docstr: Mean Subtraction performed per channel
  Mean must be calculated ONLY on the training set
docstr_tok: ["Mean","Subtraction","performed","per","channel","Mean","must","be","calculated","ONLY","on","the","training","set"]
code: def mean_preprocess(self, image, channels) -> Tensor:
      """
      Mean Subtraction performed per channel
      Mean must be calculated ONLY on the training set
      """
  
      if channels == 3:
          b, g, r = cv.split(image.astype("float32"))[:3]
  
          # Subtracting the mean
          r -= self.rMean
          g -= self.gMean
          b -= self.bMean
  
          # Merging
          return cv.merge([b, g, r])
  
      image -= self.bgrMean
      return image
  
file_path: caer/caer/preprocessing/mean_subtraction.py
imports: from .._internal import _check_mean_sub_values
  from ..path import exists, list_images
  from ..io import imread
  from ..coreten import Tensor
  from ..annotations import Tuple, List, Union
  import numpy
  import cv2
label_desc: Use image node_id 2 for calling the MeanProcess obj's underlying member method code with example usage: obj.mean_preprocess(image, channels) and returns: image, cv