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app.py
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app.py
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from black import out
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():
'''
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)
if (int_features[2] > output):
prediction_text='Your Expected Points is {}'.format(output)
diff = int_features[2] - output
exp_text = 'This team has {} less points than normal'.format(diff)
else:
prediction_text='Your Teams Point should be {}'.format(output)
diff = round(output - int_features[2],2)
exp_text = 'This team has {} more points than normal'.format(diff)
return render_template('index.html', prediction_text=prediction_text, exp_text = exp_text)
@app.route('/predict_api',methods=['POST'])
def predict_api():
'''
For direct API calls trought request
'''
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)