code: def get_colormap() -> np.ndarray:
      """Loads the colormap.
  
      The colormap was precomputed using Glasbey et al. algorythm (Colour Displays
      for Categorical Images, 2017) to generate maximally distinct colors.
  
      It was generated using https://github.com/taketwo/glasbey:
  
      ```python
      gb = glasbey.Glasbey(
          base_palette=[(0, 0, 0), (228, 26, 28), (55, 126, 184), (77, 175, 74)],
          no_black=True,
      )
      palette = gb.generate_palette(size=256)
      gb.save_palette(palette, 'colormap.csv')
      ```
  
      Returns:
        colormap: A `np.array(shape=(255, 3), dtype=np.uint8)` representing the
          mapping id -> color.
      """
      colormap_path = (
          resource_utils.tfds_path() / "core/utils/colormap.csv"
      )
      with colormap_path.open() as f:
          return np.array(list(csv.reader(f)), dtype=np.uint8)
  
imports: from __future__ import annotations
  import csv
  import subprocess
  from typing import Any, List, Optional
  import numpy
  from tensorflow_datasets.core import lazy_imports_lib
  from tensorflow_datasets.core.utils import py_utils
  from tensorflow_datasets.core.utils import resource_utils
  from tensorflow_datasets.core.utils import tf_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 6 for calling a global function with example usage: get_colormap() and returns: np