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import gradio as gr
from PIL import Image, ImageDraw, ImageFont
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(fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides,
free_sulfur_dioxide, density, ph, sulphates, alcohol, type_red):
print("Calling function")
# df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
df = pd.DataFrame([[fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides,
free_sulfur_dioxide, density, ph, sulphates, alcohol, type_red]],
columns=['fixed_acidity', 'volatile_acidity', 'citric_acid', 'residual_sugar', 'chlorides',
'free_sulfur_dioxide', 'density', 'ph', 'sulphates', 'alcohol', 'type_red'])
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)
star_url = "https://raw.githubusercontent.com/SamuelHarner/review-images/main/images/" + str(res[0]+1) + "_stars.png"
img = Image.open(requests.get(star_url, stream=True).raw)
return img
demo = gr.Interface(
fn=wine,
title="Wine Quality Predictive Analytics",
description="Experiment with fixed_acidity, citric_acid, type, chlorides, volatile_acidity, density, alcohol"
"to predict of which quality the wine is.",
allow_flagging="never",
inputs=[
gr.inputs.Number(default=7.2, label="fixed acidity (3.8 ... 15.9)"),
gr.inputs.Number(default=0.34, label="volatile acidity (0.00 ... 1.58)"),
gr.inputs.Number(default=0.32, label="citric acid (0.00 ... 1.66)"),
gr.inputs.Number(default=0, label="type (0...red, 1...white)"),
gr.inputs.Number(default=10.5, label="alcohol (8.0 ... 14.9"),
gr.inputs.Number(default=0.99, label="density (0.99 ... 1.04)"),
gr.inputs.Number(default=0.06, label="chlorides (0.00 ...0.61)"),
gr.inputs.Number(default=5.07, label="residual sugar (0.60 ...65.80)"),
gr.inputs.Number(default=30.06, label="free sulfur dioxide (1.0 ...289.0)"),
gr.inputs.Number(default=3.22, label="pH (2.72 ...4.01)"),
gr.inputs.Number(default=0.53, label="sulphates (0.00 ...2.00)"),
],
outputs=gr.Image(type="pil"))
demo.launch(debug=True)
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