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gpuwarping module for image warping

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This commit is contained in:
Vladislav Vinogradov
2013-04-18 10:45:48 +04:00
parent 71eeaa7276
commit fc3730fcc2
50 changed files with 2068 additions and 1537 deletions
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modules/gpuwarping/perf/perf_main.cpp Normal file
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/*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 perf;
CV_PERF_TEST_MAIN(gpuwarping, printCudaInfo())

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modules/gpuwarping/perf/perf_precomp.cpp Normal file
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/*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"

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modules/gpuwarping/perf/perf_precomp.hpp Normal file
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/*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*/
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
# endif
#endif
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/ts/gpu_perf.hpp"
#include "opencv2/gpuwarping.hpp"
#include "opencv2/imgproc.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined
#endif
#endif

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modules/gpuwarping/perf/perf_warping.cpp Normal file
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/*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;
//////////////////////////////////////////////////////////////////////
// Remap
enum { HALF_SIZE=0, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH };
CV_ENUM(RemapMode, HALF_SIZE, UPSIDE_DOWN, REFLECTION_X, REFLECTION_BOTH)
void generateMap(cv::Mat& map_x, cv::Mat& map_y, int remapMode)
{
for (int j = 0; j < map_x.rows; ++j)
{
for (int i = 0; i < map_x.cols; ++i)
{
switch (remapMode)
{
case HALF_SIZE:
if (i > map_x.cols*0.25 && i < map_x.cols*0.75 && j > map_x.rows*0.25 && j < map_x.rows*0.75)
{
map_x.at<float>(j,i) = 2.f * (i - map_x.cols * 0.25f) + 0.5f;
map_y.at<float>(j,i) = 2.f * (j - map_x.rows * 0.25f) + 0.5f;
}
else
{
map_x.at<float>(j,i) = 0.f;
map_y.at<float>(j,i) = 0.f;
}
break;
case UPSIDE_DOWN:
map_x.at<float>(j,i) = static_cast<float>(i);
map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);
break;
case REFLECTION_X:
map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);
map_y.at<float>(j,i) = static_cast<float>(j);
break;
case REFLECTION_BOTH:
map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);
map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);
break;
} // end of switch
}
}
}
DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Border_Mode, cv::Size, MatDepth, MatCn, Interpolation, BorderMode, RemapMode);
PERF_TEST_P(Sz_Depth_Cn_Inter_Border_Mode, Remap,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4,
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
ALL_BORDER_MODES,
RemapMode::all()))
{
declare.time(20.0);
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int interpolation = GET_PARAM(3);
const int borderMode = GET_PARAM(4);
const int remapMode = GET_PARAM(5);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
cv::Mat xmap(size, CV_32FC1);
cv::Mat ymap(size, CV_32FC1);
generateMap(xmap, ymap, remapMode);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
const cv::gpu::GpuMat d_xmap(xmap);
const cv::gpu::GpuMat d_ymap(ymap);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::remap(d_src, dst, d_xmap, d_ymap, interpolation, borderMode);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::remap(src, dst, xmap, ymap, interpolation, borderMode);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// Resize
DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Scale, cv::Size, MatDepth, MatCn, Interpolation, double);
PERF_TEST_P(Sz_Depth_Cn_Inter_Scale, Resize,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4,
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
Values(0.5, 0.3, 2.0)))
{
declare.time(20.0);
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int interpolation = GET_PARAM(3);
const double f = GET_PARAM(4);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::resize(d_src, dst, cv::Size(), f, f, interpolation);
GPU_SANITY_CHECK(dst, 1e-3, ERROR_RELATIVE);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::resize(src, dst, cv::Size(), f, f, interpolation);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// ResizeArea
DEF_PARAM_TEST(Sz_Depth_Cn_Scale, cv::Size, MatDepth, MatCn, double);
PERF_TEST_P(Sz_Depth_Cn_Scale, ResizeArea,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4,
Values(0.2, 0.1, 0.05)))
{
declare.time(1.0);
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int interpolation = cv::INTER_AREA;
const double f = GET_PARAM(3);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::resize(d_src, dst, cv::Size(), f, f, interpolation);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::resize(src, dst, cv::Size(), f, f, interpolation);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// WarpAffine
DEF_PARAM_TEST(Sz_Depth_Cn_Inter_Border, cv::Size, MatDepth, MatCn, Interpolation, BorderMode);
PERF_TEST_P(Sz_Depth_Cn_Inter_Border, WarpAffine,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4,
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
ALL_BORDER_MODES))
{
