code: def transform(self, images):
      from PIL import Image
      from torchvision.transforms import (
          Compose,
          Grayscale,
          Normalize,
          ToTensor,
      )
  
      composed = Compose(
          [
              Grayscale(num_output_channels=1),
              ToTensor(),
              Normalize((0.1307,), (0.3081,)),
          ]
      )
      # reverse the channels from opencv
      return composed(Image.fromarray(images[:, :, ::-1])).unsqueeze(0)
  
file_path: evadb/evadb/functions/mnist_image_classifier.py
imports: from collections import OrderedDict
  import pandas
  from evadb.functions.abstract.pytorch_abstract_function import PytorchAbstractClassifierFunction
  from evadb.utils.generic_utils import try_to_import_torch, try_to_import_torchvision
label_desc: Use image node_id 4 for calling the MnistImageClassifier obj's underlying member method code with example usage: obj.transform(images) and returns: composed