code: def get_data_aug(
      rotation_range=40,
      zoom_range=0.2,
      width_shift_range=0.2,
      height_shift_range=0.2,
      horizontal_flip=False,
      vertical_flip=False,
      featurewise_center=True,
      featurewise_std_normalization=True,
      samplewise_center=False,
      samplewise_std_normalization=False,
      rescale=None,
      **kwargs,
  ):
      """
      ```
      This function is simply a wrapper around ImageDataGenerator
      with some reasonable defaults for data augmentation.
      Returns the default image_data_generator to support
      data augmentation and data normalization.
      Parameters can be adjusted by caller.
      Note that the ktrain.vision.model.image_classifier
      function may adjust these as needed.
      ```
      """
  
      data_aug = keras.preprocessing.image.ImageDataGenerator(
          rotation_range=rotation_range,
          zoom_range=zoom_range,
          width_shift_range=width_shift_range,
          height_shift_range=height_shift_range,
          horizontal_flip=horizontal_flip,
          vertical_flip=vertical_flip,
          featurewise_center=featurewise_center,
          featurewise_std_normalization=featurewise_std_normalization,
          samplewise_center=samplewise_center,
          samplewise_std_normalization=samplewise_std_normalization,
          rescale=rescale,
          **kwargs,
      )
      return data_aug
  
imports: from ..None import utils
  from ..imports import *
  from .preprocessor import ImagePreprocessor
label_desc: Use image node_id 5 for calling a global function with example usage: get_data_aug(rotation_range, zoom_range, width_shift_range, height_shift_range, horizontal_flip, vertical_flip, featurewise_center, featurewise_std_normalization, samplewise_center, samplewise_std_normalization, rescale) and returns: data_aug