_wrap(v_max(a, b), v_min(a, b)));
+}
+inline v_uint32x4 v_absdiff(const v_int32x4& a, const v_int32x4& b)
+{
+    v_int32x4 d = v_sub(a, b);
+    v_int32x4 m = v_lt(a, b);
+    return v_reinterpret_as_u32(v_sub(v_xor(d, m), m));
+}
+
+/** Saturating absolute difference **/
+inline v_int8x16 v_absdiffs(const v_int8x16& a, const v_int8x16& b)
+{
+    v_int8x16 d = v_sub(a, b);
+    v_int8x16 m = v_lt(a, b);
+    return v_sub(v_xor(d, m), m);
+ }
+inline v_int16x8 v_absdiffs(const v_int16x8& a, const v_int16x8& b)
+{ return v_sub(v_max(a, b), v_min(a, b)); }
+
+
+inline v_int32x4 v_fma(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_add(v_mul(a, b), c);
+}
+
+inline v_int32x4 v_muladd(const v_int32x4& a, const v_int32x4& b, const v_int32x4& c)
+{
+    return v_fma(a, b, c);
+}
+
+inline v_float32x4 v_fma(const v_float32x4& a, const v_float32x4& b, const v_float32x4& c)
+{
+    return v_add(v_mul(a, b), c);
+}
+
+inline v_float64x2 v_fma(const v_float64x2& a, const v_float64x2& b, const v_float64x2& c)
+{
+    return v_add(v_mul(a, b), c);
+}
+
+inline v_float32x4 v_absdiff(const v_float32x4& a, const v_float32x4& b)
+{
+    v128_t absmask_vec = wasm_i32x4_splat(0x7fffffff);
+    return v_float32x4(wasm_v128_and(wasm_f32x4_sub(a.val, b.val), absmask_vec));
+}
+inline v_float64x2 v_absdiff(const v_float64x2& a, const v_float64x2& b)
+{
+    v128_t absmask_vec = wasm_u64x2_shr(wasm_i32x4_splat(-1), 1);
+    return v_float64x2(wasm_v128_and(wasm_f64x2_sub(a.val, b.val), absmask_vec));
+}
+
+#define OPENCV_HAL_IMPL_WASM_MISC_FLT_OP(_Tpvec, suffix) \
+inline _Tpvec v_magnitude(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    v128_t a_Square = wasm_##suffix##_mul(a.val, a.val); \
+    v128_t b_Square = wasm_##suffix##_mul(b.val, b.val); \
+    return _Tpvec(wasm_##suffix##_sqrt(wasm_##suffix##_add(a_Square, b_Square))); \
+} \
+inline _Tpvec v_sqr_magnitude(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    v128_t a_Square = wasm_##suffix##_mul(a.val, a.val); \
+    v128_t b_Square = wasm_##suffix##_mul(b.val, b.val); \
+    return _Tpvec(wasm_##suffix##_add(a_Square, b_Square)); \
+} \
+inline _Tpvec v_muladd(const _Tpvec& a, const _Tpvec& b, const _Tpvec& c) \
+{ \
+    return _Tpvec(wasm_##suffix##_add(wasm_##suffix##_mul(a.val, b.val), c.val)); \
+}
+
+OPENCV_HAL_IMPL_WASM_MISC_FLT_OP(v_float32x4, f32x4)
+OPENCV_HAL_IMPL_WASM_MISC_FLT_OP(v_float64x2, f64x2)
+
+#define OPENCV_HAL_IMPL_WASM_SHIFT_OP(_Tpuvec, _Tpsvec, suffix, ssuffix) \
+inline _Tpuvec v_shl(const _Tpuvec& a, int imm) \
+{ \
+    return _Tpuvec(wasm_##suffix##_shl(a.val, imm)); \
+} \
+inline _Tpsvec v_shl(const _Tpsvec& a, int imm) \
+{ \
+    return _Tpsvec(wasm_##suffix##_shl(a.val, imm)); \
+} \
+inline _Tpuvec v_shr(const _Tpuvec& a, int imm) \
+{ \
+    return _Tpuvec(wasm_##ssuffix##_shr(a.val, imm)); \
+} \
+inline _Tpsvec v_shr(const _Tpsvec& a, int imm) \
+{ \
+    return _Tpsvec(wasm_##suffix##_shr(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpuvec v_shl(const _Tpuvec& a) \
+{ \
+    return _Tpuvec(wasm_##suffix##_shl(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpsvec v_shl(const _Tpsvec& a) \
+{ \
+    return _Tpsvec(wasm_##suffix##_shl(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpuvec v_shr(const _Tpuvec& a) \
+{ \
+    return _Tpuvec(wasm_##ssuffix##_shr(a.val, imm)); \
+} \
+template<int imm> \
+inline _Tpsvec v_shr(const _Tpsvec& a) \
+{ \
+    return _Tpsvec(wasm_##suffix##_shr(a.val, imm)); \
+}
+
+OPENCV_HAL_IMPL_WASM_SHIFT_OP(v_uint8x16, v_int8x16, i8x16, u8x16)
+OPENCV_HAL_IMPL_WASM_SHIFT_OP(v_uint16x8, v_int16x8, i16x8, u16x8)
+OPENCV_HAL_IMPL_WASM_SHIFT_OP(v_uint32x4, v_int32x4, i32x4, u32x4)
+OPENCV_HAL_IMPL_WASM_SHIFT_OP(v_uint64x2, v_int64x2, i64x2, u64x2)
+
+namespace hal_wasm_internal
+{
+    template <int imm,
+        bool is_invalid = ((imm < 0) || (imm > 16)),
+        bool is_first = (imm == 0),
+        bool is_second = (imm == 16),
+        bool is_other = (((imm > 0) && (imm < 16)))>
+    class v_wasm_palignr_u8_class;
+
+    template <int imm>
+    class v_wasm_palignr_u8_class<imm, true, false, false, false>;
+
+    template <int imm>
+    class v_wasm_palignr_u8_class<imm, false, true, false, false>
+    {
+    public:
+        inline v128_t operator()(const v128_t& a, const v128_t&) const
+        {
+            return a;
+        }
+    };
+
+    template <int imm>
+    class v_wasm_palignr_u8_class<imm, false, false, true, false>
+    {
+    public:
+        inline v128_t operator()(const v128_t&, const v128_t& b) const
+        {
+            return b;
+        }
+    };
+
+    template <int imm>
+    class v_wasm_palignr_u8_class<imm, false, false, false, true>
+    {
+    public:
+        inline v128_t operator()(const v128_t& a, const v128_t& b) const
+        {
+            enum { imm2 = (sizeof(v128_t) - imm) };
+            return wasm_i8x16_shuffle(a, b,
+                                      imm, imm+1, imm+2, imm+3,
+                                      imm+4, imm+5, imm+6, imm+7,
+                                      imm+8, imm+9, imm+10, imm+11,
+                                      imm+12, imm+13, imm+14, imm+15);
+        }
+    };
+
+    template <int imm>
+    inline v128_t v_wasm_palignr_u8(const v128_t& a, const v128_t& b)
+    {
+        CV_StaticAssert((imm >= 0) && (imm <= 16), "Invalid imm for v_wasm_palignr_u8.");
+        return v_wasm_palignr_u8_class<imm>()(a, b);
+    }
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_right(const _Tpvec &a)
+{
+    using namespace hal_wasm_internal;
+    enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) };
+    v128_t z = wasm_i8x16_splat(0);
+    return _Tpvec(v_wasm_palignr_u8<imm2>(a.val, z));
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_left(const _Tpvec &a)
+{
+    using namespace hal_wasm_internal;
+    enum { imm2 = ((_Tpvec::nlanes - imm) * sizeof(typename _Tpvec::lane_type)) };
+    v128_t z = wasm_i8x16_splat(0);
+    return _Tpvec(v_wasm_palignr_u8<imm2>(z, a.val));
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_right(const _Tpvec &a, const _Tpvec &b)
+{
+    using namespace hal_wasm_internal;
+    enum { imm2 = (imm * sizeof(typename _Tpvec::lane_type)) };
+    return _Tpvec(v_wasm_palignr_u8<imm2>(a.val, b.val));
+}
+
+template<int imm, typename _Tpvec>
+inline _Tpvec v_rotate_left(const _Tpvec &a, const _Tpvec &b)
+{
+    using namespace hal_wasm_internal;
+    enum { imm2 = ((_Tpvec::nlanes - imm) * sizeof(typename _Tpvec::lane_type)) };
+    return _Tpvec(v_wasm_palignr_u8<imm2>(b.val, a.val));
+}
+
+#define OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(_Tpvec, _Tp) \
+inline _Tpvec v_load(const _Tp* ptr) \
+{ return _Tpvec(wasm_v128_load(ptr)); } \
+inline _Tpvec v_load_aligned(const _Tp* ptr) \
+{ return _Tpvec(wasm_v128_load(ptr)); } \
+inline _Tpvec v_load_low(const _Tp* ptr) \
+{ \
+    _Tp tmp[_Tpvec::nlanes] = {0}; \
+    for (int i=0; i<_Tpvec::nlanes/2; ++i) { \
+        tmp[i] = ptr[i]; \
+    } \
+    return _Tpvec(wasm_v128_load(tmp)); \
+} \
+inline _Tpvec v_load_halves(const _Tp* ptr0, const _Tp* ptr1) \
+{ \
+    _Tp tmp[_Tpvec::nlanes]; \
+    for (int i=0; i<_Tpvec::nlanes/2; ++i) { \
+        tmp[i] = ptr0[i]; \
+        tmp[i+_Tpvec::nlanes/2] = ptr1[i]; \
+    } \
+    return _Tpvec(wasm_v128_load(tmp)); \
+} \
+inline void v_store(_Tp* ptr, const _Tpvec& a) \
+{ wasm_v128_store(ptr, a.val); } \
+inline void v_store_aligned(_Tp* ptr, const _Tpvec& a) \
+{ wasm_v128_store(ptr, a.val); } \
+inline void v_store_aligned_nocache(_Tp* ptr, const _Tpvec& a) \
+{ wasm_v128_store(ptr, a.val); } \
+inline void v_store(_Tp* ptr, const _Tpvec& a, hal::StoreMode /*mode*/) \
+{ \
+    wasm_v128_store(ptr, a.val); \
+} \
+inline void v_store_low(_Tp* ptr, const _Tpvec& a) \
+{ \
+    _Tpvec::lane_type a_[_Tpvec::nlanes]; \
+    wasm_v128_store(a_, a.val); \
+    for (int i = 0; i < (_Tpvec::nlanes / 2); i++) \
+        ptr[i] = a_[i]; \
+} \
+inline void v_store_high(_Tp* ptr, const _Tpvec& a) \
+{ \
+    _Tpvec::lane_type a_[_Tpvec::nlanes]; \
+    wasm_v128_store(a_, a.val); \
+    for (int i = 0; i < (_Tpvec::nlanes / 2); i++) \
+        ptr[i] = a_[i + (_Tpvec::nlanes / 2)]; \
+}
+
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_uint8x16, uchar)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_int8x16, schar)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_uint16x8, ushort)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_int16x8, short)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_uint32x4, unsigned)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_int32x4, int)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_uint64x2, uint64)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_int64x2, int64)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_float32x4, float)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INT_OP(v_float64x2, double)
+
+
+/** Reverse **/
+inline v_uint8x16 v_reverse(const v_uint8x16 &a)
+{ return v_uint8x16(wasm_i8x16_shuffle(a.val, a.val, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0)); }
+
+inline v_int8x16 v_reverse(const v_int8x16 &a)
+{ return v_reinterpret_as_s8(v_reverse(v_reinterpret_as_u8(a))); }
+
+inline v_uint16x8 v_reverse(const v_uint16x8 &a)
+{ return v_uint16x8(wasm_i8x16_shuffle(a.val, a.val, 14, 15, 12, 13, 10, 11, 8, 9, 6, 7, 4, 5, 2, 3, 0, 1)); }
+
+inline v_int16x8 v_reverse(const v_int16x8 &a)
+{ return v_reinterpret_as_s16(v_reverse(v_reinterpret_as_u16(a))); }
+
+inline v_uint32x4 v_reverse(const v_uint32x4 &a)
+{ return v_uint32x4(wasm_i8x16_shuffle(a.val, a.val, 12, 13, 14, 15, 8, 9, 10, 11, 4, 5, 6, 7, 0, 1, 2, 3)); }
+
+inline v_int32x4 v_reverse(const v_int32x4 &a)
+{ return v_reinterpret_as_s32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_float32x4 v_reverse(const v_float32x4 &a)
+{ return v_reinterpret_as_f32(v_reverse(v_reinterpret_as_u32(a))); }
+
+inline v_uint64x2 v_reverse(const v_uint64x2 &a)
+{ return v_uint64x2(wasm_i8x16_shuffle(a.val, a.val, 8, 9, 10, 11, 12, 13, 14, 15, 0, 1, 2, 3, 4, 5, 6, 7)); }
+
+inline v_int64x2 v_reverse(const v_int64x2 &a)
+{ return v_reinterpret_as_s64(v_reverse(v_reinterpret_as_u64(a))); }
+
+inline v_float64x2 v_reverse(const v_float64x2 &a)
+{ return v_reinterpret_as_f64(v_reverse(v_reinterpret_as_u64(a))); }
+
+
+#define OPENCV_HAL_IMPL_WASM_REDUCE_OP_4_SUM(_Tpvec, scalartype, regtype, suffix, esuffix) \
+inline scalartype v_reduce_sum(const _Tpvec& a) \
+{ \
+    regtype val = a.val; \
+    val = wasm_##suffix##_add(val, wasm_i8x16_shuffle(val, val, 8,9,10,11,12,13,14,15,0,1,2,3,4,5,6,7)); \
+    val = wasm_##suffix##_add(val, wasm_i8x16_shuffle(val, val, 4,5,6,7,8,9,10,11,12,13,14,15,0,1,2,3)); \
+    return (scalartype)wasm_##esuffix##_extract_lane(val, 0); \
+}
+
+OPENCV_HAL_IMPL_WASM_REDUCE_OP_4_SUM(v_uint32x4, unsigned, v128_t, i32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP_4_SUM(v_int32x4, int, v128_t, i32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP_4_SUM(v_float32x4, float, v128_t, f32x4, f32x4)
+
+// To do: Optimize v_reduce_sum with wasm intrin.
+//        Now use fallback implementation as there is no widening op in wasm intrin.
+
+#define OPENCV_HAL_IMPL_FALLBACK_REDUCE_OP_SUM(_Tpvec, scalartype) \
+inline scalartype v_reduce_sum(const _Tpvec& a) \
+{ \
+    _Tpvec::lane_type a_[_Tpvec::nlanes]; \
+    wasm_v128_store(a_, a.val); \
+    scalartype c = a_[0]; \
+    for (int i = 1; i < _Tpvec::nlanes; i++) \
+        c += a_[i]; \
+    return c; \
+}
+
+OPENCV_HAL_IMPL_FALLBACK_REDUCE_OP_SUM(v_uint8x16, unsigned)
+OPENCV_HAL_IMPL_FALLBACK_REDUCE_OP_SUM(v_int8x16, int)
+OPENCV_HAL_IMPL_FALLBACK_REDUCE_OP_SUM(v_uint16x8, unsigned)
+OPENCV_HAL_IMPL_FALLBACK_REDUCE_OP_SUM(v_int16x8, int)
+
+
+#define OPENCV_HAL_IMPL_WASM_REDUCE_OP_2_SUM(_Tpvec, scalartype, regtype, suffix, esuffix) \
+inline scalartype v_reduce_sum(const _Tpvec& a) \
+{ \
+    regtype val = a.val; \
+    val = wasm_##suffix##_add(val, wasm_i8x16_shuffle(val, val, 8,9,10,11,12,13,14,15,0,1,2,3,4,5,6,7)); \
+    return (scalartype)wasm_##esuffix##_extract_lane(val, 0); \
+}
+OPENCV_HAL_IMPL_WASM_REDUCE_OP_2_SUM(v_uint64x2, uint64, v128_t, i64x2, i64x2)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP_2_SUM(v_int64x2, int64,  v128_t, i64x2, i64x2)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP_2_SUM(v_float64x2, double,  v128_t, f64x2,f64x2)
+
+inline v_float32x4 v_reduce_sum4(const v_float32x4& a, const v_float32x4& b,
+                                 const v_float32x4& c, const v_float32x4& d)
+{
+    v128_t ac = wasm_f32x4_add(wasm_unpacklo_i32x4(a.val, c.val), wasm_unpackhi_i32x4(a.val, c.val));
+    v128_t bd = wasm_f32x4_add(wasm_unpacklo_i32x4(b.val, d.val), wasm_unpackhi_i32x4(b.val, d.val));
+    return v_float32x4(wasm_f32x4_add(wasm_unpacklo_i32x4(ac, bd), wasm_unpackhi_i32x4(ac, bd)));
+}
+
+#define OPENCV_HAL_IMPL_WASM_REDUCE_OP(_Tpvec, scalartype, func, scalar_func) \
+inline scalartype v_reduce_##func(const _Tpvec& a) \
+{ \
+    scalartype buf[_Tpvec::nlanes]; \
+    v_store(buf, a); \
+    scalartype tmp = buf[0]; \
+    for (int i=1; i<_Tpvec::nlanes; ++i) { \
+        tmp = scalar_func(tmp, buf[i]); \
+    } \
+    return tmp; \
+}
+
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_uint8x16, uchar, max, std::max)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_uint8x16, uchar, min, std::min)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_int8x16, schar, max, std::max)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_int8x16, schar, min, std::min)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_uint16x8, ushort, max, std::max)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_uint16x8, ushort, min, std::min)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_int16x8, short, max, std::max)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_int16x8, short, min, std::min)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_uint32x4, unsigned, max, std::max)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_uint32x4, unsigned, min, std::min)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_int32x4, int, max, std::max)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_int32x4, int, min, std::min)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_float32x4, float, max, std::max)
+OPENCV_HAL_IMPL_WASM_REDUCE_OP(v_float32x4, float, min, std::min)
+
+inline unsigned v_reduce_sad(const v_uint8x16& a, const v_uint8x16& b)
+{
+    v_uint16x8 l16, h16;
+    v_uint32x4 l16_l32, l16_h32, h16_l32, h16_h32;
+    v_expand(v_absdiff(a, b), l16, h16);
+    v_expand(l16, l16_l32, l16_h32);
+    v_expand(h16, h16_l32, h16_h32);
+    return v_reduce_sum(v_add(v_add(l16_l32, l16_h32), v_add(h16_l32, h16_h32)));
+}
+inline unsigned v_reduce_sad(const v_int8x16& a, const v_int8x16& b)
+{
+    v_uint16x8 l16, h16;
+    v_uint32x4 l16_l32, l16_h32, h16_l32, h16_h32;
+    v_expand(v_absdiff(a, b), l16, h16);
+    v_expand(l16, l16_l32, l16_h32);
+    v_expand(h16, h16_l32, h16_h32);
+    return v_reduce_sum(v_add(v_add(l16_l32, l16_h32), v_add(h16_l32, h16_h32)));
+}
+inline unsigned v_reduce_sad(const v_uint16x8& a, const v_uint16x8& b)
+{
+    v_uint32x4 l, h;
+    v_expand(v_absdiff(a, b), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_int16x8& a, const v_int16x8& b)
+{
+    v_uint32x4 l, h;
+    v_expand(v_absdiff(a, b), l, h);
+    return v_reduce_sum(v_add(l, h));
+}
+inline unsigned v_reduce_sad(const v_uint32x4& a, const v_uint32x4& b)
+{
+    return v_reduce_sum(v_absdiff(a, b));
+}
+inline unsigned v_reduce_sad(const v_int32x4& a, const v_int32x4& b)
+{
+    return v_reduce_sum(v_absdiff(a, b));
+}
+inline float v_reduce_sad(const v_float32x4& a, const v_float32x4& b)
+{
+    return v_reduce_sum(v_absdiff(a, b));
+}
+
+inline v_uint8x16 v_popcount(const v_uint8x16& a)
+{
+    v128_t m1 = wasm_i32x4_splat(0x55555555);
+    v128_t m2 = wasm_i32x4_splat(0x33333333);
+    v128_t m4 = wasm_i32x4_splat(0x0f0f0f0f);
+    v128_t p = a.val;
+    p = wasm_i32x4_add(wasm_v128_and(wasm_u32x4_shr(p, 1), m1), wasm_v128_and(p, m1));
+    p = wasm_i32x4_add(wasm_v128_and(wasm_u32x4_shr(p, 2), m2), wasm_v128_and(p, m2));
+    p = wasm_i32x4_add(wasm_v128_and(wasm_u32x4_shr(p, 4), m4), wasm_v128_and(p, m4));
+    return v_uint8x16(p);
+}
+inline v_uint16x8 v_popcount(const v_uint16x8& a)
+{
+    v_uint8x16 p = v_popcount(v_reinterpret_as_u8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    return v_and(v_reinterpret_as_u16(p), v_setall_u16(0x00ff));
+}
+inline v_uint32x4 v_popcount(const v_uint32x4& a)
+{
+    v_uint8x16 p = v_popcount(v_reinterpret_as_u8(a));
+    p = v_add(p, v_rotate_right<1>(p));
+    p = v_add(p, v_rotate_right<2>(p));
+    return v_and(v_reinterpret_as_u32(p), v_setall_u32(0x000000ff));
+}
+inline v_uint64x2 v_popcount(const v_uint64x2& a)
+{
+    uint64 a_[2], b_[2] = { 0 };
+    wasm_v128_store(a_, a.val);
+    for (int i = 0; i < 16; i++)
+        b_[i / 8] += popCountTable[((uint8_t*)a_)[i]];
+    return v_uint64x2(wasm_v128_load(b_));
+}
+inline v_uint8x16 v_popcount(const v_int8x16& a)
+{ return v_popcount(v_reinterpret_as_u8(a)); }
+inline v_uint16x8 v_popcount(const v_int16x8& a)
+{ return v_popcount(v_reinterpret_as_u16(a)); }
+inline v_uint32x4 v_popcount(const v_int32x4& a)
+{ return v_popcount(v_reinterpret_as_u32(a)); }
+inline v_uint64x2 v_popcount(const v_int64x2& a)
+{ return v_popcount(v_reinterpret_as_u64(a)); }
+
+#define OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(_Tpvec, suffix, scalarType) \
+inline int v_signmask(const _Tpvec& a) \
+{ \
+    _Tpvec::lane_type a_[_Tpvec::nlanes]; \
+    wasm_v128_store(a_, a.val); \
+    int mask = 0; \
+    for (int i = 0; i < _Tpvec::nlanes; i++) \
+        mask |= (reinterpret_int(a_[i]) < 0) << i; \
+    return mask; \
+} \
+inline bool v_check_all(const _Tpvec& a) \
+{ return wasm_i8x16_all_true(wasm_##suffix##_lt(a.val, wasm_##suffix##_splat(0))); } \
+inline bool v_check_any(const _Tpvec& a) \
+{ return wasm_i8x16_any_true(wasm_##suffix##_lt(a.val, wasm_##suffix##_splat(0)));; }
+
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_uint8x16, i8x16, schar)
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_int8x16, i8x16, schar)
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_uint16x8, i16x8, short)
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_int16x8, i16x8, short)
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_uint32x4, i32x4, int)
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_int32x4, i32x4, int)
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_float32x4, i32x4, float)
+OPENCV_HAL_IMPL_WASM_CHECK_SIGNS(v_float64x2, f64x2, double)
+
+#define OPENCV_HAL_IMPL_WASM_CHECK_ALL_ANY(_Tpvec, suffix, esuffix) \
+inline bool v_check_all(const _Tpvec& a) \
+{ \
+    v128_t masked = v_reinterpret_as_##esuffix(a).val; \
+    masked = wasm_i32x4_replace_lane(masked, 0, 0xffffffff); \
+    masked = wasm_i32x4_replace_lane(masked, 2, 0xffffffff); \
+    return wasm_i8x16_all_true(wasm_##suffix##_lt(masked, wasm_##suffix##_splat(0))); \
+} \
+inline bool v_check_any(const _Tpvec& a) \
+{ \
+    v128_t masked = v_reinterpret_as_##esuffix(a).val; \
+    masked = wasm_i32x4_replace_lane(masked, 0, 0x0); \
+    masked = wasm_i32x4_replace_lane(masked, 2, 0x0); \
+    return wasm_i8x16_any_true(wasm_##suffix##_lt(masked, wasm_##suffix##_splat(0))); \
+} \
+
+OPENCV_HAL_IMPL_WASM_CHECK_ALL_ANY(v_int64x2, i32x4, s32)
+OPENCV_HAL_IMPL_WASM_CHECK_ALL_ANY(v_uint64x2, i32x4, u32)
+
+
+inline int v_scan_forward(const v_int8x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_uint8x16& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))); }
+inline int v_scan_forward(const v_int16x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_uint16x8& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 2; }
+inline int v_scan_forward(const v_int32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_uint32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_float32x4& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 4; }
+inline int v_scan_forward(const v_int64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_uint64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+inline int v_scan_forward(const v_float64x2& a) { return trailingZeros32(v_signmask(v_reinterpret_as_s8(a))) / 8; }
+
+#define OPENCV_HAL_IMPL_WASM_SELECT(_Tpvec) \
+inline _Tpvec v_select(const _Tpvec& mask, const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(wasm_v128_bitselect(a.val, b.val, mask.val)); \
+}
+
+OPENCV_HAL_IMPL_WASM_SELECT(v_uint8x16)
+OPENCV_HAL_IMPL_WASM_SELECT(v_int8x16)
+OPENCV_HAL_IMPL_WASM_SELECT(v_uint16x8)
+OPENCV_HAL_IMPL_WASM_SELECT(v_int16x8)
+OPENCV_HAL_IMPL_WASM_SELECT(v_uint32x4)
+OPENCV_HAL_IMPL_WASM_SELECT(v_int32x4)
+OPENCV_HAL_IMPL_WASM_SELECT(v_uint64x2)
+OPENCV_HAL_IMPL_WASM_SELECT(v_int64x2)
+OPENCV_HAL_IMPL_WASM_SELECT(v_float32x4)
+OPENCV_HAL_IMPL_WASM_SELECT(v_float64x2)
+
+#define OPENCV_HAL_IMPL_WASM_EXPAND(_Tpvec, _Tpwvec, _Tp, intrin)    \
+inline void v_expand(const _Tpvec& a, _Tpwvec& b0, _Tpwvec& b1)      \
+{                                                                    \
+    b0.val = intrin(a.val);                                          \
+    b1.val = __CV_CAT(intrin, _high)(a.val);                         \
+}                                                                    \
+inline _Tpwvec v_expand_low(const _Tpvec& a)                         \
+{ return _Tpwvec(intrin(a.val)); }                                   \
+inline _Tpwvec v_expand_high(const _Tpvec& a)                        \
+{ return _Tpwvec(__CV_CAT(intrin, _high)(a.val)); }                  \
+inline _Tpwvec v_load_expand(const _Tp* ptr)                         \
+{                                                                    \
+    v128_t a = wasm_v128_load(ptr);                                  \
+    return _Tpwvec(intrin(a));                                       \
+}
+
+OPENCV_HAL_IMPL_WASM_EXPAND(v_uint8x16, v_uint16x8, uchar, v128_cvtu8x16_i16x8)
+OPENCV_HAL_IMPL_WASM_EXPAND(v_int8x16,  v_int16x8,  schar, v128_cvti8x16_i16x8)
+OPENCV_HAL_IMPL_WASM_EXPAND(v_uint16x8, v_uint32x4, ushort, v128_cvtu16x8_i32x4)
+OPENCV_HAL_IMPL_WASM_EXPAND(v_int16x8,  v_int32x4,  short, v128_cvti16x8_i32x4)
+OPENCV_HAL_IMPL_WASM_EXPAND(v_uint32x4, v_uint64x2, unsigned, v128_cvtu32x4_i64x2)
+OPENCV_HAL_IMPL_WASM_EXPAND(v_int32x4,  v_int64x2,  int, v128_cvti32x4_i64x2)
+
+#define OPENCV_HAL_IMPL_WASM_EXPAND_Q(_Tpvec, _Tp, intrin)  \
+inline _Tpvec v_load_expand_q(const _Tp* ptr)               \
+{                                                           \
+    v128_t a = wasm_v128_load(ptr);                         \
+    return _Tpvec(intrin(a));                               \
+}
+
+OPENCV_HAL_IMPL_WASM_EXPAND_Q(v_uint32x4, uchar, v128_cvtu8x16_i32x4)
+OPENCV_HAL_IMPL_WASM_EXPAND_Q(v_int32x4, schar, v128_cvti8x16_i32x4)
+
+#define OPENCV_HAL_IMPL_WASM_UNPACKS(_Tpvec, suffix) \
+inline void v_zip(const _Tpvec& a0, const _Tpvec& a1, _Tpvec& b0, _Tpvec& b1) \
+{ \
+    b0.val = wasm_unpacklo_##suffix(a0.val, a1.val); \
+    b1.val = wasm_unpackhi_##suffix(a0.val, a1.val); \
+} \
+inline _Tpvec v_combine_low(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(wasm_unpacklo_i64x2(a.val, b.val)); \
+} \
+inline _Tpvec v_combine_high(const _Tpvec& a, const _Tpvec& b) \
+{ \
+    return _Tpvec(wasm_unpackhi_i64x2(a.val, b.val)); \
+} \
+inline void v_recombine(const _Tpvec& a, const _Tpvec& b, _Tpvec& c, _Tpvec& d) \
+{ \
+    c.val = wasm_unpacklo_i64x2(a.val, b.val); \
+    d.val = wasm_unpackhi_i64x2(a.val, b.val); \
+}
+
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_uint8x16, i8x16)
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_int8x16, i8x16)
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_uint16x8, i16x8)
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_int16x8, i16x8)
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_uint32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_int32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_float32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_UNPACKS(v_float64x2, i64x2)
+
+template<int s, typename _Tpvec>
+inline _Tpvec v_extract(const _Tpvec& a, const _Tpvec& b)
+{
+    return v_rotate_right<s>(a, b);
+}
+
+inline v_int32x4 v_round(const v_float32x4& a)
+{
+    v128_t h = wasm_f32x4_splat(0.5);
+    return v_int32x4(wasm_i32x4_trunc_saturate_f32x4(wasm_f32x4_add(a.val, h)));
+}
+
+inline v_int32x4 v_floor(const v_float32x4& a)
+{
+    v128_t a1 = wasm_i32x4_trunc_saturate_f32x4(a.val);
+    v128_t mask = wasm_f32x4_lt(a.val, wasm_f32x4_convert_i32x4(a1));
+    return v_int32x4(wasm_i32x4_add(a1, mask));
+}
+
+inline v_int32x4 v_ceil(const v_float32x4& a)
+{
+    v128_t a1 = wasm_i32x4_trunc_saturate_f32x4(a.val);
+    v128_t mask = wasm_f32x4_gt(a.val, wasm_f32x4_convert_i32x4(a1));
+    return v_int32x4(wasm_i32x4_sub(a1, mask));
+}
+
+inline v_int32x4 v_trunc(const v_float32x4& a)
+{ return v_int32x4(wasm_i32x4_trunc_saturate_f32x4(a.val)); }
+
+#define OPENCV_HAL_IMPL_WASM_MATH_FUNC(func, cfunc) \
+inline v_int32x4 func(const v_float64x2& a) \
+{ \
+    double a_[2]; \
+    wasm_v128_store(a_, a.val); \
+    int c_[4]; \
+    c_[0] = cfunc(a_[0]); \
+    c_[1] = cfunc(a_[1]); \
+    c_[2] = 0; \
+    c_[3] = 0; \
+    return v_int32x4(wasm_v128_load(c_)); \
+}
+
+OPENCV_HAL_IMPL_WASM_MATH_FUNC(v_round, cvRound)
+OPENCV_HAL_IMPL_WASM_MATH_FUNC(v_floor, cvFloor)
+OPENCV_HAL_IMPL_WASM_MATH_FUNC(v_ceil, cvCeil)
+OPENCV_HAL_IMPL_WASM_MATH_FUNC(v_trunc, int)
+
+inline v_int32x4 v_round(const v_float64x2& a, const v_float64x2& b)
+{
+    double a_[2], b_[2];
+    wasm_v128_store(a_, a.val);
+    wasm_v128_store(b_, b.val);
+    int c_[4];
+    c_[0] = cvRound(a_[0]);
+    c_[1] = cvRound(a_[1]);
+    c_[2] = cvRound(b_[0]);
+    c_[3] = cvRound(b_[1]);
+    return v_int32x4(wasm_v128_load(c_));
+}
+
+#define OPENCV_HAL_IMPL_WASM_TRANSPOSE4x4(_Tpvec, suffix) \
+inline void v_transpose4x4(const _Tpvec& a0, const _Tpvec& a1, \
+                           const _Tpvec& a2, const _Tpvec& a3, \
+                           _Tpvec& b0, _Tpvec& b1, \
+                           _Tpvec& b2, _Tpvec& b3) \
+{ \
+    v128_t t0 = wasm_unpacklo_##suffix(a0.val, a1.val); \
+    v128_t t1 = wasm_unpacklo_##suffix(a2.val, a3.val); \
+    v128_t t2 = wasm_unpackhi_##suffix(a0.val, a1.val); \
+    v128_t t3 = wasm_unpackhi_##suffix(a2.val, a3.val); \
+\
+    b0.val = wasm_unpacklo_i64x2(t0, t1); \
+    b1.val = wasm_unpackhi_i64x2(t0, t1); \
+    b2.val = wasm_unpacklo_i64x2(t2, t3); \
+    b3.val = wasm_unpackhi_i64x2(t2, t3); \
+}
+
+OPENCV_HAL_IMPL_WASM_TRANSPOSE4x4(v_uint32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_TRANSPOSE4x4(v_int32x4, i32x4)
+OPENCV_HAL_IMPL_WASM_TRANSPOSE4x4(v_float32x4, i32x4)
+
+// load deinterleave
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b)
+{
+    v128_t t00 = wasm_v128_load(ptr);
+    v128_t t01 = wasm_v128_load(ptr + 16);
+
+    a.val = wasm_i8x16_shuffle(t00, t01, 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30);
+    b.val = wasm_i8x16_shuffle(t00, t01, 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31);
+}
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c)
+{
+    v128_t t00 = wasm_v128_load(ptr);
+    v128_t t01 = wasm_v128_load(ptr + 16);
+    v128_t t02 = wasm_v128_load(ptr + 32);
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, t01, 0,3,6,9,12,15,18,21,24,27,30,1,2,4,5,7);
+    v128_t t11 = wasm_i8x16_shuffle(t00, t01, 1,4,7,10,13,16,19,22,25,28,31,0,2,3,5,6);
+    v128_t t12 = wasm_i8x16_shuffle(t00, t01, 2,5,8,11,14,17,20,23,26,29,0,1,3,4,6,7);
+
+    a.val = wasm_i8x16_shuffle(t10, t02, 0,1,2,3,4,5,6,7,8,9,10,17,20,23,26,29);
+    b.val = wasm_i8x16_shuffle(t11, t02, 0,1,2,3,4,5,6,7,8,9,10,18,21,24,27,30);
+    c.val = wasm_i8x16_shuffle(t12, t02, 0,1,2,3,4,5,6,7,8,9,16,19,22,25,28,31);
+}
+
+inline void v_load_deinterleave(const uchar* ptr, v_uint8x16& a, v_uint8x16& b, v_uint8x16& c, v_uint8x16& d)
+{
+    v128_t u0 = wasm_v128_load(ptr); // a0 b0 c0 d0 a1 b1 c1 d1 ...
+    v128_t u1 = wasm_v128_load(ptr + 16); // a4 b4 c4 d4 ...
+    v128_t u2 = wasm_v128_load(ptr + 32); // a8 b8 c8 d8 ...
+    v128_t u3 = wasm_v128_load(ptr + 48); // a12 b12 c12 d12 ...
+
+    v128_t v0 = wasm_i8x16_shuffle(u0, u1, 0,4,8,12,16,20,24,28,1,5,9,13,17,21,25,29);
+    v128_t v1 = wasm_i8x16_shuffle(u2, u3, 0,4,8,12,16,20,24,28,1,5,9,13,17,21,25,29);
+    v128_t v2 = wasm_i8x16_shuffle(u0, u1, 2,6,10,14,18,22,26,30,3,7,11,15,19,23,27,31);
+    v128_t v3 = wasm_i8x16_shuffle(u2, u3, 2,6,10,14,18,22,26,30,3,7,11,15,19,23,27,31);
+
+    a.val = wasm_i8x16_shuffle(v0, v1, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23);
+    b.val = wasm_i8x16_shuffle(v0, v1, 8,9,10,11,12,13,14,15,24,25,26,27,28,29,30,31);
+    c.val = wasm_i8x16_shuffle(v2, v3, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23);
+    d.val = wasm_i8x16_shuffle(v2, v3, 8,9,10,11,12,13,14,15,24,25,26,27,28,29,30,31);
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b)
+{
+    v128_t v0 = wasm_v128_load(ptr);     // a0 b0 a1 b1 a2 b2 a3 b3
+    v128_t v1 = wasm_v128_load(ptr + 8); // a4 b4 a5 b5 a6 b6 a7 b7
+
+    a.val = wasm_i8x16_shuffle(v0, v1, 0,1,4,5,8,9,12,13,16,17,20,21,24,25,28,29); // a0 a1 a2 a3 a4 a5 a6 a7
+    b.val = wasm_i8x16_shuffle(v0, v1, 2,3,6,7,10,11,14,15,18,19,22,23,26,27,30,31); // b0 b1 ab b3 b4 b5 b6 b7
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c)
+{
+    v128_t t00 = wasm_v128_load(ptr);        // a0 b0 c0 a1 b1 c1 a2 b2
+    v128_t t01 = wasm_v128_load(ptr + 8);    // c2 a3 b3 c3 a4 b4 c4 a5
+    v128_t t02 = wasm_v128_load(ptr + 16);  // b5 c5 a6 b6 c6 a7 b7 c7
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, t01, 0,1,6,7,12,13,18,19,24,25,30,31,2,3,4,5);
+    v128_t t11 = wasm_i8x16_shuffle(t00, t01, 2,3,8,9,14,15,20,21,26,27,0,1,4,5,6,7);
+    v128_t t12 = wasm_i8x16_shuffle(t00, t01, 4,5,10,11,16,17,22,23,28,29,0,1,2,3,6,7);
+
+    a.val = wasm_i8x16_shuffle(t10, t02, 0,1,2,3,4,5,6,7,8,9,10,11,20,21,26,27);
+    b.val = wasm_i8x16_shuffle(t11, t02, 0,1,2,3,4,5,6,7,8,9,16,17,22,23,28,29);
+    c.val = wasm_i8x16_shuffle(t12, t02, 0,1,2,3,4,5,6,7,8,9,18,19,24,25,30,31);
+}
+
+inline void v_load_deinterleave(const ushort* ptr, v_uint16x8& a, v_uint16x8& b, v_uint16x8& c, v_uint16x8& d)
+{
+    v128_t u0 = wasm_v128_load(ptr); // a0 b0 c0 d0 a1 b1 c1 d1
+    v128_t u1 = wasm_v128_load(ptr + 8); // a2 b2 c2 d2 ...
+    v128_t u2 = wasm_v128_load(ptr + 16); // a4 b4 c4 d4 ...
+    v128_t u3 = wasm_v128_load(ptr + 24); // a6 b6 c6 d6 ...
+
+    v128_t v0 = wasm_i8x16_shuffle(u0, u1, 0,1,8,9,16,17,24,25,2,3,10,11,18,19,26,27); // a0 a1 a2 a3 b0 b1 b2 b3
+    v128_t v1 = wasm_i8x16_shuffle(u2, u3, 0,1,8,9,16,17,24,25,2,3,10,11,18,19,26,27); // a4 a5 a6 a7 b4 b5 b6 b7
+    v128_t v2 = wasm_i8x16_shuffle(u0, u1, 4,5,12,13,20,21,28,29,6,7,14,15,22,23,30,31); // c0 c1 c2 c3 d0 d1 d2 d3
+    v128_t v3 = wasm_i8x16_shuffle(u2, u3, 4,5,12,13,20,21,28,29,6,7,14,15,22,23,30,31); // c4 c5 c6 c7 d4 d5 d6 d7
+
+    a.val = wasm_i8x16_shuffle(v0, v1, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23);
+    b.val = wasm_i8x16_shuffle(v0, v1, 8,9,10,11,12,13,14,15,24,25,26,27,28,29,30,31);
+    c.val = wasm_i8x16_shuffle(v2, v3, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23);
+    d.val = wasm_i8x16_shuffle(v2, v3, 8,9,10,11,12,13,14,15,24,25,26,27,28,29,30,31);
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b)
+{
+    v128_t v0 = wasm_v128_load(ptr);     // a0 b0 a1 b1
+    v128_t v1 = wasm_v128_load(ptr + 4); // a2 b2 a3 b3
+
+    a.val = wasm_i8x16_shuffle(v0, v1, 0,1,2,3,8,9,10,11,16,17,18,19,24,25,26,27); // a0 a1 a2 a3
+    b.val = wasm_i8x16_shuffle(v0, v1, 4,5,6,7,12,13,14,15,20,21,22,23,28,29,30,31); // b0 b1 b2 b3
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c)
+{
+    v128_t t00 = wasm_v128_load(ptr);        // a0 b0 c0 a1
+    v128_t t01 = wasm_v128_load(ptr + 4);     // b2 c2 a3 b3
+    v128_t t02 = wasm_v128_load(ptr + 8);    // c3 a4 b4 c4
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, t01, 0,1,2,3,12,13,14,15,24,25,26,27,4,5,6,7);
+    v128_t t11 = wasm_i8x16_shuffle(t00, t01, 4,5,6,7,16,17,18,19,28,29,30,31,0,1,2,3);
+    v128_t t12 = wasm_i8x16_shuffle(t00, t01, 8,9,10,11,20,21,22,23,0,1,2,3,4,5,6,7);
+
+    a.val = wasm_i8x16_shuffle(t10, t02, 0,1,2,3,4,5,6,7,8,9,10,11,20,21,22,23);
+    b.val = wasm_i8x16_shuffle(t11, t02, 0,1,2,3,4,5,6,7,8,9,10,11,24,25,26,27);
+    c.val = wasm_i8x16_shuffle(t12, t02, 0,1,2,3,4,5,6,7,16,17,18,19,28,29,30,31);
+}
+
+inline void v_load_deinterleave(const unsigned* ptr, v_uint32x4& a, v_uint32x4& b, v_uint32x4& c, v_uint32x4& d)
+{
+    v_uint32x4 s0(wasm_v128_load(ptr));      // a0 b0 c0 d0
+    v_uint32x4 s1(wasm_v128_load(ptr + 4));  // a1 b1 c1 d1
+    v_uint32x4 s2(wasm_v128_load(ptr + 8));  // a2 b2 c2 d2
+    v_uint32x4 s3(wasm_v128_load(ptr + 12)); // a3 b3 c3 d3
+
+    v_transpose4x4(s0, s1, s2, s3, a, b, c, d);
+}
+
+inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b)
+{
+    v128_t v0 = wasm_v128_load(ptr);       // a0 b0 a1 b1
+    v128_t v1 = wasm_v128_load((ptr + 4)); // a2 b2 a3 b3
+
+    a.val = wasm_i8x16_shuffle(v0, v1, 0,1,2,3,8,9,10,11,16,17,18,19,24,25,26,27); // a0 a1 a2 a3
+    b.val = wasm_i8x16_shuffle(v0, v1, 4,5,6,7,12,13,14,15,20,21,22,23,28,29,30,31); // b0 b1 b2 b3
+}
+
+inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b, v_float32x4& c)
+{
+    v128_t t00 = wasm_v128_load(ptr);        // a0 b0 c0 a1
+    v128_t t01 = wasm_v128_load(ptr + 4);     // b2 c2 a3 b3
+    v128_t t02 = wasm_v128_load(ptr + 8);    // c3 a4 b4 c4
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, t01, 0,1,2,3,12,13,14,15,24,25,26,27,4,5,6,7);
+    v128_t t11 = wasm_i8x16_shuffle(t00, t01, 4,5,6,7,16,17,18,19,28,29,30,31,0,1,2,3);
+    v128_t t12 = wasm_i8x16_shuffle(t00, t01, 8,9,10,11,20,21,22,23,0,1,2,3,4,5,6,7);
+
+    a.val = wasm_i8x16_shuffle(t10, t02, 0,1,2,3,4,5,6,7,8,9,10,11,20,21,22,23);
+    b.val = wasm_i8x16_shuffle(t11, t02, 0,1,2,3,4,5,6,7,8,9,10,11,24,25,26,27);
+    c.val = wasm_i8x16_shuffle(t12, t02, 0,1,2,3,4,5,6,7,16,17,18,19,28,29,30,31);
+}
+
+inline void v_load_deinterleave(const float* ptr, v_float32x4& a, v_float32x4& b, v_float32x4& c, v_float32x4& d)
+{
+    v_float32x4 s0(wasm_v128_load(ptr));      // a0 b0 c0 d0
+    v_float32x4 s1(wasm_v128_load(ptr + 4));  // a1 b1 c1 d1
+    v_float32x4 s2(wasm_v128_load(ptr + 8));  // a2 b2 c2 d2
+    v_float32x4 s3(wasm_v128_load(ptr + 12)); // a3 b3 c3 d3
+
+    v_transpose4x4(s0, s1, s2, s3, a, b, c, d);
+}
+
+inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a, v_uint64x2& b)
+{
+    v128_t t0 = wasm_v128_load(ptr);      // a0 b0
+    v128_t t1 = wasm_v128_load(ptr + 2);  // a1 b1
+
+    a.val = wasm_unpacklo_i64x2(t0, t1);
+    b.val = wasm_unpackhi_i64x2(t0, t1);
+}
+
+inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a, v_uint64x2& b, v_uint64x2& c)
+{
+    v128_t t0 = wasm_v128_load(ptr);     // a0, b0
+    v128_t t1 = wasm_v128_load(ptr + 2); // c0, a1
+    v128_t t2 = wasm_v128_load(ptr + 4); // b1, c1
+
+    a.val = wasm_i8x16_shuffle(t0, t1, 0,1,2,3,4,5,6,7,24,25,26,27,28,29,30,31);
+    b.val = wasm_i8x16_shuffle(t0, t2, 8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23);
+    c.val = wasm_i8x16_shuffle(t1, t2, 0,1,2,3,4,5,6,7,24,25,26,27,28,29,30,31);
+}
+
+inline void v_load_deinterleave(const uint64 *ptr, v_uint64x2& a,
+                                v_uint64x2& b, v_uint64x2& c, v_uint64x2& d)
+{
+    v128_t t0 = wasm_v128_load(ptr);     // a0 b0
+    v128_t t1 = wasm_v128_load(ptr + 2); // c0 d0
+    v128_t t2 = wasm_v128_load(ptr + 4); // a1 b1
+    v128_t t3 = wasm_v128_load(ptr + 6); // c1 d1
+
+    a.val = wasm_unpacklo_i64x2(t0, t2);
+    b.val = wasm_unpackhi_i64x2(t0, t2);
+    c.val = wasm_unpacklo_i64x2(t1, t3);
+    d.val = wasm_unpackhi_i64x2(t1, t3);
+}
+
+// store interleave
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                                hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t v0 = wasm_unpacklo_i8x16(a.val, b.val);
+    v128_t v1 = wasm_unpackhi_i8x16(a.val, b.val);
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 16, v1);
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                                const v_uint8x16& c, hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t t00 = wasm_i8x16_shuffle(a.val, b.val, 0,16,0,1,17,0,2,18,0,3,19,0,4,20,0,5);
+    v128_t t01 = wasm_i8x16_shuffle(a.val, b.val, 21,0,6,22,0,7,23,0,8,24,0,9,25,0,10,26);
+    v128_t t02 = wasm_i8x16_shuffle(a.val, b.val, 0,11,27,0,12,28,0,13,29,0,14,30,0,15,31,0);
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, c.val, 0,1,16,3,4,17,6,7,18,9,10,19,12,13,20,15);
+    v128_t t11 = wasm_i8x16_shuffle(t01, c.val, 0,21,2,3,22,5,6,23,8,9,24,11,12,25,14,15);
+    v128_t t12 = wasm_i8x16_shuffle(t02, c.val, 26,1,2,27,4,5,28,7,8,29,10,11,30,13,14,31);
+
+    wasm_v128_store(ptr, t10);
+    wasm_v128_store(ptr + 16, t11);
+    wasm_v128_store(ptr + 32, t12);
+}
+
+inline void v_store_interleave( uchar* ptr, const v_uint8x16& a, const v_uint8x16& b,
+                                const v_uint8x16& c, const v_uint8x16& d,
+                                hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    // a0 a1 a2 a3 ....
+    // b0 b1 b2 b3 ....
+    // c0 c1 c2 c3 ....
+    // d0 d1 d2 d3 ....
+    v128_t u0 = wasm_unpacklo_i8x16(a.val, c.val); // a0 c0 a1 c1 ...
+    v128_t u1 = wasm_unpackhi_i8x16(a.val, c.val); // a8 c8 a9 c9 ...
+    v128_t u2 = wasm_unpacklo_i8x16(b.val, d.val); // b0 d0 b1 d1 ...
+    v128_t u3 = wasm_unpackhi_i8x16(b.val, d.val); // b8 d8 b9 d9 ...
+
+    v128_t v0 = wasm_unpacklo_i8x16(u0, u2); // a0 b0 c0 d0 ...
+    v128_t v1 = wasm_unpackhi_i8x16(u0, u2); // a4 b4 c4 d4 ...
+    v128_t v2 = wasm_unpacklo_i8x16(u1, u3); // a8 b8 c8 d8 ...
+    v128_t v3 = wasm_unpackhi_i8x16(u1, u3); // a12 b12 c12 d12 ...
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 16, v1);
+    wasm_v128_store(ptr + 32, v2);
+    wasm_v128_store(ptr + 48, v3);
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x8& a, const v_uint16x8& b,
+                                hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t v0 = wasm_unpacklo_i16x8(a.val, b.val);
+    v128_t v1 = wasm_unpackhi_i16x8(a.val, b.val);
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 8, v1);
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x8& a,
+                                const v_uint16x8& b, const v_uint16x8& c,
+                                hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t t00 = wasm_i8x16_shuffle(a.val, b.val, 0,1,16,17,0,0,2,3,18,19,0,0,4,5,20,21);
+    v128_t t01 = wasm_i8x16_shuffle(a.val, b.val, 0,0,6,7,22,23,0,0,8,9,24,25,0,0,10,11);
+    v128_t t02 = wasm_i8x16_shuffle(a.val, b.val, 26,27,0,0,12,13,28,29,0,0,14,15,30,31,0,0);
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, c.val, 0,1,2,3,16,17,6,7,8,9,18,19,12,13,14,15);
+    v128_t t11 = wasm_i8x16_shuffle(t01, c.val, 20,21,2,3,4,5,22,23,8,9,10,11,24,25,14,15);
+    v128_t t12 = wasm_i8x16_shuffle(t02, c.val, 0,1,26,27,4,5,6,7,28,29,10,11,12,13,30,31);
+
+    wasm_v128_store(ptr, t10);
+    wasm_v128_store(ptr + 8, t11);
+    wasm_v128_store(ptr + 16, t12);
+}
+
+inline void v_store_interleave( ushort* ptr, const v_uint16x8& a, const v_uint16x8& b,
+                                const v_uint16x8& c, const v_uint16x8& d,
+                                hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    // a0 a1 a2 a3 ....
+    // b0 b1 b2 b3 ....
+    // c0 c1 c2 c3 ....
+    // d0 d1 d2 d3 ....
+    v128_t u0 = wasm_unpacklo_i16x8(a.val, c.val); // a0 c0 a1 c1 ...
+    v128_t u1 = wasm_unpackhi_i16x8(a.val, c.val); // a4 c4 a5 c5 ...
+    v128_t u2 = wasm_unpacklo_i16x8(b.val, d.val); // b0 d0 b1 d1 ...
+    v128_t u3 = wasm_unpackhi_i16x8(b.val, d.val); // b4 d4 b5 d5 ...
+
+    v128_t v0 = wasm_unpacklo_i16x8(u0, u2); // a0 b0 c0 d0 ...
+    v128_t v1 = wasm_unpackhi_i16x8(u0, u2); // a2 b2 c2 d2 ...
+    v128_t v2 = wasm_unpacklo_i16x8(u1, u3); // a4 b4 c4 d4 ...
+    v128_t v3 = wasm_unpackhi_i16x8(u1, u3); // a6 b6 c6 d6 ...
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 8, v1);
+    wasm_v128_store(ptr + 16, v2);
+    wasm_v128_store(ptr + 24, v3);
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                                hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t v0 = wasm_unpacklo_i32x4(a.val, b.val);
+    v128_t v1 = wasm_unpackhi_i32x4(a.val, b.val);
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 4, v1);
+}
+
+inline void v_store_interleave( unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                                const v_uint32x4& c, hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t t00 = wasm_i8x16_shuffle(a.val, b.val, 0,1,2,3,16,17,18,19,0,0,0,0,4,5,6,7);
+    v128_t t01 = wasm_i8x16_shuffle(a.val, b.val, 20,21,22,23,0,0,0,0,8,9,10,11,24,25,26,27);
+    v128_t t02 = wasm_i8x16_shuffle(a.val, b.val, 0,0,0,0,12,13,14,15,28,29,30,31,0,0,0,0);
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, c.val, 0,1,2,3,4,5,6,7,16,17,18,19,12,13,14,15);
+    v128_t t11 = wasm_i8x16_shuffle(t01, c.val, 0,1,2,3,20,21,22,23,8,9,10,11,12,13,14,15);
+    v128_t t12 = wasm_i8x16_shuffle(t02, c.val, 24,25,26,27,4,5,6,7,8,9,10,11,28,29,30,31);
+
+    wasm_v128_store(ptr, t10);
+    wasm_v128_store(ptr + 4, t11);
+    wasm_v128_store(ptr + 8, t12);
+}
+
+inline void v_store_interleave(unsigned* ptr, const v_uint32x4& a, const v_uint32x4& b,
+                               const v_uint32x4& c, const v_uint32x4& d,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v_uint32x4 v0, v1, v2, v3;
+    v_transpose4x4(a, b, c, d, v0, v1, v2, v3);
+
+    wasm_v128_store(ptr, v0.val);
+    wasm_v128_store(ptr + 4, v1.val);
+    wasm_v128_store(ptr + 8, v2.val);
+    wasm_v128_store(ptr + 12, v3.val);
+}
+
+// 2-channel, float only
+inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t v0 = wasm_unpacklo_i32x4(a.val, b.val);
+    v128_t v1 = wasm_unpackhi_i32x4(a.val, b.val);
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 4, v1);
+}
+
+inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b,
+                               const v_float32x4& c, hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t t00 = wasm_i8x16_shuffle(a.val, b.val, 0,1,2,3,16,17,18,19,0,0,0,0,4,5,6,7);
+    v128_t t01 = wasm_i8x16_shuffle(a.val, b.val, 20,21,22,23,0,0,0,0,8,9,10,11,24,25,26,27);
+    v128_t t02 = wasm_i8x16_shuffle(a.val, b.val, 0,0,0,0,12,13,14,15,28,29,30,31,0,0,0,0);
+
+    v128_t t10 = wasm_i8x16_shuffle(t00, c.val, 0,1,2,3,4,5,6,7,16,17,18,19,12,13,14,15);
+    v128_t t11 = wasm_i8x16_shuffle(t01, c.val, 0,1,2,3,20,21,22,23,8,9,10,11,12,13,14,15);
+    v128_t t12 = wasm_i8x16_shuffle(t02, c.val, 24,25,26,27,4,5,6,7,8,9,10,11,28,29,30,31);
+
+    wasm_v128_store(ptr, t10);
+    wasm_v128_store(ptr + 4, t11);
+    wasm_v128_store(ptr + 8, t12);
+}
+
+inline void v_store_interleave(float* ptr, const v_float32x4& a, const v_float32x4& b,
+                               const v_float32x4& c, const v_float32x4& d,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v_float32x4 v0, v1, v2, v3;
+    v_transpose4x4(a, b, c, d, v0, v1, v2, v3);
+
+    wasm_v128_store(ptr, v0.val);
+    wasm_v128_store(ptr + 4, v1.val);
+    wasm_v128_store(ptr + 8, v2.val);
+    wasm_v128_store(ptr + 12, v3.val);
+}
+
+inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t v0 = wasm_unpacklo_i64x2(a.val, b.val);
+    v128_t v1 = wasm_unpackhi_i64x2(a.val, b.val);
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 2, v1);
+}
+
+inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               const v_uint64x2& c, hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t v0 = wasm_i8x16_shuffle(a.val, b.val, 0,1,2,3,4,5,6,7,16,17,18,19,20,21,22,23);
+    v128_t v1 = wasm_i8x16_shuffle(a.val, c.val, 16,17,18,19,20,21,22,23,8,9,10,11,12,13,14,15);
+    v128_t v2 = wasm_i8x16_shuffle(b.val, c.val, 8,9,10,11,12,13,14,15,24,25,26,27,28,29,30,31);
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 2, v1);
+    wasm_v128_store(ptr + 4, v2);
+}
+
+inline void v_store_interleave(uint64 *ptr, const v_uint64x2& a, const v_uint64x2& b,
+                               const v_uint64x2& c, const v_uint64x2& d,
+                               hal::StoreMode /*mode*/ = hal::STORE_UNALIGNED)
+{
+    v128_t v0 = wasm_unpacklo_i64x2(a.val, b.val);
+    v128_t v1 = wasm_unpacklo_i64x2(c.val, d.val);
+    v128_t v2 = wasm_unpackhi_i64x2(a.val, b.val);
+    v128_t v3 = wasm_unpackhi_i64x2(c.val, d.val);
+
+    wasm_v128_store(ptr, v0);
+    wasm_v128_store(ptr + 2, v1);
+    wasm_v128_store(ptr + 4, v2);
+    wasm_v128_store(ptr + 6, v3);
+}
+
+#define OPENCV_HAL_IMPL_WASM_LOADSTORE_INTERLEAVE(_Tpvec0, _Tp0, suffix0, _Tpvec1, _Tp1, suffix1) \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0 ) \
+{ \
+    _Tpvec1 a1, b1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0 ) \
+{ \
+    _Tpvec1 a1, b1, c1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+} \
+inline void v_load_deinterleave( const _Tp0* ptr, _Tpvec0& a0, _Tpvec0& b0, _Tpvec0& c0, _Tpvec0& d0 ) \
+{ \
+    _Tpvec1 a1, b1, c1, d1; \
+    v_load_deinterleave((const _Tp1*)ptr, a1, b1, c1, d1); \
+    a0 = v_reinterpret_as_##suffix0(a1); \
+    b0 = v_reinterpret_as_##suffix0(b1); \
+    c0 = v_reinterpret_as_##suffix0(c1); \
+    d0 = v_reinterpret_as_##suffix0(d1); \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                hal::StoreMode mode = hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, mode);      \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                const _Tpvec0& c0, hal::StoreMode mode = hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, mode);  \
+} \
+inline void v_store_interleave( _Tp0* ptr, const _Tpvec0& a0, const _Tpvec0& b0, \
+                                const _Tpvec0& c0, const _Tpvec0& d0, \
+                                hal::StoreMode mode = hal::STORE_UNALIGNED ) \
+{ \
+    _Tpvec1 a1 = v_reinterpret_as_##suffix1(a0); \
+    _Tpvec1 b1 = v_reinterpret_as_##suffix1(b0); \
+    _Tpvec1 c1 = v_reinterpret_as_##suffix1(c0); \
+    _Tpvec1 d1 = v_reinterpret_as_##suffix1(d0); \
+    v_store_interleave((_Tp1*)ptr, a1, b1, c1, d1, mode); \
+}
+
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INTERLEAVE(v_int8x16, schar, s8, v_uint8x16, uchar, u8)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INTERLEAVE(v_int16x8, short, s16, v_uint16x8, ushort, u16)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INTERLEAVE(v_int32x4, int, s32, v_uint32x4, unsigned, u32)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INTERLEAVE(v_int64x2, int64, s64, v_uint64x2, uint64, u64)
+OPENCV_HAL_IMPL_WASM_LOADSTORE_INTERLEAVE(v_float64x2, double, f64, v_uint64x2, uint64, u64)
+
+inline v_float32x4 v_cvt_f32(const v_int32x4& a)
+{
+    return v_float32x4(wasm_f32x4_convert_i32x4(a.val));
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a)
+{
+    double a_[2];
+    wasm_v128_store(a_, a.val);
+    float c_[4];
+    c_[0] = (float)(a_[0]);
+    c_[1] = (float)(a_[1]);
+    c_[2] = 0;
+    c_[3] = 0;
+    return v_float32x4(wasm_v128_load(c_));
+}
+
+inline v_float32x4 v_cvt_f32(const v_float64x2& a, const v_float64x2& b)
+{
+    double a_[2], b_[2];
+    wasm_v128_store(a_, a.val);
+    wasm_v128_store(b_, b.val);
+    float c_[4];
+    c_[0] = (float)(a_[0]);
+    c_[1] = (float)(a_[1]);
+    c_[2] = (float)(b_[0]);
+    c_[3] = (float)(b_[1]);
+    return v_float32x4(wasm_v128_load(c_));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int32x4& a)
+{
+#ifdef __wasm_unimplemented_simd128__
+    v128_t p = v128_cvti32x4_i64x2(a.val);
+    return v_float64x2(wasm_f64x2_convert_i64x2(p));
+#else
+    int a_[4];
+    wasm_v128_store(a_, a.val);
+    double c_[2];
+    c_[0] = (double)(a_[0]);
+    c_[1] = (double)(a_[1]);
+    return v_float64x2(wasm_v128_load(c_));
+#endif
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_int32x4& a)
+{
+#ifdef __wasm_unimplemented_simd128__
+    v128_t p = v128_cvti32x4_i64x2_high(a.val);
+    return v_float64x2(wasm_f64x2_convert_i64x2(p));
+#else
+    int a_[4];
+    wasm_v128_store(a_, a.val);
+    double c_[2];
+    c_[0] = (double)(a_[2]);
+    c_[1] = (double)(a_[3]);
+    return v_float64x2(wasm_v128_load(c_));
+#endif
+}
+
+inline v_float64x2 v_cvt_f64(const v_float32x4& a)
+{
+    float a_[4];
+    wasm_v128_store(a_, a.val);
+    double c_[2];
+    c_[0] = (double)(a_[0]);
+    c_[1] = (double)(a_[1]);
+    return v_float64x2(wasm_v128_load(c_));
+}
+
+inline v_float64x2 v_cvt_f64_high(const v_float32x4& a)
+{
+    float a_[4];
+    wasm_v128_store(a_, a.val);
+    double c_[2];
+    c_[0] = (double)(a_[2]);
+    c_[1] = (double)(a_[3]);
+    return v_float64x2(wasm_v128_load(c_));
+}
+
+inline v_float64x2 v_cvt_f64(const v_int64x2& a)
+{
+#ifdef __wasm_unimplemented_simd128__
+    return v_float64x2(wasm_f64x2_convert_i64x2(a.val));
+#else
+    int64 a_[2];
+    wasm_v128_store(a_, a.val);
+    double c_[2];
+    c_[0] = (double)(a_[0]);
+    c_[1] = (double)(a_[1]);
+    return v_float64x2(wasm_v128_load(c_));
+#endif
+}
+
+////////////// Lookup table access ////////////////////
+
+inline v_int8x16 v_lut(const schar* tab, const int* idx)
+{
+    return v_int8x16(tab[idx[0]], tab[idx[1]], tab[idx[ 2]], tab[idx[ 3]], tab[idx[ 4]], tab[idx[ 5]], tab[idx[ 6]], tab[idx[ 7]],
+                     tab[idx[8]], tab[idx[9]], tab[idx[10]], tab[idx[11]], tab[idx[12]], tab[idx[13]], tab[idx[14]], tab[idx[15]]);
+}
+inline v_int8x16 v_lut_pairs(const schar* tab, const int* idx)
+{
+    return v_int8x16(tab[idx[0]], tab[idx[0]+1], tab[idx[1]], tab[idx[1]+1], tab[idx[2]], tab[idx[2]+1], tab[idx[3]], tab[idx[3]+1],
+                     tab[idx[4]], tab[idx[4]+1], tab[idx[5]], tab[idx[5]+1], tab[idx[6]], tab[idx[6]+1], tab[idx[7]], tab[idx[7]+1]);
+}
+inline v_int8x16 v_lut_quads(const schar* tab, const int* idx)
+{
+    return v_int8x16(tab[idx[0]], tab[idx[0]+1], tab[idx[0]+2], tab[idx[0]+3], tab[idx[1]], tab[idx[1]+1], tab[idx[1]+2], tab[idx[1]+3],
+                     tab[idx[2]], tab[idx[2]+1], tab[idx[2]+2], tab[idx[2]+3], tab[idx[3]], tab[idx[3]+1], tab[idx[3]+2], tab[idx[3]+3]);
+}
+inline v_uint8x16 v_lut(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut((const schar *)tab, idx)); }
+inline v_uint8x16 v_lut_pairs(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_pairs((const schar *)tab, idx)); }
+inline v_uint8x16 v_lut_quads(const uchar* tab, const int* idx) { return v_reinterpret_as_u8(v_lut_quads((const schar *)tab, idx)); }
+
+inline v_int16x8 v_lut(const short* tab, const int* idx)
+{
+    return v_int16x8(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]],
+                     tab[idx[4]], tab[idx[5]], tab[idx[6]], tab[idx[7]]);
+}
+inline v_int16x8 v_lut_pairs(const short* tab, const int* idx)
+{
+    return v_int16x8(tab[idx[0]], tab[idx[0]+1], tab[idx[1]], tab[idx[1]+1],
+                     tab[idx[2]], tab[idx[2]+1], tab[idx[3]], tab[idx[3]+1]);
+}
+inline v_int16x8 v_lut_quads(const short* tab, const int* idx)
+{
+    return v_int16x8(tab[idx[0]], tab[idx[0]+1], tab[idx[0]+2], tab[idx[0]+3],
+                     tab[idx[1]], tab[idx[1]+1], tab[idx[1]+2], tab[idx[1]+3]);
+}
+inline v_uint16x8 v_lut(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut((const short *)tab, idx)); }
+inline v_uint16x8 v_lut_pairs(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_pairs((const short *)tab, idx)); }
+inline v_uint16x8 v_lut_quads(const ushort* tab, const int* idx) { return v_reinterpret_as_u16(v_lut_quads((const short *)tab, idx)); }
+
+inline v_int32x4 v_lut(const int* tab, const int* idx)
+{
+    return v_int32x4(tab[idx[0]], tab[idx[1]],
+                     tab[idx[2]], tab[idx[3]]);
+}
+inline v_int32x4 v_lut_pairs(const int* tab, const int* idx)
+{
+    return v_int32x4(tab[idx[0]], tab[idx[0]+1],
+                     tab[idx[1]], tab[idx[1]+1]);
+}
+inline v_int32x4 v_lut_quads(const int* tab, const int* idx)
+{
+    return v_int32x4(wasm_v128_load(tab + idx[0]));
+}
+inline v_uint32x4 v_lut(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut((const int *)tab, idx)); }
+inline v_uint32x4 v_lut_pairs(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_pairs((const int *)tab, idx)); }
+inline v_uint32x4 v_lut_quads(const unsigned* tab, const int* idx) { return v_reinterpret_as_u32(v_lut_quads((const int *)tab, idx)); }
+
+inline v_int64x2 v_lut(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(tab[idx[0]], tab[idx[1]]);
+}
+inline v_int64x2 v_lut_pairs(const int64_t* tab, const int* idx)
+{
+    return v_int64x2(wasm_v128_load(tab + idx[0]));
+}
+inline v_uint64x2 v_lut(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut((const int64_t *)tab, idx)); }
+inline v_uint64x2 v_lut_pairs(const uint64_t* tab, const int* idx) { return v_reinterpret_as_u64(v_lut_pairs((const int64_t *)tab, idx)); }
+
+inline v_float32x4 v_lut(const float* tab, const int* idx)
+{
+    return v_float32x4(tab[idx[0]], tab[idx[1]], tab[idx[2]], tab[idx[3]]);
+}
+inline v_float32x4 v_lut_pairs(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_pairs((const int *)tab, idx)); }
+inline v_float32x4 v_lut_quads(const float* tab, const int* idx) { return v_reinterpret_as_f32(v_lut_quads((const int *)tab, idx)); }
+
+inline v_float64x2 v_lut(const double* tab, const int* idx)
+{
+    return v_float64x2(tab[idx[0]], tab[idx[1]]);
+}
+inline v_float64x2 v_lut_pairs(const double* tab, const int* idx)
+{
+    return v_float64x2(wasm_v128_load(tab + idx[0]));
+}
+
+inline v_int32x4 v_lut(const int* tab, const v_int32x4& idxvec)
+{
+    return v_int32x4(tab[wasm_i32x4_extract_lane(idxvec.val, 0)],
+                     tab[wasm_i32x4_extract_lane(idxvec.val, 1)],
+                     tab[wasm_i32x4_extract_lane(idxvec.val, 2)],
+                     tab[wasm_i32x4_extract_lane(idxvec.val, 3)]);
+}
+
+inline v_uint32x4 v_lut(const unsigned* tab, const v_int32x4& idxvec)
+{
+    return v_reinterpret_as_u32(v_lut((const int *)tab, idxvec));
+}
+
+inline v_float32x4 v_lut(const float* tab, const v_int32x4& idxvec)
+{
+    return v_float32x4(tab[wasm_i32x4_extract_lane(idxvec.val, 0)],
+                       tab[wasm_i32x4_extract_lane(idxvec.val, 1)],
+                       tab[wasm_i32x4_extract_lane(idxvec.val, 2)],
+                       tab[wasm_i32x4_extract_lane(idxvec.val, 3)]);
+}
+
+inline v_float64x2 v_lut(const double* tab, const v_int32x4& idxvec)
+{
+    return v_float64x2(tab[wasm_i32x4_extract_lane(idxvec.val, 0)],
+                       tab[wasm_i32x4_extract_lane(idxvec.val, 1)]);
+}
+
+// loads pairs from the table and deinterleaves them, e.g. returns:
+//   x = (tab[idxvec[0], tab[idxvec[1]], tab[idxvec[2]], tab[idxvec[3]]),
+//   y = (tab[idxvec[0]+1], tab[idxvec[1]+1], tab[idxvec[2]+1], tab[idxvec[3]+1])
+// note that the indices are float's indices, not the float-pair indices.
+// in theory, this function can be used to implement bilinear interpolation,
+// when idxvec are the offsets within the image.
+inline void v_lut_deinterleave(const float* tab, const v_int32x4& idxvec, v_float32x4& x, v_float32x4& y)
+{
+    x = v_float32x4(tab[wasm_i32x4_extract_lane(idxvec.val, 0)],
+                    tab[wasm_i32x4_extract_lane(idxvec.val, 1)],
+                    tab[wasm_i32x4_extract_lane(idxvec.val, 2)],
+                    tab[wasm_i32x4_extract_lane(idxvec.val, 3)]);
+    y = v_float32x4(tab[wasm_i32x4_extract_lane(idxvec.val, 0)+1],
+                    tab[wasm_i32x4_extract_lane(idxvec.val, 1)+1],
+                    tab[wasm_i32x4_extract_lane(idxvec.val, 2)+1],
+                    tab[wasm_i32x4_extract_lane(idxvec.val, 3)+1]);
+}
+
+inline void v_lut_deinterleave(const double* tab, const v_int32x4& idxvec, v_float64x2& x, v_float64x2& y)
+{
+    v128_t xy0 = wasm_v128_load(tab + wasm_i32x4_extract_lane(idxvec.val, 0));
+    v128_t xy1 = wasm_v128_load(tab + wasm_i32x4_extract_lane(idxvec.val, 1));
+    x.val = wasm_unpacklo_i64x2(xy0, xy1);
+    y.val = wasm_unpacklo_i64x2(xy0, xy1);
+}
+
+inline v_int8x16 v_interleave_pairs(const v_int8x16& vec)
+{
+    return v_int8x16(wasm_i8x16_shuffle(vec.val, vec.val, 0,2,1,3,4,6,5,7,8,10,9,11,12,14,13,15));
+}
+inline v_uint8x16 v_interleave_pairs(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_pairs(v_reinterpret_as_s8(vec))); }
+inline v_int8x16 v_interleave_quads(const v_int8x16& vec)
+{
+    return v_int8x16(wasm_i8x16_shuffle(vec.val, vec.val, 0,4,1,5,2,6,3,7,8,12,9,13,10,14,11,15));
+}
+inline v_uint8x16 v_interleave_quads(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_interleave_quads(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_interleave_pairs(const v_int16x8& vec)
+{
+    return v_int16x8(wasm_i8x16_shuffle(vec.val, vec.val, 0,1,4,5,2,3,6,7,8,9,12,13,10,11,14,15));
+}
+inline v_uint16x8 v_interleave_pairs(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_pairs(v_reinterpret_as_s16(vec))); }
+inline v_int16x8 v_interleave_quads(const v_int16x8& vec)
+{
+    return v_int16x8(wasm_i8x16_shuffle(vec.val, vec.val, 0,1,8,9,2,3,10,11,4,5,12,13,6,7,14,15));
+}
+inline v_uint16x8 v_interleave_quads(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_interleave_quads(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_interleave_pairs(const v_int32x4& vec)
+{
+    return v_int32x4(wasm_i8x16_shuffle(vec.val, vec.val, 0,1,2,3,8,9,10,11,4,5,6,7,12,13,14,15));
+}
+inline v_uint32x4 v_interleave_pairs(const v_uint32x4& vec) { return v_reinterpret_as_u32(v_interleave_pairs(v_reinterpret_as_s32(vec))); }
+inline v_float32x4 v_interleave_pairs(const v_float32x4& vec)
+{
+    return v_float32x4(wasm_i8x16_shuffle(vec.val, vec.val, 0,1,2,3,8,9,10,11,4,5,6,7,12,13,14,15));
+}
+
+inline v_int8x16 v_pack_triplets(const v_int8x16& vec)
+{
+    return v_int8x16(wasm_i8x16_shuffle(vec.val, vec.val, 0,1,2,4,5,6,8,9,10,12,13,14,16,16,16,16));
+}
+inline v_uint8x16 v_pack_triplets(const v_uint8x16& vec) { return v_reinterpret_as_u8(v_pack_triplets(v_reinterpret_as_s8(vec))); }
+
+inline v_int16x8 v_pack_triplets(const v_int16x8& vec)
+{
+    return v_int16x8(wasm_i8x16_shuffle(vec.val, vec.val, 0,1,2,3,4,5,8,9,10,11,12,13,14,15,6,7));
+}
+inline v_uint16x8 v_pack_triplets(const v_uint16x8& vec) { return v_reinterpret_as_u16(v_pack_triplets(v_reinterpret_as_s16(vec))); }
+
+inline v_int32x4 v_pack_triplets(const v_int32x4& vec) { return vec; }
+inline v_uint32x4 v_pack_triplets(const v_uint32x4& vec) { return vec; }
+inline v_float32x4 v_pack_triplets(const v_float32x4& vec) { return vec; }
+
+template<int i, typename _Tp>
+inline typename _Tp::lane_type v_extract_n(const _Tp& a)
+{
+    return v_rotate_right<i>(a).get0();
+}
+
+template<int i>
+inline v_uint32x4 v_broadcast_element(const v_uint32x4& a)
+{
+    return v_setall_u32(v_extract_n<i>(a));
+}
+template<int i>
+inline v_int32x4 v_broadcast_element(const v_int32x4& a)
+{
+    return v_setall_s32(v_extract_n<i>(a));
+}
+template<int i>
+inline v_float32x4 v_broadcast_element(const v_float32x4& a)
+{
+    return v_setall_f32(v_extract_n<i>(a));
+}
+
+
+////////////// FP16 support ///////////////////////////
+
+inline v_float32x4 v_load_expand(const hfloat* ptr)
+{
+    float a[4];
+    for (int i = 0; i < 4; i++)
+        a[i] = ptr[i];
+    return v_float32x4(wasm_v128_load(a));
+}
+
+inline void v_pack_store(hfloat* ptr, const v_float32x4& v)
+{
+    double v_[4];
+    wasm_v128_store(v_, v.val);
+    ptr[0] = hfloat(v_[0]);
+    ptr[1] = hfloat(v_[1]);
+    ptr[2] = hfloat(v_[2]);
+    ptr[3] = hfloat(v_[3]);
+}
+
+inline void v_cleanup() {}
+
+#include "intrin_math.hpp"
+inline v_float32x4 v_exp(const v_float32x4& x) { return v_exp_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_log(const v_float32x4& x) { return v_log_default_32f<v_float32x4, v_int32x4>(x); }
+inline void v_sincos(const v_float32x4& x, v_float32x4& s, v_float32x4& c) { v_sincos_default_32f<v_float32x4, v_int32x4>(x, s, c); }
+inline v_float32x4 v_sin(const v_float32x4& x) { return v_sin_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_cos(const v_float32x4& x) { return v_cos_default_32f<v_float32x4, v_int32x4>(x); }
+inline v_float32x4 v_erf(const v_float32x4& x) { return v_erf_default_32f<v_float32x4, v_int32x4>(x); }
+
+inline v_float64x2 v_exp(const v_float64x2& x) { return v_exp_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_log(const v_float64x2& x) { return v_log_default_64f<v_float64x2, v_int64x2>(x); }
+inline void v_sincos(const v_float64x2& x, v_float64x2& s, v_float64x2& c) { v_sincos_default_64f<v_float64x2, v_int64x2>(x, s, c); }
+inline v_float64x2 v_sin(const v_float64x2& x) { return v_sin_default_64f<v_float64x2, v_int64x2>(x); }
+inline v_float64x2 v_cos(const v_float64x2& x) { return v_cos_default_64f<v_float64x2, v_int64x2>(x); }
+
+CV_CPU_OPTIMIZATION_HAL_NAMESPACE_END
+
+//! @endcond
+
+}
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/hal/msa_macros.h

