opencv/modules/java/generator/src/cpp/features2d_manual.hpp

474 lines
17 KiB
C++
Raw Normal View History

#ifndef __OPENCV_FEATURES_2D_MANUAL_HPP__
#define __OPENCV_FEATURES_2D_MANUAL_HPP__
#include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCV_FEATURES2D
#include "opencv2/features2d/features2d.hpp"
2012-09-15 19:36:37 +08:00
#undef SIMPLEBLOB // to solve conflict with wincrypt.h on windows
namespace cv
{
class CV_EXPORTS_AS(FeatureDetector) javaFeatureDetector : public FeatureDetector
{
public:
#if 0
//DO NOT REMOVE! The block is required for sources parser
CV_WRAP void detect( const Mat& image, CV_OUT vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
CV_WRAP void detect( const vector<Mat>& images, CV_OUT vector<vector<KeyPoint> >& keypoints, const vector<Mat>& masks=vector<Mat>() ) const;
2011-08-01 23:06:11 +08:00
CV_WRAP virtual bool empty() const;
#endif
enum
{
FAST = 1,
STAR = 2,
SIFT = 3,
SURF = 4,
ORB = 5,
MSER = 6,
GFTT = 7,
HARRIS = 8,
SIMPLEBLOB = 9,
DENSE = 10,
2012-10-12 03:14:06 +08:00
BRISK = 11,
GRIDDETECTOR = 1000,
GRID_FAST = GRIDDETECTOR + FAST,
GRID_STAR = GRIDDETECTOR + STAR,
GRID_SIFT = GRIDDETECTOR + SIFT,
GRID_SURF = GRIDDETECTOR + SURF,
GRID_ORB = GRIDDETECTOR + ORB,
GRID_MSER = GRIDDETECTOR + MSER,
GRID_GFTT = GRIDDETECTOR + GFTT,
GRID_HARRIS = GRIDDETECTOR + HARRIS,
GRID_SIMPLEBLOB = GRIDDETECTOR + SIMPLEBLOB,
GRID_DENSE = GRIDDETECTOR + DENSE,
GRID_BRISK = GRIDDETECTOR + BRISK,
PYRAMIDDETECTOR = 2000,
PYRAMID_FAST = PYRAMIDDETECTOR + FAST,
PYRAMID_STAR = PYRAMIDDETECTOR + STAR,
PYRAMID_SIFT = PYRAMIDDETECTOR + SIFT,
PYRAMID_SURF = PYRAMIDDETECTOR + SURF,
PYRAMID_ORB = PYRAMIDDETECTOR + ORB,
PYRAMID_MSER = PYRAMIDDETECTOR + MSER,
PYRAMID_GFTT = PYRAMIDDETECTOR + GFTT,
PYRAMID_HARRIS = PYRAMIDDETECTOR + HARRIS,
PYRAMID_SIMPLEBLOB = PYRAMIDDETECTOR + SIMPLEBLOB,
PYRAMID_DENSE = PYRAMIDDETECTOR + DENSE,
PYRAMID_BRISK = PYRAMIDDETECTOR + BRISK,
DYNAMICDETECTOR = 3000,
DYNAMIC_FAST = DYNAMICDETECTOR + FAST,
DYNAMIC_STAR = DYNAMICDETECTOR + STAR,
DYNAMIC_SIFT = DYNAMICDETECTOR + SIFT,
DYNAMIC_SURF = DYNAMICDETECTOR + SURF,
DYNAMIC_ORB = DYNAMICDETECTOR + ORB,
DYNAMIC_MSER = DYNAMICDETECTOR + MSER,
DYNAMIC_GFTT = DYNAMICDETECTOR + GFTT,
DYNAMIC_HARRIS = DYNAMICDETECTOR + HARRIS,
DYNAMIC_SIMPLEBLOB = DYNAMICDETECTOR + SIMPLEBLOB,
DYNAMIC_DENSE = DYNAMICDETECTOR + DENSE,
DYNAMIC_BRISK = DYNAMICDETECTOR + BRISK
};
//supported: FAST STAR SIFT SURF ORB MSER GFTT HARRIS BRISK Grid(XXXX) Pyramid(XXXX) Dynamic(XXXX)
//not supported: SimpleBlob, Dense
CV_WRAP static javaFeatureDetector* create( int detectorType )
{
string name;
if (detectorType > DYNAMICDETECTOR)
{
name = "Dynamic";
detectorType -= DYNAMICDETECTOR;
}
if (detectorType > PYRAMIDDETECTOR)
{
name = "Pyramid";
detectorType -= PYRAMIDDETECTOR;
}
if (detectorType > GRIDDETECTOR)
{
name = "Grid";
detectorType -= GRIDDETECTOR;
}
switch(detectorType)
{
case FAST:
name += "FAST";
break;
case STAR:
name += "STAR";
break;
case SIFT:
name += "SIFT";
break;
case SURF:
name += "SURF";
break;
case ORB:
name += "ORB";
break;
case MSER:
name += "MSER";
break;
case GFTT:
name += "GFTT";
break;
case HARRIS:
name += "HARRIS";
break;
case SIMPLEBLOB:
name += "SimpleBlob";
break;
case DENSE:
name += "Dense";
