Update app.py

app.py

@@ -104,23 +104,54 @@ def image_qa_app(kbvqa):
 def run_inference():
     st.title("Run Inference")
 
+    method = st.selectbox(
+        "Choose a method:",
+        ["Fine-Tuned Model", "In-Context Learning (n-shots)"],
+        index=0  # Default to the first option
+    )
+
+    detection_model = st.selectbox(
+        "Choose a model for object detection:",
+        ["yolov5", "detic"],
+        index=0  # Default to the first option
+    )
+
+    # Set default confidence based on the selected model
+    default_confidence = 0.2 if detection_model == "yolov5" else 0.4
+
+    # Slider for confidence level
+    confidence_level = st.slider(
+        "Select Detection Confidence Level",
+        min_value=0.1,
+        max_value=0.9,
+        value=default_confidence,
+        step=0.1
+    )
+
+
+    
     # Initialize session state for the model
-    if 'kbvqa' not in st.session_state:
-        st.session_state['kbvqa'] = None
-
-    # Button to load KBVQA models
-    if st.button('Load KBVQA Model'):
-        if st.session_state['kbvqa'] is not None:
-            st.write("Model already loaded.")
-        else:
-            # Call the function to load models and show progress
-            st.session_state['kbvqa'] = prepare_kbvqa_model('yolov5')  # Replace with your model
 
+    if method == "Fine-Tuned Model"
+        if 'kbvqa' not in st.session_state:
+            st.session_state['kbvqa'] = None
+    
+        # Button to load KBVQA models
+        if st.button('Load KBVQA Model'):
+            if st.session_state['kbvqa'] is not None:
+                st.write("Model already loaded.")
+            else:
+                # Call the function to load models and show progress
+                st.session_state['kbvqa'] = prepare_kbvqa_model(detection_model)
+    
+            if st.session_state['kbvqa']:
+                st.write("Model is ready for inference.")
+    
         if st.session_state['kbvqa']:
-            st.write("Model is ready for inference.")
+            image_qa_app(st.session_state['kbvqa'])
 
-    if st.session_state['kbvqa']:
-        image_qa_app(st.session_state['kbvqa'])
+    else: 
+        st.write('Model is not ready for inference yet')
 
             
 # Main function