编译Caffe for Windows
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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: 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
- DIY Deep Learning for Vision with Caffe
- Tutorial Documentation
- BVLC reference models and the community model zoo
- Installation instructions
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 pippip 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 <caffe_root>\Build\x64\Release\pycaffe
, or
* copy folder <caffe_root>\Build\x64\Release\pycaffe\caffe
under <python_root>\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 <caffe_root>\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}}
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