重要更新：

在很多尝试之后无果后，我相信是我的人品问题。今天突然看到一篇文章，解决我的问题
文章地址
其中有个帅哥的回答是这样的：

Just go to this page and dowload the Python Wheel file and just pip install it. Or if you want a pre-python 3.6 build you want download it here.

pip install dlib-file.whl

点击他的第一个链接，往下滑，终于出现了我想要的东西

捕获.PNG

苍了个天，果断下载然后以pip方式进行包的安装--bingo！成功！
接着尝试

pip install face_recognition

bingo! 成功！之后的内容可不看！

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1.cmake

1.PNG

@PBShortStop Installation of CMake in windows is very simple just grab the installation file (*.msi) from this link and install it. Remember to check the "Add CMake to system path" during the installation. Then you can simply use cmake --version in command prompt.

继续尝试安装dlib，shit! 不行
在命令行中尝试了一下cmake指令，并没有报错！
尝试下载dlib离线未编译版，再编译，运行过程中抛错误

CMake Error at CMakeLists.txt:5 (project):
No CMAKE_C_COMPILER could be found.
CMake Error at CMakeLists.txt:5 (project):
No CMAKE_CXX_COMPILER could be found.

错误信息大概如上所示，找解决办法：看到一篇文章
给出的解决办法如下所示

查看文件buile/CMakeFiles/CMakeError.log
报错如下：
LINK : fatal error LNK1158: cannot run 'rc.exe'
解决方法：
1.进入目录C:\Program Files (x86)\Microsoft SDKs\Windows\v7.1A\Bin
2.拷贝文件：RC.Exe 和 RcDll.Dll
3.放到从CMakeError.log文件中看到的链接目录下，比如：F:\VS\VC\bin

照做，运行还是报一样的错误，那就是没有添加到系统环境变量
尝试把它添加到系统环境变量当中，运行---没有之前的cmake error了

忘了，之前有一个编译boost的过程，boost的下载地址如下

https://sourceforge.net/projects/boost/files/boost-binaries/

注意事项：下载的boost版本要和MSVC编译器适配

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以上Windows安装dlib的指导主要遵循以下知道
原文地址

Hi,
I've successfully installed and tested this tool on my windows 10 machine and I'm writing a simple procedure to install it. It may be useful for some people try to use this tool on a Windows machine.
IMPORTANT: Actually this project has made for Linux systems and especially dlib. In my tests, the performance of this tool in Windows 10 was about a quarter in comparison with Ubuntu built with the same specs. But I haven't seen any difference between these two in other subjects.
Requirments:
(I've used this tutorial with these tools installed on Windows 10 but the newer version may work too.)

1. Microsoft Visual Studio 2015 with C/C++ Compiler installed. (Visual C++ 2015 Build Tools didn't work for me and I got into problems in compiling dlib)
2. Boost library version 1.63 or newer. Also, you can use precompiled binaries for specific MSVC you have but I don't suggest. (I've included the compiling procedure of Boost in this tutorial)
3. Of course Python3 (I used Python3.5 x64 but I think the other versions would work too)
4. CMake for windows and add it to your system environment variables.
   Installation:
5. Download and install scipy and numpy+mkl (must be mkl version) packages from this link (all credits goes to Christoph Gohlke). Remember to grab correct version based on your current Python version.
6. Download Boost library source code or binary release for your current MSVC from this link.
7. If you downloaded the binary version skip to step 4 else follow these steps to compile and build Boostby yourself:
   3-1. Extract the Boost source files into C:\local\boost_1_XX_X (X means the current version of Boostyou have)
   3-2. Create a system variable with these parameters:
   Name: VS140COMNTOOLS
   Value: C:\Program Files (x86)\Microsoft Visual Studio 14.0\Common7\Tools\ (or any path where you have installed MSVC)
   3-3. Open Developer Command Prompt for Visual Studio and go to the current directory of Boostextracted and try these commands to compile Boost:
   bootstrap
b2 -a --with-python address-model=64 toolset=msvc runtime-link=static
   3-4. If you successfully compile Boost, it should create compiled files in stage directory.
8. (If you have already compiled Boost skip this step) If you already download the binary release just extract the contents to C:\local\boost_1_XX_X
9. Grab latest version of dlib from this repo and extract it.
10. Go to dlibdirectory and open cmd and follow these commands to build dlib: (remember to replace XX with current version of Boost you have)
    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
11. Now you can use import dlib without any problem into your python script.
12. You can also check the current version of dlib with pip show dlib.
13. Now simply install face_recognition with pip install face_recognition.
14. Enjoy!