              if hasattr(self.args, "detector"):
                  detector = self.args.detector.replace("-", "_").lower()
              else:
                  detector = "cv2_dnn"
              if hasattr(self.args, "aligner"):
                  aligner = self.args.aligner.replace("-", "_").lower()
              else:
                  aligner = "cv2_dnn"
  
              face_filter = dict(detector=detector,
                                 aligner=aligner,
 
</s> remove             if hasattr(self.args, "detector"):
                detector = self.args.detector.replace("-", "_").lower()
 </s> add             if hasattr(self._args, "detector"):
                detector = self._args.detector.replace("-", "_").lower() </s> remove                                multiprocess=not self.args.singleprocess)
 </s> add                                multiprocess=not self._args.singleprocess) </s> remove         if ((hasattr(self.args, "filter") and self.args.filter is not None) or
                (hasattr(self.args, "nfilter") and
                 self.args.nfilter is not None)):
 </s> add         if ((hasattr(self._args, "filter") and self._args.filter is not None) or
                (hasattr(self._args, "nfilter") and
                 self._args.nfilter is not None)): </s> remove             if hasattr(self.args, "ref_threshold"):
                face_filter["ref_threshold"] = self.args.ref_threshold
 </s> add             if hasattr(self._args, "ref_threshold"):
                face_filter["ref_threshold"] = self._args.ref_threshold </s> remove         if not self.extractor:
            detected_faces = self.alignments_faces(os.path.basename(filename), image)
 </s> add         if not self._extractor:
            detected_faces = self._alignments_faces(os.path.basename(filename), image)
            if hasattr(self._args, "aligner"):
                aligner = self._args.aligner.replace("-", "_").lower()
              if hasattr(self.args, "detector"):
                  detector = self.args.detector.replace("-", "_").lower()
              else:
                  detector = "cv2_dnn"
            if hasattr(self._args, "aligner"):
                aligner = self._args.aligner.replace("-", "_").lower()
            if hasattr(self._args, "aligner"):
                aligner = self._args.aligner.replace("-", "_").lower()
              else:
                  aligner = "cv2_dnn"
  
              face_filter = dict(detector=detector,
                                 aligner=aligner,
keep keep keep keep replace replace keep keep keep keep keep
 Smart Masks to Convert (#957)

- scripts.convert - Use Smart Masks for Convert
    * Make on-the-fly conversion an explicit option

- Move BlurMask to lib.faces_detect

- tools.preview - Fix for smart masks
    * Subclass from tk.Tk
    * Options to lib.gui.control_helper
    *variable cleanup

- lib.logger - Demote more tensorflow deprecation messages

- Documentation:
    * lib.faces_detect.BlurMask
    * plugins.convert.mask
    * lib.convert
    * scripts.convert
    * scripts.fsmedia
    * tools.preview 
scripts/fsmedia.py