class_docstr: SOLOv2 network, see https://arxiv.org/abs/2003.10152
  
  Args:
      backbone (object): an backbone instance
      solov2_head (object): an `SOLOv2Head` instance
      mask_head (object): an `SOLOv2MaskHead` instance
      neck (object): neck of network, such as feature pyramid network instance
class_docstr_tok: ["SOLOv2","network",",","see","https",":","\/\/arxiv.org\/abs\/2003.10152","Args",":","backbone","(","object",")",":","an","backbone","instance","solov2_head","(","object",")",":","an","`","SOLOv2Head","`","instance","mask_head","(","object",")",":","an","`","SOLOv2MaskHead","`","instance","neck","(","object",")",":","neck","of","network",",","such","as","feature","pyramid","network","instance"]
code: def get_pred(self):
      (
          seg_masks,
          cate_labels,
          cate_scores,
          bbox_num,
      ) = self.solov2_head.get_prediction(
          self.cate_pred_list,
          self.kernel_pred_list,
          self.seg_pred,
          self.inputs["im_shape"],
          self.inputs["scale_factor"],
      )
      outs = {
          "segm": seg_masks,
          "bbox_num": bbox_num,
          "cate_label": cate_labels,
          "cate_score": cate_scores,
      }
      return outs
  
file_path: PaddleDetection/ppdet/modeling/architectures/solov2.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
label_desc: Use image node_id 5 for calling the SOLOv2 obj's underlying member method code with example usage: obj.get_pred() and returns: outs