I need help with OpenCV implementation of StructuredEdgeDetection based on the random forest based approach. I'm using [official demo](https://github.com/opencv/opencv_contrib/blob/96ea9a0d8a2dee4ec97ebdec8f79f3c8a24de3b0/modules/ximgproc/samples/edgeboxes_demo.py) and getting error on line 22 `ValueError: too many values to unpack`.

Here is python script:

```
import cv2 as cv
import numpy as np
import sys

if __name__ == '__main__':
    model = './model.yml'
    im = cv.imread('./L8C5M.png')

    edge_detection = cv.ximgproc.createStructuredEdgeDetection(model)
    rgb_im = cv.cvtColor(im, cv.COLOR_BGR2RGB)
    edges = edge_detection.detectEdges(np.float32(rgb_im) / 255.0)

    orimap = edge_detection.computeOrientation(edges)
    edges = edge_detection.edgesNms(edges, orimap)

    edge_boxes = cv.ximgproc.createEdgeBoxes()
    edge_boxes.setMaxBoxes(30)
    boxes = edge_boxes.getBoundingBoxes(edges, orimap)

    print(boxes)
    for b in boxes:
        x, y, w, h = b
        cv.rectangle(im, (x, y), (x+w, y+h), (0, 255, 0), 1, cv.LINE_AA)

    cv.imshow("edges", edges)
    cv.imshow("edgeboxes", im)
    cv.waitKey(0)
    cv.destroyAllWindows()

```

I'm expecting result like this [solution](https://stackoverflow.com/questions/54843550/edge-box-detection-using-opencv-python)