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import gradio as gr
from PIL import Image
import requests
import hopsworks
import joblib
import pandas as pd
project = hopsworks.login()
fs = project.get_feature_store()
mr = project.get_model_registry()
model = mr.get_model("wine_model", version=2)
model_dir = model.download()
model = joblib.load(model_dir + "/wine_model.pkl")
print("Model downloaded")
def wine(type,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,ph,sulphates,alcohol):
print("Calling function")
# df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
df = pd.DataFrame([[type,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,ph,sulphates,alcohol]],
columns=["type","fixed_acidity","volatile_acidity","citric_acid","residual_sugar","chlorides","free_sulfur_dioxide","total_sulfur_dioxide","density","ph","sulphates","alcohol"])
print("Predicting")
print(df)
# 'res' is a list of predictions returned as the label.
res = model.predict(df)
# We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want
# the first element.
# print("Res: {0}").format(res)
print(res)
if (res==float(0)):
wine_url = "https://media.istockphoto.com/id/117068556/sv/foto/bad-wine.jpg?s=2048x2048&w=is&k=20&c=wLOisv5qh9N8bp8AISRo1yP2nOjq_ouvt4sWeZ11yy0="
else :
wine_url = "https://i.ytimg.com/vi/9wFm7wTJ7JU/maxresdefault.jpg"
# wine_url = "https://raw.githubusercontent.com/featurestoreorg/serverless-ml-course/main/src/01-module/assets/" + res[0] + ".png"
img = Image.open(requests.get(wine_url, stream=True).raw)
return img
demo = gr.Interface(
fn=wine,
title="Wine quality Predictive Analytics",
description="Experiment with some factors to predict what quality it is.",
allow_flagging="never",
inputs=[
gr.inputs.Number(default=1.0, label="type"),
gr.inputs.Number(default=7.2, label="fixed_acidity"),
gr.inputs.Number(default=0.33, label="volatile_acidity"),
gr.inputs.Number(default=0.31, label="citric_acid"),
gr.inputs.Number(default=5.44, label="residual_sugar"),
gr.inputs.Number(default=0.056, label="chlorides"),
gr.inputs.Number(default=30.53, label="free_sulfur_dioxide"),
gr.inputs.Number(default=115.74, label="total_sulfur_dioxide"),
gr.inputs.Number(default=0.995, label="density"),
gr.inputs.Number(default=3.21, label="ph"),
gr.inputs.Number(default=0.53, label="sulphates"),
gr.inputs.Number(default=10.49, label="alcohol"),
],
outputs=gr.Image(type="pil"))
demo.launch(debug=True)
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