Optical character recognition for Japanese text, with the main focus being Japanese manga. It uses a custom end-to-end model built with PaddePaddle framework and PaddleOCR library.

This MangaOCR is inspired by an old project called manga-ocr built by kha-white and other contributors. We admit that although kha-white's manga-ocr model has excellent performance, the size of the model is large (444Mb) and the recognition speed is a bit slow. Thus, this project is built with our goal to provide another end-to-end lightweight model for text recognition in manga. And to achieve performance equivalent to manga-ocr, we also aim to handle a variety of special text types in manga:

• both vertical and horizontal text
• text with furigana
• text overlaid on images
• wide variety of fonts and font styles
• low quality images

Up until now, our model has achieved the following:

• Small model size with only about 8Mb
• Recognize both vertical and horizontal text
• Recognize text overlapping the image
• Recognize with different fonts and font styles

And things that haven't been achieved yet:

• Better recognition results when compared with manga-ocr. Currently, our model has a CER(Character Error Rate) result of about 14.4% ( 2-10% is good for printed text and 10-20% for handwritten text ).
• Full recognition of unusually long text. With texts of unusually long length (usually over 100 characters), the model is able to predict the first 25-50% of characters, then errors gradually appear.

Here are some currently cherry-picked examples showing the capability of the model.

image	Our MangaOCR result
	軍のテストフライトセンター
	つぎの日曜日は
	成魚」はこれくらい
	うわああああああああああああ
	付き合い始めたきっかけだって
	極東方面に所属不明機を多数確認！
	永遠が見えるまで駆けぬけていきたい
	極道やった経験が生かされてるやろ
	まだダイエットあきらめてなかったわけ？

This project is currently working with the usage of:

• Manga109-s dataset
• CC-100 dataset