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.
323 lines
8.7 KiB
323 lines
8.7 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 "perf_precomp.hpp" |
|
|
|
using namespace std; |
|
using namespace testing; |
|
using namespace perf; |
|
|
|
#define ARITHM_MAT_DEPTH Values(CV_8U, CV_16U, CV_32F, CV_64F) |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// Merge |
|
|
|
DEF_PARAM_TEST(Sz_Depth_Cn, cv::Size, MatDepth, MatCn); |
|
|
|
PERF_TEST_P(Sz_Depth_Cn, Merge, |
|
Combine(CUDA_TYPICAL_MAT_SIZES, |
|
ARITHM_MAT_DEPTH, |
|
Values(2, 3, 4))) |
|
{ |
|
const cv::Size size = GET_PARAM(0); |
|
const int depth = GET_PARAM(1); |
|
const int channels = GET_PARAM(2); |
|
|
|
std::vector<cv::Mat> src(channels); |
|
for (int i = 0; i < channels; ++i) |
|
{ |
|
src[i].create(size, depth); |
|
declare.in(src[i], WARMUP_RNG); |
|
} |
|
|
|
if (PERF_RUN_CUDA()) |
|
{ |
|
std::vector<cv::cuda::GpuMat> d_src(channels); |
|
for (int i = 0; i < channels; ++i) |
|
d_src[i].upload(src[i]); |
|
|
|
cv::cuda::GpuMat dst; |
|
|
|
TEST_CYCLE() cv::cuda::merge(d_src, dst); |
|
|
|
CUDA_SANITY_CHECK(dst, 1e-10); |
|
} |
|
else |
|
{ |
|
cv::Mat dst; |
|
|
|
TEST_CYCLE() cv::merge(src, dst); |
|
|
|
CPU_SANITY_CHECK(dst); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// Split |
|
|
|
PERF_TEST_P(Sz_Depth_Cn, Split, |
|
Combine(CUDA_TYPICAL_MAT_SIZES, |
|
ARITHM_MAT_DEPTH, |
|
Values(2, 3, 4))) |
|
{ |
|
const cv::Size size = GET_PARAM(0); |
|
const int depth = GET_PARAM(1); |
|
const int channels = GET_PARAM(2); |
|
|
|
cv::Mat src(size, CV_MAKE_TYPE(depth, channels)); |
|
declare.in(src, WARMUP_RNG); |
|
|
|
if (PERF_RUN_CUDA()) |
|
{ |
|
const cv::cuda::GpuMat d_src(src); |
|
std::vector<cv::cuda::GpuMat> dst; |
|
|
|
TEST_CYCLE() cv::cuda::split(d_src, dst); |
|
|
|
const cv::cuda::GpuMat& dst0 = dst[0]; |
|
const cv::cuda::GpuMat& dst1 = dst[1]; |
|
|
|
CUDA_SANITY_CHECK(dst0, 1e-10); |
|
CUDA_SANITY_CHECK(dst1, 1e-10); |
|
} |
|
else |
|
{ |
|
std::vector<cv::Mat> dst; |
|
|
|
TEST_CYCLE() cv::split(src, dst); |
|
|
|
const cv::Mat& dst0 = dst[0]; |
|
const cv::Mat& dst1 = dst[1]; |
|
|
|
CPU_SANITY_CHECK(dst0); |
|
CPU_SANITY_CHECK(dst1); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// Transpose |
|
|
|
PERF_TEST_P(Sz_Type, Transpose, |
|
Combine(CUDA_TYPICAL_MAT_SIZES, |
|
Values(CV_8UC1, CV_8UC4, CV_16UC2, CV_16SC2, CV_32SC1, CV_32SC2, CV_64FC1))) |
|
{ |
|
const cv::Size size = GET_PARAM(0); |
|
const int type = GET_PARAM(1); |
|
|
|
cv::Mat src(size, type); |
|
declare.in(src, WARMUP_RNG); |
|
|
|
if (PERF_RUN_CUDA()) |
|
{ |
|
const cv::cuda::GpuMat d_src(src); |
|
cv::cuda::GpuMat dst; |
|
|
|
TEST_CYCLE() cv::cuda::transpose(d_src, dst); |
|
|
|
CUDA_SANITY_CHECK(dst, 1e-10); |
|
} |
|
else |
|
{ |
|
cv::Mat dst; |
|
|
|
TEST_CYCLE() cv::transpose(src, dst); |
|
|
|
CPU_SANITY_CHECK(dst); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// Flip |
|
|
|
enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1}; |
|
CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y) |
|
|
|
DEF_PARAM_TEST(Sz_Depth_Cn_Code, cv::Size, MatDepth, MatCn, FlipCode); |
|
|
|
PERF_TEST_P(Sz_Depth_Cn_Code, Flip, |
|
Combine(CUDA_TYPICAL_MAT_SIZES, |
|
Values(CV_8U, CV_16U, CV_32F), |
|
