class_docstr: Image Preprocessing.
  
  Base class for applying real-time image related pre-processing.
  
  This class is meant to be used as an argument of `input_data`. When training
  a model, the defined pre-processing methods will be applied at both
  training and testing time. Note that ImageAugmentation is similar to
  ImagePreprocessing, but only applies at training time.
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code: def _samplewise_zero_center(self, batch, per_channel=False):
      for i in range(len(batch)):
          if not per_channel:
              batch[i] -= np.mean(batch[i])
          else:
              batch[i] -= np.mean(
                  batch[i], axis=(0, 1, 2), keepdims=True
              )
      return batch
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  import pickle
  import tensorflow.compat.v1
label_desc: Use image node_id 12 for calling the ImagePreprocessing obj's underlying member method code with example usage: obj._samplewise_zero_center(batch, per_channel) and returns: batch