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opencv/modules/gpuarithm/test/test_core.cpp

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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 "test_precomp.hpp"
#ifdef HAVE_CUDA
using namespace cvtest;
////////////////////////////////////////////////////////////////////////////////
// Merge
PARAM_TEST_CASE(Merge, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
}
};
GPU_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::gpu::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::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::merge(d_src, dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst;
cv::gpu::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(GPU_Core, Merge, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
testing::Values(1, 2, 3, 4),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Split
PARAM_TEST_CASE(Split, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
type = CV_MAKE_TYPE(depth, channels);
}
};
GPU_TEST_P(Split, Accuracy)
{
cv::Mat src = randomMat(size, type);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
std::vector<cv::gpu::GpuMat> dst;
cv::gpu::split(loadMat(src), dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
std::vector<cv::gpu::GpuMat> dst;
cv::gpu::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(GPU_Core, Split, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
testing::Values(1, 2, 3, 4),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Add_Array
PARAM_TEST_CASE(Add_Array, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, Channels, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
int channels;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, channels);
dtype = CV_MAKE_TYPE(depth.second, channels);
}
};
GPU_TEST_P(Add_Array, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::add(loadMat(mat1), loadMat(mat2), dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::add(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::add(mat1, mat2, dst_gold, cv::noArray(), depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Add_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
ALL_CHANNELS,
WHOLE_SUBMAT));
PARAM_TEST_CASE(Add_Array_Mask, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, 1);
dtype = CV_MAKE_TYPE(depth.second, 1);
}
};
GPU_TEST_P(Add_Array_Mask, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
cv::Mat mask = randomMat(size, CV_8UC1, 0, 2);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::add(loadMat(mat1), loadMat(mat2), dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::add(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, loadMat(mask, useRoi), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::add(mat1, mat2, dst_gold, mask, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Add_Array_Mask, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Add_Scalar
PARAM_TEST_CASE(Add_Scalar, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Add_Scalar, WithOutMask)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::add(loadMat(mat), val, dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::add(loadMat(mat, useRoi), val, dst, cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, depth.second, cv::Scalar::all(0));
cv::add(mat, val, dst_gold, cv::noArray(), depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
GPU_TEST_P(Add_Scalar, WithMask)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::add(loadMat(mat), val, dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::add(loadMat(mat, useRoi), val, dst, loadMat(mask, useRoi), depth.second);
cv::Mat dst_gold(size, depth.second, cv::Scalar::all(0));
cv::add(mat, val, dst_gold, mask, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Add_Scalar, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Subtract_Array
PARAM_TEST_CASE(Subtract_Array, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, Channels, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
int channels;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, channels);
dtype = CV_MAKE_TYPE(depth.second, channels);
}
};
GPU_TEST_P(Subtract_Array, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::subtract(loadMat(mat1), loadMat(mat2), dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::subtract(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::subtract(mat1, mat2, dst_gold, cv::noArray(), depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Subtract_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
ALL_CHANNELS,
WHOLE_SUBMAT));
PARAM_TEST_CASE(Subtract_Array_Mask, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, 1);
dtype = CV_MAKE_TYPE(depth.second, 1);
}
};
GPU_TEST_P(Subtract_Array_Mask, Accuracy)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::subtract(loadMat(mat1), loadMat(mat2), dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::subtract(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, loadMat(mask, useRoi), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::subtract(mat1, mat2, dst_gold, mask, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Subtract_Array_Mask, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Subtract_Scalar
PARAM_TEST_CASE(Subtract_Scalar, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Subtract_Scalar, WithOutMask)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::subtract(loadMat(mat), val, dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::subtract(loadMat(mat, useRoi), val, dst, cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, depth.second, cv::Scalar::all(0));
cv::subtract(mat, val, dst_gold, cv::noArray(), depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
GPU_TEST_P(Subtract_Scalar, WithMask)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::subtract(loadMat(mat), val, dst, cv::gpu::GpuMat(), depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::subtract(loadMat(mat, useRoi), val, dst, loadMat(mask, useRoi), depth.second);
cv::Mat dst_gold(size, depth.second, cv::Scalar::all(0));
cv::subtract(mat, val, dst_gold, mask, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Subtract_Scalar, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Multiply_Array
PARAM_TEST_CASE(Multiply_Array, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, Channels, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
int channels;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, channels);
dtype = CV_MAKE_TYPE(depth.second, channels);
}
};
GPU_TEST_P(Multiply_Array, WithOutScale)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::multiply(loadMat(mat1), loadMat(mat2), dst, 1, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
cv::gpu::multiply(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, 1, depth.second);
cv::Mat dst_gold;
cv::multiply(mat1, mat2, dst_gold, 1, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-2 : 0.0);
}
}
GPU_TEST_P(Multiply_Array, WithScale)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
double scale = randomDouble(0.0, 255.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::multiply(loadMat(mat1), loadMat(mat2), dst, scale, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
cv::gpu::multiply(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, scale, depth.second);
cv::Mat dst_gold;
cv::multiply(mat1, mat2, dst_gold, scale, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, 2.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Multiply_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
ALL_CHANNELS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Multiply_Array_Special
PARAM_TEST_CASE(Multiply_Array_Special, cv::gpu::DeviceInfo, cv::Size, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Multiply_Array_Special, Case_8UC4x_32FC1)
{
cv::Mat mat1 = randomMat(size, CV_8UC4);
cv::Mat mat2 = randomMat(size, CV_32FC1);
cv::gpu::GpuMat dst = createMat(size, CV_8UC4, useRoi);
cv::gpu::multiply(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst);
cv::Mat h_dst(dst);
for (int y = 0; y < h_dst.rows; ++y)
{
const cv::Vec4b* mat1_row = mat1.ptr<cv::Vec4b>(y);
