Dataset_reader_ImageSeqGen.py 文件源码

def single_read(self):
        features = tf.parse_single_example(self.serialized_example, features=self._Feature_dict)
        image = tf.image.decode_image(features[self._Image_handle])
        image.set_shape(self.image_shape)
        image = tf.image.convert_image_dtype(image, tf.float32)
        image = image - self.mean_image
        #Alright we've got images, now to get seqs and masks
        complete_seq =  features[self._Seq_handle]
        complete_mask = features[self._Seq_mask]
        '''
        decoded_seq = self.get_seq(complete_seq)
        decoded_mask = self.get_seq(complete_mask)

        sequence_lenght = len(complete_seq)
        input_seq = decoded_seq[0:sequence_lenght-1]
        target_seq = decoded_seq[1:sequence_lenght]
        final_mask = decoded_mask[0:sequence_lenght-1]
        '''
        return image, complete_seq, complete_mask