import tensorflow as tf


            self._score_summaries.update(self._proposal_targets)   #self._score_summaries.update(self._anchor_targets)  

            return rois, roi_scores

    def _anchor_component(self):
        with tf.variable_scope('ANCHOR_' + 'default'):
            # just to get the shape right
            # 根据原始输入图片通过VGG16的conv5_3后，缩小16倍，得到RPN的输入feature map大小
            height = tf.to_int32(tf.ceil(self._im_info[0, 0] / np.float32(self._feat_stride[0])))
            width = tf.to_int32(tf.ceil(self._im_info[0, 1] / np.float32(self._feat_stride[0])))

