Pear

<div align="center"> <pre> █▀▄▀█ ▄▀█ █▄ █ █▀▀ ▄▀█ ▀█▀ █▄█ █▀█ █▀▀ █▀ █▀▀ ▀█▀ ▀█▀ █▀▀ █▀█ █ ▀ █ █▀█ █ ▀█ █▄█ █▀█ █ █ █▀▀ ██▄ ▄█ ██▄ █ █ ██▄ █▀▄ lettering for scanlation, without Photoshop </pre> [](#install) [](#install) [](#install) [](https://tauri.app) [](https://svelte.dev) [](https://typesetter.komiq.cc) [](LICENSE.md) [](https://discord.gg/vhuYWbZNX5) [](https://ko-fi.com/komiq) </div> A desktop app that puts translated lettering into speech balloons. Light on memory, works over hundreds of pages, no Photoshop needed. **[Download](https://typesetter.komiq.cc)** · **[User guide (HOWTO)](HOWTO.md)** > Public beta. In daily use, but expect rough edges.  ## Recommended use Translators work in **translate** mode: translate each bubble and tag it (tagging shortcuts are still in progress). Typesetters then set a font per tag, place the text boxes, and tune them. Auto placement can be turned off. ## Features - Text box detection and auto placement - **Tags**, so you stop scrolling the font list for every line. Tags are saved per project, so the first tagging pass is the slow one - Auto fit to balloon. It is flaky, so it can be turned off in Settings, or per bubble with a shortcut - Autosave - Bulk restyle by tag or by selection, for when you change your mind - Effects: transform (warp), stacked strokes and shadows, text clipping (untested), circular curve, arc, a controllable curve for wavy text, motion blur and normal blur, font roughening, text mask clipping - Fills: solid, pattern and gradient (a better colour picker is in progress) - The normal layout controls you expect - Export to PNG, JPG, WebP or JSON, per page or per chapter - Auto updates - Low resource use, with heavy offloading to disk > **Do not use PSD export yet.** It is unfinished, and low priority, because it > is genuinely hard. ## Install Grab the installer from **<https://typesetter.komiq.cc>**. - macOS (Apple Silicon): open the `.dmg`, drag the app to Applications. The bundle is not notarised yet, so first launch needs right-click > **Open**. - Windows: run the setup `.exe`. - Linux (x86_64 or ARM64): choose the download matching your architecture. Install the `.deb`, or mark the `.AppImage` executable and run it. Both use your distro's GTK 3 and WebKitGTK 4.1 (the `.deb` pulls them in; the AppImage tells you the install command if they are missing: `libwebkit2gtk-4.1-0` on Debian and Ubuntu, `webkit2gtk4.1` on Fedora, `webkit2gtk-4.1` on Arch). - The Linux builds need glibc 2.39 or newer: Ubuntu 24.04, Mint 22, Fedora 39, Debian 13, Arch, or anything newer. On an older distro it refuses to start with `version 'GLIBC_2.39' not found`, and there is no build that does: the floor comes from the prebuilt ONNX Runtime, which is compiled against glibc 2.38 with or without a GPU feature. Reaching Ubuntu 22.04 or Debian 12 would take a Flatpak, which carries its own runtime. - The x86_64 build uses WebGPU over Vulkan when a usable driver is there and the CPU when it is not. The ARM64 build is CPU-only because its prebuilt ONNX Runtime has no WebGPU or CUDA provider. `ldd --version` prints your glibc version. Updates arrive in-app and are signature-verified. Each Linux build only updates to its own kind. ## Build from source Requires [Node](https://nodejs.org) 20+ and a [Rust toolchain](https://rustup.rs) (see the [Tauri v2 prerequisites](https://v2.tauri.app/start/prerequisites/)). ```sh git clone https://github.com/komiq-cc/manga-typesetter.git cd manga-typesetter npm install npm run tauri dev # run it npm run tauri build # bundle in src-tauri/target/release/bundle npm test # vitest ``` Detection models download on first use and are cached under your home directory; nothing ships in the bundle. Chinese and Korean recognizers can be selected independently under **Settings → System → Models**. PP-OCRv6 Medium is the quality-first Chinese default. Korean defaults to the Korean-specific PP-OCRv5 model; PP-OCRv6 does not support Korean. Alternate smaller or legacy models remain available. ### GPU Detection and OCR run on the GPU where one is usable, falling back to CPU per model, and the settings dialog names the device in use: - macOS: CoreML. - Windows: CUDA on NVIDIA machines with CUDA 13 and cuDNN 9 installed, otherwise DirectML (any GPU, nothing to install). - Linux: WebGPU over Vulkan (any GPU, nothing to install), CPU when there is no usable driver. An NVIDIA-only CUDA build exists for people with CUDA 13 + cuDNN 9, and is faster than WebGPU on those machines: ```sh npm run tauri build -- --features gpu-cuda --config src-tauri/tauri.linux-cuda.conf.json ``` Plain `cargo build` on Linux has no GPU provider; pass `--features gpu-webgpu` or `gpu-cuda`, not both. The WebGPU feature only links on a host with glibc 2.38+ and GCC 13's libstdc++ (Ubuntu 24.04 or newer). Set `MT_DEVICE=cpu` (or `cuda`, `directml`, `webgpu`, `coreml`) before launching to pin a device when a driver misbehaves. The first device probe runs in a helper copy of the app (`app --probe-device`), so a driver that aborts while starting up only kills that helper; detection then stays on CPU for the rest of the run and the log says why. On Linux the app switches WebKit's DMA-BUF renderer off when the NVIDIA proprietary driver is loaded (a blank window otherwise). Set `WEBKIT_DISABLE_DMABUF_RENDERER=0` before launching to force it back on; the app leaves the variable alone when it is already set. The AppImage bundles no GTK or WebKit on purpose: it uses the host's, exactly like the `.deb`, so WebKit's UI process and its helper processes are always the same version on every distro. `scripts/build-appimage.sh` explains why. ## Built with [Svelte 5](https://svelte.dev) · [Vite](https://vite.dev) · [Tauri 2](https://tauri.app) · [ag-psd](https://github.com/Agamnentzar/ag-psd) · [hypher](https://github.com/bramstein/hypher) · [ONNX Runtime](https://onnxruntime.ai) via [`ort`](https://ort.pyke.io) Detection models from [deepghs/manga109_yolo](https://huggingface.co/deepghs/manga109_yolo) and [kha-white/manga-ocr](https://github.com/kha-white/manga-ocr), plus PP-OCRv4/v5 Korean and PP-OCRv5/v6 Chinese recognizers published by [RapidOCR](https://github.com/RapidAI/RapidOCR). No model weights ship in the app - they download on first use from a byte-for-byte RapidOCR mirror, and each carries its publisher's own terms rather than this project's. ## License [MIT](LICENSE.md) © 2026 k-omiq Third-party licenses and notices are in [THIRD-PARTY.md](THIRD-PARTY.md).