import tensorflow.contrib.slim as slim

            bboxes = tf.stop_gradient(tf.concat([y1, x1, y2, x2], axis=1))
            # 'roi_pooling_size', 7
            pre_pool_size = cfg.FLAGS.roi_pooling_size * 2
            # 把rois对于的特征图上的部分crop出来，然后resize打破14*14的大小
            crops = tf.image.crop_and_resize(bottom, bboxes, tf.to_int32(batch_ids), [pre_pool_size, pre_pool_size], name="crops")

        return slim.max_pool2d(crops, [2, 2], padding='SAME')

    def _dropout_layer(self, bottom, name, ratio=0.5):
        return tf.nn.dropout(bottom, ratio, name=name)

    def _anchor_target_layer(self, rpn_cls_score, name):
