class_docstr: Evaluate semantic segmentation
class_docstr_tok: ["Evaluate","semantic","segmentation"]
code: def evaluate(self):
      metrics = [("All", None), ("Things", True), ("Stuff", False)]
      results = {}
      for name, isthing in metrics:
          results[name], per_class_results = self.pq_stat.pq_average(
              isthing=isthing, thing_list=self.thing_list
          )
          if name == "All":
              results["per_class"] = per_class_results
      return OrderedDict(pan_seg=results)
  
file_path: PaddleSeg/contrib/PanopticDeepLab/utils/evaluation/panoptic.py
imports: from collections import defaultdict, OrderedDict
  import numpy
label_desc: Use image node_id 3 for calling the PanopticEvaluator obj's underlying member method code with example usage: obj.evaluate() and returns: OrderedDict