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