class_docstr: FCOSHead
  Args:
      num_classes (int): Number of classes
      fcos_feat (object): Instance of 'FCOSFeat'
      fpn_stride (list): The stride of each FPN Layer
      prior_prob (float): Used to set the bias init for the class prediction layer
      norm_reg_targets (bool): Normalization the regression target if true
      centerness_on_reg (bool): The prediction of centerness on regression or clssification branch
      num_shift (float): Relative offset between the center of the first shift and the top-left corner of img
      fcos_loss (object): Instance of 'FCOSLoss'
      nms (object): Instance of 'MultiClassNMS'
      trt (bool): Whether to use trt in nms of deploy
code: def post_process(self, fcos_head_outs, scale_factor):
      locations, cls_logits, bboxes_reg, centerness = fcos_head_outs
      pred_bboxes, pred_scores = [], []
  
      for pts, cls, reg, ctn in zip(
          locations, cls_logits, bboxes_reg, centerness
      ):
          scores, boxes = self._post_process_by_level(
              pts, cls, reg, ctn, self.sqrt_score
          )
          pred_scores.append(scores)
          pred_bboxes.append(boxes)
      pred_bboxes = paddle.concat(pred_bboxes, axis=1)
      pred_scores = paddle.concat(pred_scores, axis=1)
  
      # scale bbox to origin
      scale_y, scale_x = paddle.split(scale_factor, 2, axis=-1)
      scale_factor = paddle.concat(
          [scale_x, scale_y, scale_x, scale_y], axis=-1
      ).reshape([-1, 1, 4])
      pred_bboxes /= scale_factor
  
      pred_scores = pred_scores.transpose([0, 2, 1])
      bbox_pred, bbox_num, _ = self.nms(pred_bboxes, pred_scores)
      return bbox_pred, bbox_num
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.nn.initializer import Normal, Constant
  from ppdet.core.workspace import register
  from ppdet.modeling.layers import ConvNormLayer, MultiClassNMS
label_desc: Use image node_id 6 for calling the FCOSHead obj's underlying member method code with example usage: obj.post_process(fcos_head_outs, scale_factor) and returns: bbox_pred,  bbox_num