opencv/modules/features2d/src/bagofwords.cpp
Roman Donchenko 2c4bbb313c Merge commit '43aec5ad' into merge-2.4
Conflicts:
	cmake/OpenCVConfig.cmake
	cmake/OpenCVLegacyOptions.cmake
	modules/contrib/src/retina.cpp
	modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst
	modules/gpu/doc/video.rst
	modules/gpu/src/speckle_filtering.cpp
	modules/python/src2/cv2.cv.hpp
	modules/python/test/test2.py
	samples/python/watershed.py
2013-08-27 13:26:44 +04:00

197 lines
6.0 KiB
C++

/*M///////////////////////////////////////////////////////////////////////////////////////
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// For Open Source Computer Vision Library
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#include "precomp.hpp"
namespace cv
{
BOWTrainer::BOWTrainer()
{}
BOWTrainer::~BOWTrainer()
{}
void BOWTrainer::add( const Mat& _descriptors )
{
CV_Assert( !_descriptors.empty() );
if( !descriptors.empty() )
{
CV_Assert( descriptors[0].cols == _descriptors.cols );
CV_Assert( descriptors[0].type() == _descriptors.type() );
size += _descriptors.rows;
}
else
{
size = _descriptors.rows;
}
descriptors.push_back(_descriptors);
}
const std::vector<Mat>& BOWTrainer::getDescriptors() const
{
return descriptors;
}
int BOWTrainer::descripotorsCount() const
{
return descriptors.empty() ? 0 : size;
}
void BOWTrainer::clear()
{
descriptors.clear();
}
BOWKMeansTrainer::BOWKMeansTrainer( int _clusterCount, const TermCriteria& _termcrit,
int _attempts, int _flags ) :
clusterCount(_clusterCount), termcrit(_termcrit), attempts(_attempts), flags(_flags)
{}
Mat BOWKMeansTrainer::cluster() const
{
CV_Assert( !descriptors.empty() );
int descCount = 0;
for( size_t i = 0; i < descriptors.size(); i++ )
descCount += descriptors[i].rows;
Mat mergedDescriptors( descCount, descriptors[0].cols, descriptors[0].type() );
for( size_t i = 0, start = 0; i < descriptors.size(); i++ )
{
Mat submut = mergedDescriptors.rowRange((int)start, (int)(start + descriptors[i].rows));
descriptors[i].copyTo(submut);
start += descriptors[i].rows;
}
return cluster( mergedDescriptors );
}
BOWKMeansTrainer::~BOWKMeansTrainer()
{}
Mat BOWKMeansTrainer::cluster( const Mat& _descriptors ) const
{
Mat labels, vocabulary;
kmeans( _descriptors, clusterCount, labels, termcrit, attempts, flags, vocabulary );
return vocabulary;
}
BOWImgDescriptorExtractor::BOWImgDescriptorExtractor( const Ptr<DescriptorExtractor>& _dextractor,
const Ptr<DescriptorMatcher>& _dmatcher ) :
dextractor(_dextractor), dmatcher(_dmatcher)
{}
BOWImgDescriptorExtractor::~BOWImgDescriptorExtractor()
{}
void BOWImgDescriptorExtractor::setVocabulary( const Mat& _vocabulary )
{
dmatcher->clear();
vocabulary = _vocabulary;
dmatcher->add( std::vector<Mat>(1, vocabulary) );
}
const Mat& BOWImgDescriptorExtractor::getVocabulary() const
{
return vocabulary;
}
void BOWImgDescriptorExtractor::compute( const Mat& image, std::vector<KeyPoint>& keypoints, Mat& imgDescriptor,
std::vector<std::vector<int> >* pointIdxsOfClusters, Mat* _descriptors )
{
imgDescriptor.release();
if( keypoints.empty() )
return;
int clusterCount = descriptorSize(); // = vocabulary.rows
// Compute descriptors for the image.
Mat descriptors;
dextractor->compute( image, keypoints, descriptors );
// Match keypoint descriptors to cluster center (to vocabulary)
std::vector<DMatch> matches;
dmatcher->match( descriptors, matches );
// Compute image descriptor
if( pointIdxsOfClusters )
{
pointIdxsOfClusters->clear();
pointIdxsOfClusters->resize(clusterCount);
}
imgDescriptor = Mat( 1, clusterCount, descriptorType(), Scalar::all(0.0) );
float *dptr = (float*)imgDescriptor.data;
for( size_t i = 0; i < matches.size(); i++ )
{
int queryIdx = matches[i].queryIdx;
int trainIdx = matches[i].trainIdx; // cluster index
CV_Assert( queryIdx == (int)i );
dptr[trainIdx] = dptr[trainIdx] + 1.f;
if( pointIdxsOfClusters )
(*pointIdxsOfClusters)[trainIdx].push_back( queryIdx );
}
// Normalize image descriptor.
imgDescriptor /= descriptors.rows;
// Add the descriptors of image keypoints
if (_descriptors) {
*_descriptors = descriptors.clone();
}
}
int BOWImgDescriptorExtractor::descriptorSize() const
{
return vocabulary.empty() ? 0 : vocabulary.rows;
}
int BOWImgDescriptorExtractor::descriptorType() const
{
return CV_32FC1;
}
}