Update app.py

app.py

@@ -366,24 +366,20 @@ def generate_gradcam_caption(image, processor, model, max_length=60):
     Generate a detailed analysis of GradCAM visualization using the fine-tuned BLIP model
     """
     try:
-        st.write("Debug: Starting GradCAM caption generation")
         # Process image first
         inputs = processor(image, return_tensors="pt")
         
         # Check for available GPU and move model and inputs
         device = "cuda" if torch.cuda.is_available() else "cpu"
-        st.write(f"Debug: Using device: {device}")
         model = model.to(device)
         inputs = {k: v.to(device) if hasattr(v, 'to') else v for k, v in inputs.items()}
         
         # Generate caption
-        st.write("Debug: Generating caption...")
         with torch.no_grad():
             output = model.generate(**inputs, max_length=max_length, num_beams=5)
             
         # Decode the output
         caption = processor.decode(output[0], skip_special_tokens=True)
-        st.write(f"Debug: Raw caption: {caption}")
         
         # Try to parse the caption based on different possible formats
         try:
@@ -403,8 +399,6 @@ def generate_gradcam_caption(image, processor, model, max_length=60):
             
             # If nothing was extracted using the original format, try alternative formats
             if not formatted_text.strip():
-                st.write("Debug: Trying alternative format parsing")
-                
                 # Check for newer format that might be in the Xception model
                 if ":" in caption:
                     parts = caption.split(":")
@@ -414,11 +408,9 @@ def generate_gradcam_caption(image, processor, model, max_length=60):
                     # As a fallback, just use the entire caption
                     formatted_text = f"**GradCAM Analysis**:\n{caption.strip()}"
         except Exception as parsing_error:
-            st.write(f"Debug: Error parsing caption format: {str(parsing_error)}")
             # Use the entire caption as is
             formatted_text = f"**GradCAM Analysis**:\n{caption.strip()}"
             
-        st.write(f"Debug: Formatted caption complete. Length: {len(formatted_text)}")
         return formatted_text.strip()
         
     except Exception as e:
@@ -997,17 +989,15 @@ def main():
                             # Generate caption for GradCAM overlay image if BLIP model is loaded
                             if st.session_state.blip_model_loaded and overlay:
                                 with st.spinner("Analyzing GradCAM visualization..."):
-                                    st.write("Debug: Starting GradCAM analysis")
                                     gradcam_caption = generate_gradcam_caption(
                                         overlay,
                                         st.session_state.finetuned_processor,
                                         st.session_state.finetuned_model
                                     )
                                     st.session_state.gradcam_caption = gradcam_caption
-                                    st.write(f"Debug: Saved GradCAM caption to session state, length: {len(gradcam_caption) if gradcam_caption else 0}")
                                     
                                     # Display the caption directly here as well for immediate feedback
-                                    st.markdown("### GradCAM Analysis (Direct)")
+                                    st.markdown("### GradCAM Analysis")
                                     st.markdown(gradcam_caption)
                         except Exception as e:
                             st.error(f"Error generating GradCAM: {str(e)}")
@@ -1032,11 +1022,6 @@ def main():
     # Image Analysis Summary section - AFTER Stage 2
     if hasattr(st.session_state, 'current_image') and (hasattr(st.session_state, 'image_caption') or hasattr(st.session_state, 'gradcam_caption')):
         with st.expander("Image Analysis Summary", expanded=True):
-            st.write(f"Debug: Image caption exists: {hasattr(st.session_state, 'image_caption')}")
-            st.write(f"Debug: GradCAM caption exists: {hasattr(st.session_state, 'gradcam_caption')}")
-            if hasattr(st.session_state, 'gradcam_caption'):
-                st.write(f"Debug: GradCAM caption length: {len(st.session_state.gradcam_caption)}")
-            
             # Display images and analysis in organized layout
             col1, col2 = st.columns([1, 2])