Class implementing the AKAZE keypoint detector and descriptor extractor, described in [10]. More...

#include <opencv2/features2d.hpp>

Collaboration diagram for cv::AKAZE:

Public Types
enum	DescriptorType { DESCRIPTOR_KAZE_UPRIGHT = 2 , DESCRIPTOR_KAZE = 3 , DESCRIPTOR_MLDB_UPRIGHT = 4 , DESCRIPTOR_MLDB = 5 }

Public Member Functions
virtual String	getDefaultName () const CV_OVERRIDE

virtual int	getDescriptorChannels () const =0

virtual int	getDescriptorSize () const =0

virtual AKAZE::DescriptorType	getDescriptorType () const =0

virtual KAZE::DiffusivityType	getDiffusivity () const =0

virtual int	getMaxPoints () const =0

virtual int	getNOctaveLayers () const =0

virtual int	getNOctaves () const =0

virtual double	getThreshold () const =0

virtual void	setDescriptorChannels (int dch)=0

virtual void	setDescriptorSize (int dsize)=0

virtual void	setDescriptorType (AKAZE::DescriptorType dtype)=0

virtual void	setDiffusivity (KAZE::DiffusivityType diff)=0

virtual void	setMaxPoints (int max_points)=0

virtual void	setNOctaveLayers (int octaveLayers)=0

virtual void	setNOctaves (int octaves)=0

virtual void	setThreshold (double threshold)=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.

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

void	read (const String &fileName)

void	write (const Ptr< FileStorage > &fs, const String &name) const

void	write (const String &fileName) const

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

void	write (FileStorage &fs, const String &name) 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

void	write (FileStorage &fs, const String &name) const

Static Public Member Functions
static Ptr< AKAZE >	create (AKAZE::DescriptorType descriptor_type=AKAZE::DESCRIPTOR_MLDB, int descriptor_size=0, int descriptor_channels=3, float threshold=0.001f, int nOctaves=4, int nOctaveLayers=4, KAZE::DiffusivityType diffusivity=KAZE::DIFF_PM_G2, int max_points=-1)
	The AKAZE constructor.

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.

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

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

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

Detailed Description

Class implementing the AKAZE keypoint detector and descriptor extractor, described in [10].

AKAZE descriptors can only be used with KAZE or AKAZE keypoints. This class is thread-safe.

Note: When you need descriptors use Feature2D::detectAndCompute, which provides better performance. When using Feature2D::detect followed by Feature2D::compute scale space pyramid is computed twice.; AKAZE implements T-API. When image is passed as UMat some parts of the algorithm will use OpenCL.; [ANB13] Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces. Pablo F. Alcantarilla, Jesús Nuevo and Adrien Bartoli. In British Machine Vision Conference (BMVC), Bristol, UK, September 2013.

Member Enumeration Documentation

◆ DescriptorType

enum cv::AKAZE::DescriptorType

Enumerator
DESCRIPTOR_KAZE_UPRIGHT	Upright descriptors, not invariant to rotation.
DESCRIPTOR_KAZE
DESCRIPTOR_MLDB_UPRIGHT	Upright descriptors, not invariant to rotation.
DESCRIPTOR_MLDB

Member Function Documentation

◆ create()

static Ptr< AKAZE > cv::AKAZE::create	(	AKAZE::DescriptorType	descriptor_type = `AKAZE::DESCRIPTOR_MLDB`,
		int	descriptor_size = `0`,
		int	descriptor_channels = `3`,
		float	threshold = `0.001f`,
		int	nOctaves = `4`,
		int	nOctaveLayers = `4`,
		KAZE::DiffusivityType	diffusivity = `KAZE::DIFF_PM_G2`,
		int	max_points = `-1`
	)

static

Python:
	cv.AKAZE.create(	[, descriptor_type[, descriptor_size[, descriptor_channels[, threshold[, nOctaves[, nOctaveLayers[, diffusivity[, max_points]]]]]]]]	) ->	retval
	cv.AKAZE_create(	[, descriptor_type[, descriptor_size[, descriptor_channels[, threshold[, nOctaves[, nOctaveLayers[, diffusivity[, max_points]]]]]]]]	) ->	retval

The AKAZE constructor.

