import numpy as np
import cv2

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



# img=cv2.imread('sample.jpg')
# gray =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# faces = face_cascade.detectMultiScale(gray, 1.3, 5)
# for (x,y,w,h) in faces:
#     cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),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),(0,255,0),2)

# cv2.imshow('img',img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()


cap=cv2.VideoCapture(0)

while(cap.isOpened()):
    ret,img=cap.read()
    if ret==True:
        gray =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.3, 5)
        for (x,y,w,h) in faces:
            # cv2.rectangle(gray,(x,y),(x+w,y+h),(255,0,0),2)
            cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),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_gray,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
                cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)

        cv2.imshow('img',img)
        if cv2.waitKey(16) & 0xFF ==27:
         break
    else:
        break

cap.release()
cv2.destroyAllWindows()