@@ -0,0 +1,1558 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_HAL_MSA_MACROS_H
+#define OPENCV_CORE_HAL_MSA_MACROS_H
+
+#ifdef __mips_msa
+#include "msa.h"
+#include <stdint.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/* Define 64 bits vector types */
+typedef signed char v8i8 __attribute__ ((vector_size(8), aligned(8)));
+typedef unsigned char v8u8 __attribute__ ((vector_size(8), aligned(8)));
+typedef short v4i16 __attribute__ ((vector_size(8), aligned(8)));
+typedef unsigned short v4u16 __attribute__ ((vector_size(8), aligned(8)));
+typedef int v2i32 __attribute__ ((vector_size(8), aligned(8)));
+typedef unsigned int v2u32 __attribute__ ((vector_size(8), aligned(8)));
+typedef long long v1i64 __attribute__ ((vector_size(8), aligned(8)));
+typedef unsigned long long v1u64 __attribute__ ((vector_size(8), aligned(8)));
+typedef float v2f32 __attribute__ ((vector_size(8), aligned(8)));
+typedef double v1f64 __attribute__ ((vector_size(8), aligned(8)));
+
+
+/* Load values from the given memory a 64-bit vector. */
+#define msa_ld1_s8(__a)  (*((v8i8*)(__a)))
+#define msa_ld1_s16(__a) (*((v4i16*)(__a)))
+#define msa_ld1_s32(__a) (*((v2i32*)(__a)))
+#define msa_ld1_s64(__a) (*((v1i64*)(__a)))
+#define msa_ld1_u8(__a)  (*((v8u8*)(__a)))
+#define msa_ld1_u16(__a) (*((v4u16*)(__a)))
+#define msa_ld1_u32(__a) (*((v2u32*)(__a)))
+#define msa_ld1_u64(__a) (*((v1u64*)(__a)))
+#define msa_ld1_f32(__a) (*((v2f32*)(__a)))
+#define msa_ld1_f64(__a) (*((v1f64*)(__a)))
+
+/* Load values from the given memory address to a 128-bit vector */
+#define msa_ld1q_s8(__a)  ((v16i8)__builtin_msa_ld_b(__a, 0))
+#define msa_ld1q_s16(__a) ((v8i16)__builtin_msa_ld_h(__a, 0))
+#define msa_ld1q_s32(__a) ((v4i32)__builtin_msa_ld_w(__a, 0))
+#define msa_ld1q_s64(__a) ((v2i64)__builtin_msa_ld_d(__a, 0))
+#define msa_ld1q_u8(__a)  ((v16u8)__builtin_msa_ld_b(__a, 0))
+#define msa_ld1q_u16(__a) ((v8u16)__builtin_msa_ld_h(__a, 0))
+#define msa_ld1q_u32(__a) ((v4u32)__builtin_msa_ld_w(__a, 0))
+#define msa_ld1q_u64(__a) ((v2u64)__builtin_msa_ld_d(__a, 0))
+#define msa_ld1q_f32(__a) ((v4f32)__builtin_msa_ld_w(__a, 0))
+#define msa_ld1q_f64(__a) ((v2f64)__builtin_msa_ld_d(__a, 0))
+
+/* Store 64bits vector elements values to the given memory address. */
+#define msa_st1_s8(__a, __b)  (*((v8i8*)(__a)) = __b)
+#define msa_st1_s16(__a, __b) (*((v4i16*)(__a)) = __b)
+#define msa_st1_s32(__a, __b) (*((v2i32*)(__a)) = __b)
+#define msa_st1_s64(__a, __b) (*((v1i64*)(__a)) = __b)
+#define msa_st1_u8(__a, __b)  (*((v8u8*)(__a)) = __b)
+#define msa_st1_u16(__a, __b) (*((v4u16*)(__a)) = __b)
+#define msa_st1_u32(__a, __b) (*((v2u32*)(__a)) = __b)
+#define msa_st1_u64(__a, __b) (*((v1u64*)(__a)) = __b)
+#define msa_st1_f32(__a, __b) (*((v2f32*)(__a)) = __b)
+#define msa_st1_f64(__a, __b) (*((v1f64*)(__a)) = __b)
+
+/* Store the values of elements in the 128 bits vector __a to the given memory address __a. */
+#define msa_st1q_s8(__a, __b)  (__builtin_msa_st_b((v16i8)(__b), __a, 0))
+#define msa_st1q_s16(__a, __b) (__builtin_msa_st_h((v8i16)(__b), __a, 0))
+#define msa_st1q_s32(__a, __b) (__builtin_msa_st_w((v4i32)(__b), __a, 0))
+#define msa_st1q_s64(__a, __b) (__builtin_msa_st_d((v2i64)(__b), __a, 0))
+#define msa_st1q_u8(__a, __b)  (__builtin_msa_st_b((v16i8)(__b), __a, 0))
+#define msa_st1q_u16(__a, __b) (__builtin_msa_st_h((v8i16)(__b), __a, 0))
+#define msa_st1q_u32(__a, __b) (__builtin_msa_st_w((v4i32)(__b), __a, 0))
+#define msa_st1q_u64(__a, __b) (__builtin_msa_st_d((v2i64)(__b), __a, 0))
+#define msa_st1q_f32(__a, __b) (__builtin_msa_st_w((v4i32)(__b), __a, 0))
+#define msa_st1q_f64(__a, __b) (__builtin_msa_st_d((v2i64)(__b), __a, 0))
+
+/* Store the value of the element with the index __c in vector __a to the given memory address __a. */
+#define msa_st1_lane_s8(__a, __b, __c)   (*((int8_t*)(__a)) = __b[__c])
+#define msa_st1_lane_s16(__a, __b, __c)  (*((int16_t*)(__a)) = __b[__c])
+#define msa_st1_lane_s32(__a, __b, __c)  (*((int32_t*)(__a)) = __b[__c])
+#define msa_st1_lane_s64(__a, __b, __c)  (*((int64_t*)(__a)) = __b[__c])
+#define msa_st1_lane_u8(__a, __b, __c)   (*((uint8_t*)(__a)) = __b[__c])
+#define msa_st1_lane_u16(__a, __b, __c)  (*((uint16_t*)(__a)) = __b[__c])
+#define msa_st1_lane_u32(__a, __b, __c)  (*((uint32_t*)(__a)) = __b[__c])
+#define msa_st1_lane_u64(__a, __b, __c)  (*((uint64_t*)(__a)) = __b[__c])
+#define msa_st1_lane_f32(__a, __b, __c)  (*((float*)(__a)) = __b[__c])
+#define msa_st1_lane_f64(__a, __b, __c)  (*((double*)(__a)) = __b[__c])
+#define msa_st1q_lane_s8(__a, __b, __c)  (*((int8_t*)(__a)) = (int8_t)__builtin_msa_copy_s_b(__b, __c))
+#define msa_st1q_lane_s16(__a, __b, __c) (*((int16_t*)(__a)) = (int16_t)__builtin_msa_copy_s_h(__b, __c))
+#define msa_st1q_lane_s32(__a, __b, __c) (*((int32_t*)(__a)) = __builtin_msa_copy_s_w(__b, __c))
+#define msa_st1q_lane_s64(__a, __b, __c) (*((int64_t*)(__a)) = __builtin_msa_copy_s_d(__b, __c))
+#define msa_st1q_lane_u8(__a, __b, __c)  (*((uint8_t*)(__a)) = (uint8_t)__builtin_msa_copy_u_b((v16i8)(__b), __c))
+#define msa_st1q_lane_u16(__a, __b, __c) (*((uint16_t*)(__a)) = (uint16_t)__builtin_msa_copy_u_h((v8i16)(__b), __c))
+#define msa_st1q_lane_u32(__a, __b, __c) (*((uint32_t*)(__a)) = __builtin_msa_copy_u_w((v4i32)(__b), __c))
+#define msa_st1q_lane_u64(__a, __b, __c) (*((uint64_t*)(__a)) = __builtin_msa_copy_u_d((v2i64)(__b), __c))
+#define msa_st1q_lane_f32(__a, __b, __c) (*((float*)(__a)) = __b[__c])
+#define msa_st1q_lane_f64(__a, __b, __c) (*((double*)(__a)) = __b[__c])
+
+/* Duplicate elements for 64-bit doubleword vectors */
+#define msa_dup_n_s8(__a)  ((v8i8)__builtin_msa_copy_s_d((v2i64)__builtin_msa_fill_b((int32_t)(__a)), 0))
+#define msa_dup_n_s16(__a) ((v4i16)__builtin_msa_copy_s_d((v2i64)__builtin_msa_fill_h((int32_t)(__a)), 0))
+#define msa_dup_n_s32(__a) ((v2i32){__a, __a})
+#define msa_dup_n_s64(__a) ((v1i64){__a})
+#define msa_dup_n_u8(__a)  ((v8u8)__builtin_msa_copy_u_d((v2i64)__builtin_msa_fill_b((int32_t)(__a)), 0))
+#define msa_dup_n_u16(__a) ((v4u16)__builtin_msa_copy_u_d((v2i64)__builtin_msa_fill_h((int32_t)(__a)), 0))
+#define msa_dup_n_u32(__a) ((v2u32){__a, __a})
+#define msa_dup_n_u64(__a) ((v1u64){__a})
+#define msa_dup_n_f32(__a) ((v2f32){__a, __a})
+#define msa_dup_n_f64(__a) ((v1f64){__a})
+
+/* Duplicate elements for 128-bit quadword vectors */
+#define msa_dupq_n_s8(__a)  (__builtin_msa_fill_b((int32_t)(__a)))
+#define msa_dupq_n_s16(__a) (__builtin_msa_fill_h((int32_t)(__a)))
+#define msa_dupq_n_s32(__a) (__builtin_msa_fill_w((int32_t)(__a)))
+#define msa_dupq_n_s64(__a) (__builtin_msa_fill_d((int64_t)(__a)))
+#define msa_dupq_n_u8(__a)  ((v16u8)__builtin_msa_fill_b((int32_t)(__a)))
+#define msa_dupq_n_u16(__a) ((v8u16)__builtin_msa_fill_h((int32_t)(__a)))
+#define msa_dupq_n_u32(__a) ((v4u32)__builtin_msa_fill_w((int32_t)(__a)))
+#define msa_dupq_n_u64(__a) ((v2u64)__builtin_msa_fill_d((int64_t)(__a)))
+#define msa_dupq_n_f32(__a) ((v4f32){__a, __a, __a, __a})
+#define msa_dupq_n_f64(__a) ((v2f64){__a, __a})
+#define msa_dupq_lane_s8(__a, __b)  (__builtin_msa_splat_b(__a, __b))
+#define msa_dupq_lane_s16(__a, __b) (__builtin_msa_splat_h(__a, __b))
+#define msa_dupq_lane_s32(__a, __b) (__builtin_msa_splat_w(__a, __b))
+#define msa_dupq_lane_s64(__a, __b) (__builtin_msa_splat_d(__a, __b))
+#define msa_dupq_lane_u8(__a, __b)  ((v16u8)__builtin_msa_splat_b((v16i8)(__a), __b))
+#define msa_dupq_lane_u16(__a, __b) ((v8u16)__builtin_msa_splat_h((v8i16)(__a), __b))
+#define msa_dupq_lane_u32(__a, __b) ((v4u32)__builtin_msa_splat_w((v4i32)(__a), __b))
+#define msa_dupq_lane_u64(__a, __b) ((v2u64)__builtin_msa_splat_d((v2i64)(__a), __b))
+
+/* Create a 64 bits vector */
+#define msa_create_s8(__a)  ((v8i8)((uint64_t)(__a)))
+#define msa_create_s16(__a) ((v4i16)((uint64_t)(__a)))
+#define msa_create_s32(__a) ((v2i32)((uint64_t)(__a)))
+#define msa_create_s64(__a) ((v1i64)((uint64_t)(__a)))
+#define msa_create_u8(__a)  ((v8u8)((uint64_t)(__a)))
+#define msa_create_u16(__a) ((v4u16)((uint64_t)(__a)))
+#define msa_create_u32(__a) ((v2u32)((uint64_t)(__a)))
+#define msa_create_u64(__a) ((v1u64)((uint64_t)(__a)))
+#define msa_create_f32(__a) ((v2f32)((uint64_t)(__a)))
+#define msa_create_f64(__a) ((v1f64)((uint64_t)(__a)))
+
+/* Sign extends or zero extends each element in a 64 bits vector to twice its original length, and places the results in a 128 bits vector. */
+/*Transform v8i8 to v8i16*/
+#define msa_movl_s8(__a) \
+((v8i16){(__a)[0], (__a)[1], (__a)[2], (__a)[3], \
+         (__a)[4], (__a)[5], (__a)[6], (__a)[7]})
+
+/*Transform v8u8 to v8u16*/
+#define msa_movl_u8(__a) \
+((v8u16){(__a)[0], (__a)[1], (__a)[2], (__a)[3], \
+         (__a)[4], (__a)[5], (__a)[6], (__a)[7]})
+
+/*Transform v4i16 to v8i16*/
+#define msa_movl_s16(__a) ((v4i32){(__a)[0], (__a)[1], (__a)[2], (__a)[3]})
+
+/*Transform v2i32 to v4i32*/
+#define msa_movl_s32(__a) ((v2i64){(__a)[0], (__a)[1]})
+
+/*Transform v4u16 to v8u16*/
+#define msa_movl_u16(__a) ((v4u32){(__a)[0], (__a)[1], (__a)[2], (__a)[3]})
+
+/*Transform v2u32 to v4u32*/
+#define msa_movl_u32(__a) ((v2u64){(__a)[0], (__a)[1]})
+
+/* Copies the least significant half of each element of a 128 bits vector into the corresponding elements of a 64 bits vector. */
+#define msa_movn_s16(__a) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)(__a)); \
+  (v8i8)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_movn_s32(__a) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)(__a)); \
+  (v4i16)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_movn_s64(__a) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)(__a)); \
+  (v2i32)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_movn_u16(__a) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)(__a)); \
+  (v8u8)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_movn_u32(__a) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)(__a)); \
+  (v4u16)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_movn_u64(__a) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)(__a)); \
+  (v2u32)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+/* qmovn */
+#define msa_qmovn_s16(__a) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_sat_s_h((v8i16)(__a), 7)); \
+  (v8i8)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_qmovn_s32(__a) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_sat_s_w((v4i32)(__a), 15)); \
+  (v4i16)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_qmovn_s64(__a) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_sat_s_d((v2i64)(__a), 31)); \
+  (v2i32)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_qmovn_u16(__a) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_sat_u_h((v8u16)(__a), 7)); \
+  (v8u8)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_qmovn_u32(__a) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_sat_u_w((v4u32)(__a), 15)); \
+  (v4u16)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_qmovn_u64(__a) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_sat_u_d((v2u64)(__a), 31)); \
+  (v2u32)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+/* qmovun */
+#define msa_qmovun_s16(__a) \
+({ \
+  v8i16 __d = __builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__a)); \
+  v16i8 __e = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_sat_u_h((v8u16)__d, 7)); \
+  (v8u8)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+#define msa_qmovun_s32(__a) \
+({ \
+  v4i32 __d = __builtin_msa_max_s_w(__builtin_msa_fill_w(0), (v4i32)(__a)); \
+  v8i16 __e = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_sat_u_w((v4u32)__d, 15)); \
+  (v4u16)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+#define msa_qmovun_s64(__a) \
+({ \
+  v2i64 __d = __builtin_msa_max_s_d(__builtin_msa_fill_d(0), (v2i64)(__a)); \
+  v4i32 __e = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_sat_u_d((v2u64)__d, 31)); \
+  (v2u32)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+/* Right shift elements in a 128 bits vector by an immediate value, and places the results in a 64 bits vector. */
+#define msa_shrn_n_s16(__a, __b) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_srai_h((v8i16)(__a), (int)(__b))); \
+  (v8i8)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_shrn_n_s32(__a, __b) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_srai_w((v4i32)(__a), (int)(__b))); \
+  (v4i16)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_shrn_n_s64(__a, __b) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_srai_d((v2i64)(__a), (int)(__b))); \
+  (v2i32)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_shrn_n_u16(__a, __b) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_srli_h((v8i16)(__a), (int)(__b))); \
+  (v8u8)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_shrn_n_u32(__a, __b) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_srli_w((v4i32)(__a), (int)(__b))); \
+  (v4u16)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_shrn_n_u64(__a, __b) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_srli_d((v2i64)(__a), (int)(__b))); \
+  (v2u32)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+/* Right shift elements in a 128 bits vector by an immediate value, and places the results in a 64 bits vector. */
+#define msa_rshrn_n_s16(__a, __b) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_srari_h((v8i16)(__a), (int)__b)); \
+  (v8i8)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_rshrn_n_s32(__a, __b) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_srari_w((v4i32)(__a), (int)__b)); \
+  (v4i16)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_rshrn_n_s64(__a, __b) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_srari_d((v2i64)(__a), (int)__b)); \
+  (v2i32)__builtin_msa_copy_s_d((v2i64)__d, 0); \
+})
+
+#define msa_rshrn_n_u16(__a, __b) \
+({ \
+  v16i8 __d = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_srlri_h((v8i16)(__a), (int)__b)); \
+  (v8u8)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_rshrn_n_u32(__a, __b) \
+({ \
+  v8i16 __d = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_srlri_w((v4i32)(__a), (int)__b)); \
+  (v4u16)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+#define msa_rshrn_n_u64(__a, __b) \
+({ \
+  v4i32 __d = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_srlri_d((v2i64)(__a), (int)__b)); \
+  (v2u32)__builtin_msa_copy_u_d((v2i64)__d, 0); \
+})
+
+/* Right shift elements in a 128 bits vector by an immediate value, saturate the results and them in a 64 bits vector. */
+#define msa_qrshrn_n_s16(__a, __b) \
+({ \
+  v8i16 __d = __builtin_msa_sat_s_h(__builtin_msa_srari_h((v8i16)(__a), (int)(__b)), 7); \
+  v16i8 __e = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__d); \
+  (v8i8)__builtin_msa_copy_s_d((v2i64)__e, 0); \
+})
+
+#define msa_qrshrn_n_s32(__a, __b) \
+({ \
+  v4i32 __d = __builtin_msa_sat_s_w(__builtin_msa_srari_w((v4i32)(__a), (int)(__b)), 15); \
+  v8i16 __e = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__d); \
+  (v4i16)__builtin_msa_copy_s_d((v2i64)__e, 0); \
+})
+
+#define msa_qrshrn_n_s64(__a, __b) \
+({ \
+  v2i64 __d = __builtin_msa_sat_s_d(__builtin_msa_srari_d((v2i64)(__a), (int)(__b)), 31); \
+  v4i32 __e = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__d); \
+  (v2i32)__builtin_msa_copy_s_d((v2i64)__e, 0); \
+})
+
+#define msa_qrshrn_n_u16(__a, __b) \
+({ \
+  v8u16 __d = __builtin_msa_sat_u_h((v8u16)__builtin_msa_srlri_h((v8i16)(__a), (int)(__b)), 7); \
+  v16i8 __e = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__d); \
+  (v8u8)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+#define msa_qrshrn_n_u32(__a, __b) \
+({ \
+  v4u32 __d = __builtin_msa_sat_u_w((v4u32)__builtin_msa_srlri_w((v4i32)(__a), (int)(__b)), 15); \
+  v8i16 __e = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__d); \
+  (v4u16)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+#define msa_qrshrn_n_u64(__a, __b) \
+({ \
+  v2u64 __d = __builtin_msa_sat_u_d((v2u64)__builtin_msa_srlri_d((v2i64)(__a), (int)(__b)), 31); \
+  v4i32 __e = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__d); \
+  (v2u32)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+/* Right shift elements in a 128 bits vector by an immediate value, saturate the results and them in a 64 bits vector.
+   Input is signed and output is unsigned. */
+#define msa_qrshrun_n_s16(__a, __b) \
+({ \
+  v8i16 __d = __builtin_msa_srlri_h(__builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__a)), (int)(__b)); \
+  v16i8 __e = __builtin_msa_pckev_b(__builtin_msa_fill_b(0), (v16i8)__builtin_msa_sat_u_h((v8u16)__d, 7)); \
+  (v8u8)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+#define msa_qrshrun_n_s32(__a, __b) \
+({ \
+  v4i32 __d = __builtin_msa_srlri_w(__builtin_msa_max_s_w(__builtin_msa_fill_w(0), (v4i32)(__a)), (int)(__b)); \
+  v8i16 __e = __builtin_msa_pckev_h(__builtin_msa_fill_h(0), (v8i16)__builtin_msa_sat_u_w((v4u32)__d, 15)); \
+  (v4u16)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+#define msa_qrshrun_n_s64(__a, __b) \
+({ \
+  v2i64 __d = __builtin_msa_srlri_d(__builtin_msa_max_s_d(__builtin_msa_fill_d(0), (v2i64)(__a)), (int)(__b)); \
+  v4i32 __e = __builtin_msa_pckev_w(__builtin_msa_fill_w(0), (v4i32)__builtin_msa_sat_u_d((v2u64)__d, 31)); \
+  (v2u32)__builtin_msa_copy_u_d((v2i64)__e, 0); \
+})
+
+/* pack */
+#define msa_pack_s16(__a, __b) (__builtin_msa_pckev_b((v16i8)(__b), (v16i8)(__a)))
+#define msa_pack_s32(__a, __b) (__builtin_msa_pckev_h((v8i16)(__b), (v8i16)(__a)))
+#define msa_pack_s64(__a, __b) (__builtin_msa_pckev_w((v4i32)(__b), (v4i32)(__a)))
+#define msa_pack_u16(__a, __b) ((v16u8)__builtin_msa_pckev_b((v16i8)(__b), (v16i8)(__a)))
+#define msa_pack_u32(__a, __b) ((v8u16)__builtin_msa_pckev_h((v8i16)(__b), (v8i16)(__a)))
+#define msa_pack_u64(__a, __b) ((v4u32)__builtin_msa_pckev_w((v4i32)(__b), (v4i32)(__a)))
+
+/* qpack */
+#define msa_qpack_s16(__a, __b) \
+(__builtin_msa_pckev_b((v16i8)__builtin_msa_sat_s_h((v8i16)(__b), 7), (v16i8)__builtin_msa_sat_s_h((v8i16)(__a), 7)))
+#define msa_qpack_s32(__a, __b) \
+(__builtin_msa_pckev_h((v8i16)__builtin_msa_sat_s_w((v4i32)(__b), 15), (v8i16)__builtin_msa_sat_s_w((v4i32)(__a), 15)))
+#define msa_qpack_s64(__a, __b) \
+(__builtin_msa_pckev_w((v4i32)__builtin_msa_sat_s_d((v2i64)(__b), 31), (v4i32)__builtin_msa_sat_s_d((v2i64)(__a), 31)))
+#define msa_qpack_u16(__a, __b) \
+((v16u8)__builtin_msa_pckev_b((v16i8)__builtin_msa_sat_u_h((v8u16)(__b), 7), (v16i8)__builtin_msa_sat_u_h((v8u16)(__a), 7)))
+#define msa_qpack_u32(__a, __b) \
+((v8u16)__builtin_msa_pckev_h((v8i16)__builtin_msa_sat_u_w((v4u32)(__b), 15), (v8i16)__builtin_msa_sat_u_w((v4u32)(__a), 15)))
+#define msa_qpack_u64(__a, __b) \
+((v4u32)__builtin_msa_pckev_w((v4i32)__builtin_msa_sat_u_d((v2u64)(__b), 31), (v4i32)__builtin_msa_sat_u_d((v2u64)(__a), 31)))
+
+/* qpacku */
+#define msa_qpacku_s16(__a, __b) \
+((v16u8)__builtin_msa_pckev_b((v16i8)__builtin_msa_sat_u_h((v8u16)(__builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__b))), 7), \
+                              (v16i8)__builtin_msa_sat_u_h((v8u16)(__builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__a))), 7)))
+#define msa_qpacku_s32(__a, __b) \
+((v8u16)__builtin_msa_pckev_h((v8i16)__builtin_msa_sat_u_w((v4u32)(__builtin_msa_max_s_w(__builtin_msa_fill_w(0), (v4i32)(__b))), 15), \
+                              (v8i16)__builtin_msa_sat_u_w((v4u32)(__builtin_msa_max_s_w(__builtin_msa_fill_w(0), (v4i32)(__a))), 15)))
+#define msa_qpacku_s64(__a, __b) \
+((v4u32)__builtin_msa_pckev_w((v4i32)__builtin_msa_sat_u_d((v2u64)(__builtin_msa_max_s_d(__builtin_msa_fill_d(0), (v2i64)(__b))), 31), \
+                              (v4i32)__builtin_msa_sat_u_d((v2u64)(__builtin_msa_max_s_d(__builtin_msa_fill_d(0), (v2i64)(__a))), 31)))
+
+/* packr */
+#define msa_packr_s16(__a, __b, __c) \
+(__builtin_msa_pckev_b((v16i8)__builtin_msa_srai_h((v8i16)(__b), (int)(__c)), (v16i8)__builtin_msa_srai_h((v8i16)(__a), (int)(__c))))
+#define msa_packr_s32(__a, __b, __c) \
+(__builtin_msa_pckev_h((v8i16)__builtin_msa_srai_w((v4i32)(__b), (int)(__c)), (v8i16)__builtin_msa_srai_w((v4i32)(__a), (int)(__c))))
+#define msa_packr_s64(__a, __b, __c) \
+(__builtin_msa_pckev_w((v4i32)__builtin_msa_srai_d((v2i64)(__b), (int)(__c)), (v4i32)__builtin_msa_srai_d((v2i64)(__a), (int)(__c))))
+#define msa_packr_u16(__a, __b, __c) \
+((v16u8)__builtin_msa_pckev_b((v16i8)__builtin_msa_srli_h((v8i16)(__b), (int)(__c)), (v16i8)__builtin_msa_srli_h((v8i16)(__a), (int)(__c))))
+#define msa_packr_u32(__a, __b, __c) \
+((v8u16)__builtin_msa_pckev_h((v8i16)__builtin_msa_srli_w((v4i32)(__b), (int)(__c)), (v8i16)__builtin_msa_srli_w((v4i32)(__a), (int)(__c))))
+#define msa_packr_u64(__a, __b, __c) \
+((v4u32)__builtin_msa_pckev_w((v4i32)__builtin_msa_srli_d((v2i64)(__b), (int)(__c)), (v4i32)__builtin_msa_srli_d((v2i64)(__a), (int)(__c))))
+
+/* rpackr */
+#define msa_rpackr_s16(__a, __b, __c) \
+(__builtin_msa_pckev_b((v16i8)__builtin_msa_srari_h((v8i16)(__b), (int)(__c)), (v16i8)__builtin_msa_srari_h((v8i16)(__a), (int)(__c))))
+#define msa_rpackr_s32(__a, __b, __c) \
+(__builtin_msa_pckev_h((v8i16)__builtin_msa_srari_w((v4i32)(__b), (int)(__c)), (v8i16)__builtin_msa_srari_w((v4i32)(__a), (int)(__c))))
+#define msa_rpackr_s64(__a, __b, __c) \
+(__builtin_msa_pckev_w((v4i32)__builtin_msa_srari_d((v2i64)(__b), (int)(__c)), (v4i32)__builtin_msa_srari_d((v2i64)(__a), (int)(__c))))
+#define msa_rpackr_u16(__a, __b, __c) \
+((v16u8)__builtin_msa_pckev_b((v16i8)__builtin_msa_srlri_h((v8i16)(__b), (int)(__c)), (v16i8)__builtin_msa_srlri_h((v8i16)(__a), (int)(__c))))
+#define msa_rpackr_u32(__a, __b, __c) \
+((v8u16)__builtin_msa_pckev_h((v8i16)__builtin_msa_srlri_w((v4i32)(__b), (int)(__c)), (v8i16)__builtin_msa_srlri_w((v4i32)(__a), (int)(__c))))
+#define msa_rpackr_u64(__a, __b, __c) \
+((v4u32)__builtin_msa_pckev_w((v4i32)__builtin_msa_srlri_d((v2i64)(__b), (int)(__c)), (v4i32)__builtin_msa_srlri_d((v2i64)(__a), (int)(__c))))
+
+/* qrpackr */
+#define msa_qrpackr_s16(__a, __b, __c) \
+(__builtin_msa_pckev_b((v16i8)__builtin_msa_sat_s_h(__builtin_msa_srari_h((v8i16)(__b), (int)(__c)), 7), \
+                       (v16i8)__builtin_msa_sat_s_h(__builtin_msa_srari_h((v8i16)(__a), (int)(__c)), 7)))
+#define msa_qrpackr_s32(__a, __b, __c) \
+(__builtin_msa_pckev_h((v8i16)__builtin_msa_sat_s_w(__builtin_msa_srari_w((v4i32)(__b), (int)(__c)), 15), \
+                       (v8i16)__builtin_msa_sat_s_w(__builtin_msa_srari_w((v4i32)(__a), (int)(__c)), 15)))
+#define msa_qrpackr_s64(__a, __b, __c) \
+(__builtin_msa_pckev_w((v4i32)__builtin_msa_sat_s_d(__builtin_msa_srari_d((v2i64)(__b), (int)(__c)), 31), \
+                       (v4i32)__builtin_msa_sat_s_d(__builtin_msa_srari_d((v2i64)(__a), (int)(__c)), 31)))
+#define msa_qrpackr_u16(__a, __b, __c) \
+((v16u8)__builtin_msa_pckev_b((v16i8)__builtin_msa_sat_u_h((v8u16)__builtin_msa_srlri_h((v8i16)(__b), (int)(__c)), 7), \
+                              (v16i8)__builtin_msa_sat_u_h((v8u16)__builtin_msa_srlri_h((v8i16)(__a), (int)(__c)), 7)))
+#define msa_qrpackr_u32(__a, __b, __c) \
+((v8u16)__builtin_msa_pckev_h((v8i16)__builtin_msa_sat_u_w((v4u32)__builtin_msa_srlri_w((v4i32)(__b), (int)(__c)), 15), \
+                              (v8i16)__builtin_msa_sat_u_w((v4u32)__builtin_msa_srlri_w((v4i32)(__a), (int)(__c)), 15)))
+#define msa_qrpackr_u64(__a, __b, __c) \
+((v4u32)__builtin_msa_pckev_w((v4i32)__builtin_msa_sat_u_d((v2u64)__builtin_msa_srlri_d((v2i64)(__b), (int)(__c)), 31), \
+                              (v4i32)__builtin_msa_sat_u_d((v2u64)__builtin_msa_srlri_d((v2i64)(__a), (int)(__c)), 31)))
+
+/* qrpackru */
+#define msa_qrpackru_s16(__a, __b, __c) \
+({ \
+  v8i16 __d = __builtin_msa_srlri_h(__builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__a)), (int)(__c)); \
+  v8i16 __e = __builtin_msa_srlri_h(__builtin_msa_max_s_h(__builtin_msa_fill_h(0), (v8i16)(__b)), (int)(__c)); \
+  (v16u8)__builtin_msa_pckev_b((v16i8)__builtin_msa_sat_u_h((v8u16)__e, 7), (v16i8)__builtin_msa_sat_u_h((v8u16)__d, 7)); \
+})
+
+#define msa_qrpackru_s32(__a, __b, __c) \
+({ \
+  v4i32 __d = __builtin_msa_srlri_w(__builtin_msa_max_s_w(__builtin_msa_fill_w(0), (v4i32)(__a)), (int)(__c)); \
+  v4i32 __e = __builtin_msa_srlri_w(__builtin_msa_max_s_w(__builtin_msa_fill_w(0), (v4i32)(__b)), (int)(__c)); \
+  (v8u16)__builtin_msa_pckev_h((v8i16)__builtin_msa_sat_u_w((v4u32)__e, 15), (v8i16)__builtin_msa_sat_u_w((v4u32)__d, 15)); \
+})
+
+#define msa_qrpackru_s64(__a, __b, __c) \
+({ \
+  v2i64 __d = __builtin_msa_srlri_d(__builtin_msa_max_s_d(__builtin_msa_fill_d(0), (v2i64)(__a)), (int)(__c)); \
+  v2i64 __e = __builtin_msa_srlri_d(__builtin_msa_max_s_d(__builtin_msa_fill_d(0), (v2i64)(__b)), (int)(__c)); \
+  (v4u32)__builtin_msa_pckev_w((v4i32)__builtin_msa_sat_u_d((v2u64)__e, 31), (v4i32)__builtin_msa_sat_u_d((v2u64)__d, 31)); \
+})
+
+/* Minimum values between corresponding elements in the two vectors are written to the returned vector. */
+#define msa_minq_s8(__a, __b)  (__builtin_msa_min_s_b(__a, __b))
+#define msa_minq_s16(__a, __b) (__builtin_msa_min_s_h(__a, __b))
+#define msa_minq_s32(__a, __b) (__builtin_msa_min_s_w(__a, __b))
+#define msa_minq_s64(__a, __b) (__builtin_msa_min_s_d(__a, __b))
+#define msa_minq_u8(__a, __b)  ((v16u8)__builtin_msa_min_u_b(__a, __b))
+#define msa_minq_u16(__a, __b) ((v8u16)__builtin_msa_min_u_h(__a, __b))
+#define msa_minq_u32(__a, __b) ((v4u32)__builtin_msa_min_u_w(__a, __b))
+#define msa_minq_u64(__a, __b) ((v2u64)__builtin_msa_min_u_d(__a, __b))
+#define msa_minq_f32(__a, __b) (__builtin_msa_fmin_w(__a, __b))
+#define msa_minq_f64(__a, __b) (__builtin_msa_fmin_d(__a, __b))
+
+/* Maximum values between corresponding elements in the two vectors are written to the returned vector. */
+#define msa_maxq_s8(__a, __b)  (__builtin_msa_max_s_b(__a, __b))
+#define msa_maxq_s16(__a, __b) (__builtin_msa_max_s_h(__a, __b))
+#define msa_maxq_s32(__a, __b) (__builtin_msa_max_s_w(__a, __b))
+#define msa_maxq_s64(__a, __b) (__builtin_msa_max_s_d(__a, __b))
+#define msa_maxq_u8(__a, __b)  ((v16u8)__builtin_msa_max_u_b(__a, __b))
+#define msa_maxq_u16(__a, __b) ((v8u16)__builtin_msa_max_u_h(__a, __b))
+#define msa_maxq_u32(__a, __b) ((v4u32)__builtin_msa_max_u_w(__a, __b))
+#define msa_maxq_u64(__a, __b) ((v2u64)__builtin_msa_max_u_d(__a, __b))
+#define msa_maxq_f32(__a, __b) (__builtin_msa_fmax_w(__a, __b))
+#define msa_maxq_f64(__a, __b) (__builtin_msa_fmax_d(__a, __b))
+
+/* Vector type reinterpretion */
+#define MSA_TPV_REINTERPRET(_Tpv, Vec) ((_Tpv)(Vec))
+
+/* Add the odd elements in vector __a with the even elements in vector __b to double width elements in the returned vector. */
+/* v8i16 msa_hadd_s16 ((v16i8)__a, (v16i8)__b) */
+#define msa_hadd_s16(__a, __b) (__builtin_msa_hadd_s_h((v16i8)(__a), (v16i8)(__b)))
+/* v4i32 msa_hadd_s32 ((v8i16)__a, (v8i16)__b) */
+#define msa_hadd_s32(__a, __b) (__builtin_msa_hadd_s_w((v8i16)(__a), (v8i16)(__b)))
+/* v2i64 msa_hadd_s64 ((v4i32)__a, (v4i32)__b) */
+#define msa_hadd_s64(__a, __b) (__builtin_msa_hadd_s_d((v4i32)(__a), (v4i32)(__b)))
+
+/* Copy even elements in __a to the left half and even elements in __b to the right half and return the result vector. */
+#define msa_pckev_s8(__a, __b)  (__builtin_msa_pckev_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_pckev_s16(__a, __b) (__builtin_msa_pckev_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_pckev_s32(__a, __b) (__builtin_msa_pckev_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_pckev_s64(__a, __b) (__builtin_msa_pckev_d((v2i64)(__a), (v2i64)(__b)))
+
+/* Copy even elements in __a to the left half and even elements in __b to the right half and return the result vector. */
+#define msa_pckod_s8(__a, __b)  (__builtin_msa_pckod_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_pckod_s16(__a, __b) (__builtin_msa_pckod_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_pckod_s32(__a, __b) (__builtin_msa_pckod_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_pckod_s64(__a, __b) (__builtin_msa_pckod_d((v2i64)(__a), (v2i64)(__b)))
+
+#ifdef _MIPSEB
+#define LANE_IMM0_1(x)  (0b1 - ((x) & 0b1))
+#define LANE_IMM0_3(x)  (0b11 - ((x) & 0b11))
+#define LANE_IMM0_7(x)  (0b111 - ((x) & 0b111))
+#define LANE_IMM0_15(x) (0b1111 - ((x) & 0b1111))
+#else
+#define LANE_IMM0_1(x)  ((x) & 0b1)
+#define LANE_IMM0_3(x)  ((x) & 0b11)
+#define LANE_IMM0_7(x)  ((x) & 0b111)
+#define LANE_IMM0_15(x) ((x) & 0b1111)
+#endif
+
+#define msa_get_lane_u8(__a, __b)        ((uint8_t)(__a)[LANE_IMM0_7(__b)])
+#define msa_get_lane_s8(__a, __b)        ((int8_t)(__a)[LANE_IMM0_7(__b)])
+#define msa_get_lane_u16(__a, __b)       ((uint16_t)(__a)[LANE_IMM0_3(__b)])
+#define msa_get_lane_s16(__a, __b)       ((int16_t)(__a)[LANE_IMM0_3(__b)])
+#define msa_get_lane_u32(__a, __b)       ((uint32_t)(__a)[LANE_IMM0_1(__b)])
+#define msa_get_lane_s32(__a, __b)       ((int32_t)(__a)[LANE_IMM0_1(__b)])
+#define msa_get_lane_f32(__a, __b)       ((float)(__a)[LANE_IMM0_3(__b)])
+#define msa_get_lane_s64(__a, __b)       ((int64_t)(__a)[LANE_IMM0_1(__b)])
+#define msa_get_lane_u64(__a, __b)       ((uint64_t)(__a)[LANE_IMM0_1(__b)])
+#define msa_get_lane_f64(__a, __b)       ((double)(__a)[LANE_IMM0_1(__b)])
+#define msa_getq_lane_u8(__a, imm0_15)   ((uint8_t)__builtin_msa_copy_u_b((v16i8)(__a), imm0_15))
+#define msa_getq_lane_s8(__a, imm0_15)   ((int8_t)__builtin_msa_copy_s_b(__a, imm0_15))
+#define msa_getq_lane_u16(__a, imm0_7)   ((uint16_t)__builtin_msa_copy_u_h((v8i16)(__a), imm0_7))
+#define msa_getq_lane_s16(__a, imm0_7)   ((int16_t)__builtin_msa_copy_s_h(__a, imm0_7))
+#define msa_getq_lane_u32(__a, imm0_3)   __builtin_msa_copy_u_w((v4i32)(__a), imm0_3)
+#define msa_getq_lane_s32                __builtin_msa_copy_s_w
+#define msa_getq_lane_f32(__a, __b)      ((float)(__a)[LANE_IMM0_3(__b)])
+#define msa_getq_lane_f64(__a, __b)      ((double)(__a)[LANE_IMM0_1(__b)])
+#if (__mips == 64)
+#define msa_getq_lane_u64(__a, imm0_1)   __builtin_msa_copy_u_d((v2i64)(__a), imm0_1)
+#define msa_getq_lane_s64                __builtin_msa_copy_s_d
+#else
+#define msa_getq_lane_u64(__a, imm0_1)   ((uint64_t)(__a)[LANE_IMM0_1(imm0_1)])
+#define msa_getq_lane_s64(__a, imm0_1)   ((int64_t)(__a)[LANE_IMM0_1(imm0_1)])
+#endif
+
+/* combine */
+#if (__mips == 64)
+#define __COMBINE_64_64(__TYPE, a, b)    ((__TYPE)((v2u64){((v1u64)(a))[0], ((v1u64)(b))[0]}))
+#else
+#define __COMBINE_64_64(__TYPE, a, b)    ((__TYPE)((v4u32){((v2u32)(a))[0], ((v2u32)(a))[1],  \
+                                                           ((v2u32)(b))[0], ((v2u32)(b))[1]}))
+#endif
+
+/* v16i8 msa_combine_s8 (v8i8 __a, v8i8 __b) */
+#define msa_combine_s8(__a, __b)  __COMBINE_64_64(v16i8, __a, __b)
+
+/* v8i16 msa_combine_s16(v4i16 __a, v4i16 __b) */
+#define msa_combine_s16(__a, __b)  __COMBINE_64_64(v8i16, __a, __b)
+
+/* v4i32 msa_combine_s32(v2i32 __a, v2i32 __b) */
+#define msa_combine_s32(__a, __b)  __COMBINE_64_64(v4i32, __a, __b)
+
+/* v2i64 msa_combine_s64(v1i64 __a, v1i64 __b) */
+#define msa_combine_s64(__a, __b)  __COMBINE_64_64(v2i64, __a, __b)
+
+/* v4f32 msa_combine_f32(v2f32 __a, v2f32 __b) */
+#define msa_combine_f32(__a, __b)  __COMBINE_64_64(v4f32, __a, __b)
+
+/* v16u8 msa_combine_u8(v8u8 __a, v8u8 __b) */
+#define msa_combine_u8(__a, __b)  __COMBINE_64_64(v16u8, __a, __b)
+
+/* v8u16 msa_combine_u16(v4u16 __a, v4u16 __b) */
+#define msa_combine_u16(__a, __b)  __COMBINE_64_64(v8u16, __a, __b)
+
+/* v4u32 msa_combine_u32(v2u32 __a, v2u32 __b) */
+#define msa_combine_u32(__a, __b)  __COMBINE_64_64(v4u32, __a, __b)
+
+/* v2u64 msa_combine_u64(v1u64 __a, v1u64 __b) */
+#define msa_combine_u64(__a, __b)  __COMBINE_64_64(v2u64, __a, __b)
+
+/* v2f64 msa_combine_f64(v1f64 __a, v1f64 __b) */
+#define msa_combine_f64(__a, __b)  __COMBINE_64_64(v2f64, __a, __b)
+
+/* get_low, get_high */
+#if (__mips == 64)
+#define __GET_LOW(__TYPE, a)   ((__TYPE)((v1u64)(__builtin_msa_copy_u_d((v2i64)(a), 0))))
+#define __GET_HIGH(__TYPE, a)  ((__TYPE)((v1u64)(__builtin_msa_copy_u_d((v2i64)(a), 1))))
+#else
+#define __GET_LOW(__TYPE, a)   ((__TYPE)(((v2u64)(a))[0]))
+#define __GET_HIGH(__TYPE, a)  ((__TYPE)(((v2u64)(a))[1]))
+#endif
+
+/* v8i8 msa_get_low_s8(v16i8 __a) */
+#define msa_get_low_s8(__a)  __GET_LOW(v8i8, __a)
+
+/* v4i16 msa_get_low_s16(v8i16 __a) */
+#define msa_get_low_s16(__a)  __GET_LOW(v4i16, __a)
+
+/* v2i32 msa_get_low_s32(v4i32 __a) */
+#define msa_get_low_s32(__a)  __GET_LOW(v2i32, __a)
+
+/* v1i64 msa_get_low_s64(v2i64 __a) */
+#define msa_get_low_s64(__a)  __GET_LOW(v1i64, __a)
+
+/* v8u8 msa_get_low_u8(v16u8 __a) */
+#define msa_get_low_u8(__a)  __GET_LOW(v8u8, __a)
+
+/* v4u16 msa_get_low_u16(v8u16 __a) */
+#define msa_get_low_u16(__a)  __GET_LOW(v4u16, __a)
+
+/* v2u32 msa_get_low_u32(v4u32 __a) */
+#define msa_get_low_u32(__a)  __GET_LOW(v2u32, __a)
+
+/* v1u64 msa_get_low_u64(v2u64 __a) */
+#define msa_get_low_u64(__a)  __GET_LOW(v1u64, __a)
+
+/* v2f32 msa_get_low_f32(v4f32 __a) */
+#define msa_get_low_f32(__a)  __GET_LOW(v2f32, __a)
+
+/* v1f64 msa_get_low_f64(v2f64 __a) */
+#define msa_get_low_f64(__a)  __GET_LOW(v1f64, __a)
+
+/* v8i8 msa_get_high_s8(v16i8 __a) */
+#define msa_get_high_s8(__a)  __GET_HIGH(v8i8, __a)
+
+/* v4i16 msa_get_high_s16(v8i16 __a) */
+#define msa_get_high_s16(__a)  __GET_HIGH(v4i16, __a)
+
+/* v2i32 msa_get_high_s32(v4i32 __a) */
+#define msa_get_high_s32(__a)  __GET_HIGH(v2i32, __a)
+
+/* v1i64 msa_get_high_s64(v2i64 __a) */
+#define msa_get_high_s64(__a)  __GET_HIGH(v1i64, __a)
+
+/* v8u8 msa_get_high_u8(v16u8 __a) */
+#define msa_get_high_u8(__a)  __GET_HIGH(v8u8, __a)
+
+/* v4u16 msa_get_high_u16(v8u16 __a) */
+#define msa_get_high_u16(__a)  __GET_HIGH(v4u16, __a)
+
+/* v2u32 msa_get_high_u32(v4u32 __a) */
+#define msa_get_high_u32(__a)  __GET_HIGH(v2u32, __a)
+
+/* v1u64 msa_get_high_u64(v2u64 __a) */
+#define msa_get_high_u64(__a)  __GET_HIGH(v1u64, __a)
+
+/* v2f32 msa_get_high_f32(v4f32 __a) */
+#define msa_get_high_f32(__a)  __GET_HIGH(v2f32, __a)
+
+/* v1f64 msa_get_high_f64(v2f64 __a) */
+#define msa_get_high_f64(__a)  __GET_HIGH(v1f64, __a)
+
+/* ri = ai * b[lane] */
+/* v4f32 msa_mulq_lane_f32(v4f32 __a, v4f32 __b, const int __lane) */
+#define msa_mulq_lane_f32(__a, __b, __lane)  ((__a) * msa_getq_lane_f32(__b, __lane))
+
+/* ri = ai + bi * c[lane] */
+/* v4f32 msa_mlaq_lane_f32(v4f32 __a, v4f32 __b, v4f32 __c, const int __lane) */
+#define msa_mlaq_lane_f32(__a, __b, __c, __lane)  ((__a) + ((__b) * msa_getq_lane_f32(__c, __lane)))
+
+/* uint16_t msa_sum_u16(v8u16 __a)*/
+#define msa_sum_u16(__a)                         \
+({                                               \
+  v4u32 _b;                                      \
+  v2u64 _c;                                      \
+  _b = __builtin_msa_hadd_u_w(__a, __a);         \
+  _c = __builtin_msa_hadd_u_d(_b, _b);           \
+  (uint16_t)(_c[0] + _c[1]);                     \
+})
+
+/* int16_t msa_sum_s16(v8i16 __a) */
+#define msa_sum_s16(__a)                        \
+({                                              \
+  v4i32 _b;                                     \
+  v2i64 _c;                                     \
+  _b = __builtin_msa_hadd_s_w(__a, __a);        \
+  _c = __builtin_msa_hadd_s_d(_b, _b);          \
+  (int32_t)(_c[0] + _c[1]);                     \
+})
+
+
+/* uint32_t msa_sum_u32(v4u32 __a)*/
+#define msa_sum_u32(__a)                       \
+({                                             \
+  v2u64 _b;                                    \
+  _b = __builtin_msa_hadd_u_d(__a, __a);       \
+  (uint32_t)(_b[0] + _b[1]);                   \
+})
+
+/* int32_t  msa_sum_s32(v4i32 __a)*/
+#define msa_sum_s32(__a)                       \
+({                                             \
+  v2i64 _b;                                    \
+  _b = __builtin_msa_hadd_s_d(__a, __a);       \
+  (int64_t)(_b[0] + _b[1]);                    \
+})
+
+/* uint8_t msa_sum_u8(v16u8 __a)*/
+#define msa_sum_u8(__a)                        \
+({                                             \
+  v8u16 _b16;                                    \
+  v4u32 _c32;                                    \
+  _b16 = __builtin_msa_hadd_u_h(__a, __a);       \
+  _c32 = __builtin_msa_hadd_u_w(_b16, _b16);         \
+  (uint8_t)msa_sum_u32(_c32);                    \
+})
+
+/* int8_t msa_sum_s8(v16s8 __a)*/
+#define msa_sum_s8(__a)                        \
+({                                             \
+  v8i16 _b16;                                    \
+  v4i32 _c32;                                    \
+  _b16 = __builtin_msa_hadd_s_h(__a, __a);       \
+  _c32 = __builtin_msa_hadd_s_w(_b16, _b16);         \
+  (int16_t)msa_sum_s32(_c32);                     \
+})
+
+/* float msa_sum_f32(v4f32 __a)*/
+#define msa_sum_f32(__a)  ((__a)[0] + (__a)[1] + (__a)[2] + (__a)[3])
+
+/* v8u16 msa_paddlq_u8(v16u8 __a) */
+#define msa_paddlq_u8(__a)  (__builtin_msa_hadd_u_h(__a, __a))
+
+/* v8i16 msa_paddlq_s8(v16i8 __a) */
+#define msa_paddlq_s8(__a)  (__builtin_msa_hadd_s_h(__a, __a))
+
+/* v4u32 msa_paddlq_u16 (v8u16 __a)*/
+#define msa_paddlq_u16(__a)  (__builtin_msa_hadd_u_w(__a, __a))
+
+/* v4i32 msa_paddlq_s16 (v8i16 __a)*/
+#define msa_paddlq_s16(__a)  (__builtin_msa_hadd_s_w(__a, __a))
+
+/* v2u64 msa_paddlq_u32(v4u32 __a) */
+#define msa_paddlq_u32(__a)  (__builtin_msa_hadd_u_d(__a, __a))
+
+/* v2i64 msa_paddlq_s32(v4i32 __a) */
+#define msa_paddlq_s32(__a)  (__builtin_msa_hadd_s_d(__a, __a))
+
+#define V8U8_2_V8U16(x)   {(uint16_t)x[0], (uint16_t)x[1], (uint16_t)x[2], (uint16_t)x[3], \
+                           (uint16_t)x[4], (uint16_t)x[5], (uint16_t)x[6], (uint16_t)x[7]}
+#define V8U8_2_V8I16(x)   {(int16_t)x[0], (int16_t)x[1], (int16_t)x[2], (int16_t)x[3], \
+                           (int16_t)x[4], (int16_t)x[5], (int16_t)x[6], (int16_t)x[7]}
+#define V8I8_2_V8I16(x)   {(int16_t)x[0], (int16_t)x[1], (int16_t)x[2], (int16_t)x[3], \
+                           (int16_t)x[4], (int16_t)x[5], (int16_t)x[6], (int16_t)x[7]}
+#define V4U16_2_V4U32(x)  {(uint32_t)x[0], (uint32_t)x[1], (uint32_t)x[2], (uint32_t)x[3]}
+#define V4U16_2_V4I32(x)  {(int32_t)x[0], (int32_t)x[1], (int32_t)x[2], (int32_t)x[3]}
+#define V4I16_2_V4I32(x)  {(int32_t)x[0], (int32_t)x[1], (int32_t)x[2], (int32_t)x[3]}
+#define V2U32_2_V2U64(x)  {(uint64_t)x[0], (uint64_t)x[1]}
+#define V2U32_2_V2I64(x)  {(int64_t)x[0], (int64_t)x[1]}
+
+/* v8u16 msa_mull_u8(v8u8 __a, v8u8 __b) */
+#define msa_mull_u8(__a, __b)  ((v8u16)__builtin_msa_mulv_h((v8i16)V8U8_2_V8I16(__a), (v8i16)V8U8_2_V8I16(__b)))
+
+/* v8i16 msa_mull_s8(v8i8 __a, v8i8 __b)*/
+#define msa_mull_s8(__a, __b)  (__builtin_msa_mulv_h((v8i16)V8I8_2_V8I16(__a), (v8i16)V8I8_2_V8I16(__b)))
+
+/* v4u32 msa_mull_u16(v4u16 __a, v4u16 __b) */
+#define msa_mull_u16(__a, __b)  ((v4u32)__builtin_msa_mulv_w((v4i32)V4U16_2_V4I32(__a), (v4i32)V4U16_2_V4I32(__b)))
+
+/* v4i32 msa_mull_s16(v4i16 __a, v4i16 __b) */
+#define msa_mull_s16(__a, __b)  (__builtin_msa_mulv_w((v4i32)V4I16_2_V4I32(__a), (v4i32)V4I16_2_V4I32(__b)))
+
+/* v2u64 msa_mull_u32(v2u32 __a, v2u32 __b) */
+#define msa_mull_u32(__a, __b)  ((v2u64)__builtin_msa_mulv_d((v2i64)V2U32_2_V2I64(__a), (v2i64)V2U32_2_V2I64(__b)))
+
+/* bitwise and: __builtin_msa_and_v */
+#define msa_andq_u8(__a, __b)  ((v16u8)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_andq_s8(__a, __b)  ((v16i8)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_andq_u16(__a, __b) ((v8u16)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_andq_s16(__a, __b) ((v8i16)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_andq_u32(__a, __b) ((v4u32)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_andq_s32(__a, __b) ((v4i32)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_andq_u64(__a, __b) ((v2u64)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_andq_s64(__a, __b) ((v2i64)__builtin_msa_and_v((v16u8)(__a), (v16u8)(__b)))
+
+/* bitwise or: __builtin_msa_or_v */
+#define msa_orrq_u8(__a, __b)  ((v16u8)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_orrq_s8(__a, __b)  ((v16i8)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_orrq_u16(__a, __b) ((v8u16)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_orrq_s16(__a, __b) ((v8i16)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_orrq_u32(__a, __b) ((v4u32)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_orrq_s32(__a, __b) ((v4i32)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_orrq_u64(__a, __b) ((v2u64)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_orrq_s64(__a, __b) ((v2i64)__builtin_msa_or_v((v16u8)(__a), (v16u8)(__b)))
+
+/* bitwise xor: __builtin_msa_xor_v */
+#define msa_eorq_u8(__a, __b)  ((v16u8)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_eorq_s8(__a, __b)  ((v16i8)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_eorq_u16(__a, __b) ((v8u16)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_eorq_s16(__a, __b) ((v8i16)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_eorq_u32(__a, __b) ((v4u32)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_eorq_s32(__a, __b) ((v4i32)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_eorq_u64(__a, __b) ((v2u64)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+#define msa_eorq_s64(__a, __b) ((v2i64)__builtin_msa_xor_v((v16u8)(__a), (v16u8)(__b)))
+
+/* bitwise not: v16u8 __builtin_msa_xori_b (v16u8, 0xff) */
+#define msa_mvnq_u8(__a)  ((v16u8)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+#define msa_mvnq_s8(__a)  ((v16i8)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+#define msa_mvnq_u16(__a) ((v8u16)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+#define msa_mvnq_s16(__a) ((v8i16)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+#define msa_mvnq_u32(__a) ((v4u32)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+#define msa_mvnq_s32(__a) ((v4i32)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+#define msa_mvnq_u64(__a) ((v2u64)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+#define msa_mvnq_s64(__a) ((v2i64)__builtin_msa_xori_b((v16u8)(__a), 0xFF))
+
+/* compare equal: ceq -> ri = ai == bi ? 1...1:0...0 */
+#define msa_ceqq_u8(__a, __b)  ((v16u8)__builtin_msa_ceq_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_ceqq_s8(__a, __b)  ((v16u8)__builtin_msa_ceq_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_ceqq_u16(__a, __b) ((v8u16)__builtin_msa_ceq_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_ceqq_s16(__a, __b) ((v8u16)__builtin_msa_ceq_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_ceqq_u32(__a, __b) ((v4u32)__builtin_msa_ceq_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_ceqq_s32(__a, __b) ((v4u32)__builtin_msa_ceq_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_ceqq_f32(__a, __b) ((v4u32)__builtin_msa_fceq_w((v4f32)(__a), (v4f32)(__b)))
+#define msa_ceqq_u64(__a, __b) ((v2u64)__builtin_msa_ceq_d((v2i64)(__a), (v2i64)(__b)))
+#define msa_ceqq_s64(__a, __b) ((v2u64)__builtin_msa_ceq_d((v2i64)(__a), (v2i64)(__b)))
+#define msa_ceqq_f64(__a, __b) ((v2u64)__builtin_msa_fceq_d((v2f64)(__a), (v2f64)(__b)))
+
+/* Compare less-than: clt -> ri = ai < bi ? 1...1:0...0 */
+#define msa_cltq_u8(__a, __b)  ((v16u8)__builtin_msa_clt_u_b((v16u8)(__a), (v16u8)(__b)))
+#define msa_cltq_s8(__a, __b)  ((v16u8)__builtin_msa_clt_s_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_cltq_u16(__a, __b) ((v8u16)__builtin_msa_clt_u_h((v8u16)(__a), (v8u16)(__b)))
+#define msa_cltq_s16(__a, __b) ((v8u16)__builtin_msa_clt_s_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_cltq_u32(__a, __b) ((v4u32)__builtin_msa_clt_u_w((v4u32)(__a), (v4u32)(__b)))
+#define msa_cltq_s32(__a, __b) ((v4u32)__builtin_msa_clt_s_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_cltq_f32(__a, __b) ((v4u32)__builtin_msa_fclt_w((v4f32)(__a), (v4f32)(__b)))
+#define msa_cltq_u64(__a, __b) ((v2u64)__builtin_msa_clt_u_d((v2u64)(__a), (v2u64)(__b)))
+#define msa_cltq_s64(__a, __b) ((v2u64)__builtin_msa_clt_s_d((v2i64)(__a), (v2i64)(__b)))
+#define msa_cltq_f64(__a, __b) ((v2u64)__builtin_msa_fclt_d((v2f64)(__a), (v2f64)(__b)))
+
+/* compare greater-than: cgt -> ri = ai > bi ? 1...1:0...0 */
+#define msa_cgtq_u8(__a, __b)  ((v16u8)__builtin_msa_clt_u_b((v16u8)(__b), (v16u8)(__a)))
+#define msa_cgtq_s8(__a, __b)  ((v16u8)__builtin_msa_clt_s_b((v16i8)(__b), (v16i8)(__a)))
+#define msa_cgtq_u16(__a, __b) ((v8u16)__builtin_msa_clt_u_h((v8u16)(__b), (v8u16)(__a)))
+#define msa_cgtq_s16(__a, __b) ((v8u16)__builtin_msa_clt_s_h((v8i16)(__b), (v8i16)(__a)))
+#define msa_cgtq_u32(__a, __b) ((v4u32)__builtin_msa_clt_u_w((v4u32)(__b), (v4u32)(__a)))
+#define msa_cgtq_s32(__a, __b) ((v4u32)__builtin_msa_clt_s_w((v4i32)(__b), (v4i32)(__a)))
+#define msa_cgtq_f32(__a, __b) ((v4u32)__builtin_msa_fclt_w((v4f32)(__b), (v4f32)(__a)))
+#define msa_cgtq_u64(__a, __b) ((v2u64)__builtin_msa_clt_u_d((v2u64)(__b), (v2u64)(__a)))
+#define msa_cgtq_s64(__a, __b) ((v2u64)__builtin_msa_clt_s_d((v2i64)(__b), (v2i64)(__a)))
+#define msa_cgtq_f64(__a, __b) ((v2u64)__builtin_msa_fclt_d((v2f64)(__b), (v2f64)(__a)))
+
+/* compare less-equal: cle -> ri = ai <= bi ? 1...1:0...0 */
+#define msa_cleq_u8(__a, __b)  ((v16u8)__builtin_msa_cle_u_b((v16u8)(__a), (v16u8)(__b)))
+#define msa_cleq_s8(__a, __b)  ((v16u8)__builtin_msa_cle_s_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_cleq_u16(__a, __b) ((v8u16)__builtin_msa_cle_u_h((v8u16)(__a), (v8u16)(__b)))
+#define msa_cleq_s16(__a, __b) ((v8u16)__builtin_msa_cle_s_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_cleq_u32(__a, __b) ((v4u32)__builtin_msa_cle_u_w((v4u32)(__a), (v4u32)(__b)))
+#define msa_cleq_s32(__a, __b) ((v4u32)__builtin_msa_cle_s_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_cleq_f32(__a, __b) ((v4u32)__builtin_msa_fcle_w((v4f32)(__a), (v4f32)(__b)))
+#define msa_cleq_u64(__a, __b) ((v2u64)__builtin_msa_cle_u_d((v2u64)(__a), (v2u64)(__b)))
+#define msa_cleq_s64(__a, __b) ((v2u64)__builtin_msa_cle_s_d((v2i64)(__a), (v2i64)(__b)))
+#define msa_cleq_f64(__a, __b) ((v2u64)__builtin_msa_fcle_d((v2f64)(__a), (v2f64)(__b)))
+
+/* compare greater-equal: cge -> ri = ai >= bi ? 1...1:0...0 */
+#define msa_cgeq_u8(__a, __b)  ((v16u8)__builtin_msa_cle_u_b((v16u8)(__b), (v16u8)(__a)))
+#define msa_cgeq_s8(__a, __b)  ((v16u8)__builtin_msa_cle_s_b((v16i8)(__b), (v16i8)(__a)))
+#define msa_cgeq_u16(__a, __b) ((v8u16)__builtin_msa_cle_u_h((v8u16)(__b), (v8u16)(__a)))
+#define msa_cgeq_s16(__a, __b) ((v8u16)__builtin_msa_cle_s_h((v8i16)(__b), (v8i16)(__a)))
+#define msa_cgeq_u32(__a, __b) ((v4u32)__builtin_msa_cle_u_w((v4u32)(__b), (v4u32)(__a)))
+#define msa_cgeq_s32(__a, __b) ((v4u32)__builtin_msa_cle_s_w((v4i32)(__b), (v4i32)(__a)))
+#define msa_cgeq_f32(__a, __b) ((v4u32)__builtin_msa_fcle_w((v4f32)(__b), (v4f32)(__a)))
+#define msa_cgeq_u64(__a, __b) ((v2u64)__builtin_msa_cle_u_d((v2u64)(__b), (v2u64)(__a)))
+#define msa_cgeq_s64(__a, __b) ((v2u64)__builtin_msa_cle_s_d((v2i64)(__b), (v2i64)(__a)))
+#define msa_cgeq_f64(__a, __b) ((v2u64)__builtin_msa_fcle_d((v2f64)(__b), (v2f64)(__a)))
+
+/* Shift Left Logical: shl -> ri = ai << bi; */
+#define msa_shlq_u8(__a, __b)  ((v16u8)__builtin_msa_sll_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_shlq_s8(__a, __b)  ((v16i8)__builtin_msa_sll_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_shlq_u16(__a, __b) ((v8u16)__builtin_msa_sll_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_shlq_s16(__a, __b) ((v8i16)__builtin_msa_sll_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_shlq_u32(__a, __b) ((v4u32)__builtin_msa_sll_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_shlq_s32(__a, __b) ((v4i32)__builtin_msa_sll_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_shlq_u64(__a, __b) ((v2u64)__builtin_msa_sll_d((v2i64)(__a), (v2i64)(__b)))
+#define msa_shlq_s64(__a, __b) ((v2i64)__builtin_msa_sll_d((v2i64)(__a), (v2i64)(__b)))
+
+/* Immediate Shift Left Logical: shl -> ri = ai << imm; */
+#define msa_shlq_n_u8(__a, __imm)  ((v16u8)__builtin_msa_slli_b((v16i8)(__a), __imm))
+#define msa_shlq_n_s8(__a, __imm)  ((v16i8)__builtin_msa_slli_b((v16i8)(__a), __imm))
+#define msa_shlq_n_u16(__a, __imm) ((v8u16)__builtin_msa_slli_h((v8i16)(__a), __imm))
+#define msa_shlq_n_s16(__a, __imm) ((v8i16)__builtin_msa_slli_h((v8i16)(__a), __imm))
+#define msa_shlq_n_u32(__a, __imm) ((v4u32)__builtin_msa_slli_w((v4i32)(__a), __imm))
+#define msa_shlq_n_s32(__a, __imm) ((v4i32)__builtin_msa_slli_w((v4i32)(__a), __imm))
+#define msa_shlq_n_u64(__a, __imm) ((v2u64)__builtin_msa_slli_d((v2i64)(__a), __imm))
+#define msa_shlq_n_s64(__a, __imm) ((v2i64)__builtin_msa_slli_d((v2i64)(__a), __imm))
+
+/* shift right: shrq -> ri = ai >> bi; */
+#define msa_shrq_u8(__a, __b)  ((v16u8)__builtin_msa_srl_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_shrq_s8(__a, __b)  ((v16i8)__builtin_msa_sra_b((v16i8)(__a), (v16i8)(__b)))
+#define msa_shrq_u16(__a, __b) ((v8u16)__builtin_msa_srl_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_shrq_s16(__a, __b) ((v8i16)__builtin_msa_sra_h((v8i16)(__a), (v8i16)(__b)))
+#define msa_shrq_u32(__a, __b) ((v4u32)__builtin_msa_srl_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_shrq_s32(__a, __b) ((v4i32)__builtin_msa_sra_w((v4i32)(__a), (v4i32)(__b)))
+#define msa_shrq_u64(__a, __b) ((v2u64)__builtin_msa_srl_d((v2i64)(__a), (v2i64)(__b)))
+#define msa_shrq_s64(__a, __b) ((v2i64)__builtin_msa_sra_d((v2i64)(__a), (v2i64)(__b)))
+
+/* Immediate Shift Right: shr -> ri = ai >> imm; */
+#define msa_shrq_n_u8(__a, __imm)  ((v16u8)__builtin_msa_srli_b((v16i8)(__a), __imm))
+#define msa_shrq_n_s8(__a, __imm)  ((v16i8)__builtin_msa_srai_b((v16i8)(__a), __imm))
+#define msa_shrq_n_u16(__a, __imm) ((v8u16)__builtin_msa_srli_h((v8i16)(__a), __imm))
+#define msa_shrq_n_s16(__a, __imm) ((v8i16)__builtin_msa_srai_h((v8i16)(__a), __imm))
+#define msa_shrq_n_u32(__a, __imm) ((v4u32)__builtin_msa_srli_w((v4i32)(__a), __imm))
+#define msa_shrq_n_s32(__a, __imm) ((v4i32)__builtin_msa_srai_w((v4i32)(__a), __imm))
+#define msa_shrq_n_u64(__a, __imm) ((v2u64)__builtin_msa_srli_d((v2i64)(__a), __imm))
+#define msa_shrq_n_s64(__a, __imm) ((v2i64)__builtin_msa_srai_d((v2i64)(__a), __imm))
+
+/* Immediate Shift Right Rounded: shr -> ri = ai >> (rounded)imm; */
+#define msa_rshrq_n_u8(__a, __imm)  ((v16u8)__builtin_msa_srlri_b((v16i8)(__a), __imm))
+#define msa_rshrq_n_s8(__a, __imm)  ((v16i8)__builtin_msa_srari_b((v16i8)(__a), __imm))
+#define msa_rshrq_n_u16(__a, __imm) ((v8u16)__builtin_msa_srlri_h((v8i16)(__a), __imm))
+#define msa_rshrq_n_s16(__a, __imm) ((v8i16)__builtin_msa_srari_h((v8i16)(__a), __imm))
+#define msa_rshrq_n_u32(__a, __imm) ((v4u32)__builtin_msa_srlri_w((v4i32)(__a), __imm))
+#define msa_rshrq_n_s32(__a, __imm) ((v4i32)__builtin_msa_srari_w((v4i32)(__a), __imm))
+#define msa_rshrq_n_u64(__a, __imm) ((v2u64)__builtin_msa_srlri_d((v2i64)(__a), __imm))
+#define msa_rshrq_n_s64(__a, __imm) ((v2i64)__builtin_msa_srari_d((v2i64)(__a), __imm))
+
+/* Vector saturating rounding shift left, qrshl -> ri = ai << bi; */
+#define msa_qrshrq_s32(a, b)  ((v4i32)__msa_srar_w((v4i32)(a), (v4i32)(b)))
+
+/* Rename the msa builtin func to unify the name style for intrin_msa.hpp */
+#define msa_qaddq_u8          __builtin_msa_adds_u_b
+#define msa_qaddq_s8          __builtin_msa_adds_s_b
+#define msa_qaddq_u16         __builtin_msa_adds_u_h
+#define msa_qaddq_s16         __builtin_msa_adds_s_h
+#define msa_qaddq_u32         __builtin_msa_adds_u_w
+#define msa_qaddq_s32         __builtin_msa_adds_s_w
+#define msa_qaddq_u64         __builtin_msa_adds_u_d
+#define msa_qaddq_s64         __builtin_msa_adds_s_d
+#define msa_addq_u8(a, b)     ((v16u8)__builtin_msa_addv_b((v16i8)(a), (v16i8)(b)))
+#define msa_addq_s8           __builtin_msa_addv_b
+#define msa_addq_u16(a, b)    ((v8u16)__builtin_msa_addv_h((v8i16)(a), (v8i16)(b)))
+#define msa_addq_s16          __builtin_msa_addv_h
+#define msa_addq_u32(a, b)    ((v4u32)__builtin_msa_addv_w((v4i32)(a), (v4i32)(b)))
+#define msa_addq_s32          __builtin_msa_addv_w
+#define msa_addq_f32          __builtin_msa_fadd_w
+#define msa_addq_u64(a, b)    ((v2u64)__builtin_msa_addv_d((v2i64)(a), (v2i64)(b)))
+#define msa_addq_s64          __builtin_msa_addv_d
+#define msa_addq_f64          __builtin_msa_fadd_d
+#define msa_qsubq_u8          __builtin_msa_subs_u_b
+#define msa_qsubq_s8          __builtin_msa_subs_s_b
+#define msa_qsubq_u16         __builtin_msa_subs_u_h
+#define msa_qsubq_s16         __builtin_msa_subs_s_h
+#define msa_subq_u8(a, b)     ((v16u8)__builtin_msa_subv_b((v16i8)(a), (v16i8)(b)))
+#define msa_subq_s8           __builtin_msa_subv_b
+#define msa_subq_u16(a, b)    ((v8u16)__builtin_msa_subv_h((v8i16)(a), (v8i16)(b)))
+#define msa_subq_s16          __builtin_msa_subv_h
+#define msa_subq_u32(a, b)    ((v4u32)__builtin_msa_subv_w((v4i32)(a), (v4i32)(b)))
+#define msa_subq_s32          __builtin_msa_subv_w
+#define msa_subq_f32          __builtin_msa_fsub_w
+#define msa_subq_u64(a, b)    ((v2u64)__builtin_msa_subv_d((v2i64)(a), (v2i64)(b)))
+#define msa_subq_s64          __builtin_msa_subv_d
+#define msa_subq_f64          __builtin_msa_fsub_d
+#define msa_mulq_u8(a, b)     ((v16u8)__builtin_msa_mulv_b((v16i8)(a), (v16i8)(b)))
+#define msa_mulq_s8(a, b)     ((v16i8)__builtin_msa_mulv_b((v16i8)(a), (v16i8)(b)))
+#define msa_mulq_u16(a, b)    ((v8u16)__builtin_msa_mulv_h((v8i16)(a), (v8i16)(b)))
+#define msa_mulq_s16(a, b)    ((v8i16)__builtin_msa_mulv_h((v8i16)(a), (v8i16)(b)))
+#define msa_mulq_u32(a, b)    ((v4u32)__builtin_msa_mulv_w((v4i32)(a), (v4i32)(b)))
+#define msa_mulq_s32(a, b)    ((v4i32)__builtin_msa_mulv_w((v4i32)(a), (v4i32)(b)))
+#define msa_mulq_u64(a, b)    ((v2u64)__builtin_msa_mulv_d((v2i64)(a), (v2i64)(b)))
+#define msa_mulq_s64(a, b)    ((v2i64)__builtin_msa_mulv_d((v2i64)(a), (v2i64)(b)))
+#define msa_mulq_f32          __builtin_msa_fmul_w
+#define msa_mulq_f64          __builtin_msa_fmul_d
+#define msa_divq_f32          __builtin_msa_fdiv_w
+#define msa_divq_f64          __builtin_msa_fdiv_d
+#define msa_dotp_s_h          __builtin_msa_dotp_s_h
+#define msa_dotp_s_w          __builtin_msa_dotp_s_w
+#define msa_dotp_s_d          __builtin_msa_dotp_s_d
+#define msa_dotp_u_h          __builtin_msa_dotp_u_h
+#define msa_dotp_u_w          __builtin_msa_dotp_u_w
+#define msa_dotp_u_d          __builtin_msa_dotp_u_d
+#define msa_dpadd_s_h         __builtin_msa_dpadd_s_h
+#define msa_dpadd_s_w         __builtin_msa_dpadd_s_w
+#define msa_dpadd_s_d         __builtin_msa_dpadd_s_d
+#define msa_dpadd_u_h         __builtin_msa_dpadd_u_h
+#define msa_dpadd_u_w         __builtin_msa_dpadd_u_w
+#define msa_dpadd_u_d         __builtin_msa_dpadd_u_d
+
+#define ILVRL_B2(RTYPE, in0, in1, low, hi) do {       \
+      low = (RTYPE)__builtin_msa_ilvr_b((v16i8)(in0), (v16i8)(in1));  \
+      hi  = (RTYPE)__builtin_msa_ilvl_b((v16i8)(in0), (v16i8)(in1));  \
+    } while (0)
+#define ILVRL_B2_UB(...) ILVRL_B2(v16u8, __VA_ARGS__)
+#define ILVRL_B2_SB(...) ILVRL_B2(v16i8, __VA_ARGS__)
+#define ILVRL_B2_UH(...) ILVRL_B2(v8u16, __VA_ARGS__)
+#define ILVRL_B2_SH(...) ILVRL_B2(v8i16, __VA_ARGS__)
+#define ILVRL_B2_SW(...) ILVRL_B2(v4i32, __VA_ARGS__)
+
+#define ILVRL_H2(RTYPE, in0, in1, low, hi) do {       \
+      low = (RTYPE)__builtin_msa_ilvr_h((v8i16)(in0), (v8i16)(in1));  \
+      hi  = (RTYPE)__builtin_msa_ilvl_h((v8i16)(in0), (v8i16)(in1));  \
+    } while (0)
+#define ILVRL_H2_UB(...) ILVRL_H2(v16u8, __VA_ARGS__)
+#define ILVRL_H2_SB(...) ILVRL_H2(v16i8, __VA_ARGS__)
+#define ILVRL_H2_UH(...) ILVRL_H2(v8u16, __VA_ARGS__)
+#define ILVRL_H2_SH(...) ILVRL_H2(v8i16, __VA_ARGS__)
+#define ILVRL_H2_SW(...) ILVRL_H2(v4i32, __VA_ARGS__)
+#define ILVRL_H2_UW(...) ILVRL_H2(v4u32, __VA_ARGS__)
+
+#define ILVRL_W2(RTYPE, in0, in1, low, hi) do {       \
+      low = (RTYPE)__builtin_msa_ilvr_w((v4i32)(in0), (v4i32)(in1));  \
+      hi  = (RTYPE)__builtin_msa_ilvl_w((v4i32)(in0), (v4i32)(in1));  \
+    } while (0)
+#define ILVRL_W2_UB(...) ILVRL_W2(v16u8, __VA_ARGS__)
+#define ILVRL_W2_SH(...) ILVRL_W2(v8i16, __VA_ARGS__)
+#define ILVRL_W2_SW(...) ILVRL_W2(v4i32, __VA_ARGS__)
+#define ILVRL_W2_UW(...) ILVRL_W2(v4u32, __VA_ARGS__)
+
+/* absq, qabsq (r = |a|;) */
+#define msa_absq_s8(a)        __builtin_msa_add_a_b(a, __builtin_msa_fill_b(0))
+#define msa_absq_s16(a)       __builtin_msa_add_a_h(a, __builtin_msa_fill_h(0))
+#define msa_absq_s32(a)       __builtin_msa_add_a_w(a, __builtin_msa_fill_w(0))
+#define msa_absq_s64(a)       __builtin_msa_add_a_d(a, __builtin_msa_fill_d(0))
+#define msa_absq_f32(a)       ((v4f32)__builtin_msa_bclri_w((v4u32)(a), 31))
+#define msa_absq_f64(a)       ((v2f64)__builtin_msa_bclri_d((v2u64)(a), 63))
+#define msa_qabsq_s8(a)       __builtin_msa_adds_a_b(a, __builtin_msa_fill_b(0))
+#define msa_qabsq_s16(a)      __builtin_msa_adds_a_h(a, __builtin_msa_fill_h(0))
+#define msa_qabsq_s32(a)      __builtin_msa_adds_a_w(a, __builtin_msa_fill_w(0))
+#define msa_qabsq_s64(a)      __builtin_msa_adds_a_d(a, __builtin_msa_fill_d(0))
+
+/* abdq, qabdq (r = |a - b|;) */
+#define msa_abdq_u8           __builtin_msa_asub_u_b
+#define msa_abdq_s8           __builtin_msa_asub_s_b
+#define msa_abdq_u16          __builtin_msa_asub_u_h
+#define msa_abdq_s16          __builtin_msa_asub_s_h
+#define msa_abdq_u32          __builtin_msa_asub_u_w
+#define msa_abdq_s32          __builtin_msa_asub_s_w
+#define msa_abdq_u64          __builtin_msa_asub_u_d
+#define msa_abdq_s64          __builtin_msa_asub_s_d
+#define msa_abdq_f32(a, b)    msa_absq_f32(__builtin_msa_fsub_w(a, b))
+#define msa_abdq_f64(a, b)    msa_absq_f64(__builtin_msa_fsub_d(a, b))
+#define msa_qabdq_s8(a, b)    msa_qabsq_s8(__builtin_msa_subs_s_b(a, b))
+#define msa_qabdq_s16(a, b)   msa_qabsq_s16(__builtin_msa_subs_s_h(a, b))
+#define msa_qabdq_s32(a, b)   msa_qabsq_s32(__builtin_msa_subs_s_w(a, b))
+#define msa_qabdq_s64(a, b)   msa_qabsq_s64(__builtin_msa_subs_s_d(a, b))
+
+/* sqrtq, rsqrtq */
+#define msa_sqrtq_f32         __builtin_msa_fsqrt_w
+#define msa_sqrtq_f64         __builtin_msa_fsqrt_d
+#define msa_rsqrtq_f32        __builtin_msa_frsqrt_w
+#define msa_rsqrtq_f64        __builtin_msa_frsqrt_d
+
+
+/* mlaq: r = a + b * c; */
+__extension__ extern __inline v4i32
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__))
+msa_mlaq_s32(v4i32 __a, v4i32 __b, v4i32 __c)
+{
+  __asm__ volatile("maddv.w %w[__a], %w[__b], %w[__c]\n"
+               // Outputs
+               : [__a] "+f"(__a)
+               // Inputs
+               : [__b] "f"(__b), [__c] "f"(__c));
+  return __a;
+}
+
+__extension__ extern __inline v2i64
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__))
+msa_mlaq_s64(v2i64 __a, v2i64 __b, v2i64 __c)
+{
+  __asm__ volatile("maddv.d %w[__a], %w[__b], %w[__c]\n"
+               // Outputs
+               : [__a] "+f"(__a)
+               // Inputs
+               : [__b] "f"(__b), [__c] "f"(__c));
+  return __a;
+}
+
+__extension__ extern __inline v4f32
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__))
+msa_mlaq_f32(v4f32 __a, v4f32 __b, v4f32 __c)
+{
+  __asm__ volatile("fmadd.w %w[__a], %w[__b], %w[__c]\n"
+               // Outputs
+               : [__a] "+f"(__a)
+               // Inputs
+               : [__b] "f"(__b), [__c] "f"(__c));
+  return __a;
+}
+
+__extension__ extern __inline v2f64
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__))
+msa_mlaq_f64(v2f64 __a, v2f64 __b, v2f64 __c)
+{
+  __asm__ volatile("fmadd.d %w[__a], %w[__b], %w[__c]\n"
+               // Outputs
+               : [__a] "+f"(__a)
+               // Inputs
+               : [__b] "f"(__b), [__c] "f"(__c));
+  return __a;
+}
+
+/* cntq */
+#define msa_cntq_s8           __builtin_msa_pcnt_b
+#define msa_cntq_s16          __builtin_msa_pcnt_h
+#define msa_cntq_s32          __builtin_msa_pcnt_w
+#define msa_cntq_s64          __builtin_msa_pcnt_d
+
+/* bslq (a: mask; r = b(if a == 0); r = c(if a == 1);) */
+#define msa_bslq_u8           __builtin_msa_bsel_v
+
+/* ilvrq, ilvlq (For EL only, ilvrq: b0, a0, b1, a1; ilvlq: b2, a2, b3, a3;) */
+#define msa_ilvrq_s8          __builtin_msa_ilvr_b
+#define msa_ilvrq_s16         __builtin_msa_ilvr_h
+#define msa_ilvrq_s32         __builtin_msa_ilvr_w
+#define msa_ilvrq_s64         __builtin_msa_ilvr_d
+#define msa_ilvlq_s8          __builtin_msa_ilvl_b
+#define msa_ilvlq_s16         __builtin_msa_ilvl_h
+#define msa_ilvlq_s32         __builtin_msa_ilvl_w
+#define msa_ilvlq_s64         __builtin_msa_ilvl_d
+
+/* ilvevq, ilvodq (ilvevq: b0, a0, b2, a2; ilvodq: b1, a1, b3, a3; ) */
+#define msa_ilvevq_s8         __builtin_msa_ilvev_b
+#define msa_ilvevq_s16        __builtin_msa_ilvev_h
+#define msa_ilvevq_s32        __builtin_msa_ilvev_w
+#define msa_ilvevq_s64        __builtin_msa_ilvev_d
+#define msa_ilvodq_s8         __builtin_msa_ilvod_b
+#define msa_ilvodq_s16        __builtin_msa_ilvod_h
+#define msa_ilvodq_s32        __builtin_msa_ilvod_w
+#define msa_ilvodq_s64        __builtin_msa_ilvod_d
+
+/* extq (r = (a || b); a concatenation b and get elements from index c) */
+#ifdef _MIPSEB
+#define msa_extq_s8(a, b, c)  \
+(__builtin_msa_vshf_b(__builtin_msa_subv_b((v16i8)((v2i64){0x1716151413121110, 0x1F1E1D1C1B1A1918}), __builtin_msa_fill_b(c)), a, b))
+#define msa_extq_s16(a, b, c) \
+(__builtin_msa_vshf_h(__builtin_msa_subv_h((v8i16)((v2i64){0x000B000A00090008, 0x000F000E000D000C}), __builtin_msa_fill_h(c)), a, b))
+#define msa_extq_s32(a, b, c) \
+(__builtin_msa_vshf_w(__builtin_msa_subv_w((v4i32)((v2i64){0x0000000500000004, 0x0000000700000006}), __builtin_msa_fill_w(c)), a, b))
+#define msa_extq_s64(a, b, c) \
+(__builtin_msa_vshf_d(__builtin_msa_subv_d((v2i64){0x0000000000000002, 0x0000000000000003}, __builtin_msa_fill_d(c)), a, b))
+#else
+#define msa_extq_s8(a, b, c)  \
+(__builtin_msa_vshf_b(__builtin_msa_addv_b((v16i8)((v2i64){0x0706050403020100, 0x0F0E0D0C0B0A0908}), __builtin_msa_fill_b(c)), b, a))
+#define msa_extq_s16(a, b, c) \
+(__builtin_msa_vshf_h(__builtin_msa_addv_h((v8i16)((v2i64){0x0003000200010000, 0x0007000600050004}), __builtin_msa_fill_h(c)), b, a))
+#define msa_extq_s32(a, b, c) \
+(__builtin_msa_vshf_w(__builtin_msa_addv_w((v4i32)((v2i64){0x0000000100000000, 0x0000000300000002}), __builtin_msa_fill_w(c)), b, a))
+#define msa_extq_s64(a, b, c) \
+(__builtin_msa_vshf_d(__builtin_msa_addv_d((v2i64){0x0000000000000000, 0x0000000000000001}, __builtin_msa_fill_d(c)), b, a))
+#endif /* _MIPSEB */
+
+/* cvttruncq, cvttintq, cvtrintq */
+#define msa_cvttruncq_u32_f32 __builtin_msa_ftrunc_u_w
+#define msa_cvttruncq_s32_f32 __builtin_msa_ftrunc_s_w
+#define msa_cvttruncq_u64_f64 __builtin_msa_ftrunc_u_d
+#define msa_cvttruncq_s64_f64 __builtin_msa_ftrunc_s_d
+#define msa_cvttintq_u32_f32  __builtin_msa_ftint_u_w
+#define msa_cvttintq_s32_f32  __builtin_msa_ftint_s_w
+#define msa_cvttintq_u64_f64  __builtin_msa_ftint_u_d
+#define msa_cvttintq_s64_f64  __builtin_msa_ftint_s_d
+#define msa_cvtrintq_f32      __builtin_msa_frint_w
+#define msa_cvtrintq_f64      __builtin_msa_frint_d
+
+/* cvtfintq, cvtfq */
+#define msa_cvtfintq_f32_u32  __builtin_msa_ffint_u_w
+#define msa_cvtfintq_f32_s32  __builtin_msa_ffint_s_w
+#define msa_cvtfintq_f64_u64  __builtin_msa_ffint_u_d
+#define msa_cvtfintq_f64_s64  __builtin_msa_ffint_s_d
+#define msa_cvtfq_f32_f64     __builtin_msa_fexdo_w
+#define msa_cvtflq_f64_f32    __builtin_msa_fexupr_d
+#define msa_cvtfhq_f64_f32    __builtin_msa_fexupl_d
+
+#define msa_addl_u8(a, b)     ((v8u16)__builtin_msa_addv_h((v8i16)V8U8_2_V8I16(a), (v8i16)V8U8_2_V8I16(b)))
+#define msa_addl_s8(a, b)     (__builtin_msa_addv_h((v8i16)V8I8_2_V8I16(a), (v8i16)V8I8_2_V8I16(b)))
+#define msa_addl_u16(a, b)    ((v4u32)__builtin_msa_addv_w((v4i32)V4U16_2_V4I32(a), (v4i32)V4U16_2_V4I32(b)))
+#define msa_addl_s16(a, b)    (__builtin_msa_addv_w((v4i32)V4I16_2_V4I32(a), (v4i32)V4I16_2_V4I32(b)))
+#define msa_subl_s16(a, b)    (__builtin_msa_subv_w((v4i32)V4I16_2_V4I32(a), (v4i32)V4I16_2_V4I32(b)))
+#define msa_recpeq_f32        __builtin_msa_frcp_w
+#define msa_recpsq_f32(a, b)  (__builtin_msa_fsub_w(msa_dupq_n_f32(2.0f), __builtin_msa_fmul_w(a, b)))
+
+#define MSA_INTERLEAVED_IMPL_LOAD2_STORE2(_Tp, _Tpv, _Tpvs, suffix, df, nlanes) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld2q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b) \
+{ \
+  _Tpv v0 = msa_ld1q_##suffix(ptr); \
+  _Tpv v1 = msa_ld1q_##suffix(ptr + nlanes); \
+  *a = (_Tpv)__builtin_msa_pckev_##df((_Tpvs)v1, (_Tpvs)v0); \
+  *b = (_Tpv)__builtin_msa_pckod_##df((_Tpvs)v1, (_Tpvs)v0); \
+} \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st2q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b) \
+{ \
+  msa_st1q_##suffix(ptr, (_Tpv)__builtin_msa_ilvr_##df((_Tpvs)b, (_Tpvs)a)); \
+  msa_st1q_##suffix(ptr + nlanes, (_Tpv)__builtin_msa_ilvl_##df((_Tpvs)b, (_Tpvs)a)); \
+}
+
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(uint8_t, v16u8, v16i8, u8, b, 16)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(int8_t, v16i8, v16i8, s8, b, 16)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(uint16_t, v8u16, v8i16, u16, h, 8)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(int16_t, v8i16, v8i16, s16, h, 8)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(uint32_t, v4u32, v4i32, u32, w, 4)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(int32_t, v4i32, v4i32, s32, w, 4)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(float, v4f32, v4i32, f32, w, 4)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(uint64_t, v2u64, v2i64, u64, d, 2)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(int64_t, v2i64, v2i64, s64, d, 2)
+MSA_INTERLEAVED_IMPL_LOAD2_STORE2(double, v2f64, v2i64, f64, d, 2)
+
+#ifdef _MIPSEB
+#define MSA_INTERLEAVED_IMPL_LOAD3_8(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld3q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c) \
+{ \
+  _Tpv v0 = msa_ld1q_##suffix(ptr); \
+  _Tpv v1 = msa_ld1q_##suffix(ptr + 16); \
+  _Tpv v2 = msa_ld1q_##suffix(ptr + 32); \
+  _Tpvs v3 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0704011F1F1F1F1F, 0x1F1C191613100D0A}), (_Tpvs)v0, (_Tpvs)v1); \
+  *a = (_Tpv)__builtin_msa_vshf_b((_Tpvs)((v2i64){0x1716150E0B080502, 0x1F1E1D1C1B1A1918}), v3, (_Tpvs)v2); \
+  v3 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0603001F1F1F1F1F, 0x1E1B1815120F0C09}), (_Tpvs)v0, (_Tpvs)v1); \
+  *b = (_Tpv)__builtin_msa_vshf_b((_Tpvs)((v2i64){0x1716150D0A070401, 0x1F1E1D1C1B1A1918}), v3, (_Tpvs)v2); \
+  v3 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x05021F1F1F1F1F1F, 0x1D1A1714110E0B08}), (_Tpvs)v0, (_Tpvs)v1); \
+  *c = (_Tpv)__builtin_msa_vshf_b((_Tpvs)((v2i64){0x17160F0C09060300, 0x1F1E1D1C1B1A1918}), v3, (_Tpvs)v2); \
+}
+#else
+#define MSA_INTERLEAVED_IMPL_LOAD3_8(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld3q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c) \
+{ \
+  _Tpv v0 = msa_ld1q_##suffix(ptr); \
+  _Tpv v1 = msa_ld1q_##suffix(ptr + 16); \
+  _Tpv v2 = msa_ld1q_##suffix(ptr + 32); \
+  _Tpvs v3 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x15120F0C09060300, 0x00000000001E1B18}), (_Tpvs)v1, (_Tpvs)v0); \
+  *a = (_Tpv)__builtin_msa_vshf_b((_Tpvs)((v2i64){0x0706050403020100, 0x1D1A1714110A0908}), (_Tpvs)v2, v3); \
+  v3 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x1613100D0A070401, 0x00000000001F1C19}), (_Tpvs)v1, (_Tpvs)v0); \
+  *b = (_Tpv)__builtin_msa_vshf_b((_Tpvs)((v2i64){0x0706050403020100, 0x1E1B1815120A0908}), (_Tpvs)v2, v3); \
+  v3 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x1714110E0B080502, 0x0000000000001D1A}), (_Tpvs)v1, (_Tpvs)v0); \
+  *c = (_Tpv)__builtin_msa_vshf_b((_Tpvs)((v2i64){0x0706050403020100, 0x1F1C191613100908}), (_Tpvs)v2, v3); \
+}
+#endif
+
+MSA_INTERLEAVED_IMPL_LOAD3_8(uint8_t, v16u8, v16i8, u8)
+MSA_INTERLEAVED_IMPL_LOAD3_8(int8_t, v16i8, v16i8, s8)
+
+#ifdef _MIPSEB
+#define MSA_INTERLEAVED_IMPL_LOAD3_16(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld3q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c) \
+{ \
+  _Tpv v0 = msa_ld1q_##suffix(ptr); \
+  _Tpv v1 = msa_ld1q_##suffix(ptr + 8); \
+  _Tpv v2 = msa_ld1q_##suffix(ptr + 16); \
+  _Tpvs v3 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x00030000000F000F, 0x000F000C00090006}), (_Tpvs)v1, (_Tpvs)v0); \
+  *a = (_Tpv)__builtin_msa_vshf_h((_Tpvs)((v2i64){0x000B000A00050002, 0x000F000E000D000C}), (_Tpvs)v2, v3); \
+  v3 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0002000F000F000F, 0x000E000B00080005}), (_Tpvs)v1, (_Tpvs)v0); \
+  *b = (_Tpv)__builtin_msa_vshf_h((_Tpvs)((v2i64){0x000B000700040001, 0x000F000E000D000C}), (_Tpvs)v2, v3); \
+  v3 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0001000F000F000F, 0x000D000A00070004}), (_Tpvs)v1, (_Tpvs)v0); \
+  *c = (_Tpv)__builtin_msa_vshf_h((_Tpvs)((v2i64){0x000B000600030000, 0x000F000E000D000C}), (_Tpvs)v2, v3); \
+}
+#else
+#define MSA_INTERLEAVED_IMPL_LOAD3_16(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld3q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c) \
+{ \
+  _Tpv v0 = msa_ld1q_##suffix(ptr); \
+  _Tpv v1 = msa_ld1q_##suffix(ptr + 8); \
+  _Tpv v2 = msa_ld1q_##suffix(ptr + 16); \
+  _Tpvs v3 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0009000600030000, 0x00000000000F000C}), (_Tpvs)v1, (_Tpvs)v0); \
+  *a = (_Tpv)__builtin_msa_vshf_h((_Tpvs)((v2i64){0x0003000200010000, 0x000D000A00050004}), (_Tpvs)v2, v3); \
+  v3 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x000A000700040001, 0x000000000000000D}), (_Tpvs)v1, (_Tpvs)v0); \
+  *b = (_Tpv)__builtin_msa_vshf_h((_Tpvs)((v2i64){0x0003000200010000, 0x000E000B00080004}), (_Tpvs)v2, v3); \
+  v3 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x000B000800050002, 0x000000000000000E}), (_Tpvs)v1, (_Tpvs)v0); \
+  *c = (_Tpv)__builtin_msa_vshf_h((_Tpvs)((v2i64){0x0003000200010000, 0x000F000C00090004}), (_Tpvs)v2, v3); \
+}
+#endif
+
+MSA_INTERLEAVED_IMPL_LOAD3_16(uint16_t, v8u16, v8i16, u16)
+MSA_INTERLEAVED_IMPL_LOAD3_16(int16_t, v8i16, v8i16, s16)
+
+#define MSA_INTERLEAVED_IMPL_LOAD3_32(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld3q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c) \
+{ \
+  _Tpv v00 = msa_ld1q_##suffix(ptr); \
+  _Tpv v01 = msa_ld1q_##suffix(ptr + 4); \
+  _Tpv v02 = msa_ld1q_##suffix(ptr + 8); \
+  _Tpvs v10 = __builtin_msa_ilvr_w((_Tpvs)__builtin_msa_ilvl_d((v2i64)v01, (v2i64)v01), (_Tpvs)v00); \
+  _Tpvs v11 = __builtin_msa_ilvr_w((_Tpvs)v02, (_Tpvs)__builtin_msa_ilvl_d((v2i64)v00, (v2i64)v00)); \
+  _Tpvs v12 = __builtin_msa_ilvr_w((_Tpvs)__builtin_msa_ilvl_d((v2i64)v02, (v2i64)v02), (_Tpvs)v01); \
+  *a = (_Tpv)__builtin_msa_ilvr_w((_Tpvs)__builtin_msa_ilvl_d((v2i64)v11, (v2i64)v11), v10); \
+  *b = (_Tpv)__builtin_msa_ilvr_w(v12, (_Tpvs)__builtin_msa_ilvl_d((v2i64)v10, (v2i64)v10)); \
+  *c = (_Tpv)__builtin_msa_ilvr_w((_Tpvs)__builtin_msa_ilvl_d((v2i64)v12, (v2i64)v12), v11); \
+}
+
+MSA_INTERLEAVED_IMPL_LOAD3_32(uint32_t, v4u32, v4i32, u32)
+MSA_INTERLEAVED_IMPL_LOAD3_32(int32_t, v4i32, v4i32, s32)
+MSA_INTERLEAVED_IMPL_LOAD3_32(float, v4f32, v4i32, f32)
+
+#define MSA_INTERLEAVED_IMPL_LOAD3_64(_Tp, _Tpv, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld3q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c) \
+{ \
+  *((_Tp*)a) = *ptr;           *((_Tp*)b) = *(ptr + 1);     *((_Tp*)c) = *(ptr + 2);     \
+  *((_Tp*)a + 1) = *(ptr + 3); *((_Tp*)b + 1) = *(ptr + 4); *((_Tp*)c + 1) = *(ptr + 5); \
+}
+
+MSA_INTERLEAVED_IMPL_LOAD3_64(uint64_t, v2u64, u64)
+MSA_INTERLEAVED_IMPL_LOAD3_64(int64_t, v2i64, s64)
+MSA_INTERLEAVED_IMPL_LOAD3_64(double, v2f64, f64)
+
+#ifdef _MIPSEB
+#define MSA_INTERLEAVED_IMPL_STORE3_8(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st3q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c) \
+{ \
+  _Tpvs v0 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0F0E0D0C0B1F1F1F, 0x1F1E1D1C1B1A1F1F}), (_Tpvs)b, (_Tpvs)a); \
+  _Tpvs v1 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0D1C140C1B130B1A, 0x1F170F1E160E1D15}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0A09080706051F1F, 0x19181716151F1F1F}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x1D14071C13061B12, 0x170A1F16091E1508}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 16, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x04030201001F1F1F, 0x14131211101F1F1F}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x15021C14011B1300, 0x051F17041E16031D}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 32, (_Tpv)v1); \
+}
+#else
+#define MSA_INTERLEAVED_IMPL_STORE3_8(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st3q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c) \
+{ \
+  _Tpvs v0 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0000050403020100, 0x0000001413121110}), (_Tpvs)b, (_Tpvs)a); \
+  _Tpvs v1 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0A02110901100800, 0x05140C04130B0312}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0000000A09080706, 0x00001A1918171615}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x170A011609001508, 0x0D04190C03180B02}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 16, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x0000000F0E0D0C0B, 0x0000001F1E1D1C1B}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_b((_Tpvs)((v2i64){0x021C09011B08001A, 0x1F0C041E0B031D0A}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 32, (_Tpv)v1); \
+}
+#endif
+
+MSA_INTERLEAVED_IMPL_STORE3_8(uint8_t, v16u8, v16i8, u8)
+MSA_INTERLEAVED_IMPL_STORE3_8(int8_t, v16i8, v16i8, s8)
+
+#ifdef _MIPSEB
+#define MSA_INTERLEAVED_IMPL_STORE3_16(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st3q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c) \
+{ \
+  _Tpvs v0 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x000700060005000F, 0x000F000E000D000F}), (_Tpvs)b, (_Tpvs)a); \
+  _Tpvs v1 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x000A0006000D0009, 0x000F000B0007000E}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x00040003000F000F, 0x000C000B000A000F}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x000E000A0003000D, 0x0005000F000B0004}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 8, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x000200010000000F, 0x00090008000F000F}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0001000E00090000, 0x000B0002000F000A}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 16, (_Tpv)v1); \
+}
+#else
+#define MSA_INTERLEAVED_IMPL_STORE3_16(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st3q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c) \
+{ \
+  _Tpvs v0 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0000000200010000, 0x0000000A00090008}), (_Tpvs)b, (_Tpvs)a); \
+  _Tpvs v1 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0001000800040000, 0x0006000200090005}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0000000500040003, 0x00000000000C000B}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x000B00040000000A, 0x0002000C00050001}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 8, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x0000000000070006, 0x0000000F000E000D}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_h((_Tpvs)((v2i64){0x00050000000D0004, 0x000F00060001000E}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 16, (_Tpv)v1); \
+}
+#endif
+
+MSA_INTERLEAVED_IMPL_STORE3_16(uint16_t, v8u16, v8i16, u16)
+MSA_INTERLEAVED_IMPL_STORE3_16(int16_t, v8i16, v8i16, s16)
+
+#ifdef _MIPSEB
+#define MSA_INTERLEAVED_IMPL_STORE3_32(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st3q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c) \
+{ \
+  _Tpvs v0 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000300000007, 0x0000000700000006}), (_Tpvs)b, (_Tpvs)a); \
+  _Tpvs v1 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000300000006, 0x0000000700000005}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000200000001, 0x0000000500000007}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000700000004, 0x0000000500000002}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 4, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000000000007, 0x0000000400000007}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000500000000, 0x0000000100000007}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 8, (_Tpv)v1); \
+}
+#else
+#define MSA_INTERLEAVED_IMPL_STORE3_32(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st3q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c) \
+{ \
+  _Tpvs v0 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000100000000, 0x0000000000000004}), (_Tpvs)b, (_Tpvs)a); \
+  _Tpvs v1 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000200000000, 0x0000000100000004}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000000000002, 0x0000000600000005}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000500000002, 0x0000000300000000}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 4, (_Tpv)v1); \
+  v0 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000000000003, 0x0000000000000007}), (_Tpvs)b, (_Tpvs)a); \
+  v1 = __builtin_msa_vshf_w((_Tpvs)((v2i64){0x0000000000000006, 0x0000000700000002}), (_Tpvs)c, (_Tpvs)v0); \
+  msa_st1q_##suffix(ptr + 8, (_Tpv)v1); \
+}
+#endif
+
+MSA_INTERLEAVED_IMPL_STORE3_32(uint32_t, v4u32, v4i32, u32)
+MSA_INTERLEAVED_IMPL_STORE3_32(int32_t, v4i32, v4i32, s32)
+MSA_INTERLEAVED_IMPL_STORE3_32(float, v4f32, v4i32, f32)
+
+#define MSA_INTERLEAVED_IMPL_STORE3_64(_Tp, _Tpv, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st3q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c) \
+{ \
+  *ptr = a[0];       *(ptr + 1) = b[0]; *(ptr + 2) = c[0]; \
+  *(ptr + 3) = a[1]; *(ptr + 4) = b[1]; *(ptr + 5) = c[1]; \
+}
+
+MSA_INTERLEAVED_IMPL_STORE3_64(uint64_t, v2u64, u64)
+MSA_INTERLEAVED_IMPL_STORE3_64(int64_t, v2i64, s64)
+MSA_INTERLEAVED_IMPL_STORE3_64(double, v2f64, f64)
+
+#define MSA_INTERLEAVED_IMPL_LOAD4_STORE4(_Tp, _Tpv, _Tpvs, suffix, df, nlanes) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld4q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c, _Tpv* d) \
+{ \
+  _Tpv v0 = msa_ld1q_##suffix(ptr); \
+  _Tpv v1 = msa_ld1q_##suffix(ptr + nlanes); \
+  _Tpv v2 = msa_ld1q_##suffix(ptr + nlanes * 2); \
+  _Tpv v3 = msa_ld1q_##suffix(ptr + nlanes * 3); \
+  _Tpvs t0 = __builtin_msa_pckev_##df((_Tpvs)v1, (_Tpvs)v0); \
+  _Tpvs t1 = __builtin_msa_pckev_##df((_Tpvs)v3, (_Tpvs)v2); \
+  _Tpvs t2 = __builtin_msa_pckod_##df((_Tpvs)v1, (_Tpvs)v0); \
+  _Tpvs t3 = __builtin_msa_pckod_##df((_Tpvs)v3, (_Tpvs)v2); \
+  *a = (_Tpv)__builtin_msa_pckev_##df(t1, t0); \
+  *b = (_Tpv)__builtin_msa_pckev_##df(t3, t2); \
+  *c = (_Tpv)__builtin_msa_pckod_##df(t1, t0); \
+  *d = (_Tpv)__builtin_msa_pckod_##df(t3, t2); \
+} \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st4q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c, const _Tpv d) \
+{ \
+  _Tpvs v0 = __builtin_msa_ilvr_##df((_Tpvs)c, (_Tpvs)a); \
+  _Tpvs v1 = __builtin_msa_ilvr_##df((_Tpvs)d, (_Tpvs)b); \
+  _Tpvs v2 = __builtin_msa_ilvl_##df((_Tpvs)c, (_Tpvs)a); \
+  _Tpvs v3 = __builtin_msa_ilvl_##df((_Tpvs)d, (_Tpvs)b); \
+  msa_st1q_##suffix(ptr, (_Tpv)__builtin_msa_ilvr_##df(v1, v0)); \
+  msa_st1q_##suffix(ptr + nlanes, (_Tpv)__builtin_msa_ilvl_##df(v1, v0)); \
+  msa_st1q_##suffix(ptr + 2 * nlanes, (_Tpv)__builtin_msa_ilvr_##df(v3, v2)); \
+  msa_st1q_##suffix(ptr + 3 * nlanes, (_Tpv)__builtin_msa_ilvl_##df(v3, v2)); \
+}
+
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4(uint8_t, v16u8, v16i8, u8, b, 16)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4(int8_t, v16i8, v16i8, s8, b, 16)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4(uint16_t, v8u16, v8i16, u16, h, 8)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4(int16_t, v8i16, v8i16, s16, h, 8)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4(uint32_t, v4u32, v4i32, u32, w, 4)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4(int32_t, v4i32, v4i32, s32, w, 4)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4(float, v4f32, v4i32, f32, w, 4)
+
+#define MSA_INTERLEAVED_IMPL_LOAD4_STORE4_64(_Tp, _Tpv, _Tpvs, suffix) \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_ld4q_##suffix(const _Tp* ptr, _Tpv* a, _Tpv* b, _Tpv* c, _Tpv* d) \
+{ \
+  _Tpv v0 = msa_ld1q_##suffix(ptr); \
+  _Tpv v1 = msa_ld1q_##suffix(ptr + 2); \
+  _Tpv v2 = msa_ld1q_##suffix(ptr + 4); \
+  _Tpv v3 = msa_ld1q_##suffix(ptr + 6); \
+  *a = (_Tpv)__builtin_msa_ilvr_d((_Tpvs)v2, (_Tpvs)v0); \
+  *b = (_Tpv)__builtin_msa_ilvl_d((_Tpvs)v2, (_Tpvs)v0); \
+  *c = (_Tpv)__builtin_msa_ilvr_d((_Tpvs)v3, (_Tpvs)v1); \
+  *d = (_Tpv)__builtin_msa_ilvl_d((_Tpvs)v3, (_Tpvs)v1); \
+} \
+__extension__ extern __inline void \
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__)) \
+msa_st4q_##suffix(_Tp* ptr, const _Tpv a, const _Tpv b, const _Tpv c, const _Tpv d) \
+{ \
+  msa_st1q_##suffix(ptr, (_Tpv)__builtin_msa_ilvr_d((_Tpvs)b, (_Tpvs)a)); \
+  msa_st1q_##suffix(ptr + 2, (_Tpv)__builtin_msa_ilvr_d((_Tpvs)d, (_Tpvs)c)); \
+  msa_st1q_##suffix(ptr + 4, (_Tpv)__builtin_msa_ilvl_d((_Tpvs)b, (_Tpvs)a)); \
+  msa_st1q_##suffix(ptr + 6, (_Tpv)__builtin_msa_ilvl_d((_Tpvs)d, (_Tpvs)c)); \
+}
+
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4_64(uint64_t, v2u64, v2i64, u64)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4_64(int64_t, v2i64, v2i64, s64)
+MSA_INTERLEAVED_IMPL_LOAD4_STORE4_64(double, v2f64, v2i64, f64)
+
+__extension__ extern __inline v8i16
+__attribute__ ((__always_inline__, __gnu_inline__, __artificial__))
+msa_qdmulhq_n_s16(v8i16 a, int16_t b)
+{
+  v8i16 a_lo, a_hi;
+  ILVRL_H2_SH(a, msa_dupq_n_s16(0), a_lo, a_hi);
+  return msa_packr_s32(msa_shlq_n_s32(msa_mulq_s32(msa_paddlq_s16(a_lo), msa_dupq_n_s32(b)), 1),
+                       msa_shlq_n_s32(msa_mulq_s32(msa_paddlq_s16(a_hi), msa_dupq_n_s32(b)), 1), 16);
+}
+
+#ifdef __cplusplus
+} // extern "C"
+#endif
+
+#endif /*__mips_msa*/
+#endif /* OPENCV_CORE_MSA_MACROS_H */

