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vendor: OpenCV 5.0.0 snapshot at 40738fb16ceddb5fb3fea747585f7ce6abb0605b

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modules/features/perf/opencl/perf_brute_force_matcher.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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Fangfang Bai, fangfang@multicorewareinc.com
// Jin Ma, jin@multicorewareinc.com
//
// 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 "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#ifdef HAVE_OPENCL
namespace opencv_test {
namespace ocl {
//////////////////// BruteForceMatch /////////////////
typedef Size_MatType BruteForceMatcherFixture;
OCL_PERF_TEST_P(BruteForceMatcherFixture, Match, ::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3), OCL_PERF_ENUM((MatType)CV_32FC1) ) )
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
checkDeviceMaxMemoryAllocSize(srcSize, type);
vector<DMatch> matches;
UMat uquery(srcSize, type), utrain(srcSize, type);
declare.in(uquery, utrain, WARMUP_RNG);
BFMatcher matcher(NORM_L2);
OCL_TEST_CYCLE()
matcher.match(uquery, utrain, matches);
SANITY_CHECK_MATCHES(matches, 1e-3);
}
OCL_PERF_TEST_P(BruteForceMatcherFixture, KnnMatch, ::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3), OCL_PERF_ENUM((MatType)CV_32FC1) ) )
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
checkDeviceMaxMemoryAllocSize(srcSize, type);
vector< vector<DMatch> > matches;
UMat uquery(srcSize, type), utrain(srcSize, type);
declare.in(uquery, utrain, WARMUP_RNG);
BFMatcher matcher(NORM_L2);
OCL_TEST_CYCLE()
matcher.knnMatch(uquery, utrain, matches, 2);
vector<DMatch> & matches0 = matches[0], & matches1 = matches[1];
SANITY_CHECK_MATCHES(matches0, 1e-3);
SANITY_CHECK_MATCHES(matches1, 1e-3);
}
OCL_PERF_TEST_P(BruteForceMatcherFixture, RadiusMatch, ::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3), OCL_PERF_ENUM((MatType)CV_32FC1) ) )
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
checkDeviceMaxMemoryAllocSize(srcSize, type);
vector< vector<DMatch> > matches;
UMat uquery(srcSize, type), utrain(srcSize, type);
declare.in(uquery, utrain, WARMUP_RNG);
BFMatcher matcher(NORM_L2);
OCL_TEST_CYCLE()
matcher.radiusMatch(uquery, utrain, matches, 2.0f);
vector<DMatch> & matches0 = matches[0], & matches1 = matches[1];
SANITY_CHECK_MATCHES(matches0, 1e-3);
SANITY_CHECK_MATCHES(matches1, 1e-3);
}
OCL_PERF_TEST_P(BruteForceMatcherFixture, MatchCrossCheck, ::testing::Combine(OCL_PERF_ENUM(OCL_SIZE_1, OCL_SIZE_2, OCL_SIZE_3), OCL_PERF_ENUM((MatType)CV_32FC1) ) )
{
const Size_MatType_t params = GetParam();
const Size srcSize = get<0>(params);
const int type = get<1>(params);
checkDeviceMaxMemoryAllocSize(srcSize, type);
vector<DMatch> matches;
UMat uquery(srcSize, type), utrain(srcSize, type);
declare.in(uquery, utrain, WARMUP_RNG);
BFMatcher matcher(NORM_L2, true /*crossCheck*/);
OCL_TEST_CYCLE()
matcher.match(uquery, utrain, matches);
SANITY_CHECK_MATCHES(matches, 1e-3);
}
} // ocl
} // cvtest
#endif // HAVE_OPENCL
modules/features/perf/opencl/perf_feature2d.cpp
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#include "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#include "../perf_feature2d.hpp"
#ifdef HAVE_OPENCL
namespace opencv_test {
namespace ocl {
OCL_PERF_TEST_P(feature2d, detect, testing::Combine(Feature2DType::all(), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat mimg = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(mimg.empty());
ASSERT_TRUE(detector);
UMat img, mask;
mimg.copyTo(img);
declare.in(img);
vector<KeyPoint> points;
OCL_TEST_CYCLE() detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
SANITY_CHECK_NOTHING();
}
