Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib’s open source licensing allows you to use it in any application, free of charge.
source (http://dlib.net/)
Update:
Based on the comment from Davis E King, the maker of Dlib, you don’t to follow these steps. See his comment below to know how to do it!
First of all download the latest version from using this link http://dlib.net/files/dlib-19.10.tar.bz2 or go to the website and download it.
Extract the content of the file tar -xvf dlib-19.10.tar.bz2
Go to dlib dir cd dlib-19.10 and create a new dir inside mkdir build && cd build
Then run the build command, but here you have to make a choic.
If you want to build it to use the nVidia graphic card with Cuda then you have to do it as follows:
cmake .. cmake --build . --config Release sudo ldconfig sudo make install
If you want to use Dlib with no Cuda support and only use it with the cpu:
cmake .. -DUSE_AVX_INSTRUCTIONS=ON cmake --build . --config Release sudo make install sudo ldconfig
Note we used -DUSE_AVX_INSTRUCTIONS=ON explicitly. If you bought your laptop after 2012 and it has an Intel cpu then it supports AVX Instructions, otherwise you have to use
-DUSE_SSE2_INSTRUCTIONS=ON
Finally exit the build dir cd .. and run
sudo python3.6 setup.py install –no DLIB_USE_CUDA –yes USE_AVX_INSTRUCTIONS
This will build a Python package with no cuda support and with AVX_Instrcutions support! As you see I use python3.6 you can also use Python2.7 and Python3.5.
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