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import gradio as gr |
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import numpy as np |
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import requests |
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import hopsworks |
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import joblib |
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project = hopsworks.login() |
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fs = project.get_feature_store() |
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mr = project.get_model_registry() |
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model = mr.get_model("titanic_modal", version=2) |
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model_dir = model.download() |
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model = joblib.load(model_dir + "/titanic_model.pkl") |
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def titanic(age, sex, pclass, fare): |
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input_list = [] |
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input_list.append(age) |
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input_list.append(sex) |
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input_list.append(pclass) |
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input_list.append(fare) |
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res = model.predict(np.asarray(input_list).reshape(1, -1)) |
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if res[0] == 0: |
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output = "This individual probably survived the Titanic." |
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else: |
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output = "This individual unfortunately probably did not survive the Titanic." |
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return output |
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demo = gr.Interface( |
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fn=titanic, |
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title="Titanic survivor analytics", |
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description="Experiment with personal data to predict whether a person would survive the Titanic", |
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allow_flagging="never", |
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inputs=[ |
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gr.inputs.Number(default=30.0, label=" Age "), |
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gr.inputs.Number(default=1, label=" Sex (0 = Female, 1 = Male) "), |
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gr.inputs.Number(default=2, label=" Ticket class (1 = first, 2 = second, 3 = third) "), |
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gr.inputs.Number(default=1.0, label=" Passenger fare (Positive real number)"), |
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], |
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outputs=gr.outputs.Textbox(label='Prediction')) |
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demo.launch() |
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