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refactored gpu module tests

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This commit is contained in:
Vladislav Vinogradov
2011-06-29 10:14:16 +00:00
parent 6e3142f04b
commit d1b4b5f0de
37 changed files with 7383 additions and 5790 deletions
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modules/gpu/test/test_calib3d.cpp
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@@ -1,135 +1,363 @@
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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"
using namespace cv;
using namespace cv::gpu;
using namespace cvtest;
TEST(projectPoints, accuracy)
{
RNG& rng = TS::ptr()->get_rng();
Mat src = randomMat(rng, Size(1000, 1), CV_32FC3, 0, 10, false);
Mat rvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat tvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat camera_mat = randomMat(rng, Size(3, 3), CV_32F, 0, 1, false);
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;
vector<Point2f> dst;
projectPoints(src, rvec, tvec, camera_mat, Mat(1, 8, CV_32F, Scalar::all(0)), dst);
GpuMat d_dst;
projectPoints(GpuMat(src), rvec, tvec, camera_mat, Mat(), d_dst);
ASSERT_EQ(dst.size(), (size_t)d_dst.cols);
ASSERT_EQ(1, d_dst.rows);
ASSERT_EQ(CV_32FC2, d_dst.type());
Mat h_dst(d_dst);
for (size_t i = 0; i < dst.size(); ++i)
{
Point2f res_gold = dst[i];
Point2f res_actual = h_dst.at<Point2f>(0, i);
Point2f err = res_actual - res_gold;
ASSERT_LT(err.dot(err) / res_gold.dot(res_gold), 1e-3f);
}
}
TEST(transformPoints, accuracy)
{
RNG& rng = TS::ptr()->get_rng();
Mat src = randomMat(rng, Size(1000, 1), CV_32FC3, 0, 10, false);
Mat rvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat tvec = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
GpuMat d_dst;
transformPoints(GpuMat(src), rvec, tvec, d_dst);
ASSERT_TRUE(src.size() == d_dst.size());
ASSERT_EQ(src.type(), d_dst.type());
Mat h_dst(d_dst);
Mat rot;
Rodrigues(rvec, rot);
for (int i = 0; i < h_dst.cols; ++i)
{
Point3f p = src.at<Point3f>(0, i);
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));
Point3f res_actual = h_dst.at<Point3f>(0, i);
Point3f err = res_actual - res_gold;
ASSERT_LT(err.dot(err) / res_gold.dot(res_gold), 1e-3f);
}
}
TEST(solvePnPRansac, accuracy)
{
RNG& rng = TS::ptr()->get_rng();
const int num_points = 5000;
Mat object = randomMat(rng, Size(num_points, 1), CV_32FC3, 0, 100, false);
Mat camera_mat = randomMat(rng, Size(3, 3), CV_32F, 0.5, 1, false);
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;
Mat rvec_gold = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
Mat tvec_gold = randomMat(rng, Size(3, 1), CV_32F, 0, 1, false);
vector<Point2f> image_vec;
projectPoints(object, rvec_gold, tvec_gold, camera_mat, Mat(1, 8, CV_32F, Scalar::all(0)), image_vec);
Mat image(1, image_vec.size(), CV_32FC2, &image_vec[0]);
Mat rvec, tvec;
vector<int> inliers;
gpu::solvePnPRansac(object, image, camera_mat, Mat(1, 8, CV_32F, Scalar::all(0)), rvec, tvec, false, 200, 2.f, 100, &inliers);
ASSERT_LE(norm(rvec - rvec_gold), 1e-3f);
ASSERT_LE(norm(tvec - tvec_gold), 1e-3f);
}
/*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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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
struct StereoTest : testing::TestWithParam<cv::gpu::DeviceInfo>
{
static cv::Mat img_l;
static cv::Mat img_r;
static cv::Mat img_template;
static void TearDownTestCase()
