app.py

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(sex, age, sibsp, parch, fare, embarked, pclass): #check if the order is the same in the feature hopsworks
    input_list = []
    input_list.append(sex)
    input_list.append(age)
    input_list.append(sibsp)
    input_list.append(parch)
    input_list.append(fare)
    if embarked == 1:
        input_list.append(1) 
        input_list.append(0)
        input_list.append(0)
    elif embarked == 2:
        input_list.append(0) 
        input_list.append(1)
        input_list.append(0)
    else:
        input_list.append(0) 
        input_list.append(0)
        input_list.append(1)

    if pclass == 1:
        input_list.append(1) 
        input_list.append(0)
        input_list.append(0)
    elif pclass == 2:
        input_list.append(0) 
        input_list.append(1)
        input_list.append(0)
    else:
        input_list.append(0) 
        input_list.append(0)
        input_list.append(1)
        
    # '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:
       image_url = "https://i.ibb.co/0X0JTcx/survive.jpg"
    else:
       image_url = "https://i.ibb.co/C8SdRn2/drowning.jpg"
    img = Image.open(requests.get(image_url, stream=True).raw)            
    return img
    #return res[0]
        
demo = gr.Interface(
    fn=titanic,
    title="Titanic Predictive Analytics",
    description="Experiment with titanic dataset to predicte if a passenger is survived or not",
    allow_flagging="never",
    inputs=[
        gr.inputs.Number(default=1.0, label="sex"),
        gr.inputs.Number(default=1.0, label="age"),
        gr.inputs.Number(default=1.0, label="sibsp"),
        gr.inputs.Number(default=1.0, label="parch"),
        gr.inputs.Number(default=1.0, label="fare"),
        gr.inputs.Number(default=1.0, label="embarked"),
        gr.inputs.Number(default=1.0, label="pclass"),
        ],
    outputs=gr.Image(type="pil"))
    #outputs = "number"
demo.launch(debug=True)