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Open Source Computer Vision Library
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379 lines
12 KiB
379 lines
12 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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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2000, Intel Corporation, 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 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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#ifdef HAVE_CUDA |
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////////////////////////////////////////////////////////////////////////// |
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// BlockMatching |
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struct StereoBlockMatching : testing::TestWithParam<cv::gpu::DeviceInfo> |
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{ |
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cv::Mat img_l; |
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cv::Mat img_r; |
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cv::Mat img_template; |
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cv::gpu::DeviceInfo devInfo; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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img_l = readImage("stereobm/aloe-L.png", CV_LOAD_IMAGE_GRAYSCALE); |
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img_r = readImage("stereobm/aloe-R.png", CV_LOAD_IMAGE_GRAYSCALE); |
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img_template = readImage("stereobm/aloe-disp.png", CV_LOAD_IMAGE_GRAYSCALE); |
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ASSERT_FALSE(img_l.empty()); |
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ASSERT_FALSE(img_r.empty()); |
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ASSERT_FALSE(img_template.empty()); |
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} |
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}; |
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TEST_P(StereoBlockMatching, Regression) |
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{ |
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PRINT_PARAM(devInfo); |
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cv::Mat disp; |
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ASSERT_NO_THROW( |
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cv::gpu::GpuMat dev_disp; |
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cv::gpu::StereoBM_GPU bm(0, 128, 19); |
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bm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), dev_disp); |
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dev_disp.download(disp); |
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); |
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disp.convertTo(disp, img_template.type()); |
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EXPECT_MAT_NEAR(img_template, disp, 0.0); |
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} |
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INSTANTIATE_TEST_CASE_P(Calib3D, StereoBlockMatching, testing::ValuesIn(devices())); |
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////////////////////////////////////////////////////////////////////////// |
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// BeliefPropagation |
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struct StereoBeliefPropagation : testing::TestWithParam<cv::gpu::DeviceInfo> |
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{ |
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cv::Mat img_l; |
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cv::Mat img_r; |
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cv::Mat img_template; |
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cv::gpu::DeviceInfo devInfo; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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img_l = readImage("stereobp/aloe-L.png"); |
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img_r = readImage("stereobp/aloe-R.png"); |
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img_template = readImage("stereobp/aloe-disp.png", CV_LOAD_IMAGE_GRAYSCALE); |
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ASSERT_FALSE(img_l.empty()); |
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ASSERT_FALSE(img_r.empty()); |
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ASSERT_FALSE(img_template.empty()); |
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} |
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}; |
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TEST_P(StereoBeliefPropagation, Regression) |
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{ |
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PRINT_PARAM(devInfo); |
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cv::Mat disp; |
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ASSERT_NO_THROW( |
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cv::gpu::GpuMat dev_disp; |
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cv::gpu::StereoBeliefPropagation bpm(64, 8, 2, 25, 0.1f, 15, 1, CV_16S); |
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bpm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), dev_disp); |
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dev_disp.download(disp); |
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); |
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disp.convertTo(disp, img_template.type()); |
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EXPECT_MAT_NEAR(img_template, disp, 0.0); |
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} |
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INSTANTIATE_TEST_CASE_P(Calib3D, StereoBeliefPropagation, testing::ValuesIn(devices())); |
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////////////////////////////////////////////////////////////////////////// |
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// ConstantSpaceBP |
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struct StereoConstantSpaceBP : testing::TestWithParam<cv::gpu::DeviceInfo> |
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{ |
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cv::Mat img_l; |
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cv::Mat img_r; |
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cv::Mat img_template; |
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cv::gpu::DeviceInfo devInfo; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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img_l = readImage("csstereobp/aloe-L.png"); |
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img_r = readImage("csstereobp/aloe-R.png"); |
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if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20)) |
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img_template = readImage("csstereobp/aloe-disp.png", CV_LOAD_IMAGE_GRAYSCALE); |
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else |
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img_template = readImage("csstereobp/aloe-disp_CC1X.png", CV_LOAD_IMAGE_GRAYSCALE); |
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ASSERT_FALSE(img_l.empty()); |
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ASSERT_FALSE(img_r.empty()); |
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ASSERT_FALSE(img_template.empty()); |
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} |
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}; |
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TEST_P(StereoConstantSpaceBP, Regression) |
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{ |
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PRINT_PARAM(devInfo); |
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cv::Mat disp; |
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ASSERT_NO_THROW( |
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cv::gpu::GpuMat dev_disp; |
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cv::gpu::StereoConstantSpaceBP bpm(128, 16, 4, 4); |
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bpm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), dev_disp); |
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dev_disp.download(disp); |
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); |
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disp.convertTo(disp, img_template.type()); |
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EXPECT_MAT_NEAR(img_template, disp, 1.0); |
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} |
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INSTANTIATE_TEST_CASE_P(Calib3D, StereoConstantSpaceBP, testing::ValuesIn(devices())); |
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/////////////////////////////////////////////////////////////////////////////////////////////////////// |
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// projectPoints |
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struct ProjectPoints : testing::TestWithParam<cv::gpu::DeviceInfo> |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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cv::Mat src; |
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cv::Mat rvec; |
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cv::Mat tvec; |
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cv::Mat camera_mat; |
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std::vector<cv::Point2f> dst_gold; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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cv::RNG& rng = cvtest::TS::ptr()->get_rng(); |
