OpenCV  3.4.20-dev
Open Source Computer Vision
Static Public Member Functions | List of all members
cv::xfeatures2d::HarrisLaplaceFeatureDetector Class Reference

Class implementing the Harris-Laplace feature detector as described in [157]. More...

#include <opencv2/xfeatures2d.hpp>

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

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. More...
 
- 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

- 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 (FileStorage &fs, const String &name) const
 
void write (const Ptr< FileStorage > &fs, const String &name) 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 (FileStorage &fs, const String &name) const
 
void write (const Ptr< FileStorage > &fs, const String &name=String()) const
 
- Protected Member Functions inherited from cv::Algorithm
void writeFormat (FileStorage &fs) const
 

Detailed Description

Class implementing the Harris-Laplace feature detector as described in [157].

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
Python:
cv.xfeatures2d.HarrisLaplaceFeatureDetector.create([, numOctaves[, corn_thresh[, DOG_thresh[, maxCorners[, num_layers]]]]]) -> retval
cv.xfeatures2d.HarrisLaplaceFeatureDetector_create([, numOctaves[, corn_thresh[, DOG_thresh[, maxCorners[, num_layers]]]]]) -> retval

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

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