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.
 
 
 
 
 
 

419 lines
12 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;
////////////////////////////////////////////////////////////////////////////////
// Merge
PARAM_TEST_CASE(Merge, cv::cuda::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
{
cv::cuda::DeviceInfo devInfo;
cv::Size size;
int depth;
int channels;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::cuda::setDevice(devInfo.deviceID());
}
};
CUDA_TEST_P(Merge, Accuracy)
{
std::vector<cv::Mat> src;
src.reserve(channels);
for (int i = 0; i < channels; ++i)
src.push_back(cv::Mat(size, depth, cv::Scalar::all(i)));
std::vector<cv::cuda::GpuMat> d_src;
for (int i = 0; i < channels; ++i)
d_src.push_back(loadMat(src[i], useRoi));
if (depth == CV_64F && !supportFeature(devInfo, cv::cuda::NATIVE_DOUBLE))
{
try
{
cv::cuda::GpuMat dst;
cv::cuda::merge(d_src, dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::cuda::GpuMat dst;
cv::cuda::merge(d_src, dst);
cv::Mat dst_gold;
cv::merge(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
INSTANTIATE_TEST_CASE_P(CUDA_Arithm, Merge, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
testing::Values(1, 2, 3, 4),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Split
PARAM_TEST_CASE(Split, cv::cuda::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
{
cv::cuda::DeviceInfo devInfo;
cv::Size size;
int depth;
int channels;
bool useRoi;
int type;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::cuda::setDevice(devInfo.deviceID());
type = CV_MAKE_TYPE(depth, channels);
}
};
CUDA_TEST_P(Split, Accuracy)
{
cv::Mat src = randomMat(size, type);
if (depth == CV_64F && !supportFeature(devInfo, cv::cuda::NATIVE_DOUBLE))
{
try
{
std::vector<cv::cuda::GpuMat> dst;
cv::cuda::split(loadMat(src), dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
std::vector<cv::cuda::GpuMat> dst;
cv::cuda::split(loadMat(src, useRoi), dst);
std::vector<cv::Mat> dst_gold;
cv::split(src, dst_gold);
ASSERT_EQ(dst_gold.size(), dst.size());
for (size_t i = 0; i < dst_gold.size(); ++i)
{
EXPECT_MAT_NEAR(dst_gold[i], dst[i], 0.0);
}
}
}
INSTANTIATE_TEST_CASE_P(CUDA_Arithm, Split, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
testing::Values(1, 2, 3, 4),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Transpose
PARAM_TEST_CASE(Transpose, cv::cuda::DeviceInfo, cv::Size, MatType, UseRoi)
{
cv::cuda::DeviceInfo devInfo;
cv::Size size;
int type;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::cuda::setDevice(devInfo.deviceID());
}
};
CUDA_TEST_P(Transpose, Accuracy)
{
cv::Mat src = randomMat(size, type);
if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::cuda::NATIVE_DOUBLE))
{
try
{
cv::cuda::GpuMat dst;
cv::cuda::transpose(loadMat(src), dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::cuda::GpuMat dst = createMat(cv::Size(size.height, size.width), type, useRoi);
cv::cuda::transpose(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
cv::transpose(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
INSTANTIATE_TEST_CASE_P(CUDA_Arithm, Transpose, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1),
MatType(CV_8UC4),
MatType(CV_16UC2),
MatType(CV_16SC2),
MatType(CV_32SC1),
MatType(CV_32SC2),
MatType(CV_64FC1)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Flip
enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y)
#define ALL_FLIP_CODES testing::Values(FlipCode(FLIP_BOTH), FlipCode(FLIP_X), FlipCode(FLIP_Y))
PARAM_TEST_CASE(Flip, cv::cuda::DeviceInfo, cv::Size, MatType, FlipCode, UseRoi)
{
cv::cuda::DeviceInfo devInfo;
cv::Size size;
int type;
int flip_code;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
flip_code = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::cuda::setDevice(devInfo.deviceID());
}
};
CUDA_TEST_P(Flip, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::cuda::GpuMat dst = createMat(size, type, useRoi);
cv::cuda::flip(loadMat(src, useRoi), dst, flip_code);
cv::Mat dst_gold;
cv::flip(src, dst_gold, flip_code);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(CUDA_Arithm, Flip, 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_32SC1),
MatType(CV_32SC3),
MatType(CV_32SC4),
MatType(CV_32FC1),
MatType(CV_32FC3),
MatType(CV_32FC4)),
ALL_FLIP_CODES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// LUT
PARAM_TEST_CASE(LUT, cv::cuda::DeviceInfo, cv::Size, MatType, UseRoi)
{
cv::cuda::DeviceInfo devInfo;
cv::Size size;
int type;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::cuda::setDevice(devInfo.deviceID());
}
};
CUDA_TEST_P(LUT, OneChannel)
{
cv::Mat src = randomMat(size, type);
cv::Mat lut = randomMat(cv::Size(256, 1), CV_8UC1);
cv::Ptr<cv::cuda::LookUpTable> lutAlg = cv::cuda::createLookUpTable(lut);
cv::cuda::GpuMat dst = createMat(size, CV_MAKE_TYPE(lut.depth(), src.channels()));
lutAlg->transform(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
cv::LUT(src, lut, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
CUDA_TEST_P(LUT, MultiChannel)
{
cv::Mat src = randomMat(size, type);
cv::Mat lut = randomMat(cv::Size(256, 1), CV_MAKE_TYPE(CV_8U, src.channels()));
cv::Ptr<cv::cuda::LookUpTable> lutAlg = cv::cuda::createLookUpTable(lut);
cv::cuda::GpuMat dst = createMat(size, CV_MAKE_TYPE(lut.depth(), src.channels()), useRoi);
lutAlg->transform(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
cv::LUT(src, lut, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(CUDA_Arithm, LUT, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3)),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// CopyMakeBorder
namespace
{
IMPLEMENT_PARAM_CLASS(Border, int)
}
PARAM_TEST_CASE(CopyMakeBorder, cv::cuda::DeviceInfo, cv::Size, MatType, Border, BorderType, UseRoi)
{
cv::cuda::DeviceInfo devInfo;
cv::Size size;
int type;
int border;
int borderType;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
border = GET_PARAM(3);
borderType = GET_PARAM(4);
useRoi = GET_PARAM(5);
cv::cuda::setDevice(devInfo.deviceID());
}
};
CUDA_TEST_P(CopyMakeBorder, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Scalar val = randomScalar(0, 255);
cv::cuda::GpuMat dst = createMat(cv::Size(size.width + 2 * border, size.height + 2 * border), type, useRoi);
cv::cuda::copyMakeBorder(loadMat(src, useRoi), dst, border, border, border, border, borderType, val);
cv::Mat dst_gold;
cv::copyMakeBorder(src, dst_gold, border, border, border, border, borderType, val);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(CUDA_Arithm, CopyMakeBorder, 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)),
testing::Values(Border(1), Border(10), Border(50)),
ALL_BORDER_TYPES,
WHOLE_SUBMAT));
#endif // HAVE_CUDA