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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 theproject site for all the details like

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

and step-by-step examples.

• Intel Caffe (Optimized for CPU and support for multi-node), in particular Xeon processors (HSW, BDW, Xeon Phi).
• OpenCL Caffe e.g. for AMD or Intel devices.
• Windows Caffe

Please join thecaffe-users group orgitter chat to ask questions and talk about methods and models.Framework development discussions and thorough bug reports are collected onIssues.

Happy brewing!

Caffe is released under theBSD 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}}