import pickle
import streamlit as st
from streamlit_option_menu import option_menu

#loading the saved data

heart_disease_model = pickle.load(open("heart_disease_model.sav",'rb'))

st.title('Heart Disease Prediction using ML')

col1, col2, col3 = st.columns(3)

with col1:
    age = st.text_input('Age')

with col2:
    sex = st.text_input('Sex')

with col3:
    cp = st.text_input('Chest Pain types')

with col1:
    trestbps = st.text_input('Resting Blood Pressure')

with col2:
    chol = st.text_input('Serum Cholestoral in mg/dl')

with col3:
    fbs = st.text_input('Fasting Blood Sugar > 120 mg/dl')

with col1:
    restecg = st.text_input('Resting Electrocardiographic results')

with col2:
    thalach = st.text_input('Maximum Heart Rate achieved')

with col3:
    exang = st.text_input('Exercise Induced Angina')

with col1:
    oldpeak = st.text_input('ST depression induced by exercise')

with col2:
    slope = st.text_input('Slope of the peak exercise ST segment')

with col3:
    ca = st.text_input('Major vessels colored by flourosopy')

with col1:
    thal = st.text_input('thal: 0 = normal; 1 = fixed defect; 2 = reversable defect')

    # code for Prediction
    heart_diagnosis = ''

    # creating a button for Prediction

    if st.button('Heart Disease Test Result'):
        heart_prediction = heart_disease_model.predict([[
            'age', 'sex',' cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach', 'exang', 'oldpeak', 'slope', 'ca', 'thal']])
        if (heart_prediction[0] == 1):
            heart_diagnosis = 'The person is having heart disease'
        else:
            heart_diagnosis = 'The person does not have any heart disease'

    st.success(heart_diagnosis)