code: def test_different_face_detectors():
      for detector in detectors:
          res = DeepFace.verify(
              "dataset/img1.jpg",
              "dataset/img2.jpg",
              detector_backend=detector,
          )
          assert isinstance(res, dict)
          assert "verified" in res.keys()
          assert res["verified"] in [True, False]
          assert "distance" in res.keys()
          assert "threshold" in res.keys()
          assert "model" in res.keys()
          assert "detector_backend" in res.keys()
          assert "similarity_metric" in res.keys()
          assert "facial_areas" in res.keys()
          assert "img1" in res["facial_areas"].keys()
          assert "img2" in res["facial_areas"].keys()
          assert "x" in res["facial_areas"]["img1"].keys()
          assert "y" in res["facial_areas"]["img1"].keys()
          assert "w" in res["facial_areas"]["img1"].keys()
          assert "h" in res["facial_areas"]["img1"].keys()
          assert "x" in res["facial_areas"]["img2"].keys()
          assert "y" in res["facial_areas"]["img2"].keys()
          assert "w" in res["facial_areas"]["img2"].keys()
          assert "h" in res["facial_areas"]["img2"].keys()
          logger.info(f"✅ test verify for {detector} backend done")
  
imports: import cv2
  from deepface import DeepFace
  from deepface.commons.logger import Logger
label_desc: Use image node_id 2 for calling a global function with example usage: test_different_face_detectors() without return types