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fixed DynamicAdaptedFeatureDetector
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@ -1487,20 +1487,22 @@ public:
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/** pure virtual interface
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*/
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virtual ~AdjusterAdapter() {}
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/** too few features were detected so, adjust the detector params accordingly
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* \param min the minimum number of desired features
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* \param n_detected the number previously detected
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*/
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virtual void tooFew(int min, int n_detected) = 0;
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/** too many features were detected so, adjust the detector params accordingly
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* \param max the maximum number of desired features
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* \param n_detected the number previously detected
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*/
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virtual void tooMany(int max, int n_detected) = 0;
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/** are params maxed out or still valid?
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* \return false if the parameters can't be adjusted any more
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*/
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virtual bool good() const = 0;
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/** too few features were detected so, adjust the detector params accordingly
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* \param min the minimum number of desired features
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* \param n_detected the number previously detected
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*/
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virtual void tooFew(int min, int n_detected) = 0;
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/** too many features were detected so, adjust the detector params accordingly
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* \param max the maximum number of desired features
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* \param n_detected the number previously detected
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*/
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virtual void tooMany(int max, int n_detected) = 0;
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/** are params maxed out or still valid?
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* \return false if the parameters can't be adjusted any more
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*/
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virtual bool good() const = 0;
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virtual Ptr<AdjusterAdapter> clone() const = 0;
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static Ptr<AdjusterAdapter> create( const string& detectorType );
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};
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@ -1521,11 +1523,11 @@ class CV_EXPORTS DynamicAdaptedFeatureDetector: public FeatureDetector
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public:
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/** \param adjaster an AdjusterAdapter that will do the detection and parameter adjustment
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* \param max_features the maximum desired number of features
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* \param max_iters the maximum number of times to try to adjust the feature detector params
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* for the FastAdjuster this can be high, but with Star or Surf this can get time consuming
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* \param min_features the minimum desired features
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*/
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* \param max_features the maximum desired number of features
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* \param max_iters the maximum number of times to try to adjust the feature detector params
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* for the FastAdjuster this can be high, but with Star or Surf this can get time consuming
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* \param min_features the minimum desired features
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*/
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DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>& adjaster, int min_features=400, int max_features=500, int max_iters=5 );
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virtual bool empty() const;
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@ -1534,30 +1536,34 @@ protected:
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virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
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private:
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int escape_iters_;
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int min_features_, max_features_;
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Ptr<AdjusterAdapter> adjuster_;
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int escape_iters_;
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int min_features_, max_features_;
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const Ptr<AdjusterAdapter> adjuster_;
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};
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/**\brief an adjust for the FAST detector. This will basically decrement or increment the
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* threshhold by 1
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* threshold by 1
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*/
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class CV_EXPORTS FastAdjuster: public AdjusterAdapter
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{
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public:
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/**\param init_thresh the initial threshhold to start with, default = 20
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* \param nonmax whether to use non max or not for fast feature detection
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*/
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FastAdjuster(int init_thresh = 20, bool nonmax = true);
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virtual void tooFew(int min, int n_detected);
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virtual void tooMany(int max, int n_detected);
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virtual bool good() const;
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/**\param init_thresh the initial threshold to start with, default = 20
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* \param nonmax whether to use non max or not for fast feature detection
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*/
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FastAdjuster(int init_thresh = 20, bool nonmax = true);
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virtual void tooFew(int min, int n_detected);
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virtual void tooMany(int max, int n_detected);
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virtual bool good() const;
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virtual Ptr<AdjusterAdapter> clone() const;
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protected:
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virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
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int thresh_;
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bool nonmax_;
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int thresh_;
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bool nonmax_;
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int init_thresh_;
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};
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@ -1567,30 +1573,36 @@ protected:
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class CV_EXPORTS StarAdjuster: public AdjusterAdapter
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{
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public:
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StarAdjuster(double initial_thresh = 30.0);
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virtual void tooFew(int min, int n_detected);
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virtual void tooMany(int max, int n_detected);
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virtual bool good() const;
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StarAdjuster(double initial_thresh = 30.0);
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virtual void tooFew(int min, int n_detected);
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virtual void tooMany(int max, int n_detected);
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virtual bool good() const;
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virtual Ptr<AdjusterAdapter> clone() const;
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protected:
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virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
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double thresh_;
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CvStarDetectorParams params_; //todo use these instead of thresh_
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double thresh_, init_thresh_;
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CvStarDetectorParams params_; //todo use these instead of thresh_
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};
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class CV_EXPORTS SurfAdjuster: public AdjusterAdapter
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{
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public:
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SurfAdjuster();
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virtual void tooFew(int min, int n_detected);
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virtual void tooMany(int max, int n_detected);
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virtual bool good() const;
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SurfAdjuster( double initial_thresh=400.f );
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virtual void tooFew(int min, int n_detected);
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virtual void tooMany(int max, int n_detected);
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virtual bool good() const;
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virtual Ptr<AdjusterAdapter> clone() const;
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protected:
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virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
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double thresh_;
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double thresh_, init_thresh_;
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};
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CV_EXPORTS Mat windowedMatchingMask( const vector<KeyPoint>& keypoints1, const vector<KeyPoint>& keypoints2,
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@ -56,124 +56,143 @@ bool DynamicAdaptedFeatureDetector::empty() const
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void DynamicAdaptedFeatureDetector::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const
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{
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//for oscillation testing
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bool down = false;
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bool up = false;
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//for oscillation testing
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bool down = false;
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bool up = false;
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//flag for whether the correct threshhold has been reached
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bool thresh_good = false;
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//flag for whether the correct threshhold has been reached
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bool thresh_good = false;
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//this is bad but adjuster should persist from detection to detection
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AdjusterAdapter& adjuster = const_cast<AdjusterAdapter&> (*adjuster_);
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Ptr<AdjusterAdapter> adjuster = adjuster_->clone();
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//break if the desired number hasn't been reached.
