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Open Source Computer Vision Library
https://opencv.org/
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489 lines
15 KiB
489 lines
15 KiB
#include <cstdio> |
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#ifdef HAVE_CVCONFIG_H |
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#include "cvconfig.h" |
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#endif |
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#include "opencv2/core.hpp" |
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#include "opencv2/gpu.hpp" |
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#include "opencv2/highgui.hpp" |
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#include "opencv2/video.hpp" |
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#include "opencv2/legacy.hpp" |
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#include "opencv2/ts.hpp" |
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static void printOsInfo() |
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{ |
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#if defined _WIN32 |
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# if defined _WIN64 |
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printf("[----------]\n[ GPU INFO ] \tRun on OS Windows x64.\n[----------]\n"); fflush(stdout); |
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# else |
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printf("[----------]\n[ GPU INFO ] \tRun on OS Windows x32.\n[----------]\n"); fflush(stdout); |
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# endif |
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#elif defined linux |
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# if defined _LP64 |
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printf("[----------]\n[ GPU INFO ] \tRun on OS Linux x64.\n[----------]\n"); fflush(stdout); |
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# else |
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printf("[----------]\n[ GPU INFO ] \tRun on OS Linux x32.\n[----------]\n"); fflush(stdout); |
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# endif |
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#elif defined __APPLE__ |
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# if defined _LP64 |
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printf("[----------]\n[ GPU INFO ] \tRun on OS Apple x64.\n[----------]\n"); fflush(stdout); |
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# else |
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printf("[----------]\n[ GPU INFO ] \tRun on OS Apple x32.\n[----------]\n"); fflush(stdout); |
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# endif |
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#endif |
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} |
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static void printCudaInfo() |
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{ |
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const int deviceCount = cv::gpu::getCudaEnabledDeviceCount(); |
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printf("[----------]\n"); fflush(stdout); |
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printf("[ GPU INFO ] \tCUDA device count:: %d.\n", deviceCount); fflush(stdout); |
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printf("[----------]\n"); fflush(stdout); |
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for (int i = 0; i < deviceCount; ++i) |
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{ |
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cv::gpu::DeviceInfo info(i); |
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printf("[----------]\n"); fflush(stdout); |
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printf("[ DEVICE ] \t# %d %s.\n", i, info.name().c_str()); fflush(stdout); |
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printf("[ ] \tCompute capability: %d.%d\n", info.majorVersion(), info.minorVersion()); fflush(stdout); |
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printf("[ ] \tMulti Processor Count: %d\n", info.multiProcessorCount()); fflush(stdout); |
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printf("[ ] \tTotal memory: %d Mb\n", static_cast<int>(static_cast<int>(info.totalMemory() / 1024.0) / 1024.0)); fflush(stdout); |
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printf("[ ] \tFree memory: %d Mb\n", static_cast<int>(static_cast<int>(info.freeMemory() / 1024.0) / 1024.0)); fflush(stdout); |
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if (!info.isCompatible()) |
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printf("[ GPU INFO ] \tThis device is NOT compatible with current GPU module build\n"); |
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printf("[----------]\n"); fflush(stdout); |
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} |
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} |
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int main(int argc, char* argv[]) |
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{ |
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printOsInfo(); |
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printCudaInfo(); |
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perf::Regression::Init("nv_perf_test"); |
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perf::TestBase::Init(argc, argv); |
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testing::InitGoogleTest(&argc, argv); |
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return RUN_ALL_TESTS(); |
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} |
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#define DEF_PARAM_TEST(name, ...) typedef ::perf::TestBaseWithParam< std::tr1::tuple< __VA_ARGS__ > > name |
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#define DEF_PARAM_TEST_1(name, param_type) typedef ::perf::TestBaseWithParam< param_type > name |
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////////////////////////////////////////////////////////// |
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// HoughLinesP |
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DEF_PARAM_TEST_1(Image, std::string); |
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PERF_TEST_P(Image, HoughLinesP, testing::Values(std::string("im1_1280x800.jpg"))) |
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{ |
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declare.time(30.0); |
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std::string fileName = GetParam(); |
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const float rho = 1.f; |
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const float theta = 1.f; |
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const int threshold = 40; |
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const int minLineLenght = 20; |
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const int maxLineGap = 5; |
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cv::Mat image = cv::imread(fileName, cv::IMREAD_GRAYSCALE); |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::GpuMat d_image(image); |
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cv::gpu::GpuMat d_lines; |
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cv::gpu::HoughLinesBuf d_buf; |
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cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap); |
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TEST_CYCLE() |
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{ |
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cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap); |
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} |
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} |
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else |
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{ |
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cv::Mat mask; |
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cv::Canny(image, mask, 50, 100); |
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std::vector<cv::Vec4i> lines; |
