diff --git a/modules/python/test/test_shape.py b/modules/python/test/test_shape.py deleted file mode 100644 index 1c9f07b7d4..0000000000 --- a/modules/python/test/test_shape.py +++ /dev/null @@ -1,26 +0,0 @@ -#!/usr/bin/env python -import cv2 as cv - -from tests_common import NewOpenCVTests - -class shape_test(NewOpenCVTests): - - def test_computeDistance(self): - - a = self.get_sample('samples/data/shape_sample/1.png', cv.IMREAD_GRAYSCALE) - b = self.get_sample('samples/data/shape_sample/2.png', cv.IMREAD_GRAYSCALE) - - ca, _ = cv.findContours(a, cv.RETR_CCOMP, cv.CHAIN_APPROX_TC89_KCOS) - cb, _ = cv.findContours(b, cv.RETR_CCOMP, cv.CHAIN_APPROX_TC89_KCOS) - - hd = cv.createHausdorffDistanceExtractor() - sd = cv.createShapeContextDistanceExtractor() - - d1 = hd.computeDistance(ca[0], cb[0]) - d2 = sd.computeDistance(ca[0], cb[0]) - - self.assertAlmostEqual(d1, 26.4196891785, 3, "HausdorffDistanceExtractor") - self.assertAlmostEqual(d2, 0.25804194808, 3, "ShapeContextDistanceExtractor") - -if __name__ == '__main__': - NewOpenCVTests.bootstrap() diff --git a/modules/shape/CMakeLists.txt b/modules/shape/CMakeLists.txt deleted file mode 100644 index 61beeb6607..0000000000 --- a/modules/shape/CMakeLists.txt +++ /dev/null @@ -1,2 +0,0 @@ -set(the_description "Shape descriptors and matchers") -ocv_define_module(shape opencv_core opencv_imgproc opencv_calib3d WRAP python) diff --git a/modules/shape/include/opencv2/shape.hpp b/modules/shape/include/opencv2/shape.hpp deleted file mode 100644 index f302b6bbc0..0000000000 --- a/modules/shape/include/opencv2/shape.hpp +++ /dev/null @@ -1,57 +0,0 @@ -/*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) 2009-2012, 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_SHAPE_HPP -#define OPENCV_SHAPE_HPP - -#include "opencv2/shape/emdL1.hpp" -#include "opencv2/shape/shape_transformer.hpp" -#include "opencv2/shape/hist_cost.hpp" -#include "opencv2/shape/shape_distance.hpp" - -/** - @defgroup shape Shape Distance and Matching - */ - -#endif - -/* End of file. */ diff --git a/modules/shape/include/opencv2/shape/emdL1.hpp b/modules/shape/include/opencv2/shape/emdL1.hpp deleted file mode 100644 index a15d68c222..0000000000 --- a/modules/shape/include/opencv2/shape/emdL1.hpp +++ /dev/null @@ -1,72 +0,0 @@ -/*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) 2009-2012, 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_EMD_L1_HPP -#define OPENCV_EMD_L1_HPP - -#include "opencv2/core.hpp" - -namespace cv -{ -/****************************************************************************************\ -* EMDL1 Function * -\****************************************************************************************/ - -//! @addtogroup shape -//! @{ - -/** @brief Computes the "minimal work" distance between two weighted point configurations base on the papers -"EMD-L1: An efficient and Robust Algorithm for comparing histogram-based descriptors", by Haibin -Ling and Kazunori Okuda; and "The Earth Mover's Distance is the Mallows Distance: Some Insights from -Statistics", by Elizaveta Levina and Peter Bickel. - -@param signature1 First signature, a single column floating-point matrix. Each row is the value of -the histogram in each bin. -@param signature2 Second signature of the same format and size as signature1. - */ -CV_EXPORTS float EMDL1(InputArray signature1, InputArray signature2); - -//! @} - -}//namespace cv - -#endif diff --git a/modules/shape/include/opencv2/shape/hist_cost.hpp b/modules/shape/include/opencv2/shape/hist_cost.hpp deleted file mode 100644 index 21d0d6807b..0000000000 --- a/modules/shape/include/opencv2/shape/hist_cost.hpp +++ /dev/null @@ -1,111 +0,0 @@ -/*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_HIST_COST_HPP -#define OPENCV_HIST_COST_HPP - -#include "opencv2/imgproc.hpp" - -namespace cv -{ - -//! @addtogroup shape -//! @{ - -/** @brief Abstract base class for histogram cost algorithms. - */ -class CV_EXPORTS_W HistogramCostExtractor : public Algorithm -{ -public: - CV_WRAP virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) = 0; - - CV_WRAP virtual void setNDummies(int nDummies) = 0; - CV_WRAP virtual int getNDummies() const = 0; - - CV_WRAP virtual void setDefaultCost(float defaultCost) = 0; - CV_WRAP virtual float getDefaultCost() const = 0; -}; - -/** @brief A norm based cost extraction. : - */ -class CV_EXPORTS_W NormHistogramCostExtractor : public HistogramCostExtractor -{ -public: - CV_WRAP virtual void setNormFlag(int flag) = 0; - CV_WRAP virtual int getNormFlag() const = 0; -}; - -CV_EXPORTS_W Ptr - createNormHistogramCostExtractor(int flag=DIST_L2, int nDummies=25, float defaultCost=0.2f); - -/** @brief An EMD based cost extraction. : - */ -class CV_EXPORTS_W EMDHistogramCostExtractor : public HistogramCostExtractor -{ -public: - CV_WRAP virtual void setNormFlag(int flag) = 0; - CV_WRAP virtual int getNormFlag() const = 0; -}; - -CV_EXPORTS_W Ptr - createEMDHistogramCostExtractor(int flag=DIST_L2, int nDummies=25, float defaultCost=0.2f); - -/** @brief An Chi based cost extraction. : - */ -class CV_EXPORTS_W ChiHistogramCostExtractor : public HistogramCostExtractor -{}; - -CV_EXPORTS_W Ptr createChiHistogramCostExtractor(int nDummies=25, float defaultCost=0.2f); - -/** @brief An EMD-L1 based cost extraction. : - */ -class CV_EXPORTS_W EMDL1HistogramCostExtractor : public HistogramCostExtractor -{}; - -CV_EXPORTS_W Ptr - createEMDL1HistogramCostExtractor(int nDummies=25, float defaultCost=0.2f); - -//! @} - -} // cv -#endif diff --git a/modules/shape/include/opencv2/shape/shape.hpp b/modules/shape/include/opencv2/shape/shape.hpp deleted file mode 100644 index 5c4da3cefa..0000000000 --- a/modules/shape/include/opencv2/shape/shape.hpp +++ /dev/null @@ -1,48 +0,0 @@ -/*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/shape.hpp" diff --git a/modules/shape/include/opencv2/shape/shape_distance.hpp b/modules/shape/include/opencv2/shape/shape_distance.hpp deleted file mode 100644 index 725b56ac95..0000000000 --- a/modules/shape/include/opencv2/shape/shape_distance.hpp +++ /dev/null @@ -1,227 +0,0 @@ -/*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_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 samples/cpp/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 comparer) = 0; - CV_WRAP virtual Ptr 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 transformer) = 0; - CV_WRAP virtual Ptr getTransformAlgorithm() const = 0; -}; - -/* Complete constructor */ -CV_EXPORTS_W Ptr - createShapeContextDistanceExtractor(int nAngularBins=12, int nRadialBins=4, - float innerRadius=0.2f, float outerRadius=2, int iterations=3, - const Ptr &comparer = createChiHistogramCostExtractor(), - const Ptr &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 createHausdorffDistanceExtractor(int distanceFlag=cv::NORM_L2, float rankProp=0.6f); - -//! @} - -} // cv -#endif diff --git a/modules/shape/include/opencv2/shape/shape_transformer.hpp b/modules/shape/include/opencv2/shape/shape_transformer.hpp deleted file mode 100644 index 3c3ce20c12..0000000000 --- a/modules/shape/include/opencv2/shape/shape_transformer.hpp +++ /dev/null @@ -1,132 +0,0 @@ -/*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_SHAPE_SHAPE_TRANSFORM_HPP -#define OPENCV_SHAPE_SHAPE_TRANSFORM_HPP -#include -#include "opencv2/core.hpp" -#include "opencv2/imgproc.hpp" - -namespace cv -{ - -//! @addtogroup shape -//! @{ - -/** @brief Abstract base class for shape transformation algorithms. - */ -class CV_EXPORTS_W ShapeTransformer : public Algorithm -{ -public: - /** @brief Estimate the transformation parameters of the current transformer algorithm, based on point matches. - - @param transformingShape Contour defining first shape. - @param targetShape Contour defining second shape (Target). - @param matches Standard vector of Matches between points. - */ - CV_WRAP virtual void estimateTransformation(InputArray transformingShape, InputArray targetShape, - std::vector& matches) = 0; - - /** @brief Apply a transformation, given a pre-estimated transformation parameters. - - @param input Contour (set of points) to apply the transformation. - @param output Output contour. - */ - CV_WRAP virtual float applyTransformation(InputArray input, OutputArray output=noArray()) = 0; - - /** @brief Apply a transformation, given a pre-estimated transformation parameters, to an Image. - - @param transformingImage Input image. - @param output Output image. - @param flags Image interpolation method. - @param borderMode border style. - @param borderValue border value. - */ - CV_WRAP virtual void warpImage(InputArray transformingImage, OutputArray output, - int flags=INTER_LINEAR, int borderMode=BORDER_CONSTANT, - const Scalar& borderValue=Scalar()) const = 0; -}; - -/***********************************************************************************/ -/***********************************************************************************/ - -/** @brief Definition of the transformation - -occupied in the paper "Principal Warps: Thin-Plate Splines and Decomposition of Deformations", by -F.L. Bookstein (PAMI 1989). : - */ -class CV_EXPORTS_W ThinPlateSplineShapeTransformer : public ShapeTransformer -{ -public: - /** @brief Set the regularization parameter for relaxing the exact interpolation requirements of the TPS - algorithm. - - @param beta value of the regularization parameter. - */ - CV_WRAP virtual void setRegularizationParameter(double beta) = 0; - CV_WRAP virtual double getRegularizationParameter() const = 0; -}; - -/** Complete constructor */ -CV_EXPORTS_W Ptr - createThinPlateSplineShapeTransformer(double regularizationParameter=0); - -/***********************************************************************************/ -/***********************************************************************************/ - -/** @brief Wrapper class for the