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349 lines
11 KiB
C++
349 lines
11 KiB
C++
/*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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#ifdef HAVE_CUDA
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using namespace cvtest;
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//////////////////////////////////////////////////////////////////////////
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// StereoBM
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struct StereoBM : testing::TestWithParam<cv::gpu::DeviceInfo>
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{
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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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}
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};
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GPU_TEST_P(StereoBM, Regression)
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{
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cv::Mat left_image = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
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cv::Mat right_image = readImage("stereobm/aloe-R.png", cv::IMREAD_GRAYSCALE);
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cv::Mat disp_gold = readImage("stereobm/aloe-disp.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(left_image.empty());
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ASSERT_FALSE(right_image.empty());
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ASSERT_FALSE(disp_gold.empty());
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cv::gpu::StereoBM_GPU bm(0, 128, 19);
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cv::gpu::GpuMat disp;
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bm(loadMat(left_image), loadMat(right_image), disp);
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EXPECT_MAT_NEAR(disp_gold, disp, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoBM, ALL_DEVICES);
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//////////////////////////////////////////////////////////////////////////
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// StereoBeliefPropagation
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struct StereoBeliefPropagation : testing::TestWithParam<cv::gpu::DeviceInfo>
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{
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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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}
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};
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GPU_TEST_P(StereoBeliefPropagation, Regression)
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{
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cv::Mat left_image = readImage("stereobp/aloe-L.png");
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cv::Mat right_image = readImage("stereobp/aloe-R.png");
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cv::Mat disp_gold = readImage("stereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(left_image.empty());
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ASSERT_FALSE(right_image.empty());
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ASSERT_FALSE(disp_gold.empty());
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cv::gpu::StereoBeliefPropagation bp(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
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cv::gpu::GpuMat disp;
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bp(loadMat(left_image), loadMat(right_image), disp);
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cv::Mat h_disp(disp);
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h_disp.convertTo(h_disp, disp_gold.depth());
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EXPECT_MAT_NEAR(disp_gold, h_disp, 0.0);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoBeliefPropagation, ALL_DEVICES);
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//////////////////////////////////////////////////////////////////////////
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// StereoConstantSpaceBP
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struct StereoConstantSpaceBP : testing::TestWithParam<cv::gpu::DeviceInfo>
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{
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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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}
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};
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GPU_TEST_P(StereoConstantSpaceBP, Regression)
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{
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cv::Mat left_image = readImage("csstereobp/aloe-L.png");
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cv::Mat right_image = readImage("csstereobp/aloe-R.png");
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cv::Mat disp_gold;
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if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
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disp_gold = readImage("csstereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
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else
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disp_gold = readImage("csstereobp/aloe-disp_CC1X.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(left_image.empty());
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ASSERT_FALSE(right_image.empty());
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ASSERT_FALSE(disp_gold.empty());
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cv::gpu::StereoConstantSpaceBP csbp(128, 16, 4, 4);
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cv::gpu::GpuMat disp;
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csbp(loadMat(left_image), loadMat(right_image), disp);
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cv::Mat h_disp(disp);
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h_disp.convertTo(h_disp, disp_gold.depth());
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EXPECT_MAT_SIMILAR(disp_gold, h_disp, 1e-4);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoConstantSpaceBP, ALL_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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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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}
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};
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GPU_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::gpu::GpuMat dst;
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cv::gpu::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(GPU_Calib3D, TransformPoints, ALL_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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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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}
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};
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GPU_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::gpu::GpuMat dst;
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cv::gpu::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(GPU_Calib3D, ProjectPoints, ALL_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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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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}
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};
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GPU_TEST_P(SolvePnPRansac, Accuracy)
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{
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cv::Mat object = randomMat(cv::Size(5000, 1), CV_32FC3, 0, 100);
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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, 1);
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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::gpu::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), 2e-3);
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ASSERT_LE(cv::norm(tvec - tvec_gold), 2e-3);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Calib3D, SolvePnPRansac, ALL_DEVICES);
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////////////////////////////////////////////////////////////////////////////////
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// reprojectImageTo3D
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PARAM_TEST_CASE(ReprojectImageTo3D, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
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{
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cv::gpu::DeviceInfo devInfo;
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cv::Size size;
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int depth;
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bool useRoi;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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size = GET_PARAM(1);
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depth = GET_PARAM(2);
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useRoi = GET_PARAM(3);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(ReprojectImageTo3D, Accuracy)
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{
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cv::Mat disp = randomMat(size, depth, 5.0, 30.0);
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cv::Mat Q = randomMat(cv::Size(4, 4), CV_32FC1, 0.1, 1.0);
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cv::gpu::GpuMat dst;
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cv::gpu::reprojectImageTo3D(loadMat(disp, useRoi), dst, Q, 3);
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cv::Mat dst_gold;
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cv::reprojectImageTo3D(disp, dst_gold, Q, false);
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EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
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}
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INSTANTIATE_TEST_CASE_P(GPU_Calib3D, ReprojectImageTo3D, testing::Combine(
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ALL_DEVICES,
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DIFFERENT_SIZES,
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testing::Values(MatDepth(CV_8U), MatDepth(CV_16S)),
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WHOLE_SUBMAT));
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#endif // HAVE_CUDA
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