Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/LingDong-/edges2calligraphy
Using pix2pix to convert scribbles to Chinese calligraphy
https://github.com/LingDong-/edges2calligraphy
calligraphy chinese deeplearnjs edges machine-learning pix2pix
Last synced: 6 days ago
JSON representation
Using pix2pix to convert scribbles to Chinese calligraphy
- Host: GitHub
- URL: https://github.com/LingDong-/edges2calligraphy
- Owner: LingDong-
- License: mit
- Created: 2018-04-03T14:17:42.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-11-30T19:19:09.000Z (almost 4 years ago)
- Last Synced: 2024-10-30T20:53:54.185Z (17 days ago)
- Topics: calligraphy, chinese, deeplearnjs, edges, machine-learning, pix2pix
- Language: JavaScript
- Homepage:
- Size: 47.3 MB
- Stars: 117
- Watchers: 8
- Forks: 19
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-hackchinese - edges2calligraphy
README
![](screenshots/icon.png)
# edges2calligraphy
*From scribbles to Chinese calligraphy* (潦草字->赵体草书)
### Interactive demo: https://lingdong-.github.io/edges2calligraphy/This project uses a neural network called [pix2pix](https://arxiv.org/pdf/1611.07004.pdf) to transfer your scribbles into Chinese Calligraphy. It is trained on ~200 cursive characters from [Zhao Mengfu](https://en.wikipedia.org/wiki/Zhao_Mengfu)'s *Thousand Character Classic in Regular and Cursive Script* (《赵孟頫真草千字文》), labeled using custom software. It is largely based on [affinelayer's edges2cats demo](https://affinelayer.com/pixsrv/) and [pix2pix-tensorflow](https://github.com/affinelayer/pix2pix-tensorflow) project, and uses [deeplearn.js](https://deeplearnjs.org) to perform GPU accelerated computation in your browser.
Try the online deomo: https://lingdong-.github.io/edges2calligraphy/. (Tested in Chrome and Firefox. Does not work in Safari.)
## Examples
![](screenshots/screen01.png)
## Training
This project uses [pix2pix-tensorflow](https://github.com/affinelayer/pix2pix-tensorflow) for training. See [`/tools/README.md`](/tools/README.md) for details.