/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "perf_precomp.hpp" using namespace std; using namespace testing; using namespace perf; /////////////////////////////////////////////////////////////// // HOG DEF_PARAM_TEST_1(Image, string); PERF_TEST_P(Image, ObjDetect_HOG, Values("gpu/hog/road.png", "gpu/caltech/image_00000009_0.png", "gpu/caltech/image_00000032_0.png", "gpu/caltech/image_00000165_0.png", "gpu/caltech/image_00000261_0.png", "gpu/caltech/image_00000469_0.png", "gpu/caltech/image_00000527_0.png", "gpu/caltech/image_00000574_0.png")) { declare.time(300.0); const cv::Mat img = readImage(GetParam(), cv::IMREAD_GRAYSCALE); ASSERT_FALSE(img.empty()); if (PERF_RUN_CUDA()) { const cv::cuda::GpuMat d_img(img); std::vector gpu_found_locations; cv::cuda::HOGDescriptor d_hog; d_hog.setSVMDetector(cv::cuda::HOGDescriptor::getDefaultPeopleDetector()); TEST_CYCLE() d_hog.detectMultiScale(d_img, gpu_found_locations); SANITY_CHECK(gpu_found_locations); } else { std::vector cpu_found_locations; cv::HOGDescriptor hog; hog.setSVMDetector(cv::cuda::HOGDescriptor::getDefaultPeopleDetector()); TEST_CYCLE() hog.detectMultiScale(img, cpu_found_locations); SANITY_CHECK(cpu_found_locations); } } /////////////////////////////////////////////////////////////// // HaarClassifier typedef pair pair_string; DEF_PARAM_TEST_1(ImageAndCascade, pair_string); PERF_TEST_P(ImageAndCascade, ObjDetect_HaarClassifier, Values(make_pair("gpu/haarcascade/group_1_640x480_VGA.pgm", "gpu/perf/haarcascade_frontalface_alt.xml"))) { const cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(img.empty()); if (PERF_RUN_CUDA()) { cv::cuda::CascadeClassifier_CUDA d_cascade; ASSERT_TRUE(d_cascade.load(perf::TestBase::getDataPath(GetParam().second))); const cv::cuda::GpuMat d_img(img); cv::cuda::GpuMat objects_buffer; int detections_num = 0; TEST_CYCLE() detections_num = d_cascade.detectMultiScale(d_img, objects_buffer); std::vector gpu_rects(detections_num); cv::Mat gpu_rects_mat(1, detections_num, cv::DataType::type, &gpu_rects[0]); objects_buffer.colRange(0, detections_num).download(gpu_rects_mat); cv::groupRectangles(gpu_rects, 3, 0.2); SANITY_CHECK(gpu_rects); } else { cv::CascadeClassifier cascade; ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath("gpu/perf/haarcascade_frontalface_alt.xml"))); std::vector cpu_rects; TEST_CYCLE() cascade.detectMultiScale(img, cpu_rects); SANITY_CHECK(cpu_rects); } } /////////////////////////////////////////////////////////////// // LBP cascade PERF_TEST_P(ImageAndCascade, ObjDetect_LBPClassifier, Values(make_pair("gpu/haarcascade/group_1_640x480_VGA.pgm", "gpu/lbpcascade/lbpcascade_frontalface.xml"))) { const cv::Mat img = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); ASSERT_FALSE(img.empty()); if (PERF_RUN_CUDA()) { cv::cuda::CascadeClassifier_CUDA d_cascade; ASSERT_TRUE(d_cascade.load(perf::TestBase::getDataPath(GetParam().second))); const cv::cuda::GpuMat d_img(img); cv::cuda::GpuMat objects_buffer; int detections_num = 0; TEST_CYCLE() detections_num = d_cascade.detectMultiScale(d_img, objects_buffer); std::vector gpu_rects(detections_num); cv::Mat gpu_rects_mat(1, detections_num, cv::DataType::type, &gpu_rects[0]); objects_buffer.colRange(0, detections_num).download(gpu_rects_mat); cv::groupRectangles(gpu_rects, 3, 0.2); SANITY_CHECK(gpu_rects); } else { cv::CascadeClassifier cascade; ASSERT_TRUE(cascade.load(perf::TestBase::getDataPath("gpu/lbpcascade/lbpcascade_frontalface.xml"))); std::vector cpu_rects; TEST_CYCLE() cascade.detectMultiScale(img, cpu_rects); SANITY_CHECK(cpu_rects); } }