m

app.py

@@ -208,8 +208,9 @@ def main():
         
         st.markdown("### 📊 Processing Stats")
         if 'processed_count' in st.session_state:
-            st.metric("Images Processed", st.session_state.processed_count)
-        
+            # Replace st.metric with regular markdown
+            st.markdown(f"**Images Processed:** {st.session_state.processed_count}")
+
         st.markdown("---")
         
         # Add batch size limit
@@ -256,59 +257,8 @@ def main():
         results = process_batch(model, images_data, progress_bar)
         
         if results:
-            # Add summary statistics
-            st.markdown("### 📊 Summary Statistics")
-            glaucoma_count = sum(1 for r in results if r['diagnosis'] == 'Glaucoma')
-            normal_count = len(results) - glaucoma_count
-            
-            cols = st.columns(4)
-            with cols[0]:
-                st.metric("Total Processed", len(results))
-            with cols[1]:
-                st.metric("Glaucoma Detected", glaucoma_count)
-            with cols[2]:
-                st.metric("Normal", normal_count)
-            with cols[3]:
-                avg_conf = sum(r['confidence'] for r in results) / len(results)
-                st.metric("Avg Confidence", f"{avg_conf:.1f}%")
-            
-            # Add filter options
-            st.markdown("### 🔍 Filter Results")
-            show_only = st.multiselect(
-                "Show cases:",
-                ["All", "Glaucoma", "Normal"],
-                default=["All"]
-            )
-            
-            # Filter results based on selection
-            filtered_results = results
-            if "All" not in show_only:
-                filtered_results = [
-                    r for r in results 
-                    if (r['diagnosis'] == 'Glaucoma' and 'Glaucoma' in show_only) or
-                       (r['diagnosis'] == 'Normal' and 'Normal' in show_only)
-                ]
-            
-            # Display filtered results
-            for result in filtered_results:
-                with st.expander(
-                    f"📋 {result['file_name']} - {result['diagnosis']} ({result['confidence']:.1f}% confidence)"
-                ):
-                    cols = st.columns(3)
-                    with cols[0]:
-                        st.image(result['processed_image'], caption="Segmentation", use_column_width=True)
-                    with cols[1]:
-                        st.image(result['cropped_image'], caption="ROI", use_column_width=True)
-                    with cols[2]:
-                        st.write("### Metrics")
-                        st.write(f"Diagnosis: {result['diagnosis']}")
-                        st.write(f"Confidence: {result['confidence']:.1f}%")
-                        st.write(f"VCDR: {result['vcdr']:.3f}")
-                        st.write(f"Cup Confidence: {result['cup_conf']:.1f}%")
-                        st.write(f"Disc Confidence: {result['disc_conf']:.1f}%")
-
-            # Update session state
-            st.session_state.processed_count += len(results)
+            # Generate ZIP with results
+            zip_data = save_results(results, original_images)
             
             # Add export options
             st.markdown("### 📥 Export Options")
@@ -316,7 +266,7 @@ def main():
             with col1:
                 st.download_button(
                     label="📥 Download All Results (ZIP)",
-                    data=zip_data,
+                    data=zip_data,  # Now zip_data is properly defined
                     file_name=f"glaucoma_screening_{datetime.now().strftime('%Y%m%d_%H%M%S')}.zip",
                     mime="application/zip"
                 )