#include #define HAVE_CUDA 1 #include #include #include #include #include #include #include static void printOsInfo() { #if defined _WIN32 # if defined _WIN64 printf("[----------]\n[ GPU INFO ] \tRun on OS Windows x64.\n[----------]\n"); fflush(stdout); # else printf("[----------]\n[ GPU INFO ] \tRun on OS Windows x32.\n[----------]\n"); fflush(stdout); # endif #elif defined linux # if defined _LP64 printf("[----------]\n[ GPU INFO ] \tRun on OS Linux x64.\n[----------]\n"); fflush(stdout); # else printf("[----------]\n[ GPU INFO ] \tRun on OS Linux x32.\n[----------]\n"); fflush(stdout); # endif #elif defined __APPLE__ # if defined _LP64 printf("[----------]\n[ GPU INFO ] \tRun on OS Apple x64.\n[----------]\n"); fflush(stdout); # else printf("[----------]\n[ GPU INFO ] \tRun on OS Apple x32.\n[----------]\n"); fflush(stdout); # endif #endif } static void printCudaInfo() { const int deviceCount = cv::gpu::getCudaEnabledDeviceCount(); printf("[----------]\n"); fflush(stdout); printf("[ GPU INFO ] \tCUDA device count:: %d.\n", deviceCount); fflush(stdout); printf("[----------]\n"); fflush(stdout); for (int i = 0; i < deviceCount; ++i) { cv::gpu::DeviceInfo info(i); printf("[----------]\n"); fflush(stdout); printf("[ DEVICE ] \t# %d %s.\n", i, info.name().c_str()); fflush(stdout); printf("[ ] \tCompute capability: %d.%d\n", info.majorVersion(), info.minorVersion()); fflush(stdout); printf("[ ] \tMulti Processor Count: %d\n", info.multiProcessorCount()); fflush(stdout); printf("[ ] \tTotal memory: %d Mb\n", static_cast(static_cast(info.totalMemory() / 1024.0) / 1024.0)); fflush(stdout); printf("[ ] \tFree memory: %d Mb\n", static_cast(static_cast(info.freeMemory() / 1024.0) / 1024.0)); fflush(stdout); if (!info.isCompatible()) printf("[ GPU INFO ] \tThis device is NOT compatible with current GPU module build\n"); printf("[----------]\n"); fflush(stdout); } } int main(int argc, char* argv[]) { printOsInfo(); printCudaInfo(); perf::Regression::Init("nv_perf_test"); perf::TestBase::Init(argc, argv); testing::InitGoogleTest(&argc, argv); return RUN_ALL_TESTS(); } #define DEF_PARAM_TEST(name, ...) typedef ::perf::TestBaseWithParam< std::tr1::tuple< __VA_ARGS__ > > name #define DEF_PARAM_TEST_1(name, param_type) typedef ::perf::TestBaseWithParam< param_type > name ////////////////////////////////////////////////////////// // HoughLinesP DEF_PARAM_TEST_1(Image, std::string); PERF_TEST_P(Image, HoughLinesP, testing::Values(std::string("im1_1280x800.jpg"))) { declare.time(30.0); std::string fileName = GetParam(); const double rho = 1.0; const double theta = 1.0; const int threshold = 40; const int minLineLenght = 20; const int maxLineGap = 5; cv::Mat image = cv::imread(fileName, cv::IMREAD_GRAYSCALE); if (PERF_RUN_GPU()) { cv::gpu::GpuMat d_image(image); cv::gpu::GpuMat d_lines; cv::gpu::HoughLinesBuf d_buf; cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap); TEST_CYCLE() { cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap); } } else { cv::Mat mask; cv::Canny(image, mask, 50, 100); std::vector lines; cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap); TEST_CYCLE() { cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap); } } SANITY_CHECK(0); } ////////////////////////////////////////////////////////// // GoodFeaturesToTrack DEF_PARAM_TEST(Image_Depth, std::string, perf::MatDepth); PERF_TEST_P(Image_Depth, GoodFeaturesToTrack, testing::Combine( testing::Values(std::string("im1_1280x800.jpg")), testing::Values(CV_8U, CV_16U) )) { declare.time(60); const std::string fileName = std::tr1::get<0>(GetParam()); const int depth = std::tr1::get<1>(GetParam()); const int maxCorners = 5000; const double qualityLevel = 0.05; const int minDistance = 5; const int blockSize = 3; const bool useHarrisDetector = true; const double k = 0.05; cv::Mat src = cv::imread(fileName, cv::IMREAD_GRAYSCALE); if (src.empty()) FAIL() << "Unable to load source image [" << fileName << "]"; if (depth != CV_8U) src.convertTo(src, depth); cv::Mat mask(src.size(), CV_8UC1, cv::Scalar::all(1)); mask(cv::Rect(0, 0, 100, 100)).setTo(cv::Scalar::all(0)); if (PERF_RUN_GPU()) { cv::gpu::GoodFeaturesToTrackDetector_GPU