break;
case BRISK:
name += "BRISK";
break;
default:
CV_Error( CV_StsBadArg, "Specified feature detector type is not supported." );
break;
}
Ptr<FeatureDetector> detector = FeatureDetector::create(name);
detector.addref();
return (javaFeatureDetector*)((FeatureDetector*) detector);
}
CV_WRAP void write( const string& fileName ) const
{
FileStorage fs(fileName, FileStorage::WRITE);
((FeatureDetector*)this)->write(fs);
fs.release();
}
CV_WRAP void read( const string& fileName )
{
FileStorage fs(fileName, FileStorage::READ);
((FeatureDetector*)this)->read(fs.root());
fs.release();
}
};
class CV_EXPORTS_AS(DescriptorMatcher) javaDescriptorMatcher : public DescriptorMatcher
{
public:
#if 0
//DO NOT REMOVE! The block is required for sources parser
CV_WRAP virtual bool isMaskSupported() const;
CV_WRAP virtual void add( const vector<Mat>& descriptors );
CV_WRAP const vector<Mat>& getTrainDescriptors() const;
CV_WRAP virtual void clear();
CV_WRAP virtual bool empty() const;
CV_WRAP virtual void train();
CV_WRAP void match( const Mat& queryDescriptors, const Mat& trainDescriptors,
CV_OUT vector<DMatch>& matches, const Mat& mask=Mat() ) const;
CV_WRAP void knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
CV_OUT vector<vector<DMatch> >& matches, int k,
const Mat& mask=Mat(), bool compactResult=false ) const;
CV_WRAP void radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
CV_OUT vector<vector<DMatch> >& matches, float maxDistance,
const Mat& mask=Mat(), bool compactResult=false ) const;
CV_WRAP void match( const Mat& queryDescriptors, CV_OUT vector<DMatch>& matches,
const vector<Mat>& masks=vector<Mat>() );
CV_WRAP void knnMatch( const Mat& queryDescriptors, CV_OUT vector<vector<DMatch> >& matches, int k,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
CV_WRAP void radiusMatch( const Mat& queryDescriptors, CV_OUT vector<vector<DMatch> >& matches, float maxDistance,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
#endif
enum
{
FLANNBASED = 1,
BRUTEFORCE = 2,
BRUTEFORCE_L1 = 3,
BRUTEFORCE_HAMMING = 4,
BRUTEFORCE_HAMMINGLUT = 5,
BRUTEFORCE_SL2 = 6
};
CV_WRAP_AS(clone) javaDescriptorMatcher* jclone( bool emptyTrainData=false ) const
{
Ptr<DescriptorMatcher> matcher = this->clone(emptyTrainData);
matcher.addref();
return (javaDescriptorMatcher*)((DescriptorMatcher*) matcher);
}
//supported: FlannBased, BruteForce, BruteForce-L1, BruteForce-Hamming, BruteForce-HammingLUT
CV_WRAP static javaDescriptorMatcher* create( int matcherType )
{
string name;
switch(matcherType)
{
case FLANNBASED:
name = "FlannBased";
break;
case BRUTEFORCE:
name = "BruteForce";
break;
case BRUTEFORCE_L1:
name = "BruteForce-L1";
break;
case BRUTEFORCE_HAMMING:
name = "BruteForce-Hamming";
break;
case BRUTEFORCE_HAMMINGLUT:
name = "BruteForce-HammingLUT";
break;
case BRUTEFORCE_SL2:
name = "BruteForce-SL2";
break;
default:
CV_Error( CV_StsBadArg, "Specified descriptor matcher type is not supported." );
break;
}
Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create(name);
matcher.addref();
return (javaDescriptorMatcher*)((DescriptorMatcher*) matcher);
}
CV_WRAP void write( const string& fileName ) const
{
FileStorage fs(fileName, FileStorage::WRITE);
((DescriptorMatcher*)this)->write(fs);
fs.release();
}
