code: def clipped_zoom(img, zoom_factor):
      """Zoom image with clipping.
  
      Zoom the central part of the image and clip extra pixels.
  
      Args:
        img: numpy array, uncorrupted image.
        zoom_factor: numpy array, a sequence of float numbers for zoom factor.
  
      Returns:
        numpy array, zoomed image after clipping.
      """
      h = img.shape[0]
      ch = int(np.ceil(h / float(zoom_factor)))
      top_h = (h - ch) // 2
  
      w = img.shape[1]
      cw = int(np.ceil(w / float(zoom_factor)))
      top_w = (w - cw) // 2
  
      img = tfds.core.lazy_imports.scipy.ndimage.zoom(
          img[top_h : top_h + ch, top_w : top_w + cw],
          (zoom_factor, zoom_factor, 1),
          order=1,
      )
  
      # trim off any extra pixels
      trim_top_h = (img.shape[0] - h) // 2
      trim_top_w = (img.shape[1] - w) // 2
  
      return img[
          trim_top_h : trim_top_h + h, trim_top_w : trim_top_w + w
      ]
  
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 4 for calling a global function with example usage: clipped_zoom(img, zoom_factor) and returns: img