code: def infer(self) -> Union[InferTask, Dict[str, InferTask]]:
      preload = strtobool(self.conf.get("preload", "false"))
      roi_size = json.loads(self.conf.get("roi_size", "[1024, 1024]"))
      logger.info(f"Using Preload: {preload}; ROI Size: {roi_size}")
  
      task: InferTask = lib.infers.SegmentationNuclei(
          path=self.path,
          network=self.network,
          labels=self.labels,
          preload=preload,
          roi_size=roi_size,
          config={
              "label_colors": self.label_colors,
              "max_workers": max(1, multiprocessing.cpu_count() // 2),
          },
      )
      return task
  
file_path: MONAILabel/sample-apps/pathology/lib/configs/segmentation_nuclei.py
imports: import json
  import logging
  import multiprocessing
  import os
  from typing import Any, Dict, Optional, Union
  import lib.infers
  import lib.trainers
  from monai.networks.nets import BasicUNet
  from monailabel.interfaces.config import TaskConfig
  from monailabel.interfaces.tasks.infer_v2 import InferTask
  from monailabel.interfaces.tasks.train import TrainTask
  from monailabel.utils.others.generic import download_file, strtobool
label_desc: Use image node_id 2 for calling the SegmentationNuclei obj's underlying member method code with example usage: obj.infer() and returns: task