const float* mat2_row = mat2.ptr<float>(y);
const cv::Vec4b* dst_row = h_dst.ptr<cv::Vec4b>(y);
for (int x = 0; x < h_dst.cols; ++x)
{
cv::Vec4b val1 = mat1_row[x];
float val2 = mat2_row[x];
cv::Vec4b actual = dst_row[x];
cv::Vec4b gold;
gold[0] = cv::saturate_cast<uchar>(val1[0] * val2);
gold[1] = cv::saturate_cast<uchar>(val1[1] * val2);
gold[2] = cv::saturate_cast<uchar>(val1[2] * val2);
gold[3] = cv::saturate_cast<uchar>(val1[3] * val2);
ASSERT_LE(std::abs(gold[0] - actual[0]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
}
}
}
GPU_TEST_P(Multiply_Array_Special, Case_16SC4x_32FC1)
{
cv::Mat mat1 = randomMat(size, CV_16SC4);
cv::Mat mat2 = randomMat(size, CV_32FC1);
cv::gpu::GpuMat dst = createMat(size, CV_16SC4, useRoi);
cv::gpu::multiply(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst);
cv::Mat h_dst(dst);
for (int y = 0; y < h_dst.rows; ++y)
{
const cv::Vec4s* mat1_row = mat1.ptr<cv::Vec4s>(y);
const float* mat2_row = mat2.ptr<float>(y);
const cv::Vec4s* dst_row = h_dst.ptr<cv::Vec4s>(y);
for (int x = 0; x < h_dst.cols; ++x)
{
cv::Vec4s val1 = mat1_row[x];
float val2 = mat2_row[x];
cv::Vec4s actual = dst_row[x];
cv::Vec4s gold;
gold[0] = cv::saturate_cast<short>(val1[0] * val2);
gold[1] = cv::saturate_cast<short>(val1[1] * val2);
gold[2] = cv::saturate_cast<short>(val1[2] * val2);
gold[3] = cv::saturate_cast<short>(val1[3] * val2);
ASSERT_LE(std::abs(gold[0] - actual[0]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
}
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Multiply_Array_Special, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Multiply_Scalar
PARAM_TEST_CASE(Multiply_Scalar, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Multiply_Scalar, WithOutScale)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::multiply(loadMat(mat), val, dst, 1, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
cv::gpu::multiply(loadMat(mat, useRoi), val, dst, 1, depth.second);
cv::Mat dst_gold;
cv::multiply(mat, val, dst_gold, 1, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, 1.0);
}
}
GPU_TEST_P(Multiply_Scalar, WithScale)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
double scale = randomDouble(0.0, 255.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::multiply(loadMat(mat), val, dst, scale, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
cv::gpu::multiply(loadMat(mat, useRoi), val, dst, scale, depth.second);
cv::Mat dst_gold;
cv::multiply(mat, val, dst_gold, scale, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, 1.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Multiply_Scalar, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Divide_Array
PARAM_TEST_CASE(Divide_Array, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, Channels, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
int channels;
bool useRoi;
int stype;
int dtype;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
stype = CV_MAKE_TYPE(depth.first, channels);
dtype = CV_MAKE_TYPE(depth.second, channels);
}
};
GPU_TEST_P(Divide_Array, WithOutScale)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype, 1.0, 255.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::divide(loadMat(mat1), loadMat(mat2), dst, 1, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
cv::gpu::divide(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, 1, depth.second);
cv::Mat dst_gold;
cv::divide(mat1, mat2, dst_gold, 1, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 1.0);
}
}
GPU_TEST_P(Divide_Array, WithScale)
{
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype, 1.0, 255.0);
double scale = randomDouble(0.0, 255.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::divide(loadMat(mat1), loadMat(mat2), dst, scale, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
cv::gpu::divide(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, scale, depth.second);
cv::Mat dst_gold;
cv::divide(mat1, mat2, dst_gold, scale, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-2 : 1.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Divide_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
ALL_CHANNELS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Divide_Array_Special
PARAM_TEST_CASE(Divide_Array_Special, cv::gpu::DeviceInfo, cv::Size, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Divide_Array_Special, Case_8UC4x_32FC1)
{
cv::Mat mat1 = randomMat(size, CV_8UC4);
cv::Mat mat2 = randomMat(size, CV_32FC1, 1.0, 255.0);
cv::gpu::GpuMat dst = createMat(size, CV_8UC4, useRoi);
cv::gpu::divide(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst);
cv::Mat h_dst(dst);
for (int y = 0; y < h_dst.rows; ++y)
{
const cv::Vec4b* mat1_row = mat1.ptr<cv::Vec4b>(y);
const float* mat2_row = mat2.ptr<float>(y);
const cv::Vec4b* dst_row = h_dst.ptr<cv::Vec4b>(y);
for (int x = 0; x < h_dst.cols; ++x)
{
cv::Vec4b val1 = mat1_row[x];
float val2 = mat2_row[x];
cv::Vec4b actual = dst_row[x];
cv::Vec4b gold;
gold[0] = cv::saturate_cast<uchar>(val1[0] / val2);
gold[1] = cv::saturate_cast<uchar>(val1[1] / val2);
gold[2] = cv::saturate_cast<uchar>(val1[2] / val2);
gold[3] = cv::saturate_cast<uchar>(val1[3] / val2);
ASSERT_LE(std::abs(gold[0] - actual[0]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
}
}
}
GPU_TEST_P(Divide_Array_Special, Case_16SC4x_32FC1)
{
cv::Mat mat1 = randomMat(size, CV_16SC4);
cv::Mat mat2 = randomMat(size, CV_32FC1, 1.0, 255.0);
cv::gpu::GpuMat dst = createMat(size, CV_16SC4, useRoi);
cv::gpu::divide(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst);
cv::Mat h_dst(dst);
for (int y = 0; y < h_dst.rows; ++y)
{
const cv::Vec4s* mat1_row = mat1.ptr<cv::Vec4s>(y);
const float* mat2_row = mat2.ptr<float>(y);
const cv::Vec4s* dst_row = h_dst.ptr<cv::Vec4s>(y);
for (int x = 0; x < h_dst.cols; ++x)
{
cv::Vec4s val1 = mat1_row[x];
float val2 = mat2_row[x];
cv::Vec4s actual = dst_row[x];
cv::Vec4s gold;
gold[0] = cv::saturate_cast<short>(val1[0] / val2);
gold[1] = cv::saturate_cast<short>(val1[1] / val2);
gold[2] = cv::saturate_cast<short>(val1[2] / val2);
gold[3] = cv::saturate_cast<short>(val1[3] / val2);
ASSERT_LE(std::abs(gold[0] - actual[0]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
ASSERT_LE(std::abs(gold[1] - actual[1]), 1.0);
}
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Divide_Array_Special, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Divide_Scalar
PARAM_TEST_CASE(Divide_Scalar, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Divide_Scalar, WithOutScale)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(1.0, 255.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::divide(loadMat(mat), val, dst, 1, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
cv::gpu::divide(loadMat(mat, useRoi), val, dst, 1, depth.second);
cv::Mat dst_gold;
cv::divide(mat, val, dst_gold, 1, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 1.0);
}
}
GPU_TEST_P(Divide_Scalar, WithScale)
{
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(1.0, 255.0);
double scale = randomDouble(0.0, 255.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::divide(loadMat(mat), val, dst, scale, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
cv::gpu::divide(loadMat(mat, useRoi), val, dst, scale, depth.second);
cv::Mat dst_gold;
cv::divide(mat, val, dst_gold, scale, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-2 : 1.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Divide_Scalar, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Divide_Scalar_Inv
PARAM_TEST_CASE(Divide_Scalar_Inv, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatDepth, MatDepth> depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Divide_Scalar_Inv, Accuracy)
{
double scale = randomDouble(0.0, 255.0);
cv::Mat mat = randomMat(size, depth.first, 1.0, 255.0);
if ((depth.first == CV_64F || depth.second == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::divide(scale, loadMat(mat), dst, depth.second);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth.second, useRoi);
cv::gpu::divide(scale, loadMat(mat, useRoi), dst, depth.second);
cv::Mat dst_gold;
cv::divide(scale, mat, dst_gold, depth.second);
