def __call__(self, head_out, rois, im_shape, scale_factor):
        """
        Decode the bbox and do NMS if needed.

        Args:
            head_out (tuple): bbox_pred and cls_prob of bbox_head output.
            rois (tuple): roi and rois_num of rpn_head output.
            im_shape (Tensor): The shape of the input image.
            scale_factor (Tensor): The scale factor of the input image.
            export_onnx (bool): whether export model to onnx
        Returns:
            bbox_pred (Tensor): The output prediction with shape [N, 6], including
                labels, scores and bboxes. The size of bboxes are corresponding
                to the input image, the bboxes may be used in other branch.
            bbox_num (Tensor): The number of prediction boxes of each batch with
                shape [1], and is N.
        """
        if self.nms is not None:
            bboxes, score = self.decode(head_out, rois, im_shape, scale_factor)
            bbox_pred, bbox_num, before_nms_indexes = self.nms(bboxes, score,
                                                               self.num_classes)

        else:
            bbox_pred, bbox_num = self.decode(head_out, rois, im_shape,
                                              scale_factor)

        if self.export_onnx:
            # add fake box after postprocess when exporting onnx 
            fake_bboxes = paddle.to_tensor(
                np.array(
                    [[0., 0.0, 0.0, 0.0, 1.0, 1.0]], dtype='float32'))

            bbox_pred = paddle.concat([bbox_pred, fake_bboxes])
            bbox_num = bbox_num + 1

        if self.nms is not None:
            return bbox_pred, bbox_num, before_nms_indexes
        else:
            return bbox_pred, bbox_num

        Decode the bbox and do NMS if needed.

        Args:
            head_out (tuple): bbox_pred and cls_prob of bbox_head output.
            rois (tuple): roi and rois_num of rpn_head output.
            im_shape (Tensor): The shape of the input image.
            scale_factor (Tensor): The scale factor of the input image.
            export_onnx (bool): whether export model to onnx
        Returns:
            bbox_pred (Tensor): The output prediction with shape [N, 6], including
                labels, scores and bboxes. The size of bboxes are corresponding
                to the input image, the bboxes may be used in other branch.
            bbox_num (Tensor): The number of prediction boxes of each batch with
                shape [1], and is N.
        
ppdet/modeling/post_process.py