OpenCV  4.10.0-pre
Open Source Computer Vision
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Classes | Functions
Structured forests for fast edge detection

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.

Classes

class  cv::ximgproc::RFFeatureGetter
 
class  cv::ximgproc::StructuredEdgeDetection
 Class implementing edge detection algorithm from [70] : More...
 

Functions

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

Function Documentation

◆ createRFFeatureGetter()

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

◆ createStructuredEdgeDetection()

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

#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