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227 lines
10 KiB
227 lines
10 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#ifndef OPENCV_SHAPE_SHAPE_DISTANCE_HPP |
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#define OPENCV_SHAPE_SHAPE_DISTANCE_HPP |
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#include "opencv2/core.hpp" |
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#include "opencv2/shape/hist_cost.hpp" |
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#include "opencv2/shape/shape_transformer.hpp" |
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namespace cv |
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{ |
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//! @addtogroup shape |
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//! @{ |
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/** @example modules/shape/samples/shape_example.cpp |
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An example using shape distance algorithm |
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*/ |
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/** @brief Abstract base class for shape distance algorithms. |
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*/ |
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class CV_EXPORTS_W ShapeDistanceExtractor : public Algorithm |
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{ |
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public: |
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/** @brief Compute the shape distance between two shapes defined by its contours. |
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@param contour1 Contour defining first shape. |
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@param contour2 Contour defining second shape. |
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*/ |
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CV_WRAP virtual float computeDistance(InputArray contour1, InputArray contour2) = 0; |
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}; |
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/***********************************************************************************/ |
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/***********************************************************************************/ |
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/***********************************************************************************/ |
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/** @brief Implementation of the Shape Context descriptor and matching algorithm |
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proposed by Belongie et al. in "Shape Matching and Object Recognition Using Shape Contexts" (PAMI |
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2002). This implementation is packaged in a generic scheme, in order to allow you the |
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implementation of the common variations of the original pipeline. |
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*/ |
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class CV_EXPORTS_W ShapeContextDistanceExtractor : public ShapeDistanceExtractor |
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{ |
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public: |
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/** @brief Establish the number of angular bins for the Shape Context Descriptor used in the shape matching |
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pipeline. |
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@param nAngularBins The number of angular bins in the shape context descriptor. |
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*/ |
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CV_WRAP virtual void setAngularBins(int nAngularBins) = 0; |
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CV_WRAP virtual int getAngularBins() const = 0; |
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/** @brief Establish the number of radial bins for the Shape Context Descriptor used in the shape matching |
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pipeline. |
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@param nRadialBins The number of radial bins in the shape context descriptor. |
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*/ |
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CV_WRAP virtual void setRadialBins(int nRadialBins) = 0; |
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CV_WRAP virtual int getRadialBins() const = 0; |
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/** @brief Set the inner radius of the shape context descriptor. |
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@param innerRadius The value of the inner radius. |
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*/ |
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CV_WRAP virtual void setInnerRadius(float innerRadius) = 0; |
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CV_WRAP virtual float getInnerRadius() const = 0; |
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/** @brief Set the outer radius of the shape context descriptor. |
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@param outerRadius The value of the outer radius. |
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*/ |
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CV_WRAP virtual void setOuterRadius(float outerRadius) = 0; |
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CV_WRAP virtual float getOuterRadius() const = 0; |
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CV_WRAP virtual void setRotationInvariant(bool rotationInvariant) = 0; |
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CV_WRAP virtual bool getRotationInvariant() const = 0; |
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/** @brief Set the weight of the shape context distance in the final value of the shape distance. The shape |
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context distance between two shapes is defined as the symmetric sum of shape context matching costs |
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over best matching points. The final value of the shape distance is a user-defined linear |
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combination of the shape context distance, an image appearance distance, and a bending energy. |
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@param shapeContextWeight The weight of the shape context distance in the final distance value. |
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*/ |
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CV_WRAP virtual void setShapeContextWeight(float shapeContextWeight) = 0; |
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CV_WRAP virtual float getShapeContextWeight() const = 0; |
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/** @brief Set the weight of the Image Appearance cost in the final value of the shape distance. The image |
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appearance cost is defined as the sum of squared brightness differences in Gaussian windows around |
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corresponding image points. The final value of the shape distance is a user-defined linear |
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combination of the shape context distance, an image appearance distance, and a bending energy. If |
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this value is set to a number different from 0, is mandatory to set the images that correspond to |
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each shape. |
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@param imageAppearanceWeight The weight of the appearance cost in the final distance value. |
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*/ |
