code: def __init__(
      self, num_classes, thing_ids, label_divisor=1000, convert_id=None
  ):
      self.num_classes = num_classes
      self.all_ids = list(range(0, self.num_classes))
      self.thing_ids = list(thing_ids)
      self.label_divisor = label_divisor
      self.convert_id = convert_id
      if self.convert_id is not None:
          self.thing_ids = [
              self.convert_id(id_) for id_ in self.thing_ids
          ]
          self.all_ids = [self.convert_id(id_) for id_ in self.all_ids]
      self.pq_stat = PQStat(self.all_ids)
  
imports: from collections import defaultdict
  import numpy
  from paddlepanseg.cvlibs import build_info_dict
  from paddlepanseg.utils import decode_pan_id
  from .evaluator import Evaluator
label_desc: Use image node_id 1 to create a new PanSegEvaluator object from inherited base classes: Evaluator with example: obj = PanSegEvaluator(num_classes, thing_ids, label_divisor, convert_id)