caffe linux windows,caffe: Caffe on both Linux and Windows
This branch of Caffe extends BVLC-led Caffe by adding Windows support and other functionalities commonly used by Microsoft's researchers, such as managed-code wrapper, Faster-RCNN, R-FCN, etc.
Update: this branch is not actively maintained. Please checkout this for more active Windows support.
Caffe
Linux (CPU)
Windows (CPU)
Caffe is a deep learning framework made with expression, speed, and modularity in mind.
It is developed by the Berkeley Vision and Learning Center (BVLC) and community contributors.
Check out the project site for all the details like
and step-by-step examples.
Windows Setup
Requirements: Visual Studio 2013
Pre-Build Steps
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.
3rd party dependencies required by Caffe are automatically resolved via NuGet.
CUDA
Download CUDA Toolkit 7.5 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 to false.
cuDNN
Download cuDNN v4 or 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.
Python
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
Remark
After you have built solution with Python support, in order to use it you have to either:
set PythonPath environment variable to point to \Build\x64\Release\pycaffe, or
copy folder \Build\x64\Release\pycaffe\caffe under \lib\site-packages.
Matlab
To build Caffe Matlab wrapper set MatlabSupport to true and MatlabDir to the root of your Matlab installation in .\windows\CommonSettings.props.
Remark
After you have built solution with Matlab support, in order to use it you have to:
add the generated matcaffe folder to Matlab search path, and
add \Build\x64\Release to your system path.
Build
Now, you should be able to build .\windows\Caffe.sln
License and Citation
Caffe is released under the BSD 2-Clause license.
The 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}
}