EXPECT_MAT_NEAR(dst_gold, dst, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 1.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Divide_Scalar_Inv, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// AbsDiff
PARAM_TEST_CASE(AbsDiff, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(AbsDiff, Array)
{
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::absdiff(loadMat(src1), loadMat(src2), dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::absdiff(loadMat(src1, useRoi), loadMat(src2, useRoi), dst);
cv::Mat dst_gold;
cv::absdiff(src1, src2, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
GPU_TEST_P(AbsDiff, Scalar)
{
cv::Mat src = randomMat(size, depth);
cv::Scalar val = randomScalar(0.0, 255.0);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::absdiff(loadMat(src), val, dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::absdiff(loadMat(src, useRoi), val, dst);
cv::Mat dst_gold;
cv::absdiff(src, val, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, depth <= CV_32F ? 1.0 : 1e-5);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, AbsDiff, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Abs
PARAM_TEST_CASE(Abs, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Abs, Accuracy)
{
cv::Mat src = randomMat(size, depth);
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::abs(loadMat(src, useRoi), dst);
cv::Mat dst_gold = cv::abs(src);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Abs, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_16S), MatDepth(CV_32F)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Sqr
PARAM_TEST_CASE(Sqr, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Sqr, Accuracy)
{
cv::Mat src = randomMat(size, depth, 0, depth == CV_8U ? 16 : 255);
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::sqr(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
cv::multiply(src, src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Sqr, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U),
MatDepth(CV_16U),
MatDepth(CV_16S),
MatDepth(CV_32F)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Sqrt
namespace
{
template <typename T> void sqrtImpl(const cv::Mat& src, cv::Mat& dst)
{
dst.create(src.size(), src.type());
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
dst.at<T>(y, x) = static_cast<T>(std::sqrt(static_cast<float>(src.at<T>(y, x))));
}
}
void sqrtGold(const cv::Mat& src, cv::Mat& dst)
{
typedef void (*func_t)(const cv::Mat& src, cv::Mat& dst);
const func_t funcs[] =
{
sqrtImpl<uchar>, sqrtImpl<schar>, sqrtImpl<ushort>, sqrtImpl<short>,
sqrtImpl<int>, sqrtImpl<float>
};
funcs[src.depth()](src, dst);
}
}
PARAM_TEST_CASE(Sqrt, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Sqrt, Accuracy)
{
cv::Mat src = randomMat(size, depth);
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::sqrt(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
sqrtGold(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, depth < CV_32F ? 1.0 : 1e-5);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Sqrt, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U),
MatDepth(CV_16U),
MatDepth(CV_16S),
MatDepth(CV_32F)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Log
namespace
{
template <typename T> void logImpl(const cv::Mat& src, cv::Mat& dst)
{
dst.create(src.size(), src.type());
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
dst.at<T>(y, x) = static_cast<T>(std::log(static_cast<float>(src.at<T>(y, x))));
}
}
void logGold(const cv::Mat& src, cv::Mat& dst)
{
typedef void (*func_t)(const cv::Mat& src, cv::Mat& dst);
const func_t funcs[] =
{
logImpl<uchar>, logImpl<schar>, logImpl<ushort>, logImpl<short>,
logImpl<int>, logImpl<float>
};
funcs[src.depth()](src, dst);
}
}
PARAM_TEST_CASE(Log, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Log, Accuracy)
{
cv::Mat src = randomMat(size, depth, 1.0, 255.0);
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::log(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
logGold(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, depth < CV_32F ? 1.0 : 1e-6);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Log, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U),
MatDepth(CV_16U),
MatDepth(CV_16S),
MatDepth(CV_32F)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Exp
namespace
{
template <typename T> void expImpl(const cv::Mat& src, cv::Mat& dst)
{
dst.create(src.size(), src.type());
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
dst.at<T>(y, x) = cv::saturate_cast<T>(static_cast<int>(std::exp(static_cast<float>(src.at<T>(y, x)))));
}
}
void expImpl_float(const cv::Mat& src, cv::Mat& dst)
{
dst.create(src.size(), src.type());
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
dst.at<float>(y, x) = std::exp(static_cast<float>(src.at<float>(y, x)));
}
}
void expGold(const cv::Mat& src, cv::Mat& dst)
{
typedef void (*func_t)(const cv::Mat& src, cv::Mat& dst);
const func_t funcs[] =
{
expImpl<uchar>, expImpl<schar>, expImpl<ushort>, expImpl<short>,
expImpl<int>, expImpl_float
};
funcs[src.depth()](src, dst);
}
}
PARAM_TEST_CASE(Exp, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Exp, Accuracy)
{
cv::Mat src = randomMat(size, depth, 0.0, 10.0);
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::exp(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
expGold(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, depth < CV_32F ? 1.0 : 1e-2);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Exp, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U),
MatDepth(CV_16U),
MatDepth(CV_16S),
MatDepth(CV_32F)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Compare_Array
CV_ENUM(CmpCode, CMP_EQ, CMP_NE, CMP_GT, CMP_GE, CMP_LT, CMP_LE)
PARAM_TEST_CASE(Compare_Array, cv::gpu::DeviceInfo, cv::Size, MatDepth, CmpCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
int cmp_code;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
cmp_code = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Compare_Array, Accuracy)
{
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::compare(loadMat(src1), loadMat(src2), dst, cmp_code);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, CV_8UC1, useRoi);
cv::gpu::compare(loadMat(src1, useRoi), loadMat(src2, useRoi), dst, cmp_code);
cv::Mat dst_gold;
cv::compare(src1, src2, dst_gold, cmp_code);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Compare_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
CmpCode::all(),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Compare_Scalar
namespace
{
template <template <typename> class Op, typename T>
void compareScalarImpl(const cv::Mat& src, cv::Scalar sc, cv::Mat& dst)
{
Op<T> op;
const int cn = src.channels();
dst.create(src.size(), CV_MAKE_TYPE(CV_8U, cn));
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
{
for (int c = 0; c < cn; ++c)
{
T src_val = src.at<T>(y, x * cn + c);
T sc_val = cv::saturate_cast<T>(sc.val[c]);
dst.at<uchar>(y, x * cn + c) = static_cast<uchar>(static_cast<int>(op(src_val, sc_val)) * 255);
}
}
}
}
void compareScalarGold(const cv::Mat& src, cv::Scalar sc, cv::Mat& dst, int cmpop)
{
typedef void (*func_t)(const cv::Mat& src, cv::Scalar sc, cv::Mat& dst);
static const func_t funcs[7][6] =
{
{compareScalarImpl<std::equal_to, unsigned char> , compareScalarImpl<std::greater, unsigned char> , compareScalarImpl<std::greater_equal, unsigned char> , compareScalarImpl<std::less, unsigned char> , compareScalarImpl<std::less_equal, unsigned char> , compareScalarImpl<std::not_equal_to, unsigned char> },
{compareScalarImpl<std::equal_to, signed char> , compareScalarImpl<std::greater, signed char> , compareScalarImpl<std::greater_equal, signed char> , compareScalarImpl<std::less, signed char> , compareScalarImpl<std::less_equal, signed char> , compareScalarImpl<std::not_equal_to, signed char> },
{compareScalarImpl<std::equal_to, unsigned short>, compareScalarImpl<std::greater, unsigned short>, compareScalarImpl<std::greater_equal, unsigned short>, compareScalarImpl<std::less, unsigned short>, compareScalarImpl<std::less_equal, unsigned short>, compareScalarImpl<std::not_equal_to, unsigned short>},
