feature_adjuster.h

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#ifndef FEATUREADJUSTER_H
#define FEATUREADJUSTER_H
#include <opencv2/features2d/features2d.hpp>

class DetectorAdjuster: public cv::AdjusterAdapter
{
public:
    DetectorAdjuster(const char* detector_name, double initial_thresh=200.f, double min_thresh=2, double max_thresh=10000, double increase_factor=1.3, double decrease_factor=0.7 );
    
    virtual void tooFew(int minv, int n_detected);
    virtual void tooMany(int maxv, int n_detected);
    virtual bool good() const;

    virtual cv::Ptr<cv::AdjusterAdapter> clone() const;

    void setIncreaseFactor(double new_factor);
    void setDecreaseFactor(double new_factor);
protected:
    virtual void detectImpl( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints, const cv::Mat& mask=cv::Mat() ) const;

    double thresh_, min_thresh_, max_thresh_;
    double increase_factor_, decrease_factor_;
    const char* detector_name_;
};

class StatefulFeatureDetector : public cv::FeatureDetector {
  public:
    virtual cv::Ptr<StatefulFeatureDetector> clone() const = 0;
};

class VideoDynamicAdaptedFeatureDetector: public StatefulFeatureDetector
{
public:

     VideoDynamicAdaptedFeatureDetector( cv::Ptr<cv::AdjusterAdapter> adjuster, int min_features=400, int max_features=500, int max_iters=5);

    virtual cv::Ptr<StatefulFeatureDetector> clone() const;
    virtual bool empty() const;

protected:
    virtual void detectImpl( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints, const cv::Mat& mask=cv::Mat() ) const;

private:
    VideoDynamicAdaptedFeatureDetector& operator=(const VideoDynamicAdaptedFeatureDetector&);
    VideoDynamicAdaptedFeatureDetector(const VideoDynamicAdaptedFeatureDetector&);

    int escape_iters_;
    int min_features_, max_features_;
    mutable cv::Ptr<cv::AdjusterAdapter> adjuster_;
};






/*
 * Adapts a detector to partition the source image into a grid and detect
 * points in each cell. Considers the overlap between cells required for
 * not losing keypoints
 */
class VideoGridAdaptedFeatureDetector : public StatefulFeatureDetector
{
public:
    /*
     * \param detector            Detector that will be adapted.
     * \param maxTotalKeypoints   Maximum count of keypoints detected on the image. Only the strongest keypoints will be keeped.
     *  \param gridRows           Grid rows count.
     *  \param gridCols           Grid column count.
     *  \param edgeThreshold     how much overlap is needed, to not lose keypoints at the inner borders of the grid (should be the same value, e.g., as edgeThreshold for ORB)
     */
    VideoGridAdaptedFeatureDetector(const cv::Ptr<StatefulFeatureDetector>& detector,
                                    int maxTotalKeypoints=1000, int gridRows=4, 
                                    int gridCols=4, int edgeThreshold=31 );
    
    // TODO implement read/write
    virtual bool empty() const;
    virtual cv::Ptr<StatefulFeatureDetector> clone() const;

protected:
    VideoGridAdaptedFeatureDetector& operator=(const VideoGridAdaptedFeatureDetector&);
    VideoGridAdaptedFeatureDetector(const VideoGridAdaptedFeatureDetector&);

    virtual void detectImpl( const cv::Mat& image, std::vector<cv::KeyPoint>& keypoints, const cv::Mat& mask=cv::Mat() ) const;

    std::vector<cv::Ptr<StatefulFeatureDetector> > detectors;
    int maxTotalKeypoints;
    int gridRows;
    int gridCols;
    int edgeThreshold; 
};


#endif