Bild
Insightface
State-of-the-art 2D and 3D Face Analysis Project
★ 29,9 Tsd. SterneCustom (check repo)
Anleitung ansehen →rembg ist ein Open-Source-Projekt aus der Kategorie Bild von danielgatis (danielgatis/rembg auf GitHub). Es hat 24.955 Sterne auf GitHub und 2.427 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 20. September 2026 auf GitHub aktualisiert.
Rembg is a tool to remove images background
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/danielgatis/rembg.git
cd rembgIsolate 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 danielgatis/rembg with 2,427 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
Background Remover lets you Remove Background from images and video using AI with a simple command line interface that is free and open source.
Real-ESRGAN — practical blind super-resolution for real-world photos and video: restores and upscales degraded images with models trained on pure synthetic data, BSD-3-Clause
SAM 2 — Meta's Segment Anything Model 2: promptable segmentation for images and video, Apache-2.0
Die anderen Projekte der Kategorie Bild mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls rembg nicht das Richtige ist.
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
Verwandte Projekte der Kategorie Bild im Katalog, die rembg bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
The classic PyTorch implementation of CycleGAN and pix2pix for image-to-image translation
How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
Make images smaller using best-in-class codecs, right in the browser.
SAM 2 — Meta's Segment Anything Model 2: promptable segmentation for images and video, Apache-2.0
Black Forest Labs' official inference repo for the FLUX.1 image generation models
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.