OpenCV Affine Transformation algorithm. : - */ -class CV_EXPORTS_W AffineTransformer : public ShapeTransformer -{ -public: - CV_WRAP virtual void setFullAffine(bool fullAffine) = 0; - CV_WRAP virtual bool getFullAffine() const = 0; -}; - -/** Complete constructor */ -CV_EXPORTS_W Ptr createAffineTransformer(bool fullAffine); - -//! @} - -} // cv -#endif diff --git a/modules/shape/src/aff_trans.cpp b/modules/shape/src/aff_trans.cpp deleted file mode 100644 index 75daf2b173..0000000000 --- a/modules/shape/src/aff_trans.cpp +++ /dev/null @@ -1,279 +0,0 @@ -/*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*/ - -#include "precomp.hpp" - -namespace cv -{ - -class AffineTransformerImpl : public AffineTransformer -{ -public: - /* Constructors */ - AffineTransformerImpl() - { - fullAffine = true; - name_ = "ShapeTransformer.AFF"; - transformCost = 0; - } - - AffineTransformerImpl(bool _fullAffine) - { - fullAffine = _fullAffine; - name_ = "ShapeTransformer.AFF"; - transformCost = 0; - } - - /* Destructor */ - ~AffineTransformerImpl() - { - } - - //! the main operator - virtual void estimateTransformation(InputArray transformingShape, InputArray targetShape, std::vector &matches) CV_OVERRIDE; - virtual float applyTransformation(InputArray input, OutputArray output=noArray()) CV_OVERRIDE; - virtual void warpImage(InputArray transformingImage, OutputArray output, - int flags, int borderMode, const Scalar& borderValue) const CV_OVERRIDE; - - //! Setters/Getters - virtual void setFullAffine(bool _fullAffine) CV_OVERRIDE {fullAffine=_fullAffine;} - virtual bool getFullAffine() const CV_OVERRIDE {return fullAffine;} - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "affine_type" << int(fullAffine); - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - fullAffine = int(fn["affine_type"])?true:false; - } - -private: - bool fullAffine; - Mat affineMat; - float transformCost; - -protected: - String name_; -}; - -void AffineTransformerImpl::warpImage(InputArray transformingImage, OutputArray output, - int flags, int borderMode, const Scalar& borderValue) const -{ - CV_INSTRUMENT_REGION(); - - CV_Assert(!affineMat.empty()); - warpAffine(transformingImage, output, affineMat, transformingImage.getMat().size(), flags, borderMode, borderValue); -} - - -static Mat _localAffineEstimate(const std::vector& shape1, const std::vector& shape2, - bool fullAfine) -{ - Mat out(2,3,CV_32F); - int siz=2*(int)shape1.size(); - - if (fullAfine) - { - Mat matM(siz, 6, CV_32F); - Mat matP(siz,1,CV_32F); - int contPt=0; - for (int ii=0; ii(0,0)=shape1[contPt].x; - therow.at(0,1)=shape1[contPt].y; - therow.at(0,2)=1; - therow.row(0).copyTo(matM.row(ii)); - matP.at(ii,0) = shape2[contPt].x; - } - else - { - therow.at(0,3)=shape1[contPt].x; - therow.at(0,4)=shape1[contPt].y; - therow.at(0,5)=1; - therow.row(0).copyTo(matM.row(ii)); - matP.at(ii,0) = shape2[contPt].y; - contPt++; - } - } - Mat sol; - solve(matM, matP, sol, DECOMP_SVD); - out = sol.reshape(0,2); - } - else - { - Mat matM(siz, 4, CV_32F); - Mat matP(siz,1,CV_32F); - int contPt=0; - for (int ii=0; ii(0,0)=shape1[contPt].x; - therow.at(0,1)=shape1[contPt].y; - therow.at(0,2)=1; - therow.row(0).copyTo(matM.row(ii)); - matP.at(ii,0) = shape2[contPt].x; - } - else - { - therow.at(0,0)=shape1[contPt].y; - therow.at(0,1)=-shape1[contPt].x; - therow.at(0,3)=1; - therow.row(0).copyTo(matM.row(ii)); - matP.at(ii,0) = shape2[contPt].y; - contPt++; - } - } - Mat sol; - solve(matM, matP, sol, DECOMP_SVD); - out.at(0,0)=sol.at(0,0); - out.at(0,1)=sol.at(1,0); - out.at(0,2)=sol.at(2,0); - out.at(1,0)=-sol.at(1,0); - out.at(1,1)=sol.at(0,0); - out.at(1,2)=sol.at(3,0); - } - return out; -} - -void AffineTransformerImpl::estimateTransformation(InputArray _pts1, InputArray _pts2, std::vector& _matches) -{ - CV_INSTRUMENT_REGION(); - - Mat pts1 = _pts1.getMat(); - Mat pts2 = _pts2.getMat(); - CV_Assert((pts1.channels()==2) && (pts1.cols>0) && (pts2.channels()==2) && (pts2.cols>0)); - CV_Assert(_matches.size()>1); - - if (pts1.type() != CV_32F) - pts1.convertTo(pts1, CV_32F); - if (pts2.type() != CV_32F) - pts2.convertTo(pts2, CV_32F); - - // Use only valid matchings // - std::vector matches; - for (size_t i=0; i<_matches.size(); i++) - { - if (_matches[i].queryIdx shape1; // transforming shape - std::vector shape2; // target shape - for (size_t i=0; i(0,matches[i].queryIdx); - shape1.push_back(pt1); - - Point2f pt2=pts2.at(0,matches[i].trainIdx); - shape2.push_back(pt2); - } - - Mat affine; - if (fullAffine) - { - estimateAffine2D(shape1, shape2).convertTo(affine, CV_32F); - } else - { - estimateAffinePartial2D(shape1, shape2).convertTo(affine, CV_32F); - } - - if (affine.empty()) - //In case there is not good solution, just give a LLS based one - affine = _localAffineEstimate(shape1, shape2, fullAffine); - - affineMat = affine; -} - -float AffineTransformerImpl::applyTransformation(InputArray inPts, OutputArray outPts) -{ - CV_INSTRUMENT_REGION(); - - Mat pts1 = inPts.getMat(); - CV_Assert((pts1.channels()==2) && (pts1.cols>0)); - - //Apply transformation in the complete set of points - Mat fAffine; - transform(pts1, fAffine, affineMat); - - // Ensambling output // - if (outPts.needed()) - { - outPts.create(1,fAffine.cols, CV_32FC2); - Mat outMat = outPts.getMat(); - for (int i=0; i(0,i)=fAffine.at(0,i); - } - - // Updating Transform Cost // - Mat Af(2, 2, CV_32F); - Af.at(0,0)=affineMat.at(0,0); - Af.at(0,1)=affineMat.at(1,0); - Af.at(1,0)=affineMat.at(0,1); - Af.at(1,1)=affineMat.at(1,1); - SVD mysvd(Af, SVD::NO_UV); - Mat singVals=mysvd.w; - transformCost=std::log((singVals.at(0,0)+FLT_MIN)/(singVals.at(1,0)+FLT_MIN)); - - return transformCost; -} - -Ptr createAffineTransformer(bool fullAffine) -{ - return Ptr( new AffineTransformerImpl(fullAffine) ); -} - -} // cv diff --git a/modules/shape/src/emdL1.cpp b/modules/shape/src/emdL1.cpp deleted file mode 100644 index b28dc96705..0000000000 --- a/modules/shape/src/emdL1.cpp +++ /dev/null @@ -1,797 +0,0 @@ -/*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*/ - -/* - * Implementation of an optimized EMD for histograms based in - * the papers "EMD-L1: An efficient and Robust Algorithm - * for comparing histogram-based descriptors", by Haibin Ling and - * Kazunori Okuda; and "The Earth Mover's Distance is the Mallows - * Distance: Some Insights from Statistics", by Elizaveta Levina and - * Peter Bickel, based on HAIBIN LING AND KAZUNORI OKADA implementation. - */ - -#include "precomp.hpp" -#include "emdL1_def.hpp" -#include - -/****************************************************************************************\ -* EMDL1 Class * -\****************************************************************************************/ - -float EmdL1::getEMDL1(cv::Mat &sig1, cv::Mat &sig2) -{ - // Initialization - CV_Assert((sig1.rows==sig2.rows) && (sig1.cols==sig2.cols) && (!sig1.empty()) && (!sig2.empty())); - if(!initBaseTrees(sig1.rows, 1)) - return -1; - - float *H1=new float[sig1.rows], *H2 = new float[sig2.rows]; - for (int ii=0; ii(ii,0); - H2[ii]=sig2.at(ii,0); - } - - fillBaseTrees(H1,H2); // Initialize histograms - greedySolution(); // Construct an initial Basic Feasible solution - initBVTree(); // Initialize BVTree - - // Iteration - bool bOptimal = false; - m_nItr = 0; - while(!bOptimal && m_nItrpChild); - - // Optimality test - bOptimal = isOptimal(); - - // Find new solution - if(!bOptimal) - findNewSolution(); - ++m_nItr; - } - delete [] H1; - delete [] H2; - // Output the total flow - return compuTotalFlow(); -} - -void EmdL1::setMaxIteration(int _nMaxIt) -{ - nMaxIt=_nMaxIt; -} - -//-- SubFunctions called in the EMD algorithm -bool EmdL1::initBaseTrees(int n1, int n2, int n3) -{ - if(binsDim1==n1 && binsDim2==n2 && binsDim3==n3) - return true; - binsDim1 = n1; - binsDim2 = n2; - binsDim3 = n3; - if(binsDim1==0 || binsDim2==0) dimension = 0; - else dimension = (binsDim3==0)?2:3; - - if(dimension==2) - { - m_Nodes.resize(binsDim1); - m_EdgesUp.resize(binsDim1); - m_EdgesRight.resize(binsDim1); - for(int i1=0; i1 d2s(binsDim2); - d2s[0] = 0; - for(c=0; c d1s(binsDim1); - d1s[0] = 0; - for(r=0; r fabs(dFlow+d1s[r+1])); // Move upward or right - - // modify basic variables, record BV and related values - if(bUpward) - { - // move to up - pBV = &(m_EdgesUp[r][c]); - m_NBVEdges[nNBV++] = &(m_EdgesRight[r][c]); - D[r+1][c] += dFlow; // auxiliary matrix maintenance - d1s[r+1] += dFlow; // auxiliary matrix maintenance - } - else - { - // move to right, no other choice - pBV = &(m_EdgesRight[r][c]); - if(rpParent->pChild = pBV; - pBV->flow = fabs(dFlow); - pBV->iDir = dFlow>0; // 1:outward, 0:inward - } - - //- rightmost column, no choice but move upward - c = binsDim2-1; - for(r=0; rpParent->pChild= pBV; - pBV->flow = fabs(dFlow); - pBV->iDir = dFlow>0; // 1:outward, 0:inward - } - return true; -} - -bool EmdL1::greedySolution3() -{ - //- Prepare auxiliary array, D=H1-H2 - int i1,i2,i3; - std::vector D(binsDim1); - for(i1=0; i1 d1s(binsDim1); - d1s[0] = 0; - for(i1=0; i1 d2s(binsDim2); - d2s[0] = 0; - for(i2=0; i2 d3s(binsDim3); - d3s[0] = 0; - for(i3=0; i3::max(); - f2 = (i2<(binsDim2-1))?fabs(dFlow+d2s[i2+1]):std::numeric_limits::max(); - f3 = (i3<(binsDim3-1))?fabs(dFlow+d3s[i3+1]):std::numeric_limits::max(); - - if(f1flow = fabs(dFlow); - pBV->iDir = dFlow>0; // 1:outward, 0:inward - pBV->pParent->pChild= pBV; - } - } - } - return true; -} - -void EmdL1::initBVTree() -{ - // initialize BVTree from the initial BF solution - //- Using the center of the graph as the root - int r = (int)(0.5*binsDim1-.5); - int c = (int)(0.5*binsDim2-.5); - int z = (int)(0.5*binsDim3-.5); - m_pRoot = dimension==2 ? &(m_Nodes[r][c]) : &(m_3dNodes[r][c][z]); - m_pRoot->u = 0; - m_pRoot->iLevel = 0; - m_pRoot->pParent= NULL; - m_pRoot->pPEdge = NULL; - - //- Prepare a queue - m_auxQueue[0] = m_pRoot; - int nQueue = 1; // length of queue - int iQHead = 0; // head of queue - - //- Recursively build subtrees - cvPEmdEdge pCurE=NULL, pNxtE=NULL; - cvPEmdNode pCurN=NULL, pNxtN=NULL; - int nBin = binsDim1*binsDim2*std::max(binsDim3,1); - while(iQHeadpos[0]; - c = pCurN->pos[1]; - z = pCurN->pos[2]; - - // check connection from itself - pCurE = pCurN->pChild; // the initial child from initial solution - if(pCurE) - { - pNxtN = pCurE->pChild; - pNxtN->pParent = pCurN; - pNxtN->pPEdge = pCurE; - m_auxQueue[nQueue++] = pNxtN; - } - - // check four neighbor nodes - int nNB = dimension==2?4:6; - for(int k=0;k0) pNxtN = &(m_Nodes[r][c-1]); // left - else if(k==1 && r>0) pNxtN = &(m_Nodes[r-1][c]); // down - else if(k==2 && c0) pNxtN = &(m_3dNodes[r][c-1][z]); // left - else if(k==1 && c0) pNxtN = &(m_3dNodes[r-1][c][z]); // down - else if(k==3 && r0) pNxtN = &(m_3dNodes[r][c][z-1]); // shallow - else if(k==5 && zpParent) - { - CV_Assert(pNxtN != NULL); - pNxtE = pNxtN->pChild; - if(pNxtE && pNxtE->pChild==pCurN) // has connection - { - pNxtN->pParent = pCurN; - pNxtN->pPEdge = pNxtE; - pNxtN->pChild = NULL; - m_auxQueue[nQueue++] = pNxtN; - - pNxtE->pParent = pCurN; // reverse direction - pNxtE->pChild = pNxtN; - pNxtE->iDir = !pNxtE->iDir; - - if(pCurE) pCurE->pNxt = pNxtE; // add to edge list - else pCurN->pChild = pNxtE; - pCurE = pNxtE; - } - } - } - } -} - -void EmdL1::updateSubtree(cvPEmdNode pRoot) -{ - // Initialize auxiliary queue - m_auxQueue[0] = pRoot; - int nQueue = 1; // queue length - int iQHead = 0; // head of queue - - // BFS browing - cvPEmdNode pCurN=NULL,pNxtN=NULL; - cvPEmdEdge pCurE=NULL; - while(iQHeadpChild; - - // browsing all children - while(pCurE) - { - pNxtN = pCurE->pChild; - pNxtN->iLevel = pCurN->iLevel+1; - pNxtN->u = pCurE->iDir ? (pCurN->u - 1) : (pCurN->u + 1); - pCurE = pCurE->pNxt; - m_auxQueue[nQueue++] = pNxtN; - } - } -} - -bool EmdL1::isOptimal() -{ - int iC, iMinC = 0; - cvPEmdEdge pE; - m_pEnter = NULL; - m_iEnter = -1; - - // test each NON-BV edges - for(int k=0; kpParent->u + pE->pChild->u; - if(iCpParent->u - pE->pChild->u; - if(iC=0) - { - m_pEnter = m_NBVEdges[m_iEnter]; - if(iMinC == (1 - m_pEnter->pChild->u + m_pEnter->pParent->u)) { - // reverse direction - cvPEmdNode pN = m_pEnter->pParent; - m_pEnter->pParent = m_pEnter->pChild; - m_pEnter->pChild = pN; - } - - m_pEnter->iDir = 1; - } - return m_iEnter==-1; -} - -void EmdL1::findNewSolution() -{ - // Find loop formed by adding the Enter BV edge. - findLoopFromEnterBV(); - // Modify flow values along the loop - cvPEmdEdge pE = NULL; - CV_Assert(m_pLeave != NULL); - float minFlow = m_pLeave->flow; - int k; - for(k=0; kiDir) pE->flow += minFlow; // outward - else pE->flow -= minFlow; // inward - } - for(k=0; kiDir) pE->flow -= minFlow; // outward - else pE->flow += minFlow; // inward - } - - // Update BV Tree, removing the Leaving-BV edge - cvPEmdNode pLParentN = m_pLeave->pParent; - cvPEmdNode pLChildN = m_pLeave->pChild; - cvPEmdEdge pPreE = pLParentN->pChild; - if(pPreE==m_pLeave) - { - pLParentN->pChild = m_pLeave->pNxt; // Leaving-BV is the first child - } - else - { - while(pPreE->pNxt != m_pLeave) - pPreE = pPreE->pNxt; - pPreE->pNxt = m_pLeave->pNxt; // remove Leaving-BV from child list - } - pLChildN->pParent = NULL; - pLChildN->pPEdge = NULL; - - m_NBVEdges[m_iEnter]= m_pLeave; // put the leaving-BV into the NBV array - - // Add the Enter BV edge - cvPEmdNode pEParentN = m_pEnter->pParent; - cvPEmdNode pEChildN = m_pEnter->pChild; - m_pEnter->flow = minFlow; - m_pEnter->pNxt = pEParentN->pChild; // insert the Enter BV as the first child - pEParentN->pChild = m_pEnter; // of its parent - - // Recursively update the tree start from pEChildN - cvPEmdNode pPreN = pEParentN; - cvPEmdNode pCurN = pEChildN; - cvPEmdNode pNxtN; - cvPEmdEdge pNxtE, pPreE0; - pPreE = m_pEnter; - while(pCurN) - { - pNxtN = pCurN->pParent; - pNxtE = pCurN->pPEdge; - pCurN->pParent = pPreN; - pCurN->pPEdge = pPreE; - if(pNxtN) - { - // remove the edge from pNxtN's child list - if(pNxtN->pChild==pNxtE) - { - pNxtN->pChild = pNxtE->pNxt; // first child - } - else - { - pPreE0 = pNxtN->pChild; - while(pPreE0->pNxt != pNxtE) - pPreE0 = pPreE0->pNxt; - pPreE0->pNxt = pNxtE->pNxt; // remove Leaving-BV from child list - } - // reverse the parent-child direction - pNxtE->pParent = pCurN; - pNxtE->pChild = pNxtN; - pNxtE->iDir = !pNxtE->iDir; - pNxtE->pNxt = pCurN->pChild; - pCurN->pChild = pNxtE; - pPreE = pNxtE; - pPreN = pCurN; - } - pCurN = pNxtN; - } - - // Update U at the child of the Enter BV - pEChildN->u = m_pEnter->iDir?(pEParentN->u-1):(pEParentN->u + 1); - pEChildN->iLevel = pEParentN->iLevel+1; -} - -void EmdL1::findLoopFromEnterBV() -{ - // Initialize Leaving-BV edge - float minFlow = std::numeric_limits::max(); - cvPEmdEdge pE = NULL; - int iLFlag = 0; // 0: in the FROM list, 1: in the TO list - - // Using two loop list to store the loop nodes - cvPEmdNode pFrom = m_pEnter->pParent; - cvPEmdNode pTo = m_pEnter->pChild; - m_iFrom = 0; - m_iTo = 0; - m_pLeave = NULL; - - // Trace back to make pFrom and pTo at the same level - while(pFrom->iLevel > pTo->iLevel) - { - pE = pFrom->pPEdge; - m_fromLoop[m_iFrom++] = pE; - if(!pE->iDir && pE->flowflow; - m_pLeave = pE; - iLFlag = 0; // 0: in the FROM list - } - pFrom = pFrom->pParent; - } - - while(pTo->iLevel > pFrom->iLevel) - { - pE = pTo->pPEdge; - m_toLoop[m_iTo++] = pE; - if(pE->iDir && pE->flowflow; - m_pLeave = pE; - iLFlag = 1; // 1: in the TO list - } - pTo = pTo->pParent; - } - - // Trace pTo and pFrom simultaneously till find their common ancester - while(pTo!=pFrom) - { - pE = pFrom->pPEdge; - m_fromLoop[m_iFrom++] = pE; - if(!pE->iDir && pE->flowflow; - m_pLeave = pE; - iLFlag = 0; // 0: in the FROM list, 1: in the TO list - } - pFrom = pFrom->pParent; - - pE = pTo->pPEdge; - m_toLoop[m_iTo++] = pE; - if(pE->iDir && pE->flowflow; - m_pLeave = pE; - iLFlag = 1; // 0: in the FROM list, 1: in the TO list - } - pTo = pTo->pParent; - } - - // Reverse the direction of the Enter BV edge if necessary - if(iLFlag==0) - { - cvPEmdNode pN = m_pEnter->pParent; - m_pEnter->pParent = m_pEnter->pChild; - m_pEnter->pChild = pN; - m_pEnter->iDir = !m_pEnter->iDir; - } -} - -float EmdL1::compuTotalFlow() -{ - // Computing the total flow as the final distance - float f = 0; - - // Initialize auxiliary queue - m_auxQueue[0] = m_pRoot; - int nQueue = 1; // length of queue - int iQHead = 0; // head of queue - - // BFS browing the tree - cvPEmdNode pCurN=NULL,pNxtN=NULL; - cvPEmdEdge pCurE=NULL; - while(iQHeadpChild; - - // browsing all children - while(pCurE) - { - f += pCurE->flow; - pNxtN = pCurE->pChild; - pCurE = pCurE->pNxt; - m_auxQueue[nQueue++] = pNxtN; - } - } - return f; -} - -/****************************************************************************************\ -* EMDL1 Function * -\****************************************************************************************/ - -float cv::EMDL1(InputArray _signature1, InputArray _signature2) -{ - CV_INSTRUMENT_REGION(); - - Mat signature1 = _signature1.getMat(), signature2 = _signature2.getMat(); - EmdL1 emdl1; - return emdl1.getEMDL1(signature1, signature2); -} diff --git a/modules/shape/src/emdL1_def.hpp b/modules/shape/src/emdL1_def.hpp deleted file mode 100644 index e6110c778a..0000000000 --- a/modules/shape/src/emdL1_def.hpp +++ /dev/null @@ -1,148 +0,0 @@ -/*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*/ - -#include -#include -#include - -/****************************************************************************************\ -* For EMDL1 Framework * -\****************************************************************************************/ -typedef struct cvEMDEdge* cvPEmdEdge; -typedef struct cvEMDNode* cvPEmdNode; -struct cvEMDNode -{ - int pos[3]; // grid position - float d; // initial value - int u; - // tree maintenance - int iLevel; // level in the tree, 0 means root - cvPEmdNode pParent; // pointer to its parent - cvPEmdEdge pChild; - cvPEmdEdge pPEdge; // point to the edge coming out from its parent -}; -struct cvEMDEdge -{ - float flow; // initial value - int iDir; // 1:outward, 0:inward - // tree maintenance - cvPEmdNode pParent; // point to its parent - cvPEmdNode pChild; // the child node - cvPEmdEdge pNxt; // next child/edge -}; -typedef std::vector cvEMDNodeArray; -typedef std::vector cvEMDEdgeArray; -typedef std::vector cvEMDNodeArray2D; -typedef std::vector cvEMDEdgeArray2D; -typedef std::vector floatArray; -typedef std::vector floatArray2D; - -/****************************************************************************************\ -* EMDL1 Class * -\****************************************************************************************/ -class EmdL1 -{ -public: - EmdL1() - { - m_pRoot = NULL; - binsDim1 = 0; - binsDim2 = 0; - binsDim3 = 0; - dimension = 0; - nMaxIt = 500; - - m_pLeave = 0; - m_iEnter = 0; - nNBV = 0; - m_nItr = 0; - m_iTo = 0; - m_iFrom = 0; - m_pEnter = 0; - } - - ~EmdL1() - { - } - - float getEMDL1(cv::Mat &sig1, cv::Mat &sig2); - void setMaxIteration(int _nMaxIt); - -private: - //-- SubFunctions called in the EMD algorithm - bool initBaseTrees(int n1=0, int n2=0, int n3=0); - bool fillBaseTrees(float *H1, float *H2); - bool greedySolution(); - bool greedySolution2(); - bool greedySolution3(); - void initBVTree(); - void updateSubtree(cvPEmdNode pRoot); - bool isOptimal(); - void findNewSolution(); - void findLoopFromEnterBV(); - float compuTotalFlow(); - -private: - int dimension; - int binsDim1, binsDim2, binsDim3; // the histogram contains m_n1 rows and m_n2 columns - int nNBV; // number of Non-Basic Variables (NBV) - int nMaxIt; - cvEMDNodeArray2D m_Nodes; // all nodes - cvEMDEdgeArray2D m_EdgesRight; // all edges to right - cvEMDEdgeArray2D m_EdgesUp; // all edges to upward - std::vector m_3dNodes; // all nodes for 3D - std::vector m_3dEdgesRight; // all