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175 lines
6.1 KiB
175 lines
6.1 KiB
// This file is part of OpenCV project. |
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// It is subject to the license terms in the LICENSE file found in the top-level directory |
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// of this distribution and at http://opencv.org/license.html |
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#include "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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const string FEATURES2D_DIR = "features2d"; |
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const string IMAGE_FILENAME = "tsukuba.png"; |
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const string DESCRIPTOR_DIR = FEATURES2D_DIR + "/descriptor_extractors"; |
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}} // namespace |
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#include "test_descriptors_regression.impl.hpp" |
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namespace opencv_test { namespace { |
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/****************************************************************************************\ |
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* Tests registrations * |
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\****************************************************************************************/ |
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TEST( Features2d_DescriptorExtractor_BRISK, regression ) |
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{ |
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CV_DescriptorExtractorTest<Hamming> test( "descriptor-brisk", |
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(CV_DescriptorExtractorTest<Hamming>::DistanceType)2.f, |
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BRISK::create() ); |
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test.safe_run(); |
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} |
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TEST( Features2d_DescriptorExtractor_ORB, regression ) |
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{ |
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// TODO adjust the parameters below |
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CV_DescriptorExtractorTest<Hamming> test( "descriptor-orb", |
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#if CV_NEON |
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(CV_DescriptorExtractorTest<Hamming>::DistanceType)25.f, |
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#else |
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(CV_DescriptorExtractorTest<Hamming>::DistanceType)12.f, |
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#endif |
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ORB::create() ); |
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test.safe_run(); |
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} |
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TEST( Features2d_DescriptorExtractor_KAZE, regression ) |
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{ |
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CV_DescriptorExtractorTest< L2<float> > test( "descriptor-kaze", 0.03f, |
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KAZE::create(), |
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L2<float>(), KAZE::create() ); |
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test.safe_run(); |
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} |
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TEST( Features2d_DescriptorExtractor_AKAZE, regression ) |
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{ |
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CV_DescriptorExtractorTest<Hamming> test( "descriptor-akaze", |
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(CV_DescriptorExtractorTest<Hamming>::DistanceType)(486*0.05f), |
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AKAZE::create(), |
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Hamming(), AKAZE::create()); |
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test.safe_run(); |
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} |
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TEST( Features2d_DescriptorExtractor_AKAZE_DESCRIPTOR_KAZE, regression ) |
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{ |
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CV_DescriptorExtractorTest< L2<float> > test( "descriptor-akaze-with-kaze-desc", 0.03f, |
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AKAZE::create(AKAZE::DESCRIPTOR_KAZE), |
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L2<float>(), AKAZE::create(AKAZE::DESCRIPTOR_KAZE)); |
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test.safe_run(); |
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} |
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TEST( Features2d_DescriptorExtractor, batch ) |
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{ |
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string path = string(cvtest::TS::ptr()->get_data_path() + "detectors_descriptors_evaluation/images_datasets/graf"); |
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vector<Mat> imgs, descriptors; |
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vector<vector<KeyPoint> > keypoints; |
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int i, n = 6; |
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Ptr<ORB> orb = ORB::create(); |
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for( i = 0; i < n; i++ ) |
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{ |
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string imgname = format("%s/img%d.png", path.c_str(), i+1); |
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Mat img = imread(imgname, 0); |
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imgs.push_back(img); |
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} |
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orb->detect(imgs, keypoints); |
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orb->compute(imgs, keypoints, descriptors); |
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ASSERT_EQ((int)keypoints.size(), n); |
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ASSERT_EQ((int)descriptors.size(), n); |
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for( i = 0; i < n; i++ ) |
