Github上一些精致且实用的TensorFlow项目及相关论文

【导读】Github上有许多成熟的TensorFlow代码和模型,可以直接用于科研和工程中。本文会介绍其中一些与自动问答、机器翻译、风格转换等相关的精致且实用的项目。


Seq2Seq Chatbot


200行代码实现的Twitter/Cornell-Movie聊天机器人

项目地址:

https://github.com/tensorlayer/seq2seq-chatbot

相关资料:

  • Practical-Seq2Seq: 

    http://suriyadeepan.github.io/2016-12-31-practical-seq2seq/

  • The Unreasonable Effectiveness of Recurrent Neural Networks: 

    http://karpathy.github.io/2015/05/21/rnn-effectiveness/

  • Understanding LSTM Networks: 

    http://colah.github.io/posts/2015-08-Understanding-LSTMs/ 


运行样例:

Query > happy birthday have a nice day
> thank you so much
> thank babe
> thank bro
> thanks so much
> thank babe i appreciate it
Query > donald trump won last nights presidential
debate according to snap online polls
> i dont know what the fuck is that
> i think he was a racist
> he is not a racist
> he is a liar
> trump needs to be president


Domain Transfer Network (DTN)


跨域图像生成,例如输入真人照片,生成卡通头像。

项目地址:

https://github.com/yunjey/domain-transfer-network

相关论文:

  • 《Unsupervised Cross-Domain Image Generation》:

    https://arxiv.org/abs/1611.02200



neural-style-tf


利用卷积网络变换图像的风格,将普通图像变为素描、艺术画等。

项目地址:

https://github.com/cysmith/neural-style-tf

参考文章:

  • 《Image Style Transfer Using Convolutional Neural Networks》:

    http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Gatys_Image_Style_Transfer_CVPR_2016_paper.pdf

  • 《Artistic style transfer for videos》:

    https://arxiv.org/abs/1604.08610

  • 《Preserving Color in Neural Artistic Style Transfer》:

    https://arxiv.org/abs/1606.05897



darkflow


YOLO目标检测,可以直接导入Darknet的模型。

项目地址:

https://github.com/thtrieu/darkflow

相关论文:

  • YOLOv1: 

    https://arxiv.org/abs/1506.02640

  • YOLOv2:

     https://arxiv.org/abs/1612.08242



transformer


论文Attention is All you Need的实现,端到端机器翻译,可以在自己电脑上实现谷歌翻译的功能。

项目地址:

https://github.com/thtrieu/darkflow

相关论文:

  • 《Attention is All you Need》:

    https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf


运行样例(输入德语,翻译得到英语):

source: Sie war eine jährige Frau namens Alex
expected: She was a yearold woman named Alex
got: She was a woman named yearold name

source: Und als ich das hörte war ich erleichtert
expected: Now when I heard this I was so relieved
got: And when I heard that I was an

-END-

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