| OpenCV 5.0.0alpha Open Source Computer Vision

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Classes | Functions
Structured forests for fast edge detection
Extended Image Processing

## 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< RFFeatureGetter > | cv::ximgproc::createRFFeatureGetter ()
Ptr< StructuredEdgeDetection > | cv::ximgproc::createStructuredEdgeDetection (const String &model, Ptr< const RFFeatureGetter > howToGetFeatures=Ptr< RFFeatureGetter >())

## Function Documentation

## ◆ createRFFeatureGetter()

Ptr< RFFeatureGetter > cv::ximgproc::createRFFeatureGetter | ( |  | ) |

Python:
| cv.ximgproc.createRFFeatureGetter( |  | ) -> | retval

`#include <opencv2/ximgproc/structured_edge_detection.hpp>`

## ◆ createStructuredEdgeDetection()

Ptr< StructuredEdgeDetection > cv::ximgproc::createStructuredEdgeDetection | ( | const String & | model,
|  | Ptr< const RFFeatureGetter > | howToGetFeatures = Ptr< RFFeatureGetter >() )

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