Update app.py

app.py

@@ -803,26 +803,6 @@ elif page == "📊 Model Performance":
     else:
         st.dataframe(df_cls, width='content')
 
-        col1, col2 = st.columns(2)
-        with col1:
-            st.markdown("#### Accuracy")
-            st.bar_chart(
-                df_cls.set_index("Model")["Accuracy"],
-                width=520,
-            )
-        with col2:
-            st.markdown("#### F1 (weighted)")
-            st.bar_chart(
-                df_cls.set_index("Model")["F1 (weighted)"],
-                width=520,
-            )
-
-        st.markdown("#### Inference Speed (images/sec)")
-        st.bar_chart(
-            df_cls.set_index("Model")["Images/sec"],
-            width=520,
-        )
-
     # --- YOLO metrics ---
     st.markdown("### 📦 YOLOv8 Detection Model")
     yolo_m = load_yolo_metrics()
@@ -835,13 +815,27 @@ elif page == "📊 Model Performance":
         
         col1, col2, col3 = st.columns(3)
         with col1:
-            st.metric("Precision", f"{overall.get('precision', 0):.3f}")
+            st.metric("Precision", f"{overall.get("precision", 0):.3f}")
             st.metric("mAP@0.5", f"{overall.get('mAP50', 0):.3f}")
         with col2:
-            st.metric("Recall", f"{overall.get('recall', 0):.3f}")
+            st.metric("Recall", f"{overall.get("recall", 0):.3f}")
             st.metric("mAP@0.5:0.95", f"{overall.get('mAP50_95', 0):.3f}")
         with col3:
             st.metric("YOLO FPS", f"{speed.get('fps', 0):.2f}")
+ 
+    col1, col2 = st.columns(2)
+    with col1:
+        st.markdown("#### Accuracy")
+        st.bar_chart(
+            df_cls.set_index("Model")["Accuracy"],
+            width=520,
+        )
+    with col2:
+        st.markdown("#### F1 (weighted)")
+        st.bar_chart(
+            df_cls.set_index("Model")["F1 (weighted)"],
+            width=520,
+        )
 
     # --- Confusion matrix & comparison plots (if available) ---
     st.markdown("### 📈 Comparison Plots & Confusion Matrices")