"atomic bomb" commit. Reorganized OpenCV directory structure
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Vadim Pisarevsky
178
modules/features2d/src/detectors.cpp
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178
modules/features2d/src/detectors.cpp
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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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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 "precomp.hpp"
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using namespace std;
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using namespace cv;
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/*
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FeatureDetector
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*/
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struct MaskPredicate
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{
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MaskPredicate( const Mat& _mask ) : mask(_mask)
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{}
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MaskPredicate& operator=(const MaskPredicate&) {}
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bool operator() (const KeyPoint& key_pt) const
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{
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return mask.at<uchar>( (int)(key_pt.pt.y + 0.5f), (int)(key_pt.pt.x + 0.5f) ) != 0;
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}
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const Mat& mask;
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};
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void FeatureDetector::removeInvalidPoints( const Mat& mask, vector<KeyPoint>& keypoints )
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{
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if( mask.empty() )
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return;
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keypoints.erase(remove_if(keypoints.begin(), keypoints.end(), MaskPredicate(mask)), keypoints.end());
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};
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/*
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FastFeatureDetector
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*/
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FastFeatureDetector::FastFeatureDetector( int _threshold, bool _nonmaxSuppression )
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: threshold(_threshold), nonmaxSuppression(_nonmaxSuppression)
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{}
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void FastFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints) const
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{
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FAST( image, keypoints, threshold, nonmaxSuppression );
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removeInvalidPoints( mask, keypoints );
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}
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/*
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GoodFeaturesToTrackDetector
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*/
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GoodFeaturesToTrackDetector::GoodFeaturesToTrackDetector( int _maxCorners, double _qualityLevel, \
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double _minDistance, int _blockSize,
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bool _useHarrisDetector, double _k )
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: maxCorners(_maxCorners), qualityLevel(_qualityLevel), minDistance(_minDistance),
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blockSize(_blockSize), useHarrisDetector(_useHarrisDetector), k(_k)
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{}
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void GoodFeaturesToTrackDetector::detectImpl( const Mat& image, const Mat& mask,
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vector<KeyPoint>& keypoints ) const
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{
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vector<Point2f> corners;
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goodFeaturesToTrack( image, corners, maxCorners, qualityLevel, minDistance, mask,
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blockSize, useHarrisDetector, k );
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keypoints.resize(corners.size());
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vector<Point2f>::const_iterator corner_it = corners.begin();
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vector<KeyPoint>::iterator keypoint_it = keypoints.begin();
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for( ; corner_it != corners.end(); ++corner_it, ++keypoint_it )
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{
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*keypoint_it = KeyPoint( *corner_it, 1.f );
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}
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}
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/*
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MserFeatureDetector
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*/
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MserFeatureDetector::MserFeatureDetector( int delta, int minArea, int maxArea,
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float maxVariation, float minDiversity,
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int maxEvolution, double areaThreshold,
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double minMargin, int edgeBlurSize )
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: mser( delta, minArea, maxArea, maxVariation, minDiversity,
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maxEvolution, areaThreshold, minMargin, edgeBlurSize )
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{}
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void MserFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints ) const
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{
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vector<vector<Point> > msers;
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mser(image, msers, mask);
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keypoints.resize( msers.size() );
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vector<vector<Point> >::const_iterator contour_it = msers.begin();
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vector<KeyPoint>::iterator keypoint_it = keypoints.begin();
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for( ; contour_it != msers.end(); ++contour_it, ++keypoint_it )
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{
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RotatedRect rect = fitEllipse(Mat(*contour_it));
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*keypoint_it = KeyPoint( rect.center, min(rect.size.height, rect.size.width), rect.angle);
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}
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}
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/*
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StarFeatureDetector
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*/
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StarFeatureDetector::StarFeatureDetector(int maxSize, int responseThreshold,
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int lineThresholdProjected,
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int lineThresholdBinarized,
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int suppressNonmaxSize)
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: star( maxSize, responseThreshold, lineThresholdProjected,
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lineThresholdBinarized, suppressNonmaxSize)
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{}
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void StarFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector<KeyPoint>& keypoints) const
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{
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star(image, keypoints);
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removeInvalidPoints(mask, keypoints);
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}
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/*
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SiftFeatureDetector
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*/
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SiftFeatureDetector::SiftFeatureDetector(double threshold, double edgeThreshold, int angleMode,
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int nOctaves, int nOctaveLayers, int firstOctave) :
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sift(threshold, edgeThreshold, angleMode, nOctaves, nOctaveLayers, firstOctave)
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{
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}
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void SiftFeatureDetector::detectImpl( const Mat& image, const Mat& mask,
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vector<KeyPoint>& keypoints) const
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{
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sift(image, mask, keypoints);
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}
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/*
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SurfFeatureDetector
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*/
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SurfFeatureDetector::SurfFeatureDetector( double hessianThreshold, int octaves, int octaveLayers)
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: surf(hessianThreshold, octaves, octaveLayers)
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{}
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void SurfFeatureDetector::detectImpl( const Mat& image, const Mat& mask,
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vector<KeyPoint>& keypoints) const
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{
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surf(image, mask, keypoints);
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}
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