GameAssist/GameAssist/include/cv2/opencv2/core/hal/simd_utils.impl.hpp

@@ -0,0 +1,186 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html
+
+// This header is not standalone. Don't include directly, use "intrin.hpp" instead.
+#ifdef OPENCV_HAL_INTRIN_HPP  // defined in intrin.hpp
+
+
+#if CV_SIMD128 || CV_SIMD128_CPP
+
+template<typename _T> struct Type2Vec128_Traits;
+#define CV_INTRIN_DEF_TYPE2VEC128_TRAITS(type_, vec_type_) \
+    template<> struct Type2Vec128_Traits<type_> \
+    { \
+        typedef vec_type_ vec_type; \
+    }
+
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(uchar, v_uint8x16);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(schar, v_int8x16);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(ushort, v_uint16x8);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(short, v_int16x8);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(unsigned, v_uint32x4);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(int, v_int32x4);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(float, v_float32x4);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(uint64, v_uint64x2);
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(int64, v_int64x2);
+#if CV_SIMD128_64F
+CV_INTRIN_DEF_TYPE2VEC128_TRAITS(double, v_float64x2);
+#endif
+
+template<typename _T> static inline
+typename Type2Vec128_Traits<_T>::vec_type v_setall(const _T& a);
+
+template<> inline Type2Vec128_Traits< uchar>::vec_type v_setall< uchar>(const  uchar& a) { return v_setall_u8(a); }
+template<> inline Type2Vec128_Traits< schar>::vec_type v_setall< schar>(const  schar& a) { return v_setall_s8(a); }
+template<> inline Type2Vec128_Traits<ushort>::vec_type v_setall<ushort>(const ushort& a) { return v_setall_u16(a); }
+template<> inline Type2Vec128_Traits< short>::vec_type v_setall< short>(const  short& a) { return v_setall_s16(a); }
+template<> inline Type2Vec128_Traits<  uint>::vec_type v_setall<  uint>(const   uint& a) { return v_setall_u32(a); }
+template<> inline Type2Vec128_Traits<   int>::vec_type v_setall<   int>(const    int& a) { return v_setall_s32(a); }
+template<> inline Type2Vec128_Traits<uint64>::vec_type v_setall<uint64>(const uint64& a) { return v_setall_u64(a); }
+template<> inline Type2Vec128_Traits< int64>::vec_type v_setall< int64>(const  int64& a) { return v_setall_s64(a); }
+template<> inline Type2Vec128_Traits< float>::vec_type v_setall< float>(const  float& a) { return v_setall_f32(a); }
+#if CV_SIMD128_64F
+template<> inline Type2Vec128_Traits<double>::vec_type v_setall<double>(const double& a) { return v_setall_f64(a); }
+#endif
+
+#endif  // SIMD128
+
+
+#if CV_SIMD256
+
+template<typename _T> struct Type2Vec256_Traits;
+#define CV_INTRIN_DEF_TYPE2VEC256_TRAITS(type_, vec_type_) \
+    template<> struct Type2Vec256_Traits<type_> \
+    { \
+        typedef vec_type_ vec_type; \
+    }
+
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(uchar, v_uint8x32);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(schar, v_int8x32);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(ushort, v_uint16x16);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(short, v_int16x16);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(unsigned, v_uint32x8);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(int, v_int32x8);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(float, v_float32x8);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(uint64, v_uint64x4);
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(int64, v_int64x4);
+#if CV_SIMD256_64F
+CV_INTRIN_DEF_TYPE2VEC256_TRAITS(double, v_float64x4);
+#endif
+
+template<typename _T> static inline
+typename Type2Vec256_Traits<_T>::vec_type v256_setall(const _T& a);
+
+template<> inline Type2Vec256_Traits< uchar>::vec_type v256_setall< uchar>(const  uchar& a) { return v256_setall_u8(a); }
+template<> inline Type2Vec256_Traits< schar>::vec_type v256_setall< schar>(const  schar& a) { return v256_setall_s8(a); }
+template<> inline Type2Vec256_Traits<ushort>::vec_type v256_setall<ushort>(const ushort& a) { return v256_setall_u16(a); }
+template<> inline Type2Vec256_Traits< short>::vec_type v256_setall< short>(const  short& a) { return v256_setall_s16(a); }
+template<> inline Type2Vec256_Traits<  uint>::vec_type v256_setall<  uint>(const   uint& a) { return v256_setall_u32(a); }
+template<> inline Type2Vec256_Traits<   int>::vec_type v256_setall<   int>(const    int& a) { return v256_setall_s32(a); }
+template<> inline Type2Vec256_Traits<uint64>::vec_type v256_setall<uint64>(const uint64& a) { return v256_setall_u64(a); }
+template<> inline Type2Vec256_Traits< int64>::vec_type v256_setall< int64>(const  int64& a) { return v256_setall_s64(a); }
+template<> inline Type2Vec256_Traits< float>::vec_type v256_setall< float>(const  float& a) { return v256_setall_f32(a); }
+#if CV_SIMD256_64F
+template<> inline Type2Vec256_Traits<double>::vec_type v256_setall<double>(const double& a) { return v256_setall_f64(a); }
+#endif
+
+#endif  // SIMD256
+
+
+#if CV_SIMD512
+
+template<typename _T> struct Type2Vec512_Traits;
+#define CV_INTRIN_DEF_TYPE2VEC512_TRAITS(type_, vec_type_) \
+    template<> struct Type2Vec512_Traits<type_> \
+    { \
+        typedef vec_type_ vec_type; \
+    }
+
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(uchar, v_uint8x64);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(schar, v_int8x64);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(ushort, v_uint16x32);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(short, v_int16x32);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(unsigned, v_uint32x16);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(int, v_int32x16);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(float, v_float32x16);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(uint64, v_uint64x8);
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(int64, v_int64x8);
+#if CV_SIMD512_64F
+CV_INTRIN_DEF_TYPE2VEC512_TRAITS(double, v_float64x8);
+#endif
+
+template<typename _T> static inline
+typename Type2Vec512_Traits<_T>::vec_type v512_setall(const _T& a);
+
+template<> inline Type2Vec512_Traits< uchar>::vec_type v512_setall< uchar>(const  uchar& a) { return v512_setall_u8(a); }
+template<> inline Type2Vec512_Traits< schar>::vec_type v512_setall< schar>(const  schar& a) { return v512_setall_s8(a); }
+template<> inline Type2Vec512_Traits<ushort>::vec_type v512_setall<ushort>(const ushort& a) { return v512_setall_u16(a); }
+template<> inline Type2Vec512_Traits< short>::vec_type v512_setall< short>(const  short& a) { return v512_setall_s16(a); }
+template<> inline Type2Vec512_Traits<  uint>::vec_type v512_setall<  uint>(const   uint& a) { return v512_setall_u32(a); }
+template<> inline Type2Vec512_Traits<   int>::vec_type v512_setall<   int>(const    int& a) { return v512_setall_s32(a); }
+template<> inline Type2Vec512_Traits<uint64>::vec_type v512_setall<uint64>(const uint64& a) { return v512_setall_u64(a); }
+template<> inline Type2Vec512_Traits< int64>::vec_type v512_setall< int64>(const  int64& a) { return v512_setall_s64(a); }
+template<> inline Type2Vec512_Traits< float>::vec_type v512_setall< float>(const  float& a) { return v512_setall_f32(a); }
+#if CV_SIMD512_64F
+template<> inline Type2Vec512_Traits<double>::vec_type v512_setall<double>(const double& a) { return v512_setall_f64(a); }
+#endif
+
+#endif  // SIMD512
+
+#if CV_SIMD_SCALABLE
+template<typename _T> struct Type2Vec_Traits;
+#define CV_INTRIN_DEF_TYPE2VEC_TRAITS(type_, vec_type_) \
+    template<> struct Type2Vec_Traits<type_> \
+    { \
+        typedef vec_type_ vec_type; \
+    }
+
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(uchar, v_uint8);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(schar, v_int8);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(ushort, v_uint16);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(short, v_int16);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(unsigned, v_uint32);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(int, v_int32);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(float, v_float32);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(uint64, v_uint64);
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(int64, v_int64);
+#if CV_SIMD_SCALABLE_64F
+CV_INTRIN_DEF_TYPE2VEC_TRAITS(double, v_float64);
+#endif
+template<typename _T> static inline
+typename Type2Vec_Traits<_T>::vec_type v_setall(const _T& a);
+
+template<> inline Type2Vec_Traits< uchar>::vec_type v_setall< uchar>(const  uchar& a) { return v_setall_u8(a); }
+template<> inline Type2Vec_Traits< schar>::vec_type v_setall< schar>(const  schar& a) { return v_setall_s8(a); }
+template<> inline Type2Vec_Traits<ushort>::vec_type v_setall<ushort>(const ushort& a) { return v_setall_u16(a); }
+template<> inline Type2Vec_Traits< short>::vec_type v_setall< short>(const  short& a) { return v_setall_s16(a); }
+template<> inline Type2Vec_Traits<  uint>::vec_type v_setall<  uint>(const   uint& a) { return v_setall_u32(a); }
+template<> inline Type2Vec_Traits<   int>::vec_type v_setall<   int>(const    int& a) { return v_setall_s32(a); }
+template<> inline Type2Vec_Traits<uint64>::vec_type v_setall<uint64>(const uint64& a) { return v_setall_u64(a); }
+template<> inline Type2Vec_Traits< int64>::vec_type v_setall< int64>(const  int64& a) { return v_setall_s64(a); }
+template<> inline Type2Vec_Traits< float>::vec_type v_setall< float>(const  float& a) { return v_setall_f32(a); }
+#if CV_SIMD_SCALABLE_64F
+template<> inline Type2Vec_Traits<double>::vec_type v_setall<double>(const double& a) { return v_setall_f64(a); }
+#endif
+#endif
+
+
+#if CV_SIMD_SCALABLE
+template<typename _T> static inline
+typename Type2Vec_Traits<_T>::vec_type vx_setall(const _T& a) { return v_setall(a); }
+#elif CV_SIMD_WIDTH == 16
+template<typename _T> static inline
+typename Type2Vec128_Traits<_T>::vec_type vx_setall(const _T& a) { return v_setall(a); }
+#elif CV_SIMD_WIDTH == 32
+template<typename _T> static inline
+typename Type2Vec256_Traits<_T>::vec_type vx_setall(const _T& a) { return v256_setall(a); }
+#elif CV_SIMD_WIDTH == 64
+template<typename _T> static inline
+typename Type2Vec512_Traits<_T>::vec_type vx_setall(const _T& a) { return v512_setall(a); }
+#else
+#error "Build configuration error, unsupported CV_SIMD_WIDTH"
+#endif
+
+
+#endif  // OPENCV_HAL_INTRIN_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/mat.hpp

