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than adding them. This way, the gradient buffer can be used as scratch space during the loss computation. |
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dlib | ||
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examples | ||
python_examples | ||
tools | ||
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MANIFEST.in | ||
README.txt | ||
setup.py |
README.txt
dlib C++ library 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 for the main project documentation and API reference. COMPILING DLIB C++ EXAMPLE PROGRAMS Go into the examples folder and type: mkdir build; cd build; cmake .. ; cmake --build . That will build all the examples. If you have a CPU that supports AVX instructions then turn them on like this: mkdir build; cd build; cmake .. -DUSE_AVX_INSTRUCTIONS=1; cmake --build . Doing so will make some things run faster. COMPILING DLIB Python API Before you can run the Python example programs you must compile dlib. Type: python setup.py install or type python setup.py install --yes USE_AVX_INSTRUCTIONS if you have a CPU that supports AVX instructions, since this makes some things run faster. RUNNING THE UNIT TEST SUITE Type the following to compile and run the dlib unit test suite: 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. The long and short of the license is that you can use dlib however you like, even in closed source commercial software. Dlib Sponsors: This code development was funded by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via IARPA R&D Contract No. 2014-14071600010