class_docstr: Post-Processing Configuration Callback.
  
  Args:
      normalization_method(NormalizationMethod): Normalization method. <none, min_max, cdf>
      threshold_method (ThresholdMethod): Flag indicating whether threshold should be manual or adaptive.
      manual_image_threshold (float | None): Default manual image threshold value.
      manual_pixel_threshold (float | None): Default manual pixel threshold value.
code: def __init__(
      self,
      normalization_method: NormalizationMethod = NormalizationMethod.MIN_MAX,
      threshold_method: ThresholdMethod = ThresholdMethod.ADAPTIVE,
      manual_image_threshold: float | None = None,
      manual_pixel_threshold: float | None = None,
  ) -> None:
      super().__init__()
      self.normalization_method = normalization_method
  
      if threshold_method == ThresholdMethod.ADAPTIVE and all(
          i is not None
          for i in (manual_image_threshold, manual_pixel_threshold)
      ):
          raise ValueError(
              "When `threshold_method` is set to `adaptive`, `manual_image_threshold` and `manual_pixel_threshold` "
              "must not be set."
          )
  
      if threshold_method == ThresholdMethod.MANUAL and all(
          i is None
          for i in (manual_image_threshold, manual_pixel_threshold)
      ):
          raise ValueError(
              "When `threshold_method` is set to `manual`, `manual_image_threshold` and `manual_pixel_threshold` "
              "must be set."
          )
  
      self.threshold_method = threshold_method
      self.manual_image_threshold = manual_image_threshold
      self.manual_pixel_threshold = manual_pixel_threshold
  
file_path: anomalib/src/anomalib/utils/callbacks/post_processing_configuration.py
imports: from __future__ import annotations
  import logging
  import torch
  from pytorch_lightning import Callback, LightningModule, Trainer
  from anomalib.models.components.base.anomaly_module import AnomalyModule
  from anomalib.post_processing import NormalizationMethod, ThresholdMethod
label_desc: Use image node_id 1 to create a new PostProcessingConfigurationCallback object from inherited base classes: Callback with example: obj = PostProcessingConfigurationCallback(normalization_method, threshold_method, manual_image_threshold, manual_pixel_threshold)