OpenCV  4.1.2-dev
Open Source Computer Vision
Public Member Functions | Static Public Member Functions | List of all members
cv::xfeatures2d::SURF Class Referenceabstract

Class for extracting Speeded Up Robust Features from an image [12] . More...

#include <opencv2/xfeatures2d/nonfree.hpp>

Inheritance diagram for cv::xfeatures2d::SURF:
cv::Feature2D cv::Algorithm

Public Member Functions

virtual bool getExtended () const =0
 
virtual double getHessianThreshold () const =0
 
virtual int getNOctaveLayers () const =0
 
virtual int getNOctaves () const =0
 
virtual bool getUpright () const =0
 
virtual void setExtended (bool extended)=0
 
virtual void setHessianThreshold (double hessianThreshold)=0
 
virtual void setNOctaveLayers (int nOctaveLayers)=0
 
virtual void setNOctaves (int nOctaves)=0
 
virtual void setUpright (bool upright)=0
 
- Public Member Functions inherited from cv::Feature2D
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 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< SURFcreate (double hessianThreshold=100, int nOctaves=4, int nOctaveLayers=3, bool extended=false, bool upright=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 for extracting Speeded Up Robust Features from an image [12] .

The algorithm parameters:

Member Function Documentation

§ create()

static Ptr<SURF> cv::xfeatures2d::SURF::create ( double  hessianThreshold = 100,
int  nOctaves = 4,
int  nOctaveLayers = 3,
bool  extended = false,
bool  upright = false 
)
static
Python:
retval=cv.xfeatures2d.SURF_create([, hessianThreshold[, nOctaves[, nOctaveLayers[, extended[, upright]]]]])
Parameters
hessianThresholdThreshold for hessian keypoint detector used in SURF.
nOctavesNumber of pyramid octaves the keypoint detector will use.
nOctaveLayersNumber of octave layers within each octave.
extendedExtended descriptor flag (true - use extended 128-element descriptors; false - use 64-element descriptors).
uprightUp-right or rotated features flag (true - do not compute orientation of features; false - compute orientation).

§ getExtended()

virtual bool cv::xfeatures2d::SURF::getExtended ( ) const
pure virtual
Python:
retval=cv.xfeatures2d_SURF.getExtended()

§ getHessianThreshold()

virtual double cv::xfeatures2d::SURF::getHessianThreshold ( ) const
pure virtual
Python:
retval=cv.xfeatures2d_SURF.getHessianThreshold()

§ getNOctaveLayers()

virtual int cv::xfeatures2d::SURF::getNOctaveLayers ( ) const
pure virtual
Python:
retval=cv.xfeatures2d_SURF.getNOctaveLayers()

§ getNOctaves()

virtual int cv::xfeatures2d::SURF::getNOctaves ( ) const
pure virtual
Python:
retval=cv.xfeatures2d_SURF.getNOctaves()

§ getUpright()

virtual bool cv::xfeatures2d::SURF::getUpright ( ) const
pure virtual
Python:
retval=cv.xfeatures2d_SURF.getUpright()

§ setExtended()

virtual void cv::xfeatures2d::SURF::setExtended ( bool  extended)
pure virtual
Python:
None=cv.xfeatures2d_SURF.setExtended(extended)

§ setHessianThreshold()

virtual void cv::xfeatures2d::SURF::setHessianThreshold ( double  hessianThreshold)
pure virtual
Python:
None=cv.xfeatures2d_SURF.setHessianThreshold(hessianThreshold)

§ setNOctaveLayers()

virtual void cv::xfeatures2d::SURF::setNOctaveLayers ( int  nOctaveLayers)
pure virtual
Python:
None=cv.xfeatures2d_SURF.setNOctaveLayers(nOctaveLayers)

§ setNOctaves()

virtual void cv::xfeatures2d::SURF::setNOctaves ( int  nOctaves)
pure virtual
Python:
None=cv.xfeatures2d_SURF.setNOctaves(nOctaves)

§ setUpright()

virtual void cv::xfeatures2d::SURF::setUpright ( bool  upright)
pure virtual
Python:
None=cv.xfeatures2d_SURF.setUpright(upright)

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