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{ |
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EXPECT_GT((int)keypoints[i].size(), 100); |
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EXPECT_GT(descriptors[i].rows, 100); |
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} |
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} |
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class DescriptorImage : public TestWithParam<std::string> |
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{ |
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protected: |
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virtual void SetUp() { |
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pattern = GetParam(); |
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} |
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std::string pattern; |
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}; |
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TEST_P(DescriptorImage, no_crash) |
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{ |
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vector<String> fnames; |
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glob(cvtest::TS::ptr()->get_data_path() + pattern, fnames, false); |
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sort(fnames.begin(), fnames.end()); |
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Ptr<AKAZE> akaze_mldb = AKAZE::create(AKAZE::DESCRIPTOR_MLDB); |
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Ptr<AKAZE> akaze_mldb_upright = AKAZE::create(AKAZE::DESCRIPTOR_MLDB_UPRIGHT); |
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Ptr<AKAZE> akaze_mldb_256 = AKAZE::create(AKAZE::DESCRIPTOR_MLDB, 256); |
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Ptr<AKAZE> akaze_mldb_upright_256 = AKAZE::create(AKAZE::DESCRIPTOR_MLDB_UPRIGHT, 256); |
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Ptr<AKAZE> akaze_kaze = AKAZE::create(AKAZE::DESCRIPTOR_KAZE); |
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Ptr<AKAZE> akaze_kaze_upright = AKAZE::create(AKAZE::DESCRIPTOR_KAZE_UPRIGHT); |
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Ptr<ORB> orb = ORB::create(); |
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Ptr<KAZE> kaze = KAZE::create(); |
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Ptr<BRISK> brisk = BRISK::create(); |
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size_t n = fnames.size(); |
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vector<KeyPoint> keypoints; |
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Mat descriptors; |
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orb->setMaxFeatures(5000); |
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for(size_t i = 0; i < n; i++ ) |
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{ |
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printf("%d. image: %s:\n", (int)i, fnames[i].c_str()); |
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if( strstr(fnames[i].c_str(), "MP.png") != 0 ) |
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{ |
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printf("\tskip\n"); |
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continue; |
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} |
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bool checkCount = strstr(fnames[i].c_str(), "templ.png") == 0; |
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Mat img = imread(fnames[i], -1); |
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printf("\t%dx%d\n", img.cols, img.rows); |
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#define TEST_DETECTOR(name, descriptor) \ |
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keypoints.clear(); descriptors.release(); \ |
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printf("\t" name "\n"); fflush(stdout); \ |
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descriptor->detectAndCompute(img, noArray(), keypoints, descriptors); \ |
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printf("\t\t\t(%d keypoints, descriptor size = %d)\n", (int)keypoints.size(), descriptors.cols); fflush(stdout); \ |
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if (checkCount) \ |
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{ \ |
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EXPECT_GT((int)keypoints.size(), 0); \ |
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} \ |
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ASSERT_EQ(descriptors.rows, (int)keypoints.size()); |
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TEST_DETECTOR("AKAZE:MLDB", akaze_mldb); |
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TEST_DETECTOR("AKAZE:MLDB_UPRIGHT", akaze_mldb_upright); |
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TEST_DETECTOR("AKAZE:MLDB_256", akaze_mldb_256); |
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TEST_DETECTOR("AKAZE:MLDB_UPRIGHT_256", akaze_mldb_upright_256); |
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TEST_DETECTOR("AKAZE:KAZE", akaze_kaze); |
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TEST_DETECTOR("AKAZE:KAZE_UPRIGHT", akaze_kaze_upright); |
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TEST_DETECTOR("KAZE", kaze); |
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TEST_DETECTOR("ORB", orb); |
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TEST_DETECTOR("BRISK", brisk); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Features2d, DescriptorImage, |
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testing::Values( |
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"shared/lena.png", |
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"shared/box*.png", |
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"shared/fruits*.png", |
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"shared/airplane.png", |
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"shared/graffiti.png", |
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"shared/1_itseez-0001*.png", |
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"shared/pic*.png", |
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"shared/templ.png" |
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) |
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); |
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}} // namespace
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