declare.time(20.0);
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int interpolation = GET_PARAM(3);
const int borderMode = GET_PARAM(4);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
const double aplha = CV_PI / 4;
const double mat[2 * 3] =
{
std::cos(aplha), -std::sin(aplha), src.cols / 2,
std::sin(aplha), std::cos(aplha), 0
};
const cv::Mat M(2, 3, CV_64F, (void*) mat);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::warpAffine(d_src, dst, M, size, interpolation, borderMode);
GPU_SANITY_CHECK(dst, 1);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::warpAffine(src, dst, M, size, interpolation, borderMode);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// WarpPerspective
PERF_TEST_P(Sz_Depth_Cn_Inter_Border, WarpPerspective,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4,
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
ALL_BORDER_MODES))
{
declare.time(20.0);
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int interpolation = GET_PARAM(3);
const int borderMode = GET_PARAM(4);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
const double aplha = CV_PI / 4;
double mat[3][3] = { {std::cos(aplha), -std::sin(aplha), src.cols / 2},
{std::sin(aplha), std::cos(aplha), 0},
{0.0, 0.0, 1.0}};
const cv::Mat M(3, 3, CV_64F, (void*) mat);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::warpPerspective(d_src, dst, M, size, interpolation, borderMode);
GPU_SANITY_CHECK(dst, 1);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::warpPerspective(src, dst, M, size, interpolation, borderMode);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// BuildWarpPlaneMaps
PERF_TEST_P(Sz, BuildWarpPlaneMaps,
GPU_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
const cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1);
const cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1);
const cv::Mat T = cv::Mat::zeros(1, 3, CV_32F);
if (PERF_RUN_GPU())
{
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
TEST_CYCLE() cv::gpu::buildWarpPlaneMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, T, 1.0, map_x, map_y);
GPU_SANITY_CHECK(map_x);
GPU_SANITY_CHECK(map_y);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// BuildWarpCylindricalMaps
PERF_TEST_P(Sz, BuildWarpCylindricalMaps,
GPU_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
const cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1);
const cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1);
if (PERF_RUN_GPU())
{
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
TEST_CYCLE() cv::gpu::buildWarpCylindricalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y);
GPU_SANITY_CHECK(map_x);
GPU_SANITY_CHECK(map_y);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// BuildWarpSphericalMaps
PERF_TEST_P(Sz, BuildWarpSphericalMaps,
GPU_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
const cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1);
const cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1);
if (PERF_RUN_GPU())
{
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
TEST_CYCLE() cv::gpu::buildWarpSphericalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y);
GPU_SANITY_CHECK(map_x);
GPU_SANITY_CHECK(map_y);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// Rotate
DEF_PARAM_TEST(Sz_Depth_Cn_Inter, cv::Size, MatDepth, MatCn, Interpolation);
PERF_TEST_P(Sz_Depth_Cn_Inter, Rotate,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4,
Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC))))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int interpolation = GET_PARAM(3);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::rotate(d_src, dst, size, 30.0, 0, 0, interpolation);
GPU_SANITY_CHECK(dst, 1e-3, ERROR_RELATIVE);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// PyrDown
PERF_TEST_P(Sz_Depth_Cn, PyrDown,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::pyrDown(d_src, dst);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::pyrDown(src, dst);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// PyrUp
PERF_TEST_P(Sz_Depth_Cn, PyrUp,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::pyrUp(d_src, dst);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::pyrUp(src, dst);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// ImagePyramidBuild
PERF_TEST_P(Sz_Depth_Cn, ImagePyramidBuild,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
const int nLayers = 5;
const cv::Size dstSize(size.width / 2 + 10, size.height / 2 + 10);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::ImagePyramid d_pyr;
TEST_CYCLE() d_pyr.build(d_src, nLayers);
cv::gpu::GpuMat dst;
d_pyr.getLayer(dst, dstSize);
GPU_SANITY_CHECK(dst);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// ImagePyramidGetLayer
PERF_TEST_P(Sz_Depth_Cn, ImagePyramidGetLayer,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_32F),
GPU_CHANNELS_1_3_4))
{
const cv::Size size = GET_PARAM(0);
const int depth = GET_PARAM(1);
const int channels = GET_PARAM(2);
const int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src(size, type);
declare.in(src, WARMUP_RNG);
const int nLayers = 3;
const cv::Size dstSize(size.width / 2 + 10, size.height / 2 + 10);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
cv::gpu::ImagePyramid d_pyr(d_src, nLayers);
TEST_CYCLE() d_pyr.getLayer(dst, dstSize);
GPU_SANITY_CHECK(dst);
}
else
{
FAIL_NO_CPU();
}
}