OCL_PERF_TEST_P(feature2d, extract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = ORB::create();
Ptr<Feature2D> extractor = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat mimg = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(mimg.empty());
ASSERT_TRUE(extractor);
UMat img, mask;
mimg.copyTo(img);
declare.in(img);
vector<KeyPoint> points;
detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
UMat descriptors;
OCL_TEST_CYCLE() extractor->compute(img, points, descriptors);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
OCL_PERF_TEST_P(feature2d, detectAndExtract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat mimg = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(mimg.empty());
ASSERT_TRUE(detector);
UMat img, mask;
mimg.copyTo(img);
declare.in(img);
vector<KeyPoint> points;
UMat descriptors;
OCL_TEST_CYCLE() detector->detectAndCompute(img, mask, points, descriptors, false);
EXPECT_GT(points.size(), 20u);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
} // ocl
} // cvtest
#endif // HAVE_OPENCL
modules/features/perf/opencl/perf_gftt.cpp
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///////////////////////////////////////////////////////////////////////////////////////
//
// 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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Institute Of Software Chinese Academy Of Science, all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, 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 "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#include <sstream>
#ifdef HAVE_OPENCL
namespace opencv_test {
namespace ocl {
//////////////////////////// GoodFeaturesToTrack //////////////////////////
typedef tuple<String, double, bool> GoodFeaturesToTrackParams;
typedef TestBaseWithParam<GoodFeaturesToTrackParams> GoodFeaturesToTrackFixture;
OCL_PERF_TEST_P(GoodFeaturesToTrackFixture, GoodFeaturesToTrack,
::testing::Combine(OCL_PERF_ENUM(String("gpu/opticalflow/rubberwhale1.png")),
OCL_PERF_ENUM(0.0, 3.0), Bool()))
{
GoodFeaturesToTrackParams params = GetParam();
const String fileName = get<0>(params);
const double minDistance = get<1>(params), qualityLevel = 0.01;
const bool harrisDetector = get<2>(params);
const int maxCorners = 1000;
Mat img = imread(getDataPath(fileName), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty()) << "could not load " << fileName;
checkDeviceMaxMemoryAllocSize(img.size(), img.type());
UMat src(img.size(), img.type()), dst(1, maxCorners, CV_32FC2);
img.copyTo(src);
declare.in(src, WARMUP_READ).out(dst);
OCL_TEST_CYCLE() cv::goodFeaturesToTrack(src, dst, maxCorners, qualityLevel,
minDistance, noArray(), 3, 3, harrisDetector, 0.04);
SANITY_CHECK(dst);
}
OCL_PERF_TEST_P(GoodFeaturesToTrackFixture, GoodFeaturesToTrackWithQuality,
::testing::Combine(OCL_PERF_ENUM(String("gpu/opticalflow/rubberwhale1.png")),
OCL_PERF_ENUM(3.0), Bool()))
{
GoodFeaturesToTrackParams params = GetParam();
const String fileName = get<0>(params);
const double minDistance = get<1>(params), qualityLevel = 0.01;
const bool harrisDetector = get<2>(params);
const int maxCorners = 1000;
Mat img = imread(getDataPath(fileName), cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty()) << "could not load " << fileName;
checkDeviceMaxMemoryAllocSize(img.size(), img.type());
UMat src(img.size(), img.type()), dst(1, maxCorners, CV_32FC2);
img.copyTo(src);
std::vector<float> cornersQuality;
declare.in(src, WARMUP_READ).out(dst);
OCL_TEST_CYCLE() cv::goodFeaturesToTrack(src, dst, maxCorners, qualityLevel, minDistance,
noArray(), cornersQuality, 3, 3, harrisDetector, 0.04);
SANITY_CHECK(dst);
SANITY_CHECK(cornersQuality, 1e-6);
}
} } // namespace opencv_test::ocl
#endif
