mirror of
https://github.com/opencv/opencv.git
synced 2025-01-18 06:03:15 +08:00
Java: removed usages of Ptr<T>::addref().
Now the features2d class wrappers use composition instead of inheritance.
This commit is contained in:
Roman Donchenko
parent
2a2c21bb63
commit
2f942efdf7
@ -11,15 +11,17 @@
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namespace cv
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{
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class CV_EXPORTS_AS(FeatureDetector) javaFeatureDetector : public FeatureDetector
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class CV_EXPORTS_AS(FeatureDetector) javaFeatureDetector
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{
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public:
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#if 0
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//DO NOT REMOVE! The block is required for sources parser
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CV_WRAP void detect( const Mat& image, CV_OUT std::vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const;
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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;
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CV_WRAP virtual bool empty() const;
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#endif
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CV_WRAP void detect( const Mat& image, CV_OUT std::vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const
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{ return wrapped->detect(image, keypoints, mask); }
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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
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{ return wrapped->detect(images, keypoints, masks); }
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CV_WRAP bool empty() const
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{ return wrapped->empty(); }
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enum
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{
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@ -141,52 +143,74 @@ public:
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break;
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}
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Ptr<FeatureDetector> detector = FeatureDetector::create(name);
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detector.addref();
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return (javaFeatureDetector*)((FeatureDetector*) detector);
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return new javaFeatureDetector(FeatureDetector::create(name));
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}
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CV_WRAP void write( const String& fileName ) const
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{
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FileStorage fs(fileName, FileStorage::WRITE);
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((FeatureDetector*)this)->write(fs);
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fs.release();
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wrapped->write(fs);
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}
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CV_WRAP void read( const String& fileName )
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{
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FileStorage fs(fileName, FileStorage::READ);
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((FeatureDetector*)this)->read(fs.root());
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fs.release();
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wrapped->read(fs.root());
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}
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private:
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javaFeatureDetector(Ptr<FeatureDetector> _wrapped) : wrapped(_wrapped)
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{}
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Ptr<FeatureDetector> wrapped;
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};
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class CV_EXPORTS_AS(DescriptorMatcher) javaDescriptorMatcher : public DescriptorMatcher
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class CV_EXPORTS_AS(DescriptorMatcher) javaDescriptorMatcher
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{
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public:
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#if 0
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//DO NOT REMOVE! The block is required for sources parser
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CV_WRAP virtual bool isMaskSupported() const;
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CV_WRAP virtual void add( const std::vector<Mat>& descriptors );
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CV_WRAP const std::vector<Mat>& getTrainDescriptors() const;
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CV_WRAP virtual void clear();
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CV_WRAP virtual bool empty() const;
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CV_WRAP virtual void train();
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CV_WRAP bool isMaskSupported() const
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{ return wrapped->isMaskSupported(); }
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CV_WRAP void add( const std::vector<Mat>& descriptors )
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{ return wrapped->add(descriptors); }
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CV_WRAP const std::vector<Mat>& getTrainDescriptors() const
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{ return wrapped->getTrainDescriptors(); }
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CV_WRAP void clear()
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{ return wrapped->clear(); }
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CV_WRAP bool empty() const
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{ return wrapped->empty(); }
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CV_WRAP void train()
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{ return wrapped->train(); }
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CV_WRAP void match( const Mat& queryDescriptors, const Mat& trainDescriptors,
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CV_OUT std::vector<DMatch>& matches, const Mat& mask=Mat() ) const;
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CV_OUT std::vector<DMatch>& matches, const Mat& mask=Mat() ) const
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{ return wrapped->match(queryDescriptors, trainDescriptors, matches, mask); }
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CV_WRAP void knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
