OpenCV  4.4.0-pre
Open Source Computer Vision
Classes | Functions
Structured forests for fast edge detection

Classes

class  cv::ximgproc::RFFeatureGetter
 
class  cv::ximgproc::StructuredEdgeDetection
 Class implementing edge detection algorithm from [52] : More...
 

Functions

Ptr< RFFeatureGettercv::ximgproc::createRFFeatureGetter ()
 
Ptr< StructuredEdgeDetectioncv::ximgproc::createStructuredEdgeDetection (const String &model, Ptr< const RFFeatureGetter > howToGetFeatures=Ptr< RFFeatureGetter >())
 

Detailed Description

This module contains implementations of modern structured edge detection algorithms, i.e. algorithms which somehow takes into account pixel affinities in natural images.

Function Documentation

◆ createRFFeatureGetter()

Ptr<RFFeatureGetter> cv::ximgproc::createRFFeatureGetter ( )
Python:
retval=cv.ximgproc.createRFFeatureGetter()

◆ createStructuredEdgeDetection()

Ptr<StructuredEdgeDetection> cv::ximgproc::createStructuredEdgeDetection ( const String model,
Ptr< const RFFeatureGetter howToGetFeatures = PtrRFFeatureGetter >() 
)
Python:
retval=cv.ximgproc.createStructuredEdgeDetection(model[, howToGetFeatures])

#include <opencv2/ximgproc/structured_edge_detection.hpp>

The only constructor

Parameters
model: name of the file where the model is stored
howToGetFeatures: optional object inheriting from RFFeatureGetter. You need it only if you would like to train your own forest, pass NULL otherwise