nexar_large_speed.py 文件源码

def decode_jpeg_original(self, image_buffer, scope=None):
        with tf.op_scope([image_buffer], scope, 'decode_jpeg'):
            # decode jpeg
            fn = lambda encoded: tf.image.decode_jpeg(encoded,
                                                      channels=3,
                                                      ratio=FLAGS.decode_downsample_factor)
            # TODO: change parallel iterations
            decoded = tf.map_fn(fn,
                                image_buffer,
                                dtype=tf.uint8,
                                parallel_iterations=1,
                                back_prop=False,
                                swap_memory=False,
                                infer_shape=True,
                                name="map_decode_jpeg")

            # move the float convertion to GPU, to save bandwidth
            # to float, to the range 0.0 - 255.0
            #images = tf.cast(decoded, dtype=tf.float32, name="image_to_float")
            decoded.set_shape([FLAGS.FRAMES_IN_SEG // FLAGS.temporal_downsample_factor,
                              FLAGS.IM_HEIGHT / FLAGS.decode_downsample_factor,
                              FLAGS.IM_WIDTH / FLAGS.decode_downsample_factor, 3])
            return decoded