{compareScalarImpl<std::equal_to, short> , compareScalarImpl<std::greater, short> , compareScalarImpl<std::greater_equal, short> , compareScalarImpl<std::less, short> , compareScalarImpl<std::less_equal, short> , compareScalarImpl<std::not_equal_to, short> },
{compareScalarImpl<std::equal_to, int> , compareScalarImpl<std::greater, int> , compareScalarImpl<std::greater_equal, int> , compareScalarImpl<std::less, int> , compareScalarImpl<std::less_equal, int> , compareScalarImpl<std::not_equal_to, int> },
{compareScalarImpl<std::equal_to, float> , compareScalarImpl<std::greater, float> , compareScalarImpl<std::greater_equal, float> , compareScalarImpl<std::less, float> , compareScalarImpl<std::less_equal, float> , compareScalarImpl<std::not_equal_to, float> },
{compareScalarImpl<std::equal_to, double> , compareScalarImpl<std::greater, double> , compareScalarImpl<std::greater_equal, double> , compareScalarImpl<std::less, double> , compareScalarImpl<std::less_equal, double> , compareScalarImpl<std::not_equal_to, double> }
};
funcs[src.depth()][cmpop](src, sc, dst);
}
}
PARAM_TEST_CASE(Compare_Scalar, cv::gpu::DeviceInfo, cv::Size, MatType, CmpCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
int cmp_code;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
cmp_code = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Compare_Scalar, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Scalar sc = randomScalar(0.0, 255.0);
if (src.depth() < CV_32F)
{
sc.val[0] = cvRound(sc.val[0]);
sc.val[1] = cvRound(sc.val[1]);
sc.val[2] = cvRound(sc.val[2]);
sc.val[3] = cvRound(sc.val[3]);
}
if (src.depth() == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::compare(loadMat(src), sc, dst, cmp_code);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, CV_MAKE_TYPE(CV_8U, src.channels()), useRoi);
cv::gpu::compare(loadMat(src, useRoi), sc, dst, cmp_code);
cv::Mat dst_gold;
compareScalarGold(src, sc, dst_gold, cmp_code);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Compare_Scalar, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
TYPES(CV_8U, CV_64F, 1, 4),
CmpCode::all(),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// Bitwise_Array
PARAM_TEST_CASE(Bitwise_Array, cv::gpu::DeviceInfo, cv::Size, MatType)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
cv::Mat src1;
cv::Mat src2;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
src1 = randomMat(size, type, 0.0, std::numeric_limits<int>::max());
src2 = randomMat(size, type, 0.0, std::numeric_limits<int>::max());
}
};
GPU_TEST_P(Bitwise_Array, Not)
{
cv::gpu::GpuMat dst;
cv::gpu::bitwise_not(loadMat(src1), dst);
cv::Mat dst_gold = ~src1;
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
GPU_TEST_P(Bitwise_Array, Or)
{
cv::gpu::GpuMat dst;
cv::gpu::bitwise_or(loadMat(src1), loadMat(src2), dst);
cv::Mat dst_gold = src1 | src2;
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
GPU_TEST_P(Bitwise_Array, And)
{
cv::gpu::GpuMat dst;
cv::gpu::bitwise_and(loadMat(src1), loadMat(src2), dst);
cv::Mat dst_gold = src1 & src2;
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
GPU_TEST_P(Bitwise_Array, Xor)
{
cv::gpu::GpuMat dst;
cv::gpu::bitwise_xor(loadMat(src1), loadMat(src2), dst);
cv::Mat dst_gold = src1 ^ src2;
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Bitwise_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
TYPES(CV_8U, CV_32S, 1, 4)));
//////////////////////////////////////////////////////////////////////////////
// Bitwise_Scalar
PARAM_TEST_CASE(Bitwise_Scalar, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
int channels;
cv::Mat src;
cv::Scalar val;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
src = randomMat(size, CV_MAKE_TYPE(depth, channels));
cv::Scalar_<int> ival = randomScalar(0.0, std::numeric_limits<int>::max());
val = ival;
}
};
GPU_TEST_P(Bitwise_Scalar, Or)
{
cv::gpu::GpuMat dst;
cv::gpu::bitwise_or(loadMat(src), val, dst);
cv::Mat dst_gold;
cv::bitwise_or(src, val, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
GPU_TEST_P(Bitwise_Scalar, And)
{
cv::gpu::GpuMat dst;
cv::gpu::bitwise_and(loadMat(src), val, dst);
cv::Mat dst_gold;
cv::bitwise_and(src, val, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
GPU_TEST_P(Bitwise_Scalar, Xor)
{
cv::gpu::GpuMat dst;
cv::gpu::bitwise_xor(loadMat(src), val, dst);
cv::Mat dst_gold;
cv::bitwise_xor(src, val, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Bitwise_Scalar, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_32S)),
IMAGE_CHANNELS));
//////////////////////////////////////////////////////////////////////////////
// RShift
namespace
{
template <typename T> void rhiftImpl(const cv::Mat& src, cv::Scalar_<int> val, cv::Mat& dst)
{
const int cn = src.channels();
dst.create(src.size(), src.type());
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
{
for (int c = 0; c < cn; ++c)
dst.at<T>(y, x * cn + c) = src.at<T>(y, x * cn + c) >> val.val[c];
}
}
}
void rhiftGold(const cv::Mat& src, cv::Scalar_<int> val, cv::Mat& dst)
{
typedef void (*func_t)(const cv::Mat& src, cv::Scalar_<int> val, cv::Mat& dst);
const func_t funcs[] =
{
rhiftImpl<uchar>, rhiftImpl<schar>, rhiftImpl<ushort>, rhiftImpl<short>, rhiftImpl<int>
};
funcs[src.depth()](src, val, dst);
}
}
PARAM_TEST_CASE(RShift, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(RShift, Accuracy)
{
int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src = randomMat(size, type);
cv::Scalar_<int> val = randomScalar(0.0, 8.0);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::rshift(loadMat(src, useRoi), val, dst);
cv::Mat dst_gold;
rhiftGold(src, val, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, RShift, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U),
MatDepth(CV_8S),
MatDepth(CV_16U),
MatDepth(CV_16S),
MatDepth(CV_32S)),
IMAGE_CHANNELS,
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// LShift
namespace
{
template <typename T> void lhiftImpl(const cv::Mat& src, cv::Scalar_<int> val, cv::Mat& dst)
{
const int cn = src.channels();
dst.create(src.size(), src.type());
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
{
for (int c = 0; c < cn; ++c)
dst.at<T>(y, x * cn + c) = src.at<T>(y, x * cn + c) << val.val[c];
}
}
}
void lhiftGold(const cv::Mat& src, cv::Scalar_<int> val, cv::Mat& dst)
{
typedef void (*func_t)(const cv::Mat& src, cv::Scalar_<int> val, cv::Mat& dst);
const func_t funcs[] =
{
lhiftImpl<uchar>, lhiftImpl<schar>, lhiftImpl<ushort>, lhiftImpl<short>, lhiftImpl<int>
};
funcs[src.depth()](src, val, dst);
}
}
PARAM_TEST_CASE(LShift, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(LShift, Accuracy)
{
int type = CV_MAKE_TYPE(depth, channels);
cv::Mat src = randomMat(size, type);
cv::Scalar_<int> val = randomScalar(0.0, 8.0);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::lshift(loadMat(src, useRoi), val, dst);
cv::Mat dst_gold;
lhiftGold(src, val, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, LShift, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_32S)),
IMAGE_CHANNELS,
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// Min
PARAM_TEST_CASE(Min, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Min, Array)
{
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::min(loadMat(src1), loadMat(src2), dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::min(loadMat(src1, useRoi), loadMat(src2, useRoi), dst);
cv::Mat dst_gold = cv::min(src1, src2);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
GPU_TEST_P(Min, Scalar)
{
cv::Mat src = randomMat(size, depth);
double val = randomDouble(0.0, 255.0);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::min(loadMat(src), val, dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::min(loadMat(src, useRoi), val, dst);
cv::Mat dst_gold = cv::min(src, val);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Min, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// Max
PARAM_TEST_CASE(Max, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Max, Array)
{
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::max(loadMat(src1), loadMat(src2), dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::max(loadMat(src1, useRoi), loadMat(src2, useRoi), dst);
