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import gradio as gr |
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def predict_amputation(age, gender, race, diabetes_type): |
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return "ALLAH" |
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title = "DIabetes-related Amputation Risk Calculator (DIARC)" |
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description = "A diabetes-related amputation machine learning model trained on the diabetes dataset from the Inkosi Albert Luthuli Central Hospital (IALCH) in Durban, KwaZulu-Natal, South Africa." |
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iface = gr.Interface( |
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fn=predict_amputation, |
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title=title, |
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description=description, |
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inputs=[gr.inputs.Slider(minimum=0,maximum=100, step=1, label="Age"), gr.inputs.Dropdown(["Female", "Male"], default="Male", label="Gender"), gr.inputs.Dropdown(["Asian", "Black", "Coloured", "White", "Other"], default="Asian", label="Race"), gr.inputs.Dropdown(["1", "2"], default="1", label="Diabetes Type")], |
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outputs="text", |
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theme="darkhuggingface", |
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examples=[ |
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[50, "Male", "Black", 2], |
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[76, "Female", "Asian", 2], |
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[12, "Female", "White", 1], |
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[30, "Male", "Coloured", 1], |
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[65, "Female", "Other", 2], |
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], |
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) |
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iface.test_launch() |
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if __name__ == "__main__": |
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iface.launch() |
