def preprocess_image(self, image): padded_image = layers.get_padded_tensor(image, 32, 0.0) normed_image = (padded_image - np.array( self.cfg.img_mean, dtype=np.float32)[None, :, None, None]) / np.array( self.cfg.img_std, dtype=np.float32)[None, :, None, None] return normed_image
def preprocess_image(self, image): normed_image = (image - np.array( self.cfg.img_mean)[None, :, None, None]) / np.array( self.cfg.img_std)[None, :, None, None] return layers.get_padded_tensor(normed_image, 32, 0.0)