import numpy as np
import cv2
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height
while True:
    ret, img = cap.read()
    #img = cv2.flip(img, -1)
    #frame = cv2.flip(frame, -1) # Flip camera vertically
    ##Convert RBG Image to Grayimage
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    ## call classifier function and pass in the scaling facotor,no.of neighbouts and minimum size of detected face
    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(20, 20)
    )
    for (x,y,w,h) in faces:
        ##pass image/Top,left:x,y/Bottom,right corner:x+w,y+h//BGR//thickness
        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]
    cv2.imshow('video',img)
    k = cv2.waitKey(30) & 0xff
    if k == 27: # press 'ESC' to quit
        break
cap.release()
cv2.destroyAllWindows()