code: def _process_image(
      filename: str, coder: ImageCoder
  ) -> Tuple[str, int, int]:
      """Processes a single image file.
  
      Args:
      filename: string, path to an image file e.g., '/path/to/example.JPG'.
      coder: instance of ImageCoder to provide TensorFlow image coding utils.
  
      Returns:
      image_buffer: string, JPEG encoding of RGB image.
      height: integer, image height in pixels.
      width: integer, image width in pixels.
  
      """
      # Read the image file.
      with tf.gfile.FastGFile(filename, "rb") as f:
          image_data = f.read()
  
      # Clean the dirty data.
      if _is_png(filename):
          # 1 image is a PNG.
          print("Converting PNG to JPEG for %s", filename)
          image_data = coder.png_to_jpeg(image_data)
      elif _is_cmyk(filename):
          # 22 JPEG images are in CMYK colorspace.
          print("Converting CMYK to RGB for %s", filename)
          image_data = coder.cmyk_to_rgb(image_data)
  
      # Decode the RGB JPEG.
      image = coder.decode_jpeg(image_data)
  
      # Check that image converted to RGB
      assert len(image.shape) == 3
      height = image.shape[0]
      width = image.shape[1]
      assert image.shape[2] == 3
  
      return image_data, height, width
  
imports: from datetime import datetime
  import math
  import os
  import random
  from typing import Iterable, List, Mapping, Union, Tuple
  import sys
  import threading
  import numpy
  import tensorflow
label_desc: Use image node_id 3 for calling a global function with example usage: _process_image(filename, coder) and returns: image_data,  height,  width