通过Python的face_recognition模块实现人脸检测功能，首先需要安装好face_recognition包：可通过pycharm直接安装，也可以用pip安装，还可以通过anaconda安装。

示例代码如下：

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自动识别人脸特征

filename : find_facial_features_in_picture.py

from PIL import Image, ImageDraw
import face_recognition

将jpg文件加载到numpy 数组中

image = face_recognition.load_image_file("linuxidc.com.jpg")

查找图像中所有面部的所有面部特征

face_landmarks_list = face_recognition.face_landmarks(image)
print("I found {} face(s) in this photograph.".format(len(face_landmarks_list)))
pil_image = Image.fromarray(image)
d = ImageDraw.Draw(pil_image)
for face_landmarks in face_landmarks_list:
#打印此图像中每个面部特征的位置
facial_features = [
'chin',
'left_eyebrow',
'right_eyebrow',
'nose_bridge',
'nose_tip',
'left_eye',
'right_eye',
'top_lip',
'bottom_lip'
]
for facial_feature in facial_features:
print("The {} in this face has the following points: {}".format(facial_feature, face_landmarks[facial_feature]))
#在图像中画出每个人脸特征！
for facial_feature in facial_features:
d.line(face_landmarks[facial_feature], width=5)
pil_image.show()
</pre>

自动识别出人脸特征(轮廓)，如下图：

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<input class="pgc-img-caption-ipt" placeholder="图片描述(最多50字)" value="" style="box-sizing: border-box; outline: 0px; color: rgb(102, 102, 102); position: absolute; left: 187.5px; transform: translateX(-50%); padding: 6px 7px; max-width: 100%; width: 375px; text-align: center; cursor: text; font-size: 12px; line-height: 1.5; background-color: rgb(255, 255, 255); background-image: none; border: 0px solid rgb(217, 217, 217); border-radius: 4px; transition: all 0.2s cubic-bezier(0.645, 0.045, 0.355, 1) 0s;"></tt-image>