modules/features/perf/perf_batchDistance.cpp
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#include "perf_precomp.hpp"
namespace opencv_test
{
using namespace perf;
CV_ENUM(NormType, NORM_L1, NORM_L2, NORM_L2SQR, NORM_HAMMING, NORM_HAMMING2)
typedef tuple<NormType, MatType, bool> Norm_Destination_CrossCheck_t;
typedef perf::TestBaseWithParam<Norm_Destination_CrossCheck_t> Norm_Destination_CrossCheck;
typedef tuple<NormType, bool> Norm_CrossCheck_t;
typedef perf::TestBaseWithParam<Norm_CrossCheck_t> Norm_CrossCheck;
typedef tuple<MatType, bool> Source_CrossCheck_t;
typedef perf::TestBaseWithParam<Source_CrossCheck_t> Source_CrossCheck;
void generateData( Mat& query, Mat& train, const int sourceType );
PERF_TEST_P(Norm_Destination_CrossCheck, batchDistance_8U,
testing::Combine(testing::Values((int)NORM_L1, (int)NORM_L2SQR),
testing::Values(CV_32S, CV_32F),
testing::Bool()
)
)
{
NormType normType = get<0>(GetParam());
int destinationType = get<1>(GetParam());
bool isCrossCheck = get<2>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
generateData(queryDescriptors, trainDescriptors, CV_8U);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, destinationType, (isCrossCheck) ? ndix : noArray(),
normType, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist);
if (isCrossCheck) SANITY_CHECK(ndix);
}
PERF_TEST_P(Norm_CrossCheck, batchDistance_Dest_32S,
testing::Combine(testing::Values((int)NORM_HAMMING, (int)NORM_HAMMING2),
testing::Bool()
)
)
{
NormType normType = get<0>(GetParam());
bool isCrossCheck = get<1>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
generateData(queryDescriptors, trainDescriptors, CV_8U);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, CV_32S, (isCrossCheck) ? ndix : noArray(),
normType, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist);
if (isCrossCheck) SANITY_CHECK(ndix);
}
PERF_TEST_P(Source_CrossCheck, batchDistance_L2,
testing::Combine(testing::Values(CV_8U, CV_32F),
testing::Bool()
)
)
{
int sourceType = get<0>(GetParam());
bool isCrossCheck = get<1>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
generateData(queryDescriptors, trainDescriptors, sourceType);
declare.time(50);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, CV_32F, (isCrossCheck) ? ndix : noArray(),
NORM_L2, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist);
if (isCrossCheck) SANITY_CHECK(ndix);
}
PERF_TEST_P(Norm_CrossCheck, batchDistance_32F,
testing::Combine(testing::Values((int)NORM_L1, (int)NORM_L2SQR),
testing::Bool()
)
)
{
NormType normType = get<0>(GetParam());
bool isCrossCheck = get<1>(GetParam());
int knn = isCrossCheck ? 1 : 0;
Mat queryDescriptors;
Mat trainDescriptors;
Mat dist;
Mat ndix;
generateData(queryDescriptors, trainDescriptors, CV_32F);
declare.time(100);
TEST_CYCLE()
{
batchDistance(queryDescriptors, trainDescriptors, dist, CV_32F, (isCrossCheck) ? ndix : noArray(),
normType, knn, Mat(), 0, isCrossCheck);
}
SANITY_CHECK(dist, 1e-4);
if (isCrossCheck) SANITY_CHECK(ndix);
}
void generateData( Mat& query, Mat& train, const int sourceType )
{
const int dim = 500;
const int queryDescCount = 300; // must be even number because we split train data in some cases in two
const int countFactor = 4; // do not change it
RNG& rng = theRNG();
// Generate query descriptors randomly.
// Descriptor vector elements are integer values.
Mat buf( queryDescCount, dim, CV_32SC1 );
rng.fill( buf, RNG::UNIFORM, Scalar::all(0), Scalar(3) );
buf.convertTo( query, sourceType );
// Generate train descriptors as follows:
// copy each query descriptor to train set countFactor times
// and perturb some one element of the copied descriptors in
// in ascending order. General boundaries of the perturbation
// are (0.f, 1.f).
