feat: Improve error reporting and fix bug

src/careamics_napari/training_plugin.py

@@ -336,9 +336,9 @@ def _update_from_prediction(self, update: PredictionUpdate) -> None:
 
             if _has_napari:
                 ntf.show_error(
-                    "An error occurred during prediction. Check the console for more "
-                    "information. Note: if you get an error due to the sizes of "
-                    "Tensors, try using tiling."
+                    f"An error occurred during prediction: \n {update.value} \n"
+                    f"Note: if you get an error due to the sizes of "
+                    f"Tensors, try using tiling."
                 )
 
         else:
@@ -365,11 +365,8 @@ def _update_from_saving(self, update: SavingUpdate) -> None:
         elif update.type == SavingUpdateType.EXCEPTION:
             self.save_status.state = SavingState.CRASHED
 
-            # print exception without raising it
-            print(f"Error: {update.value}")
-
             if _has_napari:
-                ntf.show_error("An error occurred during saving.")
+                ntf.show_error(f"An error occurred during saving: \n {update.value}")
 
     def _set_data_from_algorithm(self, name: str) -> None:
         """Update the data selection widget based on the algorithm.

src/careamics_napari/widgets/predict_data_widget.py

@@ -149,7 +149,7 @@ def _update_pred_layer(self: Self, layer: Image) -> None:
         layer : Image
             The selected layer.
         """
-        if self.config_signal.layer_pred is not None:
+        if self.config_signal is not None:
             self.config_signal.layer_pred = layer
 
     def _update_pred_folder(self: Self, folder: str) -> None:

src/careamics_napari/widgets/train_data_widget.py

@@ -112,7 +112,6 @@ def _set_layer_tab(
 
                 # tool tips
                 self.target_train.native.setToolTip("Select a training target layer.")
-
                 self.target_val.native.setToolTip("Select a validation target layer.")
 
                 # connection actions for targets

src/careamics_napari/workers/prediction_worker.py

@@ -1,5 +1,6 @@
 """A thread worker function running CAREamics prediction."""
 
+import traceback
 from collections.abc import Generator
 from queue import Queue
 from threading import Thread
@@ -75,6 +76,11 @@ def _push_exception(queue: Queue, e: Exception) -> None:
     e : Exception
         Exception.
     """
+    try:
+        raise e
+    except Exception as _:
+        traceback.print_exc()
+
     queue.put(PredictionUpdate(PredictionUpdateType.EXCEPTION, e))
 
 
@@ -108,6 +114,7 @@ def _predict(
             _push_exception(
                 update_queue, ValueError("Prediction layer has not been selected.")
             )
+            return
 
         elif config_signal.layer_pred.data is None:
             _push_exception(
@@ -116,6 +123,7 @@ def _predict(
                     f"Prediction layer {config_signal.layer_pred.name} is empty."
                 ),
             )
+            return
         else:
             pred_data = config_signal.layer_pred.data
 
@@ -173,6 +181,8 @@ def _predict(
         #     time.sleep(0.2)
 
     except Exception as e:
+        traceback.print_exc()
+
         update_queue.put(PredictionUpdate(PredictionUpdateType.EXCEPTION, e))
         return
 

src/careamics_napari/workers/saving_worker.py

@@ -1,5 +1,6 @@
 """A thread worker function running CAREamics prediction."""
 
+import traceback
 from collections.abc import Generator
 
 from careamics import CAREamist
@@ -59,6 +60,8 @@ def save_worker(
             )
 
     except Exception as e:
+        traceback.print_exc()
+
         yield SavingUpdate(SavingUpdateType.EXCEPTION, e)
 
     yield SavingUpdate(SavingUpdateType.STATE, SavingState.DONE)

src/careamics_napari/workers/training_worker.py

@@ -1,5 +1,6 @@
 """A thread worker function running CAREamics training."""
 
+import traceback
 from collections.abc import Generator
 from queue import Queue
 from threading import Thread
@@ -250,6 +251,8 @@ def _train(
         #     time.sleep(0.2)
 
     except Exception as e:
+        traceback.print_exc()
+
         training_queue.put(TrainUpdate(TrainUpdateType.EXCEPTION, e))
 
     training_queue.put(TrainUpdate(TrainUpdateType.STATE, TrainingState.DONE))