<commit_before>#### Building on Windows Visual Studio
##### Prerequisites
* Install Visual Studio 2013:
  
  **Note**: `Visual Studio Express` and `Visual Studio 2015` are not supported!(I tried but not work ^_^)

  [Nvidia reference](http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-microsoft-windows/index.html#axzz44vwAc5Qx)

* Install Cuda 7.5:
  Also refer to above link. [download](https://developer.nvidia.com/cuda-downloads)

* Install CMake:
  The latest version is OK. [download](https://cmake.org/) 

* Install OpenCV:
  I installed 3.1, other versions should also work. [download](http://opencv.org/)
  * Run the EXE to extract the files. This EXE does not have an installer. Instead, you put your files where you want, and then add an environment variable
  * Adding the environment variable named "OpenCV_DIR" (no quotes) to the "build" subfolder in the folder where you extracted.(The exact folder you need will have one very important file in it: OpenCVConfig.cmake - this tells CMake which variables to set for you.)
  * Add a dir of "OpenCV binary DLLs" to Windows $PATH.(like f:/software/opencv/build/x64/vc12/bin)

##### Compile the solution
* Use the cmake-gui tool:

  Open the cmake-gui tool and selete the location of **Source and Build**.
  Then press configure to specify the generator: In this case, it's **Visual Studio 12 2013 Win64**.
  Last, press generate.

* Use the cmake command line:

  mkdir build && cd build/ && cmake -G "Visual Studio 12 2013 Win64"

**Done!** Just use Visual Studio to open the project-solution in dir build/ and compile everything.

=======
### Original README.md 

AprilTags library

Detect April tags (2D bar codes) in images; reports unique ID of each
detection, and optionally its position and orientation relative to a
calibrated camera.

See examples/apriltags_demo.cpp for a simple example that detects
April tags (see tags/pdf/tag36h11.pdf) in laptop or webcam images and
marks any tags in the live image.<commit_msg>Update readme: add opencv compile with cuda<commit_after>#### Building on Windows Visual Studio
##### Prerequisites
* Install Visual Studio 2013:
  
  **Note**: `Visual Studio Express` and `Visual Studio 2015` are not supported! 
  Update(2016.6): Now CUDA 8 RC could support VS2015 Update 1

  [Nvidia reference](http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-microsoft-windows/index.html#axzz44vwAc5Qx)

* Install Cuda 7.5:
  Also refer to above link. [download](https://developer.nvidia.com/cuda-downloads)

* Install CMake:
  The latest version is OK. [download](https://cmake.org/) 

* Install OpenCV:
  I installed 3.1, other versions should also work. [download](http://opencv.org/)
  * Run the EXE to extract the files. This EXE does not have an installer. Instead, you put your files where you want, and then add an environment variable
  * Adding the environment variable named "OpenCV_DIR" (no quotes) to the "build" subfolder in the folder where you extracted.(The exact folder you need will have one very important file in it: OpenCVConfig.cmake - this tells CMake which variables to set for you.)
  * Add a dir of "OpenCV binary DLLs" to Windows $PATH.(like f:/software/opencv/build/x64/vc12/bin)
  * If we run CUDA build, Opencv should be recompiled with CUDA options on, as the pre-built version does not support CUDA functions. Options suggested:
    * -DWITH_CUDA=ON -DBUILD_DOCS=OFF -DBUILD_TESTS=OFF -DBUILD_PERF_TESTS=OFF -DBUILD_SHARED_LIBS=OFF -DBUILD_WITH_STATIC_CRT=OFF -DBUILD_opencv_apps=OFF -DWITH_TBB=ON -DWITH_OPENMP=ON -DWITH_IPP=ON

##### Compile the solution
* Use the cmake-gui tool:

  Open the cmake-gui tool and selete the location of **Source and Build**.
  Then press configure to specify the generator: In this case, it's **Visual Studio 12 2013 Win64**.
  Last, press generate.

* Use the cmake command line:

  mkdir build && cd build/ && cmake -G "Visual Studio 12 2013 Win64"

**Done!** Just use Visual Studio to open the project-solution in dir build/ and compile everything.

=======
### Original README.md 

AprilTags library

Detect April tags (2D bar codes) in images; reports unique ID of each
detection, and optionally its position and orientation relative to a
calibrated camera.

See examples/apriltags_demo.cpp for a simple example that detects
April tags (see tags/pdf/tag36h11.pdf) in laptop or webcam images and
marks any tags in the live image.
{'fraction_non_alphanumeric': 0.09165154264972777, 'fraction_numerical': 0.020644283121597096, 'mean_word_length': 4.312048192771084, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 4, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 8, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '6042240', 'n_tokens_mistral': 1419, 'n_tokens_neox': 1277, 'n_words': 561}