AutoCJK

AutoCJK is a tool for generating low-resolution predictions of uncommon CJK characters, given full-width images of their components.

Example:

(Left-to-right: (a) source left-hand component, (b) source right-hand component, (c) expected composition, (d) predicted composition, (e) c/d difference)

How do I generate a new character?

First install the project and its dependencies. See platform-specific instructions on the wiki.

Given a font at ~/Downloads/font.otf, we can render ⿰市來 and write the generated image to /tmp/out.png with:

bazel run //src:main -- \
  --font_path=<path_to_font> \
  --input='⿰市來' \
  --out=/tmp/out.png

Usage guide:

Bundled with this repo is /src/generator.h5, a trained model with pretty good results. This generator was trained on ~270k image pairs, generated by extracting characters from the fonts NotoSansCJKsc-* and NotoSerifCJKsc-*.

The resultant generator is pretty good at generating characters in that style. It might even be pretty good at generating characters in a new style. If you discover it's not, you can (a) generate a new batch of training images in your own font style, and (b) run model.py in order to train a new model. If you save that model as src/generator.h5, you can continue to use bazel run //src:main as expected.