guist

I also get a similar result with the original image: 

I tried following normalize functions: ``` def normalize(origin_img): origin_img = np.array(origin_img, dtype=np.float32) origin_img -= np.mean(origin_img) origin_img /= np.std(origin_img, ddof=1) return origin_img ``` and ``` def normalize(origin_img): origin_img = np.array(origin_img, dtype=np.float32)...