mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
312 lines
7.9 KiB
312 lines
7.9 KiB
#include "perf_precomp.hpp" |
|
|
|
using namespace std; |
|
using namespace testing; |
|
|
|
namespace { |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// SURF |
|
|
|
DEF_PARAM_TEST_1(Image, string); |
|
|
|
PERF_TEST_P(Image, Features2D_SURF, Values<string>("gpu/perf/aloe.png")) |
|
{ |
|
declare.time(50.0); |
|
|
|
cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE); |
|
ASSERT_FALSE(img.empty()); |
|
|
|
if (PERF_RUN_GPU()) |
|
{ |
|
cv::gpu::SURF_GPU d_surf; |
|
|
|
cv::gpu::GpuMat d_img(img); |
|
cv::gpu::GpuMat d_keypoints, d_descriptors; |
|
|
|
d_surf(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
|
|
|
TEST_CYCLE() |
|
{ |
|
d_surf(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
|
} |
|
|
|
GPU_SANITY_CHECK(d_descriptors, 1e-4); |
|
GPU_SANITY_CHECK_KEYPOINTS(SURF, d_keypoints); |
|
} |
|
else |
|
{ |
|
cv::SURF surf; |
|
|
|
std::vector<cv::KeyPoint> keypoints; |
|
cv::Mat descriptors; |
|
|
|
surf(img, cv::noArray(), keypoints, descriptors); |
|
|
|
TEST_CYCLE() |
|
{ |
|
keypoints.clear(); |
|
surf(img, cv::noArray(), keypoints, descriptors); |
|
} |
|
|
|
SANITY_CHECK_KEYPOINTS(keypoints); |
|
SANITY_CHECK(descriptors, 1e-4); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// FAST |
|
|
|
PERF_TEST_P(Image, Features2D_FAST, Values<string>("gpu/perf/aloe.png")) |
|
{ |
|
cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE); |
|
ASSERT_FALSE(img.empty()); |
|
|
|
if (PERF_RUN_GPU()) |
|
{ |
|
cv::gpu::FAST_GPU d_fast(20); |
|
|
|
cv::gpu::GpuMat d_img(img); |
|
cv::gpu::GpuMat d_keypoints; |
|
|
|
d_fast(d_img, cv::gpu::GpuMat(), d_keypoints); |
|
|
|
TEST_CYCLE() |
|
{ |
|
d_fast(d_img, cv::gpu::GpuMat(), d_keypoints); |
|
} |
|
|
|
GPU_SANITY_CHECK_RESPONSE(FAST, d_keypoints); |
|
} |
|
else |
|
{ |
|
std::vector<cv::KeyPoint> keypoints; |
|
|
|
cv::FAST(img, keypoints, 20); |
|
|
|
TEST_CYCLE() |
|
{ |
|
keypoints.clear(); |
|
cv::FAST(img, keypoints, 20); |
|
} |
|
|
|
SANITY_CHECK_KEYPOINTS(keypoints); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// ORB |
|
|
|
PERF_TEST_P(Image, Features2D_ORB, Values<string>("gpu/perf/aloe.png")) |
|
{ |
|
cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE); |
|
ASSERT_FALSE(img.empty()); |
|
|
|
if (PERF_RUN_GPU()) |
|
{ |
|
cv::gpu::ORB_GPU d_orb(4000); |
|
|
|
cv::gpu::GpuMat d_img(img); |
|
cv::gpu::GpuMat d_keypoints, d_descriptors; |
|
|
|
d_orb(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
|
|
|
TEST_CYCLE() |
|
{ |
|
d_orb(d_img, cv::gpu::GpuMat(), d_keypoints, d_descriptors); |
|
} |
|
|
|
GPU_SANITY_CHECK_KEYPOINTS(ORB, d_keypoints); |
|
GPU_SANITY_CHECK(d_descriptors); |
|
} |
|
else |
|
{ |
|
cv::ORB orb(4000); |
|
|
|
std::vector<cv::KeyPoint> keypoints; |
|
cv::Mat descriptors; |
|
|
|
orb(img, cv::noArray(), keypoints, descriptors); |
|
|
|
TEST_CYCLE() |
|
{ |
|
keypoints.clear(); |
|
orb(img, cv::noArray(), keypoints, descriptors); |
|
} |
|
|
|
SANITY_CHECK_KEYPOINTS(keypoints); |
|
SANITY_CHECK(descriptors); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// BFMatch |
|
|
|
DEF_PARAM_TEST(DescSize_Norm, int, NormType); |
|
|
|
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)))) |
|
{ |
|
declare.time(20.0); |
|
|
|
int desc_size = GET_PARAM(0); |
|
int normType = GET_PARAM(1); |
|
|
|
int type = normType == cv::NORM_HAMMING ? CV_8U : CV_32F; |
|
|
|
cv::Mat query(3000, desc_size, type); |
|
fillRandom(query); |
|
|
|
cv::Mat train(3000, desc_size, type); |
|
fillRandom(train); |
|
|
|
