code: def zoom_blur(x, severity=1):
    
    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)
docs: 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.