data augmented

main.py

@@ -162,15 +162,15 @@ def save_pred(model, data_val, output_path,  criterion_rt, metric_rt, wandb=None
 
         loss_rt = criterion_rt(rt, pr_rt)
         losses_rt += loss_rt.item()
-        dist_rt = metric_rt(rt, pred_rt)
+        dist_rt = metric_rt(rt, pr_rt)
         dist_rt_acc += dist_rt.item()
 
     if wandb is not None:
         wdb.log({"test rt loss": losses_rt / len(data_val),
                  "test rt mean metric": dist_rt_acc / len(data_val)})
 
-    print('val rt loss', losses_rt / len(data_val),
-          "val rt mean metric : ",
+    print('test rt loss', losses_rt / len(data_val),
+          "test rt mean metric : ",
           dist_rt_acc / len(data_val))
 
     data_frame['rt pred'] = pred_rt