├── contributing.md ├── LICENSE └── README.md /contributing.md: -------------------------------------------------------------------------------- 1 | # Contribution Guidelines 2 | 3 | Please note that this project is released with a [Contributor Code of Conduct](code-of-conduct.md). By participating in this project you agree to abide by its terms. 4 | 5 | ## Table of Contents 6 | 7 | - [Adding to this list](#adding-to-this-list) 8 | - [Creating your own awesome list](#creating-your-own-awesome-list) 9 | - [Adding something to an awesome list](#adding-something-to-an-awesome-list) 10 | - [Updating your Pull Request](#updating-your-pull-request) 11 | 12 | ## Adding to this list 13 | 14 | Please ensure your pull request adheres to the following guidelines: 15 | 16 | - Search previous suggestions before making a new one, as yours may be a duplicate. 17 | - Make sure the list is useful before submitting. That implies it has enough content and every item has a good succinct description. 18 | - Make an individual pull request for each suggestion. 19 | - Use [title-casing](http://titlecapitalization.com) (AP style). 20 | - Use the following format: `[List Name](link)` 21 | - Link additions should be added to the bottom of the relevant category. 22 | - New categories or improvements to the existing categorization are welcome. 23 | - Check your spelling and grammar. 24 | - Make sure your text editor is set to remove trailing whitespace. 25 | - The pull request and commit should have a useful title. 26 | - The body of your commit message should contain a link to the repository. 27 | 28 | Thank you for your suggestions! 29 | 30 | ## Creating your own awesome list 31 | 32 | To create your own list, check out the [instructions](create-list.md). 33 | 34 | ## Adding something to an awesome list 35 | 36 | If you have something awesome to contribute to an awesome list, this is how you do it. 37 | 38 | You'll need a [GitHub account](https://github.com/join)! 39 | 40 | 1. Access the awesome list's GitHub page. For example: https://github.com/sindresorhus/awesome 41 | 2. Click on the `readme.md` file: ![Step 2 Click on Readme.md](https://cloud.githubusercontent.com/assets/170270/9402920/53a7e3ea-480c-11e5-9d81-aecf64be55eb.png) 42 | 3. Now click on the edit icon. ![Step 3 - Click on Edit](https://cloud.githubusercontent.com/assets/170270/9402927/6506af22-480c-11e5-8c18-7ea823530099.png) 43 | 4. You can start editing the text of the file in the in-browser editor. Make sure you follow guidelines above. You can use [GitHub Flavored Markdown](https://help.github.com/articles/github-flavored-markdown/). ![Step 4 - Edit the file](https://cloud.githubusercontent.com/assets/170270/9402932/7301c3a0-480c-11e5-81f5-7e343b71674f.png) 44 | 5. Say why you're proposing the changes, and then click on "Propose file change". ![Step 5 - Propose Changes](https://cloud.githubusercontent.com/assets/170270/9402937/7dd0652a-480c-11e5-9138-bd14244593d5.png) 45 | 6. Submit the [pull request](https://help.github.com/articles/using-pull-requests/)! 46 | 47 | ## Updating your Pull Request 48 | 49 | Sometimes, a maintainer of an awesome list will ask you to edit your Pull Request before it is included. This is normally due to spelling errors or because your PR didn't match the awesome-* list guidelines. 50 | 51 | [Here](https://github.com/RichardLitt/docs/blob/master/amending-a-commit-guide.md) is a write up on how to change a Pull Request, and the different ways you can do that. 52 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | CC0 1.0 Universal 2 | 3 | Statement of Purpose 4 | 5 | The laws of most jurisdictions throughout the world automatically confer 6 | exclusive Copyright and Related Rights (defined below) upon the creator and 7 | subsequent owner(s) (each and all, an "owner") of an original work of 8 | authorship and/or a database (each, a "Work"). 