app.py

from flask import Flask, render_template, request
from keras.models import load_model
from keras.preprocessing import image

app = Flask(__name__)
model = load_model('model.h5')
model.make_predict_function()

def predict_label(img_path):
	i = image.load_img(img_path, target_size=(100,100))
	i = image.img_to_array(i)/255.0
	i = i.reshape(1, 100,100,3)
	p = model.predict(i)
	if(p[0][0] < p[0][1]):
		return "Mask on"
	else:
		return "No Mask detected"

# routes
@app.route("/", methods=['GET', 'POST'])
def main():
	return render_template("index.html")

@app.route("/about")
def about_page():
	return "Flask app....."

@app.route("/submit", methods = ['GET', 'POST'])
def get_output():
	if request.method == 'POST':
		img = request.files['my_image']
		img_path = "static/" + img.filename	
		img.save(img_path)
		p = predict_label(img_path)

	return render_template("index.html", prediction = p, img_path = img_path)


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