code: def _rgb_relative_intensity_mean(
      batch: List[np.ndarray],
  ) -> List[Tuple[float, float, float]]:
      """Calculate normalized mean for each channel (rgb) in image.
  
      The normalized mean of each channel is calculated by first normalizing the image's pixels (meaning, each color
      is normalized to its relevant intensity, by dividing the color intensity by the other colors). Then, the mean
      for each image channel is calculated.
  
      Parameters
      ----------
      batch: List[np.ndarray]
          A list of arrays, each arrays represents an image in the required deepchecks format.
  
      Returns
      -------
      List[np.ndarray]:
          List of 3-dimensional arrays, each dimension is the normalized mean of the color channel. An array is
          returned for each image.
      """
      return [
          _normalize_pixelwise(img).mean(axis=(1, 2))
          if not _is_grayscale(img)
          else (None, None, None)
          for img in batch
      ]
  
imports: from typing import Dict, List, Tuple
  import numpy
  from cv2 import CV_64F, Laplacian
  from skimage.color import rgb2gray
label_desc: Use image node_id 11 for calling a global function with example usage: _rgb_relative_intensity_mean(batch) and returns: unknown