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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def zoom_blur(x, severity=1):
 """Zoom blurring to images. Applying zoom blurring to images by zooming the central part of the 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 zoom blur. """

  c = [
      np.arange(1, 1.11, 0.01),
      np.arange(1, 1.16, 0.01),
      np.arange(1, 1.21, 0.02),
      np.arange(1, 1.26, 0.02),
      np.arange(1, 1.31, 0.03)
  ][severity - 1]
  x = (np.array(x) / 255.).astype(np.float32)
  out = np.zeros_like(x)
  for zoom_factor in c:
    out += clipped_zoom(x, zoom_factor)
  x = (x + out) / (len(c) + 1)
  x_clip = np.clip(x, 0, 1) * 255
  return around_and_astype(x_clip)