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opencv/modules/gpu/test/test_arithm.cpp
Vladislav Vinogradov 844bdea5ac fixed several bugs in gpu arithm functions 
refactored tests for them
2012-03-19 14:18:12 +00:00

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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.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#ifdef HAVE_CUDA
////////////////////////////////////////////////////////////////////////////////
// Add_Array
PARAM_TEST_CASE(Add_Array, cv::gpu::DeviceInfo, cv::Size, std::pair<MatDepth, MatDepth>, int, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatType, MatType> 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);
}
};
TEST_P(Add_Array, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::add(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, channels == 1 ? loadMat(mask, useRoi) : cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::add(mat1, mat2, dst_gold, channels == 1 ? mask : 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,
testing::Values(1, 2, 3, 4),
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<MatType, MatType> 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());
}
};
TEST_P(Add_Scalar, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
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>, int, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatType, MatType> 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);
}
};
TEST_P(Subtract_Array, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
cv::gpu::GpuMat dst = createMat(size, dtype, useRoi);
dst.setTo(cv::Scalar::all(0));
cv::gpu::subtract(loadMat(mat1, useRoi), loadMat(mat2, useRoi), dst, channels == 1 ? loadMat(mask, useRoi) : cv::gpu::GpuMat(), depth.second);
cv::Mat dst_gold(size, dtype, cv::Scalar::all(0));
cv::subtract(mat1, mat2, dst_gold, channels == 1 ? mask : 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,
testing::Values(1, 2, 3, 4),
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<MatType, MatType> 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());
}
};
TEST_P(Subtract_Scalar, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
cv::Mat mask = randomMat(size, CV_8UC1, 0.0, 2.0);
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>, int, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatType, MatType> 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);
}
};
TEST_P(Multiply_Array, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype);
double scale = randomDouble(0.0, 255.0);
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, 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Multiply_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
testing::Values(1, 2, 3, 4),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Multiply_Array_Special_Case
PARAM_TEST_CASE(Multiply_Array_Special_Case, 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());
}
};
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);
}
}
}
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_Case, 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<MatType, MatType> 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());
}
};
TEST_P(Multiply_Scalar, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(0, 255);
double scale = randomDouble(0.0, 255.0);
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, depth.first >= CV_32F || depth.second >= CV_32F ? 1e-4 : 0.0);
}
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>, int, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
std::pair<MatType, MatType> 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);
}
};
TEST_P(Divide_Array, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat1 = randomMat(size, stype);
cv::Mat mat2 = randomMat(size, stype, 1.0, 255.0);
double scale = randomDouble(0.0, 255.0);
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, 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Divide_Array, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
DEPTH_PAIRS,
testing::Values(1, 2, 3, 4),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Divide_Array_Special_Case
PARAM_TEST_CASE(Divide_Array_Special_Case, 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());
}
};
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);
}
}
}
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_Case, 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<MatType, MatType> 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());
}
};
TEST_P(Divide_Scalar, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat mat = randomMat(size, depth.first);
cv::Scalar val = randomScalar(1.0, 255.0);