CUDA_CHANNELS_1_3_4, |
|
FlipCode::all())) |
|
{ |
|
const cv::Size size = GET_PARAM(0); |
|
const int depth = GET_PARAM(1); |
|
const int channels = GET_PARAM(2); |
|
const int flipCode = GET_PARAM(3); |
|
|
|
const int type = CV_MAKE_TYPE(depth, channels); |
|
|
|
cv::Mat src(size, type); |
|
declare.in(src, WARMUP_RNG); |
|
|
|
if (PERF_RUN_CUDA()) |
|
{ |
|
const cv::cuda::GpuMat d_src(src); |
|
cv::cuda::GpuMat dst; |
|
|
|
TEST_CYCLE() cv::cuda::flip(d_src, dst, flipCode); |
|
|
|
CUDA_SANITY_CHECK(dst); |
|
} |
|
else |
|
{ |
|
cv::Mat dst; |
|
|
|
TEST_CYCLE() cv::flip(src, dst, flipCode); |
|
|
|
CPU_SANITY_CHECK(dst); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// LutOneChannel |
|
|
|
PERF_TEST_P(Sz_Type, LutOneChannel, |
|
Combine(CUDA_TYPICAL_MAT_SIZES, |
|
Values(CV_8UC1, CV_8UC3))) |
|
{ |
|
const cv::Size size = GET_PARAM(0); |
|
const int type = GET_PARAM(1); |
|
|
|
cv::Mat src(size, type); |
|
declare.in(src, WARMUP_RNG); |
|
|
|
cv::Mat lut(1, 256, CV_8UC1); |
|
declare.in(lut, WARMUP_RNG); |
|
|
|
if (PERF_RUN_CUDA()) |
|
{ |
|
cv::Ptr<cv::cuda::LookUpTable> lutAlg = cv::cuda::createLookUpTable(lut); |
|
|
|
const cv::cuda::GpuMat d_src(src); |
|
cv::cuda::GpuMat dst; |
|
|
|
TEST_CYCLE() lutAlg->transform(d_src, dst); |
|
|
|
CUDA_SANITY_CHECK(dst); |
|
} |
|
else |
|
{ |
|
cv::Mat dst; |
|
|
|
TEST_CYCLE() cv::LUT(src, lut, dst); |
|
|
|
CPU_SANITY_CHECK(dst); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// LutMultiChannel |
|
|
|
PERF_TEST_P(Sz_Type, LutMultiChannel, |
|
Combine(CUDA_TYPICAL_MAT_SIZES, |
|
Values<MatType>(CV_8UC3))) |
|
{ |
|
const cv::Size size = GET_PARAM(0); |
|
const int type = GET_PARAM(1); |
|
|
|
cv::Mat src(size, type); |
|
declare.in(src, WARMUP_RNG); |
|
|
|
cv::Mat lut(1, 256, CV_MAKE_TYPE(CV_8U, src.channels())); |
|
declare.in(lut, WARMUP_RNG); |
|
|
|
if (PERF_RUN_CUDA()) |
|
{ |
|
cv::Ptr<cv::cuda::LookUpTable> lutAlg = cv::cuda::createLookUpTable(lut); |
|
|
|
const cv::cuda::GpuMat d_src(src); |
|
cv::cuda::GpuMat dst; |
|
|
|
TEST_CYCLE() lutAlg->transform(d_src, dst); |
|
|
|
CUDA_SANITY_CHECK(dst); |
|
} |
|
else |
|
{ |
|
cv::Mat dst; |
|
|
|
TEST_CYCLE() cv::LUT(src, lut, dst); |
|
|
|
CPU_SANITY_CHECK(dst); |
|
} |
|
} |
|
|
|
////////////////////////////////////////////////////////////////////// |
|
// CopyMakeBorder |
|
|
|
DEF_PARAM_TEST(Sz_Depth_Cn_Border, cv::Size, MatDepth, MatCn, BorderMode); |
|
|
|
PERF_TEST_P(Sz_Depth_Cn_Border, CopyMakeBorder, |
|
Combine(CUDA_TYPICAL_MAT_SIZES, |
|
Values(CV_8U, CV_16U, CV_32F), |
|
CUDA_CHANNELS_1_3_4, |
|
ALL_BORDER_MODES)) |
|
{ |
|
const cv::Size size = GET_PARAM(0); |
|
const int depth = GET_PARAM(1); |
|
const int channels = GET_PARAM(2); |
|
const int borderMode = GET_PARAM(3); |
|
|
|
const int type = CV_MAKE_TYPE(depth, channels); |
|
|
|
cv::Mat src(size, type); |
|
declare.in(src, WARMUP_RNG); |
|
|
|
if (PERF_RUN_CUDA()) |
|
{ |
|
const cv::cuda::GpuMat d_src(src); |
|
cv::cuda::GpuMat dst; |
|
|
|
TEST_CYCLE() cv::cuda::copyMakeBorder(d_src, dst, 5, 5, 5, 5, borderMode); |
|
|
|
CUDA_SANITY_CHECK(dst); |
|
} |
|
else |
|
{ |
|
cv::Mat dst; |
|
|
|
TEST_CYCLE() cv::copyMakeBorder(src, dst, 5, 5, 5, 5, borderMode); |
|
|
|
CPU_SANITY_CHECK(dst); |
|
} |
|
}
|
|
|