train.create( query.rows*countFactor, query.cols, sourceType );
float step = (sourceType == CV_8U ? 256.f : 1.f) / countFactor;
for( int qIdx = 0; qIdx < query.rows; qIdx++ )
{
Mat queryDescriptor = query.row(qIdx);
for( int c = 0; c < countFactor; c++ )
{
int tIdx = qIdx * countFactor + c;
Mat trainDescriptor = train.row(tIdx);
queryDescriptor.copyTo( trainDescriptor );
int elem = rng(dim);
float diff = rng.uniform( step*c, step*(c+1) );
trainDescriptor.col(elem) += diff;
}
}
}
} // namespace
modules/features/perf/perf_fast.cpp
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#include "perf_precomp.hpp"
#include "perf_feature2d.hpp"
namespace opencv_test
{
using namespace perf;
typedef tuple<int, int, bool, string> Fast_Params_t;
typedef perf::TestBaseWithParam<Fast_Params_t> Fast_Params;
PERF_TEST_P(Fast_Params, detect,
testing::Combine(
testing::Values(20,30,100), // threshold
testing::Values(
// (int)FastFeatureDetector::TYPE_5_8,
// (int)FastFeatureDetector::TYPE_7_12,
(int)FastFeatureDetector::TYPE_9_16 // detector_type
),
testing::Bool(), // nonmaxSuppression
testing::Values("cv/inpaint/orig.png",
"cv/cameracalibration/chess9.png")
))
{
int threshold_p = get<0>(GetParam());
int type_p = get<1>(GetParam());
bool nonmaxSuppression_p = get<2>(GetParam());
string filename = getDataPath(get<3>(GetParam()));
Mat img = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty()) << "Failed to load image: " << filename;
vector<KeyPoint> keypoints;
declare.in(img);
TEST_CYCLE()
{
FAST(img, keypoints, threshold_p, nonmaxSuppression_p, (FastFeatureDetector::DetectorType)type_p);
}
SANITY_CHECK_NOTHING();
}
} // namespace opencv_test
modules/features/perf/perf_feature2d.cpp
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#include "perf_feature2d.hpp"
namespace opencv_test
{
using namespace perf;
PERF_TEST_P(feature2d, detect, testing::Combine(Feature2DType::all(), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat img = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
ASSERT_TRUE(detector);
declare.in(img);
Mat mask;
vector<KeyPoint> points;
TEST_CYCLE() detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
SANITY_CHECK_NOTHING();
}
PERF_TEST_P(feature2d, extract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = ORB::create();
Ptr<Feature2D> extractor = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat img = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
ASSERT_TRUE(extractor);
declare.in(img);
Mat mask;
vector<KeyPoint> points;
detector->detect(img, points, mask);
EXPECT_GT(points.size(), 20u);
Mat descriptors;
TEST_CYCLE() extractor->compute(img, points, descriptors);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
PERF_TEST_P(feature2d, detectAndExtract, testing::Combine(testing::Values(DETECTORS_EXTRACTORS), TEST_IMAGES))
{
Ptr<Feature2D> detector = getFeature2D(get<0>(GetParam()));
std::string filename = getDataPath(get<1>(GetParam()));
Mat img = imread(filename, IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
ASSERT_TRUE(detector);
declare.in(img);
Mat mask;
vector<KeyPoint> points;
Mat descriptors;
TEST_CYCLE() detector->detectAndCompute(img, mask, points, descriptors, false);
EXPECT_GT(points.size(), 20u);
EXPECT_EQ((size_t)descriptors.rows, points.size());
SANITY_CHECK_NOTHING();
}
} // namespace
modules/features/perf/perf_feature2d.hpp
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#ifndef __OPENCV_PERF_FEATURES_HPP__
#define __OPENCV_PERF_FEATURES_HPP__
#include "perf_precomp.hpp"
namespace opencv_test
{
/* configuration for tests of detectors/descriptors. shared between ocl and cpu tests. */
// detectors/descriptors configurations to test
#define DETECTORS_ONLY \
FAST_DEFAULT, FAST_20_TRUE_TYPE5_8, FAST_20_TRUE_TYPE7_12, FAST_20_TRUE_TYPE9_16, \
FAST_20_FALSE_TYPE5_8, FAST_20_FALSE_TYPE7_12, FAST_20_FALSE_TYPE9_16, \
\
MSER_DEFAULT
#define DETECTORS_EXTRACTORS \
ORB_DEFAULT, ORB_1500_13_1, \
SIFT_DEFAULT
#define CV_ENUM_EXPAND(name, ...) CV_ENUM(name, __VA_ARGS__)
enum Feature2DVals { DETECTORS_ONLY, DETECTORS_EXTRACTORS };
CV_ENUM_EXPAND(Feature2DType, DETECTORS_ONLY, DETECTORS_EXTRACTORS)