@@ -0,0 +1,3814 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_MAT_HPP
+#define OPENCV_CORE_MAT_HPP
+
+#ifndef __cplusplus
+#  error mat.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/core/matx.hpp"
+#include "opencv2/core/types.hpp"
+
+#include "opencv2/core/bufferpool.hpp"
+
+#include <array>
+#include <type_traits>
+
+namespace cv
+{
+
+//! @addtogroup core_basic
+//! @{
+
+enum AccessFlag { ACCESS_READ=1<<24, ACCESS_WRITE=1<<25,
+    ACCESS_RW=3<<24, ACCESS_MASK=ACCESS_RW, ACCESS_FAST=1<<26 };
+CV_ENUM_FLAGS(AccessFlag)
+__CV_ENUM_FLAGS_BITWISE_AND(AccessFlag, int, AccessFlag)
+
+CV__DEBUG_NS_BEGIN
+
+class CV_EXPORTS _OutputArray;
+
+//////////////////////// Input/Output Array Arguments /////////////////////////////////
+
+/** @brief This is the proxy class for passing read-only input arrays into OpenCV functions.
+
+It is defined as:
+@code
+    typedef const _InputArray& InputArray;
+@endcode
+where \ref cv::_InputArray is a class that can be constructed from \ref cv::Mat, \ref cv::Mat_<T>,
+\ref cv::Matx<T, m, n>, std::vector<T>, std::vector<std::vector<T>>, std::vector<Mat>,
+std::vector<Mat_<T>>, \ref cv::UMat, std::vector<UMat> or `double`. It can also be constructed from
+a matrix expression.
+
+Since this is mostly implementation-level class, and its interface may change in future versions, we
+do not describe it in details. There are a few key things, though, that should be kept in mind:
+
+-   When you see in the reference manual or in OpenCV source code a function that takes
+    InputArray, it means that you can actually pass `Mat`, `Matx`, `vector<T>` etc. (see above the
+    complete list).
+-   Optional input arguments: If some of the input arrays may be empty, pass cv::noArray() (or
+    simply cv::Mat() as you probably did before).
+-   The class is designed solely for passing parameters. That is, normally you *should not*
+    declare class members, local and global variables of this type.
+-   If you want to design your own function or a class method that can operate of arrays of
+    multiple types, you can use InputArray (or OutputArray) for the respective parameters. Inside
+    a function you should use _InputArray::getMat() method to construct a matrix header for the
+    array (without copying data). _InputArray::kind() can be used to distinguish Mat from
+    `vector<>` etc., but normally it is not needed.
+
+Here is how you can use a function that takes InputArray :
+@code
+    std::vector<Point2f> vec;
+    // points or a circle
+    for( int i = 0; i < 30; i++ )
+        vec.push_back(Point2f((float)(100 + 30*cos(i*CV_PI*2/5)),
+                              (float)(100 - 30*sin(i*CV_PI*2/5))));
+    cv::transform(vec, vec, cv::Matx23f(0.707, -0.707, 10, 0.707, 0.707, 20));
+@endcode
+That is, we form an STL vector containing points, and apply in-place affine transformation to the
+vector using the 2x3 matrix created inline as `Matx<float, 2, 3>` instance.
+
+Here is how such a function can be implemented (for simplicity, we implement a very specific case of
+it, according to the assertion statement inside) :
+@code
+    void myAffineTransform(InputArray _src, OutputArray _dst, InputArray _m)
+    {
+        // get Mat headers for input arrays. This is O(1) operation,
+        // unless _src and/or _m are matrix expressions.
+        Mat src = _src.getMat(), m = _m.getMat();
+        CV_Assert( src.type() == CV_32FC2 && m.type() == CV_32F && m.size() == Size(3, 2) );
+
+        // [re]create the output array so that it has the proper size and type.
+        // In case of Mat it calls Mat::create, in case of STL vector it calls vector::resize.
+        _dst.create(src.size(), src.type());
+        Mat dst = _dst.getMat();
+
+        for( int i = 0; i < src.rows; i++ )
+            for( int j = 0; j < src.cols; j++ )
+            {
+                Point2f pt = src.at<Point2f>(i, j);
+                dst.at<Point2f>(i, j) = Point2f(m.at<float>(0, 0)*pt.x +
+                                                m.at<float>(0, 1)*pt.y +
+                                                m.at<float>(0, 2),
+                                                m.at<float>(1, 0)*pt.x +
+                                                m.at<float>(1, 1)*pt.y +
+                                                m.at<float>(1, 2));
+            }
+    }
+@endcode
+There is another related type, InputArrayOfArrays, which is currently defined as a synonym for
+InputArray:
+@code
+    typedef InputArray InputArrayOfArrays;
+@endcode
+It denotes function arguments that are either vectors of vectors or vectors of matrices. A separate
+synonym is needed to generate Python/Java etc. wrappers properly. At the function implementation
+level their use is similar, but _InputArray::getMat(idx) should be used to get header for the
+idx-th component of the outer vector and _InputArray::size().area() should be used to find the
+number of components (vectors/matrices) of the outer vector.
+
+In general, type support is limited to cv::Mat types. Other types are forbidden.
+But in some cases we need to support passing of custom non-general Mat types, like arrays of cv::KeyPoint, cv::DMatch, etc.
+This data is not intended to be interpreted as an image data, or processed somehow like regular cv::Mat.
+To pass such custom type use rawIn() / rawOut() / rawInOut() wrappers.
+Custom type is wrapped as Mat-compatible `CV_8UC<N>` values (N = sizeof(T), N <= CV_CN_MAX).
+ */
+class CV_EXPORTS _InputArray
+{
+public:
+    enum KindFlag {
+        KIND_SHIFT = 16,
+        FIXED_TYPE = 0x8000 << KIND_SHIFT,
+        FIXED_SIZE = 0x4000 << KIND_SHIFT,
+        KIND_MASK = 31 << KIND_SHIFT,
+
+        NONE              = 0 << KIND_SHIFT,
+        MAT               = 1 << KIND_SHIFT,
+        MATX              = 2 << KIND_SHIFT,
+        STD_VECTOR        = 3 << KIND_SHIFT,
+        STD_VECTOR_VECTOR = 4 << KIND_SHIFT,
+        STD_VECTOR_MAT    = 5 << KIND_SHIFT,
+#if OPENCV_ABI_COMPATIBILITY < 500
+        EXPR              = 6 << KIND_SHIFT,  //!< removed: https://github.com/opencv/opencv/pull/17046
+#endif
+        OPENGL_BUFFER     = 7 << KIND_SHIFT,
+        CUDA_HOST_MEM     = 8 << KIND_SHIFT,
+        CUDA_GPU_MAT      = 9 << KIND_SHIFT,
+        UMAT              =10 << KIND_SHIFT,
+        STD_VECTOR_UMAT   =11 << KIND_SHIFT,
+        STD_BOOL_VECTOR   =12 << KIND_SHIFT,
+        STD_VECTOR_CUDA_GPU_MAT = 13 << KIND_SHIFT,
+#if OPENCV_ABI_COMPATIBILITY < 500
+        STD_ARRAY         =14 << KIND_SHIFT,  //!< removed: https://github.com/opencv/opencv/issues/18897
+#endif
+        STD_ARRAY_MAT     =15 << KIND_SHIFT
+    };
+
+    _InputArray();
+    _InputArray(int _flags, void* _obj);
+    _InputArray(const Mat& m);
+    _InputArray(const MatExpr& expr);
+    _InputArray(const std::vector<Mat>& vec);
+    template<typename _Tp> _InputArray(const Mat_<_Tp>& m);
+    template<typename _Tp> _InputArray(const std::vector<_Tp>& vec);
+    _InputArray(const std::vector<bool>& vec);
+    template<typename _Tp> _InputArray(const std::vector<std::vector<_Tp> >& vec);
+    _InputArray(const std::vector<std::vector<bool> >&) = delete;  // not supported
+    template<typename _Tp> _InputArray(const std::vector<Mat_<_Tp> >& vec);
+    template<typename _Tp> _InputArray(const _Tp* vec, int n);
+    template<typename _Tp, int m, int n> _InputArray(const Matx<_Tp, m, n>& matx);
+    _InputArray(const double& val);
+    _InputArray(const cuda::GpuMat& d_mat);
+    _InputArray(const std::vector<cuda::GpuMat>& d_mat_array);
+    _InputArray(const ogl::Buffer& buf);
+    _InputArray(const cuda::HostMem& cuda_mem);
+    template<typename _Tp> _InputArray(const cudev::GpuMat_<_Tp>& m);
+    _InputArray(const UMat& um);
+    _InputArray(const std::vector<UMat>& umv);
+
+    template<typename _Tp, std::size_t _Nm> _InputArray(const std::array<_Tp, _Nm>& arr);
+    template<std::size_t _Nm> _InputArray(const std::array<Mat, _Nm>& arr);
+
+    template<typename _Tp> static _InputArray rawIn(const std::vector<_Tp>& vec);
+    template<typename _Tp, std::size_t _Nm> static _InputArray rawIn(const std::array<_Tp, _Nm>& arr);
+
+    Mat getMat(int idx=-1) const;
+    Mat getMat_(int idx=-1) const;
+    UMat getUMat(int idx=-1) const;
+    void getMatVector(std::vector<Mat>& mv) const;
+    void getUMatVector(std::vector<UMat>& umv) const;
+    void getGpuMatVector(std::vector<cuda::GpuMat>& gpumv) const;
+    cuda::GpuMat getGpuMat() const;
+    ogl::Buffer getOGlBuffer() const;
+
+    int getFlags() const;
+    void* getObj() const;
+    Size getSz() const;
+
+    _InputArray::KindFlag kind() const;
+    int dims(int i=-1) const;
+    int cols(int i=-1) const;
+    int rows(int i=-1) const;
+    Size size(int i=-1) const;
+    int sizend(int* sz, int i=-1) const;
+    bool sameSize(const _InputArray& arr) const;
+    size_t total(int i=-1) const;
+    int type(int i=-1) const;
+    int depth(int i=-1) const;
+    int channels(int i=-1) const;
+    bool isContinuous(int i=-1) const;
+    bool isSubmatrix(int i=-1) const;
+    bool empty() const;
+    void copyTo(const _OutputArray& arr) const;
+    void copyTo(const _OutputArray& arr, const _InputArray & mask) const;
+    size_t offset(int i=-1) const;
+    size_t step(int i=-1) const;
+    bool isMat() const;
+    bool isUMat() const;
+    bool isMatVector() const;
+    bool isUMatVector() const;
+    bool isMatx() const;
+    bool isVector() const;
+    bool isGpuMat() const;
+    bool isGpuMatVector() const;
+    ~_InputArray();
+
+protected:
+    int flags;
+    void* obj;
+    Size sz;
+
+    void init(int _flags, const void* _obj);
+    void init(int _flags, const void* _obj, Size _sz);
+};
+CV_ENUM_FLAGS(_InputArray::KindFlag)
+__CV_ENUM_FLAGS_BITWISE_AND(_InputArray::KindFlag, int, _InputArray::KindFlag)
+
+/** @brief This type is very similar to InputArray except that it is used for input/output and output function
+parameters.
+
+Just like with InputArray, OpenCV users should not care about OutputArray, they just pass `Mat`,
+`vector<T>` etc. to the functions. The same limitation as for `InputArray`: *Do not explicitly
+create OutputArray instances* applies here too.
+
+If you want to make your function polymorphic (i.e. accept different arrays as output parameters),
+it is also not very difficult. Take the sample above as the reference. Note that
+_OutputArray::create() needs to be called before _OutputArray::getMat(). This way you guarantee
+that the output array is properly allocated.
+
+Optional output parameters. If you do not need certain output array to be computed and returned to
+you, pass cv::noArray(), just like you would in the case of optional input array. At the
+implementation level, use _OutputArray::needed() to check if certain output array needs to be
+computed or not.
+
+There are several synonyms for OutputArray that are used to assist automatic Python/Java/... wrapper
+generators:
+@code
+    typedef OutputArray OutputArrayOfArrays;
+    typedef OutputArray InputOutputArray;
+    typedef OutputArray InputOutputArrayOfArrays;
+@endcode
+ */
+class CV_EXPORTS _OutputArray : public _InputArray
+{
+public:
+    enum DepthMask
+    {
+        DEPTH_MASK_8U = 1 << CV_8U,
+        DEPTH_MASK_8S = 1 << CV_8S,
+        DEPTH_MASK_16U = 1 << CV_16U,
+        DEPTH_MASK_16S = 1 << CV_16S,
+        DEPTH_MASK_32S = 1 << CV_32S,
+        DEPTH_MASK_32F = 1 << CV_32F,
+        DEPTH_MASK_64F = 1 << CV_64F,
+        DEPTH_MASK_16F = 1 << CV_16F,
+        DEPTH_MASK_ALL = (DEPTH_MASK_64F<<1)-1,
+        DEPTH_MASK_ALL_BUT_8S = DEPTH_MASK_ALL & ~DEPTH_MASK_8S,
+        DEPTH_MASK_ALL_16F = (DEPTH_MASK_16F<<1)-1,
+        DEPTH_MASK_FLT = DEPTH_MASK_32F + DEPTH_MASK_64F
+    };
+
+    _OutputArray();
+    _OutputArray(int _flags, void* _obj);
+    _OutputArray(Mat& m);
+    _OutputArray(std::vector<Mat>& vec);
+    _OutputArray(cuda::GpuMat& d_mat);
+    _OutputArray(std::vector<cuda::GpuMat>& d_mat);
+    _OutputArray(ogl::Buffer& buf);
+    _OutputArray(cuda::HostMem& cuda_mem);
+    template<typename _Tp> _OutputArray(cudev::GpuMat_<_Tp>& m);
+    template<typename _Tp> _OutputArray(std::vector<_Tp>& vec);
+    _OutputArray(std::vector<bool>& vec) = delete;  // not supported
+    template<typename _Tp> _OutputArray(std::vector<std::vector<_Tp> >& vec);
+    _OutputArray(std::vector<std::vector<bool> >&) = delete;  // not supported
+    template<typename _Tp> _OutputArray(std::vector<Mat_<_Tp> >& vec);
+    template<typename _Tp> _OutputArray(Mat_<_Tp>& m);
+    template<typename _Tp> _OutputArray(_Tp* vec, int n);
+    template<typename _Tp, int m, int n> _OutputArray(Matx<_Tp, m, n>& matx);
+    _OutputArray(UMat& m);
+    _OutputArray(std::vector<UMat>& vec);
+
+    _OutputArray(const Mat& m);
+    _OutputArray(const std::vector<Mat>& vec);
+    _OutputArray(const cuda::GpuMat& d_mat);
+    _OutputArray(const std::vector<cuda::GpuMat>& d_mat);
+    _OutputArray(const ogl::Buffer& buf);
+    _OutputArray(const cuda::HostMem& cuda_mem);
+    template<typename _Tp> _OutputArray(const cudev::GpuMat_<_Tp>& m);
+    template<typename _Tp> _OutputArray(const std::vector<_Tp>& vec);
+    template<typename _Tp> _OutputArray(const std::vector<std::vector<_Tp> >& vec);
+    template<typename _Tp> _OutputArray(const std::vector<Mat_<_Tp> >& vec);
+    template<typename _Tp> _OutputArray(const Mat_<_Tp>& m);
+    template<typename _Tp> _OutputArray(const _Tp* vec, int n);
+    template<typename _Tp, int m, int n> _OutputArray(const Matx<_Tp, m, n>& matx);
+    _OutputArray(const UMat& m);
+    _OutputArray(const std::vector<UMat>& vec);
+
+    template<typename _Tp, std::size_t _Nm> _OutputArray(std::array<_Tp, _Nm>& arr);
+    template<typename _Tp, std::size_t _Nm> _OutputArray(const std::array<_Tp, _Nm>& arr);
+    template<std::size_t _Nm> _OutputArray(std::array<Mat, _Nm>& arr);
+    template<std::size_t _Nm> _OutputArray(const std::array<Mat, _Nm>& arr);
+
+    template<typename _Tp> static _OutputArray rawOut(std::vector<_Tp>& vec);
+    template<typename _Tp, std::size_t _Nm> static _OutputArray rawOut(std::array<_Tp, _Nm>& arr);
+
+    bool fixedSize() const;
+    bool fixedType() const;
+    bool needed() const;
+    Mat& getMatRef(int i=-1) const;
+    UMat& getUMatRef(int i=-1) const;
+    cuda::GpuMat& getGpuMatRef() const;
+    std::vector<cuda::GpuMat>& getGpuMatVecRef() const;
+    ogl::Buffer& getOGlBufferRef() const;
+    cuda::HostMem& getHostMemRef() const;
+    void create(Size sz, int type, int i=-1, bool allowTransposed=false, _OutputArray::DepthMask fixedDepthMask=static_cast<_OutputArray::DepthMask>(0)) const;
+    void create(int rows, int cols, int type, int i=-1, bool allowTransposed=false, _OutputArray::DepthMask fixedDepthMask=static_cast<_OutputArray::DepthMask>(0)) const;
+    void create(int dims, const int* size, int type, int i=-1, bool allowTransposed=false, _OutputArray::DepthMask fixedDepthMask=static_cast<_OutputArray::DepthMask>(0)) const;
+    void createSameSize(const _InputArray& arr, int mtype) const;
+    void release() const;
+    void clear() const;
+    void setTo(const _InputArray& value, const _InputArray & mask = _InputArray()) const;
+
+    void assign(const UMat& u) const;
+    void assign(const Mat& m) const;
+
+    void assign(const std::vector<UMat>& v) const;
+    void assign(const std::vector<Mat>& v) const;
+
+    void move(UMat& u) const;
+    void move(Mat& m) const;
+};
+
+
+class CV_EXPORTS _InputOutputArray : public _OutputArray
+{
+public:
+    _InputOutputArray();
+    _InputOutputArray(int _flags, void* _obj);
+    _InputOutputArray(Mat& m);
+    _InputOutputArray(std::vector<Mat>& vec);
+    _InputOutputArray(cuda::GpuMat& d_mat);
+    _InputOutputArray(ogl::Buffer& buf);
+    _InputOutputArray(cuda::HostMem& cuda_mem);
+    template<typename _Tp> _InputOutputArray(cudev::GpuMat_<_Tp>& m);
+    template<typename _Tp> _InputOutputArray(std::vector<_Tp>& vec);
+    _InputOutputArray(std::vector<bool>& vec) = delete;  // not supported
+    template<typename _Tp> _InputOutputArray(std::vector<std::vector<_Tp> >& vec);
+    template<typename _Tp> _InputOutputArray(std::vector<Mat_<_Tp> >& vec);
+    template<typename _Tp> _InputOutputArray(Mat_<_Tp>& m);
+    template<typename _Tp> _InputOutputArray(_Tp* vec, int n);
+    template<typename _Tp, int m, int n> _InputOutputArray(Matx<_Tp, m, n>& matx);
+    _InputOutputArray(UMat& m);
+    _InputOutputArray(std::vector<UMat>& vec);
+
+    _InputOutputArray(const Mat& m);
+    _InputOutputArray(const std::vector<Mat>& vec);
+    _InputOutputArray(const cuda::GpuMat& d_mat);
+    _InputOutputArray(const std::vector<cuda::GpuMat>& d_mat);
+    _InputOutputArray(const ogl::Buffer& buf);
+    _InputOutputArray(const cuda::HostMem& cuda_mem);
+    template<typename _Tp> _InputOutputArray(const cudev::GpuMat_<_Tp>& m);
+    template<typename _Tp> _InputOutputArray(const std::vector<_Tp>& vec);
+    template<typename _Tp> _InputOutputArray(const std::vector<std::vector<_Tp> >& vec);
+    template<typename _Tp> _InputOutputArray(const std::vector<Mat_<_Tp> >& vec);
+    template<typename _Tp> _InputOutputArray(const Mat_<_Tp>& m);
+    template<typename _Tp> _InputOutputArray(const _Tp* vec, int n);
+    template<typename _Tp, int m, int n> _InputOutputArray(const Matx<_Tp, m, n>& matx);
+    _InputOutputArray(const UMat& m);
+    _InputOutputArray(const std::vector<UMat>& vec);
+
+    template<typename _Tp, std::size_t _Nm> _InputOutputArray(std::array<_Tp, _Nm>& arr);
+    template<typename _Tp, std::size_t _Nm> _InputOutputArray(const std::array<_Tp, _Nm>& arr);
+    template<std::size_t _Nm> _InputOutputArray(std::array<Mat, _Nm>& arr);
+    template<std::size_t _Nm> _InputOutputArray(const std::array<Mat, _Nm>& arr);
+
+    template<typename _Tp> static _InputOutputArray rawInOut(std::vector<_Tp>& vec);
+    template<typename _Tp, std::size_t _Nm> _InputOutputArray rawInOut(std::array<_Tp, _Nm>& arr);
+
+};
+
+/** Helper to wrap custom types. @see InputArray */
+template<typename _Tp> static inline _InputArray rawIn(_Tp& v);
+/** Helper to wrap custom types. @see InputArray */
+template<typename _Tp> static inline _OutputArray rawOut(_Tp& v);
+/** Helper to wrap custom types. @see InputArray */
+template<typename _Tp> static inline _InputOutputArray rawInOut(_Tp& v);
+
+CV__DEBUG_NS_END
+
+typedef const _InputArray& InputArray;
+typedef InputArray InputArrayOfArrays;
+typedef const _OutputArray& OutputArray;
+typedef OutputArray OutputArrayOfArrays;
+typedef const _InputOutputArray& InputOutputArray;
+typedef InputOutputArray InputOutputArrayOfArrays;
+
+/** @brief Returns an empty InputArray or OutputArray.
+
+ This function is used to provide an "empty" or "null" array when certain functions
+ take optional input or output arrays that you don't want to provide.
+
+ Many OpenCV functions accept optional arguments as `cv::InputArray` or `cv::OutputArray`.
+ When you don't want to pass any data for these optional parameters, you can use `cv::noArray()`
+ to indicate that you are omitting them.
+
+ @return An empty `cv::InputArray` or `cv::OutputArray` that can be used as a placeholder.
+
+ @note This is often used when a function has optional arrays, and you do not want to
+ provide a specific input or output array.
+
+ @see cv::InputArray, cv::OutputArray
+ */
+CV_EXPORTS InputOutputArray noArray();
+
+/////////////////////////////////// MatAllocator //////////////////////////////////////
+
+/** @brief  Usage flags for allocator
+
+ @warning  All flags except `USAGE_DEFAULT` are experimental.
+
+ @warning  For the OpenCL allocator, `USAGE_ALLOCATE_SHARED_MEMORY` depends on
+ OpenCV's optional, experimental integration with OpenCL SVM. To enable this
+ integration, build OpenCV using the `WITH_OPENCL_SVM=ON` CMake option and, at
+ runtime, call `cv::ocl::Context::getDefault().setUseSVM(true);` or similar
+ code. Note that SVM is incompatible with OpenCL 1.x.
+*/
+enum UMatUsageFlags
+{
+    USAGE_DEFAULT = 0,
+
+    // buffer allocation policy is platform and usage specific
+    USAGE_ALLOCATE_HOST_MEMORY = 1 << 0,
+    USAGE_ALLOCATE_DEVICE_MEMORY = 1 << 1,
+    USAGE_ALLOCATE_SHARED_MEMORY = 1 << 2, // It is not equal to: USAGE_ALLOCATE_HOST_MEMORY | USAGE_ALLOCATE_DEVICE_MEMORY
+
+    __UMAT_USAGE_FLAGS_32BIT = 0x7fffffff // Binary compatibility hint
+};
+
+struct CV_EXPORTS UMatData;
+
+/** @brief  Custom array allocator
+*/
+class CV_EXPORTS MatAllocator
+{
+public:
+    MatAllocator() {}
+    virtual ~MatAllocator() {}
+
+    // let's comment it off for now to detect and fix all the uses of allocator
+    //virtual void allocate(int dims, const int* sizes, int type, int*& refcount,
+    //                      uchar*& datastart, uchar*& data, size_t* step) = 0;
+    //virtual void deallocate(int* refcount, uchar* datastart, uchar* data) = 0;
+    virtual UMatData* allocate(int dims, const int* sizes, int type,
+                               void* data, size_t* step, AccessFlag flags, UMatUsageFlags usageFlags) const = 0;
+    virtual bool allocate(UMatData* data, AccessFlag accessflags, UMatUsageFlags usageFlags) const = 0;
+    virtual void deallocate(UMatData* data) const = 0;
+    virtual void map(UMatData* data, AccessFlag accessflags) const;
+    virtual void unmap(UMatData* data) const;
+    virtual void download(UMatData* data, void* dst, int dims, const size_t sz[],
+                          const size_t srcofs[], const size_t srcstep[],
+                          const size_t dststep[]) const;
+    virtual void upload(UMatData* data, const void* src, int dims, const size_t sz[],
+                        const size_t dstofs[], const size_t dststep[],
+                        const size_t srcstep[]) const;
+    virtual void copy(UMatData* srcdata, UMatData* dstdata, int dims, const size_t sz[],
+                      const size_t srcofs[], const size_t srcstep[],
+                      const size_t dstofs[], const size_t dststep[], bool sync) const;
+
+    // default implementation returns DummyBufferPoolController
+    virtual BufferPoolController* getBufferPoolController(const char* id = NULL) const;
+};
+
+
+//////////////////////////////// MatCommaInitializer //////////////////////////////////
+
+/** @brief  Comma-separated Matrix Initializer
+
+ The class instances are usually not created explicitly.
+ Instead, they are created on "matrix << firstValue" operator.
+
+ The sample below initializes 2x2 rotation matrix:
+
+ \code
+ double angle = 30, a = cos(angle*CV_PI/180), b = sin(angle*CV_PI/180);
+ Mat R = (Mat_<double>(2,2) << a, -b, b, a);
+ \endcode
+*/
+template<typename _Tp> class MatCommaInitializer_
+{
+public:
+    //! the constructor, created by "matrix << firstValue" operator, where matrix is cv::Mat
+    MatCommaInitializer_(Mat_<_Tp>* _m);
+    //! the operator that takes the next value and put it to the matrix
+    template<typename T2> MatCommaInitializer_<_Tp>& operator , (T2 v);
+    //! another form of conversion operator
+    operator Mat_<_Tp>() const;
+protected:
+    MatIterator_<_Tp> it;
+};
+
+
+/////////////////////////////////////// Mat ///////////////////////////////////////////
+
+// note that umatdata might be allocated together
+// with the matrix data, not as a separate object.
+// therefore, it does not have constructor or destructor;
+// it should be explicitly initialized using init().
+struct CV_EXPORTS UMatData
+{
+    enum MemoryFlag { COPY_ON_MAP=1, HOST_COPY_OBSOLETE=2,
+        DEVICE_COPY_OBSOLETE=4, TEMP_UMAT=8, TEMP_COPIED_UMAT=24,
+        USER_ALLOCATED=32, DEVICE_MEM_MAPPED=64,
+        ASYNC_CLEANUP=128
+    };
+    UMatData(const MatAllocator* allocator);
+    ~UMatData();
+
+    // provide atomic access to the structure
+    void lock();
+    void unlock();
+
+    bool hostCopyObsolete() const;
+    bool deviceCopyObsolete() const;
+    bool deviceMemMapped() const;
+    bool copyOnMap() const;
+    bool tempUMat() const;
+    bool tempCopiedUMat() const;
+    void markHostCopyObsolete(bool flag);
+    void markDeviceCopyObsolete(bool flag);
+    void markDeviceMemMapped(bool flag);
+
+    const MatAllocator* prevAllocator;
+    const MatAllocator* currAllocator;
+    int urefcount;
+    int refcount;
+    uchar* data;
+    uchar* origdata;
+    size_t size;
+
+    UMatData::MemoryFlag flags;
+    void* handle;
+    void* userdata;
+    int allocatorFlags_;
+    int mapcount;
+    UMatData* originalUMatData;
+    std::shared_ptr<void> allocatorContext;
+};
+CV_ENUM_FLAGS(UMatData::MemoryFlag)
+
+
+struct CV_EXPORTS MatSize
+{
+    explicit MatSize(int* _p) CV_NOEXCEPT;
+    int dims() const CV_NOEXCEPT;
+    Size operator()() const;
+    const int& operator[](int i) const;
+    int& operator[](int i);
+    operator const int*() const CV_NOEXCEPT;  // TODO OpenCV 4.0: drop this
+    bool operator == (const MatSize& sz) const CV_NOEXCEPT;
+    bool operator != (const MatSize& sz) const CV_NOEXCEPT;
+
+    int* p;
+};
+
+struct CV_EXPORTS MatStep
+{
+    MatStep() CV_NOEXCEPT;
+    explicit MatStep(size_t s) CV_NOEXCEPT;
+    const size_t& operator[](int i) const CV_NOEXCEPT;
+    size_t& operator[](int i) CV_NOEXCEPT;
+    operator size_t() const;
+    MatStep& operator = (size_t s);
+
+    size_t* p;
+    size_t buf[2];
+protected:
+    MatStep& operator = (const MatStep&);
+};
+
+/** @example samples/cpp/cout_mat.cpp
+An example demonstrating the serial out capabilities of cv::Mat
+*/
+
+ /** @brief n-dimensional dense array class \anchor CVMat_Details
+
+The class Mat represents an n-dimensional dense numerical single-channel or multi-channel array. It
+can be used to store real or complex-valued vectors and matrices, grayscale or color images, voxel
+volumes, vector fields, point clouds, tensors, histograms (though, very high-dimensional histograms
+may be better stored in a SparseMat ). The data layout of the array `M` is defined by the array
+`M.step[]`, so that the address of element \f$(i_0,...,i_{M.dims-1})\f$, where \f$0\leq i_k<M.size[k]\f$, is
+computed as:
+\f[addr(M_{i_0,...,i_{M.dims-1}}) = M.data + M.step[0]*i_0 + M.step[1]*i_1 + ... + M.step[M.dims-1]*i_{M.dims-1}\f]
+In case of a 2-dimensional array, the above formula is reduced to:
+\f[addr(M_{i,j}) = M.data + M.step[0]*i + M.step[1]*j\f]
+Note that `M.step[i] >= M.step[i+1]` (in fact, `M.step[i] >= M.step[i+1]*M.size[i+1]` ). This means
+that 2-dimensional matrices are stored row-by-row, 3-dimensional matrices are stored plane-by-plane,
+and so on. M.step[M.dims-1] is minimal and always equal to the element size M.elemSize() .
+
+So, the data layout in Mat is compatible with the majority of dense array types from the standard
+toolkits and SDKs, such as Numpy (ndarray), Win32 (independent device bitmaps), and others,
+that is, with any array that uses *steps* (or *strides*) to compute the position of a pixel.
+Due to this compatibility, it is possible to make a Mat header for user-allocated data and process
+it in-place using OpenCV functions.
+
+There are many different ways to create a Mat object. The most popular options are listed below:
+
+- Use the create(nrows, ncols, type) method or the similar Mat(nrows, ncols, type[, fillValue])
+constructor. A new array of the specified size and type is allocated. type has the same meaning as
+in the cvCreateMat method. For example, CV_8UC1 means a 8-bit single-channel array, CV_32FC2
+means a 2-channel (complex) floating-point array, and so on.
+@code
+    // make a 7x7 complex matrix filled with 1+3j.
+    Mat M(7,7,CV_32FC2,Scalar(1,3));
+    // and now turn M to a 100x60 15-channel 8-bit matrix.
+    // The old content will be deallocated
+    M.create(100,60,CV_8UC(15));
+@endcode
+As noted in the introduction to this chapter, create() allocates only a new array when the shape
+or type of the current array are different from the specified ones.
+
+- Create a multi-dimensional array:
+@code
+    // create a 100x100x100 8-bit array
+    int sz[] = {100, 100, 100};
+    Mat bigCube(3, sz, CV_8U, Scalar::all(0));
+@endcode
+It passes the number of dimensions =1 to the Mat constructor but the created array will be
+2-dimensional with the number of columns set to 1. So, Mat::dims is always \>= 2 (can also be 0
+when the array is empty).
+
+- Use a copy constructor or assignment operator where there can be an array or expression on the
+right side (see below). As noted in the introduction, the array assignment is an O(1) operation
+because it only copies the header and increases the reference counter. The Mat::clone() method can
+be used to get a full (deep) copy of the array when you need it.
+
+- Construct a header for a part of another array. It can be a single row, single column, several
+rows, several columns, rectangular region in the array (called a *minor* in algebra) or a
+diagonal. Such operations are also O(1) because the new header references the same data. You can
+actually modify a part of the array using this feature, for example:
+@code
+    // add the 5-th row, multiplied by 3 to the 3rd row
+    M.row(3) = M.row(3) + M.row(5)*3;
+    // now copy the 7-th column to the 1-st column
+    // M.col(1) = M.col(7); // this will not work
+    Mat M1 = M.col(1);
+    M.col(7).copyTo(M1);
+    // create a new 320x240 image
+    Mat img(Size(320,240),CV_8UC3);
+    // select a ROI
+    Mat roi(img, Rect(10,10,100,100));
+    // fill the ROI with (0,255,0) (which is green in RGB space);
+    // the original 320x240 image will be modified
+    roi = Scalar(0,255,0);
+@endcode
+Due to the additional datastart and dataend members, it is possible to compute a relative
+sub-array position in the main *container* array using locateROI():
+@code
+    Mat A = Mat::eye(10, 10, CV_32S);
+    // extracts A columns, 1 (inclusive) to 3 (exclusive).
+    Mat B = A(Range::all(), Range(1, 3));
+    // extracts B rows, 5 (inclusive) to 9 (exclusive).
+    // that is, C \~ A(Range(5, 9), Range(1, 3))
+    Mat C = B(Range(5, 9), Range::all());
+    Size size; Point ofs;
+    C.locateROI(size, ofs);
+    // size will be (width=10,height=10) and the ofs will be (x=1, y=5)
+@endcode
+As in case of whole matrices, if you need a deep copy, use the `clone()` method of the extracted
+sub-matrices.
+
+- Make a header for user-allocated data. It can be useful to do the following:
+    -# Process "foreign" data using OpenCV (for example, when you implement a DirectShow\* filter or
+    a processing module for gstreamer, and so on). For example:
+    @code
+        Mat process_video_frame(const unsigned char* pixels,
+                                int width, int height, int step)
+        {
+            // wrap input buffer
+            Mat img(height, width, CV_8UC3, (unsigned char*)pixels, step);
+
+            Mat result;
+            GaussianBlur(img, result, Size(7, 7), 1.5, 1.5);
+
+            return result;
+        }
+    @endcode
+    -# Quickly initialize small matrices and/or get a super-fast element access.
+    @code
+        double m[3][3] = {{a, b, c}, {d, e, f}, {g, h, i}};
+        Mat M = Mat(3, 3, CV_64F, m).inv();
+    @endcode
+    .
+
+- Use MATLAB-style array initializers, zeros(), ones(), eye(), for example:
+@code
+    // create a double-precision identity matrix and add it to M.
+    M += Mat::eye(M.rows, M.cols, CV_64F);
+@endcode
+
+- Use a comma-separated initializer:
+@code
+    // create a 3x3 double-precision identity matrix
+    Mat M = (Mat_<double>(3,3) << 1, 0, 0, 0, 1, 0, 0, 0, 1);
+@endcode
+With this approach, you first call a constructor of the Mat class with the proper parameters, and
+then you just put `<< operator` followed by comma-separated values that can be constants,
+variables, expressions, and so on. Also, note the extra parentheses required to avoid compilation
+errors.
+
+Once the array is created, it is automatically managed via a reference-counting mechanism. If the
+array header is built on top of user-allocated data, you should handle the data by yourself. The
+array data is deallocated when no one points to it. If you want to release the data pointed by a
+array header before the array destructor is called, use Mat::release().
+
+The next important thing to learn about the array class is element access. This manual already
+described how to compute an address of each array element. Normally, you are not required to use the
+formula directly in the code. If you know the array element type (which can be retrieved using the
+method Mat::type() ), you can access the element \f$M_{ij}\f$ of a 2-dimensional array as:
+@code
+    M.at<double>(i,j) += 1.f;
+@endcode
+assuming that `M` is a double-precision floating-point array. There are several variants of the method
+at for a different number of dimensions.
+
+If you need to process a whole row of a 2D array, the most efficient way is to get the pointer to
+the row first, and then just use the plain C operator [] :
+@code
+    // compute sum of positive matrix elements
+    // (assuming that M is a double-precision matrix)
+    double sum=0;
+    for(int i = 0; i < M.rows; i++)
+    {
+        const double* Mi = M.ptr<double>(i);
+        for(int j = 0; j < M.cols; j++)
+            sum += std::max(Mi[j], 0.);
+    }
+@endcode
+Some operations, like the one above, do not actually depend on the array shape. They just process
+elements of an array one by one (or elements from multiple arrays that have the same coordinates,
+for example, array addition). Such operations are called *element-wise*. It makes sense to check
+whether all the input/output arrays are continuous, namely, have no gaps at the end of each row. If
+yes, process them as a long single row:
+@code
+    // compute the sum of positive matrix elements, optimized variant
+    double sum=0;
+    int cols = M.cols, rows = M.rows;
+    if(M.isContinuous())
+    {
+        cols *= rows;
+        rows = 1;
+    }
+    for(int i = 0; i < rows; i++)
+    {
+        const double* Mi = M.ptr<double>(i);
+        for(int j = 0; j < cols; j++)
+            sum += std::max(Mi[j], 0.);
+    }
+@endcode
+In case of the continuous matrix, the outer loop body is executed just once. So, the overhead is
+smaller, which is especially noticeable in case of small matrices.
+
+Finally, there are STL-style iterators that are smart enough to skip gaps between successive rows:
+@code
+    // compute sum of positive matrix elements, iterator-based variant
+    double sum=0;
+    MatConstIterator_<double> it = M.begin<double>(), it_end = M.end<double>();
+    for(; it != it_end; ++it)
+        sum += std::max(*it, 0.);
+@endcode
+The matrix iterators are random-access iterators, so they can be passed to any STL algorithm,
+including std::sort().
+
+@note Matrix Expressions and arithmetic see MatExpr
+*/
+class CV_EXPORTS Mat
+{
+public:
+    /**
+    These are various constructors that form a matrix. As noted in the AutomaticAllocation, often
+    the default constructor is enough, and the proper matrix will be allocated by an OpenCV function.
+    The constructed matrix can further be assigned to another matrix or matrix expression or can be
+    allocated with Mat::create . In the former case, the old content is de-referenced.
+     */
+    Mat() CV_NOEXCEPT;
+
+    /** @overload
+    @param rows Number of rows in a 2D array.
+    @param cols Number of columns in a 2D array.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    */
+    Mat(int rows, int cols, int type);
+
+    /** @overload
+    @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the
+    number of columns go in the reverse order.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+      */
+    Mat(Size size, int type);
+
+    /** @overload
+    @param rows Number of rows in a 2D array.
+    @param cols Number of columns in a 2D array.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param s An optional value to initialize each matrix element with. To set all the matrix elements to
+    the particular value after the construction, use the assignment operator
+    Mat::operator=(const Scalar& value) .
+    */
+    Mat(int rows, int cols, int type, const Scalar& s);
+
+    /** @overload
+    @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the
+    number of columns go in the reverse order.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param s An optional value to initialize each matrix element with. To set all the matrix elements to
+    the particular value after the construction, use the assignment operator
+    Mat::operator=(const Scalar& value) .
+      */
+    Mat(Size size, int type, const Scalar& s);
+
+    /** @overload
+    @param ndims Array dimensionality.
+    @param sizes Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    */
+    Mat(int ndims, const int* sizes, int type);
+
+    /** @overload
+    @param sizes Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    */
+    Mat(const std::vector<int>& sizes, int type);
+
+    /** @overload
+    @param ndims Array dimensionality.
+    @param sizes Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param s An optional value to initialize each matrix element with. To set all the matrix elements to
+    the particular value after the construction, use the assignment operator
+    Mat::operator=(const Scalar& value) .
+    */
+    Mat(int ndims, const int* sizes, int type, const Scalar& s);
+
+    /** @overload
+    @param sizes Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param s An optional value to initialize each matrix element with. To set all the matrix elements to
+    the particular value after the construction, use the assignment operator
+    Mat::operator=(const Scalar& value) .
+    */
+    Mat(const std::vector<int>& sizes, int type, const Scalar& s);
+
+
+    /** @overload
+    @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
+    by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
+    associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
+    formed using such a constructor, you also modify the corresponding elements of m . If you want to
+    have an independent copy of the sub-array, use Mat::clone() .
+    */
+    Mat(const Mat& m);
+
+    /** @overload
+    @param rows Number of rows in a 2D array.
+    @param cols Number of columns in a 2D array.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
+    allocate matrix data. Instead, they just initialize the matrix header that points to the specified
+    data, which means that no data is copied. This operation is very efficient and can be used to
+    process external data using OpenCV functions. The external data is not automatically deallocated, so
+    you should take care of it.
+    @param step Number of bytes each matrix row occupies. The value should include the padding bytes at
+    the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed
+    and the actual step is calculated as cols*elemSize(). See Mat::elemSize.
+    */
+    Mat(int rows, int cols, int type, void* data, size_t step=AUTO_STEP);
+
+    /** @overload
+    @param size 2D array size: Size(cols, rows) . In the Size() constructor, the number of rows and the
+    number of columns go in the reverse order.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
+    allocate matrix data. Instead, they just initialize the matrix header that points to the specified
+    data, which means that no data is copied. This operation is very efficient and can be used to
+    process external data using OpenCV functions. The external data is not automatically deallocated, so
+    you should take care of it.
+    @param step Number of bytes each matrix row occupies. The value should include the padding bytes at
+    the end of each row, if any. If the parameter is missing (set to AUTO_STEP ), no padding is assumed
+    and the actual step is calculated as cols*elemSize(). See Mat::elemSize.
+    */
+    Mat(Size size, int type, void* data, size_t step=AUTO_STEP);
+
+    /** @overload
+    @param ndims Array dimensionality.
+    @param sizes Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
+    allocate matrix data. Instead, they just initialize the matrix header that points to the specified
+    data, which means that no data is copied. This operation is very efficient and can be used to
+    process external data using OpenCV functions. The external data is not automatically deallocated, so
+    you should take care of it.
+    @param steps Array of ndims-1 steps in case of a multi-dimensional array (the last step is always
+    set to the element size). If not specified, the matrix is assumed to be continuous.
+    */
+    Mat(int ndims, const int* sizes, int type, void* data, const size_t* steps=0);
+
+    /** @overload
+    @param sizes Array of integers specifying an n-dimensional array shape.
+    @param type Array type. Use CV_8UC1, ..., CV_64FC4 to create 1-4 channel matrices, or
+    CV_8UC(n), ..., CV_64FC(n) to create multi-channel (up to CV_CN_MAX channels) matrices.
+    @param data Pointer to the user data. Matrix constructors that take data and step parameters do not
+    allocate matrix data. Instead, they just initialize the matrix header that points to the specified
+    data, which means that no data is copied. This operation is very efficient and can be used to
+    process external data using OpenCV functions. The external data is not automatically deallocated, so
+    you should take care of it.
+    @param steps Array of ndims-1 steps in case of a multi-dimensional array (the last step is always
+    set to the element size). If not specified, the matrix is assumed to be continuous.
+    */
+    Mat(const std::vector<int>& sizes, int type, void* data, const size_t* steps=0);
+
+    /** @overload
+    @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
+    by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
+    associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
+    formed using such a constructor, you also modify the corresponding elements of m . If you want to
+    have an independent copy of the sub-array, use Mat::clone() .
+    @param rowRange Range of the m rows to take. As usual, the range start is inclusive and the range
+    end is exclusive. Use Range::all() to take all the rows.
+    @param colRange Range of the m columns to take. Use Range::all() to take all the columns.
+    */
+    Mat(const Mat& m, const Range& rowRange, const Range& colRange=Range::all());
+
+    /** @overload
+    @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
+    by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
+    associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
+    formed using such a constructor, you also modify the corresponding elements of m . If you want to
+    have an independent copy of the sub-array, use Mat::clone() .
+    @param roi Region of interest.
+    */
+    Mat(const Mat& m, const Rect& roi);
+
+    /** @overload
+    @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
+    by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
+    associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
+    formed using such a constructor, you also modify the corresponding elements of m . If you want to
+    have an independent copy of the sub-array, use Mat::clone() .
+    @param ranges Array of selected ranges of m along each dimensionality.
+    */
+    Mat(const Mat& m, const Range* ranges);
+
+    /** @overload
+    @param m Array that (as a whole or partly) is assigned to the constructed matrix. No data is copied
+    by these constructors. Instead, the header pointing to m data or its sub-array is constructed and
+    associated with it. The reference counter, if any, is incremented. So, when you modify the matrix
+    formed using such a constructor, you also modify the corresponding elements of m . If you want to
+    have an independent copy of the sub-array, use Mat::clone() .
+    @param ranges Array of selected ranges of m along each dimensionality.
+    */
+    Mat(const Mat& m, const std::vector<Range>& ranges);
+
+    /** @overload
+    @param vec STL vector whose elements form the matrix. The matrix has a single column and the number
+    of rows equal to the number of vector elements. Type of the matrix matches the type of vector
+    elements. The constructor can handle arbitrary types, for which there is a properly declared
+    DataType . This means that the vector elements must be primitive numbers or uni-type numerical
+    tuples of numbers. Mixed-type structures are not supported. The corresponding constructor is
+    explicit. Since STL vectors are not automatically converted to Mat instances, you should write
+    Mat(vec) explicitly. Unless you copy the data into the matrix ( copyData=true ), no new elements
+    will be added to the vector because it can potentially yield vector data reallocation, and, thus,
+    the matrix data pointer will be invalid.
+    @param copyData Flag to specify whether the underlying data of the STL vector should be copied
+    to (true) or shared with (false) the newly constructed matrix. When the data is copied, the
+    allocated buffer is managed using Mat reference counting mechanism. While the data is shared,
+    the reference counter is NULL, and you should not deallocate the data until the matrix is
+    destructed.
+    */
+    template<typename _Tp> explicit Mat(const std::vector<_Tp>& vec, bool copyData=false);
+
+    /** @overload
+    */
+    template<typename _Tp, typename = typename std::enable_if<std::is_arithmetic<_Tp>::value>::type>
+    explicit Mat(const std::initializer_list<_Tp> list);
+
+    /** @overload
+    */
+    template<typename _Tp> explicit Mat(const std::initializer_list<int> sizes, const std::initializer_list<_Tp> list);
+
+    /** @overload
+    */
+    template<typename _Tp, size_t _Nm> explicit Mat(const std::array<_Tp, _Nm>& arr, bool copyData=false);
+
+    /** @overload
+    */
+    template<typename _Tp, int n> explicit Mat(const Vec<_Tp, n>& vec, bool copyData=true);
+
+    /** @overload
+    */
+    template<typename _Tp, int m, int n> explicit Mat(const Matx<_Tp, m, n>& mtx, bool copyData=true);
+
+    /** @overload
+    */
+    template<typename _Tp> explicit Mat(const Point_<_Tp>& pt, bool copyData=true);
+
+    /** @overload
+    */
+    template<typename _Tp> explicit Mat(const Point3_<_Tp>& pt, bool copyData=true);
+
+    /** @overload
+    */
+    template<typename _Tp> explicit Mat(const MatCommaInitializer_<_Tp>& commaInitializer);
+
+    //! download data from GpuMat
+    explicit Mat(const cuda::GpuMat& m);
+
+    //! destructor - calls release()
+    ~Mat();
+
+    /** @brief assignment operators
+
+    These are available assignment operators. Since they all are very different, make sure to read the
+    operator parameters description.
+    @param m Assigned, right-hand-side matrix. Matrix assignment is an O(1) operation. This means that
+    no data is copied but the data is shared and the reference counter, if any, is incremented. Before
+    assigning new data, the old data is de-referenced via Mat::release .
+     */
+    Mat& operator = (const Mat& m);
+
+    /** @overload
+    @param expr Assigned matrix expression object. As opposite to the first form of the assignment
+    operation, the second form can reuse already allocated matrix if it has the right size and type to
+    fit the matrix expression result. It is automatically handled by the real function that the matrix
+    expressions is expanded to. For example, C=A+B is expanded to add(A, B, C), and add takes care of
+    automatic C reallocation.
+    */
+    Mat& operator = (const MatExpr& expr);
+
+    //! retrieve UMat from Mat
+    UMat getUMat(AccessFlag accessFlags, UMatUsageFlags usageFlags = USAGE_DEFAULT) const;
+
+    /** @brief Creates a matrix header for the specified matrix row.
+
+    The method makes a new header for the specified matrix row and returns it. This is an O(1)
+    operation, regardless of the matrix size. The underlying data of the new matrix is shared with the
+    original matrix. Here is the example of one of the classical basic matrix processing operations,
+    axpy, used by LU and many other algorithms:
+    @code
+        inline void matrix_axpy(Mat& A, int i, int j, double alpha)
+        {
+            A.row(i) += A.row(j)*alpha;
+        }
+    @endcode
+    @note In the current implementation, the following code does not work as expected:
+    @code
+        Mat A;
+        ...
+        A.row(i) = A.row(j); // will not work
+    @endcode
+    This happens because A.row(i) forms a temporary header that is further assigned to another header.
+    Remember that each of these operations is O(1), that is, no data is copied. Thus, the above
+    assignment is not true if you may have expected the j-th row to be copied to the i-th row. To
+    achieve that, you should either turn this simple assignment into an expression or use the
+    Mat::copyTo method:
+    @code
+        Mat A;
+        ...
+        // works, but looks a bit obscure.
+        A.row(i) = A.row(j) + 0;
+        // this is a bit longer, but the recommended method.
+        A.row(j).copyTo(A.row(i));
+    @endcode
+    @param y A 0-based row index.
+     */
+    Mat row(int y) const;
+
+    /** @brief Creates a matrix header for the specified matrix column.
+
+    The method makes a new header for the specified matrix column and returns it. This is an O(1)
+    operation, regardless of the matrix size. The underlying data of the new matrix is shared with the
+    original matrix. See also the Mat::row description.
+    @param x A 0-based column index.
+     */
+    Mat col(int x) const;
+
+    /** @brief Creates a matrix header for the specified row span.
+
+    The method makes a new header for the specified row span of the matrix. Similarly to Mat::row and
+    Mat::col , this is an O(1) operation.
+    @param startrow An inclusive 0-based start index of the row span.
+    @param endrow An exclusive 0-based ending index of the row span.
+     */
+    Mat rowRange(int startrow, int endrow) const;
+
+    /** @overload
+    @param r Range structure containing both the start and the end indices.
+    */
+    Mat rowRange(const Range& r) const;
+
+    /** @brief Creates a matrix header for the specified column span.
+
+    The method makes a new header for the specified column span of the matrix. Similarly to Mat::row and
+    Mat::col , this is an O(1) operation.
+    @param startcol An inclusive 0-based start index of the column span.
+    @param endcol An exclusive 0-based ending index of the column span.
+     */
+    Mat colRange(int startcol, int endcol) const;
+
+    /** @overload
+    @param r Range structure containing both the start and the end indices.
+    */
+    Mat colRange(const Range& r) const;
+
+    /** @brief Extracts a diagonal from a matrix
+
+    The method makes a new header for the specified matrix diagonal. The new matrix is represented as a
+    single-column matrix. Similarly to Mat::row and Mat::col, this is an O(1) operation.
+    @param d index of the diagonal, with the following values:
+    - `d=0` is the main diagonal.
+    - `d<0` is a diagonal from the lower half. For example, d=-1 means the diagonal is set
+      immediately below the main one.
+    - `d>0` is a diagonal from the upper half. For example, d=1 means the diagonal is set
+      immediately above the main one.
+    For example:
+    @code
+        Mat m = (Mat_<int>(3,3) <<
+                    1,2,3,
+                    4,5,6,
+                    7,8,9);
+        Mat d0 = m.diag(0);
+        Mat d1 = m.diag(1);
+        Mat d_1 = m.diag(-1);
+    @endcode
+    The resulting matrices are
+    @code
+     d0 =
+       [1;
+        5;
+        9]
+     d1 =
+       [2;
+        6]
+     d_1 =
+       [4;
+        8]
+    @endcode
+     */
+    Mat diag(int d=0) const;
+
+    /** @brief creates a diagonal matrix
+
+    The method creates a square diagonal matrix from specified main diagonal.
+    @param d One-dimensional matrix that represents the main diagonal.
+     */
+    CV_NODISCARD_STD static Mat diag(const Mat& d);
+
+    /** @brief Creates a full copy of the array and the underlying data.
+
+    The method creates a full copy of the array. The original step[] is not taken into account. So, the
+    array copy is a continuous array occupying total()*elemSize() bytes.
+     */
+    CV_NODISCARD_STD Mat clone() const;
+
+    /** @brief Copies the matrix to another one.
+
+    The method copies the matrix data to another matrix. Before copying the data, the method invokes :
+    @code
+        m.create(this->size(), this->type());
+    @endcode
+    so that the destination matrix is reallocated if needed. While m.copyTo(m); works flawlessly, the
+    function does not handle the case of a partial overlap between the source and the destination
+    matrices.
+
+    When the operation mask is specified, if the Mat::create call shown above reallocates the matrix,
+    the newly allocated matrix is initialized with all zeros before copying the data.
+    @param m Destination matrix. If it does not have a proper size or type before the operation, it is
+    reallocated.
+     */
+    void copyTo( OutputArray m ) const;
+
+    /** @overload
+    @param m Destination matrix. If it does not have a proper size or type before the operation, it is
+    reallocated.
+    @param mask Operation mask of the same size as \*this. Its non-zero elements indicate which matrix
+    elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels.
+    */
+    void copyTo( OutputArray m, InputArray mask ) const;
+
+    /** @brief Converts an array to another data type with optional scaling.
+
+    The method converts source pixel values to the target data type. saturate_cast\<\> is applied at
+    the end to avoid possible overflows:
+
+    \f[m(x,y) = saturate \_ cast<rType>( \alpha (*this)(x,y) +  \beta )\f]
+    @param m output matrix; if it does not have a proper size or type before the operation, it is
+    reallocated.
+    @param rtype desired output matrix type or, rather, the depth since the number of channels are the
+    same as the input has; if rtype is negative, the output matrix will have the same type as the input.
+    @param alpha optional scale factor.
+    @param beta optional delta added to the scaled values.
+     */
+    void convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const;
+
+    /** @brief Provides a functional form of convertTo.
+
+    This is an internally used method called by the @ref MatrixExpressions engine.
+    @param m Destination array.
+    @param type Desired destination array depth (or -1 if it should be the same as the source type).
+     */
+    void assignTo( Mat& m, int type=-1 ) const;
+
+    /** @brief Sets all or some of the array elements to the specified value.
+    @param s Assigned scalar converted to the actual array type.
+    */
+    Mat& operator = (const Scalar& s);
+
+    /** @brief Sets all or some of the array elements to the specified value.
+
+    This is an advanced variant of the Mat::operator=(const Scalar& s) operator.
+    @param value Assigned scalar converted to the actual array type.
+    @param mask Operation mask of the same size as \*this. Its non-zero elements indicate which matrix
+    elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels
+     */
+    Mat& setTo(InputArray value, InputArray mask=noArray());
+
+    /** @brief Changes the shape and/or the number of channels of a 2D matrix without copying the data.
+
+    The method makes a new matrix header for \*this elements. The new matrix may have a different size
+    and/or different number of channels. Any combination is possible if:
+    -   No extra elements are included into the new matrix and no elements are excluded. Consequently,
+        the product rows\*cols\*channels() must stay the same after the transformation.
+    -   No data is copied. That is, this is an O(1) operation. Consequently, if you change the number of
+        rows, or the operation changes the indices of elements row in some other way, the matrix must be
+        continuous. See Mat::isContinuous .
+
+    For example, if there is a set of 3D points stored as an STL vector, and you want to represent the
+    points as a 3xN matrix, do the following:
+    @code
+        std::vector<Point3f> vec;
+        ...
+        Mat pointMat = Mat(vec). // convert vector to Mat, O(1) operation
+                          reshape(1). // make Nx3 1-channel matrix out of Nx1 3-channel.
+                                      // Also, an O(1) operation
+                             t(); // finally, transpose the Nx3 matrix.
+                                  // This involves copying all the elements
+    @endcode
+    3-channel 2x2 matrix reshaped to 1-channel 4x3 matrix, each column has values from one of original channels:
+    @code
+    Mat m(Size(2, 2), CV_8UC3, Scalar(1, 2, 3));
+    vector<int> new_shape {4, 3};
+    m = m.reshape(1, new_shape);
+    @endcode
+    or:
+    @code
+    Mat m(Size(2, 2), CV_8UC3, Scalar(1, 2, 3));
+    const int new_shape[] = {4, 3};
+    m = m.reshape(1, 2, new_shape);
+    @endcode
+    @param cn New number of channels. If the parameter is 0, the number of channels remains the same.
+    @param rows New number of rows. If the parameter is 0, the number of rows remains the same.
+     */
+    Mat reshape(int cn, int rows=0) const;
+
+    /** @overload
+     * @param cn New number of channels. If the parameter is 0, the number of channels remains the same.
+     * @param newndims New number of dimentions.
+     * @param newsz Array with new matrix size by all dimentions. If some sizes are zero,
+     * the original sizes in those dimensions are presumed.
+     */
+    Mat reshape(int cn, int newndims, const int* newsz) const;
+
+    /** @overload
+     * @param cn New number of channels. If the parameter is 0, the number of channels remains the same.
+     * @param newshape Vector with new matrix size by all dimentions. If some sizes are zero,
+     * the original sizes in those dimensions are presumed.
+     */
+    Mat reshape(int cn, const std::vector<int>& newshape) const;
+
+    /** @brief Transposes a matrix.
+
+    The method performs matrix transposition by means of matrix expressions. It does not perform the
+    actual transposition but returns a temporary matrix transposition object that can be further used as
+    a part of more complex matrix expressions or can be assigned to a matrix:
+    @code
+        Mat A1 = A + Mat::eye(A.size(), A.type())*lambda;
+        Mat C = A1.t()*A1; // compute (A + lambda*I)^t * (A + lamda*I)
+    @endcode
+     */
+    MatExpr t() const;
+
+    /** @brief Inverses a matrix.
+
+    The method performs a matrix inversion by means of matrix expressions. This means that a temporary
+    matrix inversion object is returned by the method and can be used further as a part of more complex
+    matrix expressions or can be assigned to a matrix.
+    @param method Matrix inversion method. One of cv::DecompTypes
+     */
+    MatExpr inv(int method=DECOMP_LU) const;
+
+    /** @brief Performs an element-wise multiplication or division of the two matrices.
+
+    The method returns a temporary object encoding per-element array multiplication, with optional
+    scale. Note that this is not a matrix multiplication that corresponds to a simpler "\*" operator.
+
+    Example:
+    @code
+        Mat C = A.mul(5/B); // equivalent to divide(A, B, C, 5)
+    @endcode
+    @param m Another array of the same type and the same size as \*this, or a matrix expression.
+    @param scale Optional scale factor.
+     */
+    MatExpr mul(InputArray m, double scale=1) const;
+
+    /** @brief Computes a cross-product of two 3-element vectors.
+
+    The method computes a cross-product of two 3-element vectors. The vectors must be 3-element
+    floating-point vectors of the same shape and size. The result is another 3-element vector of the
+    same shape and type as operands.
+    @param m Another cross-product operand.
+     */
+    Mat cross(InputArray m) const;
+
+    /** @brief Computes a dot-product of two vectors.
+
+    The method computes a dot-product of two matrices. If the matrices are not single-column or
+    single-row vectors, the top-to-bottom left-to-right scan ordering is used to treat them as 1D
+    vectors. The vectors must have the same size and type. If the matrices have more than one channel,
+    the dot products from all the channels are summed together.
+    @param m another dot-product operand.
+     */
+    double dot(InputArray m) const;
+
+    /** @brief Returns a zero array of the specified size and type.
+
+    The method returns a Matlab-style zero array initializer. It can be used to quickly form a constant
+    array as a function parameter, part of a matrix expression, or as a matrix initializer:
+    @code
+        Mat A;
+        A = Mat::zeros(3, 3, CV_32F);
+    @endcode
+    In the example above, a new matrix is allocated only if A is not a 3x3 floating-point matrix.
+    Otherwise, the existing matrix A is filled with zeros.
+    @param rows Number of rows.
+    @param cols Number of columns.
+    @param type Created matrix type.
+     */
+    CV_NODISCARD_STD static MatExpr zeros(int rows, int cols, int type);
+
+    /** @overload
+    @param size Alternative to the matrix size specification Size(cols, rows) .
+    @param type Created matrix type.
+    */
+    CV_NODISCARD_STD static MatExpr zeros(Size size, int type);
+
+    /** @overload
+    @param ndims Array dimensionality.
+    @param sz Array of integers specifying the array shape.
+    @param type Created matrix type.
+    */
+    CV_NODISCARD_STD static MatExpr zeros(int ndims, const int* sz, int type);
+
+    /** @brief Returns an array of all 1's of the specified size and type.
+
+    The method returns a Matlab-style 1's array initializer, similarly to Mat::zeros. Note that using
+    this method you can initialize an array with an arbitrary value, using the following Matlab idiom:
+    @code
+        Mat A = Mat::ones(100, 100, CV_8U)*3; // make 100x100 matrix filled with 3.
+    @endcode
+    The above operation does not form a 100x100 matrix of 1's and then multiply it by 3. Instead, it
+    just remembers the scale factor (3 in this case) and use it when actually invoking the matrix
+    initializer.
+    @note In case of multi-channels type, only the first channel will be initialized with 1's, the
+    others will be set to 0's.
+    @param rows Number of rows.
+    @param cols Number of columns.
+    @param type Created matrix type.
+     */
+    CV_NODISCARD_STD static MatExpr ones(int rows, int cols, int type);
+
+    /** @overload
+    @param size Alternative to the matrix size specification Size(cols, rows) .
+    @param type Created matrix type.
+    */
+    CV_NODISCARD_STD static MatExpr ones(Size size, int type);
+
+    /** @overload
+    @param ndims Array dimensionality.
+    @param sz Array of integers specifying the array shape.
+    @param type Created matrix type.
+    */
+    CV_NODISCARD_STD static MatExpr ones(int ndims, const int* sz, int type);
+
+    /** @brief Returns an identity matrix of the specified size and type.
+
+    The method returns a Matlab-style identity matrix initializer, similarly to Mat::zeros. Similarly to
+    Mat::ones, you can use a scale operation to create a scaled identity matrix efficiently:
+    @code
+        // make a 4x4 diagonal matrix with 0.1's on the diagonal.
+        Mat A = Mat::eye(4, 4, CV_32F)*0.1;
+    @endcode
+    @note In case of multi-channels type, identity matrix will be initialized only for the first channel,
+    the others will be set to 0's
+    @param rows Number of rows.
+    @param cols Number of columns.
+    @param type Created matrix type.
+     */
+    CV_NODISCARD_STD static MatExpr eye(int rows, int cols, int type);
+
+    /** @overload
+    @param size Alternative matrix size specification as Size(cols, rows) .
+    @param type Created matrix type.
+    */
+    CV_NODISCARD_STD static MatExpr eye(Size size, int type);
+
+    /** @brief Allocates new array data if needed.
+
+    This is one of the key Mat methods. Most new-style OpenCV functions and methods that produce arrays
+    call this method for each output array. The method uses the following algorithm:
+
+    -# If the current array shape and the type match the new ones, return immediately. Otherwise,
+       de-reference the previous data by calling Mat::release.
+    -# Initialize the new header.
+    -# Allocate the new data of total()\*elemSize() bytes.
+    -# Allocate the new, associated with the data, reference counter and set it to 1.
+
+    Such a scheme makes the memory management robust and efficient at the same time and helps avoid
+    extra typing for you. This means that usually there is no need to explicitly allocate output arrays.
+    That is, instead of writing:
+    @code
+        Mat color;
+        ...
+        Mat gray(color.rows, color.cols, color.depth());
+        cvtColor(color, gray, COLOR_BGR2GRAY);
+    @endcode
+    you can simply write:
+    @code
+        Mat color;
+        ...
+        Mat gray;
+        cvtColor(color, gray, COLOR_BGR2GRAY);
+    @endcode
+    because cvtColor, as well as the most of OpenCV functions, calls Mat::create() for the output array
+    internally.
+    @param rows New number of rows.
+    @param cols New number of columns.
+    @param type New matrix type.
+     */
+    void create(int rows, int cols, int type);
+
+    /** @overload
+    @param size Alternative new matrix size specification: Size(cols, rows)
+    @param type New matrix type.
+    */
+    void create(Size size, int type);
+
+    /** @overload
+    @param ndims New array dimensionality.
+    @param sizes Array of integers specifying a new array shape.
+    @param type New matrix type.
+    */
+    void create(int ndims, const int* sizes, int type);
+
+    /** @overload
+    @param sizes Array of integers specifying a new array shape.
+    @param type New matrix type.
+    */
+    void create(const std::vector<int>& sizes, int type);
+
+    /** @brief Increments the reference counter.
+
+    The method increments the reference counter associated with the matrix data. If the matrix header
+    points to an external data set (see Mat::Mat ), the reference counter is NULL, and the method has no
+    effect in this case. Normally, to avoid memory leaks, the method should not be called explicitly. It
+    is called implicitly by the matrix assignment operator. The reference counter increment is an atomic
+    operation on the platforms that support it. Thus, it is safe to operate on the same matrices
+    asynchronously in different threads.
+     */
+    void addref();
+
+    /** @brief Decrements the reference counter and deallocates the matrix if needed.
+
+    The method decrements the reference counter associated with the matrix data. When the reference
+    counter reaches 0, the matrix data is deallocated and the data and the reference counter pointers
+    are set to NULL's. If the matrix header points to an external data set (see Mat::Mat ), the
+    reference counter is NULL, and the method has no effect in this case.
+
+    This method can be called manually to force the matrix data deallocation. But since this method is
+    automatically called in the destructor, or by any other method that changes the data pointer, it is
+    usually not needed. The reference counter decrement and check for 0 is an atomic operation on the
+    platforms that support it. Thus, it is safe to operate on the same matrices asynchronously in
+    different threads.
+     */
+    void release();
+
+    //! internal use function, consider to use 'release' method instead; deallocates the matrix data
+    void deallocate();
+    //! internal use function; properly re-allocates _size, _step arrays
+    void copySize(const Mat& m);
+
+    /** @brief Reserves space for the certain number of rows.
+
+    The method reserves space for sz rows. If the matrix already has enough space to store sz rows,
+    nothing happens. If the matrix is reallocated, the first Mat::rows rows are preserved. The method
+    emulates the corresponding method of the STL vector class.
+    @param sz Number of rows.
+     */
+    void reserve(size_t sz);
+
+    /** @brief Reserves space for the certain number of bytes.
+
+    The method reserves space for sz bytes. If the matrix already has enough space to store sz bytes,
+    nothing happens. If matrix has to be reallocated its previous content could be lost.
+    @param sz Number of bytes.
+    */
+    void reserveBuffer(size_t sz);
+
+    /** @brief Changes the number of matrix rows.
+
+    The methods change the number of matrix rows. If the matrix is reallocated, the first
+    min(Mat::rows, sz) rows are preserved. The methods emulate the corresponding methods of the STL
+    vector class.
+    @param sz New number of rows.
+     */
+    void resize(size_t sz);
+
+    /** @overload
+    @param sz New number of rows.
+    @param s Value assigned to the newly added elements.
+     */
+    void resize(size_t sz, const Scalar& s);
+
+    //! internal function
+    void push_back_(const void* elem);
+
+    /** @brief Adds elements to the bottom of the matrix.
+
+    The methods add one or more elements to the bottom of the matrix. They emulate the corresponding
+    method of the STL vector class. When elem is Mat , its type and the number of columns must be the
+    same as in the container matrix.
+    @param elem Added element(s).
+     */
+    template<typename _Tp> void push_back(const _Tp& elem);
+
+    /** @overload
+    @param elem Added element(s).
+    */
+    template<typename _Tp> void push_back(const Mat_<_Tp>& elem);
+
+    /** @overload
+    @param elem Added element(s).
+    */
+    template<typename _Tp> void push_back(const std::vector<_Tp>& elem);
+
+    /** @overload
+    @param m Added line(s).
+    */
+    void push_back(const Mat& m);
+
+    /** @brief Removes elements from the bottom of the matrix.
+
+    The method removes one or more rows from the bottom of the matrix.
+    @param nelems Number of removed rows. If it is greater than the total number of rows, an exception
+    is thrown.
+     */
+    void pop_back(size_t nelems=1);
+
+    /** @brief Locates the matrix header within a parent matrix.
+
+    After you extracted a submatrix from a matrix using Mat::row, Mat::col, Mat::rowRange,
+    Mat::colRange, and others, the resultant submatrix points just to the part of the original big
+    matrix. However, each submatrix contains information (represented by datastart and dataend
+    fields) that helps reconstruct the original matrix size and the position of the extracted
+    submatrix within the original matrix. The method locateROI does exactly that.
+    @param wholeSize Output parameter that contains the size of the whole matrix containing *this*
+    as a part.
+    @param ofs Output parameter that contains an offset of *this* inside the whole matrix.
+     */
+    void locateROI( Size& wholeSize, Point& ofs ) const;
+
+    /** @brief Adjusts a submatrix size and position within the parent matrix.
+
+    The method is complimentary to Mat::locateROI . The typical use of these functions is to determine
+    the submatrix position within the parent matrix and then shift the position somehow. Typically, it
+    can be required for filtering operations when pixels outside of the ROI should be taken into
+    account. When all the method parameters are positive, the ROI needs to grow in all directions by the
+    specified amount, for example:
+    @code
+        A.adjustROI(2, 2, 2, 2);
+    @endcode
+    In this example, the matrix size is increased by 4 elements in each direction. The matrix is shifted
+    by 2 elements to the left and 2 elements up, which brings in all the necessary pixels for the
+    filtering with the 5x5 kernel.
+
+    adjustROI forces the adjusted ROI to be inside of the parent matrix that is boundaries of the
+    adjusted ROI are constrained by boundaries of the parent matrix. For example, if the submatrix A is
+    located in the first row of a parent matrix and you called A.adjustROI(2, 2, 2, 2) then A will not
+    be increased in the upward direction.
+
+    The function is used internally by the OpenCV filtering functions, like filter2D , morphological
+    operations, and so on.
+    @param dtop Shift of the top submatrix boundary upwards.
+    @param dbottom Shift of the bottom submatrix boundary downwards.
+    @param dleft Shift of the left submatrix boundary to the left.
+    @param dright Shift of the right submatrix boundary to the right.
+    @sa copyMakeBorder
+     */
+    Mat& adjustROI( int dtop, int dbottom, int dleft, int dright );
+
+    /** @brief Extracts a rectangular submatrix.
+
+    The operators make a new header for the specified sub-array of \*this . They are the most
+    generalized forms of Mat::row, Mat::col, Mat::rowRange, and Mat::colRange . For example,
+    `A(Range(0, 10), Range::all())` is equivalent to `A.rowRange(0, 10)`. Similarly to all of the above,
+    the operators are O(1) operations, that is, no matrix data is copied.
+    @param rowRange Start and end row of the extracted submatrix. The upper boundary is not included. To
+    select all the rows, use Range::all().
+    @param colRange Start and end column of the extracted submatrix. The upper boundary is not included.
+    To select all the columns, use Range::all().
+     */
+    Mat operator()( Range rowRange, Range colRange ) const;
+
+    /** @overload
+    @param roi Extracted submatrix specified as a rectangle.
+    */
+    Mat operator()( const Rect& roi ) const;
+
+    /** @overload
+    @param ranges Array of selected ranges along each array dimension.
+    */
+    Mat operator()( const Range* ranges ) const;
+
+    /** @overload
+    @param ranges Array of selected ranges along each array dimension.
+    */
+    Mat operator()(const std::vector<Range>& ranges) const;
+
+    template<typename _Tp> operator std::vector<_Tp>() const;
+    template<typename _Tp, int n> operator Vec<_Tp, n>() const;
+    template<typename _Tp, int m, int n> operator Matx<_Tp, m, n>() const;
+
+    template<typename _Tp, std::size_t _Nm> operator std::array<_Tp, _Nm>() const;
+
+    /** @brief Reports whether the matrix is continuous or not.
+
+    The method returns true if the matrix elements are stored continuously without gaps at the end of
+    each row. Otherwise, it returns false. Obviously, 1x1 or 1xN matrices are always continuous.
+    Matrices created with Mat::create are always continuous. But if you extract a part of the matrix
+    using Mat::col, Mat::diag, and so on, or constructed a matrix header for externally allocated data,
+    such matrices may no longer have this property.
+
+    The continuity flag is stored as a bit in the Mat::flags field and is computed automatically when
+    you construct a matrix header. Thus, the continuity check is a very fast operation, though
+    theoretically it could be done as follows:
+    @code
+        // alternative implementation of Mat::isContinuous()
+        bool myCheckMatContinuity(const Mat& m)
+        {
+            //return (m.flags & Mat::CONTINUOUS_FLAG) != 0;
+            return m.rows == 1 || m.step == m.cols*m.elemSize();
+        }
+    @endcode
+    The method is used in quite a few of OpenCV functions. The point is that element-wise operations
+    (such as arithmetic and logical operations, math functions, alpha blending, color space
+    transformations, and others) do not depend on the image geometry. Thus, if all the input and output
+    arrays are continuous, the functions can process them as very long single-row vectors. The example
+    below illustrates how an alpha-blending function can be implemented:
+    @code
+        template<typename T>
+        void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst)
+        {
+            const float alpha_scale = (float)std::numeric_limits<T>::max(),
+                        inv_scale = 1.f/alpha_scale;
+
+            CV_Assert( src1.type() == src2.type() &&
+                       src1.type() == CV_MAKETYPE(traits::Depth<T>::value, 4) &&
+                       src1.size() == src2.size());
+            Size size = src1.size();
+            dst.create(size, src1.type());
+
+            // here is the idiom: check the arrays for continuity and,
+            // if this is the case,
+            // treat the arrays as 1D vectors
+            if( src1.isContinuous() && src2.isContinuous() && dst.isContinuous() )
+            {
+                size.width *= size.height;
+                size.height = 1;
+            }
+            size.width *= 4;
+
+            for( int i = 0; i < size.height; i++ )
+            {
+                // when the arrays are continuous,
+                // the outer loop is executed only once
+                const T* ptr1 = src1.ptr<T>(i);
+                const T* ptr2 = src2.ptr<T>(i);
+                T* dptr = dst.ptr<T>(i);
+
+                for( int j = 0; j < size.width; j += 4 )
+                {
+                    float alpha = ptr1[j+3]*inv_scale, beta = ptr2[j+3]*inv_scale;
+                    dptr[j] = saturate_cast<T>(ptr1[j]*alpha + ptr2[j]*beta);
+                    dptr[j+1] = saturate_cast<T>(ptr1[j+1]*alpha + ptr2[j+1]*beta);
+                    dptr[j+2] = saturate_cast<T>(ptr1[j+2]*alpha + ptr2[j+2]*beta);
+                    dptr[j+3] = saturate_cast<T>((1 - (1-alpha)*(1-beta))*alpha_scale);
+                }
+            }
+        }
+    @endcode
+    This approach, while being very simple, can boost the performance of a simple element-operation by
+    10-20 percents, especially if the image is rather small and the operation is quite simple.
+
+    Another OpenCV idiom in this function, a call of Mat::create for the destination array, that
+    allocates the destination array unless it already has the proper size and type. And while the newly
+    allocated arrays are always continuous, you still need to check the destination array because
+    Mat::create does not always allocate a new matrix.
+     */
+    bool isContinuous() const;
+
+    //! returns true if the matrix is a submatrix of another matrix
+    bool isSubmatrix() const;
+
+    /** @brief Returns the matrix element size in bytes.
+
+    The method returns the matrix element size in bytes. For example, if the matrix type is CV_16SC3 ,
+    the method returns 3\*sizeof(short) or 6.
+     */
+    size_t elemSize() const;
+
+    /** @brief Returns the size of each matrix element channel in bytes.
+
+    The method returns the matrix element channel size in bytes, that is, it ignores the number of
+    channels. For example, if the matrix type is CV_16SC3 , the method returns sizeof(short) or 2.
+     */
+    size_t elemSize1() const;
+
+    /** @brief Returns the type of a matrix element.
+
+    The method returns a matrix element type. This is an identifier compatible with the CvMat type
+    system, like CV_16SC3 or 16-bit signed 3-channel array, and so on.
+     */
+    int type() const;
+
+    /** @brief Returns the depth of a matrix element.
+
+    The method returns the identifier of the matrix element depth (the type of each individual channel).
+    For example, for a 16-bit signed element array, the method returns CV_16S . A complete list of
+    matrix types contains the following values:
+    -   CV_8U - 8-bit unsigned integers ( 0..255 )
+    -   CV_8S - 8-bit signed integers ( -128..127 )
+    -   CV_16U - 16-bit unsigned integers ( 0..65535 )
+    -   CV_16S - 16-bit signed integers ( -32768..32767 )
+    -   CV_32S - 32-bit signed integers ( -2147483648..2147483647 )
+    -   CV_32F - 32-bit floating-point numbers ( -FLT_MAX..FLT_MAX, INF, NAN )
+    -   CV_64F - 64-bit floating-point numbers ( -DBL_MAX..DBL_MAX, INF, NAN )
+     */
+    int depth() const;
+
+    /** @brief Returns the number of matrix channels.
+
+    The method returns the number of matrix channels.
+     */
+    int channels() const;
+
+    /** @brief Returns a normalized step.
+
+    The method returns a matrix step divided by Mat::elemSize1() . It can be useful to quickly access an
+    arbitrary matrix element.
+     */
+    size_t step1(int i=0) const;
+
+    /** @brief Returns true if the array has no elements.
+
+    The method returns true if Mat::total() is 0 or if Mat::data is NULL. Because of pop_back() and
+    resize() methods `M.total() == 0` does not imply that `M.data == NULL`.
+     */
+    bool empty() const;
+
+    /** @brief Returns the total number of array elements.
+
+    The method returns the number of array elements (a number of pixels if the array represents an
+    image).
+     */
+    size_t total() const;
+
+    /** @brief Returns the total number of array elements.
+
+     The method returns the number of elements within a certain sub-array slice with startDim <= dim < endDim
+     */
+    size_t total(int startDim, int endDim=INT_MAX) const;
+
+    /**
+     * @param elemChannels Number of channels or number of columns the matrix should have.
+     *                     For a 2-D matrix, when the matrix has only 1 column, then it should have
+     *                     elemChannels channels; When the matrix has only 1 channel,
+     *                     then it should have elemChannels columns.
+     *                     For a 3-D matrix, it should have only one channel. Furthermore,
+     *                     if the number of planes is not one, then the number of rows
+     *                     within every plane has to be 1; if the number of rows within
+     *                     every plane is not 1, then the number of planes has to be 1.
+     * @param depth The depth the matrix should have. Set it to -1 when any depth is fine.
+     * @param requireContinuous Set it to true to require the matrix to be continuous
+     * @return -1 if the requirement is not satisfied.
+     *         Otherwise, it returns the number of elements in the matrix. Note
+     *         that an element may have multiple channels.
+     *
+     * The following code demonstrates its usage for a 2-d matrix:
+     * @snippet snippets/core_mat_checkVector.cpp example-2d
+     *
+     * The following code demonstrates its usage for a 3-d matrix:
+     * @snippet snippets/core_mat_checkVector.cpp example-3d
+     */
+    int checkVector(int elemChannels, int depth=-1, bool requireContinuous=true) const;
+
+    /** @brief Returns a pointer to the specified matrix row.
+
+    The methods return `uchar*` or typed pointer to the specified matrix row. See the sample in
+    Mat::isContinuous to know how to use these methods.
+    @param i0 A 0-based row index.
+     */
+    uchar* ptr(int i0=0);
+    /** @overload */
+    const uchar* ptr(int i0=0) const;
+
+    /** @overload
+    @param row Index along the dimension 0
+    @param col Index along the dimension 1
+    */
+    uchar* ptr(int row, int col);
+    /** @overload
+    @param row Index along the dimension 0
+    @param col Index along the dimension 1
+    */
+    const uchar* ptr(int row, int col) const;
+
+    /** @overload */
+    uchar* ptr(int i0, int i1, int i2);
+    /** @overload */
+    const uchar* ptr(int i0, int i1, int i2) const;
+
+    /** @overload */
+    uchar* ptr(const int* idx);
+    /** @overload */
+    const uchar* ptr(const int* idx) const;
+    /** @overload */
+    template<int n> uchar* ptr(const Vec<int, n>& idx);
+    /** @overload */
+    template<int n> const uchar* ptr(const Vec<int, n>& idx) const;
+
+    /** @overload */
+    template<typename _Tp> _Tp* ptr(int i0=0);
+    /** @overload */
+    template<typename _Tp> const _Tp* ptr(int i0=0) const;
+    /** @overload
+    @param row Index along the dimension 0
+    @param col Index along the dimension 1
+    */
+    template<typename _Tp> _Tp* ptr(int row, int col);
+    /** @overload
+    @param row Index along the dimension 0
+    @param col Index along the dimension 1
+    */
+    template<typename _Tp> const _Tp* ptr(int row, int col) const;
+    /** @overload */
+    template<typename _Tp> _Tp* ptr(int i0, int i1, int i2);
+    /** @overload */
+    template<typename _Tp> const _Tp* ptr(int i0, int i1, int i2) const;
+    /** @overload */
+    template<typename _Tp> _Tp* ptr(const int* idx);
+    /** @overload */
+    template<typename _Tp> const _Tp* ptr(const int* idx) const;
+    /** @overload */
+    template<typename _Tp, int n> _Tp* ptr(const Vec<int, n>& idx);
+    /** @overload */
+    template<typename _Tp, int n> const _Tp* ptr(const Vec<int, n>& idx) const;
+
+    /** @brief Returns a reference to the specified array element.
+
+    The template methods return a reference to the specified array element. For the sake of higher
+    performance, the index range checks are only performed in the Debug configuration.
+
+    Note that the variants with a single index (i) can be used to access elements of single-row or
+    single-column 2-dimensional arrays. That is, if, for example, A is a 1 x N floating-point matrix and
+    B is an M x 1 integer matrix, you can simply write `A.at<float>(k+4)` and `B.at<int>(2*i+1)`
+    instead of `A.at<float>(0,k+4)` and `B.at<int>(2*i+1,0)`, respectively.
+
+    The example below initializes a Hilbert matrix:
+    @code
+        Mat H(100, 100, CV_64F);
+        for(int i = 0; i < H.rows; i++)
+            for(int j = 0; j < H.cols; j++)
+                H.at<double>(i,j)=1./(i+j+1);
+    @endcode
+
+    Keep in mind that the size identifier used in the at operator cannot be chosen at random. It depends
+    on the image from which you are trying to retrieve the data. The table below gives a better insight in this:
+     - If matrix is of type `CV_8U` then use `Mat.at<uchar>(y,x)`.
+     - If matrix is of type `CV_8S` then use `Mat.at<schar>(y,x)`.
+     - If matrix is of type `CV_16U` then use `Mat.at<ushort>(y,x)`.
+     - If matrix is of type `CV_16S` then use `Mat.at<short>(y,x)`.
+     - If matrix is of type `CV_32S`  then use `Mat.at<int>(y,x)`.
+     - If matrix is of type `CV_32F`  then use `Mat.at<float>(y,x)`.
+     - If matrix is of type `CV_64F` then use `Mat.at<double>(y,x)`.
+
+    @param i0 Index along the dimension 0
+     */
+    template<typename _Tp> _Tp& at(int i0=0);
+    /** @overload
+    @param i0 Index along the dimension 0
+    */
+    template<typename _Tp> const _Tp& at(int i0=0) const;
+    /** @overload
+    @param row Index along the dimension 0
+    @param col Index along the dimension 1
+    */
+    template<typename _Tp> _Tp& at(int row, int col);
+    /** @overload
+    @param row Index along the dimension 0
+    @param col Index along the dimension 1
+    */
+    template<typename _Tp> const _Tp& at(int row, int col) const;
+
+    /** @overload
+    @param i0 Index along the dimension 0
+    @param i1 Index along the dimension 1
+    @param i2 Index along the dimension 2
+    */
+    template<typename _Tp> _Tp& at(int i0, int i1, int i2);
+    /** @overload
+    @param i0 Index along the dimension 0
+    @param i1 Index along the dimension 1
+    @param i2 Index along the dimension 2
+    */
+    template<typename _Tp> const _Tp& at(int i0, int i1, int i2) const;
+
+    /** @overload
+    @param idx Array of Mat::dims indices.
+    */
+    template<typename _Tp> _Tp& at(const int* idx);
+    /** @overload
+    @param idx Array of Mat::dims indices.
+    */
+    template<typename _Tp> const _Tp& at(const int* idx) const;
+
+    /** @overload */
+    template<typename _Tp, int n> _Tp& at(const Vec<int, n>& idx);
+    /** @overload */
+    template<typename _Tp, int n> const _Tp& at(const Vec<int, n>& idx) const;
+
+    /** @overload
+    special versions for 2D arrays (especially convenient for referencing image pixels)
+    @param pt Element position specified as Point(j,i) .
+    */
+    template<typename _Tp> _Tp& at(Point pt);
+    /** @overload
+    special versions for 2D arrays (especially convenient for referencing image pixels)
+    @param pt Element position specified as Point(j,i) .
+    */
+    template<typename _Tp> const _Tp& at(Point pt) const;
+
+    /** @brief Returns the matrix iterator and sets it to the first matrix element.
+
+    The methods return the matrix read-only or read-write iterators. The use of matrix iterators is very
+    similar to the use of bi-directional STL iterators. In the example below, the alpha blending
+    function is rewritten using the matrix iterators:
+    @code
+        template<typename T>
+        void alphaBlendRGBA(const Mat& src1, const Mat& src2, Mat& dst)
+        {
+            typedef Vec<T, 4> VT;
+
+            const float alpha_scale = (float)std::numeric_limits<T>::max(),
+                        inv_scale = 1.f/alpha_scale;
+
+            CV_Assert( src1.type() == src2.type() &&
+                       src1.type() == traits::Type<VT>::value &&
+                       src1.size() == src2.size());
+            Size size = src1.size();
+            dst.create(size, src1.type());
+
+            MatConstIterator_<VT> it1 = src1.begin<VT>(), it1_end = src1.end<VT>();
+            MatConstIterator_<VT> it2 = src2.begin<VT>();
+            MatIterator_<VT> dst_it = dst.begin<VT>();
+
+            for( ; it1 != it1_end; ++it1, ++it2, ++dst_it )
+            {
+                VT pix1 = *it1, pix2 = *it2;
+                float alpha = pix1[3]*inv_scale, beta = pix2[3]*inv_scale;
+                *dst_it = VT(saturate_cast<T>(pix1[0]*alpha + pix2[0]*beta),
+                             saturate_cast<T>(pix1[1]*alpha + pix2[1]*beta),
+                             saturate_cast<T>(pix1[2]*alpha + pix2[2]*beta),
+                             saturate_cast<T>((1 - (1-alpha)*(1-beta))*alpha_scale));
+            }
+        }
+    @endcode
+     */
+    template<typename _Tp> MatIterator_<_Tp> begin();
+    template<typename _Tp> MatConstIterator_<_Tp> begin() const;
+
+    /** @brief Same as begin() but for inverse traversal
+     */
+    template<typename _Tp> std::reverse_iterator<MatIterator_<_Tp>> rbegin();
+    template<typename _Tp> std::reverse_iterator<MatConstIterator_<_Tp>> rbegin() const;
+
+    /** @brief Returns the matrix iterator and sets it to the after-last matrix element.
+
+    The methods return the matrix read-only or read-write iterators, set to the point following the last
+    matrix element.
+     */
+    template<typename _Tp> MatIterator_<_Tp> end();
+    template<typename _Tp> MatConstIterator_<_Tp> end() const;
+
+    /** @brief Same as end() but for inverse traversal
+     */
+    template<typename _Tp> std::reverse_iterator< MatIterator_<_Tp>> rend();
+    template<typename _Tp> std::reverse_iterator< MatConstIterator_<_Tp>> rend() const;
+
+
+    /** @brief Runs the given functor over all matrix elements in parallel.
+
+    The operation passed as argument has to be a function pointer, a function object or a lambda(C++11).
+
+    Example 1. All of the operations below put 0xFF the first channel of all matrix elements:
+    @code
+        Mat image(1920, 1080, CV_8UC3);
+        typedef cv::Point3_<uint8_t> Pixel;
+
+        // first. raw pointer access.
+        for (int r = 0; r < image.rows; ++r) {
+            Pixel* ptr = image.ptr<Pixel>(r, 0);
+            const Pixel* ptr_end = ptr + image.cols;
+            for (; ptr != ptr_end; ++ptr) {
+                ptr->x = 255;
+            }
+        }
+
+        // Using MatIterator. (Simple but there are a Iterator's overhead)
+        for (Pixel &p : cv::Mat_<Pixel>(image)) {
+            p.x = 255;
+        }
+
+        // Parallel execution with function object.
+        struct Operator {
+            void operator ()(Pixel &pixel, const int * position) {
+                pixel.x = 255;
+            }
+        };
+        image.forEach<Pixel>(Operator());
+
+        // Parallel execution using C++11 lambda.
+        image.forEach<Pixel>([](Pixel &p, const int * position) -> void {
+            p.x = 255;
+        });
+    @endcode
+    Example 2. Using the pixel's position:
+    @code
+        // Creating 3D matrix (255 x 255 x 255) typed uint8_t
+        // and initialize all elements by the value which equals elements position.
+        // i.e. pixels (x,y,z) = (1,2,3) is (b,g,r) = (1,2,3).
+
+        int sizes[] = { 255, 255, 255 };
+        typedef cv::Point3_<uint8_t> Pixel;
+
+        Mat_<Pixel> image = Mat::zeros(3, sizes, CV_8UC3);
+
+        image.forEach<Pixel>([](Pixel& pixel, const int position[]) -> void {
+            pixel.x = position[0];
+            pixel.y = position[1];
+            pixel.z = position[2];
+        });
+    @endcode
+     */
+    template<typename _Tp, typename Functor> void forEach(const Functor& operation);
+    /** @overload */
+    template<typename _Tp, typename Functor> void forEach(const Functor& operation) const;
+
+    Mat(Mat&& m) CV_NOEXCEPT;
+    Mat& operator = (Mat&& m);
+
+    enum { MAGIC_VAL  = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG };
+    enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7 };
+
+    /*! includes several bit-fields:
+         - the magic signature
+         - continuity flag
+         - depth
+         - number of channels
+     */
+    int flags;
+    //! the matrix dimensionality, >= 2
+    int dims;
+    //! the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
+    int rows, cols;
+    //! pointer to the data
+    uchar* data;
+
+    //! helper fields used in locateROI and adjustROI
+    const uchar* datastart;
+    const uchar* dataend;
+    const uchar* datalimit;
+
+    //! custom allocator
+    MatAllocator* allocator;
+    //! and the standard allocator
+    static MatAllocator* getStdAllocator();
+    static MatAllocator* getDefaultAllocator();
+    static void setDefaultAllocator(MatAllocator* allocator);
+
+    //! internal use method: updates the continuity flag
+    void updateContinuityFlag();
+
+    //! interaction with UMat
+    UMatData* u;
+
+    MatSize size;
+    MatStep step;
+
+protected:
+    template<typename _Tp, typename Functor> void forEach_impl(const Functor& operation);
+};
+
+
+///////////////////////////////// Mat_<_Tp> ////////////////////////////////////
+
+/** @brief Template matrix class derived from Mat
+
+@code{.cpp}
+    template<typename _Tp> class Mat_ : public Mat
+    {
+    public:
+        // ... some specific methods
+        //         and
+        // no new extra fields
+    };
+@endcode
+The class `Mat_<_Tp>` is a *thin* template wrapper on top of the Mat class. It does not have any
+extra data fields. Nor this class nor Mat has any virtual methods. Thus, references or pointers to
+these two classes can be freely but carefully converted one to another. For example:
+@code{.cpp}
+    // create a 100x100 8-bit matrix
+    Mat M(100,100,CV_8U);
+    // this will be compiled fine. no any data conversion will be done.
+    Mat_<float>& M1 = (Mat_<float>&)M;
+    // the program is likely to crash at the statement below
+    M1(99,99) = 1.f;
+@endcode
+While Mat is sufficient in most cases, Mat_ can be more convenient if you use a lot of element
+access operations and if you know matrix type at the compilation time. Note that
+`Mat::at(int y,int x)` and `Mat_::operator()(int y,int x)` do absolutely the same
+and run at the same speed, but the latter is certainly shorter:
+@code{.cpp}
+    Mat_<double> M(20,20);
+    for(int i = 0; i < M.rows; i++)
+        for(int j = 0; j < M.cols; j++)
+            M(i,j) = 1./(i+j+1);
+    Mat E, V;
+    eigen(M,E,V);
+    cout << E.at<double>(0,0)/E.at<double>(M.rows-1,0);
+@endcode
+To use Mat_ for multi-channel images/matrices, pass Vec as a Mat_ parameter:
+@code{.cpp}
+    // allocate a 320x240 color image and fill it with green (in RGB space)
+    Mat_<Vec3b> img(240, 320, Vec3b(0,255,0));
+    // now draw a diagonal white line
+    for(int i = 0; i < 100; i++)
+        img(i,i)=Vec3b(255,255,255);
+    // and now scramble the 2nd (red) channel of each pixel
+    for(int i = 0; i < img.rows; i++)
+        for(int j = 0; j < img.cols; j++)
+            img(i,j)[2] ^= (uchar)(i ^ j);
+@endcode
+Mat_ is fully compatible with C++11 range-based for loop. For example such loop
+can be used to safely apply look-up table:
+@code{.cpp}
+void applyTable(Mat_<uchar>& I, const uchar* const table)
+{
+    for(auto& pixel : I)
+    {
+        pixel = table[pixel];
+    }
+}
+@endcode
+ */
+template<typename _Tp> class Mat_ : public Mat
+{
+public:
+    typedef _Tp value_type;
+    typedef typename DataType<_Tp>::channel_type channel_type;
+    typedef MatIterator_<_Tp> iterator;
+    typedef MatConstIterator_<_Tp> const_iterator;
+
+    //! default constructor
+    Mat_() CV_NOEXCEPT;
+    //! equivalent to Mat(_rows, _cols, DataType<_Tp>::type)
+    Mat_(int _rows, int _cols);
+    //! constructor that sets each matrix element to specified value
+    Mat_(int _rows, int _cols, const _Tp& value);
+    //! equivalent to Mat(_size, DataType<_Tp>::type)
+    explicit Mat_(Size _size);
+    //! constructor that sets each matrix element to specified value
+    Mat_(Size _size, const _Tp& value);
+    //! n-dim array constructor
+    Mat_(int _ndims, const int* _sizes);
+    //! n-dim array constructor that sets each matrix element to specified value
+    Mat_(int _ndims, const int* _sizes, const _Tp& value);
+    //! copy/conversion constructor. If m is of different type, it's converted
+    Mat_(const Mat& m);
+    //! copy constructor
+    Mat_(const Mat_& m);
+    //! constructs a matrix on top of user-allocated data. step is in bytes(!!!), regardless of the type
+    Mat_(int _rows, int _cols, _Tp* _data, size_t _step=AUTO_STEP);
+    //! constructs n-dim matrix on top of user-allocated data. steps are in bytes(!!!), regardless of the type
+    Mat_(int _ndims, const int* _sizes, _Tp* _data, const size_t* _steps=0);
+    //! selects a submatrix
+    Mat_(const Mat_& m, const Range& rowRange, const Range& colRange=Range::all());
+    //! selects a submatrix
+    Mat_(const Mat_& m, const Rect& roi);
+    //! selects a submatrix, n-dim version
+    Mat_(const Mat_& m, const Range* ranges);
+    //! selects a submatrix, n-dim version
+    Mat_(const Mat_& m, const std::vector<Range>& ranges);
+    //! from a matrix expression
+    explicit Mat_(const MatExpr& e);
+    //! makes a matrix out of Vec, std::vector, Point_ or Point3_. The matrix will have a single column
+    explicit Mat_(const std::vector<_Tp>& vec, bool copyData=false);
+    template<int n> explicit Mat_(const Vec<typename DataType<_Tp>::channel_type, n>& vec, bool copyData=true);
+    template<int m, int n> explicit Mat_(const Matx<typename DataType<_Tp>::channel_type, m, n>& mtx, bool copyData=true);
+    explicit Mat_(const Point_<typename DataType<_Tp>::channel_type>& pt, bool copyData=true);
+    explicit Mat_(const Point3_<typename DataType<_Tp>::channel_type>& pt, bool copyData=true);
+    explicit Mat_(const MatCommaInitializer_<_Tp>& commaInitializer);
+
+    Mat_(std::initializer_list<_Tp> values);
+    explicit Mat_(const std::initializer_list<int> sizes, const std::initializer_list<_Tp> values);
+
+    template <std::size_t _Nm> explicit Mat_(const std::array<_Tp, _Nm>& arr, bool copyData=false);
+
+    Mat_& operator = (const Mat& m);
+    Mat_& operator = (const Mat_& m);
+    //! set all the elements to s.
+    Mat_& operator = (const _Tp& s);
+    //! assign a matrix expression
+    Mat_& operator = (const MatExpr& e);
+
+    //! iterators; they are smart enough to skip gaps in the end of rows
+    iterator begin();
+    iterator end();
+    const_iterator begin() const;
+    const_iterator end() const;
+
+    //reverse iterators
+    std::reverse_iterator<iterator> rbegin();
+    std::reverse_iterator<iterator> rend();
+    std::reverse_iterator<const_iterator> rbegin() const;
+    std::reverse_iterator<const_iterator> rend() const;
+
+    //! template methods for operation over all matrix elements.
+    // the operations take care of skipping gaps in the end of rows (if any)
+    template<typename Functor> void forEach(const Functor& operation);
+    template<typename Functor> void forEach(const Functor& operation) const;
+
+    //! equivalent to Mat::create(_rows, _cols, DataType<_Tp>::type)
+    void create(int _rows, int _cols);
+    //! equivalent to Mat::create(_size, DataType<_Tp>::type)
+    void create(Size _size);
+    //! equivalent to Mat::create(_ndims, _sizes, DatType<_Tp>::type)
+    void create(int _ndims, const int* _sizes);
+    //! equivalent to Mat::release()
+    void release();
+    //! cross-product
+    Mat_ cross(const Mat_& m) const;
+    //! data type conversion
+    template<typename T2> operator Mat_<T2>() const;
+    //! overridden forms of Mat::row() etc.
+    Mat_ row(int y) const;
+    Mat_ col(int x) const;
+    Mat_ diag(int d=0) const;
+    CV_NODISCARD_STD Mat_ clone() const;
+
+    //! overridden forms of Mat::elemSize() etc.
+    size_t elemSize() const;
+    size_t elemSize1() const;
+    int type() const;
+    int depth() const;
+    int channels() const;
+    size_t step1(int i=0) const;
+    //! returns step()/sizeof(_Tp)
+    size_t stepT(int i=0) const;
+
+    //! overridden forms of Mat::zeros() etc. Data type is omitted, of course
+    CV_NODISCARD_STD static MatExpr zeros(int rows, int cols);
+    CV_NODISCARD_STD static MatExpr zeros(Size size);
+    CV_NODISCARD_STD static MatExpr zeros(int _ndims, const int* _sizes);
+    CV_NODISCARD_STD static MatExpr ones(int rows, int cols);
+    CV_NODISCARD_STD static MatExpr ones(Size size);
+    CV_NODISCARD_STD static MatExpr ones(int _ndims, const int* _sizes);
+    CV_NODISCARD_STD static MatExpr eye(int rows, int cols);
+    CV_NODISCARD_STD static MatExpr eye(Size size);
+
+    //! some more overridden methods
+    Mat_& adjustROI( int dtop, int dbottom, int dleft, int dright );
+    Mat_ operator()( const Range& rowRange, const Range& colRange ) const;
+    Mat_ operator()( const Rect& roi ) const;
+    Mat_ operator()( const Range* ranges ) const;
+    Mat_ operator()(const std::vector<Range>& ranges) const;
+
+    //! more convenient forms of row and element access operators
+    _Tp* operator [](int y);
+    const _Tp* operator [](int y) const;
+
+    //! returns reference to the specified element
+    _Tp& operator ()(const int* idx);
+    //! returns read-only reference to the specified element
+    const _Tp& operator ()(const int* idx) const;
+
+    //! returns reference to the specified element
+    template<int n> _Tp& operator ()(const Vec<int, n>& idx);
+    //! returns read-only reference to the specified element
+    template<int n> const _Tp& operator ()(const Vec<int, n>& idx) const;
+
+    //! returns reference to the specified element (1D case)
+    _Tp& operator ()(int idx0);
+    //! returns read-only reference to the specified element (1D case)
+    const _Tp& operator ()(int idx0) const;
+    //! returns reference to the specified element (2D case)
+    _Tp& operator ()(int row, int col);
+    //! returns read-only reference to the specified element (2D case)
+    const _Tp& operator ()(int row, int col) const;
+    //! returns reference to the specified element (3D case)
+    _Tp& operator ()(int idx0, int idx1, int idx2);
+    //! returns read-only reference to the specified element (3D case)
+    const _Tp& operator ()(int idx0, int idx1, int idx2) const;
+
+    _Tp& operator ()(Point pt);
+    const _Tp& operator ()(Point pt) const;
+
+    //! conversion to vector.
+    operator std::vector<_Tp>() const;
+
+    //! conversion to array.
+    template<std::size_t _Nm> operator std::array<_Tp, _Nm>() const;
+
+    //! conversion to Vec
+    template<int n> operator Vec<typename DataType<_Tp>::channel_type, n>() const;
+    //! conversion to Matx
+    template<int m, int n> operator Matx<typename DataType<_Tp>::channel_type, m, n>() const;
+
+    Mat_(Mat_&& m);
+    Mat_& operator = (Mat_&& m);
+
+    Mat_(Mat&& m);
+    Mat_& operator = (Mat&& m);
+
+    Mat_(MatExpr&& e);
+};
+
+typedef Mat_<uchar> Mat1b;
+typedef Mat_<Vec2b> Mat2b;
+typedef Mat_<Vec3b> Mat3b;
+typedef Mat_<Vec4b> Mat4b;
+
+typedef Mat_<short> Mat1s;
+typedef Mat_<Vec2s> Mat2s;
+typedef Mat_<Vec3s> Mat3s;
+typedef Mat_<Vec4s> Mat4s;
+
+typedef Mat_<ushort> Mat1w;
+typedef Mat_<Vec2w> Mat2w;
+typedef Mat_<Vec3w> Mat3w;
+typedef Mat_<Vec4w> Mat4w;
+
+typedef Mat_<int>   Mat1i;
+typedef Mat_<Vec2i> Mat2i;
+typedef Mat_<Vec3i> Mat3i;
+typedef Mat_<Vec4i> Mat4i;
+
+typedef Mat_<float> Mat1f;
+typedef Mat_<Vec2f> Mat2f;
+typedef Mat_<Vec3f> Mat3f;
+typedef Mat_<Vec4f> Mat4f;
+
+typedef Mat_<double> Mat1d;
+typedef Mat_<Vec2d> Mat2d;
+typedef Mat_<Vec3d> Mat3d;
+typedef Mat_<Vec4d> Mat4d;
+
+/** @todo document */
+class CV_EXPORTS UMat
+{
+public:
+    //! default constructor
+    UMat(UMatUsageFlags usageFlags = USAGE_DEFAULT) CV_NOEXCEPT;
+    //! constructs 2D matrix of the specified size and type
+    // (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.)
+    UMat(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+    UMat(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+    //! constructs 2D matrix and fills it with the specified value _s.
+    UMat(int rows, int cols, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+    UMat(Size size, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+
+    //! constructs n-dimensional matrix
+    UMat(int ndims, const int* sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+    UMat(int ndims, const int* sizes, int type, const Scalar& s, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+
+    //! copy constructor
+    UMat(const UMat& m);
+
+    //! creates a matrix header for a part of the bigger matrix
+    UMat(const UMat& m, const Range& rowRange, const Range& colRange=Range::all());
+    UMat(const UMat& m, const Rect& roi);
+    UMat(const UMat& m, const Range* ranges);
+    UMat(const UMat& m, const std::vector<Range>& ranges);
+
+    // FIXIT copyData=false is not implemented, drop this in favor of cv::Mat (OpenCV 5.0)
+    //! builds matrix from std::vector with or without copying the data
+    template<typename _Tp> explicit UMat(const std::vector<_Tp>& vec, bool copyData=false);
+
+    //! destructor - calls release()
+    ~UMat();
+    //! assignment operators
+    UMat& operator = (const UMat& m);
+
+    Mat getMat(AccessFlag flags) const;
+
+    //! returns a new matrix header for the specified row
+    UMat row(int y) const;
+    //! returns a new matrix header for the specified column
+    UMat col(int x) const;
+    //! ... for the specified row span
+    UMat rowRange(int startrow, int endrow) const;
+    UMat rowRange(const Range& r) const;
+    //! ... for the specified column span
+    UMat colRange(int startcol, int endcol) const;
+    UMat colRange(const Range& r) const;
+    //! ... for the specified diagonal
+    //! (d=0 - the main diagonal,
+    //!  >0 - a diagonal from the upper half,
+    //!  <0 - a diagonal from the lower half)
+    UMat diag(int d=0) const;
+    //! constructs a square diagonal matrix which main diagonal is vector "d"
+    CV_NODISCARD_STD static UMat diag(const UMat& d, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat diag(const UMat& d) { return diag(d, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+
+    //! returns deep copy of the matrix, i.e. the data is copied
+    CV_NODISCARD_STD UMat clone() const;
+    //! copies the matrix content to "m".
+    // It calls m.create(this->size(), this->type()).
+    void copyTo( OutputArray m ) const;
+    //! copies those matrix elements to "m" that are marked with non-zero mask elements.
+    void copyTo( OutputArray m, InputArray mask ) const;
+    //! converts matrix to another datatype with optional scaling. See cvConvertScale.
+    void convertTo( OutputArray m, int rtype, double alpha=1, double beta=0 ) const;
+
+    void assignTo( UMat& m, int type=-1 ) const;
+
+    //! sets every matrix element to s
+    UMat& operator = (const Scalar& s);
+    //! sets some of the matrix elements to s, according to the mask
+    UMat& setTo(InputArray value, InputArray mask=noArray());
+    //! creates alternative matrix header for the same data, with different
+    // number of channels and/or different number of rows. see cvReshape.
+    UMat reshape(int cn, int rows=0) const;
+    UMat reshape(int cn, int newndims, const int* newsz) const;
+
+    //! matrix transposition by means of matrix expressions
+    UMat t() const;
+    //! matrix inversion by means of matrix expressions
+    UMat inv(int method=DECOMP_LU) const;
+    //! per-element matrix multiplication by means of matrix expressions
+    UMat mul(InputArray m, double scale=1) const;
+
+    //! computes dot-product
+    double dot(InputArray m) const;
+
+    //! Matlab-style matrix initialization
+    CV_NODISCARD_STD static UMat zeros(int rows, int cols, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat zeros(Size size, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat zeros(int ndims, const int* sz, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat zeros(int rows, int cols, int type) { return zeros(rows, cols, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+    CV_NODISCARD_STD static UMat zeros(Size size, int type) { return zeros(size, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+    CV_NODISCARD_STD static UMat zeros(int ndims, const int* sz, int type) { return zeros(ndims, sz, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+    CV_NODISCARD_STD static UMat ones(int rows, int cols, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat ones(Size size, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat ones(int ndims, const int* sz, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat ones(int rows, int cols, int type) { return ones(rows, cols, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+    CV_NODISCARD_STD static UMat ones(Size size, int type) { return ones(size, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+    CV_NODISCARD_STD static UMat ones(int ndims, const int* sz, int type) { return ones(ndims, sz, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+    CV_NODISCARD_STD static UMat eye(int rows, int cols, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat eye(Size size, int type, UMatUsageFlags usageFlags /*= USAGE_DEFAULT*/);
+    CV_NODISCARD_STD static UMat eye(int rows, int cols, int type) { return eye(rows, cols, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+    CV_NODISCARD_STD static UMat eye(Size size, int type) { return eye(size, type, USAGE_DEFAULT); }  // OpenCV 5.0: remove abi compatibility overload
+
+    //! allocates new matrix data unless the matrix already has specified size and type.
+    // previous data is unreferenced if needed.
+    void create(int rows, int cols, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+    void create(Size size, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+    void create(int ndims, const int* sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+    void create(const std::vector<int>& sizes, int type, UMatUsageFlags usageFlags = USAGE_DEFAULT);
+
+    //! increases the reference counter; use with care to avoid memleaks
+    void addref();
+    //! decreases reference counter;
+    // deallocates the data when reference counter reaches 0.
+    void release();
+
+    //! deallocates the matrix data
+    void deallocate();
+    //! internal use function; properly re-allocates _size, _step arrays
+    void copySize(const UMat& m);
+
+    //! locates matrix header within a parent matrix. See below
+    void locateROI( Size& wholeSize, Point& ofs ) const;
+    //! moves/resizes the current matrix ROI inside the parent matrix.
+    UMat& adjustROI( int dtop, int dbottom, int dleft, int dright );
+    //! extracts a rectangular sub-matrix
+    // (this is a generalized form of row, rowRange etc.)
+    UMat operator()( Range rowRange, Range colRange ) const;
+    UMat operator()( const Rect& roi ) const;
+    UMat operator()( const Range* ranges ) const;
+    UMat operator()(const std::vector<Range>& ranges) const;
+
+    //! returns true iff the matrix data is continuous
+    // (i.e. when there are no gaps between successive rows).
+    // similar to CV_IS_MAT_CONT(cvmat->type)
+    bool isContinuous() const;
+
+    //! returns true if the matrix is a submatrix of another matrix
+    bool isSubmatrix() const;
+
+    //! returns element size in bytes,
+    // similar to CV_ELEM_SIZE(cvmat->type)
+    size_t elemSize() const;
+    //! returns the size of element channel in bytes.
+    size_t elemSize1() const;
+    //! returns element type, similar to CV_MAT_TYPE(cvmat->type)
+    int type() const;
+    //! returns element type, similar to CV_MAT_DEPTH(cvmat->type)
+    int depth() const;
+    //! returns element type, similar to CV_MAT_CN(cvmat->type)
+    int channels() const;
+    //! returns step/elemSize1()
+    size_t step1(int i=0) const;
+    //! returns true if matrix data is NULL
+    bool empty() const;
+    //! returns the total number of matrix elements
+    size_t total() const;
+
+    //! returns N if the matrix is 1-channel (N x ptdim) or ptdim-channel (1 x N) or (N x 1); negative number otherwise
+    int checkVector(int elemChannels, int depth=-1, bool requireContinuous=true) const;
+
+    UMat(UMat&& m);
+    UMat& operator = (UMat&& m);
+
+    /*! Returns the OpenCL buffer handle on which UMat operates on.
+        The UMat instance should be kept alive during the use of the handle to prevent the buffer to be
+        returned to the OpenCV buffer pool.
+     */
+    void* handle(AccessFlag accessFlags) const;
+    void ndoffset(size_t* ofs) const;
+
+    enum { MAGIC_VAL  = 0x42FF0000, AUTO_STEP = 0, CONTINUOUS_FLAG = CV_MAT_CONT_FLAG, SUBMATRIX_FLAG = CV_SUBMAT_FLAG };
+    enum { MAGIC_MASK = 0xFFFF0000, TYPE_MASK = 0x00000FFF, DEPTH_MASK = 7 };
+
+    /*! includes several bit-fields:
+         - the magic signature
+         - continuity flag
+         - depth
+         - number of channels
+     */
+    int flags;
+
+    //! the matrix dimensionality, >= 2
+    int dims;
+
+    //! number of rows in the matrix; -1 when the matrix has more than 2 dimensions
+    int rows;
+
+    //! number of columns in the matrix; -1 when the matrix has more than 2 dimensions
+    int cols;
+
+    //! custom allocator
+    MatAllocator* allocator;
+
+    //! usage flags for allocator; recommend do not set directly, instead set during construct/create/getUMat
+    UMatUsageFlags usageFlags;
+
+    //! and the standard allocator
+    static MatAllocator* getStdAllocator();
+
+    //! internal use method: updates the continuity flag
+    void updateContinuityFlag();
+
+    //! black-box container of UMat data
+    UMatData* u;
+
+    //! offset of the submatrix (or 0)
+    size_t offset;
+
+    //! dimensional size of the matrix; accessible in various formats
+    MatSize size;
+
+    //! number of bytes each matrix element/row/plane/dimension occupies
+    MatStep step;
+
+protected:
+};
+
+
+/////////////////////////// multi-dimensional sparse matrix //////////////////////////
+
+/** @brief The class SparseMat represents multi-dimensional sparse numerical arrays.
+
+Such a sparse array can store elements of any type that Mat can store. *Sparse* means that only
+non-zero elements are stored (though, as a result of operations on a sparse matrix, some of its
+stored elements can actually become 0. It is up to you to detect such elements and delete them
+using SparseMat::erase ). The non-zero elements are stored in a hash table that grows when it is
+filled so that the search time is O(1) in average (regardless of whether element is there or not).
+Elements can be accessed using the following methods:
+-   Query operations (SparseMat::ptr and the higher-level SparseMat::ref, SparseMat::value and
+    SparseMat::find), for example:
+    @code
+        const int dims = 5;
+        int size[5] = {10, 10, 10, 10, 10};
+        SparseMat sparse_mat(dims, size, CV_32F);
+        for(int i = 0; i < 1000; i++)
+        {
+            int idx[dims];
+            for(int k = 0; k < dims; k++)
+                idx[k] = rand() % size[k];
+            sparse_mat.ref<float>(idx) += 1.f;
+        }
+        cout << "nnz = " << sparse_mat.nzcount() << endl;
+    @endcode
+-   Sparse matrix iterators. They are similar to MatIterator but different from NAryMatIterator.
+    That is, the iteration loop is familiar to STL users:
+    @code
+        // prints elements of a sparse floating-point matrix
+        // and the sum of elements.
+        SparseMatConstIterator_<float>
+            it = sparse_mat.begin<float>(),
+            it_end = sparse_mat.end<float>();
+        double s = 0;
+        int dims = sparse_mat.dims();
+        for(; it != it_end; ++it)
+        {
+            // print element indices and the element value
+            const SparseMat::Node* n = it.node();
+            printf("(");
+            for(int i = 0; i < dims; i++)
+                printf("%d%s", n->idx[i], i < dims-1 ? ", " : ")");
+            printf(": %g\n", it.value<float>());
+            s += *it;
+        }
+        printf("Element sum is %g\n", s);
+    @endcode
+    If you run this loop, you will notice that elements are not enumerated in a logical order
+    (lexicographical, and so on). They come in the same order as they are stored in the hash table
+    (semi-randomly). You may collect pointers to the nodes and sort them to get the proper ordering.
+    Note, however, that pointers to the nodes may become invalid when you add more elements to the
+    matrix. This may happen due to possible buffer reallocation.
+-   Combination of the above 2 methods when you need to process 2 or more sparse matrices
+    simultaneously. For example, this is how you can compute unnormalized cross-correlation of the 2
+    floating-point sparse matrices:
+    @code
+        double cross_corr(const SparseMat& a, const SparseMat& b)
+        {
+            const SparseMat *_a = &a, *_b = &b;
+            // if b contains less elements than a,
+            // it is faster to iterate through b
+            if(_a->nzcount() > _b->nzcount())
+                std::swap(_a, _b);
+            SparseMatConstIterator_<float> it = _a->begin<float>(),
+                                           it_end = _a->end<float>();
+            double ccorr = 0;
+            for(; it != it_end; ++it)
+            {
+                // take the next element from the first matrix
+                float avalue = *it;
+                const Node* anode = it.node();
+                // and try to find an element with the same index in the second matrix.
+                // since the hash value depends only on the element index,
+                // reuse the hash value stored in the node
+                float bvalue = _b->value<float>(anode->idx,&anode->hashval);
+                ccorr += avalue*bvalue;
+            }
+            return ccorr;
+        }
+    @endcode
+ */
+class CV_EXPORTS SparseMat
+{
+public:
+    typedef SparseMatIterator iterator;
+    typedef SparseMatConstIterator const_iterator;
+
+    enum { MAGIC_VAL=0x42FD0000, MAX_DIM=32, HASH_SCALE=0x5bd1e995, HASH_BIT=0x80000000 };
+
+    //! the sparse matrix header
+    struct CV_EXPORTS Hdr
+    {
+        Hdr(int _dims, const int* _sizes, int _type);
+        void clear();
+        int refcount;
+        int dims;
+        int valueOffset;
+        size_t nodeSize;
+        size_t nodeCount;
+        size_t freeList;
+        std::vector<uchar> pool;
+        std::vector<size_t> hashtab;
+        int size[MAX_DIM];
+    };
+
+    //! sparse matrix node - element of a hash table
+    struct CV_EXPORTS Node
+    {
+        //! hash value
+        size_t hashval;
+        //! index of the next node in the same hash table entry
+        size_t next;
+        //! index of the matrix element
+        int idx[MAX_DIM];
+    };
+
+    /** @brief Various SparseMat constructors.
+     */
+    SparseMat();
+
+    /** @overload
+    @param dims Array dimensionality.
+    @param _sizes Sparce matrix size on all dementions.
+    @param _type Sparse matrix data type.
+    */
+    SparseMat(int dims, const int* _sizes, int _type);
+
+    /** @overload
+    @param m Source matrix for copy constructor. If m is dense matrix (ocvMat) then it will be converted
+    to sparse representation.
+    */
+    SparseMat(const SparseMat& m);
+
+    /** @overload
+    @param m Source matrix for copy constructor. If m is dense matrix (ocvMat) then it will be converted
+    to sparse representation.
+    */
+    explicit SparseMat(const Mat& m);
+
+    //! the destructor
+    ~SparseMat();
+
+    //! assignment operator. This is O(1) operation, i.e. no data is copied
+    SparseMat& operator = (const SparseMat& m);
+    //! equivalent to the corresponding constructor
+    SparseMat& operator = (const Mat& m);
+
+    //! creates full copy of the matrix
+    CV_NODISCARD_STD SparseMat clone() const;
+
+    //! copies all the data to the destination matrix. All the previous content of m is erased
+    void copyTo( SparseMat& m ) const;
+    //! converts sparse matrix to dense matrix.
+    void copyTo( Mat& m ) const;
+    //! multiplies all the matrix elements by the specified scale factor alpha and converts the results to the specified data type
+    void convertTo( SparseMat& m, int rtype, double alpha=1 ) const;
+    //! converts sparse matrix to dense n-dim matrix with optional type conversion and scaling.
+    /*!
+        @param [out] m - output matrix; if it does not have a proper size or type before the operation,
+            it is reallocated
+        @param [in] rtype - desired output matrix type or, rather, the depth since the number of channels
+            are the same as the input has; if rtype is negative, the output matrix will have the
+            same type as the input.
+        @param [in] alpha - optional scale factor
+        @param [in] beta - optional delta added to the scaled values
+    */
+    void convertTo( Mat& m, int rtype, double alpha=1, double beta=0 ) const;
+
+    // not used now
+    void assignTo( SparseMat& m, int type=-1 ) const;
+
+    //! reallocates sparse matrix.
+    /*!
+        If the matrix already had the proper size and type,
+        it is simply cleared with clear(), otherwise,
+        the old matrix is released (using release()) and the new one is allocated.
+    */
+    void create(int dims, const int* _sizes, int _type);
+    //! sets all the sparse matrix elements to 0, which means clearing the hash table.
+    void clear();
+    //! manually increments the reference counter to the header.
+    void addref();
+    // decrements the header reference counter. When the counter reaches 0, the header and all the underlying data are deallocated.
+    void release();
+
+    //! converts sparse matrix to the old-style representation; all the elements are copied.
+    //operator CvSparseMat*() const;
+    //! returns the size of each element in bytes (not including the overhead - the space occupied by SparseMat::Node elements)
+    size_t elemSize() const;
+    //! returns elemSize()/channels()
+    size_t elemSize1() const;
+
+    //! returns type of sparse matrix elements
+    int type() const;
+    //! returns the depth of sparse matrix elements
+    int depth() const;
+    //! returns the number of channels
+    int channels() const;
+
+    //! returns the array of sizes, or NULL if the matrix is not allocated
+    const int* size() const;
+    //! returns the size of i-th matrix dimension (or 0)
+    int size(int i) const;
+    //! returns the matrix dimensionality
+    int dims() const;
+    //! returns the number of non-zero elements (=the number of hash table nodes)
+    size_t nzcount() const;
+
+    //! computes the element hash value (1D case)
+    size_t hash(int i0) const;
+    //! computes the element hash value (2D case)
+    size_t hash(int i0, int i1) const;
+    //! computes the element hash value (3D case)
+    size_t hash(int i0, int i1, int i2) const;
+    //! computes the element hash value (nD case)
+    size_t hash(const int* idx) const;
+
+    //!@{
+    /*!
+     specialized variants for 1D, 2D, 3D cases and the generic_type one for n-D case.
+     return pointer to the matrix element.
+      - if the element is there (it's non-zero), the pointer to it is returned
+      - if it's not there and createMissing=false, NULL pointer is returned
+      - if it's not there and createMissing=true, then the new element
+        is created and initialized with 0. Pointer to it is returned
+      - if the optional hashval pointer is not NULL, the element hash value is
+        not computed, but *hashval is taken instead.
+    */
+    //! returns pointer to the specified element (1D case)
+    uchar* ptr(int i0, bool createMissing, size_t* hashval=0);
+    //! returns pointer to the specified element (2D case)
+    uchar* ptr(int i0, int i1, bool createMissing, size_t* hashval=0);
+    //! returns pointer to the specified element (3D case)
+    uchar* ptr(int i0, int i1, int i2, bool createMissing, size_t* hashval=0);
+    //! returns pointer to the specified element (nD case)
+    uchar* ptr(const int* idx, bool createMissing, size_t* hashval=0);
+    //!@}
+
+    //!@{
+    /*!
+     return read-write reference to the specified sparse matrix element.
+
+     `ref<_Tp>(i0,...[,hashval])` is equivalent to `*(_Tp*)ptr(i0,...,true[,hashval])`.
+     The methods always return a valid reference.
+     If the element did not exist, it is created and initialized with 0.
+    */
+    //! returns reference to the specified element (1D case)
+    template<typename _Tp> _Tp& ref(int i0, size_t* hashval=0);
+    //! returns reference to the specified element (2D case)
+    template<typename _Tp> _Tp& ref(int i0, int i1, size_t* hashval=0);
+    //! returns reference to the specified element (3D case)
+    template<typename _Tp> _Tp& ref(int i0, int i1, int i2, size_t* hashval=0);
+    //! returns reference to the specified element (nD case)
+    template<typename _Tp> _Tp& ref(const int* idx, size_t* hashval=0);
+    //!@}
+
+    //!@{
+    /*!
+     return value of the specified sparse matrix element.
+
+     `value<_Tp>(i0,...[,hashval])` is equivalent to
+     @code
+     { const _Tp* p = find<_Tp>(i0,...[,hashval]); return p ? *p : _Tp(); }
+     @endcode
+
+     That is, if the element did not exist, the methods return 0.
+     */
+    //! returns value of the specified element (1D case)
+    template<typename _Tp> _Tp value(int i0, size_t* hashval=0) const;
+    //! returns value of the specified element (2D case)
+    template<typename _Tp> _Tp value(int i0, int i1, size_t* hashval=0) const;
+    //! returns value of the specified element (3D case)
+    template<typename _Tp> _Tp value(int i0, int i1, int i2, size_t* hashval=0) const;
+    //! returns value of the specified element (nD case)
+    template<typename _Tp> _Tp value(const int* idx, size_t* hashval=0) const;
+    //!@}
+
+    //!@{
+    /*!
+     Return pointer to the specified sparse matrix element if it exists
+
+     `find<_Tp>(i0,...[,hashval])` is equivalent to `(_const Tp*)ptr(i0,...false[,hashval])`.
+
+     If the specified element does not exist, the methods return NULL.
+    */
+    //! returns pointer to the specified element (1D case)
+    template<typename _Tp> const _Tp* find(int i0, size_t* hashval=0) const;
+    //! returns pointer to the specified element (2D case)
+    template<typename _Tp> const _Tp* find(int i0, int i1, size_t* hashval=0) const;
+    //! returns pointer to the specified element (3D case)
+    template<typename _Tp> const _Tp* find(int i0, int i1, int i2, size_t* hashval=0) const;
+    //! returns pointer to the specified element (nD case)
+    template<typename _Tp> const _Tp* find(const int* idx, size_t* hashval=0) const;
+    //!@}
+
+    //! erases the specified element (2D case)
+    void erase(int i0, int i1, size_t* hashval=0);
+    //! erases the specified element (3D case)
+    void erase(int i0, int i1, int i2, size_t* hashval=0);
+    //! erases the specified element (nD case)
+    void erase(const int* idx, size_t* hashval=0);
+
+    //!@{
+    /*!
+       return the sparse matrix iterator pointing to the first sparse matrix element
+    */
+    //! returns the sparse matrix iterator at the matrix beginning
+    SparseMatIterator begin();
+    //! returns the sparse matrix iterator at the matrix beginning
+    template<typename _Tp> SparseMatIterator_<_Tp> begin();
+    //! returns the read-only sparse matrix iterator at the matrix beginning
+    SparseMatConstIterator begin() const;
+    //! returns the read-only sparse matrix iterator at the matrix beginning
+    template<typename _Tp> SparseMatConstIterator_<_Tp> begin() const;
+    //!@}
+    /*!
+       return the sparse matrix iterator pointing to the element following the last sparse matrix element
+    */
+    //! returns the sparse matrix iterator at the matrix end
+    SparseMatIterator end();
+    //! returns the read-only sparse matrix iterator at the matrix end
+    SparseMatConstIterator end() const;
+    //! returns the typed sparse matrix iterator at the matrix end
+    template<typename _Tp> SparseMatIterator_<_Tp> end();
+    //! returns the typed read-only sparse matrix iterator at the matrix end
+    template<typename _Tp> SparseMatConstIterator_<_Tp> end() const;
+
+    //! returns the value stored in the sparse martix node
+    template<typename _Tp> _Tp& value(Node* n);
+    //! returns the value stored in the sparse martix node
+    template<typename _Tp> const _Tp& value(const Node* n) const;
+
+    ////////////// some internal-use methods ///////////////
+    Node* node(size_t nidx);
+    const Node* node(size_t nidx) const;
+
+    uchar* newNode(const int* idx, size_t hashval);
+    void removeNode(size_t hidx, size_t nidx, size_t previdx);
+    void resizeHashTab(size_t newsize);
+
+    int flags;
+    Hdr* hdr;
+};
+
+
+
+///////////////////////////////// SparseMat_<_Tp> ////////////////////////////////////
+
+/** @brief Template sparse n-dimensional array class derived from SparseMat
+
+SparseMat_ is a thin wrapper on top of SparseMat created in the same way as Mat_ . It simplifies
+notation of some operations:
+@code
+    int sz[] = {10, 20, 30};
+    SparseMat_<double> M(3, sz);
+    ...
+    M.ref(1, 2, 3) = M(4, 5, 6) + M(7, 8, 9);
+@endcode
+ */
+template<typename _Tp> class SparseMat_ : public SparseMat
+{
+public:
+    typedef SparseMatIterator_<_Tp> iterator;
+    typedef SparseMatConstIterator_<_Tp> const_iterator;
+
+    //! the default constructor
+    SparseMat_();
+    //! the full constructor equivalent to SparseMat(dims, _sizes, DataType<_Tp>::type)
+    SparseMat_(int dims, const int* _sizes);
+    //! the copy constructor. If DataType<_Tp>.type != m.type(), the m elements are converted
+    SparseMat_(const SparseMat& m);
+    //! the copy constructor. This is O(1) operation - no data is copied
+    SparseMat_(const SparseMat_& m);
+    //! converts dense matrix to the sparse form
+    SparseMat_(const Mat& m);
+    //! converts the old-style sparse matrix to the C++ class. All the elements are copied
+    //SparseMat_(const CvSparseMat* m);
+    //! the assignment operator. If DataType<_Tp>.type != m.type(), the m elements are converted
+    SparseMat_& operator = (const SparseMat& m);
+    //! the assignment operator. This is O(1) operation - no data is copied
+    SparseMat_& operator = (const SparseMat_& m);
+    //! converts dense matrix to the sparse form
+    SparseMat_& operator = (const Mat& m);
+
+    //! makes full copy of the matrix. All the elements are duplicated
+    CV_NODISCARD_STD SparseMat_ clone() const;
+    //! equivalent to cv::SparseMat::create(dims, _sizes, DataType<_Tp>::type)
+    void create(int dims, const int* _sizes);
+    //! converts sparse matrix to the old-style CvSparseMat. All the elements are copied
+    //operator CvSparseMat*() const;
+
+    //! returns type of the matrix elements
+    int type() const;
+    //! returns depth of the matrix elements
+    int depth() const;
+    //! returns the number of channels in each matrix element
+    int channels() const;
+
+    //! equivalent to SparseMat::ref<_Tp>(i0, hashval)
+    _Tp& ref(int i0, size_t* hashval=0);
+    //! equivalent to SparseMat::ref<_Tp>(i0, i1, hashval)
+    _Tp& ref(int i0, int i1, size_t* hashval=0);
+    //! equivalent to SparseMat::ref<_Tp>(i0, i1, i2, hashval)
+    _Tp& ref(int i0, int i1, int i2, size_t* hashval=0);
+    //! equivalent to SparseMat::ref<_Tp>(idx, hashval)
+    _Tp& ref(const int* idx, size_t* hashval=0);
+
+    //! equivalent to SparseMat::value<_Tp>(i0, hashval)
+    _Tp operator()(int i0, size_t* hashval=0) const;
+    //! equivalent to SparseMat::value<_Tp>(i0, i1, hashval)
+    _Tp operator()(int i0, int i1, size_t* hashval=0) const;
+    //! equivalent to SparseMat::value<_Tp>(i0, i1, i2, hashval)
+    _Tp operator()(int i0, int i1, int i2, size_t* hashval=0) const;
+    //! equivalent to SparseMat::value<_Tp>(idx, hashval)
+    _Tp operator()(const int* idx, size_t* hashval=0) const;
+
+    //! returns sparse matrix iterator pointing to the first sparse matrix element
+    SparseMatIterator_<_Tp> begin();
+    //! returns read-only sparse matrix iterator pointing to the first sparse matrix element
+    SparseMatConstIterator_<_Tp> begin() const;
+    //! returns sparse matrix iterator pointing to the element following the last sparse matrix element
+    SparseMatIterator_<_Tp> end();
+    //! returns read-only sparse matrix iterator pointing to the element following the last sparse matrix element
+    SparseMatConstIterator_<_Tp> end() const;
+};
+
+
+
+////////////////////////////////// MatConstIterator //////////////////////////////////
+
+class CV_EXPORTS MatConstIterator
+{
+public:
+    typedef uchar* value_type;
+    typedef ptrdiff_t difference_type;
+    typedef const uchar** pointer;
+    typedef uchar* reference;
+
+    typedef std::random_access_iterator_tag iterator_category;
+
+    //! default constructor
+    MatConstIterator();
+    //! constructor that sets the iterator to the beginning of the matrix
+    MatConstIterator(const Mat* _m);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatConstIterator(const Mat* _m, int _row, int _col=0);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatConstIterator(const Mat* _m, Point _pt);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatConstIterator(const Mat* _m, const int* _idx);
+    //! copy constructor
+    MatConstIterator(const MatConstIterator& it);
+
+    //! copy operator
+    MatConstIterator& operator = (const MatConstIterator& it);
+    //! returns the current matrix element
+    const uchar* operator *() const;
+    //! returns the i-th matrix element, relative to the current
+    const uchar* operator [](ptrdiff_t i) const;
+
+    //! shifts the iterator forward by the specified number of elements
+    MatConstIterator& operator += (ptrdiff_t ofs);
+    //! shifts the iterator backward by the specified number of elements
+    MatConstIterator& operator -= (ptrdiff_t ofs);
+    //! decrements the iterator
+    MatConstIterator& operator --();
+    //! decrements the iterator
+    MatConstIterator operator --(int);
+    //! increments the iterator
+    MatConstIterator& operator ++();
+    //! increments the iterator
+    MatConstIterator operator ++(int);
+    //! returns the current iterator position
+    Point pos() const;
+    //! returns the current iterator position
+    void pos(int* _idx) const;
+
+    ptrdiff_t lpos() const;
+    void seek(ptrdiff_t ofs, bool relative = false);
+    void seek(const int* _idx, bool relative = false);
+
+    const Mat* m;
+    size_t elemSize;
+    const uchar* ptr;
+    const uchar* sliceStart;
+    const uchar* sliceEnd;
+};
+
+
+
+////////////////////////////////// MatConstIterator_ /////////////////////////////////
+
+/** @brief Matrix read-only iterator
+ */
+template<typename _Tp>
+class MatConstIterator_ : public MatConstIterator
+{
+public:
+    typedef _Tp value_type;
+    typedef ptrdiff_t difference_type;
+    typedef const _Tp* pointer;
+    typedef const _Tp& reference;
+
+    typedef std::random_access_iterator_tag iterator_category;
+
+    //! default constructor
+    MatConstIterator_();
+    //! constructor that sets the iterator to the beginning of the matrix
+    MatConstIterator_(const Mat_<_Tp>* _m);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatConstIterator_(const Mat_<_Tp>* _m, int _row, int _col=0);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatConstIterator_(const Mat_<_Tp>* _m, Point _pt);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatConstIterator_(const Mat_<_Tp>* _m, const int* _idx);
+    //! copy constructor
+    MatConstIterator_(const MatConstIterator_& it);
+
+    //! copy operator
+    MatConstIterator_& operator = (const MatConstIterator_& it);
+    //! returns the current matrix element
+    const _Tp& operator *() const;
+    //! returns the i-th matrix element, relative to the current
+    const _Tp& operator [](ptrdiff_t i) const;
+
+    //! shifts the iterator forward by the specified number of elements
+    MatConstIterator_& operator += (ptrdiff_t ofs);
+    //! shifts the iterator backward by the specified number of elements
+    MatConstIterator_& operator -= (ptrdiff_t ofs);
+    //! decrements the iterator
+    MatConstIterator_& operator --();
+    //! decrements the iterator
+    MatConstIterator_ operator --(int);
+    //! increments the iterator
+    MatConstIterator_& operator ++();
+    //! increments the iterator
+    MatConstIterator_ operator ++(int);
+    //! returns the current iterator position
+    Point pos() const;
+};
+
+
+
+//////////////////////////////////// MatIterator_ ////////////////////////////////////
+
+/** @brief Matrix read-write iterator
+*/
+template<typename _Tp>
+class MatIterator_ : public MatConstIterator_<_Tp>
+{
+public:
+    typedef _Tp* pointer;
+    typedef _Tp& reference;
+
+    typedef std::random_access_iterator_tag iterator_category;
+
+    //! the default constructor
+    MatIterator_();
+    //! constructor that sets the iterator to the beginning of the matrix
+    MatIterator_(Mat_<_Tp>* _m);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatIterator_(Mat_<_Tp>* _m, int _row, int _col=0);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatIterator_(Mat_<_Tp>* _m, Point _pt);
+    //! constructor that sets the iterator to the specified element of the matrix
+    MatIterator_(Mat_<_Tp>* _m, const int* _idx);
+    //! copy constructor
+    MatIterator_(const MatIterator_& it);
+    //! copy operator
+    MatIterator_& operator = (const MatIterator_<_Tp>& it );
+
+    //! returns the current matrix element
+    _Tp& operator *() const;
+    //! returns the i-th matrix element, relative to the current
+    _Tp& operator [](ptrdiff_t i) const;
+
+    //! shifts the iterator forward by the specified number of elements
+    MatIterator_& operator += (ptrdiff_t ofs);
+    //! shifts the iterator backward by the specified number of elements
+    MatIterator_& operator -= (ptrdiff_t ofs);
+    //! decrements the iterator
+    MatIterator_& operator --();
+    //! decrements the iterator
+    MatIterator_ operator --(int);
+    //! increments the iterator
+    MatIterator_& operator ++();
+    //! increments the iterator
+    MatIterator_ operator ++(int);
+};
+
+
+
+/////////////////////////////// SparseMatConstIterator ///////////////////////////////
+
+/**  @brief Read-Only Sparse Matrix Iterator.
+
+ Here is how to use the iterator to compute the sum of floating-point sparse matrix elements:
+
+ \code
+ SparseMatConstIterator it = m.begin(), it_end = m.end();
+ double s = 0;
+ CV_Assert( m.type() == CV_32F );
+ for( ; it != it_end; ++it )
+    s += it.value<float>();
+ \endcode
+*/
+class CV_EXPORTS SparseMatConstIterator
+{
+public:
+    //! the default constructor
+    SparseMatConstIterator();
+    //! the full constructor setting the iterator to the first sparse matrix element
+    SparseMatConstIterator(const SparseMat* _m);
+    //! the copy constructor
+    SparseMatConstIterator(const SparseMatConstIterator& it);
+
+    //! the assignment operator
+    SparseMatConstIterator& operator = (const SparseMatConstIterator& it);
+
+    //! template method returning the current matrix element
+    template<typename _Tp> const _Tp& value() const;
+    //! returns the current node of the sparse matrix. it.node->idx is the current element index
+    const SparseMat::Node* node() const;
+
+    //! moves iterator to the previous element
+    SparseMatConstIterator& operator --();
+    //! moves iterator to the previous element
+    SparseMatConstIterator operator --(int);
+    //! moves iterator to the next element
+    SparseMatConstIterator& operator ++();
+    //! moves iterator to the next element
+    SparseMatConstIterator operator ++(int);
+
+    //! moves iterator to the element after the last element
+    void seekEnd();
+
+    const SparseMat* m;
+    size_t hashidx;
+    uchar* ptr;
+};
+
+
+
+////////////////////////////////// SparseMatIterator /////////////////////////////////
+
+/** @brief  Read-write Sparse Matrix Iterator
+
+ The class is similar to cv::SparseMatConstIterator,
+ but can be used for in-place modification of the matrix elements.
+*/
+class CV_EXPORTS SparseMatIterator : public SparseMatConstIterator
+{
+public:
+    //! the default constructor
+    SparseMatIterator();
+    //! the full constructor setting the iterator to the first sparse matrix element
+    SparseMatIterator(SparseMat* _m);
+    //! the full constructor setting the iterator to the specified sparse matrix element
+    SparseMatIterator(SparseMat* _m, const int* idx);
+    //! the copy constructor
+    SparseMatIterator(const SparseMatIterator& it);
+
+    //! the assignment operator
+    SparseMatIterator& operator = (const SparseMatIterator& it);
+    //! returns read-write reference to the current sparse matrix element
+    template<typename _Tp> _Tp& value() const;
+    //! returns pointer to the current sparse matrix node. it.node->idx is the index of the current element (do not modify it!)
+    SparseMat::Node* node() const;
+
+    //! moves iterator to the next element
+    SparseMatIterator& operator ++();
+    //! moves iterator to the next element
+    SparseMatIterator operator ++(int);
+};
+
+
+
+/////////////////////////////// SparseMatConstIterator_ //////////////////////////////
+
+/** @brief  Template Read-Only Sparse Matrix Iterator Class.
+
+ This is the derived from SparseMatConstIterator class that
+ introduces more convenient operator *() for accessing the current element.
+*/
+template<typename _Tp> class SparseMatConstIterator_ : public SparseMatConstIterator
+{
+public:
+
+    typedef std::forward_iterator_tag iterator_category;
+
+    //! the default constructor
+    SparseMatConstIterator_();
+    //! the full constructor setting the iterator to the first sparse matrix element
+    SparseMatConstIterator_(const SparseMat_<_Tp>* _m);
+    SparseMatConstIterator_(const SparseMat* _m);
+    //! the copy constructor
+    SparseMatConstIterator_(const SparseMatConstIterator_& it);
+
+    //! the assignment operator
+    SparseMatConstIterator_& operator = (const SparseMatConstIterator_& it);
+    //! the element access operator
+    const _Tp& operator *() const;
+
+    //! moves iterator to the next element
+    SparseMatConstIterator_& operator ++();
+    //! moves iterator to the next element
+    SparseMatConstIterator_ operator ++(int);
+};
+
+
+
+///////////////////////////////// SparseMatIterator_ /////////////////////////////////
+
+/** @brief  Template Read-Write Sparse Matrix Iterator Class.
+
+ This is the derived from cv::SparseMatConstIterator_ class that
+ introduces more convenient operator *() for accessing the current element.
+*/
+template<typename _Tp> class SparseMatIterator_ : public SparseMatConstIterator_<_Tp>
+{
+public:
+
+    typedef std::forward_iterator_tag iterator_category;
+
+    //! the default constructor
+    SparseMatIterator_();
+    //! the full constructor setting the iterator to the first sparse matrix element
+    SparseMatIterator_(SparseMat_<_Tp>* _m);
+    SparseMatIterator_(SparseMat* _m);
+    //! the copy constructor
+    SparseMatIterator_(const SparseMatIterator_& it);
+
+    //! the assignment operator
+    SparseMatIterator_& operator = (const SparseMatIterator_& it);
+    //! returns the reference to the current element
+    _Tp& operator *() const;
+
+    //! moves the iterator to the next element
+    SparseMatIterator_& operator ++();
+    //! moves the iterator to the next element
+    SparseMatIterator_ operator ++(int);
+};
+
+
+
+/////////////////////////////////// NAryMatIterator //////////////////////////////////
+
+/** @brief n-ary multi-dimensional array iterator.
+
+Use the class to implement unary, binary, and, generally, n-ary element-wise operations on
+multi-dimensional arrays. Some of the arguments of an n-ary function may be continuous arrays, some
+may be not. It is possible to use conventional MatIterator 's for each array but incrementing all of
+the iterators after each small operations may be a big overhead. In this case consider using
+NAryMatIterator to iterate through several matrices simultaneously as long as they have the same
+geometry (dimensionality and all the dimension sizes are the same). On each iteration `it.planes[0]`,
+`it.planes[1]`,... will be the slices of the corresponding matrices.
+
+The example below illustrates how you can compute a normalized and threshold 3D color histogram:
+@code
+    void computeNormalizedColorHist(const Mat& image, Mat& hist, int N, double minProb)
+    {
+        const int histSize[] = {N, N, N};
+
+        // make sure that the histogram has a proper size and type
+        hist.create(3, histSize, CV_32F);
+
+        // and clear it
+        hist = Scalar(0);
+
+        // the loop below assumes that the image
+        // is a 8-bit 3-channel. check it.
+        CV_Assert(image.type() == CV_8UC3);
+        MatConstIterator_<Vec3b> it = image.begin<Vec3b>(),
+                                 it_end = image.end<Vec3b>();
+        for( ; it != it_end; ++it )
+        {
+            const Vec3b& pix = *it;
+            hist.at<float>(pix[0]*N/256, pix[1]*N/256, pix[2]*N/256) += 1.f;
+        }
+
+        minProb *= image.rows*image.cols;
+
+        // initialize iterator (the style is different from STL).
+        // after initialization the iterator will contain
+        // the number of slices or planes the iterator will go through.
+        // it simultaneously increments iterators for several matrices
+        // supplied as a null terminated list of pointers
+        const Mat* arrays[] = {&hist, 0};
+        Mat planes[1];
+        NAryMatIterator itNAry(arrays, planes, 1);
+        double s = 0;
+        // iterate through the matrix. on each iteration
+        // itNAry.planes[i] (of type Mat) will be set to the current plane
+        // of the i-th n-dim matrix passed to the iterator constructor.
+        for(int p = 0; p < itNAry.nplanes; p++, ++itNAry)
+        {
+            threshold(itNAry.planes[0], itNAry.planes[0], minProb, 0, THRESH_TOZERO);
+            s += sum(itNAry.planes[0])[0];
+        }
+
+        s = 1./s;
+        itNAry = NAryMatIterator(arrays, planes, 1);
+        for(int p = 0; p < itNAry.nplanes; p++, ++itNAry)
+            itNAry.planes[0] *= s;
+    }
+@endcode
+ */
+class CV_EXPORTS NAryMatIterator
+{
+public:
+    //! the default constructor
+    NAryMatIterator();
+    //! the full constructor taking arbitrary number of n-dim matrices
+    NAryMatIterator(const Mat** arrays, uchar** ptrs, int narrays=-1);
+    //! the full constructor taking arbitrary number of n-dim matrices
+    NAryMatIterator(const Mat** arrays, Mat* planes, int narrays=-1);
+    //! the separate iterator initialization method
+    void init(const Mat** arrays, Mat* planes, uchar** ptrs, int narrays=-1);
+
+    //! proceeds to the next plane of every iterated matrix
+    NAryMatIterator& operator ++();
+    //! proceeds to the next plane of every iterated matrix (postfix increment operator)
+    NAryMatIterator operator ++(int);
+
+    //! the iterated arrays
+    const Mat** arrays;
+    //! the current planes
+    Mat* planes;
+    //! data pointers
+    uchar** ptrs;
+    //! the number of arrays
+    int narrays;
+    //! the number of hyper-planes that the iterator steps through
+    size_t nplanes;
+    //! the size of each segment (in elements)
+    size_t size;
+protected:
+    int iterdepth;
+    size_t idx;
+};
+
+
+
+///////////////////////////////// Matrix Expressions /////////////////////////////////
+
+class CV_EXPORTS MatOp
+{
+public:
+    MatOp();
+    virtual ~MatOp();
+
+    virtual bool elementWise(const MatExpr& expr) const;
+    virtual void assign(const MatExpr& expr, Mat& m, int type=-1) const = 0;
+    virtual void roi(const MatExpr& expr, const Range& rowRange,
+                     const Range& colRange, MatExpr& res) const;
+    virtual void diag(const MatExpr& expr, int d, MatExpr& res) const;
+    virtual void augAssignAdd(const MatExpr& expr, Mat& m) const;
+    virtual void augAssignSubtract(const MatExpr& expr, Mat& m) const;
+    virtual void augAssignMultiply(const MatExpr& expr, Mat& m) const;
+    virtual void augAssignDivide(const MatExpr& expr, Mat& m) const;
+    virtual void augAssignAnd(const MatExpr& expr, Mat& m) const;
+    virtual void augAssignOr(const MatExpr& expr, Mat& m) const;
+    virtual void augAssignXor(const MatExpr& expr, Mat& m) const;
+
+    virtual void add(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
+    virtual void add(const MatExpr& expr1, const Scalar& s, MatExpr& res) const;
+
+    virtual void subtract(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
+    virtual void subtract(const Scalar& s, const MatExpr& expr, MatExpr& res) const;
+
+    virtual void multiply(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res, double scale=1) const;
+    virtual void multiply(const MatExpr& expr1, double s, MatExpr& res) const;
+
+    virtual void divide(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res, double scale=1) const;
+    virtual void divide(double s, const MatExpr& expr, MatExpr& res) const;
+
+    virtual void abs(const MatExpr& expr, MatExpr& res) const;
+
+    virtual void transpose(const MatExpr& expr, MatExpr& res) const;
+    virtual void matmul(const MatExpr& expr1, const MatExpr& expr2, MatExpr& res) const;
+    virtual void invert(const MatExpr& expr, int method, MatExpr& res) const;
+
+    virtual Size size(const MatExpr& expr) const;
+    virtual int type(const MatExpr& expr) const;
+};
+
+/** @brief Matrix expression representation
+@anchor MatrixExpressions
+This is a list of implemented matrix operations that can be combined in arbitrary complex
+expressions (here A, B stand for matrices ( Mat ), s for a scalar ( Scalar ), alpha for a
+real-valued scalar ( double )):
+-   Addition, subtraction, negation: `A+B`, `A-B`, `A+s`, `A-s`, `s+A`, `s-A`, `-A`
+-   Scaling: `A*alpha`
+-   Per-element multiplication and division: `A.mul(B)`, `A/B`, `alpha/A`
+-   Matrix multiplication: `A*B`
+-   Transposition: `A.t()` (means A<sup>T</sup>)
+-   Matrix inversion and pseudo-inversion, solving linear systems and least-squares problems:
+    `A.inv([method]) (~ A<sup>-1</sup>)`,   `A.inv([method])*B (~ X: AX=B)`
+-   Comparison: `A cmpop B`, `A cmpop alpha`, `alpha cmpop A`, where *cmpop* is one of
+  `>`, `>=`, `==`, `!=`, `<=`, `<`. The result of comparison is an 8-bit single channel mask whose
+    elements are set to 255 (if the particular element or pair of elements satisfy the condition) or
+    0.
+-   Bitwise logical operations: `A logicop B`, `A logicop s`, `s logicop A`, `~A`, where *logicop* is one of
+  `&`, `|`, `^`.
+-   Element-wise minimum and maximum: `min(A, B)`, `min(A, alpha)`, `max(A, B)`, `max(A, alpha)`
+-   Element-wise absolute value: `abs(A)`
+-   Cross-product, dot-product: `A.cross(B)`, `A.dot(B)`
+-   Any function of matrix or matrices and scalars that returns a matrix or a scalar, such as norm,
+    mean, sum, countNonZero, trace, determinant, repeat, and others.
+-   Matrix initializers ( Mat::eye(), Mat::zeros(), Mat::ones() ), matrix comma-separated
+    initializers, matrix constructors and operators that extract sub-matrices (see Mat description).
+-   Mat_<destination_type>() constructors to cast the result to the proper type.
+@note Comma-separated initializers and probably some other operations may require additional
+explicit Mat() or Mat_<T>() constructor calls to resolve a possible ambiguity.
+
+Here are examples of matrix expressions:
+@code
+    // compute pseudo-inverse of A, equivalent to A.inv(DECOMP_SVD)
+    SVD svd(A);
+    Mat pinvA = svd.vt.t()*Mat::diag(1./svd.w)*svd.u.t();
+
+    // compute the new vector of parameters in the Levenberg-Marquardt algorithm
+    x -= (A.t()*A + lambda*Mat::eye(A.cols,A.cols,A.type())).inv(DECOMP_CHOLESKY)*(A.t()*err);
+
+    // sharpen image using "unsharp mask" algorithm
+    Mat blurred; double sigma = 1, threshold = 5, amount = 1;
+    GaussianBlur(img, blurred, Size(), sigma, sigma);
+    Mat lowContrastMask = abs(img - blurred) < threshold;
+    Mat sharpened = img*(1+amount) + blurred*(-amount);
+    img.copyTo(sharpened, lowContrastMask);
+@endcode
+*/
+class CV_EXPORTS MatExpr
+{
+public:
+    MatExpr();
+    explicit MatExpr(const Mat& m);
+
+    MatExpr(const MatOp* _op, int _flags, const Mat& _a = Mat(), const Mat& _b = Mat(),
+            const Mat& _c = Mat(), double _alpha = 1, double _beta = 1, const Scalar& _s = Scalar());
+
+    operator Mat() const;
+    template<typename _Tp> operator Mat_<_Tp>() const;
+
+    Size size() const;
+    int type() const;
+
+    MatExpr row(int y) const;
+    MatExpr col(int x) const;
+    MatExpr diag(int d = 0) const;
+    MatExpr operator()( const Range& rowRange, const Range& colRange ) const;
+    MatExpr operator()( const Rect& roi ) const;
+
+    MatExpr t() const;
+    MatExpr inv(int method = DECOMP_LU) const;
+    MatExpr mul(const MatExpr& e, double scale=1) const;
+    MatExpr mul(const Mat& m, double scale=1) const;
+
+    Mat cross(const Mat& m) const;
+    double dot(const Mat& m) const;
+
+    void swap(MatExpr& b);
+
+    const MatOp* op;
+    int flags;
+
+    Mat a, b, c;
+    double alpha, beta;
+    Scalar s;
+};
+
+//! @} core_basic
+
+//! @relates cv::MatExpr
+//! @{
+CV_EXPORTS MatExpr operator + (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator + (const Mat& a, const Scalar& s);
+CV_EXPORTS MatExpr operator + (const Scalar& s, const Mat& a);
+CV_EXPORTS MatExpr operator + (const MatExpr& e, const Mat& m);
+CV_EXPORTS MatExpr operator + (const Mat& m, const MatExpr& e);
+CV_EXPORTS MatExpr operator + (const MatExpr& e, const Scalar& s);
+CV_EXPORTS MatExpr operator + (const Scalar& s, const MatExpr& e);
+CV_EXPORTS MatExpr operator + (const MatExpr& e1, const MatExpr& e2);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator + (const Mat& a, const Matx<_Tp, m, n>& b) { return a + Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator + (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) + b; }
+
+CV_EXPORTS MatExpr operator - (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator - (const Mat& a, const Scalar& s);
+CV_EXPORTS MatExpr operator - (const Scalar& s, const Mat& a);
+CV_EXPORTS MatExpr operator - (const MatExpr& e, const Mat& m);
+CV_EXPORTS MatExpr operator - (const Mat& m, const MatExpr& e);
+CV_EXPORTS MatExpr operator - (const MatExpr& e, const Scalar& s);
+CV_EXPORTS MatExpr operator - (const Scalar& s, const MatExpr& e);
+CV_EXPORTS MatExpr operator - (const MatExpr& e1, const MatExpr& e2);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator - (const Mat& a, const Matx<_Tp, m, n>& b) { return a - Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator - (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) - b; }
+
+CV_EXPORTS MatExpr operator - (const Mat& m);
+CV_EXPORTS MatExpr operator - (const MatExpr& e);
+
+CV_EXPORTS MatExpr operator * (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator * (const Mat& a, double s);
+CV_EXPORTS MatExpr operator * (double s, const Mat& a);
+CV_EXPORTS MatExpr operator * (const MatExpr& e, const Mat& m);
+CV_EXPORTS MatExpr operator * (const Mat& m, const MatExpr& e);
+CV_EXPORTS MatExpr operator * (const MatExpr& e, double s);
+CV_EXPORTS MatExpr operator * (double s, const MatExpr& e);
+CV_EXPORTS MatExpr operator * (const MatExpr& e1, const MatExpr& e2);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator * (const Mat& a, const Matx<_Tp, m, n>& b) { return a * Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator * (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) * b; }
+
+CV_EXPORTS MatExpr operator / (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator / (const Mat& a, double s);
+CV_EXPORTS MatExpr operator / (double s, const Mat& a);
+CV_EXPORTS MatExpr operator / (const MatExpr& e, const Mat& m);
+CV_EXPORTS MatExpr operator / (const Mat& m, const MatExpr& e);
+CV_EXPORTS MatExpr operator / (const MatExpr& e, double s);
+CV_EXPORTS MatExpr operator / (double s, const MatExpr& e);
+CV_EXPORTS MatExpr operator / (const MatExpr& e1, const MatExpr& e2);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator / (const Mat& a, const Matx<_Tp, m, n>& b) { return a / Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator / (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) / b; }
+
+CV_EXPORTS MatExpr operator < (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator < (const Mat& a, double s);
+CV_EXPORTS MatExpr operator < (double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator < (const Mat& a, const Matx<_Tp, m, n>& b) { return a < Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator < (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) < b; }
+
+CV_EXPORTS MatExpr operator <= (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator <= (const Mat& a, double s);
+CV_EXPORTS MatExpr operator <= (double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator <= (const Mat& a, const Matx<_Tp, m, n>& b) { return a <= Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator <= (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) <= b; }
+
+CV_EXPORTS MatExpr operator == (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator == (const Mat& a, double s);
+CV_EXPORTS MatExpr operator == (double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator == (const Mat& a, const Matx<_Tp, m, n>& b) { return a == Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator == (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) == b; }
+
+CV_EXPORTS MatExpr operator != (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator != (const Mat& a, double s);
+CV_EXPORTS MatExpr operator != (double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator != (const Mat& a, const Matx<_Tp, m, n>& b) { return a != Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator != (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) != b; }
+
+CV_EXPORTS MatExpr operator >= (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator >= (const Mat& a, double s);
+CV_EXPORTS MatExpr operator >= (double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator >= (const Mat& a, const Matx<_Tp, m, n>& b) { return a >= Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator >= (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) >= b; }
+
+CV_EXPORTS MatExpr operator > (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator > (const Mat& a, double s);
+CV_EXPORTS MatExpr operator > (double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator > (const Mat& a, const Matx<_Tp, m, n>& b) { return a > Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator > (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) > b; }
+
+CV_EXPORTS MatExpr operator & (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator & (const Mat& a, const Scalar& s);
+CV_EXPORTS MatExpr operator & (const Scalar& s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator & (const Mat& a, const Matx<_Tp, m, n>& b) { return a & Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator & (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) & b; }
+
+CV_EXPORTS MatExpr operator | (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator | (const Mat& a, const Scalar& s);
+CV_EXPORTS MatExpr operator | (const Scalar& s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator | (const Mat& a, const Matx<_Tp, m, n>& b) { return a | Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator | (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) | b; }
+
+CV_EXPORTS MatExpr operator ^ (const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr operator ^ (const Mat& a, const Scalar& s);
+CV_EXPORTS MatExpr operator ^ (const Scalar& s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr operator ^ (const Mat& a, const Matx<_Tp, m, n>& b) { return a ^ Mat(b); }
+template<typename _Tp, int m, int n> static inline
+MatExpr operator ^ (const Matx<_Tp, m, n>& a, const Mat& b) { return Mat(a) ^ b; }
+
+CV_EXPORTS MatExpr operator ~(const Mat& m);
+
+CV_EXPORTS MatExpr min(const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr min(const Mat& a, double s);
+CV_EXPORTS MatExpr min(double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr min (const Mat& a, const Matx<_Tp, m, n>& b) { return min(a, Mat(b)); }
+template<typename _Tp, int m, int n> static inline
+MatExpr min (const Matx<_Tp, m, n>& a, const Mat& b) { return min(Mat(a), b); }
+
+CV_EXPORTS MatExpr max(const Mat& a, const Mat& b);
+CV_EXPORTS MatExpr max(const Mat& a, double s);
+CV_EXPORTS MatExpr max(double s, const Mat& a);
+template<typename _Tp, int m, int n> static inline
+MatExpr max (const Mat& a, const Matx<_Tp, m, n>& b) { return max(a, Mat(b)); }
+template<typename _Tp, int m, int n> static inline
+MatExpr max (const Matx<_Tp, m, n>& a, const Mat& b) { return max(Mat(a), b); }
+
+/** @brief Calculates an absolute value of each matrix element.
+
+abs is a meta-function that is expanded to one of absdiff or convertScaleAbs forms:
+- C = abs(A-B) is equivalent to `absdiff(A, B, C)`
+- C = abs(A) is equivalent to `absdiff(A, Scalar::all(0), C)`
+- C = `Mat_<Vec<uchar,n> >(abs(A*alpha + beta))` is equivalent to `convertScaleAbs(A, C, alpha,
+beta)`
+
+The output matrix has the same size and the same type as the input one except for the last case,
+where C is depth=CV_8U .
+@param m matrix.
+@sa @ref MatrixExpressions, absdiff, convertScaleAbs
+ */
+CV_EXPORTS MatExpr abs(const Mat& m);
+/** @overload
+@param e matrix expression.
+*/
+CV_EXPORTS MatExpr abs(const MatExpr& e);
+//! @} relates cv::MatExpr
+
+} // cv
+
+#include "opencv2/core/mat.inl.hpp"
+
+#endif // OPENCV_CORE_MAT_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/mat.inl.hpp

