import cv2

#Loading classifiers
face_cascade = cv2.CascadeClassifier('haars/haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haars/haarcascade_eye.xml')

#Detecting function

def detect(gray,frame):

    faces = face_cascade.detectMultiScale(gray,1.3,5)

    #1.3 is kernel size
    #5 is number of neighbors

    for (x,y,w,h) in faces:
        cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)

        roi_gray = gray[y:y+h,x:x+w]
        roi_color = frame[y:y+h,x:x+w]

        eyes = eye_cascade.detectMultiScale(roi_gray,1.1,3)

        for (ex,ey,ew,eh) in eyes:
            cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(255,0,0),2)

    return frame


video_capture = cv2.VideoCapture(0)

while True:
    _,frame = video_capture.read()

    # Now we convert read frame to gray coz cascading only works on gray

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

    #calling detector

    canvas = detect(gray,frame)

    cv2.imshow("Video",canvas)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

video_capture.release()
cv2.destroyAllWindows()
