class_docstr: CenterNet network, see http://arxiv.org/abs/1904.07850
  
  Args:
      backbone (object): backbone instance
      neck (object): FPN instance, default use 'CenterNetDLAFPN'
      head (object): 'CenterNetHead' instance
      post_process (object): 'CenterNetPostProcess' instance
      for_mot (bool): whether return other features used in tracking model
code: def get_pred(self):
      head_out = self._forward()
      (
          bbox,
          bbox_num,
          bbox_inds,
          topk_clses,
          topk_ys,
          topk_xs,
      ) = self.post_process(
          head_out["heatmap"],
          head_out["size"],
          head_out["offset"],
          im_shape=self.inputs["im_shape"],
          scale_factor=self.inputs["scale_factor"],
      )
  
      if self.for_mot:
          output = {
              "bbox": bbox,
              "bbox_num": bbox_num,
              "bbox_inds": bbox_inds,
              "topk_clses": topk_clses,
              "topk_ys": topk_ys,
              "topk_xs": topk_xs,
              "neck_feat": head_out["neck_feat"],
          }
      else:
          output = {"bbox": bbox, "bbox_num": bbox_num}
      return output
  
file_path: PaddleDetection/ppdet/modeling/architectures/centernet.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
label_desc: Use image node_id 4 for calling the CenterNet obj's underlying member method code with example usage: obj.get_pred() and returns: output