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e1563a8 0c5e018 e1563a8 6ce7110 e1563a8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | 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=1)
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, 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, density, ph, sulphates, alcohol]],
columns=["type", "fixed_acidity", "volatile_acidity", "citric_acid", "residual_sugar", "chlorides"
, "free_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)
wine_url = "https://raw.githubusercontent.com/Epoxyra/id2223_lab1_wine/main/images/" + res[0] + ".jpg"
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 different properties of wine to predict what is its quality.",
allow_flagging="never",
inputs=[
gr.Number(value=1, label="wine color (1 for red, 0 for white)"),
gr.Number(value=8.0, label="fixed acidity (g/L)"),
gr.Number(value=8.0, label="volatile acidity (g/L)"),
gr.Number(value=8.0, label="citric acid (g/L)"),
gr.Number(value=2.5, label="residual sugar (g/L)"),
gr.Number(value=2.5, label="chlorides (g/L)"),
gr.Number(value=16.0, label="free_sulfur_dioxide (mg/l)"),
gr.Number(value=46.0, label="density (g/mL)"),
gr.Number(value=46.0, label="ph"),
gr.Number(value=46.0, label="sulphates (mg/L)"),
gr.Number(value=10.0, label="alcohol(°)"),
],
outputs=gr.Image(type="pil"))
demo.launch(debug=True)
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