          origin_h, origin_w = batch.shape[1:3]
          rectangles = self.detect_pnet(batch, origin_h, origin_w)
          rectangles = self.detect_rnet(batch, rectangles, origin_h, origin_w)
          rectangles = self.detect_onet(batch, rectangles, origin_h, origin_w)
          ret_boxes = list()
          ret_points = list()
          for rects in rectangles:
              if rects:
                  total_boxes = np.array([result[:5] for result in rects])
                  points = np.array([result[5:] for result in rects]).T
              else:
 
</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 = list()
 </s> add         ret = [] </s> remove         retval = list()
 </s> add         retval = []
        ret_boxes = []
        ret_points = []
          origin_h, origin_w = batch.shape[1:3]
          rectangles = self.detect_pnet(batch, origin_h, origin_w)
          rectangles = self.detect_rnet(batch, rectangles, origin_h, origin_w)
          rectangles = self.detect_onet(batch, rectangles, origin_h, origin_w)
        ret_boxes = []
        ret_points = []
        ret_boxes = []
        ret_points = []
          for rects in rectangles:
              if rects:
                  total_boxes = np.array([result[:5] for result in rects])
                  points = np.array([result[5:] for result in rects]).T
              else:
keep keep keep keep replace 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