/*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 "test_precomp.hpp" #ifdef HAVE_CUDA namespace opencv_test { namespace { /////////////////////////////////////////////////////////////////////////////////////////////////////// // HistEven PARAM_TEST_CASE(HistEven, cv::cuda::DeviceInfo, cv::Size) { cv::cuda::DeviceInfo devInfo; cv::Size size; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); cv::cuda::setDevice(devInfo.deviceID()); } }; CUDA_TEST_P(HistEven, Accuracy) { cv::Mat src = randomMat(size, CV_8UC1); int hbins = 30; float hranges[] = {50.0f, 200.0f}; cv::cuda::GpuMat hist; cv::cuda::histEven(loadMat(src), hist, hbins, (int) hranges[0], (int) hranges[1]); cv::Mat hist_gold; int histSize[] = {hbins}; const float* ranges[] = {hranges}; int channels[] = {0}; cv::calcHist(&src, 1, channels, cv::Mat(), hist_gold, 1, histSize, ranges); hist_gold = hist_gold.t(); hist_gold.convertTo(hist_gold, CV_32S); EXPECT_MAT_NEAR(hist_gold, hist, 0.0); } INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, HistEven, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES)); /////////////////////////////////////////////////////////////////////////////////////////////////////// // CalcHist PARAM_TEST_CASE(CalcHist, cv::cuda::DeviceInfo, cv::Size) { cv::cuda::DeviceInfo devInfo; cv::Size size; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); cv::cuda::setDevice(devInfo.deviceID()); } }; CUDA_TEST_P(CalcHist, Accuracy) { cv::Mat src = randomMat(size, CV_8UC1); cv::cuda::GpuMat hist; cv::cuda::calcHist(loadMat(src), hist); cv::Mat hist_gold; const int hbins = 256; const float hranges[] = {0.0f, 256.0f}; const int histSize[] = {hbins}; const float* ranges[] = {hranges}; const int channels[] = {0}; cv::calcHist(&src, 1, channels, cv::Mat(), hist_gold, 1, histSize, ranges); hist_gold = hist_gold.reshape(1, 1); hist_gold.convertTo(hist_gold, CV_32S); EXPECT_MAT_NEAR(hist_gold, hist, 0.0); } INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CalcHist, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES)); PARAM_TEST_CASE(CalcHistWithMask, cv::cuda::DeviceInfo, cv::Size) { cv::cuda::DeviceInfo devInfo; cv::Size size; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); cv::cuda::setDevice(devInfo.deviceID()); } }; CUDA_TEST_P(CalcHistWithMask, Accuracy) { cv::Mat src = randomMat(size, CV_8UC1); cv::Mat mask = randomMat(size, CV_8UC1); cv::Mat(mask, cv::Rect(0, 0, size.width / 2, size.height / 2)).setTo(0); cv::cuda::GpuMat hist; cv::cuda::calcHist(loadMat(src), loadMat(mask), hist); cv::Mat hist_gold; const int hbins = 256; const float hranges[] = {0.0f, 256.0f}; const int histSize[] = {hbins}; const float* ranges[] = {hranges}; const int channels[] = {0}; cv::calcHist(&src, 1, channels, mask, hist_gold, 1, histSize, ranges); hist_gold = hist_gold.reshape(1, 1); hist_gold.convertTo(hist_gold, CV_32S); EXPECT_MAT_NEAR(hist_gold, hist, 0.0); } INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CalcHistWithMask, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES)); /////////////////////////////////////////////////////////////////////////////////////////////////////// // EqualizeHist PARAM_TEST_CASE(EqualizeHist, cv::cuda::DeviceInfo, cv::Size) { cv::cuda::DeviceInfo devInfo; cv::Size size; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); cv::cuda::setDevice(devInfo.deviceID()); } }; CUDA_TEST_P(EqualizeHist, Async) { cv::Mat src = randomMat(size, CV_8UC1); cv::cuda::Stream stream; cv::cuda::GpuMat dst; cv::cuda::equalizeHist(loadMat(src), dst, stream); stream.waitForCompletion(); cv::Mat