                  logger.trace("Got from queue: '%s'", item["filename"])
                  faces_count = len(item["detected_faces"])
                  self.faces_count += faces_count
                  if faces_count > 1:
                      self.verify_output = True
                      logger.verbose("Found more than one face in an image! '%s'",
                                     os.path.basename(item["filename"]))
  
 
</s> remove             if faces_seen < self.batchsize and item != "EOF":
                logger.trace("Continuing. Current batchsize: %s", faces_seen)
 </s> add             if item != "EOF" and (faces_seen < self.batchsize and
                                  consecutive_no_faces < self.batchsize):
                logger.trace("Continuing. Current batchsize: %s, consecutive_no_faces: %s",
                             faces_seen, consecutive_no_faces) </s> remove             import_path = dirpath.replace(base_path, "").replace("/", ".")[1:]
 </s> add             import_path = ".".join(full_path_split(dirpath.replace(base_path, ""))[1:]) </s> remove             import_path = dirpath.replace(base_path, "").replace("/", ".")[1:]
 </s> add             import_path = ".".join(full_path_split(dirpath.replace(base_path, ""))[1:]) </s> remove             import_path = dirpath.replace(base_path, "").replace("/", ".")[1:]
 </s> add             import_path = ".".join(full_path_split(dirpath.replace(base_path, ""))[1:])
                # Safety measure. If a large stream of frames appear that do not have faces,
                # these will stack up into RAM. Keep a count of consecutive frames with no faces.
                # If self.batchsize number of frames appear, force the current batch through
                # to clear RAM.
                consecutive_no_faces = consecutive_no_faces + 1 if faces_count == 0 else 0
                  logger.trace("Got from queue: '%s'", item["filename"])
                  faces_count = len(item["detected_faces"])
                # Safety measure. If a large stream of frames appear that do not have faces,
                # these will stack up into RAM. Keep a count of consecutive frames with no faces.
                # If self.batchsize number of frames appear, force the current batch through
                # to clear RAM.
                consecutive_no_faces = consecutive_no_faces + 1 if faces_count == 0 else 0
                  self.faces_count += faces_count
                  if faces_count > 1:
                      self.verify_output = True
                      logger.verbose("Found more than one face in an image! '%s'",
                                     os.path.basename(item["filename"]))
  
keep add keep keep keep keep keep keep
 Bugfixes and minor changes

Fix: Occasional memory leak in convert
Fix: Dynamic config loading in Windows
Change: Better folder naming for snapshots 
scripts/convert.py