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Open Source Computer Vision Library
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172 lines
6.3 KiB
172 lines
6.3 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) 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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// Peng Xiao, pengxiao@multicorewareinc.com |
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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 oclMaterials 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 "precomp.hpp" |
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#define PERF_TEST 0 |
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//////////////////////////////////////////////////////////////////////////////// |
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// MatchTemplate |
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#define ALL_TEMPLATE_METHODS testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR), TemplateMethod(cv::TM_CCOEFF), TemplateMethod(cv::TM_SQDIFF_NORMED), TemplateMethod(cv::TM_CCORR_NORMED), TemplateMethod(cv::TM_CCOEFF_NORMED)) |
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IMPLEMENT_PARAM_CLASS(TemplateSize, cv::Size); |
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const char* TEMPLATE_METHOD_NAMES[6] = {"TM_SQDIFF", "TM_SQDIFF_NORMED", "TM_CCORR", "TM_CCORR_NORMED", "TM_CCOEFF", "TM_CCOEFF_NORMED"}; |
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PARAM_TEST_CASE(MatchTemplate8U, cv::Size, TemplateSize, Channels, TemplateMethod) |
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{ |
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cv::Size size; |
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cv::Size templ_size; |
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int cn; |
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int method; |
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//std::vector<cv::ocl::Info> oclinfo; |
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virtual void SetUp() |
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{ |
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size = GET_PARAM(0); |
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templ_size = GET_PARAM(1); |
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cn = GET_PARAM(2); |
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method = GET_PARAM(3); |
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//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE); |
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//CV_Assert(devnums > 0); |
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} |
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}; |
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TEST_P(MatchTemplate8U, Accuracy) |
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{ |
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std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl; |
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std::cout << "Image Size: (" << size.width << ", " << size.height << ")"<< std::endl; |
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std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")"<< std::endl; |
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std::cout << "Channels: " << cn << std::endl; |
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cv::Mat image = randomMat(size, CV_MAKETYPE(CV_8U, cn)); |
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cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_8U, cn)); |
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cv::ocl::oclMat dst, ocl_image(image), ocl_templ(templ); |
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cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method); |
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cv::Mat dst_gold; |
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cv::matchTemplate(image, templ, dst_gold, method); |
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char sss [100] = ""; |
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cv::Mat mat_dst; |
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dst.download(mat_dst); |
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EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss); |
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#if PERF_TEST |
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{ |
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P_TEST_FULL({}, {cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);}, {}); |
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P_TEST_FULL({}, {cv::matchTemplate(image, templ, dst_gold, method);}, {}); |
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} |
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#endif // PERF_TEST |
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} |
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PARAM_TEST_CASE(MatchTemplate32F, cv::Size, TemplateSize, Channels, TemplateMethod) |
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{ |
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cv::Size size; |
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cv::Size templ_size; |
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int cn; |
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int method; |
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//std::vector<cv::ocl::Info> oclinfo; |
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virtual void SetUp() |
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{ |
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size = GET_PARAM(0); |
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templ_size = GET_PARAM(1); |
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cn = GET_PARAM(2); |
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method = GET_PARAM(3); |
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//int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE); |
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//CV_Assert(devnums > 0); |
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} |
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}; |
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TEST_P(MatchTemplate32F, Accuracy) |
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{ |
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cv::Mat image = randomMat(size, CV_MAKETYPE(CV_32F, cn)); |
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cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_32F, cn)); |
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cv::ocl::oclMat dst, ocl_image(image), ocl_templ(templ); |
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cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method); |
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cv::Mat dst_gold; |
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cv::matchTemplate(image, templ, dst_gold, method); |
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char sss [100] = ""; |
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cv::Mat mat_dst; |
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dst.download(mat_dst); |
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EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss); |
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#if PERF_TEST |
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{ |
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std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl; |
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std::cout << "Image Size: (" << size.width << ", " << size.height << ")"<< std::endl; |
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std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")"<< std::endl; |
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std::cout << "Channels: " << cn << std::endl; |
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P_TEST_FULL({}, {cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);}, {}); |
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P_TEST_FULL({}, {cv::matchTemplate(image, templ, dst_gold, method);}, {}); |
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} |
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#endif // PERF_TEST |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate8U, |
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testing::Combine( |
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DIFFERENT_SIZES, |
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testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/), |
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testing::Values(Channels(1), Channels(4)), |
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ALL_TEMPLATE_METHODS |
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) |
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); |
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate32F, testing::Combine( |
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DIFFERENT_SIZES, |
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testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/), |
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testing::Values(Channels(1), Channels(4)), |
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testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR)))); |
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