Class implementing DAISY descriptor, described in [247]. More...

#include <opencv2/xfeatures2d.hpp>

Inheritance diagram for cv::xfeatures2d::DAISY:

Public Types
enum	NormalizationType { NRM_NONE = 100, NRM_PARTIAL = 101, NRM_FULL = 102, NRM_SIFT = 103 }

Public Member Functions
virtual void	compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors) CV_OVERRIDE=0

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

virtual void	compute (InputArray image, Rect roi, OutputArray descriptors)=0

virtual void	compute (InputArray image, OutputArray descriptors)=0

virtual void	GetDescriptor (double y, double x, int orientation, float *descriptor) const =0

virtual bool	GetDescriptor (double y, double x, int orientation, float descriptor, double H) const =0

virtual void	GetUnnormalizedDescriptor (double y, double x, int orientation, float *descriptor) const =0

virtual bool	GetUnnormalizedDescriptor (double y, double x, int orientation, float descriptor, double H) const =0

Public Member Functions inherited from cv::Feature2D
virtual	~Feature2D ()

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...

virtual String	getDefaultName () const CV_OVERRIDE

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< DAISY >	create (float radius=15, int q_radius=3, int q_theta=8, int q_hist=8, DAISY::NormalizationType norm=DAISY::NRM_NONE, InputArray H=noArray(), bool interpolation=true, bool use_orientation=false)

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

Class implementing DAISY descriptor, described in [247].

Parameters

radius	radius of the descriptor at the initial scale
q_radius	amount of radial range division quantity
q_theta	amount of angular range division quantity
q_hist	amount of gradient orientations range division quantity
norm	choose descriptors normalization type, where DAISY::NRM_NONE will not do any normalization (default), DAISY::NRM_PARTIAL mean that histograms are normalized independently for L2 norm equal to 1.0, DAISY::NRM_FULL mean that descriptors are normalized for L2 norm equal to 1.0, DAISY::NRM_SIFT mean that descriptors are normalized for L2 norm equal to 1.0 but no individual one is bigger than 0.154 as in SIFT
H	optional 3x3 homography matrix used to warp the grid of daisy but sampling keypoints remains unwarped on image
interpolation	switch to disable interpolation for speed improvement at minor quality loss
use_orientation	sample patterns using keypoints orientation, disabled by default.

Member Enumeration Documentation

◆ NormalizationType

enum cv::xfeatures2d::DAISY::NormalizationType

Enumerator
NRM_NONE
NRM_PARTIAL
NRM_FULL
NRM_SIFT

Member Function Documentation

◆ compute() [1/4]

virtual void cv::xfeatures2d::DAISY::compute	(	InputArray	image,
		std::vector< KeyPoint > &	keypoints,
		OutputArray	descriptors
	)

pure virtual

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

Parameters

image	image to extract descriptors
keypoints	of interest within image
descriptors	resulted descriptors array

Reimplemented from cv::Feature2D.

◆ compute() [2/4]

virtual void cv::xfeatures2d::DAISY::compute	(	InputArrayOfArrays	images,
		std::vector< std::vector< KeyPoint > > &	keypoints,
		OutputArrayOfArrays	descriptors
	)

virtual

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.

Reimplemented from cv::Feature2D.

◆ compute() [3/4]

virtual void cv::xfeatures2d::DAISY::compute	(	InputArray	image,
		Rect	roi,
		OutputArray	descriptors
	)

pure virtual

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

Parameters

image	image to extract descriptors
roi	region of interest within image
descriptors	resulted descriptors array for roi image pixels

◆ compute() [4/4]

virtual void cv::xfeatures2d::DAISY::compute	(	InputArray	image,
		OutputArray	descriptors
	)

pure virtual

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

Parameters

image	image to extract descriptors
descriptors	resulted descriptors array for all image pixels

◆ create()

static Ptr<DAISY> cv::xfeatures2d::DAISY::create	(	float	radius = `15`,
		int	q_radius = `3`,
		int	q_theta = `8`,
		int	q_hist = `8`,
		DAISY::NormalizationType	norm = `DAISY::NRM_NONE`,
		InputArray	H = `noArray()`,
		bool	interpolation = `true`,
		bool	use_orientation = `false`
	)

static

Python:
	cv.xfeatures2d.DAISY_create(	[, radius[, q_radius[, q_theta[, q_hist[, norm[, H[, interpolation[, use_orientation]]]]]]]]	) ->	retval

◆ GetDescriptor() [1/2]

virtual void cv::xfeatures2d::DAISY::GetDescriptor	(	double	y,
		double	x,
		int	orientation,
		float *	descriptor
	)		const

pure virtual

Parameters

y	position y on image
x	position x on image
orientation	orientation on image (0->360)
descriptor	supplied array for descriptor storage

◆ GetDescriptor() [2/2]

virtual bool cv::xfeatures2d::DAISY::GetDescriptor	(	double	y,
		double	x,
		int	orientation,
		float *	descriptor,
		double *	H
	)		const

pure virtual

Parameters

y	position y on image
x	position x on image
orientation	orientation on image (0->360)
descriptor	supplied array for descriptor storage
H	homography matrix for warped grid

◆ GetUnnormalizedDescriptor() [1/2]

virtual void cv::xfeatures2d::DAISY::GetUnnormalizedDescriptor	(	double	y,
		double	x,
		int	orientation,
		float *	descriptor
	)		const

pure virtual

Parameters

y	position y on image
x	position x on image
orientation	orientation on image (0->360)
descriptor	supplied array for descriptor storage

◆ GetUnnormalizedDescriptor() [2/2]

virtual bool cv::xfeatures2d::DAISY::GetUnnormalizedDescriptor	(	double	y,
		double	x,
		int	orientation,
		float *	descriptor,
		double *	H
	)		const

pure virtual

Parameters

y	position y on image
x	position x on image
orientation	orientation on image (0->360)
descriptor	supplied array for descriptor storage
H	homography matrix for warped grid

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

opencv2/xfeatures2d.hpp

Public Types

Public Member Functions

Static Public Member Functions

Additional Inherited Members

Detailed Description

Member Enumeration Documentation

◆ NormalizationType

Member Function Documentation

◆ compute() [1/4]

◆ compute() [2/4]

◆ compute() [3/4]

◆ compute() [4/4]

◆ create()

◆ GetDescriptor() [1/2]

◆ GetDescriptor() [2/2]

◆ GetUnnormalizedDescriptor() [1/2]

◆ GetUnnormalizedDescriptor() [2/2]