typedef tuple<Feature2DType, string> Feature2DType_String_t;
typedef perf::TestBaseWithParam<Feature2DType_String_t> feature2d;
#define TEST_IMAGES testing::Values(\
"cv/detectors_descriptors_evaluation/images_datasets/leuven/img1.png",\
"stitching/a3.png", \
"stitching/s2.jpg")
static inline Ptr<Feature2D> getFeature2D(Feature2DType type)
{
switch(type) {
case ORB_DEFAULT:
return ORB::create();
case ORB_1500_13_1:
return ORB::create(1500, 1.3f, 1);
case FAST_DEFAULT:
return FastFeatureDetector::create();
case FAST_20_TRUE_TYPE5_8:
return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_5_8);
case FAST_20_TRUE_TYPE7_12:
return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_7_12);
case FAST_20_TRUE_TYPE9_16:
return FastFeatureDetector::create(20, true, FastFeatureDetector::TYPE_9_16);
case FAST_20_FALSE_TYPE5_8:
return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_5_8);
case FAST_20_FALSE_TYPE7_12:
return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_7_12);
case FAST_20_FALSE_TYPE9_16:
return FastFeatureDetector::create(20, false, FastFeatureDetector::TYPE_9_16);
case MSER_DEFAULT:
return MSER::create();
case SIFT_DEFAULT:
return SIFT::create();
default:
return Ptr<Feature2D>();
}
}
} // namespace
#endif // __OPENCV_PERF_FEATURES_HPP__
modules/features/perf/perf_goodFeaturesToTrack.cpp
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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#include "perf_precomp.hpp"
namespace opencv_test {
typedef tuple<string, int, double, int, int, bool> Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris_t;
typedef perf::TestBaseWithParam<Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris_t> Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris;
PERF_TEST_P(Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris, goodFeaturesToTrack,
testing::Combine(
testing::Values( "stitching/a1.png", "cv/shared/pic5.png"),
testing::Values( 100, 500 ),
testing::Values( 0.1, 0.01 ),
testing::Values( 3, 5 ),
testing::Values( 3, 5 ),
testing::Bool()
)
)
{
string filename = getDataPath(get<0>(GetParam()));
int maxCorners = get<1>(GetParam());
double qualityLevel = get<2>(GetParam());
int blockSize = get<3>(GetParam());
int gradientSize = get<4>(GetParam());
bool useHarrisDetector = get<5>(GetParam());
Mat image = imread(filename, IMREAD_GRAYSCALE);
if (image.empty())
FAIL() << "Unable to load source image" << filename;
std::vector<Point2f> corners;
double minDistance = 1;
TEST_CYCLE() goodFeaturesToTrack(image, corners, maxCorners, qualityLevel, minDistance, noArray(), blockSize, gradientSize, useHarrisDetector);
if (corners.size() > 50)
corners.erase(corners.begin() + 50, corners.end());
SANITY_CHECK(corners);
}
PERF_TEST_P(Image_MaxCorners_QualityLevel_MinDistance_BlockSize_gradientSize_UseHarris, goodFeaturesToTrackWithQuality,
testing::Combine(
testing::Values( "stitching/a1.png", "cv/shared/pic5.png"),
testing::Values( 50 ),
testing::Values( 0.01 ),
testing::Values( 3 ),
testing::Values( 3 ),
testing::Bool()
)
)
{
string filename = getDataPath(get<0>(GetParam()));
int maxCorners = get<1>(GetParam());
double qualityLevel = get<2>(GetParam());
int blockSize = get<3>(GetParam());
int gradientSize = get<4>(GetParam());
bool useHarrisDetector = get<5>(GetParam());
double minDistance = 1;
Mat image = imread(filename, IMREAD_GRAYSCALE);
if (image.empty())
FAIL() << "Unable to load source image" << filename;
std::vector<Point2f> corners;
std::vector<float> cornersQuality;
TEST_CYCLE() goodFeaturesToTrack(image, corners, maxCorners, qualityLevel, minDistance, noArray(),
cornersQuality, blockSize, gradientSize, useHarrisDetector);
SANITY_CHECK(corners);
SANITY_CHECK(cornersQuality, 1e-6);
}
} // namespace
modules/features/perf/perf_main.cpp
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#include "perf_precomp.hpp"
#if defined(HAVE_HPX)
#include <hpx/hpx_main.hpp>
#endif
CV_PERF_TEST_MAIN(features2d)
modules/features/perf/perf_precomp.hpp
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#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/features.hpp"
#endif