Updated monitor

app.py

@@ -9,23 +9,23 @@ fs = project.get_feature_store()
 
 dataset_api = project.get_dataset_api()
 
-#dataset_api.download("Resources/images/latest_iris.png") # fix later
-#dataset_api.download("Resources/images/actual_iris.png")
-#dataset_api.download("Resources/images/df_recent.png")
-#dataset_api.download("Resources/images/confusion_matrix.png")
+dataset_api.download("Resources/wine_images/latest_wine.png") # fix later
+dataset_api.download("Resources/wine_images/actual_wine.png")
+dataset_api.download("Resources/wine_images/df_recent.png")
+dataset_api.download("Resources/wine_images/confusion_matrix.png")
 
 with gr.Blocks() as demo:
     with gr.Row():
       with gr.Column():
-          gr.Label("Today's Predicted Wine Quality")
-          #input_img = gr.Image("latest_iris.png", elem_id="predicted-img")
+          gr.Label("Today's Predicted Wine")
+          input_img = gr.Image("latest_wine.png", elem_id="predicted-img")
       with gr.Column():          
-          gr.Label("Today's Actual Wine Quality")
-          #input_img = gr.Image("actual_iris.png", elem_id="actual-img")        
+          gr.Label("Today's Actual Wine")
+          input_img = gr.Image("actual_wine.png", elem_id="actual-img")        
     with gr.Row():
       with gr.Column():
           gr.Label("Recent Prediction History")
-          #input_img = gr.Image("df_recent.png", elem_id="recent-predictions")
+          input_img = gr.Image("df_recent.png", elem_id="recent-predictions")
       with gr.Column():          
           gr.Label("Confusion Maxtrix with Historical Prediction Performance")
           #input_img = gr.Image("confusion_matrix.png", elem_id="confusion-matrix")