code: def create_header_file(
      name, section, tensor_name, tensor_data, output_path
  ):
      """
      This function generates a header file containing the data from the numpy array provided.
      """
      file_path = pathlib.Path(f"{output_path}/" + name).resolve()
      # Create header file with npy_data as a C array
      raw_path = file_path.with_suffix(".h").resolve()
      with open(raw_path, "w") as header_file:
          header_file.write(
              "#include <tvmgen_default.h>\n"
              + f"const size_t {tensor_name}_len = {tensor_data.size};\n"
              + f'int8_t {tensor_name}[] __attribute__((section("{section}"), aligned(16))) = "'
          )
  
          data_hexstr = tensor_data.tobytes().hex()
          for i in range(0, len(data_hexstr), 2):
              header_file.write(f"\\x{data_hexstr[i:i+2]}")
          header_file.write('";\n\n')
  
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 1 for calling a global function with example usage: create_header_file(name, section, tensor_name, tensor_data, output_path) without return types