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5f20e802d2
[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 19538cac1e.
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!
87 lines
3.6 KiB
C++
87 lines
3.6 KiB
C++
#ifndef __OPENCV_PERF_FEATURE2D_HPP__
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#define __OPENCV_PERF_FEATURE2D_HPP__
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#include "perf_precomp.hpp"
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/* cofiguration for tests of detectors/descriptors. shared between ocl and cpu tests. */
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using namespace std;
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using namespace cv;
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using namespace perf;
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using std::tr1::make_tuple;
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using std::tr1::get;
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// detectors/descriptors configurations to test
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#define DETECTORS_ONLY \
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FAST_DEFAULT, FAST_20_TRUE_TYPE5_8, FAST_20_TRUE_TYPE7_12, FAST_20_TRUE_TYPE9_16, \
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FAST_20_FALSE_TYPE5_8, FAST_20_FALSE_TYPE7_12, FAST_20_FALSE_TYPE9_16, \
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\
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AGAST_DEFAULT, AGAST_5_8, AGAST_7_12d, AGAST_7_12s, AGAST_OAST_9_16, \
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\
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MSER_DEFAULT
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#define DETECTORS_EXTRACTORS \
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ORB_DEFAULT, ORB_1500_13_1, \
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AKAZE_DEFAULT, AKAZE_DESCRIPTOR_KAZE, \
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BRISK_DEFAULT, \
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KAZE_DEFAULT
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#define CV_ENUM_EXPAND(name, ...) CV_ENUM(name, __VA_ARGS__)
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enum Feature2DVals { DETECTORS_ONLY, DETECTORS_EXTRACTORS };
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CV_ENUM_EXPAND(Feature2DType, DETECTORS_ONLY, DETECTORS_EXTRACTORS)
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typedef std::tr1::tuple<Feature2DType, string> Feature2DType_String_t;
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typedef perf::TestBaseWithParam<Feature2DType_String_t> feature2d;
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#define TEST_IMAGES testing::Values(\
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"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
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"stitching/a3.png")
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static inline Ptr<Feature2D> getFeature2D(Feature2DType type)
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{
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switch(type) {
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case ORB_DEFAULT:
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return ORB::create();
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case ORB_1500_13_1:
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return ORB::create(1500, 1.3f, 1);
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case FAST_DEFAULT:
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return FastFeatureDetector::create();
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case FAST_20_TRUE_TYPE5_8:
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return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_5_8);
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case FAST_20_TRUE_TYPE7_12:
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return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_7_12);
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case FAST_20_TRUE_TYPE9_16:
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return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_9_16);
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case FAST_20_FALSE_TYPE5_8:
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return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_5_8);
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case FAST_20_FALSE_TYPE7_12:
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return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_7_12);
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case FAST_20_FALSE_TYPE9_16:
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return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_9_16);
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case AGAST_DEFAULT:
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return AgastFeatureDetector::create();
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case AGAST_5_8:
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return AgastFeatureDetector::create(70, true, AgastFeatureDetector::AGAST_5_8);
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case AGAST_7_12d:
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return AgastFeatureDetector::create(70, true, AgastFeatureDetector::AGAST_7_12d);
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case AGAST_7_12s:
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return AgastFeatureDetector::create(70, true, AgastFeatureDetector::AGAST_7_12s);
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case AGAST_OAST_9_16:
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return AgastFeatureDetector::create(70, true, AgastFeatureDetector::OAST_9_16);
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case AKAZE_DEFAULT:
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return AKAZE::create();
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case AKAZE_DESCRIPTOR_KAZE:
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return AKAZE::create(AKAZE::DESCRIPTOR_KAZE);
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case BRISK_DEFAULT:
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return BRISK::create();
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case KAZE_DEFAULT:
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return KAZE::create();
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case MSER_DEFAULT:
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return MSER::create();
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default:
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return Ptr<Feature2D>();
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}
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}
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#endif // __OPENCV_PERF_FEATURE2D_HPP__
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