[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9626":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":32,"readmeContent":33,"aiSummary":34,"trendingCount":16,"starSnapshotCount":16,"syncStatus":17,"lastSyncTime":35,"discoverSource":36},9626,"dlib","davisking\u002Fdlib","davisking","A toolkit for making real world machine learning and data analysis applications in C++","http:\u002F\u002Fdlib.net",null,"C++",14396,3453,471,39,0,2,6,23,9,45,"Boost Software License 1.0",false,"master",[26,27,28,5,29,30,31],"c-plus-plus","computer-vision","deep-learning","machine-learning","machine-learning-library","python","2026-06-12 02:02:10","# dlib C++ library  [![GitHub Actions C++ Status](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib\u002Factions\u002Fworkflows\u002Fbuild_cpp.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib\u002Factions\u002Fworkflows\u002Fbuild_cpp.yml) [![GitHub Actions Python Status](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib\u002Factions\u002Fworkflows\u002Fbuild_python.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib\u002Factions\u002Fworkflows\u002Fbuild_python.yml)\n\nDlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. See [http:\u002F\u002Fdlib.net](http:\u002F\u002Fdlib.net) for the main project documentation and API reference.\n\n\n\n## Compiling dlib C++ example programs\n\nGo into the examples folder and type:\n\n```bash\nmkdir build; cd build; cmake .. ; cmake --build .\n```\n\nThat will build all the examples.\nIf you have a CPU that supports AVX instructions then turn them on like this:\n\n```bash\nmkdir build; cd build; cmake .. -DUSE_AVX_INSTRUCTIONS=1; cmake --build .\n```\n\nDoing so will make some things run faster.\n\nFinally, Visual Studio users should usually do everything in 64bit mode.  By default Visual Studio is 32bit, both in its outputs and its own execution, so you have to explicitly tell it to use 64bits.  Since it's not the 1990s anymore you probably want to use 64bits.  Do that with a cmake invocation like this:\n```bash\ncmake .. -G \"Visual Studio 14 2015 Win64\" -T host=x64\n```\n\n## Compiling your own C++ programs that use dlib\n\nThe examples folder has a [CMake tutorial](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib\u002Fblob\u002Fmaster\u002Fexamples\u002FCMakeLists.txt) that tells you what to do.  There are also additional instructions on the [dlib web site](http:\u002F\u002Fdlib.net\u002Fcompile.html).\n\nAlternatively, if you are using the [vcpkg](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fvcpkg\u002F) dependency manager you can download and install dlib with CMake integration in a single command:\n```bash\nvcpkg install dlib\n```\n\n## Compiling dlib Python API\n\nEither fetch the latest stable release of dlib from PyPi and install that:\n```bash\npip install dlib\n```\nOr fetch the very latest version from github and install that:\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib.git\ncd dlib\npip install .\n```\n\nIt's possible to change build settings by passing parameters to `setup.py` or `DLIB_*` environment variables.\nFor example, setting the environment variable `DLIB_NO_GUI_SUPPORT` to `ON` will add the cmake option\n`-DDLIB_NO_GUI_SUPPORT=ON`.\n\n\n## Running the unit test suite\n\nType the following to compile and run the dlib unit test suite:\n\n```bash\ncd dlib\u002Ftest\nmkdir build\ncd build\ncmake ..\ncmake --build . --config Release\n.\u002Fdtest --runall\n```\n\nNote that on windows your compiler might put the test executable in a subfolder called `Release`. If that's the case then you have to go to that folder before running the test.\n\nThis library is licensed under the Boost Software License, which can be found in [dlib\u002FLICENSE.txt](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib\u002Fblob\u002Fmaster\u002Fdlib\u002FLICENSE.txt).  The long and short of the license is that you can use dlib however you like, even in closed source commercial software.\n\n## dlib sponsors\n\nThis research is based in part upon work supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) under contract number 2014-14071600010. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of ODNI, IARPA, or the U.S. Government.\n","dlib 是一个用 C++ 编写的工具包，用于构建解决实际问题的机器学习和数据分析应用。它提供了丰富的机器学习算法、图像处理技术以及深度学习功能，并支持 Python 绑定，方便不同背景的开发者使用。核心特点包括高效的数据结构、强大的线性代数库支持及优化过的计算性能（如通过 AVX 指令集加速）。适用于需要在 C++ 环境下开发计算机视觉项目、人脸识别系统或任何基于机器学习的应用场景。","2026-06-11 03:23:49","top_topic"]