def _adjust_bbox(img_shapes, bbox, ratio=1.1) -> List[int]:
    """
    Adapts bounding box coordinates so that they can be used by
    torchvision.transforms.functional.crop function.

    This also pads each bounding box according to the `ratio` parameter.

    :param img_shapes: a list of shapes, with each element in the format
        "[img.shape[0], img.shape[1]]".
    :param bbox: A list of elements in the format "[right, left, top, bottom]".
    :param ratio: The amount of padding. Defaults to "1.1".

    :returns: A list of adapted bounding box coordinates.
    """
    cw = bbox[0] - bbox[1]
    ch = bbox[2] - bbox[3]
    center = [int(bbox[1] + cw / 2), int(bbox[3] + ch / 2)]
    bbox = [
        min([int(center[0] + (cw * ratio / 2)), img_shapes[0]]),
        max([int(center[0] - (cw * ratio / 2)), 0]),
        min([int(center[1] + (ch * ratio / 2)), img_shapes[1]]),
        max([int(center[1] - (ch * ratio / 2)), 0]),
    ]
    return [bbox[3], bbox[1], bbox[2] - bbox[3], bbox[0] - bbox[1]]

    Adapts bounding box coordinates so that they can be used by
    torchvision.transforms.functional.crop function.

    This also pads each bounding box according to the `ratio` parameter.

    :param img_shapes: a list of shapes, with each element in the format
        "[img.shape[0], img.shape[1]]".
    :param bbox: A list of elements in the format "[right, left, top, bottom]".
    :param ratio: The amount of padding. Defaults to "1.1".

    :returns: A list of adapted bounding box coordinates.
    
avalanche/benchmarks/classic/stream51.py