457 lines
18 KiB
C++
457 lines
18 KiB
C++
/*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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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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#include "precomp.hpp"
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using namespace std;
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namespace cv
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{
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/****************************************************************************************\
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* DescriptorExtractor *
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\****************************************************************************************/
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/*
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* DescriptorExtractor
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*/
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DescriptorExtractor::~DescriptorExtractor()
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{}
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void DescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const
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{
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if( image.empty() || keypoints.empty() )
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{
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descriptors.release();
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return;
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}
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KeyPointsFilter::runByImageBorder( keypoints, image.size(), 0 );
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KeyPointsFilter::runByKeypointSize( keypoints, std::numeric_limits<float>::epsilon() );
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computeImpl( image, keypoints, descriptors );
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}
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void DescriptorExtractor::compute( const vector<Mat>& imageCollection, vector<vector<KeyPoint> >& pointCollection, vector<Mat>& descCollection ) const
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{
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CV_Assert( imageCollection.size() == pointCollection.size() );
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descCollection.resize( imageCollection.size() );
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for( size_t i = 0; i < imageCollection.size(); i++ )
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compute( imageCollection[i], pointCollection[i], descCollection[i] );
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}
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void DescriptorExtractor::read( const FileNode& )
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{}
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void DescriptorExtractor::write( FileStorage& ) const
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{}
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bool DescriptorExtractor::empty() const
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{
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return false;
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}
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void DescriptorExtractor::removeBorderKeypoints( vector<KeyPoint>& keypoints,
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Size imageSize, int borderSize )
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{
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KeyPointsFilter::runByImageBorder( keypoints, imageSize, borderSize );
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}
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Ptr<DescriptorExtractor> DescriptorExtractor::create(const string& descriptorExtractorType)
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{
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DescriptorExtractor* de = 0;
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size_t pos = 0;
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if (!descriptorExtractorType.compare("SIFT"))
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{
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de = new SiftDescriptorExtractor();
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}
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else if (!descriptorExtractorType.compare("SURF"))
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{
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de = new SurfDescriptorExtractor();
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}
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else if (!descriptorExtractorType.compare("ORB"))
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{
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de = new OrbDescriptorExtractor();
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}
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else if (!descriptorExtractorType.compare("BRIEF"))
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{
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de = new BriefDescriptorExtractor();
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}
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else if ( (pos=descriptorExtractorType.find("Opponent")) == 0)
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{
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pos += string("Opponent").size();
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de = new OpponentColorDescriptorExtractor( DescriptorExtractor::create(descriptorExtractorType.substr(pos)) );
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}
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return de;
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}
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/****************************************************************************************\
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* SiftDescriptorExtractor *
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\****************************************************************************************/
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SiftDescriptorExtractor::SiftDescriptorExtractor(const SIFT::DescriptorParams& descriptorParams,
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const SIFT::CommonParams& commonParams)
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: sift( descriptorParams.magnification, descriptorParams.isNormalize, descriptorParams.recalculateAngles,
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commonParams.nOctaves, commonParams.nOctaveLayers, commonParams.firstOctave, commonParams.angleMode )
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{}
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SiftDescriptorExtractor::SiftDescriptorExtractor( double magnification, bool isNormalize, bool recalculateAngles,
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int nOctaves, int nOctaveLayers, int firstOctave, int angleMode )
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: sift( magnification, isNormalize, recalculateAngles, nOctaves, nOctaveLayers, firstOctave, angleMode )
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{}
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void SiftDescriptorExtractor::computeImpl( const Mat& image,
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vector<KeyPoint>& keypoints,
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Mat& descriptors) const
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{
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bool useProvidedKeypoints = true;
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Mat grayImage = image;
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if( image.type() != CV_8U ) cvtColor( image, grayImage, CV_BGR2GRAY );
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sift(grayImage, Mat(), keypoints, descriptors, useProvidedKeypoints);
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}
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void SiftDescriptorExtractor::read (const FileNode &fn)
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{
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double magnification = fn["magnification"];
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bool isNormalize = (int)fn["isNormalize"] != 0;
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bool recalculateAngles = (int)fn["recalculateAngles"] != 0;
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int nOctaves = fn["nOctaves"];
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int nOctaveLayers = fn["nOctaveLayers"];
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int firstOctave = fn["firstOctave"];
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int angleMode = fn["angleMode"];
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sift = SIFT( magnification, isNormalize, recalculateAngles, nOctaves, nOctaveLayers, firstOctave, angleMode );
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}
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void SiftDescriptorExtractor::write (FileStorage &fs) const
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{
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// fs << "algorithm" << getAlgorithmName ();
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SIFT::CommonParams commParams = sift.getCommonParams ();
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SIFT::DescriptorParams descriptorParams = sift.getDescriptorParams ();
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fs << "magnification" << descriptorParams.magnification;
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fs << "isNormalize" << descriptorParams.isNormalize;
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fs << "recalculateAngles" << descriptorParams.recalculateAngles;
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fs << "nOctaves" << commParams.nOctaves;
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fs << "nOctaveLayers" << commParams.nOctaveLayers;
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fs << "firstOctave" << commParams.firstOctave;
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fs << "angleMode" << commParams.angleMode;
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}
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int SiftDescriptorExtractor::descriptorSize() const
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{
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return sift.descriptorSize();
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}
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int SiftDescriptorExtractor::descriptorType() const
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{
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return CV_32FC1;
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}
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/****************************************************************************************\
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* SurfDescriptorExtractor *
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\****************************************************************************************/
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SurfDescriptorExtractor::SurfDescriptorExtractor( int nOctaves,
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int nOctaveLayers, bool extended, bool upright )
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: surf( 0.0, nOctaves, nOctaveLayers, extended, upright )
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{}
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void SurfDescriptorExtractor::computeImpl( const Mat& image,
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vector<KeyPoint>& keypoints,
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Mat& descriptors) const
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{
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// Compute descriptors for given keypoints
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vector<float> _descriptors;
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Mat mask;
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bool useProvidedKeypoints = true;
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Mat grayImage = image;
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if( image.type() != CV_8U ) cvtColor( image, grayImage, CV_BGR2GRAY );
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surf(grayImage, mask, keypoints, _descriptors, useProvidedKeypoints);
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descriptors.create((int)keypoints.size(), (int)surf.descriptorSize(), CV_32FC1);
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assert( (int)_descriptors.size() == descriptors.rows * descriptors.cols );
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std::copy(_descriptors.begin(), _descriptors.end(), descriptors.begin<float>());
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}
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void SurfDescriptorExtractor::read( const FileNode &fn )
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{
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int nOctaves = fn["nOctaves"];
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int nOctaveLayers = fn["nOctaveLayers"];
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bool extended = (int)fn["extended"] != 0;
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bool upright = (int)fn["upright"] != 0;
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surf = SURF( 0.0, nOctaves, nOctaveLayers, extended, upright );
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}
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void SurfDescriptorExtractor::write( FileStorage &fs ) const
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{
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// fs << "algorithm" << getAlgorithmName ();
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fs << "nOctaves" << surf.nOctaves;
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fs << "nOctaveLayers" << surf.nOctaveLayers;
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fs << "extended" << surf.extended;
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fs << "upright" << surf.upright;
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}
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int SurfDescriptorExtractor::descriptorSize() const
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{
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return surf.descriptorSize();
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}
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int SurfDescriptorExtractor::descriptorType() const
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{
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return CV_32FC1;
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/** Default constructor */
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OrbDescriptorExtractor::OrbDescriptorExtractor(ORB::CommonParams params) :
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params_(params)
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{
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orb_ = ORB(0, params);
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}
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void OrbDescriptorExtractor::computeImpl(const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints,
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cv::Mat& descriptors) const
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{
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cv::Mat empty_mask;
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orb_(image, empty_mask, keypoints, descriptors, true);
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}
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void OrbDescriptorExtractor::read(const cv::FileNode& fn)
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{
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params_.read(fn);
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}
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void OrbDescriptorExtractor::write(cv::FileStorage& fs) const
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{
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params_.write(fs);
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}
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int OrbDescriptorExtractor::descriptorSize() const
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{
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return ORB::kBytes;
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}
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int OrbDescriptorExtractor::descriptorType() const
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{
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return CV_8UC1;
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/****************************************************************************************\
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* OpponentColorDescriptorExtractor *
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\****************************************************************************************/
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OpponentColorDescriptorExtractor::OpponentColorDescriptorExtractor( const Ptr<DescriptorExtractor>& _descriptorExtractor ) :
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descriptorExtractor(_descriptorExtractor)
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{
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CV_Assert( !descriptorExtractor.empty() );
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}
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void convertBGRImageToOpponentColorSpace( const Mat& bgrImage, vector<Mat>& opponentChannels )
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{
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if( bgrImage.type() != CV_8UC3 )
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CV_Error( CV_StsBadArg, "input image must be an BGR image of type CV_8UC3" );
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// Split image into RGB to allow conversion to Opponent Color Space.
