mirror of
https://github.com/opencv/opencv.git
synced 2024-12-04 08:49:14 +08:00
181 lines
9.3 KiB
C++
181 lines
9.3 KiB
C++
/*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));
|
|
|
|
///////////////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
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));
|
|
|
|
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();
|
|
|
|
return all;
|
|
}
|