opencv/modules/nonfree/include/opencv2/nonfree/features2d.hpp

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#ifndef __OPENCV_NONFREE_FEATURES_2D_HPP__
#define __OPENCV_NONFREE_FEATURES_2D_HPP__

#include "opencv2/features2d.hpp"

namespace cv
{

/*!
 SIFT implementation.

 The class implements SIFT algorithm by D. Lowe.
*/
class CV_EXPORTS_W SIFT : public Feature2D
{
public:
    CV_WRAP explicit SIFT( int nfeatures = 0, int nOctaveLayers = 3,
          double contrastThreshold = 0.04, double edgeThreshold = 10,
          double sigma = 1.6);

    //! returns the descriptor size in floats (128)
    CV_WRAP int descriptorSize() const;

    //! returns the descriptor type
    CV_WRAP int descriptorType() const;

    //! returns the default norm type
    CV_WRAP int defaultNorm() const;

    //! finds the keypoints using SIFT algorithm
    void operator()(InputArray img, InputArray mask,
                    std::vector<KeyPoint>& keypoints) const;
    //! finds the keypoints and computes descriptors for them using SIFT algorithm.
    //! Optionally it can compute descriptors for the user-provided keypoints
    void operator()(InputArray img, InputArray mask,
                    std::vector<KeyPoint>& keypoints,
                    OutputArray descriptors,
                    bool useProvidedKeypoints = false) const;

    AlgorithmInfo* info() const;

    void buildGaussianPyramid( const Mat& base, std::vector<Mat>& pyr, int nOctaves ) const;
    void buildDoGPyramid( const std::vector<Mat>& pyr, std::vector<Mat>& dogpyr ) const;
    void findScaleSpaceExtrema( const std::vector<Mat>& gauss_pyr, const std::vector<Mat>& dog_pyr,
                                std::vector<KeyPoint>& keypoints ) const;

protected:
    void detectImpl( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask = noArray() ) const;
    void computeImpl( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ) const;

    CV_PROP_RW int nfeatures;
    CV_PROP_RW int nOctaveLayers;
    CV_PROP_RW double contrastThreshold;
    CV_PROP_RW double edgeThreshold;
    CV_PROP_RW double sigma;
};

typedef SIFT SiftFeatureDetector;
typedef SIFT SiftDescriptorExtractor;

/*!
 SURF implementation.

 The class implements SURF algorithm by H. Bay et al.
 */
class CV_EXPORTS_W SURF : public Feature2D
{
public:
    //! the default constructor
    CV_WRAP SURF();
    //! the full constructor taking all the necessary parameters
    explicit CV_WRAP SURF(double hessianThreshold,
                  int nOctaves = 4, int nOctaveLayers = 2,
                  bool extended = true, bool upright = false);

    //! returns the descriptor size in float's (64 or 128)
    CV_WRAP int descriptorSize() const;

    //! returns the descriptor type
    CV_WRAP int descriptorType() const;

    //! returns the descriptor type
    CV_WRAP int defaultNorm() const;

    //! finds the keypoints using fast hessian detector used in SURF
    void operator()(InputArray img, InputArray mask,
                    CV_OUT std::vector<KeyPoint>& keypoints) const;
    //! finds the keypoints and computes their descriptors. Optionally it can compute descriptors for the user-provided keypoints
    void operator()(InputArray img, InputArray mask,
                    CV_OUT std::vector<KeyPoint>& keypoints,
                    OutputArray descriptors,
                    bool useProvidedKeypoints = false) const;

    AlgorithmInfo* info() const;

    CV_PROP_RW double hessianThreshold;
    CV_PROP_RW int nOctaves;
    CV_PROP_RW int nOctaveLayers;
    CV_PROP_RW bool extended;
    CV_PROP_RW bool upright;

protected:
    void detectImpl( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask = noArray() ) const;
    void computeImpl( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ) const;
};

typedef SURF SurfFeatureDetector;
typedef SURF SurfDescriptorExtractor;

} /* namespace cv */

#endif