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CV_WRAP virtual void setImageAppearanceWeight(float imageAppearanceWeight) = 0; |
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CV_WRAP virtual float getImageAppearanceWeight() const = 0; |
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/** @brief Set the weight of the Bending Energy in the final value of the shape distance. The bending energy |
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definition depends on what transformation is being used to align the shapes. The final value of the |
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shape distance is a user-defined linear combination of the shape context distance, an image |
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appearance distance, and a bending energy. |
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@param bendingEnergyWeight The weight of the Bending Energy in the final distance value. |
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*/ |
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CV_WRAP virtual void setBendingEnergyWeight(float bendingEnergyWeight) = 0; |
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CV_WRAP virtual float getBendingEnergyWeight() const = 0; |
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/** @brief Set the images that correspond to each shape. This images are used in the calculation of the Image |
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Appearance cost. |
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@param image1 Image corresponding to the shape defined by contours1. |
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@param image2 Image corresponding to the shape defined by contours2. |
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*/ |
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CV_WRAP virtual void setImages(InputArray image1, InputArray image2) = 0; |
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CV_WRAP virtual void getImages(OutputArray image1, OutputArray image2) const = 0; |
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CV_WRAP virtual void setIterations(int iterations) = 0; |
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CV_WRAP virtual int getIterations() const = 0; |
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/** @brief Set the algorithm used for building the shape context descriptor cost matrix. |
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@param comparer Smart pointer to a HistogramCostExtractor, an algorithm that defines the cost |
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matrix between descriptors. |
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*/ |
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CV_WRAP virtual void setCostExtractor(Ptr<HistogramCostExtractor> comparer) = 0; |
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CV_WRAP virtual Ptr<HistogramCostExtractor> getCostExtractor() const = 0; |
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/** @brief Set the value of the standard deviation for the Gaussian window for the image appearance cost. |
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@param sigma Standard Deviation. |
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*/ |
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CV_WRAP virtual void setStdDev(float sigma) = 0; |
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CV_WRAP virtual float getStdDev() const = 0; |
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/** @brief Set the algorithm used for aligning the shapes. |
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@param transformer Smart pointer to a ShapeTransformer, an algorithm that defines the aligning |
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transformation. |
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*/ |
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CV_WRAP virtual void setTransformAlgorithm(Ptr<ShapeTransformer> transformer) = 0; |
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CV_WRAP virtual Ptr<ShapeTransformer> getTransformAlgorithm() const = 0; |
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}; |
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/* Complete constructor */ |
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CV_EXPORTS_W Ptr<ShapeContextDistanceExtractor> |
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createShapeContextDistanceExtractor(int nAngularBins=12, int nRadialBins=4, |
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float innerRadius=0.2f, float outerRadius=2, int iterations=3, |
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const Ptr<HistogramCostExtractor> &comparer = createChiHistogramCostExtractor(), |
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const Ptr<ShapeTransformer> &transformer = createThinPlateSplineShapeTransformer()); |
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/***********************************************************************************/ |
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/***********************************************************************************/ |
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/***********************************************************************************/ |
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/** @brief A simple Hausdorff distance measure between shapes defined by contours |
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according to the paper "Comparing Images using the Hausdorff distance." by D.P. Huttenlocher, G.A. |
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Klanderman, and W.J. Rucklidge. (PAMI 1993). : |
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*/ |
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class CV_EXPORTS_W HausdorffDistanceExtractor : public ShapeDistanceExtractor |
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{ |
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public: |
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/** @brief Set the norm used to compute the Hausdorff value between two shapes. It can be L1 or L2 norm. |
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@param distanceFlag Flag indicating which norm is used to compute the Hausdorff distance |
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(NORM_L1, NORM_L2). |
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*/ |
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CV_WRAP virtual void setDistanceFlag(int distanceFlag) = 0; |
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CV_WRAP virtual int getDistanceFlag() const = 0; |
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/** @brief This method sets the rank proportion (or fractional value) that establish the Kth ranked value of |
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the partial Hausdorff distance. Experimentally had been shown that 0.6 is a good value to compare |
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shapes. |
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@param rankProportion fractional value (between 0 and 1). |
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*/ |
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CV_WRAP virtual void setRankProportion(float rankProportion) = 0; |
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CV_WRAP virtual float getRankProportion() const = 0; |
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}; |
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/* Constructor */ |
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CV_EXPORTS_W Ptr<HausdorffDistanceExtractor> createHausdorffDistanceExtractor(int distanceFlag=cv::NORM_L2, float rankProp=0.6f); |
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//! @} |
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} // cv |
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#endif
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