code: def __call__(self, image):
      face = futils.dlib.detect(image)
  
      if not face:
          return
      face_on_image = face[0]
      image, face, crop_face = futils.dlib.crop(
          image,
          face_on_image,
          self.up_ratio,
          self.down_ratio,
          self.width_ratio,
      )
      np_image = np.array(image)
      image_trans = self.transform(np_image)
      mask = self.face_parser.parse(
          np.float32(cv2.resize(np_image, (512, 512)))
      )
      mask = cv2.resize(
          mask.numpy(),
          (self.img_size, self.img_size),
          interpolation=cv2.INTER_NEAREST,
      )
      mask = mask.astype(np.uint8)
      mask_tensor = paddle.to_tensor(mask)
  
      lms = (
          futils.dlib.landmarks(image, face)
          / image_trans.shape[:2]
          * self.img_size
      )
      lms = lms.round()
  
      P_np = generate_P_from_lmks(
          lms, self.img_size, self.img_size, self.img_size
      )
  
      mask_aug = generate_mask_aug(mask, lms)
  
      return (
          [
              self.norm(image_trans).unsqueeze(0),
              np.float32(mask_aug),
              np.float32(P_np),
              np.float32(mask),
          ],
          face_on_image,
          crop_face,
      )
  
imports: import argparse
  import os
  import sys
  from pathlib import Path
  import numpy
  import paddle
  import paddle.vision.transforms
  import ppgan.faceutils
  from paddle.utils.download import get_weights_path_from_url
  from PIL import Image
  from ppgan.models.builder import build_model
  from ppgan.utils.config import get_config
  from ppgan.utils.filesystem import load
  from ppgan.utils.options import parse_args
  from ppgan.utils.preprocess import *
label_desc: Use image node_id 2 for calling the PreProcess obj's underlying member method code with example usage: obj.__call__(image) and returns: list,  face_on_image,  crop_face