opencv/modules/features2d/src/descriptors.cpp

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#include "precomp.hpp"

using namespace std;

namespace cv
{

/****************************************************************************************\
*                                 DescriptorExtractor                                    *
\****************************************************************************************/
/*
 *   DescriptorExtractor
 */
DescriptorExtractor::~DescriptorExtractor()
{}

void DescriptorExtractor::compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const
{
    if( image.empty() || keypoints.empty() )
    {
        descriptors.release();
        return;
    }

    KeyPointsFilter::runByImageBorder( keypoints, image.size(), 0 );
    KeyPointsFilter::runByKeypointSize( keypoints, std::numeric_limits<float>::epsilon() );

    computeImpl( image, keypoints, descriptors );
}

void DescriptorExtractor::compute( const vector<Mat>& imageCollection, vector<vector<KeyPoint> >& pointCollection, vector<Mat>& descCollection ) const
{
    CV_Assert( imageCollection.size() == pointCollection.size() );
    descCollection.resize( imageCollection.size() );
    for( size_t i = 0; i < imageCollection.size(); i++ )
        compute( imageCollection[i], pointCollection[i], descCollection[i] );
}

/*void DescriptorExtractor::read( const FileNode& )
{}

void DescriptorExtractor::write( FileStorage& ) const
{}*/

bool DescriptorExtractor::empty() const
{
    return false;
}

void DescriptorExtractor::removeBorderKeypoints( vector<KeyPoint>& keypoints,
                                                 Size imageSize, int borderSize )
{
    KeyPointsFilter::runByImageBorder( keypoints, imageSize, borderSize );
}

Ptr<DescriptorExtractor> DescriptorExtractor::create(const string& descriptorExtractorType)
{
    if( descriptorExtractorType.find("Opponent") == 0 )
    {
        size_t pos = string("Opponent").size();
        string type = descriptorExtractorType.substr(pos);
        return new OpponentColorDescriptorExtractor(DescriptorExtractor::create(type));
    }

    return Algorithm::create<DescriptorExtractor>("Feature2D." + descriptorExtractorType);
}

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////

/****************************************************************************************\
*                             OpponentColorDescriptorExtractor                           *
\****************************************************************************************/
OpponentColorDescriptorExtractor::OpponentColorDescriptorExtractor( const Ptr<DescriptorExtractor>& _descriptorExtractor ) :
        descriptorExtractor(_descriptorExtractor)
{
    CV_Assert( !descriptorExtractor.empty() );
}

static void convertBGRImageToOpponentColorSpace( const Mat& bgrImage, vector<Mat>& opponentChannels )
{
    if( bgrImage.type() != CV_8UC3 )
        CV_Error( CV_StsBadArg, "input image must be an BGR image of type CV_8UC3" );

    // Split image into RGB to allow conversion to Opponent Color Space.
    vector<Mat> bgrChannels(3);
    split( bgrImage, bgrChannels );

    // Prepare opponent color space storage matrices.
    opponentChannels.resize( 3 );
    opponentChannels[0] = cv::Mat(bgrImage.size(), CV_8UC1); // R-G RED-GREEN
    opponentChannels[1] = cv::Mat(bgrImage.size(), CV_8UC1); // R+G-2B YELLOW-BLUE
    opponentChannels[2] = cv::Mat(bgrImage.size(), CV_8UC1); // R+G+B

    // Calculate the channels of the opponent color space
    {
        // (R - G) / sqrt(2)
        MatConstIterator_<signed char> rIt = bgrChannels[2].begin<signed char>();
        MatConstIterator_<signed char> gIt = bgrChannels[1].begin<signed char>();
        MatIterator_<unsigned char> dstIt = opponentChannels[0].begin<unsigned char>();
        float factor = 1.f / sqrt(2.f);
        for( ; dstIt != opponentChannels[0].end<unsigned char>(); ++rIt, ++gIt, ++dstIt )
        {
            int value = static_cast<int>( static_cast<float>(static_cast<int>(*gIt)-static_cast<int>(*rIt)) * factor );
            if( value < 0 ) value = 0;
            if( value > 255 ) value = 255;
            (*dstIt) = static_cast<unsigned char>(value);
        }
    }
    {
        // (R + G - 2B)/sqrt(6)
        MatConstIterator_<signed char> rIt = bgrChannels[2].begin<signed char>();
        MatConstIterator_<signed char> gIt = bgrChannels[1].begin<signed char>();
        MatConstIterator_<signed char> bIt = bgrChannels[0].begin<signed char>();
        MatIterator_<unsigned char> dstIt = opponentChannels[1].begin<unsigned char>();
        float factor = 1.f / sqrt(6.f);
        for( ; dstIt != opponentChannels[1].end<unsigned char>(); ++rIt, ++gIt, ++bIt, ++dstIt )
        {
            int value = static_cast<int>( static_cast<float>(static_cast<int>(*rIt) + static_cast<int>(*gIt) - 2*static_cast<int>(*bIt)) *
                                          factor );
            if( value < 0 ) value = 0;
            if( value > 255 ) value = 255;
            (*dstIt) = static_cast<unsigned char>(value);
        }
    }
    {
        // (R + G + B)/sqrt(3)
        MatConstIterator_<signed char> rIt = bgrChannels[2].begin<signed char>();
        MatConstIterator_<signed char> gIt = bgrChannels[1].begin<signed char>();
        MatConstIterator_<signed char> bIt = bgrChannels[0].begin<signed char>();
        MatIterator_<unsigned char> dstIt = opponentChannels[2].begin<unsigned char>();
        float factor = 1.f / sqrt(3.f);
        for( ; dstIt != opponentChannels[2].end<unsigned char>(); ++rIt, ++gIt, ++bIt, ++dstIt )
        {
            int value = static_cast<int>( static_cast<float>(static_cast<int>(*rIt) + static_cast<int>(*gIt) + static_cast<int>(*bIt)) *
                                          factor );
            if( value < 0 ) value = 0;
            if( value > 255 ) value = 255;
            (*dstIt) = static_cast<unsigned char>(value);
        }
    }
}

