174 lines
6.1 KiB
C++
174 lines
6.1 KiB
C++
/*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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namespace opencv_test { 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,
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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_CUDA())
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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::Ptr<cv::cuda::HOG> d_hog = cv::cuda::HOG::create();
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d_hog->setSVMDetector(d_hog->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::Ptr<cv::cuda::HOG> d_hog = cv::cuda::HOG::create();
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cv::HOGDescriptor hog;
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hog.setSVMDetector(d_hog->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_CUDA())
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{
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cv::Ptr<cv::cuda::CascadeClassifier> d_cascade =
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cv::cuda::CascadeClassifier::create(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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TEST_CYCLE() d_cascade->detectMultiScale(d_img, objects_buffer);
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std::vector<cv::Rect> gpu_rects;
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d_cascade->convert(objects_buffer, gpu_rects);
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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_CUDA())
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{
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cv::Ptr<cv::cuda::CascadeClassifier> d_cascade =
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cv::cuda::CascadeClassifier::create(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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TEST_CYCLE() d_cascade->detectMultiScale(d_img, objects_buffer);
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std::vector<cv::Rect> gpu_rects;
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d_cascade->convert(objects_buffer, gpu_rects);
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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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}} // namespace
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