* gridRows Grid rows count.
* gridCols Grid column count.
*/
- CV_WRAP GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& detector,
+ CV_WRAP GridAdaptedFeatureDetector( const Ptr<FeatureDetector>& detector=0,
int maxTotalKeypoints=1000,
int gridRows=4, int gridCols=4 );
// TODO implement read/write
virtual bool empty() const;
+
+ AlgorithmInfo* info() const;
protected:
virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
obj.info()->addParam(obj, "varyXyStepWithScale", obj.varyXyStepWithScale);
obj.info()->addParam(obj, "varyImgBoundWithScale", obj.varyImgBoundWithScale));
+CV_INIT_ALGORITHM(GridAdaptedFeatureDetector, "Feature2D.Grid",
+ obj.info()->addParam(obj, "detector", (Ptr<Algorithm>&)obj.detector);
+ obj.info()->addParam(obj, "maxTotalKeypoints", obj.maxTotalKeypoints);
+ obj.info()->addParam(obj, "gridRows", obj.gridRows);
+ obj.info()->addParam(obj, "gridCols", obj.gridCols));
+
bool initModule_features2d(void)
{
Ptr<Algorithm> brief = createBriefDescriptorExtractor(), orb = createORB(),
star = createStarDetector(), fastd = createFastFeatureDetector(), mser = createMSER(),
- dense = createDenseFeatureDetector(), gftt = createGFTTDetector(), harris = createHarrisDetector();
+ dense = createDenseFeatureDetector(), gftt = createGFTTDetector(),
+ harris = createHarrisDetector(), grid = createGridAdaptedFeatureDetector();
return brief->info() != 0 && orb->info() != 0 && star->info() != 0 &&
fastd->info() != 0 && mser->info() != 0 && dense->info() != 0 &&
- gftt->info() != 0 && harris->info() != 0;
+ gftt->info() != 0 && harris->info() != 0 && grid->info() != 0;
}
}