double scale = randomDouble(0.0, 255.0);
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-4 : 0.0);
}
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<MatType, MatType> 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());
}
};
TEST_P(Divide_Scalar_Inv, Accuracy)
{
if (depth.first == CV_64F || depth.second == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
double scale = randomDouble(0.0, 255.0);
cv::Mat mat = randomMat(size, depth.first, 1.0, 255.0);
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 : 0.0);
}
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());
}
};
TEST_P(AbsDiff, Array)
{
if (depth == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
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);
}
TEST_P(AbsDiff, Scalar)
{
if (depth == CV_64F)
{
if (!devInfo.supports(cv::gpu::NATIVE_DOUBLE))
return;
}
cv::Mat src = randomMat(size, depth);
cv::Scalar val = randomScalar(0.0, 255.0);
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, 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());
}
};
TEST_P(Abs, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(size, type, 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(MatType(CV_16SC1), MatType(CV_32FC1)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Sqr
PARAM_TEST_CASE(Sqr, 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());
}
};
TEST_P(Sqr, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(size, type, 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(MatType(CV_8UC1), MatType(CV_16UC1), MatType(CV_16SC1), MatType(CV_32FC1)),
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, 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());
}
};
TEST_P(Sqrt, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::sqrt(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
sqrtGold(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Sqrt, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_16UC1), MatType(CV_16SC1), MatType(CV_32FC1)),
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, 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());
}
};
TEST_P(Log, Accuracy)
{
cv::Mat src = randomMat(size, type, 1.0, 255.0);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::log(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
logGold(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-6);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Log, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_16UC1), MatType(CV_16SC1), MatType(CV_32FC1)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// Exp
PARAM_TEST_CASE(Exp, 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());
}
};
TEST_P(Exp, Accuracy)
{
cv::Mat src = randomMat(size, type, 0.0, 10.0);
cv::gpu::GpuMat dst = createMat(size, type, useRoi);
cv::gpu::exp(loadMat(src, useRoi), dst);
cv::Mat dst_gold;
cv::exp(src, dst_gold);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-2);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Exp, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_32FC1)),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// compare
PARAM_TEST_CASE(Compare, 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());
}
};
TEST_P(Compare, Accuracy)
{
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
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, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
ALL_CMP_CODES,
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());
}
};
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);
}
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);
}
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);
}
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, int)
{
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, 255.0);
val = ival;
}
};
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);
}
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);
}
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)),
testing::Values(1, 3, 4)));
//////////////////////////////////////////////////////////////////////////////
// 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, int, 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());
}
};
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)),
testing::Values(1, 3, 4),
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, int, 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());
}
};
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::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, LShift, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_32S)),
testing::Values(1, 3, 4),
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());
