code: def superimpose_anomaly_map(
      anomaly_map: np.ndarray,
      image: np.ndarray,
      alpha: float = 0.4,
      gamma: int = 0,
      normalize: bool = False,
  ) -> np.ndarray:
      """Superimpose anomaly map on top of in the input image.
  
      Args:
          anomaly_map (np.ndarray): Anomaly map
          image (np.ndarray): Input image
          alpha (float, optional): Weight to overlay anomaly map
              on the input image. Defaults to 0.4.
          gamma (int, optional): Value to add to the blended image
              to smooth the processing. Defaults to 0. Overall,
              the formula to compute the blended image is
              I' = (alpha*I1 + (1-alpha)*I2) + gamma
          normalize: whether or not the anomaly maps should
              be normalized to image min-max
  
  
      Returns:
          np.ndarray: Image with anomaly map superimposed on top of it.
      """
  
      anomaly_map = anomaly_map_to_color_map(
          anomaly_map.squeeze(), normalize=normalize
      )
      superimposed_map = cv2.addWeighted(
          anomaly_map, alpha, image, (1 - alpha), gamma
      )
      return superimposed_map
  
file_path: anomalib/src/anomalib/post_processing/post_process.py
imports: from __future__ import annotations
  import math
  from enum import Enum
  import cv2
  import numpy
  from skimage import morphology
label_desc: Use image node_id 5 for calling a global function with example usage: superimpose_anomaly_map(anomaly_map, image, alpha, gamma, normalize) and returns: superimposed_map