edges to right, 3D - std::vector m_3dEdgesUp; // all edges to upward, 3D - std::vector m_3dEdgesDeep; // all edges to deep, 3D - std::vector m_NBVEdges; // pointers to all NON-BV edges - std::vector m_auxQueue; // auxiliary node queue - cvPEmdNode m_pRoot; // root of the BV Tree - cvPEmdEdge m_pEnter; // Enter BV edge - int m_iEnter; // Enter BV edge, index in m_NBVEdges - cvPEmdEdge m_pLeave; // Leave BV edge - int m_nItr; // number of iteration - // auxiliary variables for searching a new loop - std::vector m_fromLoop; - std::vector m_toLoop; - int m_iFrom; - int m_iTo; -}; diff --git a/modules/shape/src/haus_dis.cpp b/modules/shape/src/haus_dis.cpp deleted file mode 100644 index a544edcaa5..0000000000 --- a/modules/shape/src/haus_dis.cpp +++ /dev/null @@ -1,157 +0,0 @@ -/*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. -// -// -// Intel License Agreement -// For Open Source Computer Vision Library -// -// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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*/ - -#include "precomp.hpp" - -namespace cv -{ - -class HausdorffDistanceExtractorImpl CV_FINAL : public HausdorffDistanceExtractor -{ -public: - /* Constructor */ - HausdorffDistanceExtractorImpl(int _distanceFlag = NORM_L1, float _rankProportion=0.6) - { - distanceFlag = _distanceFlag; - rankProportion = _rankProportion; - name_ = "ShapeDistanceExtractor.HAU"; - } - - /* Destructor */ - ~HausdorffDistanceExtractorImpl() - { - } - - //! the main operator - virtual float computeDistance(InputArray contour1, InputArray contour2) CV_OVERRIDE; - - //! Setters/Getters - virtual void setDistanceFlag(int _distanceFlag) CV_OVERRIDE {distanceFlag=_distanceFlag;} - virtual int getDistanceFlag() const CV_OVERRIDE {return distanceFlag;} - - virtual void setRankProportion(float _rankProportion) CV_OVERRIDE - { - CV_Assert((_rankProportion>0) && (_rankProportion<=1)); - rankProportion=_rankProportion; - } - virtual float getRankProportion() const CV_OVERRIDE {return rankProportion;} - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "distance" << distanceFlag - << "rank" << rankProportion; - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - distanceFlag = (int)fn["distance"]; - rankProportion = (float)fn["rank"]; - } - -private: - int distanceFlag; - float rankProportion; - -protected: - String name_; -}; - -//! Hausdorff distance for a pair of set of points -static float _apply(const Mat &set1, const Mat &set2, int distType, double propRank) -{ - // Building distance matrix // - Mat disMat(set1.cols, set2.cols, CV_32F); - int K = int(propRank*(disMat.rows-1)); - - for (int r=0; r(0,r)-set2.at(0,c); - disMat.at(r,c) = (float)norm(Mat(diff), distType); - } - } - - Mat shortest(disMat.rows,1,CV_32F); - for (int ii=0; ii(ii,0) = float(mindis); - } - Mat sorted; - cv::sort(shortest, sorted, SORT_EVERY_ROW | SORT_DESCENDING); - return sorted.at(K,0); -} - -float HausdorffDistanceExtractorImpl::computeDistance(InputArray contour1, InputArray contour2) -{ - CV_INSTRUMENT_REGION(); - - Mat set1=contour1.getMat(), set2=contour2.getMat(); - if (set1.type() != CV_32F) - set1.convertTo(set1, CV_32F); - if (set2.type() != CV_32F) - set2.convertTo(set2, CV_32F); - CV_Assert((set1.channels()==2) && (set1.cols>0)); - CV_Assert((set2.channels()==2) && (set2.cols>0)); - - // Force vectors column-based - if (set1.dims > 1) - set1 = set1.reshape(2, 1); - if (set2.dims > 1) - set2 = set2.reshape(2, 1); - - return std::max( _apply(set1, set2, distanceFlag, rankProportion), - _apply(set2, set1, distanceFlag, rankProportion) ); -} - -Ptr createHausdorffDistanceExtractor(int distanceFlag, float rankProp) -{ - return Ptr(new HausdorffDistanceExtractorImpl(distanceFlag, rankProp)); -} - -} // cv diff --git a/modules/shape/src/hist_cost.cpp b/modules/shape/src/hist_cost.cpp deleted file mode 100644 index f255d60694..0000000000 --- a/modules/shape/src/hist_cost.cpp +++ /dev/null @@ -1,549 +0,0 @@ -/*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. -// -// -// Intel License Agreement -// For Open Source Computer Vision Library -// -// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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*/ - -#include "precomp.hpp" - -namespace cv -{ - -/*! */ -class NormHistogramCostExtractorImpl CV_FINAL : public NormHistogramCostExtractor -{ -public: - /* Constructors */ - NormHistogramCostExtractorImpl(int _flag, int _nDummies, float _defaultCost) - { - flag=_flag; - nDummies=_nDummies; - defaultCost=_defaultCost; - name_ = "HistogramCostExtractor.NOR"; - } - - /* Destructor */ - ~NormHistogramCostExtractorImpl() CV_OVERRIDE - { - } - - //! the main operator - virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; - - //! Setters/Getters - void setNDummies(int _nDummies) CV_OVERRIDE - { - nDummies=_nDummies; - } - - int getNDummies() const CV_OVERRIDE - { - return nDummies; - } - - void setDefaultCost(float _defaultCost) CV_OVERRIDE - { - defaultCost=_defaultCost; - } - - float getDefaultCost() const CV_OVERRIDE - { - return defaultCost; - } - - virtual void setNormFlag(int _flag) CV_OVERRIDE - { - flag=_flag; - } - - virtual int getNormFlag() const CV_OVERRIDE - { - return flag; - } - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "flag" << flag - << "dummies" << nDummies - << "default" << defaultCost; - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - flag = (int)fn["flag"]; - nDummies = (int)fn["dummies"]; - defaultCost = (float)fn["default"]; - } - -private: - int flag; - int nDummies; - float defaultCost; - -protected: - String name_; -}; - -void NormHistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) -{ - CV_INSTRUMENT_REGION(); - - // size of the costMatrix with dummies // - Mat descriptors1=_descriptors1.getMat(); - Mat descriptors2=_descriptors2.getMat(); - int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; - _costMatrix.create(costrows, costrows, CV_32F); - Mat costMatrix=_costMatrix.getMat(); - - - // Obtain copies of the descriptors // - cv::Mat scd1 = descriptors1.clone(); - cv::Mat scd2 = descriptors2.clone(); - - // row normalization // - for(int i=0; i(i,j)=(float)norm(columnDiff, flag); - } - else - { - costMatrix.at(i,j)=defaultCost; - } - } - } -} - -Ptr createNormHistogramCostExtractor(int flag, int nDummies, float defaultCost) -{ - return Ptr ( new NormHistogramCostExtractorImpl(flag, nDummies, defaultCost) ); -} - -/*! */ -class EMDHistogramCostExtractorImpl CV_FINAL : public EMDHistogramCostExtractor -{ -public: - /* Constructors */ - EMDHistogramCostExtractorImpl(int _flag, int _nDummies, float _defaultCost) - { - flag=_flag; - nDummies=_nDummies; - defaultCost=_defaultCost; - name_ = "HistogramCostExtractor.EMD"; - } - - /* Destructor */ - ~EMDHistogramCostExtractorImpl() CV_OVERRIDE - { - } - - //! the main operator - virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; - - //! Setters/Getters - void setNDummies(int _nDummies) CV_OVERRIDE - { - nDummies=_nDummies; - } - - int getNDummies() const CV_OVERRIDE - { - return nDummies; - } - - void setDefaultCost(float _defaultCost) CV_OVERRIDE - { - defaultCost=_defaultCost; - } - - float getDefaultCost() const CV_OVERRIDE - { - return defaultCost; - } - - virtual void setNormFlag(int _flag) CV_OVERRIDE - { - flag=_flag; - } - - virtual int getNormFlag() const CV_OVERRIDE - { - return flag; - } - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "flag" << flag - << "dummies" << nDummies - << "default" << defaultCost; - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - flag = (int)fn["flag"]; - nDummies = (int)fn["dummies"]; - defaultCost = (float)fn["default"]; - } - -private: - int flag; - int nDummies; - float defaultCost; - -protected: - String name_; -}; - -void EMDHistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) -{ - CV_INSTRUMENT_REGION(); - - // size of the costMatrix with dummies // - Mat descriptors1=_descriptors1.getMat(); - Mat descriptors2=_descriptors2.getMat(); - int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; - _costMatrix.create(costrows, costrows, CV_32F); - Mat costMatrix=_costMatrix.getMat(); - - // Obtain copies of the descriptors // - cv::Mat scd1=descriptors1.clone(); - cv::Mat scd2=descriptors2.clone(); - - // row normalization // - for(int i=0; i(k,1)=float(k); - } - for (int k=0; k(k,1)=float(k); - } - - costMatrix.at(i,j) = cv::EMD(sig1, sig2, flag); - } - else - { - costMatrix.at(i,j) = defaultCost; - } - } - } -} - -Ptr createEMDHistogramCostExtractor(int flag, int nDummies, float defaultCost) -{ - return Ptr ( new EMDHistogramCostExtractorImpl(flag, nDummies, defaultCost) ); -} - -/*! */ -class ChiHistogramCostExtractorImpl CV_FINAL : public ChiHistogramCostExtractor -{ -public: - /* Constructors */ - ChiHistogramCostExtractorImpl(int _nDummies, float _defaultCost) - { - name_ = "HistogramCostExtractor.CHI"; - nDummies=_nDummies; - defaultCost=_defaultCost; - } - - /* Destructor */ - ~ChiHistogramCostExtractorImpl() CV_OVERRIDE - { - } - - //! the main operator - virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; - - //! setters / getters - void setNDummies(int _nDummies) CV_OVERRIDE - { - nDummies=_nDummies; - } - - int getNDummies() const CV_OVERRIDE - { - return nDummies; - } - - void setDefaultCost(float _defaultCost) CV_OVERRIDE - { - defaultCost=_defaultCost; - } - - float getDefaultCost() const CV_OVERRIDE - { - return defaultCost; - } - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "dummies" << nDummies - << "default" << defaultCost; - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - nDummies = (int)fn["dummies"]; - defaultCost = (float)fn["default"]; - } - -protected: - String name_; - int nDummies; - float defaultCost; -}; - -void ChiHistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) -{ - CV_INSTRUMENT_REGION(); - - // size of the costMatrix