def resize()

in training/dataset/transforms.py [0:0]

• 37 lines of code
• 10 McCabe index (conditional complexity)

def resize(datapoint, index, size, max_size=None, square=False, v2=False):
    # size can be min_size (scalar) or (w, h) tuple

    def get_size(image_size, size, max_size=None):
        if isinstance(size, (list, tuple)):
            return size[::-1]
        else:
            return get_size_with_aspect_ratio(image_size, size, max_size)

    if square:
        size = size, size
    else:
        cur_size = (
            datapoint.frames[index].data.size()[-2:][::-1]
            if v2
            else datapoint.frames[index].data.size
        )
        size = get_size(cur_size, size, max_size)

    old_size = (
        datapoint.frames[index].data.size()[-2:][::-1]
        if v2
        else datapoint.frames[index].data.size
    )
    if v2:
        datapoint.frames[index].data = Fv2.resize(
            datapoint.frames[index].data, size, antialias=True
        )
    else:
        datapoint.frames[index].data = F.resize(datapoint.frames[index].data, size)

    new_size = (
        datapoint.frames[index].data.size()[-2:][::-1]
        if v2
        else datapoint.frames[index].data.size
    )

    for obj in datapoint.frames[index].objects:
        if obj.segment is not None:
            obj.segment = F.resize(obj.segment[None, None], size).squeeze()

    h, w = size
    datapoint.frames[index].size = (h, w)
    return datapoint