Open Source Computer Vision Library https://opencv.org/
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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.
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// This software is provided by the copyright holders and contributors "as is" and
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// 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,
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//M*/
#include "test_precomp.hpp"
#ifdef HAVE_CUDA
using namespace cvtest;
///////////////////////////////////////////////////////////////////////////////////////////////////////
// CornerHarris
namespace
{
IMPLEMENT_PARAM_CLASS(BlockSize, int);
IMPLEMENT_PARAM_CLASS(ApertureSize, int);
}
PARAM_TEST_CASE(CornerHarris, cv::gpu::DeviceInfo, MatType, BorderType, BlockSize, ApertureSize)
{
cv::gpu::DeviceInfo devInfo;
int type;
int borderType;
int blockSize;
int apertureSize;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
borderType = GET_PARAM(2);
blockSize = GET_PARAM(3);
apertureSize = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(CornerHarris, Accuracy)
{
cv::Mat src = readImageType("stereobm/aloe-L.png", type);
ASSERT_FALSE(src.empty());
double k = randomDouble(0.1, 0.9);
cv::Ptr<cv::gpu::CornernessCriteria> harris = cv::gpu::createHarrisCorner(src.type(), blockSize, apertureSize, k, borderType);
cv::gpu::GpuMat dst;
harris->compute(loadMat(src), dst);
cv::Mat dst_gold;
cv::cornerHarris(src, dst_gold, blockSize, apertureSize, k, borderType);
EXPECT_MAT_NEAR(dst_gold, dst, 0.02);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CornerHarris, testing::Combine(
ALL_DEVICES,
testing::Values(MatType(CV_8UC1), MatType(CV_32FC1)),
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_REFLECT)),
testing::Values(BlockSize(3), BlockSize(5), BlockSize(7)),
testing::Values(ApertureSize(0), ApertureSize(3), ApertureSize(5), ApertureSize(7))));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// cornerMinEigen
PARAM_TEST_CASE(CornerMinEigen, cv::gpu::DeviceInfo, MatType, BorderType, BlockSize, ApertureSize)
{
cv::gpu::DeviceInfo devInfo;
int type;
int borderType;
int blockSize;
int apertureSize;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
borderType = GET_PARAM(2);
blockSize = GET_PARAM(3);
apertureSize = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(CornerMinEigen, Accuracy)
{
cv::Mat src = readImageType("stereobm/aloe-L.png", type);
ASSERT_FALSE(src.empty());
cv::Ptr<cv::gpu::CornernessCriteria> minEigenVal = cv::gpu::createMinEigenValCorner(src.type(), blockSize, apertureSize, borderType);
cv::gpu::GpuMat dst;
minEigenVal->compute(loadMat(src), dst);
cv::Mat dst_gold;
cv::cornerMinEigenVal(src, dst_gold, blockSize, apertureSize, borderType);
EXPECT_MAT_NEAR(dst_gold, dst, 0.02);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, CornerMinEigen, testing::Combine(
ALL_DEVICES,
testing::Values(MatType(CV_8UC1), MatType(CV_32FC1)),
testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_REFLECT)),
testing::Values(BlockSize(3), BlockSize(5), BlockSize(7)),
testing::Values(ApertureSize(0), ApertureSize(3), ApertureSize(5), ApertureSize(7))));
#endif // HAVE_CUDA