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). More...

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). More...

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. More...

void	read (const String &fileName)

virtual void	read (const FileNode &) CV_OVERRIDE
	Reads algorithm parameters from a file storage. More...

void	write (const String &fileName) const

virtual void	write (FileStorage &) const CV_OVERRIDE
	Stores algorithm parameters in a file storage. More...

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. More...

virtual void	save (const String &filename) const

void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

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)

Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file. More...

template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String. More...

template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node. More...

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

◆ create() [1/2]

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


cv.GFTTDetector.create(	[, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]	) ->	retval
cv.GFTTDetector.create(	maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]	) ->	retval
cv.GFTTDetector_create(	[, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]	) ->	retval
cv.GFTTDetector_create(	maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]	) ->	retval

◆ create() [2/2]

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

static


cv.GFTTDetector.create(	[, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]	) ->	retval
cv.GFTTDetector.create(	maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]	) ->	retval
cv.GFTTDetector_create(	[, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]	) ->	retval
cv.GFTTDetector_create(	maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]	) ->	retval

◆ getBlockSize()

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

pure virtual

Python:
	cv.GFTTDetector.getBlockSize(		) ->	retval

◆ getDefaultName()

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

virtual

Python:
	cv.GFTTDetector.getDefaultName(		) ->	retval

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.

◆ getHarrisDetector()

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

pure virtual

Python:
	cv.GFTTDetector.getHarrisDetector(		) ->	retval

◆ getK()

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

pure virtual

Python:
	cv.GFTTDetector.getK(		) ->	retval

◆ getMaxFeatures()

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

pure virtual

Python:
	cv.GFTTDetector.getMaxFeatures(		) ->	retval

◆ getMinDistance()

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

pure virtual

Python:
	cv.GFTTDetector.getMinDistance(		) ->	retval

◆ getQualityLevel()

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

pure virtual

Python:
	cv.GFTTDetector.getQualityLevel(		) ->	retval

◆ setBlockSize()

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

pure virtual

Python:
	cv.GFTTDetector.setBlockSize(	blockSize	) ->	None

◆ setHarrisDetector()

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

pure virtual

Python:
	cv.GFTTDetector.setHarrisDetector(	val	) ->	None

◆ setK()

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

pure virtual

Python:
	cv.GFTTDetector.setK(	k	) ->	None

◆ setMaxFeatures()

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

pure virtual

Python:
	cv.GFTTDetector.setMaxFeatures(	maxFeatures	) ->	None

◆ setMinDistance()

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

pure virtual

Python:
	cv.GFTTDetector.setMinDistance(	minDistance	) ->	None

◆ setQualityLevel()

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

pure virtual

Python:
	cv.GFTTDetector.setQualityLevel(	qlevel	) ->	None

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

opencv2/features2d.hpp

Public Member Functions

Static Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ create() [1/2]

◆ create() [2/2]

◆ getBlockSize()

◆ getDefaultName()

◆ getHarrisDetector()

◆ getK()

◆ getMaxFeatures()

◆ getMinDistance()

◆ getQualityLevel()

◆ setBlockSize()

◆ setHarrisDetector()

◆ setK()

◆ setMaxFeatures()

◆ setMinDistance()

◆ setQualityLevel()