app.py

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

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

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

@app.route('/predict',methods=['POST'])
def predict():

    int_features = [int(x) for x in request.form.values()]
    final_features = [np.array(int_features)]
    prediction = model.predict(final_features)

    output = round(prediction[0], 2)

    return render_template('index.html', prediction_text='Car speed should be {} mph'.format(output*50))

@app.route('/results',methods=['POST'])
def results():

    data = request.get_json(force=True)
    prediction = model.predict([np.array(list(data.values()))])

    output = prediction[0]
    return jsonify(output)

@app.route('/hello/<user>')
def hello_name(user):
    return render_template('hello.html',name=user)

@app.route('/submitpost',methods=['POST'])
def testpost():
    final_features = [x for x in request.form.values()]
    return render_template('hello.html', submitted_values='Array of submitted values : {}'.format(final_features))


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

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