add error

can handle if there is nothing is detected with an error

app.py

@@ -42,20 +42,24 @@ def main():
             del st.session_state.prediction
             return
 
-        with prediction_result_placeholder.container():
-            if is_mobile:
-                display_options(st.session_state.crop_image, st.session_state.score_threshold, is_mobile, int(5/6*screen_width))
-            else:
-                with st.expander("Show result of prediction"):
+        if len(st.session_state.prediction['labels'])==0:
+            error("No prediction available. Please upload a BPMN image or decrease the detection score treshold.")
+        else:
+            with prediction_result_placeholder.container():
+                if is_mobile:
                     display_options(st.session_state.crop_image, st.session_state.score_threshold, is_mobile, int(5/6*screen_width))
+                else:
+                    with st.expander("Show result of prediction"):
+                        display_options(st.session_state.crop_image, st.session_state.score_threshold, is_mobile, int(5/6*screen_width))
 
-        if not is_mobile:
-            with additional_options_placeholder.container():
-                modify_results()
+            if not is_mobile:
+                with additional_options_placeholder.container():
+                    state = modify_results()
 
-        with modeler_placeholder.container():
-            modeler_options(is_mobile)
-            display_bpmn_modeler(is_mobile, screen_width)
+          
+            with modeler_placeholder.container():
+                modeler_options(is_mobile)
+                display_bpmn_modeler(is_mobile, screen_width)
     else:
         prediction_result_placeholder.empty()
         additional_options_placeholder.empty()

modules/eval.py

@@ -164,6 +164,9 @@ def mix_predictions(objects_pred, arrow_pred):
         object_keypoints.append(keypoints)
 
     #concatenate the two predictions
+    if len(arrow_pred['boxes']) == 0:
+        return objects_pred['boxes'], objects_pred['labels'], objects_pred['scores'], object_keypoints
+    
     boxes = np.concatenate((objects_pred['boxes'], arrow_pred['boxes']))
     labels = np.concatenate((objects_pred['labels'], arrow_pred['labels']))
     scores = np.concatenate((objects_pred['scores'], arrow_pred['scores']))

modules/streamlit_utils.py

@@ -411,6 +411,8 @@ def modify_results(percentage_text_dist_thresh=0.5):
             if changes:
                 st.rerun()
 
+            return True
+