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CV_OUT std::vector<std::vector<DMatch> >& matches, int k,
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const Mat& mask=Mat(), bool compactResult=false ) const;
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const Mat& mask=Mat(), bool compactResult=false ) const
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{ return wrapped->knnMatch(queryDescriptors, trainDescriptors, matches, k, mask, compactResult); }
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CV_WRAP void radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
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CV_OUT std::vector<std::vector<DMatch> >& matches, float maxDistance,
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const Mat& mask=Mat(), bool compactResult=false ) const;
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const Mat& mask=Mat(), bool compactResult=false ) const
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{ return wrapped->radiusMatch(queryDescriptors, trainDescriptors, matches, maxDistance, mask, compactResult); }
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CV_WRAP void match( const Mat& queryDescriptors, CV_OUT std::vector<DMatch>& matches,
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const std::vector<Mat>& masks=std::vector<Mat>() );
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const std::vector<Mat>& masks=std::vector<Mat>() )
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{ return wrapped->match(queryDescriptors, matches, masks); }
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CV_WRAP void knnMatch( const Mat& queryDescriptors, CV_OUT std::vector<std::vector<DMatch> >& matches, int k,
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false )
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{ return wrapped->knnMatch(queryDescriptors, matches, k, masks, compactResult); }
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CV_WRAP void radiusMatch( const Mat& queryDescriptors, CV_OUT std::vector<std::vector<DMatch> >& matches, float maxDistance,
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
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#endif
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false )
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{ return wrapped->radiusMatch(queryDescriptors, matches, maxDistance, masks, compactResult); }
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enum
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{
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@ -200,9 +224,7 @@ public:
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CV_WRAP_AS(clone) javaDescriptorMatcher* jclone( bool emptyTrainData=false ) const
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{
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Ptr<DescriptorMatcher> matcher = this->clone(emptyTrainData);
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matcher.addref();
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return (javaDescriptorMatcher*)((DescriptorMatcher*) matcher);
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return new javaDescriptorMatcher(wrapped->clone(emptyTrainData));
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}
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//supported: FlannBased, BruteForce, BruteForce-L1, BruteForce-Hamming, BruteForce-HammingLUT
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@ -235,38 +257,45 @@ public:
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break;
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}
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Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create(name);
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matcher.addref();
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return (javaDescriptorMatcher*)((DescriptorMatcher*) matcher);
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return new javaDescriptorMatcher(DescriptorMatcher::create(name));
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}
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CV_WRAP void write( const String& fileName ) const
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{
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FileStorage fs(fileName, FileStorage::WRITE);
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((DescriptorMatcher*)this)->write(fs);
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fs.release();
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wrapped->write(fs);
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}
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CV_WRAP void read( const String& fileName )
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{
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FileStorage fs(fileName, FileStorage::READ);
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((DescriptorMatcher*)this)->read(fs.root());
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fs.release();
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wrapped->read(fs.root());
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}
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private:
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javaDescriptorMatcher(Ptr<DescriptorMatcher> _wrapped) : wrapped(_wrapped)
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{}
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Ptr<DescriptorMatcher> wrapped;
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};
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class CV_EXPORTS_AS(DescriptorExtractor) javaDescriptorExtractor : public DescriptorExtractor
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class CV_EXPORTS_AS(DescriptorExtractor) javaDescriptorExtractor
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{
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public:
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#if 0
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//DO NOT REMOVE! The block is required for sources parser
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CV_WRAP void compute( const Mat& image, CV_IN_OUT std::vector<KeyPoint>& keypoints, Mat& descriptors ) const;
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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;
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CV_WRAP virtual int descriptorSize() const;
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CV_WRAP virtual int descriptorType() const;
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CV_WRAP void compute( const Mat& image, CV_IN_OUT std::vector<KeyPoint>& keypoints, Mat& descriptors ) const
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{ return wrapped->compute(image, keypoints, descriptors); }
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CV_WRAP virtual bool empty() const;
