Update app.py

app.py

@@ -23,8 +23,11 @@ def normalize_data(data):
     return df_test_value
 
 def plot_test_data(df_test_value):
-    fig, ax = plt.subplots()
+    fig, ax = plt.subplots(figsize=(12, 6))
     df_test_value.plot(legend=False, ax=ax)
+    ax.set_xlabel("Time")
+    ax.set_ylabel("Value")
+    ax.set_title("Input Test Data")
     return fig
 
 def get_anomalies(df_test_value):
@@ -48,9 +51,12 @@ def plot_anomalies(df_test_value, data, anomalies):
         if np.all(anomalies[data_idx - TIME_STEPS + 1 : data_idx]):
             anomalous_data_indices.append(data_idx)
     df_subset = data.iloc[anomalous_data_indices]
-    fig, ax = plt.subplots()
+    fig, ax = plt.subplots(figsize=(12, 6))
     data.plot(legend=False, ax=ax)
     df_subset.plot(legend=False, ax=ax, color="r")
+    ax.set_xlabel("Time")
+    ax.set_ylabel("Value")
+    ax.set_title("Anomalous Data Points")
     return fig
                                       
 def master(file):
@@ -65,13 +71,13 @@ def master(file):
     plot2 = plot_anomalies(df_test_value, data, anomalies)
     return plot2
 
-outputs = gr.Plot()
+outputs = gr.outputs.Image()
 
-
-iface = gr.Interface(master,
-gr.inputs.File(label="csv file"),
-outputs=outputs, 
-examples=["art_daily_jumpsup.csv"], title="Timeseries Anomaly Detection Using an Autoencoder",
+iface = gr.Interface(
+    fn=master,
+    inputs=gr.inputs.File(label="CSV File"),
+    outputs=outputs,
+    examples=["art_daily_jumpsup.csv"], title="Timeseries Anomaly Detection Using an Autoencoder",
 description = "Anomaly detection of timeseries data.",
                 article = "Space by: <a href=\"https://www.linkedin.com/in/olohireme-ajayi/\">Reme Ajayi</a> <br> Keras Example by <a href=\"https://github.com/pavithrasv/\"> Pavithra Vijay</a>")