Update app.py

app.py

@@ -121,7 +121,7 @@ def run_inference():
     )
 
     if 'model_settings' not in st.session_state:
-        st.session_state['model_settings'] = {'detection_model': None, 'confidence_level': None}
+        st.session_state['model_settings'] = {'detection_model': detection_model, 'confidence_level': confidence_level}
 
     settings_changed = (st.session_state['model_settings']['detection_model'] != detection_model or
                         st.session_state['model_settings']['confidence_level'] != confidence_level)
@@ -133,9 +133,18 @@ def run_inference():
             st.session_state['kbvqa'] = None
 
         if st.button(button_label):
+            
             free_gpu_resources()
-            if st.session_state['kbvqa'] is not None and not settings_changed:
-                st.write("Model already loaded.")
+            if st.session_state['kbvqa'] is not None:
+                if not settings_changed:
+                    st.write("Model already loaded.")
+                else: 
+                    free_gpu_resources()
+                    detection_model = st.session_state['model_settings']['detection_model']
+                    confidence_level = st.session_state['model_settings']['confidence_level']
+                    prepare_kbvqa_model(detection_model, only_reload_detection_model=True)  # only reload detection model with new settings
+                    st.session_state['kbvqa'].detection_confidence = confidence_level
+                    free_gpu_resources()
             else:
                 st.text("Loading the model will take no more than a few minutes . .")
                 st.session_state['kbvqa'] = prepare_kbvqa_model(detection_model)
@@ -144,6 +153,8 @@ def run_inference():
                 st.write("Model is ready for inference.")
                 free_gpu_resources()
 
+                
+
         if st.session_state['kbvqa']:
             image_qa_app(st.session_state['kbvqa'])
 
@@ -191,6 +202,7 @@ def main():
 
 
     elif selection == "Run Inference":
+        st.text("Please note that this is not a general purpose model, it is specifically trained on OK-VQA dataset and is designed to give short answers to the given questions.")
         run_inference()
 
     elif selection == "Code":