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 32x320
    img = cv2.imread(img_path)
    img = resize_norm_img(img, [3, 32, 320])
    img_data = img.astype("float32")

    # # Add the batch dimension, as we are expecting 4-dimensional input: NCHW.
    img_data = np.expand_dims(img_data, axis=0)

    if os.path.exists("./include/inputs.h"):
        os.remove("./include/inputs.h")
    if os.path.exists("./include/outputs.h"):
        os.remove("./include/outputs.h")
    # Create input header file
    create_header_file("inputs", "input", img_data, "./include")
    # Create output header file
    output_data = np.zeros([8500], np.float32)
    create_header_file(
        "outputs",
        "output0",
        output_data,
        "./include", )
    output_data = np.zeros([170000], np.float32)
    create_header_file(
        "outputs",
        "output1",
        output_data,
        "./include", )

    This function generates C header files for the input and output arrays required to run inferences
    
deploy/third_engine/demo_avh/convert_image.py