Loading...
Searching...
No Matches

Class implementing the Harris-Laplace feature detector as described in [Mikolajczyk2004]. More...

#include <opencv2/xfeatures2d.hpp>

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

Public Member Functions

virtual float getCornThresh () const =0
 
String getDefaultName () const CV_OVERRIDE
 
virtual float getDOGThresh () const =0
 
virtual int getMaxCorners () const =0
 
virtual int getNumLayers () const =0
 
virtual int getNumOctaves () const =0
 
virtual void setCornThresh (float corn_thresh_)=0
 
virtual void setDOGThresh (float DOG_thresh_)=0
 
virtual void setMaxCorners (int maxCorners_)=0
 
virtual void setNumLayers (int num_layers_)=0
 
virtual void setNumOctaves (int numOctaves_)=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).
 
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).
 
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.
 
virtual String getDefaultName () const CV_OVERRIDE
 
virtual void read (const FileNode &) CV_OVERRIDE
 Reads algorithm parameters from a file storage.
 
void read (const String &fileName)
 
void write (const Ptr< FileStorage > &fs, const String &name) const
 
void write (const String &fileName) const
 
virtual void write (FileStorage &) const CV_OVERRIDE
 Stores algorithm parameters in a file storage.
 
void write (FileStorage &fs, const String &name) const
 
- Public Member Functions inherited from cv::Algorithm
 Algorithm ()
 
virtual ~Algorithm ()
 
virtual void clear ()
 Clears the algorithm state.
 
virtual bool empty () const
 Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
 
virtual String getDefaultName () const
 
virtual void read (const FileNode &fn)
 Reads algorithm parameters from a file storage.
 
virtual void save (const String &filename) const
 
void write (const Ptr< FileStorage > &fs, const String &name=String()) const
 
virtual void write (FileStorage &fs) const
 Stores algorithm parameters in a file storage.
 
void write (FileStorage &fs, const String &name) const
 

Static Public Member Functions

static Ptr< HarrisLaplaceFeatureDetectorcreate (int numOctaves=6, float corn_thresh=0.01f, float DOG_thresh=0.01f, int maxCorners=5000, int num_layers=4)
 Creates a new implementation instance.
 
- Static Public Member Functions inherited from cv::Algorithm
template<typename _Tp >
static Ptr< _Tpload (const String &filename, const String &objname=String())
 Loads algorithm from the file.
 
template<typename _Tp >
static Ptr< _TploadFromString (const String &strModel, const String &objname=String())
 Loads algorithm from a String.
 
template<typename _Tp >
static Ptr< _Tpread (const FileNode &fn)
 Reads algorithm from the file node.
 

Additional Inherited Members

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

Detailed Description

Class implementing the Harris-Laplace feature detector as described in [Mikolajczyk2004].

Member Function Documentation

◆ create()

static Ptr< HarrisLaplaceFeatureDetector > cv::xfeatures2d::HarrisLaplaceFeatureDetector::create ( int  numOctaves = 6,
float  corn_thresh = 0.01f,
float  DOG_thresh = 0.01f,
int  maxCorners = 5000,
int  num_layers = 4 
)
static

Creates a new implementation instance.

Parameters
numOctavesthe number of octaves in the scale-space pyramid
corn_threshthe threshold for the Harris cornerness measure
DOG_threshthe threshold for the Difference-of-Gaussians scale selection
maxCornersthe maximum number of corners to consider
num_layersthe number of intermediate scales per octave

◆ getCornThresh()

virtual float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getCornThresh ( ) const
pure virtual

◆ getDefaultName()

String cv::xfeatures2d::HarrisLaplaceFeatureDetector::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.

◆ getDOGThresh()

virtual float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getDOGThresh ( ) const
pure virtual

◆ getMaxCorners()

virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getMaxCorners ( ) const
pure virtual

◆ getNumLayers()

virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumLayers ( ) const
pure virtual

◆ getNumOctaves()

virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumOctaves ( ) const
pure virtual

◆ setCornThresh()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setCornThresh ( float  corn_thresh_)
pure virtual

◆ setDOGThresh()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setDOGThresh ( float  DOG_thresh_)
pure virtual

◆ setMaxCorners()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setMaxCorners ( int  maxCorners_)
pure virtual

◆ setNumLayers()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumLayers ( int  num_layers_)
pure virtual

◆ setNumOctaves()

virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumOctaves ( int  numOctaves_)
pure virtual

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