with dummies // - Mat descriptors1=_descriptors1.getMat(); - Mat descriptors2=_descriptors2.getMat(); - int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; - _costMatrix.create(costrows, costrows, CV_32FC1); - Mat costMatrix=_costMatrix.getMat(); - - // Obtain copies of the descriptors // - cv::Mat scd1=descriptors1.clone(); - cv::Mat scd2=descriptors2.clone(); - - // row normalization // - for(int i=0; i(i,k)-scd2.at(j,k); - float suma=scd1.at(i,k)+scd2.at(j,k); - csum += resta*resta/(FLT_EPSILON+suma); - } - costMatrix.at(i,j)=csum/2; - } - else - { - costMatrix.at(i,j)=defaultCost; - } - } - } -} - -Ptr createChiHistogramCostExtractor(int nDummies, float defaultCost) -{ - return Ptr ( new ChiHistogramCostExtractorImpl(nDummies, defaultCost) ); -} - -/*! */ -class EMDL1HistogramCostExtractorImpl CV_FINAL : public EMDL1HistogramCostExtractor -{ -public: - /* Constructors */ - EMDL1HistogramCostExtractorImpl(int _nDummies, float _defaultCost) - { - name_ = "HistogramCostExtractor.CHI"; - nDummies=_nDummies; - defaultCost=_defaultCost; - } - - /* Destructor */ - ~EMDL1HistogramCostExtractorImpl() CV_OVERRIDE - { - } - - //! the main operator - virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; - - //! setters / getters - void setNDummies(int _nDummies) CV_OVERRIDE - { - nDummies=_nDummies; - } - - int getNDummies() const CV_OVERRIDE - { - return nDummies; - } - - void setDefaultCost(float _defaultCost) CV_OVERRIDE - { - defaultCost=_defaultCost; - } - - float getDefaultCost() const CV_OVERRIDE - { - return defaultCost; - } - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "dummies" << nDummies - << "default" << defaultCost; - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - nDummies = (int)fn["dummies"]; - defaultCost = (float)fn["default"]; - } - -protected: - String name_; - int nDummies; - float defaultCost; -}; - -void EMDL1HistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) -{ - CV_INSTRUMENT_REGION(); - - // size of the costMatrix with dummies // - Mat descriptors1=_descriptors1.getMat(); - Mat descriptors2=_descriptors2.getMat(); - int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; - _costMatrix.create(costrows, costrows, CV_32F); - Mat costMatrix=_costMatrix.getMat(); - - // Obtain copies of the descriptors // - cv::Mat scd1=descriptors1.clone(); - cv::Mat scd2=descriptors2.clone(); - - // row normalization // - for(int i=0; i(i,j) = cv::EMDL1(sig1, sig2); - } - else - { - costMatrix.at(i,j) = defaultCost; - } - } - } -} - -Ptr createEMDL1HistogramCostExtractor(int nDummies, float defaultCost) -{ - return Ptr ( new EMDL1HistogramCostExtractorImpl(nDummies, defaultCost) ); -} - -} // cv diff --git a/modules/shape/src/precomp.hpp b/modules/shape/src/precomp.hpp deleted file mode 100644 index a059b97b5a..0000000000 --- a/modules/shape/src/precomp.hpp +++ /dev/null @@ -1,59 +0,0 @@ -/*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_PRECOMP_H__ -#define __OPENCV_PRECOMP_H__ - -#include -#include -#include - -#include "opencv2/calib3d.hpp" -#include "opencv2/imgproc.hpp" -#include "opencv2/shape.hpp" - -#include "opencv2/core/utility.hpp" -#include "opencv2/core/private.hpp" - -#include "opencv2/opencv_modules.hpp" - -#endif diff --git a/modules/shape/src/sc_dis.cpp b/modules/shape/src/sc_dis.cpp deleted file mode 100644 index 23c77f0717..0000000000 --- a/modules/shape/src/sc_dis.cpp +++ /dev/null @@ -1,793 +0,0 @@ -/*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*/ - -/* - * Implementation of the paper Shape Matching and Object Recognition Using Shape Contexts - * Belongie et al., 2002 by Juan Manuel Perez for GSoC 2013. - */ - -#include "precomp.hpp" -#include "opencv2/core.hpp" -#include "scd_def.hpp" -#include - -namespace cv -{ -class ShapeContextDistanceExtractorImpl : public ShapeContextDistanceExtractor -{ -public: - /* Constructors */ - ShapeContextDistanceExtractorImpl(int _nAngularBins, int _nRadialBins, float _innerRadius, float _outerRadius, int _iterations, - const Ptr &_comparer, const Ptr &_transformer) - { - nAngularBins=_nAngularBins; - nRadialBins=_nRadialBins; - innerRadius=_innerRadius; - outerRadius=_outerRadius; - rotationInvariant=false; - comparer=_comparer; - iterations=_iterations; - transformer=_transformer; - bendingEnergyWeight=0.3f; - imageAppearanceWeight=0.0f; - shapeContextWeight=1.0f; - sigma=10.0f; - name_ = "ShapeDistanceExtractor.SCD"; - costFlag = 0; - } - - /* Destructor */ - ~ShapeContextDistanceExtractorImpl() CV_OVERRIDE - { - } - - //! the main operator - virtual float computeDistance(InputArray contour1, InputArray contour2) CV_OVERRIDE; - - //! Setters/Getters - virtual void setAngularBins(int _nAngularBins) CV_OVERRIDE { CV_Assert(_nAngularBins>0); nAngularBins=_nAngularBins; } - virtual int getAngularBins() const CV_OVERRIDE { return nAngularBins; } - - virtual void setRadialBins(int _nRadialBins) CV_OVERRIDE { CV_Assert(_nRadialBins>0); nRadialBins=_nRadialBins; } - virtual int getRadialBins() const CV_OVERRIDE { return nRadialBins; } - - virtual void setInnerRadius(float _innerRadius) CV_OVERRIDE { CV_Assert(_innerRadius>0); innerRadius=_innerRadius; } - virtual float getInnerRadius() const CV_OVERRIDE { return innerRadius; } - - virtual void setOuterRadius(float _outerRadius) CV_OVERRIDE { CV_Assert(_outerRadius>0); outerRadius=_outerRadius; } - virtual float getOuterRadius() const CV_OVERRIDE { return outerRadius; } - - virtual void setRotationInvariant(bool _rotationInvariant) CV_OVERRIDE { rotationInvariant=_rotationInvariant; } - virtual bool getRotationInvariant() const CV_OVERRIDE { return rotationInvariant; } - - virtual void setCostExtractor(Ptr _comparer) CV_OVERRIDE { comparer = _comparer; } - virtual Ptr getCostExtractor() const CV_OVERRIDE { return comparer; } - - virtual void setShapeContextWeight(float _shapeContextWeight) CV_OVERRIDE { shapeContextWeight=_shapeContextWeight; } - virtual float getShapeContextWeight() const CV_OVERRIDE { return shapeContextWeight; } - - virtual void setImageAppearanceWeight(float _imageAppearanceWeight) CV_OVERRIDE { imageAppearanceWeight=_imageAppearanceWeight; } - virtual float getImageAppearanceWeight() const CV_OVERRIDE { return imageAppearanceWeight; } - - virtual void setBendingEnergyWeight(float _bendingEnergyWeight) CV_OVERRIDE { bendingEnergyWeight=_bendingEnergyWeight; } - virtual float getBendingEnergyWeight() const CV_OVERRIDE { return bendingEnergyWeight; } - - virtual void setStdDev(float _sigma) CV_OVERRIDE { sigma=_sigma; } - virtual float getStdDev() const CV_OVERRIDE { return sigma; } - - virtual void setImages(InputArray _image1, InputArray _image2) CV_OVERRIDE - { - Mat image1_=_image1.getMat(), image2_=_image2.getMat(); - CV_Assert((image1_.depth()==0) && (image2_.depth()==0)); - image1=image1_; - image2=image2_; - } - - virtual void getImages(OutputArray _image1, OutputArray _image2) const CV_OVERRIDE - { - CV_Assert((!image1.empty()) && (!image2.empty())); - image1.copyTo(_image1); - image2.copyTo(_image2); - } - - virtual void setIterations(int _iterations) CV_OVERRIDE {CV_Assert(_iterations>0); iterations=_iterations;} - virtual int getIterations() const CV_OVERRIDE {return iterations;} - - virtual void setTransformAlgorithm(Ptr _transformer) CV_OVERRIDE {transformer=_transformer;} - virtual Ptr getTransformAlgorithm() const CV_OVERRIDE {return transformer;} - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "nRads" << nRadialBins - << "nAngs" << nAngularBins - << "iters" << iterations - << "img_1" << image1 - << "img_2" << image2 - << "beWei" << bendingEnergyWeight - << "scWei" << shapeContextWeight - << "iaWei" << imageAppearanceWeight - << "costF" << costFlag - << "rotIn" << rotationInvariant - << "sigma" << sigma; - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - nRadialBins = (int)fn["nRads"]; - nAngularBins = (int)fn["nAngs"]; - iterations = (int)fn["iters"]; - bendingEnergyWeight = (float)fn["beWei"]; - shapeContextWeight = (float)fn["scWei"]; - imageAppearanceWeight = (float)fn["iaWei"]; - costFlag = (int)fn["costF"]; - sigma = (float)fn["sigma"]; - } - -protected: - int nAngularBins; - int nRadialBins; - float innerRadius; - float outerRadius; - bool rotationInvariant; - int costFlag; - int iterations; - Ptr transformer; - Ptr comparer; - Mat image1; - Mat image2; - float bendingEnergyWeight; - float imageAppearanceWeight; - float shapeContextWeight; - float sigma; - String name_; -}; - -float ShapeContextDistanceExtractorImpl::computeDistance(InputArray contour1, InputArray contour2) -{ - CV_INSTRUMENT_REGION(); - - // Checking // - Mat sset1=contour1.getMat(), sset2=contour2.getMat(), set1, set2; - if (set1.type() != CV_32F) - sset1.convertTo(set1, CV_32F); - else - sset1.copyTo(set1); - - if (set2.type() != CV_32F) - sset2.convertTo(set2, CV_32F); - else - sset2.copyTo(set2); - - CV_Assert((set1.channels()==2) && (set1.cols>0)); - CV_Assert((set2.channels()==2) && (set2.cols>0)); - - // Force vectors column-based - if (set1.dims > 1) - set1 = set1.reshape(2, 1); - if (set2.dims > 1) - set2 = set2.reshape(2, 1); - - if (imageAppearanceWeight!=0) - { - CV_Assert((!image1.empty()) && (!image2.empty())); - } - - // Initializing Extractor, Descriptor structures and Matcher // - SCD set1SCE(nAngularBins, nRadialBins, innerRadius, outerRadius, rotationInvariant); - Mat set1SCD; - SCD set2SCE(nAngularBins, nRadialBins, innerRadius, outerRadius, rotationInvariant); - Mat set2SCD; - SCDMatcher matcher; - std::vector matches; - - // Distance components (The output is a linear combination of these 3) // - float sDistance=0, bEnergy=0, iAppearance=0; - float beta; - - // Initializing some variables // - std::vector inliers1, inliers2; - - Ptr transDown = transformer.dynamicCast(); - - Mat warpedImage; - int ii, jj, pt; - - for (ii=0; iisetRegularizationParameter(beta); - transformer->estimateTransformation(set1, set2, matches); - bEnergy += transformer->applyTransformation(set1, set1); - - // Image appearance // - if (imageAppearanceWeight!