Update app.py

app.py

@@ -41,17 +41,25 @@ st.write("Upload a brain scan (JPG format), and the model will predict its class
 uploaded_file = st.file_uploader("Choose a JPG image...", type="jpg")
 
 if uploaded_file is not None:
-    st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
-    st.write("Detecting...")
+    # Display the uploaded image on the left side
+    col1, col2 = st.columns([2, 1])  # Create two columns
 
-    # Load and preprocess the image
-    processed_image = load_and_preprocess_image(uploaded_file)
+    with col1:
+        st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
     
-    # Make prediction
-    predicted_class_index = predict_image(processed_image)
-    
-    # Get predicted class label
-    predicted_class_label = get_class_label(predicted_class_index)
-    
-    # Display the result
-    st.markdown(f"<h3 style='color: #4CAF50;'>The predicted class is: <strong>{predicted_class_label}</strong></h3>", unsafe_allow_html=True)
+    with col2:
+        # Button to trigger prediction
+        if st.button("Detect"):
+            st.write("Detecting...")
+            # Load and preprocess the image
+            processed_image = load_and_preprocess_image(uploaded_file)
+            
+            # Make prediction
+            predicted_class_index = predict_image(processed_image)
+            
+            # Get predicted class label
+            predicted_class_label = get_class_label(predicted_class_index)
+            
+            # Center display for the prediction result
+            st.markdown(f"<h3 style='color: #4CAF50; text-align: center;'>The predicted class is: <strong>{predicted_class_label}</strong></h3>", unsafe_allow_html=True)
+