Agents IA
Adala
Autonomous data-labeling agents: let AI do the annotation grunt work.
★ 1,6 k étoilesApache-2.0
Voir le guide →// agents · HumanSignal/label-studio
label-studio
label-studio est un projet de agents IA open source, créé par HumanSignal (HumanSignal/label-studio sur GitHub). Il compte 28 418 étoiles sur GitHub et 3 734 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.
The open-source studio for labeling data of every type.
★ 28,4 k étoiles⑂ 3,7 k forksApache-2.0mis à jour oct. 2026
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet
Détails du projet
- Étoiles GitHub
- 28 418
- Forks
- 3 734
- Licence
- Apache-2.0
- Dernière mise à jour sur GitHub
- 8 octobre 2026
- Catégorie
- Agents IA
- Type de fiche
- Guide d'installation complet
- Site officiel
- Official site
// fonctionnement
Comment ça marche
- Know your goal
Be clear about the problem you are solving before installing.
- Get the code
Clone the repository and skim the docs for hardware or key requirements.
- Configure it
Install dependencies, then add API keys, endpoints, or local-model settings.
- Take it for a spin
Launch the example flow and verify the output matches expectations.
// fonctionnalités
Pourquoi on l'adore
Multi-type labeling
Text, image, audio, video, and time-series annotation.
Standardized output
Consistent export formats for training pipelines.
Computer vision ready
Bounding boxes and segmentation support.
Team workflows
Built for collaborative labeling teams.
Self-hostable
Run it on your own infrastructure.
Apache-2.0
Permissive licensing.
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// lancez-le
Lancez-le vous-même
- Step 1 — Clone the repo
Download the source and move into the project folder.
git clone https://github.com/HumanSignal/label-studio.git cd label-studio - Step 2 — Install frontend deps
Install the TypeScript dependencies (see README for the full stack).
npm install - Step 3 — Launch it
Start the app per the install docs — Docker is the common path.
# see README for backend + Docker setup npm run start
// cas d'usage
Ce que vous pouvez créer
- Label training data for a custom model.
- Annotate images with bounding boxes for detection.
- Build evaluation datasets for agent benchmarks.
- Run a collaborative data-labeling team.
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// faq
Questions fréquentes
Who maintains Label Studio?
It is maintained by HumanSignal at HumanSignal/label-studio, with 3,734 forks. Check the releases for the current version.
Is Label Studio free to use?
The community edition is free under Apache-2.0; an enterprise offering also exists.
Do I need a paid API to use it?
No — the self-hosted community edition is free to run on your own infrastructure.
How does it compare to other annotation tools?
Compare on supported data types, workflow features, and export formats for your pipeline.
How do I get started?
Follow the install docs — the Docker route is the most common — then create your first labeling project.
// continuez l'exploration
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