car_stop_model.py 文件源码

def motion_tower(stage_status, image_features):
    with tf.variable_scope(stage_status):
        with tf.variable_scope('Ptrain'):
            if FLAGS.ss_bottleneck_arch:
                assert (FLAGS.early_split == False)
                image_features = slim.conv2d(image_features, FLAGS.city_num_classes, [1, 1], 1,
                                             normalizer_fn=None,
                                             activation_fn=None,
                                             biases_initializer=init_ops.zeros_initializer,
                                             padding='VALID',
                                             scope='segmentation_fc8',
                                             reuse=True if FLAGS.city_data else False)

                # reduce the dimensionality from the conv5 feature map
                with tf.variable_scope('motion_tower'):
                    # size 224/8 = 28
                    image_features = slim.conv2d(image_features, 64, [5, 5], 3, scope='motion1')
                    # size 9
                    image_features = slim.conv2d(image_features, 128, [5, 5], 3, scope='motion2')
                    # size 3
    return image_features