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src = cvtest::randomMat(rng, cv::Size(1000, 1), CV_32FC3, 0, 10, false); |
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rvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false); |
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tvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false); |
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camera_mat = cvtest::randomMat(rng, cv::Size(3, 3), CV_32F, 0, 1, false); |
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camera_mat.at<float>(0, 1) = 0.f; |
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camera_mat.at<float>(1, 0) = 0.f; |
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camera_mat.at<float>(2, 0) = 0.f; |
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camera_mat.at<float>(2, 1) = 0.f; |
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cv::projectPoints(src, rvec, tvec, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), dst_gold); |
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} |
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}; |
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TEST_P(ProjectPoints, Accuracy) |
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{ |
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PRINT_PARAM(devInfo); |
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cv::Mat dst; |
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ASSERT_NO_THROW( |
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cv::gpu::GpuMat d_dst; |
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cv::gpu::projectPoints(cv::gpu::GpuMat(src), rvec, tvec, camera_mat, cv::Mat(), d_dst); |
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d_dst.download(dst); |
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); |
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ASSERT_EQ(dst_gold.size(), dst.cols); |
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ASSERT_EQ(1, dst.rows); |
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ASSERT_EQ(CV_32FC2, dst.type()); |
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for (size_t i = 0; i < dst_gold.size(); ++i) |
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{ |
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cv::Point2f res_gold = dst_gold[i]; |
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cv::Point2f res_actual = dst.at<cv::Point2f>(0, i); |
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cv::Point2f err = res_actual - res_gold; |
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ASSERT_LE(err.dot(err) / res_gold.dot(res_gold), 1e-3f); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Calib3D, ProjectPoints, testing::ValuesIn(devices())); |
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/////////////////////////////////////////////////////////////////////////////////////////////////////// |
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// transformPoints |
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struct TransformPoints : testing::TestWithParam<cv::gpu::DeviceInfo> |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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cv::Mat src; |
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cv::Mat rvec; |
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cv::Mat tvec; |
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cv::Mat rot; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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cv::RNG& rng = cvtest::TS::ptr()->get_rng(); |
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src = cvtest::randomMat(rng, cv::Size(1000, 1), CV_32FC3, 0, 10, false); |
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rvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false); |
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tvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false); |
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cv::Rodrigues(rvec, rot); |
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} |
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}; |
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TEST_P(TransformPoints, Accuracy) |
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{ |
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PRINT_PARAM(devInfo); |
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cv::Mat dst; |
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ASSERT_NO_THROW( |
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cv::gpu::GpuMat d_dst; |
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cv::gpu::transformPoints(cv::gpu::GpuMat(src), rvec, tvec, d_dst); |
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d_dst.download(dst); |
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); |
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ASSERT_EQ(src.size(), dst.size()); |
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ASSERT_EQ(src.type(), dst.type()); |
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for (int i = 0; i < dst.cols; ++i) |
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{ |
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cv::Point3f p = src.at<cv::Point3f>(0, i); |
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cv::Point3f res_gold( |
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rot.at<float>(0, 0) * p.x + rot.at<float>(0, 1) * p.y + rot.at<float>(0, 2) * p.z + tvec.at<float>(0, 0), |
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rot.at<float>(1, 0) * p.x + rot.at<float>(1, 1) * p.y + rot.at<float>(1, 2) * p.z + tvec.at<float>(0, 1), |
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rot.at<float>(2, 0) * p.x + rot.at<float>(2, 1) * p.y + rot.at<float>(2, 2) * p.z + tvec.at<float>(0, 2)); |
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cv::Point3f res_actual = dst.at<cv::Point3f>(0, i); |
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cv::Point3f err = res_actual - res_gold; |
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ASSERT_LE(err.dot(err) / res_gold.dot(res_gold), 1e-3f); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(Calib3D, TransformPoints, testing::ValuesIn(devices())); |
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/////////////////////////////////////////////////////////////////////////////////////////////////////// |
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// solvePnPRansac |
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struct SolvePnPRansac : testing::TestWithParam<cv::gpu::DeviceInfo> |
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{ |
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static const int num_points = 5000; |
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cv::gpu::DeviceInfo devInfo; |
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cv::Mat object; |
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cv::Mat camera_mat; |
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std::vector<cv::Point2f> image_vec; |
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cv::Mat rvec_gold; |
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cv::Mat tvec_gold; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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cv::RNG& rng = cvtest::TS::ptr()->get_rng(); |
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object = cvtest::randomMat(rng, cv::Size(num_points, 1), CV_32FC3, 0, 100, false); |
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camera_mat = cvtest::randomMat(rng, cv::Size(3, 3), CV_32F, 0.5, 1, false); |
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camera_mat.at<float>(0, 1) = 0.f; |
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camera_mat.at<float>(1, 0) = 0.f; |
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camera_mat.at<float>(2, 0) = 0.f; |
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camera_mat.at<float>(2, 1) = 0.f; |
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rvec_gold = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false); |
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tvec_gold = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false); |
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cv::projectPoints(object, rvec_gold, tvec_gold, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), image_vec); |
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} |
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}; |
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TEST_P(SolvePnPRansac, Accuracy) |
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{ |
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PRINT_PARAM(devInfo); |
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cv::Mat rvec, tvec; |
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std::vector<int> inliers; |
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ASSERT_NO_THROW( |
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cv::gpu::solvePnPRansac(object, cv::Mat(1, image_vec.size(), CV_32FC2, &image_vec[0]), camera_mat, |
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cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), rvec, tvec, false, 200, 2.f, 100, &inliers); |
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); |
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ASSERT_LE(cv::norm(rvec - rvec_gold), 1e-3f); |
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ASSERT_LE(cv::norm(tvec - tvec_gold), 1e-3f); |
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} |
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INSTANTIATE_TEST_CASE_P(Calib3D, SolvePnPRansac, testing::ValuesIn(devices())); |
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#endif // HAVE_CUDA
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