Update app.py

app.py

@@ -20,6 +20,7 @@ model_path = hf_hub_download(repo_id=repo_id, filename=filename, cache_dir=cache
 # Load the model
 model = tf.keras.models.load_model(model_path) 
 
+
 # Streamlit UI
 st.title("Christmas Tree Classifier")
 st.write("Upload an image of a Christmas tree to classify it:")
@@ -45,4 +46,17 @@ if uploaded_file is not None:
     predicted_class = "Decorated" if prediction[0][0] >= 0.5 else "Undecorated"
 
     # Display the prediction
-    st.write(f"Prediction: {predicted_class}")
+    st.write(f"Prediction: {predicted_class}")
+
+    # Create tabs here (after the main UI elements)
+tab1, tab2 = st.tabs(["Christmas Tree Classifier", "Sample Images"])
+
+# Tab 1: Christmas Tree Classifier
+with tab1:
+    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+    if uploaded_file is not None:
+        # ... (Rest of the code for image processing and prediction) ...
+
+# Tab 2: Sample Images
+with tab2:
+    # ... (Code for Tab 2 remains the same) ...