Update app.py

app.py

@@ -68,10 +68,18 @@ def master(file):
     # predict
     anomalies = get_anomalies(df_test_value)
     # plot anomalous data points
-    plot2, anomalous_indices = plot_anomalies(df_test_value, data, anomalies)
-    return plot2, anomalous_indices
+    plot2, anomalous_data_indices = plot_anomalies(df_test_value, data, anomalies)
+    # convert indices to string
+    anomalous_data_indices_str = [str(idx) for idx in anomalous_data_indices]
+    return format_output(plot2, anomalous_data_indices_str)
 
-outputs = [gr.outputs.Image(), "text"]
+def format_output(plot, indices):
+    # Combine the plot and indices into a single output
+    fig, ax = plot
+    ax.text(0.5, -0.2, f"Anomalous Data Indices: {', '.join(indices)}", transform=ax.transAxes, fontsize=12, ha='center')
+    return fig
+
+outputs = gr.outputs.Image()
 
 iface = gr.Interface(
     fn=master,
@@ -82,5 +90,9 @@ iface = gr.Interface(
     description="Anomaly detection of timeseries data."
 )
 
-# Display the interface
 iface.launch()
+```
+
+With this code, the interface will display the plot of the anomalous data points along with the indices of the anomalous data points below the plot. The user can upload a CSV file, and the interface will generate the plot and detect the anomalies in the timeseries data.
+
+I hope this helps! Let me know if you have any further questions.