class_docstr: This provides Inference Engine for pre-trained Hovernet segmentation + Classification model.
code: def writer(self, data, extension=None, dtype=None):
      writer = PolygonWriter(
          label=self.output_label_key, json=self.output_json_key
      )
      return writer(data)
  
file_path: MONAILabel/sample-apps/pathology/lib/infers/hovernet_nuclei.py
imports: import logging
  from typing import Any, Callable, Dict, Sequence
  import numpy
  from lib.transforms import LoadImagePatchd, PostFilterLabeld
  from monai.transforms import FromMetaTensord, LoadImaged, SaveImaged, SqueezeDimd
  from monailabel.interfaces.tasks.infer_v2 import InferType
  from monailabel.tasks.infer.bundle import BundleInferTask
  from monailabel.transform.post import FindContoursd, RenameKeyd
  from monailabel.transform.writer import PolygonWriter
label_desc: Use image node_id 5 for calling the HovernetNuclei obj's underlying member method code with example usage: obj.writer(data, extension, dtype) and returns: writer