[GSOC] Speeding-up AKAZE, part #1 (#8869) * ts: expand arguments before stringifications in CV_ENUM and CV_FLAGS added protective macros to always force macro expansion of arguments. This allows using CV_ENUM and CV_FLAGS with macro arguments. * feature2d: unify perf test use the same test for all detectors/descriptors we have. * added AKAZE tests * features2d: extend perf tests * add BRISK, KAZE, MSER * run all extract tests on AKAZE keypoints, so that the test si more comparable for the speed of extraction * feature2d: rework opencl perf tests use the same configuration as cpu tests * feature2d: fix descriptors allocation for AKAZE and KAZE fix crash when descriptors are UMat * feature2d: name enum to fix build with older gcc * Revert "ts: expand arguments before stringifications in CV_ENUM and CV_FLAGS" This reverts commit 19538cac1e45b0cec98190cf06a5ecb07d9b596e. This wasn't a great idea after all. There is a lot of flags implemented as #define, that we don't want to expand. * feature2d: fix expansion problems with CV_ENUM in perf * expand arguments before passing them to CV_ENUM. This does not need modifications of CV_ENUM. * added include guards to `perf_feature2d.hpp` * feature2d: fix crash in AKAZE when using KAZE descriptors * out-of-bound access in Get_MSURF_Descriptor_64 * this happened reliably when running on provided keypoints (not computed by the same instance) * feature2d: added regression tests for AKAZE * test with both MLDB and KAZE keypoints * feature2d: do not compute keypoints orientation twice * always compute keypoints orientation, when computing keypoints * do not recompute keypoint orientation when computing descriptors this allows to test detection and extraction separately * features2d: fix crash in AKAZE * out-of-bound reads near the image edge * same as the bug in KAZE descriptors * feature2d: refactor invariance testing * split detectors and descriptors tests * rewrite to google test to simplify debugging * add tests for AKAZE and one test for ORB * stitching: add tests with AKAZE feature finder * added basic stitching cpu and ocl tests * fix bug in AKAZE wrapper for stitching pipeline causing lots of ! OPENCV warning: getUMat()/getMat() call chain possible problem. ! Base object is dead, while nested/derived object is still alive or processed. ! Please check lifetime of UMat/Mat objects!
200 lines
6.9 KiB
C++
200 lines
6.9 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2008, Willow Garage Inc., all rights reserved.
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// * The name of Intel Corporation may not be used to endorse or promote products
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//M*/
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/*
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OpenCV wrapper of reference implementation of
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[1] KAZE Features. Pablo F. Alcantarilla, Adrien Bartoli and Andrew J. Davison.
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In European Conference on Computer Vision (ECCV), Fiorenze, Italy, October 2012
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http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla12eccv.pdf
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@author Eugene Khvedchenya <ekhvedchenya@gmail.com>
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*/
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#include "precomp.hpp"
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#include "kaze/KAZEFeatures.h"
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namespace cv
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{
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class KAZE_Impl : public KAZE
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{
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public:
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KAZE_Impl(bool _extended, bool _upright, float _threshold, int _octaves,
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int _sublevels, int _diffusivity)
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: extended(_extended)
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, upright(_upright)
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, threshold(_threshold)
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, octaves(_octaves)
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, sublevels(_sublevels)
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, diffusivity(_diffusivity)
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{
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}
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virtual ~KAZE_Impl() {}
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void setExtended(bool extended_) { extended = extended_; }
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bool getExtended() const { return extended; }
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void setUpright(bool upright_) { upright = upright_; }
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bool getUpright() const { return upright; }
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void setThreshold(double threshold_) { threshold = (float)threshold_; }
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double getThreshold() const { return threshold; }
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void setNOctaves(int octaves_) { octaves = octaves_; }
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int getNOctaves() const { return octaves; }
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void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; }
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int getNOctaveLayers() const { return sublevels; }
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void setDiffusivity(int diff_) { diffusivity = diff_; }
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int getDiffusivity() const { return diffusivity; }
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// returns the descriptor size in bytes
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int descriptorSize() const
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{
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return extended ? 128 : 64;
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}
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// returns the descriptor type
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int descriptorType() const
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{
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return CV_32F;
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}
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// returns the default norm type
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int defaultNorm() const
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{
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return NORM_L2;
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}
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void detectAndCompute(InputArray image, InputArray mask,
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std::vector<KeyPoint>& keypoints,
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OutputArray descriptors,
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bool useProvidedKeypoints)
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{
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CV_INSTRUMENT_REGION()
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cv::Mat img = image.getMat();
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if (img.channels() > 1)
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cvtColor(image, img, COLOR_BGR2GRAY);
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Mat img1_32;
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if ( img.depth() == CV_32F )
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img1_32 = img;
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else if ( img.depth() == CV_8U )
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img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
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else if ( img.depth() == CV_16U )
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img.convertTo(img1_32, CV_32F, 1.0 / 65535.0, 0);
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CV_Assert( ! img1_32.empty() );
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KAZEOptions options;
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options.img_width = img.cols;
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options.img_height = img.rows;
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options.extended = extended;
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options.upright = upright;
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options.dthreshold = threshold;
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options.omax = octaves;
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options.nsublevels = sublevels;
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options.diffusivity = diffusivity;
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KAZEFeatures impl(options);
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impl.Create_Nonlinear_Scale_Space(img1_32);
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if (!useProvidedKeypoints)
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{
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impl.Feature_Detection(keypoints);
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}
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if (!mask.empty())
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{
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cv::KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat());
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}
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if( descriptors.needed() )
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{
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Mat desc;
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impl.Feature_Description(keypoints, desc);
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desc.copyTo(descriptors);
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CV_Assert((!desc.rows || desc.cols == descriptorSize()));
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CV_Assert((!desc.rows || (desc.type() == descriptorType())));
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}
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}
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void write(FileStorage& fs) const
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{
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writeFormat(fs);
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fs << "extended" << (int)extended;
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fs << "upright" << (int)upright;
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fs << "threshold" << threshold;
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fs << "octaves" << octaves;
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fs << "sublevels" << sublevels;
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fs << "diffusivity" << diffusivity;
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}
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void read(const FileNode& fn)
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{
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extended = (int)fn["extended"] != 0;
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upright = (int)fn["upright"] != 0;
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threshold = (float)fn["threshold"];
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octaves = (int)fn["octaves"];
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sublevels = (int)fn["sublevels"];
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diffusivity = (int)fn["diffusivity"];
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}
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bool extended;
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bool upright;
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float threshold;
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int octaves;
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int sublevels;
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int diffusivity;
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};
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Ptr<KAZE> KAZE::create(bool extended, bool upright,
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float threshold,
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int octaves, int sublevels,
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int diffusivity)
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{
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return makePtr<KAZE_Impl>(extended, upright, threshold, octaves, sublevels, diffusivity);
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}
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}
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