code: def test_different_detectors():
      detectors = ["opencv", "mtcnn"]
  
      for detector in detectors:
          img_objs = DeepFace.extract_faces(
              img_path="dataset/img11.jpg", detector_backend=detector
          )
          for img_obj in img_objs:
              assert "face" in img_obj.keys()
              assert "facial_area" in img_obj.keys()
              assert isinstance(img_obj["facial_area"], dict)
              assert "x" in img_obj["facial_area"].keys()
              assert "y" in img_obj["facial_area"].keys()
              assert "w" in img_obj["facial_area"].keys()
              assert "h" in img_obj["facial_area"].keys()
              assert "confidence" in img_obj.keys()
  
              img = img_obj["face"]
              assert img.shape[0] > 0 and img.shape[1] > 0
          logger.info(
              f"✅ extract_faces for {detector} backend test is done"
          )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_different_detectors() without return types