9 | 10 | Certain owners wish to permanently relinquish those rights to a Work for the 11 | purpose of contributing to a commons of creative, cultural and scientific 12 | works ("Commons") that the public can reliably and without fear of later 13 | claims of infringement build upon, modify, incorporate in other works, reuse 14 | and redistribute as freely as possible in any form whatsoever and for any 15 | purposes, including without limitation commercial purposes. These owners may 16 | contribute to the Commons to promote the ideal of a free culture and the 17 | further production of creative, cultural and scientific works, or to gain 18 | reputation or greater distribution for their Work in part through the use and 19 | efforts of others. 20 | 21 | For these and/or other purposes and motivations, and without any expectation 22 | of additional consideration or compensation, the person associating CC0 with a 23 | Work (the "Affirmer"), to the extent that he or she is an owner of Copyright 24 | and Related Rights in the Work, voluntarily elects to apply CC0 to the Work 25 | and publicly distribute the Work under its terms, with knowledge of his or her 26 | Copyright and Related Rights in the Work and the meaning and intended legal 27 | effect of CC0 on those rights. 28 | 29 | 1. Copyright and Related Rights. A Work made available under CC0 may be 30 | protected by copyright and related or neighboring rights ("Copyright and 31 | Related Rights"). Copyright and Related Rights include, but are not limited 32 | to, the following: 33 | 34 | i. the right to reproduce, adapt, distribute, perform, display, communicate, 35 | and translate a Work; 36 | 37 | ii. moral rights retained by the original author(s) and/or performer(s); 38 | 39 | iii. publicity and privacy rights pertaining to a person's image or likeness 40 | depicted in a Work; 41 | 42 | iv. rights protecting against unfair competition in regards to a Work, 43 | subject to the limitations in paragraph 4(a), below; 44 | 45 | v. rights protecting the extraction, dissemination, use and reuse of data in 46 | a Work; 47 | 48 | vi. database rights (such as those arising under Directive 96/9/EC of the 49 | European Parliament and of the Council of 11 March 1996 on the legal 50 | protection of databases, and under any national implementation thereof, 51 | including any amended or successor version of such directive); and 52 | 53 | vii. other similar, equivalent or corresponding rights throughout the world 54 | based on applicable law or treaty, and any national implementations thereof. 55 | 56 | 2. Waiver. To the greatest extent permitted by, but not in contravention of, 57 | applicable law, Affirmer hereby overtly, fully, permanently, irrevocably and 58 | unconditionally waives, abandons, and surrenders all of Affirmer's Copyright 59 | and Related Rights and associated claims and causes of action, whether now 60 | known or unknown (including existing as well as future claims and causes of 61 | action), in the Work (i) in all territories worldwide, (ii) for the maximum 62 | duration provided by applicable law or treaty (including future time 63 | extensions), (iii) in any current or future medium and for any number of 64 | copies, and (iv) for any purpose whatsoever, including without limitation 65 | commercial, advertising or promotional purposes (the "Waiver"). Affirmer makes 66 | the Waiver for the benefit of each member of the public at large and to the 67 | detriment of Affirmer's heirs and successors, fully intending that such Waiver 68 | shall not be subject to revocation, rescission, cancellation, termination, or 69 | any other legal or equitable action to disrupt the quiet enjoyment of the Work 70 | by the public as contemplated by Affirmer's express Statement of Purpose. 