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| /*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"#ifdef CV_CXX11#include <initializer_list>#endifnamespace cv{//! @addtogroup core_basic//! @{////////////////////////////// Small Matrix /////////////////////////////! @cond IGNOREDstruct CV_EXPORTS Matx_AddOp {};struct CV_EXPORTS Matx_SubOp {};struct CV_EXPORTS Matx_ScaleOp {};struct CV_EXPORTS Matx_MulOp {};struct CV_EXPORTS Matx_DivOp {};struct CV_EXPORTS Matx_MatMulOp {};struct CV_EXPORTS Matx_TOp {};//! @endcond/** @brief Template class for small matrices whose type and size are known at compilation timeIf you need a more flexible type, use Mat . The elements of the matrix M are accessible using theM(i,j) notation. Most of the common matrix operations (see also @ref MatrixExpressions ) areavailable. To do an operation on Matx that is not implemented, you can easily convert the matrix toMat and backwards:@code{.cpp}    Matx33f m(1, 2, 3,              4, 5, 6,              7, 8, 9);    cout << sum(Mat(m*m.t())) << endl;@endcodeExcept 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);@endcodeIn case if C++11 features are avaliable, std::initializer_list can be also used to initizlize 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();    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#ifdef CV_CXX11    Matx(std::initializer_list<_Tp>); //!< initialize from an initializer list#endif    static Matx all(_Tp alpha);    static Matx zeros();    static Matx ones();    static Matx eye();    static Matx diag(const diag_type& d);    static Matx randu(_Tp a, _Tp b);    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 i, int j) 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 i, int j) const;    _Tp& operator ()(int i, int j);    //! 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;/*!  traits*/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;};/* Utility methods*/template<typename _Tp, int m> static double determinant(const Matx<_Tp, m, m>& a);template<typename _Tp, int m, int n> static double trace(const Matx<_Tp, m, n>& a);template<typename _Tp, int m, int n> static double norm(const Matx<_Tp, m, n>& M);template<typename _Tp, int m, int n> static double norm(const Matx<_Tp, m, n>& M, int normType);/////////////////////// Vec (used as element of multi-channel images //////////////////////** @brief Template class for short numerical vectors, a partial case of MatxThis template class represents short numerical vectors (of 1, 2, 3, 4 ... elements) on which youcan perform basic arithmetical operations, access individual elements using [] operator etc. Thevectors are allocated on stack, as opposite to std::valarray, std::vector, cv::Mat etc., whichelements are dynamically allocated in the heap.The template takes 2 parameters:@tparam _Tp element type@tparam cn the number of elementsIn addition to the universal notation like Vec<float, 3>, you can use shorter aliasesfor 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);#ifdef CV_CXX11    Vec(std::initializer_list<_Tp>);#endif    Vec(const Vec<_Tp, cn>& v);    static Vec all(_Tp alpha);    //! 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(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;/** @} *//*!  traits*/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, int cn> static Vec<_Tp, cn> normalize(const Vec<_Tp, cn>& v);//! @} core_basic//! @cond IGNORED///////////////////////////////////// helper classes /////////////////////////////////////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 Implementation ///////////////////////////////////template<typename _Tp, int m, int n> inlineMatx<_Tp, m, n>::Matx(){    for(int i = 0; i < channels; i++) val[i] = _Tp(0);}template<typename _Tp, int m, int n> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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);}template<typename _Tp, int m, int n> inlineMatx<_Tp, m, n>::Matx(const _Tp* values){    for( int i = 0; i < channels; i++ ) val[i] = values[i];}#ifdef CV_CXX11template<typename _Tp, int m, int n> inlineMatx<_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;    }}#endiftemplate<typename _Tp, int m, int n> inlineMatx<_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> inlineMatx<_Tp,m,n> Matx<_Tp,m,n>::zeros(){    return all(0);}template<typename _Tp, int m, int n> inlineMatx<_Tp,m,n> Matx<_Tp,m,n>::ones(){    return all(1);}template<typename _Tp, int m, int n> inlineMatx<_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> inlinedouble 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> inlineMatx<_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> inlineMatx<_Tp, m1, n1> Matx<_Tp, m, n>::reshape() const{    CV_StaticAssert(m1*n1 == m*n, "Input and destnarion 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> inlineMatx<_Tp, m1, n1> Matx<_Tp, m, n>::get_minor(int i, int j) const{    CV_DbgAssert(0 <= i && i+m1 <= m && 0 <= j && j+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)(i+di, j+dj);    return s;}template<typename _Tp, int m, int n> inlineMatx<_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> inlineMatx<_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> inlinetypename 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> inlineconst _Tp& Matx<_Tp, m, n>::operator()(int i, int j) const{    CV_DbgAssert( (unsigned)i < (unsigned)m && (unsigned)j < (unsigned)n );    return this->val[i*n + j];}template<typename _Tp, int m, int n> inline_Tp& Matx<_Tp, m, n>::operator ()(int i, int j){    CV_DbgAssert( (unsigned)i < (unsigned)m && (unsigned)j < (unsigned)n );    return val[i*n + j];}template<typename _Tp, int m, int n> inlineconst _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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_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> inlineMatx<_Tp, n, m> Matx<_Tp, m, n>::t() const{    return Matx<_Tp, n, m>(*this, Matx_TOp());}template<typename _Tp, int m, int n> inlineVec<_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 inlinedouble determinant(const Matx<_Tp, m, m>& a){    return cv::internal::Matx_DetOp<_Tp, m>()(a);}template<typename _Tp, int m, int