mirror of
https://github.com/opencv/opencv.git
synced 2024-12-15 18:09:11 +08:00
6f3163f62d
Added the defaultNorm() method to the DescriptorExtractor class. This method returns the default norm type for each descriptor type. The tests and C/C++ samples were updated to get the norm type directly from the DescriptorExtractor inherited classes. This was reported in feature report #2182 (http://code.opencv.org/issues/2182). It will make it possible to get the norm type usually applied matching method for each descriptor, instead of passing it manually.
199 lines
6.9 KiB
C++
199 lines
6.9 KiB
C++
/*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;
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
// SURF
|
|
|
|
#ifdef HAVE_OPENCV_CUDAARITHM
|
|
|
|
namespace
|
|
{
|
|
IMPLEMENT_PARAM_CLASS(SURF_HessianThreshold, double)
|
|
IMPLEMENT_PARAM_CLASS(SURF_Octaves, int)
|
|
IMPLEMENT_PARAM_CLASS(SURF_OctaveLayers, int)
|
|
IMPLEMENT_PARAM_CLASS(SURF_Extended, bool)
|
|
IMPLEMENT_PARAM_CLASS(SURF_Upright, bool)
|
|
}
|
|
|
|
PARAM_TEST_CASE(SURF, SURF_HessianThreshold, SURF_Octaves, SURF_OctaveLayers, SURF_Extended, SURF_Upright)
|
|
{
|
|
double hessianThreshold;
|
|
int nOctaves;
|
|
int nOctaveLayers;
|
|
bool extended;
|
|
bool upright;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
hessianThreshold = GET_PARAM(0);
|
|
nOctaves = GET_PARAM(1);
|
|
nOctaveLayers = GET_PARAM(2);
|
|
extended = GET_PARAM(3);
|
|
upright = GET_PARAM(4);
|
|
}
|
|
};
|
|
|
|
CUDA_TEST_P(SURF, Detector)
|
|
{
|
|
cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE);
|
|
ASSERT_FALSE(image.empty());
|
|
|
|
cv::cuda::SURF_CUDA surf;
|
|
surf.hessianThreshold = hessianThreshold;
|
|
surf.nOctaves = nOctaves;
|
|
surf.nOctaveLayers = nOctaveLayers;
|
|
surf.extended = extended;
|
|
surf.upright = upright;
|
|
surf.keypointsRatio = 0.05f;
|
|
|
|
std::vector<cv::KeyPoint> keypoints;
|
|
surf(loadMat(image), cv::cuda::GpuMat(), keypoints);
|
|
|
|
cv::SURF surf_gold;
|
|
surf_gold.hessianThreshold = hessianThreshold;
|
|
surf_gold.nOctaves = nOctaves;
|
|
surf_gold.nOctaveLayers = nOctaveLayers;
|
|
surf_gold.extended = extended;
|
|
surf_gold.upright = upright;
|
|
|
|
std::vector<cv::KeyPoint> keypoints_gold;
|
|
surf_gold(image, cv::noArray(), keypoints_gold);
|
|
|
|
ASSERT_EQ(keypoints_gold.size(), keypoints.size());
|
|
int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints);
|
|
double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size();
|
|
|
|
EXPECT_GT(matchedRatio, 0.95);
|
|
}
|
|
|
|
CUDA_TEST_P(SURF, Detector_Masked)
|
|
{
|
|
cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE);
|
|
ASSERT_FALSE(image.empty());
|
|
|
|
cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1));
|
|
mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0));
|
|
|
|
cv::cuda::SURF_CUDA surf;
|
|
surf.hessianThreshold = hessianThreshold;
|
|
surf.nOctaves = nOctaves;
|
|
surf.nOctaveLayers = nOctaveLayers;
|
|
surf.extended = extended;
|
|
surf.upright = upright;
|
|
surf.keypointsRatio = 0.05f;
|
|
|
|
std::vector<cv::KeyPoint> keypoints;
|
|
surf(loadMat(image), loadMat(mask), keypoints);
|
|
|
|
cv::SURF surf_gold;
|
|
surf_gold.hessianThreshold = hessianThreshold;
|
|
surf_gold.nOctaves = nOctaves;
|
|
surf_gold.nOctaveLayers = nOctaveLayers;
|
|
surf_gold.extended = extended;
|
|
surf_gold.upright = upright;
|
|
|
|
std::vector<cv::KeyPoint> keypoints_gold;
|
|
surf_gold(image, mask, keypoints_gold);
|
|
|
|
ASSERT_EQ(keypoints_gold.size(), keypoints.size());
|
|
int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints);
|
|
double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size();
|
|
|
|
EXPECT_GT(matchedRatio, 0.95);
|
|
}
|
|
|
|
CUDA_TEST_P(SURF, Descriptor)
|
|
{
|
|
cv::Mat image = readImage("../gpu/features2d/aloe.png", cv::IMREAD_GRAYSCALE);
|
|
ASSERT_FALSE(image.empty());
|
|
|
|
cv::cuda::SURF_CUDA surf;
|
|
surf.hessianThreshold = hessianThreshold;
|
|
surf.nOctaves = nOctaves;
|
|
surf.nOctaveLayers = nOctaveLayers;
|
|
surf.extended = extended;
|
|
surf.upright = upright;
|
|
surf.keypointsRatio = 0.05f;
|
|
|
|
cv::SURF surf_gold;
|
|
surf_gold.hessianThreshold = hessianThreshold;
|
|
surf_gold.nOctaves = nOctaves;
|
|
surf_gold.nOctaveLayers = nOctaveLayers;
|
|
surf_gold.extended = extended;
|
|
surf_gold.upright = upright;
|
|
|
|
std::vector<cv::KeyPoint> keypoints;
|
|
surf_gold(image, cv::noArray(), keypoints);
|
|
|
|
cv::cuda::GpuMat descriptors;
|
|
surf(loadMat(image), cv::cuda::GpuMat(), keypoints, descriptors, true);
|
|
|
|
cv::Mat descriptors_gold;
|
|
surf_gold(image, cv::noArray(), keypoints, descriptors_gold, true);
|
|
|
|
cv::BFMatcher matcher(surf.defaultNorm());
|
|
std::vector<cv::DMatch> matches;
|
|
matcher.match(descriptors_gold, cv::Mat(descriptors), matches);
|
|
|
|
int matchedCount = getMatchedPointsCount(keypoints, keypoints, matches);
|
|
double matchedRatio = static_cast<double>(matchedCount) / keypoints.size();
|
|
|
|
EXPECT_GT(matchedRatio, 0.6);
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(CUDA_Features2D, SURF, testing::Combine(
|
|
testing::Values(SURF_HessianThreshold(100.0), SURF_HessianThreshold(500.0), SURF_HessianThreshold(1000.0)),
|
|
testing::Values(SURF_Octaves(3), SURF_Octaves(4)),
|
|
testing::Values(SURF_OctaveLayers(2), SURF_OctaveLayers(3)),
|
|
testing::Values(SURF_Extended(false), SURF_Extended(true)),
|
|
testing::Values(SURF_Upright(false), SURF_Upright(true))));
|
|
|
|
#endif // HAVE_OPENCV_CUDAARITHM
|
|
|
|
#endif // HAVE_CUDA
|