m

app.py

@@ -182,115 +182,72 @@ def save_results(results, original_images):
 
 # --- Streamlit Interface ---
 def main():
-    st.set_page_config(layout="wide", page_title="Glaucoma Screening Tool")
+    # Use the old layout setting method
+    st.set_page_config(layout="wide")
     
-    print("App started") # Debug print
+    # Use simple title instead of markdown
+    st.title("Glaucoma Screening from Retinal Fundus Images")
+    st.write("Upload retinal images for automated glaucoma detection and optic disc/cup segmentation")
     
-    st.markdown("""
-        <h1 style='text-align: center;'>Glaucoma Screening from Retinal Fundus Images</h1>
-        <p style='text-align: center; color: gray;'>Upload retinal images for automated glaucoma detection and optic disc/cup segmentation</p>
-        """, unsafe_allow_html=True)
-    
-    # Simple sidebar without columns
-    st.sidebar.markdown("### 📤 Upload Images")
+    # Sidebar using old method
+    st.sidebar.title("Upload Images")
+    st.set_option('deprecation.showfileUploaderEncoding', False)  # Important for old versions
     uploaded_files = st.sidebar.file_uploader(
-        "Upload Retinal Images", 
+        "Upload retinal images", 
         type=['png', 'jpeg', 'jpg'], 
-        accept_multiple_files=True,
-        help="Support multiple images in PNG, JPEG formats"
+        accept_multiple_files=True
     )
     
-    print(f"Files uploaded: {uploaded_files}") # Debug print
-    
-    st.sidebar.markdown("### Settings")
-    max_batch = st.sidebar.number_input("Max Batch Size", 
-        min_value=1, 
-        max_value=100, 
-        value=20)
+    # Simple explanation in sidebar
+    st.sidebar.markdown("""
+        ### Understanding Results:
+        - Diagnosis Confidence: AI certainty level
+        - VCDR: Cup to disc ratio (>0.7 high risk)
+        - Segmentation: Accuracy of detection
+    """)
     
     if uploaded_files:
-        print("Processing uploaded files") # Debug print
-        
-        if len(uploaded_files) > max_batch:
-            st.warning(f"Please upload maximum {max_batch} images at once.")
-            return
-
-        st.markdown(f"Total images: {len(uploaded_files)}")
-        st.markdown(f"Using: {'GPU' if torch.cuda.is_available() else 'CPU'}")
+        st.write("Loading AI models...")
         
         try:
-            # Initialize model
-            print("Initializing model") # Debug print
             model = GlaucomaModel(device=torch.device("cuda:0" if torch.cuda.is_available() else "cpu"))
             
-            # Process images
-            images_data = []
-            original_images = []
-            print("Starting image processing") # Debug print
-            
             for file in uploaded_files:
                 try:
-                    print(f"Processing file: {file.name}") # Debug print
+                    # Process each image
+                    st.write(f"Processing: {file.name}")
                     image = Image.open(file).convert('RGB')
                     image_np = np.array(image)
-                    images_data.append((file.name, image_np))
-                    original_images.append(image_np)
+                    
+                    # Get predictions
+                    disease_idx, disc_cup_image, vcdr, cls_conf, cup_conf, disc_conf, cropped_image = model.process(image_np)
+                    
+                    # Display results using old methods
+                    st.write("---")
+                    st.write(f"Results for {file.name}")
+                    
+                    # Show diagnosis
+                    diagnosis = model.cls_id2label[disease_idx]
+                    st.write(f"Diagnosis: {diagnosis}")
+                    st.write(f"Confidence: {cls_conf:.1f}%")
+                    st.write(f"VCDR: {vcdr:.3f}")
+                    
+                    # Display images
+                    st.write("Segmentation Result:")
+                    st.image(disc_cup_image, caption="Green: Optic Disc | Red: Optic Cup")
+                    st.write("Region of Interest:")
+                    st.image(cropped_image, caption="ROI")
+                    
                 except Exception as e:
-                    print(f"Error processing file {file.name}: {str(e)}") # Debug print
-                    st.error(f"Error loading {file.name}: {str(e)}")
+                    st.error(f"Error processing {file.name}: {str(e)}")
                     continue
             
-            if not images_data:
-                st.error("No valid images to process!")
-                return
-                
-            progress = st.progress(0)
-            st.write(f"Processing {len(images_data)} images...")
-            
-            # Process all images
-            print("Starting batch processing") # Debug print
-            results = process_batch(model, images_data, progress)
-            print(f"Batch processing complete. Results: {len(results)}") # Debug print
+            # Simple summary at the end
+            st.write("---")
+            st.write("Processing complete!")
             
-            if results:
-                print("Showing results") # Debug print
-                # Show results one by one
-                for result in results:
-                    st.markdown(f"### Results for {result['file_name']}")
-                    st.markdown(f"**Diagnosis:** {result['diagnosis']}")
-                    st.markdown(f"**Confidence:** {result['confidence']:.1f}%")
-                    st.markdown(f"**VCDR:** {result['vcdr']:.3f}")
-                    
-                    # Display images
-                    st.image(result['processed_image'], caption="Segmentation")
-                    st.image(result['cropped_image'], caption="ROI")
-                    st.markdown("---")
-                
-                # Generate downloads
-                print("Generating ZIP file") # Debug print
-                zip_data = save_results(results, original_images)
-                
-                st.markdown("### Download Results")
-                # Replace download_button with direct download link
-                filename = f"glaucoma_screening_{datetime.now().strftime('%Y%m%d_%H%M%S')}.zip"
-                st.markdown(
-                    f'<a href="data:application/zip;base64,{base64.b64encode(zip_data).decode()}" download="{filename}">Download All Results (ZIP)</a>', 
-                    unsafe_allow_html=True
-                )
-                
-                # Simple summary
-                st.markdown("### Summary")
-                glaucoma_count = sum(1 for r in results if r['diagnosis'] == 'Glaucoma')
-                normal_count = len(results) - glaucoma_count
-                st.markdown(f"**Total Processed:** {len(results)}")
-                st.markdown(f"**Glaucoma Detected:** {glaucoma_count}")
-                st.markdown(f"**Normal:** {normal_count}")
-                st.markdown(f"**Average Confidence:** {sum(r['confidence'] for r in results) / len(results):.1f}%")
-        
         except Exception as e:
-            print(f"Error in main processing: {str(e)}") # Debug print
             st.error(f"An error occurred: {str(e)}")
 
 if __name__ == "__main__":
-    print("Starting main") # Debug print
     main()