# -*-coding:utf8-*-
import os
import cv2
import time
import shutil
def getAllPath(dirpath, *suffix):
PathArray = []
for r, ds, fs in os.walk(dirpath):
for fn in fs:
if os.path.splitext(fn)[1] in suffix:
fname = os.path.join(r, fn)
PathArray.append(fname)
return PathArray
def readPicSaveFace_1(sourcePath, targetPath, invalidPath, *suffix):
try:
ImagePaths = getAllPath(sourcePath, *suffix)
# 对list中图片逐一进行检查,找出其中的人脸然后写到目标文件夹下
count = 1
# haarcascade_frontalface_alt.xml为库训练好的分类器文件，下载opencv，安装目录中可找到
face_cascade = cv2.CascadeClassifier('E:\BaiduNetdiskDownload\opencv\sources\data\haarcascades\haarcascade_frontalface_alt.xml')
for imagePath in ImagePaths:
try:
img = cv2.imread(imagePath)
if type(img) != str:
faces = face_cascade.detectMultiScale(img, 1.1, 5)
if len(faces):
for (x, y, w, h) in faces:
# 设置人脸宽度大于16像素，去除较小的人脸
if w >= 16 and h >= 16:
# 以时间戳和读取的排序作为文件名称
listStr = [str(int(time.time())), str(count)]
fileName = ''.join(listStr)
# 扩大图片，可根据坐标调整
X = int(x)
#W = min(int(x + w), img.shape[1])
W=max(int(x + w), img.shape[1])
Y = int(y)
#H = min(int(y + h), img.shape[0])
H=max(int(y + h), img.shape[0])
f = cv2.resize(img[Y:H, X:W], (256, 256))
cv2.imwrite(targetPath + os.sep + '%s.jpg' % fileName, f)
count += 1
print(imagePath + "have face")
# else:
# shutil.move(imagePath, invalidPath)
except:
continue
except IOError:
print("Error")
else:
print('Find ' + str(count - 1) + ' faces to Destination ' + targetPath)
if __name__ == '__main__':
invalidPath = r'E:\tupianshaixuan\unused1'
sourcePath = r'E:\tupianshaixuan\source1'
targetPath1 = r'E:tupianshaixuan\target1'
readPicSaveFace_1(sourcePath, targetPath1, invalidPath, '.jpg', '.JPG', 'png', 'PNG')
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