Class implementing the AKAZE keypoint detector and descriptor extractor, described in [1]. More...

#include <opencv2/features2d.hpp>

Inheritance diagram for cv::AKAZE:

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 void	clear ()
	Clears the algorithm state. More...

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)
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

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())
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...

virtual void	detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
	Detects keypoints and computes the descriptors. More...

virtual bool	empty () const CV_OVERRIDE
	Return true if detector object is empty. More...

virtual String	getDefaultName () const CV_OVERRIDE
	Returns the algorithm string identifier. More...

virtual int	getDescriptorChannels () const =0

virtual int	getDescriptorSize () const =0

virtual AKAZE::DescriptorType	getDescriptorType () const =0

virtual KAZE::DiffusivityType	getDiffusivity () const =0

virtual int	getNOctaveLayers () const =0

virtual int	getNOctaves () const =0

virtual double	getThreshold () const =0

void	read (const String &fileName)

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

virtual void	save (const String &filename) const
	Saves the algorithm to a file. More...

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	setNOctaveLayers (int octaveLayers)=0

virtual void	setNOctaves (int octaves)=0

virtual void	setThreshold (double threshold)=0

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

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)
	The AKAZE constructor. More...

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...

Protected Member Functions
void	writeFormat (FileStorage &fs) const

Detailed Description

Class implementing the AKAZE keypoint detector and descriptor extractor, described in [1].

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

◆ clear()

virtual void cv::Algorithm::clear ( )

inlinevirtualinherited

Clears the algorithm state.

Reimplemented in cv::FlannBasedMatcher, and cv::DescriptorMatcher.

◆ compute() [1/2]

virtual void cv::Feature2D::compute	(	InputArray	image,
		std::vector< KeyPoint > &	keypoints,
		OutputArray	descriptors
	)

virtualinherited

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

Parameters

image	Image.
keypoints	Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).
descriptors	Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

◆ compute() [2/2]

virtual void cv::Feature2D::compute	(	InputArrayOfArrays	images,
		std::vector< std::vector< KeyPoint > > &	keypoints,
		OutputArrayOfArrays	descriptors
	)

virtualinherited

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters

images	Image set.
keypoints	Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).
descriptors	Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

◆ 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`
	)

static

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

◆ defaultNorm()

virtual int cv::Feature2D::defaultNorm ( ) const

virtualinherited

◆ descriptorSize()

virtual int cv::Feature2D::descriptorSize ( ) const

virtualinherited

◆ descriptorType()

virtual int cv::Feature2D::descriptorType ( ) const

virtualinherited

◆ detect() [1/2]

virtual void cv::Feature2D::detect	(	InputArray	image,
		std::vector< KeyPoint > &	keypoints,
		InputArray	mask = `noArray()`
	)

virtualinherited

Detects keypoints in an image (first variant) or image set (second variant).

Parameters

image	Image.
keypoints	The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .
mask	Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

◆ detect() [2/2]

virtual void cv::Feature2D::detect	(	InputArrayOfArrays	images,
		std::vector< std::vector< KeyPoint > > &	keypoints,
		InputArrayOfArrays	masks = `noArray()`
	)

virtualinherited

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters

images	Image set.
keypoints	The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .
masks	Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i].

◆ detectAndCompute()

virtual void cv::Feature2D::detectAndCompute	(	InputArray	image,
		InputArray	mask,
		std::vector< KeyPoint > &	keypoints,
		OutputArray	descriptors,
		bool	useProvidedKeypoints = `false`
	)

virtualinherited

Detects keypoints and computes the descriptors.

◆ empty()

virtual bool cv::Feature2D::empty ( ) const

virtualinherited

Return true if detector object is empty.

Reimplemented from cv::Algorithm.

◆ getDefaultName()

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

virtual

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

◆ getDescriptorSize()

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

pure virtual

◆ getDescriptorType()

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

pure virtual

◆ getDiffusivity()

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

pure virtual

◆ getNOctaveLayers()

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

pure virtual

◆ getNOctaves()

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

pure virtual

◆ getThreshold()

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

pure virtual

◆ load()

template<typename _Tp >

static Ptr<_Tp> cv::Algorithm::load	(	const String &	filename,
		const String &	objname = `String()`
	)

inlinestaticinherited

Loads algorithm from the file.

Parameters

filename	Name of the file to read.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

Ptr<SVM> svm = Algorithm::load<SVM>("my_svm_model.xml");

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn).

References CV_Assert, cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), cv::FileStorage::isOpened(), and cv::FileStorage::READ.

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◆ loadFromString()

template<typename _Tp >

static Ptr<_Tp> cv::Algorithm::loadFromString	(	const String &	strModel,
		const String &	objname = `String()`
	)

inlinestaticinherited

Loads algorithm from a String.

Parameters

strModel	The string variable containing the model you want to load.
objname	The optional name of the node to read (if empty, the first top-level node will be used)

This is static template method of Algorithm. It's usage is following (in the case of SVM):

Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);

References CV_WRAP, cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), cv::FileStorage::MEMORY, and cv::FileStorage::READ.

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◆ read() [1/2]

void cv::Feature2D::read ( const String & fileName )

inherited

◆ read() [2/2]

virtual void cv::Feature2D::read ( const FileNode & fn )

virtualinherited

Reads algorithm parameters from a file storage.

Reimplemented from cv::Algorithm.

◆ save()

virtual void cv::Algorithm::save ( const String & filename ) const

virtualinherited

Saves the algorithm to a file.

In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

◆ setDescriptorChannels()

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

pure virtual

◆ setDescriptorSize()

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

pure virtual

◆ setDescriptorType()

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

pure virtual

◆ setDiffusivity()

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

pure virtual

◆ setNOctaveLayers()

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

pure virtual

◆ setNOctaves()

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

pure virtual

◆ setThreshold()

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

pure virtual

◆ write() [1/3]

void cv::Feature2D::write ( const String & fileName ) const

inherited

◆ write() [2/3]

virtual void cv::Feature2D::write ( FileStorage & fs ) const

virtualinherited

Stores algorithm parameters in a file storage.

Reimplemented from cv::Algorithm.

◆ write() [3/3]

void cv::Feature2D::write	(	const Ptr< FileStorage > &	fs,
		const String &	name = `String()`
	)		const

inlineinherited

References cv::Algorithm::write().

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◆ writeFormat()

void cv::Algorithm::writeFormat ( FileStorage & fs ) const

protectedinherited

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

opencv2/features2d.hpp

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Detailed Description

Member Enumeration Documentation

◆ DescriptorType

Member Function Documentation

◆ clear()

◆ compute() [1/2]

◆ compute() [2/2]

◆ create()

◆ defaultNorm()

◆ descriptorSize()

◆ descriptorType()

◆ detect() [1/2]

◆ detect() [2/2]

◆ detectAndCompute()

◆ empty()

◆ getDefaultName()

◆ getDescriptorChannels()

◆ getDescriptorSize()

◆ getDescriptorType()

◆ getDiffusivity()

◆ getNOctaveLayers()

◆ getNOctaves()

◆ getThreshold()

◆ load()

◆ loadFromString()

◆ read() [1/2]

◆ read() [2/2]

◆ save()

◆ setDescriptorChannels()

◆ setDescriptorSize()

◆ setDescriptorType()

◆ setDiffusivity()

◆ setNOctaveLayers()

◆ setNOctaves()

◆ setThreshold()

◆ write() [1/3]

◆ write() [2/3]

◆ write() [3/3]

◆ writeFormat()