class_docstr: This provides Inference Engine for pre-trained segmentation (UNet) model over MSD Dataset.
code: def info(self) -> Dict[str, Any]:
      d = super().info()
      d["pathology"] = True
      return d
  
file_path: MONAILabel/sample-apps/pathology/lib/infers/segmentation_nuclei.py
imports: import logging
  from typing import Any, Callable, Dict, Sequence
  import numpy
  from lib.transforms import LoadImagePatchd, PostFilterLabeld
  from monai.transforms import Activationsd, AsDiscreted, ScaleIntensityRangeD, SqueezeDimd, Transposed
  from monailabel.interfaces.tasks.infer_v2 import InferType
  from monailabel.tasks.infer.basic_infer import BasicInferTask
  from monailabel.transform.post import FindContoursd
  from monailabel.transform.writer import PolygonWriter
label_desc: Use image node_id 2 for calling the SegmentationNuclei obj's underlying member method code with example usage: obj.info() and returns: d