OpenCV  4.9.0
Open Source Computer Vision
Public Member Functions | List of all members
cv::GeneralizedHough Class Referenceabstract

finds arbitrary template in the grayscale image using Generalized Hough Transform More...

#include <opencv2/imgproc.hpp>

Inheritance diagram for cv::GeneralizedHough:
cv::Algorithm cv::GeneralizedHoughBallard cv::GeneralizedHoughGuil

Public Member Functions

virtual void detect (InputArray image, OutputArray positions, OutputArray votes=noArray())=0
 find template on image More...
 
virtual void detect (InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes=noArray())=0
 
virtual int getCannyHighThresh () const =0
 
virtual int getCannyLowThresh () const =0
 
virtual double getDp () const =0
 
virtual int getMaxBufferSize () const =0
 
virtual double getMinDist () const =0
 
virtual void setCannyHighThresh (int cannyHighThresh)=0
 Canny high threshold. More...
 
virtual void setCannyLowThresh (int cannyLowThresh)=0
 Canny low threshold. More...
 
virtual void setDp (double dp)=0
 Inverse ratio of the accumulator resolution to the image resolution. More...
 
virtual void setMaxBufferSize (int maxBufferSize)=0
 Maximal size of inner buffers. More...
 
virtual void setMinDist (double minDist)=0
 Minimum distance between the centers of the detected objects. More...
 
virtual void setTemplate (InputArray templ, Point templCenter=Point(-1, -1))=0
 set template to search More...
 
virtual void setTemplate (InputArray edges, InputArray dx, InputArray dy, Point templCenter=Point(-1, -1))=0
 
- Public Member Functions inherited from cv::Algorithm
 Algorithm ()
 
virtual ~Algorithm ()
 
virtual void clear ()
 Clears the algorithm state. More...
 
virtual bool empty () const
 Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
 
virtual String getDefaultName () const
 
virtual void read (const FileNode &fn)
 Reads algorithm parameters from a file storage. More...
 
virtual void save (const String &filename) const
 
virtual void write (FileStorage &fs) const
 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=String()) const
 

Additional Inherited Members

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

Detailed Description

finds arbitrary template in the grayscale image using Generalized Hough Transform

Member Function Documentation

◆ detect() [1/2]

virtual void cv::GeneralizedHough::detect ( InputArray  image,
OutputArray  positions,
OutputArray  votes = noArray() 
)
pure virtual
Python:
cv.GeneralizedHough.detect(image[, positions[, votes]]) -> positions, votes
cv.GeneralizedHough.detect(edges, dx, dy[, positions[, votes]]) -> positions, votes

find template on image

◆ detect() [2/2]

virtual void cv::GeneralizedHough::detect ( InputArray  edges,
InputArray  dx,
InputArray  dy,
OutputArray  positions,
OutputArray  votes = noArray() 
)
pure virtual
Python:
cv.GeneralizedHough.detect(image[, positions[, votes]]) -> positions, votes
cv.GeneralizedHough.detect(edges, dx, dy[, positions[, votes]]) -> positions, votes

◆ getCannyHighThresh()

virtual int cv::GeneralizedHough::getCannyHighThresh ( ) const
pure virtual
Python:
cv.GeneralizedHough.getCannyHighThresh() -> retval

◆ getCannyLowThresh()

virtual int cv::GeneralizedHough::getCannyLowThresh ( ) const
pure virtual
Python:
cv.GeneralizedHough.getCannyLowThresh() -> retval

◆ getDp()

virtual double cv::GeneralizedHough::getDp ( ) const
pure virtual
Python:
cv.GeneralizedHough.getDp() -> retval

◆ getMaxBufferSize()

virtual int cv::GeneralizedHough::getMaxBufferSize ( ) const
pure virtual
Python:
cv.GeneralizedHough.getMaxBufferSize() -> retval

◆ getMinDist()

virtual double cv::GeneralizedHough::getMinDist ( ) const
pure virtual
Python:
cv.GeneralizedHough.getMinDist() -> retval

◆ setCannyHighThresh()

virtual void cv::GeneralizedHough::setCannyHighThresh ( int  cannyHighThresh)
pure virtual
Python:
cv.GeneralizedHough.setCannyHighThresh(cannyHighThresh) -> None

Canny high threshold.

◆ setCannyLowThresh()

virtual void cv::GeneralizedHough::setCannyLowThresh ( int  cannyLowThresh)
pure virtual
Python:
cv.GeneralizedHough.setCannyLowThresh(cannyLowThresh) -> None

Canny low threshold.

◆ setDp()

virtual void cv::GeneralizedHough::setDp ( double  dp)
pure virtual
Python:
cv.GeneralizedHough.setDp(dp) -> None

Inverse ratio of the accumulator resolution to the image resolution.

◆ setMaxBufferSize()

virtual void cv::GeneralizedHough::setMaxBufferSize ( int  maxBufferSize)
pure virtual
Python:
cv.GeneralizedHough.setMaxBufferSize(maxBufferSize) -> None

Maximal size of inner buffers.

◆ setMinDist()

virtual void cv::GeneralizedHough::setMinDist ( double  minDist)
pure virtual
Python:
cv.GeneralizedHough.setMinDist(minDist) -> None

Minimum distance between the centers of the detected objects.

◆ setTemplate() [1/2]

virtual void cv::GeneralizedHough::setTemplate ( InputArray  templ,
Point  templCenter = Point(-1, -1) 
)
pure virtual
Python:
cv.GeneralizedHough.setTemplate(templ[, templCenter]) -> None
cv.GeneralizedHough.setTemplate(edges, dx, dy[, templCenter]) -> None

set template to search

◆ setTemplate() [2/2]

virtual void cv::GeneralizedHough::setTemplate ( InputArray  edges,
InputArray  dx,
InputArray  dy,
Point  templCenter = Point(-1, -1) 
)
pure virtual
Python:
cv.GeneralizedHough.setTemplate(templ[, templCenter]) -> None
cv.GeneralizedHough.setTemplate(edges, dx, dy[, templCenter]) -> None

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