cv::Mat dst_gold = cv::max(src1, src2);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
GPU_TEST_P(Max, Scalar)
{
cv::Mat src = randomMat(size, depth);
double val = randomDouble(0.0, 255.0);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::max(loadMat(src), val, dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::max(loadMat(src, useRoi), val, dst);
cv::Mat dst_gold = cv::max(src, val);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Max, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Pow
PARAM_TEST_CASE(Pow, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Pow, Accuracy)
{
cv::Mat src = randomMat(size, depth, 0.0, 10.0);
double power = randomDouble(2.0, 4.0);
if (src.depth() < CV_32F)
power = static_cast<int>(power);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::pow(loadMat(src), power, dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, depth, useRoi);
cv::gpu::pow(loadMat(src, useRoi), power, dst);
cv::Mat dst_gold;
cv::pow(src, power, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, depth < CV_32F ? 0.0 : 1e-1);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Pow, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// AddWeighted
PARAM_TEST_CASE(AddWeighted, cv::gpu::DeviceInfo, cv::Size, MatDepth, MatDepth, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth1;
int depth2;
int dst_depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth1 = GET_PARAM(2);
depth2 = GET_PARAM(3);
dst_depth = GET_PARAM(4);
useRoi = GET_PARAM(5);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(AddWeighted, Accuracy)
{
cv::Mat src1 = randomMat(size, depth1);
cv::Mat src2 = randomMat(size, depth2);
double alpha = randomDouble(-10.0, 10.0);
double beta = randomDouble(-10.0, 10.0);
double gamma = randomDouble(-10.0, 10.0);
if ((depth1 == CV_64F || depth2 == CV_64F || dst_depth == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::addWeighted(loadMat(src1), alpha, loadMat(src2), beta, gamma, dst, dst_depth);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, dst_depth, useRoi);
cv::gpu::addWeighted(loadMat(src1, useRoi), alpha, loadMat(src2, useRoi), beta, gamma, dst, dst_depth);
cv::Mat dst_gold;
cv::addWeighted(src1, alpha, src2, beta, gamma, dst_gold, dst_depth);
EXPECT_MAT_NEAR(dst_gold, dst, dst_depth < CV_32F ? 1.0 : 1e-3);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, AddWeighted, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
ALL_DEPTH,
ALL_DEPTH,
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// GEMM
#ifdef HAVE_CUBLAS
CV_FLAGS(GemmFlags, 0, GEMM_1_T, GEMM_2_T, GEMM_3_T);
#define ALL_GEMM_FLAGS testing::Values(GemmFlags(0), GemmFlags(cv::GEMM_1_T), GemmFlags(cv::GEMM_2_T), GemmFlags(cv::GEMM_3_T), GemmFlags(cv::GEMM_1_T | cv::GEMM_2_T), GemmFlags(cv::GEMM_1_T | cv::GEMM_3_T), GemmFlags(cv::GEMM_1_T | cv::GEMM_2_T | cv::GEMM_3_T))
PARAM_TEST_CASE(GEMM, cv::gpu::DeviceInfo, cv::Size, MatType, GemmFlags, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
int flags;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
flags = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(GEMM, Accuracy)
{
cv::Mat src1 = randomMat(size, type, -10.0, 10.0);
cv::Mat src2 = randomMat(size, type, -10.0, 10.0);
cv::Mat src3 = randomMat(size, type, -10.0, 10.0);
double alpha = randomDouble(-10.0, 10.0);
double beta = randomDouble(-10.0, 10.0);
if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::gemm(loadMat(src1), loadMat(src2), alpha, loadMat(src3), beta, dst, flags);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else if (type == CV_64FC2 && flags != 0)
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::gemm(loadMat(src1), loadMat(src2), alpha, loadMat(src3), beta, dst, flags);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsNotImplemented, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::gemm(loadMat(src1, useRoi), loadMat(src2, useRoi), alpha, loadMat(src3, useRoi), beta, dst, flags);
cv::Mat dst_gold;
cv::gemm(src1, src2, alpha, src3, beta, dst_gold, flags);
EXPECT_MAT_NEAR(dst_gold, dst, CV_MAT_DEPTH(type) == CV_32F ? 1e-1 : 1e-10);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, GEMM, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_32FC1), MatType(CV_32FC2), MatType(CV_64FC1), MatType(CV_64FC2)),
ALL_GEMM_FLAGS,
WHOLE_SUBMAT));
#endif // HAVE_CUBLAS
////////////////////////////////////////////////////////////////////////////////
// Transpose
PARAM_TEST_CASE(Transpose, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Transpose, Accuracy)
{
cv::Mat src = randomMat(size, type);
if (CV_MAT_DEPTH(type) == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::GpuMat dst;
cv::gpu::transpose(loadMat(src), dst);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
cv::gpu::GpuMat dst = createMat(cv::Size(size.height, size.width), type, useRoi);
cv::gpu::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(GPU_Core, 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::gpu::DeviceInfo, cv::Size, MatType, FlipCode, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Flip, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::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(GPU_Core, 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::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(LUT, OneChannel)
{
cv::Mat src = randomMat(size, type);
cv::Mat lut = randomMat(cv::Size(256, 1), CV_8UC1);
cv::gpu::GpuMat dst = createMat(size, CV_MAKE_TYPE(lut.depth(), src.channels()));
cv::gpu::LUT(loadMat(src, useRoi), lut, dst);
cv::Mat dst_gold;
cv::LUT(src, lut, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
GPU_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::gpu::GpuMat dst = createMat(size, CV_MAKE_TYPE(lut.depth(), src.channels()), useRoi);
cv::gpu::LUT(loadMat(src, useRoi), lut, dst);
cv::Mat dst_gold;
cv::LUT(src, lut, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, LUT, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Magnitude
PARAM_TEST_CASE(Magnitude, cv::gpu::DeviceInfo, cv::Size, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Magnitude, NPP)
{
cv::Mat src = randomMat(size, CV_32FC2);
cv::gpu::GpuMat dst = createMat(size, CV_32FC1, useRoi);
cv::gpu::magnitude(loadMat(src, useRoi), dst);
cv::Mat arr[2];
cv::split(src, arr);
cv::Mat dst_gold;
cv::magnitude(arr[0], arr[1], dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-4);
}
GPU_TEST_P(Magnitude, Sqr_NPP)
{
cv::Mat src = randomMat(size, CV_32FC2);
cv::gpu::GpuMat dst = createMat(size, CV_32FC1, useRoi);
cv::gpu::magnitudeSqr(loadMat(src, useRoi), dst);
cv::Mat arr[2];
cv::split(src, arr);
cv::Mat dst_gold;
cv::magnitude(arr[0], arr[1], dst_gold);
cv::multiply(dst_gold, dst_gold, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-1);
}
GPU_TEST_P(Magnitude, Accuracy)
{
cv::Mat x = randomMat(size, CV_32FC1);
cv::Mat y = randomMat(size, CV_32FC1);
cv::gpu::GpuMat dst = createMat(size, CV_32FC1, useRoi);
cv::gpu::magnitude(loadMat(x, useRoi), loadMat(y, useRoi), dst);
cv::Mat dst_gold;
cv::magnitude(x, y, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-4);
}
GPU_TEST_P(Magnitude, Sqr_Accuracy)
{
cv::Mat x = randomMat(size, CV_32FC1);
cv::Mat y = randomMat(size, CV_32FC1);
cv::gpu::GpuMat dst = createMat(size, CV_32FC1, useRoi);
cv::gpu::magnitudeSqr(loadMat(x, useRoi), loadMat(y, useRoi), dst);
cv::Mat dst_gold;
cv::magnitude(x, y, dst_gold);
cv::multiply(dst_gold, dst_gold, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-1);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Magnitude, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Phase
namespace
{
IMPLEMENT_PARAM_CLASS(AngleInDegrees, bool)
}
PARAM_TEST_CASE(Phase, cv::gpu::DeviceInfo, cv::Size, AngleInDegrees, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool angleInDegrees;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
angleInDegrees = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Phase, Accuracy)
{
cv::Mat x = randomMat(size, CV_32FC1);
cv::Mat y = randomMat(size, CV_32FC1);
cv::gpu::GpuMat dst = createMat(size, CV_32FC1, useRoi);
