Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. See [http://dlib.net](http://dlib.net) for the main project documentation and API reference.
The examples folder has a [CMake tutorial](https://github.com/davisking/dlib/blob/master/examples/CMakeLists.txt) that tells you what to do. There are also additional instructions on the [dlib web site](http://dlib.net/compile.html).
if you have a CPU that supports AVX instructions, since this makes some things run faster. Note that you need to have boost-python installed to compile the Python API.
Type the following to compile and run the dlib unit test suite:
```bash
cd dlib/test
mkdir build
cd build
cmake ..
cmake --build . --config Release
./dtest --runall
```
Note 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.
This library is licensed under the Boost Software License, which can be found in [dlib/LICENSE.txt](https://github.com/davisking/dlib/blob/master/dlib/LICENSE.txt). The long and short of the license is that you can use dlib however you like, even in closed source commercial software.
This 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.