Update app.py

app.py

@@ -220,16 +220,27 @@ with st.sidebar:
     if not st.session_state.blip_model_loaded:
         if st.button("📥 Load BLIP Models", type="primary"):
             # Load BLIP models
-            original_processor, original_model, finetuned_processor, finetuned_model = load_blip_models()
-            if all([original_processor, original_model, finetuned_processor, finetuned_model]):
-                st.session_state.original_processor = original_processor
-                st.session_state.original_model = original_model
-                st.session_state.finetuned_processor = finetuned_processor
-                st.session_state.finetuned_model = finetuned_model
-                st.session_state.blip_model_loaded = True
-                st.success("✅ BLIP models loaded!")
-            else:
-                st.error("❌ Failed to load BLIP models.")
+            try:
+                with st.spinner("Loading BLIP captioning models..."):
+                    # Load original BLIP model for general image captioning
+                    original_processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
+                    original_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
+                    
+                    # Load fine-tuned BLIP model for GradCAM analysis
+                    finetuned_processor = BlipProcessor.from_pretrained("saakshigupta/gradcam-xception-finetuned")
+                    finetuned_model = BlipForConditionalGeneration.from_pretrained("saakshigupta/gradcam-xception-finetuned")
+                    
+                    if all([original_processor, original_model, finetuned_processor, finetuned_model]):
+                        st.session_state.original_processor = original_processor
+                        st.session_state.original_model = original_model
+                        st.session_state.finetuned_processor = finetuned_processor
+                        st.session_state.finetuned_model = finetuned_model
+                        st.session_state.blip_model_loaded = True
+                        st.success("✅ BLIP models loaded!")
+                    else:
+                        st.error("❌ Failed to load BLIP models.")
+            except Exception as e:
+                st.error(f"Error loading BLIP models: {str(e)}")
     else:
         st.success("✅ BLIP models loaded")
     
@@ -399,24 +410,6 @@ def load_detection_model_xception():
 
 # ----- BLIP Image Captioning -----
 
-# Function to load BLIP captioning models
-@st.cache_resource
-def load_blip_models():
-    with st.spinner("Loading BLIP captioning models..."):
-        try:
-            # Load original BLIP model for general image captioning
-            original_processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
-            original_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
-            
-            # Load fine-tuned BLIP model for GradCAM analysis
-            finetuned_processor = BlipProcessor.from_pretrained("saakshigupta/gradcam-xception-finetuned")
-            finetuned_model = BlipForConditionalGeneration.from_pretrained("saakshigupta/gradcam-xception-finetuned")
-            
-            return original_processor, original_model, finetuned_processor, finetuned_model
-        except Exception as e:
-            st.error(f"Error loading BLIP models: {str(e)}")
-            return None, None, None, None
-
 # Function to generate image caption using BLIP's VQA approach for GradCAM
 def generate_gradcam_caption(image, processor, model, max_length=60):
     """