d_detector(maxCorners, qualityLevel, minDistance, blockSize, useHarrisDetector, k); cv::gpu::GpuMat d_src(src); cv::gpu::GpuMat d_mask(mask); cv::gpu::GpuMat d_pts; d_detector(d_src, d_pts, d_mask); TEST_CYCLE() { d_detector(d_src, d_pts, d_mask); } } else { if (depth != CV_8U) FAIL() << "Unsupported depth"; cv::Mat pts; cv::goodFeaturesToTrack(src, pts, maxCorners, qualityLevel, minDistance, mask, blockSize, useHarrisDetector, k); TEST_CYCLE() { cv::goodFeaturesToTrack(src, pts, maxCorners, qualityLevel, minDistance, mask, blockSize, useHarrisDetector, k); } } SANITY_CHECK(0); } ////////////////////////////////////////////////////////// // OpticalFlowPyrLKSparse typedef std::pair string_pair; DEF_PARAM_TEST(ImagePair_Depth_GraySource, string_pair, perf::MatDepth, bool); PERF_TEST_P(ImagePair_Depth_GraySource, OpticalFlowPyrLKSparse, testing::Combine( testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), testing::Values(CV_8U, CV_16U), testing::Bool() )) { declare.time(60); const string_pair fileNames = std::tr1::get<0>(GetParam()); const int depth = std::tr1::get<1>(GetParam()); const bool graySource = std::tr1::get<2>(GetParam()); // PyrLK params const cv::Size winSize(15, 15); const int maxLevel = 5; const cv::TermCriteria criteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 30, 0.01); // GoodFeaturesToTrack params const int maxCorners = 5000; const double qualityLevel = 0.05; const int minDistance = 5; const int blockSize = 3; const bool useHarrisDetector = true; const double k = 0.05; cv::Mat src1 = cv::imread(fileNames.first, graySource ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); if (src1.empty()) FAIL() << "Unable to load source image [" << fileNames.first << "]"; cv::Mat src2 = cv::imread(fileNames.second, graySource ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); if (src2.empty()) FAIL() << "Unable to load source image [" << fileNames.second << "]"; cv::Mat gray_src; if (graySource) gray_src = src1; else cv::cvtColor(src1, gray_src, cv::COLOR_BGR2GRAY); cv::Mat pts; cv::goodFeaturesToTrack(gray_src, pts, maxCorners, qualityLevel, minDistance, cv::noArray(), blockSize, useHarrisDetector, k); if (depth != CV_8U) { src1.convertTo(src1, depth); src2.convertTo(src2, depth); } if (PERF_RUN_GPU()) { cv::gpu::GpuMat d_src1(src1); cv::gpu::GpuMat d_src2(src2); cv::gpu::GpuMat d_pts(pts.reshape(2, 1)); cv::gpu::GpuMat d_nextPts; cv::gpu::GpuMat d_status; cv::gpu::PyrLKOpticalFlow d_pyrLK; d_pyrLK.winSize = winSize; d_pyrLK.maxLevel = maxLevel; d_pyrLK.iters = criteria.maxCount; d_pyrLK.useInitialFlow = false; d_pyrLK.sparse(d_src1, d_src2, d_pts, d_nextPts, d_status); TEST_CYCLE() { d_pyrLK.sparse(d_src1, d_src2, d_pts, d_nextPts, d_status); } } else { if (depth != CV_8U) FAIL() << "Unsupported depth"; cv::Mat nextPts; cv::Mat status; cv::calcOpticalFlowPyrLK(src1, src2, pts, nextPts, status, cv::noArray(), winSize, maxLevel, criteria); TEST_CYCLE() { cv::calcOpticalFlowPyrLK(src1, src2, pts, nextPts, status, cv::noArray(), winSize, maxLevel, criteria); } } SANITY_CHECK(0); } ////////////////////////////////////////////////////////// // OpticalFlowFarneback DEF_PARAM_TEST(ImagePair_Depth, string_pair, perf::MatDepth); PERF_TEST_P(ImagePair_Depth, OpticalFlowFarneback, testing::Combine( testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), testing::Values(CV_8U, CV_16U) )) { declare.time(500); const string_pair fileNames = std::tr1::get<0>(GetParam()); const int depth = std::tr1::get<1>(GetParam()); const double pyrScale = 0.5; const int numLevels = 6; const int winSize = 7; const int numIters = 15; const int polyN = 7; const double polySigma = 1.5; const int flags = cv::OPTFLOW_USE_INITIAL_FLOW; cv::Mat src1 = cv::imread(fileNames.first, cv::IMREAD_GRAYSCALE); if (src1.empty()) FAIL() << "Unable to load source image [" << fileNames.first << "]"; cv::Mat src2 = cv::imread(fileNames.second, cv::IMREAD_GRAYSCALE); if (src2.empty()) FAIL() << "Unable to load source image [" << fileNames.second << "]"; if (depth != CV_8U) { src1.convertTo(src1, depth); src2.convertTo(src2, depth); } if (PERF_RUN_GPU()) { cv::gpu::GpuMat d_src1(src1); cv::gpu::GpuMat