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opencv/modules/features2d/misc/java/src/cpp/features2d_manual.hpp

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#ifndef __OPENCV_FEATURES_2D_MANUAL_HPP__
#define __OPENCV_FEATURES_2D_MANUAL_HPP__
#include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCV_FEATURES2D
#include "opencv2/features2d.hpp"
#include "features2d_converters.hpp"
#undef SIMPLEBLOB // to solve conflict with wincrypt.h on windows
namespace cv
{
class CV_EXPORTS_AS(FeatureDetector) javaFeatureDetector
{
public:
CV_WRAP void detect( const Mat& image, CV_OUT std::vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const
{ return wrapped->detect(image, keypoints, mask); }
CV_WRAP void detect( const std::vector<Mat>& images, CV_OUT std::vector<std::vector<KeyPoint> >& keypoints, const std::vector<Mat>& masks=std::vector<Mat>() ) const
{ return wrapped->detect(images, keypoints, masks); }
CV_WRAP bool empty() const
{ return wrapped->empty(); }
enum
{
FAST = 1,
STAR = 2,
SIFT = 3,
SURF = 4,
ORB = 5,
MSER = 6,
GFTT = 7,
HARRIS = 8,
SIMPLEBLOB = 9,
DENSE = 10,
BRISK = 11,
AKAZE = 12,
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,
GRID_AKAZE = GRIDDETECTOR + AKAZE,
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,
PYRAMID_AKAZE = PYRAMIDDETECTOR + AKAZE,
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,
DYNAMIC_AKAZE = DYNAMICDETECTOR + AKAZE
};
//supported: FAST STAR SIFT SURF ORB MSER GFTT HARRIS BRISK AKAZE 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;
}
Ptr<FeatureDetector> fd;
switch(detectorType)
{
case FAST:
fd = FastFeatureDetector::create();
break;
//case STAR:
// fd = xfeatures2d::StarDetector::create();
// break;
//case SIFT:
// name = name + "SIFT";
// break;
//case SURF:
// name = name + "SURF";
// break;
case ORB:
fd = ORB::create();
break;
case MSER:
fd = MSER::create();
break;
case GFTT:
fd = GFTTDetector::create();
break;
case HARRIS:
{
Ptr<GFTTDetector> gftt = GFTTDetector::create();
gftt->setHarrisDetector(true);
fd = gftt;
}
break;
case SIMPLEBLOB:
fd = SimpleBlobDetector::create();
break;
//case DENSE:
// name = name + "Dense";
// break;
case BRISK:
fd = BRISK::create();
break;
case AKAZE:
fd = AKAZE::create();
break;
default:
CV_Error( Error::StsBadArg, "Specified feature detector type is not supported." );
break;
}
return new javaFeatureDetector(fd);
}
CV_WRAP void write( const String& fileName ) const
{
FileStorage fs(fileName, FileStorage::WRITE);
wrapped->write(fs);
}
CV_WRAP void read( const String& fileName )
{
FileStorage fs(fileName, FileStorage::READ);
wrapped->read(fs.root());
}
private:
javaFeatureDetector(Ptr<FeatureDetector> _wrapped) : wrapped(_wrapped)
{}
Ptr<FeatureDetector> wrapped;
};
class CV_EXPORTS_AS(DescriptorMatcher) javaDescriptorMatcher
{
public:
CV_WRAP bool isMaskSupported() const
{ return wrapped->isMaskSupported(); }
CV_WRAP void add( const std::vector<Mat>& descriptors )
{ return wrapped->add(descriptors); }
CV_WRAP const std::vector<Mat>& getTrainDescriptors() const
{ return wrapped->getTrainDescriptors(); }
CV_WRAP void clear()
{ return wrapped->clear(); }
CV_WRAP bool empty() const
{ return wrapped->empty(); }
CV_WRAP void train()
{ return wrapped->train(); }
CV_WRAP void match( const Mat& queryDescriptors, const Mat& trainDescriptors,
CV_OUT std::vector<DMatch>& matches, const Mat& mask=Mat() ) const
{ return wrapped->match(queryDescriptors, trainDescriptors, matches, mask); }
CV_WRAP void knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
CV_OUT std::vector<std::vector<DMatch> >& matches, int k,
const Mat& mask=Mat(), bool compactResult=false ) const
{ return wrapped->knnMatch(queryDescriptors, trainDescriptors, matches, k, mask, compactResult); }
CV_WRAP void radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
CV_OUT std::vector<std::vector<DMatch> >& matches, float maxDistance,
const Mat& mask=Mat(), bool compactResult=false ) const
{ return wrapped->radiusMatch(queryDescriptors, trainDescriptors, matches, maxDistance, mask, compactResult); }
CV_WRAP void match( const Mat& queryDescriptors, CV_OUT std::vector<DMatch>& matches,
