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app.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[ ]:
+
+
+import gradio as gr
+from PIL import Image
+import hopsworks
+
+project = hopsworks.login()
+fs = project.get_feature_store()
+
+dataset_api = project.get_dataset_api()
+
+dataset_api.download("Resources/images/pred_passenger.png", overwrite=True)
+dataset_api.download("Resources/images/actual_passenger.png", overwrite=True)
+dataset_api.download("Resources/images/df_recent.png", overwrite=True)
+dataset_api.download("Resources/images/confusion_matrix.png", overwrite=True)
+
+with gr.Blocks() as demo:
+    with gr.Row():
+      with gr.Column():
+          gr.Label("Today's Predicted Image")
+          input_img = gr.Image("pred_passenger.png", elem_id="predicted-img")
+      with gr.Column():          
+          gr.Label("Today's Actual Image")
+          input_img = gr.Image("actual_passenger.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()
+
+
+# In[ ]:
+
+
+
+

requirements.txt

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+hopsworks
+joblib
+scikit-learn