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Open Source Computer Vision Library
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193 lines
6.7 KiB
193 lines
6.7 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) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage 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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// 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 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 "test_precomp.hpp" |
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#if defined HAVE_CUDA && defined HAVE_OPENCV_CALIB3D |
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#include "opencv2/calib3d.hpp" |
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namespace opencv_test { namespace { |
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/////////////////////////////////////////////////////////////////////////////////////////////////////// |
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// transformPoints |
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struct TransformPoints : testing::TestWithParam<cv::cuda::DeviceInfo> |
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{ |
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cv::cuda::DeviceInfo devInfo; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::cuda::setDevice(devInfo.deviceID()); |
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} |
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}; |
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CUDA_TEST_P(TransformPoints, Accuracy) |
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{ |
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cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10); |
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cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
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cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
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cv::cuda::GpuMat dst; |
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cv::cuda::transformPoints(loadMat(src), rvec, tvec, dst); |
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ASSERT_EQ(src.size(), dst.size()); |
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ASSERT_EQ(src.type(), dst.type()); |
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cv::Mat h_dst(dst); |
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cv::Mat rot; |
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cv::Rodrigues(rvec, rot); |
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for (int i = 0; i < h_dst.cols; ++i) |
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{ |
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cv::Point3f res = h_dst.at<cv::Point3f>(0, i); |
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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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ASSERT_POINT3_NEAR(res_gold, res, 1e-5); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(CUDA_Calib3D, TransformPoints, ALL_DEVICES); |
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/////////////////////////////////////////////////////////////////////////////////////////////////////// |
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// ProjectPoints |
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struct ProjectPoints : testing::TestWithParam<cv::cuda::DeviceInfo> |
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{ |
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cv::cuda::DeviceInfo devInfo; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::cuda::setDevice(devInfo.deviceID()); |
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} |
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}; |
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CUDA_TEST_P(ProjectPoints, Accuracy) |
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{ |
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cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10); |
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cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
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cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
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cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1); |
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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::cuda::GpuMat dst; |
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cv::cuda::projectPoints(loadMat(src), rvec, tvec, camera_mat, cv::Mat(), dst); |
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ASSERT_EQ(1, dst.rows); |
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ASSERT_EQ(MatType(CV_32FC2), MatType(dst.type())); |
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std::vector<cv::Point2f> dst_gold; |
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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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ASSERT_EQ(dst_gold.size(), static_cast<size_t>(dst.cols)); |
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cv::Mat h_dst(dst); |
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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 = h_dst.at<cv::Point2f>(0, (int)i); |
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cv::Point2f res_gold = dst_gold[i]; |
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ASSERT_LE(cv::norm(res_gold - res) / cv::norm(res_gold), 1e-3f); |
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} |
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} |
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INSTANTIATE_TEST_CASE_P(CUDA_Calib3D, ProjectPoints, ALL_DEVICES); |
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/////////////////////////////////////////////////////////////////////////////////////////////////////// |
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// SolvePnPRansac |
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struct SolvePnPRansac : testing::TestWithParam<cv::cuda::DeviceInfo> |
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{ |
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cv::cuda::DeviceInfo devInfo; |
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virtual void SetUp() |
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{ |
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devInfo = GetParam(); |
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cv::cuda::setDevice(devInfo.deviceID()); |
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} |
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}; |
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CUDA_TEST_P(SolvePnPRansac, Accuracy) |
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{ |
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cv::Mat object = randomMat(cv::Size(5000, 1), CV_32FC3, -2000, 2000); |
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cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1); |
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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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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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rvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
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tvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1000); |
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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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cv::Mat rvec, tvec; |
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std::vector<int> inliers; |
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cv::cuda::solvePnPRansac(object, cv::Mat(1, (int)image_vec.size(), CV_32FC2, &image_vec[0]), |
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camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), |
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rvec, tvec, false, 200, 2.f, 100, &inliers); |
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ASSERT_LE(cv::norm(rvec - rvec_gold), 1e-3); |
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ASSERT_LE(cv::norm(tvec, tvec_gold, NORM_L2 | NORM_RELATIVE), 1e-3); |
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} |
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INSTANTIATE_TEST_CASE_P(CUDA_Calib3D, SolvePnPRansac, ALL_DEVICES); |
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}} // namespace |
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#endif // HAVE_CUDA
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