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.
302 lines
11 KiB
302 lines
11 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; |
|
|
|
namespace |
|
{ |
|
cv::Mat createTransfomMatrix(cv::Size srcSize, double angle) |
|
{ |
|
cv::Mat M(3, 3, CV_64FC1); |
|
|
|
M.at<double>(0, 0) = std::cos(angle); M.at<double>(0, 1) = -std::sin(angle); M.at<double>(0, 2) = srcSize.width / 2; |
|
M.at<double>(1, 0) = std::sin(angle); M.at<double>(1, 1) = std::cos(angle); M.at<double>(1, 2) = 0.0; |
|
M.at<double>(2, 0) = 0.0 ; M.at<double>(2, 1) = 0.0 ; M.at<double>(2, 2) = 1.0; |
|
|
|
return M; |
|
} |
|
} |
|
|
|
/////////////////////////////////////////////////////////////////// |
|
// Test buildWarpPerspectiveMaps |
|
|
|
PARAM_TEST_CASE(BuildWarpPerspectiveMaps, cv::gpu::DeviceInfo, cv::Size, Inverse) |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
cv::Size size; |
|
bool inverse; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GET_PARAM(0); |
|
size = GET_PARAM(1); |
|
inverse = GET_PARAM(2); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
GPU_TEST_P(BuildWarpPerspectiveMaps, Accuracy) |
|
{ |
|
cv::Mat M = createTransfomMatrix(size, CV_PI / 4); |
|
|
|
cv::gpu::GpuMat xmap, ymap; |
|
cv::gpu::buildWarpPerspectiveMaps(M, inverse, size, xmap, ymap); |
|
|
|
cv::Mat src = randomMat(randomSize(200, 400), CV_8UC1); |
|
int interpolation = cv::INTER_NEAREST; |
|
int borderMode = cv::BORDER_CONSTANT; |
|
int flags = interpolation; |
|
if (inverse) |
|
flags |= cv::WARP_INVERSE_MAP; |
|
|
|
cv::Mat dst; |
|
cv::remap(src, dst, cv::Mat(xmap), cv::Mat(ymap), interpolation, borderMode); |
|
|
|
cv::Mat dst_gold; |
|
cv::warpPerspective(src, dst_gold, M, size, flags, borderMode); |
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, 0.0); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, BuildWarpPerspectiveMaps, testing::Combine( |
|
ALL_DEVICES, |
|
DIFFERENT_SIZES, |
|
DIRECT_INVERSE)); |
|
|
|
/////////////////////////////////////////////////////////////////// |
|
// Gold implementation |
|
|
|
namespace |
|
{ |
|
template <typename T, template <typename> class Interpolator> void warpPerspectiveImpl(const cv::Mat& src, const cv::Mat& M, cv::Size dsize, cv::Mat& dst, int borderType, cv::Scalar borderVal) |
|
{ |
|
const int cn = src.channels(); |
|
|
|
dst.create(dsize, src.type()); |
|
|
|
for (int y = 0; y < dsize.height; ++y) |
|
{ |
|
for (int x = 0; x < dsize.width; ++x) |
|
{ |
|
float coeff = static_cast<float>(M.at<double>(2, 0) * x + M.at<double>(2, 1) * y + M.at<double>(2, 2)); |
|
|
|
float xcoo = static_cast<float>((M.at<double>(0, 0) * x + M.at<double>(0, 1) * y + M.at<double>(0, 2)) / coeff); |
|
float ycoo = static_cast<float>((M.at<double>(1, 0) * x + M.at<double>(1, 1) * y + M.at<double>(1, 2)) / coeff); |
|
|
|
for (int c = 0; c < cn; ++c) |
|
dst.at<T>(y, x * cn + c) = Interpolator<T>::getValue(src, ycoo, xcoo, c, borderType, borderVal); |
|
} |
|
} |
|
} |
|
|
|
void warpPerspectiveGold(const cv::Mat& src, const cv::Mat& M, bool inverse, cv::Size dsize, cv::Mat& dst, int interpolation, int borderType, cv::Scalar borderVal) |
|
{ |
|
typedef void (*func_t)(const cv::Mat& src, const cv::Mat& M, cv::Size dsize, cv::Mat& dst, int borderType, cv::Scalar borderVal); |
|
|
|
static const func_t nearest_funcs[] = |
|
{ |
|
warpPerspectiveImpl<unsigned char, NearestInterpolator>, |
|
warpPerspectiveImpl<signed char, NearestInterpolator>, |
|
warpPerspectiveImpl<unsigned short, NearestInterpolator>, |
|
warpPerspectiveImpl<short, NearestInterpolator>, |
|
warpPerspectiveImpl<int, NearestInterpolator>, |
|
warpPerspectiveImpl<float, NearestInterpolator> |
|
}; |
|
|
|
static const func_t linear_funcs[] = |
|
{ |
|
warpPerspectiveImpl<unsigned char, LinearInterpolator>, |
|
warpPerspectiveImpl<signed char, LinearInterpolator>, |
|
warpPerspectiveImpl<unsigned short, LinearInterpolator>, |
|
warpPerspectiveImpl<short, LinearInterpolator>, |
|
warpPerspectiveImpl<int, LinearInterpolator>, |
|
warpPerspectiveImpl<float, LinearInterpolator> |
|
}; |
|
|
|
static const func_t cubic_funcs[] = |
|
{ |
|
warpPerspectiveImpl<unsigned char, CubicInterpolator>, |
|
warpPerspectiveImpl<signed char, CubicInterpolator>, |
|
warpPerspectiveImpl<unsigned short, CubicInterpolator>, |
