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# Here we will just add a random Gaussian noise to our original image

noise_Gaussian = np.zeros((image.shape[0], image.shape[1]), dtype='uint8');

# Here a value of 64 is specified for a noise mean
# and 32 is specified for the standard deviation

cv2.randn(noise_Gaussian, 64, 32)


# Adding a very mild noise