import cv2

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

img = cv2.imread("photo.jpg")
img2 = cv2.imread("news.jpg")

gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray_img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)

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

faces2 = face_cascade.detectMultiScale(gray_img2,
scaleFactor=1.05,
minNeighbors=5)

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

for x, y, w, h in faces2:
    img2=cv2.rectangle(img2,(x,y),(x+w,y+h),(255,0,0),3)

# print(type(faces))
# print(faces)

# resized=cv2.resize(img,(int(img.shape[1]/3),int(img.shape[0]/3)))
# cv2.imshow("Gray", resized)
# cv2.waitKey(0)

cv2.imshow("Gray", img)
cv2.waitKey(0)

cv2.imshow("Gray", img2)
cv2.waitKey(0)

cv2.destroyAllWindows()
149f1f4c5c65cdc7bcea1b2814a176395a967713
<mask token>

<mask token>
for x, y, w, h in faces:
    img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
for x, y, w, h in faces2:
    img2 = cv2.rectangle(img2, (x, y), (x + w, y + h), (255, 0, 0), 3)
cv2.imshow('Gray', img)
cv2.waitKey(0)
cv2.imshow('Gray', img2)
cv2.waitKey(0)
cv2.destroyAllWindows()

<mask token>
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
img = cv2.imread('photo.jpg')
img2 = cv2.imread('news.jpg')
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray_img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray_img, scaleFactor=1.05,
    minNeighbors=5)
faces2 = face_cascade.detectMultiScale(gray_img2, scaleFactor=1.05,
    minNeighbors=5)
for x, y, w, h in faces:
    img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
for x, y, w, h in faces2:
    img2 = cv2.rectangle(img2, (x, y), (x + w, y + h), (255, 0, 0), 3)
cv2.imshow('Gray', img)
cv2.waitKey(0)
cv2.imshow('Gray', img2)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
img = cv2.imread('photo.jpg')
img2 = cv2.imread('news.jpg')
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray_img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray_img, scaleFactor=1.05,
    minNeighbors=5)
faces2 = face_cascade.detectMultiScale(gray_img2, scaleFactor=1.05,
    minNeighbors=5)
for x, y, w, h in faces:
    img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
for x, y, w, h in faces2:
    img2 = cv2.rectangle(img2, (x, y), (x + w, y + h), (255, 0, 0), 3)
cv2.imshow('Gray', img)
cv2.waitKey(0)
cv2.imshow('Gray', img2)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2

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

img = cv2.imread("photo.jpg")
img2 = cv2.imread("news.jpg")

gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray_img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)

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

faces2 = face_cascade.detectMultiScale(gray_img2,
scaleFactor=1.05,
minNeighbors=5)

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

for x, y, w, h in faces2:
    img2=cv2.rectangle(img2,(x,y),(x+w,y+h),(255,0,0),3)

# print(type(faces))
# print(faces)

# resized=cv2.resize(img,(int(img.shape[1]/3),int(img.shape[0]/3)))
# cv2.imshow("Gray", resized)
# cv2.waitKey(0)

cv2.imshow("Gray", img)
cv2.waitKey(0)

cv2.imshow("Gray", img2)
cv2.waitKey(0)

cv2.destroyAllWindows()