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#endif
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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
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{ return wrapped->compute(images, keypoints, descriptors); }
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CV_WRAP int descriptorSize() const
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{ return wrapped->descriptorSize(); }
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CV_WRAP int descriptorType() const
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{ return wrapped->descriptorType(); }
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CV_WRAP bool empty() const
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{ return wrapped->empty(); }
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enum
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{
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@ -327,62 +356,93 @@ public:
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break;
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}
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Ptr<DescriptorExtractor> extractor = DescriptorExtractor::create(name);
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extractor.addref();
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return (javaDescriptorExtractor*)((DescriptorExtractor*) extractor);
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return new javaDescriptorExtractor(DescriptorExtractor::create(name));
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}
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CV_WRAP void write( const String& fileName ) const
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{
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FileStorage fs(fileName, FileStorage::WRITE);
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((DescriptorExtractor*)this)->write(fs);
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fs.release();
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wrapped->write(fs);
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}
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CV_WRAP void read( const String& fileName )
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{
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FileStorage fs(fileName, FileStorage::READ);
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((DescriptorExtractor*)this)->read(fs.root());
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fs.release();
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wrapped->read(fs.root());
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}
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private:
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javaDescriptorExtractor(Ptr<DescriptorExtractor> _wrapped) : wrapped(_wrapped)
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{}
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Ptr<DescriptorExtractor> wrapped;
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};
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class CV_EXPORTS_AS(GenericDescriptorMatcher) javaGenericDescriptorMatcher : public GenericDescriptorMatcher
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class CV_EXPORTS_AS(GenericDescriptorMatcher) javaGenericDescriptorMatcher
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{
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public:
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#if 0
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//DO NOT REMOVE! The block is required for sources parser
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CV_WRAP virtual void add( const std::vector<Mat>& images,
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std::vector<std::vector<KeyPoint> >& keypoints );
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CV_WRAP const std::vector<Mat>& getTrainImages() const;
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CV_WRAP const std::vector<std::vector<KeyPoint> >& getTrainKeypoints() const;
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CV_WRAP virtual void clear();
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CV_WRAP virtual bool isMaskSupported();
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CV_WRAP virtual void train();
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CV_WRAP void add( const std::vector<Mat>& images,
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std::vector<std::vector<KeyPoint> >& keypoints )
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{ return wrapped->add(images, keypoints); }
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CV_WRAP const std::vector<Mat>& getTrainImages() const
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{ return wrapped->getTrainImages(); }
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CV_WRAP const std::vector<std::vector<KeyPoint> >& getTrainKeypoints() const
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{ return wrapped->getTrainKeypoints(); }
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CV_WRAP void clear()
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{ return wrapped->clear(); }
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CV_WRAP bool isMaskSupported()
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{ return wrapped->isMaskSupported(); }
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CV_WRAP void train()
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{ return wrapped->train(); }
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CV_WRAP void classify( const Mat& queryImage, CV_IN_OUT std::vector<KeyPoint>& queryKeypoints,
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const Mat& trainImage, std::vector<KeyPoint>& trainKeypoints ) const;
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CV_WRAP void classify( const Mat& queryImage, CV_IN_OUT std::vector<KeyPoint>& queryKeypoints );
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const Mat& trainImage, std::vector<KeyPoint>& trainKeypoints ) const
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{ return wrapped->classify(queryImage, queryKeypoints, trainImage, trainKeypoints); }
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CV_WRAP void classify( const Mat& queryImage, CV_IN_OUT std::vector<KeyPoint>& queryKeypoints )
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{ return wrapped->classify(queryImage, queryKeypoints); }
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CV_WRAP void match( const Mat& queryImage, std::vector<KeyPoint>& queryKeypoints,
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const Mat& trainImage, std::vector<KeyPoint>& trainKeypoints,
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CV_OUT std::vector<DMatch>& matches, const Mat& mask=Mat() ) const;
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CV_OUT std::vector<DMatch>& matches, const Mat& mask=Mat() ) const
