Update main.py

main.py

@@ -78,7 +78,7 @@ def find_samples_to_label():
 
     # Get all predictions
     # And then get the 5 samples with the lowest prediction score
-    preds = loaded_model.predict(unlabeled_data)
+    preds = loaded_model.predict(processed_data)
     top_pred_confs = 1 - np.max(preds, axis=1)
     idx_to_label = np.argpartition(top_pred_confs, -5)[-5:]