cv::gpu::phase(loadMat(x, useRoi), loadMat(y, useRoi), dst, angleInDegrees);
cv::Mat dst_gold;
cv::phase(x, y, dst_gold, angleInDegrees);
EXPECT_MAT_NEAR(dst_gold, dst, angleInDegrees ? 1e-2 : 1e-3);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Phase, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(AngleInDegrees(false), AngleInDegrees(true)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// CartToPolar
PARAM_TEST_CASE(CartToPolar, cv::gpu::DeviceInfo, cv::Size, AngleInDegrees, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool angleInDegrees;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
angleInDegrees = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(CartToPolar, Accuracy)
{
cv::Mat x = randomMat(size, CV_32FC1);
cv::Mat y = randomMat(size, CV_32FC1);
cv::gpu::GpuMat mag = createMat(size, CV_32FC1, useRoi);
cv::gpu::GpuMat angle = createMat(size, CV_32FC1, useRoi);
cv::gpu::cartToPolar(loadMat(x, useRoi), loadMat(y, useRoi), mag, angle, angleInDegrees);
cv::Mat mag_gold;
cv::Mat angle_gold;
cv::cartToPolar(x, y, mag_gold, angle_gold, angleInDegrees);
EXPECT_MAT_NEAR(mag_gold, mag, 1e-4);
EXPECT_MAT_NEAR(angle_gold, angle, angleInDegrees ? 1e-2 : 1e-3);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, CartToPolar, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(AngleInDegrees(false), AngleInDegrees(true)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// polarToCart
PARAM_TEST_CASE(PolarToCart, cv::gpu::DeviceInfo, cv::Size, AngleInDegrees, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool angleInDegrees;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
angleInDegrees = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(PolarToCart, Accuracy)
{
cv::Mat magnitude = randomMat(size, CV_32FC1);
cv::Mat angle = randomMat(size, CV_32FC1);
cv::gpu::GpuMat x = createMat(size, CV_32FC1, useRoi);
cv::gpu::GpuMat y = createMat(size, CV_32FC1, useRoi);
cv::gpu::polarToCart(loadMat(magnitude, useRoi), loadMat(angle, useRoi), x, y, angleInDegrees);
cv::Mat x_gold;
cv::Mat y_gold;
cv::polarToCart(magnitude, angle, x_gold, y_gold, angleInDegrees);
EXPECT_MAT_NEAR(x_gold, x, 1e-4);
EXPECT_MAT_NEAR(y_gold, y, 1e-4);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, PolarToCart, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(AngleInDegrees(false), AngleInDegrees(true)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// MeanStdDev
PARAM_TEST_CASE(MeanStdDev, cv::gpu::DeviceInfo, cv::Size, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(MeanStdDev, Accuracy)
{
cv::Mat src = randomMat(size, CV_8UC1);
if (!supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_13))
{
try
{
cv::Scalar mean;
cv::Scalar stddev;
cv::gpu::meanStdDev(loadMat(src, useRoi), mean, stddev);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsNotImplemented, e.code);
}
}
else
{
cv::Scalar mean;
cv::Scalar stddev;
cv::gpu::meanStdDev(loadMat(src, useRoi), mean, stddev);
cv::Scalar mean_gold;
cv::Scalar stddev_gold;
cv::meanStdDev(src, mean_gold, stddev_gold);
EXPECT_SCALAR_NEAR(mean_gold, mean, 1e-5);
EXPECT_SCALAR_NEAR(stddev_gold, stddev, 1e-5);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, MeanStdDev, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Norm
PARAM_TEST_CASE(Norm, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
int normCode;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
normCode = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Norm, Accuracy)
{
cv::Mat src = randomMat(size, depth);
cv::Mat mask = randomMat(size, CV_8UC1, 0, 2);
cv::gpu::GpuMat d_buf;
double val = cv::gpu::norm(loadMat(src, useRoi), normCode, loadMat(mask, useRoi), d_buf);
double val_gold = cv::norm(src, normCode, mask);
EXPECT_NEAR(val_gold, val, depth < CV_32F ? 0.0 : 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Norm, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U),
MatDepth(CV_8S),
MatDepth(CV_16U),
MatDepth(CV_16S),
MatDepth(CV_32S),
MatDepth(CV_32F)),
testing::Values(NormCode(cv::NORM_L1), NormCode(cv::NORM_L2), NormCode(cv::NORM_INF)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// normDiff
PARAM_TEST_CASE(NormDiff, cv::gpu::DeviceInfo, cv::Size, NormCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int normCode;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
normCode = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(NormDiff, Accuracy)
{
cv::Mat src1 = randomMat(size, CV_8UC1);
cv::Mat src2 = randomMat(size, CV_8UC1);
double val = cv::gpu::norm(loadMat(src1, useRoi), loadMat(src2, useRoi), normCode);
double val_gold = cv::norm(src1, src2, normCode);
EXPECT_NEAR(val_gold, val, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, NormDiff, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(NormCode(cv::NORM_L1), NormCode(cv::NORM_L2), NormCode(cv::NORM_INF)),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// Sum
namespace
{
template <typename T>
cv::Scalar absSumImpl(const cv::Mat& src)
{
const int cn = src.channels();
cv::Scalar sum = cv::Scalar::all(0);
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
{
for (int c = 0; c < cn; ++c)
sum[c] += std::abs(src.at<T>(y, x * cn + c));
}
}
return sum;
}
cv::Scalar absSumGold(const cv::Mat& src)
{
typedef cv::Scalar (*func_t)(const cv::Mat& src);
static const func_t funcs[] =
{
absSumImpl<uchar>,
absSumImpl<schar>,
absSumImpl<ushort>,
absSumImpl<short>,
absSumImpl<int>,
absSumImpl<float>,
absSumImpl<double>
};
return funcs[src.depth()](src);
}
template <typename T>
cv::Scalar sqrSumImpl(const cv::Mat& src)
{
const int cn = src.channels();
cv::Scalar sum = cv::Scalar::all(0);
for (int y = 0; y < src.rows; ++y)
{
for (int x = 0; x < src.cols; ++x)
{
for (int c = 0; c < cn; ++c)
{
const T val = src.at<T>(y, x * cn + c);
sum[c] += val * val;
}
}
}
return sum;
}
cv::Scalar sqrSumGold(const cv::Mat& src)
{
typedef cv::Scalar (*func_t)(const cv::Mat& src);
static const func_t funcs[] =
{
sqrSumImpl<uchar>,
sqrSumImpl<schar>,
sqrSumImpl<ushort>,
sqrSumImpl<short>,
sqrSumImpl<int>,
sqrSumImpl<float>,
sqrSumImpl<double>
};
return funcs[src.depth()](src);
}
}
PARAM_TEST_CASE(Sum, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
bool useRoi;
cv::Mat src;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
src = randomMat(size, type, -128.0, 128.0);
}
};
GPU_TEST_P(Sum, Simple)
{
cv::Scalar val = cv::gpu::sum(loadMat(src, useRoi));
cv::Scalar val_gold = cv::sum(src);
EXPECT_SCALAR_NEAR(val_gold, val, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.5);
}
GPU_TEST_P(Sum, Abs)
{
cv::Scalar val = cv::gpu::absSum(loadMat(src, useRoi));
cv::Scalar val_gold = absSumGold(src);
EXPECT_SCALAR_NEAR(val_gold, val, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.5);
}
GPU_TEST_P(Sum, Sqr)
{
cv::Scalar val = cv::gpu::sqrSum(loadMat(src, useRoi));
cv::Scalar val_gold = sqrSumGold(src);
EXPECT_SCALAR_NEAR(val_gold, val, CV_MAT_DEPTH(type) < CV_32F ? 0.0 : 0.5);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Sum, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
TYPES(CV_8U, CV_64F, 1, 4),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// MinMax
PARAM_TEST_CASE(MinMax, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(MinMax, WithoutMask)
{
cv::Mat src = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
double minVal, maxVal;
cv::gpu::minMax(loadMat(src), &minVal, &maxVal);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
double minVal, maxVal;
cv::gpu::minMax(loadMat(src, useRoi), &minVal, &maxVal);
double minVal_gold, maxVal_gold;
minMaxLocGold(src, &minVal_gold, &maxVal_gold);
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
}
}
GPU_TEST_P(MinMax, WithMask)
{
cv::Mat src = randomMat(size, depth);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
double minVal, maxVal;
cv::gpu::minMax(loadMat(src), &minVal, &maxVal, loadMat(mask));
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
double minVal, maxVal;
cv::gpu::minMax(loadMat(src, useRoi), &minVal, &maxVal, loadMat(mask, useRoi));
double minVal_gold, maxVal_gold;
minMaxLocGold(src, &minVal_gold, &maxVal_gold, 0, 0, mask);