=0) - { - // Have to accumulate the transformation along all the iterations - if (ii==0) - { - if ( !transDown.empty() ) - { - image2.copyTo(warpedImage); - } - else - { - image1.copyTo(warpedImage); - } - } - transformer->warpImage(warpedImage, warpedImage); - } - } - - Mat gaussWindow, diffIm; - if (imageAppearanceWeight!=0) - { - // compute appearance cost - if ( !transDown.empty() ) - { - resize(warpedImage, warpedImage, image1.size(), 0, 0, INTER_LINEAR_EXACT); - Mat temp=(warpedImage-image1); - multiply(temp, temp, diffIm); - } - else - { - resize(warpedImage, warpedImage, image2.size(), 0, 0, INTER_LINEAR_EXACT); - Mat temp=(warpedImage-image2); - multiply(temp, temp, diffIm); - } - gaussWindow = Mat::zeros(warpedImage.rows, warpedImage.cols, CV_32F); - for (pt=0; pt(0,pt); - for (ii=0; ii(ii,jj) += val; - } - } - } - - Mat appIm(diffIm.rows, diffIm.cols, CV_32F); - for (ii=0; ii(ii,jj) )/255; - float elemb=gaussWindow.at(ii,jj); - appIm.at(ii,jj) = elema*elemb; - } - } - iAppearance = float(cv::sum(appIm)[0]/sset1.cols); - } - sDistance = matcher.getMatchingCost(); - - return (sDistance*shapeContextWeight+bEnergy*bendingEnergyWeight+iAppearance*imageAppearanceWeight); -} - -Ptr createShapeContextDistanceExtractor(int nAngularBins, int nRadialBins, float innerRadius, float outerRadius, int iterations, - const Ptr &comparer, const Ptr &transformer) -{ - return Ptr ( new ShapeContextDistanceExtractorImpl(nAngularBins, nRadialBins, innerRadius, - outerRadius, iterations, comparer, transformer) ); -} - -//! SCD -void SCD::extractSCD(cv::Mat &contour, cv::Mat &descriptors, const std::vector &queryInliers, const float _meanDistance) -{ - cv::Mat contourMat = contour; - cv::Mat disMatrix = cv::Mat::zeros(contourMat.cols, contourMat.cols, CV_32F); - cv::Mat angleMatrix = cv::Mat::zeros(contourMat.cols, contourMat.cols, CV_32F); - - std::vector logspaces, angspaces; - logarithmicSpaces(logspaces); - angularSpaces(angspaces); - buildNormalizedDistanceMatrix(contourMat, disMatrix, queryInliers, _meanDistance); - buildAngleMatrix(contourMat, angleMatrix); - - // Now, build the descriptor matrix (each row is a point) // - descriptors = cv::Mat::zeros(contourMat.cols, descriptorSize(), CV_32F); - - for (int ptidx=0; ptidx0) - { - if (queryInliers[ptidx]==0 || queryInliers[cmp]==0) continue; //avoid outliers - } - - int angidx=-1, radidx=-1; - for (int i=0; i(ptidx, cmp)(ptidx, cmp)(ptidx, idx)++; - } - } - } -} - -void SCD::logarithmicSpaces(std::vector &vecSpaces) const -{ - double logmin=log10(innerRadius); - double logmax=log10(outerRadius); - double delta=(logmax-logmin)/(nRadialBins-1); - double accdelta=0; - - for (int i=0; i &vecSpaces) const -{ - double delta=2*CV_PI/nAngularBins; - double val=0; - - for (int i=0; i &queryInliers, const float _meanDistance) -{ - cv::Mat contourMat = contour; - cv::Mat mask(disMatrix.rows, disMatrix.cols, CV_8U); - - for (int i=0; i(i,j) = (float)norm( cv::Mat(contourMat.at(0,i)-contourMat.at(0,j)), cv::NORM_L2 ); - if (_meanDistance<0) - { - if (queryInliers.size()>0) - { - mask.at(i,j)=char(queryInliers[j] && queryInliers[i]); - } - else - { - mask.at(i,j)=1; - } - } - } - } - - if (_meanDistance<0) - { - meanDistance=(float)mean(disMatrix, mask)[0]; - } - else - { - meanDistance=_meanDistance; - } - disMatrix/=meanDistance+FLT_EPSILON; -} - -void SCD::buildAngleMatrix(cv::Mat &contour, cv::Mat &angleMatrix) const -{ - cv::Mat contourMat = contour; - - // if descriptor is rotationInvariant compute massCenter // - cv::Point2f massCenter(0,0); - if (rotationInvariant) - { - for (int i=0; i(0,i); - } - massCenter.x=massCenter.x/(float)contourMat.cols; - massCenter.y=massCenter.y/(float)contourMat.cols; - } - - - for (int i=0; i(i,j)=0.0; - } - else - { - cv::Point2f dif = contourMat.at(0,i) - contourMat.at(0,j); - angleMatrix.at(i,j) = std::atan2(dif.y, dif.x); - - if (rotationInvariant) - { - cv::Point2f refPt = contourMat.at(0,i) - massCenter; - float refAngle = atan2(refPt.y, refPt.x); - angleMatrix.at(i,j) -= refAngle; - } - angleMatrix.at(i,j) = float(fmod(double(angleMatrix.at(i,j)+(double)FLT_EPSILON),2*CV_PI)+CV_PI); - } - } - } -} - -//! SCDMatcher -void SCDMatcher::matchDescriptors(cv::Mat &descriptors1, cv::Mat &descriptors2, std::vector &matches, - cv::Ptr &comparer, std::vector &inliers1, std::vector &inliers2) -{ - matches.clear(); - - // Build the cost Matrix between descriptors // - cv::Mat costMat; - buildCostMatrix(descriptors1, descriptors2, costMat, comparer); - - // Solve the matching problem using the hungarian method // - hungarian(costMat, matches, inliers1, inliers2, descriptors1.rows, descriptors2.rows); -} - -void SCDMatcher::buildCostMatrix(const cv::Mat &descriptors1, const cv::Mat &descriptors2, - cv::Mat &costMatrix, cv::Ptr &comparer) const -{ - CV_INSTRUMENT_REGION(); - - comparer->buildCostMatrix(descriptors1, descriptors2, costMatrix); -} - -void SCDMatcher::hungarian(cv::Mat &costMatrix, std::vector &outMatches, std::vector &inliers1, - std::vector &inliers2, int sizeScd1, int sizeScd2) -{ - std::vector free(costMatrix.rows, 0), collist(costMatrix.rows, 0); - std::vector matches(costMatrix.rows, 0), colsol(costMatrix.rows), rowsol(costMatrix.rows); - std::vector d(costMatrix.rows), pred(costMatrix.rows), v(costMatrix.rows); - - const float LOWV = 1e-10f; - bool unassignedfound; - int i=0, imin=0, numfree=0, prvnumfree=0, f=0, i0=0, k=0, freerow=0; - int j=0, j1=0, j2=0, endofpath=0, last=0, low=0, up=0; - float min=0, h=0, umin=0, usubmin=0, v2=0; - - // COLUMN REDUCTION // - for (j = costMatrix.rows-1; j >= 0; j--) - { - // find minimum cost over rows. - min = costMatrix.at(0,j); - imin = 0; - for (i = 1; i < costMatrix.rows; i++) - if (costMatrix.at(i,j) < min) - { - min = costMatrix.at(i,j); - imin = i; - } - v[j] = min; - - if (++matches[imin] == 1) - { - rowsol[imin] = j; - colsol[j] = imin; - } - else - { - colsol[j]=-1; - } - } - - // REDUCTION TRANSFER // - for (i=0; i::max(); - for (j=0; j(i,j)-v[j] < min) - { - min=costMatrix.at(i,j)-v[j]; - } - } - } - v[j1] = v[j1]-min; - } - } - } - // AUGMENTING ROW REDUCTION // - int loopcnt = 0; - do - { - loopcnt++; - k=0; - prvnumfree=numfree; - numfree=0; - while (k < prvnumfree) - { - i=free[k]; - k++; - umin = costMatrix.at(i,0)-v[0]; - j1=0; - usubmin = std::numeric_limits::max(); - for (j=1; j(i,j)-v[j]; - if (h < usubmin) - { - if (h >= umin) - { - usubmin = h; - j2 = j; - } - else - { - usubmin = umin; - umin = h; - j2 = j1; - j1 = j; - } - } - } - i0 = colsol[j1]; - - if (fabs(umin-usubmin) > LOWV) //if( umin < usubmin ) - { - v[j1] = v[j1] - (usubmin - umin); - } - else // minimum and subminimum equal. - { - if (i0 >= 0) // minimum column j1 is assigned. - { - j1 = j2; - i0 = colsol[j2]; - } - } - // (re-)assign i to j1, possibly de-assigning an i0. - rowsol[i]=j1; - colsol[j1]=i; - - if (i0 >= 0) - { - //if( umin < usubmin ) - if (fabs(umin-usubmin) > LOWV) - { - free[--k] = i0; - } - else - { - free[numfree++] = i0; - } - } - } - }while (loopcnt<2); // repeat once. - - // AUGMENT SOLUTION for each free row // - for (f = 0; f(freerow,j) - v[j]; - pred[j] = float(freerow); - collist[j] = j; // init column list. - } - - low=0; // columns in 0..low-1 are ready, now none. - up=0; // columns in low..up-1 are to be scanned for current minimum, now none. - unassignedfound = false; - do - { - if (up == low) - { - last=low-1; - min = d[collist[up++]]; - for (k = up; k < costMatrix.rows; k++) - { - j = collist[k]; - h = d[j]; - if (h <= min) - { - if (h < min) // new minimum. - { - up = low; // restart list at index low. - min = h; - } - collist[k] = collist[up]; - collist[up++] = j; - } - } - for (k=low; k(i,j1)-v[j1]-min; - - for (k = up; k < costMatrix.rows; k++) - { - j = collist[k]; - v2 = costMatrix.at(i,j) - v[j] - h; - if (v2 < d[j]) - { - pred[j] = float(i); - if (v2 == min) - { - if (colsol[j] < 0) - { - // if unassigned, shortest augmenting path is complete. - endofpath = j; - unassignedfound = true; - break; - } - else - { - collist[k] = collist[up]; - collist[up++] = j; - } - } - d[j] = v2; - } - } - } - }while (!unassignedfound); - - // update column prices. - for (k = 0; k <= last; k++) - { - j1 = collist[k]; - v[j1] = v[j1] + d[j1] - min; - } - - // reset row and column assignments along the alternating path. - do - { - i = int(pred[endofpath]); - colsol[endofpath] = i; - j1 = endofpath; - endofpath = rowsol[i]; - rowsol[i] = j1; - }while (i != freerow); - } - - // calculate symmetric shape context cost - cv::Mat trueCostMatrix(costMatrix, cv::Rect(0,0,sizeScd1, sizeScd2)); - CV_Assert(!trueCostMatrix.empty()); - float leftcost = 0; - for (int nrow=0; nrow(colsol[i],i));//queryIdx,trainIdx,distance - outMatches.push_back(singleMatch); - } - - // Update inliers - inliers1.reserve(sizeScd1); - for (size_t kc = 0; kc -#include -#include - -namespace cv -{ -/* - * ShapeContextDescriptor class - */ -class SCD -{ -public: - //! the full constructor taking all the necessary parameters - explicit SCD(int _nAngularBins=12, int _nRadialBins=5, - double _innerRadius=0.1, double _outerRadius=1, bool _rotationInvariant=false) - { - setAngularBins(_nAngularBins); - setRadialBins(_nRadialBins); - setInnerRadius(_innerRadius); - setOuterRadius(_outerRadius); - setRotationInvariant(_rotationInvariant); - meanDistance = 0; - } - - void extractSCD(cv::Mat& contour, cv::Mat& descriptors, - const std::vector& queryInliers=std::vector(), - const float _meanDistance=-1); - - int descriptorSize() {return nAngularBins*nRadialBins;} - void setAngularBins(int angularBins) { nAngularBins=angularBins; } - void setRadialBins(int radialBins) { nRadialBins=radialBins; } - void setInnerRadius(double _innerRadius) { innerRadius=_innerRadius; } - void setOuterRadius(double _outerRadius) { outerRadius=_outerRadius; } - void setRotationInvariant(bool _rotationInvariant) { rotationInvariant=_rotationInvariant; } - int getAngularBins() const { return nAngularBins; } - int getRadialBins() const { return nRadialBins; } - double getInnerRadius() const { return innerRadius; } - double getOuterRadius() const { return outerRadius; } - bool getRotationInvariant() const { return rotationInvariant; } - float getMeanDistance() const { return meanDistance; } - -private: - int nAngularBins; - int nRadialBins; - double innerRadius; - double outerRadius; - bool rotationInvariant; - float meanDistance; - -protected: - void logarithmicSpaces(std::vector& vecSpaces) const; - void angularSpaces(std::vector& vecSpaces) const; - - void buildNormalizedDistanceMatrix(cv::Mat& contour, - cv::Mat& disMatrix, const std::vector &queryInliers, - const float _meanDistance=-1); - - void buildAngleMatrix(cv::Mat& contour, - cv::Mat& angleMatrix) const; -}; - -/* - * Matcher - */ -class SCDMatcher -{ -public: - // the full constructor - SCDMatcher() : minMatchCost(0) - { - } - - // the matcher function using Hungarian method - void matchDescriptors(cv::Mat& descriptors1, cv::Mat& descriptors2, std::vector& matches, cv::Ptr& comparer, - std::vector& inliers1, std::vector &inliers2); - - // matching cost - float getMatchingCost() const {return minMatchCost;} - -private: - float minMatchCost; -protected: - void buildCostMatrix(const cv::Mat& descriptors1, const cv::Mat& descriptors2, - cv::Mat& costMatrix, cv::Ptr& comparer) const; - void hungarian(cv::Mat& costMatrix, std::vector& outMatches, std::vector &inliers1, - std::vector &inliers2, int sizeScd1=0, int sizeScd2=0); - -}; - -} diff --git a/modules/shape/src/tps_trans.cpp b/modules/shape/src/tps_trans.cpp deleted file mode 100644 index 5818c7973e..0000000000 --- a/modules/shape/src/tps_trans.cpp +++ /dev/null @@ -1,295 +0,0 @@ -/*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*/ - -#include "precomp.hpp" - -namespace cv -{ - -class ThinPlateSplineShapeTransformerImpl CV_FINAL : public ThinPlateSplineShapeTransformer -{ -public: - /* Constructors */ - ThinPlateSplineShapeTransformerImpl() - { - regularizationParameter=0; - name_ = "ShapeTransformer.TPS"; - tpsComputed=false; - transformCost = 0; - } - - ThinPlateSplineShapeTransformerImpl(double _regularizationParameter) - { - regularizationParameter=_regularizationParameter; - name_ = "ShapeTransformer.TPS"; - tpsComputed=false; - transformCost = 0; - } - - /* Destructor */ - ~ThinPlateSplineShapeTransformerImpl() CV_OVERRIDE - { - } - - //! the main operators - virtual void estimateTransformation(InputArray transformingShape, InputArray targetShape, std::vector &matches) CV_OVERRIDE; - virtual float applyTransformation(InputArray inPts, OutputArray output=noArray()) CV_OVERRIDE; - virtual void warpImage(InputArray transformingImage, OutputArray output, - int flags, int borderMode, const Scalar& borderValue) const CV_OVERRIDE; - - //! Setters/Getters - virtual void setRegularizationParameter(double _regularizationParameter) CV_OVERRIDE { regularizationParameter=_regularizationParameter; } - virtual double getRegularizationParameter() const CV_OVERRIDE { return regularizationParameter; } - - //! write/read - virtual void write(FileStorage& fs) const CV_OVERRIDE - { - writeFormat(fs); - fs << "name" << name_ - << "regularization" << regularizationParameter; - } - - virtual void read(const FileNode& fn) CV_OVERRIDE - { - CV_Assert( (String)fn["name"] == name_ ); - regularizationParameter = (int)fn["regularization"]; - } - -private: - bool tpsComputed; - double regularizationParameter; - float transformCost; - Mat tpsParameters; - Mat shapeReference; - -protected: - String name_; -}; - -static float distance(Point2f p, Point2f q) -{ - Point2f diff = p - q; - float norma = diff.x*diff.x + diff.y*diff.y;// - 2*diff.x*diff.y; - if (norma<0) norma=0; - //else norma = std::sqrt(norma); - norma = norma*std::log(norma+FLT_EPSILON); - return norma; -} - -static Point2f _applyTransformation(const Mat &shapeRef, const Point2f point, const Mat &tpsParameters) -{ - Point2f out; - for (int i=0; i<2; i++) - { - float a1=tpsParameters.at(tpsParameters.rows-3,i); - float ax=tpsParameters.at(tpsParameters.rows-2,i); - float ay=tpsParameters.at(tpsParameters.rows-1,i); - - float affine=a1+ax*point.x+ay*point.y; - float nonrigid=0; - for (int j=0; j(j,i)* - distance(Point2f(shapeRef.at(j,0),shapeRef.at(j,1)), - point); - } - if (i==0) - { - out.x=affine+nonrigid; - } - if (i==1) - { - out.y=affine+nonrigid; - } - } - return out; -} - -/* public methods */ -void ThinPlateSplineShapeTransformerImpl::warpImage(InputArray transformingImage, OutputArray output, - int flags, int borderMode, const Scalar& borderValue) const -{ - CV_INSTRUMENT_REGION(); - - CV_Assert(tpsComputed==true); - - Mat theinput = transformingImage.getMat(); - Mat mapX(theinput.rows, theinput.cols, CV_32FC1); - Mat mapY(theinput.rows, theinput.cols, CV_32FC1); - - for (int row = 0; row < theinput.rows; row++) - { - for (int col = 0; col < theinput.cols; col++) - { - Point2f pt = _applyTransformation(shapeReference, Point2f(float(col), float(row)), tpsParameters); - mapX.at(row, col) = pt.x; - mapY.at(row, col) = pt.y; - } - } - remap(transformingImage, output, mapX, mapY, flags, borderMode, borderValue); -} - -float ThinPlateSplineShapeTransformerImpl::applyTransformation(InputArray inPts, OutputArray outPts) -{ - CV_INSTRUMENT_REGION(); - - CV_Assert(tpsComputed); - Mat pts1 = inPts.getMat(); - CV_Assert((pts1.channels()==2) && (pts1.cols>0)); - - //Apply transformation in the complete set of points - // Ensambling output // - if (outPts.needed()) - { - outPts.create(1,pts1.cols, CV_32FC2); - Mat outMat = outPts.getMat(); - for (int i=0; i(0,i); - outMat.at(0,i)=_applyTransformation(shapeReference, pt, tpsParameters); - } - } - - return transformCost; -} - -void ThinPlateSplineShapeTransformerImpl::estimateTransformation(InputArray _pts1, InputArray _pts2, - std::vector& _matches ) -{ - CV_INSTRUMENT_REGION(); - - Mat pts1 = _pts1.getMat(); - Mat pts2 = _pts2.getMat(); - CV_Assert((pts1.channels()==2) && (pts1.cols>0) && (pts2.channels()==2) && (pts2.cols>0)); - CV_Assert(_matches.size()>1); - - if (pts1.type() != CV_32F) - pts1.convertTo(pts1, CV_32F); - if (pts2.type() != CV_32F) - pts2.convertTo(pts2, CV_32F); - - // Use only valid matchings // - std::vector matches; - for (size_t i=0; i<_matches.size(); i++) - { - if (_matches[i].queryIdx(0,matches[i].queryIdx); - shape1.at(i,0) = pt1.x; - shape1.at(i,1) = pt1.y; - - Point2f pt2=pts2.at(0,matches[i].trainIdx); - shape2.at(i,0) = pt2.x; - shape2.at(i,1) = pt2.y; - } - shape1.copyTo(shapeReference); - - // Building the matrices for solving the L*(w|a)=(v|0) problem with L={[K|P];[P'|0]} - - //Building K and P (Needed to build L) - Mat matK((int)matches.size(),(int)matches.size(),CV_32F); - Mat matP((int)matches.size(),3,CV_32F); - for (int i=0, end=(int)matches.size(); i(i,j)=float(regularizationParameter); - } - else - { - matK.at(i,j) = distance(Point2f(shape1.at(i,0),shape1.at(i,1)), - Point2f(shape1.at(j,0),shape1.at(j,1))); - } - } - matP.at(i,0) = 1; - matP.at(i,1) = shape1.at(i,0); - matP.at(i,2) = shape1.at(i,1); - } - - //Building L - Mat matL=Mat::zeros((int)matches.size()+3,(int)matches.size()+3,CV_32F); - Mat matLroi(matL, Rect(0,0,(int)matches.size(),(int)matches.size())); //roi for K - matK.copyTo(matLroi); - matLroi = Mat(matL,Rect((int)matches.size(),0,3,(int)matches.size())); //roi for P - matP.copyTo(matLroi); - Mat matPt; - transpose(matP,matPt); - matLroi = Mat(matL,Rect(0,(int)matches.size(),(int)matches.size(),3)); //roi for P' - matPt.copyTo(matLroi); - - //Building B (v|0) - Mat matB = Mat::zeros((int)matches.size()+3,2,CV_32F); - for (int i=0, end = (int)matches.size(); i(i,0) = shape2.at(i,0); //x's - matB.at(i,1) = shape2.at(i,1); //y's - } - - //Obtaining transformation params (w|a) - solve(matL, matB, tpsParameters, DECOMP_LU); - //tpsParameters = matL.inv()*matB; - - //Setting transform Cost and Shape reference - Mat w(tpsParameters, Rect(0,0,2,tpsParameters.rows-3)); - Mat Q=w.t()*matK*w; - transformCost=fabs(Q.at(0,0)*Q.at(1,1));//fabs(mean(Q.diag(0))[0]);//std::max(Q.at(0,0),Q.at(1,1)); - tpsComputed=true; -} - -Ptr createThinPlateSplineShapeTransformer(double regularizationParameter) -{ - return Ptr( new ThinPlateSplineShapeTransformerImpl(regularizationParameter) ); -} - -} // cv diff --git a/modules/shape/test/test_main.cpp b/modules/shape/test/test_main.cpp deleted file mode 100644 index 93e4d2860e..0000000000 --- a/modules/shape/test/test_main.cpp +++ /dev/null @@ -1,10 +0,0 @@ -// 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 "test_precomp.hpp" - -#if defined(HAVE_HPX) - #include -#endif - -CV_TEST_MAIN("cv") diff --git a/modules/shape/test/test_precomp.hpp b/modules/shape/test/test_precomp.hpp deleted file mode 100644 index 09d98c6e08..0000000000 --- a/modules/shape/test/test_precomp.hpp +++ /dev/null @@ -1,10 +0,0 @@ -// 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_TEST_PRECOMP_HPP__ -#define __OPENCV_TEST_PRECOMP_HPP__ - -#include "opencv2/ts.hpp" -#include "opencv2/shape.hpp" - -#endif diff --git a/modules/shape/test/test_shape.cpp b/modules/shape/test/test_shape.cpp deleted file mode 100644 index cf3d3f8f7b..0000000000 --- a/modules/shape/test/test_shape.cpp +++ /dev/null @@ -1,324 +0,0 @@ -/*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. -// -// -// Intel License Agreement -// For Open Source Computer Vision Library -// -// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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*/ - -#include "test_precomp.hpp" - -namespace opencv_test { namespace { - -template -class