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feature2d: unify perf test
use the same test for all detectors/descriptors we have. * added AKAZE tests
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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_precomp.hpp"
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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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#define DETECTORS_DESCRIPTORS \
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ORB_DEFAULT, ORB_1500_13_1, \
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\
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AKAZE_DEFAULT, AKAZE_DESCRIPTOR_KAZE
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enum { DETECTORS_DESCRIPTORS, DETECTORS_ONLY };
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CV_ENUM(Feature2DType, DETECTORS_DESCRIPTORS, DETECTORS_ONLY)
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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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default:
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return Ptr<Feature2D>();
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}
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}
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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_DESCRIPTORS), 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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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() detector->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_DESCRIPTORS), 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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}

‎modules/features2d/perf/perf_orb.cpp

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