koharu-cnmirror¶

koharu-cnmirror

项目信息
仓库	https://github.com/Maicarons/koharu-cnmirror
在线体验	https://koharu.rs
主要语言	Rust
Stars	0
类型	Fork（镜像 / 二次开发）
许可证	GPL-3.0
最近更新	2026-08-05

ℹ️ 本仓库为 Fork，基于上游项目进行镜像或二次开发。

Koharu

ML-powered manga translator, written in Rust.

Getting Started · Docs · Bug reports · Discord

日本語 | 简体中文

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] Support and discussion are available on the Discord server.

Features¶

Automatic detection of text regions, speech bubbles, and cleanup masks
OCR for manga dialogue, captions, and other page text
Inpainting to remove source lettering from the page
Translation with local or remote LLM backends
Advanced text rendering with vertical CJK and RTL support
Layered PSD export with editable text

GPU Acceleration¶

Koharu supports CUDA, ROCm / HIP, Metal, and Vulkan. CPU fallback is always available when the accelerated path is unavailable or not worth the setup cost on your system.

CUDA¶

Koharu supports NVIDIA GPUs on Windows and Linux through CUDA. Ensure you have the latest NVIDIA driver installed.

HIP / ROCm¶

Koharu supports AMD GPUs on Windows through ROCm and HIP. Ensure you have the latest AMD driver installed.

Metal¶

Koharu supports Metal on Apple Silicon Macs.

Vulkan¶

Koharu also supports Vulkan on Windows and Linux as an alternative to CUDA and HIP.

CPU Fallback¶

You can always force Koharu to use CPU for inference:

## macOS / Linux
koharu --cpu
## Windows
koharu.exe --cpu

Machine Learning Models¶

Koharu uses a staged stack of vision and language models instead of trying to solve the entire page with a single network.

Computer Vision Models¶

Koharu uses multiple pretrained models, each tuned for a specific part of the page pipeline.

Detection and Layout¶

Koharu uses object detection to find text regions, speech bubbles, and segmentation masks.

Koharu Layout RF-DETR Seg 2XL

OCR¶

These models recognize source text after detection.

Inpainting¶

These models remove source lettering before translated text is rendered back onto the page.

Large Language Models¶

Koharu has a flexible LLM backend that can run locally or connect to a remote API.

General-Purpose Local Models¶

LFM 2.5: lfm2.5-1.2b-instruct
Ministral 3: ministral-3-8b-instruct
Gemma 4 instruct (QAT): gemma4-e2b-it, gemma4-e4b-it, gemma4-12b-it, gemma4-26b-a4b-it, gemma4-31b-it
Qwen 3.5: qwen3.5-0.8b, qwen3.5-2b, qwen3.5-4b, qwen3.5-9b, qwen3.5-27b, qwen3.5-35b-a3b
Qwen 3.6: qwen3.6-27b, qwen3.6-35b-a3b

Uncensored Local Models¶

Gemma 4 uncensored: gemma4-e2b-uncensored, gemma4-e4b-uncensored, gemma4-12b-uncensored, gemma4-26b-a4b-uncensored, gemma4-31b-uncensored
Qwen 3.5 uncensored: qwen3.5-2b-uncensored, qwen3.5-4b-uncensored, qwen3.5-9b-uncensored
Qwen 3.6 uncensored: qwen3.6-27b-uncensored, qwen3.6-35b-a3b-uncensored

Cloud Providers¶

Koharu supports hosted APIs from Atlas Cloud, OpenAI, Gemini, Claude, DeepSeek, and OpenRouter.

Machine Translation Providers¶

For pure machine-translation use cases, Koharu also supports DeepL, Google Cloud Translation, and Caiyun.

OpenAI-Compatible Providers¶

Koharu supports any provider that implements the OpenAI-compatible API.

Installation¶

You can download the latest release of Koharu from the releases page.

We provide prebuilt binaries for Windows, macOS, and Linux.

WinGet¶

On Windows, you can install Koharu with winget:

winget install koharu

Homebrew¶

On macOS, you can install Koharu with Homebrew:

brew install --cask koharu

Troubleshooting¶

Koharu provides a diagnostic mode that outputs detailed logs and system information to help identify issues with installation, GPU acceleration, model loading, and more. To enable it, run:

## macOS / Linux
koharu --debug
## Windows
koharu.exe --debug

You can also set the RUST_LOG environment variable to debug or trace to see more verbose logs:

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

Development¶

To build Koharu from source, follow the steps below.

Prerequisites¶

Rust 1.95 or later (Rust 2024 edition)
Bun 1.0 or later
LLVM 15 or later
ninja 1.11 or later

Install dependencies¶

bun install

Development¶

bun dev

Build¶

bun run build

The built binaries are written to target/release.

Sponsorship¶

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

Contributors ❤️¶

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

License¶

Koharu is licensed under the GNU General Public License v3.0.