mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
190 lines
6.6 KiB
190 lines
6.6 KiB
/*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 |
|
|
|
using namespace cvtest; |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
// transformPoints |
|
|
|
struct TransformPoints : testing::TestWithParam<cv::gpu::DeviceInfo> |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GetParam(); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
GPU_TEST_P(TransformPoints, Accuracy) |
|
{ |
|
cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10); |
|
cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
|
cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
|
|
|
cv::gpu::GpuMat dst; |
|
cv::gpu::transformPoints(loadMat(src), rvec, tvec, dst); |
|
|
|
ASSERT_EQ(src.size(), dst.size()); |
|
ASSERT_EQ(src.type(), dst.type()); |
|
|
|
cv::Mat h_dst(dst); |
|
|
|
cv::Mat rot; |
|
cv::Rodrigues(rvec, rot); |
|
|
|
for (int i = 0; i < h_dst.cols; ++i) |
|
{ |
|
cv::Point3f res = h_dst.at<cv::Point3f>(0, i); |
|
|
|
cv::Point3f p = src.at<cv::Point3f>(0, i); |
|
cv::Point3f res_gold( |
|
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), |
|
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), |
|
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)); |
|
|
|
ASSERT_POINT3_NEAR(res_gold, res, 1e-5); |
|
} |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, TransformPoints, ALL_DEVICES); |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
// ProjectPoints |
|
|
|
struct ProjectPoints : testing::TestWithParam<cv::gpu::DeviceInfo> |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GetParam(); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
GPU_TEST_P(ProjectPoints, Accuracy) |
|
{ |
|
cv::Mat src = randomMat(cv::Size(1000, 1), CV_32FC3, 0, 10); |
|
cv::Mat rvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
|
cv::Mat tvec = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
|
cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1); |
|
camera_mat.at<float>(0, 1) = 0.f; |
|
camera_mat.at<float>(1, 0) = 0.f; |
|
camera_mat.at<float>(2, 0) = 0.f; |
|
camera_mat.at<float>(2, 1) = 0.f; |
|
|
|
cv::gpu::GpuMat dst; |
|
cv::gpu::projectPoints(loadMat(src), rvec, tvec, camera_mat, cv::Mat(), dst); |
|
|
|
ASSERT_EQ(1, dst.rows); |
|
ASSERT_EQ(MatType(CV_32FC2), MatType(dst.type())); |
|
|
|
std::vector<cv::Point2f> dst_gold; |
|
cv::projectPoints(src, rvec, tvec, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), dst_gold); |
|
|
|
ASSERT_EQ(dst_gold.size(), static_cast<size_t>(dst.cols)); |
|
|
|
cv::Mat h_dst(dst); |
|
|
|
for (size_t i = 0; i < dst_gold.size(); ++i) |
|
{ |
|
cv::Point2f res = h_dst.at<cv::Point2f>(0, (int)i); |
|
cv::Point2f res_gold = dst_gold[i]; |
|
|
|
ASSERT_LE(cv::norm(res_gold - res) / cv::norm(res_gold), 1e-3f); |
|
} |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, ProjectPoints, ALL_DEVICES); |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
// SolvePnPRansac |
|
|
|
struct SolvePnPRansac : testing::TestWithParam<cv::gpu::DeviceInfo> |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GetParam(); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
GPU_TEST_P(SolvePnPRansac, Accuracy) |
|
{ |
|
cv::Mat object = randomMat(cv::Size(5000, 1), CV_32FC3, 0, 100); |
|
cv::Mat camera_mat = randomMat(cv::Size(3, 3), CV_32F, 0.5, 1); |
|
camera_mat.at<float>(0, 1) = 0.f; |
|
camera_mat.at<float>(1, 0) = 0.f; |
|
camera_mat.at<float>(2, 0) = 0.f; |
|
camera_mat.at<float>(2, 1) = 0.f; |
|
|
|
std::vector<cv::Point2f> image_vec; |
|
cv::Mat rvec_gold; |
|
cv::Mat tvec_gold; |
|
rvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
|
tvec_gold = randomMat(cv::Size(3, 1), CV_32F, 0, 1); |
|
cv::projectPoints(object, rvec_gold, tvec_gold, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), image_vec); |
|
|
|
cv::Mat rvec, tvec; |
|
std::vector<int> inliers; |
|
cv::gpu::solvePnPRansac(object, cv::Mat(1, (int)image_vec.size(), CV_32FC2, &image_vec[0]), |
|
camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), |
|
rvec, tvec, false, 200, 2.f, 100, &inliers); |
|
|
|
ASSERT_LE(cv::norm(rvec - rvec_gold), 1e-3); |
|
ASSERT_LE(cv::norm(tvec - tvec_gold), 1e-3); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, SolvePnPRansac, ALL_DEVICES); |
|
|
|
#endif // HAVE_CUDA
|
|
|