OpenCV  4.5.1
Open Source Computer Vision
Public Member Functions | List of all members
cv::ximgproc::segmentation::SelectiveSearchSegmentation Class Referenceabstract

Selective search segmentation algorithm The class implements the algorithm described in [245]. More...

#include <opencv2/ximgproc/segmentation.hpp>

Inheritance diagram for cv::ximgproc::segmentation::SelectiveSearchSegmentation:
cv::Algorithm

Public Member Functions

virtual void addGraphSegmentation (Ptr< GraphSegmentation > g)=0
 Add a new graph segmentation in the list of graph segementations to process. More...
 
virtual void addImage (InputArray img)=0
 Add a new image in the list of images to process. More...
 
virtual void addStrategy (Ptr< SelectiveSearchSegmentationStrategy > s)=0
 Add a new strategy in the list of strategy to process. More...
 
virtual void clearGraphSegmentations ()=0
 Clear the list of graph segmentations to process;. More...
 
virtual void clearImages ()=0
 Clear the list of images to process. More...
 
virtual void clearStrategies ()=0
 Clear the list of strategy to process;. More...
 
virtual void process (std::vector< Rect > &rects)=0
 Based on all images, graph segmentations and stragies, computes all possible rects and return them. More...
 
virtual void setBaseImage (InputArray img)=0
 Set a image used by switch* functions to initialize the class. More...
 
virtual void switchToSelectiveSearchFast (int base_k=150, int inc_k=150, float sigma=0.8f)=0
 Initialize the class with the 'Selective search fast' parameters describled in [245]. More...
 
virtual void switchToSelectiveSearchQuality (int base_k=150, int inc_k=150, float sigma=0.8f)=0
 Initialize the class with the 'Selective search fast' parameters describled in [245]. More...
 
virtual void switchToSingleStrategy (int k=200, float sigma=0.8f)=0
 Initialize the class with the 'Single stragegy' parameters describled in [245]. More...
 
- 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 (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...
 

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

Selective search segmentation algorithm The class implements the algorithm described in [245].

Member Function Documentation

◆ addGraphSegmentation()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::addGraphSegmentation ( Ptr< GraphSegmentation g)
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.addGraphSegmentation(g)

Add a new graph segmentation in the list of graph segementations to process.

Parameters
gThe graph segmentation

◆ addImage()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::addImage ( InputArray  img)
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.addImage(img)

Add a new image in the list of images to process.

Parameters
imgThe image

◆ addStrategy()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::addStrategy ( Ptr< SelectiveSearchSegmentationStrategy s)
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.addStrategy(s)

Add a new strategy in the list of strategy to process.

Parameters
sThe strategy

◆ clearGraphSegmentations()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::clearGraphSegmentations ( )
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.clearGraphSegmentations()

Clear the list of graph segmentations to process;.

◆ clearImages()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::clearImages ( )
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.clearImages()

Clear the list of images to process.

◆ clearStrategies()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::clearStrategies ( )
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.clearStrategies()

Clear the list of strategy to process;.

◆ process()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::process ( std::vector< Rect > &  rects)
pure virtual
Python:
rects=cv.ximgproc_segmentation_SelectiveSearchSegmentation.process()

Based on all images, graph segmentations and stragies, computes all possible rects and return them.

Parameters
rectsThe list of rects. The first ones are more relevents than the lasts ones.

◆ setBaseImage()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::setBaseImage ( InputArray  img)
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.setBaseImage(img)

Set a image used by switch* functions to initialize the class.

Parameters
imgThe image

◆ switchToSelectiveSearchFast()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::switchToSelectiveSearchFast ( int  base_k = 150,
int  inc_k = 150,
float  sigma = 0.8f 
)
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.switchToSelectiveSearchFast([, base_k[, inc_k[, sigma]]])

Initialize the class with the 'Selective search fast' parameters describled in [245].

Parameters
base_kThe k parameter for the first graph segmentation
inc_kThe increment of the k parameter for all graph segmentations
sigmaThe sigma parameter for the graph segmentation

◆ switchToSelectiveSearchQuality()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::switchToSelectiveSearchQuality ( int  base_k = 150,
int  inc_k = 150,
float  sigma = 0.8f 
)
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.switchToSelectiveSearchQuality([, base_k[, inc_k[, sigma]]])

Initialize the class with the 'Selective search fast' parameters describled in [245].

Parameters
base_kThe k parameter for the first graph segmentation
inc_kThe increment of the k parameter for all graph segmentations
sigmaThe sigma parameter for the graph segmentation

◆ switchToSingleStrategy()

virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentation::switchToSingleStrategy ( int  k = 200,
float  sigma = 0.8f 
)
pure virtual
Python:
None=cv.ximgproc_segmentation_SelectiveSearchSegmentation.switchToSingleStrategy([, k[, sigma]])

Initialize the class with the 'Single stragegy' parameters describled in [245].

Parameters
kThe k parameter for the graph segmentation
sigmaThe sigma parameter for the graph segmentation

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