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{ return wrapped->match(queryImage, queryKeypoints, trainImage, trainKeypoints, matches, mask); }
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CV_WRAP void knnMatch( const Mat& queryImage, std::vector<KeyPoint>& queryKeypoints,
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const Mat& trainImage, std::vector<KeyPoint>& trainKeypoints,
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CV_OUT std::vector<std::vector<DMatch> >& matches, int k,
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const Mat& mask=Mat(), bool compactResult=false ) const;
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const Mat& mask=Mat(), bool compactResult=false ) const
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{ return wrapped->knnMatch(queryImage, queryKeypoints, trainImage, trainKeypoints,
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matches, k, mask, compactResult); }
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CV_WRAP void radiusMatch( const Mat& queryImage, std::vector<KeyPoint>& queryKeypoints,
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const Mat& trainImage, std::vector<KeyPoint>& trainKeypoints,
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CV_OUT std::vector<std::vector<DMatch> >& matches, float maxDistance,
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const Mat& mask=Mat(), bool compactResult=false ) const;
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const Mat& mask=Mat(), bool compactResult=false ) const
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{ return wrapped->radiusMatch(queryImage, queryKeypoints, trainImage, trainKeypoints,
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matches, maxDistance, mask, compactResult); }
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CV_WRAP void match( const Mat& queryImage, std::vector<KeyPoint>& queryKeypoints,
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CV_OUT std::vector<DMatch>& matches, const std::vector<Mat>& masks=std::vector<Mat>() );
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CV_OUT std::vector<DMatch>& matches, const std::vector<Mat>& masks=std::vector<Mat>() )
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{ return wrapped->match(queryImage, queryKeypoints, matches, masks); }
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CV_WRAP void knnMatch( const Mat& queryImage, std::vector<KeyPoint>& queryKeypoints,
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CV_OUT std::vector<std::vector<DMatch> >& matches, int k,
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false )
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{ return wrapped->knnMatch(queryImage, queryKeypoints, matches, k, masks, compactResult); }
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CV_WRAP void radiusMatch( const Mat& queryImage, std::vector<KeyPoint>& queryKeypoints,
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CV_OUT std::vector<std::vector<DMatch> >& matches, float maxDistance,
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
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CV_WRAP virtual bool empty() const;
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#endif
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const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false )
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{ return wrapped->radiusMatch(queryImage, queryKeypoints, matches, maxDistance, masks, compactResult); }
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CV_WRAP bool empty() const
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{ return wrapped->empty(); }
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enum
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{
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@ -392,9 +452,7 @@ public:
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CV_WRAP_AS(clone) javaGenericDescriptorMatcher* jclone( bool emptyTrainData=false ) const
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{
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Ptr<GenericDescriptorMatcher> matcher = this->clone(emptyTrainData);
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matcher.addref();
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return (javaGenericDescriptorMatcher*)((GenericDescriptorMatcher*) matcher);
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return new javaGenericDescriptorMatcher(wrapped->clone(emptyTrainData));
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}
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//supported: OneWay, Fern
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@ -416,24 +474,26 @@ public:
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break;
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}
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Ptr<GenericDescriptorMatcher> matcher = GenericDescriptorMatcher::create(name);
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matcher.addref();
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return (javaGenericDescriptorMatcher*)((GenericDescriptorMatcher*) matcher);
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return new javaGenericDescriptorMatcher(GenericDescriptorMatcher::create(name));
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}
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CV_WRAP void write( const String& fileName ) const
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{
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FileStorage fs(fileName, FileStorage::WRITE);
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((GenericDescriptorMatcher*)this)->write(fs);
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fs.release();
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wrapped->write(fs);
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}
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CV_WRAP void read( const String& fileName )
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{
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FileStorage fs(fileName, FileStorage::READ);
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((GenericDescriptorMatcher*)this)->read(fs.root());
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fs.release();
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wrapped->read(fs.root());
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}
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private:
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javaGenericDescriptorMatcher(Ptr<GenericDescriptorMatcher> _wrapped) : wrapped(_wrapped)
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{}
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Ptr<GenericDescriptorMatcher> wrapped;
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};
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#if 0
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