OpenCV  3.3.1-dev
Open Source Computer Vision
Public Member Functions | Static Public Member Functions | List of all members
cv::GFTTDetector Class Referenceabstract

Wrapping class for feature detection using the goodFeaturesToTrack function. : More...

#include "features2d.hpp"

Inheritance diagram for cv::GFTTDetector:
cv::Feature2D cv::Algorithm

Public Member Functions

virtual int getBlockSize () const =0
 
virtual String getDefaultName () const
 
virtual bool getHarrisDetector () const =0
 
virtual double getK () const =0
 
virtual int getMaxFeatures () const =0
 
virtual double getMinDistance () const =0
 
virtual double getQualityLevel () const =0
 
virtual void setBlockSize (int blockSize)=0
 
virtual void setHarrisDetector (bool val)=0
 
virtual void setK (double k)=0
 
virtual void setMaxFeatures (int maxFeatures)=0
 
virtual void setMinDistance (double minDistance)=0
 
virtual void setQualityLevel (double qlevel)=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
 Return true if detector object is empty. More...
 
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...
 

Static Public Member Functions

static Ptr< GFTTDetectorcreate (int maxCorners=1000, double qualityLevel=0.01, double minDistance=1, int blockSize=3, bool useHarrisDetector=false, double k=0.04)
 
static Ptr< GFTTDetectorcreate (int maxCorners, double qualityLevel, double minDistance, int blockSize, int gradiantSize, bool useHarrisDetector=false, double k=0.04)
 
- 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

Wrapping class for feature detection using the goodFeaturesToTrack function. :

Member Function Documentation

§ create() [1/2]

static Ptr<GFTTDetector> cv::GFTTDetector::create ( int  maxCorners = 1000,
double  qualityLevel = 0.01,
double  minDistance = 1,
int  blockSize = 3,
bool  useHarrisDetector = false,
double  k = 0.04 
)
static
Python:
retval=cv.GFTTDetector_create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]])
retval=cv.GFTTDetector_create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]])

§ create() [2/2]

static Ptr<GFTTDetector> cv::GFTTDetector::create ( int  maxCorners,
double  qualityLevel,
double  minDistance,
int  blockSize,
int  gradiantSize,
bool  useHarrisDetector = false,
double  k = 0.04 
)
static
Python:
retval=cv.GFTTDetector_create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]])
retval=cv.GFTTDetector_create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]])

§ getBlockSize()

virtual int cv::GFTTDetector::getBlockSize ( ) const
pure virtual
Python:
retval=cv.GFTTDetector.getBlockSize()

§ getDefaultName()

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

§ getHarrisDetector()

virtual bool cv::GFTTDetector::getHarrisDetector ( ) const
pure virtual
Python:
retval=cv.GFTTDetector.getHarrisDetector()

§ getK()

virtual double cv::GFTTDetector::getK ( ) const
pure virtual
Python:
retval=cv.GFTTDetector.getK()

§ getMaxFeatures()

virtual int cv::GFTTDetector::getMaxFeatures ( ) const
pure virtual
Python:
retval=cv.GFTTDetector.getMaxFeatures()

§ getMinDistance()

virtual double cv::GFTTDetector::getMinDistance ( ) const
pure virtual
Python:
retval=cv.GFTTDetector.getMinDistance()

§ getQualityLevel()

virtual double cv::GFTTDetector::getQualityLevel ( ) const
pure virtual
Python:
retval=cv.GFTTDetector.getQualityLevel()

§ setBlockSize()

virtual void cv::GFTTDetector::setBlockSize ( int  blockSize)
pure virtual
Python:
None=cv.GFTTDetector.setBlockSize(blockSize)

§ setHarrisDetector()

virtual void cv::GFTTDetector::setHarrisDetector ( bool  val)
pure virtual
Python:
None=cv.GFTTDetector.setHarrisDetector(val)

§ setK()

virtual void cv::GFTTDetector::setK ( double  k)
pure virtual
Python:
None=cv.GFTTDetector.setK(k)

§ setMaxFeatures()

virtual void cv::GFTTDetector::setMaxFeatures ( int  maxFeatures)
pure virtual
Python:
None=cv.GFTTDetector.setMaxFeatures(maxFeatures)

§ setMinDistance()

virtual void cv::GFTTDetector::setMinDistance ( double  minDistance)
pure virtual
Python:
None=cv.GFTTDetector.setMinDistance(minDistance)

§ setQualityLevel()

virtual void cv::GFTTDetector::setQualityLevel ( double  qlevel)
pure virtual
Python:
None=cv.GFTTDetector.setQualityLevel(qlevel)

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