code: def create_headers(image_name):
      """
      This function generates C header files for the input and output arrays required to run inferences
      """
      img_path = os.path.join("./", f"{image_name}")
  
      # Resize image to 224x224
      resized_image = Image.open(img_path).resize((224, 224))
      img_data = np.asarray(resized_image).astype("float32")
  
      # # Add the batch dimension, as we are expecting 4-dimensional input: NCHW.
      img_data = np.expand_dims(img_data, axis=0)
  
      # Create input header file
      input_data = img_data - 128
      input_data = input_data.astype(np.int8)
      create_header_file(
          "inputs", "ethosu_scratch", "input", input_data, "./include"
      )
      # Create output header file
      output_data = np.zeros([1001], np.int8)
      create_header_file(
          "outputs",
          "output_data_sec",
          "output",
          output_data,
          "./include",
      )
  
file_path: tvm/apps/microtvm/ethosu/convert_image.py
imports: import os
  import pathlib
  import re
  import sys
  from PIL import Image
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: create_headers(image_name) without return types