@@ -0,0 +1,3422 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_MATRIX_OPERATIONS_HPP
+#define OPENCV_CORE_MATRIX_OPERATIONS_HPP
+
+#ifndef __cplusplus
+#  error mat.inl.hpp header must be compiled as C++
+#endif
+
+#ifdef _MSC_VER
+#pragma warning( push )
+#pragma warning( disable: 4127 5054 )
+#endif
+
+#if defined(CV_SKIP_DISABLE_CLANG_ENUM_WARNINGS)
+  // nothing
+#elif defined(CV_FORCE_DISABLE_CLANG_ENUM_WARNINGS)
+  #define CV_DISABLE_CLANG_ENUM_WARNINGS
+#elif defined(__clang__) && defined(__has_warning)
+  #if __has_warning("-Wdeprecated-enum-enum-conversion") && __has_warning("-Wdeprecated-anon-enum-enum-conversion")
+    #define CV_DISABLE_CLANG_ENUM_WARNINGS
+  #endif
+#endif
+#ifdef CV_DISABLE_CLANG_ENUM_WARNINGS
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wdeprecated-enum-enum-conversion"
+#pragma clang diagnostic ignored "-Wdeprecated-anon-enum-enum-conversion"
+#endif
+
+namespace cv
+{
+CV__DEBUG_NS_BEGIN
+
+
+//! @cond IGNORED
+
+////////////////////////// Custom (raw) type wrapper //////////////////////////
+
+template<typename _Tp> static inline
+int rawType()
+{
+    CV_StaticAssert(sizeof(_Tp) <= CV_CN_MAX, "sizeof(_Tp) is too large");
+    const int elemSize = sizeof(_Tp);
+    return (int)CV_MAKETYPE(CV_8U, elemSize);
+}
+
+//////////////////////// Input/Output Arrays ////////////////////////
+
+inline void _InputArray::init(int _flags, const void* _obj)
+{ flags = _flags; obj = (void*)_obj; }
+
+inline void _InputArray::init(int _flags, const void* _obj, Size _sz)
+{ flags = _flags; obj = (void*)_obj; sz = _sz; }
+
+inline void* _InputArray::getObj() const { return obj; }
+inline int _InputArray::getFlags() const { return flags; }
+inline Size _InputArray::getSz() const { return sz; }
+
+inline _InputArray::_InputArray() { init(0 + NONE, 0); }
+inline _InputArray::_InputArray(int _flags, void* _obj) { init(_flags, _obj); }
+inline _InputArray::_InputArray(const Mat& m) { init(+MAT+ACCESS_READ, &m); }
+inline _InputArray::_InputArray(const std::vector<Mat>& vec) { init(+STD_VECTOR_MAT+ACCESS_READ, &vec); }
+inline _InputArray::_InputArray(const UMat& m) { init(+UMAT+ACCESS_READ, &m); }
+inline _InputArray::_InputArray(const std::vector<UMat>& vec) { init(+STD_VECTOR_UMAT+ACCESS_READ, &vec); }
+
+template<typename _Tp> inline
+_InputArray::_InputArray(const std::vector<_Tp>& vec)
+{ init(FIXED_TYPE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_READ, &vec); }
+
+template<typename _Tp, std::size_t _Nm> inline
+_InputArray::_InputArray(const std::array<_Tp, _Nm>& arr)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_READ, arr.data(), Size(1, _Nm)); }
+
+template<std::size_t _Nm> inline
+_InputArray::_InputArray(const std::array<Mat, _Nm>& arr)
+{ init(+STD_ARRAY_MAT + ACCESS_READ, arr.data(), Size(1, _Nm)); }
+
+inline
+_InputArray::_InputArray(const std::vector<bool>& vec)
+{ init(FIXED_TYPE + STD_BOOL_VECTOR + traits::Type<bool>::value + ACCESS_READ, &vec); }
+
+template<typename _Tp> inline
+_InputArray::_InputArray(const std::vector<std::vector<_Tp> >& vec)
+{ init(FIXED_TYPE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_READ, &vec); }
+
+template<typename _Tp> inline
+_InputArray::_InputArray(const std::vector<Mat_<_Tp> >& vec)
+{ init(FIXED_TYPE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_READ, &vec); }
+
+template<typename _Tp, int m, int n> inline
+_InputArray::_InputArray(const Matx<_Tp, m, n>& mtx)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_READ, &mtx, Size(n, m)); }
+
+template<typename _Tp> inline
+_InputArray::_InputArray(const _Tp* vec, int n)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_READ, vec, Size(n, 1)); }
+
+template<typename _Tp> inline
+_InputArray::_InputArray(const Mat_<_Tp>& m)
+{ init(FIXED_TYPE + MAT + traits::Type<_Tp>::value + ACCESS_READ, &m); }
+
+inline _InputArray::_InputArray(const double& val)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + CV_64F + ACCESS_READ, &val, Size(1,1)); }
+
+inline _InputArray::_InputArray(const cuda::GpuMat& d_mat)
+{ init(+CUDA_GPU_MAT + ACCESS_READ, &d_mat); }
+
+inline _InputArray::_InputArray(const std::vector<cuda::GpuMat>& d_mat)
+{	init(+STD_VECTOR_CUDA_GPU_MAT + ACCESS_READ, &d_mat);}
+
+inline _InputArray::_InputArray(const ogl::Buffer& buf)
+{ init(+OPENGL_BUFFER + ACCESS_READ, &buf); }
+
+inline _InputArray::_InputArray(const cuda::HostMem& cuda_mem)
+{ init(+CUDA_HOST_MEM + ACCESS_READ, &cuda_mem); }
+
+template<typename _Tp> inline
+_InputArray _InputArray::rawIn(const std::vector<_Tp>& vec)
+{
+    _InputArray v;
+    v.flags = _InputArray::FIXED_TYPE + _InputArray::STD_VECTOR + rawType<_Tp>() + ACCESS_READ;
+    v.obj = (void*)&vec;
+    return v;
+}
+
+template<typename _Tp, std::size_t _Nm> inline
+_InputArray _InputArray::rawIn(const std::array<_Tp, _Nm>& arr)
+{
+    _InputArray v;
+    v.flags = FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_READ;
+    v.obj = (void*)arr.data();
+    v.sz = Size(1, _Nm);
+    return v;
+}
+
+inline _InputArray::~_InputArray() {}
+
+inline Mat _InputArray::getMat(int i) const
+{
+    if( kind() == MAT && i < 0 )
+        return *(const Mat*)obj;
+    return getMat_(i);
+}
+
+inline bool _InputArray::isMat() const { return kind() == _InputArray::MAT; }
+inline bool _InputArray::isUMat() const  { return kind() == _InputArray::UMAT; }
+inline bool _InputArray::isMatVector() const { return kind() == _InputArray::STD_VECTOR_MAT; }
+inline bool _InputArray::isUMatVector() const  { return kind() == _InputArray::STD_VECTOR_UMAT; }
+inline bool _InputArray::isMatx() const { return kind() == _InputArray::MATX; }
+inline bool _InputArray::isVector() const { return kind() == _InputArray::STD_VECTOR ||
+                                                   kind() == _InputArray::STD_BOOL_VECTOR ||
+                                                   (kind() == _InputArray::MATX && (sz.width <= 1 || sz.height <= 1)); }
+inline bool _InputArray::isGpuMat() const { return kind() == _InputArray::CUDA_GPU_MAT; }
+inline bool _InputArray::isGpuMatVector() const { return kind() == _InputArray::STD_VECTOR_CUDA_GPU_MAT; }
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+inline _OutputArray::_OutputArray() { init(+NONE + ACCESS_WRITE, 0); }
+inline _OutputArray::_OutputArray(int _flags, void* _obj) { init(_flags + ACCESS_WRITE, _obj); }
+inline _OutputArray::_OutputArray(Mat& m) { init(+MAT+ACCESS_WRITE, &m); }
+inline _OutputArray::_OutputArray(std::vector<Mat>& vec) { init(+STD_VECTOR_MAT + ACCESS_WRITE, &vec); }
+inline _OutputArray::_OutputArray(UMat& m) { init(+UMAT + ACCESS_WRITE, &m); }
+inline _OutputArray::_OutputArray(std::vector<UMat>& vec) { init(+STD_VECTOR_UMAT + ACCESS_WRITE, &vec); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(std::vector<_Tp>& vec)
+{ init(FIXED_TYPE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); }
+
+template<typename _Tp, std::size_t _Nm> inline
+_OutputArray::_OutputArray(std::array<_Tp, _Nm>& arr)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, arr.data(), Size(1, _Nm)); }
+
+template<std::size_t _Nm> inline
+_OutputArray::_OutputArray(std::array<Mat, _Nm>& arr)
+{ init(+STD_ARRAY_MAT + ACCESS_WRITE, arr.data(), Size(1, _Nm)); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(std::vector<std::vector<_Tp> >& vec)
+{ init(FIXED_TYPE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(std::vector<Mat_<_Tp> >& vec)
+{ init(FIXED_TYPE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(Mat_<_Tp>& m)
+{ init(FIXED_TYPE + MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &m); }
+
+template<typename _Tp, int m, int n> inline
+_OutputArray::_OutputArray(Matx<_Tp, m, n>& mtx)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, &mtx, Size(n, m)); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(_Tp* vec, int n)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, vec, Size(n, 1)); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(const std::vector<_Tp>& vec)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); }
+
+template<typename _Tp, std::size_t _Nm> inline
+_OutputArray::_OutputArray(const std::array<_Tp, _Nm>& arr)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, arr.data(), Size(1, _Nm)); }
+
+template<std::size_t _Nm> inline
+_OutputArray::_OutputArray(const std::array<Mat, _Nm>& arr)
+{ init(FIXED_SIZE + STD_ARRAY_MAT + ACCESS_WRITE, arr.data(), Size(1, _Nm)); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(const std::vector<std::vector<_Tp> >& vec)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(const std::vector<Mat_<_Tp> >& vec)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &vec); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(const Mat_<_Tp>& m)
+{ init(FIXED_TYPE + FIXED_SIZE + MAT + traits::Type<_Tp>::value + ACCESS_WRITE, &m); }
+
+template<typename _Tp, int m, int n> inline
+_OutputArray::_OutputArray(const Matx<_Tp, m, n>& mtx)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, &mtx, Size(n, m)); }
+
+template<typename _Tp> inline
+_OutputArray::_OutputArray(const _Tp* vec, int n)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE, vec, Size(n, 1)); }
+
+inline _OutputArray::_OutputArray(cuda::GpuMat& d_mat)
+{ init(+CUDA_GPU_MAT + ACCESS_WRITE, &d_mat); }
+
+inline _OutputArray::_OutputArray(std::vector<cuda::GpuMat>& d_mat)
+{	init(+STD_VECTOR_CUDA_GPU_MAT + ACCESS_WRITE, &d_mat);}
+
+inline _OutputArray::_OutputArray(ogl::Buffer& buf)
+{ init(+OPENGL_BUFFER + ACCESS_WRITE, &buf); }
+
+inline _OutputArray::_OutputArray(cuda::HostMem& cuda_mem)
+{ init(+CUDA_HOST_MEM + ACCESS_WRITE, &cuda_mem); }
+
+inline _OutputArray::_OutputArray(const Mat& m)
+{ init(FIXED_TYPE + FIXED_SIZE + MAT + ACCESS_WRITE, &m); }
+
+inline _OutputArray::_OutputArray(const std::vector<Mat>& vec)
+{ init(FIXED_SIZE + STD_VECTOR_MAT + ACCESS_WRITE, &vec); }
+
+inline _OutputArray::_OutputArray(const UMat& m)
+{ init(FIXED_TYPE + FIXED_SIZE + UMAT + ACCESS_WRITE, &m); }
+
+inline _OutputArray::_OutputArray(const std::vector<UMat>& vec)
+{ init(FIXED_SIZE + STD_VECTOR_UMAT + ACCESS_WRITE, &vec); }
+
+inline _OutputArray::_OutputArray(const cuda::GpuMat& d_mat)
+{ init(FIXED_TYPE + FIXED_SIZE + CUDA_GPU_MAT + ACCESS_WRITE, &d_mat); }
+
+
+inline _OutputArray::_OutputArray(const ogl::Buffer& buf)
+{ init(FIXED_TYPE + FIXED_SIZE + OPENGL_BUFFER + ACCESS_WRITE, &buf); }
+
+inline _OutputArray::_OutputArray(const cuda::HostMem& cuda_mem)
+{ init(FIXED_TYPE + FIXED_SIZE + CUDA_HOST_MEM + ACCESS_WRITE, &cuda_mem); }
+
+template<typename _Tp> inline
+_OutputArray _OutputArray::rawOut(std::vector<_Tp>& vec)
+{
+    _OutputArray v;
+    v.flags = _InputArray::FIXED_TYPE + _InputArray::STD_VECTOR + rawType<_Tp>() + ACCESS_WRITE;
+    v.obj = (void*)&vec;
+    return v;
+}
+
+template<typename _Tp, std::size_t _Nm> inline
+_OutputArray _OutputArray::rawOut(std::array<_Tp, _Nm>& arr)
+{
+    _OutputArray v;
+    v.flags = FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_WRITE;
+    v.obj = (void*)arr.data();
+    v.sz = Size(1, _Nm);
+    return v;
+}
+
+///////////////////////////////////////////////////////////////////////////////////////////
+
+inline _InputOutputArray::_InputOutputArray() { init(0+ACCESS_RW, 0); }
+inline _InputOutputArray::_InputOutputArray(int _flags, void* _obj) { init(_flags+ACCESS_RW, _obj); }
+inline _InputOutputArray::_InputOutputArray(Mat& m) { init(+MAT+ACCESS_RW, &m); }
+inline _InputOutputArray::_InputOutputArray(std::vector<Mat>& vec) { init(+STD_VECTOR_MAT+ACCESS_RW, &vec); }
+inline _InputOutputArray::_InputOutputArray(UMat& m) { init(+UMAT+ACCESS_RW, &m); }
+inline _InputOutputArray::_InputOutputArray(std::vector<UMat>& vec) { init(+STD_VECTOR_UMAT+ACCESS_RW, &vec); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(std::vector<_Tp>& vec)
+{ init(FIXED_TYPE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); }
+
+template<typename _Tp, std::size_t _Nm> inline
+_InputOutputArray::_InputOutputArray(std::array<_Tp, _Nm>& arr)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, arr.data(), Size(1, _Nm)); }
+
+template<std::size_t _Nm> inline
+_InputOutputArray::_InputOutputArray(std::array<Mat, _Nm>& arr)
+{ init(+STD_ARRAY_MAT + ACCESS_RW, arr.data(), Size(1, _Nm)); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(std::vector<std::vector<_Tp> >& vec)
+{ init(FIXED_TYPE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(std::vector<Mat_<_Tp> >& vec)
+{ init(FIXED_TYPE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_RW, &vec); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(Mat_<_Tp>& m)
+{ init(FIXED_TYPE + MAT + traits::Type<_Tp>::value + ACCESS_RW, &m); }
+
+template<typename _Tp, int m, int n> inline
+_InputOutputArray::_InputOutputArray(Matx<_Tp, m, n>& mtx)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, &mtx, Size(n, m)); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(_Tp* vec, int n)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, vec, Size(n, 1)); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(const std::vector<_Tp>& vec)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); }
+
+template<typename _Tp, std::size_t _Nm> inline
+_InputOutputArray::_InputOutputArray(const std::array<_Tp, _Nm>& arr)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, arr.data(), Size(1, _Nm)); }
+
+template<std::size_t _Nm> inline
+_InputOutputArray::_InputOutputArray(const std::array<Mat, _Nm>& arr)
+{ init(FIXED_SIZE + STD_ARRAY_MAT + ACCESS_RW, arr.data(), Size(1, _Nm)); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(const std::vector<std::vector<_Tp> >& vec)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_VECTOR + traits::Type<_Tp>::value + ACCESS_RW, &vec); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(const std::vector<Mat_<_Tp> >& vec)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_MAT + traits::Type<_Tp>::value + ACCESS_RW, &vec); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(const Mat_<_Tp>& m)
+{ init(FIXED_TYPE + FIXED_SIZE + MAT + traits::Type<_Tp>::value + ACCESS_RW, &m); }
+
+template<typename _Tp, int m, int n> inline
+_InputOutputArray::_InputOutputArray(const Matx<_Tp, m, n>& mtx)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, &mtx, Size(n, m)); }
+
+template<typename _Tp> inline
+_InputOutputArray::_InputOutputArray(const _Tp* vec, int n)
+{ init(FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW, vec, Size(n, 1)); }
+
+inline _InputOutputArray::_InputOutputArray(cuda::GpuMat& d_mat)
+{ init(+CUDA_GPU_MAT + ACCESS_RW, &d_mat); }
+
+inline _InputOutputArray::_InputOutputArray(ogl::Buffer& buf)
+{ init(+OPENGL_BUFFER + ACCESS_RW, &buf); }
+
+inline _InputOutputArray::_InputOutputArray(cuda::HostMem& cuda_mem)
+{ init(+CUDA_HOST_MEM + ACCESS_RW, &cuda_mem); }
+
+inline _InputOutputArray::_InputOutputArray(const Mat& m)
+{ init(FIXED_TYPE + FIXED_SIZE + MAT + ACCESS_RW, &m); }
+
+inline _InputOutputArray::_InputOutputArray(const std::vector<Mat>& vec)
+{ init(FIXED_SIZE + STD_VECTOR_MAT + ACCESS_RW, &vec); }
+
+inline _InputOutputArray::_InputOutputArray(const UMat& m)
+{ init(FIXED_TYPE + FIXED_SIZE + UMAT + ACCESS_RW, &m); }
+
+inline _InputOutputArray::_InputOutputArray(const std::vector<UMat>& vec)
+{ init(FIXED_SIZE + STD_VECTOR_UMAT + ACCESS_RW, &vec); }
+
+inline _InputOutputArray::_InputOutputArray(const cuda::GpuMat& d_mat)
+{ init(FIXED_TYPE + FIXED_SIZE + CUDA_GPU_MAT + ACCESS_RW, &d_mat); }
+
+inline _InputOutputArray::_InputOutputArray(const std::vector<cuda::GpuMat>& d_mat)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_CUDA_GPU_MAT + ACCESS_RW, &d_mat);}
+
+template<> inline _InputOutputArray::_InputOutputArray(std::vector<cuda::GpuMat>& d_mat)
+{ init(FIXED_TYPE + FIXED_SIZE + STD_VECTOR_CUDA_GPU_MAT + ACCESS_RW, &d_mat);}
+
+inline _InputOutputArray::_InputOutputArray(const ogl::Buffer& buf)
+{ init(FIXED_TYPE + FIXED_SIZE + OPENGL_BUFFER + ACCESS_RW, &buf); }
+
+inline _InputOutputArray::_InputOutputArray(const cuda::HostMem& cuda_mem)
+{ init(FIXED_TYPE + FIXED_SIZE + CUDA_HOST_MEM + ACCESS_RW, &cuda_mem); }
+
+template<typename _Tp> inline
+_InputOutputArray _InputOutputArray::rawInOut(std::vector<_Tp>& vec)
+{
+    _InputOutputArray v;
+    v.flags = _InputArray::FIXED_TYPE + _InputArray::STD_VECTOR + rawType<_Tp>() + ACCESS_RW;
+    v.obj = (void*)&vec;
+    return v;
+}
+
+template<typename _Tp, std::size_t _Nm> inline
+_InputOutputArray _InputOutputArray::rawInOut(std::array<_Tp, _Nm>& arr)
+{
+    _InputOutputArray v;
+    v.flags = FIXED_TYPE + FIXED_SIZE + MATX + traits::Type<_Tp>::value + ACCESS_RW;
+    v.obj = (void*)arr.data();
+    v.sz = Size(1, _Nm);
+    return v;
+}
+
+
+template<typename _Tp> static inline _InputArray rawIn(_Tp& v) { return _InputArray::rawIn(v); }
+template<typename _Tp> static inline _OutputArray rawOut(_Tp& v) { return _OutputArray::rawOut(v); }
+template<typename _Tp> static inline _InputOutputArray rawInOut(_Tp& v) { return _InputOutputArray::rawInOut(v); }
+
+CV__DEBUG_NS_END
+
+//////////////////////////////////////////// Mat //////////////////////////////////////////
+
+template<typename _Tp> inline
+Mat::Mat(const std::vector<_Tp>& vec, bool copyData)
+    : flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()),
+      cols(1), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
+{
+    if(vec.empty())
+        return;
+    if( !copyData )
+    {
+        step[0] = step[1] = sizeof(_Tp);
+        datastart = data = (uchar*)&vec[0];
+        datalimit = dataend = datastart + rows * step[0];
+    }
+    else
+        Mat((int)vec.size(), 1, traits::Type<_Tp>::value, (uchar*)&vec[0]).copyTo(*this);
+}
+
+template<typename _Tp, typename> inline
+Mat::Mat(const std::initializer_list<_Tp> list)
+    : Mat()
+{
+    CV_Assert(list.size() != 0);
+    Mat((int)list.size(), 1, traits::Type<_Tp>::value, (uchar*)list.begin()).copyTo(*this);
+}
+
+template<typename _Tp> inline
+Mat::Mat(const std::initializer_list<int> sizes, const std::initializer_list<_Tp> list)
+    : Mat()
+{
+    size_t size_total = 1;
+    for(auto s : sizes)
+        size_total *= s;
+    CV_Assert(list.size() != 0);
+    CV_Assert(size_total == list.size());
+    Mat((int)sizes.size(), (int*)sizes.begin(), traits::Type<_Tp>::value, (uchar*)list.begin()).copyTo(*this);
+}
+
+template<typename _Tp, std::size_t _Nm> inline
+Mat::Mat(const std::array<_Tp, _Nm>& arr, bool copyData)
+    : flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows((int)arr.size()),
+      cols(1), data(0), datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
+{
+    if(arr.empty())
+        return;
+    if( !copyData )
+    {
+        step[0] = step[1] = sizeof(_Tp);
+        datastart = data = (uchar*)arr.data();
+        datalimit = dataend = datastart + rows * step[0];
+    }
+    else
+        Mat((int)arr.size(), 1, traits::Type<_Tp>::value, (uchar*)arr.data()).copyTo(*this);
+}
+
+template<typename _Tp, int n> inline
+Mat::Mat(const Vec<_Tp, n>& vec, bool copyData)
+    : flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(n), cols(1), data(0),
+      datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
+{
+    if( !copyData )
+    {
+        step[0] = step[1] = sizeof(_Tp);
+        datastart = data = (uchar*)vec.val;
+        datalimit = dataend = datastart + rows * step[0];
+    }
+    else
+        Mat(n, 1, traits::Type<_Tp>::value, (void*)vec.val).copyTo(*this);
+}
+
+
+template<typename _Tp, int m, int n> inline
+Mat::Mat(const Matx<_Tp,m,n>& M, bool copyData)
+    : flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(m), cols(n), data(0),
+      datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
+{
+    if( !copyData )
+    {
+        step[0] = cols * sizeof(_Tp);
+        step[1] = sizeof(_Tp);
+        datastart = data = (uchar*)M.val;
+        datalimit = dataend = datastart + rows * step[0];
+    }
+    else
+        Mat(m, n, traits::Type<_Tp>::value, (uchar*)M.val).copyTo(*this);
+}
+
+template<typename _Tp> inline
+Mat::Mat(const Point_<_Tp>& pt, bool copyData)
+    : flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(2), cols(1), data(0),
+      datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
+{
+    if( !copyData )
+    {
+        step[0] = step[1] = sizeof(_Tp);
+        datastart = data = (uchar*)&pt.x;
+        datalimit = dataend = datastart + rows * step[0];
+    }
+    else
+    {
+        create(2, 1, traits::Type<_Tp>::value);
+        ((_Tp*)data)[0] = pt.x;
+        ((_Tp*)data)[1] = pt.y;
+    }
+}
+
+template<typename _Tp> inline
+Mat::Mat(const Point3_<_Tp>& pt, bool copyData)
+    : flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows(3), cols(1), data(0),
+      datastart(0), dataend(0), datalimit(0), allocator(0), u(0), size(&rows), step(0)
+{
+    if( !copyData )
+    {
+        step[0] = step[1] = sizeof(_Tp);
+        datastart = data = (uchar*)&pt.x;
+        datalimit = dataend = datastart + rows * step[0];
+    }
+    else
+    {
+        create(3, 1, traits::Type<_Tp>::value);
+        ((_Tp*)data)[0] = pt.x;
+        ((_Tp*)data)[1] = pt.y;
+        ((_Tp*)data)[2] = pt.z;
+    }
+}
+
+template<typename _Tp> inline
+Mat::Mat(const MatCommaInitializer_<_Tp>& commaInitializer)
+    : flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(0), rows(0), cols(0), data(0),
+      datastart(0), dataend(0), allocator(0), u(0), size(&rows)
+{
+    *this = commaInitializer.operator Mat_<_Tp>();
+}
+
+inline
+Mat Mat::row(int y) const
+{
+    return Mat(*this, Range(y, y + 1), Range::all());
+}
+
+inline
+Mat Mat::col(int x) const
+{
+    return Mat(*this, Range::all(), Range(x, x + 1));
+}
+
+inline
+Mat Mat::rowRange(int startrow, int endrow) const
+{
+    return Mat(*this, Range(startrow, endrow), Range::all());
+}
+
+inline
+Mat Mat::rowRange(const Range& r) const
+{
+    return Mat(*this, r, Range::all());
+}
+
+inline
+Mat Mat::colRange(int startcol, int endcol) const
+{
+    return Mat(*this, Range::all(), Range(startcol, endcol));
+}
+
+inline
+Mat Mat::colRange(const Range& r) const
+{
+    return Mat(*this, Range::all(), r);
+}
+
+inline
+Mat Mat::operator()( Range _rowRange, Range _colRange ) const
+{
+    return Mat(*this, _rowRange, _colRange);
+}
+
+inline
+Mat Mat::operator()( const Rect& roi ) const
+{
+    return Mat(*this, roi);
+}
+
+inline
+Mat Mat::operator()(const Range* ranges) const
+{
+    return Mat(*this, ranges);
+}
+
+inline
+Mat Mat::operator()(const std::vector<Range>& ranges) const
+{
+    return Mat(*this, ranges);
+}
+
+inline
+bool Mat::isContinuous() const
+{
+    return (flags & CONTINUOUS_FLAG) != 0;
+}
+
+inline
+bool Mat::isSubmatrix() const
+{
+    return (flags & SUBMATRIX_FLAG) != 0;
+}
+
+inline
+size_t Mat::elemSize() const
+{
+    size_t res = dims > 0 ? step.p[dims - 1] : 0;
+    CV_DbgAssert(res != 0);
+    return res;
+}
+
+inline
+size_t Mat::elemSize1() const
+{
+    return CV_ELEM_SIZE1(flags);
+}
+
+inline
+int Mat::type() const
+{
+    return CV_MAT_TYPE(flags);
+}
+
+inline
+int Mat::depth() const
+{
+    return CV_MAT_DEPTH(flags);
+}
+
+inline
+int Mat::channels() const
+{
+    return CV_MAT_CN(flags);
+}
+
+inline
+uchar* Mat::ptr(int y)
+{
+    CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) );
+    return data + step.p[0] * y;
+}
+
+inline
+const uchar* Mat::ptr(int y) const
+{
+    CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) );
+    return data + step.p[0] * y;
+}
+
+template<typename _Tp> inline
+_Tp* Mat::ptr(int y)
+{
+    CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) );
+    return (_Tp*)(data + step.p[0] * y);
+}
+
+template<typename _Tp> inline
+const _Tp* Mat::ptr(int y) const
+{
+    CV_DbgAssert( y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0]) );
+    return (const _Tp*)(data + step.p[0] * y);
+}
+
+inline
+uchar* Mat::ptr(int i0, int i1)
+{
+    CV_DbgAssert(dims >= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    return data + i0 * step.p[0] + i1 * step.p[1];
+}
+
+inline
+const uchar* Mat::ptr(int i0, int i1) const
+{
+    CV_DbgAssert(dims >= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    return data + i0 * step.p[0] + i1 * step.p[1];
+}
+
+template<typename _Tp> inline
+_Tp* Mat::ptr(int i0, int i1)
+{
+    CV_DbgAssert(dims >= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    return (_Tp*)(data + i0 * step.p[0] + i1 * step.p[1]);
+}
+
+template<typename _Tp> inline
+const _Tp* Mat::ptr(int i0, int i1) const
+{
+    CV_DbgAssert(dims >= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    return (const _Tp*)(data + i0 * step.p[0] + i1 * step.p[1]);
+}
+
+inline
+uchar* Mat::ptr(int i0, int i1, int i2)
+{
+    CV_DbgAssert(dims >= 3);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]);
+    return data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2];
+}
+
+inline
+const uchar* Mat::ptr(int i0, int i1, int i2) const
+{
+    CV_DbgAssert(dims >= 3);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]);
+    return data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2];
+}
+
+template<typename _Tp> inline
+_Tp* Mat::ptr(int i0, int i1, int i2)
+{
+    CV_DbgAssert(dims >= 3);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]);
+    return (_Tp*)(data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2]);
+}
+
+template<typename _Tp> inline
+const _Tp* Mat::ptr(int i0, int i1, int i2) const
+{
+    CV_DbgAssert(dims >= 3);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    CV_DbgAssert((unsigned)i2 < (unsigned)size.p[2]);
+    return (const _Tp*)(data + i0 * step.p[0] + i1 * step.p[1] + i2 * step.p[2]);
+}
+
+inline
+uchar* Mat::ptr(const int* idx)
+{
+    int i, d = dims;
+    uchar* p = data;
+    CV_DbgAssert( d >= 1 && p );
+    for( i = 0; i < d; i++ )
+    {
+        CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] );
+        p += idx[i] * step.p[i];
+    }
+    return p;
+}
+
+inline
+const uchar* Mat::ptr(const int* idx) const
+{
+    int i, d = dims;
+    uchar* p = data;
+    CV_DbgAssert( d >= 1 && p );
+    for( i = 0; i < d; i++ )
+    {
+        CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] );
+        p += idx[i] * step.p[i];
+    }
+    return p;
+}
+
+template<typename _Tp> inline
+_Tp* Mat::ptr(const int* idx)
+{
+    int i, d = dims;
+    uchar* p = data;
+    CV_DbgAssert( d >= 1 && p );
+    for( i = 0; i < d; i++ )
+    {
+        CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] );
+        p += idx[i] * step.p[i];
+    }
+    return (_Tp*)p;
+}
+
+template<typename _Tp> inline
+const _Tp* Mat::ptr(const int* idx) const
+{
+    int i, d = dims;
+    uchar* p = data;
+    CV_DbgAssert( d >= 1 && p );
+    for( i = 0; i < d; i++ )
+    {
+        CV_DbgAssert( (unsigned)idx[i] < (unsigned)size.p[i] );
+        p += idx[i] * step.p[i];
+    }
+    return (const _Tp*)p;
+}
+
+template<int n> inline
+uchar* Mat::ptr(const Vec<int, n>& idx)
+{
+    return Mat::ptr(idx.val);
+}
+
+template<int n> inline
+const uchar* Mat::ptr(const Vec<int, n>& idx) const
+{
+    return Mat::ptr(idx.val);
+}
+
+template<typename _Tp, int n> inline
+_Tp* Mat::ptr(const Vec<int, n>& idx)
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return Mat::ptr<_Tp>(idx.val);
+}
+
+template<typename _Tp, int n> inline
+const _Tp* Mat::ptr(const Vec<int, n>& idx) const
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return Mat::ptr<_Tp>(idx.val);
+}
+
+
+template<typename _Tp> inline
+_Tp& Mat::at(int i0, int i1)
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)(i1 * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels()));
+    CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1());
+    return ((_Tp*)(data + step.p[0] * i0))[i1];
+}
+
+template<typename _Tp> inline
+const _Tp& Mat::at(int i0, int i1) const
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)(i1 * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels()));
+    CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1());
+    return ((const _Tp*)(data + step.p[0] * i0))[i1];
+}
+
+template<typename _Tp> inline
+_Tp& Mat::at(Point pt)
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)(pt.x * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels()));
+    CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1());
+    return ((_Tp*)(data + step.p[0] * pt.y))[pt.x];
+}
+
+template<typename _Tp> inline
+const _Tp& Mat::at(Point pt) const
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)(pt.x * DataType<_Tp>::channels) < (unsigned)(size.p[1] * channels()));
+    CV_DbgAssert(CV_ELEM_SIZE1(traits::Depth<_Tp>::value) == elemSize1());
+    return ((const _Tp*)(data + step.p[0] * pt.y))[pt.x];
+}
+
+template<typename _Tp> inline
+_Tp& Mat::at(int i0)
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)(size.p[0] * size.p[1]));
+    CV_DbgAssert(elemSize() == sizeof(_Tp));
+    if( isContinuous() || size.p[0] == 1 )
+        return ((_Tp*)data)[i0];
+    if( size.p[1] == 1 )
+        return *(_Tp*)(data + step.p[0] * i0);
+    int i = i0 / cols, j = i0 - i * cols;
+    return ((_Tp*)(data + step.p[0] * i))[j];
+}
+
+template<typename _Tp> inline
+const _Tp& Mat::at(int i0) const
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)(size.p[0] * size.p[1]));
+    CV_DbgAssert(elemSize() == sizeof(_Tp));
+    if( isContinuous() || size.p[0] == 1 )
+        return ((const _Tp*)data)[i0];
+    if( size.p[1] == 1 )
+        return *(const _Tp*)(data + step.p[0] * i0);
+    int i = i0 / cols, j = i0 - i * cols;
+    return ((const _Tp*)(data + step.p[0] * i))[j];
+}
+
+template<typename _Tp> inline
+_Tp& Mat::at(int i0, int i1, int i2)
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return *(_Tp*)ptr(i0, i1, i2);
+}
+
+template<typename _Tp> inline
+const _Tp& Mat::at(int i0, int i1, int i2) const
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return *(const _Tp*)ptr(i0, i1, i2);
+}
+
+template<typename _Tp> inline
+_Tp& Mat::at(const int* idx)
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return *(_Tp*)ptr(idx);
+}
+
+template<typename _Tp> inline
+const _Tp& Mat::at(const int* idx) const
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return *(const _Tp*)ptr(idx);
+}
+
+template<typename _Tp, int n> inline
+_Tp& Mat::at(const Vec<int, n>& idx)
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return *(_Tp*)ptr(idx.val);
+}
+
+template<typename _Tp, int n> inline
+const _Tp& Mat::at(const Vec<int, n>& idx) const
+{
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return *(const _Tp*)ptr(idx.val);
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp> Mat::begin() const
+{
+    if (empty())
+        return MatConstIterator_<_Tp>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return MatConstIterator_<_Tp>((const Mat_<_Tp>*)this);
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatConstIterator_<_Tp>> Mat::rbegin() const
+{
+    if (empty())
+        return std::reverse_iterator<MatConstIterator_<_Tp>>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    MatConstIterator_<_Tp> it((const Mat_<_Tp>*)this);
+    it += total();
+    return std::reverse_iterator<MatConstIterator_<_Tp>> (it);
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp> Mat::end() const
+{
+    if (empty())
+        return MatConstIterator_<_Tp>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    MatConstIterator_<_Tp> it((const Mat_<_Tp>*)this);
+    it += total();
+    return it;
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatConstIterator_<_Tp>> Mat::rend() const
+{
+    if (empty())
+        return std::reverse_iterator<MatConstIterator_<_Tp>>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return std::reverse_iterator<MatConstIterator_<_Tp>>((const Mat_<_Tp>*)this);
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp> Mat::begin()
+{
+    if (empty())
+        return MatIterator_<_Tp>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return MatIterator_<_Tp>((Mat_<_Tp>*)this);
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatIterator_<_Tp>> Mat::rbegin()
+{
+    if (empty())
+        return std::reverse_iterator<MatIterator_<_Tp>>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    MatIterator_<_Tp> it((Mat_<_Tp>*)this);
+    it += total();
+    return std::reverse_iterator<MatIterator_<_Tp>>(it);
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp> Mat::end()
+{
+    if (empty())
+        return MatIterator_<_Tp>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    MatIterator_<_Tp> it((Mat_<_Tp>*)this);
+    it += total();
+    return it;
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatIterator_<_Tp>> Mat::rend()
+{
+    if (empty())
+        return std::reverse_iterator<MatIterator_<_Tp>>();
+    CV_DbgAssert( elemSize() == sizeof(_Tp) );
+    return std::reverse_iterator<MatIterator_<_Tp>>(MatIterator_<_Tp>((Mat_<_Tp>*)this));
+}
+
+template<typename _Tp, typename Functor> inline
+void Mat::forEach(const Functor& operation) {
+    this->forEach_impl<_Tp>(operation);
+}
+
+template<typename _Tp, typename Functor> inline
+void Mat::forEach(const Functor& operation) const {
+    // call as not const
+    (const_cast<Mat*>(this))->forEach<_Tp>(operation);
+}
+
+template<typename _Tp> inline
+Mat::operator std::vector<_Tp>() const
+{
+    std::vector<_Tp> v;
+    copyTo(v);
+    return v;
+}
+
+template<typename _Tp, std::size_t _Nm> inline
+Mat::operator std::array<_Tp, _Nm>() const
+{
+    std::array<_Tp, _Nm> v;
+    copyTo(v);
+    return v;
+}
+
+template<typename _Tp, int n> inline
+Mat::operator Vec<_Tp, n>() const
+{
+    CV_Assert( data && dims <= 2 && (rows == 1 || cols == 1) &&
+               rows + cols - 1 == n && channels() == 1 );
+
+    if( isContinuous() && type() == traits::Type<_Tp>::value )
+        return Vec<_Tp, n>((_Tp*)data);
+    Vec<_Tp, n> v;
+    Mat tmp(rows, cols, traits::Type<_Tp>::value, v.val);
+    convertTo(tmp, tmp.type());
+    return v;
+}
+
+template<typename _Tp, int m, int n> inline
+Mat::operator Matx<_Tp, m, n>() const
+{
+    CV_Assert( data && dims <= 2 && rows == m && cols == n && channels() == 1 );
+
+    if( isContinuous() && type() == traits::Type<_Tp>::value )
+        return Matx<_Tp, m, n>((_Tp*)data);
+    Matx<_Tp, m, n> mtx;
+    Mat tmp(rows, cols, traits::Type<_Tp>::value, mtx.val);
+    convertTo(tmp, tmp.type());
+    return mtx;
+}
+
+template<typename _Tp> inline
+void Mat::push_back(const _Tp& elem)
+{
+    if( !data )
+    {
+        *this = Mat(1, 1, traits::Type<_Tp>::value, (void*)&elem).clone();
+        return;
+    }
+    CV_Assert(traits::Type<_Tp>::value == type() && cols == 1
+              /* && dims == 2 (cols == 1 implies dims == 2) */);
+    const uchar* tmp = dataend + step[0];
+    if( !isSubmatrix() && isContinuous() && tmp <= datalimit )
+    {
+        *(_Tp*)(data + (size.p[0]++) * step.p[0]) = elem;
+        dataend = tmp;
+    }
+    else
+        push_back_(&elem);
+}
+
+template<typename _Tp> inline
+void Mat::push_back(const Mat_<_Tp>& m)
+{
+    push_back((const Mat&)m);
+}
+
+template<> inline
+void Mat::push_back(const MatExpr& expr)
+{
+    push_back(static_cast<Mat>(expr));
+}
+
+
+template<typename _Tp> inline
+void Mat::push_back(const std::vector<_Tp>& v)
+{
+    push_back(Mat(v));
+}
+
+
+///////////////////////////// MatSize ////////////////////////////
+
+inline
+MatSize::MatSize(int* _p) CV_NOEXCEPT
+    : p(_p) {}
+
+inline
+int MatSize::dims() const CV_NOEXCEPT
+{
+    return (p - 1)[0];
+}
+
+inline
+Size MatSize::operator()() const
+{
+    CV_DbgAssert(dims() <= 2);
+    return Size(p[1], p[0]);
+}
+
+inline
+const int& MatSize::operator[](int i) const
+{
+    CV_DbgAssert(i < dims());
+#ifdef __OPENCV_BUILD
+    CV_DbgAssert(i >= 0);
+#endif
+    return p[i];
+}
+
+inline
+int& MatSize::operator[](int i)
+{
+    CV_DbgAssert(i < dims());
+#ifdef __OPENCV_BUILD
+    CV_DbgAssert(i >= 0);
+#endif
+    return p[i];
+}
+
+inline
+MatSize::operator const int*() const CV_NOEXCEPT
+{
+    return p;
+}
+
+inline
+bool MatSize::operator != (const MatSize& sz) const CV_NOEXCEPT
+{
+    return !(*this == sz);
+}
+
+
+
+///////////////////////////// MatStep ////////////////////////////
+
+inline
+MatStep::MatStep() CV_NOEXCEPT
+{
+    p = buf; p[0] = p[1] = 0;
+}
+
+inline
+MatStep::MatStep(size_t s) CV_NOEXCEPT
+{
+    p = buf; p[0] = s; p[1] = 0;
+}
+
+inline
+const size_t& MatStep::operator[](int i) const CV_NOEXCEPT
+{
+    return p[i];
+}
+
+inline
+size_t& MatStep::operator[](int i) CV_NOEXCEPT
+{
+    return p[i];
+}
+
+inline MatStep::operator size_t() const
+{
+    CV_DbgAssert( p == buf );
+    return buf[0];
+}
+
+inline MatStep& MatStep::operator = (size_t s)
+{
+    CV_DbgAssert( p == buf );
+    buf[0] = s;
+    return *this;
+}
+
+
+
+////////////////////////////// Mat_<_Tp> ////////////////////////////
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_() CV_NOEXCEPT
+    : Mat()
+{
+    flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(int _rows, int _cols)
+    : Mat(_rows, _cols, traits::Type<_Tp>::value)
+{
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(int _rows, int _cols, const _Tp& value)
+    : Mat(_rows, _cols, traits::Type<_Tp>::value)
+{
+    *this = value;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(Size _sz)
+    : Mat(_sz.height, _sz.width, traits::Type<_Tp>::value)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(Size _sz, const _Tp& value)
+    : Mat(_sz.height, _sz.width, traits::Type<_Tp>::value)
+{
+    *this = value;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(int _dims, const int* _sz)
+    : Mat(_dims, _sz, traits::Type<_Tp>::value)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(int _dims, const int* _sz, const _Tp& _s)
+    : Mat(_dims, _sz, traits::Type<_Tp>::value, Scalar(_s))
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(int _dims, const int* _sz, _Tp* _data, const size_t* _steps)
+    : Mat(_dims, _sz, traits::Type<_Tp>::value, _data, _steps)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Mat_<_Tp>& m, const Range* ranges)
+    : Mat(m, ranges)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Mat_<_Tp>& m, const std::vector<Range>& ranges)
+    : Mat(m, ranges)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Mat& m)
+    : Mat()
+{
+    flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
+    *this = m;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Mat_& m)
+    : Mat(m)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(int _rows, int _cols, _Tp* _data, size_t steps)
+    : Mat(_rows, _cols, traits::Type<_Tp>::value, _data, steps)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Mat_& m, const Range& _rowRange, const Range& _colRange)
+    : Mat(m, _rowRange, _colRange)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Mat_& m, const Rect& roi)
+    : Mat(m, roi)
+{}
+
+template<typename _Tp> template<int n> inline
+Mat_<_Tp>::Mat_(const Vec<typename DataType<_Tp>::channel_type, n>& vec, bool copyData)
+    : Mat(n / DataType<_Tp>::channels, 1, traits::Type<_Tp>::value, (void*)&vec)
+{
+    CV_Assert(n%DataType<_Tp>::channels == 0);
+    if( copyData )
+        *this = clone();
+}
+
+template<typename _Tp> template<int m, int n> inline
+Mat_<_Tp>::Mat_(const Matx<typename DataType<_Tp>::channel_type, m, n>& M, bool copyData)
+    : Mat(m, n / DataType<_Tp>::channels, traits::Type<_Tp>::value, (void*)&M)
+{
+    CV_Assert(n % DataType<_Tp>::channels == 0);
+    if( copyData )
+        *this = clone();
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Point_<typename DataType<_Tp>::channel_type>& pt, bool copyData)
+    : Mat(2 / DataType<_Tp>::channels, 1, traits::Type<_Tp>::value, (void*)&pt)
+{
+    CV_Assert(2 % DataType<_Tp>::channels == 0);
+    if( copyData )
+        *this = clone();
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const Point3_<typename DataType<_Tp>::channel_type>& pt, bool copyData)
+    : Mat(3 / DataType<_Tp>::channels, 1, traits::Type<_Tp>::value, (void*)&pt)
+{
+    CV_Assert(3 % DataType<_Tp>::channels == 0);
+    if( copyData )
+        *this = clone();
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const MatCommaInitializer_<_Tp>& commaInitializer)
+    : Mat(commaInitializer)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const std::vector<_Tp>& vec, bool copyData)
+    : Mat(vec, copyData)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(std::initializer_list<_Tp> list)
+    : Mat(list)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const std::initializer_list<int> sizes, std::initializer_list<_Tp> list)
+    : Mat(sizes, list)
+{}
+
+template<typename _Tp> template<std::size_t _Nm> inline
+Mat_<_Tp>::Mat_(const std::array<_Tp, _Nm>& arr, bool copyData)
+    : Mat(arr, copyData)
+{}
+
+template<typename _Tp> inline
+Mat_<_Tp>& Mat_<_Tp>::operator = (const Mat& m)
+{
+    if (m.empty())
+    {
+        release();
+        return *this;
+    }
+    if( traits::Type<_Tp>::value == m.type() )
+    {
+        Mat::operator = (m);
+        return *this;
+    }
+    if( traits::Depth<_Tp>::value == m.depth() )
+    {
+        return (*this = m.reshape(DataType<_Tp>::channels, m.dims, 0));
+    }
+    CV_Assert(DataType<_Tp>::channels == m.channels() || m.empty());
+    m.convertTo(*this, type());
+    return *this;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>& Mat_<_Tp>::operator = (const Mat_& m)
+{
+    Mat::operator=(m);
+    return *this;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>& Mat_<_Tp>::operator = (const _Tp& s)
+{
+    typedef typename DataType<_Tp>::vec_type VT;
+    Mat::operator=(Scalar((const VT&)s));
+    return *this;
+}
+
+template<typename _Tp> inline
+void Mat_<_Tp>::create(int _rows, int _cols)
+{
+    Mat::create(_rows, _cols, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+void Mat_<_Tp>::create(Size _sz)
+{
+    Mat::create(_sz, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+void Mat_<_Tp>::create(int _dims, const int* _sz)
+{
+    Mat::create(_dims, _sz, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+void Mat_<_Tp>::release()
+{
+    Mat::release();
+    flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::cross(const Mat_& m) const
+{
+    return Mat_<_Tp>(Mat::cross(m));
+}
+
+template<typename _Tp> template<typename T2> inline
+Mat_<_Tp>::operator Mat_<T2>() const
+{
+    return Mat_<T2>(static_cast<const Mat&>(*this));
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::row(int y) const
+{
+    return Mat_(*this, Range(y, y+1), Range::all());
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::col(int x) const
+{
+    return Mat_(*this, Range::all(), Range(x, x+1));
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::diag(int d) const
+{
+    return Mat_(Mat::diag(d));
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::clone() const
+{
+    return Mat_(Mat::clone());
+}
+
+template<typename _Tp> inline
+size_t Mat_<_Tp>::elemSize() const
+{
+    CV_DbgAssert( Mat::elemSize() == sizeof(_Tp) );
+    return sizeof(_Tp);
+}
+
+template<typename _Tp> inline
+size_t Mat_<_Tp>::elemSize1() const
+{
+    CV_DbgAssert( Mat::elemSize1() == sizeof(_Tp) / DataType<_Tp>::channels );
+    return sizeof(_Tp) / DataType<_Tp>::channels;
+}
+
+template<typename _Tp> inline
+int Mat_<_Tp>::type() const
+{
+    CV_DbgAssert( Mat::type() == traits::Type<_Tp>::value );
+    return traits::Type<_Tp>::value;
+}
+
+template<typename _Tp> inline
+int Mat_<_Tp>::depth() const
+{
+    CV_DbgAssert( Mat::depth() == traits::Depth<_Tp>::value );
+    return traits::Depth<_Tp>::value;
+}
+
+template<typename _Tp> inline
+int Mat_<_Tp>::channels() const
+{
+    CV_DbgAssert( Mat::channels() == DataType<_Tp>::channels );
+    return DataType<_Tp>::channels;
+}
+
+template<typename _Tp> inline
+size_t Mat_<_Tp>::stepT(int i) const
+{
+    return step.p[i] / elemSize();
+}
+
+template<typename _Tp> inline
+size_t Mat_<_Tp>::step1(int i) const
+{
+    return step.p[i] / elemSize1();
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>& Mat_<_Tp>::adjustROI( int dtop, int dbottom, int dleft, int dright )
+{
+    return (Mat_<_Tp>&)(Mat::adjustROI(dtop, dbottom, dleft, dright));
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::operator()( const Range& _rowRange, const Range& _colRange ) const
+{
+    return Mat_<_Tp>(*this, _rowRange, _colRange);
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::operator()( const Rect& roi ) const
+{
+    return Mat_<_Tp>(*this, roi);
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::operator()( const Range* ranges ) const
+{
+    return Mat_<_Tp>(*this, ranges);
+}
+
+template<typename _Tp> inline
+Mat_<_Tp> Mat_<_Tp>::operator()(const std::vector<Range>& ranges) const
+{
+    return Mat_<_Tp>(*this, ranges);
+}
+
+template<typename _Tp> inline
+_Tp* Mat_<_Tp>::operator [](int y)
+{
+    CV_DbgAssert( 0 <= y && y < size.p[0] );
+    return (_Tp*)(data + y*step.p[0]);
+}
+
+template<typename _Tp> inline
+const _Tp* Mat_<_Tp>::operator [](int y) const
+{
+    CV_DbgAssert( 0 <= y && y < size.p[0] );
+    return (const _Tp*)(data + y*step.p[0]);
+}
+
+template<typename _Tp> inline
+_Tp& Mat_<_Tp>::operator ()(int i0, int i1)
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    CV_DbgAssert(type() == traits::Type<_Tp>::value);
+    return ((_Tp*)(data + step.p[0] * i0))[i1];
+}
+
+template<typename _Tp> inline
+const _Tp& Mat_<_Tp>::operator ()(int i0, int i1) const
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)i0 < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)i1 < (unsigned)size.p[1]);
+    CV_DbgAssert(type() == traits::Type<_Tp>::value);
+    return ((const _Tp*)(data + step.p[0] * i0))[i1];
+}
+
+template<typename _Tp> inline
+_Tp& Mat_<_Tp>::operator ()(Point pt)
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)pt.x < (unsigned)size.p[1]);
+    CV_DbgAssert(type() == traits::Type<_Tp>::value);
+    return ((_Tp*)(data + step.p[0] * pt.y))[pt.x];
+}
+
+template<typename _Tp> inline
+const _Tp& Mat_<_Tp>::operator ()(Point pt) const
+{
+    CV_DbgAssert(dims <= 2);
+    CV_DbgAssert(data);
+    CV_DbgAssert((unsigned)pt.y < (unsigned)size.p[0]);
+    CV_DbgAssert((unsigned)pt.x < (unsigned)size.p[1]);
+    CV_DbgAssert(type() == traits::Type<_Tp>::value);
+    return ((const _Tp*)(data + step.p[0] * pt.y))[pt.x];
+}
+
+template<typename _Tp> inline
+_Tp& Mat_<_Tp>::operator ()(const int* idx)
+{
+    return Mat::at<_Tp>(idx);
+}
+
+template<typename _Tp> inline
+const _Tp& Mat_<_Tp>::operator ()(const int* idx) const
+{
+    return Mat::at<_Tp>(idx);
+}
+
+template<typename _Tp> template<int n> inline
+_Tp& Mat_<_Tp>::operator ()(const Vec<int, n>& idx)
+{
+    return Mat::at<_Tp>(idx);
+}
+
+template<typename _Tp> template<int n> inline
+const _Tp& Mat_<_Tp>::operator ()(const Vec<int, n>& idx) const
+{
+    return Mat::at<_Tp>(idx);
+}
+
+template<typename _Tp> inline
+_Tp& Mat_<_Tp>::operator ()(int i0)
+{
+    return this->at<_Tp>(i0);
+}
+
+template<typename _Tp> inline
+const _Tp& Mat_<_Tp>::operator ()(int i0) const
+{
+    return this->at<_Tp>(i0);
+}
+
+template<typename _Tp> inline
+_Tp& Mat_<_Tp>::operator ()(int i0, int i1, int i2)
+{
+    return this->at<_Tp>(i0, i1, i2);
+}
+
+template<typename _Tp> inline
+const _Tp& Mat_<_Tp>::operator ()(int i0, int i1, int i2) const
+{
+    return this->at<_Tp>(i0, i1, i2);
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::operator std::vector<_Tp>() const
+{
+    std::vector<_Tp> v;
+    copyTo(v);
+    return v;
+}
+
+template<typename _Tp> template<std::size_t _Nm> inline
+Mat_<_Tp>::operator std::array<_Tp, _Nm>() const
+{
+    std::array<_Tp, _Nm> a;
+    copyTo(a);
+    return a;
+}
+
+template<typename _Tp> template<int n> inline
+Mat_<_Tp>::operator Vec<typename DataType<_Tp>::channel_type, n>() const
+{
+    CV_Assert(n % DataType<_Tp>::channels == 0);
+
+#if defined _MSC_VER
+    const Mat* pMat = (const Mat*)this; // workaround for MSVS <= 2012 compiler bugs (but GCC 4.6 dislikes this workaround)
+    return pMat->operator Vec<typename DataType<_Tp>::channel_type, n>();
+#else
+    return this->Mat::operator Vec<typename DataType<_Tp>::channel_type, n>();
+#endif
+}
+
+template<typename _Tp> template<int m, int n> inline
+Mat_<_Tp>::operator Matx<typename DataType<_Tp>::channel_type, m, n>() const
+{
+    CV_Assert(n % DataType<_Tp>::channels == 0);
+
+#if defined _MSC_VER
+    const Mat* pMat = (const Mat*)this; // workaround for MSVS <= 2012 compiler bugs (but GCC 4.6 dislikes this workaround)
+    Matx<typename DataType<_Tp>::channel_type, m, n> res = pMat->operator Matx<typename DataType<_Tp>::channel_type, m, n>();
+    return res;
+#else
+    Matx<typename DataType<_Tp>::channel_type, m, n> res = this->Mat::operator Matx<typename DataType<_Tp>::channel_type, m, n>();
+    return res;
+#endif
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp> Mat_<_Tp>::begin() const
+{
+    return Mat::begin<_Tp>();
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatConstIterator_<_Tp>> Mat_<_Tp>::rbegin() const
+{
+    return Mat::rbegin<_Tp>();
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp> Mat_<_Tp>::end() const
+{
+    return Mat::end<_Tp>();
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatConstIterator_<_Tp>> Mat_<_Tp>::rend() const
+{
+    return Mat::rend<_Tp>();
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp> Mat_<_Tp>::begin()
+{
+    return Mat::begin<_Tp>();
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatIterator_<_Tp>> Mat_<_Tp>::rbegin()
+{
+    return Mat::rbegin<_Tp>();
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp> Mat_<_Tp>::end()
+{
+    return Mat::end<_Tp>();
+}
+
+template<typename _Tp> inline
+std::reverse_iterator<MatIterator_<_Tp>> Mat_<_Tp>::rend()
+{
+    return Mat::rend<_Tp>();
+}
+
+template<typename _Tp> template<typename Functor> inline
+void Mat_<_Tp>::forEach(const Functor& operation) {
+    Mat::forEach<_Tp, Functor>(operation);
+}
+
+template<typename _Tp> template<typename Functor> inline
+void Mat_<_Tp>::forEach(const Functor& operation) const {
+    Mat::forEach<_Tp, Functor>(operation);
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(Mat_&& m)
+    : Mat(std::move(m))
+{
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>& Mat_<_Tp>::operator = (Mat_&& m)
+{
+    Mat::operator = (std::move(m));
+    return *this;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(Mat&& m)
+    : Mat()
+{
+    flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
+    *this = std::move(m);
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>& Mat_<_Tp>::operator = (Mat&& m)
+{
+    if (m.empty())
+    {
+        release();
+        return *this;
+    }
+    if( traits::Type<_Tp>::value == m.type() )
+    {
+        Mat::operator = ((Mat&&)m);
+        return *this;
+    }
+    if( traits::Depth<_Tp>::value == m.depth() )
+    {
+        Mat::operator = ((Mat&&)m.reshape(DataType<_Tp>::channels, m.dims, 0));
+        return *this;
+    }
+    CV_DbgAssert(DataType<_Tp>::channels == m.channels());
+    m.convertTo(*this, type());
+    return *this;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(MatExpr&& e)
+    : Mat()
+{
+    flags = (flags & ~CV_MAT_TYPE_MASK) + traits::Type<_Tp>::value;
+    *this = Mat(e);
+}
+
+
+///////////////////////////// SparseMat /////////////////////////////
+
+inline
+SparseMat SparseMat::clone() const
+{
+    SparseMat temp;
+    this->copyTo(temp);
+    return temp;
+}
+
+inline
+size_t SparseMat::elemSize() const
+{
+    return CV_ELEM_SIZE(flags);
+}
+
+inline
+size_t SparseMat::elemSize1() const
+{
+    return CV_ELEM_SIZE1(flags);
+}
+
+inline
+int SparseMat::type() const
+{
+    return CV_MAT_TYPE(flags);
+}
+
+inline
+int SparseMat::depth() const
+{
+    return CV_MAT_DEPTH(flags);
+}
+
+inline
+int SparseMat::channels() const
+{
+    return CV_MAT_CN(flags);
+}
+
+inline
+const int* SparseMat::size() const
+{
+    return hdr ? hdr->size : 0;
+}
+
+inline
+int SparseMat::size(int i) const
+{
+    if( hdr )
+    {
+        CV_DbgAssert((unsigned)i < (unsigned)hdr->dims);
+        return hdr->size[i];
+    }
+    return 0;
+}
+
+inline
+int SparseMat::dims() const
+{
+    return hdr ? hdr->dims : 0;
+}
+
+inline
+size_t SparseMat::nzcount() const
+{
+    return hdr ? hdr->nodeCount : 0;
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat::ref(int i0, size_t* hashval)
+{
+    return *(_Tp*)((SparseMat*)this)->ptr(i0, true, hashval);
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat::ref(int i0, int i1, size_t* hashval)
+{
+    return *(_Tp*)((SparseMat*)this)->ptr(i0, i1, true, hashval);
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat::ref(int i0, int i1, int i2, size_t* hashval)
+{
+    return *(_Tp*)((SparseMat*)this)->ptr(i0, i1, i2, true, hashval);
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat::ref(const int* idx, size_t* hashval)
+{
+    return *(_Tp*)((SparseMat*)this)->ptr(idx, true, hashval);
+}
+
+template<typename _Tp> inline
+_Tp SparseMat::value(int i0, size_t* hashval) const
+{
+    const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(i0, false, hashval);
+    return p ? *p : _Tp();
+}
+
+template<typename _Tp> inline
+_Tp SparseMat::value(int i0, int i1, size_t* hashval) const
+{
+    const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(i0, i1, false, hashval);
+    return p ? *p : _Tp();
+}
+
+template<typename _Tp> inline
+_Tp SparseMat::value(int i0, int i1, int i2, size_t* hashval) const
+{
+    const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(i0, i1, i2, false, hashval);
+    return p ? *p : _Tp();
+}
+
+template<typename _Tp> inline
+_Tp SparseMat::value(const int* idx, size_t* hashval) const
+{
+    const _Tp* p = (const _Tp*)((SparseMat*)this)->ptr(idx, false, hashval);
+    return p ? *p : _Tp();
+}
+
+template<typename _Tp> inline
+const _Tp* SparseMat::find(int i0, size_t* hashval) const
+{
+    return (const _Tp*)((SparseMat*)this)->ptr(i0, false, hashval);
+}
+
+template<typename _Tp> inline
+const _Tp* SparseMat::find(int i0, int i1, size_t* hashval) const
+{
+    return (const _Tp*)((SparseMat*)this)->ptr(i0, i1, false, hashval);
+}
+
+template<typename _Tp> inline
+const _Tp* SparseMat::find(int i0, int i1, int i2, size_t* hashval) const
+{
+    return (const _Tp*)((SparseMat*)this)->ptr(i0, i1, i2, false, hashval);
+}
+
+template<typename _Tp> inline
+const _Tp* SparseMat::find(const int* idx, size_t* hashval) const
+{
+    return (const _Tp*)((SparseMat*)this)->ptr(idx, false, hashval);
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat::value(Node* n)
+{
+    return *(_Tp*)((uchar*)n + hdr->valueOffset);
+}
+
+template<typename _Tp> inline
+const _Tp& SparseMat::value(const Node* n) const
+{
+    return *(const _Tp*)((const uchar*)n + hdr->valueOffset);
+}
+
+inline
+SparseMat::Node* SparseMat::node(size_t nidx)
+{
+    return (Node*)(void*)&hdr->pool[nidx];
+}
+
+inline
+const SparseMat::Node* SparseMat::node(size_t nidx) const
+{
+    return (const Node*)(const void*)&hdr->pool[nidx];
+}
+
+inline
+SparseMatIterator SparseMat::begin()
+{
+    return SparseMatIterator(this);
+}
+
+inline
+SparseMatConstIterator SparseMat::begin() const
+{
+    return SparseMatConstIterator(this);
+}
+
+inline
+SparseMatIterator SparseMat::end()
+{
+    SparseMatIterator it(this);
+    it.seekEnd();
+    return it;
+}
+
+inline
+SparseMatConstIterator SparseMat::end() const
+{
+    SparseMatConstIterator it(this);
+    it.seekEnd();
+    return it;
+}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp> SparseMat::begin()
+{
+    return SparseMatIterator_<_Tp>(this);
+}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp> SparseMat::begin() const
+{
+    return SparseMatConstIterator_<_Tp>(this);
+}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp> SparseMat::end()
+{
+    SparseMatIterator_<_Tp> it(this);
+    it.seekEnd();
+    return it;
+}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp> SparseMat::end() const
+{
+    SparseMatConstIterator_<_Tp> it(this);
+    it.seekEnd();
+    return it;
+}
+
+
+
+///////////////////////////// SparseMat_ ////////////////////////////
+
+template<typename _Tp> inline
+SparseMat_<_Tp>::SparseMat_()
+{
+    flags = +MAGIC_VAL + traits::Type<_Tp>::value;
+}
+
+template<typename _Tp> inline
+SparseMat_<_Tp>::SparseMat_(int _dims, const int* _sizes)
+    : SparseMat(_dims, _sizes, traits::Type<_Tp>::value)
+{}
+
+template<typename _Tp> inline
+SparseMat_<_Tp>::SparseMat_(const SparseMat& m)
+{
+    if( m.type() == traits::Type<_Tp>::value )
+        *this = (const SparseMat_<_Tp>&)m;
+    else
+        m.convertTo(*this, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+SparseMat_<_Tp>::SparseMat_(const SparseMat_<_Tp>& m)
+{
+    this->flags = m.flags;
+    this->hdr = m.hdr;
+    if( this->hdr )
+        CV_XADD(&this->hdr->refcount, 1);
+}
+
+template<typename _Tp> inline
+SparseMat_<_Tp>::SparseMat_(const Mat& m)
+{
+    SparseMat sm(m);
+    *this = sm;
+}
+
+template<typename _Tp> inline
+SparseMat_<_Tp>& SparseMat_<_Tp>::operator = (const SparseMat_<_Tp>& m)
+{
+    if( this != &m )
+    {
+        if( m.hdr ) CV_XADD(&m.hdr->refcount, 1);
+        release();
+        flags = m.flags;
+        hdr = m.hdr;
+    }
+    return *this;
+}
+
+template<typename _Tp> inline
+SparseMat_<_Tp>& SparseMat_<_Tp>::operator = (const SparseMat& m)
+{
+    if( m.type() == traits::Type<_Tp>::value )
+        return (*this = (const SparseMat_<_Tp>&)m);
+    m.convertTo(*this, traits::Type<_Tp>::value);
+    return *this;
+}
+
+template<typename _Tp> inline
+SparseMat_<_Tp>& SparseMat_<_Tp>::operator = (const Mat& m)
+{
+    return (*this = SparseMat(m));
+}
+
+template<typename _Tp> inline
+SparseMat_<_Tp> SparseMat_<_Tp>::clone() const
+{
+    SparseMat_<_Tp> m;
+    this->copyTo(m);
+    return m;
+}
+
+template<typename _Tp> inline
+void SparseMat_<_Tp>::create(int _dims, const int* _sizes)
+{
+    SparseMat::create(_dims, _sizes, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+int SparseMat_<_Tp>::type() const
+{
+    return traits::Type<_Tp>::value;
+}
+
+template<typename _Tp> inline
+int SparseMat_<_Tp>::depth() const
+{
+    return traits::Depth<_Tp>::value;
+}
+
+template<typename _Tp> inline
+int SparseMat_<_Tp>::channels() const
+{
+    return DataType<_Tp>::channels;
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat_<_Tp>::ref(int i0, size_t* hashval)
+{
+    return SparseMat::ref<_Tp>(i0, hashval);
+}
+
+template<typename _Tp> inline
+_Tp SparseMat_<_Tp>::operator()(int i0, size_t* hashval) const
+{
+    return SparseMat::value<_Tp>(i0, hashval);
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat_<_Tp>::ref(int i0, int i1, size_t* hashval)
+{
+    return SparseMat::ref<_Tp>(i0, i1, hashval);
+}
+
+template<typename _Tp> inline
+_Tp SparseMat_<_Tp>::operator()(int i0, int i1, size_t* hashval) const
+{
+    return SparseMat::value<_Tp>(i0, i1, hashval);
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat_<_Tp>::ref(int i0, int i1, int i2, size_t* hashval)
+{
+    return SparseMat::ref<_Tp>(i0, i1, i2, hashval);
+}
+
+template<typename _Tp> inline
+_Tp SparseMat_<_Tp>::operator()(int i0, int i1, int i2, size_t* hashval) const
+{
+    return SparseMat::value<_Tp>(i0, i1, i2, hashval);
+}
+
+template<typename _Tp> inline
+_Tp& SparseMat_<_Tp>::ref(const int* idx, size_t* hashval)
+{
+    return SparseMat::ref<_Tp>(idx, hashval);
+}
+
+template<typename _Tp> inline
+_Tp SparseMat_<_Tp>::operator()(const int* idx, size_t* hashval) const
+{
+    return SparseMat::value<_Tp>(idx, hashval);
+}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp> SparseMat_<_Tp>::begin()
+{
+    return SparseMatIterator_<_Tp>(this);
+}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp> SparseMat_<_Tp>::begin() const
+{
+    return SparseMatConstIterator_<_Tp>(this);
+}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp> SparseMat_<_Tp>::end()
+{
+    SparseMatIterator_<_Tp> it(this);
+    it.seekEnd();
+    return it;
+}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp> SparseMat_<_Tp>::end() const
+{
+    SparseMatConstIterator_<_Tp> it(this);
+    it.seekEnd();
+    return it;
+}
+
+
+
+////////////////////////// MatConstIterator /////////////////////////
+
+inline
+MatConstIterator::MatConstIterator()
+    : m(0), elemSize(0), ptr(0), sliceStart(0), sliceEnd(0)
+{}
+
+inline
+MatConstIterator::MatConstIterator(const Mat* _m)
+    : m(_m), elemSize(_m->elemSize()), ptr(0), sliceStart(0), sliceEnd(0)
+{
+    if( m && m->isContinuous() )
+    {
+        CV_Assert(!m->empty());
+        sliceStart = m->ptr();
+        sliceEnd = sliceStart + m->total()*elemSize;
+    }
+    seek((const int*)0);
+}
+
+inline
+MatConstIterator::MatConstIterator(const Mat* _m, int _row, int _col)
+    : m(_m), elemSize(_m->elemSize()), ptr(0), sliceStart(0), sliceEnd(0)
+{
+    CV_Assert(m && m->dims <= 2);
+    if( m->isContinuous() )
+    {
+        CV_Assert(!m->empty());
+        sliceStart = m->ptr();
+        sliceEnd = sliceStart + m->total()*elemSize;
+    }
+    int idx[] = {_row, _col};
+    seek(idx);
+}
+
+inline
+MatConstIterator::MatConstIterator(const Mat* _m, Point _pt)
+    : m(_m), elemSize(_m->elemSize()), ptr(0), sliceStart(0), sliceEnd(0)
+{
+    CV_Assert(m && m->dims <= 2);
+    if( m->isContinuous() )
+    {
+        CV_Assert(!m->empty());
+        sliceStart = m->ptr();
+        sliceEnd = sliceStart + m->total()*elemSize;
+    }
+    int idx[] = {_pt.y, _pt.x};
+    seek(idx);
+}
+
+inline
+MatConstIterator::MatConstIterator(const MatConstIterator& it)
+    : m(it.m), elemSize(it.elemSize), ptr(it.ptr), sliceStart(it.sliceStart), sliceEnd(it.sliceEnd)
+{}
+
+inline
+MatConstIterator& MatConstIterator::operator = (const MatConstIterator& it )
+{
+    m = it.m; elemSize = it.elemSize; ptr = it.ptr;
+    sliceStart = it.sliceStart; sliceEnd = it.sliceEnd;
+    return *this;
+}
+
+inline
+const uchar* MatConstIterator::operator *() const
+{
+    return ptr;
+}
+
+inline MatConstIterator& MatConstIterator::operator += (ptrdiff_t ofs)
+{
+    if( !m || ofs == 0 )
+        return *this;
+    ptrdiff_t ofsb = ofs*elemSize;
+    ptr += ofsb;
+    if( ptr < sliceStart || sliceEnd <= ptr )
+    {
+        ptr -= ofsb;
+        seek(ofs, true);
+    }
+    return *this;
+}
+
+inline
+MatConstIterator& MatConstIterator::operator -= (ptrdiff_t ofs)
+{
+    return (*this += -ofs);
+}
+
+inline
+MatConstIterator& MatConstIterator::operator --()
+{
+    if( m && (ptr -= elemSize) < sliceStart )
+    {
+        ptr += elemSize;
+        seek(-1, true);
+    }
+    return *this;
+}
+
+inline
+MatConstIterator MatConstIterator::operator --(int)
+{
+    MatConstIterator b = *this;
+    *this += -1;
+    return b;
+}
+
+inline
+MatConstIterator& MatConstIterator::operator ++()
+{
+    if( m && (ptr += elemSize) >= sliceEnd )
+    {
+        ptr -= elemSize;
+        seek(1, true);
+    }
+    return *this;
+}
+
+inline MatConstIterator MatConstIterator::operator ++(int)
+{
+    MatConstIterator b = *this;
+    *this += 1;
+    return b;
+}
+
+
+static inline
+bool operator == (const MatConstIterator& a, const MatConstIterator& b)
+{
+    return a.m == b.m && a.ptr == b.ptr;
+}
+
+static inline
+bool operator != (const MatConstIterator& a, const MatConstIterator& b)
+{
+    return !(a == b);
+}
+
+static inline
+bool operator < (const MatConstIterator& a, const MatConstIterator& b)
+{
+    return a.ptr < b.ptr;
+}
+
+static inline
+bool operator > (const MatConstIterator& a, const MatConstIterator& b)
+{
+    return a.ptr > b.ptr;
+}
+
+static inline
+bool operator <= (const MatConstIterator& a, const MatConstIterator& b)
+{
+    return a.ptr <= b.ptr;
+}
+
+static inline
+bool operator >= (const MatConstIterator& a, const MatConstIterator& b)
+{
+    return a.ptr >= b.ptr;
+}
+
+static inline
+ptrdiff_t operator - (const MatConstIterator& b, const MatConstIterator& a)
+{
+    if( a.m != b.m )
+        return ((size_t)(-1) >> 1);
+    if( a.sliceEnd == b.sliceEnd )
+        return (b.ptr - a.ptr)/static_cast<ptrdiff_t>(b.elemSize);
+
+    return b.lpos() - a.lpos();
+}
+
+static inline
+MatConstIterator operator + (const MatConstIterator& a, ptrdiff_t ofs)
+{
+    MatConstIterator b = a;
+    return b += ofs;
+}
+
+static inline
+MatConstIterator operator + (ptrdiff_t ofs, const MatConstIterator& a)
+{
+    MatConstIterator b = a;
+    return b += ofs;
+}
+
+static inline
+MatConstIterator operator - (const MatConstIterator& a, ptrdiff_t ofs)
+{
+    MatConstIterator b = a;
+    return b += -ofs;
+}
+
+
+inline
+const uchar* MatConstIterator::operator [](ptrdiff_t i) const
+{
+    return *(*this + i);
+}
+
+
+
+///////////////////////// MatConstIterator_ /////////////////////////
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>::MatConstIterator_()
+{}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>::MatConstIterator_(const Mat_<_Tp>* _m)
+    : MatConstIterator(_m)
+{}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>::MatConstIterator_(const Mat_<_Tp>* _m, int _row, int _col)
+    : MatConstIterator(_m, _row, _col)
+{}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>::MatConstIterator_(const Mat_<_Tp>* _m, Point _pt)
+    : MatConstIterator(_m, _pt)
+{}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>::MatConstIterator_(const MatConstIterator_& it)
+    : MatConstIterator(it)
+{}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator = (const MatConstIterator_& it )
+{
+    MatConstIterator::operator = (it);
+    return *this;
+}
+
+template<typename _Tp> inline
+const _Tp& MatConstIterator_<_Tp>::operator *() const
+{
+    return *(_Tp*)(this->ptr);
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator += (ptrdiff_t ofs)
+{
+    MatConstIterator::operator += (ofs);
+    return *this;
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator -= (ptrdiff_t ofs)
+{
+    return (*this += -ofs);
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator --()
+{
+    MatConstIterator::operator --();
+    return *this;
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp> MatConstIterator_<_Tp>::operator --(int)
+{
+    MatConstIterator_ b = *this;
+    MatConstIterator::operator --();
+    return b;
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp>& MatConstIterator_<_Tp>::operator ++()
+{
+    MatConstIterator::operator ++();
+    return *this;
+}
+
+template<typename _Tp> inline
+MatConstIterator_<_Tp> MatConstIterator_<_Tp>::operator ++(int)
+{
+    MatConstIterator_ b = *this;
+    MatConstIterator::operator ++();
+    return b;
+}
+
+
+template<typename _Tp> inline
+Point MatConstIterator_<_Tp>::pos() const
+{
+    if( !m )
+        return Point();
+    CV_DbgAssert( m->dims <= 2 );
+    if( m->isContinuous() )
+    {
+        ptrdiff_t ofs = (const _Tp*)ptr - (const _Tp*)m->data;
+        int y = (int)(ofs / m->cols);
+        int x = (int)(ofs - (ptrdiff_t)y * m->cols);
+        return Point(x, y);
+    }
+    else
+    {
+        ptrdiff_t ofs = (uchar*)ptr - m->data;
+        int y = (int)(ofs / m->step);
+        int x = (int)((ofs - y * m->step)/sizeof(_Tp));
+        return Point(x, y);
+    }
+}
+
+
+template<typename _Tp> static inline
+bool operator == (const MatConstIterator_<_Tp>& a, const MatConstIterator_<_Tp>& b)
+{
+    return a.m == b.m && a.ptr == b.ptr;
+}
+
+template<typename _Tp> static inline
+bool operator != (const MatConstIterator_<_Tp>& a, const MatConstIterator_<_Tp>& b)
+{
+    return a.m != b.m || a.ptr != b.ptr;
+}
+
+template<typename _Tp> static inline
+MatConstIterator_<_Tp> operator + (const MatConstIterator_<_Tp>& a, ptrdiff_t ofs)
+{
+    MatConstIterator t = (const MatConstIterator&)a + ofs;
+    return (MatConstIterator_<_Tp>&)t;
+}
+
+template<typename _Tp> static inline
+MatConstIterator_<_Tp> operator + (ptrdiff_t ofs, const MatConstIterator_<_Tp>& a)
+{
+    MatConstIterator t = (const MatConstIterator&)a + ofs;
+    return (MatConstIterator_<_Tp>&)t;
+}
+
+template<typename _Tp> static inline
+MatConstIterator_<_Tp> operator - (const MatConstIterator_<_Tp>& a, ptrdiff_t ofs)
+{
+    MatConstIterator t = (const MatConstIterator&)a - ofs;
+    return (MatConstIterator_<_Tp>&)t;
+}
+
+template<typename _Tp> inline
+const _Tp& MatConstIterator_<_Tp>::operator [](ptrdiff_t i) const
+{
+    return *(_Tp*)MatConstIterator::operator [](i);
+}
+
+
+
+//////////////////////////// MatIterator_ ///////////////////////////
+
+template<typename _Tp> inline
+MatIterator_<_Tp>::MatIterator_()
+    : MatConstIterator_<_Tp>()
+{}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m)
+    : MatConstIterator_<_Tp>(_m)
+{}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, int _row, int _col)
+    : MatConstIterator_<_Tp>(_m, _row, _col)
+{}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, Point _pt)
+    : MatConstIterator_<_Tp>(_m, _pt)
+{}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>::MatIterator_(Mat_<_Tp>* _m, const int* _idx)
+    : MatConstIterator_<_Tp>(_m, _idx)
+{}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>::MatIterator_(const MatIterator_& it)
+    : MatConstIterator_<_Tp>(it)
+{}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>& MatIterator_<_Tp>::operator = (const MatIterator_<_Tp>& it )
+{
+    MatConstIterator::operator = (it);
+    return *this;
+}
+
+template<typename _Tp> inline
+_Tp& MatIterator_<_Tp>::operator *() const
+{
+    return *(_Tp*)(this->ptr);
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>& MatIterator_<_Tp>::operator += (ptrdiff_t ofs)
+{
+    MatConstIterator::operator += (ofs);
+    return *this;
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>& MatIterator_<_Tp>::operator -= (ptrdiff_t ofs)
+{
+    MatConstIterator::operator += (-ofs);
+    return *this;
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>& MatIterator_<_Tp>::operator --()
+{
+    MatConstIterator::operator --();
+    return *this;
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp> MatIterator_<_Tp>::operator --(int)
+{
+    MatIterator_ b = *this;
+    MatConstIterator::operator --();
+    return b;
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp>& MatIterator_<_Tp>::operator ++()
+{
+    MatConstIterator::operator ++();
+    return *this;
+}
+
+template<typename _Tp> inline
+MatIterator_<_Tp> MatIterator_<_Tp>::operator ++(int)
+{
+    MatIterator_ b = *this;
+    MatConstIterator::operator ++();
+    return b;
+}
+
+template<typename _Tp> inline
+_Tp& MatIterator_<_Tp>::operator [](ptrdiff_t i) const
+{
+    return *(*this + i);
+}
+
+
+template<typename _Tp> static inline
+bool operator == (const MatIterator_<_Tp>& a, const MatIterator_<_Tp>& b)
+{
+    return a.m == b.m && a.ptr == b.ptr;
+}
+
+template<typename _Tp> static inline
+bool operator != (const MatIterator_<_Tp>& a, const MatIterator_<_Tp>& b)
+{
+    return a.m != b.m || a.ptr != b.ptr;
+}
+
+template<typename _Tp> static inline
+MatIterator_<_Tp> operator + (const MatIterator_<_Tp>& a, ptrdiff_t ofs)
+{
+    MatConstIterator t = (const MatConstIterator&)a + ofs;
+    return (MatIterator_<_Tp>&)t;
+}
+
+template<typename _Tp> static inline
+MatIterator_<_Tp> operator + (ptrdiff_t ofs, const MatIterator_<_Tp>& a)
+{
+    MatConstIterator t = (const MatConstIterator&)a + ofs;
+    return (MatIterator_<_Tp>&)t;
+}
+
+template<typename _Tp> static inline
+MatIterator_<_Tp> operator - (const MatIterator_<_Tp>& a, ptrdiff_t ofs)
+{
+    MatConstIterator t = (const MatConstIterator&)a - ofs;
+    return (MatIterator_<_Tp>&)t;
+}
+
+
+
+/////////////////////// SparseMatConstIterator //////////////////////
+
+inline
+SparseMatConstIterator::SparseMatConstIterator()
+    : m(0), hashidx(0), ptr(0)
+{}
+
+inline
+SparseMatConstIterator::SparseMatConstIterator(const SparseMatConstIterator& it)
+    : m(it.m), hashidx(it.hashidx), ptr(it.ptr)
+{}
+
+inline SparseMatConstIterator& SparseMatConstIterator::operator = (const SparseMatConstIterator& it)
+{
+    if( this != &it )
+    {
+        m = it.m;
+        hashidx = it.hashidx;
+        ptr = it.ptr;
+    }
+    return *this;
+}
+
+template<typename _Tp> inline
+const _Tp& SparseMatConstIterator::value() const
+{
+    return *(const _Tp*)ptr;
+}
+
+inline
+const SparseMat::Node* SparseMatConstIterator::node() const
+{
+    return (ptr && m && m->hdr) ? (const SparseMat::Node*)(const void*)(ptr - m->hdr->valueOffset) : 0;
+}
+
+inline
+SparseMatConstIterator SparseMatConstIterator::operator ++(int)
+{
+    SparseMatConstIterator it = *this;
+    ++*this;
+    return it;
+}
+
+inline
+void SparseMatConstIterator::seekEnd()
+{
+    if( m && m->hdr )
+    {
+        hashidx = m->hdr->hashtab.size();
+        ptr = 0;
+    }
+}
+
+
+static inline
+bool operator == (const SparseMatConstIterator& it1, const SparseMatConstIterator& it2)
+{
+    return it1.m == it2.m && it1.ptr == it2.ptr;
+}
+
+static inline
+bool operator != (const SparseMatConstIterator& it1, const SparseMatConstIterator& it2)
+{
+    return !(it1 == it2);
+}
+
+
+
+///////////////////////// SparseMatIterator /////////////////////////
+
+inline
+SparseMatIterator::SparseMatIterator()
+{}
+
+inline
+SparseMatIterator::SparseMatIterator(SparseMat* _m)
+    : SparseMatConstIterator(_m)
+{}
+
+inline
+SparseMatIterator::SparseMatIterator(const SparseMatIterator& it)
+    : SparseMatConstIterator(it)
+{}
+
+inline
+SparseMatIterator& SparseMatIterator::operator = (const SparseMatIterator& it)
+{
+    (SparseMatConstIterator&)*this = it;
+    return *this;
+}
+
+template<typename _Tp> inline
+_Tp& SparseMatIterator::value() const
+{
+    return *(_Tp*)ptr;
+}
+
+inline
+SparseMat::Node* SparseMatIterator::node() const
+{
+    return (SparseMat::Node*)SparseMatConstIterator::node();
+}
+
+inline
+SparseMatIterator& SparseMatIterator::operator ++()
+{
+    SparseMatConstIterator::operator ++();
+    return *this;
+}
+
+inline
+SparseMatIterator SparseMatIterator::operator ++(int)
+{
+    SparseMatIterator it = *this;
+    ++*this;
+    return it;
+}
+
+
+
+////////////////////// SparseMatConstIterator_ //////////////////////
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp>::SparseMatConstIterator_()
+{}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp>::SparseMatConstIterator_(const SparseMat_<_Tp>* _m)
+    : SparseMatConstIterator(_m)
+{}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp>::SparseMatConstIterator_(const SparseMat* _m)
+    : SparseMatConstIterator(_m)
+{
+    CV_Assert( _m->type() == traits::Type<_Tp>::value );
+}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp>::SparseMatConstIterator_(const SparseMatConstIterator_<_Tp>& it)
+    : SparseMatConstIterator(it)
+{}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp>& SparseMatConstIterator_<_Tp>::operator = (const SparseMatConstIterator_<_Tp>& it)
+{
+    return reinterpret_cast<SparseMatConstIterator_<_Tp>&>
+         (*reinterpret_cast<SparseMatConstIterator*>(this) =
+           reinterpret_cast<const SparseMatConstIterator&>(it));
+}
+
+template<typename _Tp> inline
+const _Tp& SparseMatConstIterator_<_Tp>::operator *() const
+{
+    return *(const _Tp*)this->ptr;
+}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp>& SparseMatConstIterator_<_Tp>::operator ++()
+{
+    SparseMatConstIterator::operator ++();
+    return *this;
+}
+
+template<typename _Tp> inline
+SparseMatConstIterator_<_Tp> SparseMatConstIterator_<_Tp>::operator ++(int)
+{
+    SparseMatConstIterator_<_Tp> it = *this;
+    SparseMatConstIterator::operator ++();
+    return it;
+}
+
+
+
+///////////////////////// SparseMatIterator_ ////////////////////////
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp>::SparseMatIterator_()
+{}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp>::SparseMatIterator_(SparseMat_<_Tp>* _m)
+    : SparseMatConstIterator_<_Tp>(_m)
+{}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp>::SparseMatIterator_(SparseMat* _m)
+    : SparseMatConstIterator_<_Tp>(_m)
+{}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp>::SparseMatIterator_(const SparseMatIterator_<_Tp>& it)
+    : SparseMatConstIterator_<_Tp>(it)
+{}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp>& SparseMatIterator_<_Tp>::operator = (const SparseMatIterator_<_Tp>& it)
+{
+    return reinterpret_cast<SparseMatIterator_<_Tp>&>
+         (*reinterpret_cast<SparseMatConstIterator*>(this) =
+           reinterpret_cast<const SparseMatConstIterator&>(it));
+}
+
+template<typename _Tp> inline
+_Tp& SparseMatIterator_<_Tp>::operator *() const
+{
+    return *(_Tp*)this->ptr;
+}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp>& SparseMatIterator_<_Tp>::operator ++()
+{
+    SparseMatConstIterator::operator ++();
+    return *this;
+}
+
+template<typename _Tp> inline
+SparseMatIterator_<_Tp> SparseMatIterator_<_Tp>::operator ++(int)
+{
+    SparseMatIterator_<_Tp> it = *this;
+    SparseMatConstIterator::operator ++();
+    return it;
+}
+
+
+
+//////////////////////// MatCommaInitializer_ ///////////////////////
+
+template<typename _Tp> inline
+MatCommaInitializer_<_Tp>::MatCommaInitializer_(Mat_<_Tp>* _m)
+    : it(_m)
+{}
+
+template<typename _Tp> template<typename T2> inline
+MatCommaInitializer_<_Tp>& MatCommaInitializer_<_Tp>::operator , (T2 v)
+{
+    CV_DbgAssert( this->it < ((const Mat_<_Tp>*)this->it.m)->end() );
+    *this->it = _Tp(v);
+    ++this->it;
+    return *this;
+}
+
+template<typename _Tp> inline
+MatCommaInitializer_<_Tp>::operator Mat_<_Tp>() const
+{
+    CV_DbgAssert( this->it == ((const Mat_<_Tp>*)this->it.m)->end() );
+    return Mat_<_Tp>(*this->it.m);
+}
+
+
+template<typename _Tp, typename T2> static inline
+MatCommaInitializer_<_Tp> operator << (const Mat_<_Tp>& m, T2 val)
+{
+    MatCommaInitializer_<_Tp> commaInitializer((Mat_<_Tp>*)&m);
+    return (commaInitializer, val);
+}
+
+
+
+///////////////////////// Matrix Expressions ////////////////////////
+
+inline
+Mat& Mat::operator = (const MatExpr& e)
+{
+    e.op->assign(e, *this);
+    return *this;
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>::Mat_(const MatExpr& e)
+{
+    e.op->assign(e, *this, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+Mat_<_Tp>& Mat_<_Tp>::operator = (const MatExpr& e)
+{
+    e.op->assign(e, *this, traits::Type<_Tp>::value);
+    return *this;
+}
+
+template<typename _Tp> inline
+MatExpr Mat_<_Tp>::zeros(int rows, int cols)
+{
+    return Mat::zeros(rows, cols, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+MatExpr Mat_<_Tp>::zeros(Size sz)
+{
+    return Mat::zeros(sz, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+MatExpr Mat_<_Tp>::ones(int rows, int cols)
+{
+    return Mat::ones(rows, cols, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+MatExpr Mat_<_Tp>::ones(Size sz)
+{
+    return Mat::ones(sz, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+MatExpr Mat_<_Tp>::eye(int rows, int cols)
+{
+    return Mat::eye(rows, cols, traits::Type<_Tp>::value);
+}
+
+template<typename _Tp> inline
+MatExpr Mat_<_Tp>::eye(Size sz)
+{
+    return Mat::eye(sz, traits::Type<_Tp>::value);
+}
+
+inline
+MatExpr::MatExpr()
+    : op(0), flags(0), a(Mat()), b(Mat()), c(Mat()), alpha(0), beta(0), s()
+{}
+
+inline
+MatExpr::MatExpr(const MatOp* _op, int _flags, const Mat& _a, const Mat& _b,
+                 const Mat& _c, double _alpha, double _beta, const Scalar& _s)
+    : op(_op), flags(_flags), a(_a), b(_b), c(_c), alpha(_alpha), beta(_beta), s(_s)
+{}
+
+inline
+MatExpr::operator Mat() const
+{
+    Mat m;
+    op->assign(*this, m);
+    return m;
+}
+
+template<typename _Tp> inline
+MatExpr::operator Mat_<_Tp>() const
+{
+    Mat_<_Tp> m;
+    op->assign(*this, m, traits::Type<_Tp>::value);
+    return m;
+}
+
+
+template<typename _Tp> static inline
+MatExpr min(const Mat_<_Tp>& a, const Mat_<_Tp>& b)
+{
+    return cv::min((const Mat&)a, (const Mat&)b);
+}
+
+template<typename _Tp> static inline
+MatExpr min(const Mat_<_Tp>& a, double s)
+{
+    return cv::min((const Mat&)a, s);
+}
+
+template<typename _Tp> static inline
+MatExpr min(double s, const Mat_<_Tp>& a)
+{
+    return cv::min((const Mat&)a, s);
+}
+
+template<typename _Tp> static inline
+MatExpr max(const Mat_<_Tp>& a, const Mat_<_Tp>& b)
+{
+    return cv::max((const Mat&)a, (const Mat&)b);
+}
+
+template<typename _Tp> static inline
+MatExpr max(const Mat_<_Tp>& a, double s)
+{
+    return cv::max((const Mat&)a, s);
+}
+
+template<typename _Tp> static inline
+MatExpr max(double s, const Mat_<_Tp>& a)
+{
+    return cv::max((const Mat&)a, s);
+}
+
+template<typename _Tp> static inline
+MatExpr abs(const Mat_<_Tp>& m)
+{
+    return cv::abs((const Mat&)m);
+}
+
+
+static inline
+Mat& operator += (Mat& a, const MatExpr& b)
+{
+    b.op->augAssignAdd(b, a);
+    return a;
+}
+
+static inline
+const Mat& operator += (const Mat& a, const MatExpr& b)
+{
+    b.op->augAssignAdd(b, (Mat&)a);
+    return a;
+}
+
+template<typename _Tp> static inline
+Mat_<_Tp>& operator += (Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignAdd(b, a);
+    return a;
+}
+
+template<typename _Tp> static inline
+const Mat_<_Tp>& operator += (const Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignAdd(b, (Mat&)a);
+    return a;
+}
+
+static inline
+Mat& operator -= (Mat& a, const MatExpr& b)
+{
+    b.op->augAssignSubtract(b, a);
+    return a;
+}
+
+static inline
+const Mat& operator -= (const Mat& a, const MatExpr& b)
+{
+    b.op->augAssignSubtract(b, (Mat&)a);
+    return a;
+}
+
+template<typename _Tp> static inline
+Mat_<_Tp>& operator -= (Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignSubtract(b, a);
+    return a;
+}
+
+template<typename _Tp> static inline
+const Mat_<_Tp>& operator -= (const Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignSubtract(b, (Mat&)a);
+    return a;
+}
+
+static inline
+Mat& operator *= (Mat& a, const MatExpr& b)
+{
+    b.op->augAssignMultiply(b, a);
+    return a;
+}
+
+static inline
+const Mat& operator *= (const Mat& a, const MatExpr& b)
+{
+    b.op->augAssignMultiply(b, (Mat&)a);
+    return a;
+}
+
+template<typename _Tp> static inline
+Mat_<_Tp>& operator *= (Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignMultiply(b, a);
+    return a;
+}
+
+template<typename _Tp> static inline
+const Mat_<_Tp>& operator *= (const Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignMultiply(b, (Mat&)a);
+    return a;
+}
+
+static inline
+Mat& operator /= (Mat& a, const MatExpr& b)
+{
+    b.op->augAssignDivide(b, a);
+    return a;
+}
+
+static inline
+const Mat& operator /= (const Mat& a, const MatExpr& b)
+{
+    b.op->augAssignDivide(b, (Mat&)a);
+    return a;
+}
+
+template<typename _Tp> static inline
+Mat_<_Tp>& operator /= (Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignDivide(b, a);
+    return a;
+}
+
+template<typename _Tp> static inline
+const Mat_<_Tp>& operator /= (const Mat_<_Tp>& a, const MatExpr& b)
+{
+    b.op->augAssignDivide(b, (Mat&)a);
+    return a;
+}
+
+
+//////////////////////////////// UMat ////////////////////////////////
+
+template<typename _Tp> inline
+UMat::UMat(const std::vector<_Tp>& vec, bool copyData)
+: flags(+MAGIC_VAL + traits::Type<_Tp>::value + CV_MAT_CONT_FLAG), dims(2), rows((int)vec.size()),
+cols(1), allocator(0), usageFlags(USAGE_DEFAULT), u(0), offset(0), size(&rows)
+{
+    if(vec.empty())
+        return;
+    if( !copyData )
+    {
+        // !!!TODO!!!
+        CV_Error(Error::StsNotImplemented, "");
+    }
+    else
+        Mat((int)vec.size(), 1, traits::Type<_Tp>::value, (uchar*)&vec[0]).copyTo(*this);
+}
+
+inline
+UMat UMat::row(int y) const
+{
+    return UMat(*this, Range(y, y + 1), Range::all());
+}
+
+inline
+UMat UMat::col(int x) const
+{
+    return UMat(*this, Range::all(), Range(x, x + 1));
+}
+
+inline
+UMat UMat::rowRange(int startrow, int endrow) const
+{
+    return UMat(*this, Range(startrow, endrow), Range::all());
+}
+
+inline
+UMat UMat::rowRange(const Range& r) const
+{
+    return UMat(*this, r, Range::all());
+}
+
+inline
+UMat UMat::colRange(int startcol, int endcol) const
+{
+    return UMat(*this, Range::all(), Range(startcol, endcol));
+}
+
+inline
+UMat UMat::colRange(const Range& r) const
+{
+    return UMat(*this, Range::all(), r);
+}
+
+inline
+UMat UMat::operator()( Range _rowRange, Range _colRange ) const
+{
+    return UMat(*this, _rowRange, _colRange);
+}
+
+inline
+UMat UMat::operator()( const Rect& roi ) const
+{
+    return UMat(*this, roi);
+}
+
+inline
+UMat UMat::operator()(const Range* ranges) const
+{
+    return UMat(*this, ranges);
+}
+
+inline
+UMat UMat::operator()(const std::vector<Range>& ranges) const
+{
+    return UMat(*this, ranges);
+}
+
+inline
+bool UMat::isContinuous() const
+{
+    return (flags & CONTINUOUS_FLAG) != 0;
+}
+
+inline
+bool UMat::isSubmatrix() const
+{
+    return (flags & SUBMATRIX_FLAG) != 0;
+}
+
+inline
+size_t UMat::elemSize() const
+{
+    size_t res = dims > 0 ? step.p[dims - 1] : 0;
+    CV_DbgAssert(res != 0);
+    return res;
+}
+
+inline
+size_t UMat::elemSize1() const
+{
+    return CV_ELEM_SIZE1(flags);
+}
+
+inline
+int UMat::type() const
+{
+    return CV_MAT_TYPE(flags);
+}
+
+inline
+int UMat::depth() const
+{
+    return CV_MAT_DEPTH(flags);
+}
+
+inline
+int UMat::channels() const
+{
+    return CV_MAT_CN(flags);
+}
+
+inline
+size_t UMat::step1(int i) const
+{
+    return step.p[i] / elemSize1();
+}
+
+
+inline bool UMatData::hostCopyObsolete() const { return (flags & HOST_COPY_OBSOLETE) != 0; }
+inline bool UMatData::deviceCopyObsolete() const { return (flags & DEVICE_COPY_OBSOLETE) != 0; }
+inline bool UMatData::deviceMemMapped() const { return (flags & DEVICE_MEM_MAPPED) != 0; }
+inline bool UMatData::copyOnMap() const { return (flags & COPY_ON_MAP) != 0; }
+inline bool UMatData::tempUMat() const { return (flags & TEMP_UMAT) != 0; }
+inline bool UMatData::tempCopiedUMat() const { return (flags & TEMP_COPIED_UMAT) == TEMP_COPIED_UMAT; }
+
+inline void UMatData::markDeviceMemMapped(bool flag)
+{
+  if(flag)
+    flags |= DEVICE_MEM_MAPPED;
+  else
+    flags &= ~DEVICE_MEM_MAPPED;
+}
+
+inline void UMatData::markHostCopyObsolete(bool flag)
+{
+    if(flag)
+        flags |= HOST_COPY_OBSOLETE;
+    else
+        flags &= ~HOST_COPY_OBSOLETE;
+}
+inline void UMatData::markDeviceCopyObsolete(bool flag)
+{
+    if(flag)
+        flags |= DEVICE_COPY_OBSOLETE;
+    else
+        flags &= ~DEVICE_COPY_OBSOLETE;
+}
+
+//! @endcond
+
+static inline
+void swap(MatExpr& a, MatExpr& b) { a.swap(b); }
+
+} //cv
+
+#ifdef _MSC_VER
+#pragma warning( pop )
+#endif
+
+#ifdef CV_DISABLE_CLANG_ENUM_WARNINGS
+#undef CV_DISABLE_CLANG_ENUM_WARNINGS
+#pragma clang diagnostic pop
+#endif
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/matx.hpp