Parameters

descriptor_type	Type of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
descriptor_size	Size of the descriptor in bits. 0 -> Full size
descriptor_channels	Number of channels in the descriptor (1, 2, 3)
threshold	Detector response threshold to accept point
nOctaves	Maximum octave evolution of the image
nOctaveLayers	Default number of sublevels per scale level
diffusivity	Diffusivity type. DIFF_PM_G1, DIFF_PM_G2, DIFF_WEICKERT or DIFF_CHARBONNIER
max_points	Maximum amount of returned points. In case if image contains more features, then the features with highest response are returned. Negative value means no limitation.

◆ getDefaultName()

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

virtual

Python:
	cv.AKAZE.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.

◆ getDescriptorChannels()

virtual int cv::AKAZE::getDescriptorChannels ( ) const

pure virtual

Python:
	cv.AKAZE.getDescriptorChannels(		) ->	retval

◆ getDescriptorSize()

virtual int cv::AKAZE::getDescriptorSize ( ) const

pure virtual

Python:
	cv.AKAZE.getDescriptorSize(		) ->	retval

◆ getDescriptorType()

virtual AKAZE::DescriptorType cv::AKAZE::getDescriptorType ( ) const

pure virtual

Python:
	cv.AKAZE.getDescriptorType(		) ->	retval

◆ getDiffusivity()

virtual KAZE::DiffusivityType cv::AKAZE::getDiffusivity ( ) const

pure virtual

Python:
	cv.AKAZE.getDiffusivity(		) ->	retval

◆ getMaxPoints()

virtual int cv::AKAZE::getMaxPoints ( ) const

pure virtual

Python:
	cv.AKAZE.getMaxPoints(		) ->	retval

◆ getNOctaveLayers()

virtual int cv::AKAZE::getNOctaveLayers ( ) const

pure virtual

Python:
	cv.AKAZE.getNOctaveLayers(		) ->	retval

◆ getNOctaves()

virtual int cv::AKAZE::getNOctaves ( ) const

pure virtual

Python:
	cv.AKAZE.getNOctaves(		) ->	retval

◆ getThreshold()

virtual double cv::AKAZE::getThreshold ( ) const

pure virtual

Python:
	cv.AKAZE.getThreshold(		) ->	retval

◆ setDescriptorChannels()

virtual void cv::AKAZE::setDescriptorChannels ( int dch )

pure virtual

Python:
	cv.AKAZE.setDescriptorChannels(	dch	) ->	None

◆ setDescriptorSize()

virtual void cv::AKAZE::setDescriptorSize ( int dsize )

pure virtual

Python:
	cv.AKAZE.setDescriptorSize(	dsize	) ->	None

◆ setDescriptorType()

virtual void cv::AKAZE::setDescriptorType ( AKAZE::DescriptorType dtype )

pure virtual

Python:
	cv.AKAZE.setDescriptorType(	dtype	) ->	None

◆ setDiffusivity()

virtual void cv::AKAZE::setDiffusivity ( KAZE::DiffusivityType diff )

pure virtual

Python:
	cv.AKAZE.setDiffusivity(	diff	) ->	None

◆ setMaxPoints()

virtual void cv::AKAZE::setMaxPoints ( int max_points )

pure virtual

Python:
	cv.AKAZE.setMaxPoints(	max_points	) ->	None

◆ setNOctaveLayers()

virtual void cv::AKAZE::setNOctaveLayers ( int octaveLayers )

pure virtual

Python:
	cv.AKAZE.setNOctaveLayers(	octaveLayers	) ->	None

◆ setNOctaves()

virtual void cv::AKAZE::setNOctaves ( int octaves )

pure virtual

Python:
	cv.AKAZE.setNOctaves(	octaves	) ->	None

◆ setThreshold()

virtual void cv::AKAZE::setThreshold ( double threshold )

pure virtual

Python:
	cv.AKAZE.setThreshold(	threshold	) ->	None

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

opencv2/features2d.hpp

Public Types

Public Member Functions

Static Public Member Functions

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

◆ DescriptorType

Member Function Documentation

◆ create()

◆ getDefaultName()

◆ getDescriptorChannels()

◆ getDescriptorSize()

◆ getDescriptorType()

◆ getDiffusivity()

◆ getMaxPoints()

◆ getNOctaveLayers()

◆ getNOctaves()

◆ getThreshold()

◆ setDescriptorChannels()

◆ setDescriptorSize()

◆ setDescriptorType()

◆ setDiffusivity()

◆ setMaxPoints()

◆ setNOctaveLayers()

◆ setNOctaves()

◆ setThreshold()