app.py

import gradio as gr
from PIL import Image
import hopsworks
    
project = hopsworks.login(project = "Scalable_ML_lab1")
fs = project.get_feature_store()

dataset_api = project.get_dataset_api()
    
dataset_api.download("Resources/images/latest_quality.png",overwrite = True)
dataset_api.download("Resources/images/actual_quality.png",overwrite = True)
dataset_api.download("Resources/images/wine_df_recent.png",overwrite = True)
dataset_api.download("Resources/images/wine_confusion_matrix.png",overwrite = True)
    
with gr.Blocks() as demo:
    with gr.Row():
      with gr.Column():
          gr.Label("Today's Predicted Qualtiy")
          input_img = gr.Image("latest_quality.png", elem_id="predicted-img")
      with gr.Column():          
          gr.Label("Today's Actual Quality")
          input_img = gr.Image("actual_quality.png", elem_id="actual-img")        
    with gr.Row():
      with gr.Column():
          gr.Label("Recent Prediction History")
          input_img = gr.Image("wine_df_recent.png", elem_id="recent-predictions")
      with gr.Column():          
          gr.Label("Confusion Maxtrix with Historical Prediction Performance")
          input_img = gr.Image("wine_confusion_matrix.png", elem_id="confusion-matrix")        
        
demo.launch(share=True)