code: def create_mb_source(
      image_height, image_width, num_channels, map_file
  ):
      transforms = [
          xforms.scale(
              width=image_width,
              height=image_height,
              channels=num_channels,
              interpolations="linear",
          )
      ]
      return C.io.MinibatchSource(
          C.io.ImageDeserializer(
              map_file,
              C.io.StreamDefs(
                  features=C.io.StreamDef(
                      field="image", transforms=transforms
                  ),
                  labels=C.io.StreamDef(field="label", shape=1000),
              ),
          ),
          randomize=False,
      )
  
file_path: CNTK/Examples/Image/FeatureExtraction/FeatureExtraction.py
imports: from __future__ import print_function
  import os
  import numpy
  import cntk
  from cntk import load_model, combine
  import cntk.io.transforms
  from cntk.logging import graph
  from cntk.logging.graph import get_node_outputs
label_desc: Use image node_id 1 for calling a global function with example usage: create_mb_source(image_height, image_width, num_channels, map_file) and returns: C