@@ -0,0 +1,544 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_MATX_HPP
+#define OPENCV_CORE_MATX_HPP
+
+#ifndef __cplusplus
+#  error matx.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/core/cvdef.h"
+#include "opencv2/core/base.hpp"
+#include "opencv2/core/traits.hpp"
+#include "opencv2/core/saturate.hpp"
+
+#include <initializer_list>
+
+namespace cv
+{
+
+//! @addtogroup core_basic
+//! @{
+
+//! @cond IGNORED
+// FIXIT Remove this (especially CV_EXPORTS modifier)
+struct CV_EXPORTS Matx_AddOp { Matx_AddOp() {} Matx_AddOp(const Matx_AddOp&) {} };
+struct CV_EXPORTS Matx_SubOp { Matx_SubOp() {} Matx_SubOp(const Matx_SubOp&) {} };
+struct CV_EXPORTS Matx_ScaleOp { Matx_ScaleOp() {} Matx_ScaleOp(const Matx_ScaleOp&) {} };
+struct CV_EXPORTS Matx_MulOp { Matx_MulOp() {} Matx_MulOp(const Matx_MulOp&) {} };
+struct CV_EXPORTS Matx_DivOp { Matx_DivOp() {} Matx_DivOp(const Matx_DivOp&) {} };
+struct CV_EXPORTS Matx_MatMulOp { Matx_MatMulOp() {} Matx_MatMulOp(const Matx_MatMulOp&) {} };
+struct CV_EXPORTS Matx_TOp { Matx_TOp() {} Matx_TOp(const Matx_TOp&) {} };
+//! @endcond
+
+////////////////////////////// Small Matrix ///////////////////////////
+
+/** @brief Template class for small matrices whose type and size are known at compilation time
+
+If you need a more flexible type, use Mat . The elements of the matrix M are accessible using the
+M(i,j) notation. Most of the common matrix operations (see also @ref MatrixExpressions ) are
+available. To do an operation on Matx that is not implemented, you can easily convert the matrix to
+Mat and backwards:
+@code{.cpp}
+    Matx33f m(1, 2, 3,
+              4, 5, 6,
+              7, 8, 9);
+    cout << sum(Mat(m*m.t())) << endl;
+@endcode
+Except of the plain constructor which takes a list of elements, Matx can be initialized from a C-array:
+@code{.cpp}
+    float values[] = { 1, 2, 3};
+    Matx31f m(values);
+@endcode
+In case if C++11 features are available, std::initializer_list can be also used to initialize Matx:
+@code{.cpp}
+    Matx31f m = { 1, 2, 3};
+@endcode
+ */
+template<typename _Tp, int m, int n> class Matx
+{
+public:
+    enum {
+           rows     = m,
+           cols     = n,
+           channels = rows*cols,
+#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED
+           depth    = traits::Type<_Tp>::value,
+           type     = CV_MAKETYPE(depth, channels),
+#endif
+           shortdim = (m < n ? m : n)
+         };
+
+    typedef _Tp                           value_type;
+    typedef Matx<_Tp, m, n>               mat_type;
+    typedef Matx<_Tp, shortdim, 1> diag_type;
+
+    //! default constructor
+    Matx();
+
+    explicit Matx(_Tp v0); //!< 1x1 matrix
+    Matx(_Tp v0, _Tp v1); //!< 1x2 or 2x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2); //!< 1x3 or 3x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3); //!< 1x4, 2x2 or 4x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4); //!< 1x5 or 5x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5); //!< 1x6, 2x3, 3x2 or 6x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6); //!< 1x7 or 7x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7); //!< 1x8, 2x4, 4x2 or 8x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8); //!< 1x9, 3x3 or 9x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9); //!< 1x10, 2x5 or 5x2 or 10x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
+         _Tp v4, _Tp v5, _Tp v6, _Tp v7,
+         _Tp v8, _Tp v9, _Tp v10, _Tp v11); //!< 1x12, 2x6, 3x4, 4x3, 6x2 or 12x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
+         _Tp v4, _Tp v5, _Tp v6, _Tp v7,
+         _Tp v8, _Tp v9, _Tp v10, _Tp v11,
+         _Tp v12, _Tp v13); //!< 1x14, 2x7, 7x2 or 14x1 matrix
+    Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3,
+         _Tp v4, _Tp v5, _Tp v6, _Tp v7,
+         _Tp v8, _Tp v9, _Tp v10, _Tp v11,
+         _Tp v12, _Tp v13, _Tp v14, _Tp v15); //!< 1x16, 4x4 or 16x1 matrix
+    explicit Matx(const _Tp* vals); //!< initialize from a plain array
+
+    Matx(std::initializer_list<_Tp>); //!< initialize from an initializer list
+
+    CV_NODISCARD_STD static Matx all(_Tp alpha);
+    CV_NODISCARD_STD static Matx zeros();
+    CV_NODISCARD_STD static Matx ones();
+    CV_NODISCARD_STD static Matx eye();
+    CV_NODISCARD_STD static Matx diag(const diag_type& d);
+    /** @brief Generates uniformly distributed random numbers
+    @param a Range boundary.
+    @param b The other range boundary (boundaries don't have to be ordered, the lower boundary is inclusive,
+    the upper one is exclusive).
+     */
+    CV_NODISCARD_STD static Matx randu(_Tp a, _Tp b);
+    /** @brief Generates normally distributed random numbers
+    @param a Mean value.
+    @param b Standard deviation.
+     */
+    CV_NODISCARD_STD static Matx randn(_Tp a, _Tp b);
+
+    //! dot product computed with the default precision
+    _Tp dot(const Matx<_Tp, m, n>& v) const;
+
+    //! dot product computed in double-precision arithmetics
+    double ddot(const Matx<_Tp, m, n>& v) const;
+
+    //! conversion to another data type
+    template<typename T2> operator Matx<T2, m, n>() const;
+
+    //! change the matrix shape
+    template<int m1, int n1> Matx<_Tp, m1, n1> reshape() const;
+
+    //! extract part of the matrix
+    template<int m1, int n1> Matx<_Tp, m1, n1> get_minor(int base_row, int base_col) const;
+
+    //! extract the matrix row
+    Matx<_Tp, 1, n> row(int i) const;
+
+    //! extract the matrix column
+    Matx<_Tp, m, 1> col(int i) const;
+
+    //! extract the matrix diagonal
+    diag_type diag() const;
+
+    //! transpose the matrix
+    Matx<_Tp, n, m> t() const;
+
+    //! invert the matrix
+    Matx<_Tp, n, m> inv(int method=DECOMP_LU, bool *p_is_ok = NULL) const;
+
+    //! solve linear system
+    template<int l> Matx<_Tp, n, l> solve(const Matx<_Tp, m, l>& rhs, int flags=DECOMP_LU) const;
+    Vec<_Tp, n> solve(const Vec<_Tp, m>& rhs, int method) const;
+
+    //! multiply two matrices element-wise
+    Matx<_Tp, m, n> mul(const Matx<_Tp, m, n>& a) const;
+
+    //! divide two matrices element-wise
+    Matx<_Tp, m, n> div(const Matx<_Tp, m, n>& a) const;
+
+    //! element access
+    const _Tp& operator ()(int row, int col) const;
+    _Tp& operator ()(int row, int col);
+
+    //! 1D element access
+    const _Tp& operator ()(int i) const;
+    _Tp& operator ()(int i);
+
+    Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_AddOp);
+    Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_SubOp);
+    template<typename _T2> Matx(const Matx<_Tp, m, n>& a, _T2 alpha, Matx_ScaleOp);
+    Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_MulOp);
+    Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_DivOp);
+    template<int l> Matx(const Matx<_Tp, m, l>& a, const Matx<_Tp, l, n>& b, Matx_MatMulOp);
+    Matx(const Matx<_Tp, n, m>& a, Matx_TOp);
+
+    _Tp val[m*n]; ///< matrix elements
+};
+
+typedef Matx<float, 1, 2> Matx12f;
+typedef Matx<double, 1, 2> Matx12d;
+typedef Matx<float, 1, 3> Matx13f;
+typedef Matx<double, 1, 3> Matx13d;
+typedef Matx<float, 1, 4> Matx14f;
+typedef Matx<double, 1, 4> Matx14d;
+typedef Matx<float, 1, 6> Matx16f;
+typedef Matx<double, 1, 6> Matx16d;
+
+typedef Matx<float, 2, 1> Matx21f;
+typedef Matx<double, 2, 1> Matx21d;
+typedef Matx<float, 3, 1> Matx31f;
+typedef Matx<double, 3, 1> Matx31d;
+typedef Matx<float, 4, 1> Matx41f;
+typedef Matx<double, 4, 1> Matx41d;
+typedef Matx<float, 6, 1> Matx61f;
+typedef Matx<double, 6, 1> Matx61d;
+
+typedef Matx<float, 2, 2> Matx22f;
+typedef Matx<double, 2, 2> Matx22d;
+typedef Matx<float, 2, 3> Matx23f;
+typedef Matx<double, 2, 3> Matx23d;
+typedef Matx<float, 3, 2> Matx32f;
+typedef Matx<double, 3, 2> Matx32d;
+
+typedef Matx<float, 3, 3> Matx33f;
+typedef Matx<double, 3, 3> Matx33d;
+
+typedef Matx<float, 3, 4> Matx34f;
+typedef Matx<double, 3, 4> Matx34d;
+typedef Matx<float, 4, 3> Matx43f;
+typedef Matx<double, 4, 3> Matx43d;
+
+typedef Matx<float, 4, 4> Matx44f;
+typedef Matx<double, 4, 4> Matx44d;
+typedef Matx<float, 6, 6> Matx66f;
+typedef Matx<double, 6, 6> Matx66d;
+
+template<typename _Tp, int m> static inline
+double determinant(const Matx<_Tp, m, m>& a);
+
+template<typename _Tp, int m, int n> static inline
+double trace(const Matx<_Tp, m, n>& a);
+
+template<typename _Tp, int m, int n> static inline
+double norm(const Matx<_Tp, m, n>& M);
+
+template<typename _Tp, int m, int n> static inline
+double norm(const Matx<_Tp, m, n>& M, int normType);
+
+template<typename _Tp1, typename _Tp2, int m, int n> static inline
+Matx<_Tp1, m, n>& operator += (Matx<_Tp1, m, n>& a, const Matx<_Tp2, m, n>& b);
+
+template<typename _Tp1, typename _Tp2, int m, int n> static inline
+Matx<_Tp1, m, n>& operator -= (Matx<_Tp1, m, n>& a, const Matx<_Tp2, m, n>& b);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator + (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator - (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, int alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, float alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, double alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, int alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, float alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, double alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (int alpha, const Matx<_Tp, m, n>& a);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (float alpha, const Matx<_Tp, m, n>& a);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (double alpha, const Matx<_Tp, m, n>& a);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator /= (Matx<_Tp, m, n>& a, float alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator /= (Matx<_Tp, m, n>& a, double alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator / (const Matx<_Tp, m, n>& a, float alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator / (const Matx<_Tp, m, n>& a, double alpha);
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator - (const Matx<_Tp, m, n>& a);
+
+template<typename _Tp, int m, int n, int l> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, l>& a, const Matx<_Tp, l, n>& b);
+
+template<typename _Tp, int m, int n> static inline
+Vec<_Tp, m> operator * (const Matx<_Tp, m, n>& a, const Vec<_Tp, n>& b);
+
+template<typename _Tp, int m, int n> static inline
+bool operator == (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b);
+
+template<typename _Tp, int m, int n> static inline
+bool operator != (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b);
+
+
+/////////////////////// Vec (used as element of multi-channel images /////////////////////
+
+/** @brief Template class for short numerical vectors, a partial case of Matx
+
+This template class represents short numerical vectors (of 1, 2, 3, 4 ... elements) on which you
+can perform basic arithmetical operations, access individual elements using [] operator etc. The
+vectors are allocated on stack, as opposite to std::valarray, std::vector, cv::Mat etc., which
+elements are dynamically allocated in the heap.
+
+The template takes 2 parameters:
+@tparam _Tp element type
+@tparam cn the number of elements
+
+In addition to the universal notation like Vec<float, 3>, you can use shorter aliases
+for the most popular specialized variants of Vec, e.g. Vec3f ~ Vec<float, 3>.
+
+It is possible to convert Vec\<T,2\> to/from Point_, Vec\<T,3\> to/from Point3_ , and Vec\<T,4\>
+to CvScalar or Scalar_. Use operator[] to access the elements of Vec.
+
+All the expected vector operations are also implemented:
+-   v1 = v2 + v3
+-   v1 = v2 - v3
+-   v1 = v2 \* scale
+-   v1 = scale \* v2
+-   v1 = -v2
+-   v1 += v2 and other augmenting operations
+-   v1 == v2, v1 != v2
+-   norm(v1) (euclidean norm)
+The Vec class is commonly used to describe pixel types of multi-channel arrays. See Mat for details.
+*/
+template<typename _Tp, int cn> class Vec : public Matx<_Tp, cn, 1>
+{
+public:
+    typedef _Tp value_type;
+    enum {
+           channels = cn,
+#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED
+           depth    = Matx<_Tp, cn, 1>::depth,
+           type     = CV_MAKETYPE(depth, channels),
+#endif
+           _dummy_enum_finalizer = 0
+         };
+
+    //! default constructor
+    Vec();
+
+    Vec(_Tp v0); //!< 1-element vector constructor
+    Vec(_Tp v0, _Tp v1); //!< 2-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2); //!< 3-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3); //!< 4-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4); //!< 5-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5); //!< 6-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6); //!< 7-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7); //!< 8-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8); //!< 9-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9); //!< 10-element vector constructor
+    Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13); //!< 14-element vector constructor
+    explicit Vec(const _Tp* values);
+
+    Vec(std::initializer_list<_Tp>);
+
+    Vec(const Vec<_Tp, cn>& v);
+
+    static Vec all(_Tp alpha);
+    static Vec ones();
+    static Vec randn(_Tp a, _Tp b);
+    static Vec randu(_Tp a, _Tp b);
+    static Vec zeros();
+    static Vec diag(_Tp alpha) = delete;
+    static Vec eye() = delete;
+
+    //! per-element multiplication
+    Vec mul(const Vec<_Tp, cn>& v) const;
+
+    //! conjugation (makes sense for complex numbers and quaternions)
+    Vec conj() const;
+
+    /*!
+      cross product of the two 3D vectors.
+
+      For other dimensionalities the exception is raised
+    */
+    Vec cross(const Vec& v) const;
+    //! conversion to another data type
+    template<typename T2> operator Vec<T2, cn>() const;
+
+    /*! element access */
+    const _Tp& operator [](int i) const;
+    _Tp& operator[](int i);
+    const _Tp& operator ()(int i) const;
+    _Tp& operator ()(int i);
+
+    Vec<_Tp, cn>& operator=(const Vec<_Tp, cn>& rhs) = default;
+
+    Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_AddOp);
+    Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_SubOp);
+    template<typename _T2> Vec(const Matx<_Tp, cn, 1>& a, _T2 alpha, Matx_ScaleOp);
+};
+
+/** @name Shorter aliases for the most popular specializations of Vec<T,n>
+  @{
+*/
+typedef Vec<uchar, 2> Vec2b;
+typedef Vec<uchar, 3> Vec3b;
+typedef Vec<uchar, 4> Vec4b;
+
+typedef Vec<short, 2> Vec2s;
+typedef Vec<short, 3> Vec3s;
+typedef Vec<short, 4> Vec4s;
+
+typedef Vec<ushort, 2> Vec2w;
+typedef Vec<ushort, 3> Vec3w;
+typedef Vec<ushort, 4> Vec4w;
+
+typedef Vec<int, 2> Vec2i;
+typedef Vec<int, 3> Vec3i;
+typedef Vec<int, 4> Vec4i;
+typedef Vec<int, 6> Vec6i;
+typedef Vec<int, 8> Vec8i;
+
+typedef Vec<float, 2> Vec2f;
+typedef Vec<float, 3> Vec3f;
+typedef Vec<float, 4> Vec4f;
+typedef Vec<float, 6> Vec6f;
+
+typedef Vec<double, 2> Vec2d;
+typedef Vec<double, 3> Vec3d;
+typedef Vec<double, 4> Vec4d;
+typedef Vec<double, 6> Vec6d;
+/** @} */
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> normalize(const Vec<_Tp, cn>& v);
+
+template<typename _Tp1, typename _Tp2, int cn> static inline
+Vec<_Tp1, cn>& operator += (Vec<_Tp1, cn>& a, const Vec<_Tp2, cn>& b);
+
+template<typename _Tp1, typename _Tp2, int cn> static inline
+Vec<_Tp1, cn>& operator -= (Vec<_Tp1, cn>& a, const Vec<_Tp2, cn>& b);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator + (const Vec<_Tp, cn>& a, const Vec<_Tp, cn>& b);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator - (const Vec<_Tp, cn>& a, const Vec<_Tp, cn>& b);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, int alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, float alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, double alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, int alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, float alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, double alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, int alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (int alpha, const Vec<_Tp, cn>& a);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, float alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (float alpha, const Vec<_Tp, cn>& a);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, double alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (double alpha, const Vec<_Tp, cn>& a);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, int alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, float alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, double alpha);
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator - (const Vec<_Tp, cn>& a);
+
+template<typename _Tp> inline
+Vec<_Tp, 4> operator * (const Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2);
+
+template<typename _Tp> inline
+Vec<_Tp, 4>& operator *= (Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2);
+
+//! @} core_basic
+
+} // cv
+
+#include "opencv2/core/matx.inl.hpp"
+
+#endif // OPENCV_CORE_MATX_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/matx.inl.hpp

@@ -0,0 +1,1115 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#ifndef OPENCV_CORE_MATX_INL_HPP
+#define OPENCV_CORE_MATX_INL_HPP
+
+#ifndef __cplusplus
+#  error matx.inl.hpp header must be compiled as C++
+#endif
+
+#include "opencv2/core/matx.hpp"
+
+namespace cv
+{
+
+//==============================================================================
+// Helpers
+
+namespace internal
+{
+
+template<typename _Tp, int m> struct Matx_DetOp
+{
+    double operator ()(const Matx<_Tp, m, m>& a) const
+    {
+        Matx<_Tp, m, m> temp = a;
+        double p = LU(temp.val, m*sizeof(_Tp), m, 0, 0, 0);
+        if( p == 0 )
+            return p;
+        for( int i = 0; i < m; i++ )
+            p *= temp(i, i);
+        return p;
+    }
+};
+
+template<typename _Tp> struct Matx_DetOp<_Tp, 1>
+{
+    double operator ()(const Matx<_Tp, 1, 1>& a) const
+    {
+        return a(0,0);
+    }
+};
+
+template<typename _Tp> struct Matx_DetOp<_Tp, 2>
+{
+    double operator ()(const Matx<_Tp, 2, 2>& a) const
+    {
+        return a(0,0)*a(1,1) - a(0,1)*a(1,0);
+    }
+};
+
+template<typename _Tp> struct Matx_DetOp<_Tp, 3>
+{
+    double operator ()(const Matx<_Tp, 3, 3>& a) const
+    {
+        return a(0,0)*(a(1,1)*a(2,2) - a(2,1)*a(1,2)) -
+            a(0,1)*(a(1,0)*a(2,2) - a(2,0)*a(1,2)) +
+            a(0,2)*(a(1,0)*a(2,1) - a(2,0)*a(1,1));
+    }
+};
+
+template<typename _Tp> Vec<_Tp, 2> inline conjugate(const Vec<_Tp, 2>& v)
+{
+    return Vec<_Tp, 2>(v[0], -v[1]);
+}
+
+template<typename _Tp> Vec<_Tp, 4> inline conjugate(const Vec<_Tp, 4>& v)
+{
+    return Vec<_Tp, 4>(v[0], -v[1], -v[2], -v[3]);
+}
+
+} // internal::
+
+
+//==============================================================================
+// Matx
+
+template<typename _Tp, int m, int n> class DataType< Matx<_Tp, m, n> >
+{
+public:
+    typedef Matx<_Tp, m, n>                               value_type;
+    typedef Matx<typename DataType<_Tp>::work_type, m, n> work_type;
+    typedef _Tp                                           channel_type;
+    typedef value_type                                    vec_type;
+
+    enum { generic_type = 0,
+           channels     = m * n,
+           fmt          = traits::SafeFmt<channel_type>::fmt + ((channels - 1) << 8)
+#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED
+           ,depth        = DataType<channel_type>::depth
+           ,type         = CV_MAKETYPE(depth, channels)
+#endif
+         };
+};
+
+
+namespace traits {
+template<typename _Tp, int m, int n>
+struct Depth< Matx<_Tp, m, n> > { enum { value = Depth<_Tp>::value }; };
+template<typename _Tp, int m, int n>
+struct Type< Matx<_Tp, m, n> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, n*m) }; };
+} // namespace
+
+
+//! @brief  Comma-separated Matrix Initializer
+template<typename _Tp, int m, int n> class MatxCommaInitializer
+{
+public:
+    MatxCommaInitializer(Matx<_Tp, m, n>* _mtx);
+    template<typename T2> MatxCommaInitializer<_Tp, m, n>& operator , (T2 val);
+    Matx<_Tp, m, n> operator *() const;
+
+    Matx<_Tp, m, n>* dst;
+    int idx;
+};
+
+template<typename _Tp, typename _T2, int m, int n> static inline
+MatxCommaInitializer<_Tp, m, n> operator << (const Matx<_Tp, m, n>& mtx, _T2 val)
+{
+    MatxCommaInitializer<_Tp, m, n> commaInitializer((Matx<_Tp, m, n>*)&mtx);
+    return (commaInitializer, val);
+}
+
+template<typename _Tp, int m, int n> inline
+MatxCommaInitializer<_Tp, m, n>::MatxCommaInitializer(Matx<_Tp, m, n>* _mtx)
+    : dst(_mtx), idx(0)
+{}
+
+template<typename _Tp, int m, int n> template<typename _T2> inline
+MatxCommaInitializer<_Tp, m, n>& MatxCommaInitializer<_Tp, m, n>::operator , (_T2 value)
+{
+    CV_DbgAssert( idx < m*n );
+    dst->val[idx++] = saturate_cast<_Tp>(value);
+    return *this;
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n> MatxCommaInitializer<_Tp, m, n>::operator *() const
+{
+    CV_DbgAssert( idx == n*m );
+    return *dst;
+}
+
+////////////////////////////////// Matx Implementation ///////////////////////////////////
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx()
+{
+    for(int i = 0; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0)
+{
+    val[0] = v0;
+    for(int i = 1; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1)
+{
+    CV_StaticAssert(channels >= 2, "Matx should have at least 2 elements.");
+    val[0] = v0; val[1] = v1;
+    for(int i = 2; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2)
+{
+    CV_StaticAssert(channels >= 3, "Matx should have at least 3 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2;
+    for(int i = 3; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3)
+{
+    CV_StaticAssert(channels >= 4, "Matx should have at least 4 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    for(int i = 4; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4)
+{
+    CV_StaticAssert(channels >= 5, "Matx should have at least 5 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3; val[4] = v4;
+    for(int i = 5; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5)
+{
+    CV_StaticAssert(channels >= 6, "Matx should have at least 6 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5;
+    for(int i = 6; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6)
+{
+    CV_StaticAssert(channels >= 7, "Matx should have at least 7 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5; val[6] = v6;
+    for(int i = 7; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7)
+{
+    CV_StaticAssert(channels >= 8, "Matx should have at least 8 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
+    for(int i = 8; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8)
+{
+    CV_StaticAssert(channels >= 9, "Matx should have at least 9 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
+    val[8] = v8;
+    for(int i = 9; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9)
+{
+    CV_StaticAssert(channels >= 10, "Matx should have at least 10 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
+    val[8] = v8; val[9] = v9;
+    for(int i = 10; i < channels; i++) val[i] = _Tp(0);
+}
+
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11)
+{
+    CV_StaticAssert(channels >= 12, "Matx should have at least 12 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
+    val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11;
+    for(int i = 12; i < channels; i++) val[i] = _Tp(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13)
+{
+    CV_StaticAssert(channels >= 14, "Matx should have at least 14 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
+    val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11;
+    val[12] = v12; val[13] = v13;
+    for (int i = 14; i < channels; i++) val[i] = _Tp(0);
+}
+
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13, _Tp v14, _Tp v15)
+{
+    CV_StaticAssert(channels >= 16, "Matx should have at least 16 elements.");
+    val[0] = v0; val[1] = v1; val[2] = v2; val[3] = v3;
+    val[4] = v4; val[5] = v5; val[6] = v6; val[7] = v7;
+    val[8] = v8; val[9] = v9; val[10] = v10; val[11] = v11;
+    val[12] = v12; val[13] = v13; val[14] = v14; val[15] = v15;
+    for(int i = 16; i < channels; i++) val[i] = _Tp(0);
+}
+
+// WARNING: unreachable code using Ninja
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(push)
+#pragma warning(disable: 4702)
+#endif
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(const _Tp* values)
+{
+    for( int i = 0; i < channels; i++ ) val[i] = values[i];
+}
+#if defined _MSC_VER && _MSC_VER >= 1920
+#pragma warning(pop)
+#endif
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n>::Matx(std::initializer_list<_Tp> list)
+{
+    CV_DbgAssert(list.size() == channels);
+    int i = 0;
+    for(const auto& elem : list)
+    {
+        val[i++] = elem;
+    }
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n> Matx<_Tp, m, n>::all(_Tp alpha)
+{
+    Matx<_Tp, m, n> M;
+    for( int i = 0; i < m*n; i++ ) M.val[i] = alpha;
+    return M;
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n> Matx<_Tp,m,n>::zeros()
+{
+    return all(0);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n> Matx<_Tp,m,n>::ones()
+{
+    return all(1);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n> Matx<_Tp,m,n>::eye()
+{
+    Matx<_Tp,m,n> M;
+    for(int i = 0; i < shortdim; i++)
+        M(i,i) = 1;
+    return M;
+}
+
+template<typename _Tp, int m, int n> inline
+_Tp Matx<_Tp, m, n>::dot(const Matx<_Tp, m, n>& M) const
+{
+    _Tp s = 0;
+    for( int i = 0; i < channels; i++ ) s += val[i]*M.val[i];
+    return s;
+}
+
+template<typename _Tp, int m, int n> inline
+double Matx<_Tp, m, n>::ddot(const Matx<_Tp, m, n>& M) const
+{
+    double s = 0;
+    for( int i = 0; i < channels; i++ ) s += (double)val[i]*M.val[i];
+    return s;
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n> Matx<_Tp,m,n>::diag(const typename Matx<_Tp,m,n>::diag_type& d)
+{
+    Matx<_Tp,m,n> M;
+    for(int i = 0; i < shortdim; i++)
+        M(i,i) = d(i, 0);
+    return M;
+}
+
+template<typename _Tp, int m, int n> template<typename T2>
+inline Matx<_Tp, m, n>::operator Matx<T2, m, n>() const
+{
+    Matx<T2, m, n> M;
+    for( int i = 0; i < m*n; i++ ) M.val[i] = saturate_cast<T2>(val[i]);
+    return M;
+}
+
+template<typename _Tp, int m, int n> template<int m1, int n1> inline
+Matx<_Tp, m1, n1> Matx<_Tp, m, n>::reshape() const
+{
+    CV_StaticAssert(m1*n1 == m*n, "Input and destination matrices must have the same number of elements");
+    return (const Matx<_Tp, m1, n1>&)*this;
+}
+
+template<typename _Tp, int m, int n>
+template<int m1, int n1> inline
+Matx<_Tp, m1, n1> Matx<_Tp, m, n>::get_minor(int base_row, int base_col) const
+{
+    CV_DbgAssert(0 <= base_row && base_row+m1 <= m && 0 <= base_col && base_col+n1 <= n);
+    Matx<_Tp, m1, n1> s;
+    for( int di = 0; di < m1; di++ )
+        for( int dj = 0; dj < n1; dj++ )
+            s(di, dj) = (*this)(base_row+di, base_col+dj);
+    return s;
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, 1, n> Matx<_Tp, m, n>::row(int i) const
+{
+    CV_DbgAssert((unsigned)i < (unsigned)m);
+    return Matx<_Tp, 1, n>(&val[i*n]);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, 1> Matx<_Tp, m, n>::col(int j) const
+{
+    CV_DbgAssert((unsigned)j < (unsigned)n);
+    Matx<_Tp, m, 1> v;
+    for( int i = 0; i < m; i++ )
+        v.val[i] = val[i*n + j];
+    return v;
+}
+
+template<typename _Tp, int m, int n> inline
+typename Matx<_Tp, m, n>::diag_type Matx<_Tp, m, n>::diag() const
+{
+    diag_type d;
+    for( int i = 0; i < shortdim; i++ )
+        d.val[i] = val[i*n + i];
+    return d;
+}
+
+template<typename _Tp, int m, int n> inline
+const _Tp& Matx<_Tp, m, n>::operator()(int row_idx, int col_idx) const
+{
+    CV_DbgAssert( (unsigned)row_idx < (unsigned)m && (unsigned)col_idx < (unsigned)n );
+    return this->val[row_idx*n + col_idx];
+}
+
+template<typename _Tp, int m, int n> inline
+_Tp& Matx<_Tp, m, n>::operator ()(int row_idx, int col_idx)
+{
+    CV_DbgAssert( (unsigned)row_idx < (unsigned)m && (unsigned)col_idx < (unsigned)n );
+    return val[row_idx*n + col_idx];
+}
+
+template<typename _Tp, int m, int n> inline
+const _Tp& Matx<_Tp, m, n>::operator ()(int i) const
+{
+    CV_StaticAssert(m == 1 || n == 1, "Single index indexation requires matrix to be a column or a row");
+    CV_DbgAssert( (unsigned)i < (unsigned)(m+n-1) );
+    return val[i];
+}
+
+template<typename _Tp, int m, int n> inline
+_Tp& Matx<_Tp, m, n>::operator ()(int i)
+{
+    CV_StaticAssert(m == 1 || n == 1, "Single index indexation requires matrix to be a column or a row");
+    CV_DbgAssert( (unsigned)i < (unsigned)(m+n-1) );
+    return val[i];
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_AddOp)
+{
+    for( int i = 0; i < channels; i++ )
+        val[i] = saturate_cast<_Tp>(a.val[i] + b.val[i]);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_SubOp)
+{
+    for( int i = 0; i < channels; i++ )
+        val[i] = saturate_cast<_Tp>(a.val[i] - b.val[i]);
+}
+
+template<typename _Tp, int m, int n> template<typename _T2> inline
+Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, _T2 alpha, Matx_ScaleOp)
+{
+    for( int i = 0; i < channels; i++ )
+        val[i] = saturate_cast<_Tp>(a.val[i] * alpha);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_MulOp)
+{
+    for( int i = 0; i < channels; i++ )
+        val[i] = saturate_cast<_Tp>(a.val[i] * b.val[i]);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b, Matx_DivOp)
+{
+    for( int i = 0; i < channels; i++ )
+        val[i] = saturate_cast<_Tp>(a.val[i] / b.val[i]);
+}
+
+template<typename _Tp, int m, int n> template<int l> inline
+Matx<_Tp,m,n>::Matx(const Matx<_Tp, m, l>& a, const Matx<_Tp, l, n>& b, Matx_MatMulOp)
+{
+    for( int i = 0; i < m; i++ )
+        for( int j = 0; j < n; j++ )
+        {
+            _Tp s = 0;
+            for( int k = 0; k < l; k++ )
+                s += a(i, k) * b(k, j);
+            val[i*n + j] = s;
+        }
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp,m,n>::Matx(const Matx<_Tp, n, m>& a, Matx_TOp)
+{
+    for( int i = 0; i < m; i++ )
+        for( int j = 0; j < n; j++ )
+            val[i*n + j] = a(j, i);
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n> Matx<_Tp, m, n>::mul(const Matx<_Tp, m, n>& a) const
+{
+    return Matx<_Tp, m, n>(*this, a, Matx_MulOp());
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, m, n> Matx<_Tp, m, n>::div(const Matx<_Tp, m, n>& a) const
+{
+    return Matx<_Tp, m, n>(*this, a, Matx_DivOp());
+}
+
+template<typename _Tp, int m, int n> inline
+Matx<_Tp, n, m> Matx<_Tp, m, n>::t() const
+{
+    return Matx<_Tp, n, m>(*this, Matx_TOp());
+}
+
+template<typename _Tp, int m, int n> inline
+Vec<_Tp, n> Matx<_Tp, m, n>::solve(const Vec<_Tp, m>& rhs, int method) const
+{
+    Matx<_Tp, n, 1> x = solve((const Matx<_Tp, m, 1>&)(rhs), method);
+    return (Vec<_Tp, n>&)(x);
+}
+
+template<typename _Tp, int m> static inline
+double determinant(const Matx<_Tp, m, m>& a)
+{
+    return cv::internal::Matx_DetOp<_Tp, m>()(a);
+}
+
+template<typename _Tp, int m, int n> static inline
+double trace(const Matx<_Tp, m, n>& a)
+{
+    _Tp s = 0;
+    for( int i = 0; i < std::min(m, n); i++ )
+        s += a(i,i);
+    return s;
+}
+
+template<typename _Tp, int m, int n> static inline
+double norm(const Matx<_Tp, m, n>& M)
+{
+    return std::sqrt(normL2Sqr<_Tp, double>(M.val, m*n));
+}
+
+template<typename _Tp, int m, int n> static inline
+double norm(const Matx<_Tp, m, n>& M, int normType)
+{
+    switch(normType) {
+    case NORM_INF:
+        return (double)normInf<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n);
+    case NORM_L1:
+        return (double)normL1<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n);
+    case NORM_L2SQR:
+        return (double)normL2Sqr<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n);
+    default:
+    case NORM_L2:
+        return std::sqrt((double)normL2Sqr<_Tp, typename DataType<_Tp>::work_type>(M.val, m*n));
+    }
+}
+
+template<typename _Tp1, typename _Tp2, int m, int n> static inline
+Matx<_Tp1, m, n>& operator += (Matx<_Tp1, m, n>& a, const Matx<_Tp2, m, n>& b)
+{
+    for( int i = 0; i < m*n; i++ )
+        a.val[i] = saturate_cast<_Tp1>(a.val[i] + b.val[i]);
+    return a;
+}
+
+template<typename _Tp1, typename _Tp2, int m, int n> static inline
+Matx<_Tp1, m, n>& operator -= (Matx<_Tp1, m, n>& a, const Matx<_Tp2, m, n>& b)
+{
+    for( int i = 0; i < m*n; i++ )
+        a.val[i] = saturate_cast<_Tp1>(a.val[i] - b.val[i]);
+    return a;
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator + (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b)
+{
+    return Matx<_Tp, m, n>(a, b, Matx_AddOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator - (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b)
+{
+    return Matx<_Tp, m, n>(a, b, Matx_SubOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, int alpha)
+{
+    for( int i = 0; i < m*n; i++ )
+        a.val[i] = saturate_cast<_Tp>(a.val[i] * alpha);
+    return a;
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, float alpha)
+{
+    for( int i = 0; i < m*n; i++ )
+        a.val[i] = saturate_cast<_Tp>(a.val[i] * alpha);
+    return a;
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator *= (Matx<_Tp, m, n>& a, double alpha)
+{
+    for( int i = 0; i < m*n; i++ )
+        a.val[i] = saturate_cast<_Tp>(a.val[i] * alpha);
+    return a;
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, int alpha)
+{
+    return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, float alpha)
+{
+    return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, n>& a, double alpha)
+{
+    return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (int alpha, const Matx<_Tp, m, n>& a)
+{
+    return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (float alpha, const Matx<_Tp, m, n>& a)
+{
+    return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator * (double alpha, const Matx<_Tp, m, n>& a)
+{
+    return Matx<_Tp, m, n>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator /= (Matx<_Tp, m, n>& a, float alpha)
+{
+    for( int i = 0; i < m*n; i++ )
+        a.val[i] = a.val[i] / alpha;
+    return a;
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n>& operator /= (Matx<_Tp, m, n>& a, double alpha)
+{
+    for( int i = 0; i < m*n; i++ )
+        a.val[i] = a.val[i] / alpha;
+    return a;
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator / (const Matx<_Tp, m, n>& a, float alpha)
+{
+    return Matx<_Tp, m, n>(a, 1.f/alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator / (const Matx<_Tp, m, n>& a, double alpha)
+{
+    return Matx<_Tp, m, n>(a, 1./alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Matx<_Tp, m, n> operator - (const Matx<_Tp, m, n>& a)
+{
+    return Matx<_Tp, m, n>(a, -1, Matx_ScaleOp());
+}
+
+template<typename _Tp, int m, int n, int l> static inline
+Matx<_Tp, m, n> operator * (const Matx<_Tp, m, l>& a, const Matx<_Tp, l, n>& b)
+{
+    return Matx<_Tp, m, n>(a, b, Matx_MatMulOp());
+}
+
+template<typename _Tp, int m, int n> static inline
+Vec<_Tp, m> operator * (const Matx<_Tp, m, n>& a, const Vec<_Tp, n>& b)
+{
+    Matx<_Tp, m, 1> c(a, b, Matx_MatMulOp());
+    return (const Vec<_Tp, m>&)(c);
+}
+
+template<typename _Tp, int m, int n> static inline
+bool operator == (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b)
+{
+    for( int i = 0; i < m*n; i++ )
+        if( a.val[i] != b.val[i] ) return false;
+    return true;
+}
+
+template<typename _Tp, int m, int n> static inline
+bool operator != (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b)
+{
+    return !(a == b);
+}
+
+//==============================================================================
+// Vec
+
+template<typename _Tp, int cn> class DataType< Vec<_Tp, cn> >
+{
+public:
+    typedef Vec<_Tp, cn>                               value_type;
+    typedef Vec<typename DataType<_Tp>::work_type, cn> work_type;
+    typedef _Tp                                        channel_type;
+    typedef value_type                                 vec_type;
+
+    enum { generic_type = 0,
+           channels     = cn,
+           fmt          = DataType<channel_type>::fmt + ((channels - 1) << 8),
+#ifdef OPENCV_TRAITS_ENABLE_DEPRECATED
+           depth        = DataType<channel_type>::depth,
+           type         = CV_MAKETYPE(depth, channels),
+#endif
+           _dummy_enum_finalizer = 0
+         };
+};
+
+namespace traits {
+template<typename _Tp, int cn>
+struct Depth< Vec<_Tp, cn> > { enum { value = Depth<_Tp>::value }; };
+template<typename _Tp, int cn>
+struct Type< Vec<_Tp, cn> > { enum { value = CV_MAKETYPE(Depth<_Tp>::value, cn) }; };
+} // namespace
+
+/** @brief  Comma-separated Vec Initializer
+*/
+template<typename _Tp, int m> class VecCommaInitializer : public MatxCommaInitializer<_Tp, m, 1>
+{
+public:
+    VecCommaInitializer(Vec<_Tp, m>* _vec);
+    template<typename T2> VecCommaInitializer<_Tp, m>& operator , (T2 val);
+    Vec<_Tp, m> operator *() const;
+};
+
+template<typename _Tp, typename _T2, int cn> static inline
+VecCommaInitializer<_Tp, cn> operator << (const Vec<_Tp, cn>& vec, _T2 val)
+{
+    VecCommaInitializer<_Tp, cn> commaInitializer((Vec<_Tp, cn>*)&vec);
+    return (commaInitializer, val);
+}
+
+template<typename _Tp, int cn> inline
+VecCommaInitializer<_Tp, cn>::VecCommaInitializer(Vec<_Tp, cn>* _vec)
+    : MatxCommaInitializer<_Tp, cn, 1>(_vec)
+{}
+
+template<typename _Tp, int cn> template<typename _T2> inline
+VecCommaInitializer<_Tp, cn>& VecCommaInitializer<_Tp, cn>::operator , (_T2 value)
+{
+    CV_DbgAssert( this->idx < cn );
+    this->dst->val[this->idx++] = saturate_cast<_Tp>(value);
+    return *this;
+}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> VecCommaInitializer<_Tp, cn>::operator *() const
+{
+    CV_DbgAssert( this->idx == cn );
+    return *this->dst;
+}
+
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec() {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0)
+    : Matx<_Tp, cn, 1>(v0) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1)
+    : Matx<_Tp, cn, 1>(v0, v1) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2)
+    : Matx<_Tp, cn, 1>(v0, v1, v2) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3, _Tp v4, _Tp v5, _Tp v6, _Tp v7, _Tp v8, _Tp v9, _Tp v10, _Tp v11, _Tp v12, _Tp v13)
+    : Matx<_Tp, cn, 1>(v0, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(const _Tp* values)
+    : Matx<_Tp, cn, 1>(values) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(std::initializer_list<_Tp> list)
+    : Matx<_Tp, cn, 1>(list) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(const Vec<_Tp, cn>& m)
+    : Matx<_Tp, cn, 1>(m.val) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_AddOp op)
+    : Matx<_Tp, cn, 1>(a, b, op) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn>::Vec(const Matx<_Tp, cn, 1>& a, const Matx<_Tp, cn, 1>& b, Matx_SubOp op)
+    : Matx<_Tp, cn, 1>(a, b, op) {}
+
+template<typename _Tp, int cn> template<typename _T2> inline
+Vec<_Tp, cn>::Vec(const Matx<_Tp, cn, 1>& a, _T2 alpha, Matx_ScaleOp op)
+    : Matx<_Tp, cn, 1>(a, alpha, op) {}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> Vec<_Tp, cn>::all(_Tp alpha)
+{
+    Vec v;
+    for( int i = 0; i < cn; i++ ) v.val[i] = alpha;
+    return v;
+}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> Vec<_Tp, cn>::ones()
+{
+    return Vec::all(1);
+}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> Vec<_Tp, cn>::zeros()
+{
+    return Vec::all(0);
+}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> Vec<_Tp, cn>::mul(const Vec<_Tp, cn>& v) const
+{
+    Vec<_Tp, cn> w;
+    for( int i = 0; i < cn; i++ ) w.val[i] = saturate_cast<_Tp>(this->val[i]*v.val[i]);
+    return w;
+}
+
+template<> inline
+Vec<float, 2> Vec<float, 2>::conj() const
+{
+    return cv::internal::conjugate(*this);
+}
+
+template<> inline
+Vec<double, 2> Vec<double, 2>::conj() const
+{
+    return cv::internal::conjugate(*this);
+}
+
+template<> inline
+Vec<float, 4> Vec<float, 4>::conj() const
+{
+    return cv::internal::conjugate(*this);
+}
+
+template<> inline
+Vec<double, 4> Vec<double, 4>::conj() const
+{
+    return cv::internal::conjugate(*this);
+}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> Vec<_Tp, cn>::cross(const Vec<_Tp, cn>&) const
+{
+    CV_StaticAssert(cn == 3, "for arbitrary-size vector there is no cross-product defined");
+    return Vec<_Tp, cn>();
+}
+
+template<> inline
+Vec<float, 3> Vec<float, 3>::cross(const Vec<float, 3>& v) const
+{
+    return Vec<float,3>(this->val[1]*v.val[2] - this->val[2]*v.val[1],
+                     this->val[2]*v.val[0] - this->val[0]*v.val[2],
+                     this->val[0]*v.val[1] - this->val[1]*v.val[0]);
+}
+
+template<> inline
+Vec<double, 3> Vec<double, 3>::cross(const Vec<double, 3>& v) const
+{
+    return Vec<double,3>(this->val[1]*v.val[2] - this->val[2]*v.val[1],
+                     this->val[2]*v.val[0] - this->val[0]*v.val[2],
+                     this->val[0]*v.val[1] - this->val[1]*v.val[0]);
+}
+
+template<typename _Tp, int cn> template<typename T2> inline
+Vec<_Tp, cn>::operator Vec<T2, cn>() const
+{
+    Vec<T2, cn> v;
+    for( int i = 0; i < cn; i++ ) v.val[i] = saturate_cast<T2>(this->val[i]);
+    return v;
+}
+
+template<typename _Tp, int cn> inline
+const _Tp& Vec<_Tp, cn>::operator [](int i) const
+{
+    CV_DbgAssert( (unsigned)i < (unsigned)cn );
+    return this->val[i];
+}
+
+template<typename _Tp, int cn> inline
+_Tp& Vec<_Tp, cn>::operator [](int i)
+{
+    CV_DbgAssert( (unsigned)i < (unsigned)cn );
+    return this->val[i];
+}
+
+template<typename _Tp, int cn> inline
+const _Tp& Vec<_Tp, cn>::operator ()(int i) const
+{
+    CV_DbgAssert( (unsigned)i < (unsigned)cn );
+    return this->val[i];
+}
+
+template<typename _Tp, int cn> inline
+_Tp& Vec<_Tp, cn>::operator ()(int i)
+{
+    CV_DbgAssert( (unsigned)i < (unsigned)cn );
+    return this->val[i];
+}
+
+template<typename _Tp, int cn> inline
+Vec<_Tp, cn> normalize(const Vec<_Tp, cn>& v)
+{
+    double nv = norm(v);
+    return v * (nv ? 1./nv : 0.);
+}
+
+template<typename _Tp1, typename _Tp2, int cn> static inline
+Vec<_Tp1, cn>& operator += (Vec<_Tp1, cn>& a, const Vec<_Tp2, cn>& b)
+{
+    for( int i = 0; i < cn; i++ )
+        a.val[i] = saturate_cast<_Tp1>(a.val[i] + b.val[i]);
+    return a;
+}
+
+template<typename _Tp1, typename _Tp2, int cn> static inline
+Vec<_Tp1, cn>& operator -= (Vec<_Tp1, cn>& a, const Vec<_Tp2, cn>& b)
+{
+    for( int i = 0; i < cn; i++ )
+        a.val[i] = saturate_cast<_Tp1>(a.val[i] - b.val[i]);
+    return a;
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator + (const Vec<_Tp, cn>& a, const Vec<_Tp, cn>& b)
+{
+    return Vec<_Tp, cn>(a, b, Matx_AddOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator - (const Vec<_Tp, cn>& a, const Vec<_Tp, cn>& b)
+{
+    return Vec<_Tp, cn>(a, b, Matx_SubOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, int alpha)
+{
+    for( int i = 0; i < cn; i++ )
+        a[i] = saturate_cast<_Tp>(a[i]*alpha);
+    return a;
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, float alpha)
+{
+    for( int i = 0; i < cn; i++ )
+        a[i] = saturate_cast<_Tp>(a[i]*alpha);
+    return a;
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator *= (Vec<_Tp, cn>& a, double alpha)
+{
+    for( int i = 0; i < cn; i++ )
+        a[i] = saturate_cast<_Tp>(a[i]*alpha);
+    return a;
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, int alpha)
+{
+    double ialpha = 1./alpha;
+    for( int i = 0; i < cn; i++ )
+        a[i] = saturate_cast<_Tp>(a[i]*ialpha);
+    return a;
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, float alpha)
+{
+    float ialpha = 1.f/alpha;
+    for( int i = 0; i < cn; i++ )
+        a[i] = saturate_cast<_Tp>(a[i]*ialpha);
+    return a;
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn>& operator /= (Vec<_Tp, cn>& a, double alpha)
+{
+    double ialpha = 1./alpha;
+    for( int i = 0; i < cn; i++ )
+        a[i] = saturate_cast<_Tp>(a[i]*ialpha);
+    return a;
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, int alpha)
+{
+    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (int alpha, const Vec<_Tp, cn>& a)
+{
+    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, float alpha)
+{
+    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (float alpha, const Vec<_Tp, cn>& a)
+{
+    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, double alpha)
+{
+    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator * (double alpha, const Vec<_Tp, cn>& a)
+{
+    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, int alpha)
+{
+    return Vec<_Tp, cn>(a, 1./alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, float alpha)
+{
+    return Vec<_Tp, cn>(a, 1.f/alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator / (const Vec<_Tp, cn>& a, double alpha)
+{
+    return Vec<_Tp, cn>(a, 1./alpha, Matx_ScaleOp());
+}
+
+template<typename _Tp, int cn> static inline
+Vec<_Tp, cn> operator - (const Vec<_Tp, cn>& a)
+{
+    Vec<_Tp,cn> t;
+    for( int i = 0; i < cn; i++ ) t.val[i] = saturate_cast<_Tp>(-a.val[i]);
+    return t;
+}
+
+template<typename _Tp> inline Vec<_Tp, 4> operator * (const Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2)
+{
+    return Vec<_Tp, 4>(saturate_cast<_Tp>(v1[0]*v2[0] - v1[1]*v2[1] - v1[2]*v2[2] - v1[3]*v2[3]),
+                       saturate_cast<_Tp>(v1[0]*v2[1] + v1[1]*v2[0] + v1[2]*v2[3] - v1[3]*v2[2]),
+                       saturate_cast<_Tp>(v1[0]*v2[2] - v1[1]*v2[3] + v1[2]*v2[0] + v1[3]*v2[1]),
+                       saturate_cast<_Tp>(v1[0]*v2[3] + v1[1]*v2[2] - v1[2]*v2[1] + v1[3]*v2[0]));
+}
+
+template<typename _Tp> inline Vec<_Tp, 4>& operator *= (Vec<_Tp, 4>& v1, const Vec<_Tp, 4>& v2)
+{
+    v1 = v1 * v2;
+    return v1;
+}
+
+} // cv::
+
+#endif // OPENCV_CORE_MATX_INL_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/neon_utils.hpp

