          final_faces = list()
  
          for idx, face in enumerate(detected_faces):
              detected_face = DetectedFace()
              detected_face.from_dlib_rect(face)
              detected_face.landmarksXY = landmarks[idx]
              final_faces.append(detected_face)
          return final_faces
  
      # Saving tasks
 
</s> remove                        "and dlib pose predictor for landmarks. It is recommended "
                       "to perfom Extract first for superior results")
 </s> add                        "and  landmarks. It is recommended to perfom Extract first for "
                       "superior results") </s> remove                         "aligner": "dlib",
 </s> add                         "aligner": "cv2_dnn",
            detected_face.from_bounding_box(face)
          final_faces = list()
  
          for idx, face in enumerate(detected_faces):
              detected_face = DetectedFace()
            detected_face.from_bounding_box(face)
              detected_face.landmarksXY = landmarks[idx]
              final_faces.append(detected_face)
          return final_faces
  
      # Saving tasks
keep keep keep keep replace keep keep keep keep keep
 On-The_Fly conversion to use cv-dnn aligner 
scripts/convert.py