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vector<Mat> bgrChannels(3);
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split( bgrImage, bgrChannels );
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// Prepare opponent color space storage matrices.
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opponentChannels.resize( 3 );
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opponentChannels[0] = cv::Mat(bgrImage.size(), CV_8UC1); // R-G RED-GREEN
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opponentChannels[1] = cv::Mat(bgrImage.size(), CV_8UC1); // R+G-2B YELLOW-BLUE
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opponentChannels[2] = cv::Mat(bgrImage.size(), CV_8UC1); // R+G+B
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// Calculate the channels of the opponent color space
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{
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// (R - G) / sqrt(2)
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MatConstIterator_<signed char> rIt = bgrChannels[2].begin<signed char>();
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MatConstIterator_<signed char> gIt = bgrChannels[1].begin<signed char>();
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MatIterator_<unsigned char> dstIt = opponentChannels[0].begin<unsigned char>();
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float factor = 1.f / sqrt(2.f);
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for( ; dstIt != opponentChannels[0].end<unsigned char>(); ++rIt, ++gIt, ++dstIt )
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{
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int value = static_cast<int>( static_cast<float>(static_cast<int>(*gIt)-static_cast<int>(*rIt)) * factor );
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if( value < 0 ) value = 0;
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if( value > 255 ) value = 255;
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(*dstIt) = static_cast<unsigned char>(value);
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}
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}
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{
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// (R + G - 2B)/sqrt(6)
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MatConstIterator_<signed char> rIt = bgrChannels[2].begin<signed char>();
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MatConstIterator_<signed char> gIt = bgrChannels[1].begin<signed char>();
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MatConstIterator_<signed char> bIt = bgrChannels[0].begin<signed char>();
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MatIterator_<unsigned char> dstIt = opponentChannels[1].begin<unsigned char>();
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float factor = 1.f / sqrt(6.f);
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for( ; dstIt != opponentChannels[1].end<unsigned char>(); ++rIt, ++gIt, ++bIt, ++dstIt )
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{
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int value = static_cast<int>( static_cast<float>(static_cast<int>(*rIt) + static_cast<int>(*gIt) - 2*static_cast<int>(*bIt)) *
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factor );
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if( value < 0 ) value = 0;
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if( value > 255 ) value = 255;
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(*dstIt) = static_cast<unsigned char>(value);
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}
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}
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{
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// (R + G + B)/sqrt(3)
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MatConstIterator_<signed char> rIt = bgrChannels[2].begin<signed char>();
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MatConstIterator_<signed char> gIt = bgrChannels[1].begin<signed char>();
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MatConstIterator_<signed char> bIt = bgrChannels[0].begin<signed char>();
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MatIterator_<unsigned char> dstIt = opponentChannels[2].begin<unsigned char>();
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float factor = 1.f / sqrt(3.f);
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for( ; dstIt != opponentChannels[2].end<unsigned char>(); ++rIt, ++gIt, ++bIt, ++dstIt )
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{
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int value = static_cast<int>( static_cast<float>(static_cast<int>(*rIt) + static_cast<int>(*gIt) + static_cast<int>(*bIt)) *
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factor );
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if( value < 0 ) value = 0;
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if( value > 255 ) value = 255;
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(*dstIt) = static_cast<unsigned char>(value);
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}
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}
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}
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struct KP_LessThan
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{
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KP_LessThan(const vector<KeyPoint>& _kp) : kp(&_kp) {}
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bool operator()(int i, int j) const
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{
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return (*kp)[i].class_id < (*kp)[j].class_id;
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}
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const vector<KeyPoint>* kp;
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};
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void OpponentColorDescriptorExtractor::computeImpl( const Mat& bgrImage, vector<KeyPoint>& keypoints, Mat& descriptors ) const
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{
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vector<Mat> opponentChannels;
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convertBGRImageToOpponentColorSpace( bgrImage, opponentChannels );
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const int N = 3; // channels count
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vector<KeyPoint> channelKeypoints[N];
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Mat channelDescriptors[N];
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vector<int> idxs[N];
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// Compute descriptors three times, once for each Opponent channel to concatenate into a single color descriptor
