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README.md
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README.md
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# dlib C++ library ![Travis Status](https://travis-ci.org/davisking/dlib.svg?branch=master)
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# dlib C++ library [![Travis Status](https://travis-ci.org/davisking/dlib.svg?branch=master)](https://travis-ci.org/davisking/dlib)
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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.
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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.
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```bash
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```bash
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mkdir build; cd build; cmake .. ; cmake --build .
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mkdir build; cd build; cmake .. ; cmake --build .
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```
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```
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That will build all the examples.
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That will build all the examples.
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If you have a CPU that supports AVX instructions then turn them on like this:
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If you have a CPU that supports AVX instructions then turn them on like this:
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```bash
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```bash
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mkdir build; cd build; cmake .. -DUSE_AVX_INSTRUCTIONS=1; cmake --build .
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mkdir build; cd build; cmake .. -DUSE_AVX_INSTRUCTIONS=1; cmake --build .
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```
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```
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## Compiling dlib Python API
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## Compiling dlib Python API
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Before you can run the Python example programs you must compile dlib. Type:
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Before you can run the Python example programs you must compile dlib. Type:
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```bash
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```bash
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python setup.py install
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python setup.py install
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```bash
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```bash
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python setup.py install --yes USE_AVX_INSTRUCTIONS
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python setup.py install --yes USE_AVX_INSTRUCTIONS
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```
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```
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if you have a CPU that supports AVX instructions, since this makes some things run faster.
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if you have a CPU that supports AVX instructions, since this makes some things run faster.
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@ -60,5 +60,5 @@ This library is licensed under the Boost Software License, which can be found in
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## dlib sponsors
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## dlib sponsors
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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.
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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.
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