{
img_l.release();
img_r.release();
img_template.release();
}
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
cv::Mat StereoTest::img_l;
cv::Mat StereoTest::img_r;
cv::Mat StereoTest::img_template;
//////////////////////////////////////////////////////////////////////////
// BlockMatching
struct StereoBlockMatching : StereoTest
{
static void SetUpTestCase()
{
img_l = readImage("stereobm/aloe-L.png", CV_LOAD_IMAGE_GRAYSCALE);
img_r = readImage("stereobm/aloe-R.png", CV_LOAD_IMAGE_GRAYSCALE);
img_template = readImage("stereobm/aloe-disp.png", CV_LOAD_IMAGE_GRAYSCALE);
}
};
TEST_P(StereoBlockMatching, Regression)
{
ASSERT_TRUE(!img_l.empty() && !img_r.empty() && !img_template.empty());
PRINT_PARAM(devInfo);
cv::gpu::GpuMat disp;
cv::gpu::StereoBM_GPU bm(0, 128, 19);
bm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), disp);
disp.convertTo(disp, img_template.type());
ASSERT_EQ(img_template.size(), disp.size());
double norm = cv::norm(img_template, (cv::Mat)disp, cv::NORM_INF);
ASSERT_EQ(0.0, norm);
}
INSTANTIATE_TEST_CASE_P(Calib3D, StereoBlockMatching, testing::ValuesIn(devices()));
//////////////////////////////////////////////////////////////////////////
// BeliefPropagation
struct StereoBeliefPropagation : StereoTest
{
static void SetUpTestCase()
{
img_l = readImage("stereobp/aloe-L.png");
img_r = readImage("stereobp/aloe-R.png");
img_template = readImage("stereobp/aloe-disp.png", CV_LOAD_IMAGE_GRAYSCALE);
}
};
TEST_P(StereoBeliefPropagation, Regression)
{
ASSERT_TRUE(!img_l.empty() && !img_r.empty() && !img_template.empty());
PRINT_PARAM(devInfo);
cv::gpu::GpuMat disp;
cv::gpu::StereoBeliefPropagation bpm(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
bpm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), disp);
disp.convertTo(disp, img_template.type());
ASSERT_EQ(img_template.size(), disp.size());
double norm = cv::norm(img_template, (cv::Mat)disp, cv::NORM_INF);
ASSERT_EQ(0.0, norm);
}
INSTANTIATE_TEST_CASE_P(Calib3D, StereoBeliefPropagation, testing::ValuesIn(devices()));
//////////////////////////////////////////////////////////////////////////
// ConstantSpaceBP
struct StereoConstantSpaceBP : StereoTest
{
static void SetUpTestCase()
{
img_l = readImage("csstereobp/aloe-L.png");
img_r = readImage("csstereobp/aloe-R.png");
}
virtual void SetUp()
{
StereoTest::SetUp();
if (supportFeature(GetParam(), cv::gpu::FEATURE_SET_COMPUTE_20))
img_template = readImage("csstereobp/aloe-disp.png", CV_LOAD_IMAGE_GRAYSCALE);
else
img_template = readImage("csstereobp/aloe-disp_CC1X.png", CV_LOAD_IMAGE_GRAYSCALE);
}
};
TEST_P(StereoConstantSpaceBP, Regression)
{
ASSERT_TRUE(!img_l.empty() && !img_r.empty() && !img_template.empty());
PRINT_PARAM(devInfo);
cv::gpu::GpuMat disp;
cv::gpu::StereoConstantSpaceBP bpm(128, 16, 4, 4);
bpm(cv::gpu::GpuMat(img_l), cv::gpu::GpuMat(img_r), disp);
disp.convertTo(disp, img_template.type());
ASSERT_EQ(img_template.size(), disp.size());
double norm = cv::norm(img_template, (cv::Mat)disp, cv::NORM_INF);
ASSERT_EQ(0.0, norm);
}
INSTANTIATE_TEST_CASE_P(Calib3D, StereoConstantSpaceBP, testing::ValuesIn(devices()));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// projectPoints
struct ProjectPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
cv::Mat src;
cv::Mat rvec;
cv::Mat tvec;
cv::Mat camera_mat;
std::vector<cv::Point2f> dst_gold;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = cvtest::TS::ptr()->get_rng();