}
};
TEST_P(Min, Accuracy)
{
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
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);
}
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());
}
};
TEST_P(Max, Accuracy)
{
cv::Mat src1 = randomMat(size, depth);
cv::Mat src2 = randomMat(size, depth);
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);
}
INSTANTIATE_TEST_CASE_P(GPU_Core, Max, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
ALL_DEPTH,
WHOLE_SUBMAT));
using namespace cvtest;
using namespace testing;
PARAM_TEST_CASE(ArithmTestBase, cv::gpu::DeviceInfo, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
bool useRoi;
cv::Size size;
cv::Mat mat1;
cv::Mat mat2;
cv::Scalar val;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat1 = randomMat(rng, size, type, 5, 16, false);
mat2 = randomMat(rng, size, type, 5, 16, false);
val = cv::Scalar(rng.uniform(1, 3), rng.uniform(1, 3), rng.uniform(1, 3), rng.uniform(1, 3));
}
};
////////////////////////////////////////////////////////////////////////////////
// transpose
struct Transpose : ArithmTestBase {};
TEST_P(Transpose, Accuracy)
{
cv::Mat dst_gold;
cv::transpose(mat1, dst_gold);
cv::Mat dst;
cv::gpu::GpuMat gpuRes;
cv::gpu::transpose(loadMat(mat1, useRoi), gpuRes);
gpuRes.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(Arithm, Transpose, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_8UC4, CV_8SC1, CV_8SC4, CV_16UC2, CV_16SC2, CV_32SC1, CV_32SC2, CV_32FC1, CV_32FC2, CV_64FC1),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// meanStdDev
PARAM_TEST_CASE(MeanStdDev, cv::gpu::DeviceInfo, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
bool useRoi;
cv::Size size;
cv::Mat mat;
cv::Scalar mean_gold;
cv::Scalar stddev_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
useRoi = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat = randomMat(rng, size, CV_8UC1, 1, 255, false);
cv::meanStdDev(mat, mean_gold, stddev_gold);
}
};
TEST_P(MeanStdDev, Accuracy)
{
cv::Scalar mean;
cv::Scalar stddev;
cv::gpu::meanStdDev(loadMat(mat, useRoi), mean, stddev);
EXPECT_NEAR(mean_gold[0], mean[0], 1e-5);
EXPECT_NEAR(mean_gold[1], mean[1], 1e-5);
EXPECT_NEAR(mean_gold[2], mean[2], 1e-5);
EXPECT_NEAR(mean_gold[3], mean[3], 1e-5);
EXPECT_NEAR(stddev_gold[0], stddev[0], 1e-5);
EXPECT_NEAR(stddev_gold[1], stddev[1], 1e-5);
EXPECT_NEAR(stddev_gold[2], stddev[2], 1e-5);
EXPECT_NEAR(stddev_gold[3], stddev[3], 1e-5);
}
INSTANTIATE_TEST_CASE_P(Arithm, MeanStdDev, Combine(
ALL_DEVICES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// normDiff
PARAM_TEST_CASE(NormDiff, cv::gpu::DeviceInfo, NormCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int normCode;
bool useRoi;
cv::Size size;
cv::Mat mat1, mat2;
double norm_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
normCode = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat1 = randomMat(rng, size, CV_8UC1, 1, 255, false);
mat2 = randomMat(rng, size, CV_8UC1, 1, 255, false);
norm_gold = cv::norm(mat1, mat2, normCode);
}
};
TEST_P(NormDiff, Accuracy)
{
double norm = cv::gpu::norm(loadMat(mat1, useRoi), loadMat(mat2, useRoi), normCode);
EXPECT_NEAR(norm_gold, norm, 1e-6);
}
INSTANTIATE_TEST_CASE_P(Arithm, NormDiff, Combine(
ALL_DEVICES,
Values((int) cv::NORM_INF, (int) cv::NORM_L1, (int) cv::NORM_L2),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// flip
PARAM_TEST_CASE(Flip, cv::gpu::DeviceInfo, MatType, FlipCode, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
int flip_code;
bool useRoi;
cv::Size size;
cv::Mat mat;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
flip_code = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat = randomMat(rng, size, type, 1, 255, false);
cv::flip(mat, dst_gold, flip_code);
}
};
TEST_P(Flip, Accuracy)
{
cv::Mat dst;
cv::gpu::GpuMat gpu_res;
cv::gpu::flip(loadMat(mat, useRoi), gpu_res, flip_code);
gpu_res.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(Arithm, Flip, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32SC1, CV_32SC3, CV_32SC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((int)FLIP_BOTH, (int)FLIP_X, (int)FLIP_Y),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// LUT
PARAM_TEST_CASE(LUT, cv::gpu::DeviceInfo, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
bool useRoi;
cv::Size size;
cv::Mat mat;
cv::Mat lut;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat = randomMat(rng, size, type, 1, 255, false);
lut = randomMat(rng, cv::Size(256, 1), CV_8UC1, 100, 200, false);
cv::LUT(mat, lut, dst_gold);
}
};
TEST_P(LUT, Accuracy)
{
cv::Mat dst;
cv::gpu::GpuMat gpu_res;
cv::gpu::LUT(loadMat(mat, useRoi), lut, gpu_res);
