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def get_images_and_labels ( path ) :
image_paths = [ os . path . join ( path , f ) for f in os . listdir ( path ) ]
# 新建连个list用于存放
face_samples = [ ]
ids = [ ]
# 遍历图片路径，
for image_path in image_paths :
# 通过图片路径将其转换为灰度图片
img = Image . open ( image_path ) . convert ( ' L ' )
# 将图片转化为数组
img_np = np . array ( img , ' uint8 ' )
if os . path . split ( image_path ) [ - 1 ] . split ( " . " ) [ - 1 ] != ' jpg ' :
continue
# 为了获取id，
id = int ( os . path . split ( image_path ) [ - 1 ] . split ( " . " ) [ 1 ] )
# 调用熟悉的人脸分类器
detector = cv2 . CascadeClassifier ( ' haarcascade_frontalface_default.xml ' )
faces = detector . detectMultiScale ( img_np )
# 将获取的图片和id添加到list中
for ( x , y , w , h ) in faces :
face_samples . append ( img_np [ y : y + h , x : x + w ] )
ids . append ( id )
return face_samples , ids
