Update app.py

app.py

@@ -34,9 +34,7 @@ sample_images = ["Files/sample1.jpg", "Files/sample2.jpg", "Files/sample3.jpg",
 
 
 def analyze_image(image, model):
-    # Placeholder for your analysis function
-    # This function should prepare captions, detect objects, etc.
-    # For example:
+    st.write("Analyzing . . .")
     caption = model.get_caption(image)
     image_with_boxes, detected_objects_str = model.detect_objects(image)
     return caption, detected_objects_str
@@ -147,6 +145,7 @@ def run_inference():
             else:
                 # Call the function to load models and show progress
                 st.session_state['kbvqa'] = prepare_kbvqa_model(detection_model)
+                st.session_state['kbvqa'].detection_confidence = confidence_level
     
             if st.session_state['kbvqa']:
                 st.write("Model is ready for inference.")
@@ -161,7 +160,7 @@ def run_inference():
 # Main function
 def main():
     st.sidebar.title("Navigation")
-    selection = st.sidebar.radio("Go to", ["Home", "Dataset Analysis", "Evaluation Results", "Run Inference", "Dissertation Report", "Object Detection"])
+    selection = st.sidebar.radio("Go to", ["Home", "Dataset Analysis", "Evaluation Results", "Run Inference", "Dissertation Report", "More Pages will follow .. "])
 
     if selection == "Home":
         st.title("MultiModal Learning for Knowledg-Based Visual Question Answering")
@@ -191,9 +190,12 @@ def main():
 
     elif selection == "Run Inference":
         run_inference()
+
+    elif selection == "More Pages will follow .. ":
+        st.title("Staye Tuned")
+        st.write("This is a Place Holder until the contents are uploaded.")
             
-    elif selection == "Object Detection":
-        run_object_detection()
+
 
 if __name__ == "__main__":
     main()