              return
          ret_faces = list()
          for idx, detect_face in enumerate(output_item["detected_faces"]):
              check_item = detect_face["face"] if isinstance(detect_face, dict) else detect_face
              if not self.filter.check(check_item):
                  logger.verbose("Skipping not recognized face: (Frame: %s Face %s)",
                                 output_item["filename"], idx)
                  continue
              logger.trace("Accepting recognised face. Frame: %s. Face: %s",
                           output_item["filename"], idx)
 
</s> remove         logger.trace("Loading aligned face: (size: %s, align_eyes: %s, dtype: %s)",
                     size, align_eyes, dtype)
        padding = int(size * self.extract_ratio) // 2
        self.aligned["size"] = size
        self.aligned["padding"] = padding
        self.aligned["align_eyes"] = align_eyes
        self.aligned["matrix"] = get_align_mat(self, size, align_eyes)
        if image is None:
            self.aligned["face"] = None
 </s> add         # Don't reload an already aligned face:
        if self.aligned:
            logger.trace("Skipping alignment calculation for already aligned face") </s> remove             if self.task.command == "train":
                self.tk_vars["istraining"].set(False)
 </s> add  </s> remove         dst = str(get_folder("{}_snapshot_{}_iters".format(self.model_dir, iterations)))
 </s> add         snapshot_dir = "{}_snapshot_{}_iters".format(self.model_dir, iterations)

        if os.path.isdir(snapshot_dir):
            logger.debug("Removing previously existing snapshot folder: '%s'", snapshot_dir)
            rmtree(snapshot_dir)

        dst = str(get_folder(snapshot_dir))
            check_item.load_aligned(output_item["image"])
              return
          ret_faces = list()
          for idx, detect_face in enumerate(output_item["detected_faces"]):
              check_item = detect_face["face"] if isinstance(detect_face, dict) else detect_face
            check_item.load_aligned(output_item["image"])
              if not self.filter.check(check_item):
                  logger.verbose("Skipping not recognized face: (Frame: %s Face %s)",
                                 output_item["filename"], idx)
                  continue
              logger.trace("Accepting recognised face. Frame: %s. Face: %s",
                           output_item["filename"], idx)
keep keep keep add keep keep keep keep keep keep
 Bugfixes

- Fix filter/nfilter for convert
- Remove existing snapshot folder before creating if it pre-exists
- Don't initialize training session until after first save. "Nonetype" session fix 
scripts/fsmedia.py