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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 defocus_blur(x, severity=1):
 """Defocus blurring to images. Apply defocus blurring to images using Gaussian kernel. 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 defocus blur. """

  c = [(3, 0.1), (4, 0.5), (6, 0.5), (8, 0.5), (10, 0.5)][severity - 1]
  x = np.array(x) / 255.
  kernel = disk(radius=c[0], alias_blur=c[1])
  channels = []
  for d in range(3):
    channels.append(tfds.core.lazy_imports.cv2.filter2D(x[:, :, d], -1, kernel))
  channels = np.array(channels).transpose((1, 2, 0))  # 3x224x224 -> 224x224x3
  x_clip = np.clip(channels, 0, 1) * 255
  return around_and_astype(x_clip)