OpenCV  3.3.1-dev
Open Source Computer Vision
Public Member Functions | List of all members
cv::Feature2D Class Reference

Abstract base class for 2D image feature detectors and descriptor extractors. More...

#include "features2d.hpp"

Inheritance diagram for cv::Feature2D:
cv::Algorithm cv::AgastFeatureDetector cv::AKAZE cv::BRISK cv::FastFeatureDetector cv::GFTTDetector cv::KAZE cv::MSER cv::ORB cv::SimpleBlobDetector cv::xfeatures2d::AffineFeature2D cv::xfeatures2d::BoostDesc cv::xfeatures2d::BriefDescriptorExtractor cv::xfeatures2d::DAISY cv::xfeatures2d::FREAK cv::xfeatures2d::HarrisLaplaceFeatureDetector cv::xfeatures2d::LATCH cv::xfeatures2d::LUCID cv::xfeatures2d::MSDDetector cv::xfeatures2d::SIFT cv::xfeatures2d::StarDetector cv::xfeatures2d::SURF cv::xfeatures2d::VGG

Public Member Functions

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). More...
 
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). 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
 Return true if detector object is empty. More...
 
virtual String getDefaultName () const
 
void read (const String &fileName)
 
virtual void read (const FileNode &)
 Reads algorithm parameters from a file storage. More...
 
void write (const String &fileName) const
 
virtual void write (FileStorage &) const
 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...
 

Additional Inherited Members

- 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...
 
- Protected Member Functions inherited from cv::Algorithm
void writeFormat (FileStorage &fs) const
 

Detailed Description

Abstract base class for 2D image feature detectors and descriptor extractors.

Constructor & Destructor Documentation

§ ~Feature2D()

virtual cv::Feature2D::~Feature2D ( )
virtual

Member Function Documentation

§ compute() [1/2]

virtual void cv::Feature2D::compute ( InputArray  image,
std::vector< KeyPoint > &  keypoints,
OutputArray  descriptors 
)
virtual
Python:
keypoints, descriptors=cv.Feature2D.compute(image, keypoints[, descriptors])
keypoints, descriptors=cv.Feature2D.compute(images, keypoints[, descriptors])

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.

Reimplemented in cv::xfeatures2d::VGG, and cv::xfeatures2d::DAISY.

§ compute() [2/2]

virtual void cv::Feature2D::compute ( InputArrayOfArrays  images,
std::vector< std::vector< KeyPoint > > &  keypoints,
OutputArrayOfArrays  descriptors 
)
virtual
Python:
keypoints, descriptors=cv.Feature2D.compute(image, keypoints[, descriptors])
keypoints, descriptors=cv.Feature2D.compute(images, keypoints[, descriptors])

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.

Reimplemented in cv::xfeatures2d::DAISY.

§ defaultNorm()

virtual int cv::Feature2D::defaultNorm ( ) const
virtual
Python:
retval=cv.Feature2D.defaultNorm()

§ descriptorSize()

virtual int cv::Feature2D::descriptorSize ( ) const
virtual
Python:
retval=cv.Feature2D.descriptorSize()

§ descriptorType()

virtual int cv::Feature2D::descriptorType ( ) const
virtual
Python:
retval=cv.Feature2D.descriptorType()

§ detect() [1/2]

virtual void cv::Feature2D::detect ( InputArray  image,
std::vector< KeyPoint > &  keypoints,
InputArray  mask = noArray() 
)
virtual
Python:
keypoints=cv.Feature2D.detect(image[, mask])
keypoints=cv.Feature2D.detect(images[, masks])

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() 
)
virtual
Python:
keypoints=cv.Feature2D.detect(image[, mask])
keypoints=cv.Feature2D.detect(images[, masks])

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 
)
virtual
Python:
keypoints, descriptors=cv.Feature2D.detectAndCompute(image, mask[, descriptors[, useProvidedKeypoints]])

Detects keypoints and computes the descriptors

§ empty()

virtual bool cv::Feature2D::empty ( ) const
virtual
Python:
retval=cv.Feature2D.empty()

Return true if detector object is empty.

Reimplemented from cv::Algorithm.

§ getDefaultName()

virtual String cv::Feature2D::getDefaultName ( ) const
virtual
Python:
retval=cv.Feature2D.getDefaultName()

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::Algorithm.

Reimplemented in cv::AKAZE, cv::KAZE, cv::SimpleBlobDetector, cv::GFTTDetector, cv::AgastFeatureDetector, cv::FastFeatureDetector, cv::MSER, cv::ORB, and cv::BRISK.

§ read() [1/2]

void cv::Feature2D::read ( const String fileName)
Python:
None=cv.Feature2D.read(fileName)
None=cv.Feature2D.read(arg1)

§ read() [2/2]

virtual void cv::Feature2D::read ( const FileNode fn)
virtual
Python:
None=cv.Feature2D.read(fileName)
None=cv.Feature2D.read(arg1)

Reads algorithm parameters from a file storage.

Reimplemented from cv::Algorithm.

§ write() [1/3]

void cv::Feature2D::write ( const String fileName) const
Python:
None=cv.Feature2D.write(fileName)
None=cv.Feature2D.write(fs[, name])

§ write() [2/3]

virtual void cv::Feature2D::write ( FileStorage fs) const
virtual
Python:
None=cv.Feature2D.write(fileName)
None=cv.Feature2D.write(fs[, name])

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
inline
Python:
None=cv.Feature2D.write(fileName)
None=cv.Feature2D.write(fs[, name])

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