Update my_model/utilities/state_manager.py

my_model/utilities/state_manager.py

@@ -13,27 +13,28 @@ class StateManager:
         if 'images_data' not in st.session_state:
             st.session_state['images_data'] = {}
         if 'method' not in st.session_state:
-            st.selectbox("Choose a method:", ["Fine-Tuned Model", "In-Context Learning (n-shots)"], index=0, key='method')
+            st.session_state['method'] = None
         if 'detection_model' not in st.session_state:
-            self.detection_model = st.selectbox("Choose a model for objects detection:", ["yolov5", "detic"], index=1, key='detection_model')
+            st.session_state['detection_model'] = None
         if 'kbvqa' not in st.session_state:
             st.session_state['kbvqa'] = None
-
-        self.default_confidence = 0.2 if self.detection_model == "yolov5" else 0.4
         if 'confidence_level' not in st.session_state:
-            self.set_slider_value(text="Select minimum detection confidence level", 
-                                                    min_value=0.1, 
-                                                    max_value=0.9, 
-                                                    value=self.default_confidence, 
-                                                    step=0.1, 
-                                                    slider_key_name='confidence_level'
-                                                    )
+            st.session_state['confidence_level'] = None
 
 
     
-   # confidence_level = st.slider("Select minimum detection confidence level", min_value=0.1, max_value=0.9, value=default_confidence, step=0.1)
-
-
+    def set_up_widgets(self):
+        st.selectbox("Choose a method:", ["Fine-Tuned Model", "In-Context Learning (n-shots)"], index=0, key='method')
+        self.detection_model = st.selectbox("Choose a model for objects detection:", ["yolov5", "detic"], index=1, key='detection_model')
+        default_confidence = 0.2 if self.detection_model == "yolov5" else 0.4
+        self.set_slider_value(text="Select minimum detection confidence level", 
+                                min_value=0.1, 
+                                max_value=0.9, 
+                                value=default_confidence, 
+                                step=0.1, 
+                                slider_key_name='confidence_level'
+                                                    )
+        
 
     def set_slider_value(self, text, min_value, max_value, value, step, slider_key_name):