code: def init(
      self,
      name: str,
      model_dir: str,
      conf: Dict[str, str],
      planner: Any,
      **kwargs,
  ):
      super().init(name, model_dir, conf, planner, **kwargs)
  
      # Labels
      self.labels = {
          "Neoplastic cells": 1,
          "Inflammatory": 2,
          "Connective/Soft tissue cells": 3,
          "Dead Cells": 4,
          "Epithelial": 5,
      }
      self.label_colors = {
          "Neoplastic cells": (255, 0, 0),
          "Inflammatory": (255, 255, 0),
          "Connective/Soft tissue cells": (0, 255, 0),
          "Dead Cells": (0, 0, 0),
          "Epithelial": (0, 0, 255),
      }
  
      consep = strtobool(self.conf.get("consep", "true"))
      if consep:
          self.labels = {
              "Other": 1,
              "Inflammatory": 2,
              "Epithelial": 3,
              "Spindle-Shaped": 4,
          }
          self.label_colors = {
              "Other": (255, 0, 0),
              "Inflammatory": (255, 255, 0),
              "Epithelial": (0, 0, 255),
              "Spindle-Shaped": (0, 255, 0),
          }
  
      # Model Files
      self.path = [
          os.path.join(
              self.model_dir,
              f"pretrained_{name}{'_consep' if consep else ''}.pt",
          ),  # pretrained
          os.path.join(
              self.model_dir, f"{name}{'_consep' if consep else ''}.pt"
          ),  # published
      ]
  
      # Download PreTrained Model
      if strtobool(self.conf.get("use_pretrained_model", "true")):
          url = f"{self.conf.get('pretrained_path', self.PRE_TRAINED_PATH)}"
          url = f"{url}/pathology_segmentation_bunet_nuclei{'_consep' if consep else ''}.pt"
          download_file(url, self.path[0])
  
      # Network
      self.network = BasicUNet(
          spatial_dims=2,
          in_channels=3,
          out_channels=len(self.labels) + 1,
          features=(32, 64, 128, 256, 512, 32),
      )
  
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 1 for calling the SegmentationNuclei obj's underlying member method code with example usage: obj.init(name, model_dir, conf, planner) without return types