#include "perf_precomp.hpp" #define GPU_PERF_TEST_P(fixture, name, params) \ class fixture##_##name : public fixture {\ public:\ fixture##_##name() {}\ protected:\ virtual void __cpu();\ virtual void __gpu();\ virtual void PerfTestBody();\ };\ TEST_P(fixture##_##name, name /*perf*/){ RunPerfTestBody(); if (PERF_RUN_GPU()) __gpu(); else __cpu();}\ INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);\ void fixture##_##name::PerfTestBody() #define RUN_CPU(fixture, name)\ void fixture##_##name::__cpu() #define RUN_GPU(fixture, name)\ void fixture##_##name::__gpu() #define NO_CPU(fixture, name)\ void fixture##_##name::__cpu() { FAIL() << "No such CPU implementation analogy";} namespace { struct DetectionLess { bool operator()(const cv::gpu::SCascade::Detection& a, const cv::gpu::SCascade::Detection& b) const { if (a.x != b.x) return a.x < b.x; else if (a.y != b.y) return a.y < b.y; else if (a.w != b.w) return a.w < b.w; else return a.h < b.h; } }; cv::Mat sortDetections(cv::gpu::GpuMat& objects) { cv::Mat detections(objects); typedef cv::gpu::SCascade::Detection Detection; Detection* begin = (Detection*)(detections.ptr(0)); Detection* end = (Detection*)(detections.ptr(0) + detections.cols); std::sort(begin, end, DetectionLess()); return detections; } } typedef std::tr1::tuple fixture_t; typedef perf::TestBaseWithParam SCascadeTest; GPU_PERF_TEST_P(SCascadeTest, detect, testing::Combine( testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")), testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")))) { } RUN_GPU(SCascadeTest, detect) { cv::Mat cpu = readImage (GET_PARAM(1)); ASSERT_FALSE(cpu.empty()); cv::gpu::GpuMat colored(cpu); cv::gpu::SCascade cascade; cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(0)), cv::FileStorage::READ); ASSERT_TRUE(fs.isOpened()); ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); cv::gpu::GpuMat objectBoxes(1, 10000 * sizeof(cv::gpu::SCascade::Detection), CV_8UC1), rois(colored.size(), CV_8UC1), trois; rois.setTo(1); cascade.genRoi(rois, trois); cascade.detect(colored, trois, objectBoxes); TEST_CYCLE() { cascade.detect(colored, trois, objectBoxes); } SANITY_CHECK(sortDetections(objectBoxes)); } NO_CPU(SCascadeTest, detect) static cv::Rect getFromTable(int idx) { static const cv::Rect rois[] = { cv::Rect( 65 * 4, 20 * 4, 35 * 4, 80 * 4), cv::Rect( 95 * 4, 35 * 4, 45 * 4, 40 * 4), cv::Rect( 45 * 4, 35 * 4, 45 * 4, 40 * 4), cv::Rect( 25 * 4, 27 * 4, 50 * 4, 45 * 4), cv::Rect(100 * 4, 50 * 4, 45 * 4, 40 * 4), cv::Rect( 60 * 4, 30 * 4, 45 * 4, 40 * 4), cv::Rect( 40 * 4, 55 * 4, 50 * 4, 40 * 4), cv::Rect( 48 * 4, 37 * 4, 72 * 4, 80 * 4), cv::Rect( 48 * 4, 32 * 4, 85 * 4, 58 * 4), cv::Rect( 48 * 4, 0 * 4, 32 * 4, 27 * 4) }; return rois[idx]; } typedef std::tr1::tuple roi_fixture_t; typedef perf::TestBaseWithParam SCascadeTestRoi; GPU_PERF_TEST_P(SCascadeTestRoi, detectInRoi, testing::Combine( testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")), testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")), testing::Range(0, 5))) {} RUN_GPU(SCascadeTestRoi, detectInRoi) { cv::Mat cpu = readImage (GET_PARAM(1)); ASSERT_FALSE(cpu.empty()); cv::gpu::GpuMat colored(cpu); cv::gpu::SCascade cascade; cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(0)), cv::FileStorage::READ); ASSERT_TRUE(fs.isOpened()); ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(colored.size(), CV_8UC1); rois.setTo(0); int nroi = GET_PARAM(2); cv::RNG rng; for (int i = 0; i < nroi; ++i) { cv::Rect r = getFromTable(rng(10)); cv::gpu::GpuMat