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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(project = "Scalable_ML_lab1")
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(fixed_acidity, volatile_acidity, citric_acid, residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,ph,sulphates,alchohol):
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,total_sulfur_dioxide,density,ph,sulphates,alchohol]],
columns=['fixed_acidity', 'volatile_acidity', 'citric_acid', 'residual_sugar','chlorides','free_sulfur_dioxide','total_sulfur_dioxide','density','ph','sulphates','alchohol'])
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)
# flower_url = "https://raw.githubusercontent.com/featurestoreorg/serverless-ml-course/main/src/01-module/assets/" + res[0] + ".png"
image_url = "https://raw.githubusercontent.com/GGmorello/serverless-ml/main/lab1/wine/numbers/" + str(res[0]) + ".png"
img = Image.open(requests.get(image_url, stream=True).raw)
return img
demo = gr.Interface(
fn=wine,
title="Wine Quality Predictive Analytics",
description="Experiment with the wine features to predict the quality of the wine",
allow_flagging="never",
inputs=[
gr.Number(value=8.22, label="fixed_acidity"),
gr.Number(value=0.54, label="volatile_acidity"),
gr.Number(value=0.26, label="citric_acid"),
gr.Number(value=2.58, label="residual_sugar"),
gr.Number(value=0.09, label="chlorides"),
gr.Number(value=16.76, label="free_sulfur_dioxide"),
gr.Number(value=47.93, label="total_sulfur_dioxide"),
gr.Number(value=0.996, label="density"),
gr.Number(value=3.31, label="ph"),
gr.Number(value=0.66, label="sulphates"),
gr.Number(value=10.36, label="alchohol")
],
outputs=gr.Image(type="pil"))
demo.launch(debug=True) |