code: def image_preprocess(input_data):
      if input_data.ndim == 3:
          if np.min(input_data) == np.max(input_data):
              input_data[:] = 0
              return input_data
          else:
              input_data = (
                  (255) * (input_data - np.min(input_data))
              ) / (np.max(input_data) - np.min(input_data))
              return input_data
  
file_path: DeepNeuro/deepneuro/utilities/visualize.py
imports: import numpy
  import matplotlib.pyplot
  import os
  from collections import OrderedDict
  from deepneuro.utilities.conversion import save_data, read_image_files
  from deepneuro.utilities.util import replace_suffix, nifti_splitext
label_desc: Use image node_id 2 for calling a global function with example usage: image_preprocess(input_data) and returns: input_data, input_data