Scanned Light Novel / Manga -> EPUB & Translation Tooling

Turns a folder of scanned Japanese pages into either a proper .epub (light novels) or transcribed/translated text (manga), using a multimodal LLM to do the OCR instead of a traditional column-segmentation pipeline. Light novel and manga pages get separate tooling, since their layouts need genuinely different logic — dense running prose vs. scattered speech bubbles that benefit from translation, a glossary, and cross-page context.

Pipeline

scanned page images
        │
        ▼
   ocr/ module          → transcribes (or translates) each page into
                            pages_txt/<name>.txt
        │
        ▼
  (manual step,          → sort the .txt files (and any illustration
   light novel only)       images) into chapters/chNN_name/ folders
        │
        ▼
epub_builder/ module     → assembles chapters/ into a finished .epub
                            (light novel only — manga output is meant for
                            your own typesetting workflow instead)

1. ocr/ — batch-OCRs scanned pages into per-page .txt files, or translates them directly. novel_ocr.py (light novel) and manga_ocr_llm.py (manga) are the recommended entry points, both via any OpenAI-compatible API; google_vision_ocr.py (Google Cloud Vision) and local_mangaocr_ocr.py (fully offline manga-ocr) are pure-OCR alternatives with no translation.
2. Manual sorting (light novel only) — split the resulting pages into chapter folders (ch00_frontmatter/, ch01_chapter00/, ...), optionally dropping in a cover.jpg and illustration images alongside the .txt files. This step is manual because automatically detecting chapter boundaries from OCR'd headers turned out to be unreliable — folder structure is simple and unambiguous instead.
3. epub_builder/ — assembles the sorted chapters/ folder into a valid .epub: furigana notation becomes <ruby> markup, images are placed inline, a font from font/ gets embedded, and metadata comes from the root config.json.

Both modules read their settings from a single config.json at the repo root (copy config.example.json to get started) — see each module's own README for the exact fields.

See each module's own README for setup and usage details.

Quick start

# 0. One-time setup: copy the shared config and fill it in
cp config.example.json config.json
# fill in ocr.api_key / ocr.base_url / ocr.model, epub.title / epub.author / ...

# 1a. OCR a light novel
cd ocr
pip install openai pillow natsort tqdm
python novel_ocr.py --input /path/to/scans --output ./out

# 1b. ...or OCR/translate manga instead
python manga_ocr_llm.py --input /path/to/scans --output ./out
python manga_ocr_llm.py --input /path/to/scans --output ./out --translate --target-lang Russian

# 2. (light novel) Sort ./out/pages_txt/*.txt by hand into epub_builder/chapters/chNN_name/

# 3. (light novel) Build the epub
cd ../epub_builder
pip install natsort
python build_epub.py

⚠️ A note on copyright

This repository contains only the tooling. It is not meant to, and should not, be used to host or distribute:

• scanned page images,
• OCR'd or translated text extracted from a copyrighted book,
• or a resulting .epub file,

for any book you don't hold the rights to. The .gitignore in this repo already excludes chapters/, pages_txt/, out/, and *.epub for this reason — keep it that way if you fork or extend this project. This tool is intended for personal-use digitization of books you own, not redistribution.

Requirements

See requirements.txt for the full list. Not every dependency is needed at once — install only what the OCR backend and features you're using require (see each module's README).

Status

This is a personal toolkit, still evolving. Contributions/forks welcome, but expect rough edges — issues and PRs are handled best-effort.