Training on a 3D dataset

[davidpagnon]

Hi everyone,
I would like to create a 3D dataset but I cannot find much about how to properly do it. Should I simply do something like described on this page, but with 'keypoints' being [x,y,z,v] instead of [x,y,v]? Is there anything else that could help me figure out how to train once the dataset is created?
Thanks in advance

'images': [
    {
        'file_name': '000000001268.jpg',
        'height': 427,
        'width': 640,
        'id': 1268
    },
    ...
],
'annotations': [
    {
        'segmentation': [[426.36,
            ...
            424.34,
            223.3]],
        'keypoints': [0,0,0,
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            0,0,0,
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            431,287,2,
            0,0,0,
            458,265,2,
            0,0,0,
            466,300,1],
        'num_keypoints': 10,
        'area': 3894.5826,
        'iscrowd': 0,
        'image_id': 1268,
        'bbox': [402.34, 205.02, 65.26, 88.45],
        'category_id': 1,
        'id': 215218
    },
    ...
],
'categories': [
    {'id': 1, 'name': 'person'},
 ]