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Check for empty objects via .area() is not a good practice due overflows
Results are not stable with srand()
[GSOC] Speeding-up AKAZE, part #3 (#9249) * use finding of scale extremas from fast_akaze * incorporade finding of extremas and subpixel refinement from Hideaki Suzuki's fast_akaze (https://github.com/h2suzuki/fast_akaze) * use opencv parallel framework * do not search for keypoints near the border, where we can't compute sensible descriptors (bugs fixed in ffd9ad9, 2c53895), but the descriptors were not 100% correct. this is a better solution this version produces less keypoints with the same treshold. It is more effective in pruning similar keypoints (which do not bring any new information), so we have less keypoints, but with high quality. Accuracy is about the same. * incorporate bugfix from upstream * fix bug in subpixel refinement * see commit db3dc22981e856ca8111f2f7fe57d9c2e0286efc in Pablo's repo * rework finding of scale space extremas * store just keypoints positions * store positions in uchar mask for effective spatial search for neighbours * construct keypoints structs at the very end * lower inlier threshold in test * win32 has lower accuracy
cmake: fix __STDC macros for opencv_world build
- integer division => divUp() - cast to 'int' => cvCeil()
Update miniflann.cpp Update test_stereomatching.cpp
CUDA implementation wants to convert std::vector<KeyPoint> <-> GpuMat. There is no direct mapping from KeyPoint (mix of int/float fields) into cv::Mat element type, so this conversion must be avoided. Legacy mode is turned back for CUDA builds.
* Refactor Python Classes
Manual IPP dispatcher simplification;
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