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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 contrast(x, severity=1):
 """Change contrast 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]. Changed contrast. """

  c = [0.4, .3, .2, .1, .05][severity - 1]

  x = np.array(x) / 255.
  means = np.mean(x, axis=(0, 1), keepdims=True)
  x_clip = np.clip((x - means) * c + means, 0, 1) * 255
  return around_and_astype(x_clip)