71 | 72 | 3. Public License Fallback. Should any part of the Waiver for any reason be 73 | judged legally invalid or ineffective under applicable law, then the Waiver 74 | shall be preserved to the maximum extent permitted taking into account 75 | Affirmer's express Statement of Purpose. In addition, to the extent the Waiver 76 | is so judged Affirmer hereby grants to each affected person a royalty-free, 77 | non transferable, non sublicensable, non exclusive, irrevocable and 78 | unconditional license to exercise Affirmer's Copyright and Related Rights in 79 | the Work (i) in all territories worldwide, (ii) for the maximum duration 80 | provided by applicable law or treaty (including future time extensions), (iii) 81 | in any current or future medium and for any number of copies, and (iv) for any 82 | purpose whatsoever, including without limitation commercial, advertising or 83 | promotional purposes (the "License"). The License shall be deemed effective as 84 | of the date CC0 was applied by Affirmer to the Work. Should any part of the 85 | License for any reason be judged legally invalid or ineffective under 86 | applicable law, such partial invalidity or ineffectiveness shall not 87 | invalidate the remainder of the License, and in such case Affirmer hereby 88 | affirms that he or she will not (i) exercise any of his or her remaining 89 | Copyright and Related Rights in the Work or (ii) assert any associated claims 90 | and causes of action with respect to the Work, in either case contrary to 91 | Affirmer's express Statement of Purpose. 92 | 93 | 4. Limitations and Disclaimers. 94 | 95 | a. No trademark or patent rights held by Affirmer are waived, abandoned, 96 | surrendered, licensed or otherwise affected by this document. 97 | 98 | b. Affirmer offers the Work as-is and makes no representations or warranties 99 | of any kind concerning the Work, express, implied, statutory or otherwise, 100 | including without limitation warranties of title, merchantability, fitness 101 | for a particular purpose, non infringement, or the absence of latent or 102 | other defects, accuracy, or the present or absence of errors, whether or not 103 | discoverable, all to the greatest extent permissible under applicable law. 104 | 105 | c. Affirmer disclaims responsibility for clearing rights of other persons 106 | that may apply to the Work or any use thereof, including without limitation 107 | any person's Copyright and Related Rights in the Work. Further, Affirmer 108 | disclaims responsibility for obtaining any necessary consents, permissions 109 | or other rights required for any use of the Work. 110 | 111 | d. Affirmer understands and acknowledges that Creative Commons is not a 112 | party to this document and has no duty or obligation with respect to this 113 | CC0 or use of the Work. 114 | 115 | For more information, please see 116 | 117 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Awesome Caffe [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/jtoy/awesome) 2 | 3 | This page contains a curated list of awesome Caffe examples, tutorials and blogs. It is inspired by awesome-php and awesome-machine-learning. 4 | 5 | ## Contributing 6 | 7 | If you think I have missed out on something (or) have any suggestions (papers, implementations and other resources), feel free to pull a request 8 | 9 | Feedback and contributions are welcome! 