app.py

from flask import Flask, render_template, request, redirect, url_for, session
import numpy as np
from database import *
import pickle

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

app.secret_key = b'_5#y2L"F4Q8z\n\xec]/'

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


@app.route('/login', methods=['GET', 'POST'])
def login():
    if request.method == 'POST':
        email = request.form['email']
        password = request.form['password']

        user = get_user(email)

        if verify_password(user, password):
            # Store user in the session
            session['user'] = email
            return redirect(url_for('predict_disease'))
        else:
            return 'Invalid username or password.'
    return render_template('login.html')


@app.route('/signup', methods=['GET', 'POST'])
def signup():
    if request.method == 'POST':
        email = request.form['email']
        password = request.form['password']
        confirm_password = request.form['confirm-password']
        username = request.form['name']
        phone = request.form['mobile']

        if password != confirm_password:
            return 'Password and Confirm Password do not match.'

        existing_user = get_user(email)
        if existing_user:
            return 'Email address is already registered.'

        # Create a new user
        insert_user(username=username, mobile=phone, email=email, password=password)

        # Redirect to login page after successful signup
        return redirect(url_for('login'))
    return render_template('signup.html')





@app.route('/predict', methods=['POST', 'GET'])
def predict_disease():
    if 'user' not in session:
        return redirect(url_for('login'))
    if request.method == "POST":
        age = int(request.form.get('age'))
        gender = int(request.form.get('gender'))
        cp = int(request.form.get('cp'))
        trestbps = int(request.form.get('trestbps'))
        chol = int(request.form.get('chol'))
        fasting_blood_sugar = int(request.form.get('fasting_blood_sugar'))
        ecg = int(request.form.get('ecg'))
        thalach = int(request.form.get('thalach'))
        exang = int(request.form.get('exang'))
        oldpeak = float(request.form.get('oldpeak'))
        slope = int(request.form.get('slope'))
        ca = int(request.form.get('ca'))
        thal = int(request.form.get('thal'))

        

        final_features = np.array(
            [age, gender, cp, trestbps, chol, fasting_blood_sugar, ecg, thalach, exang, oldpeak, slope, ca,
             thal]).reshape(-1, 13)
        print(final_features)
        prediction = model.predict(final_features)
        print(prediction[0])

        return render_template('output.html', has_disease=prediction[0])
    return render_template('predictor.html')


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