code: def test_analyze_for_different_detectors():
      img_paths = [
          "dataset/img1.jpg",
          "dataset/img5.jpg",
          "dataset/img6.jpg",
          "dataset/img8.jpg",
          "dataset/img1.jpg",
          "dataset/img2.jpg",
          "dataset/img1.jpg",
          "dataset/img2.jpg",
          "dataset/img6.jpg",
          "dataset/img6.jpg",
      ]
  
      for img_path in img_paths:
          for detector in detectors:
              results = DeepFace.analyze(
                  img_path,
                  actions=("gender",),
                  detector_backend=detector,
                  enforce_detection=False,
              )
              for result in results:
                  logger.debug(result)
  
                  # validate keys
                  assert "gender" in result.keys()
                  assert "dominant_gender" in result.keys() and result[
                      "dominant_gender"
                  ] in [
                      "Man",
                      "Woman",
                  ]
  
                  # validate probabilities
                  if result["dominant_gender"] == "Man":
                      assert (
                          result["gender"]["Man"]
                          > result["gender"]["Woman"]
                      )
                  else:
                      assert (
                          result["gender"]["Man"]
                          < result["gender"]["Woman"]
                      )
  
file_path: deepface/tests/test_analyze.py
imports: import cv2
  from deepface import DeepFace
  from deepface.commons.logger import Logger
label_desc: Use image node_id 6 for calling a global function with example usage: test_analyze_for_different_detectors() without return types