const std::vector<Mat>& masks=std::vector<Mat>() )
{ return wrapped->match(queryDescriptors, matches, masks); }
CV_WRAP void knnMatch( const Mat& queryDescriptors, CV_OUT std::vector<std::vector<DMatch> >& matches, int k,
const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false )
{ return wrapped->knnMatch(queryDescriptors, matches, k, masks, compactResult); }
CV_WRAP void radiusMatch( const Mat& queryDescriptors, CV_OUT std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false )
{ return wrapped->radiusMatch(queryDescriptors, matches, maxDistance, masks, compactResult); }
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
{
return new javaDescriptorMatcher(wrapped->clone(emptyTrainData));
}
//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( Error::StsBadArg, "Specified descriptor matcher type is not supported." );
break;
}
return new javaDescriptorMatcher(DescriptorMatcher::create(name));
}
CV_WRAP void write( const String& fileName ) const
{
FileStorage fs(fileName, FileStorage::WRITE);
wrapped->write(fs);
}
CV_WRAP void read( const String& fileName )
{
FileStorage fs(fileName, FileStorage::READ);
wrapped->read(fs.root());
}
private:
javaDescriptorMatcher(Ptr<DescriptorMatcher> _wrapped) : wrapped(_wrapped)
{}
Ptr<DescriptorMatcher> wrapped;
};
class CV_EXPORTS_AS(DescriptorExtractor) javaDescriptorExtractor
{
public:
CV_WRAP void compute( const Mat& image, CV_IN_OUT std::vector<KeyPoint>& keypoints, Mat& descriptors ) const
{ return wrapped->compute(image, keypoints, descriptors); }
CV_WRAP void compute( const std::vector<Mat>& images, CV_IN_OUT std::vector<std::vector<KeyPoint> >& keypoints, CV_OUT std::vector<Mat>& descriptors ) const
{ return wrapped->compute(images, keypoints, descriptors); }
CV_WRAP int descriptorSize() const
{ return wrapped->descriptorSize(); }
CV_WRAP int descriptorType() const
{ return wrapped->descriptorType(); }
CV_WRAP bool empty() const
{ return wrapped->empty(); }
enum
{
SIFT = 1,
SURF = 2,
ORB = 3,
BRIEF = 4,
BRISK = 5,
FREAK = 6,
AKAZE = 7,
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,
OPPONENT_AKAZE = OPPONENTEXTRACTOR + AKAZE
};
//supported SIFT, SURF, ORB, BRIEF, BRISK, FREAK, AKAZE, Opponent(XXXX)
//not supported: Calonder
CV_WRAP static javaDescriptorExtractor* create( int extractorType )
{
//String name;
if (extractorType > OPPONENTEXTRACTOR)
{
//name = "Opponent";
extractorType -= OPPONENTEXTRACTOR;
}
Ptr<DescriptorExtractor> de;
switch(extractorType)
{
//case SIFT:
// name = name + "SIFT";
// break;
//case SURF:
// name = name + "SURF";
// break;
case ORB:
de = ORB::create();
break;
//case BRIEF:
// name = name + "BRIEF";
// break;
case BRISK:
de = BRISK::create();
break;
//case FREAK:
// name = name + "FREAK";
// break;
case AKAZE:
de = AKAZE::create();
break;
default:
CV_Error( Error::StsBadArg, "Specified descriptor extractor type is not supported." );
break;
}
return new javaDescriptorExtractor(de);
}
CV_WRAP void write( const String& fileName ) const
{
FileStorage fs(fileName, FileStorage::WRITE);
wrapped->write(fs);
}
CV_WRAP void read( const String& fileName )
{
FileStorage fs(fileName, FileStorage::READ);
wrapped->read(fs.root());
}
private:
javaDescriptorExtractor(Ptr<DescriptorExtractor> _wrapped) : wrapped(_wrapped)
{}
Ptr<DescriptorExtractor> wrapped;
};
#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 std::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 std::vector<KeyPoint>& keypoints1,
const Mat& img2, const std::vector<KeyPoint>& keypoints2,
const std::vector<DMatch>& matches1to2, Mat& outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const std::vector<char>& matchesMask=std::vector<char>(), int flags=0 );
CV_EXPORTS_AS(drawMatches2) void drawMatches( const Mat& img1, const std::vector<KeyPoint>& keypoints1,
const Mat& img2, const std::vector<KeyPoint>& keypoints2,
const std::vector<std::vector<DMatch> >& matches1to2, Mat& outImg,
const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),
const std::vector<std::vector<char> >& matchesMask=std::vector<std::vector<char> >(), int flags=0);
#endif
} //cv
#endif // HAVE_OPENCV_FEATURES2D
#endif // __OPENCV_FEATURES_2D_MANUAL_HPP__