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README
Apache-2.0

face-recognition-service

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介绍

使用 Face Recognition & Flask 构建的人脸比对服务,提供HTTP接口,Pyinstaller打包项目为可独立运行的exe程序。

新增人脸比对差值,可参考接口返回结果中的 face_distances 自行判定是否比对通过。

本地没环境?打包太麻烦?此处直接下载最新发行版 face-recognition-service releases

配置文件说明 config.ini

[config]
; 服务端口号,默认5000
port=5000
; 阈值,太低容易造成无法成功识别人脸,太高容易造成人脸识别混淆,默认0.6,推荐0.39、0.49
; 也可以理解为两张人脸的差值(不相似度),比对结果 < 此值,人脸比对通过
tolerance=0.49
; 允许上传文件的扩展名,默认png,jpg,jpeg
allowed_extension=png,jpg,jpeg

运行效果

截图

截图

开发环境

安装所需文件打包下载地址:face_recognition_win10_install_requires.zip

  • Windows 10 64 Bit
  • Python 3.6
  • numpy-1.15.0+mkl-cp36-cp36m-win_amd64
  • scipy-1.1.0-cp36-cp36m-win_amd64
  • boost_1_68_0-msvc-14.0-64
  • dlib-19.15
  • cmake-3.12.1-win64-x64

安装要求

新版本dlib 不再需要 Boost了,所以你可以跳过它。请记住,您仍需要满足以下要求

  1. 安装了C / C ++编译器的Microsoft Visual Studio 2015(或更高版本)
  2. Python3(我使用的是 Python 3.6 x64,其他版本应该也可以)
  3. Boost 库版本1.63或更新的版本
  4. CMake 安装并且添加到系统环境变量

安装教程

参考教程:Windows Installation Tutorial

  1. 从此 链接 下载并安装 scipynumpy+mkl(必须是mkl版本)软件包。请记住根据您当前的Python版本获取正确的版本
  2. 从此 链接 下载当前二进制版本的 Boost,并解压到C:\local\boost_1_XX_X
  3. 从此 仓库 中获取最新版本的 dlib,并解压至任意目录
  4. 转到 dlib 目录打开cmd并按照以下命令构建dlib:(记得用 Boost 的当前版本替换XX)
set BOOST_ROOT=C:\local\boost_X_XX_X
set BOOST_LIBRARYDIR=C:\local\boost_X_XX_X\stage\lib
python setup.py install --yes USE_AVX_INSTRUCTIONS
or
python setup.py install --yes USE_AVX_INSTRUCTIONS --yes DLIB_USE_CUDA
  1. pip show dlib
  2. pip install face_recognition
  3. pip install configparser flask flask_cors
  4. cd 当前项目目录
  5. python main.py
  6. 请享用

打包教程

参考教程:Freeze your script with Pyinstaller

  1. 确保您已经正确安装了项目相关依赖,并且脚本能正常运行
  2. pip install pyinstaller
  3. Python安装目录/Lib/site-packages 中复制 face_recognition_modelsscipy-extra-dll 到当前项目根目录,如果没有 scipy-extra-dll,在当前项目根目录创建一个同名的空文件夹
  4. 修改 main.spec 第13行 pathex 的值为当前项目在你电脑的绝对路径
  5. 运行 build.bat (打包过程会比较慢,耐心等待...)
  6. 如果没有看到错误信息,则可以在 dist 目录中找到您的可执行文件 main.exe
  7. 请享用

参与贡献

  1. Fork 本仓库
  2. 新建 Feat_xxx 分支
  3. 提交代码
  4. 新建 Pull Request
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简介

😉 使用 Face Recognition & Flask 构建的人脸比对服务,提供HTTP接口,Pyinstaller打包项目为可独立运行的exe程序 展开 收起
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