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Open Source Computer Vision Library
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278 lines
6.8 KiB
278 lines
6.8 KiB
#include "perf_precomp.hpp" |
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using namespace std; |
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using namespace testing; |
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namespace { |
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////////////////////////////////////////////////////////////////////// |
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// SURF |
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DEF_PARAM_TEST_1(Image, string); |
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PERF_TEST_P(Image, Features2D_SURF, Values<string>("gpu/perf/aloe.jpg")) |
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{ |
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declare.time(50.0); |
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cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(img.empty()); |
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if (runOnGpu) |
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{ |
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cv::gpu::SURF_GPU d_surf; |
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cv::gpu::GpuMat d_img(img); |
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cv::gpu::GpuMat d_keypoints, d_descriptors; |
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d_surf(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
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TEST_CYCLE() |
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{ |
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d_surf(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
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} |
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} |
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else |
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{ |
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cv::SURF surf; |
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std::vector<cv::KeyPoint> keypoints; |
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cv::Mat descriptors; |
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surf(img, cv::noArray(), keypoints, descriptors); |
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TEST_CYCLE() |
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{ |
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keypoints.clear(); |
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surf(img, cv::noArray(), keypoints, descriptors); |
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} |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// FAST |
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PERF_TEST_P(Image, Features2D_FAST, Values<string>("gpu/perf/aloe.jpg")) |
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{ |
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cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(img.empty()); |
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if (runOnGpu) |
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{ |
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cv::gpu::FAST_GPU d_fast(20); |
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cv::gpu::GpuMat d_img(img); |
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cv::gpu::GpuMat d_keypoints; |
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d_fast(d_img, cv::gpu::GpuMat(), d_keypoints); |
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TEST_CYCLE() |
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{ |
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d_fast(d_img, cv::gpu::GpuMat(), d_keypoints); |
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} |
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} |
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else |
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{ |
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std::vector<cv::KeyPoint> keypoints; |
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cv::FAST(img, keypoints, 20); |
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TEST_CYCLE() |
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{ |
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keypoints.clear(); |
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cv::FAST(img, keypoints, 20); |
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} |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// ORB |
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PERF_TEST_P(Image, Features2D_ORB, Values<string>("gpu/perf/aloe.jpg")) |
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{ |
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cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE); |
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ASSERT_FALSE(img.empty()); |
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if (runOnGpu) |
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{ |
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cv::gpu::ORB_GPU d_orb(4000); |
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cv::gpu::GpuMat d_img(img); |
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cv::gpu::GpuMat d_keypoints, d_descriptors; |
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d_orb(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
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TEST_CYCLE() |
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{ |
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d_orb(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
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} |
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} |
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else |
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{ |
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cv::ORB orb(4000); |
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std::vector<cv::KeyPoint> keypoints; |
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cv::Mat descriptors; |
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orb(img, cv::noArray(), keypoints, descriptors); |
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TEST_CYCLE() |
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{ |
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keypoints.clear(); |
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orb(img, cv::noArray(), keypoints, descriptors); |
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} |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// BFMatch |
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DEF_PARAM_TEST(DescSize_Norm, int, NormType); |
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PERF_TEST_P(DescSize_Norm, Features2D_BFMatch, Combine(Values(64, 128, 256), Values(NormType(cv::NORM_L1), NormType(cv::NORM_L2), NormType(cv::NORM_HAMMING)))) |
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{ |
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declare.time(20.0); |
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int desc_size = GET_PARAM(0); |
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int normType = GET_PARAM(1); |
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int type = normType == cv::NORM_HAMMING ? CV_8U : CV_32F; |
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cv::Mat query(3000, desc_size, type); |
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fillRandom(query); |
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cv::Mat train(3000, desc_size, type); |
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fillRandom(train); |
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if (runOnGpu) |
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{ |
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cv::gpu::BFMatcher_GPU d_matcher(normType); |
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cv::gpu::GpuMat d_query(query); |
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cv::gpu::GpuMat d_train(train); |
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cv::gpu::GpuMat d_trainIdx, d_distance; |
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d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
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TEST_CYCLE() |
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{ |
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d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
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} |
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} |
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else |
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{ |
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cv::BFMatcher matcher(normType); |
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std::vector<cv::DMatch> matches; |
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matcher.match(query, train, matches); |
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TEST_CYCLE() |
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{ |
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matcher.match(query, train, matches); |
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} |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// BFKnnMatch |
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DEF_PARAM_TEST(DescSize_K_Norm, int, int, NormType); |
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PERF_TEST_P(DescSize_K_Norm, Features2D_BFKnnMatch, Combine( |
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Values(64, 128, 256), |
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Values(2, 3), |
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Values(NormType(cv::NORM_L1), NormType(cv::NORM_L2), NormType(cv::NORM_HAMMING)))) |
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{ |
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declare.time(30.0); |
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int desc_size = GET_PARAM(0); |
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int k = GET_PARAM(1); |
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int normType = GET_PARAM(2); |
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int type = normType == cv::NORM_HAMMING ? CV_8U : CV_32F; |
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cv::Mat query(3000, desc_size, type); |
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fillRandom(query); |
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cv::Mat train(3000, desc_size, type); |
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fillRandom(train); |
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if (runOnGpu) |
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{ |
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cv::gpu::BFMatcher_GPU d_matcher(normType); |
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cv::gpu::GpuMat d_query(query); |
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cv::gpu::GpuMat d_train(train); |
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cv::gpu::GpuMat d_trainIdx, d_distance, d_allDist; |
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d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, k); |
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TEST_CYCLE() |
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{ |
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d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, k); |
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} |
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} |
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else |
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{ |
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cv::BFMatcher matcher(normType); |
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std::vector< std::vector<cv::DMatch> > matches; |
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matcher.knnMatch(query, train, matches, k); |
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TEST_CYCLE() |
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{ |
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matcher.knnMatch(query, train, matches, k); |
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} |
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} |
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} |
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////////////////////////////////////////////////////////////////////// |
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// BFRadiusMatch |
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PERF_TEST_P(DescSize_Norm, Features2D_BFRadiusMatch, Combine(Values(64, 128, 256), Values(NormType(cv::NORM_L1), NormType(cv::NORM_L2), NormType(cv::NORM_HAMMING)))) |
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{ |
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declare.time(30.0); |
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int desc_size = GET_PARAM(0); |
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int normType = GET_PARAM(1); |
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int type = normType == cv::NORM_HAMMING ? CV_8U : CV_32F; |
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cv::Mat query(3000, desc_size, type); |
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fillRandom(query, 0.0, 1.0); |
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cv::Mat train(3000, desc_size, type); |
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fillRandom(train, 0.0, 1.0); |
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if (runOnGpu) |
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{ |
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cv::gpu::BFMatcher_GPU d_matcher(normType); |
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cv::gpu::GpuMat d_query(query); |
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cv::gpu::GpuMat d_train(train); |
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cv::gpu::GpuMat d_trainIdx, d_nMatches, d_distance; |
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d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, 2.0); |
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TEST_CYCLE() |
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{ |
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d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, 2.0); |
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} |
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} |
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else |
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{ |
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cv::BFMatcher matcher(normType); |
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std::vector< std::vector<cv::DMatch> > matches; |
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matcher.radiusMatch(query, train, matches, 2.0); |
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TEST_CYCLE() |
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{ |
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matcher.radiusMatch(query, train, matches, 2.0); |
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} |
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} |
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} |
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} // namespace
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