app.py

from flask import Flask, render_template,session,url_for, redirect
import numpy as np
from flask_wtf import FlaskForm
from wtforms import TextField, SubmitField
from tensorflow.keras.models import load_model
import joblib




def return_prediction(model,scaler,sample_json):
    s_len = sample_json["sepal_length"]
    s_wid = sample_json["sepal_width"]
    p_len = sample_json["petal_length"]
    p_wid = sample_json["petal_width"]
    
    flower = [[s_len,s_wid,p_len,p_wid]]
    classes = np.array(['Iris-setosa', 'Iris-versicolor', 'Iris-virginica'])
    
    flower = scaler.transform(flower)
    
    class_ind = model.predict_classes(flower)[0]
    
    return classes[class_ind]

app = Flask(__name__)
app.config['SECRET_KEY'] = 'mysecretkey'



class FlowerForm(FlaskForm):

	sep_len = TextField("Sepal Length")
	sep_wid = TextField("Sepal Width")
	pet_len = TextField("Petal Length")
	pet_wid = TextField("Petal Width")

	submit = SubmitField("Analyze")

flower_model = load_model('final_iris_model.h5')
flower_scaler = joblib.load('iris_scaler.pkl')
@app.route("/",methods=['GET','POST'])
def index():
	
	form = FlowerForm()
	if form.validate_on_submit():
		session['sep_len'] = form.sep_len.data
		session['sep_wid'] = form.sep_wid.data
		session['pet_len'] = form.pet_len.data
		session['pet_wid'] = form.pet_wid.data

		return redirect(url_for("prediction"))

	return render_template('home.html',form=form)



@app.route('/prediction')
def prediction():
	# content = request.json
	# results = return_prediction(flower_model,flower_scaler,content)
	# return results
	content = {}
	content['sepal_length'] = float(session['sep_len'])
	content['sepal_width'] = float(session['sep_wid'])
	content['petal_length'] = float(session['pet_len'])
	content['petal_width'] = float(session['pet_wid'])

	results = return_prediction(flower_model,flower_scaler,content)
	# print("----------------------")
	# print('\n\n')
	# print(results)
	# print('\n\n')
	# print('-----------------------')
	return render_template('prediction.html',results=results)

if __name__=='__main__':
	app.run()