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.
228 lines
7.8 KiB
228 lines
7.8 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. |
|
// |
|
// |
|
// 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 "precomp.hpp" |
|
#include <iostream> |
|
|
|
#ifdef HAVE_CUDA |
|
|
|
/////////////////////////////////////////////////////////////////// |
|
// Gold implementation |
|
|
|
namespace |
|
{ |
|
template <typename T, template <typename> class Interpolator> |
|
void resizeImpl(const cv::Mat& src, cv::Mat& dst, double fx, double fy) |
|
{ |
|
const int cn = src.channels(); |
|
|
|
cv::Size dsize(cv::saturate_cast<int>(src.cols * fx), cv::saturate_cast<int>(src.rows * fy)); |
|
|
|
dst.create(dsize, src.type()); |
|
|
|
float ifx = static_cast<float>(1.0 / fx); |
|
float ify = static_cast<float>(1.0 / fy); |
|
|
|
for (int y = 0; y < dsize.height; ++y) |
|
{ |
|
for (int x = 0; x < dsize.width; ++x) |
|
{ |
|
for (int c = 0; c < cn; ++c) |
|
dst.at<T>(y, x * cn + c) = Interpolator<T>::getValue(src, y * ify, x * ifx, c, cv::BORDER_REPLICATE); |
|
} |
|
} |
|
} |
|
|
|
void resizeGold(const cv::Mat& src, cv::Mat& dst, double fx, double fy, int interpolation) |
|
{ |
|
typedef void (*func_t)(const cv::Mat& src, cv::Mat& dst, double fx, double fy); |
|
|
|
static const func_t nearest_funcs[] = |
|
{ |
|
resizeImpl<unsigned char, NearestInterpolator>, |
|
resizeImpl<signed char, NearestInterpolator>, |
|
resizeImpl<unsigned short, NearestInterpolator>, |
|
resizeImpl<short, NearestInterpolator>, |
|
resizeImpl<int, NearestInterpolator>, |
|
resizeImpl<float, NearestInterpolator> |
|
}; |
|
|
|
|
|
static const func_t linear_funcs[] = |
|
{ |
|
resizeImpl<unsigned char, LinearInterpolator>, |
|
resizeImpl<signed char, LinearInterpolator>, |
|
resizeImpl<unsigned short, LinearInterpolator>, |
|
resizeImpl<short, LinearInterpolator>, |
|
resizeImpl<int, LinearInterpolator>, |
|
resizeImpl<float, LinearInterpolator> |
|
}; |
|
|
|
static const func_t cubic_funcs[] = |
|
{ |
|
resizeImpl<unsigned char, CubicInterpolator>, |
|
resizeImpl<signed char, CubicInterpolator>, |
|
resizeImpl<unsigned short, CubicInterpolator>, |
|
resizeImpl<short, CubicInterpolator>, |
|
resizeImpl<int, CubicInterpolator>, |
|
resizeImpl<float, CubicInterpolator> |
|
}; |
|
|
|
static const func_t* funcs[] = {nearest_funcs, linear_funcs, cubic_funcs}; |
|
|
|
funcs[interpolation][src.depth()](src, dst, fx, fy); |
|
} |
|
} |
|
|
|
/////////////////////////////////////////////////////////////////// |
|
// Test |
|
|
|
PARAM_TEST_CASE(Resize, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpolation, UseRoi) |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
cv::Size size; |
|
double coeff; |
|
int interpolation; |
|
int type; |
|
bool useRoi; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GET_PARAM(0); |
|
size = GET_PARAM(1); |
|
type = GET_PARAM(2); |
|
coeff = GET_PARAM(3); |
|
interpolation = GET_PARAM(4); |
|
useRoi = GET_PARAM(5); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
TEST_P(Resize, Accuracy) |
|
{ |
|
cv::Mat src = randomMat(size, type); |
|
|
|
cv::gpu::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi); |
|
cv::gpu::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, interpolation); |
|
|
|
cv::Mat dst_gold; |
|
resizeGold(src, dst_gold, coeff, coeff, interpolation); |
|
|
|
EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-2 : 1.0); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine( |
|
ALL_DEVICES, |
|
DIFFERENT_SIZES, |
|
testing::Values(MatType(CV_8UC3), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
|
testing::Values(0.3, 0.5, 1.5, 2.0), |
|
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)), |
|
WHOLE_SUBMAT)); |
|
|
|
|
|
///////////////// |
|
PARAM_TEST_CASE(ResizeArea, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpolation, UseRoi) |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
cv::Size size; |
|
double coeff; |
|
int interpolation; |
|
int type; |
|
bool useRoi; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GET_PARAM(0); |
|
size = GET_PARAM(1); |
|
type = GET_PARAM(2); |
|
coeff = GET_PARAM(3); |
|
interpolation = GET_PARAM(4); |
|
useRoi = GET_PARAM(5); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
/////////////////////////////////////////////////////////////////// |
|
// Test NPP |
|
|
|
PARAM_TEST_CASE(ResizeNPP, cv::gpu::DeviceInfo, MatType, double, Interpolation) |
|
{ |
|
cv::gpu::DeviceInfo devInfo; |
|
double coeff; |
|
int interpolation; |
|
int type; |
|
|
|
virtual void SetUp() |
|
{ |
|
devInfo = GET_PARAM(0); |
|
type = GET_PARAM(1); |
|
coeff = GET_PARAM(2); |
|
interpolation = GET_PARAM(3); |
|
|
|
cv::gpu::setDevice(devInfo.deviceID()); |
|
} |
|
}; |
|
|
|
TEST_P(ResizeNPP, Accuracy) |
|
{ |
|
if (type == CV_8UC1 && interpolation == cv::INTER_CUBIC) |
|
return; |
|
|
|
cv::Mat src = readImageType("stereobp/aloe-L.png", type); |
|
|
|
cv::gpu::GpuMat dst; |
|
cv::gpu::resize(loadMat(src), dst, cv::Size(), coeff, coeff, interpolation); |
|
|
|
cv::Mat dst_gold; |
|
resizeGold(src, dst_gold, coeff, coeff, interpolation); |
|
|
|
EXPECT_MAT_SIMILAR(dst_gold, dst, 1e-1); |
|
} |
|
|
|
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeNPP, testing::Combine( |
|
ALL_DEVICES, |
|
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4)), |
|
testing::Values(0.3, 0.5, 1.5, 2.0), |
|
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)))); |
|
|
|
#endif // HAVE_CUDA
|
|
|