Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+from PIL import Image
+import hopsworks
+
+hopsworks_iris_api_key = "bP6PFOAzbXllM89C.l9gzwKTyxct786c3V1gwIQEvbQfZnSELxp7UM4RdBhw0eTaqkdl1Ld2a4A32UmR9"
+project = hopsworks.login(api_key_value = hopsworks_iris_api_key)
+fs = project.get_feature_store()
+
+dataset_api = project.get_dataset_api()
+
+dataset_api.download("Resources/images/latest_iris.png")
+dataset_api.download("Resources/images/actual_iris.png")
+dataset_api.download("Resources/images/df_recent.png")
+dataset_api.download("Resources/images/confusion_matrix.png")
+
+with gr.Blocks() as demo:
+    with gr.Row():
+      with gr.Column():
+          gr.Label("Today's Predicted Image")
+          input_img = gr.Image("latest_iris.png", elem_id="predicted-img")
+      with gr.Column():          
+          gr.Label("Today's Actual Image")
+          input_img = gr.Image("actual_iris.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")
+      with gr.Column():          
+          gr.Label("Confusion Maxtrix with Historical Prediction Performance")
+          input_img = gr.Image("confusion_matrix.png", elem_id="confusion-matrix")        
+
+demo.launch()