app.py

#!/usr/bin/env python
# coding: utf-8

# In[1]:


import numpy as np
import pandas as pd
from flask import Flask, request, jsonify, render_template
import pickle


# In[2]:


app = Flask(__name__,template_folder='templates')
model = pickle.load(open('model.pkl', 'rb'))

@app.route('/')
def home():
    return render_template('index.html')

@app.route('/predict',methods=['POST'])
def predict():
    '''
    For rendering results on HTML GUI
    '''
    features = [x for x in request.form.values()]
    final_features = [np.array(features)]
    column_names=['HR','O2Sat','Temp','SBP','MAP','DBP','Resp','EtCO2','BaseExcess','HCO3','FiO2','pH','PaCO2','SaO2','AST','BUN','Alkalinephos',
                  'Calcium','Chloride','Creatinine','Bilirubin_direct','Glucose','Lactate','Magnesium','Phosphate','Potassium','Bilirubin_total','TroponinI','Hct','Hgb','PTT','WBC','Fibrinogen','Platelets','Age','Gender','Unit1','Unit2','HospAdmTime','ICULOS']
    final_features=pd.DataFrame(final_features,columns=column_names)
    prediction= model.predict(final_features)
    a=""
    if prediction[0]==0:
        a+="NO SEPSIS"
    else:
        a+="SEPSIS"
    return render_template('index.html', prediction_text='{}'.format(a))


if __name__ == '__main__':
	app.run()