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265 lines
8.4 KiB
C++
265 lines
8.4 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, 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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// @Authors
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// Yao Wang, bitwangyaoyao@gmail.com
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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 Intel Corporation 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 "test_precomp.hpp"
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#include "opencv2/core/core.hpp"
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#include "opencv2/objdetect/objdetect.hpp"
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using namespace cv;
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using namespace testing;
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#ifdef HAVE_OPENCL
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extern string workdir;
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///////////////////// HOG /////////////////////////////
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PARAM_TEST_CASE(HOG, Size, int)
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{
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Size winSize;
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int type;
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Mat img_rgb;
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virtual void SetUp()
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{
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winSize = GET_PARAM(0);
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type = GET_PARAM(1);
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img_rgb = readImage("gpu/hog/road.png");
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ASSERT_FALSE(img_rgb.empty());
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}
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};
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TEST_P(HOG, GetDescriptors)
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{
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// Convert image
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Mat img;
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switch (type)
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{
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case CV_8UC1:
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cvtColor(img_rgb, img, CV_BGR2GRAY);
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break;
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case CV_8UC4:
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default:
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cvtColor(img_rgb, img, CV_BGR2BGRA);
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break;
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}
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ocl::oclMat d_img(img);
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// HOGs
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ocl::HOGDescriptor ocl_hog;
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ocl_hog.gamma_correction = true;
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HOGDescriptor hog;
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hog.gammaCorrection = true;
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// Compute descriptor
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ocl::oclMat d_descriptors;
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ocl_hog.getDescriptors(d_img, ocl_hog.win_size, d_descriptors, ocl_hog.DESCR_FORMAT_COL_BY_COL);
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Mat down_descriptors;
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d_descriptors.download(down_descriptors);
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down_descriptors = down_descriptors.reshape(0, down_descriptors.cols * down_descriptors.rows);
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hog.setSVMDetector(hog.getDefaultPeopleDetector());
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std::vector<float> descriptors;
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switch (type)
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{
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case CV_8UC1:
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hog.compute(img, descriptors, ocl_hog.win_size);
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break;
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case CV_8UC4:
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default:
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hog.compute(img_rgb, descriptors, ocl_hog.win_size);
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break;
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}
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Mat cpu_descriptors(descriptors);
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EXPECT_MAT_SIMILAR(down_descriptors, cpu_descriptors, 1e-2);
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}
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TEST_P(HOG, Detect)
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{
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// Convert image
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Mat img;
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switch (type)
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{
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case CV_8UC1:
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cvtColor(img_rgb, img, CV_BGR2GRAY);
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break;
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case CV_8UC4:
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default:
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cvtColor(img_rgb, img, CV_BGR2BGRA);
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break;
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}
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ocl::oclMat d_img(img);
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// HOGs
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if ((winSize != Size(48, 96)) && (winSize != Size(64, 128)))
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winSize = Size(64, 128);
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ocl::HOGDescriptor ocl_hog(winSize);
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ocl_hog.gamma_correction = true;
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HOGDescriptor hog;
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hog.winSize = winSize;
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hog.gammaCorrection = true;
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if (winSize.width == 48 && winSize.height == 96)
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{
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// daimler's base
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ocl_hog.setSVMDetector(hog.getDaimlerPeopleDetector());
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hog.setSVMDetector(hog.getDaimlerPeopleDetector());
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}
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else if (winSize.width == 64 && winSize.height == 128)
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{
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ocl_hog.setSVMDetector(hog.getDefaultPeopleDetector());
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hog.setSVMDetector(hog.getDefaultPeopleDetector());
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}
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else
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{
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ocl_hog.setSVMDetector(hog.getDefaultPeopleDetector());
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hog.setSVMDetector(hog.getDefaultPeopleDetector());
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}
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// OpenCL detection
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std::vector<Rect> d_found;
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ocl_hog.detectMultiScale(d_img, d_found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
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// CPU detection
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std::vector<Rect> found;
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switch (type)
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{
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case CV_8UC1:
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hog.detectMultiScale(img, found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
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break;
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case CV_8UC4:
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default:
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hog.detectMultiScale(img_rgb, found, 0, Size(8, 8), Size(0, 0), 1.05, 6);
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break;
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}
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EXPECT_LT(checkRectSimilarity(img.size(), found, d_found), 1.0);
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}
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INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
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testing::Values(Size(64, 128), Size(48, 96)),
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC4))));
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///////////////////////////// Haar //////////////////////////////
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IMPLEMENT_PARAM_CLASS(CascadeName, std::string);
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CascadeName cascade_frontalface_alt(std::string("haarcascade_frontalface_alt.xml"));
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CascadeName cascade_frontalface_alt2(std::string("haarcascade_frontalface_alt2.xml"));
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struct getRect
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{
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Rect operator ()(const CvAvgComp &e) const
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{
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return e.rect;
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}
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};
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PARAM_TEST_CASE(Haar, int, CascadeName)
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{
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ocl::OclCascadeClassifier cascade, nestedCascade;
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CascadeClassifier cpucascade, cpunestedCascade;
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int flags;
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std::string cascadeName;
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vector<Rect> faces, oclfaces;
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Mat img;
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ocl::oclMat d_img;
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virtual void SetUp()
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{
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flags = GET_PARAM(0);
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cascadeName = (string(cvtest::TS::ptr()->get_data_path()) + "cv/cascadeandhog/cascades/").append(GET_PARAM(1));
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ASSERT_TRUE(cascade.load( cascadeName ));
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ASSERT_TRUE(cpucascade.load(cascadeName));
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img = readImage("cv/shared/lena.png", IMREAD_GRAYSCALE);
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ASSERT_FALSE(img.empty());
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equalizeHist(img, img);
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d_img.upload(img);
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}
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};
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TEST_P(Haar, FaceDetect)
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{
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MemStorage storage(cvCreateMemStorage(0));
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CvSeq *_objects;
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_objects = cascade.oclHaarDetectObjects(d_img, storage, 1.1, 3,
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flags, Size(30, 30), Size(0, 0));
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vector<CvAvgComp> vecAvgComp;
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Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
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oclfaces.resize(vecAvgComp.size());
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std::transform(vecAvgComp.begin(), vecAvgComp.end(), oclfaces.begin(), getRect());
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cpucascade.detectMultiScale(img, faces, 1.1, 3,
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flags,
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Size(30, 30), Size(0, 0));
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EXPECT_LT(checkRectSimilarity(img.size(), faces, oclfaces), 1.0);
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}
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TEST_P(Haar, FaceDetectUseBuf)
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{
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ocl::OclCascadeClassifierBuf cascadebuf;
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ASSERT_TRUE(cascadebuf.load(cascadeName)) << "could not load classifier cascade for FaceDetectUseBuf!";
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cascadebuf.detectMultiScale(d_img, oclfaces, 1.1, 3,
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flags,
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Size(30, 30), Size(0, 0));
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cpucascade.detectMultiScale(img, faces, 1.1, 3,
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flags,
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Size(30, 30), Size(0, 0));
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// intentionally run ocl facedetect again and check if it still works after the first run
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cascadebuf.detectMultiScale(d_img, oclfaces, 1.1, 3,
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flags,
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Size(30, 30));
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cascadebuf.release();
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EXPECT_LT(checkRectSimilarity(img.size(), faces, oclfaces), 1.0);
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}
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INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, Haar,
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Combine(Values(CV_HAAR_SCALE_IMAGE, 0),
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Values(cascade_frontalface_alt/*, cascade_frontalface_alt2*/)));
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#endif //HAVE_OPENCL
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