nexar_large_speed.py 文件源码

def decode_png(self, image_buffer, scope=None):
        with tf.op_scope([image_buffer], scope, 'decode_png'):
            # decode PNG
            fn = lambda encoded: tf.image.decode_png(encoded,
                                                      channels=1)

            decoded = tf.map_fn(fn,
                                image_buffer,
                                dtype=tf.uint8,
                                parallel_iterations=10,
                                back_prop=False,
                                swap_memory=False,
                                infer_shape=True,
                                name="map_decode_png")

            # to float, to the range 0.0 - 255.0
            images = tf.cast(decoded, dtype=tf.int32, name="image_to_float")
            tf.image.resize_nearest_neighbor(images, [FLAGS.IM_HEIGHT, FLAGS.IM_WIDTH], align_corners=None, name=None)
            images.set_shape([FLAGS.FRAMES_IN_SEG // FLAGS.temporal_downsample_factor,
                              FLAGS.IM_HEIGHT / FLAGS.decode_downsample_factor,
                              FLAGS.IM_WIDTH / FLAGS.decode_downsample_factor, 1])
            return images