code: def _raw_face_locations(img, number_of_times_to_upsample=1, model="hog"):
      
      if model == "cnn":
          return cnn_face_detector(img, number_of_times_to_upsample)
      else:
          return face_detector(img, number_of_times_to_upsample)
docs: Returns an array of bounding boxes of human faces in a image
  
      :param img: An image (as a numpy array)
      :param number_of_times_to_upsample: How many times to upsample the image looking for faces. Higher numbers find smaller faces.
      :param model: Which face detection model to use. "hog" is less accurate but faster on CPUs. "cnn" is a more accurate
                    deep-learning model which is GPU/CUDA accelerated (if available). The default is "hog".
      :return: A list of dlib 'rect' objects of found face locations