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hrnralalek
hrnr
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Merge pull request opencv#8869 from hrnr:akaze_part1
[GSOC] Speeding-up AKAZE, part opencv#1 (opencv#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 19538ca. 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!
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‎modules/features2d/perf/opencl/perf_fast.cpp

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‎modules/features2d/perf/opencl/perf_feature2d.cpp

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#include "../perf_precomp.hpp"
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#include "opencv2/ts/ocl_perf.hpp"
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#include "../perf_feature2d.hpp"
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#ifdef HAVE_OPENCL
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namespace cvtest {
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namespace ocl {
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OCL_PERF_TEST_P(feature2d, detect, testing::Combine(Feature2DType::all(), TEST_IMAGES))
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{
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Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
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std::string filename = getDataPath(get<1>(GetParam()));
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Mat mimg = imread(filename, IMREAD_GRAYSCALE);
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ASSERT_FALSE(mimg.empty());
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ASSERT_TRUE(detector);
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UMat img, mask;
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mimg.copyTo(img);
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declare.in(img);
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vector<KeyPoint> points;
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OCL_TEST_CYCLE() detector->detect(img, points, mask);
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EXPECT_GT(points.size(), 20u);
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SANITY_CHECK_NOTHING();
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}
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OCL_PERF_TEST_P(feature2d, extract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
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{
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Ptr<Feature2D> detector = AKAZE::create();
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Ptr<Feature2D> extractor = getFeature2D(get<0>(GetParam()));
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std::string filename = getDataPath(get<1>(GetParam()));
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Mat mimg = imread(filename, IMREAD_GRAYSCALE);
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ASSERT_FALSE(mimg.empty());
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ASSERT_TRUE(extractor);
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UMat img, mask;
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mimg.copyTo(img);
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declare.in(img);
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vector<KeyPoint> points;
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detector->detect(img, points, mask);
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EXPECT_GT(points.size(), 20u);
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UMat descriptors;
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OCL_TEST_CYCLE() extractor->compute(img, points, descriptors);
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EXPECT_EQ((size_t)descriptors.rows, points.size());
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SANITY_CHECK_NOTHING();
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}
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OCL_PERF_TEST_P(feature2d, detectAndExtract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
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{
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Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
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std::string filename = getDataPath(get<1>(GetParam()));
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Mat mimg = imread(filename, IMREAD_GRAYSCALE);
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ASSERT_FALSE(mimg.empty());
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ASSERT_TRUE(detector);
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UMat img, mask;
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mimg.copyTo(img);
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declare.in(img);
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vector<KeyPoint> points;
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UMat descriptors;
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OCL_TEST_CYCLE() detector->detectAndCompute(img, mask, points, descriptors, false);
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EXPECT_GT(points.size(), 20u);
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EXPECT_EQ((size_t)descriptors.rows, points.size());
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SANITY_CHECK_NOTHING();
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}
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} // ocl
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} // cvtest
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#endif // HAVE_OPENCL

‎modules/features2d/perf/opencl/perf_orb.cpp

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‎modules/features2d/perf/perf_agast.cpp

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‎modules/features2d/perf/perf_fast.cpp

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‎modules/features2d/perf/perf_feature2d.cpp

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#include "perf_feature2d.hpp"
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PERF_TEST_P(feature2d, detect, testing::Combine(Feature2DType::all(), TEST_IMAGES))
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{
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Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
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std::string filename = getDataPath(get<1>(GetParam()));
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Mat img = imread(filename, IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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ASSERT_TRUE(detector);
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declare.in(img);
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Mat mask;
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vector<KeyPoint> points;
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TEST_CYCLE() detector->detect(img, points, mask);
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EXPECT_GT(points.size(), 20u);
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P(feature2d, extract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
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{
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Ptr<Feature2D> detector = AKAZE::create();
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Ptr<Feature2D> extractor = getFeature2D(get<0>(GetParam()));
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std::string filename = getDataPath(get<1>(GetParam()));
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Mat img = imread(filename, IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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ASSERT_TRUE(extractor);
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declare.in(img);
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Mat mask;
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vector<KeyPoint> points;
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detector->detect(img, points, mask);
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EXPECT_GT(points.size(), 20u);
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Mat descriptors;
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TEST_CYCLE() extractor->compute(img, points, descriptors);
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EXPECT_EQ((size_t)descriptors.rows, points.size());
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SANITY_CHECK_NOTHING();
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}
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PERF_TEST_P(feature2d, detectAndExtract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
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{
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Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
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std::string filename = getDataPath(get<1>(GetParam()));
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Mat img = imread(filename, IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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ASSERT_TRUE(detector);
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declare.in(img);
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Mat mask;
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vector<KeyPoint> points;
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Mat descriptors;
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TEST_CYCLE() detector->detectAndCompute(img, mask, points, descriptors, false);
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EXPECT_GT(points.size(), 20u);
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EXPECT_EQ((size_t)descriptors.rows, points.size());
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SANITY_CHECK_NOTHING();
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}

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