Image
stable-diffusion.cpp
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++
★ 7,5 k étoilesMIT
Voir le guide →kohya_ss est un projet de image open source, créé par bmaltais (bmaltais/kohya_ss sur GitHub). Il compte 12 615 étoiles sur GitHub et 1 606 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 1er août 2026.
kohya_ss — open-source image project on GitHub.
Generation studio, upscaler, background remover, or photo library — match the tool to the task.
Desktop apps, Docker images, and portable builds cover most platforms; pick the simplest for your OS.
Generation tools need checkpoint files; utilities like upscalers usually bundle everything.
Generate, enhance, or import — then export, share, or keep building your library.
Single-job tools (upscale, de-background, restore) that do one thing excellently.
Bring any compatible open checkpoint; you are never locked to one vendor's style.
Your images stay on your machine — important for client work and privacy.
The defining trait of this whole category: professional results without monthly fees.
Edits stay reversible; originals are never touched.
Run whole folders through upscalers and converters unattended.
Download the source and move into the project folder.
git clone https://github.com/bmaltais/kohya_ss.git
cd kohya_ssEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at bmaltais/kohya_ss with 1,606 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Apache 2.0 licensed — commercial use allowed with attribution.
Mostly yes under MIT/Apache/GPL — but verify each license, especially for client deliverables.
Generation benefits hugely from one; upscalers and photo managers are far lighter.
For generation: a polished studio interface. For enhancement: a dedicated upscaler. For libraries: a photo manager.
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++
A lite C++ AI toolkit: 100+ models with MNN, ORT and TRT, including Det, Seg, Stable-Diffusion, Face-Fusion.
A general fine-tuning kit geared toward image/video/audio diffusion models.
Kandinsky 2.2 — multilingual text-to-image latent diffusion with ControlNet, inpainting and image fusion
CUT — contrastive unpaired image-to-image translation in PyTorch, faster and lighter than CycleGAN (ECCV 2020)
Open-source AI-as-a-service platform — LLMs, image and audio via one REST API
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.