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cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap); |
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TEST_CYCLE() |
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{ |
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cv::HoughLinesP(mask, lines, rho, theta, threshold, minLineLenght, maxLineGap); |
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} |
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} |
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SANITY_CHECK(0); |
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} |
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////////////////////////////////////////////////////////// |
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// GoodFeaturesToTrack |
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DEF_PARAM_TEST(Image_Depth, std::string, perf::MatDepth); |
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PERF_TEST_P(Image_Depth, GoodFeaturesToTrack, |
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testing::Combine( |
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testing::Values(std::string("im1_1280x800.jpg")), |
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testing::Values(CV_8U, CV_16U) |
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)) |
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{ |
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declare.time(60); |
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const std::string fileName = std::tr1::get<0>(GetParam()); |
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const int depth = std::tr1::get<1>(GetParam()); |
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const int maxCorners = 5000; |
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const double qualityLevel = 0.05; |
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const int minDistance = 5; |
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const int blockSize = 3; |
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const bool useHarrisDetector = true; |
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const double k = 0.05; |
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cv::Mat src = cv::imread(fileName, cv::IMREAD_GRAYSCALE); |
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if (src.empty()) |
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FAIL() << "Unable to load source image [" << fileName << "]"; |
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if (depth != CV_8U) |
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src.convertTo(src, depth); |
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cv::Mat mask(src.size(), CV_8UC1, cv::Scalar::all(1)); |
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mask(cv::Rect(0, 0, 100, 100)).setTo(cv::Scalar::all(0)); |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::GoodFeaturesToTrackDetector_GPU d_detector(maxCorners, qualityLevel, minDistance, blockSize, useHarrisDetector, k); |
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cv::gpu::GpuMat d_src(src); |
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cv::gpu::GpuMat d_mask(mask); |
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cv::gpu::GpuMat d_pts; |
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d_detector(d_src, d_pts, d_mask); |
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TEST_CYCLE() |
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{ |
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d_detector(d_src, d_pts, d_mask); |
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} |
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} |
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else |
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{ |
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if (depth != CV_8U) |
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FAIL() << "Unsupported depth"; |
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cv::Mat pts; |
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cv::goodFeaturesToTrack(src, pts, maxCorners, qualityLevel, minDistance, mask, blockSize, useHarrisDetector, k); |
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TEST_CYCLE() |
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{ |
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cv::goodFeaturesToTrack(src, pts, maxCorners, qualityLevel, minDistance, mask, blockSize, useHarrisDetector, k); |
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} |
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} |
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SANITY_CHECK(0); |
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} |
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////////////////////////////////////////////////////////// |
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// OpticalFlowPyrLKSparse |
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typedef std::pair<std::string, std::string> string_pair; |
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DEF_PARAM_TEST(ImagePair_Depth_GraySource, string_pair, perf::MatDepth, bool); |
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PERF_TEST_P(ImagePair_Depth_GraySource, OpticalFlowPyrLKSparse, |
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testing::Combine( |
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testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), |
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testing::Values(CV_8U, CV_16U), |
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testing::Bool() |
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)) |
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{ |
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declare.time(60); |
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const string_pair fileNames = std::tr1::get<0>(GetParam()); |
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const int depth = std::tr1::get<1>(GetParam()); |
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const bool graySource = std::tr1::get<2>(GetParam()); |
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// PyrLK params |
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const cv::Size winSize(15, 15); |
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const int maxLevel = 5; |
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const cv::TermCriteria criteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 30, 0.01); |
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// GoodFeaturesToTrack params |
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const int maxCorners = 5000; |
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const double qualityLevel = 0.05; |
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const int minDistance = 5; |
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const int blockSize = 3; |
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const bool useHarrisDetector = true; |
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const double k = 0.05; |
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cv::Mat src1 = cv::imread(fileNames.first, graySource ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); |
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if (src1.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.first << "]"; |
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cv::Mat src2 = cv::imread(fileNames.second, graySource ? cv::IMREAD_GRAYSCALE : cv::IMREAD_COLOR); |
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if (src2.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.second << "]"; |
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cv::Mat gray_src; |
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if (graySource) |
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gray_src = src1; |
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else |
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cv::cvtColor(src1, gray_src, cv::COLOR_BGR2GRAY); |
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cv::Mat pts; |
