opencv/modules/features2d/src/gftt.cpp

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#include "precomp.hpp"

namespace cv
{

class GFTTDetector_Impl CV_FINAL : public GFTTDetector
{
public:
    GFTTDetector_Impl( int _nfeatures, double _qualityLevel,
                      double _minDistance, int _blockSize, int _gradientSize,
                      bool _useHarrisDetector, double _k )
        : nfeatures(_nfeatures), qualityLevel(_qualityLevel), minDistance(_minDistance),
        blockSize(_blockSize), gradSize(_gradientSize), useHarrisDetector(_useHarrisDetector), k(_k)
    {
    }

    void setMaxFeatures(int maxFeatures) CV_OVERRIDE { nfeatures = maxFeatures; }
    int getMaxFeatures() const CV_OVERRIDE { return nfeatures; }

    void setQualityLevel(double qlevel) CV_OVERRIDE { qualityLevel = qlevel; }
    double getQualityLevel() const CV_OVERRIDE { return qualityLevel; }

    void setMinDistance(double minDistance_) CV_OVERRIDE { minDistance = minDistance_; }
    double getMinDistance() const CV_OVERRIDE { return minDistance; }

    void setBlockSize(int blockSize_) CV_OVERRIDE { blockSize = blockSize_; }
    int getBlockSize() const CV_OVERRIDE { return blockSize; }

    //void setGradientSize(int gradientSize_) { gradSize = gradientSize_; }
    //int getGradientSize() { return gradSize; }

    void setHarrisDetector(bool val) CV_OVERRIDE { useHarrisDetector = val; }
    bool getHarrisDetector() const CV_OVERRIDE { return useHarrisDetector; }

    void setK(double k_) CV_OVERRIDE { k = k_; }
    double getK() const CV_OVERRIDE { return k; }

    void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask ) CV_OVERRIDE
    {
        CV_INSTRUMENT_REGION();

        if(_image.empty())
        {
            keypoints.clear();
            return;
        }

        std::vector<Point2f> corners;
        std::vector<float> cornersQuality;

        if (_image.isUMat())
        {
            UMat ugrayImage;
            if( _image.type() != CV_8U )
                cvtColor( _image, ugrayImage, COLOR_BGR2GRAY );
            else
                ugrayImage = _image.getUMat();

            goodFeaturesToTrack( ugrayImage, corners, nfeatures, qualityLevel, minDistance, _mask,
                                 cornersQuality, blockSize, gradSize, useHarrisDetector, k );
        }
        else
        {
            Mat image = _image.getMat(), grayImage = image;
            if( image.type() != CV_8U )
                cvtColor( image, grayImage, COLOR_BGR2GRAY );

            goodFeaturesToTrack( grayImage, corners, nfeatures, qualityLevel, minDistance, _mask,
                                 cornersQuality, blockSize, gradSize, useHarrisDetector, k );
        }

        CV_Assert(corners.size() == cornersQuality.size());

        keypoints.resize(corners.size());
        for (size_t i = 0; i < corners.size(); i++)
            keypoints[i] = KeyPoint(corners[i], (float)blockSize, -1, cornersQuality[i]);

    }

    int nfeatures;
    double qualityLevel;
    double minDistance;
    int blockSize;
    int gradSize;
    bool useHarrisDetector;
    double k;
};


Ptr<GFTTDetector> GFTTDetector::create( int _nfeatures, double _qualityLevel,
                         double _minDistance, int _blockSize, int _gradientSize,
                         bool _useHarrisDetector, double _k )
{
    return makePtr<GFTTDetector_Impl>(_nfeatures, _qualityLevel,
                                      _minDistance, _blockSize, _gradientSize, _useHarrisDetector, _k);
}

Ptr<GFTTDetector> GFTTDetector::create( int _nfeatures, double _qualityLevel,
                         double _minDistance, int _blockSize,
                         bool _useHarrisDetector, double _k )
{
    return makePtr<GFTTDetector_Impl>(_nfeatures, _qualityLevel,
                                      _minDistance, _blockSize, 3, _useHarrisDetector, _k);
}

String GFTTDetector::getDefaultName() const
{
    return (Feature2D::getDefaultName() + ".GFTTDetector");
}

}