struct KP_LessThan
{
    KP_LessThan(const vector<KeyPoint>& _kp) : kp(&_kp) {}
    bool operator()(int i, int j) const
    {
        return (*kp)[i].class_id < (*kp)[j].class_id;
    }
    const vector<KeyPoint>* kp;
};

void OpponentColorDescriptorExtractor::computeImpl( const Mat& bgrImage, vector<KeyPoint>& keypoints, Mat& descriptors ) const
{
    vector<Mat> opponentChannels;
    convertBGRImageToOpponentColorSpace( bgrImage, opponentChannels );

    const int N = 3; // channels count
    vector<KeyPoint> channelKeypoints[N];
    Mat channelDescriptors[N];
    vector<int> idxs[N];

    // Compute descriptors three times, once for each Opponent channel to concatenate into a single color descriptor
    int maxKeypointsCount = 0;
    for( int ci = 0; ci < N; ci++ )
    {
        channelKeypoints[ci].insert( channelKeypoints[ci].begin(), keypoints.begin(), keypoints.end() );
        // Use class_id member to get indices into initial keypoints vector
        for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ )
            channelKeypoints[ci][ki].class_id = (int)ki;

        descriptorExtractor->compute( opponentChannels[ci], channelKeypoints[ci], channelDescriptors[ci] );
        idxs[ci].resize( channelKeypoints[ci].size() );
        for( size_t ki = 0; ki < channelKeypoints[ci].size(); ki++ )
        {
            idxs[ci][ki] = (int)ki;
        }
        std::sort( idxs[ci].begin(), idxs[ci].end(), KP_LessThan(channelKeypoints[ci]) );
        maxKeypointsCount = std::max( maxKeypointsCount, (int)channelKeypoints[ci].size());
    }

    vector<KeyPoint> outKeypoints;
    outKeypoints.reserve( keypoints.size() );

    int dSize = descriptorExtractor->descriptorSize();
    Mat mergedDescriptors( maxKeypointsCount, 3*dSize, descriptorExtractor->descriptorType() );
    int mergedCount = 0;
    // cp - current channel position
    size_t cp[] = {0, 0, 0};
    while( cp[0] < channelKeypoints[0].size() &&
           cp[1] < channelKeypoints[1].size() &&
           cp[2] < channelKeypoints[2].size() )
    {
        const int maxInitIdx = std::max( 0, std::max( channelKeypoints[0][idxs[0][cp[0]]].class_id,
                                                      std::max( channelKeypoints[1][idxs[1][cp[1]]].class_id,
                                                                channelKeypoints[2][idxs[2][cp[2]]].class_id ) ) );

        while( channelKeypoints[0][idxs[0][cp[0]]].class_id < maxInitIdx && cp[0] < channelKeypoints[0].size() ) { cp[0]++; }
        while( channelKeypoints[1][idxs[1][cp[1]]].class_id < maxInitIdx && cp[1] < channelKeypoints[1].size() ) { cp[1]++; }
        while( channelKeypoints[2][idxs[2][cp[2]]].class_id < maxInitIdx && cp[2] < channelKeypoints[2].size() ) { cp[2]++; }
        if( cp[0] >= channelKeypoints[0].size() || cp[1] >= channelKeypoints[1].size() || cp[2] >= channelKeypoints[2].size() )
            break;

        if( channelKeypoints[0][idxs[0][cp[0]]].class_id == maxInitIdx &&
            channelKeypoints[1][idxs[1][cp[1]]].class_id == maxInitIdx &&
            channelKeypoints[2][idxs[2][cp[2]]].class_id == maxInitIdx )
        {
            outKeypoints.push_back( keypoints[maxInitIdx] );
            // merge descriptors
            for( int ci = 0; ci < N; ci++ )
            {
                Mat dst = mergedDescriptors(Range(mergedCount, mergedCount+1), Range(ci*dSize, (ci+1)*dSize));
                channelDescriptors[ci].row( idxs[ci][cp[ci]] ).copyTo( dst );
                cp[ci]++;
            }
            mergedCount++;
        }
    }
    mergedDescriptors.rowRange(0, mergedCount).copyTo( descriptors );
    std::swap( outKeypoints, keypoints );
}

void OpponentColorDescriptorExtractor::read( const FileNode& fn )
{
    descriptorExtractor->read(fn);
}

void OpponentColorDescriptorExtractor::write( FileStorage& fs ) const
{
    descriptorExtractor->write(fs);
}

int OpponentColorDescriptorExtractor::descriptorSize() const
{
    return 3*descriptorExtractor->descriptorSize();
}

int OpponentColorDescriptorExtractor::descriptorType() const
{
    return descriptorExtractor->descriptorType();
}

bool OpponentColorDescriptorExtractor::empty() const
{
    return descriptorExtractor.empty() || (DescriptorExtractor*)(descriptorExtractor)->empty();
}

}