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cv::goodFeaturesToTrack(gray_src, pts, maxCorners, qualityLevel, minDistance, cv::noArray(), blockSize, useHarrisDetector, k); |
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if (depth != CV_8U) |
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{ |
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src1.convertTo(src1, depth); |
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src2.convertTo(src2, depth); |
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} |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::GpuMat d_src1(src1); |
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cv::gpu::GpuMat d_src2(src2); |
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cv::gpu::GpuMat d_pts(pts.reshape(2, 1)); |
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cv::gpu::GpuMat d_nextPts; |
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cv::gpu::GpuMat d_status; |
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cv::gpu::PyrLKOpticalFlow d_pyrLK; |
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d_pyrLK.winSize = winSize; |
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d_pyrLK.maxLevel = maxLevel; |
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d_pyrLK.iters = criteria.maxCount; |
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d_pyrLK.useInitialFlow = false; |
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d_pyrLK.sparse(d_src1, d_src2, d_pts, d_nextPts, d_status); |
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TEST_CYCLE() |
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{ |
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d_pyrLK.sparse(d_src1, d_src2, d_pts, d_nextPts, d_status); |
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} |
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} |
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else |
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{ |
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if (depth != CV_8U) |
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FAIL() << "Unsupported depth"; |
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cv::Mat nextPts; |
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cv::Mat status; |
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cv::calcOpticalFlowPyrLK(src1, src2, pts, nextPts, status, cv::noArray(), winSize, maxLevel, criteria); |
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TEST_CYCLE() |
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{ |
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cv::calcOpticalFlowPyrLK(src1, src2, pts, nextPts, status, cv::noArray(), winSize, maxLevel, criteria); |
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} |
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} |
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SANITY_CHECK(0); |
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} |
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////////////////////////////////////////////////////////// |
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// OpticalFlowFarneback |
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DEF_PARAM_TEST(ImagePair_Depth, string_pair, perf::MatDepth); |
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PERF_TEST_P(ImagePair_Depth, OpticalFlowFarneback, |
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testing::Combine( |
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testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), |
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testing::Values(CV_8U, CV_16U) |
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)) |
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{ |
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declare.time(500); |
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const string_pair fileNames = std::tr1::get<0>(GetParam()); |
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const int depth = std::tr1::get<1>(GetParam()); |
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const double pyrScale = 0.5; |
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const int numLevels = 6; |
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const int winSize = 7; |
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const int numIters = 15; |
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const int polyN = 7; |
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const double polySigma = 1.5; |
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const int flags = cv::OPTFLOW_USE_INITIAL_FLOW; |
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cv::Mat src1 = cv::imread(fileNames.first, cv::IMREAD_GRAYSCALE); |
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if (src1.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.first << "]"; |
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cv::Mat src2 = cv::imread(fileNames.second, cv::IMREAD_GRAYSCALE); |
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if (src2.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.second << "]"; |
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if (depth != CV_8U) |
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{ |
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src1.convertTo(src1, depth); |
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src2.convertTo(src2, depth); |
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} |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::GpuMat d_src1(src1); |
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cv::gpu::GpuMat d_src2(src2); |
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cv::gpu::GpuMat d_u(src1.size(), CV_32FC1, cv::Scalar::all(0)); |
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cv::gpu::GpuMat d_v(src1.size(), CV_32FC1, cv::Scalar::all(0)); |
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cv::gpu::FarnebackOpticalFlow d_farneback; |
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d_farneback.pyrScale = pyrScale; |
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d_farneback.numLevels = numLevels; |
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d_farneback.winSize = winSize; |
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d_farneback.numIters = numIters; |
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d_farneback.polyN = polyN; |
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d_farneback.polySigma = polySigma; |
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d_farneback.flags = flags; |
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d_farneback(d_src1, d_src2, d_u, d_v); |
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TEST_CYCLE_N(10) |
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{ |
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d_farneback(d_src1, d_src2, d_u, d_v); |
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} |
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} |
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else |
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{ |
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if (depth != CV_8U) |
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FAIL() << "Unsupported depth"; |
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cv::Mat flow(src1.size(), CV_32FC2, cv::Scalar::all(0)); |
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cv::calcOpticalFlowFarneback(src1, src2, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags); |
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TEST_CYCLE_N(10) |
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{ |
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cv::calcOpticalFlowFarneback(src1, src2, flow, pyrScale, numLevels, winSize, numIters, polyN, polySigma, flags); |
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} |
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} |
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SANITY_CHECK(0); |
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} |
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////////////////////////////////////////////////////////// |
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// OpticalFlowBM |
