smile det

import cv2

faceCascade = cv2.CascadeClassifier('D:\\opencv\\OpenCV Final Softwares\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml')
smileCascade= cv2.CascadeClassifier('D:\\opencv\\OpenCV Final Softwares\\opencv\\sources\\data\\haarcascades\\haarcascade_smile.xml')

# grab the reference to the webcam
vs = cv2.VideoCapture(0)

# keep looping
while True:
# grab the current frame
ret, frame = vs.read()
 
# if we are viewing a video and we did not grab a frame,
# then we have reached the end of the video
if frame is None:
break

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.equalizeHist(gray)

faces = faceCascade.detectMultiScale(frame, scaleFactor=1.05, minNeighbors=5, minSize=(45, 45))

for (x,y,w,h) in faces:
#cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
face_gray = gray[y:y+h, x:x+w]
face_color = frame[y:y+h, x:x+w]
smiles = smileCascade.detectMultiScale(face_gray, scaleFactor=1.7, minNeighbors=3, minSize=(15, 15))
for (ex,ey,ew,eh) in smiles:
cv2.rectangle(face_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),1)

# show the frame to our screen
cv2.imshow("Video", frame)
key = cv2.waitKey(1) & 0xFF

# if the 'q' key is pressed, stop the loop
if key == ord("q"):
break

# close all windows
cv2.destroyAllWindows()