Face recognition from camera with Dlib
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Introduction
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Detect and recognize single/multi-faces from camera;
调用摄像头进行人脸识别，支持多张人脸同时识别;
#. 摄像头人脸录入 / Face register
.. image:: introduction/get_face_from_camera.png
:align: center
请不要离摄像头过近，人脸超出摄像头范围时会有 "OUT OF RANGE" 提醒 /
Please do not too close to the camera, or you can't save faces with "OUT OF RANGE" warning;
.. image:: introduction/get_face_from_camera_out_of_range.png
:align: center
#. 提取特征建立人脸数据库 / Generate database from images captured
#. 利用摄像头进行人脸识别 / Face recognizer
当单张人脸 / When single-face:
.. image:: introduction/face_reco_single_person.png
:align: center
当多张人脸 / When multi-faces:
一张已录入人脸 + 未录入 unknown 人脸 / 1x known face + 1x unknown face:
.. image:: introduction/face_reco_two_people.png
:align: center
同时识别多张已录入人脸 / multi-faces recognition at the same time:
.. image:: introduction/face_reco_two_people_in_database.png
:align: center
** 关于精度 / About accuracy:
* When using a distance threshold of ``0.6``, the dlib model obtains an accuracy of ``99.38%`` on the standard LFW face recognition benchmark.
Overview
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此项目中人脸识别的实现流程 / The design of this repo:
.. image:: introduction/overview.png
:align: center
Steps
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#. 下载源码 / Download zip from website or via GitHub Desktop in windows, or git clone in Ubuntu
.. code-block:: bash
git clone https://github.com/coneypo/Dlib_face_recognition_from_camera
#. 进行 face register / 人脸信息采集录入
.. code-block:: bash
python3 get_face_from_camera.py
#. 提取所有录入人脸数据存入 features_all.csv / Features extraction and save into features_all.csv
.. code-block:: bash
python3 features_extraction_to_csv.py
#. 调用摄像头进行实时人脸识别 / Real-time face recognition
.. code-block:: bash
python3 face_reco_from_camera.py
About Source Code
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Repo 的 tree / 树状图:
::
.
├── get_faces_from_camera.py # Step1. Faces register
├── features_extraction_to_csv.py # Step2. Features extraction
├── face_reco_from_camera.py # Step3. Faces recognition
├── how_to_use_camera.py # Use the default camera by opencv
├── data
│ ├── data_dlib # Dlib's model
│ │ ├── dlib_face_recognition_resnet_model_v1.dat
│ │ ├── shape_predictor_5_face_landmarks.dat
│ │ └── shape_predictor_68_face_landmarks.dat
│ ├── data_faces_from_camera # Face images captured from camera (will generate after step 1)
│ │ ├── person_1
│ │ │ ├── img_face_1.jpg
│ │ │ └── img_face_2.jpg
│ │ └── person_2
│ │ └── img_face_1.jpg
│ │ └── img_face_2.jpg
│ └── features_all.csv # CSV to save all the features of known faces (will generate after step 2)
├── introduction # Some files for readme.rst
│ ├── Dlib_Face_recognition_by_coneypo.pptx
│ ├── face_reco_single_person_customize_name.png
│ ├── face_reco_single_person.png
│ ├── face_reco_two_people_in_database.png
│ ├── face_reco_two_people.png
│ ├── get_face_from_camera_out_of_range.png
│ ├── get_face_from_camera.png
│ └── overview.png
├── README.rst
└── requirements.txt # Some python packages needed
用到的 Dlib 相关模型函数:
#. Dlib 正向人脸检测器 (based on HOG), output: <class 'dlib.dlib.rectangles'>
.. code-block:: python
detector = dlib.get_frontal_face_detector()
faces = detector(img_gray, 0)
#. Dlib 人脸预测器, output: <class 'dlib.dlib.full_object_detection'>
.. code-block:: python
predictor = dlib.shape_predictor("data/data_dlib/shape_predictor_5_face_landmarks.dat")
shape = predictor(img_rd, faces[i])
#. 特征描述子 Face recognition model, the object maps human faces into 128D vectors
.. code-block:: python
face_rec = dlib.face_recognition_model_v1("data/data_dlib/dlib_face_recognition_resnet_model_v1.dat")
Python 源码介绍如下:
#. get_face_from_camera.py:
进行 Face register / 人脸信息采集录入
* 请注意存储人脸图片时，矩形框不要超出摄像头范围，要不然无法保存到本地;
* 超出会有 "out of range" 的提醒;
#. features_extraction_to_csv.py:
从上一步存下来的图像文件中，提取人脸数据存入CSV;
* 会生成一个存储所有特征人脸数据的 "features_all.csv"；
* size: n*128 , n means n people you registered and 128 means 128D features of the face
#. face_reco_from_camera.py:
这一步将调用摄像头进行实时人脸识别; / This part will implement real-time face recognition;
* Compare the faces captured from camera with the faces you have registered which are saved in "features_all.csv"
* 将捕获到的人脸数据和之前存的人脸数据进行对比计算欧式距离, 由此判断是否是同一个人;
More
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Tips:
#. 如果希望详细了解 dlib 的用法，请参考 Dlib 官方 Python api 的网站 / You can refer to this link for more information of how to use dlib: http://dlib.net/python/index.html
#. Windows下建议不要把代码放到 ``C:\``, 可能会出现权限读取问题 / In windows, we will not recommend that running this repo in dir ``C:\``
#. 代码最好不要有中文路径 / No chinese characters in your code directory
#. 人脸录入的时候先建文件夹再保存图片, 先 ``N`` 再 ``S`` / Press ``N`` before ``S``
可以访问我的博客获取本项目的更详细介绍，如有问题可以邮件联系我 /
For more details, please refer to my blog (in chinese) or mail to me :
* Blog: https://www.cnblogs.com/AdaminXie/p/9010298.html
* Mail: coneypo@foxmail.com ( Dlib 相关 repo 问题请联系 @foxmail 而不是 @intel )
仅限于交流学习, 商业合作勿扰;
Thanks for your support.