sub(rois, r); sub.setTo(1); } cv::gpu::GpuMat trois; cascade.genRoi(rois, trois); cascade.detect(colored, trois, objectBoxes); TEST_CYCLE() { cascade.detect(colored, trois, objectBoxes); } SANITY_CHECK(sortDetections(objectBoxes)); } NO_CPU(SCascadeTestRoi, detectInRoi) GPU_PERF_TEST_P(SCascadeTestRoi, detectEachRoi, testing::Combine( testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")), testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")), testing::Range(0, 10))) {} RUN_GPU(SCascadeTestRoi, detectEachRoi) { cv::Mat cpu = readImage (GET_PARAM(1)); ASSERT_FALSE(cpu.empty()); cv::gpu::GpuMat colored(cpu); cv::gpu::SCascade cascade; cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(0)), cv::FileStorage::READ); ASSERT_TRUE(fs.isOpened()); ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); cv::gpu::GpuMat objectBoxes(1, 16384 * 20, CV_8UC1), rois(colored.size(), CV_8UC1); rois.setTo(0); int idx = GET_PARAM(2); cv::Rect r = getFromTable(idx); cv::gpu::GpuMat sub(rois, r); sub.setTo(1); cv::gpu::GpuMat trois; cascade.genRoi(rois, trois); cascade.detect(colored, trois, objectBoxes); TEST_CYCLE() { cascade.detect(colored, trois, objectBoxes); } SANITY_CHECK(sortDetections(objectBoxes)); } NO_CPU(SCascadeTestRoi, detectEachRoi) GPU_PERF_TEST_P(SCascadeTest, detectOnIntegral, testing::Combine( testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")), testing::Values(std::string("cv/cascadeandhog/integrals.xml")))) { } static std::string itoa(long i) { static char s[65]; sprintf(s, "%ld", i); return std::string(s); } RUN_GPU(SCascadeTest, detectOnIntegral) { cv::FileStorage fsi(perf::TestBase::getDataPath(GET_PARAM(1)), cv::FileStorage::READ); ASSERT_TRUE(fsi.isOpened()); cv::gpu::GpuMat hogluv(121 * 10, 161, CV_32SC1); for (int i = 0; i < 10; ++i) { cv::Mat channel; fsi[std::string("channel") + itoa(i)] >> channel; cv::gpu::GpuMat gchannel(hogluv, cv::Rect(0, 121 * i, 161, 121)); gchannel.upload(channel); } cv::gpu::SCascade cascade; cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(0)), cv::FileStorage::READ); ASSERT_TRUE(fs.isOpened()); ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); cv::gpu::GpuMat objectBoxes(1, 10000 * sizeof(cv::gpu::SCascade::Detection), CV_8UC1), rois(cv::Size(640, 480), CV_8UC1), trois; rois.setTo(1); cascade.genRoi(rois, trois); cascade.detect(hogluv, trois, objectBoxes); TEST_CYCLE() { cascade.detect(hogluv, trois, objectBoxes); } SANITY_CHECK(sortDetections(objectBoxes)); } NO_CPU(SCascadeTest, detectOnIntegral) GPU_PERF_TEST_P(SCascadeTest, detectStream, testing::Combine( testing::Values(std::string("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")), testing::Values(std::string("cv/cascadeandhog/bahnhof/image_00000000_0.png")))) { } RUN_GPU(SCascadeTest, detectStream) { cv::Mat cpu = readImage (GET_PARAM(1)); ASSERT_FALSE(cpu.empty()); cv::gpu::GpuMat colored(cpu); cv::gpu::SCascade cascade; cv::FileStorage fs(perf::TestBase::getDataPath(GET_PARAM(0)), cv::FileStorage::READ); ASSERT_TRUE(fs.isOpened()); ASSERT_TRUE(cascade.load(fs.getFirstTopLevelNode())); cv::gpu::GpuMat objectBoxes(1, 10000 * sizeof(cv::gpu::SCascade::Detection), CV_8UC1), rois(colored.size(), CV_8UC1), trois; rois.setTo(1); cv::gpu::Stream s; cascade.genRoi(rois, trois, s); cascade.detect(colored, trois, objectBoxes, s); TEST_CYCLE() { cascade.detect(colored, trois, objectBoxes, s); } #ifdef HAVE_CUDA cudaDeviceSynchronize(); #endif SANITY_CHECK(sortDetections(objectBoxes)); } NO_CPU(SCascadeTest, detectStream)