Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
218 lines
12 KiB
218 lines
12 KiB
/*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 "precomp.hpp" |
|
#include "fast_score.hpp" |
|
|
|
using namespace cv; |
|
|
|
Ptr<Feature2D> Feature2D::create( const string& feature2DType ) |
|
{ |
|
return Algorithm::create<Feature2D>("Feature2D." + feature2DType); |
|
} |
|
|
|
/////////////////////// AlgorithmInfo for various detector & descriptors //////////////////////////// |
|
|
|
/* NOTE!!! |
|
All the AlgorithmInfo-related stuff should be in the same file as initModule_features2d(). |
|
Otherwise, linker may throw away some seemingly unused stuff. |
|
*/ |
|
|
|
CV_INIT_ALGORITHM(BRISK, "Feature2D.BRISK", |
|
obj.info()->addParam(obj, "thres", obj.threshold); |
|
obj.info()->addParam(obj, "octaves", obj.octaves)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF", |
|
obj.info()->addParam(obj, "bytes", obj.bytes_)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(FastFeatureDetector, "Feature2D.FAST", |
|
obj.info()->addParam(obj, "threshold", obj.threshold); |
|
obj.info()->addParam(obj, "nonmaxSuppression", obj.nonmaxSuppression)) |
|
|
|
CV_INIT_ALGORITHM(FastFeatureDetector2, "Feature2D.FASTX", |
|
obj.info()->addParam(obj, "threshold", obj.threshold); |
|
obj.info()->addParam(obj, "nonmaxSuppression", obj.nonmaxSuppression); |
|
obj.info()->addParam(obj, "type", obj.type)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(StarDetector, "Feature2D.STAR", |
|
obj.info()->addParam(obj, "maxSize", obj.maxSize); |
|
obj.info()->addParam(obj, "responseThreshold", obj.responseThreshold); |
|
obj.info()->addParam(obj, "lineThresholdProjected", obj.lineThresholdProjected); |
|
obj.info()->addParam(obj, "lineThresholdBinarized", obj.lineThresholdBinarized); |
|
obj.info()->addParam(obj, "suppressNonmaxSize", obj.suppressNonmaxSize)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(MSER, "Feature2D.MSER", |
|
obj.info()->addParam(obj, "delta", obj.delta); |
|
obj.info()->addParam(obj, "minArea", obj.minArea); |
|
obj.info()->addParam(obj, "maxArea", obj.maxArea); |
|
obj.info()->addParam(obj, "maxVariation", obj.maxVariation); |
|
obj.info()->addParam(obj, "minDiversity", obj.minDiversity); |
|
obj.info()->addParam(obj, "maxEvolution", obj.maxEvolution); |
|
obj.info()->addParam(obj, "areaThreshold", obj.areaThreshold); |
|
obj.info()->addParam(obj, "minMargin", obj.minMargin); |
|
obj.info()->addParam(obj, "edgeBlurSize", obj.edgeBlurSize)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(ORB, "Feature2D.ORB", |
|
obj.info()->addParam(obj, "nFeatures", obj.nfeatures); |
|
obj.info()->addParam(obj, "scaleFactor", obj.scaleFactor); |
|
obj.info()->addParam(obj, "nLevels", obj.nlevels); |
|
obj.info()->addParam(obj, "firstLevel", obj.firstLevel); |
|
obj.info()->addParam(obj, "edgeThreshold", obj.edgeThreshold); |
|
obj.info()->addParam(obj, "patchSize", obj.patchSize); |
|
obj.info()->addParam(obj, "WTA_K", obj.WTA_K); |
|
obj.info()->addParam(obj, "scoreType", obj.scoreType)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(FREAK, "Feature2D.FREAK", |
|
obj.info()->addParam(obj, "orientationNormalized", obj.orientationNormalized); |
|
obj.info()->addParam(obj, "scaleNormalized", obj.scaleNormalized); |
|
obj.info()->addParam(obj, "patternScale", obj.patternScale); |
|
obj.info()->addParam(obj, "nbOctave", obj.nOctaves)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(GFTTDetector, "Feature2D.GFTT", |
|
obj.info()->addParam(obj, "nfeatures", obj.nfeatures); |
|
obj.info()->addParam(obj, "qualityLevel", obj.qualityLevel); |
|
obj.info()->addParam(obj, "minDistance", obj.minDistance); |
|
obj.info()->addParam(obj, "useHarrisDetector", obj.useHarrisDetector); |
|
obj.info()->addParam(obj, "k", obj.k)) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(SimpleBlobDetector, "Feature2D.SimpleBlob", |
|
obj.info()->addParam(obj, "thresholdStep", obj.params.thresholdStep); |
|
obj.info()->addParam(obj, "minThreshold", obj.params.minThreshold); |
|
obj.info()->addParam(obj, "maxThreshold", obj.params.maxThreshold); |
|