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void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr, |
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cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious, |
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cv::Mat& velx, cv::Mat& vely) |
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{ |
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cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height); |
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velx.create(sz, CV_32FC1); |
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vely.create(sz, CV_32FC1); |
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CvMat cvprev = prev; |
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CvMat cvcurr = curr; |
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CvMat cvvelx = velx; |
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CvMat cvvely = vely; |
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cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely); |
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} |
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DEF_PARAM_TEST(ImagePair_BlockSize_ShiftSize_MaxRange, string_pair, cv::Size, cv::Size, cv::Size); |
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PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, OpticalFlowBM, |
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testing::Combine( |
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testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), |
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testing::Values(cv::Size(16, 16)), |
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testing::Values(cv::Size(2, 2)), |
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testing::Values(cv::Size(16, 16)) |
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)) |
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{ |
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declare.time(3000); |
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const string_pair fileNames = std::tr1::get<0>(GetParam()); |
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const cv::Size block_size = std::tr1::get<1>(GetParam()); |
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const cv::Size shift_size = std::tr1::get<2>(GetParam()); |
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const cv::Size max_range = std::tr1::get<3>(GetParam()); |
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cv::Mat src1 = cv::imread(fileNames.first, cv::IMREAD_GRAYSCALE); |
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if (src1.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.first << "]"; |
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cv::Mat src2 = cv::imread(fileNames.second, cv::IMREAD_GRAYSCALE); |
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if (src2.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.second << "]"; |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::GpuMat d_src1(src1); |
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cv::gpu::GpuMat d_src2(src2); |
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cv::gpu::GpuMat d_velx, d_vely, buf; |
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cv::gpu::calcOpticalFlowBM(d_src1, d_src2, block_size, shift_size, max_range, false, d_velx, d_vely, buf); |
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TEST_CYCLE_N(10) |
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{ |
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cv::gpu::calcOpticalFlowBM(d_src1, d_src2, block_size, shift_size, max_range, false, d_velx, d_vely, buf); |
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} |
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} |
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else |
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{ |
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cv::Mat velx, vely; |
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calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); |
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TEST_CYCLE_N(10) |
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{ |
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calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); |
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} |
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} |
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SANITY_CHECK(0); |
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} |
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PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, FastOpticalFlowBM, |
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testing::Combine( |
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testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")), |
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testing::Values(cv::Size(16, 16)), |
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testing::Values(cv::Size(1, 1)), |
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testing::Values(cv::Size(16, 16)) |
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)) |
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{ |
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declare.time(3000); |
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const string_pair fileNames = std::tr1::get<0>(GetParam()); |
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const cv::Size block_size = std::tr1::get<1>(GetParam()); |
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const cv::Size shift_size = std::tr1::get<2>(GetParam()); |
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const cv::Size max_range = std::tr1::get<3>(GetParam()); |
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cv::Mat src1 = cv::imread(fileNames.first, cv::IMREAD_GRAYSCALE); |
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if (src1.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.first << "]"; |
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cv::Mat src2 = cv::imread(fileNames.second, cv::IMREAD_GRAYSCALE); |
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if (src2.empty()) |
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FAIL() << "Unable to load source image [" << fileNames.second << "]"; |
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if (PERF_RUN_GPU()) |
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{ |
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cv::gpu::GpuMat d_src1(src1); |
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cv::gpu::GpuMat d_src2(src2); |
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cv::gpu::GpuMat d_velx, d_vely; |
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cv::gpu::FastOpticalFlowBM fastBM; |
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fastBM(d_src1, d_src2, d_velx, d_vely, max_range.width, block_size.width); |
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TEST_CYCLE_N(10) |
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{ |
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fastBM(d_src1, d_src2, d_velx, d_vely, max_range.width, block_size.width); |
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} |
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} |
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else |
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{ |
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cv::Mat velx, vely; |
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calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); |
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TEST_CYCLE_N(10) |
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{ |
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calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely); |
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} |
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} |
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SANITY_CHECK(0); |
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}
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