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AKAZE Class Reference
Public Types | Public Member Functions | Static Public Member Functions

AKAZE Class Reference
[Feature Detection and Description]

Class implementing the AKAZE keypoint detector and descriptor extractor, described in ANB13 . More...

#include <features2d.hpp>

Inherits cv::Feature2D.

Public Types

enum  { DESCRIPTOR_KAZE_UPRIGHT = 2 , DESCRIPTOR_MLDB_UPRIGHT = 4 }

Public Member Functions

virtual CV_WRAP void detect (InputArray image, CV_OUT 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())
 This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
virtual CV_WRAP void compute (InputArray image, CV_OUT CV_IN_OUT 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)
 This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
virtual CV_WRAP void detectAndCompute (InputArray image, InputArray mask, CV_OUT std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false)
 Detects keypoints and computes the descriptors.
virtual CV_WRAP bool empty () const
 Return true if detector object is empty.
virtual CV_WRAP void clear ()
 Clears the algorithm state.
virtual void write (FileStorage &fs) const
 Stores algorithm parameters in a file storage.
virtual void read (const FileNode &fn)
 Reads algorithm parameters from a file storage.
virtual CV_WRAP void save (const String &filename) const
 Saves the algorithm to a file.
virtual CV_WRAP String getDefaultName () const
 Returns the algorithm string identifier.

Static Public Member Functions

static CV_WRAP Ptr< AKAZE > create (int descriptor_type=AKAZE::DESCRIPTOR_MLDB, int descriptor_size=0, int descriptor_channels=3, float threshold=0.001f, int nOctaves=4, int nOctaveLayers=4, int diffusivity=KAZE::DIFF_PM_G2)
 The AKAZE constructor.
template<typename _Tp >
static Ptr< _Tp > read (const FileNode &fn)
 Reads algorithm from the file node.
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.

Detailed Description

Class implementing the AKAZE keypoint detector and descriptor extractor, described in ANB13 .

:

Note:
AKAZE descriptors can only be used with KAZE or AKAZE keypoints. Try to avoid using *extract* and *detect* instead of *operator()* due to performance reasons. .. [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.

Definition at line 643 of file features2d.hpp.

Member Enumeration Documentation

anonymous enum
Enumerator:
DESCRIPTOR_KAZE_UPRIGHT 

Upright descriptors, not invariant to rotation.

DESCRIPTOR_MLDB_UPRIGHT 

Upright descriptors, not invariant to rotation.

Definition at line 647 of file features2d.hpp.

Member Function Documentation

virtual CV_WRAP void clear (  ) [virtual, inherited]

Clears the algorithm state.

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 2984 of file core.hpp.

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

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.
virtual CV_WRAP void compute ( InputArray  image,
CV_OUT CV_IN_OUT std::vector< KeyPoint > &  keypoints,
OutputArray  descriptors 
) [virtual, inherited]

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.
static CV_WRAP Ptr<AKAZE> create ( int  descriptor_type = AKAZE::DESCRIPTOR_MLDB,
int  descriptor_size = 0,
int  descriptor_channels = 3,
float  threshold = 0.001f,
int  nOctaves = 4,
int  nOctaveLayers = 4,
int  diffusivity = KAZE::DIFF_PM_G2 
) [static]

The AKAZE constructor.

Parameters:
descriptor_typeType of the extracted descriptor: DESCRIPTOR_KAZE, DESCRIPTOR_KAZE_UPRIGHT, DESCRIPTOR_MLDB or DESCRIPTOR_MLDB_UPRIGHT.
descriptor_sizeSize of the descriptor in bits. 0 -> Full size
descriptor_channelsNumber of channels in the descriptor (1, 2, 3)
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
virtual CV_WRAP void detect ( InputArray  image,
CV_OUT std::vector< KeyPoint > &  keypoints,
InputArray  mask = noArray() 
) [virtual, inherited]

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.
virtual void detect ( InputArrayOfArrays  images,
std::vector< std::vector< KeyPoint > > &  keypoints,
InputArrayOfArrays  masks = noArray() 
) [virtual, inherited]

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].
virtual CV_WRAP void detectAndCompute ( InputArray  image,
InputArray  mask,
CV_OUT std::vector< KeyPoint > &  keypoints,
OutputArray  descriptors,
bool  useProvidedKeypoints = false 
) [virtual, inherited]

Detects keypoints and computes the descriptors.

virtual CV_WRAP bool empty (  ) const [virtual, inherited]

Return true if detector object is empty.

Reimplemented from Algorithm.

virtual CV_WRAP String getDefaultName (  ) const [virtual, inherited]

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.

static Ptr<_Tp> load ( const String &  filename,
const String &  objname = String() 
) [static, inherited]

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).

Definition at line 3027 of file core.hpp.

static Ptr<_Tp> loadFromString ( const String &  strModel,
const String &  objname = String() 
) [static, inherited]

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);

Definition at line 3046 of file core.hpp.

static Ptr<_Tp> read ( const FileNode &  fn ) [static, inherited]

Reads algorithm from the file node.

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

     Ptr<SVM> svm = Algorithm::read<SVM>(fn);

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn) and also have static create() method without parameters (or with all the optional parameters)

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 3008 of file core.hpp.

virtual void read ( const FileNode &  fn ) [virtual, inherited]

Reads algorithm parameters from a file storage.

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 2992 of file core.hpp.

virtual CV_WRAP void save ( const String &  filename ) const [virtual, inherited]

Saves the algorithm to a file.

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

virtual void write ( FileStorage &  fs ) const [virtual, inherited]

Stores algorithm parameters in a file storage.

Reimplemented in DescriptorMatcher, and FlannBasedMatcher.

Definition at line 2988 of file core.hpp.

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