obj.info()->addParam_(obj, "minRepeatability", (sizeof(size_t) == sizeof(uint64))?Param::UINT64 : Param::UNSIGNED_INT, &obj.params.minRepeatability, false, 0, 0); |
|
obj.info()->addParam(obj, "minDistBetweenBlobs", obj.params.minDistBetweenBlobs); |
|
obj.info()->addParam(obj, "filterByColor", obj.params.filterByColor); |
|
obj.info()->addParam(obj, "blobColor", obj.params.blobColor); |
|
obj.info()->addParam(obj, "filterByArea", obj.params.filterByArea); |
|
obj.info()->addParam(obj, "maxArea", obj.params.maxArea); |
|
obj.info()->addParam(obj, "filterByCircularity", obj.params.filterByCircularity); |
|
obj.info()->addParam(obj, "maxCircularity", obj.params.maxCircularity); |
|
obj.info()->addParam(obj, "filterByInertia", obj.params.filterByInertia); |
|
obj.info()->addParam(obj, "maxInertiaRatio", obj.params.maxInertiaRatio); |
|
obj.info()->addParam(obj, "filterByConvexity", obj.params.filterByConvexity); |
|
obj.info()->addParam(obj, "maxConvexity", obj.params.maxConvexity); |
|
) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
class CV_EXPORTS HarrisDetector : public GFTTDetector |
|
{ |
|
public: |
|
HarrisDetector( int maxCorners=1000, double qualityLevel=0.01, double minDistance=1, |
|
int blockSize=3, bool useHarrisDetector=true, double k=0.04 ); |
|
AlgorithmInfo* info() const; |
|
}; |
|
|
|
inline HarrisDetector::HarrisDetector( int _maxCorners, double _qualityLevel, double _minDistance, |
|
int _blockSize, bool _useHarrisDetector, double _k ) |
|
: GFTTDetector( _maxCorners, _qualityLevel, _minDistance, _blockSize, _useHarrisDetector, _k ) {} |
|
|
|
CV_INIT_ALGORITHM(HarrisDetector, "Feature2D.HARRIS", |
|
obj.info()->addParam(obj, "nfeatures", obj.nfeatures); |
|
obj.info()->addParam(obj, "qualityLevel", obj.qualityLevel); |
|
obj.info()->addParam(obj, "minDistance", obj.minDistance); |
|
obj.info()->addParam(obj, "useHarrisDetector", obj.useHarrisDetector); |
|
obj.info()->addParam(obj, "k", obj.k)) |
|
|
|
//////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(DenseFeatureDetector, "Feature2D.Dense", |
|
obj.info()->addParam(obj, "initFeatureScale", obj.initFeatureScale); |
|
obj.info()->addParam(obj, "featureScaleLevels", obj.featureScaleLevels); |
|
obj.info()->addParam(obj, "featureScaleMul", obj.featureScaleMul); |
|
obj.info()->addParam(obj, "initXyStep", obj.initXyStep); |
|
obj.info()->addParam(obj, "initImgBound", obj.initImgBound); |
|
obj.info()->addParam(obj, "varyXyStepWithScale", obj.varyXyStepWithScale); |
|
obj.info()->addParam(obj, "varyImgBoundWithScale", obj.varyImgBoundWithScale)) |
|
|
|
CV_INIT_ALGORITHM(GridAdaptedFeatureDetector, "Feature2D.Grid", |
|
obj.info()->addParam<FeatureDetector>(obj, "detector", obj.detector, false, 0, 0); // Extra params added to avoid VS2013 fatal error in opencv2/core.hpp (decl. of addParam) |
|
obj.info()->addParam(obj, "maxTotalKeypoints", obj.maxTotalKeypoints); |
|
obj.info()->addParam(obj, "gridRows", obj.gridRows); |
|
obj.info()->addParam(obj, "gridCols", obj.gridCols)) |
|
|
|
//////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
CV_INIT_ALGORITHM(BFMatcher, "DescriptorMatcher.BFMatcher", |
|
obj.info()->addParam(obj, "normType", obj.normType); |
|
obj.info()->addParam(obj, "crossCheck", obj.crossCheck)) |
|
|
|
CV_INIT_ALGORITHM(FlannBasedMatcher, "DescriptorMatcher.FlannBasedMatcher",) |
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////////////// |
|
|
|
bool cv::initModule_features2d(void) |
|
{ |
|
bool all = true; |
|
all &= !BriefDescriptorExtractor_info_auto.name().empty(); |
|
all &= !BRISK_info_auto.name().empty(); |
|
all &= !FastFeatureDetector_info_auto.name().empty(); |
|
all &= !FastFeatureDetector2_info_auto.name().empty(); |
|
all &= !StarDetector_info_auto.name().empty(); |
|
all &= !MSER_info_auto.name().empty(); |
|
all &= !FREAK_info_auto.name().empty(); |
|
all &= !ORB_info_auto.name().empty(); |
|
all &= !GFTTDetector_info_auto.name().empty(); |
|
all &= !HarrisDetector_info_auto.name().empty(); |
|
all &= !DenseFeatureDetector_info_auto.name().empty(); |
|
all &= !GridAdaptedFeatureDetector_info_auto.name().empty(); |
|
all &= !BFMatcher_info_auto.name().empty(); |
|
all &= !FlannBasedMatcher_info_auto.name().empty(); |
|
|
|
return all; |
|
}
|
|
|