          consecutive_no_faces = 0
          batch = list()
          while True:
              item = self.in_queue.get()
              if item != "EOF":
                  logger.trace("Got from queue: '%s'", item["filename"])
                  faces_count = len(item["detected_faces"])
  
 
</s> remove                     predicted = self.predict(feed_faces)
 </s> add                     batch_size = None
                    if is_plaidml and feed_faces.shape[0] != self.batchsize:
                        logger.verbose("Fallback to BS=1")
                        batch_size = 1
                    predicted = self.predict(feed_faces, batch_size) </s> remove         predicted = self.predictor(feed)
 </s> add         predicted = self.predictor(feed, batch_size=batch_size) </s> remove     def get_queue(self, name, maxsize=0):
 </s> add     def get_queue(self, name, maxsize=0, multiprocessing_queue=True): </s> remove             self.add_queue(name, maxsize)
 </s> add             self.add_queue(name, maxsize, multiprocessing_queue) </s> remove             passed_angles = [int(angle)
                             for angle in rotation.split(",")]
 </s> add             passed_angles = [
                int(angle)
                for angle in rotation.split(",")
                if int(angle) != 0
            ]
        is_plaidml = GPUStats().is_plaidml
          consecutive_no_faces = 0
          batch = list()
        is_plaidml = GPUStats().is_plaidml
          while True:
              item = self.in_queue.get()
              if item != "EOF":
                  logger.trace("Got from queue: '%s'", item["filename"])
                  faces_count = len(item["detected_faces"])
  
keep add keep keep keep keep keep keep
 Added s3fd-amd + minor fixes (#837) 
scripts/convert.py