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
}
}
GPU_TEST_P(MinMax, NullPtr)
{
cv::Mat src = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
double minVal, maxVal;
cv::gpu::minMax(loadMat(src), &minVal, 0);
cv::gpu::minMax(loadMat(src), 0, &maxVal);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
double minVal, maxVal;
cv::gpu::minMax(loadMat(src, useRoi), &minVal, 0);
cv::gpu::minMax(loadMat(src, useRoi), 0, &maxVal);
double minVal_gold, maxVal_gold;
minMaxLocGold(src, &minVal_gold, &maxVal_gold, 0, 0);
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, MinMax, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// MinMaxLoc
namespace
{
template <typename T>
void expectEqualImpl(const cv::Mat& src, cv::Point loc_gold, cv::Point loc)
{
EXPECT_EQ(src.at<T>(loc_gold.y, loc_gold.x), src.at<T>(loc.y, loc.x));
}
void expectEqual(const cv::Mat& src, cv::Point loc_gold, cv::Point loc)
{
typedef void (*func_t)(const cv::Mat& src, cv::Point loc_gold, cv::Point loc);
static const func_t funcs[] =
{
expectEqualImpl<uchar>,
expectEqualImpl<schar>,
expectEqualImpl<ushort>,
expectEqualImpl<short>,
expectEqualImpl<int>,
expectEqualImpl<float>,
expectEqualImpl<double>
};
funcs[src.depth()](src, loc_gold, loc);
}
}
PARAM_TEST_CASE(MinMaxLoc, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(MinMaxLoc, WithoutMask)
{
cv::Mat src = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
double minVal, maxVal;
cv::Point minLoc, maxLoc;
cv::gpu::minMaxLoc(loadMat(src), &minVal, &maxVal, &minLoc, &maxLoc);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
double minVal, maxVal;
cv::Point minLoc, maxLoc;
cv::gpu::minMaxLoc(loadMat(src, useRoi), &minVal, &maxVal, &minLoc, &maxLoc);
double minVal_gold, maxVal_gold;
cv::Point minLoc_gold, maxLoc_gold;
minMaxLocGold(src, &minVal_gold, &maxVal_gold, &minLoc_gold, &maxLoc_gold);
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
expectEqual(src, minLoc_gold, minLoc);
expectEqual(src, maxLoc_gold, maxLoc);
}
}
GPU_TEST_P(MinMaxLoc, WithMask)
{
cv::Mat src = randomMat(size, depth);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
double minVal, maxVal;
cv::Point minLoc, maxLoc;
cv::gpu::minMaxLoc(loadMat(src), &minVal, &maxVal, &minLoc, &maxLoc, loadMat(mask));
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
double minVal, maxVal;
cv::Point minLoc, maxLoc;
cv::gpu::minMaxLoc(loadMat(src, useRoi), &minVal, &maxVal, &minLoc, &maxLoc, loadMat(mask, useRoi));
double minVal_gold, maxVal_gold;
cv::Point minLoc_gold, maxLoc_gold;
minMaxLocGold(src, &minVal_gold, &maxVal_gold, &minLoc_gold, &maxLoc_gold, mask);
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
expectEqual(src, minLoc_gold, minLoc);
expectEqual(src, maxLoc_gold, maxLoc);
}
}
GPU_TEST_P(MinMaxLoc, NullPtr)
{
cv::Mat src = randomMat(size, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
double minVal, maxVal;
cv::Point minLoc, maxLoc;
cv::gpu::minMaxLoc(loadMat(src, useRoi), &minVal, 0, 0, 0);
cv::gpu::minMaxLoc(loadMat(src, useRoi), 0, &maxVal, 0, 0);
cv::gpu::minMaxLoc(loadMat(src, useRoi), 0, 0, &minLoc, 0);
cv::gpu::minMaxLoc(loadMat(src, useRoi), 0, 0, 0, &maxLoc);
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
double minVal, maxVal;
cv::Point minLoc, maxLoc;
cv::gpu::minMaxLoc(loadMat(src, useRoi), &minVal, 0, 0, 0);
cv::gpu::minMaxLoc(loadMat(src, useRoi), 0, &maxVal, 0, 0);
cv::gpu::minMaxLoc(loadMat(src, useRoi), 0, 0, &minLoc, 0);
cv::gpu::minMaxLoc(loadMat(src, useRoi), 0, 0, 0, &maxLoc);
double minVal_gold, maxVal_gold;
cv::Point minLoc_gold, maxLoc_gold;
minMaxLocGold(src, &minVal_gold, &maxVal_gold, &minLoc_gold, &maxLoc_gold);
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
expectEqual(src, minLoc_gold, minLoc);
expectEqual(src, maxLoc_gold, maxLoc);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, MinMaxLoc, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////
// CountNonZero
PARAM_TEST_CASE(CountNonZero, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(CountNonZero, Accuracy)
{
cv::Mat srcBase = randomMat(size, CV_8U, 0.0, 1.5);
cv::Mat src;
srcBase.convertTo(src, depth);
if (depth == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
{
try
{
cv::gpu::countNonZero(loadMat(src));
}
catch (const cv::Exception& e)
{
ASSERT_EQ(cv::Error::StsUnsupportedFormat, e.code);
}
}
else
{
int val = cv::gpu::countNonZero(loadMat(src, useRoi));
int val_gold = cv::countNonZero(src);
ASSERT_EQ(val_gold, val);
}
}
INSTANTIATE_TEST_CASE_P(GPU_Core, CountNonZero, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// Reduce
CV_ENUM(ReduceCode, REDUCE_SUM, REDUCE_AVG, REDUCE_MAX, REDUCE_MIN)
PARAM_TEST_CASE(Reduce, cv::gpu::DeviceInfo, cv::Size, MatDepth, Channels, ReduceCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
int channels;
int reduceOp;
bool useRoi;
int type;
int dst_depth;
int dst_type;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
channels = GET_PARAM(3);
reduceOp = GET_PARAM(4);
useRoi = GET_PARAM(5);
cv::gpu::setDevice(devInfo.deviceID());
type = CV_MAKE_TYPE(depth, channels);
if (reduceOp == cv::REDUCE_MAX || reduceOp == cv::REDUCE_MIN)
dst_depth = depth;
else if (reduceOp == cv::REDUCE_SUM)
dst_depth = depth == CV_8U ? CV_32S : depth < CV_64F ? CV_32F : depth;
else
dst_depth = depth < CV_32F ? CV_32F : depth;
dst_type = CV_MAKE_TYPE(dst_depth, channels);
}
};
GPU_TEST_P(Reduce, Rows)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(cv::Size(src.cols, 1), dst_type, useRoi);
cv::gpu::reduce(loadMat(src, useRoi), dst, 0, reduceOp, dst_depth);
cv::Mat dst_gold;
cv::reduce(src, dst_gold, 0, reduceOp, dst_depth);
EXPECT_MAT_NEAR(dst_gold, dst, dst_depth < CV_32F ? 0.0 : 0.02);
}
GPU_TEST_P(Reduce, Cols)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(cv::Size(src.rows, 1), dst_type, useRoi);
cv::gpu::reduce(loadMat(src, useRoi), dst, 1, reduceOp, dst_depth);
cv::Mat dst_gold;
cv::reduce(src, dst_gold, 1, reduceOp, dst_depth);
dst_gold.cols = dst_gold.rows;
dst_gold.rows = 1;
dst_gold.step = dst_gold.cols * dst_gold.elemSize();
EXPECT_MAT_NEAR(dst_gold, dst, dst_depth < CV_32F ? 0.0 : 0.02);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Reduce, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U),
MatDepth(CV_16U),
MatDepth(CV_16S),
MatDepth(CV_32F),
MatDepth(CV_64F)),
ALL_CHANNELS,
ReduceCode::all(),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// Normalize
PARAM_TEST_CASE(Normalize, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int type;
int norm_type;
bool useRoi;
double alpha;
double beta;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
norm_type = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
alpha = 1;
beta = 0;
}
};
GPU_TEST_P(Normalize, WithOutMask)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::normalize(loadMat(src, useRoi), dst, alpha, beta, norm_type, type);
cv::Mat dst_gold;
cv::normalize(src, dst_gold, alpha, beta, norm_type, type);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-6);
}
GPU_TEST_P(Normalize, WithMask)
{
cv::Mat src = randomMat(size, type);
cv::Mat mask = randomMat(size, CV_8UC1, 0, 2);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::normalize(loadMat(src, useRoi), dst, alpha, beta, norm_type, type, loadMat(mask, useRoi));
cv::Mat dst_gold(size, type);
dst_gold.setTo(cv::Scalar::all(0));
cv::normalize(src, dst_gold, alpha, beta, norm_type, type, mask);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-6);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Normalize, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
testing::Values(NormCode(cv::NORM_L1), NormCode(cv::NORM_L2), NormCode(cv::NORM_INF), NormCode(cv::NORM_MINMAX)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////
// MulSpectrums
CV_FLAGS(DftFlags, 0, cv::DFT_INVERSE, cv::DFT_SCALE, cv::DFT_ROWS, cv::DFT_COMPLEX_OUTPUT, cv::DFT_REAL_OUTPUT)
PARAM_TEST_CASE(MulSpectrums, cv::gpu::DeviceInfo, cv::Size, DftFlags)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int flag;
cv::Mat a, b;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
flag = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
a = randomMat(size, CV_32FC2);
