[MSE]Mean square error #python

mse.py

def mse(imageA, imageB):
    # the 'Mean Squared Error' between the two images is the
    # sum of the squared difference between the two images;
    # NOTE: the two images must have the same dimension
    err = np.sum((imageA - imageB) ** 2)
    err /= float(imageA.shape[0] * imageA.shape[1])
    # return the MSE, the lower the error, the more "similar"
    # the two images are
    return err