cv::GFTTDetector Class Reference

Wrapping class for feature detection using the goodFeaturesToTrack function. : More...

#include <opencv2/features2d.hpp>

Inheritance diagram for cv::GFTTDetector:

Public Member Functions
virtual int	getBlockSize () const =0
virtual String	getDefaultName () const CV_OVERRIDE
virtual bool	getHarrisDetector () const =0
virtual double	getK () const =0
virtual int	getMaxFeatures () const =0
virtual double	getMinDistance () const =0
virtual double	getQualityLevel () const =0
virtual void	setBlockSize (int blockSize)=0
virtual void	setHarrisDetector (bool val)=0
virtual void	setK (double k)=0
virtual void	setMaxFeatures (int maxFeatures)=0
virtual void	setMinDistance (double minDistance)=0
virtual void	setQualityLevel (double qlevel)=0
Public Member Functions inherited from cv::Feature2D
virtual	~Feature2D ()
virtual void	compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)
	Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
virtual void	compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors)
virtual int	defaultNorm () const
virtual int	descriptorSize () const
virtual int	descriptorType () const
virtual void	detect (InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray())
	Detects keypoints in an image (first variant) or image set (second variant).
virtual void	detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray())
virtual void	detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
virtual bool	empty () const CV_OVERRIDE
	Return true if detector object is empty.
void	read (const String &fileName)
virtual void	read (const FileNode &) CV_OVERRIDE
	Reads algorithm parameters from a file storage.
void	write (const String &fileName) const
virtual void	write (FileStorage &) const CV_OVERRIDE
	Stores algorithm parameters in a file storage.
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
Public Member Functions inherited from cv::Algorithm
	Algorithm ()
virtual	~Algorithm ()
virtual void	clear ()
	Clears the algorithm state.
virtual void	save (const String &filename) const
void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindingsThis is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Static Public Member Functions
static Ptr< GFTTDetector >	create (int maxCorners=1000, double qualityLevel=0.01, double minDistance=1, int blockSize=3, bool useHarrisDetector=false, double k=0.04)
static Ptr< GFTTDetector >	create (int maxCorners, double qualityLevel, double minDistance, int blockSize, int gradiantSize, bool useHarrisDetector=false, double k=0.04)

Additional Inherited Members
Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Wrapping class for feature detection using the goodFeaturesToTrack function. :

Member Function Documentation

static Ptr<GFTTDetector> cv::GFTTDetector::create ( int  maxCorners = 1000, double  qualityLevel = 0.01, double  minDistance = 1, int  blockSize = 3, bool  useHarrisDetector = false, double  k = 0.04  )

static

Python:
	retval	=	cv.GFTTDetector_create(	[, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]	)
	retval	=	cv.GFTTDetector_create(	maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]	)

static Ptr<GFTTDetector> cv::GFTTDetector::create ( int  maxCorners, double  qualityLevel, double  minDistance, int  blockSize, int  gradiantSize, bool  useHarrisDetector = false, double  k = 0.04  )

static

Python:
	retval	=	cv.GFTTDetector_create(	[, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]	)
	retval	=	cv.GFTTDetector_create(	maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]	)

virtual int cv::GFTTDetector::getBlockSize ( ) const

pure virtual

Python:
	retval	=	cv.GFTTDetector.getBlockSize(		)

virtual String cv::GFTTDetector::getDefaultName ( ) const

virtual

Python:
	retval	=	cv.GFTTDetector.getDefaultName(		)

Returns the algorithm string identifier.

This string is used as top level xml/yml node tag when the object is saved to a file or string.

Reimplemented from cv::Feature2D.

virtual bool cv::GFTTDetector::getHarrisDetector ( ) const

pure virtual

Python:
	retval	=	cv.GFTTDetector.getHarrisDetector(		)

virtual double cv::GFTTDetector::getK ( ) const

pure virtual

Python:
	retval	=	cv.GFTTDetector.getK(		)

virtual int cv::GFTTDetector::getMaxFeatures ( ) const

pure virtual

Python:
	retval	=	cv.GFTTDetector.getMaxFeatures(		)

virtual double cv::GFTTDetector::getMinDistance ( ) const

pure virtual

Python:
	retval	=	cv.GFTTDetector.getMinDistance(		)

virtual double cv::GFTTDetector::getQualityLevel ( ) const

pure virtual

Python:
	retval	=	cv.GFTTDetector.getQualityLevel(		)

virtual void cv::GFTTDetector::setBlockSize ( int  blockSize )

pure virtual

Python:
	None	=	cv.GFTTDetector.setBlockSize(	blockSize	)

virtual void cv::GFTTDetector::setHarrisDetector ( bool  val )

pure virtual

Python:
	None	=	cv.GFTTDetector.setHarrisDetector(	val	)

virtual void cv::GFTTDetector::setK ( double  k )

pure virtual

Python:
	None	=	cv.GFTTDetector.setK(	k	)

virtual void cv::GFTTDetector::setMaxFeatures ( int  maxFeatures )

pure virtual

Python:
	None	=	cv.GFTTDetector.setMaxFeatures(	maxFeatures	)

virtual void cv::GFTTDetector::setMinDistance ( double  minDistance )

pure virtual

Python:
	None	=	cv.GFTTDetector.setMinDistance(	minDistance	)

virtual void cv::GFTTDetector::setQualityLevel ( double  qlevel )

pure virtual

Python:
	None	=	cv.GFTTDetector.setQualityLevel(	qlevel	)

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The documentation for this class was generated from the following file:

• features2d.hpp