src = cvtest::randomMat(rng, cv::Size(1000, 1), CV_32FC3, 0, 10, false);
rvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false);
tvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false);
camera_mat = cvtest::randomMat(rng, cv::Size(3, 3), CV_32F, 0, 1, false);
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::projectPoints(src, rvec, tvec, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), dst_gold);
}
};
TEST_P(ProjectPoints, Accuracy)
{
PRINT_PARAM(devInfo);
cv::Mat dst;
ASSERT_NO_THROW(
cv::gpu::GpuMat d_dst;
cv::gpu::projectPoints(cv::gpu::GpuMat(src), rvec, tvec, camera_mat, cv::Mat(), d_dst);
d_dst.download(dst);
);
ASSERT_EQ(dst_gold.size(), dst.cols);
ASSERT_EQ(1, dst.rows);
ASSERT_EQ(CV_32FC2, dst.type());
for (size_t i = 0; i < dst_gold.size(); ++i)
{
cv::Point2f res_gold = dst_gold[i];
cv::Point2f res_actual = dst.at<cv::Point2f>(0, i);
cv::Point2f err = res_actual - res_gold;
ASSERT_LE(err.dot(err) / res_gold.dot(res_gold), 1e-3f);
}
}
INSTANTIATE_TEST_CASE_P(Calib3D, ProjectPoints, testing::ValuesIn(devices()));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// transformPoints
struct TransformPoints : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
cv::Mat src;
cv::Mat rvec;
cv::Mat tvec;
cv::Mat rot;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = cvtest::TS::ptr()->get_rng();
src = cvtest::randomMat(rng, cv::Size(1000, 1), CV_32FC3, 0, 10, false);
rvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false);
tvec = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false);
cv::Rodrigues(rvec, rot);
}
};
TEST_P(TransformPoints, Accuracy)
{
PRINT_PARAM(devInfo);
cv::Mat dst;
ASSERT_NO_THROW(
cv::gpu::GpuMat d_dst;
cv::gpu::transformPoints(cv::gpu::GpuMat(src), rvec, tvec, d_dst);
d_dst.download(dst);
);
ASSERT_EQ(src.size(), dst.size());
ASSERT_EQ(src.type(), dst.type());
for (int i = 0; i < dst.cols; ++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));
cv::Point3f res_actual = dst.at<cv::Point3f>(0, i);
cv::Point3f err = res_actual - res_gold;
ASSERT_LE(err.dot(err) / res_gold.dot(res_gold), 1e-3f);
}
}
INSTANTIATE_TEST_CASE_P(Calib3D, TransformPoints, testing::ValuesIn(devices()));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// solvePnPRansac
struct SolvePnPRansac : testing::TestWithParam<cv::gpu::DeviceInfo>
{
static const int num_points = 5000;
cv::gpu::DeviceInfo devInfo;
cv::Mat object;
cv::Mat camera_mat;
std::vector<cv::Point2f> image_vec;
cv::Mat rvec_gold;
cv::Mat tvec_gold;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = cvtest::TS::ptr()->get_rng();
object = cvtest::randomMat(rng, cv::Size(num_points, 1), CV_32FC3, 0, 100, false);
camera_mat = cvtest::randomMat(rng, cv::Size(3, 3), CV_32F, 0.5, 1, false);
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;
rvec_gold = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false);
tvec_gold = cvtest::randomMat(rng, cv::Size(3, 1), CV_32F, 0, 1, false);
cv::projectPoints(object, rvec_gold, tvec_gold, camera_mat, cv::Mat(1, 8, CV_32F, cv::Scalar::all(0)), image_vec);
}
};
TEST_P(SolvePnPRansac, Accuracy)
{
PRINT_PARAM(devInfo);
cv::Mat rvec, tvec;
std::vector<int> inliers;
ASSERT_NO_THROW(
cv::gpu::solvePnPRansac(object, cv::Mat(1, 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-3f);
ASSERT_LE(cv::norm(tvec - tvec_gold), 1e-3f);
}
INSTANTIATE_TEST_CASE_P(Calib3D, SolvePnPRansac, testing::ValuesIn(devices()));
#endif // HAVE_CUDA