class_docstr: This provides Inference Engine for pre-trained classification model.
code: def __init__(self, path: str, conf: Dict[str, str], **kwargs):
      super().__init__(
          path,
          conf,
          type=InferType.CLASSIFICATION,
          add_post_restore=False,
          load_strict=False,
          **kwargs,
      )
  
      # Override Labels
      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),
      }
      self._config["label_colors"] = self.label_colors
  
file_path: MONAILabel/sample-apps/pathology/lib/infers/classification_nuclei.py
imports: import logging
  from typing import Any, Dict
  from monailabel.interfaces.tasks.infer_v2 import InferType
  from monailabel.tasks.infer.bundle import BundleInferTask
label_desc: Use image node_id 1 to create a new ClassificationNuclei object from inherited base classes: BundleInferTask with example: obj = ClassificationNuclei(path, conf)