Изображения
Insightface
State-of-the-art 2D and 3D Face Analysis Project
★ 29,9 тыс. звёздCustom (check repo)
Смотреть руководство →Automatic — проект с открытым исходным кодом из категории «Изображения» от vladmandic (vladmandic/sdnext на GitHub). У него 7 353 звезды на GitHub и 584 форка, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 3 октября 2026.
SD.Next: All-in-one WebUI for AI generative image and video creation, captioning and processing
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.
The defining trait of this whole category: professional results without monthly fees.
Your images stay on your machine — important for client work and privacy.
Bring any compatible open checkpoint; you are never locked to one vendor's style.
Single-job tools (upscale, de-background, restore) that do one thing excellently.
Self-hosted managers with AI tagging, face recognition, and deduplication.
Extensions, scripts, and community presets extend the popular studios far beyond stock.
Download the source and move into the project folder.
git clone https://github.com/vladmandic/sdnext.git
cd sdnextIsolate dependencies so nothing clashes with your other projects.
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activateInstall the requirements, then follow the README's launch command (it varies per project).
pip install -r requirements.txtFor generation: a polished studio interface. For enhancement: a dedicated upscaler. For libraries: a photo manager. The guides above narrow it down.
Generation benefits hugely from one; upscalers and photo managers are far lighter.
It is an open-source project at vladmandic/sdnext with 584 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Mostly yes under MIT/Apache/GPL — but verify each license, especially for client deliverables.
With the right open checkpoints, absolutely — the interface matters less than the model you load.
Community hubs like CivitAI and Hugging Face host thousands of open checkpoints.
State-of-the-art 2D and 3D Face Analysis Project
Stable Diffusion web UI
Focus on prompting and generating
C# generative AI SDK — text, image, video and audio via ONNX
MMagic — OpenMMLab's generative-AI toolbox: diffusion, text-to-image, restoration and a model zoo.
OmniGen: one unified model for text-to-image, editing, subject-driven and identity-preserving generation
Другие проекты из категории «Изображения» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если Automatic вам не подходит.
Stable Diffusion web UI
The node-graph powerhouse for precise, professional AI image and video generation.
High performance self-hosted photo and video management solution
PhotoCraft — a clean-room Photoshop reimplementation in pure Rust: layers, masks, adjustment layers, type, vectors, brushes and real PSD files, offline, MIT / Apache-2.0
Focus on prompting and generating
Соседние проекты из категории «Изображения» в каталоге, ближайшие по числу звёзд к Automatic — продолжайте изучать полку по обе стороны от него.
MMagic — OpenMMLab's generative-AI toolbox: diffusion, text-to-image, restoration and a model zoo.
An APP that integrates mainstream large language models and image generation models, built with Flutter, with fully open-source code.
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++
Photo gallery for self-hosted personal servers
Stable Diffusion web UI
Read-only mirror of https://gitlab.gnome.org/GNOME/gimp
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.