cv2. 01_face_dataset

import cv2
import os


cascPath = './data/'
face_detector = cv2.CascadeClassifier(cascPath + 'haarcascade_frontalface_alt.xml')


cam = cv2.VideoCapture(0)

cam.set(3,640)

cam.set(4,480)
# For each person, enter one numeric face id
face_id = input('\n enter user id end press <return> ==> ')
print('\n [INFO] Initializing face capture. Look the camera and wait ...')
#Initialize individual face count
count = 0

def creat_dir(path):

#判断路径是否存在，返回True，或者False
    is_exists = os.path.exists(path)

if is_exists:
print('The path is exist')

else:

os.makedirs(path)
print('Create the dir successfully.')


savepath = './face_dataset/'
dirpath = savepath + '{}/'.format(face_id)

creat_dir(dirpath)

while True:

ret,img = cam.read()
# frame = cv2.flip(frame,-1)#旋转屏幕
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

faces = face_detector.detectMultiScale(gray,scaleFactor=1.3,minNeighbors=5)

for (x,y,w,h) in faces:

cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)

count += 1
        # Save the captured image into the datasets folder
        cv2.imwrite(dirpath + str(face_id) +'.' + str(count) + '.jpg', gray[y:y+h, x:x+w])

cv2.imshow('img',img)



k = cv2.waitKey(100) & 0xff
    if k == 27:  #press 'ESC' to quit
        break
    elif count >= 30: # Take 30 face sample and stop video
        break

# Do a bit of cleanup
print('\n [INFO] Exiting Program and cleanup stuff')

cam.release()

cv2.destroyAllWindows()