使用Python3实现识别图片中的所有人脸并显示出来，代码如下：

# -*- coding: utf-8 -*-  
#  识别图片中的所有人脸并显示出来  
# filename : find_faces_in_picture.py  
from PIL import Image  
import face_recognition  
# 将jpg文件加载到numpy 数组中  
image = face_recognition.load_image_file("linuxidc.com.jpg")  
# 使用默认的给予HOG模型查找图像中所有人脸  
# 这个方法已经相当准确了，但还是不如CNN模型那么准确，因为没有使用GPU加速  
# 另请参见: find_faces_in_picture_cnn.py  
face_locations = face_recognition.face_locations(image)  
# 使用CNN模型  
# face_locations = face_recognition.face_locations(image, number_of_times_to_upsample=0, model="cnn")  
# 打印：我从图片中找到了 多少 张人脸  
print("I found {} face(s) in this photograph.".format(len(face_locations)))  
# 循环找到的所有人脸  
for face_location in face_locations:  
        # 打印每张脸的位置信息  
        top, right, bottom, left = face_location  
        print("A face is located at pixel location Top: {}, Left: {}, Bottom: {}, Right: {}".format(top, left, bottom, right))  
# 指定人脸的位置信息，然后显示人脸图片  
        face_image = image[top:bottom, left:right]  
        pil_image = Image.fromarray(face_image)  
        pil_image.show()  

# 或者执行python文件  
$ python3 www.linuxidc.com.py

从图片中识别出10张人脸，并显示出来。

I found 10 face(s) in this photograph.  
A face is located at pixel location Top: 445, Left: 1867, Bottom: 534, Right: 1957  
A face is located at pixel location Top: 544, Left: 643, Bottom: 619, Right: 718  
A face is located at pixel location Top: 478, Left: 1647, Bottom: 553, Right: 1722  
A face is located at pixel location Top: 504, Left: 126, Bottom: 594, Right: 215  
A face is located at pixel location Top: 536, Left: 395, Bottom: 611, Right: 469  
A face is located at pixel location Top: 544, Left: 1042, Bottom: 619, Right: 1116  
A face is located at pixel location Top: 553, Left: 818, Bottom: 627, Right: 892  
A face is located at pixel location Top: 511, Left: 1431, Bottom: 586, Right: 1506  
A face is located at pixel location Top: 564, Left: 1227, Bottom: 626, Right: 1289  
A face is located at pixel location Top: 965, Left: 498, Bottom: 1017, Right: 550 

如下图：

原文来自：https://mp.weixin.qq.com/s/l82m6rzRYGW2fdho6qkSAA

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