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Predict.py
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Predict.py
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from flask import Flask, flash, request, redirect, url_for,render_template,jsonify
import pickle
from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.ensemble import StackingClassifier
import numpy as np
app = Flask(__name__)
def Predict(L):
filename = 'finalized_model.sav'
loaded_model = pickle.load(open(filename, 'rb'))
P = loaded_model.predict_proba(np.array([L]))
print(P)
print("Loaded Successfully")
return P;
@app.route('/', methods = ['GET','POST'])
def Connect():
return render_template("home.html")
@app.route('/Predict', methods = ['GET','POST'])
def Samples():
if request.method == 'POST':
data = request.json
print(data)
R = list(Predict(data)[0]);
print(R)
print(type(R))
return jsonify(R)
# console.log(value);
return render_template("home.html")
if __name__=="__main__":
app.run(debug = True)