Watch_detection.py

import cv2

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

eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') 

watch_cascade = cv2.CascadeClassifier('watch-cascade.xml')
 
cap = cv2.VideoCapture(0)
 
while 1: 
 
    ret, img = cap.read() 
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    watches = watch_cascade.detectMultiScale(gray, 3, 6)

    for (x,y,w,h) in watches:
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2)
        font = cv2.FONT_HERSHEY_SIMPLEX
        cv2.putText(img, 'Watch', (x-w, y-h), font, 0.5, (0,255,255), 2, cv2.LINE_AA)
        
    for (x,y,w,h) in faces:
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2) 
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]
 
        eyes = eye_cascade.detectMultiScale(roi_gray) 
 
        for (ex,ey,ew,eh) in eyes:
            cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,127,255),2)
 
    cv2.imshow('img',img)
 
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
 
cap.release()

cv2.destroyAllWindows()