def _transform_within_tags(text: str, scale_factor: float, tokenizer) -> List[int]:
    """
    Given a bounding box of the fashion <box>1, 2, 3, 4</box> | <point>1, 2</point> This function is responsible for
    converting 1, 2, 3, 4 into tokens of 1 2 3 4 without any commas.
    """
    # Convert the text into a list of strings.
    num_int_strs = text.split(",")
    if len(num_int_strs) == 2:
        # If there are any open or close tags, remove them.
        token_space_open_string = tokenizer.vocab[TOKEN_POINT_OPEN_STRING]
        token_space_close_string = tokenizer.vocab[TOKEN_POINT_CLOSE_STRING]
    else:
        token_space_open_string = tokenizer.vocab[TOKEN_BBOX_OPEN_STRING]
        token_space_close_string = tokenizer.vocab[TOKEN_BBOX_CLOSE_STRING]

    # Remove all spaces from num_ints
    num_ints = [float(num.strip()) for num in num_int_strs]
    # scale to transformed image siz
    if len(num_ints) == 2:
        num_ints_translated = scale_point_to_transformed_image(x=num_ints[0], y=num_ints[1], scale_factor=scale_factor)
    elif len(num_ints) == 4:
        num_ints_translated = scale_bbox_to_transformed_image(
            top=num_ints[0],
            left=num_ints[1],
            bottom=num_ints[2],
            right=num_ints[3],
            scale_factor=scale_factor,
        )
    else:
        raise ValueError(f"Invalid number of ints: {len(num_ints)}")
    # Tokenize the text, skipping the
    tokens = [tokenizer.vocab[str(num)] for num in num_ints_translated]
    return [token_space_open_string] + tokens + [token_space_close_string]

    Given a bounding box of the fashion <box>1, 2, 3, 4</box> | <point>1, 2</point> This function is responsible for
    converting 1, 2, 3, 4 into tokens of 1 2 3 4 without any commas.
    
dpkd/transformers/src/transformers/models/fuyu/processing_fuyu.py