import joblib
import pandas as pd
import streamlit as st 

model = joblib.load('modelB.joblib')
unique_values = joblib.load('unique_valuesB.joblib')
    
unique_gender =  unique_values["Gender"]
def BMI_Cat(BMI):
    if BMI == 0:
        return "Extremly Weak"
    elif BMI == 1:
        return "Weak"
    elif BMI == 2:
        return "Normal"
    elif BMI == 3:
        return "Overweight"
    elif BMI == 4:
        return "Obesity"
    elif BMI == 5:
        return "Extremly Obesity"

def main():
    st.title("BMI Predict")

    with st.form("questionaire"):
        Gender = st.selectbox("Gender",unique_gender)
        Height = st.slider("Height", min_value=140, max_value=199)
        Weight = st.slider("Weight", min_value=50, max_value=160)

        clicked = st.form_submit_button("BMI Result")
        if clicked:
            result=model.predict(pd.DataFrame({"Gender": [Gender],
                                               "Height": [Height],
                                               "Weight": [Weight]}))
            result= BMI_Cat(result[0])
            st.success('The predicted BMI is {}'.format(result))

if __name__=='__main__':
    main()