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228 lines
6.1 KiB
C++
228 lines
6.1 KiB
C++
#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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// HOG
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DEF_PARAM_TEST_1(Image, string);
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PERF_TEST_P(Image, ObjDetect_HOG, Values<string>("gpu/hog/road.png"))
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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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std::vector<cv::Rect> found_locations;
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if (PERF_RUN_GPU())
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{
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cv::gpu::GpuMat d_img(img);
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cv::gpu::HOGDescriptor d_hog;
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d_hog.setSVMDetector(cv::gpu::HOGDescriptor::getDefaultPeopleDetector());
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d_hog.detectMultiScale(d_img, found_locations);
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TEST_CYCLE()
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{
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d_hog.detectMultiScale(d_img, found_locations);
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}
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}
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else
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{
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cv::HOGDescriptor hog;
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hog.setSVMDetector(cv::gpu::HOGDescriptor::getDefaultPeopleDetector());
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hog.detectMultiScale(img, found_locations);
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TEST_CYCLE()
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{
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hog.detectMultiScale(img, found_locations);
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}
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}
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SANITY_CHECK(found_locations);
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}
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//===========test for CalTech data =============//
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DEF_PARAM_TEST_1(HOG, string);
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PERF_TEST_P(HOG, CalTech, Values<string>("gpu/caltech/image_00000009_0.png", "gpu/caltech/image_00000032_0.png",
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"gpu/caltech/image_00000165_0.png", "gpu/caltech/image_00000261_0.png", "gpu/caltech/image_00000469_0.png",
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"gpu/caltech/image_00000527_0.png", "gpu/caltech/image_00000574_0.png"))
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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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std::vector<cv::Rect> found_locations;
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if (PERF_RUN_GPU())
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{
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cv::gpu::GpuMat d_img(img);
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cv::gpu::HOGDescriptor d_hog;
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d_hog.setSVMDetector(cv::gpu::HOGDescriptor::getDefaultPeopleDetector());
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d_hog.detectMultiScale(d_img, found_locations);
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TEST_CYCLE()
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{
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d_hog.detectMultiScale(d_img, found_locations);
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}
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}
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else
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{
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cv::HOGDescriptor hog;
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hog.setSVMDetector(cv::gpu::HOGDescriptor::getDefaultPeopleDetector());
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hog.detectMultiScale(img, found_locations);
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TEST_CYCLE()
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{
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hog.detectMultiScale(img, found_locations);
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}
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}
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SANITY_CHECK(found_locations);
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}
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typedef pair<string, string> pair_string;
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DEF_PARAM_TEST_1(SoftCascade, pair_string);
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PERF_TEST_P(SoftCascade, detect, Values<pair_string>(make_pair("cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml",
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"cv/cascadeandhog/bahnhof/image_00000000_0.png")))
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{
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if (runOnGpu)
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{
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cv::Mat cpu = readImage (GetParam().second);
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ASSERT_FALSE(cpu.empty());
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cv::gpu::GpuMat colored(cpu);
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cv::gpu::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath(GetParam().first)));
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cv::gpu::GpuMat objectBoxes(1, 16384, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
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rois.setTo(0);
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cv::gpu::GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
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sub.setTo(cv::Scalar::all(1));
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cascade.detectMultiScale(colored, rois, objectBoxes);
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TEST_CYCLE()
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{
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cascade.detectMultiScale(colored, rois, objectBoxes);
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}
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} else
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{
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cv::Mat colored = readImage(GetParam().second);
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ASSERT_FALSE(colored.empty());
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cv::SoftCascade cascade;
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ASSERT_TRUE(cascade.load(getDataPath(GetParam().first)));
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std::vector<cv::Rect> rois, objectBoxes;
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cascade.detectMultiScale(colored, rois, objectBoxes);
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TEST_CYCLE()
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{
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cascade.detectMultiScale(colored, rois, objectBoxes);
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}
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}
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}
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///////////////////////////////////////////////////////////////
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// HaarClassifier
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typedef pair<string, string> pair_string;
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DEF_PARAM_TEST_1(ImageAndCascade, pair_string);
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PERF_TEST_P(ImageAndCascade, ObjDetect_HaarClassifier,
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Values<pair_string>(make_pair("gpu/haarcascade/group_1_640x480_VGA.pgm", "gpu/perf/haarcascade_frontalface_alt.xml")))
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{
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cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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if (PERF_RUN_GPU())
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{
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cv::gpu::CascadeClassifier_GPU d_cascade;
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ASSERT_TRUE(d_cascade.load(perf::TestBase::getDataPath(GetParam().second)));
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cv::gpu::GpuMat d_img(img);
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cv::gpu::GpuMat d_objects_buffer;
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d_cascade.detectMultiScale(d_img, d_objects_buffer);
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TEST_CYCLE()
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{
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d_cascade.detectMultiScale(d_img, d_objects_buffer);
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}
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GPU_SANITY_CHECK(d_objects_buffer);
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}
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else
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{
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cv::CascadeClassifier cascade;
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ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath("gpu/perf/haarcascade_frontalface_alt.xml")));
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std::vector<cv::Rect> rects;
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cascade.detectMultiScale(img, rects);
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TEST_CYCLE()
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{
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cascade.detectMultiScale(img, rects);
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}
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CPU_SANITY_CHECK(rects);
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}
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}
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///////////////////////////////////////////////////////////////
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// LBP cascade
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PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier,
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Values<pair_string>(make_pair("gpu/haarcascade/group_1_640x480_VGA.pgm", "gpu/lbpcascade/lbpcascade_frontalface.xml")))
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{
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cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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if (PERF_RUN_GPU())
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{
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cv::gpu::CascadeClassifier_GPU d_cascade;
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ASSERT_TRUE(d_cascade.load(perf::TestBase::getDataPath(GetParam().second)));
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cv::gpu::GpuMat d_img(img);
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cv::gpu::GpuMat d_gpu_rects;
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d_cascade.detectMultiScale(d_img, d_gpu_rects);
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TEST_CYCLE()
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{
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d_cascade.detectMultiScale(d_img, d_gpu_rects);
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}
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GPU_SANITY_CHECK(d_gpu_rects);
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}
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else
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{
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cv::CascadeClassifier cascade;
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ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath("gpu/lbpcascade/lbpcascade_frontalface.xml")));
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std::vector<cv::Rect> rects;
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cascade.detectMultiScale(img, rects);
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TEST_CYCLE()
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{
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cascade.detectMultiScale(img, rects);
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}
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CPU_SANITY_CHECK(rects);
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}
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}
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} // namespace
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