Update app.py

app.py

@@ -162,14 +162,14 @@ def infer(inputs, additional_inputs):
     return [gr.ScatterPlot(
             value=df_val,
             x="Prediction",
-            y="True Loss",
+            y="Target",
             title="Scatter",
-            tooltip=["Prediction", "True Loss"],
+            tooltip=["Prediction", "Target"],
             x_lim=[min(min(predictions), min(df_val[y_column]))-0.25, max(max(predictions), max(df_val[y_column]))+0.25],
             y_lim=[min(min(predictions), min(df_val[y_column]))-0.25, max(max(predictions), max(df_val[y_column]))+0.25]
         ), 
         gr.Image(Image.open('tmp.png')),
-        df_val[['True Loss', 'Prediction']], ]
+        df_val[['Target', 'Prediction']], ]
 
 def upload_csv(file):
     df = pd.read_csv(file.name, 
@@ -183,7 +183,7 @@ df = pd.read_csv('data.csv')
 headers = df.columns.tolist()
 
 inputs = [gr.Dataframe(headers=headers, row_count = (8, "dynamic"), datatype='number', col_count=(4,"fixed"), label="Dataset", interactive=1)]
-outputs = [gr.ScatterPlot(), gr.Image(), gr.Dataframe(row_count = (2, "dynamic"), col_count=(2, "fixed"), datatype='number', label="Results", headers=["True Loss", "Pred Loss"])]
+outputs = [gr.ScatterPlot(), gr.Image(), gr.Dataframe(row_count = (2, "dynamic"), col_count=(2, "fixed"), datatype='number', label="Results", headers=["Target", "Prediction"])]
 
 with gr.Blocks() as demo: