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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) 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"
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);
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(obj, "detector", obj.detector);
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 &= !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;
}