.
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('/home/seanpwc/mysite/templates/index.html')
#@app.route('/predict',methods=['POST'])
#def predict():
'''
For rendering results on HTML GUI
'''
#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)
# output= 10000
# return render_template('index.html', Predicting_Issue='Employee Salary should be $ {}'.format(output))
#@app.route('/predict_api',methods = ['POST'])
#def predict_api():
# '''
# For direct API calls only
# '''
# data = request.get_json(force=True)
# prediction = model.predict([np.array(list(data.values()))])
# output = prediction[0]
# return jsonify(output)
if __name__ == "__main__":
app.run(debug=True)
[edit by admin: formatting]