CV_WRAP void read( const string& fileName )
{
FileStorage fs(fileName, FileStorage::READ);
((DescriptorMatcher*)this)->read(fs.root());
fs.release();
}
};
class CV_EXPORTS_AS(DescriptorExtractor) javaDescriptorExtractor : public DescriptorExtractor
{
public:
#if 0
//DO NOT REMOVE! The block is required for sources parser
CV_WRAP void compute( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
CV_WRAP void compute( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints, CV_OUT vector<Mat>& descriptors ) const;
CV_WRAP virtual int descriptorSize() const;
CV_WRAP virtual int descriptorType() const;
CV_WRAP virtual bool empty() const;
#endif
enum
{
SIFT = 1,
SURF = 2,
ORB = 3,
BRIEF = 4,
2012-10-12 03:14:06 +08:00
BRISK = 5,
FREAK = 6,
OPPONENTEXTRACTOR = 1000,
OPPONENT_SIFT = OPPONENTEXTRACTOR + SIFT,
OPPONENT_SURF = OPPONENTEXTRACTOR + SURF,
OPPONENT_ORB = OPPONENTEXTRACTOR + ORB,
OPPONENT_BRIEF = OPPONENTEXTRACTOR + BRIEF,
OPPONENT_BRISK = OPPONENTEXTRACTOR + BRISK,
OPPONENT_FREAK = OPPONENTEXTRACTOR + FREAK
};
//supported SIFT, SURF, ORB, BRIEF, BRISK, FREAK, Opponent(XXXX)
//not supported: Calonder
CV_WRAP static javaDescriptorExtractor* create( int extractorType )
{
string name;
if (extractorType > OPPONENTEXTRACTOR)
{
name = "Opponent";
extractorType -= OPPONENTEXTRACTOR;
}
switch(extractorType)
{
case SIFT:
name += "SIFT";
break;
case SURF:
name += "SURF";
break;
case ORB:
name += "ORB";
break;
case BRIEF:
name += "BRIEF";
break;
case BRISK:
name += "BRISK";
break;
case FREAK:
name += "FREAK";
break;
default:
CV_Error( CV_StsBadArg, "Specified descriptor extractor type is not supported." );
break;
}
Ptr<DescriptorExtractor> extractor = DescriptorExtractor::create(name);
extractor.addref();
return (javaDescriptorExtractor*)((DescriptorExtractor*) extractor);
}
CV_WRAP void write( const string& fileName ) const
{
FileStorage fs(fileName, FileStorage::WRITE);
((DescriptorExtractor*)this)->write(fs);
fs.release();
}
CV_WRAP void read( const string& fileName )
{
FileStorage fs(fileName, FileStorage::READ);
((DescriptorExtractor*)this)->read(fs.root());
fs.release();
}
};
class CV_EXPORTS_AS(GenericDescriptorMatcher) javaGenericDescriptorMatcher : public GenericDescriptorMatcher
{
public:
#if 0
//DO NOT REMOVE! The block is required for sources parser
CV_WRAP virtual void add( const vector<Mat>& images,
vector<vector<KeyPoint> >& keypoints );
CV_WRAP const vector<Mat>& getTrainImages() const;
CV_WRAP const vector<vector<KeyPoint> >& getTrainKeypoints() const;
CV_WRAP virtual void clear();
CV_WRAP virtual bool isMaskSupported();
CV_WRAP virtual void train();
CV_WRAP void classify( const Mat& queryImage, CV_IN_OUT vector<KeyPoint>& queryKeypoints,
const Mat& trainImage, vector<KeyPoint>& trainKeypoints ) const;
CV_WRAP void classify( const Mat& queryImage, CV_IN_OUT vector<KeyPoint>& queryKeypoints );
CV_WRAP void match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const Mat& trainImage, vector<KeyPoint>& trainKeypoints,
CV_OUT vector<DMatch>& matches, const Mat& mask=Mat() ) const;
CV_WRAP void knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const Mat& trainImage, vector<KeyPoint>& trainKeypoints,
CV_OUT vector<vector<DMatch> >& matches, int k,
