import cv2

#create a cascadeclassifier Object
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

#Reading an Image

img= cv2.imread("sample.jpg",1)

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

#search the Co-ordinates
faces =  face_cascade.detectMultiScale(gray_img, scaleFactor=1.05, minNeighbors=5)
print(type(faces))
print(faces)

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

resized = cv2.resize(img,(int(img.shape[1]/2),int(img.shape[0]/2)))

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

#===========================================================Video Image Recognition====================================

b7bc532bff006b3d83e89b5e37cf790a05d760eb
<mask token>

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

<mask token>
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
img = cv2.imread('sample.jpg', 1)
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray_img, scaleFactor=1.05,
    minNeighbors=5)
print(type(faces))
print(faces)
for x, y, w, h in faces:
    img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
resized = cv2.resize(img, (int(img.shape[1] / 2), int(img.shape[0] / 2)))
cv2.imshow('Gray', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
img = cv2.imread('sample.jpg', 1)
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray_img, scaleFactor=1.05,
    minNeighbors=5)
print(type(faces))
print(faces)
for x, y, w, h in faces:
    img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 3)
resized = cv2.resize(img, (int(img.shape[1] / 2), int(img.shape[0] / 2)))
cv2.imshow('Gray', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2

#create a cascadeclassifier Object
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

#Reading an Image

img= cv2.imread("sample.jpg",1)

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

#search the Co-ordinates
faces =  face_cascade.detectMultiScale(gray_img, scaleFactor=1.05, minNeighbors=5)
print(type(faces))
print(faces)

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

resized = cv2.resize(img,(int(img.shape[1]/2),int(img.shape[0]/2)))

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

#===========================================================Video Image Recognition====================================
