-[Caffe: Convolutional Architecture for Fast Feature Extraction](http://caffe.berkeleyvision.org)
+# Caffe
-Created by [Yangqing Jia](http://daggerfs.com), UC Berkeley EECS department.
-In active development by the Berkeley Vision and Learning Center ([BVLC](http://bvlc.eecs.berkeley.edu/)).
+[](https://travis-ci.org/BVLC/caffe)
+[](LICENSE)
-## Introduction
+Caffe is a deep learning framework made with expression, speed, and modularity in mind.
+It is developed by Berkeley AI Research ([BAIR](http://bair.berkeley.edu))/The Berkeley Vision and Learning Center (BVLC) and community contributors.
-Caffe aims to provide computer vision scientists with a **clean, modifiable
-implementation** of state-of-the-art deep learning algorithms. Network structure
-is easily specified in separate config files, with no mess of hard-coded
-parameters in the code. Python and Matlab wrappers are provided.
+Check out the [project site](http://caffe.berkeleyvision.org) for all the details like
-At the same time, Caffe fits industry needs, with blazing fast C++/Cuda code for
-GPU computation. Caffe is currently the fastest GPU CNN implementation publicly
-available, and is able to process more than **20 million images per day** on a
-single Tesla K20 machine \*.
+- [DIY Deep Learning for Vision with Caffe](https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.p)
+- [Tutorial Documentation](http://caffe.berkeleyvision.org/tutorial/)
+- [BAIR reference models](http://caffe.berkeleyvision.org/model_zoo.html) and the [community model zoo](https://github.com/BVLC/caffe/wiki/Model-Zoo)
+- [Installation instructions](http://caffe.berkeleyvision.org/installation.html)
-Caffe also provides **seamless switching between CPU and GPU**, which allows one
-to train models with fast GPUs and then deploy them on non-GPU clusters with one
-line of code: `Caffe::set_mode(Caffe::CPU)`.
+and step-by-step examples.
-Even in CPU mode, computing predictions on an image takes only 20 ms when images
-are processed in batch mode.
+## Custom distributions
-* [Installation instructions](http://caffe.berkeleyvision.org/installation.html)
-* [Caffe presentation](https://docs.google.com/presentation/d/1lzyXMRQFlOYE2Jy0lCNaqltpcCIKuRzKJxQ7vCuPRc8/edit?usp=sharing) at the Berkeley Vision Group meeting
+ - [Intel Caffe](https://github.com/BVLC/caffe/tree/intel) (Optimized for CPU and support for multi-node), in particular Intel® Xeon processors.
+- [OpenCL Caffe](https://github.com/BVLC/caffe/tree/opencl) e.g. for AMD or Intel devices.
+- [Windows Caffe](https://github.com/BVLC/caffe/tree/windows)
-\* When measured with the [SuperVision](http://www.image-net.org/challenges/LSVRC/2012/supervision.pdf) model that won the ImageNet Large Scale Visual Recognition Challenge 2012.
+## Community
-## License
+[](https://gitter.im/BVLC/caffe?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
-Caffe is BSD 2-Clause licensed (refer to the
-[LICENSE](http://caffe.berkeleyvision.org/license.html) for details).
+Please join the [caffe-users group](https://groups.google.com/forum/#!forum/caffe-users) or [gitter chat](https://gitter.im/BVLC/caffe) to ask questions and talk about methods and models.
+Framework development discussions and thorough bug reports are collected on [Issues](https://github.com/BVLC/caffe/issues).
-The pretrained models published by the BVLC, such as the
-[Caffe reference ImageNet model](https://www.dropbox.com/s/n3jups0gr7uj0dv/caffe_reference_imagenet_model)
-are licensed for academic research / non-commercial use only. However, Caffe is
-a full toolkit for model training, so start brewing your own Caffe model today!
+Happy brewing!
-## Citing Caffe
+## License and Citation
-Please kindly cite Caffe in your publications if it helps your research:
+Caffe is released under the [BSD 2-Clause license](https://github.com/BVLC/caffe/blob/master/LICENSE).
+The BAIR/BVLC reference models are released for unrestricted use.
- @misc{Jia13caffe,
- Author = {Yangqing Jia},
- Title = { {Caffe}: An Open Source Convolutional Architecture for Fast Feature Embedding},
- Year = {2013},
- Howpublished = {\url{http://caffe.berkeleyvision.org/}
- }
-
-## Building documentation
-
-Tutorials and general documentation is written in Markdown format in the `docs/` folder.
-While the format is quite easy to read directly, you may prefer to view the whole thing as a website.
-To do so, simply run `jekyll serve -s docs` and view the documentation website at `http://0.0.0.0:4000` (to get jekyll, you must have ruby and do `gem install jekyll`).
-
-We strive to provide provide lots of usage examples, and to document all code in docstrings.
-We'd appreciate your contribution to this effort!
-
-## Contributing
-
-Caffe is developed with active participation of the community by the [Berkeley Vision and Learning Center](http://bvlc.eecs.berkeley.edu/).
-We welcome all contributions!
-
-Our workflow is this:
+Please cite Caffe in your publications if it helps your research:
-- The `dev` branch is for new development, community contributions, and testing.
-- The `master` branch is handled by BVLC, which will integrate changes from `dev` on a roughly monthly schedule.
-- Do new development in [feature branches](https://www.atlassian.com/git/workflows#!workflow-feature-branch) with decriptive names.
-- Bring your work up-to-date by [rebasing](http://git-scm.com/book/en/Git-Branching-Rebasing) onto the latest `dev`. (Polish your changes by [interactive rebase](https://help.github.com/articles/interactive-rebase), if you'd like.)
-- [Pull request](https://help.github.com/articles/using-pull-requests) your contribution to BVLC/caffe's `dev` branch for discussion and review.
-
-#### [Shelhamer's](https://github.com/shelhamer) "life of a branch in four acts":
-
-Make the `feature` branch off of the latest `bvlc/dev`
-```
-git checkout dev
-git pull upstream dev
-git checkout -b feature
-# do your work, make commits
-```
-
-Prepare to merge by rebasing your branch on the latest `bvlc/dev`
-```
-# make sure dev is fresh
-git checkout dev
-git pull upstream dev
-# rebase your branch on the tip of dev
-git checkout feature
-git rebase --preserve-merges dev
-```
-
-Push your branch to pull request it into `dev`
-```
-git push origin feature
-# ...make pull request... you can do `git pull-request` if you install [hub](https://github.com/github/hub)
-```
-
-The pull request of feature into `dev` will be a clean merge, applause.
+ @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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