mirror of
https://github.com/opencv/opencv.git
synced 2024-12-27 11:28:14 +08:00
284 lines
10 KiB
C++
284 lines
10 KiB
C++
/*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::cuda::DeviceInfo, cv::Size, Inverse)
|
|
{
|
|
cv::cuda::DeviceInfo devInfo;
|
|
cv::Size size;
|
|
bool inverse;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
devInfo = GET_PARAM(0);
|
|
size = GET_PARAM(1);
|
|
inverse = GET_PARAM(2);
|
|
|
|
cv::cuda::setDevice(devInfo.deviceID());
|
|
}
|
|
};
|
|
|
|
CUDA_TEST_P(BuildWarpPerspectiveMaps, Accuracy)
|
|
{
|
|
cv::Mat M = createTransfomMatrix(size, CV_PI / 4);
|
|
|
|
cv::cuda::GpuMat xmap, ymap;
|
|
cv::cuda::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(CUDA_Warping, 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::cuda::DeviceInfo, cv::Size, MatType, Inverse, Interpolation, BorderType, UseRoi)
|
|
{
|
|
cv::cuda::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::cuda::setDevice(devInfo.deviceID());
|
|
}
|
|
};
|
|
|
|
CUDA_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::cuda::GpuMat dst = createMat(size, type, useRoi);
|
|
cv::cuda::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);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(CUDA_Warping, 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));
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
// Test NPP
|
|
|
|
PARAM_TEST_CASE(WarpPerspectiveNPP, cv::cuda::DeviceInfo, MatType, Inverse, Interpolation)
|
|
{
|
|
cv::cuda::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::cuda::setDevice(devInfo.deviceID());
|
|
}
|
|
};
|
|
|
|
CUDA_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::cuda::GpuMat dst;
|
|
cv::cuda::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);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(CUDA_Warping, 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 // HAVE_CUDA
|