Update app.py

app.py

@@ -1,6 +1,5 @@
 """
 Hugging Face Spaces - Pneumonia Detection App
-
 This is a self-contained version for Hugging Face Spaces deployment.
 Copy this file as 'app.py' to your HF Spaces repository.
 """
@@ -13,6 +12,7 @@ from PIL import Image
 import numpy as np
 from pytorch_grad_cam import GradCAM
 from pytorch_grad_cam.utils.image import show_cam_on_image
+import time
 
 # =============================================================================
 # Configuration
@@ -192,14 +192,16 @@ if model_loaded:
         image = Image.open(uploaded_file).convert("RGB")
 
         with col1:
-            st.image(image, caption="Uploaded X-Ray", width="stretch")
-            analyze = st.button("🔬 Analyze Image", type="primary", width="stretch")
+            st.image(image, caption="Uploaded X-Ray", use_container_width=True)
+            analyze = st.button("🔬 Analyze Image", type="primary", use_container_width=True)
 
         if analyze:
             with col2:
                 with st.spinner("Analyzing..."):
+                    start_time = time.time()
                     pred_class, confidence, img_tensor = predict(model, image, device)
                     cam_image, original = generate_gradcam(model, img_tensor, device)
+                    inference_time = (time.time() - start_time) * 1000
 
                 # Results
                 if pred_class == "PNEUMONIA":
@@ -217,11 +219,17 @@ if model_loaded:
                     </div>
                     """, unsafe_allow_html=True)
 
+                # Metrics row
+                m1, m2, m3 = st.columns(3)
+                m1.metric("Prediction", pred_class)
+                m2.metric("Confidence", f"{confidence:.1%}")
+                m3.metric("Time", f"{inference_time:.0f}ms")
+
                 # Grad-CAM
                 st.subheader("🔥 Grad-CAM")
                 gcol1, gcol2 = st.columns(2)
-                gcol1.image(original, caption="Original", width="stretch")
-                gcol2.image(cam_image, caption="Heatmap", width="stretch")
+                gcol1.image(original, caption="Original", use_container_width=True)
+                gcol2.image(cam_image, caption="Heatmap", use_container_width=True)
 
                 st.warning("**Disclaimer:** For educational purposes only. Consult a healthcare professional.")