code: def normalize_box(box, width, height):
      return [
          int(1000 * (box[0] / width)),
          int(1000 * (box[1] / height)),
          int(1000 * (box[2] / width)),
          int(1000 * (box[3] / height)),
      ]
  
file_path: transformers/src/transformers/models/layoutlmv2/image_processing_layoutlmv2.py
imports: from typing import Dict, Optional, Union
  import numpy
  from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
  from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
  from ...image_utils import ChannelDimension, ImageInput, PILImageResampling, infer_channel_dimension_format, make_list_of_images, to_numpy_array, valid_images
  from ...utils import TensorType, is_pytesseract_available, is_vision_available, logging, requires_backends
label_desc: Use image node_id 1 for calling a global function with example usage: normalize_box(box, width, height) and returns: list