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https://github.com/pavelgonchar/neural-art-mini
Lightweight version of mxnet neural art implementation
https://github.com/pavelgonchar/neural-art-mini
Last synced: about 2 months ago
JSON representation
Lightweight version of mxnet neural art implementation
- Host: GitHub
- URL: https://github.com/pavelgonchar/neural-art-mini
- Owner: pavelgonchar
- License: bsd-2-clause
- Created: 2016-06-04T13:04:05.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2016-06-05T15:54:12.000Z (over 8 years ago)
- Last Synced: 2024-11-08T18:45:29.688Z (2 months ago)
- Language: Python
- Size: 15.6 MB
- Stars: 265
- Watchers: 10
- Forks: 35
- Open Issues: 2
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-MXNet - neural-art-mini
README
# neural-art-mini
Lightweight version of mxnet neural art implementation using ~4.8M SqueezeNet model. Compressed model is less than 500KB![input](input/minsk.jpg?raw=true "input")
![style](input/starry_night.jpg?raw=true "style")
![output](output/tmp_950.jpg?raw=true "output")![animated](output/animated.gif?raw=true "animated")
Sources
-------
- [SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size](http://arxiv.org/abs/1602.07360)
- [MXNet Neural Art](https://github.com/dmlc/mxnet/tree/master/example/neural-style)
- [SqueezeNet pre-trained model](https://github.com/DeepScale/SqueezeNet)