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owocr/README.md
Maciej Budyś 7c79777c92 update readme
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Manga OCR

Optical character recognition for Japanese text, with the main focus being Japanese manga. It uses a custom end-to-end model built with Transformers' Vision Encoder Decoder framework.

Manga OCR can be used as a general purpose printed Japanese OCR, but its main goal was to provide a high quality text recognition, robust against various scenarios specific to manga:

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

Unlike many OCR models, Manga OCR supports recognizing multi-line text in a single forward pass, so that text bubbles found in manga can be processed at once, without splitting them into lines.

Installation

You need Python 3.6+.

If you want to run with GPU, install PyTorch as described here, otherwise this step can be skipped.

Run in command line:

pip3 install manga-ocr

Usage

Python API

from manga_ocr import MangaOcr

mocr = MangaOcr()
text = mocr('/path/to/img')

or

import PIL.Image

from manga_ocr import MangaOcr

mocr = MangaOcr()
img = PIL.Image.open('/path/to/img')
text = mocr(img)

Running in the background

Manga OCR can run in the background and process new images as they appear.

You might use a tool like ShareX to manually capture a region of the screen and let the OCR read it either from the system clipboard, or a specified directory. By default, Manga OCR will write recognized text to clipboard, from which it can be read by a dictionary like Yomichan.

Your full setup for reading manga in Japanese with a dictionary might look like this:

capture region with ShareX -> write image to clipboard -> Manga OCR -> write text to clipboard -> Yomichan

https://user-images.githubusercontent.com/22717958/150238361-052b95d1-0152-485f-a441-48a957536239.mp4

  • To read images from clipboard and write recognized texts to clipboard, run in command line:
    manga_ocr
    
  • To read images from ShareX's screenshot folder, run in command line:
    manga_ocr "/path/to/sharex/screenshot/folder"
    

When running for the first time, downloading the model (~400 MB) might take a few minutes. The OCR is ready to use after OCR ready message appears in the logs.

  • To see other options, run in command line:
    manga_ocr --help
    

If manga_ocr doesn't work, you might also try replacing it with python -m manga_ocr.

Usage tips

  • OCR supports multi-line text, but the longer the text, the more likely some errors are to occur. If the recognition failed for some part of a longer text, you might try to run it on a smaller portion of the image.
  • The model was trained specifically to handle manga well, but should do a decent job on other types of printed text, such as novels or video games. It probably won't be able to handle handwritten text though.
  • The model always attempts to recognize some text on the image, even if there is none. Because it uses a transformer decoder (and therefore has some understanding of the Japanese language), it might even "dream up" some realistically looking sentences! This shouldn't be a problem for most use cases, but it might get improved in the next version.

Examples

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

image Manga OCR result
素直にあやまるしか
立川で見た〝穴〟の下の巨大な眼は:
実戦剣術も一流です
第30話重苦しい闇の奥で静かに呼吸づきながら
よかったじゃないわよ!何逃げてるのよ!!早くあいつを退治してよ!
ぎゃっ
ピンポーーン
LINK!私達7人の力でガノンの塔の結界をやぶります
ファイアパンチ
少し黙っている
わかるかな〜?
警察にも先生にも町中の人達に!!

Acknowledgments

This project was done with the usage of Manga109-s dataset.