vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e
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/*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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namespace cv
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{
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namespace xfeatures2d
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{
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BOWTrainer::BOWTrainer() : size(0)
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{}
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BOWTrainer::~BOWTrainer()
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{}
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void BOWTrainer::add( const Mat& _descriptors )
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{
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CV_Assert( !_descriptors.empty() );
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if( !descriptors.empty() )
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{
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CV_Assert( descriptors[0].cols == _descriptors.cols );
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CV_Assert( descriptors[0].type() == _descriptors.type() );
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size += _descriptors.rows;
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}
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else
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{
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size = _descriptors.rows;
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}
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descriptors.push_back(_descriptors);
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}
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const std::vector<Mat>& BOWTrainer::getDescriptors() const
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{
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return descriptors;
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}
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int BOWTrainer::descriptorsCount() const
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{
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return descriptors.empty() ? 0 : size;
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}
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void BOWTrainer::clear()
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{
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descriptors.clear();
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}
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BOWKMeansTrainer::BOWKMeansTrainer( int _clusterCount, const TermCriteria& _termcrit,
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int _attempts, int _flags ) :
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clusterCount(_clusterCount), termcrit(_termcrit), attempts(_attempts), flags(_flags)
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{}
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Mat BOWKMeansTrainer::cluster() const
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{
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CV_INSTRUMENT_REGION();
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CV_Assert( !descriptors.empty() );
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Mat mergedDescriptors( descriptorsCount(), descriptors[0].cols, descriptors[0].type() );
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for( size_t i = 0, start = 0; i < descriptors.size(); i++ )
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{
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Mat submut = mergedDescriptors.rowRange((int)start, (int)(start + descriptors[i].rows));
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descriptors[i].copyTo(submut);
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start += descriptors[i].rows;
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}
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return cluster( mergedDescriptors );
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}
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BOWKMeansTrainer::~BOWKMeansTrainer()
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{}
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Mat BOWKMeansTrainer::cluster( const Mat& _descriptors ) const
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{
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CV_INSTRUMENT_REGION();
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Mat labels, vocabulary;
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kmeans( _descriptors, clusterCount, labels, termcrit, attempts, flags, vocabulary );
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return vocabulary;
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}
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BOWImgDescriptorExtractor::BOWImgDescriptorExtractor( const Ptr<DescriptorExtractor>& _dextractor,
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const Ptr<DescriptorMatcher>& _dmatcher ) :
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dextractor(_dextractor), dmatcher(_dmatcher)
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{}
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BOWImgDescriptorExtractor::BOWImgDescriptorExtractor( const Ptr<DescriptorMatcher>& _dmatcher ) :
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dmatcher(_dmatcher)
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{}
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BOWImgDescriptorExtractor::~BOWImgDescriptorExtractor()
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{}
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void BOWImgDescriptorExtractor::setVocabulary( const Mat& _vocabulary )
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{
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dmatcher->clear();
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vocabulary = _vocabulary;
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dmatcher->add( std::vector<Mat>(1, vocabulary) );
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}
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const Mat& BOWImgDescriptorExtractor::getVocabulary() const
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{
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return vocabulary;
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}
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void BOWImgDescriptorExtractor::compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray imgDescriptor,
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std::vector<std::vector<int> >* pointIdxsOfClusters, Mat* descriptors )
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{
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CV_INSTRUMENT_REGION();
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imgDescriptor.release();
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if( keypoints.empty() )
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return;
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// Compute descriptors for the image.
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Mat _descriptors;
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dextractor->compute( image, keypoints, _descriptors );
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compute( _descriptors, imgDescriptor, pointIdxsOfClusters );
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// Add the descriptors of image keypoints
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if (descriptors) {
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*descriptors = _descriptors.clone();
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}
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}
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int BOWImgDescriptorExtractor::descriptorSize() const
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{
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return vocabulary.empty() ? 0 : vocabulary.rows;
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}
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int BOWImgDescriptorExtractor::descriptorType() const
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{
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return CV_32FC1;
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}
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void BOWImgDescriptorExtractor::compute( InputArray keypointDescriptors, OutputArray _imgDescriptor, std::vector<std::vector<int> >* pointIdxsOfClusters )
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{
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CV_INSTRUMENT_REGION();
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CV_Assert( !vocabulary.empty() );
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CV_Assert(!keypointDescriptors.empty());
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int clusterCount = descriptorSize(); // = vocabulary.rows
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// Match keypoint descriptors to cluster center (to vocabulary)
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std::vector<DMatch> matches;
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dmatcher->match( keypointDescriptors, matches );
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// Compute image descriptor
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if( pointIdxsOfClusters )
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{
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pointIdxsOfClusters->clear();
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pointIdxsOfClusters->resize(clusterCount);
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}
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_imgDescriptor.create(1, clusterCount, descriptorType());
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_imgDescriptor.setTo(Scalar::all(0));
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Mat imgDescriptor = _imgDescriptor.getMat();
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float *dptr = imgDescriptor.ptr<float>();
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for( size_t i = 0; i < matches.size(); i++ )
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{
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int queryIdx = matches[i].queryIdx;
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int trainIdx = matches[i].trainIdx; // cluster index
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CV_Assert( queryIdx == (int)i );
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dptr[trainIdx] = dptr[trainIdx] + 1.f;
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if( pointIdxsOfClusters )
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(*pointIdxsOfClusters)[trainIdx].push_back( queryIdx );
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}
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// Normalize image descriptor.
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imgDescriptor /= keypointDescriptors.size().height;
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}
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}
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} // namespace cv
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