maskDetection.py

from keras.models import load_model
import cv2
import numpy as np


model = load_model('model-007.model')

face_clsfr=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

source=cv2.VideoCapture(0)

labels_dict={0:'No MASK',1:'MASK'}
color_dict={0:(0,0,255),1:(0,255,0)}

while (True):
	
	ret, img = source.read()
	gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
	faces = face_clsfr.detectMultiScale(gray, 1.3, 5)
	
	for (x, y, w, h) in faces:
		face_img = gray[y:y + w, x:x + w]
		resized = cv2.resize(face_img, (100, 100))
		normalized = resized / 255.0
		reshaped = np.reshape(normalized, (1, 100, 100, 1))
		result = model.predict(reshaped)
		
		label = np.argmax(result, axis=1)[0]
		
		cv2.rectangle(img, (x, y), (x + w, y + h), color_dict[label], 2)
		cv2.rectangle(img, (x, y - 40), (x + w, y), color_dict[label], -1)
		cv2.putText(img, labels_dict[label], (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 2)
	
	cv2.imshow('LIVE', img)
	key = cv2.waitKey(1)
	
	if (key == 27):
		break

cv2.destroyAllWindows()
source.release()