prediction_app / app.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Jan 10 13:32:52 2023
@author: Bonn_arts
"""
import numpy as np
import pickle
import streamlit as st
loaded_model = pickle.load(open('trained_model.sav', 'rb'))
def malaria_prediction(input_data):
input_data_as_numpy_array = np.asarray(input_data)
input_data_reshaped = input_data_as_numpy_array.reshape(1,-1)
prediction = loaded_model.predict(input_data_reshaped)
print(prediction)
if (prediction[0]==1):
return'outbreak; control measures: vector control, case management and vaccines'
else:
return 'medium threat; control measures: antimalaria, IRS, ITN'
def main():
st.title('Malaria prediction web app')
r = st.number_input('value of Rainfall',)
m = st.number_input('value of Min-Temperature')
mt = st.number_input('value of Max-temprature')
rel1 = st.number_input('value of Relative humidity 1(0800hrs)' )
rel2 = st.number_input('value of Relative humidity 2(1400hrs)' )
mosqp = st.number_input('value of Mosquito population')
case = st.number_input('number of cases')
diagnosis = ""
if st.button('test result'):
diagnosis = malaria_prediction([r,m,mt,rel1 ,rel2,mosqp,case])
st.success(diagnosis)
if __name__=='__main__':
main()