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import joblib
import pandas as pd
import streamlit as st
model = joblib.load('rf.joblib')
unique_values = joblib.load('unique_values1.joblib')
unique_sex = unique_values["Gender"]
unique_occupation = unique_values["Occupation"]
unique_ฺBMI = unique_values["BMI Category"]
unique_Blood = unique_values["Blood Pressure"]
def main():
st.title("Sleeping Health")
with st.form("questionaire"):
Gender = st.selectbox("Gender", unique_sex)
age = st.slider("Age", min_value=1, max_value=100)
occupation = st.selectbox("Occupation", unique_occupation)
Sleep_Duration = st.slider("Sleep Duration", min_value=0, max_value=24)
Quality_of_Sleep = st.slider("Quality of Sleep", min_value=1, max_value=10)
Physical_Activity_Level = st.slider("Quality of Sleep", min_value=0, max_value=1440)
BMI_Category = st.selectbox("ฺBMI Category", unique_ฺBMI)
Blood_Pressure = st.selectbox("Blood Pressure", unique_Blood)
Heart_Rate = st.slider("Heart Rate", min_value=60, max_value=100)
Daily_Steps = st.slider("Daily Steps", min_value=3000, max_value=10000)
clicked = st.form_submit_button("Predict Sleep Health")
if clicked:
result=model.predict(pd.DataFrame({"age": [age],
"Gender": [Gender],
"Occupation": [occupation],
"Sleep Duration (hours)": [Sleep_Duration],
"Quality of Sleep (scale: 1-10)": [Quality_of_Sleep],
"Physical Activity Level (minutes/day)": [Physical_Activity_Level],
"BMI Category": [BMI_Category],
"Blood Pressure (systolic/diastolic)": [Blood_Pressure],
"Heart Rate (bpm)": [Heart_Rate],
"Daily Steps": [Daily_Steps]
}))
if result[0] == 0:
result_message = "No Sleep Disorder"
elif result[0] == 1:
result_message = "Insomnia"
elif result[0] == 2:
result_message = "Sleep Apnea"
st.success(result_message)
if __name__=='__main__':
main()
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