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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("incident_modal", version=1)
model_dir = model.download()
model = joblib.load(model_dir + "/incident_model.pkl")
def incident(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)
incident = model.predict(np.asarray(input_list).reshape(1, -1))
incident_url = "https://raw.githubusercontent.com/Hope-Liang/ID2223Project/main/images/" + incident[0] + ".png"
img = Image.open(requests.get(incident_url, stream=True).raw)
return img
demo = gr.Interface(
fn=incident,
title="Incident Predictive Analytics",
description="Experiment with incident features/attributes to predict what kind of incident category took place.",
allow_flagging="never",
inputs=[
gr.inputs.Textbox(default="Saturday", label="Incident Day of Week (Saturday, Sunday etc...)"),
gr.inputs.Textbox(default="Il", label="Report Type Code (Il, IS, Vl, VS)"),
gr.inputs.Number(default="Northern", label="Police District (Northern, Bayview, Southern, Mission, Ingleside, Tenderloin, Taraval, Central, Richmond, Park)"),
gr.inputs.Number(default=1.0, label="latitude"),
gr.inputs.Number(default=1.0, label="longitude"),
gr.inputs.Number(default=2023, label="Incident Year (e.g 2019)"),
gr.inputs.Number(default=1, label="Incident Month (1-12)"),
gr.inputs.Number(default=1, label="Incident Hour (0-23)"),
],
outputs=gr.Image(type="pil"))
demo.launch()