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import cv2
import numpy as np
labels_dict={0:'No mask',1:'Mask'}
color_dict={0:(0,0,255),1:(0,255,0)}
imgsize = 4 #set image resize
camera = cv2.VideoCapture(0) # Turn on camera
# Identify frontal face
classifier = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
while True:
(rval, im) = camera.read()
im=cv2.flip(im,1,1) #mirrow the image
imgs = cv2.resize(im, (im.shape[1] // imgsize, im.shape[0] //
imgsize))
face_rec = classifier.detectMultiScale(imgs)
for i in face_rec: # Overlay rectangle on face
(x, y, l, w) = [v * imgsize for v in i]
face_img = im[y:y+w, x:x+l]
resized=cv2.resize(face_img,(150,150))
normalized=resized/255.0
reshaped=np.reshape(normalized,(1,150,150,3))
reshaped = np.vstack([reshaped])
result=cnn.predict(reshaped)
label=np.argmax(result,axis=1)[0]
cv2.rectangle(im,(x,y),(x+l,y+w),color_dict[label],2)
cv2.rectangle(im,(x,y-40),(x+l,y),color_dict[label],-1)
cv2.putText(im, labels_dict[label], (x, y-
10),cv2.FONT_HERSHEY_SIMPLEX,0.8,(255,255,255),2)
cv2.imshow('LIVE',im)
key = cv2.waitKey(10)
# stop loop by ESC
if key == 27: # The Esc key
break
webcam.release()
cv2.destroyAllWindows()
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