code: def preprocess_face(
      img: Union[str, np.ndarray],
      target_size=(224, 224),
      detector_backend="opencv",
      grayscale=False,
      enforce_detection=True,
      align=True,
  ) -> Union[np.ndarray, None]:
      """
      Preprocess only one face
  
      Args:
          img (str or numpy): the input image.
          target_size (tuple, optional): the target size. Defaults to (224, 224).
          detector_backend (str, optional): the detector backend. Defaults to "opencv".
          grayscale (bool, optional): whether to convert to grayscale. Defaults to False.
          enforce_detection (bool, optional): whether to enforce face detection. Defaults to True.
          align (bool, optional): whether to align the face. Defaults to True.
  
      Returns:
          loaded image (numpt): the preprocessed face.
  
      Raises:
          ValueError: if face is not detected and enforce_detection is True.
  
      Deprecated:
          0.0.78: Use extract_faces instead of preprocess_face.
      """
      logger.warn(
          "Function preprocess_face is deprecated. Use extract_faces instead."
      )
      result = None
      img_objs = extract_faces(
          img=img,
          target_size=target_size,
          detector_backend=detector_backend,
          grayscale=grayscale,
          enforce_detection=enforce_detection,
          align=align,
      )
  
      if len(img_objs) > 0:
          result, _, _ = img_objs[0]
          # discard expanded dimension
          if len(result.shape) == 4:
              result = result[0]
  
      return result
  
file_path: deepface/deepface/commons/functions.py
imports: import os
  from typing import Union, Tuple
  import base64
  from pathlib import Path
  from PIL import Image
  import requests
  import numpy
  import cv2
  import tensorflow
  from deprecated import deprecated
  from deepface.detectors import FaceDetector
  from deepface.commons.logger import Logger
label_desc: Use image node_id 8 for calling a global function with example usage: preprocess_face(img, target_size, detector_backend, grayscale, enforce_detection, align) and returns: result