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cv::KAZE Class Referenceabstract

Class implementing the KAZE keypoint detector and descriptor extractor, described in [2] . More...

#include <opencv2/features2d.hpp>

Inheritance diagram for cv::KAZE:
Collaboration diagram for cv::KAZE:

Public Types

enum  DiffusivityType {
  DIFF_PM_G1 = 0,
  DIFF_PM_G2 = 1,
  DIFF_WEICKERT = 2,
  DIFF_CHARBONNIER = 3
}
 

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 KAZE::DiffusivityType getDiffusivity () const =0
 
virtual bool getExtended () const =0
 
virtual int getNOctaveLayers () const =0
 
virtual int getNOctaves () const =0
 
virtual double getThreshold () const =0
 
virtual bool getUpright () 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 setDiffusivity (KAZE::DiffusivityType diff)=0
 
virtual void setExtended (bool extended)=0
 
virtual void setNOctaveLayers (int octaveLayers)=0
 
virtual void setNOctaves (int octaves)=0
 
virtual void setThreshold (double threshold)=0
 
virtual void setUpright (bool upright)=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< KAZEcreate (bool extended=false, bool upright=false, float threshold=0.001f, int nOctaves=4, int nOctaveLayers=4, KAZE::DiffusivityType diffusivity=KAZE::DIFF_PM_G2)
 The KAZE 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 KAZE keypoint detector and descriptor extractor, described in [2] .

Note
AKAZE descriptor can only be used with KAZE or AKAZE keypoints .. [ABD12] KAZE Features. Pablo F. Alcantarilla, Adrien Bartoli and Andrew J. Davison. In European Conference on Computer Vision (ECCV), Fiorenze, Italy, October 2012.

Member Enumeration Documentation

◆ DiffusivityType

Enumerator
DIFF_PM_G1 
DIFF_PM_G2 
DIFF_WEICKERT 
DIFF_CHARBONNIER 

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
imageImage.
keypointsInput 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).
descriptorsComputed 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
imagesImage set.
keypointsInput 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).
descriptorsComputed 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<KAZE> cv::KAZE::create ( bool  extended = false,
bool  upright = false,
float  threshold = 0.001f,
int  nOctaves = 4,
int  nOctaveLayers = 4,
KAZE::DiffusivityType  diffusivity = KAZE::DIFF_PM_G2 
)
static

The KAZE constructor.

Parameters
extendedSet to enable extraction of extended (128-byte) descriptor.
uprightSet to enable use of upright descriptors (non rotation-invariant).
thresholdDetector response threshold to accept point
nOctavesMaximum octave evolution of the image
nOctaveLayersDefault number of sublevels per scale level
diffusivityDiffusivity 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
imageImage.
keypointsThe detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .
maskMask 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
imagesImage set.
keypointsThe detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .
masksMasks 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::KAZE::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.

◆ getDiffusivity()

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

◆ getExtended()

virtual bool cv::KAZE::getExtended ( ) const
pure virtual

◆ getNOctaveLayers()

virtual int cv::KAZE::getNOctaveLayers ( ) const
pure virtual

◆ getNOctaves()

virtual int cv::KAZE::getNOctaves ( ) const
pure virtual

◆ getThreshold()

virtual double cv::KAZE::getThreshold ( ) const
pure virtual

◆ getUpright()

virtual bool cv::KAZE::getUpright ( ) 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
filenameName of the file to read.
objnameThe 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
strModelThe string variable containing the model you want to load.
objnameThe 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).

◆ setDiffusivity()

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

◆ setExtended()

virtual void cv::KAZE::setExtended ( bool  extended)
pure virtual

◆ setNOctaveLayers()

virtual void cv::KAZE::setNOctaveLayers ( int  octaveLayers)
pure virtual

◆ setNOctaves()

virtual void cv::KAZE::setNOctaves ( int  octaves)
pure virtual

◆ setThreshold()

virtual void cv::KAZE::setThreshold ( double  threshold)
pure virtual

◆ setUpright()

virtual void cv::KAZE::setUpright ( bool  upright)
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: