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@@ -1,115 +1,3 @@ -[Caffe: Convolutional Architecture for Fast Feature Extraction](http://caffe.berkeleyvision.org) +Caffe: Convolutional Architecture for Fast Feature Embedding -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/)). - -## Introduction - -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. - -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 **40 million images per day** on a -single NVIDIA K40 GPU (or 20 million per day on a K20)\*. - -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)`. - -Even in CPU mode, computing predictions on an image takes only 20 ms when images -are processed in batch mode. - -* [Caffe introductory presentation](https://www.dropbox.com/s/10fx16yp5etb8dv/caffe-presentation.pdf) -* [Installation instructions](http://caffe.berkeleyvision.org/installation.html) - -\* 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. - -## License - -Caffe is BSD 2-Clause licensed (refer to the -[LICENSE](http://caffe.berkeleyvision.org/license.html) for details). - -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! - -## Citing Caffe - -Please kindly cite Caffe in your publications if it helps your research: - - @misc{Jia13caffe, - Author = {Yangqing Jia}, - Title = { {Caffe}: An Open Source Convolutional Architecture for Fast Feature Embedding}, - Year = {2013}, - Howpublished = {\url{http://caffe.berkeleyvision.org/}} - } - -## Documentation - -Tutorials and general documentation are 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](http://jekyllrb.com/), 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! - -## Development - -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! - -### The release cycle - -- The `dev` branch is for new development, including community contributions. We aim to keep it in a functional state, but large changes may occur and things may get broken every now and then. Use this if you want the "bleeding edge". -- The `master` branch is handled by BVLC, which will integrate changes from `dev` on a roughly monthly schedule, giving it a release tag. Use this if you want more stability. - -### Setting priorities - -- Make GitHub Issues for bugs, features you'd like to see, questions, etc. -- Development work is guided by [milestones](https://github.com/BVLC/caffe/issues?milestone=1), which are sets of issues selected for concurrent release (integration from `dev` to `master`). -- Please note that since the core developers are largely researchers, we may work on a feature in isolation from the open-source community for some time before releasing it, so as to claim honest academic contribution. We do release it as soon as a reasonable technical report may be written about the work, and we still aim to inform the community of ongoing development through Issues. - -### Contibuting - -- Do new development in [feature branches](https://www.atlassian.com/git/workflows#!workflow-feature-branch) with descriptive 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. - * PRs should live fast, die young, and leave a beautiful merge. Pull request sooner than later so that discussion can guide development. - * Code must be accompanied by documentation and tests at all times. - * Only fast-forward merges will be accepted. - -See our [development guidelines](http://caffe.berkeleyvision.org/development.html) for further details–the more closely these are followed, the sooner your work will be merged. - -#### [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 dev -``` - -Push your branch to pull request it into `dev` -``` -git push origin feature -# ...make pull request to dev... -``` - -Now make a pull request! You can do this from the command line (`git pull-request -b dev`) if you install [hub](https://github.com/github/hub). - -The pull request of `feature` into `dev` will be a clean merge. Applause. +Consult the [project website](http://caffe.berkeleyvision.org) for all documentation. |