const Mat& mask=Mat(), bool compactResult=false ) const;
CV_WRAP void radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
const Mat& trainImage, vector<KeyPoint>& trainKeypoints,
CV_OUT vector<vector<DMatch> >& matches, float maxDistance,
const Mat& mask=Mat(), bool compactResult=false ) const;
CV_WRAP void match( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
CV_OUT vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() );
CV_WRAP void knnMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
CV_OUT vector<vector<DMatch> >& matches, int k,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
CV_WRAP void radiusMatch( const Mat& queryImage, vector<KeyPoint>& queryKeypoints,
CV_OUT vector<vector<DMatch> >& matches, float maxDistance,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
CV_WRAP virtual bool empty() const;
#endif
enum
{
ONEWAY = 1,
FERN = 2
};
CV_WRAP_AS(clone) javaGenericDescriptorMatcher* jclone( bool emptyTrainData=false ) const
{
Ptr<GenericDescriptorMatcher> matcher = this->clone(emptyTrainData);
matcher.addref();
return (javaGenericDescriptorMatcher*)((GenericDescriptorMatcher*) matcher);
}
//supported: OneWay, Fern
//unsupported: Vector
CV_WRAP static javaGenericDescriptorMatcher* create( int matcherType )
{
string name;
switch(matcherType)
{
case ONEWAY:
name = "ONEWAY";
break;
case FERN:
name = "FERN";
break;
default:
CV_Error( CV_StsBadArg, "Specified generic descriptor matcher type is not supported." );
break;
}
Ptr<GenericDescriptorMatcher> matcher = GenericDescriptorMatcher::create(name);
matcher.addref();
return (javaGenericDescriptorMatcher*)((GenericDescriptorMatcher*) matcher);
}
CV_WRAP void write( const string& fileName ) const
{
FileStorage fs(fileName, FileStorage::WRITE);
((GenericDescriptorMatcher*)this)->write(fs);
fs.release();
}
CV_WRAP void read( const string& fileName )
{
FileStorage fs(fileName, FileStorage::READ);
((GenericDescriptorMatcher*)this)->read(fs.root());
fs.release();
}
};
#if 0
//DO NOT REMOVE! The block is required for sources parser
enum
{
DRAW_OVER_OUTIMG = 1, // Output image matrix will not be created (Mat::create).
// Matches will be drawn on existing content of output image.
NOT_DRAW_SINGLE_POINTS = 2, // Single keypoints will not be drawn.
DRAW_RICH_KEYPOINTS = 4 // For each keypoint the circle around keypoint with keypoint size and
// orientation will be drawn.
};
// Draw keypoints.
CV_EXPORTS_W void drawKeypoints( const Mat& image, const vector<KeyPoint>& keypoints, Mat& outImage,
const Scalar& color=Scalar::all(-1), int flags=0 );
// Draws matches of keypints from two images on output image.
CV_EXPORTS_W void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
const vector<DMatch>& matches1to2, Mat& outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const vector<char>& matchesMask=vector<char>(), int flags=0 );
CV_EXPORTS_AS(drawMatches2) void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,
const Mat& img2, const vector<KeyPoint>& keypoints2,
const vector<vector<DMatch> >& matches1to2, Mat& outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const vector<vector<char> >& matchesMask=vector<vector<char> >(), int flags=0);
#endif
} //cv
#endif // HAVE_OPENCV_FEATURES2D
#endif // __OPENCV_FEATURES_2D_MANUAL_HPP__