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      return scipy.ndimage.shift(

          self.Image, [height, width, 0], order=order, mode=mode)

  def gaussian_noise(self):

  def gaussian_noise(self, mean=0, std=25.5):

    '''Adds gaussian noise to the image

    Parameters:

      mean - mean of gaussian.

      std - standard deviation of gaussian.

        '''

    x = (self.Image - np.min(self.Image)) / (

        np.max(self.Image) - np.min(self.Image))

    x = x + np.random.normal(loc=0, scale=0.1, size=self.Image.shape)

    x[x > 1] = 1

    x = x * (np.max(self.Image) - np.min(self.Image)) + np.min(self.Image)

    x = self.Image

    x = x + np.random.normal(loc=mean, scale=std, size=self.Image.shape)

    return x

  def salt_pepper_noise(self, prob=0.05):

  def salt_pepper_noise(self, prob=0.05, salt=255, pepper=0):

    '''Adds salt and pepper noise to the image

    Parameters:

      prob - probability of the noise.

      salt - value of salt noise.

      pepper - value of pepper noise.

        '''

    x = (self.Image - np.min(self.Image)) / (

        np.max(self.Image) - np.min(self.Image))

    noise = np.random.random(size=self.Image.shape)

    x[noise < (prob / 2)] = 0

    x[noise > (1 - prob / 2)] = 1

    x = x * (np.max(self.Image) - np.min(self.Image)) + np.min(self.Image)

    x = self.Image

    x[noise < (prob / 2)] = pepper

    x[noise > (1 - prob / 2)] = salt

    return x