text: from keras.models import load_model
  import cv2
  import numpy as np
  
  model = load_model('model-013.model')
  
  face_clsfr=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
  
  source=cv2.VideoCapture(0)
  
  labels_dict={0:'MASK',1:'NO MASK'}
  color_dict={0:(0,255,0),1:(0,0,255)}
  
  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()