import cv2
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
img = cv2.imread("news.jpg")
# can use 0=grayscale but using another method to convert it into greyscal
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# faces = face_cascade.detectMultiScale(
#     gray_img, scaleFactor=1.05, minNeighbors=5)

faces = face_cascade.detectMultiScale(
    gray_img, scaleFactor=1.1, minNeighbors=5)

for x, y, w, h in faces:
    img = cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 3)

resized_img = cv2.resize(img, (int(img.shape[1]/3), int(img.shape[0]/3)))

cv2.imshow("img", resized_img)
cv2.waitKey(0)
cv2.destroyAllWindows()


# cv2.imshow("grayimg", gray_img)
# cv2.waitKey(2000)
# cv2.destroyAllWindows()
