Model file for OpenCV's structured edge detector

Question

OpenCV implements StructuredEdgeDetection based on the random forest based approach outlined in "Structured Forests for Fast Edge Detection" (2013) by P. Dollár and C. Zitnick. The authors have published an implementation for Matlab and there's also one for Python, both of which also contain a pretrained model based on the BSDS500 dataset.

The OpenCV implementation seems to be lacking a pretrained model and I'm also unable to uncover what format the only constructor it offers expects:

Ptr<cv::StructuredEdgeDetection> createStructuredEdgeDetection(String model)
The only available constructor
Parameters: model – model file name

The documentation also doesn't outline how to train the OpenCV implementation, so I'm left quite in the dark.

To recap, how to use the OpenCV implementation? Is a trained model available? If not, how to train one using OpenCV?

Answer 1

You can use this model from opencv_extra ximgproc test data.

If you want to train your own model, you can follow instructions on OpenCV tutorials.

Image:

Edges:

Code:

#include <opencv2\opencv.hpp>
#include <opencv2\ximgproc.hpp>

using namespace cv;
using namespace cv::ximgproc;

int main()
{
    Ptr<StructuredEdgeDetection> pDollar = createStructuredEdgeDetection("path_to_model.yml.gz");

    Mat3b src = imread("path_to_image");

    Mat3f fsrc;
    src.convertTo(fsrc, CV_32F, 1.0 / 255.0);

    Mat1f edges;
    pDollar->detectEdges(fsrc, edges);

    imshow("Image", src);
    imshow("Edges", edges);
    waitKey();

    return 0;
}