gpu_res.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(Arithm, LUT, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_8UC3),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// pow
PARAM_TEST_CASE(Pow, cv::gpu::DeviceInfo, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
bool useRoi;
double power;
cv::Size size;
cv::Mat mat;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat = randomMat(rng, size, type, 0.0, 100.0, false);
if (mat.depth() == CV_32F)
power = rng.uniform(1.2f, 3.f);
else
{
int ipower = rng.uniform(2, 8);
power = (float)ipower;
}
cv::pow(mat, power, dst_gold);
}
};
TEST_P(Pow, Accuracy)
{
cv::Mat dst;
cv::gpu::GpuMat gpu_res;
cv::gpu::pow(loadMat(mat, useRoi), power, gpu_res);
gpu_res.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 2);
}
INSTANTIATE_TEST_CASE_P(Arithm, Pow, Combine(
ALL_DEVICES,
Values(CV_32F, CV_32FC3),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// magnitude
PARAM_TEST_CASE(Magnitude, cv::gpu::DeviceInfo, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
bool useRoi;
cv::Size size;
cv::Mat mat1, mat2;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
useRoi = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat1 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
mat2 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
cv::magnitude(mat1, mat2, dst_gold);
}
};
TEST_P(Magnitude, Accuracy)
{
cv::Mat dst;
cv::gpu::GpuMat gpu_res;
cv::gpu::magnitude(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpu_res);
gpu_res.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-4);
}
INSTANTIATE_TEST_CASE_P(Arithm, Magnitude, Combine(
ALL_DEVICES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// phase
PARAM_TEST_CASE(Phase, cv::gpu::DeviceInfo, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
bool useRoi;
cv::Size size;
cv::Mat mat1, mat2;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
useRoi = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat1 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
mat2 = randomMat(rng, size, CV_32FC1, 0.0, 100.0, false);
cv::phase(mat1, mat2, dst_gold);
}
};
TEST_P(Phase, Accuracy)
{
cv::Mat dst;
cv::gpu::GpuMat gpu_res;
cv::gpu::phase(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpu_res);
gpu_res.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-3);
}
INSTANTIATE_TEST_CASE_P(Arithm, Phase, Combine(
ALL_DEVICES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// cartToPolar
PARAM_TEST_CASE(CartToPolar, cv::gpu::DeviceInfo, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
bool useRoi;
cv::Size size;
cv::Mat mat1, mat2;
cv::Mat mag_gold;
cv::Mat angle_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
useRoi = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat1 = randomMat(rng, size, CV_32FC1, -100.0, 100.0, false);
mat2 = randomMat(rng, size, CV_32FC1, -100.0, 100.0, false);
cv::cartToPolar(mat1, mat2, mag_gold, angle_gold);
}
};
TEST_P(CartToPolar, Accuracy)
{
cv::Mat mag, angle;
cv::gpu::GpuMat gpuMag;
cv::gpu::GpuMat gpuAngle;
cv::gpu::cartToPolar(loadMat(mat1, useRoi), loadMat(mat2, useRoi), gpuMag, gpuAngle);
gpuMag.download(mag);
gpuAngle.download(angle);
EXPECT_MAT_NEAR(mag_gold, mag, 1e-4);
EXPECT_MAT_NEAR(angle_gold, angle, 1e-3);
}
INSTANTIATE_TEST_CASE_P(Arithm, CartToPolar, Combine(
ALL_DEVICES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// polarToCart
PARAM_TEST_CASE(PolarToCart, cv::gpu::DeviceInfo, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
bool useRoi;
cv::Size size;
cv::Mat mag;
cv::Mat angle;
cv::Mat x_gold;
cv::Mat y_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
useRoi = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mag = randomMat(rng, size, CV_32FC1, -100.0, 100.0, false);
angle = randomMat(rng, size, CV_32FC1, 0.0, 2.0 * CV_PI, false);
cv::polarToCart(mag, angle, x_gold, y_gold);
}
};
TEST_P(PolarToCart, Accuracy)
{
cv::Mat x, y;
cv::gpu::GpuMat gpuX;
cv::gpu::GpuMat gpuY;
cv::gpu::polarToCart(loadMat(mag, useRoi), loadMat(angle, useRoi), gpuX, gpuY);
gpuX.download(x);
gpuY.download(y);
EXPECT_MAT_NEAR(x_gold, x, 1e-4);
EXPECT_MAT_NEAR(y_gold, y, 1e-4);
}
INSTANTIATE_TEST_CASE_P(Arithm, PolarToCart, Combine(
ALL_DEVICES,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// minMax
PARAM_TEST_CASE(MinMax, cv::gpu::DeviceInfo, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
bool useRoi;
cv::Size size;
cv::Mat mat;
cv::Mat mask;
double minVal_gold;
double maxVal_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat = randomMat(rng, size, type, 0.0, 127.0, false);
mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
if (type != CV_8S)
{
