title: I am trying to understand how the process of calculating the mean for every channel of RGB image
body: <p>I am trying to preprocess an RGB image before sending it into my model. The shape of the image is (2560, 1440,3). For that I need to calculate the mean of every channel and substract them from corresponding channel pixels. I know that I can do it by:
  np.mean(image_array, axis=(0, 1)).
  However, I cannot understand the process how it is being done.
  I am aware of how axes work individually (axis=0 for columns and axis = 1 for rows). How does the axis = (0,1) work in this situation?</p>
  <p>And also how can I do the same thing for multiple images, say, train_data_shape = (1000, 256, 256, 3)?
  I appreciate every feedback!</p>