def load_rcnn_image(image_name: str, size: Tuple = (320,320)) -> Tuple[ImageType, FloatTensor, Tuple[int, int]]:
    """this is the loading and processing for the input

    Args:
        image_name (str): the image or image name
        size (Tuple, optional): the size the image will be resized to.

    Returns:
        Tuple[ImageType, FloatTensor, Tuple[int, int]]: return the PIL image, pytorch image and the original image size
    """
    
    if isinstance(image_name, ImageType):
        image = image_name 
    elif isinstance(image_name, str):
        image = load_image_from_path(image_name, {})
    else:
        raise TypeError(f"received {type(image_name)} but expected a string or PIL image")

    original_size = image.size
    image = image.convert('RGB').resize(size)
    image_pt = transforms.ToTensor()(image)

    return image, image_pt,original_size
this is the loading and processing for the input

    Args:
        image_name (str): the image or image name
        size (Tuple, optional): the size the image will be resized to.

    Returns:
        Tuple[ImageType, FloatTensor, Tuple[int, int]]: return the PIL image, pytorch image and the original image size
    
src/marqo/s2_inference/processing/image_utils.py