                  else:
                      logger.trace("Discarding frame: '%s'", filename)
                  continue
  
              detected_faces = self.get_detected_faces(filename, image, extract_queue)
              item = dict(filename=filename, image=image, detected_faces=detected_faces)
              self.pre_process.do_actions(item)
              self.load_queue.put(item)
  
          self.load_queue.put("EOF")
 
</s> remove             detected_faces = self.detect_faces(extract_queue, filename, image)
 </s> add             detected_faces = self.detect_faces(filename, image) </s> remove     def get_detected_faces(self, filename, image, extract_queue):
 </s> add     def get_detected_faces(self, filename, image): </s> remove             item = save_queue.get()
 </s> add             item = self.save_queue.get()
            logger.trace(item) </s> remove         load_queue = queue_manager.get_queue("detect")
 </s> add         load_queue = self.extractor.input_queue </s> remove             if save_queue.shutdown.is_set():
 </s> add             if self.save_queue.shutdown.is_set():
            detected_faces = self.get_detected_faces(filename, image)
                  else:
                      logger.trace("Discarding frame: '%s'", filename)
                  continue
  
            detected_faces = self.get_detected_faces(filename, image)
              item = dict(filename=filename, image=image, detected_faces=detected_faces)
              self.pre_process.do_actions(item)
              self.load_queue.put(item)
  
          self.load_queue.put("EOF")
keep keep keep keep replace keep keep keep keep keep
 Face filter vgg face (#724)

* Implement extraction pipeline

* Face filter to vgg_face. Resume partial model downloads

* On-the-fly conversion to extraction pipeline

* Move git model ids from get_model to model definition 
scripts/convert.py