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Koharu

ML-powered manga translator, written in Rust.

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mayocream%2Fkoharu | Trendshift

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Koharu introduces a local-first workflow for manga translation, utilizing the power of ML to automate the process. It combines the capabilities of object detection, OCR, inpainting, and LLMs to create a seamless translation experience.

Note

Koharu runs its vision models and LLMs locally on your machine to keep your data private and secure.


screenshot

Note

Join our Discord server for support and discussion.

Features

Hardware Acceleration

Koharu supports GPU acceleration with CUDA and ROCm / HIP on Windows and Linux, Metal on Apple silicon, and Vulkan on Windows and Linux. Runtime and hardware requirements vary by backend and operating system.

CUDA

The CUDA backend targets CUDA 13.0 on Windows and Linux. Make sure to install the latest NVIDIA driver. CUDA 13.0 requires R580 or newer.

ROCm / HIP

ROCm / HIP is available for AMD GPUs on Windows and Linux. Make sure to install the official ROCm Core SDK with HIP.

Metal

Metal is used on Apple silicon Macs.

Vulkan

Vulkan is available on Windows and Linux as an alternative to CUDA and ROCm / HIP.

WebGPU

The editor canvas uses WebGPU inside the embedded CEF webview. WebGPU requires a current graphics driver even when inference runs on the CPU.

CPU

Koharu uses the CPU when no accelerator is available or initialization fails. No GPU SDK is required, but inference is slower.

Machine Learning Models

Koharu uses separate models for detection, OCR, inpainting, and translation. Vision and inpainting and translation and generation have separate model settings.

Computer Vision Models

Detection, OCR, and inpainting models are selected separately.

Detection and Layout

The detection model finds text regions, speech bubbles, and segmentation masks.

OCR

OCR reads source text from detected regions.

Inpainting

Inpainting reconstructs the image behind source text before the translation is rendered.

Large Language Models

Translation can use a local language model or a remote API.

General-Purpose Local Models

Uncensored Local Models

Cloud Providers

Hosted LLM providers: Atlas Cloud, OpenAI, Gemini, Claude, Grok, MiniMax, DeepSeek, and OpenRouter.

Machine Translation Providers

Machine-translation providers: DeepL, Google Cloud Translation, and Caiyun.

OpenAI-Compatible Providers

OpenAI-compatible endpoints are also supported.

Installation

Download release builds from the releases page. Installation requirements and first launch vary by operating system.

Builds are available for Windows, macOS, and Linux.

WinGet

Install on Windows with winget:

winget install koharu

Homebrew

Install on macOS with Homebrew:

brew install --cask koharu

Troubleshooting

Startup, runtime, model, and provider errors are covered in Troubleshooting. Set RUST_LOG to debug or trace for verbose logs:

# macOS / Linux
RUST_LOG=debug koharu
# Windows (PowerShell)
$env:RUST_LOG="debug"; koharu.exe

Development

Platform dependencies and validation commands for local builds are listed in Development Setup.

Prerequisites

  • Rust 1.97.1 or later (Rust 2024 edition)
  • Bun 1.3.14 or later
  • LLVM 22.1.8 or later
  • Ninja 1.13.2 or later

Install dependencies

bun install

Development

bun dev

Build

bun run build

The executable is written to target/release.

Sponsorship

If Koharu is useful in your workflow, consider sponsoring the project.

sponsors

Contributors ❤️

Thanks to all the contributors who have helped make Koharu better!

License

Copyright 2025-2026 Mayo Takanashi and Koharu contributors.

Koharu is dual-licensed under the MIT License or the Apache License, Version 2.0, at your option.

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ML-powered manga translator, written in Rust.

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