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initial addition of BRISK with some tests
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@ -267,6 +267,92 @@ public:
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static Ptr<Feature2D> create( const string& name );
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};
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/*!
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BRISK implementation
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*/
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class CV_EXPORTS_W BRISK : public Feature2D
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{
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public:
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CV_WRAP explicit BRISK(int thresh=30, int octaves=3, float patternScale=1.0f);
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virtual ~BRISK();
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// returns the descriptor size in bytes
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int descriptorSize() const;
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// returns the descriptor type
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int descriptorType() const;
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// Compute the BRISK features on an image
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void operator()(InputArray image, InputArray mask, vector<KeyPoint>& keypoints) const;
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// Compute the BRISK features and descriptors on an image
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void operator()( InputArray image, InputArray mask, vector<KeyPoint>& keypoints,
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OutputArray descriptors, bool useProvidedKeypoints=false ) const;
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AlgorithmInfo* info() const;
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// custom setup
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CV_WRAP explicit BRISK(std::vector<float> &radiusList, std::vector<int> &numberList,
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float dMax=5.85f, float dMin=8.2f, std::vector<int> indexChange=std::vector<int>());
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// call this to generate the kernel:
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// circle of radius r (pixels), with n points;
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// short pairings with dMax, long pairings with dMin
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CV_WRAP void generateKernel(std::vector<float> &radiusList,
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std::vector<int> &numberList, float dMax=5.85f, float dMin=8.2f,
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std::vector<int> indexChange=std::vector<int>());
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protected:
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void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
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void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
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// Feature parameters
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CV_PROP_RW int threshold;
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CV_PROP_RW int octaves;
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// some helper structures for the Brisk pattern representation
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struct BriskPatternPoint{
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float x; // x coordinate relative to center
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float y; // x coordinate relative to center
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float sigma; // Gaussian smoothing sigma
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};
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struct BriskShortPair{
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unsigned int i; // index of the first pattern point
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unsigned int j; // index of other pattern point
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};
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struct BriskLongPair{
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unsigned int i; // index of the first pattern point
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unsigned int j; // index of other pattern point
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int weighted_dx; // 1024.0/dx
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int weighted_dy; // 1024.0/dy
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};
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inline int smoothedIntensity(const cv::Mat& image,
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const cv::Mat& integral,const float key_x,
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const float key_y, const unsigned int scale,
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const unsigned int rot, const unsigned int point) const;
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// pattern properties
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BriskPatternPoint* patternPoints_; //[i][rotation][scale]
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unsigned int points_; // total number of collocation points
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float* scaleList_; // lists the scaling per scale index [scale]
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unsigned int* sizeList_; // lists the total pattern size per scale index [scale]
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static const unsigned int scales_; // scales discretization
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static const float scalerange_; // span of sizes 40->4 Octaves - else, this needs to be adjusted...
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static const unsigned int n_rot_; // discretization of the rotation look-up
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// pairs
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int strings_; // number of uchars the descriptor consists of
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float dMax_; // short pair maximum distance
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float dMin_; // long pair maximum distance
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BriskShortPair* shortPairs_; // d<_dMax
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BriskLongPair* longPairs_; // d>_dMin
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unsigned int noShortPairs_; // number of shortParis
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unsigned int noLongPairs_; // number of longParis
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// general
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static const float basicSize_;
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};
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/*!
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ORB implementation.
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2277
modules/features2d/src/brisk.cpp
Executable file
2277
modules/features2d/src/brisk.cpp
Executable file
File diff suppressed because it is too large
Load Diff
@ -51,6 +51,12 @@ using namespace cv;
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Otherwise, linker may throw away some seemingly unused stuff.
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*/
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CV_INIT_ALGORITHM(BRISK, "Feature2D.BRISK",
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obj.info()->addParam(obj, "thres", obj.threshold);
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obj.info()->addParam(obj, "octaves", obj.octaves));
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///////////////////////////////////////////////////////////////////////////////////////////////////////////
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CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF",
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obj.info()->addParam(obj, "bytes", obj.bytes_));
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@ -154,6 +160,7 @@ bool cv::initModule_features2d(void)
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{
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bool all = true;
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all &= !BriefDescriptorExtractor_info_auto.name().empty();
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all &= !BRISK_info_auto.name().empty();
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all &= !FastFeatureDetector_info_auto.name().empty();
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all &= !StarDetector_info_auto.name().empty();
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all &= !MSER_info_auto.name().empty();
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95
modules/features2d/test/test_brisk.cpp
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95
modules/features2d/test/test_brisk.cpp
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@ -0,0 +1,95 @@
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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using namespace cv;
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class CV_BRISKTest : public cvtest::BaseTest
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{
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public:
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CV_BRISKTest();
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~CV_BRISKTest();
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protected:
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void run(int);
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};
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CV_BRISKTest::CV_BRISKTest() {}
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CV_BRISKTest::~CV_BRISKTest() {}
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void CV_BRISKTest::run( int )
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{
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Mat image1 = imread(string(ts->get_data_path()) + "inpaint/orig.jpg");
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Mat image2 = imread(string(ts->get_data_path()) + "cameracalibration/chess9.jpg");
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if (image1.empty() || image2.empty())
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
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return;
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}
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Mat gray1, gray2;
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cvtColor(image1, gray1, CV_BGR2GRAY);
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cvtColor(image2, gray2, CV_BGR2GRAY);
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Ptr<FeatureDetector> detector = Algorithm::create<FeatureDetector>("Feature2D.BRISK");
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vector<KeyPoint> keypoints1;
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vector<KeyPoint> keypoints2;
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detector->detect(image1, keypoints1);
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detector->detect(image2, keypoints2);
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for(size_t i = 0; i < keypoints1.size(); ++i)
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{
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const KeyPoint& kp = keypoints1[i];
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ASSERT_NE(kp.angle, -1);
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}
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for(size_t i = 0; i < keypoints2.size(); ++i)
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{
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const KeyPoint& kp = keypoints2[i];
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ASSERT_NE(kp.angle, -1);
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}
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}
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TEST(Features2d_BRISK, regression) { CV_BRISKTest test; test.safe_run(); }
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@ -301,6 +301,13 @@ private:
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* Tests registrations *
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\****************************************************************************************/
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TEST( Features2d_DescriptorExtractor_BRISK, regression )
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{
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CV_DescriptorExtractorTest<Hamming> test( "descriptor-brisk", (CV_DescriptorExtractorTest<Hamming>::DistanceType)2.f,
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DescriptorExtractor::create("BRISK") );
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test.safe_run();
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}
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TEST( Features2d_DescriptorExtractor_ORB, regression )
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{
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// TODO adjust the parameters below
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* Tests registrations *
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\****************************************************************************************/
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TEST( Features2d_Detector_BRISK, regression )
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{
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CV_FeatureDetectorTest test( "detector-brisk", FeatureDetector::create("BRISK") );
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test.safe_run();
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}
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TEST( Features2d_Detector_FAST, regression )
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{
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CV_FeatureDetectorTest test( "detector-fast", FeatureDetector::create("FAST") );
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