dst_gold; cv::equalizeHist(src, dst_gold); EXPECT_MAT_NEAR(dst_gold, dst, 0.0); } CUDA_TEST_P(EqualizeHist, Accuracy) { cv::Mat src = randomMat(size, CV_8UC1); cv::cuda::GpuMat dst; cv::cuda::equalizeHist(loadMat(src), dst); cv::Mat dst_gold; cv::equalizeHist(src, dst_gold); EXPECT_MAT_NEAR(dst_gold, dst, 0.0); } INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, EqualizeHist, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES)); TEST(EqualizeHistIssue, Issue18035) { std::vector imgPaths; imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/3MP.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/5MP.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/airplane.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/baboon.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/box.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/box_in_scene.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/fruits.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/fruits_ecc.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/graffiti.png"); imgPaths.push_back(std::string(cvtest::TS::ptr()->get_data_path()) + "../cv/shared/lena.png"); for (size_t i = 0; i < imgPaths.size(); ++i) { std::string imgPath = imgPaths[i]; cv::Mat src = cv::imread(imgPath, cv::IMREAD_GRAYSCALE); src = src / 30; cv::cuda::GpuMat d_src, dst; d_src.upload(src); cv::cuda::equalizeHist(d_src, dst); cv::Mat dst_gold; cv::equalizeHist(src, dst_gold); EXPECT_MAT_NEAR(dst_gold, dst, 0.0); } } PARAM_TEST_CASE(EqualizeHistExtreme, cv::cuda::DeviceInfo, cv::Size, int) { cv::cuda::DeviceInfo devInfo; cv::Size size; int val; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); val = GET_PARAM(2); cv::cuda::setDevice(devInfo.deviceID()); } }; CUDA_TEST_P(EqualizeHistExtreme, Case1) { cv::Mat src(size, CV_8UC1, val); cv::cuda::GpuMat dst; cv::cuda::equalizeHist(loadMat(src), dst); cv::Mat dst_gold; cv::equalizeHist(src, dst_gold); EXPECT_MAT_NEAR(dst_gold, dst, 0.0); } CUDA_TEST_P(EqualizeHistExtreme, Case2) { cv::Mat src = randomMat(size, CV_8UC1, val); cv::cuda::GpuMat dst; cv::cuda::equalizeHist(loadMat(src), dst); cv::Mat dst_gold; cv::equalizeHist(src, dst_gold); EXPECT_MAT_NEAR(dst_gold, dst, 0.0); } INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, EqualizeHistExtreme, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES, testing::Range(0, 256))); /////////////////////////////////////////////////////////////////////////////////////////////////////// // CLAHE namespace { IMPLEMENT_PARAM_CLASS(ClipLimit, double) } PARAM_TEST_CASE(CLAHE, cv::cuda::DeviceInfo, cv::Size, ClipLimit, MatType) { cv::cuda::DeviceInfo devInfo; cv::Size size; double clipLimit; int type; virtual void SetUp() { devInfo = GET_PARAM(0); size = GET_PARAM(1); clipLimit = GET_PARAM(2); type = GET_PARAM(3); cv::cuda::setDevice(devInfo.deviceID()); } }; CUDA_TEST_P(CLAHE, Accuracy) { cv::Mat src; if (type == CV_8UC1) src = randomMat(size, type); else if (type == CV_16UC1) src = randomMat(size, type, 0, 65535); cv::Ptr clahe = cv::cuda::createCLAHE(clipLimit); cv::cuda::GpuMat dst; clahe->apply(loadMat(src), dst); cv::Ptr clahe_gold = cv::createCLAHE(clipLimit); cv::Mat dst_gold; clahe_gold->apply(src, dst_gold); ASSERT_MAT_NEAR(dst_gold, dst, 1.0); } INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, CLAHE, testing::Combine( ALL_DEVICES, DIFFERENT_SIZES, testing::Values(0.0, 5.0, 10.0, 20.0, 40.0), testing::Values(MatType(CV_8UC1), MatType(CV_16UC1)))); }} // namespace #endif // HAVE_CUDA