code: def __init__(self, app_dir, studies, conf):
      self.models = get_bundle_models(app_dir, conf)
      # Add Epistemic model for scoring
      self.epistemic_models = (
          get_bundle_models(app_dir, conf, conf_key="epistemic_model")
          if conf.get("epistemic_model")
          else None
      )
      if self.epistemic_models:
          # Get epistemic parameters
          self.epistemic_max_samples = int(
              conf.get("epistemic_max_samples", "0")
          )
          self.epistemic_simulation_size = int(
              conf.get("epistemic_simulation_size", "5")
          )
          self.epistemic_dropout = float(
              conf.get("epistemic_dropout", "0.2")
          )
  
      super().__init__(
          app_dir=app_dir,
          studies=studies,
          conf=conf,
          name=f"MONAILabel - Zoo/Bundle ({monailabel.__version__})",
          description="DeepLearning models provided via MONAI Zoo/Bundle",
          version=monailabel.__version__,
      )
  
imports: import logging
  import os
  from typing import Dict
  from monai.transforms import Invertd, SaveImaged
  import monailabel
  from monailabel.interfaces.app import MONAILabelApp
  from monailabel.interfaces.tasks.infer_v2 import InferTask
  from monailabel.interfaces.tasks.scoring import ScoringMethod
  from monailabel.interfaces.tasks.strategy import Strategy
  from monailabel.interfaces.tasks.train import TrainTask
  from monailabel.tasks.activelearning.first import First
  from monailabel.tasks.activelearning.random import Random
  from monailabel.tasks.infer.bundle import BundleInferTask
  from monailabel.tasks.scoring.epistemic_v2 import EpistemicScoring
  from monailabel.tasks.train.bundle import BundleTrainTask
  from monailabel.utils.others.generic import get_bundle_models, strtobool
label_desc: Use image node_id 1 to create a new MyApp object from inherited base classes: MONAILabelApp with example: obj = MyApp(app_dir, studies, conf)