docs: def _convert_to_example(filename, image_buffer, label, text, height, width):
    """Build an Example proto for an example.
  
    Args:
      filename: string, path to an image file, e.g., '/path/to/example.JPG'
      image_buffer: string, JPEG encoding of RGB image
      label: integer, identifier for the ground truth for the network
      text: string, unique human-readable, e.g. 'dog'
      height: integer, image height in pixels
      width: integer, image width in pixels
    Returns:
      Example proto
    """
  
    colorspace = 'RGB'
    channels = 3
    image_format = 'JPEG'
  
    example = tf.train.Example(features=tf.train.Features(feature={
        'image/height': _int64_feature(height),
        'image/width': _int64_feature(width),
        'image/colorspace': _bytes_feature(tf.compat.as_bytes(colorspace)),
        'image/channels': _int64_feature(channels),
        'image/class/label': _int64_feature(label),
        'image/class/text': _bytes_feature(tf.compat.as_bytes(text)),
        'image/format': _bytes_feature(tf.compat.as_bytes(image_format)),
        'image/filename': _bytes_feature(tf.compat.as_bytes(os.path.basename(filename))),
        'image/encoded': _bytes_feature(tf.compat.as_bytes(image_buffer))}))
    return example