b = randomMat(size, CV_32FC2);
}
};
GPU_TEST_P(MulSpectrums, Simple)
{
cv::gpu::GpuMat c;
cv::gpu::mulSpectrums(loadMat(a), loadMat(b), c, flag, false);
cv::Mat c_gold;
cv::mulSpectrums(a, b, c_gold, flag, false);
EXPECT_MAT_NEAR(c_gold, c, 1e-2);
}
GPU_TEST_P(MulSpectrums, Scaled)
{
float scale = 1.f / size.area();
cv::gpu::GpuMat c;
cv::gpu::mulAndScaleSpectrums(loadMat(a), loadMat(b), c, flag, scale, false);
cv::Mat c_gold;
cv::mulSpectrums(a, b, c_gold, flag, false);
c_gold.convertTo(c_gold, c_gold.type(), scale);
EXPECT_MAT_NEAR(c_gold, c, 1e-2);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MulSpectrums, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(DftFlags(0), DftFlags(cv::DFT_ROWS))));
////////////////////////////////////////////////////////////////////////////
// Dft
struct Dft : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
namespace
{
void testC2C(const std::string& hint, int cols, int rows, int flags, bool inplace)
{
SCOPED_TRACE(hint);
cv::Mat a = randomMat(cv::Size(cols, rows), CV_32FC2, 0.0, 10.0);
cv::Mat b_gold;
cv::dft(a, b_gold, flags);
cv::gpu::GpuMat d_b;
cv::gpu::GpuMat d_b_data;
if (inplace)
{
d_b_data.create(1, a.size().area(), CV_32FC2);
d_b = cv::gpu::GpuMat(a.rows, a.cols, CV_32FC2, d_b_data.ptr(), a.cols * d_b_data.elemSize());
}
cv::gpu::dft(loadMat(a), d_b, cv::Size(cols, rows), flags);
EXPECT_TRUE(!inplace || d_b.ptr() == d_b_data.ptr());
ASSERT_EQ(CV_32F, d_b.depth());
ASSERT_EQ(2, d_b.channels());
EXPECT_MAT_NEAR(b_gold, cv::Mat(d_b), rows * cols * 1e-4);
}
}
GPU_TEST_P(Dft, C2C)
{
int cols = randomInt(2, 100);
int rows = randomInt(2, 100);
for (int i = 0; i < 2; ++i)
{
bool inplace = i != 0;
testC2C("no flags", cols, rows, 0, inplace);
testC2C("no flags 0 1", cols, rows + 1, 0, inplace);
testC2C("no flags 1 0", cols, rows + 1, 0, inplace);
testC2C("no flags 1 1", cols + 1, rows, 0, inplace);
testC2C("DFT_INVERSE", cols, rows, cv::DFT_INVERSE, inplace);
testC2C("DFT_ROWS", cols, rows, cv::DFT_ROWS, inplace);
testC2C("single col", 1, rows, 0, inplace);
testC2C("single row", cols, 1, 0, inplace);
testC2C("single col inversed", 1, rows, cv::DFT_INVERSE, inplace);
testC2C("single row inversed", cols, 1, cv::DFT_INVERSE, inplace);
testC2C("single row DFT_ROWS", cols, 1, cv::DFT_ROWS, inplace);
testC2C("size 1 2", 1, 2, 0, inplace);
testC2C("size 2 1", 2, 1, 0, inplace);
}
}
namespace
{
void testR2CThenC2R(const std::string& hint, int cols, int rows, bool inplace)
{
SCOPED_TRACE(hint);
cv::Mat a = randomMat(cv::Size(cols, rows), CV_32FC1, 0.0, 10.0);
cv::gpu::GpuMat d_b, d_c;
cv::gpu::GpuMat d_b_data, d_c_data;
if (inplace)
{
if (a.cols == 1)
{
d_b_data.create(1, (a.rows / 2 + 1) * a.cols, CV_32FC2);
d_b = cv::gpu::GpuMat(a.rows / 2 + 1, a.cols, CV_32FC2, d_b_data.ptr(), a.cols * d_b_data.elemSize());
}
else
{
d_b_data.create(1, a.rows * (a.cols / 2 + 1), CV_32FC2);
d_b = cv::gpu::GpuMat(a.rows, a.cols / 2 + 1, CV_32FC2, d_b_data.ptr(), (a.cols / 2 + 1) * d_b_data.elemSize());
}
d_c_data.create(1, a.size().area(), CV_32F);
d_c = cv::gpu::GpuMat(a.rows, a.cols, CV_32F, d_c_data.ptr(), a.cols * d_c_data.elemSize());
}
cv::gpu::dft(loadMat(a), d_b, cv::Size(cols, rows), 0);
cv::gpu::dft(d_b, d_c, cv::Size(cols, rows), cv::DFT_REAL_OUTPUT | cv::DFT_SCALE);
EXPECT_TRUE(!inplace || d_b.ptr() == d_b_data.ptr());
EXPECT_TRUE(!inplace || d_c.ptr() == d_c_data.ptr());
ASSERT_EQ(CV_32F, d_c.depth());
ASSERT_EQ(1, d_c.channels());
cv::Mat c(d_c);
EXPECT_MAT_NEAR(a, c, rows * cols * 1e-5);
}
}
GPU_TEST_P(Dft, R2CThenC2R)
{
int cols = randomInt(2, 100);
int rows = randomInt(2, 100);
testR2CThenC2R("sanity", cols, rows, false);
testR2CThenC2R("sanity 0 1", cols, rows + 1, false);
testR2CThenC2R("sanity 1 0", cols + 1, rows, false);
testR2CThenC2R("sanity 1 1", cols + 1, rows + 1, false);
testR2CThenC2R("single col", 1, rows, false);
testR2CThenC2R("single col 1", 1, rows + 1, false);
testR2CThenC2R("single row", cols, 1, false);
testR2CThenC2R("single row 1", cols + 1, 1, false);
testR2CThenC2R("sanity", cols, rows, true);
testR2CThenC2R("sanity 0 1", cols, rows + 1, true);
testR2CThenC2R("sanity 1 0", cols + 1, rows, true);
testR2CThenC2R("sanity 1 1", cols + 1, rows + 1, true);
testR2CThenC2R("single row", cols, 1, true);
testR2CThenC2R("single row 1", cols + 1, 1, true);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Dft, ALL_DEVICES);
////////////////////////////////////////////////////////
// Convolve
namespace
{
void convolveDFT(const cv::Mat& A, const cv::Mat& B, cv::Mat& C, bool ccorr = false)
{
// reallocate the output array if needed
C.create(std::abs(A.rows - B.rows) + 1, std::abs(A.cols - B.cols) + 1, A.type());
cv::Size dftSize;
// compute the size of DFT transform
dftSize.width = cv::getOptimalDFTSize(A.cols + B.cols - 1);
dftSize.height = cv::getOptimalDFTSize(A.rows + B.rows - 1);
// allocate temporary buffers and initialize them with 0s
cv::Mat tempA(dftSize, A.type(), cv::Scalar::all(0));
cv::Mat tempB(dftSize, B.type(), cv::Scalar::all(0));
// copy A and B to the top-left corners of tempA and tempB, respectively
cv::Mat roiA(tempA, cv::Rect(0, 0, A.cols, A.rows));
A.copyTo(roiA);
cv::Mat roiB(tempB, cv::Rect(0, 0, B.cols, B.rows));
B.copyTo(roiB);
// now transform the padded A & B in-place;
// use "nonzeroRows" hint for faster processing
cv::dft(tempA, tempA, 0, A.rows);
cv::dft(tempB, tempB, 0, B.rows);
// multiply the spectrums;
// the function handles packed spectrum representations well
cv::mulSpectrums(tempA, tempB, tempA, 0, ccorr);
// transform the product back from the frequency domain.
// Even though all the result rows will be non-zero,
// you need only the first C.rows of them, and thus you
// pass nonzeroRows == C.rows
cv::dft(tempA, tempA, cv::DFT_INVERSE + cv::DFT_SCALE, C.rows);
// now copy the result back to C.
tempA(cv::Rect(0, 0, C.cols, C.rows)).copyTo(C);
}
IMPLEMENT_PARAM_CLASS(KSize, int)
IMPLEMENT_PARAM_CLASS(Ccorr, bool)
}
PARAM_TEST_CASE(Convolve, cv::gpu::DeviceInfo, cv::Size, KSize, Ccorr)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int ksize;
bool ccorr;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
ksize = GET_PARAM(2);
ccorr = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Convolve, Accuracy)
{
cv::Mat src = randomMat(size, CV_32FC1, 0.0, 100.0);
cv::Mat kernel = randomMat(cv::Size(ksize, ksize), CV_32FC1, 0.0, 1.0);
cv::gpu::GpuMat dst;
cv::gpu::convolve(loadMat(src), loadMat(kernel), dst, ccorr);
cv::Mat dst_gold;
convolveDFT(src, kernel, dst_gold, ccorr);
EXPECT_MAT_NEAR(dst, dst_gold, 1e-1);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Convolve, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(KSize(3), KSize(7), KSize(11), KSize(17), KSize(19), KSize(23), KSize(45)),
testing::Values(Ccorr(false), Ccorr(true))));
#ifdef HAVE_OPENCV_IMGPROC
//////////////////////////////////////////////////////////////////////////////
// CopyMakeBorder
namespace
{
IMPLEMENT_PARAM_CLASS(Border, int)
}
PARAM_TEST_CASE(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, Border, BorderType, UseRoi)
{
cv::gpu::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::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(CopyMakeBorder, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::Scalar val = randomScalar(0, 255);
cv::gpu::GpuMat dst = createMat(cv::Size(size.width + 2 * border, size.height + 2 * border), type, useRoi);
cv::gpu::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(GPU_ImgProc, 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));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// Integral
PARAM_TEST_CASE(Integral, cv::gpu::DeviceInfo, cv::Size, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(Integral, Accuracy)
{
cv::Mat src = randomMat(size, CV_8UC1);
cv::gpu::GpuMat dst = createMat(cv::Size(src.cols + 1, src.rows + 1), CV_32SC1, useRoi);
cv::gpu::integral(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
cv::integral(src, dst_gold, CV_32S);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Integral, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
WHOLE_SUBMAT));
#endif
#endif // HAVE_CUDA