Update python_utils/get_model.py

python_utils/get_model.py

@@ -24,11 +24,20 @@ def load_model():
 
     ## define relevant parameters
     cfg = get_cfg()
+    
     cfg.merge_from_file("./configs/test_model_config.yaml")
     if not torch.cuda.is_available():
         cfg.MODEL.DEVICE = "cpu"
     else:
         cfg.MODEL.DEVICE = 'cuda'
+
+    ## when rerouting to use the final model (final_tz_segmentor) USE_FED_LOSS has to be set to false
+    ## this setting requires the training data to calculate class imbalance that the app will not have access to
+    ## some messages will appear when using the model that certain weights are not being used 
+    ## but these are used during training and not inference and shouldn't affect the model performance
+    ## code below
+    ## cfg.MODEL.ROI_BOX_HEAD.USE_FED_LOSS = false
+    
     predictor = DefaultPredictor(cfg)
 
     return predictor