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