371 lines
11 KiB
C++
371 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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// 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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using namespace cvtest;
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using namespace testing;
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//////////////////////////////////////////////////////////////////////////
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// BlockMatching
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struct StereoBlockMatching : 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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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, ALL_DEVICES);
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//////////////////////////////////////////////////////////////////////////
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// BeliefPropagation
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struct StereoBeliefPropagation : 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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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, ALL_DEVICES);
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//////////////////////////////////////////////////////////////////////////
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// ConstantSpaceBP
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struct StereoConstantSpaceBP : 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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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, ALL_DEVICES);
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///////////////////////////////////////////////////////////////////////////////////////////////////////
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// projectPoints
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struct ProjectPoints : 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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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, ALL_DEVICES);
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///////////////////////////////////////////////////////////////////////////////////////////////////////
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// transformPoints
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struct TransformPoints : 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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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, ALL_DEVICES);
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///////////////////////////////////////////////////////////////////////////////////////////////////////
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// solvePnPRansac
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struct SolvePnPRansac : 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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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, ALL_DEVICES);
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#endif // HAVE_CUDA
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