n> static inlinedouble 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 inlinedouble 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 inlinedouble 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));    }}//////////////////////////////// matx comma initializer //////////////////////////////////template<typename _Tp, typename _T2, int m, int n> static inlineMatxCommaInitializer<_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> inlineMatxCommaInitializer<_Tp, m, n>::MatxCommaInitializer(Matx<_Tp, m, n>* _mtx)    : dst(_mtx), idx(0){}template<typename _Tp, int m, int n> template<typename _T2> inlineMatxCommaInitializer<_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> inlineMatx<_Tp, m, n> MatxCommaInitializer<_Tp, m, n>::operator *() const{    CV_DbgAssert( idx == n*m );    return *dst;}/////////////////////////////////// Vec Implementation ///////////////////////////////////template<typename _Tp, int cn> inlineVec<_Tp, cn>::Vec() {}template<typename _Tp, int cn> inlineVec<_Tp, cn>::Vec(_Tp v0)    : Matx<_Tp, cn, 1>(v0) {}template<typename _Tp, int cn> inlineVec<_Tp, cn>::Vec(_Tp v0, _Tp v1)    : Matx<_Tp, cn, 1>(v0, v1) {}template<typename _Tp, int cn> inlineVec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2)    : Matx<_Tp, cn, 1>(v0, v1, v2) {}template<typename _Tp, int cn> inlineVec<_Tp, cn>::Vec(_Tp v0, _Tp v1, _Tp v2, _Tp v3)    : Matx<_Tp, cn, 1>(v0, v1, v2, v3) {}template<typename _Tp, int cn> inlineVec<_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> inlineVec<_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> inlineVec<_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> inlineVec<_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> inlineVec<_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> inlineVec<_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> inlineVec<_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> inlineVec<_Tp, cn>::Vec(const _Tp* values)    : Matx<_Tp, cn, 1>(values) {}#ifdef CV_CXX11template<typename _Tp, int cn> inlineVec<_Tp, cn>::Vec(std::initializer_list<_Tp> list)    : Matx<_Tp, cn, 1>(list) {}#endiftemplate<typename _Tp, int cn> inlineVec<_Tp, cn>::Vec(const Vec<_Tp, cn>& m)    : Matx<_Tp, cn, 1>(m.val) {}template<typename _Tp, int cn> inlineVec<_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> inlineVec<_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> inlineVec<_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> inlineVec<_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> inlineVec<_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<> inlineVec<float, 2> Vec<float, 2>::conj() const{    return cv::internal::conjugate(*this);}template<> inlineVec<double, 2> Vec<double, 2>::conj() const{    return cv::internal::conjugate(*this);}template<> inlineVec<float, 4> Vec<float, 4>::conj() const{    return cv::internal::conjugate(*this);}template<> inlineVec<double, 4> Vec<double, 4>::conj() const{    return cv::internal::conjugate(*this);}template<typename _Tp, int cn> inlineVec<_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<> inlineVec<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<> inlineVec<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> inlineVec<_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> inlineconst _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> inlineconst _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> inlineVec<_Tp, cn> normalize(const Vec<_Tp, cn>& v){    double nv = norm(v);    return v * (nv ? 1./nv : 0.);}//////////////////////////////// vec comma initializer //////////////////////////////////template<typename _Tp, typename _T2, int cn> static inlineVecCommaInitializer<_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> inlineVecCommaInitializer<_Tp, cn>::VecCommaInitializer(Vec<_Tp, cn>* _vec)    : MatxCommaInitializer<_Tp, cn, 1>(_vec){}template<typename _Tp, int cn> template<typename _T2> inlineVecCommaInitializer<_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> inlineVec<_Tp, cn> VecCommaInitializer<_Tp, cn>::operator *() const{    CV_DbgAssert( this->idx == cn );    return *this->dst;}//! @endcond///////////////////////////// Matx out-of-class operators //////////////////////////////////! @relates cv::Matx//! @{template<typename _Tp1, typename _Tp2, int m, int n> static inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineMatx<_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 inlineVec<_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 inlinebool 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 inlinebool operator != (const Matx<_Tp, m, n>& a, const Matx<_Tp, m, n>& b){    return !(a == b);}//! @}////////////////////////////// Vec out-of-class operators //////////////////////////////////! @relates cv::Vec//! @{template<typename _Tp1, typename _Tp2, int cn> static inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, int alpha){    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());}template<typename _Tp, int cn> static inlineVec<_Tp, cn> operator * (int alpha, const Vec<_Tp, cn>& a){    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());}template<typename _Tp, int cn> static inlineVec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, float alpha){    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());}template<typename _Tp, int cn> static inlineVec<_Tp, cn> operator * (float alpha, const Vec<_Tp, cn>& a){    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());}template<typename _Tp, int cn> static inlineVec<_Tp, cn> operator * (const Vec<_Tp, cn>& a, double alpha){    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());}template<typename _Tp, int cn> static inlineVec<_Tp, cn> operator * (double alpha, const Vec<_Tp, cn>& a){    return Vec<_Tp, cn>(a, alpha, Matx_ScaleOp());}template<typename _Tp, int cn> static inlineVec<_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 inlineVec<_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 inlineVec<_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 inlineVec<_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_HPP
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