|
warpPerspectiveImpl<short, CubicInterpolator>, |
|
warpPerspectiveImpl<int, CubicInterpolator>, |
|
warpPerspectiveImpl<float, CubicInterpolator> |
|
}; |
|
|
|
static const func_t* funcs[] = {nearest_funcs, linear_funcs, cubic_funcs}; |
|
|
|
if (inverse) |
|
funcs[interpolation][src.depth()](src, M, dsize, dst, borderType, borderVal); |
|
else |
|
{ |
|
cv::Mat iM; |
|
cv::invert(M, iM); |
|
funcs[interpolation][src.depth()](src, iM, dsize, dst, borderType, borderVal); |
|
} |
|
} |
|
} |
|
|
|
/////////////////////////////////////////////////////////////////// |
|
// Test |
|
|
|
PARAM_TEST_CASE(WarpPerspective, cv::gpu::DeviceInfo, cv::Size, MatType, Inverse, Interpolation, BorderType, UseRoi) |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
cv::Size size; |
|
int type; |
|
bool inverse; |
|
int interpolation; |
|
int borderType; |
|
bool useRoi; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GET_PARAM(0); |
|
size = GET_PARAM(1); |
|
type = GET_PARAM(2); |
|
inverse = GET_PARAM(3); |
|
interpolation = GET_PARAM(4); |
|
borderType = GET_PARAM(5); |
|
useRoi = GET_PARAM(6); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
GPU_TEST_P(WarpPerspective, Accuracy) |
|
{ |
|
cv::Mat src = randomMat(size, type); |
|
cv::Mat M = createTransfomMatrix(size, CV_PI / 3); |
|
int flags = interpolation; |
|
if (inverse) |
|
flags |= cv::WARP_INVERSE_MAP; |
|
cv::Scalar val = randomScalar(0.0, 255.0); |
|
|
|
cv::gpu::GpuMat dst = createMat(size, type, useRoi); |
|
cv::gpu::warpPerspective(loadMat(src, useRoi), dst, M, size, flags, borderType, val); |
|
|
|
cv::Mat dst_gold; |
|
warpPerspectiveGold(src, M, inverse, size, dst_gold, interpolation, borderType, val); |
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-1 : 1.0); |
|
} |
|
|
|
#ifdef OPENCV_TINY_GPU_MODULE |
|
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpPerspective, testing::Combine( |
|
ALL_DEVICES, |
|
DIFFERENT_SIZES, |
|
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
|
DIRECT_INVERSE, |
|
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR)), |
|
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_REFLECT)), |
|
WHOLE_SUBMAT)); |
|
#else |
|
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpPerspective, testing::Combine( |
|
ALL_DEVICES, |
|
DIFFERENT_SIZES, |
|
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
|
DIRECT_INVERSE, |
|
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), |
|
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_REFLECT), BorderType(cv::BORDER_WRAP)), |
|
WHOLE_SUBMAT)); |
|
#endif |
|
|
|
/////////////////////////////////////////////////////////////////// |
|
// Test NPP |
|
|
|
PARAM_TEST_CASE(WarpPerspectiveNPP, cv::gpu::DeviceInfo, MatType, Inverse, Interpolation) |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
int type; |
|
bool inverse; |
|
int interpolation; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GET_PARAM(0); |
|
type = GET_PARAM(1); |
|
inverse = GET_PARAM(2); |
|
interpolation = GET_PARAM(3); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
GPU_TEST_P(WarpPerspectiveNPP, Accuracy) |
|
{ |
|
cv::Mat src = readImageType("stereobp/aloe-L.png", type); |
|
ASSERT_FALSE(src.empty()); |
|
|
|
cv::Mat M = createTransfomMatrix(src.size(), CV_PI / 4); |
|
int flags = interpolation; |
|
if (inverse) |
|
flags |= cv::WARP_INVERSE_MAP; |
|
|
|
cv::gpu::GpuMat dst; |
|
cv::gpu::warpPerspective(loadMat(src), dst, M, src.size(), flags); |
|
|
|
cv::Mat dst_gold; |
|
warpPerspectiveGold(src, M, inverse, src.size(), dst_gold, interpolation, cv::BORDER_CONSTANT, cv::Scalar::all(0)); |
|
|
|
EXPECT_MAT_SIMILAR(dst_gold, dst, 2e-2); |
|
} |
|
|
|
#ifdef OPENCV_TINY_GPU_MODULE |
|
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpPerspectiveNPP, testing::Combine( |
|
ALL_DEVICES, |
|
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
|
DIRECT_INVERSE, |
|
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR)))); |
|
#else |
|
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, WarpPerspectiveNPP, testing::Combine( |
|
ALL_DEVICES, |
|
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
|
DIRECT_INVERSE, |
|
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)))); |
|
#endif |
|
|
|
#endif // HAVE_CUDA
|
|
|