if (PERF_RUN_GPU()) |
|
{ |
|
cv::gpu::BruteForceMatcher_GPU_base d_matcher( |
|
cv::gpu::BruteForceMatcher_GPU_base::DistType((normType -2) / 2)); |
|
|
|
cv::gpu::GpuMat d_query(query); |
|
cv::gpu::GpuMat d_train(train); |
|
cv::gpu::GpuMat d_trainIdx, d_distance; |
|
|
|
d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
|
|
|
TEST_CYCLE() |
|
{ |
|
d_matcher.matchSingle(d_query, d_train, d_trainIdx, d_distance); |
|
} |
|
|
|
GPU_SANITY_CHECK(d_trainIdx); |
|
GPU_SANITY_CHECK(d_distance); |
|
} |
|
else |
|
{ |
|
cv::BFMatcher matcher(normType); |
|
|
|
std::vector<cv::DMatch> matches; |
|
|
|
matcher.match(query, train, matches); |
|
|
|
TEST_CYCLE() |
|
{ |
|
matcher.match(query, train, matches); |
|
} |
|
|
|
SANITY_CHECK(matches); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// BFKnnMatch |
|
|
|
DEF_PARAM_TEST(DescSize_K_Norm, int, int, NormType); |
|
|
|
PERF_TEST_P(DescSize_K_Norm, Features2D_BFKnnMatch, Combine( |
|
Values(64, 128, 256), |
|
Values(2, 3), |
|
Values(NormType(cv::NORM_L1), NormType(cv::NORM_L2), NormType(cv::NORM_HAMMING)))) |
|
{ |
|
declare.time(30.0); |
|
|
|
int desc_size = GET_PARAM(0); |
|
int k = GET_PARAM(1); |
|
int normType = GET_PARAM(2); |
|
|
|
int type = normType == cv::NORM_HAMMING ? CV_8U : CV_32F; |
|
|
|
cv::Mat query(3000, desc_size, type); |
|
fillRandom(query); |
|
|
|
cv::Mat train(3000, desc_size, type); |
|
fillRandom(train); |
|
|
|
if (PERF_RUN_GPU()) |
|
{ |
|
cv::gpu::BruteForceMatcher_GPU_base d_matcher( |
|
cv::gpu::BruteForceMatcher_GPU_base::DistType((normType -2) / 2)); |
|
|
|
cv::gpu::GpuMat d_query(query); |
|
cv::gpu::GpuMat d_train(train); |
|
cv::gpu::GpuMat d_trainIdx, d_distance, d_allDist; |
|
|
|
d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, k); |
|
|
|
TEST_CYCLE() |
|
{ |
|
d_matcher.knnMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_allDist, k); |
|
} |
|
|
|
GPU_SANITY_CHECK(d_trainIdx); |
|
GPU_SANITY_CHECK(d_distance); |
|
} |
|
else |
|
{ |
|
cv::BFMatcher matcher(normType); |
|
|
|
std::vector< std::vector<cv::DMatch> > matches; |
|
|
|
matcher.knnMatch(query, train, matches, k); |
|
|
|
TEST_CYCLE() |
|
{ |
|
matcher.knnMatch(query, train, matches, k); |
|
} |
|
|
|
SANITY_CHECK(matches); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// BFRadiusMatch |
|
|
|
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)))) |
|
{ |
|
declare.time(30.0); |
|
|
|
int desc_size = GET_PARAM(0); |
|
int normType = GET_PARAM(1); |
|
|
|
int type = normType == cv::NORM_HAMMING ? CV_8U : CV_32F; |
|
|
|
cv::Mat query(3000, desc_size, type); |
|
fillRandom(query, 0.0, 1.0); |
|
|
|
cv::Mat train(3000, desc_size, type); |
|
fillRandom(train, 0.0, 1.0); |
|
|
|
if (PERF_RUN_GPU()) |
|
{ |
|
cv::gpu::BruteForceMatcher_GPU_base d_matcher( |
|
cv::gpu::BruteForceMatcher_GPU_base::DistType((normType -2) / 2)); |
|
|
|
cv::gpu::GpuMat d_query(query); |
|
cv::gpu::GpuMat d_train(train); |
|
cv::gpu::GpuMat d_trainIdx, d_nMatches, d_distance; |
|
|
|
d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, 2.0); |
|
|
|
TEST_CYCLE() |
|
{ |
|
d_matcher.radiusMatchSingle(d_query, d_train, d_trainIdx, d_distance, d_nMatches, 2.0); |
|
} |
|
|
|
GPU_SANITY_CHECK(d_trainIdx); |
|
GPU_SANITY_CHECK(d_distance); |
|
} |
|
else |
|
{ |
|
cv::BFMatcher matcher(normType); |
|
|
|
std::vector< std::vector<cv::DMatch> > matches; |
|
|
|
matcher.radiusMatch(query, train, matches, 2.0); |
|
|
|
TEST_CYCLE() |
|
{ |
|
matcher.radiusMatch(query, train, matches, 2.0); |
|
} |
|
|
|
SANITY_CHECK(matches); |
|
} |
|
} |
|
|
|
} // namespace
|
|
|