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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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