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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| import joblib | |
| # load the model from disk | |
| filename = 'finalized_model.sav' | |
| loaded_model = joblib.load(filename) | |
| def generate_prediction(input_array): | |
| ans = loaded_model.predict(input_array) | |
| return ans | |
| def main(): | |
| # Face Analysis Application # | |
| st.title("Online Food Order Prediction") | |
| activiteis = ["Home", "Prediction","About"] | |
| choice = st.sidebar.selectbox("Select Activity", activiteis) | |
| if choice == "Home": | |
| html_temp_home1 = """<div style="background-color:#6D7B8D;padding:10px"> | |
| <h3 style="color:yellow;text-align:center;"> Welcome to world of AI with Prince </h3> | |
| <h4 style="color:white;text-align:center;"> | |
| Online Food Order Prediction using Python.</h4> | |
| </div> | |
| </br>""" | |
| st.markdown(html_temp_home1, unsafe_allow_html=True) | |
| st.write(""" | |
| Predicting the premium of health insurance | |
| """) | |
| if choice == "Prediction": | |
| val1 = 0 | |
| val2 = 0 | |
| val3 = 0 | |
| val4 = 0 | |
| st.header("Predicting the premium of health insurance") | |
| # Define the input fields | |
| age = st.number_input("Age", min_value=0, max_value=120, value=30, step=1) | |
| Bmi = st.number_input("bmi", min_value=0, max_value=1000000, value=50000, step=1000) | |
| children = st.number_input("children", min_value=1, max_value=10, value=4, step=1) | |
| gender = { "Male" :1,"Female" : 0} | |
| Gender_index = st.selectbox("Gender", options=list(gender.keys())) | |
| Gender = gender[Gender_index] | |
| smoke = { "Yes" :1,"No" : 0} | |
| Smoke = st.selectbox("Smoke", options=list(smoke.keys())) | |
| Snoke = smoke[Smoke] | |
| Region = {"northeast" : 1, "northwest": 2,"southeast" : 3, "southwest":4} | |
| Region = st.selectbox("Region", options=list(smoke.keys())) | |
| Region = smoke[Smoke] | |
| if Region == 1: | |
| val1 = 1 | |
| if Region == 2: | |
| val2 = 1 | |
| if Region == 3: | |
| val3 = 1 | |
| if Region == 4: | |
| val4 = 1 | |
| # Create a button to trigger the model | |
| if st.button("Predict"): | |
| # TODO: Replace with your model code | |
| prediction = generate_prediction(np.array([[age, Bmi, children, Gender, val1, val2, val3, val4 ]])) | |
| # Show the prediction | |
| st.write("Prediction:", prediction[0]) | |
| elif choice == "About": | |
| st.subheader("About this app") | |
| html_temp_about1= """<div style="background-color:#6D7B8D;padding:10px"> | |
| <h4 style="color:white;text-align:center;"> | |
| Predicting the premium of health insurance .</h4> | |
| </div> | |
| </br>""" | |
| st.markdown(html_temp_about1, unsafe_allow_html=True) | |
| html_temp4 = """ | |
| <div style="background-color:#98AFC7;padding:10px"> | |
| <h4 style="color:white;text-align:center;">Thanks for Visiting</h4> | |
| </div> | |
| <br></br> | |
| <br></br>""" | |
| st.markdown(html_temp4, unsafe_allow_html=True) | |
| else: | |
| pass | |
| if __name__ == "__main__": | |
| main() | |
| # import streamlit as st | |