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							- /*M///////////////////////////////////////////////////////////////////////////////////////
 
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- //  copy or use the software.
 
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- //                          License Agreement
 
- //                For Open Source Computer Vision Library
 
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- // 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:
 
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- //   * 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,
 
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- //   * The name of the copyright holders may not be used to endorse or promote products
 
- //     derived from this software without specific prior written permission.
 
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- //M*/
 
- #ifndef OPENCV_SHAPE_SHAPE_DISTANCE_HPP
 
- #define OPENCV_SHAPE_SHAPE_DISTANCE_HPP
 
- #include "opencv2/core.hpp"
 
- #include "opencv2/shape/hist_cost.hpp"
 
- #include "opencv2/shape/shape_transformer.hpp"
 
- namespace cv
 
- {
 
- //! @addtogroup shape
 
- //! @{
 
- /** @example shape_example.cpp
 
- An example using shape distance algorithm
 
- */
 
- /** @brief Abstract base class for shape distance algorithms.
 
-  */
 
- class CV_EXPORTS_W ShapeDistanceExtractor : public Algorithm
 
- {
 
- public:
 
-     /** @brief Compute the shape distance between two shapes defined by its contours.
 
-     @param contour1 Contour defining first shape.
 
-     @param contour2 Contour defining second shape.
 
-      */
 
-     CV_WRAP virtual float computeDistance(InputArray contour1, InputArray contour2) = 0;
 
- };
 
- /***********************************************************************************/
 
- /***********************************************************************************/
 
- /***********************************************************************************/
 
- /** @brief Implementation of the Shape Context descriptor and matching algorithm
 
- proposed by Belongie et al. in "Shape Matching and Object Recognition Using Shape Contexts" (PAMI
 
- 2002). This implementation is packaged in a generic scheme, in order to allow you the
 
- implementation of the common variations of the original pipeline.
 
- */
 
- class CV_EXPORTS_W ShapeContextDistanceExtractor : public ShapeDistanceExtractor
 
- {
 
- public:
 
-     /** @brief Establish the number of angular bins for the Shape Context Descriptor used in the shape matching
 
-     pipeline.
 
-     @param nAngularBins The number of angular bins in the shape context descriptor.
 
-      */
 
-     CV_WRAP virtual void setAngularBins(int nAngularBins) = 0;
 
-     CV_WRAP virtual int getAngularBins() const = 0;
 
-     /** @brief Establish the number of radial bins for the Shape Context Descriptor used in the shape matching
 
-     pipeline.
 
-     @param nRadialBins The number of radial bins in the shape context descriptor.
 
-      */
 
-     CV_WRAP virtual void setRadialBins(int nRadialBins) = 0;
 
-     CV_WRAP virtual int getRadialBins() const = 0;
 
-     /** @brief Set the inner radius of the shape context descriptor.
 
-     @param innerRadius The value of the inner radius.
 
-      */
 
-     CV_WRAP virtual void setInnerRadius(float innerRadius) = 0;
 
-     CV_WRAP virtual float getInnerRadius() const = 0;
 
-     /** @brief Set the outer radius of the shape context descriptor.
 
-     @param outerRadius The value of the outer radius.
 
-      */
 
-     CV_WRAP virtual void setOuterRadius(float outerRadius) = 0;
 
-     CV_WRAP virtual float getOuterRadius() const = 0;
 
-     CV_WRAP virtual void setRotationInvariant(bool rotationInvariant) = 0;
 
-     CV_WRAP virtual bool getRotationInvariant() const = 0;
 
-     /** @brief Set the weight of the shape context distance in the final value of the shape distance. The shape
 
-     context distance between two shapes is defined as the symmetric sum of shape context matching costs
 
-     over best matching points. The final value of the shape distance is a user-defined linear
 
-     combination of the shape context distance, an image appearance distance, and a bending energy.
 
-     @param shapeContextWeight The weight of the shape context distance in the final distance value.
 
-      */
 
-     CV_WRAP virtual void setShapeContextWeight(float shapeContextWeight) = 0;
 
-     CV_WRAP virtual float getShapeContextWeight() const = 0;
 
-     /** @brief Set the weight of the Image Appearance cost in the final value of the shape distance. The image
 
-     appearance cost is defined as the sum of squared brightness differences in Gaussian windows around
 
-     corresponding image points. The final value of the shape distance is a user-defined linear
 
-     combination of the shape context distance, an image appearance distance, and a bending energy. If
 
-     this value is set to a number different from 0, is mandatory to set the images that correspond to
 
-     each shape.
 
-     @param imageAppearanceWeight The weight of the appearance cost in the final distance value.
 
