How do you convert the polygons from .json format to .mat file used in DOOBNet ? about instancelabeltool

[GuoxiaWang]

@MichaelRamamonjisoa
Yes, I have the code. If you need, I can push the code to the Repo. But the code in my disk, so I need to find out.

If you can not to wait, you can write the orientation conversion code by yourself according to the code atan formulas. For the edge image, you just need draw the polygons on a binary image.

Thank you for reading my paper, I hope my paper and label tool can help you!

[MichaelRamamonjisoa]

Thank you for your reply. I have indeed drawn boundaries as you said. However I did not try to export orientations, since I do not need it yet. I'd be glad if you could push your code to the Repo since I will probably use it for next work.

I have another request, which I can put in another issue if you want since it will probably require a specific commit.

[GuoxiaWang]

@MichaelRamamonjisoa

I have found the calculation code of orientations from my driven disk. Here is the code snippet, and I will don't push the code to the Repo:

def get_edge_and_ori_map(obj):

    imsize = (obj.imgHeight, obj.imgWidth)
    edge_map = np.zeros(imsize, dtype=np.uint8)
    ori_map = np.zeros(imsize, dtype=np.float32)

    for edge in obj.boundaries.polygon:
        npix = len(edge)
        for idx, pt in enumerate(edge):
            
            # First, we calculate orientation
            idx0 = max(idx-5, 0)
            pt0 = edge[idx0]
            idx1 = min(idx+5, npix-1)
            pt1 = edge[idx1]

            theta = math.atan2(pt1.y-pt0.y, pt1.x-pt0.x)
            ori_map[pt.y][pt.x] = theta
            edge_map[pt.y][pt.x] = 1

    return edge_map, ori_map

and you can invoke the function like this:

    from lib.annotation import *

    ann = Annotation()
    ann.fromJsonFile(json_file_name)
    edge_map, ori_map = get_edge_and_ori_map(ann)

    height, width = edge_map.shape
    label = np.zeros((1, 2, height, width), dtype=np.float32)
    label[0, 0, ...] = edge_map
    label[0, 1, ...] = ori_map

    with h5py.File(h5_filename, 'w') as f:
        f['label'] = label