Update app.py

app.py

@@ -162,17 +162,30 @@ if st.session_state.image is not None:
         if car_data is not None:
             processed_car_data, label_encoders = preprocess_car_data(car_data)
             closest_car = find_closest_car(processed_car_data, label_encoders, make_name, model_name, current_year)
+
+            a, b, c, d = st.columns(4)
+            e, f, g = st.columns(3)
+            
+            a.metric("Year", closest_car['year'], border=True)
+            b.metric("Price", closest_car['price'], border=True)
+            c.metric("Condition", closest_car['condition'], border=True)
+            d.metric("Fuel", closest_car['fuel'], border=True)
+            e.metric("Transmission", closest_car['transmission'], border=True)
+            f.metric("Drive", closest_car['drive'], border=True)
+            g.metric("Type", closest_car['type'], border=True)
+
+
             
             # st.write(f"Closest match in database:")
-            st.write(f"Year: {closest_car['year']}")
+            # st.write(f"Year: {closest_car['year']}")
             # st.write(f"Make: {label_encoders['make'].inverse_transform([closest_car['make']])[0]}")
             # st.write(f"Model: {label_encoders['model'].inverse_transform([closest_car['model']])[0]}")
-            st.write(f"Price: ${closest_car['price']}")
-            st.write(f"Condition: {closest_car['condition']}")
-            st.write(f"Fuel: {closest_car['fuel']}")
-            st.write(f"Transmission: {closest_car['transmission']}")
-            st.write(f"Drive: {closest_car['drive']}")
-            st.write(f"Type: {closest_car['type']}")
+            # st.write(f"Price: ${closest_car['price']}")
+            # st.write(f"Condition: {closest_car['condition']}")
+            # st.write(f"Fuel: {closest_car['fuel']}")
+            # st.write(f"Transmission: {closest_car['transmission']}")
+            # st.write(f"Drive: {closest_car['drive']}")
+            # st.write(f"Type: {closest_car['type']}")
 
         st.divider()