ShapeBaseTest : public cvtest::BaseTest -{ -public: - typedef Point_ PointType; - ShapeBaseTest(int _NSN, int _NP, float _CURRENT_MAX_ACCUR) - : NSN(_NSN), NP(_NP), CURRENT_MAX_ACCUR(_CURRENT_MAX_ACCUR) - { - // generate file list - vector shapeNames; - shapeNames.push_back("apple"); //ok - shapeNames.push_back("children"); // ok - shapeNames.push_back("device7"); // ok - shapeNames.push_back("Heart"); // ok - shapeNames.push_back("teddy"); // ok - for (vector::const_iterator i = shapeNames.begin(); i != shapeNames.end(); ++i) - { - for (int j = 0; j < NSN; ++j) - { - std::stringstream filename; - filename << cvtest::TS::ptr()->get_data_path() - << "shape/mpeg_test/" << *i << "-" << j + 1 << ".png"; - filenames.push_back(filename.str()); - } - } - // distance matrix - const int totalCount = (int)filenames.size(); - distanceMat = Mat::zeros(totalCount, totalCount, CV_32F); - } - -protected: - void run(int) - { - mpegTest(); - displayMPEGResults(); - } - - vector convertContourType(const Mat& currentQuery) const - { - if (currentQuery.empty()) { - return vector(); - } - vector > _contoursQuery; - findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE); - - vector contoursQuery; - for (size_t border=0; border<_contoursQuery.size(); border++) - { - for (size_t p=0; p<_contoursQuery[border].size(); p++) - { - contoursQuery.push_back(PointType((T)_contoursQuery[border][p].x, - (T)_contoursQuery[border][p].y)); - } - } - - // In case actual number of points is less than n - for (int add=(int)contoursQuery.size()-1; add cont; - for (int i=0; i contoursQuery1, contoursQuery2, contoursQuery3, contoursTesting; - // reading query and computing its properties - for (vector::const_iterator a = filenames.begin(); a != filenames.end(); ++a) - { - // read current image - int aIndex = (int)(a - filenames.begin()); - Mat currentQuery = imread(*a, IMREAD_GRAYSCALE); - Mat flippedHQuery, flippedVQuery; - flip(currentQuery, flippedHQuery, 0); - flip(currentQuery, flippedVQuery, 1); - // compute border of the query and its flipped versions - contoursQuery1=convertContourType(currentQuery); - contoursQuery2=convertContourType(flippedHQuery); - contoursQuery3=convertContourType(flippedVQuery); - // compare with all the rest of the images: testing - for (vector::const_iterator b = filenames.begin(); b != filenames.end(); ++b) - { - int bIndex = (int)(b - filenames.begin()); - float distance = 0; - // skip self-comparisson - if (a != b) - { - // read testing image - Mat currentTest = imread(*b, IMREAD_GRAYSCALE); - // compute border of the testing - contoursTesting=convertContourType(currentTest); - // compute shape distance - distance = cmp(contoursQuery1, contoursQuery2, - contoursQuery3, contoursTesting); - } - distanceMat.at(aIndex, bIndex) = distance; - } - } - } - - void displayMPEGResults() - { - const int FIRST_MANY=2*NSN; - - int corrects=0; - int divi=0; - for (int row=0; row(row,col) > distanceMat.at(row,i)) - { - nsmall++; - } - } - if (nsmall<=FIRST_MANY) - { - corrects++; - } - } - } - float porc = 100*float(corrects)/(NSN*distanceMat.rows); - std::cout << "Test result: " << porc << "%" << std::endl; - if (porc >= CURRENT_MAX_ACCUR) - ts->set_failed_test_info(cvtest::TS::OK); - else - ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); - } - -protected: - int NSN; - int NP; - float CURRENT_MAX_ACCUR; - vector filenames; - Mat distanceMat; - compute cmp; -}; - -//------------------------------------------------------------------------ -// Test Shape_SCD.regression -//------------------------------------------------------------------------ - -class computeShapeDistance_Chi -{ - Ptr mysc; -public: - computeShapeDistance_Chi() - { - const int angularBins=12; - const int radialBins=4; - const float minRad=0.2f; - const float maxRad=2; - mysc = createShapeContextDistanceExtractor(angularBins, radialBins, minRad, maxRad); - mysc->setIterations(1); - mysc->setCostExtractor(createChiHistogramCostExtractor(30,0.15f)); - mysc->setTransformAlgorithm( createThinPlateSplineShapeTransformer() ); - } - float operator()(vector & query1, vector & query2, - vector & query3, vector & testq) - { - return std::min(mysc->computeDistance(query1, testq), - std::min(mysc->computeDistance(query2, testq), - mysc->computeDistance(query3, testq))); - } -}; - -TEST(Shape_SCD, regression) -{ - const int NSN_val=5;//10;//20; //number of shapes per class - const int NP_val=120; //number of points simplifying the contour - const float CURRENT_MAX_ACCUR_val=95; //99% and 100% reached in several tests, 95 is fixed as minimum boundary - ShapeBaseTest test(NSN_val, NP_val, CURRENT_MAX_ACCUR_val); - test.safe_run(); -} - -//------------------------------------------------------------------------ -// Test ShapeEMD_SCD.regression -//------------------------------------------------------------------------ - -class computeShapeDistance_EMD -{ - Ptr mysc; -public: - computeShapeDistance_EMD() - { - const int angularBins=12; - const int radialBins=4; - const float minRad=0.2f; - const float maxRad=2; - mysc = createShapeContextDistanceExtractor(angularBins, radialBins, minRad, maxRad); - mysc->setIterations(1); - mysc->setCostExtractor( createEMDL1HistogramCostExtractor() ); - mysc->setTransformAlgorithm( createThinPlateSplineShapeTransformer() ); - } - float operator()(vector & query1, vector & query2, - vector & query3, vector & testq) - { - return std::min(mysc->computeDistance(query1, testq), - std::min(mysc->computeDistance(query2, testq), - mysc->computeDistance(query3, testq))); - } -}; - -TEST(ShapeEMD_SCD, regression) -{ - const int NSN_val=5;//10;//20; //number of shapes per class - const int NP_val=100; //number of points simplifying the contour - const float CURRENT_MAX_ACCUR_val=95; //98% and 99% reached in several tests, 95 is fixed as minimum boundary - ShapeBaseTest test(NSN_val, NP_val, CURRENT_MAX_ACCUR_val); - test.safe_run(); -} - -//------------------------------------------------------------------------ -// Test Hauss.regression -//------------------------------------------------------------------------ - -class computeShapeDistance_Haussdorf -{ - Ptr haus; -public: - computeShapeDistance_Haussdorf() - { - haus = createHausdorffDistanceExtractor(); - } - float operator()(vector &query1, vector &query2, - vector &query3, vector &testq) - { - return std::min(haus->computeDistance(query1,testq), - std::min(haus->computeDistance(query2,testq), - haus->computeDistance(query3,testq))); - } -}; - -TEST(Hauss, regression) -{ - const int NSN_val=5;//10;//20; //number of shapes per class - const int NP_val = 180; //number of points simplifying the contour - const float CURRENT_MAX_ACCUR_val=85; //90% and 91% reached in several tests, 85 is fixed as minimum boundary - ShapeBaseTest test(NSN_val, NP_val, CURRENT_MAX_ACCUR_val); - test.safe_run(); -} - -TEST(computeDistance, regression_4976) -{ - Mat a = imread(cvtest::findDataFile("shape/samples/1.png"), 0); - Mat b = imread(cvtest::findDataFile("shape/samples/2.png"), 0); - - vector > ca,cb; - findContours(a, ca, cv::RETR_CCOMP, cv::CHAIN_APPROX_TC89_KCOS); - findContours(b, cb, cv::RETR_CCOMP, cv::CHAIN_APPROX_TC89_KCOS); - - Ptr hd = createHausdorffDistanceExtractor(); - Ptr sd = createShapeContextDistanceExtractor(); - - double d1 = hd->computeDistance(ca[0],cb[0]); - double d2 = sd->computeDistance(ca[0],cb[0]); - - EXPECT_NEAR(d1, 26.4196891785, 1e-3) << "HausdorffDistanceExtractor"; - EXPECT_NEAR(d2, 0.25804194808, 1e-3) << "ShapeContextDistanceExtractor"; -} - -}} // namespace diff --git a/samples/cpp/CMakeLists.txt b/samples/cpp/CMakeLists.txt index c3786aaf74..131681e61c 100644 --- a/samples/cpp/CMakeLists.txt +++ b/samples/cpp/CMakeLists.txt @@ -15,7 +15,6 @@ set(OPENCV_CPP_SAMPLES_REQUIRED_DEPS opencv_calib3d opencv_stitching opencv_videostab - opencv_shape ${OPENCV_MODULES_PUBLIC} ${OpenCV_LIB_COMPONENTS}) ocv_check_dependencies(${OPENCV_CPP_SAMPLES_REQUIRED_DEPS}) diff --git a/samples/cpp/shape_example.cpp b/samples/cpp/shape_example.cpp deleted file mode 100644 index 6269a942ef..0000000000 --- a/samples/cpp/shape_example.cpp +++ /dev/null @@ -1,121 +0,0 @@ -/* - * shape_context.cpp -- Shape context demo for shape matching - */ - -#include "opencv2/shape.hpp" -#include "opencv2/imgcodecs.hpp" -#include "opencv2/highgui.hpp" -#include "opencv2/imgproc.hpp" -#include -#include -#include - -using namespace std; -using namespace cv; - -static void help() -{ - printf("\n" - "This program demonstrates a method for shape comparison based on Shape Context\n" - "You should run the program providing a number between 1 and 20 for selecting an image in the folder ../data/shape_sample.\n" - "Call\n" - "./shape_example [number between 1 and 20, 1 default]\n\n"); -} - -static vector simpleContour( const Mat& currentQuery, int n=300 ) -{ - vector > _contoursQuery; - vector contoursQuery; - findContours(currentQuery, _contoursQuery, RETR_LIST, CHAIN_APPROX_NONE); - for (size_t border=0; border<_contoursQuery.size(); border++) - { - for (size_t p=0; p<_contoursQuery[border].size(); p++) - { - contoursQuery.push_back( _contoursQuery[border][p] ); - } - } - - // In case actual number of points is less than n - int dummy=0; - for (int add=(int)contoursQuery.size()-1; add cont; - for (int i=0; i("@input"); - if (!parser.check()) - { - parser.printErrors(); - help(); - return 1; - } - if (indexQuery < 1 || indexQuery > 20) - { - help(); - return 1; - } - cv::Ptr mysc = cv::createShapeContextDistanceExtractor(); - - Size sz2Sh(300,300); - stringstream queryName; - queryName< contQuery = simpleContour(query); - int bestMatch = 0; - float bestDis=FLT_MAX; - for ( int ii=1; ii<=20; ii++ ) - { - if (ii==indexQuery) continue; - waitKey(30); - stringstream iiname; - iiname< contii = simpleContour(iiIm); - float dis = mysc->computeDistance( contQuery, contii ); - if ( dis