app.py

#DevTown :  PYTHON-ZERO TO HERO-5 DAYS FREE BOOTCAMP Project
#Gmail : adinathjagtap9702@gmail.com
from flask import Flask, render_template, request
import pickle
import numpy as np


app = Flask(__name__)

with open('house_price_analysis.pkl','rb') as f:
    model=pickle.load(f);
    
@app.route('/')
def home():
    return render_template('index.html')

@app.route('/predict', methods=['POST'])
def predict():
    features = [
        float(request.form['CRIM']),
        float(request.form['ZN']),
        float(request.form['INDUS']),
        float(request.form['CHAS']),
        float(request.form['NOX']),
        float(request.form['RM']),
        float(request.form['AGE']),
        float(request.form['DIS']),
        float(request.form['RAD']),
        float(request.form['TAX']),
        float(request.form['PTRATIO']),
        float(request.form['B']),
        float(request.form['LSTAT'])
    ]
    
    features_array = np.array([features])
    
    prediction = model.predict(features_array)
    output = round(prediction[0],2)
    
    return render_template('index.html', prediction_text=f"Predicted Price: {output}")


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