Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.

Check out the project site for all the details like

• DIY Deep Learning for Vision with Caffe
• Tutorial Documentation
• BAIR reference models and the community model zoo
• Installation instructions

and step-by-step examples.

Requirements: Visual Studio 2015, CUDA 8.0, third party libraries: Baidu Yun or Google Drive. Please extract the archive into ./windows/thirdparty/. Then, add the folder ./windows/thirdparty/bins to the environment variable PATH.

Copy .\windows\CommonSettings.props.example to .\windows\CommonSettings.props

By defaults Windows build requires CUDA and cuDNN libraries. Both can be disabled by adjusting build variables in .\windows\CommonSettings.props. Python support is disabled by default, but can be enabled via .\windows\CommonSettings.props as well.

Download CUDA Toolkit 8.0 from nVidia website. If you don't have CUDA installed, you can experiment with CPU_ONLY build. In .\windows\CommonSettings.props set CpuOnlyBuild to true and set UseCuDNN & UseNCCL to false.

Download cuDNN v5 from nVidia website. Unpack downloaded zip to %CUDA_PATH% (environment variable set by CUDA installer). Alternatively, you can unpack zip to any location and set CuDnnPath to point to this location in .\windows\CommonSettings.props. CuDnnPath defined in .\windows\CommonSettings.props. Also, you can disable cuDNN by setting UseCuDNN to false in the property file.

To build Caffe Python wrapper set PythonSupport to true in .\windows\CommonSettings.props. Download Miniconda 2.7 64-bit Windows installer [from Miniconda website] (http://conda.pydata.org/miniconda.html). Install for all users and add Python to PATH (through installer).

Run the following commands from elevated command prompt:

conda install --yes numpy scipy matplotlib scikit-image pip
pip install protobuf

After you have built solution with Python support, in order to use it you have to either:

• set PythonPath environment variable to point to <caffe_root>\Build\x64\Release\pycaffe, or
• copy folder <caffe_root>\Build\x64\Release\pycaffe\caffe under <python_root>\lib\site-packages.

To build Caffe Matlab wrapper set MatlabSupport to true and MatlabDir to the root of your Matlab installation in .\windows\CommonSettings.props.

After you have built solution with Matlab support, in order to use it you have to add the ./matlab folder to Matlab search path.

Now, you should be able to build .\windows\Caffe.sln

Caffe is released under the BSD 2-Clause license. The BAIR/BVLC reference models are released for unrestricted use.

Please cite Caffe in your publications if it helps your research:

@article{jia2014caffe,
  Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
  Journal = {arXiv preprint arXiv:1408.5093},
  Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
  Year = {2014}
}