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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) |