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int iter_count = escape_iters_;
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//break if the desired number hasn't been reached.
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int iter_count = escape_iters_;
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do
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while( iter_count > 0 && !(down && up) && !thresh_good && adjuster->good() )
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{
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keypoints.clear();
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keypoints.clear();
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//the adjuster takes care of calling the detector with updated parameters
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adjuster.detect(image, keypoints,mask);
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//the adjuster takes care of calling the detector with updated parameters
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adjuster->detect(image, keypoints,mask);
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if (int(keypoints.size()) < min_features_)
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if( int(keypoints.size()) < min_features_ )
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{
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down = true;
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adjuster.tooFew(min_features_, (int)keypoints.size());
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down = true;
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adjuster->tooFew(min_features_, (int)keypoints.size());
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}
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else if (int(keypoints.size()) > max_features_)
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else if( int(keypoints.size()) > max_features_ )
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{
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up = true;
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adjuster.tooMany(max_features_, (int)keypoints.size());
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up = true;
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adjuster->tooMany(max_features_, (int)keypoints.size());
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}
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else
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thresh_good = true;
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thresh_good = true;
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iter_count--;
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}
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while (--iter_count >= 0 && !(down && up) && !thresh_good && adjuster.good());
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}
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FastAdjuster::FastAdjuster(int init_thresh, bool nonmax) :
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thresh_(init_thresh), nonmax_(nonmax)
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thresh_(init_thresh), nonmax_(nonmax), init_thresh_(init_thresh)
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{}
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void FastAdjuster::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const
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{
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FastFeatureDetector(thresh_, nonmax_).detect(image, keypoints, mask);
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FastFeatureDetector(thresh_, nonmax_).detect(image, keypoints, mask);
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}
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void FastAdjuster::tooFew(int, int)
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{
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//fast is easy to adjust
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thresh_--;
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//fast is easy to adjust
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thresh_--;
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}
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void FastAdjuster::tooMany(int, int)
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{
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//fast is easy to adjust
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thresh_++;
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//fast is easy to adjust
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thresh_++;
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}
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//return whether or not the threshhold is beyond
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//a useful point
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bool FastAdjuster::good() const
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{
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return (thresh_ > 1) && (thresh_ < 200);
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return (thresh_ > 1) && (thresh_ < 200);
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}
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Ptr<AdjusterAdapter> FastAdjuster::clone() const
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{
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Ptr<AdjusterAdapter> cloned_obj = new FastAdjuster( init_thresh_, nonmax_ );
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return cloned_obj;
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}
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StarAdjuster::StarAdjuster(double initial_thresh) :
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thresh_(initial_thresh)
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thresh_(initial_thresh), init_thresh_(initial_thresh)
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{}
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void StarAdjuster::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const
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{
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StarFeatureDetector detector_tmp(16, cvRound(thresh_), 10, 8, 3);
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detector_tmp.detect(image, keypoints, mask);
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StarFeatureDetector detector_tmp(16, cvRound(thresh_), 10, 8, 3);
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detector_tmp.detect(image, keypoints, mask);
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}
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void StarAdjuster::tooFew(int, int)
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{
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thresh_ *= 0.9;
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if (thresh_ < 1.1)
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thresh_ = 1.1;
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thresh_ *= 0.9;
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if (thresh_ < 1.1)
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thresh_ = 1.1;
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}
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void StarAdjuster::tooMany(int, int)
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{
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thresh_ *= 1.1;
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thresh_ *= 1.1;
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}
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bool StarAdjuster::good() const
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{
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return (thresh_ > 2) && (thresh_ < 200);
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return (thresh_ > 2) && (thresh_ < 200);
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}
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SurfAdjuster::SurfAdjuster() :
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thresh_(400.0)
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Ptr<AdjusterAdapter> StarAdjuster::clone() const
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{
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Ptr<AdjusterAdapter> cloned_obj = new StarAdjuster( init_thresh_ );
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return cloned_obj;
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}
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SurfAdjuster::SurfAdjuster( double initial_thresh ) :
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thresh_(initial_thresh), init_thresh_(initial_thresh)
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{}
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void SurfAdjuster::detectImpl(const Mat& image, vector<KeyPoint>& keypoints, const cv::Mat& mask) const
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{
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SurfFeatureDetector detector_tmp(thresh_);
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detector_tmp.detect(image, keypoints, mask);
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SurfFeatureDetector detector_tmp(thresh_);
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detector_tmp.detect(image, keypoints, mask);
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}
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void SurfAdjuster::tooFew(int, int)
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{
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thresh_ *= 0.9;
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if (thresh_ < 1.1)
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thresh_ = 1.1;
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thresh_ *= 0.9;
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if (thresh_ < 1.1)
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thresh_ = 1.1;
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}
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void SurfAdjuster::tooMany(int, int)
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{
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thresh_ *= 1.1;
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thresh_ *= 1.1;
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}
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//return whether or not the threshhold is beyond
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//a useful point
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bool SurfAdjuster::good() const
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{
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return (thresh_ > 2) && (thresh_ < 1000);
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return (thresh_ > 2) && (thresh_ < 1000);
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}
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Ptr<AdjusterAdapter> SurfAdjuster::clone() const
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{
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Ptr<AdjusterAdapter> cloned_obj = new SurfAdjuster( init_thresh_ );
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return cloned_obj;
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}
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Ptr<AdjusterAdapter> AdjusterAdapter::create( const string& detectorType )
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