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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()
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