cv::Feature2D Class Reference 2D 特征框架


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

#include <opencv2/features2d.hpp>

Inheritance diagram for cv::Feature2D:
cv::Algorithm cv::AgastFeatureDetector cv::AKAZE cv::BRISK cv::cuda::Feature2DAsync 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). 更多...
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). 更多...
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. 更多...
virtual 字符串 getDefaultName () const CV_OVERRIDE
void read (const 字符串 &fileName)
virtual void read (const FileNode &) CV_OVERRIDE
Reads algorithm parameters from a file storage. 更多...
void write (const 字符串 &fileName) const
virtual void write ( FileStorage &) const CV_OVERRIDE
Stores algorithm parameters in a file storage. 更多...
void write (const Ptr < FileStorage > &fs, const 字符串 &name= 字符串 ()) const
- Public Member Functions inherited from cv::Algorithm
Algorithm ()
virtual ~Algorithm ()
virtual void clear ()
Clears the algorithm state. 更多...
virtual void save (const 字符串 &filename) const
void write (const Ptr < FileStorage > &fs, const 字符串 &name= 字符串 ()) 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. 更多...

额外继承成员

- Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr < _Tp > load (const 字符串 &filename, const 字符串 &objname= 字符串 ())
Loads algorithm from the file. 更多...
template<typename _Tp >
static Ptr < _Tp > loadFromString (const 字符串 &strModel, const 字符串 &objname= 字符串 ())
Loads algorithm from a String. 更多...
template<typename _Tp >
static Ptr < _Tp > read (const FileNode &fn)
Reads algorithm from the file node. 更多...
- Protected Member Functions inherited from cv::Algorithm
void writeFormat ( FileStorage &fs) const

详细描述

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

Constructor & Destructor Documentation

~Feature2D()

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

成员函数文档编制

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).

参数
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.

Reimplemented in 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.

参数
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 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).

参数
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 ()
)
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.

参数
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
)
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 字符串 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 ,和 cv::BRISK .

read() [1/2]

void cv::Feature2D::read ( const 字符串 & 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 字符串 & 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 字符串 & name = 字符串 ()
) 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: