  
      @staticmethod
      def _nms(boxes, threshold):
          """ Perform Non-Maximum Suppression """
          retained_box_indices = list()
  
          areas = (boxes[:, 2] - boxes[:, 0] + 1) * (boxes[:, 3] - boxes[:, 1] + 1)
          ranked_indices = boxes[:, 4].argsort()[::-1]
          while ranked_indices.size > 0:
              best = ranked_indices[0]
 
</s> remove         retval = list()
 </s> add         retval = [] </s> remove         results = list()
 </s> add         results = [] </s> remove         self._name = "conv{}_".format(level)
 </s> add         self._name = f"conv{level}_" </s> remove         self._name = "conv{}_".format(level)
 </s> add         self._name = f"conv{level}_" </s> remove         ret = list()
 </s> add         ret = []
        retained_box_indices = []
  
      @staticmethod
      def _nms(boxes, threshold):
          """ Perform Non-Maximum Suppression """
        retained_box_indices = []
  
          areas = (boxes[:, 2] - boxes[:, 0] + 1) * (boxes[:, 3] - boxes[:, 1] + 1)
          ranked_indices = boxes[:, 4].argsort()[::-1]
          while ranked_indices.size > 0:
              best = ranked_indices[0]
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/s3fd.py