code: def saturate(x, severity=1):
      """Increase saturation of images.
  
      Args:
        x: numpy array, uncorrupted image, assumed to have uint8 pixel in [0,255].
        severity: integer, severity of corruption.
  
      Returns:
        numpy array, image with uint8 pixels in [0,255]. Applied saturation.
      """
      c = [(0.3, 0), (0.1, 0), (2, 0), (5, 0.1), (20, 0.2)][
          severity - 1
      ]
  
      x = np.array(x) / 255.0
      x = tfds.core.lazy_imports.skimage.color.rgb2hsv(x)
      x[:, :, 1] = np.clip(x[:, :, 1] * c[0] + c[1], 0, 1)
      x = tfds.core.lazy_imports.skimage.color.hsv2rgb(x)
      x = np.clip(x, 0, 1) * 255
  
      return around_and_astype(x)
  
imports: import io
  import subprocess
  import tempfile
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 22 for calling a global function with example usage: saturate(x, severity) and returns: around_and_astype