code: def _normalize_bbox(
      original_coords: List[int], img_height: int, img_width: int
  ):
      """Converts from COCO to TFDS format."""
      if len(original_coords) != 4:
          raise ValueError(f"Malformed BBox: {original_coords}")
      # COCO format: [x_min, y_min, width, height] in absolute values.
      x_min, y_min, bbox_width, bbox_height = original_coords
      # TFDS format: [y_min, x_min, y_max, x_max] in normalized values.
      x_max = x_min + bbox_width
      y_max = y_min + bbox_height
      return np.array(
          [
              y_min / img_height,
              x_min / img_width,
              y_max / img_height,
              x_max / img_width,
          ]
      )
  
file_path: datasets/tensorflow_datasets/datasets/segment_anything/segment_anything_dataset_builder.py
imports: import csv
  import json
  from typing import Dict, List
  from etils import epath
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling a global function with example usage: _normalize_bbox(original_coords, img_height, img_width) and returns: np