          return ret
  
      def detect_onet(self, images, rectangle_batch, height, width):
          """ third stage - further refinement and facial landmarks positions with o-net """
          ret = list()
          # TODO: batching
          for idx, rectangles in enumerate(rectangle_batch):
              if not rectangles:
                  ret.append(list())
                  continue
 
</s> remove                 ret.append(list())
 </s> add                 ret.append([]) </s> remove                 ret.append(list())
 </s> add                 ret.append([]) </s> remove         ret = list()
 </s> add         ret = [] </s> remove         ret_boxes = list()
        ret_points = list()
 </s> add         ret_boxes = []
        ret_points = [] </s> remove             valid = [x for x in _MODEL_MAPPING if not _MODEL_MAPPING[x].get('no_amd')]
 </s> add             valid = [k for k, v in _MODEL_MAPPING.items() if not v.get('no_amd')]
        ret = []
          return ret
  
      def detect_onet(self, images, rectangle_batch, height, width):
          """ third stage - further refinement and facial landmarks positions with o-net """
        ret = []
          # TODO: batching
          for idx, rectangles in enumerate(rectangle_batch):
              if not rectangles:
                  ret.append(list())
                  continue
keep keep keep keep replace keep keep keep keep keep
 Update all Keras Imports to be conditional (#1214)

* Remove custom keras importer

* first round keras imports fix

* launcher.py: Remove KerasFinder references

* 2nd round keras imports update (lib and extract)

* 3rd round keras imports update (train)

* remove KerasFinder from tests

* 4th round keras imports update (tests) 
plugins/extract/detect/mtcnn.py