-      */
 
-     CV_WRAP virtual void setImageAppearanceWeight(float imageAppearanceWeight) = 0;
 
-     CV_WRAP virtual float getImageAppearanceWeight() const = 0;
 
-     /** @brief Set the weight of the Bending Energy in the final value of the shape distance. The bending energy
 
-     definition depends on what transformation is being used to align the shapes. The final value of the
 
-     shape distance is a user-defined linear combination of the shape context distance, an image
 
-     appearance distance, and a bending energy.
 
-     @param bendingEnergyWeight The weight of the Bending Energy in the final distance value.
 
-      */
 
-     CV_WRAP virtual void setBendingEnergyWeight(float bendingEnergyWeight) = 0;
 
-     CV_WRAP virtual float getBendingEnergyWeight() const = 0;
 
-     /** @brief Set the images that correspond to each shape. This images are used in the calculation of the Image
 
-     Appearance cost.
 
-     @param image1 Image corresponding to the shape defined by contours1.
 
-     @param image2 Image corresponding to the shape defined by contours2.
 
-      */
 
-     CV_WRAP virtual void setImages(InputArray image1, InputArray image2) = 0;
 
-     CV_WRAP virtual void getImages(OutputArray image1, OutputArray image2) const = 0;
 
-     CV_WRAP virtual void setIterations(int iterations) = 0;
 
-     CV_WRAP virtual int getIterations() const = 0;
 
-     /** @brief Set the algorithm used for building the shape context descriptor cost matrix.
 
-     @param comparer Smart pointer to a HistogramCostExtractor, an algorithm that defines the cost
 
-     matrix between descriptors.
 
-      */
 
-     CV_WRAP virtual void setCostExtractor(Ptr<HistogramCostExtractor> comparer) = 0;
 
-     CV_WRAP virtual Ptr<HistogramCostExtractor> getCostExtractor() const = 0;
 
-     /** @brief Set the value of the standard deviation for the Gaussian window for the image appearance cost.
 
-     @param sigma Standard Deviation.
 
-      */
 
-     CV_WRAP virtual void setStdDev(float sigma) = 0;
 
-     CV_WRAP virtual float getStdDev() const = 0;
 
-     /** @brief Set the algorithm used for aligning the shapes.
 
-     @param transformer Smart pointer to a ShapeTransformer, an algorithm that defines the aligning
 
-     transformation.
 
-      */
 
-     CV_WRAP virtual void setTransformAlgorithm(Ptr<ShapeTransformer> transformer) = 0;
 
-     CV_WRAP virtual Ptr<ShapeTransformer> getTransformAlgorithm() const = 0;
 
- };
 
- /* Complete constructor */
 
- CV_EXPORTS_W Ptr<ShapeContextDistanceExtractor>
 
-     createShapeContextDistanceExtractor(int nAngularBins=12, int nRadialBins=4,
 
-                                         float innerRadius=0.2f, float outerRadius=2, int iterations=3,
 
-                                         const Ptr<HistogramCostExtractor> &comparer = createChiHistogramCostExtractor(),
 
-                                         const Ptr<ShapeTransformer> &transformer = createThinPlateSplineShapeTransformer());
 
- /***********************************************************************************/
 
- /***********************************************************************************/
 
- /***********************************************************************************/
 
- /** @brief A simple Hausdorff distance measure between shapes defined by contours
 
- according to the paper "Comparing Images using the Hausdorff distance." by D.P. Huttenlocher, G.A.
 
- Klanderman, and W.J. Rucklidge. (PAMI 1993). :
 
-  */
 
- class CV_EXPORTS_W HausdorffDistanceExtractor : public ShapeDistanceExtractor
 
- {
 
- public:
 
-     /** @brief Set the norm used to compute the Hausdorff value between two shapes. It can be L1 or L2 norm.
 
-     @param distanceFlag Flag indicating which norm is used to compute the Hausdorff distance
 
-     (NORM_L1, NORM_L2).
 
-      */
 
-     CV_WRAP virtual void setDistanceFlag(int distanceFlag) = 0;
 
-     CV_WRAP virtual int getDistanceFlag() const = 0;
 
-     /** @brief This method sets the rank proportion (or fractional value) that establish the Kth ranked value of
 
-     the partial Hausdorff distance. Experimentally had been shown that 0.6 is a good value to compare
 
-     shapes.
 
-     @param rankProportion fractional value (between 0 and 1).
 
-      */
 
-     CV_WRAP virtual void setRankProportion(float rankProportion) = 0;
 
-     CV_WRAP virtual float getRankProportion() const = 0;
 
- };
 
- /* Constructor */
 
- CV_EXPORTS_W Ptr<HausdorffDistanceExtractor> createHausdorffDistanceExtractor(int distanceFlag=cv::NORM_L2, float rankProp=0.6f);
 
- //! @}
 
- } // cv
 
- #endif
 
 
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