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for( int ci = 0; ci < N; ci++ )
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{
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channelKeypoints[ci].insert( channelKeypoints[ci].begin(), keypoints.begin(), keypoints.end() );
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// Use class_id member to get indices into initial keypoints vector
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for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ )
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channelKeypoints[ci][ki].class_id = ki;
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descriptorExtractor->compute( opponentChannels[ci], channelKeypoints[ci], channelDescriptors[ci] );
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idxs[ci].resize( channelKeypoints[ci].size() );
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for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ )
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{
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idxs[ci][ki] = ki;
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}
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std::sort( idxs[ci].begin(), idxs[ci].end(), KP_LessThan(channelKeypoints[ci]) );
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}
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vector<KeyPoint> outKeypoints;
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outKeypoints.reserve( keypoints.size() );
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int descriptorSize = descriptorExtractor->descriptorSize();
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Mat mergedDescriptors( (int)keypoints.size(), 3*descriptorSize, descriptorExtractor->descriptorType() );
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int mergedCount = 0;
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// cp - current channel position
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size_t cp[] = {0, 0, 0};
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while( cp[0] < channelKeypoints[0].size() &&
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cp[1] < channelKeypoints[1].size() &&
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cp[2] < channelKeypoints[2].size() )
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{
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const int maxInitIdx = std::max( channelKeypoints[0][idxs[0][cp[0]]].class_id,
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std::max( channelKeypoints[1][idxs[1][cp[1]]].class_id,
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channelKeypoints[2][idxs[2][cp[2]]].class_id ) );
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while( channelKeypoints[0][idxs[0][cp[0]]].class_id < maxInitIdx && cp[0] < channelKeypoints[0].size() ) { cp[0]++; }
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while( channelKeypoints[1][idxs[1][cp[1]]].class_id < maxInitIdx && cp[1] < channelKeypoints[1].size() ) { cp[1]++; }
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while( channelKeypoints[2][idxs[2][cp[2]]].class_id < maxInitIdx && cp[2] < channelKeypoints[2].size() ) { cp[2]++; }
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if( cp[0] >= channelKeypoints[0].size() || cp[1] >= channelKeypoints[1].size() || cp[2] >= channelKeypoints[2].size() )
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break;
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if( channelKeypoints[0][idxs[0][cp[0]]].class_id == maxInitIdx &&
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channelKeypoints[1][idxs[1][cp[1]]].class_id == maxInitIdx &&
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channelKeypoints[2][idxs[2][cp[2]]].class_id == maxInitIdx )
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{
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outKeypoints.push_back( keypoints[maxInitIdx] );
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// merge descriptors
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for( int ci = 0; ci < N; ci++ )
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{
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Mat dst = mergedDescriptors(Range(mergedCount, mergedCount+1), Range(ci*descriptorSize, (ci+1)*descriptorSize));
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channelDescriptors[ci].row( idxs[ci][cp[ci]] ).copyTo( dst );
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cp[ci]++;
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}
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mergedCount++;
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}
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}
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mergedDescriptors.rowRange(0, mergedCount).copyTo( descriptors );
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std::swap( outKeypoints, keypoints );
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}
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void OpponentColorDescriptorExtractor::read( const FileNode& fn )
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{
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descriptorExtractor->read(fn);
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}
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void OpponentColorDescriptorExtractor::write( FileStorage& fs ) const
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{
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descriptorExtractor->write(fs);
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}
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int OpponentColorDescriptorExtractor::descriptorSize() const
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{
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return 3*descriptorExtractor->descriptorSize();
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}
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int OpponentColorDescriptorExtractor::descriptorType() const
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{
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return descriptorExtractor->descriptorType();
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}
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bool OpponentColorDescriptorExtractor::empty() const
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{
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return descriptorExtractor.empty() || (DescriptorExtractor*)(descriptorExtractor)->empty();
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}
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}
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