10 | 11 | ## Table of Contents 12 | - [1. Tutorials](#Tutorials) 13 | - [2. Vision](#Vision) 14 | - [3. NLP](#NLP) 15 | - [4. Speech](#Speech) 16 | - [5. Building Blocks](#Building) 17 | - [6. Tools](#Tools) 18 | 19 | ============================================================================================================ 20 | ## Books 21 | - [Deep Learning - Ian Goodfellow and Yoshua Bengio and Aaron Courville](http://www.deeplearningbook.org/) 22 | - [Deep Learning (Simplified Chinese)](https://github.com/exacity/deeplearningbook-chinese) 23 | 24 | 25 | ## 1. Tutorials 26 | - [DIY Deep Learning for Vision with Caffe](https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.p) 27 | - [Tutorial Documentation](http://caffe.berkeleyvision.org/tutorial/) 28 | - [Tutorial Documentation (Simplified Chinese)](http://caffecn.cn/?/page/tutorial) 29 | 30 | 31 | ## 2. Vision 32 | >> ### 2.1 Image Classification 33 | >> - [ResNet-v3](https://github.com/terrychenism/ResNeXt) 34 | >> - [denseNet](https://github.com/liuzhuang13/DenseNet) 35 | >> - [Deep Residual Networks](https://github.com/KaimingHe/deep-residual-networks) 36 | >> - [Highway Networks](https://github.com/flukeskywalker/highway-networks) 37 | >> - [Deep-Compression-AlexNet](https://github.com/songhan/Deep-Compression-AlexNet) 38 | >> - [SqueezeNet](https://github.com/DeepScale/SqueezeNet) 39 | >> - [GoogleNet-V2](https://github.com/lim0606/caffe-googlenet-bn) 40 | >> - [Oriented Response Networks](https://github.com/ZhouYanzhao/ORN) 41 | 42 | >> ### 2.2 Object Detection 43 | >> - [PVANet](https://github.com/sanghoon/pva-faster-rcnn) 44 | >> - [R-FCN](https://github.com/Orpine/py-R-FCN) 45 | >> - [SSD: Single Shot MultiBox Detector](https://github.com/weiliu89/caffe/tree/ssd) 46 | >> - [YOLO in caffe](https://github.com/xingwangsfu/caffe-yolo) 47 | >> - [DeepBox](https://github.com/weichengkuo/DeepBox) 48 | >> - [Faster R-CNN](https://github.com/rbgirshick/py-faster-rcnn) 49 | >> - [Fast R-CNN](https://github.com/rbgirshick/fast-rcnn) 50 | 51 | >> ### 2.3 Image Segmentation 52 | >> - [Mask R-CNN](https://github.com/jasjeetIM/Mask-RCNN) 53 | >> - [DeepLab](https://bitbucket.org/aquariusjay/deeplab-public-ver2) 54 | >> - [CRF-RNN](https://github.com/torrvision/crfasrnn) 55 | >> - [SegNet](https://github.com/alexgkendall/caffe-segnet) 56 | >> - [DeconvNet: Learning Deconvolution Network for Semantic Segmentation](https://github.com/HyeonwooNoh/DeconvNet) 57 | >> - [Fully Convolutional Networks for Semantic Segmentation](https://github.com/shelhamer/fcn.berkeleyvision.org) 58 | 59 | >> ### 2.4 Face Detection / Recognition / Verification 60 | >> - [Center Loss](https://github.com/ydwen/caffe-face) 61 | >> - [MTCNN_face_detection_alignment](https://github.com/DaFuCoding/MTCNN_Caffe) 62 | >> - [VGG-Face](http://www.robots.ox.ac.uk/~vgg/software/vgg_face/) 63 | >> - [TripletLoss(FaceNet)](https://github.com/pinguo-luhaofang/tripletloss) 64 | >> - [dockerface](https://github.com/natanielruiz/dockerface) - Easy to install and use deep learning Faster R-CNN face detection for images and video in a docker container. 65 | 66 | >> ### 2.5 Action Recognition 67 | >> - [UntrimmedNets](https://github.com/wanglimin/UntrimmedNet) 68 | >> - [C3D](https://github.com/chuckcho/video-caffe) (a recent version of Caffe) 69 | >> - [TDD](https://github.com/wanglimin/TDD) 70 | >> - [LRCN](https://github.com/LisaAnne/lisa-caffe-public/tree/lstm_video_deploy) 71 | 72 | >> ### 2.6 Object Tracking 73 | >> - [FCNT](https://github.com/scott89/FCNT) 74 | 75 | >> ### 2.7 Scene Classification 76 | >> - [Places CNN](http://places.csail.mit.edu/downloadCNN.html) 77 | 78 | >> ### 2.8 Image Super-resolution 79 | >> - [SRCNN](http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html) 80 | 81 | >> ### 2.9 