Adding class for BOW image matcher (Feature #3005).
Same prototype as BOWImgDescriptorExtractor, but do only the matching. If the feature is accepted, the BOWImgDescriptorExtractor and BOWImgDescriptorMatcher should probably refactor with inheritance. Add a class to compute the keypoints, descriptors and matching from an image should be added to.
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@ -1519,6 +1519,41 @@ protected:
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Ptr<DescriptorMatcher> dmatcher;
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};
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/*
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* Class to match image descriptors using bag of visual words.
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*/
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class CV_EXPORTS BOWImgDescriptorMatcher
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{
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public:
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BOWImgDescriptorMatcher( const Ptr<DescriptorMatcher>& _dmatcher );
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virtual ~BOWImgDescriptorMatcher();
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/*
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* Compute the matching of the current descriptor according to the vocabulary.
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*
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* vocDescriptor the descriptors to match
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* pointIdxsOfClusters vector of matching
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*/
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void compute( const Mat & descriptors, Mat& vocDescriptor, std::vector< std::vector< int > > * pointIdxsOfClusters = 0 );
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/*
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* Set the vocabulary
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*/
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void setVocabulary( const Mat& vocabulary );
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const Mat& getVocabulary() const;
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int descriptorSize() const;
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int descriptorType() const;
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protected:
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Mat vocabulary;
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Ptr<DescriptorMatcher> dmatcher;
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private:
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int _type;
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};
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} /* namespace cv */
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#endif
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@ -193,4 +193,76 @@ int BOWImgDescriptorExtractor::descriptorType() const
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return CV_32FC1;
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}
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BOWImgDescriptorMatcher::BOWImgDescriptorMatcher( const Ptr<DescriptorMatcher>& _dmatcher ) :
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dmatcher(_dmatcher),
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_type( -1 )
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{}
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BOWImgDescriptorMatcher::~BOWImgDescriptorMatcher()
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{}
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void BOWImgDescriptorMatcher::setVocabulary( const Mat& _vocabulary )
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{
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dmatcher->clear();
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CV_Assert( _vocabulary.type() == CV_32F );
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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& BOWImgDescriptorMatcher::getVocabulary() const
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{
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return vocabulary;
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}
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void BOWImgDescriptorMatcher::compute( const Mat & descriptors, Mat& vocDescriptor, std::vector<std::vector<int> > * pointIdxsOfClusters )
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{
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vocDescriptor.release();
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int clusterCount = descriptorSize(); // = vocabulary.rows
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_type = descriptors.type();
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Mat _descriptors;
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if( _type != CV_32F )
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descriptors.convertTo( _descriptors, CV_32F );
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else
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descriptors.copyTo( _descriptors );
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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( _descriptors, 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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vocDescriptor = Mat::zeros( 1, clusterCount, descriptorType() );
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float *dptr = (float*)vocDescriptor.data;
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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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vocDescriptor /= descriptors.rows;
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}
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int BOWImgDescriptorMatcher::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 BOWImgDescriptorMatcher::descriptorType() const
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{
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return _type;
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}
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}
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