standardizer.py 文件源码

def __call__(self, img, is_training):
        if self.channel_wise:
            img_mean = img.mean(axis=(1, 2))
            img_std = img.std(axis=(1, 2))
            np.subtract(img, img_mean.reshape(3, 1, 1), out=img)
            np.divide(img, (img_std + 1e-4).reshape(3, 1, 1), out=img)
        else:
            img_mean = img.mean()
            img_std = img.std()
            np.subtract(img, img_mean, out=img)
            np.divide(img, img_std + 1e-4, out=img)

        np.clip(img, -self.clip, self.clip, out=img)
        return img