cv::minMaxLoc(mat, &minVal_gold, &maxVal_gold, 0, 0, mask);
}
else
{
// OpenCV's minMaxLoc doesn't support CV_8S type
minVal_gold = std::numeric_limits<double>::max();
maxVal_gold = -std::numeric_limits<double>::max();
for (int i = 0; i < mat.rows; ++i)
{
const signed char* mat_row = mat.ptr<signed char>(i);
const unsigned char* mask_row = mask.ptr<unsigned char>(i);
for (int j = 0; j < mat.cols; ++j)
{
if (mask_row[j])
{
signed char val = mat_row[j];
if (val < minVal_gold) minVal_gold = val;
if (val > maxVal_gold) maxVal_gold = val;
}
}
}
}
}
};
TEST_P(MinMax, Accuracy)
{
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
return;
double minVal, maxVal;
cv::gpu::minMax(loadMat(mat, useRoi), &minVal, &maxVal, loadMat(mask, useRoi));
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
}
INSTANTIATE_TEST_CASE_P(Arithm, MinMax, Combine(
ALL_DEVICES,
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// minMaxLoc
PARAM_TEST_CASE(MinMaxLoc, cv::gpu::DeviceInfo, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
bool useRoi;
cv::Size size;
cv::Mat mat;
cv::Mat mask;
double minVal_gold;
double maxVal_gold;
cv::Point minLoc_gold;
cv::Point maxLoc_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat = randomMat(rng, size, type, 0.0, 127.0, false);
mask = randomMat(rng, size, CV_8UC1, 0, 2, false);
if (type != CV_8S)
{
cv::minMaxLoc(mat, &minVal_gold, &maxVal_gold, &minLoc_gold, &maxLoc_gold, mask);
}
else
{
// OpenCV's minMaxLoc doesn't support CV_8S type
minVal_gold = std::numeric_limits<double>::max();
maxVal_gold = -std::numeric_limits<double>::max();
for (int i = 0; i < mat.rows; ++i)
{
const signed char* mat_row = mat.ptr<signed char>(i);
const unsigned char* mask_row = mask.ptr<unsigned char>(i);
for (int j = 0; j < mat.cols; ++j)
{
if (mask_row[j])
{
signed char val = mat_row[j];
if (val < minVal_gold) { minVal_gold = val; minLoc_gold = cv::Point(j, i); }
if (val > maxVal_gold) { maxVal_gold = val; maxLoc_gold = cv::Point(j, i); }
}
}
}
}
}
};
TEST_P(MinMaxLoc, Accuracy)
{
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
return;
double minVal, maxVal;
cv::Point minLoc, maxLoc;
cv::gpu::minMaxLoc(loadMat(mat, useRoi), &minVal, &maxVal, &minLoc, &maxLoc, loadMat(mask, useRoi));
EXPECT_DOUBLE_EQ(minVal_gold, minVal);
EXPECT_DOUBLE_EQ(maxVal_gold, maxVal);
int cmpMinVals = memcmp(mat.data + minLoc_gold.y * mat.step + minLoc_gold.x * mat.elemSize(),
mat.data + minLoc.y * mat.step + minLoc.x * mat.elemSize(),
mat.elemSize());
int cmpMaxVals = memcmp(mat.data + maxLoc_gold.y * mat.step + maxLoc_gold.x * mat.elemSize(),
mat.data + maxLoc.y * mat.step + maxLoc.x * mat.elemSize(),
mat.elemSize());
EXPECT_EQ(0, cmpMinVals);
EXPECT_EQ(0, cmpMaxVals);
}
INSTANTIATE_TEST_CASE_P(Arithm, MinMaxLoc, Combine(
ALL_DEVICES,
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////
// countNonZero
PARAM_TEST_CASE(CountNonZero, cv::gpu::DeviceInfo, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
bool useRoi;
cv::Size size;
cv::Mat mat;
int n_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
cv::Mat matBase = randomMat(rng, size, CV_8U, 0.0, 1.0, false);
matBase.convertTo(mat, type);
n_gold = cv::countNonZero(mat);
}
};
TEST_P(CountNonZero, Accuracy)
{
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
return;
int n = cv::gpu::countNonZero(loadMat(mat, useRoi));
ASSERT_EQ(n_gold, n);
}
INSTANTIATE_TEST_CASE_P(Arithm, CountNonZero, Combine(
ALL_DEVICES,
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// sum
PARAM_TEST_CASE(Sum, cv::gpu::DeviceInfo, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
bool useRoi;
cv::Size size;
cv::Mat mat;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
useRoi = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat = randomMat(rng, size, CV_8U, 0.0, 10.0, false);
}
};
TEST_P(Sum, Simple)
{
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
return;
cv::Scalar sum_gold = cv::sum(mat);
cv::Scalar sum = cv::gpu::sum(loadMat(mat, useRoi));
EXPECT_NEAR(sum[0], sum_gold[0], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[1], sum_gold[1], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[2], sum_gold[2], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[3], sum_gold[3], mat.size().area() * 1e-5);
}
TEST_P(Sum, Abs)
{
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
return;
cv::Scalar sum_gold = cv::norm(mat, cv::NORM_L1);
cv::Scalar sum = cv::gpu::absSum(loadMat(mat, useRoi));
EXPECT_NEAR(sum[0], sum_gold[0], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[1], sum_gold[1], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[2], sum_gold[2], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[3], sum_gold[3], mat.size().area() * 1e-5);