@@ -0,0 +1,128 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                          License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2015, Itseez Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_HAL_NEON_UTILS_HPP
+#define OPENCV_HAL_NEON_UTILS_HPP
+
+#include "opencv2/core/cvdef.h"
+
+//! @addtogroup core_utils_neon
+//! @{
+
+#if CV_NEON
+
+inline int32x2_t cv_vrnd_s32_f32(float32x2_t v)
+{
+    static int32x2_t v_sign = vdup_n_s32(1 << 31),
+        v_05 = vreinterpret_s32_f32(vdup_n_f32(0.5f));
+
+    int32x2_t v_addition = vorr_s32(v_05, vand_s32(v_sign, vreinterpret_s32_f32(v)));
+    return vcvt_s32_f32(vadd_f32(v, vreinterpret_f32_s32(v_addition)));
+}
+
+inline int32x4_t cv_vrndq_s32_f32(float32x4_t v)
+{
+    static int32x4_t v_sign = vdupq_n_s32(1 << 31),
+        v_05 = vreinterpretq_s32_f32(vdupq_n_f32(0.5f));
+
+    int32x4_t v_addition = vorrq_s32(v_05, vandq_s32(v_sign, vreinterpretq_s32_f32(v)));
+    return vcvtq_s32_f32(vaddq_f32(v, vreinterpretq_f32_s32(v_addition)));
+}
+
+inline uint32x2_t cv_vrnd_u32_f32(float32x2_t v)
+{
+    static float32x2_t v_05 = vdup_n_f32(0.5f);
+    return vcvt_u32_f32(vadd_f32(v, v_05));
+}
+
+inline uint32x4_t cv_vrndq_u32_f32(float32x4_t v)
+{
+    static float32x4_t v_05 = vdupq_n_f32(0.5f);
+    return vcvtq_u32_f32(vaddq_f32(v, v_05));
+}
+
+inline float32x4_t cv_vrecpq_f32(float32x4_t val)
+{
+    float32x4_t reciprocal = vrecpeq_f32(val);
+    reciprocal = vmulq_f32(vrecpsq_f32(val, reciprocal), reciprocal);
+    reciprocal = vmulq_f32(vrecpsq_f32(val, reciprocal), reciprocal);
+    return reciprocal;
+}
+
+inline float32x2_t cv_vrecp_f32(float32x2_t val)
+{
+    float32x2_t reciprocal = vrecpe_f32(val);
+    reciprocal = vmul_f32(vrecps_f32(val, reciprocal), reciprocal);
+    reciprocal = vmul_f32(vrecps_f32(val, reciprocal), reciprocal);
+    return reciprocal;
+}
+
+inline float32x4_t cv_vrsqrtq_f32(float32x4_t val)
+{
+    float32x4_t e = vrsqrteq_f32(val);
+    e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(e, e), val), e);
+    e = vmulq_f32(vrsqrtsq_f32(vmulq_f32(e, e), val), e);
+    return e;
+}
+
+inline float32x2_t cv_vrsqrt_f32(float32x2_t val)
+{
+    float32x2_t e = vrsqrte_f32(val);
+    e = vmul_f32(vrsqrts_f32(vmul_f32(e, e), val), e);
+    e = vmul_f32(vrsqrts_f32(vmul_f32(e, e), val), e);
+    return e;
+}
+
+inline float32x4_t cv_vsqrtq_f32(float32x4_t val)
+{
+    return cv_vrecpq_f32(cv_vrsqrtq_f32(val));
+}
+
+inline float32x2_t cv_vsqrt_f32(float32x2_t val)
+{
+    return cv_vrecp_f32(cv_vrsqrt_f32(val));
+}
+
+#endif
+
+//! @}
+
+#endif // OPENCV_HAL_NEON_UTILS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/ocl.hpp

@@ -0,0 +1,923 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the OpenCV Foundation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_OPENCL_HPP
+#define OPENCV_OPENCL_HPP
+
+#include "opencv2/core.hpp"
+#include <typeinfo>
+#include <typeindex>
+
+namespace cv { namespace ocl {
+
+//! @addtogroup core_opencl
+//! @{
+
+CV_EXPORTS_W bool haveOpenCL();
+CV_EXPORTS_W bool useOpenCL();
+CV_EXPORTS_W bool haveAmdBlas();
+CV_EXPORTS_W bool haveAmdFft();
+CV_EXPORTS_W void setUseOpenCL(bool flag);
+CV_EXPORTS_W void finish();
+
+CV_EXPORTS bool haveSVM();
+
+class CV_EXPORTS Context;
+class CV_EXPORTS_W_SIMPLE Device;
+class CV_EXPORTS Kernel;
+class CV_EXPORTS Program;
+class CV_EXPORTS ProgramSource;
+class CV_EXPORTS Queue;
+class CV_EXPORTS PlatformInfo;
+class CV_EXPORTS Image2D;
+
+class CV_EXPORTS_W_SIMPLE Device
+{
+public:
+    CV_WRAP Device() CV_NOEXCEPT;
+    explicit Device(void* d);
+    Device(const Device& d);
+    Device& operator = (const Device& d);
+    Device(Device&& d) CV_NOEXCEPT;
+    Device& operator = (Device&& d) CV_NOEXCEPT;
+    CV_WRAP ~Device();
+
+    void set(void* d);
+
+    enum
+    {
+        TYPE_DEFAULT     = (1 << 0),
+        TYPE_CPU         = (1 << 1),
+        TYPE_GPU         = (1 << 2),
+        TYPE_ACCELERATOR = (1 << 3),
+        TYPE_DGPU        = TYPE_GPU + (1 << 16),
+        TYPE_IGPU        = TYPE_GPU + (1 << 17),
+        TYPE_ALL         = 0xFFFFFFFF
+    };
+
+    CV_WRAP String name() const;
+    CV_WRAP String extensions() const;
+    CV_WRAP bool isExtensionSupported(const String& extensionName) const;
+    CV_WRAP String version() const;
+    CV_WRAP String vendorName() const;
+    CV_WRAP String OpenCL_C_Version() const;
+    CV_WRAP String OpenCLVersion() const;
+    CV_WRAP int deviceVersionMajor() const;
+    CV_WRAP int deviceVersionMinor() const;
+    CV_WRAP String driverVersion() const;
+    void* ptr() const;
+
+    CV_WRAP int type() const;
+
+    CV_WRAP int addressBits() const;
+    CV_WRAP bool available() const;
+    CV_WRAP bool compilerAvailable() const;
+    CV_WRAP bool linkerAvailable() const;
+
+    enum
+    {
+        FP_DENORM=(1 << 0),
+        FP_INF_NAN=(1 << 1),
+        FP_ROUND_TO_NEAREST=(1 << 2),
+        FP_ROUND_TO_ZERO=(1 << 3),
+        FP_ROUND_TO_INF=(1 << 4),
+        FP_FMA=(1 << 5),
+        FP_SOFT_FLOAT=(1 << 6),
+        FP_CORRECTLY_ROUNDED_DIVIDE_SQRT=(1 << 7)
+    };
+    CV_WRAP int doubleFPConfig() const;
+    CV_WRAP int singleFPConfig() const;
+    CV_WRAP int halfFPConfig() const;
+
+    /// true if 'cl_khr_fp64' extension is available
+    CV_WRAP bool hasFP64() const;
+    /// true if 'cl_khr_fp16' extension is available
+    CV_WRAP bool hasFP16() const;
+
+    CV_WRAP bool endianLittle() const;
+    CV_WRAP bool errorCorrectionSupport() const;
+
+    enum
+    {
+        EXEC_KERNEL=(1 << 0),
+        EXEC_NATIVE_KERNEL=(1 << 1)
+    };
+    CV_WRAP int executionCapabilities() const;
+
+    CV_WRAP size_t globalMemCacheSize() const;
+
+    enum
+    {
+        NO_CACHE=0,
+        READ_ONLY_CACHE=1,
+        READ_WRITE_CACHE=2
+    };
+    CV_WRAP int globalMemCacheType() const;
+    CV_WRAP int globalMemCacheLineSize() const;
+    CV_WRAP size_t globalMemSize() const;
+
+    CV_WRAP size_t localMemSize() const;
+    enum
+    {
+        NO_LOCAL_MEM=0,
+        LOCAL_IS_LOCAL=1,
+        LOCAL_IS_GLOBAL=2
+    };
+    CV_WRAP int localMemType() const;
+    CV_WRAP bool hostUnifiedMemory() const;
+
+    CV_WRAP bool imageSupport() const;
+
+    CV_WRAP bool imageFromBufferSupport() const;
+    uint imagePitchAlignment() const;
+    uint imageBaseAddressAlignment() const;
+
+    /// deprecated, use isExtensionSupported() method (probably with "cl_khr_subgroups" value)
+    CV_WRAP bool intelSubgroupsSupport() const;
+
+    CV_WRAP size_t image2DMaxWidth() const;
+    CV_WRAP size_t image2DMaxHeight() const;
+
+    CV_WRAP size_t image3DMaxWidth() const;
+    CV_WRAP size_t image3DMaxHeight() const;
+    CV_WRAP size_t image3DMaxDepth() const;
+
+    CV_WRAP size_t imageMaxBufferSize() const;
+    CV_WRAP size_t imageMaxArraySize() const;
+
+    enum
+    {
+        UNKNOWN_VENDOR=0,
+        VENDOR_AMD=1,
+        VENDOR_INTEL=2,
+        VENDOR_NVIDIA=3
+    };
+    CV_WRAP int vendorID() const;
+    // FIXIT
+    // dev.isAMD() doesn't work for OpenCL CPU devices from AMD OpenCL platform.
+    // This method should use platform name instead of vendor name.
+    // After fix restore code in arithm.cpp: ocl_compare()
+    CV_WRAP inline bool isAMD() const { return vendorID() == VENDOR_AMD; }
+    CV_WRAP inline bool isIntel() const { return vendorID() == VENDOR_INTEL; }
+    CV_WRAP inline bool isNVidia() const { return vendorID() == VENDOR_NVIDIA; }
+
+    CV_WRAP int maxClockFrequency() const;
+    CV_WRAP int maxComputeUnits() const;
+    CV_WRAP int maxConstantArgs() const;
+    CV_WRAP size_t maxConstantBufferSize() const;
+
+    CV_WRAP size_t maxMemAllocSize() const;
+    CV_WRAP size_t maxParameterSize() const;
+
+    CV_WRAP int maxReadImageArgs() const;
+    CV_WRAP int maxWriteImageArgs() const;
+    CV_WRAP int maxSamplers() const;
+
+    CV_WRAP size_t maxWorkGroupSize() const;
+    CV_WRAP int maxWorkItemDims() const;
+    void maxWorkItemSizes(size_t*) const;
+
+    CV_WRAP int memBaseAddrAlign() const;
+
+    CV_WRAP int nativeVectorWidthChar() const;
+    CV_WRAP int nativeVectorWidthShort() const;
+    CV_WRAP int nativeVectorWidthInt() const;
+    CV_WRAP int nativeVectorWidthLong() const;
+    CV_WRAP int nativeVectorWidthFloat() const;
+    CV_WRAP int nativeVectorWidthDouble() const;
+    CV_WRAP int nativeVectorWidthHalf() const;
+
+    CV_WRAP int preferredVectorWidthChar() const;
+    CV_WRAP int preferredVectorWidthShort() const;
+    CV_WRAP int preferredVectorWidthInt() const;
+    CV_WRAP int preferredVectorWidthLong() const;
+    CV_WRAP int preferredVectorWidthFloat() const;
+    CV_WRAP int preferredVectorWidthDouble() const;
+    CV_WRAP int preferredVectorWidthHalf() const;
+
+    CV_WRAP size_t printfBufferSize() const;
+    CV_WRAP size_t profilingTimerResolution() const;
+
+    CV_WRAP static const Device& getDefault();
+
+    /**
+     * @param d OpenCL handle (cl_device_id). clRetainDevice() is called on success.
+     *
+     * @note Ownership of the passed device is passed to OpenCV on success.
+     * The caller should additionally call `clRetainDevice` on it if it intends
+     * to continue using the device.
+      */
+    static Device fromHandle(void* d);
+
+    struct Impl;
+    inline Impl* getImpl() const { return (Impl*)p; }
+    inline bool empty() const { return !p; }
+protected:
+    Impl* p;
+};
+
+
+class CV_EXPORTS Context
+{
+public:
+    Context() CV_NOEXCEPT;
+    explicit Context(int dtype);  //!< @deprecated
+    ~Context();
+    Context(const Context& c);
+    Context& operator= (const Context& c);
+    Context(Context&& c) CV_NOEXCEPT;
+    Context& operator = (Context&& c) CV_NOEXCEPT;
+
+    /** @deprecated */
+    bool create();
+    /** @deprecated */
+    bool create(int dtype);
+
+    size_t ndevices() const;
+    Device& device(size_t idx) const;
+    Program getProg(const ProgramSource& prog,
+                    const String& buildopt, String& errmsg);
+    void unloadProg(Program& prog);
+
+
+    /** Get thread-local OpenCL context (initialize if necessary) */
+#if 0  // OpenCV 5.0
+    static Context& getDefault();
+#else
+    static Context& getDefault(bool initialize = true);
+#endif
+
+    /** @returns cl_context value */
+    void* ptr() const;
+
+    /**
+     * @brief Get OpenCL context property specified on context creation
+     * @param propertyId Property id (CL_CONTEXT_* as defined in cl_context_properties type)
+     * @returns Property value if property was specified on clCreateContext, or NULL if context created without the property
+     */
+    void* getOpenCLContextProperty(int propertyId) const;
+
+    bool useSVM() const;
+    void setUseSVM(bool enabled);
+
+    /**
+     * @param context OpenCL handle (cl_context). clRetainContext() is called on success
+     */
+    static Context fromHandle(void* context);
+    static Context fromDevice(const ocl::Device& device);
+    static Context create(const std::string& configuration);
+
+    void release();
+
+    class CV_EXPORTS UserContext {
+    public:
+        virtual ~UserContext();
+    };
+    template <typename T>
+    inline void setUserContext(const std::shared_ptr<T>& userContext) {
+        setUserContext(typeid(T), userContext);
+    }
+    template <typename T>
+    inline std::shared_ptr<T> getUserContext() {
+        return std::dynamic_pointer_cast<T>(getUserContext(typeid(T)));
+    }
+    void setUserContext(std::type_index typeId, const std::shared_ptr<UserContext>& userContext);
+    std::shared_ptr<UserContext> getUserContext(std::type_index typeId);
+
+    struct Impl;
+    inline Impl* getImpl() const { return (Impl*)p; }
+    inline bool empty() const { return !p; }
+// TODO OpenCV 5.0
+//protected:
+    Impl* p;
+};
+
+/** @deprecated */
+class CV_EXPORTS Platform
+{
+public:
+    Platform() CV_NOEXCEPT;
+    ~Platform();
+    Platform(const Platform& p);
+    Platform& operator = (const Platform& p);
+    Platform(Platform&& p) CV_NOEXCEPT;
+    Platform& operator = (Platform&& p) CV_NOEXCEPT;
+
+    void* ptr() const;
+
+    /** @deprecated */
+    static Platform& getDefault();
+
+    struct Impl;
+    inline Impl* getImpl() const { return (Impl*)p; }
+    inline bool empty() const { return !p; }
+protected:
+    Impl* p;
+};
+
+/** @brief Attaches OpenCL context to OpenCV
+@note
+  OpenCV will check if available OpenCL platform has platformName name, then assign context to
+  OpenCV and call `clRetainContext` function. The deviceID device will be used as target device and
+  new command queue will be created.
+@param platformName name of OpenCL platform to attach, this string is used to check if platform is available to OpenCV at runtime
+@param platformID ID of platform attached context was created for
+@param context OpenCL context to be attached to OpenCV
+@param deviceID ID of device, must be created from attached context
+*/
+CV_EXPORTS void attachContext(const String& platformName, void* platformID, void* context, void* deviceID);
+
+/** @brief Convert OpenCL buffer to UMat
+@note
+  OpenCL buffer (cl_mem_buffer) should contain 2D image data, compatible with OpenCV. Memory
+  content is not copied from `clBuffer` to UMat. Instead, buffer handle assigned to UMat and
+  `clRetainMemObject` is called.
+@param cl_mem_buffer source clBuffer handle
+@param step num of bytes in single row
+@param rows number of rows
+@param cols number of cols
+@param type OpenCV type of image
+@param dst destination UMat
+*/
+CV_EXPORTS void convertFromBuffer(void* cl_mem_buffer, size_t step, int rows, int cols, int type, UMat& dst);
+
+/** @brief Convert OpenCL image2d_t to UMat
+@note
+  OpenCL `image2d_t` (cl_mem_image), should be compatible with OpenCV UMat formats. Memory content
+  is copied from image to UMat with `clEnqueueCopyImageToBuffer` function.
+@param cl_mem_image source image2d_t handle
+@param dst destination UMat
+*/
+CV_EXPORTS void convertFromImage(void* cl_mem_image, UMat& dst);
+
+// TODO Move to internal header
+/// @deprecated
+void initializeContextFromHandle(Context& ctx, void* platform, void* context, void* device);
+
+class CV_EXPORTS Queue
+{
+public:
+    Queue() CV_NOEXCEPT;
+    explicit Queue(const Context& c, const Device& d=Device());
+    ~Queue();
+    Queue(const Queue& q);
+    Queue& operator = (const Queue& q);
+    Queue(Queue&& q) CV_NOEXCEPT;
+    Queue& operator = (Queue&& q) CV_NOEXCEPT;
+
+    bool create(const Context& c=Context(), const Device& d=Device());
+    void finish();
+    void* ptr() const;
+    static Queue& getDefault();
+
+    /// @brief Returns OpenCL command queue with enable profiling mode support
+    const Queue& getProfilingQueue() const;
+
+    struct Impl; friend struct Impl;
+    inline Impl* getImpl() const { return p; }
+    inline bool empty() const { return !p; }
+protected:
+    Impl* p;
+};
+
+
+class CV_EXPORTS KernelArg
+{
+public:
+    enum { LOCAL=1, READ_ONLY=2, WRITE_ONLY=4, READ_WRITE=6, CONSTANT=8, PTR_ONLY = 16, NO_SIZE=256 };
+    KernelArg(int _flags, UMat* _m, int wscale=1, int iwscale=1, const void* _obj=0, size_t _sz=0);
+    KernelArg() CV_NOEXCEPT;
+
+    static KernelArg Local(size_t localMemSize)
+    { return KernelArg(LOCAL, 0, 1, 1, 0, localMemSize); }
+    static KernelArg PtrWriteOnly(const UMat& m)
+    { return KernelArg(PTR_ONLY+WRITE_ONLY, (UMat*)&m); }
+    static KernelArg PtrReadOnly(const UMat& m)
+    { return KernelArg(PTR_ONLY+READ_ONLY, (UMat*)&m); }
+    static KernelArg PtrReadWrite(const UMat& m)
+    { return KernelArg(PTR_ONLY+READ_WRITE, (UMat*)&m); }
+    static KernelArg ReadWrite(const UMat& m, int wscale=1, int iwscale=1)
+    { return KernelArg(READ_WRITE, (UMat*)&m, wscale, iwscale); }
+    static KernelArg ReadWriteNoSize(const UMat& m, int wscale=1, int iwscale=1)
+    { return KernelArg(READ_WRITE+NO_SIZE, (UMat*)&m, wscale, iwscale); }
+    static KernelArg ReadOnly(const UMat& m, int wscale=1, int iwscale=1)
+    { return KernelArg(READ_ONLY, (UMat*)&m, wscale, iwscale); }
+    static KernelArg WriteOnly(const UMat& m, int wscale=1, int iwscale=1)
+    { return KernelArg(WRITE_ONLY, (UMat*)&m, wscale, iwscale); }
+    static KernelArg ReadOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1)
+    { return KernelArg(READ_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); }
+    static KernelArg WriteOnlyNoSize(const UMat& m, int wscale=1, int iwscale=1)
+    { return KernelArg(WRITE_ONLY+NO_SIZE, (UMat*)&m, wscale, iwscale); }
+    static KernelArg Constant(const Mat& m);
+    template<typename _Tp> static KernelArg Constant(const _Tp* arr, size_t n)
+    { return KernelArg(CONSTANT, 0, 1, 1, (void*)arr, n); }
+
+    int flags;
+    UMat* m;
+    const void* obj;
+    size_t sz;
+    int wscale, iwscale;
+};
+
+
+class CV_EXPORTS Kernel
+{
+public:
+    Kernel() CV_NOEXCEPT;
+    Kernel(const char* kname, const Program& prog);
+    Kernel(const char* kname, const ProgramSource& prog,
+           const String& buildopts = String(), String* errmsg=0);
+    ~Kernel();
+    Kernel(const Kernel& k);
+    Kernel& operator = (const Kernel& k);
+    Kernel(Kernel&& k) CV_NOEXCEPT;
+    Kernel& operator = (Kernel&& k) CV_NOEXCEPT;
+
+    bool empty() const;
+    bool create(const char* kname, const Program& prog);
+    bool create(const char* kname, const ProgramSource& prog,
+                const String& buildopts, String* errmsg=0);
+
+    int set(int i, const void* value, size_t sz);
+    int set(int i, const Image2D& image2D);
+    int set(int i, const UMat& m);
+    int set(int i, const KernelArg& arg);
+    template<typename _Tp> int set(int i, const _Tp& value)
+    { return set(i, &value, sizeof(value)); }
+
+
+protected:
+    template<typename _Tp0> inline
+    int set_args_(int i, const _Tp0& a0) { return set(i, a0); }
+    template<typename _Tp0, typename... _Tps> inline
+    int set_args_(int i, const _Tp0& a0, const _Tps&... rest_args) { i = set(i, a0); return set_args_(i, rest_args...); }
+public:
+    /** @brief Setup OpenCL Kernel arguments.
+    Avoid direct using of set(i, ...) methods.
+    @code
+    bool ok = kernel
+        .args(
+            srcUMat, dstUMat,
+            (float)some_float_param
+        ).run(ndims, globalSize, localSize);
+    if (!ok) return false;
+    @endcode
+    */
+    template<typename... _Tps> inline
+    Kernel& args(const _Tps&... kernel_args) { set_args_(0, kernel_args...); return *this; }
+
+    /** @brief Run the OpenCL kernel (globalsize value may be adjusted)
+
+    @param dims the work problem dimensions. It is the length of globalsize and localsize. It can be either 1, 2 or 3.
+    @param globalsize work items for each dimension. It is not the final globalsize passed to
+      OpenCL. Each dimension will be adjusted to the nearest integer divisible by the corresponding
+      value in localsize. If localsize is NULL, it will still be adjusted depending on dims. The
+      adjusted values are greater than or equal to the original values.
+    @param localsize work-group size for each dimension.
+    @param sync specify whether to wait for OpenCL computation to finish before return.
+    @param q command queue
+
+    @note Use run_() if your kernel code doesn't support adjusted globalsize.
+    */
+    bool run(int dims, size_t globalsize[],
+             size_t localsize[], bool sync, const Queue& q=Queue());
+
+    /** @brief Run the OpenCL kernel
+     *
+     * @param dims the work problem dimensions. It is the length of globalsize and localsize. It can be either 1, 2 or 3.
+     * @param globalsize work items for each dimension. This value is passed to OpenCL without changes.
+     * @param localsize work-group size for each dimension.
+     * @param sync specify whether to wait for OpenCL computation to finish before return.
+     * @param q command queue
+     */
+    bool run_(int dims, size_t globalsize[], size_t localsize[], bool sync, const Queue& q=Queue());
+
+    bool runTask(bool sync, const Queue& q=Queue());
+
+    /** @brief Similar to synchronized run_() call with returning of kernel execution time
+     *
+     * Separate OpenCL command queue may be used (with CL_QUEUE_PROFILING_ENABLE)
+     * @return Execution time in nanoseconds or negative number on error
+     */
+    int64 runProfiling(int dims, size_t globalsize[], size_t localsize[], const Queue& q=Queue());
+
+    size_t workGroupSize() const;
+    size_t preferedWorkGroupSizeMultiple() const;
+    bool compileWorkGroupSize(size_t wsz[]) const;
+    size_t localMemSize() const;
+
+    void* ptr() const;
+    struct Impl;
+
+protected:
+    Impl* p;
+};
+
+class CV_EXPORTS Program
+{
+public:
+    Program() CV_NOEXCEPT;
+    Program(const ProgramSource& src,
+            const String& buildflags, String& errmsg);
+    Program(const Program& prog);
+    Program& operator = (const Program& prog);
+    Program(Program&& prog) CV_NOEXCEPT;
+    Program& operator = (Program&& prog) CV_NOEXCEPT;
+    ~Program();
+
+    bool create(const ProgramSource& src,
+                const String& buildflags, String& errmsg);
+
+    void* ptr() const;
+
+    /**
+     * @brief Query device-specific program binary.
+     *
+     * Returns RAW OpenCL executable binary without additional attachments.
+     *
+     * @sa ProgramSource::fromBinary
+     *
+     * @param[out] binary output buffer
+     */
+    void getBinary(std::vector<char>& binary) const;
+
+    struct Impl; friend struct Impl;
+    inline Impl* getImpl() const { return (Impl*)p; }
+    inline bool empty() const { return !p; }
+protected:
+    Impl* p;
+public:
+#ifndef OPENCV_REMOVE_DEPRECATED_API
+    // TODO Remove this
+    CV_DEPRECATED bool read(const String& buf, const String& buildflags); // removed, use ProgramSource instead
+    CV_DEPRECATED bool write(String& buf) const; // removed, use getBinary() method instead (RAW OpenCL binary)
+    CV_DEPRECATED const ProgramSource& source() const; // implementation removed
+    CV_DEPRECATED String getPrefix() const; // deprecated, implementation replaced
+    CV_DEPRECATED static String getPrefix(const String& buildflags); // deprecated, implementation replaced
+#endif
+};
+
+
+class CV_EXPORTS ProgramSource
+{
+public:
+    typedef uint64 hash_t; // deprecated
+
+    ProgramSource() CV_NOEXCEPT;
+    explicit ProgramSource(const String& module, const String& name, const String& codeStr, const String& codeHash);
+    explicit ProgramSource(const String& prog); // deprecated
+    explicit ProgramSource(const char* prog); // deprecated
+    ~ProgramSource();
+    ProgramSource(const ProgramSource& prog);
+    ProgramSource& operator = (const ProgramSource& prog);
+    ProgramSource(ProgramSource&& prog) CV_NOEXCEPT;
+    ProgramSource& operator = (ProgramSource&& prog) CV_NOEXCEPT;
+
+    const String& source() const; // deprecated
+    hash_t hash() const; // deprecated
+
+
+    /** @brief Describe OpenCL program binary.
+     * Do not call clCreateProgramWithBinary() and/or clBuildProgram().
+     *
+     * Caller should guarantee binary buffer lifetime greater than ProgramSource object (and any of its copies).
+     *
+     * This kind of binary is not portable between platforms in general - it is specific to OpenCL vendor / device / driver version.
+     *
+     * @param module name of program owner module
+     * @param name unique name of program (module+name is used as key for OpenCL program caching)
+     * @param binary buffer address. See buffer lifetime requirement in description.
+     * @param size buffer size
+     * @param buildOptions additional program-related build options passed to clBuildProgram()
+     * @return created ProgramSource object
+     */
+    static ProgramSource fromBinary(const String& module, const String& name,
+            const unsigned char* binary, const size_t size,
+            const cv::String& buildOptions = cv::String());
+
+    /** @brief Describe OpenCL program in SPIR format.
+     * Do not call clCreateProgramWithBinary() and/or clBuildProgram().
+     *
+     * Supports SPIR 1.2 by default (pass '-spir-std=X.Y' in buildOptions to override this behavior)
+     *
+     * Caller should guarantee binary buffer lifetime greater than ProgramSource object (and any of its copies).
+     *
+     * Programs in this format are portable between OpenCL implementations with 'khr_spir' extension:
+     * https://www.khronos.org/registry/OpenCL/sdk/2.0/docs/man/xhtml/cl_khr_spir.html
+     * (but they are not portable between different platforms: 32-bit / 64-bit)
+     *
+     * Note: these programs can't support vendor specific extensions, like 'cl_intel_subgroups'.
+     *
+     * @param module name of program owner module
+     * @param name unique name of program (module+name is used as key for OpenCL program caching)
+     * @param binary buffer address. See buffer lifetime requirement in description.
+     * @param size buffer size
+     * @param buildOptions additional program-related build options passed to clBuildProgram()
+     *        (these options are added automatically: '-x spir' and '-spir-std=1.2')
+     * @return created ProgramSource object.
+     */
+    static ProgramSource fromSPIR(const String& module, const String& name,
+            const unsigned char* binary, const size_t size,
+            const cv::String& buildOptions = cv::String());
+
+    //OpenCL 2.1+ only
+    //static Program fromSPIRV(const String& module, const String& name,
+    //        const unsigned char* binary, const size_t size,
+    //        const cv::String& buildOptions = cv::String());
+
+    struct Impl; friend struct Impl;
+    inline Impl* getImpl() const { return (Impl*)p; }
+    inline bool empty() const { return !p; }
+protected:
+    Impl* p;
+};
+
+class CV_EXPORTS PlatformInfo
+{
+public:
+    PlatformInfo() CV_NOEXCEPT;
+    /**
+     * @param id pointer cl_platform_id (cl_platform_id*)
+     */
+    explicit PlatformInfo(void* id);
+    ~PlatformInfo();
+
+    PlatformInfo(const PlatformInfo& i);
+    PlatformInfo& operator =(const PlatformInfo& i);
+    PlatformInfo(PlatformInfo&& i) CV_NOEXCEPT;
+    PlatformInfo& operator = (PlatformInfo&& i) CV_NOEXCEPT;
+
+    String name() const;
+    String vendor() const;
+
+    /// See CL_PLATFORM_VERSION
+    String version() const;
+    int versionMajor() const;
+    int versionMinor() const;
+
+    int deviceNumber() const;
+    void getDevice(Device& device, int d) const;
+
+    struct Impl;
+    bool empty() const { return !p; }
+protected:
+    Impl* p;
+};
+
+CV_EXPORTS CV_DEPRECATED const char* convertTypeStr(int sdepth, int ddepth, int cn, char* buf);
+CV_EXPORTS const char* convertTypeStr(int sdepth, int ddepth, int cn, char* buf, size_t buf_size);
+CV_EXPORTS const char* typeToStr(int t);
+CV_EXPORTS const char* memopTypeToStr(int t);
+CV_EXPORTS const char* vecopTypeToStr(int t);
+CV_EXPORTS const char* getOpenCLErrorString(int errorCode);
+CV_EXPORTS String kernelToStr(InputArray _kernel, int ddepth = -1, const char * name = NULL);
+CV_EXPORTS void getPlatfomsInfo(std::vector<PlatformInfo>& platform_info);
+
+
+enum OclVectorStrategy
+{
+    // all matrices have its own vector width
+    OCL_VECTOR_OWN = 0,
+    // all matrices have maximal vector width among all matrices
+    // (useful for cases when matrices have different data types)
+    OCL_VECTOR_MAX = 1,
+
+    // default strategy
+    OCL_VECTOR_DEFAULT = OCL_VECTOR_OWN
+};
+
+CV_EXPORTS int predictOptimalVectorWidth(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
+                                         InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
+                                         InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(),
+                                         OclVectorStrategy strat = OCL_VECTOR_DEFAULT);
+
+CV_EXPORTS int checkOptimalVectorWidth(const int *vectorWidths,
+                                       InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
+                                       InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
+                                       InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(),
+                                       OclVectorStrategy strat = OCL_VECTOR_DEFAULT);
+
+// with OCL_VECTOR_MAX strategy
+CV_EXPORTS int predictOptimalVectorWidthMax(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
+                                            InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
+                                            InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray());
+
+CV_EXPORTS void buildOptionsAddMatrixDescription(String& buildOptions, const String& name, InputArray _m);
+
+class CV_EXPORTS Image2D
+{
+public:
+    Image2D() CV_NOEXCEPT;
+
+    /**
+    @param src UMat object from which to get image properties and data
+    @param norm flag to enable the use of normalized channel data types
+    @param alias flag indicating that the image should alias the src UMat. If true, changes to the
+        image or src will be reflected in both objects.
+    */
+    explicit Image2D(const UMat &src, bool norm = false, bool alias = false);
+    Image2D(const Image2D & i);
+    ~Image2D();
+
+    Image2D & operator = (const Image2D & i);
+    Image2D(Image2D &&) CV_NOEXCEPT;
+    Image2D &operator=(Image2D &&) CV_NOEXCEPT;
+
+    /** Indicates if creating an aliased image should succeed.
+    Depends on the underlying platform and the dimensions of the UMat.
+    */
+    static bool canCreateAlias(const UMat &u);
+
+    /** Indicates if the image format is supported.
+    */
+    static bool isFormatSupported(int depth, int cn, bool norm);
+
+    void* ptr() const;
+protected:
+    struct Impl;
+    Impl* p;
+};
+
+class CV_EXPORTS Timer
+{
+public:
+    Timer(const Queue& q);
+    ~Timer();
+    void start();
+    void stop();
+
+    uint64 durationNS() const; ///< duration in nanoseconds
+
+protected:
+    struct Impl;
+    Impl* const p;
+
+private:
+    Timer(const Timer&); // disabled
+    Timer& operator=(const Timer&); // disabled
+};
+
+CV_EXPORTS MatAllocator* getOpenCLAllocator();
+
+
+class CV_EXPORTS_W OpenCLExecutionContext
+{
+public:
+    OpenCLExecutionContext() = default;
+    ~OpenCLExecutionContext() = default;
+
+    OpenCLExecutionContext(const OpenCLExecutionContext&) = default;
+    OpenCLExecutionContext(OpenCLExecutionContext&&) = default;
+
+    OpenCLExecutionContext& operator=(const OpenCLExecutionContext&) = default;
+    OpenCLExecutionContext& operator=(OpenCLExecutionContext&&) = default;
+
+    /** Get associated ocl::Context */
+    Context& getContext() const;
+    /** Get the single default associated ocl::Device */
+    Device& getDevice() const;
+    /** Get the single ocl::Queue that is associated with the ocl::Context and
+     *  the single default ocl::Device
+     */
+    Queue& getQueue() const;
+
+    bool useOpenCL() const;
+    void setUseOpenCL(bool flag);
+
+    /** Get OpenCL execution context of current thread.
+     *
+     * Initialize OpenCL execution context if it is empty
+     * - create new
+     * - reuse context of the main thread (threadID = 0)
+     */
+    static OpenCLExecutionContext& getCurrent();
+
+    /** Get OpenCL execution context of current thread (can be empty) */
+    static OpenCLExecutionContext& getCurrentRef();
+
+    /** Bind this OpenCL execution context to current thread.
+     *
+     * Context can't be empty.
+     *
+     * @note clFinish is not called for queue of previous execution context
+     */
+    void bind() const;
+
+    /** Creates new execution context with same OpenCV context and device
+     *
+     * @param q OpenCL queue
+     */
+    OpenCLExecutionContext cloneWithNewQueue(const ocl::Queue& q) const;
+    /** @overload */
+    OpenCLExecutionContext cloneWithNewQueue() const;
+
+    /** @brief Creates OpenCL execution context
+     * OpenCV will check if available OpenCL platform has platformName name,
+     * then assign context to OpenCV.
+     * The deviceID device will be used as target device and a new command queue will be created.
+     *
+     * @note On success, ownership of one reference of the context and device is taken.
+     * The caller should additionally call `clRetainContext` and/or `clRetainDevice`
+     * to increase the reference count if it wishes to continue using them.
+     *
+     * @param platformName name of OpenCL platform to attach, this string is used to check if platform is available to OpenCV at runtime
+     * @param platformID ID of platform attached context was created for (cl_platform_id)
+     * @param context OpenCL context to be attached to OpenCV (cl_context)
+     * @param deviceID OpenCL device (cl_device_id)
+     */
+    static OpenCLExecutionContext create(const std::string& platformName, void* platformID, void* context, void* deviceID);
+
+    /** @brief Creates OpenCL execution context
+     *
+     * @param context non-empty OpenCL context
+     * @param device non-empty OpenCL device (must be a part of context)
+     * @param queue non-empty OpenCL queue for provided context and device
+     */
+    static OpenCLExecutionContext create(const Context& context, const Device& device, const ocl::Queue& queue);
+    /** @overload */
+    static OpenCLExecutionContext create(const Context& context, const Device& device);
+
+    struct Impl;
+    inline bool empty() const { return !p; }
+    void release();
+protected:
+    std::shared_ptr<Impl> p;
+};
+
+class OpenCLExecutionContextScope
+{
+    OpenCLExecutionContext ctx_;
+public:
+    inline OpenCLExecutionContextScope(const OpenCLExecutionContext& ctx)
+    {
+        CV_Assert(!ctx.empty());
+        ctx_ = OpenCLExecutionContext::getCurrentRef();
+        ctx.bind();
+    }
+
+    inline ~OpenCLExecutionContextScope()
+    {
+        if (!ctx_.empty())
+        {
+            ctx_.bind();
+        }
+    }
+};
+
+#ifdef __OPENCV_BUILD
+namespace internal {
+
+CV_EXPORTS bool isOpenCLForced();
+#define OCL_FORCE_CHECK(condition) (cv::ocl::internal::isOpenCLForced() || (condition))
+
+CV_EXPORTS bool isPerformanceCheckBypassed();
+#define OCL_PERFORMANCE_CHECK(condition) (cv::ocl::internal::isPerformanceCheckBypassed() || (condition))
+
+CV_EXPORTS bool isCLBuffer(UMat& u);
+
+} // namespace internal
+#endif
+
+//! @}
+
+}}
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/ocl_genbase.hpp

@@ -0,0 +1,69 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the OpenCV Foundation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_OPENCL_GENBASE_HPP
+#define OPENCV_OPENCL_GENBASE_HPP
+
+//! @cond IGNORED
+
+namespace cv {
+namespace ocl {
+
+class ProgramSource;
+
+namespace internal {
+
+struct CV_EXPORTS ProgramEntry
+{
+    const char* module;
+    const char* name;
+    const char* programCode;
+    const char* programHash;
+    ProgramSource* pProgramSource;
+
+    operator ProgramSource& () const;
+};
+
+} } } // namespace
+
+//! @endcond
+
+#endif

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/ocl_defs.hpp

@@ -0,0 +1,82 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+
+#ifndef OPENCV_CORE_OPENCL_DEFS_HPP
+#define OPENCV_CORE_OPENCL_DEFS_HPP
+
+#include "opencv2/core/utility.hpp"
+#include "cvconfig.h"
+
+namespace cv { namespace ocl {
+#ifdef HAVE_OPENCL
+/// Call is similar to useOpenCL() but doesn't try to load OpenCL runtime or create OpenCL context
+CV_EXPORTS bool isOpenCLActivated();
+#else
+static inline bool isOpenCLActivated() { return false; }
+#endif
+}} // namespace
+
+
+//#define CV_OPENCL_RUN_ASSERT
+
+#ifdef HAVE_OPENCL
+
+#ifdef CV_OPENCL_RUN_VERBOSE
+#define CV_OCL_RUN_(condition, func, ...)                                   \
+    {                                                                       \
+        if (cv::ocl::isOpenCLActivated() && (condition) && func)            \
+        {                                                                   \
+            printf("%s: OpenCL implementation is running\n", CV_Func);      \
+            fflush(stdout);                                                 \
+            CV_IMPL_ADD(CV_IMPL_OCL);                                       \
+            return __VA_ARGS__;                                             \
+        }                                                                   \
+        else                                                                \
+        {                                                                   \
+            printf("%s: Plain implementation is running\n", CV_Func);       \
+            fflush(stdout);                                                 \
+        }                                                                   \
+    }
+#elif defined CV_OPENCL_RUN_ASSERT
+#define CV_OCL_RUN_(condition, func, ...)                                   \
+    {                                                                       \
+        if (cv::ocl::isOpenCLActivated() && (condition))                    \
+        {                                                                   \
+            if(func)                                                        \
+            {                                                               \
+                CV_IMPL_ADD(CV_IMPL_OCL);                                   \
+            }                                                               \
+            else                                                            \
+            {                                                               \
+                CV_Error(cv::Error::StsAssert, #func);                      \
+            }                                                               \
+            return __VA_ARGS__;                                             \
+        }                                                                   \
+    }
+#else
+#define CV_OCL_RUN_(condition, func, ...)                                   \
+try \
+{ \
+    if (cv::ocl::isOpenCLActivated() && (condition) && func)                \
+    {                                                                       \
+        CV_IMPL_ADD(CV_IMPL_OCL);                                           \
+        return __VA_ARGS__;                                                 \
+    } \
+} \
+catch (const cv::Exception& e) \
+{ \
+    CV_UNUSED(e); /* TODO: Add some logging here */ \
+}
+#endif
+
+#else
+#define CV_OCL_RUN_(condition, func, ...)
+#endif
+
+#define CV_OCL_RUN(condition, func) CV_OCL_RUN_(condition, func)
+
+#endif // OPENCV_CORE_OPENCL_DEFS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/opencl_info.hpp

@@ -0,0 +1,213 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#include <iostream>
+#include <sstream>
+
+#include <opencv2/core.hpp>
+#include <opencv2/core/ocl.hpp>
+
+#ifndef DUMP_CONFIG_PROPERTY
+#define DUMP_CONFIG_PROPERTY(...)
+#endif
+
+#ifndef DUMP_MESSAGE_STDOUT
+#define DUMP_MESSAGE_STDOUT(...) do { std::cout << __VA_ARGS__ << std::endl; } while (false)
+#endif
+
+namespace cv {
+
+namespace {
+static std::string bytesToStringRepr(size_t value)
+{
+    size_t b = value % 1024;
+    value /= 1024;
+
+    size_t kb = value % 1024;
+    value /= 1024;
+
+    size_t mb = value % 1024;
+    value /= 1024;
+
+    size_t gb = value;
+
+    std::ostringstream stream;
+
+    if (gb > 0)
+        stream << gb << " GB ";
+    if (mb > 0)
+        stream << mb << " MB ";
+    if (kb > 0)
+        stream << kb << " KB ";
+    if (b > 0)
+        stream << b << " B";
+
+    std::string s = stream.str();
+    if (s[s.size() - 1] == ' ')
+        s = s.substr(0, s.size() - 1);
+    return s;
+}
+
+static String getDeviceTypeString(const cv::ocl::Device& device)
+{
+    if (device.type() == cv::ocl::Device::TYPE_CPU) {
+        return "CPU";
+    }
+
+    if (device.type() == cv::ocl::Device::TYPE_GPU) {
+        if (device.hostUnifiedMemory()) {
+            return "iGPU";
+        } else {
+            return "dGPU";
+        }
+    }
+
+    return "unknown";
+}
+} // namespace
+
+static void dumpOpenCLInformation()
+{
+    using namespace cv::ocl;
+
+    try
+    {
+        if (!haveOpenCL() || !useOpenCL())
+        {
+            DUMP_MESSAGE_STDOUT("OpenCL is disabled");
+            DUMP_CONFIG_PROPERTY("cv_ocl", "disabled");
+            return;
+        }
+
+        std::vector<PlatformInfo> platforms;
+        cv::ocl::getPlatfomsInfo(platforms);
+        if (platforms.empty())
+        {
+            DUMP_MESSAGE_STDOUT("OpenCL is not available");
+            DUMP_CONFIG_PROPERTY("cv_ocl", "not available");
+            return;
+        }
+
+        DUMP_MESSAGE_STDOUT("OpenCL Platforms: ");
+        for (size_t i = 0; i < platforms.size(); i++)
+        {
+            const PlatformInfo* platform = &platforms[i];
+            DUMP_MESSAGE_STDOUT("    " << platform->name());
+            Device current_device;
+            for (int j = 0; j < platform->deviceNumber(); j++)
+            {
+                platform->getDevice(current_device, j);
+                String deviceTypeStr = getDeviceTypeString(current_device);
+                DUMP_MESSAGE_STDOUT( "        " << deviceTypeStr << ": " << current_device.name() << " (" << current_device.version() << ")");
+                DUMP_CONFIG_PROPERTY( cv::format("cv_ocl_platform_%d_device_%d", (int)i, j ),
+                    cv::format("(Platform=%s)(Type=%s)(Name=%s)(Version=%s)",
+                    platform->name().c_str(), deviceTypeStr.c_str(), current_device.name().c_str(), current_device.version().c_str()) );
+            }
+        }
+        const Device& device = Device::getDefault();
+        if (!device.available())
+            CV_Error(Error::OpenCLInitError, "OpenCL device is not available");
+
+        DUMP_MESSAGE_STDOUT("Current OpenCL device: ");
+
+        String deviceTypeStr = getDeviceTypeString(device);
+        DUMP_MESSAGE_STDOUT("    Type = " << deviceTypeStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_deviceType", deviceTypeStr);
+
+        DUMP_MESSAGE_STDOUT("    Name = " << device.name());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_deviceName", device.name());
+
+        DUMP_MESSAGE_STDOUT("    Version = " << device.version());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_deviceVersion", device.version());
+
+        DUMP_MESSAGE_STDOUT("    Driver version = " << device.driverVersion());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_driverVersion", device.driverVersion());
+
+        DUMP_MESSAGE_STDOUT("    Address bits = " << device.addressBits());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_addressBits", device.addressBits());
+
+        DUMP_MESSAGE_STDOUT("    Compute units = " << device.maxComputeUnits());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_maxComputeUnits", device.maxComputeUnits());
+
+        DUMP_MESSAGE_STDOUT("    Max work group size = " << device.maxWorkGroupSize());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_maxWorkGroupSize", device.maxWorkGroupSize());
+
+        std::string localMemorySizeStr = bytesToStringRepr(device.localMemSize());
+        DUMP_MESSAGE_STDOUT("    Local memory size = " << localMemorySizeStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_localMemSize", device.localMemSize());
+
+        std::string maxMemAllocSizeStr = bytesToStringRepr(device.maxMemAllocSize());
+        DUMP_MESSAGE_STDOUT("    Max memory allocation size = " << maxMemAllocSizeStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_maxMemAllocSize", device.maxMemAllocSize());
+
+        const char* doubleSupportStr = device.hasFP64() ? "Yes" : "No";
+        DUMP_MESSAGE_STDOUT("    Double support = " << doubleSupportStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_haveDoubleSupport", device.hasFP64());
+
+        const char* halfSupportStr = device.hasFP16() ? "Yes" : "No";
+        DUMP_MESSAGE_STDOUT("    Half support = " << halfSupportStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_haveHalfSupport", device.hasFP16());
+
+        const char* isUnifiedMemoryStr = device.hostUnifiedMemory() ? "Yes" : "No";
+        DUMP_MESSAGE_STDOUT("    Host unified memory = " << isUnifiedMemoryStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_hostUnifiedMemory", device.hostUnifiedMemory());
+
+        DUMP_MESSAGE_STDOUT("    Device extensions:");
+        String extensionsStr = device.extensions();
+        size_t pos = 0;
+        while (pos < extensionsStr.size())
+        {
+            size_t pos2 = extensionsStr.find(' ', pos);
+            if (pos2 == String::npos)
+                pos2 = extensionsStr.size();
+            if (pos2 > pos)
+            {
+                String extensionName = extensionsStr.substr(pos, pos2 - pos);
+                DUMP_MESSAGE_STDOUT("        " << extensionName);
+            }
+            pos = pos2 + 1;
+        }
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_extensions", extensionsStr);
+
+        const char* haveAmdBlasStr = haveAmdBlas() ? "Yes" : "No";
+        DUMP_MESSAGE_STDOUT("    Has AMD Blas = " << haveAmdBlasStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_AmdBlas", haveAmdBlas());
+
+        const char* haveAmdFftStr = haveAmdFft() ? "Yes" : "No";
+        DUMP_MESSAGE_STDOUT("    Has AMD Fft = " << haveAmdFftStr);
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_AmdFft", haveAmdFft());
+
+
+        DUMP_MESSAGE_STDOUT("    Preferred vector width char = " << device.preferredVectorWidthChar());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthChar", device.preferredVectorWidthChar());
+
+        DUMP_MESSAGE_STDOUT("    Preferred vector width short = " << device.preferredVectorWidthShort());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthShort", device.preferredVectorWidthShort());
+
+        DUMP_MESSAGE_STDOUT("    Preferred vector width int = " << device.preferredVectorWidthInt());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthInt", device.preferredVectorWidthInt());
+
+        DUMP_MESSAGE_STDOUT("    Preferred vector width long = " << device.preferredVectorWidthLong());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthLong", device.preferredVectorWidthLong());
+
+        DUMP_MESSAGE_STDOUT("    Preferred vector width float = " << device.preferredVectorWidthFloat());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthFloat", device.preferredVectorWidthFloat());
+
+        DUMP_MESSAGE_STDOUT("    Preferred vector width double = " << device.preferredVectorWidthDouble());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthDouble", device.preferredVectorWidthDouble());
+
+        DUMP_MESSAGE_STDOUT("    Preferred vector width half = " << device.preferredVectorWidthHalf());
+        DUMP_CONFIG_PROPERTY("cv_ocl_current_preferredVectorWidthHalf", device.preferredVectorWidthHalf());
+    }
+    catch (...)
+    {
+        DUMP_MESSAGE_STDOUT("Exception. Can't dump OpenCL info");
+        DUMP_MESSAGE_STDOUT("OpenCL device not available");
+        DUMP_CONFIG_PROPERTY("cv_ocl", "not available");
+    }
+}
+#undef DUMP_MESSAGE_STDOUT
+#undef DUMP_CONFIG_PROPERTY
+
+} // namespace

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/opencl_svm.hpp

@@ -0,0 +1,81 @@
+/* See LICENSE file in the root OpenCV directory */
+
+#ifndef OPENCV_CORE_OPENCL_SVM_HPP
+#define OPENCV_CORE_OPENCL_SVM_HPP
+
+//
+// Internal usage only (binary compatibility is not guaranteed)
+//
+#ifndef __OPENCV_BUILD
+#error Internal header file
+#endif
+
+#if defined(HAVE_OPENCL) && defined(HAVE_OPENCL_SVM)
+#include "runtime/opencl_core.hpp"
+#include "runtime/opencl_svm_20.hpp"
+#include "runtime/opencl_svm_hsa_extension.hpp"
+
+namespace cv { namespace ocl { namespace svm {
+
+struct SVMCapabilities
+{
+    enum Value
+    {
+        SVM_COARSE_GRAIN_BUFFER = (1 << 0),
+        SVM_FINE_GRAIN_BUFFER = (1 << 1),
+        SVM_FINE_GRAIN_SYSTEM = (1 << 2),
+        SVM_ATOMICS = (1 << 3),
+    };
+    int value_;
+
+    SVMCapabilities(int capabilities = 0) : value_(capabilities) { }
+    operator int() const { return value_; }
+
+    inline bool isNoSVMSupport() const { return value_ == 0; }
+    inline bool isSupportCoarseGrainBuffer() const { return (value_ & SVM_COARSE_GRAIN_BUFFER) != 0; }
+    inline bool isSupportFineGrainBuffer() const { return (value_ & SVM_FINE_GRAIN_BUFFER) != 0; }
+    inline bool isSupportFineGrainSystem() const { return (value_ & SVM_FINE_GRAIN_SYSTEM) != 0; }
+    inline bool isSupportAtomics() const { return (value_ & SVM_ATOMICS) != 0; }
+};
+
+CV_EXPORTS const SVMCapabilities getSVMCapabilitites(const ocl::Context& context);
+
+struct SVMFunctions
+{
+    clSVMAllocAMD_fn fn_clSVMAlloc;
+    clSVMFreeAMD_fn fn_clSVMFree;
+    clSetKernelArgSVMPointerAMD_fn fn_clSetKernelArgSVMPointer;
+    //clSetKernelExecInfoAMD_fn fn_clSetKernelExecInfo;
+    //clEnqueueSVMFreeAMD_fn fn_clEnqueueSVMFree;
+    clEnqueueSVMMemcpyAMD_fn fn_clEnqueueSVMMemcpy;
+    clEnqueueSVMMemFillAMD_fn fn_clEnqueueSVMMemFill;
+    clEnqueueSVMMapAMD_fn fn_clEnqueueSVMMap;
+    clEnqueueSVMUnmapAMD_fn fn_clEnqueueSVMUnmap;
+
+    inline SVMFunctions()
+        : fn_clSVMAlloc(NULL), fn_clSVMFree(NULL),
+          fn_clSetKernelArgSVMPointer(NULL), /*fn_clSetKernelExecInfo(NULL),*/
+          /*fn_clEnqueueSVMFree(NULL),*/ fn_clEnqueueSVMMemcpy(NULL), fn_clEnqueueSVMMemFill(NULL),
+          fn_clEnqueueSVMMap(NULL), fn_clEnqueueSVMUnmap(NULL)
+    {
+        // nothing
+    }
+
+    inline bool isValid() const
+    {
+        return fn_clSVMAlloc != NULL && fn_clSVMFree && fn_clSetKernelArgSVMPointer &&
+                /*fn_clSetKernelExecInfo && fn_clEnqueueSVMFree &&*/ fn_clEnqueueSVMMemcpy &&
+                fn_clEnqueueSVMMemFill && fn_clEnqueueSVMMap && fn_clEnqueueSVMUnmap;
+    }
+};
+
+// We should guarantee that SVMFunctions lifetime is not less than context's lifetime
+CV_EXPORTS const SVMFunctions* getSVMFunctions(const ocl::Context& context);
+
+CV_EXPORTS bool useSVM(UMatUsageFlags usageFlags);
+
+}}} //namespace cv::ocl::svm
+#endif
+
+#endif // OPENCV_CORE_OPENCL_SVM_HPP
+/* End of file. */

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/autogenerated/opencl_clblas.hpp

@@ -0,0 +1,602 @@
+//
+// AUTOGENERATED, DO NOT EDIT
+//
+#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP
+#error "Invalid usage"
+#endif
+
+// generated by parser_clblas.py
+#define clblasCaxpy clblasCaxpy_
+#define clblasCcopy clblasCcopy_
+#define clblasCdotc clblasCdotc_
+#define clblasCdotu clblasCdotu_
+#define clblasCgbmv clblasCgbmv_
+#define clblasCgemm clblasCgemm_
+#define clblasCgemv clblasCgemv_
+#define clblasCgerc clblasCgerc_
+#define clblasCgeru clblasCgeru_
+#define clblasChbmv clblasChbmv_
+#define clblasChemm clblasChemm_
+#define clblasChemv clblasChemv_
+#define clblasCher clblasCher_
+#define clblasCher2 clblasCher2_
+#define clblasCher2k clblasCher2k_
+#define clblasCherk clblasCherk_
+#define clblasChpmv clblasChpmv_
+#define clblasChpr clblasChpr_
+#define clblasChpr2 clblasChpr2_
+#define clblasCrotg clblasCrotg_
+#define clblasCscal clblasCscal_
+#define clblasCsrot clblasCsrot_
+#define clblasCsscal clblasCsscal_
+#define clblasCswap clblasCswap_
+#define clblasCsymm clblasCsymm_
+#define clblasCsyr2k clblasCsyr2k_
+#define clblasCsyrk clblasCsyrk_
+#define clblasCtbmv clblasCtbmv_
+#define clblasCtbsv clblasCtbsv_
+#define clblasCtpmv clblasCtpmv_
+#define clblasCtpsv clblasCtpsv_
+#define clblasCtrmm clblasCtrmm_
+#define clblasCtrmv clblasCtrmv_
+#define clblasCtrsm clblasCtrsm_
+#define clblasCtrsv clblasCtrsv_
+#define clblasDasum clblasDasum_
+#define clblasDaxpy clblasDaxpy_
+#define clblasDcopy clblasDcopy_
+#define clblasDdot clblasDdot_
+#define clblasDgbmv clblasDgbmv_
+#define clblasDgemm clblasDgemm_
+#define clblasDgemv clblasDgemv_
+#define clblasDger clblasDger_
+#define clblasDnrm2 clblasDnrm2_
+#define clblasDrot clblasDrot_
+#define clblasDrotg clblasDrotg_
+#define clblasDrotm clblasDrotm_
+#define clblasDrotmg clblasDrotmg_
+#define clblasDsbmv clblasDsbmv_
+#define clblasDscal clblasDscal_
+#define clblasDspmv clblasDspmv_
+#define clblasDspr clblasDspr_
+#define clblasDspr2 clblasDspr2_
+#define clblasDswap clblasDswap_
+#define clblasDsymm clblasDsymm_
+#define clblasDsymv clblasDsymv_
+#define clblasDsyr clblasDsyr_
+#define clblasDsyr2 clblasDsyr2_
+#define clblasDsyr2k clblasDsyr2k_
+#define clblasDsyrk clblasDsyrk_
+#define clblasDtbmv clblasDtbmv_
+#define clblasDtbsv clblasDtbsv_
+#define clblasDtpmv clblasDtpmv_
+#define clblasDtpsv clblasDtpsv_
+#define clblasDtrmm clblasDtrmm_
+#define clblasDtrmv clblasDtrmv_
+#define clblasDtrsm clblasDtrsm_
+#define clblasDtrsv clblasDtrsv_
+#define clblasDzasum clblasDzasum_
+#define clblasDznrm2 clblasDznrm2_
+#define clblasGetVersion clblasGetVersion_
+#define clblasSasum clblasSasum_
+#define clblasSaxpy clblasSaxpy_
+#define clblasScasum clblasScasum_
+#define clblasScnrm2 clblasScnrm2_
+#define clblasScopy clblasScopy_
+#define clblasSdot clblasSdot_
+#define clblasSetup clblasSetup_
+#define clblasSgbmv clblasSgbmv_
+#define clblasSgemm clblasSgemm_
+#define clblasSgemv clblasSgemv_
+#define clblasSger clblasSger_
+#define clblasSnrm2 clblasSnrm2_
+#define clblasSrot clblasSrot_
+#define clblasSrotg clblasSrotg_
+#define clblasSrotm clblasSrotm_
+#define clblasSrotmg clblasSrotmg_
+#define clblasSsbmv clblasSsbmv_
+#define clblasSscal clblasSscal_
+#define clblasSspmv clblasSspmv_
+#define clblasSspr clblasSspr_
+#define clblasSspr2 clblasSspr2_
+#define clblasSswap clblasSswap_
+#define clblasSsymm clblasSsymm_
+#define clblasSsymv clblasSsymv_
+#define clblasSsyr clblasSsyr_
+#define clblasSsyr2 clblasSsyr2_
+#define clblasSsyr2k clblasSsyr2k_
+#define clblasSsyrk clblasSsyrk_
+#define clblasStbmv clblasStbmv_
+#define clblasStbsv clblasStbsv_
+#define clblasStpmv clblasStpmv_
+#define clblasStpsv clblasStpsv_
+#define clblasStrmm clblasStrmm_
+#define clblasStrmv clblasStrmv_
+#define clblasStrsm clblasStrsm_
+#define clblasStrsv clblasStrsv_
+#define clblasTeardown clblasTeardown_
+#define clblasZaxpy clblasZaxpy_
+#define clblasZcopy clblasZcopy_
+#define clblasZdotc clblasZdotc_
+#define clblasZdotu clblasZdotu_
+#define clblasZdrot clblasZdrot_
+#define clblasZdscal clblasZdscal_
+#define clblasZgbmv clblasZgbmv_
+#define clblasZgemm clblasZgemm_
+#define clblasZgemv clblasZgemv_
+#define clblasZgerc clblasZgerc_
+#define clblasZgeru clblasZgeru_
+#define clblasZhbmv clblasZhbmv_
+#define clblasZhemm clblasZhemm_
+#define clblasZhemv clblasZhemv_
+#define clblasZher clblasZher_
+#define clblasZher2 clblasZher2_
+#define clblasZher2k clblasZher2k_
+#define clblasZherk clblasZherk_
+#define clblasZhpmv clblasZhpmv_
+#define clblasZhpr clblasZhpr_
+#define clblasZhpr2 clblasZhpr2_
+#define clblasZrotg clblasZrotg_
+#define clblasZscal clblasZscal_
+#define clblasZswap clblasZswap_
+#define clblasZsymm clblasZsymm_
+#define clblasZsyr2k clblasZsyr2k_
+#define clblasZsyrk clblasZsyrk_
+#define clblasZtbmv clblasZtbmv_
+#define clblasZtbsv clblasZtbsv_
+#define clblasZtpmv clblasZtpmv_
+#define clblasZtpsv clblasZtpsv_
+#define clblasZtrmm clblasZtrmm_
+#define clblasZtrmv clblasZtrmv_
+#define clblasZtrsm clblasZtrsm_
+#define clblasZtrsv clblasZtrsv_
+#define clblasiCamax clblasiCamax_
+#define clblasiDamax clblasiDamax_
+#define clblasiSamax clblasiSamax_
+#define clblasiZamax clblasiZamax_
+
+#include <clBLAS.h>
+
+// generated by parser_clblas.py
+#undef clblasCaxpy
+//#define clblasCaxpy clblasCaxpy_pfn
+#undef clblasCcopy
+//#define clblasCcopy clblasCcopy_pfn
+#undef clblasCdotc
+//#define clblasCdotc clblasCdotc_pfn
+#undef clblasCdotu
+//#define clblasCdotu clblasCdotu_pfn
+#undef clblasCgbmv
+//#define clblasCgbmv clblasCgbmv_pfn
+#undef clblasCgemm
+#define clblasCgemm clblasCgemm_pfn
+#undef clblasCgemv
+//#define clblasCgemv clblasCgemv_pfn
+#undef clblasCgerc
+//#define clblasCgerc clblasCgerc_pfn
+#undef clblasCgeru
+//#define clblasCgeru clblasCgeru_pfn
+#undef clblasChbmv
+//#define clblasChbmv clblasChbmv_pfn
+#undef clblasChemm
+//#define clblasChemm clblasChemm_pfn
+#undef clblasChemv
+//#define clblasChemv clblasChemv_pfn
+#undef clblasCher
+//#define clblasCher clblasCher_pfn
+#undef clblasCher2
+//#define clblasCher2 clblasCher2_pfn
+#undef clblasCher2k
+//#define clblasCher2k clblasCher2k_pfn
+#undef clblasCherk
+//#define clblasCherk clblasCherk_pfn
+#undef clblasChpmv
+//#define clblasChpmv clblasChpmv_pfn
+#undef clblasChpr
+//#define clblasChpr clblasChpr_pfn
+#undef clblasChpr2
+//#define clblasChpr2 clblasChpr2_pfn
+#undef clblasCrotg
+//#define clblasCrotg clblasCrotg_pfn
+#undef clblasCscal
+//#define clblasCscal clblasCscal_pfn
+#undef clblasCsrot
+//#define clblasCsrot clblasCsrot_pfn
+#undef clblasCsscal
+//#define clblasCsscal clblasCsscal_pfn
+#undef clblasCswap
+//#define clblasCswap clblasCswap_pfn
+#undef clblasCsymm
+//#define clblasCsymm clblasCsymm_pfn
+#undef clblasCsyr2k
+//#define clblasCsyr2k clblasCsyr2k_pfn
+#undef clblasCsyrk
+//#define clblasCsyrk clblasCsyrk_pfn
+#undef clblasCtbmv
+//#define clblasCtbmv clblasCtbmv_pfn
+#undef clblasCtbsv
+//#define clblasCtbsv clblasCtbsv_pfn
+#undef clblasCtpmv
+//#define clblasCtpmv clblasCtpmv_pfn
+#undef clblasCtpsv
+//#define clblasCtpsv clblasCtpsv_pfn
+#undef clblasCtrmm
+//#define clblasCtrmm clblasCtrmm_pfn
+#undef clblasCtrmv
+//#define clblasCtrmv clblasCtrmv_pfn
+#undef clblasCtrsm
+//#define clblasCtrsm clblasCtrsm_pfn
+#undef clblasCtrsv
+//#define clblasCtrsv clblasCtrsv_pfn
+#undef clblasDasum
+//#define clblasDasum clblasDasum_pfn
+#undef clblasDaxpy
+//#define clblasDaxpy clblasDaxpy_pfn
+#undef clblasDcopy
+//#define clblasDcopy clblasDcopy_pfn
+#undef clblasDdot
+//#define clblasDdot clblasDdot_pfn
+#undef clblasDgbmv
+//#define clblasDgbmv clblasDgbmv_pfn
+#undef clblasDgemm
+#define clblasDgemm clblasDgemm_pfn
+#undef clblasDgemv
+//#define clblasDgemv clblasDgemv_pfn
+#undef clblasDger
+//#define clblasDger clblasDger_pfn
+#undef clblasDnrm2
+//#define clblasDnrm2 clblasDnrm2_pfn
+#undef clblasDrot
+//#define clblasDrot clblasDrot_pfn
+#undef clblasDrotg
+//#define clblasDrotg clblasDrotg_pfn
+#undef clblasDrotm
+//#define clblasDrotm clblasDrotm_pfn
+#undef clblasDrotmg
+//#define clblasDrotmg clblasDrotmg_pfn
+#undef clblasDsbmv
+//#define clblasDsbmv clblasDsbmv_pfn
+#undef clblasDscal
+//#define clblasDscal clblasDscal_pfn
+#undef clblasDspmv
+//#define clblasDspmv clblasDspmv_pfn
+#undef clblasDspr
+//#define clblasDspr clblasDspr_pfn
+#undef clblasDspr2
+//#define clblasDspr2 clblasDspr2_pfn
+#undef clblasDswap
+//#define clblasDswap clblasDswap_pfn
+#undef clblasDsymm
+//#define clblasDsymm clblasDsymm_pfn
+#undef clblasDsymv
+//#define clblasDsymv clblasDsymv_pfn
+#undef clblasDsyr
+//#define clblasDsyr clblasDsyr_pfn
+#undef clblasDsyr2
+//#define clblasDsyr2 clblasDsyr2_pfn
+#undef clblasDsyr2k
+//#define clblasDsyr2k clblasDsyr2k_pfn
+#undef clblasDsyrk
+//#define clblasDsyrk clblasDsyrk_pfn
+#undef clblasDtbmv
+//#define clblasDtbmv clblasDtbmv_pfn
+#undef clblasDtbsv
+//#define clblasDtbsv clblasDtbsv_pfn
+#undef clblasDtpmv
+//#define clblasDtpmv clblasDtpmv_pfn
+#undef clblasDtpsv
+//#define clblasDtpsv clblasDtpsv_pfn
+#undef clblasDtrmm
+//#define clblasDtrmm clblasDtrmm_pfn
+#undef clblasDtrmv
+//#define clblasDtrmv clblasDtrmv_pfn
+#undef clblasDtrsm
+//#define clblasDtrsm clblasDtrsm_pfn
+#undef clblasDtrsv
+//#define clblasDtrsv clblasDtrsv_pfn
+#undef clblasDzasum
+//#define clblasDzasum clblasDzasum_pfn
+#undef clblasDznrm2
+//#define clblasDznrm2 clblasDznrm2_pfn
+#undef clblasGetVersion
+//#define clblasGetVersion clblasGetVersion_pfn
+#undef clblasSasum
+//#define clblasSasum clblasSasum_pfn
+#undef clblasSaxpy
+//#define clblasSaxpy clblasSaxpy_pfn
+#undef clblasScasum
+//#define clblasScasum clblasScasum_pfn
+#undef clblasScnrm2
+//#define clblasScnrm2 clblasScnrm2_pfn
+#undef clblasScopy
+//#define clblasScopy clblasScopy_pfn
+#undef clblasSdot
+//#define clblasSdot clblasSdot_pfn
+#undef clblasSetup
+#define clblasSetup clblasSetup_pfn
+#undef clblasSgbmv
+//#define clblasSgbmv clblasSgbmv_pfn
+#undef clblasSgemm
+#define clblasSgemm clblasSgemm_pfn
+#undef clblasSgemv
+//#define clblasSgemv clblasSgemv_pfn
+#undef clblasSger
+//#define clblasSger clblasSger_pfn
+#undef clblasSnrm2
+//#define clblasSnrm2 clblasSnrm2_pfn
+#undef clblasSrot
+//#define clblasSrot clblasSrot_pfn
+#undef clblasSrotg
+//#define clblasSrotg clblasSrotg_pfn
+#undef clblasSrotm
+//#define clblasSrotm clblasSrotm_pfn
+#undef clblasSrotmg
+//#define clblasSrotmg clblasSrotmg_pfn
+#undef clblasSsbmv
+//#define clblasSsbmv clblasSsbmv_pfn
+#undef clblasSscal
+//#define clblasSscal clblasSscal_pfn
+#undef clblasSspmv
+//#define clblasSspmv clblasSspmv_pfn
+#undef clblasSspr
+//#define clblasSspr clblasSspr_pfn
+#undef clblasSspr2
+//#define clblasSspr2 clblasSspr2_pfn
+#undef clblasSswap
+//#define clblasSswap clblasSswap_pfn
+#undef clblasSsymm
+//#define clblasSsymm clblasSsymm_pfn
+#undef clblasSsymv
+//#define clblasSsymv clblasSsymv_pfn
+#undef clblasSsyr
+//#define clblasSsyr clblasSsyr_pfn
+#undef clblasSsyr2
+//#define clblasSsyr2 clblasSsyr2_pfn
+#undef clblasSsyr2k
+//#define clblasSsyr2k clblasSsyr2k_pfn
+#undef clblasSsyrk
+//#define clblasSsyrk clblasSsyrk_pfn
+#undef clblasStbmv
+//#define clblasStbmv clblasStbmv_pfn
+#undef clblasStbsv
+//#define clblasStbsv clblasStbsv_pfn
+#undef clblasStpmv
+//#define clblasStpmv clblasStpmv_pfn
+#undef clblasStpsv
+//#define clblasStpsv clblasStpsv_pfn
+#undef clblasStrmm
+//#define clblasStrmm clblasStrmm_pfn
+#undef clblasStrmv
+//#define clblasStrmv clblasStrmv_pfn
+#undef clblasStrsm
+//#define clblasStrsm clblasStrsm_pfn
+#undef clblasStrsv
+//#define clblasStrsv clblasStrsv_pfn
+#undef clblasTeardown
+#define clblasTeardown clblasTeardown_pfn
+#undef clblasZaxpy
+//#define clblasZaxpy clblasZaxpy_pfn
+#undef clblasZcopy
+//#define clblasZcopy clblasZcopy_pfn
+#undef clblasZdotc
+//#define clblasZdotc clblasZdotc_pfn
+#undef clblasZdotu
+//#define clblasZdotu clblasZdotu_pfn
+#undef clblasZdrot
+//#define clblasZdrot clblasZdrot_pfn
+#undef clblasZdscal
+//#define clblasZdscal clblasZdscal_pfn
+#undef clblasZgbmv
+//#define clblasZgbmv clblasZgbmv_pfn
+#undef clblasZgemm
+#define clblasZgemm clblasZgemm_pfn
+#undef clblasZgemv
+//#define clblasZgemv clblasZgemv_pfn
+#undef clblasZgerc
+//#define clblasZgerc clblasZgerc_pfn
+#undef clblasZgeru
+//#define clblasZgeru clblasZgeru_pfn
+#undef clblasZhbmv
+//#define clblasZhbmv clblasZhbmv_pfn
+#undef clblasZhemm
+//#define clblasZhemm clblasZhemm_pfn
+#undef clblasZhemv
+//#define clblasZhemv clblasZhemv_pfn
+#undef clblasZher
+//#define clblasZher clblasZher_pfn
+#undef clblasZher2
+//#define clblasZher2 clblasZher2_pfn
+#undef clblasZher2k
+//#define clblasZher2k clblasZher2k_pfn
+#undef clblasZherk
+//#define clblasZherk clblasZherk_pfn
+#undef clblasZhpmv
+//#define clblasZhpmv clblasZhpmv_pfn
+#undef clblasZhpr
+//#define clblasZhpr clblasZhpr_pfn
+#undef clblasZhpr2
+//#define clblasZhpr2 clblasZhpr2_pfn
+#undef clblasZrotg
+//#define clblasZrotg clblasZrotg_pfn
+#undef clblasZscal
+//#define clblasZscal clblasZscal_pfn
+#undef clblasZswap
+//#define clblasZswap clblasZswap_pfn
+#undef clblasZsymm
+//#define clblasZsymm clblasZsymm_pfn
+#undef clblasZsyr2k
+//#define clblasZsyr2k clblasZsyr2k_pfn
+#undef clblasZsyrk
+//#define clblasZsyrk clblasZsyrk_pfn
+#undef clblasZtbmv
+//#define clblasZtbmv clblasZtbmv_pfn
+#undef clblasZtbsv
+//#define clblasZtbsv clblasZtbsv_pfn
+#undef clblasZtpmv
+//#define clblasZtpmv clblasZtpmv_pfn
+#undef clblasZtpsv
+//#define clblasZtpsv clblasZtpsv_pfn
+#undef clblasZtrmm
+//#define clblasZtrmm clblasZtrmm_pfn
+#undef clblasZtrmv
+//#define clblasZtrmv clblasZtrmv_pfn
+#undef clblasZtrsm
+//#define clblasZtrsm clblasZtrsm_pfn
+#undef clblasZtrsv
+//#define clblasZtrsv clblasZtrsv_pfn
+#undef clblasiCamax
+//#define clblasiCamax clblasiCamax_pfn
+#undef clblasiDamax
+//#define clblasiDamax clblasiDamax_pfn
+#undef clblasiSamax
+//#define clblasiSamax clblasiSamax_pfn
+#undef clblasiZamax
+//#define clblasiZamax clblasiZamax_pfn
+
+// generated by parser_clblas.py
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCaxpy)(size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCcopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCdotc)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCdotu)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCgbmv)(clblasOrder order, clblasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+extern CL_RUNTIME_EXPORT clblasStatus (*clblasCgemm)(clblasOrder order, clblasTranspose transA, clblasTranspose transB, size_t M, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, FloatComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCgemv)(clblasOrder order, clblasTranspose transA, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, FloatComplex beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCgerc)(clblasOrder order, size_t M, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCgeru)(clblasOrder order, size_t M, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasChbmv)(clblasOrder order, clblasUplo uplo, size_t N, size_t K, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasChemm)(clblasOrder order, clblasSide side, clblasUplo uplo, size_t M, size_t N, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasChemv)(clblasOrder order, clblasUplo uplo, size_t N, FloatComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, FloatComplex beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCher)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCher2)(clblasOrder order, clblasUplo uplo, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCher2k)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCherk)(clblasOrder order, clblasUplo uplo, clblasTranspose transA, size_t N, size_t K, float alpha, const cl_mem A, size_t offa, size_t lda, float beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasChpmv)(clblasOrder order, clblasUplo uplo, size_t N, cl_float2 alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_float2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasChpr)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasChpr2)(clblasOrder order, clblasUplo uplo, size_t N, cl_float2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCrotg)(cl_mem CA, size_t offCA, cl_mem CB, size_t offCB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCscal)(size_t N, cl_float2 alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCsrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_float C, cl_float S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCsscal)(size_t N, cl_float alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCsymm)(clblasOrder order, clblasSide side, clblasUplo uplo, size_t M, size_t N, cl_float2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCsyr2k)(clblasOrder order, clblasUplo uplo, clblasTranspose transAB, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, FloatComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCsyrk)(clblasOrder order, clblasUplo uplo, clblasTranspose transA, size_t N, size_t K, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, FloatComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtbmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtbsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtpmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtpsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtrmm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtrmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtrsm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, FloatComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasCtrsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDaxpy)(size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDcopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDdot)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDgbmv)(clblasOrder order, clblasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_double alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+extern CL_RUNTIME_EXPORT clblasStatus (*clblasDgemm)(clblasOrder order, clblasTranspose transA, clblasTranspose transB, size_t M, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_double beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDgemv)(clblasOrder order, clblasTranspose transA, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_double beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDger)(clblasOrder order, size_t M, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDnrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_double C, cl_double S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDrotg)(cl_mem DA, size_t offDA, cl_mem DB, size_t offDB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDrotm)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, const cl_mem DPARAM, size_t offDparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDrotmg)(cl_mem DD1, size_t offDD1, cl_mem DD2, size_t offDD2, cl_mem DX1, size_t offDX1, const cl_mem DY1, size_t offDY1, cl_mem DPARAM, size_t offDparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDsbmv)(clblasOrder order, clblasUplo uplo, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDscal)(size_t N, cl_double alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDspmv)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_double beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDspr)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDspr2)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDsymm)(clblasOrder order, clblasSide side, clblasUplo uplo, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDsymv)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_double beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDsyr)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDsyr2)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDsyr2k)(clblasOrder order, clblasUplo uplo, clblasTranspose transAB, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_double beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDsyrk)(clblasOrder order, clblasUplo uplo, clblasTranspose transA, size_t N, size_t K, cl_double alpha, const cl_mem A, size_t offA, size_t lda, cl_double beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtbmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtbsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtpmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtpsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtrmm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtrmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtrsm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, cl_double alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDtrsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDzasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasDznrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasGetVersion)(cl_uint* major, cl_uint* minor, cl_uint* patch);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSaxpy)(size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasScasum)(size_t N, cl_mem asum, size_t offAsum, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasScnrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasScopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSdot)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+extern CL_RUNTIME_EXPORT clblasStatus (*clblasSetup)();
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSgbmv)(clblasOrder order, clblasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_float alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+extern CL_RUNTIME_EXPORT clblasStatus (*clblasSgemm)(clblasOrder order, clblasTranspose transA, clblasTranspose transB, size_t M, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_float beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSgemv)(clblasOrder order, clblasTranspose transA, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_float beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSger)(clblasOrder order, size_t M, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSnrm2)(size_t N, cl_mem NRM2, size_t offNRM2, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_float C, cl_float S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSrotg)(cl_mem SA, size_t offSA, cl_mem SB, size_t offSB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSrotm)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, const cl_mem SPARAM, size_t offSparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSrotmg)(cl_mem SD1, size_t offSD1, cl_mem SD2, size_t offSD2, cl_mem SX1, size_t offSX1, const cl_mem SY1, size_t offSY1, cl_mem SPARAM, size_t offSparam, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSsbmv)(clblasOrder order, clblasUplo uplo, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_float beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSscal)(size_t N, cl_float alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSspmv)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_float beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSspr)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSspr2)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSsymm)(clblasOrder order, clblasSide side, clblasUplo uplo, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_float beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSsymv)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, cl_float beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSsyr)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSsyr2)(clblasOrder order, clblasUplo uplo, size_t N, cl_float alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSsyr2k)(clblasOrder order, clblasUplo uplo, clblasTranspose transAB, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, cl_float beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasSsyrk)(clblasOrder order, clblasUplo uplo, clblasTranspose transA, size_t N, size_t K, cl_float alpha, const cl_mem A, size_t offA, size_t lda, cl_float beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStbmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStbsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStpmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStpsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStrmm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStrmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStrsm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, cl_float alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasStrsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+extern CL_RUNTIME_EXPORT void (*clblasTeardown)();
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZaxpy)(size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZcopy)(size_t N, const cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZdotc)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZdotu)(size_t N, cl_mem dotProduct, size_t offDP, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZdrot)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_double C, cl_double S, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZdscal)(size_t N, cl_double alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZgbmv)(clblasOrder order, clblasTranspose trans, size_t M, size_t N, size_t KL, size_t KU, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+extern CL_RUNTIME_EXPORT clblasStatus (*clblasZgemm)(clblasOrder order, clblasTranspose transA, clblasTranspose transB, size_t M, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, DoubleComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZgemv)(clblasOrder order, clblasTranspose transA, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem x, size_t offx, int incx, DoubleComplex beta, cl_mem y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZgerc)(clblasOrder order, size_t M, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZgeru)(clblasOrder order, size_t M, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZhbmv)(clblasOrder order, clblasUplo uplo, size_t N, size_t K, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, cl_double2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZhemm)(clblasOrder order, clblasSide side, clblasUplo uplo, size_t M, size_t N, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZhemv)(clblasOrder order, clblasUplo uplo, size_t N, DoubleComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem X, size_t offx, int incx, DoubleComplex beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZher)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZher2)(clblasOrder order, clblasUplo uplo, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem A, size_t offa, size_t lda, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZher2k)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZherk)(clblasOrder order, clblasUplo uplo, clblasTranspose transA, size_t N, size_t K, double alpha, const cl_mem A, size_t offa, size_t lda, double beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZhpmv)(clblasOrder order, clblasUplo uplo, size_t N, cl_double2 alpha, const cl_mem AP, size_t offa, const cl_mem X, size_t offx, int incx, cl_double2 beta, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZhpr)(clblasOrder order, clblasUplo uplo, size_t N, cl_double alpha, const cl_mem X, size_t offx, int incx, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZhpr2)(clblasOrder order, clblasUplo uplo, size_t N, cl_double2 alpha, const cl_mem X, size_t offx, int incx, const cl_mem Y, size_t offy, int incy, cl_mem AP, size_t offa, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZrotg)(cl_mem CA, size_t offCA, cl_mem CB, size_t offCB, cl_mem C, size_t offC, cl_mem S, size_t offS, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZscal)(size_t N, cl_double2 alpha, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZswap)(size_t N, cl_mem X, size_t offx, int incx, cl_mem Y, size_t offy, int incy, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZsymm)(clblasOrder order, clblasSide side, clblasUplo uplo, size_t M, size_t N, cl_double2 alpha, const cl_mem A, size_t offa, size_t lda, const cl_mem B, size_t offb, size_t ldb, cl_double2 beta, cl_mem C, size_t offc, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZsyr2k)(clblasOrder order, clblasUplo uplo, clblasTranspose transAB, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, const cl_mem B, size_t offB, size_t ldb, DoubleComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZsyrk)(clblasOrder order, clblasUplo uplo, clblasTranspose transA, size_t N, size_t K, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, DoubleComplex beta, cl_mem C, size_t offC, size_t ldc, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtbmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtbsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, size_t K, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtpmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem AP, size_t offa, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtpsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtrmm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtrmv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtrsm)(clblasOrder order, clblasSide side, clblasUplo uplo, clblasTranspose transA, clblasDiag diag, size_t M, size_t N, DoubleComplex alpha, const cl_mem A, size_t offA, size_t lda, cl_mem B, size_t offB, size_t ldb, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasZtrsv)(clblasOrder order, clblasUplo uplo, clblasTranspose trans, clblasDiag diag, size_t N, const cl_mem A, size_t offa, size_t lda, cl_mem X, size_t offx, int incx, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasiCamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasiDamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasiSamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);
+//extern CL_RUNTIME_EXPORT clblasStatus (*clblasiZamax)(size_t N, cl_mem iMax, size_t offiMax, const cl_mem X, size_t offx, int incx, cl_mem scratchBuff, cl_uint numCommandQueues, cl_command_queue* commandQueues, cl_uint numEventsInWaitList, const cl_event* eventWaitList, cl_event* events);

