application.py

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

application = Flask(__name__)
app=application

scaler = pickle.load(open('Model/scaler2.pkl','rb'))
model = pickle.load(open('Model/modelForPrediction.pkl','rb'))

## Route for homepage

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

## Route for Singe data point prediction
@app.route('/predictdata',methods=['GET','POST'])
def predict_datapoint():
    result=""

    if request.method=='POST':
        Pregnancies=int(request.form.get("Pregnancies"))
        Glucose = float(request.form.get('Glucose'))
        BloodPressure = float(request.form.get('BloodPressure'))
        SkinThickness = float(request.form.get('SkinThickness'))
        Insulin = float(request.form.get('Insulin'))
        BMI = float(request.form.get('BMI'))
        DiabetesPedigreeFunction = float(request.form.get('DiabetesPedigreeFunction'))
        Age = float(request.form.get('Age'))

        new_data=scaler.transform([[Pregnancies,Glucose,BloodPressure,SkinThickness,Insulin,BMI,DiabetesPedigreeFunction,Age]])
        predict = model.predict(new_data)

        if predict[0]==1:
            result = 'Diabetic'
        else:
            result = 'Non-Diabetic'
        return render_template('single_prediction.html',result=result)

    else:
        return render_template('home.html')

if __name__=="__main__":
    app.run(host="0.0.0.0")