d_src2(src2); cv::gpu::GpuMat d_u(src1.size(), CV_32FC1, cv::Scalar::all(0)); cv::gpu::GpuMat d_v(src1.size(), CV_32FC1, cv::Scalar::all(0)); cv::gpu::FarnebackOpticalFlow d_farneback; d_farneback.pyrScale = pyrScale; d_farneback.numLevels = numLevels; d_farneback.winSize = winSize; d_farneback.numIters = numIters; d_farneback.polyN = polyN; d_farneback.polySigma = polySigma; d_farneback.flags = flags; d_farneback(d_src1, d_src2, d_u, d_v); TEST_CYCLE_N(10) { d_farneback(d_src1, d_src2, d_u, d_v); } } else { if (depth != CV_8U) FAIL() << "Unsupported depth"; cv::Mat flow(src1.size(), CV_32FC2, cv::Scalar::all(0)); cv::calcOpticalFlowFarneback(src1, src2, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags); TEST_CYCLE_N(10) { cv::calcOpticalFlowFarneback(src1, src2, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags); } } SANITY_CHECK(0); } ////////////////////////////////////////////////////////// // OpticalFlowBM void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr, cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious, cv::Mat& velx, cv::Mat& vely) { cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height); velx.create(sz, CV_32FC1); vely.create(sz, CV_32FC1); CvMat cvprev = prev; CvMat cvcurr = curr; CvMat cvvelx = velx; CvMat cvvely = vely; cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely); } DEF_PARAM_TEST(ImagePair_BlockSize_ShiftSize_MaxRange, string_pair, cv::Size, cv::Size, cv::Size); PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, OpticalFlowBM, testing::Combine( testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), testing::Values(cv::Size(16, 16)), testing::Values(cv::Size(2, 2)), testing::Values(cv::Size(16, 16)) )) { declare.time(1000); const string_pair fileNames = std::tr1::get<0>(GetParam()); const cv::Size block_size = std::tr1::get<1>(GetParam()); const cv::Size shift_size = std::tr1::get<2>(GetParam()); const cv::Size max_range = std::tr1::get<3>(GetParam()); cv::Mat src1 = cv::imread(fileNames.first, cv::IMREAD_GRAYSCALE); if (src1.empty()) FAIL() << "Unable to load source image [" << fileNames.first << "]"; cv::Mat src2 = cv::imread(fileNames.second, cv::IMREAD_GRAYSCALE); if (src2.empty()) FAIL() << "Unable to load source image [" << fileNames.second << "]"; if (PERF_RUN_GPU()) { cv::gpu::GpuMat d_src1(src1); cv::gpu::GpuMat d_src2(src2); cv::gpu::GpuMat d_velx, d_vely, buf; cv::gpu::calcOpticalFlowBM(d_src1, d_src2, block_size, shift_size, max_range, false, d_velx, d_vely, buf); TEST_CYCLE_N(10) { cv::gpu::calcOpticalFlowBM(d_src1, d_src2, block_size, shift_size, max_range, false, d_velx, d_vely, buf); } } else { cv::Mat velx, vely; calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); TEST_CYCLE_N(10) { calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); } } SANITY_CHECK(0); } PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, FastOpticalFlowBM, testing::Combine( testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), testing::Values(cv::Size(16, 16)), testing::Values(cv::Size(1, 1)), testing::Values(cv::Size(16, 16)) )) { declare.time(1000); const string_pair fileNames = std::tr1::get<0>(GetParam()); const cv::Size block_size = std::tr1::get<1>(GetParam()); const cv::Size shift_size = std::tr1::get<2>(GetParam()); const cv::Size max_range = std::tr1::get<3>(GetParam()); cv::Mat src1 = cv::imread(fileNames.first, cv::IMREAD_GRAYSCALE); if (src1.empty()) FAIL() << "Unable to load source image [" << fileNames.first << "]"; cv::Mat src2 = cv::imread(fileNames.second, cv::IMREAD_GRAYSCALE); if (src2.empty()) FAIL() << "Unable to load source image [" << fileNames.second << "]"; if (PERF_RUN_GPU()) { cv::gpu::GpuMat d_src1(src1); cv::gpu::GpuMat d_src2(src2); cv::gpu::GpuMat d_velx, d_vely; cv::gpu::FastOpticalFlowBM fastBM; fastBM(d_src1, d_src2, d_velx, d_vely, max_range.width, block_size.width); TEST_CYCLE_N(10) { fastBM(d_src1, d_src2, d_velx, d_vely, max_range.width, block_size.width); } } else { cv::Mat velx, vely; calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); TEST_CYCLE_N(10) { calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); } } SANITY_CHECK(0); }