Spaces:
Runtime error
Runtime error
File size: 2,078 Bytes
706b0ec a747208 706b0ec a747208 706b0ec 4c3a182 6186436 706b0ec bc7b153 706b0ec 8462ac3 706b0ec |
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 |
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_class_model", version=1)
model_dir = model.download()
model = joblib.load(model_dir + "/wine_class_model.pkl")
print("Model downloaded")
def wine_quality_class(fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, density, ph, sulphates, alcohol, wine_type_name):
print("Calling function")
type_white = 1.0 if wine_type_name == "white" else 0.0
df = pd.DataFrame([[fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, density, ph, sulphates, alcohol, type_white]],
columns=['fixed_acidity','volatile_acidity','citric_acid','residual_sugar','chlorides','free_sulfur_dioxide','density','ph','sulphates','alcohol','type_white'])
print("Predicting")
print(df)
# 'res' is a list of predictions returned as the label.
res = model.predict(df)
return res[0]
demo = gr.Interface(
fn=wine_quality_class,
title="Wine Quality Prediction",
description="Predicts the quality of wine based on the input parameters",
allow_flagging="never",
inputs=[
gr.inputs.Number(default=8.2, label="fixed acidity"),
gr.inputs.Number(default=0.28, label="volatile acidity"),
gr.inputs.Number(default=0.4, label="citric acid"),
gr.inputs.Number(default=2.4, label="residual sugar"),
gr.inputs.Number(default=0.052, label="chlorides"),
gr.inputs.Number(default=4, label="free sulfur dioxide"),
gr.inputs.Number(default=0.99356, label="density"),
gr.inputs.Number(default=3.33, label="ph"),
gr.inputs.Number(default=0.7, label="sulphates"),
gr.inputs.Number(default=12.8, label="alcohol"),
gr.inputs.Dropdown(["white", "red"], default="red", label="wine type")
],
outputs=gr.Textbox()
)
demo.launch(debug=True)
|