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import gradio as gr
import numpy as np
from PIL import Image
import requests
import hopsworks
import joblib
project = hopsworks.login()
fs = project.get_feature_store()
mr = project.get_model_registry()
model = mr.get_model("titanic_modal", version=1)
model_dir = model.download()
model = joblib.load(model_dir + "/titanic_model.pkl")
def titanic(pclass, sex, age, sibsp, parch, fare, embarked):
input_list = []
if sex == 'female':
input_list.append(1.0)
input_list.append(0.0)
elif sex == 'male':
input_list.append(0.0)
input_list.append(1.0)
else:
print("ERROR!")
exit()
if embarked == "C":
input_list.append(1.0)
input_list.append(0.0)
input_list.append(0.0)
elif embarked == "Q":
input_list.append(0.0)
input_list.append(1.0)
input_list.append(0.0)
elif embarked == "S":
input_list.append(0.0)
input_list.append(0.0)
input_list.append(1.0)
else:
print("ERROR!")
exit()
if age < 18:
input_list.append(1.0)
elif age < 55:
input_list.append(2.0)
else:
input_list.append(3.0)
input_list.append(sibsp)
input_list.append(parch)
input_list.append(fare)
input_list.append(pclass)
# 'res' is a list of predictions returned as the label.
res = model.predict(np.asarray(input_list).reshape(1, -1))
# We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want
# the first element.
if res[0] == 1.0:
survive_url = "https://raw.githubusercontent.com/Hope-Liang/ID2223Lab1/main/serverless-ml-titanic/images/survived.png"
else:
survive_url = "https://raw.githubusercontent.com/Hope-Liang/ID2223Lab1/main/serverless-ml-titanic/images/died.png"
img = Image.open(requests.get(survive_url, stream=True).raw)
return img
demo = gr.Interface(
fn=titanic,
title="Titanic Survival Predictive Analytics",
description="Experiment with titanic passenger features to predict whether survived or not.",
allow_flagging="never",
inputs=[
gr.inputs.Number(default=1, label="Pclass (1,2,3)"),
gr.inputs.Textbox(default="female", label="Sex (female/male)"),
gr.inputs.Number(default=30.0, label="age (years)"),
gr.inputs.Number(default=1.0, label="SibSp"),
gr.inputs.Number(default=1.0, label="Parch"),
gr.inputs.Number(default=10.0, label="Fare (GBP)"),
gr.inputs.Textbox(default="S", label="Embarked (S,C,Q)")
],
outputs=gr.Image(type="pil"))
demo.launch()
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