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/autogenerated/opencl_clfft.hpp

@@ -0,0 +1,146 @@
+//
+// AUTOGENERATED, DO NOT EDIT
+//
+#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP
+#error "Invalid usage"
+#endif
+
+// generated by parser_clfft.py
+#define clfftBakePlan clfftBakePlan_
+#define clfftCopyPlan clfftCopyPlan_
+#define clfftCreateDefaultPlan clfftCreateDefaultPlan_
+#define clfftDestroyPlan clfftDestroyPlan_
+#define clfftEnqueueTransform clfftEnqueueTransform_
+#define clfftGetLayout clfftGetLayout_
+#define clfftGetPlanBatchSize clfftGetPlanBatchSize_
+#define clfftGetPlanContext clfftGetPlanContext_
+#define clfftGetPlanDim clfftGetPlanDim_
+#define clfftGetPlanDistance clfftGetPlanDistance_
+#define clfftGetPlanInStride clfftGetPlanInStride_
+#define clfftGetPlanLength clfftGetPlanLength_
+#define clfftGetPlanOutStride clfftGetPlanOutStride_
+#define clfftGetPlanPrecision clfftGetPlanPrecision_
+#define clfftGetPlanScale clfftGetPlanScale_
+#define clfftGetPlanTransposeResult clfftGetPlanTransposeResult_
+#define clfftGetResultLocation clfftGetResultLocation_
+#define clfftGetTmpBufSize clfftGetTmpBufSize_
+#define clfftGetVersion clfftGetVersion_
+#define clfftSetLayout clfftSetLayout_
+#define clfftSetPlanBatchSize clfftSetPlanBatchSize_
+#define clfftSetPlanCallback clfftSetPlanCallback_
+#define clfftSetPlanDim clfftSetPlanDim_
+#define clfftSetPlanDistance clfftSetPlanDistance_
+#define clfftSetPlanInStride clfftSetPlanInStride_
+#define clfftSetPlanLength clfftSetPlanLength_
+#define clfftSetPlanOutStride clfftSetPlanOutStride_
+#define clfftSetPlanPrecision clfftSetPlanPrecision_
+#define clfftSetPlanScale clfftSetPlanScale_
+#define clfftSetPlanTransposeResult clfftSetPlanTransposeResult_
+#define clfftSetResultLocation clfftSetResultLocation_
+#define clfftSetup clfftSetup_
+#define clfftTeardown clfftTeardown_
+
+#include <clFFT.h>
+
+// generated by parser_clfft.py
+#undef clfftBakePlan
+#define clfftBakePlan clfftBakePlan_pfn
+#undef clfftCopyPlan
+//#define clfftCopyPlan clfftCopyPlan_pfn
+#undef clfftCreateDefaultPlan
+#define clfftCreateDefaultPlan clfftCreateDefaultPlan_pfn
+#undef clfftDestroyPlan
+#define clfftDestroyPlan clfftDestroyPlan_pfn
+#undef clfftEnqueueTransform
+#define clfftEnqueueTransform clfftEnqueueTransform_pfn
+#undef clfftGetLayout
+//#define clfftGetLayout clfftGetLayout_pfn
+#undef clfftGetPlanBatchSize
+//#define clfftGetPlanBatchSize clfftGetPlanBatchSize_pfn
+#undef clfftGetPlanContext
+//#define clfftGetPlanContext clfftGetPlanContext_pfn
+#undef clfftGetPlanDim
+//#define clfftGetPlanDim clfftGetPlanDim_pfn
+#undef clfftGetPlanDistance
+//#define clfftGetPlanDistance clfftGetPlanDistance_pfn
+#undef clfftGetPlanInStride
+//#define clfftGetPlanInStride clfftGetPlanInStride_pfn
+#undef clfftGetPlanLength
+//#define clfftGetPlanLength clfftGetPlanLength_pfn
+#undef clfftGetPlanOutStride
+//#define clfftGetPlanOutStride clfftGetPlanOutStride_pfn
+#undef clfftGetPlanPrecision
+//#define clfftGetPlanPrecision clfftGetPlanPrecision_pfn
+#undef clfftGetPlanScale
+//#define clfftGetPlanScale clfftGetPlanScale_pfn
+#undef clfftGetPlanTransposeResult
+//#define clfftGetPlanTransposeResult clfftGetPlanTransposeResult_pfn
+#undef clfftGetResultLocation
+//#define clfftGetResultLocation clfftGetResultLocation_pfn
+#undef clfftGetTmpBufSize
+#define clfftGetTmpBufSize clfftGetTmpBufSize_pfn
+#undef clfftGetVersion
+#define clfftGetVersion clfftGetVersion_pfn
+#undef clfftSetLayout
+#define clfftSetLayout clfftSetLayout_pfn
+#undef clfftSetPlanBatchSize
+#define clfftSetPlanBatchSize clfftSetPlanBatchSize_pfn
+#undef clfftSetPlanCallback
+//#define clfftSetPlanCallback clfftSetPlanCallback_pfn
+#undef clfftSetPlanDim
+//#define clfftSetPlanDim clfftSetPlanDim_pfn
+#undef clfftSetPlanDistance
+#define clfftSetPlanDistance clfftSetPlanDistance_pfn
+#undef clfftSetPlanInStride
+#define clfftSetPlanInStride clfftSetPlanInStride_pfn
+#undef clfftSetPlanLength
+//#define clfftSetPlanLength clfftSetPlanLength_pfn
+#undef clfftSetPlanOutStride
+#define clfftSetPlanOutStride clfftSetPlanOutStride_pfn
+#undef clfftSetPlanPrecision
+#define clfftSetPlanPrecision clfftSetPlanPrecision_pfn
+#undef clfftSetPlanScale
+#define clfftSetPlanScale clfftSetPlanScale_pfn
+#undef clfftSetPlanTransposeResult
+//#define clfftSetPlanTransposeResult clfftSetPlanTransposeResult_pfn
+#undef clfftSetResultLocation
+#define clfftSetResultLocation clfftSetResultLocation_pfn
+#undef clfftSetup
+#define clfftSetup clfftSetup_pfn
+#undef clfftTeardown
+#define clfftTeardown clfftTeardown_pfn
+
+// generated by parser_clfft.py
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftBakePlan)(clfftPlanHandle plHandle, cl_uint numQueues, cl_command_queue* commQueueFFT, void (CL_CALLBACK* pfn_notify) (clfftPlanHandle plHandle, void* user_data), void* user_data);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftCopyPlan)(clfftPlanHandle* out_plHandle, cl_context new_context, clfftPlanHandle in_plHandle);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftCreateDefaultPlan)(clfftPlanHandle* plHandle, cl_context context, const clfftDim dim, const size_t* clLengths);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftDestroyPlan)(clfftPlanHandle* plHandle);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftEnqueueTransform)(clfftPlanHandle plHandle, clfftDirection dir, cl_uint numQueuesAndEvents, cl_command_queue* commQueues, cl_uint numWaitEvents, const cl_event* waitEvents, cl_event* outEvents, cl_mem* inputBuffers, cl_mem* outputBuffers, cl_mem tmpBuffer);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetLayout)(const clfftPlanHandle plHandle, clfftLayout* iLayout, clfftLayout* oLayout);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanBatchSize)(const clfftPlanHandle plHandle, size_t* batchSize);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanContext)(const clfftPlanHandle plHandle, cl_context* context);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanDim)(const clfftPlanHandle plHandle, clfftDim* dim, cl_uint* size);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanDistance)(const clfftPlanHandle plHandle, size_t* iDist, size_t* oDist);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanInStride)(const clfftPlanHandle plHandle, const clfftDim dim, size_t* clStrides);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanLength)(const clfftPlanHandle plHandle, const clfftDim dim, size_t* clLengths);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanOutStride)(const clfftPlanHandle plHandle, const clfftDim dim, size_t* clStrides);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanPrecision)(const clfftPlanHandle plHandle, clfftPrecision* precision);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanScale)(const clfftPlanHandle plHandle, clfftDirection dir, cl_float* scale);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetPlanTransposeResult)(const clfftPlanHandle plHandle, clfftResultTransposed* transposed);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetResultLocation)(const clfftPlanHandle plHandle, clfftResultLocation* placeness);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetTmpBufSize)(const clfftPlanHandle plHandle, size_t* buffersize);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftGetVersion)(cl_uint* major, cl_uint* minor, cl_uint* patch);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetLayout)(clfftPlanHandle plHandle, clfftLayout iLayout, clfftLayout oLayout);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanBatchSize)(clfftPlanHandle plHandle, size_t batchSize);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanCallback)(clfftPlanHandle plHandle, const char* funcName, const char* funcString, int localMemSize, clfftCallbackType callbackType, cl_mem* userdata, int numUserdataBuffers);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanDim)(clfftPlanHandle plHandle, const clfftDim dim);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanDistance)(clfftPlanHandle plHandle, size_t iDist, size_t oDist);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanInStride)(clfftPlanHandle plHandle, const clfftDim dim, size_t* clStrides);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanLength)(clfftPlanHandle plHandle, const clfftDim dim, const size_t* clLengths);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanOutStride)(clfftPlanHandle plHandle, const clfftDim dim, size_t* clStrides);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanPrecision)(clfftPlanHandle plHandle, clfftPrecision precision);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanScale)(clfftPlanHandle plHandle, clfftDirection dir, cl_float scale);
+//extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetPlanTransposeResult)(clfftPlanHandle plHandle, clfftResultTransposed transposed);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetResultLocation)(clfftPlanHandle plHandle, clfftResultLocation placeness);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftSetup)(const clfftSetupData* setupData);
+extern CL_RUNTIME_EXPORT clfftStatus (*clfftTeardown)();

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/autogenerated/opencl_core.hpp

@@ -0,0 +1,371 @@
+//
+// AUTOGENERATED, DO NOT EDIT
+//
+#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP
+#error "Invalid usage"
+#endif
+
+// generated by parser_cl.py
+#define clBuildProgram clBuildProgram_
+#define clCompileProgram clCompileProgram_
+#define clCreateBuffer clCreateBuffer_
+#define clCreateCommandQueue clCreateCommandQueue_
+#define clCreateContext clCreateContext_
+#define clCreateContextFromType clCreateContextFromType_
+#define clCreateImage clCreateImage_
+#define clCreateImage2D clCreateImage2D_
+#define clCreateImage3D clCreateImage3D_
+#define clCreateKernel clCreateKernel_
+#define clCreateKernelsInProgram clCreateKernelsInProgram_
+#define clCreateProgramWithBinary clCreateProgramWithBinary_
+#define clCreateProgramWithBuiltInKernels clCreateProgramWithBuiltInKernels_
+#define clCreateProgramWithSource clCreateProgramWithSource_
+#define clCreateSampler clCreateSampler_
+#define clCreateSubBuffer clCreateSubBuffer_
+#define clCreateSubDevices clCreateSubDevices_
+#define clCreateUserEvent clCreateUserEvent_
+#define clEnqueueBarrier clEnqueueBarrier_
+#define clEnqueueBarrierWithWaitList clEnqueueBarrierWithWaitList_
+#define clEnqueueCopyBuffer clEnqueueCopyBuffer_
+#define clEnqueueCopyBufferRect clEnqueueCopyBufferRect_
+#define clEnqueueCopyBufferToImage clEnqueueCopyBufferToImage_
+#define clEnqueueCopyImage clEnqueueCopyImage_
+#define clEnqueueCopyImageToBuffer clEnqueueCopyImageToBuffer_
+#define clEnqueueFillBuffer clEnqueueFillBuffer_
+#define clEnqueueFillImage clEnqueueFillImage_
+#define clEnqueueMapBuffer clEnqueueMapBuffer_
+#define clEnqueueMapImage clEnqueueMapImage_
+#define clEnqueueMarker clEnqueueMarker_
+#define clEnqueueMarkerWithWaitList clEnqueueMarkerWithWaitList_
+#define clEnqueueMigrateMemObjects clEnqueueMigrateMemObjects_
+#define clEnqueueNDRangeKernel clEnqueueNDRangeKernel_
+#define clEnqueueNativeKernel clEnqueueNativeKernel_
+#define clEnqueueReadBuffer clEnqueueReadBuffer_
+#define clEnqueueReadBufferRect clEnqueueReadBufferRect_
+#define clEnqueueReadImage clEnqueueReadImage_
+#define clEnqueueTask clEnqueueTask_
+#define clEnqueueUnmapMemObject clEnqueueUnmapMemObject_
+#define clEnqueueWaitForEvents clEnqueueWaitForEvents_
+#define clEnqueueWriteBuffer clEnqueueWriteBuffer_
+#define clEnqueueWriteBufferRect clEnqueueWriteBufferRect_
+#define clEnqueueWriteImage clEnqueueWriteImage_
+#define clFinish clFinish_
+#define clFlush clFlush_
+#define clGetCommandQueueInfo clGetCommandQueueInfo_
+#define clGetContextInfo clGetContextInfo_
+#define clGetDeviceIDs clGetDeviceIDs_
+#define clGetDeviceInfo clGetDeviceInfo_
+#define clGetEventInfo clGetEventInfo_
+#define clGetEventProfilingInfo clGetEventProfilingInfo_
+#define clGetExtensionFunctionAddress clGetExtensionFunctionAddress_
+#define clGetExtensionFunctionAddressForPlatform clGetExtensionFunctionAddressForPlatform_
+#define clGetImageInfo clGetImageInfo_
+#define clGetKernelArgInfo clGetKernelArgInfo_
+#define clGetKernelInfo clGetKernelInfo_
+#define clGetKernelWorkGroupInfo clGetKernelWorkGroupInfo_
+#define clGetMemObjectInfo clGetMemObjectInfo_
+#define clGetPlatformIDs clGetPlatformIDs_
+#define clGetPlatformInfo clGetPlatformInfo_
+#define clGetProgramBuildInfo clGetProgramBuildInfo_
+#define clGetProgramInfo clGetProgramInfo_
+#define clGetSamplerInfo clGetSamplerInfo_
+#define clGetSupportedImageFormats clGetSupportedImageFormats_
+#define clLinkProgram clLinkProgram_
+#define clReleaseCommandQueue clReleaseCommandQueue_
+#define clReleaseContext clReleaseContext_
+#define clReleaseDevice clReleaseDevice_
+#define clReleaseEvent clReleaseEvent_
+#define clReleaseKernel clReleaseKernel_
+#define clReleaseMemObject clReleaseMemObject_
+#define clReleaseProgram clReleaseProgram_
+#define clReleaseSampler clReleaseSampler_
+#define clRetainCommandQueue clRetainCommandQueue_
+#define clRetainContext clRetainContext_
+#define clRetainDevice clRetainDevice_
+#define clRetainEvent clRetainEvent_
+#define clRetainKernel clRetainKernel_
+#define clRetainMemObject clRetainMemObject_
+#define clRetainProgram clRetainProgram_
+#define clRetainSampler clRetainSampler_
+#define clSetEventCallback clSetEventCallback_
+#define clSetKernelArg clSetKernelArg_
+#define clSetMemObjectDestructorCallback clSetMemObjectDestructorCallback_
+#define clSetUserEventStatus clSetUserEventStatus_
+#define clUnloadCompiler clUnloadCompiler_
+#define clUnloadPlatformCompiler clUnloadPlatformCompiler_
+#define clWaitForEvents clWaitForEvents_
+
+#if defined __APPLE__
+#define CL_SILENCE_DEPRECATION
+#include <OpenCL/cl.h>
+#else
+#include <CL/cl.h>
+#endif
+
+// generated by parser_cl.py
+#undef clBuildProgram
+#define clBuildProgram clBuildProgram_pfn
+#undef clCompileProgram
+#define clCompileProgram clCompileProgram_pfn
+#undef clCreateBuffer
+#define clCreateBuffer clCreateBuffer_pfn
+#undef clCreateCommandQueue
+#define clCreateCommandQueue clCreateCommandQueue_pfn
+#undef clCreateContext
+#define clCreateContext clCreateContext_pfn
+#undef clCreateContextFromType
+#define clCreateContextFromType clCreateContextFromType_pfn
+#undef clCreateImage
+#define clCreateImage clCreateImage_pfn
+#undef clCreateImage2D
+#define clCreateImage2D clCreateImage2D_pfn
+#undef clCreateImage3D
+#define clCreateImage3D clCreateImage3D_pfn
+#undef clCreateKernel
+#define clCreateKernel clCreateKernel_pfn
+#undef clCreateKernelsInProgram
+#define clCreateKernelsInProgram clCreateKernelsInProgram_pfn
+#undef clCreateProgramWithBinary
+#define clCreateProgramWithBinary clCreateProgramWithBinary_pfn
+#undef clCreateProgramWithBuiltInKernels
+#define clCreateProgramWithBuiltInKernels clCreateProgramWithBuiltInKernels_pfn
+#undef clCreateProgramWithSource
+#define clCreateProgramWithSource clCreateProgramWithSource_pfn
+#undef clCreateSampler
+#define clCreateSampler clCreateSampler_pfn
+#undef clCreateSubBuffer
+#define clCreateSubBuffer clCreateSubBuffer_pfn
+#undef clCreateSubDevices
+#define clCreateSubDevices clCreateSubDevices_pfn
+#undef clCreateUserEvent
+#define clCreateUserEvent clCreateUserEvent_pfn
+#undef clEnqueueBarrier
+#define clEnqueueBarrier clEnqueueBarrier_pfn
+#undef clEnqueueBarrierWithWaitList
+#define clEnqueueBarrierWithWaitList clEnqueueBarrierWithWaitList_pfn
+#undef clEnqueueCopyBuffer
+#define clEnqueueCopyBuffer clEnqueueCopyBuffer_pfn
+#undef clEnqueueCopyBufferRect
+#define clEnqueueCopyBufferRect clEnqueueCopyBufferRect_pfn
+#undef clEnqueueCopyBufferToImage
+#define clEnqueueCopyBufferToImage clEnqueueCopyBufferToImage_pfn
+#undef clEnqueueCopyImage
+#define clEnqueueCopyImage clEnqueueCopyImage_pfn
+#undef clEnqueueCopyImageToBuffer
+#define clEnqueueCopyImageToBuffer clEnqueueCopyImageToBuffer_pfn
+#undef clEnqueueFillBuffer
+#define clEnqueueFillBuffer clEnqueueFillBuffer_pfn
+#undef clEnqueueFillImage
+#define clEnqueueFillImage clEnqueueFillImage_pfn
+#undef clEnqueueMapBuffer
+#define clEnqueueMapBuffer clEnqueueMapBuffer_pfn
+#undef clEnqueueMapImage
+#define clEnqueueMapImage clEnqueueMapImage_pfn
+#undef clEnqueueMarker
+#define clEnqueueMarker clEnqueueMarker_pfn
+#undef clEnqueueMarkerWithWaitList
+#define clEnqueueMarkerWithWaitList clEnqueueMarkerWithWaitList_pfn
+#undef clEnqueueMigrateMemObjects
+#define clEnqueueMigrateMemObjects clEnqueueMigrateMemObjects_pfn
+#undef clEnqueueNDRangeKernel
+#define clEnqueueNDRangeKernel clEnqueueNDRangeKernel_pfn
+#undef clEnqueueNativeKernel
+#define clEnqueueNativeKernel clEnqueueNativeKernel_pfn
+#undef clEnqueueReadBuffer
+#define clEnqueueReadBuffer clEnqueueReadBuffer_pfn
+#undef clEnqueueReadBufferRect
+#define clEnqueueReadBufferRect clEnqueueReadBufferRect_pfn
+#undef clEnqueueReadImage
+#define clEnqueueReadImage clEnqueueReadImage_pfn
+#undef clEnqueueTask
+#define clEnqueueTask clEnqueueTask_pfn
+#undef clEnqueueUnmapMemObject
+#define clEnqueueUnmapMemObject clEnqueueUnmapMemObject_pfn
+#undef clEnqueueWaitForEvents
+#define clEnqueueWaitForEvents clEnqueueWaitForEvents_pfn
+#undef clEnqueueWriteBuffer
+#define clEnqueueWriteBuffer clEnqueueWriteBuffer_pfn
+#undef clEnqueueWriteBufferRect
+#define clEnqueueWriteBufferRect clEnqueueWriteBufferRect_pfn
+#undef clEnqueueWriteImage
+#define clEnqueueWriteImage clEnqueueWriteImage_pfn
+#undef clFinish
+#define clFinish clFinish_pfn
+#undef clFlush
+#define clFlush clFlush_pfn
+#undef clGetCommandQueueInfo
+#define clGetCommandQueueInfo clGetCommandQueueInfo_pfn
+#undef clGetContextInfo
+#define clGetContextInfo clGetContextInfo_pfn
+#undef clGetDeviceIDs
+#define clGetDeviceIDs clGetDeviceIDs_pfn
+#undef clGetDeviceInfo
+#define clGetDeviceInfo clGetDeviceInfo_pfn
+#undef clGetEventInfo
+#define clGetEventInfo clGetEventInfo_pfn
+#undef clGetEventProfilingInfo
+#define clGetEventProfilingInfo clGetEventProfilingInfo_pfn
+#undef clGetExtensionFunctionAddress
+#define clGetExtensionFunctionAddress clGetExtensionFunctionAddress_pfn
+#undef clGetExtensionFunctionAddressForPlatform
+#define clGetExtensionFunctionAddressForPlatform clGetExtensionFunctionAddressForPlatform_pfn
+#undef clGetImageInfo
+#define clGetImageInfo clGetImageInfo_pfn
+#undef clGetKernelArgInfo
+#define clGetKernelArgInfo clGetKernelArgInfo_pfn
+#undef clGetKernelInfo
+#define clGetKernelInfo clGetKernelInfo_pfn
+#undef clGetKernelWorkGroupInfo
+#define clGetKernelWorkGroupInfo clGetKernelWorkGroupInfo_pfn
+#undef clGetMemObjectInfo
+#define clGetMemObjectInfo clGetMemObjectInfo_pfn
+#undef clGetPlatformIDs
+#define clGetPlatformIDs clGetPlatformIDs_pfn
+#undef clGetPlatformInfo
+#define clGetPlatformInfo clGetPlatformInfo_pfn
+#undef clGetProgramBuildInfo
+#define clGetProgramBuildInfo clGetProgramBuildInfo_pfn
+#undef clGetProgramInfo
+#define clGetProgramInfo clGetProgramInfo_pfn
+#undef clGetSamplerInfo
+#define clGetSamplerInfo clGetSamplerInfo_pfn
+#undef clGetSupportedImageFormats
+#define clGetSupportedImageFormats clGetSupportedImageFormats_pfn
+#undef clLinkProgram
+#define clLinkProgram clLinkProgram_pfn
+#undef clReleaseCommandQueue
+#define clReleaseCommandQueue clReleaseCommandQueue_pfn
+#undef clReleaseContext
+#define clReleaseContext clReleaseContext_pfn
+#undef clReleaseDevice
+#define clReleaseDevice clReleaseDevice_pfn
+#undef clReleaseEvent
+#define clReleaseEvent clReleaseEvent_pfn
+#undef clReleaseKernel
+#define clReleaseKernel clReleaseKernel_pfn
+#undef clReleaseMemObject
+#define clReleaseMemObject clReleaseMemObject_pfn
+#undef clReleaseProgram
+#define clReleaseProgram clReleaseProgram_pfn
+#undef clReleaseSampler
+#define clReleaseSampler clReleaseSampler_pfn
+#undef clRetainCommandQueue
+#define clRetainCommandQueue clRetainCommandQueue_pfn
+#undef clRetainContext
+#define clRetainContext clRetainContext_pfn
+#undef clRetainDevice
+#define clRetainDevice clRetainDevice_pfn
+#undef clRetainEvent
+#define clRetainEvent clRetainEvent_pfn
+#undef clRetainKernel
+#define clRetainKernel clRetainKernel_pfn
+#undef clRetainMemObject
+#define clRetainMemObject clRetainMemObject_pfn
+#undef clRetainProgram
+#define clRetainProgram clRetainProgram_pfn
+#undef clRetainSampler
+#define clRetainSampler clRetainSampler_pfn
+#undef clSetEventCallback
+#define clSetEventCallback clSetEventCallback_pfn
+#undef clSetKernelArg
+#define clSetKernelArg clSetKernelArg_pfn
+#undef clSetMemObjectDestructorCallback
+#define clSetMemObjectDestructorCallback clSetMemObjectDestructorCallback_pfn
+#undef clSetUserEventStatus
+#define clSetUserEventStatus clSetUserEventStatus_pfn
+#undef clUnloadCompiler
+#define clUnloadCompiler clUnloadCompiler_pfn
+#undef clUnloadPlatformCompiler
+#define clUnloadPlatformCompiler clUnloadPlatformCompiler_pfn
+#undef clWaitForEvents
+#define clWaitForEvents clWaitForEvents_pfn
+
+// generated by parser_cl.py
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clBuildProgram)(cl_program, cl_uint, const cl_device_id*, const char*, void (CL_CALLBACK*) (cl_program, void*), void*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clCompileProgram)(cl_program, cl_uint, const cl_device_id*, const char*, cl_uint, const cl_program*, const char**, void (CL_CALLBACK*) (cl_program, void*), void*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateBuffer)(cl_context, cl_mem_flags, size_t, void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_command_queue (CL_API_CALL*clCreateCommandQueue)(cl_context, cl_device_id, cl_command_queue_properties, cl_int*);
+extern CL_RUNTIME_EXPORT cl_context (CL_API_CALL*clCreateContext)(const cl_context_properties*, cl_uint, const cl_device_id*, void (CL_CALLBACK*) (const char*, const void*, size_t, void*), void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_context (CL_API_CALL*clCreateContextFromType)(const cl_context_properties*, cl_device_type, void (CL_CALLBACK*) (const char*, const void*, size_t, void*), void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateImage)(cl_context, cl_mem_flags, const cl_image_format*, const cl_image_desc*, void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateImage2D)(cl_context, cl_mem_flags, const cl_image_format*, size_t, size_t, size_t, void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateImage3D)(cl_context, cl_mem_flags, const cl_image_format*, size_t, size_t, size_t, size_t, size_t, void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_kernel (CL_API_CALL*clCreateKernel)(cl_program, const char*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clCreateKernelsInProgram)(cl_program, cl_uint, cl_kernel*, cl_uint*);
+extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clCreateProgramWithBinary)(cl_context, cl_uint, const cl_device_id*, const size_t*, const unsigned char**, cl_int*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clCreateProgramWithBuiltInKernels)(cl_context, cl_uint, const cl_device_id*, const char*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clCreateProgramWithSource)(cl_context, cl_uint, const char**, const size_t*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_sampler (CL_API_CALL*clCreateSampler)(cl_context, cl_bool, cl_addressing_mode, cl_filter_mode, cl_int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateSubBuffer)(cl_mem, cl_mem_flags, cl_buffer_create_type, const void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clCreateSubDevices)(cl_device_id, const cl_device_partition_property*, cl_uint, cl_device_id*, cl_uint*);
+extern CL_RUNTIME_EXPORT cl_event (CL_API_CALL*clCreateUserEvent)(cl_context, cl_int*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueBarrier)(cl_command_queue);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueBarrierWithWaitList)(cl_command_queue, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyBuffer)(cl_command_queue, cl_mem, cl_mem, size_t, size_t, size_t, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyBufferRect)(cl_command_queue, cl_mem, cl_mem, const size_t*, const size_t*, const size_t*, size_t, size_t, size_t, size_t, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyBufferToImage)(cl_command_queue, cl_mem, cl_mem, size_t, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyImage)(cl_command_queue, cl_mem, cl_mem, const size_t*, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueCopyImageToBuffer)(cl_command_queue, cl_mem, cl_mem, const size_t*, const size_t*, size_t, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueFillBuffer)(cl_command_queue, cl_mem, const void*, size_t, size_t, size_t, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueFillImage)(cl_command_queue, cl_mem, const void*, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clEnqueueMapBuffer)(cl_command_queue, cl_mem, cl_bool, cl_map_flags, size_t, size_t, cl_uint, const cl_event*, cl_event*, cl_int*);
+extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clEnqueueMapImage)(cl_command_queue, cl_mem, cl_bool, cl_map_flags, const size_t*, const size_t*, size_t*, size_t*, cl_uint, const cl_event*, cl_event*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueMarker)(cl_command_queue, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueMarkerWithWaitList)(cl_command_queue, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueMigrateMemObjects)(cl_command_queue, cl_uint, const cl_mem*, cl_mem_migration_flags, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueNDRangeKernel)(cl_command_queue, cl_kernel, cl_uint, const size_t*, const size_t*, const size_t*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueNativeKernel)(cl_command_queue, void (CL_CALLBACK*) (void*), void*, size_t, cl_uint, const cl_mem*, const void**, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReadBuffer)(cl_command_queue, cl_mem, cl_bool, size_t, size_t, void*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReadBufferRect)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, const size_t*, size_t, size_t, size_t, size_t, void*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReadImage)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, size_t, size_t, void*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueTask)(cl_command_queue, cl_kernel, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueUnmapMemObject)(cl_command_queue, cl_mem, void*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWaitForEvents)(cl_command_queue, cl_uint, const cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWriteBuffer)(cl_command_queue, cl_mem, cl_bool, size_t, size_t, const void*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWriteBufferRect)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, const size_t*, size_t, size_t, size_t, size_t, const void*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueWriteImage)(cl_command_queue, cl_mem, cl_bool, const size_t*, const size_t*, size_t, size_t, const void*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clFinish)(cl_command_queue);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clFlush)(cl_command_queue);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetCommandQueueInfo)(cl_command_queue, cl_command_queue_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetContextInfo)(cl_context, cl_context_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetDeviceIDs)(cl_platform_id, cl_device_type, cl_uint, cl_device_id*, cl_uint*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetDeviceInfo)(cl_device_id, cl_device_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetEventInfo)(cl_event, cl_event_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetEventProfilingInfo)(cl_event, cl_profiling_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clGetExtensionFunctionAddress)(const char*);
+extern CL_RUNTIME_EXPORT void* (CL_API_CALL*clGetExtensionFunctionAddressForPlatform)(cl_platform_id, const char*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetImageInfo)(cl_mem, cl_image_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetKernelArgInfo)(cl_kernel, cl_uint, cl_kernel_arg_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetKernelInfo)(cl_kernel, cl_kernel_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetKernelWorkGroupInfo)(cl_kernel, cl_device_id, cl_kernel_work_group_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetMemObjectInfo)(cl_mem, cl_mem_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetPlatformIDs)(cl_uint, cl_platform_id*, cl_uint*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetPlatformInfo)(cl_platform_id, cl_platform_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetProgramBuildInfo)(cl_program, cl_device_id, cl_program_build_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetProgramInfo)(cl_program, cl_program_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetSamplerInfo)(cl_sampler, cl_sampler_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetSupportedImageFormats)(cl_context, cl_mem_flags, cl_mem_object_type, cl_uint, cl_image_format*, cl_uint*);
+extern CL_RUNTIME_EXPORT cl_program (CL_API_CALL*clLinkProgram)(cl_context, cl_uint, const cl_device_id*, const char*, cl_uint, const cl_program*, void (CL_CALLBACK*) (cl_program, void*), void*, cl_int*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseCommandQueue)(cl_command_queue);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseContext)(cl_context);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseDevice)(cl_device_id);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseEvent)(cl_event);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseKernel)(cl_kernel);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseMemObject)(cl_mem);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseProgram)(cl_program);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clReleaseSampler)(cl_sampler);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainCommandQueue)(cl_command_queue);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainContext)(cl_context);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainDevice)(cl_device_id);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainEvent)(cl_event);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainKernel)(cl_kernel);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainMemObject)(cl_mem);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainProgram)(cl_program);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clRetainSampler)(cl_sampler);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetEventCallback)(cl_event, cl_int, void (CL_CALLBACK*) (cl_event, cl_int, void*), void*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetKernelArg)(cl_kernel, cl_uint, size_t, const void*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetMemObjectDestructorCallback)(cl_mem, void (CL_CALLBACK*) (cl_mem, void*), void*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clSetUserEventStatus)(cl_event, cl_int);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clUnloadCompiler)();
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clUnloadPlatformCompiler)(cl_platform_id);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clWaitForEvents)(cl_uint, const cl_event*);

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/autogenerated/opencl_core_wrappers.hpp

@@ -0,0 +1,272 @@
+//
+// AUTOGENERATED, DO NOT EDIT
+//
+#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_WRAPPERS_HPP
+#error "Invalid usage"
+#endif
+
+// generated by parser_cl.py
+#undef clBuildProgram
+#define clBuildProgram clBuildProgram_fn
+inline cl_int clBuildProgram(cl_program p0, cl_uint p1, const cl_device_id* p2, const char* p3, void (CL_CALLBACK*p4) (cl_program, void*), void* p5) { return clBuildProgram_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clCompileProgram
+#define clCompileProgram clCompileProgram_fn
+inline cl_int clCompileProgram(cl_program p0, cl_uint p1, const cl_device_id* p2, const char* p3, cl_uint p4, const cl_program* p5, const char** p6, void (CL_CALLBACK*p7) (cl_program, void*), void* p8) { return clCompileProgram_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clCreateBuffer
+#define clCreateBuffer clCreateBuffer_fn
+inline cl_mem clCreateBuffer(cl_context p0, cl_mem_flags p1, size_t p2, void* p3, cl_int* p4) { return clCreateBuffer_pfn(p0, p1, p2, p3, p4); }
+#undef clCreateCommandQueue
+#define clCreateCommandQueue clCreateCommandQueue_fn
+inline cl_command_queue clCreateCommandQueue(cl_context p0, cl_device_id p1, cl_command_queue_properties p2, cl_int* p3) { return clCreateCommandQueue_pfn(p0, p1, p2, p3); }
+#undef clCreateContext
+#define clCreateContext clCreateContext_fn
+inline cl_context clCreateContext(const cl_context_properties* p0, cl_uint p1, const cl_device_id* p2, void (CL_CALLBACK*p3) (const char*, const void*, size_t, void*), void* p4, cl_int* p5) { return clCreateContext_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clCreateContextFromType
+#define clCreateContextFromType clCreateContextFromType_fn
+inline cl_context clCreateContextFromType(const cl_context_properties* p0, cl_device_type p1, void (CL_CALLBACK*p2) (const char*, const void*, size_t, void*), void* p3, cl_int* p4) { return clCreateContextFromType_pfn(p0, p1, p2, p3, p4); }
+#undef clCreateImage
+#define clCreateImage clCreateImage_fn
+inline cl_mem clCreateImage(cl_context p0, cl_mem_flags p1, const cl_image_format* p2, const cl_image_desc* p3, void* p4, cl_int* p5) { return clCreateImage_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clCreateImage2D
+#define clCreateImage2D clCreateImage2D_fn
+inline cl_mem clCreateImage2D(cl_context p0, cl_mem_flags p1, const cl_image_format* p2, size_t p3, size_t p4, size_t p5, void* p6, cl_int* p7) { return clCreateImage2D_pfn(p0, p1, p2, p3, p4, p5, p6, p7); }
+#undef clCreateImage3D
+#define clCreateImage3D clCreateImage3D_fn
+inline cl_mem clCreateImage3D(cl_context p0, cl_mem_flags p1, const cl_image_format* p2, size_t p3, size_t p4, size_t p5, size_t p6, size_t p7, void* p8, cl_int* p9) { return clCreateImage3D_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9); }
+#undef clCreateKernel
+#define clCreateKernel clCreateKernel_fn
+inline cl_kernel clCreateKernel(cl_program p0, const char* p1, cl_int* p2) { return clCreateKernel_pfn(p0, p1, p2); }
+#undef clCreateKernelsInProgram
+#define clCreateKernelsInProgram clCreateKernelsInProgram_fn
+inline cl_int clCreateKernelsInProgram(cl_program p0, cl_uint p1, cl_kernel* p2, cl_uint* p3) { return clCreateKernelsInProgram_pfn(p0, p1, p2, p3); }
+#undef clCreateProgramWithBinary
+#define clCreateProgramWithBinary clCreateProgramWithBinary_fn
+inline cl_program clCreateProgramWithBinary(cl_context p0, cl_uint p1, const cl_device_id* p2, const size_t* p3, const unsigned char** p4, cl_int* p5, cl_int* p6) { return clCreateProgramWithBinary_pfn(p0, p1, p2, p3, p4, p5, p6); }
+#undef clCreateProgramWithBuiltInKernels
+#define clCreateProgramWithBuiltInKernels clCreateProgramWithBuiltInKernels_fn
+inline cl_program clCreateProgramWithBuiltInKernels(cl_context p0, cl_uint p1, const cl_device_id* p2, const char* p3, cl_int* p4) { return clCreateProgramWithBuiltInKernels_pfn(p0, p1, p2, p3, p4); }
+#undef clCreateProgramWithSource
+#define clCreateProgramWithSource clCreateProgramWithSource_fn
+inline cl_program clCreateProgramWithSource(cl_context p0, cl_uint p1, const char** p2, const size_t* p3, cl_int* p4) { return clCreateProgramWithSource_pfn(p0, p1, p2, p3, p4); }
+#undef clCreateSampler
+#define clCreateSampler clCreateSampler_fn
+inline cl_sampler clCreateSampler(cl_context p0, cl_bool p1, cl_addressing_mode p2, cl_filter_mode p3, cl_int* p4) { return clCreateSampler_pfn(p0, p1, p2, p3, p4); }
+#undef clCreateSubBuffer
+#define clCreateSubBuffer clCreateSubBuffer_fn
+inline cl_mem clCreateSubBuffer(cl_mem p0, cl_mem_flags p1, cl_buffer_create_type p2, const void* p3, cl_int* p4) { return clCreateSubBuffer_pfn(p0, p1, p2, p3, p4); }
+#undef clCreateSubDevices
+#define clCreateSubDevices clCreateSubDevices_fn
+inline cl_int clCreateSubDevices(cl_device_id p0, const cl_device_partition_property* p1, cl_uint p2, cl_device_id* p3, cl_uint* p4) { return clCreateSubDevices_pfn(p0, p1, p2, p3, p4); }
+#undef clCreateUserEvent
+#define clCreateUserEvent clCreateUserEvent_fn
+inline cl_event clCreateUserEvent(cl_context p0, cl_int* p1) { return clCreateUserEvent_pfn(p0, p1); }
+#undef clEnqueueBarrier
+#define clEnqueueBarrier clEnqueueBarrier_fn
+inline cl_int clEnqueueBarrier(cl_command_queue p0) { return clEnqueueBarrier_pfn(p0); }
+#undef clEnqueueBarrierWithWaitList
+#define clEnqueueBarrierWithWaitList clEnqueueBarrierWithWaitList_fn
+inline cl_int clEnqueueBarrierWithWaitList(cl_command_queue p0, cl_uint p1, const cl_event* p2, cl_event* p3) { return clEnqueueBarrierWithWaitList_pfn(p0, p1, p2, p3); }
+#undef clEnqueueCopyBuffer
+#define clEnqueueCopyBuffer clEnqueueCopyBuffer_fn
+inline cl_int clEnqueueCopyBuffer(cl_command_queue p0, cl_mem p1, cl_mem p2, size_t p3, size_t p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueCopyBufferRect
+#define clEnqueueCopyBufferRect clEnqueueCopyBufferRect_fn
+inline cl_int clEnqueueCopyBufferRect(cl_command_queue p0, cl_mem p1, cl_mem p2, const size_t* p3, const size_t* p4, const size_t* p5, size_t p6, size_t p7, size_t p8, size_t p9, cl_uint p10, const cl_event* p11, cl_event* p12) { return clEnqueueCopyBufferRect_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12); }
+#undef clEnqueueCopyBufferToImage
+#define clEnqueueCopyBufferToImage clEnqueueCopyBufferToImage_fn
+inline cl_int clEnqueueCopyBufferToImage(cl_command_queue p0, cl_mem p1, cl_mem p2, size_t p3, const size_t* p4, const size_t* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyBufferToImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueCopyImage
+#define clEnqueueCopyImage clEnqueueCopyImage_fn
+inline cl_int clEnqueueCopyImage(cl_command_queue p0, cl_mem p1, cl_mem p2, const size_t* p3, const size_t* p4, const size_t* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueCopyImageToBuffer
+#define clEnqueueCopyImageToBuffer clEnqueueCopyImageToBuffer_fn
+inline cl_int clEnqueueCopyImageToBuffer(cl_command_queue p0, cl_mem p1, cl_mem p2, const size_t* p3, const size_t* p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueCopyImageToBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueFillBuffer
+#define clEnqueueFillBuffer clEnqueueFillBuffer_fn
+inline cl_int clEnqueueFillBuffer(cl_command_queue p0, cl_mem p1, const void* p2, size_t p3, size_t p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueFillBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueFillImage
+#define clEnqueueFillImage clEnqueueFillImage_fn
+inline cl_int clEnqueueFillImage(cl_command_queue p0, cl_mem p1, const void* p2, const size_t* p3, const size_t* p4, cl_uint p5, const cl_event* p6, cl_event* p7) { return clEnqueueFillImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7); }
+#undef clEnqueueMapBuffer
+#define clEnqueueMapBuffer clEnqueueMapBuffer_fn
+inline void* clEnqueueMapBuffer(cl_command_queue p0, cl_mem p1, cl_bool p2, cl_map_flags p3, size_t p4, size_t p5, cl_uint p6, const cl_event* p7, cl_event* p8, cl_int* p9) { return clEnqueueMapBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9); }
+#undef clEnqueueMapImage
+#define clEnqueueMapImage clEnqueueMapImage_fn
+inline void* clEnqueueMapImage(cl_command_queue p0, cl_mem p1, cl_bool p2, cl_map_flags p3, const size_t* p4, const size_t* p5, size_t* p6, size_t* p7, cl_uint p8, const cl_event* p9, cl_event* p10, cl_int* p11) { return clEnqueueMapImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11); }
+#undef clEnqueueMarker
+#define clEnqueueMarker clEnqueueMarker_fn
+inline cl_int clEnqueueMarker(cl_command_queue p0, cl_event* p1) { return clEnqueueMarker_pfn(p0, p1); }
+#undef clEnqueueMarkerWithWaitList
+#define clEnqueueMarkerWithWaitList clEnqueueMarkerWithWaitList_fn
+inline cl_int clEnqueueMarkerWithWaitList(cl_command_queue p0, cl_uint p1, const cl_event* p2, cl_event* p3) { return clEnqueueMarkerWithWaitList_pfn(p0, p1, p2, p3); }
+#undef clEnqueueMigrateMemObjects
+#define clEnqueueMigrateMemObjects clEnqueueMigrateMemObjects_fn
+inline cl_int clEnqueueMigrateMemObjects(cl_command_queue p0, cl_uint p1, const cl_mem* p2, cl_mem_migration_flags p3, cl_uint p4, const cl_event* p5, cl_event* p6) { return clEnqueueMigrateMemObjects_pfn(p0, p1, p2, p3, p4, p5, p6); }
+#undef clEnqueueNDRangeKernel
+#define clEnqueueNDRangeKernel clEnqueueNDRangeKernel_fn
+inline cl_int clEnqueueNDRangeKernel(cl_command_queue p0, cl_kernel p1, cl_uint p2, const size_t* p3, const size_t* p4, const size_t* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueNDRangeKernel_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueNativeKernel
+#define clEnqueueNativeKernel clEnqueueNativeKernel_fn
+inline cl_int clEnqueueNativeKernel(cl_command_queue p0, void (CL_CALLBACK*p1) (void*), void* p2, size_t p3, cl_uint p4, const cl_mem* p5, const void** p6, cl_uint p7, const cl_event* p8, cl_event* p9) { return clEnqueueNativeKernel_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9); }
+#undef clEnqueueReadBuffer
+#define clEnqueueReadBuffer clEnqueueReadBuffer_fn
+inline cl_int clEnqueueReadBuffer(cl_command_queue p0, cl_mem p1, cl_bool p2, size_t p3, size_t p4, void* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueReadBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueReadBufferRect
+#define clEnqueueReadBufferRect clEnqueueReadBufferRect_fn
+inline cl_int clEnqueueReadBufferRect(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, const size_t* p5, size_t p6, size_t p7, size_t p8, size_t p9, void* p10, cl_uint p11, const cl_event* p12, cl_event* p13) { return clEnqueueReadBufferRect_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13); }
+#undef clEnqueueReadImage
+#define clEnqueueReadImage clEnqueueReadImage_fn
+inline cl_int clEnqueueReadImage(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, size_t p5, size_t p6, void* p7, cl_uint p8, const cl_event* p9, cl_event* p10) { return clEnqueueReadImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10); }
+#undef clEnqueueTask
+#define clEnqueueTask clEnqueueTask_fn
+inline cl_int clEnqueueTask(cl_command_queue p0, cl_kernel p1, cl_uint p2, const cl_event* p3, cl_event* p4) { return clEnqueueTask_pfn(p0, p1, p2, p3, p4); }
+#undef clEnqueueUnmapMemObject
+#define clEnqueueUnmapMemObject clEnqueueUnmapMemObject_fn
+inline cl_int clEnqueueUnmapMemObject(cl_command_queue p0, cl_mem p1, void* p2, cl_uint p3, const cl_event* p4, cl_event* p5) { return clEnqueueUnmapMemObject_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clEnqueueWaitForEvents
+#define clEnqueueWaitForEvents clEnqueueWaitForEvents_fn
+inline cl_int clEnqueueWaitForEvents(cl_command_queue p0, cl_uint p1, const cl_event* p2) { return clEnqueueWaitForEvents_pfn(p0, p1, p2); }
+#undef clEnqueueWriteBuffer
+#define clEnqueueWriteBuffer clEnqueueWriteBuffer_fn
+inline cl_int clEnqueueWriteBuffer(cl_command_queue p0, cl_mem p1, cl_bool p2, size_t p3, size_t p4, const void* p5, cl_uint p6, const cl_event* p7, cl_event* p8) { return clEnqueueWriteBuffer_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clEnqueueWriteBufferRect
+#define clEnqueueWriteBufferRect clEnqueueWriteBufferRect_fn
+inline cl_int clEnqueueWriteBufferRect(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, const size_t* p5, size_t p6, size_t p7, size_t p8, size_t p9, const void* p10, cl_uint p11, const cl_event* p12, cl_event* p13) { return clEnqueueWriteBufferRect_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13); }
+#undef clEnqueueWriteImage
+#define clEnqueueWriteImage clEnqueueWriteImage_fn
+inline cl_int clEnqueueWriteImage(cl_command_queue p0, cl_mem p1, cl_bool p2, const size_t* p3, const size_t* p4, size_t p5, size_t p6, const void* p7, cl_uint p8, const cl_event* p9, cl_event* p10) { return clEnqueueWriteImage_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8, p9, p10); }
+#undef clFinish
+#define clFinish clFinish_fn
+inline cl_int clFinish(cl_command_queue p0) { return clFinish_pfn(p0); }
+#undef clFlush
+#define clFlush clFlush_fn
+inline cl_int clFlush(cl_command_queue p0) { return clFlush_pfn(p0); }
+#undef clGetCommandQueueInfo
+#define clGetCommandQueueInfo clGetCommandQueueInfo_fn
+inline cl_int clGetCommandQueueInfo(cl_command_queue p0, cl_command_queue_info p1, size_t p2, void* p3, size_t* p4) { return clGetCommandQueueInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetContextInfo
+#define clGetContextInfo clGetContextInfo_fn
+inline cl_int clGetContextInfo(cl_context p0, cl_context_info p1, size_t p2, void* p3, size_t* p4) { return clGetContextInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetDeviceIDs
+#define clGetDeviceIDs clGetDeviceIDs_fn
+inline cl_int clGetDeviceIDs(cl_platform_id p0, cl_device_type p1, cl_uint p2, cl_device_id* p3, cl_uint* p4) { return clGetDeviceIDs_pfn(p0, p1, p2, p3, p4); }
+#undef clGetDeviceInfo
+#define clGetDeviceInfo clGetDeviceInfo_fn
+inline cl_int clGetDeviceInfo(cl_device_id p0, cl_device_info p1, size_t p2, void* p3, size_t* p4) { return clGetDeviceInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetEventInfo
+#define clGetEventInfo clGetEventInfo_fn
+inline cl_int clGetEventInfo(cl_event p0, cl_event_info p1, size_t p2, void* p3, size_t* p4) { return clGetEventInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetEventProfilingInfo
+#define clGetEventProfilingInfo clGetEventProfilingInfo_fn
+inline cl_int clGetEventProfilingInfo(cl_event p0, cl_profiling_info p1, size_t p2, void* p3, size_t* p4) { return clGetEventProfilingInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetExtensionFunctionAddress
+#define clGetExtensionFunctionAddress clGetExtensionFunctionAddress_fn
+inline void* clGetExtensionFunctionAddress(const char* p0) { return clGetExtensionFunctionAddress_pfn(p0); }
+#undef clGetExtensionFunctionAddressForPlatform
+#define clGetExtensionFunctionAddressForPlatform clGetExtensionFunctionAddressForPlatform_fn
+inline void* clGetExtensionFunctionAddressForPlatform(cl_platform_id p0, const char* p1) { return clGetExtensionFunctionAddressForPlatform_pfn(p0, p1); }
+#undef clGetImageInfo
+#define clGetImageInfo clGetImageInfo_fn
+inline cl_int clGetImageInfo(cl_mem p0, cl_image_info p1, size_t p2, void* p3, size_t* p4) { return clGetImageInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetKernelArgInfo
+#define clGetKernelArgInfo clGetKernelArgInfo_fn
+inline cl_int clGetKernelArgInfo(cl_kernel p0, cl_uint p1, cl_kernel_arg_info p2, size_t p3, void* p4, size_t* p5) { return clGetKernelArgInfo_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clGetKernelInfo
+#define clGetKernelInfo clGetKernelInfo_fn
+inline cl_int clGetKernelInfo(cl_kernel p0, cl_kernel_info p1, size_t p2, void* p3, size_t* p4) { return clGetKernelInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetKernelWorkGroupInfo
+#define clGetKernelWorkGroupInfo clGetKernelWorkGroupInfo_fn
+inline cl_int clGetKernelWorkGroupInfo(cl_kernel p0, cl_device_id p1, cl_kernel_work_group_info p2, size_t p3, void* p4, size_t* p5) { return clGetKernelWorkGroupInfo_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clGetMemObjectInfo
+#define clGetMemObjectInfo clGetMemObjectInfo_fn
+inline cl_int clGetMemObjectInfo(cl_mem p0, cl_mem_info p1, size_t p2, void* p3, size_t* p4) { return clGetMemObjectInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetPlatformIDs
+#define clGetPlatformIDs clGetPlatformIDs_fn
+inline cl_int clGetPlatformIDs(cl_uint p0, cl_platform_id* p1, cl_uint* p2) { return clGetPlatformIDs_pfn(p0, p1, p2); }
+#undef clGetPlatformInfo
+#define clGetPlatformInfo clGetPlatformInfo_fn
+inline cl_int clGetPlatformInfo(cl_platform_id p0, cl_platform_info p1, size_t p2, void* p3, size_t* p4) { return clGetPlatformInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetProgramBuildInfo
+#define clGetProgramBuildInfo clGetProgramBuildInfo_fn
+inline cl_int clGetProgramBuildInfo(cl_program p0, cl_device_id p1, cl_program_build_info p2, size_t p3, void* p4, size_t* p5) { return clGetProgramBuildInfo_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clGetProgramInfo
+#define clGetProgramInfo clGetProgramInfo_fn
+inline cl_int clGetProgramInfo(cl_program p0, cl_program_info p1, size_t p2, void* p3, size_t* p4) { return clGetProgramInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetSamplerInfo
+#define clGetSamplerInfo clGetSamplerInfo_fn
+inline cl_int clGetSamplerInfo(cl_sampler p0, cl_sampler_info p1, size_t p2, void* p3, size_t* p4) { return clGetSamplerInfo_pfn(p0, p1, p2, p3, p4); }
+#undef clGetSupportedImageFormats
+#define clGetSupportedImageFormats clGetSupportedImageFormats_fn
+inline cl_int clGetSupportedImageFormats(cl_context p0, cl_mem_flags p1, cl_mem_object_type p2, cl_uint p3, cl_image_format* p4, cl_uint* p5) { return clGetSupportedImageFormats_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clLinkProgram
+#define clLinkProgram clLinkProgram_fn
+inline cl_program clLinkProgram(cl_context p0, cl_uint p1, const cl_device_id* p2, const char* p3, cl_uint p4, const cl_program* p5, void (CL_CALLBACK*p6) (cl_program, void*), void* p7, cl_int* p8) { return clLinkProgram_pfn(p0, p1, p2, p3, p4, p5, p6, p7, p8); }
+#undef clReleaseCommandQueue
+#define clReleaseCommandQueue clReleaseCommandQueue_fn
+inline cl_int clReleaseCommandQueue(cl_command_queue p0) { return clReleaseCommandQueue_pfn(p0); }
+#undef clReleaseContext
+#define clReleaseContext clReleaseContext_fn
+inline cl_int clReleaseContext(cl_context p0) { return clReleaseContext_pfn(p0); }
+#undef clReleaseDevice
+#define clReleaseDevice clReleaseDevice_fn
+inline cl_int clReleaseDevice(cl_device_id p0) { return clReleaseDevice_pfn(p0); }
+#undef clReleaseEvent
+#define clReleaseEvent clReleaseEvent_fn
+inline cl_int clReleaseEvent(cl_event p0) { return clReleaseEvent_pfn(p0); }
+#undef clReleaseKernel
+#define clReleaseKernel clReleaseKernel_fn
+inline cl_int clReleaseKernel(cl_kernel p0) { return clReleaseKernel_pfn(p0); }
+#undef clReleaseMemObject
+#define clReleaseMemObject clReleaseMemObject_fn
+inline cl_int clReleaseMemObject(cl_mem p0) { return clReleaseMemObject_pfn(p0); }
+#undef clReleaseProgram
+#define clReleaseProgram clReleaseProgram_fn
+inline cl_int clReleaseProgram(cl_program p0) { return clReleaseProgram_pfn(p0); }
+#undef clReleaseSampler
+#define clReleaseSampler clReleaseSampler_fn
+inline cl_int clReleaseSampler(cl_sampler p0) { return clReleaseSampler_pfn(p0); }
+#undef clRetainCommandQueue
+#define clRetainCommandQueue clRetainCommandQueue_fn
+inline cl_int clRetainCommandQueue(cl_command_queue p0) { return clRetainCommandQueue_pfn(p0); }
+#undef clRetainContext
+#define clRetainContext clRetainContext_fn
+inline cl_int clRetainContext(cl_context p0) { return clRetainContext_pfn(p0); }
+#undef clRetainDevice
+#define clRetainDevice clRetainDevice_fn
+inline cl_int clRetainDevice(cl_device_id p0) { return clRetainDevice_pfn(p0); }
+#undef clRetainEvent
+#define clRetainEvent clRetainEvent_fn
+inline cl_int clRetainEvent(cl_event p0) { return clRetainEvent_pfn(p0); }
+#undef clRetainKernel
+#define clRetainKernel clRetainKernel_fn
+inline cl_int clRetainKernel(cl_kernel p0) { return clRetainKernel_pfn(p0); }
+#undef clRetainMemObject
+#define clRetainMemObject clRetainMemObject_fn
+inline cl_int clRetainMemObject(cl_mem p0) { return clRetainMemObject_pfn(p0); }
+#undef clRetainProgram
+#define clRetainProgram clRetainProgram_fn
+inline cl_int clRetainProgram(cl_program p0) { return clRetainProgram_pfn(p0); }
+#undef clRetainSampler
+#define clRetainSampler clRetainSampler_fn
+inline cl_int clRetainSampler(cl_sampler p0) { return clRetainSampler_pfn(p0); }
+#undef clSetEventCallback
+#define clSetEventCallback clSetEventCallback_fn
+inline cl_int clSetEventCallback(cl_event p0, cl_int p1, void (CL_CALLBACK*p2) (cl_event, cl_int, void*), void* p3) { return clSetEventCallback_pfn(p0, p1, p2, p3); }
+#undef clSetKernelArg
+#define clSetKernelArg clSetKernelArg_fn
+inline cl_int clSetKernelArg(cl_kernel p0, cl_uint p1, size_t p2, const void* p3) { return clSetKernelArg_pfn(p0, p1, p2, p3); }
+#undef clSetMemObjectDestructorCallback
+#define clSetMemObjectDestructorCallback clSetMemObjectDestructorCallback_fn
+inline cl_int clSetMemObjectDestructorCallback(cl_mem p0, void (CL_CALLBACK*p1) (cl_mem, void*), void* p2) { return clSetMemObjectDestructorCallback_pfn(p0, p1, p2); }
+#undef clSetUserEventStatus
+#define clSetUserEventStatus clSetUserEventStatus_fn
+inline cl_int clSetUserEventStatus(cl_event p0, cl_int p1) { return clSetUserEventStatus_pfn(p0, p1); }
+#undef clUnloadCompiler
+#define clUnloadCompiler clUnloadCompiler_fn
+inline cl_int clUnloadCompiler() { return clUnloadCompiler_pfn(); }
+#undef clUnloadPlatformCompiler
+#define clUnloadPlatformCompiler clUnloadPlatformCompiler_fn
+inline cl_int clUnloadPlatformCompiler(cl_platform_id p0) { return clUnloadPlatformCompiler_pfn(p0); }
+#undef clWaitForEvents
+#define clWaitForEvents clWaitForEvents_fn
+inline cl_int clWaitForEvents(cl_uint p0, const cl_event* p1) { return clWaitForEvents_pfn(p0, p1); }

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/autogenerated/opencl_gl.hpp

@@ -0,0 +1,62 @@
+//
+// AUTOGENERATED, DO NOT EDIT
+//
+#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_HPP
+#error "Invalid usage"
+#endif
+
+// generated by parser_cl.py
+#define clCreateFromGLBuffer clCreateFromGLBuffer_
+#define clCreateFromGLRenderbuffer clCreateFromGLRenderbuffer_
+#define clCreateFromGLTexture clCreateFromGLTexture_
+#define clCreateFromGLTexture2D clCreateFromGLTexture2D_
+#define clCreateFromGLTexture3D clCreateFromGLTexture3D_
+#define clEnqueueAcquireGLObjects clEnqueueAcquireGLObjects_
+#define clEnqueueReleaseGLObjects clEnqueueReleaseGLObjects_
+#define clGetGLContextInfoKHR clGetGLContextInfoKHR_
+#define clGetGLObjectInfo clGetGLObjectInfo_
+#define clGetGLTextureInfo clGetGLTextureInfo_
+
+#if defined __APPLE__
+#include <OpenCL/cl_gl.h>
+#else
+#include <CL/cl_gl.h>
+#endif
+
+// generated by parser_cl.py
+#undef clCreateFromGLBuffer
+#define clCreateFromGLBuffer clCreateFromGLBuffer_pfn
+#undef clCreateFromGLRenderbuffer
+#define clCreateFromGLRenderbuffer clCreateFromGLRenderbuffer_pfn
+#undef clCreateFromGLTexture
+#define clCreateFromGLTexture clCreateFromGLTexture_pfn
+#undef clCreateFromGLTexture2D
+#define clCreateFromGLTexture2D clCreateFromGLTexture2D_pfn
+#undef clCreateFromGLTexture3D
+#define clCreateFromGLTexture3D clCreateFromGLTexture3D_pfn
+#undef clEnqueueAcquireGLObjects
+#define clEnqueueAcquireGLObjects clEnqueueAcquireGLObjects_pfn
+#undef clEnqueueReleaseGLObjects
+#define clEnqueueReleaseGLObjects clEnqueueReleaseGLObjects_pfn
+#undef clGetGLContextInfoKHR
+#define clGetGLContextInfoKHR clGetGLContextInfoKHR_pfn
+#undef clGetGLObjectInfo
+#define clGetGLObjectInfo clGetGLObjectInfo_pfn
+#undef clGetGLTextureInfo
+#define clGetGLTextureInfo clGetGLTextureInfo_pfn
+
+#ifdef cl_khr_gl_sharing
+
+// generated by parser_cl.py
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLBuffer)(cl_context, cl_mem_flags, cl_GLuint, int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLRenderbuffer)(cl_context, cl_mem_flags, cl_GLuint, cl_int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLTexture)(cl_context, cl_mem_flags, cl_GLenum, cl_GLint, cl_GLuint, cl_int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLTexture2D)(cl_context, cl_mem_flags, cl_GLenum, cl_GLint, cl_GLuint, cl_int*);
+extern CL_RUNTIME_EXPORT cl_mem (CL_API_CALL*clCreateFromGLTexture3D)(cl_context, cl_mem_flags, cl_GLenum, cl_GLint, cl_GLuint, cl_int*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueAcquireGLObjects)(cl_command_queue, cl_uint, const cl_mem*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clEnqueueReleaseGLObjects)(cl_command_queue, cl_uint, const cl_mem*, cl_uint, const cl_event*, cl_event*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetGLContextInfoKHR)(const cl_context_properties*, cl_gl_context_info, size_t, void*, size_t*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetGLObjectInfo)(cl_mem, cl_gl_object_type*, cl_GLuint*);
+extern CL_RUNTIME_EXPORT cl_int (CL_API_CALL*clGetGLTextureInfo)(cl_mem, cl_gl_texture_info, size_t, void*, size_t*);
+
+#endif // cl_khr_gl_sharing

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/autogenerated/opencl_gl_wrappers.hpp

@@ -0,0 +1,42 @@
+//
+// AUTOGENERATED, DO NOT EDIT
+//
+#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_GL_WRAPPERS_HPP
+#error "Invalid usage"
+#endif
+
+#ifdef cl_khr_gl_sharing
+
+// generated by parser_cl.py
+#undef clCreateFromGLBuffer
+#define clCreateFromGLBuffer clCreateFromGLBuffer_fn
+inline cl_mem clCreateFromGLBuffer(cl_context p0, cl_mem_flags p1, cl_GLuint p2, int* p3) { return clCreateFromGLBuffer_pfn(p0, p1, p2, p3); }
+#undef clCreateFromGLRenderbuffer
+#define clCreateFromGLRenderbuffer clCreateFromGLRenderbuffer_fn
+inline cl_mem clCreateFromGLRenderbuffer(cl_context p0, cl_mem_flags p1, cl_GLuint p2, cl_int* p3) { return clCreateFromGLRenderbuffer_pfn(p0, p1, p2, p3); }
+#undef clCreateFromGLTexture
+#define clCreateFromGLTexture clCreateFromGLTexture_fn
+inline cl_mem clCreateFromGLTexture(cl_context p0, cl_mem_flags p1, cl_GLenum p2, cl_GLint p3, cl_GLuint p4, cl_int* p5) { return clCreateFromGLTexture_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clCreateFromGLTexture2D
+#define clCreateFromGLTexture2D clCreateFromGLTexture2D_fn
+inline cl_mem clCreateFromGLTexture2D(cl_context p0, cl_mem_flags p1, cl_GLenum p2, cl_GLint p3, cl_GLuint p4, cl_int* p5) { return clCreateFromGLTexture2D_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clCreateFromGLTexture3D
+#define clCreateFromGLTexture3D clCreateFromGLTexture3D_fn
+inline cl_mem clCreateFromGLTexture3D(cl_context p0, cl_mem_flags p1, cl_GLenum p2, cl_GLint p3, cl_GLuint p4, cl_int* p5) { return clCreateFromGLTexture3D_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clEnqueueAcquireGLObjects
+#define clEnqueueAcquireGLObjects clEnqueueAcquireGLObjects_fn
+inline cl_int clEnqueueAcquireGLObjects(cl_command_queue p0, cl_uint p1, const cl_mem* p2, cl_uint p3, const cl_event* p4, cl_event* p5) { return clEnqueueAcquireGLObjects_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clEnqueueReleaseGLObjects
+#define clEnqueueReleaseGLObjects clEnqueueReleaseGLObjects_fn
+inline cl_int clEnqueueReleaseGLObjects(cl_command_queue p0, cl_uint p1, const cl_mem* p2, cl_uint p3, const cl_event* p4, cl_event* p5) { return clEnqueueReleaseGLObjects_pfn(p0, p1, p2, p3, p4, p5); }
+#undef clGetGLContextInfoKHR
+#define clGetGLContextInfoKHR clGetGLContextInfoKHR_fn
+inline cl_int clGetGLContextInfoKHR(const cl_context_properties* p0, cl_gl_context_info p1, size_t p2, void* p3, size_t* p4) { return clGetGLContextInfoKHR_pfn(p0, p1, p2, p3, p4); }
+#undef clGetGLObjectInfo
+#define clGetGLObjectInfo clGetGLObjectInfo_fn
+inline cl_int clGetGLObjectInfo(cl_mem p0, cl_gl_object_type* p1, cl_GLuint* p2) { return clGetGLObjectInfo_pfn(p0, p1, p2); }
+#undef clGetGLTextureInfo
+#define clGetGLTextureInfo clGetGLTextureInfo_fn
+inline cl_int clGetGLTextureInfo(cl_mem p0, cl_gl_texture_info p1, size_t p2, void* p3, size_t* p4) { return clGetGLTextureInfo_pfn(p0, p1, p2, p3, p4); }
+
+#endif // cl_khr_gl_sharing

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/opencl_clblas.hpp

@@ -0,0 +1,53 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the OpenCV Foundation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP
+#define OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP
+
+#ifdef HAVE_CLAMDBLAS
+
+#include "opencl_core.hpp"
+
+#include "autogenerated/opencl_clblas.hpp"
+
+#endif // HAVE_CLAMDBLAS
+
+#endif // OPENCV_CORE_OCL_RUNTIME_CLAMDBLAS_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/opencl_clfft.hpp

@@ -0,0 +1,53 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the OpenCV Foundation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP
+#define OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP
+
+#ifdef HAVE_CLAMDFFT
+
+#include "opencl_core.hpp"
+
+#include "autogenerated/opencl_clfft.hpp"
+
+#endif // HAVE_CLAMDFFT
+
+#endif // OPENCV_CORE_OCL_RUNTIME_CLAMDFFT_HPP

GameAssist/GameAssist/include/cv2/opencv2/core/opencl/runtime/opencl_core.hpp

@@ -0,0 +1,84 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the OpenCV Foundation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP
+#define OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP
+
+#ifdef HAVE_OPENCL
+
+#ifndef CL_RUNTIME_EXPORT
+#if (defined(BUILD_SHARED_LIBS) || defined(OPENCV_CORE_SHARED)) && (defined _WIN32 || defined WINCE) && \
+    !(defined(__OPENCV_BUILD) && defined(OPENCV_MODULE_IS_PART_OF_WORLD))
+#define CL_RUNTIME_EXPORT __declspec(dllimport)
+#else
+#define CL_RUNTIME_EXPORT
+#endif
+#endif
+
+#ifdef HAVE_OPENCL_SVM
+#define clSVMAlloc clSVMAlloc_
+#define clSVMFree clSVMFree_
+#define clSetKernelArgSVMPointer clSetKernelArgSVMPointer_
+#define clSetKernelExecInfo clSetKernelExecInfo_
+#define clEnqueueSVMFree clEnqueueSVMFree_
+#define clEnqueueSVMMemcpy clEnqueueSVMMemcpy_
+#define clEnqueueSVMMemFill clEnqueueSVMMemFill_
+#define clEnqueueSVMMap clEnqueueSVMMap_
+#define clEnqueueSVMUnmap clEnqueueSVMUnmap_
+#endif
+
+#include "autogenerated/opencl_core.hpp"
+
+#ifndef CL_DEVICE_DOUBLE_FP_CONFIG
+#define CL_DEVICE_DOUBLE_FP_CONFIG 0x1032
+#endif
+
+#ifndef CL_DEVICE_HALF_FP_CONFIG
+#define CL_DEVICE_HALF_FP_CONFIG 0x1033
+#endif
+
+#ifndef CL_VERSION_1_2
+#define CV_REQUIRE_OPENCL_1_2_ERROR CV_Error(cv::Error::OpenCLApiCallError, "OpenCV compiled without OpenCL v1.2 support, so we can't use functionality from OpenCL v1.2")
+#endif
+
+#endif // HAVE_OPENCL
+
+#endif // OPENCV_CORE_OCL_RUNTIME_OPENCL_CORE_HPP