}
TEST_P(Sum, Sqr)
{
if (type == CV_64F && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
return;
cv::Mat sqrmat;
multiply(mat, mat, sqrmat);
cv::Scalar sum_gold = sum(sqrmat);
cv::Scalar sum = cv::gpu::sqrSum(loadMat(mat, useRoi));
EXPECT_NEAR(sum[0], sum_gold[0], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[1], sum_gold[1], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[2], sum_gold[2], mat.size().area() * 1e-5);
EXPECT_NEAR(sum[3], sum_gold[3], mat.size().area() * 1e-5);
}
INSTANTIATE_TEST_CASE_P(Arithm, Sum, Combine(
ALL_DEVICES,
Values(CV_8U, CV_8S, CV_16U, CV_16S, CV_32S, CV_32F, CV_64F),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// addWeighted
PARAM_TEST_CASE(AddWeighted, cv::gpu::DeviceInfo, MatType, MatType, MatType, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type1;
int type2;
int dtype;
bool useRoi;
cv::Size size;
cv::Mat src1;
cv::Mat src2;
double alpha;
double beta;
double gamma;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type1 = GET_PARAM(1);
type2 = GET_PARAM(2);
dtype = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
src1 = randomMat(rng, size, type1, 0.0, 255.0, false);
src2 = randomMat(rng, size, type2, 0.0, 255.0, false);
alpha = rng.uniform(-10.0, 10.0);
beta = rng.uniform(-10.0, 10.0);
gamma = rng.uniform(-10.0, 10.0);
cv::addWeighted(src1, alpha, src2, beta, gamma, dst_gold, dtype);
}
};
TEST_P(AddWeighted, Accuracy)
{
if ((src1.depth() == CV_64F || src2.depth() == CV_64F || dst_gold.depth() == CV_64F) && !supportFeature(devInfo, cv::gpu::NATIVE_DOUBLE))
return;
cv::Mat dst;
cv::gpu::GpuMat dev_dst;
cv::gpu::addWeighted(loadMat(src1, useRoi), alpha, loadMat(src2, useRoi), beta, gamma, dev_dst, dtype);
dev_dst.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, dtype < CV_32F ? 1.0 : 1e-12);
}
INSTANTIATE_TEST_CASE_P(Arithm, AddWeighted, Combine(
ALL_DEVICES,
TYPES(CV_8U, CV_64F, 1, 1),
TYPES(CV_8U, CV_64F, 1, 1),
TYPES(CV_8U, CV_64F, 1, 1),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// reduce
PARAM_TEST_CASE(Reduce, cv::gpu::DeviceInfo, MatType, int, ReduceOp, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
int dim;
int reduceOp;
bool useRoi;
cv::Size size;
cv::Mat src;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
dim = GET_PARAM(2);
reduceOp = GET_PARAM(3);
useRoi = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 400), rng.uniform(100, 400));
src = randomMat(rng, size, type, 0.0, 255.0, false);
cv::reduce(src, dst_gold, dim, reduceOp, reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG ? CV_32F : CV_MAT_DEPTH(type));
if (dim == 1)
{
dst_gold.cols = dst_gold.rows;
dst_gold.rows = 1;
dst_gold.step = dst_gold.cols * dst_gold.elemSize();
}
}
};
TEST_P(Reduce, Accuracy)
{
cv::Mat dst;
cv::gpu::GpuMat dev_dst;
cv::gpu::reduce(loadMat(src, useRoi), dev_dst, dim, reduceOp, reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG ? CV_32F : CV_MAT_DEPTH(type));
dev_dst.download(dst);
double norm = reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG ? 1e-1 : 0.0;
EXPECT_MAT_NEAR(dst_gold, dst, norm);
}
INSTANTIATE_TEST_CASE_P(Arithm, Reduce, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values(0, 1),
Values((int)CV_REDUCE_SUM, (int)CV_REDUCE_AVG, (int)CV_REDUCE_MAX, (int)CV_REDUCE_MIN),
WHOLE_SUBMAT));
//////////////////////////////////////////////////////////////////////////////
// gemm
PARAM_TEST_CASE(GEMM, cv::gpu::DeviceInfo, MatType, GemmFlags, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
int type;
int flags;
bool useRoi;
int size;
cv::Mat src1;
cv::Mat src2;
cv::Mat src3;
double alpha;
double beta;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
flags = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = TS::ptr()->get_rng();
size = rng.uniform(100, 200);
src1 = randomMat(rng, cv::Size(size, size), type, -10.0, 10.0, false);
src2 = randomMat(rng, cv::Size(size, size), type, -10.0, 10.0, false);
src3 = randomMat(rng, cv::Size(size, size), type, -10.0, 10.0, false);
alpha = rng.uniform(-10.0, 10.0);
beta = rng.uniform(-10.0, 10.0);
cv::gemm(src1, src2, alpha, src3, beta, dst_gold, flags);
}
};
TEST_P(GEMM, Accuracy)
{
cv::Mat dst;
cv::gpu::GpuMat dev_dst;
cv::gpu::gemm(loadMat(src1, useRoi), loadMat(src2, useRoi), alpha, loadMat(src3, useRoi), beta, dev_dst, flags);
dev_dst.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-1);
}
INSTANTIATE_TEST_CASE_P(Arithm, GEMM, Combine(
ALL_DEVICES,
Values(CV_32FC1, CV_32FC2),
Values(0, (int) cv::GEMM_1_T, (int) cv::GEMM_2_T, (int) cv::GEMM_3_T),
WHOLE_SUBMAT));
#endif // HAVE_CUDA
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