Images Generation 82 | >> - [cnn-vis](https://github.com/jcjohnson/cnn-vis) 83 | >> - [style-transfer](https://github.com/fzliu/style-transfer) 84 | >> - [Colorful Image Colorization](https://github.com/richzhang/colorization) 85 | >> - [Coupled Face Generation](https://github.com/mingyuliutw/CoGAN) 86 | 87 | >> ### 2.10 Self-driving 88 | >> - [DeepDrive](http://deepdrive.io/) 89 | >> - [Berkeley DeepDrive](http://bdd.berkeley.edu/) 90 | >> - [Princeton deepdriving](http://deepdriving.cs.princeton.edu/) 91 | 92 | >> ### 2.11 Reinforcement Learning 93 | >> - [DRQN](https://github.com/mhauskn/dqn) 94 | >> - [DQN](https://github.com/muupan/dqn-in-the-caffe) 95 | 96 | >> ## 2.12 Image Generation 97 | >> - [VAE](https://github.com/cdoersch/vae_tutorial) 98 | 99 | ## 3. NLP 100 | >> - [NLP-Caffe](https://github.com/Russell91/nlpcaffe) 101 | >> - [Sentiment Analysis](http://city.shaform.com/blog/2015/06/06/caffe-sentiment-analysis.html) 102 | 103 | 104 | ## 4. Speech 105 | >> - [Speech Recognition](https://github.com/pannous/caffe-speech-recognition) 106 | >> - [Kaldi](https://github.com/kaldi-asr/kaldi) 107 | 108 | 109 | ## 5. Building Blocks 110 | >> ### 5.1 Initialization 111 | >> - [k-means initialization](https://github.com/philkr/magic_init) 112 | >> - [LSUV](https://github.com/ducha-aiki/LSUVinit) 113 | 114 | >> ### 5.2 Activation Function 115 | >> TODO 116 | 117 | ## 6. Tools 118 | >> ### 6.1 Converter 119 | >> - [caffe-tensorflow](https://github.com/ethereon/caffe-tensorflow) 120 | >> - [caffe-theano-conversion](https://github.com/kitofans/caffe-theano-conversion) 121 | >> - [CaffeToKeras](https://github.com/MarcBS/keras) 122 | 123 | >> ### 6.2 Labeling 124 | >> - [labelme](https://github.com/wkentaro/labelme) 125 | >> - [LabelImg](https://github.com/tzutalin/labelImg) 126 | >> - [BBox-Label-Tool](https://github.com/puzzledqs/BBox-Label-Tool) 127 | >> - [FastAnnotationTool](https://github.com/christopher5106/FastAnnotationTool) 128 | 129 | >> ### 6.3 Data Augmentation 130 | >> - [Augmentor](https://github.com/mdbloice/Augmentor) 131 | 132 | >> ### 6.4 Parameter Search 133 | >> - [Spearmint](https://github.com/kuz/caffe-with-spearmint) 134 | 135 | >> ### 6.5 Visualization 136 | >> - [netron](https://github.com/lutzroeder/netron) 137 | >> - [deep-visualization-toolbox](https://github.com/yosinski/deep-visualization-toolbox) 138 | >> - [DeepDraw](https://github.com/auduno/deepdraw) 139 | 140 | >> ### 6.6 Mobile Platform 141 | >> - [ncnn](https://github.com/Tencent/ncnn) 142 | >> - [ShuffleNet](https://github.com/farmingyard/ShuffleNet) 143 | >> - [caffe-android-lib](https://github.com/sh1r0/caffe-android-lib) 144 | >> - [caffe-ios](https://github.com/aleph7/caffe/) 145 | >> - [windows](https://github.com/dlunion/CC4.0) 146 | 147 | >> ### 6.7 Intel and AMD 148 | >> - [hipCaffe-AMD’s Radeon Instinct GPUs](https://github.com/ROCmSoftwarePlatform/hipCaffe) 149 | >> - [Intel® Xeon Phi™](https://software.intel.com/en-us/articles/caffe-optimized-for-intel-architecture-applying-modern-code-techniques) 150 | >> - [OpenCL-caffe](https://github.com/amd/OpenCL-caffe) 151 | >> - [SkimCaffe](https://github.com/IntelLabs/SkimCaffe) 152 | 153 | >> ### 6.8 Parallel and Distributed computing 154 | >> - [A multi-GPU and memory-reduced MAT-Caffe](https://github.com/sciencefans/CaffeMex_v2) 155 | >> - [SparkNet](https://github.com/amplab/SparkNet) 156 | >> - [CaffeOnSpark](https://github.com/yahoo/CaffeOnSpark) 157 | >> - [petuum/bosen ](https://github.com/petuum/bosen) 158 | 159 | 160 | >> ### 6.9 Net Builder 161 | >> - [pynetbuilder](https://github.com/jay-mahadeokar/pynetbuilder) 162 | --------------------------------------------------------------------------------