code: def detect_from_image(self, tensor_or_path):
      image = self.tensor_or_path_to_ndarray(tensor_or_path)
      image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
  
      detected_faces = self.face_detector(
          cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
      )
  
      if "cuda" not in self.device:
          detected_faces = [
              [d.left(), d.top(), d.right(), d.bottom()]
              for d in detected_faces
          ]
      else:
          detected_faces = [
              [
                  d.rect.left(),
                  d.rect.top(),
                  d.rect.right(),
                  d.rect.bottom(),
              ]
              for d in detected_faces
          ]
  
      return detected_faces
  
file_path: face-alignment/face_alignment/detection/dlib/dlib_detector.py
imports: import warnings
  import cv2
  import dlib
  from ..core import FaceDetector
  from ...utils import load_file_from_url
label_desc: Use image node_id 2 for calling the DlibDetector obj's underlying member method code with example usage: obj.detect_from_image(tensor_or_path) and returns: detected_faces