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Manga Image Translator

Manga Image Translator is an open-source Python application that uses OCR and machine translation to translate text in manga and other images, with image repair and typesetting options.

Independent OpenViST project profile, based on linked sources.

Manga Image Translator — OpenViST project profile in Image & Video AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you have image-based text to translate and can work with a local Python application or set up its documented web or API mode.

Who it is for

  • Readers who want to understand text in manga or other images, particularly Japanese-language material.
  • Developers seeking a Python project for image-text detection, translation, repair, and typesetting.

Documented uses

  • Translate text embedded in a manga page or other image.
  • Process a local image or folder in batch mode.
  • Remove original lettering and typeset translated text.
Before you choose

Requirements & limits

The project is publicly available as source code under the GPL-3.0 license. The README marks its older online-service address as no longer working.

  • The README lists Japanese as the main supported language, alongside Simplified and Traditional Chinese, English, and 20 other minor languages.
  • Local installation requires Python 3.12 or later and may require Git and a C++ compiler for dependencies.
  • GPU use requires a PyTorch installation matched to the CUDA version.
  • The project cautions that it is early-stage and that small or irregular text can challenge detection.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up a local Python installation

Install the project dependencies for local use.

Before you start

  • Python 3.12 or later
  • Git and a C++ compiler for building a dependency
  • On Windows, Microsoft C++ Build Tools

Steps

  1. Clone the project repository.

  2. Create and activate a Python virtual environment if desired.

  3. Install a PyTorch build that matches the CUDA version if GPU use is intended.

  4. Install project dependencies with pip from the requirements file.

Expected outcome

Project dependencies are installed; models are downloaded to the ./models directory at runtime.

Guide limitations

  • The README cautions that the very latest Python version may not work with some PyTorch libraries.
  • GPU setup requires a PyTorch version matching the CUDA installation.
  • This setup guide does not cover running a translation.
Source-based practical guide

Translate a local image or image folder

Run the documented local batch workflow on a file or folder.

Before you start

  • A local installation of the project and its dependencies
  • A path to an image file or image folder

Steps

  1. Provide the image file or folder path to the local-mode command.

  2. Run the command using the documented local mode and input option.

  3. Check the adjacent translated-output folder named with the -translated suffix.

Expected outcome

The translated results are placed in a folder based on the input folder path.

Guide limitations

  • The project describes itself as early-stage and notes it has shortcomings.
  • Small images and irregularly sized text can make detection more difficult.
Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
13 October 2026
Original website title
zyddnys/manga-image-translator · Official homepage title · retained in its source language