code: def build_model() -> dict:
      """
      Build a dlib hog face detector model
      Returns:
          model (Any)
      """
      home = functions.get_deepface_home()
  
      # this is not a must dependency. do not import it in the global level.
      try:
          import dlib
      except ModuleNotFoundError as e:
          raise ImportError(
              "Dlib is an optional detector, ensure the library is installed."
              "Please install using 'pip install dlib' "
          ) from e
  
      # check required file exists in the home/.deepface/weights folder
      if (
          os.path.isfile(
              home
              + "/.deepface/weights/shape_predictor_5_face_landmarks.dat"
          )
          != True
      ):
          file_name = "shape_predictor_5_face_landmarks.dat.bz2"
          logger.info(f"{file_name} is going to be downloaded")
  
          url = f"http://dlib.net/files/{file_name}"
          output = f"{home}/.deepface/weights/{file_name}"
  
          gdown.download(url, output, quiet=False)
  
          zipfile = bz2.BZ2File(output)
          data = zipfile.read()
          newfilepath = output[:-4]  # discard .bz2 extension
          with open(newfilepath, "wb") as f:
              f.write(data)
  
      face_detector = dlib.get_frontal_face_detector()
      sp = dlib.shape_predictor(
          home
          + "/.deepface/weights/shape_predictor_5_face_landmarks.dat"
      )
  
      detector = {}
      detector["face_detector"] = face_detector
      detector["sp"] = sp
      return detector
  
file_path: deepface/deepface/detectors/DlibWrapper.py
imports: import os
  import bz2
  import gdown
  import numpy
  from deepface.commons import functions
  from deepface.commons.logger import Logger
label_desc: Use image node_id 1 for calling a global function with example usage: build_model() and returns: detector