{"data":{"slug":"humansignal-label-studio","name":"label-studio","tagline":"A multi-type data labeling and annotation tool","github_url":"https://github.com/HumanSignal/label-studio","owner":"HumanSignal","repo":"label-studio","owner_avatar_url":"https://avatars.githubusercontent.com/u/48309720?v=4","primary_language":"TypeScript","stars":28297,"forks":3717,"topics":["annotation","annotation-tool","annotations","boundingbox","computer-vision","data-labeling","dataset","datasets","deep-learning","image-annotation","image-classification","image-labeling","image-labelling-tool","label-studio","labeling","labeling-tool","mlops","semantic-segmentation","text-annotation","yolo"],"archived":false,"github_pushed_at":"2026-09-19T01:48:24+00:00","maintenance_label":"Very active","stars_delta_30d":239,"url":"https://www.graphcanon.com/tools/humansignal-label-studio","markdown_url":"https://www.graphcanon.com/tools/humansignal-label-studio.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/humansignal-label-studio","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=humansignal-label-studio","description":"Label Studio is a multi-type data labeling and annotation tool with standardized output format","homepage_url":"https://labelstud.io","license":"Apache-2.0","open_issues":950,"watchers":187,"ai_summary":"Label Studio is used for creating annotated datasets with standardized output formats for machine learning tasks.","readme_excerpt":"### Install locally with Docker\nOfficial Label Studio docker image is [here](https://hub.docker.com/r/heartexlabs/label-studio) and it can be downloaded with `docker pull`. \nRun Label Studio in a Docker container and access it at `http://localhost:8080`.\n\n\n```bash\ndocker pull heartexlabs/label-studio:latest\ndocker run -it -p 8080:8080 -v $(pwd)/mydata:/label-studio/data heartexlabs/label-studio:latest\n```\nYou can find all the generated assets, including SQLite3 database storage `label_studio.sqlite3` and uploaded files, in the `./mydata` directory.\n\n#### Override default Docker install\nYou can override the default launch command by appending the new arguments:\n```bash\ndocker run -it -p 8080:8080 -v $(pwd)/mydata:/label-studio/data heartexlabs/label-studio:latest label-studio --log-level DEBUG\n```\n\n#### Build a local image with Docker\nIf you want to build a local image, run:\n```bash\ndocker build -t heartexlabs/label-studio:latest .\n```\n\n---\n\n### Run with Docker Compose\nDocker Compose script provides production-ready stack consisting of the following components:\n\n- Label Studio\n- [Nginx](https://www.nginx.com/) - proxy web server used to load various static data, including uploaded audio, images, etc.\n- [PostgreSQL](https://www.postgresql.org/) - production-ready database that replaces less performant SQLite3.\n\nTo start using the app from `http://localhost` run this command:\n```bash\ndocker-compose up\n```\n\n---\n\n### Run with Docker Compose + MinIO\nYou can also run it with an additional MinIO server for local S3 storage. This is particularly useful when you want to \ntest the behavior with S3 storage on your local system. To start Label Studio in this way, you need to run the following command:\n````bash\n\n---\n\n# Add sudo on Linux if you are not a member of the docker group\ndocker compose -f docker-compose.yml -f docker-compose.minio.yml up -d\n````\nIf you do not have a static IP address, you must create an entry in your hosts file so that both Label Studio and your \nbrowser can access the MinIO server. For more detailed instructions, please refer to [our guide on storing data](docs/source/guide/storedata.md).\n\n---\n\n### Install locally with Anaconda\n\n```bash\nconda create --name label-studio\nconda activate label-studio\nconda install psycopg2\npip install label-studio\n```\n\n---\n\n### Install for local development\n\nYou can run the latest Label Studio version locally without installing the package from pypi. \n\n```bash\n\n---\n\n# Install all package dependencies\npip install poetry\npoetry install\n\n---\n\n# If you're running Win64 with Python 3.8, install the packages downloaded from Gohlke:\npip install lxml‑4.5.0‑cp38‑cp38‑win_amd64.whl\n\n---\n\n# Install label studio\npip install label-studio\n```\n\n---\n\n# postgres (assumes default postgres user,db,pass. Will not work in Docker\n\n---\n\n## License\n\nThis software is licensed under the [Apache 2.0 LICENSE](/LICENSE) © [Heartex](https://www.heartex.com/). 2020-2025\n\n<img src=\"https://user-images.githubusercontent.com/12534576/192582529-cf628f58-abc5-479b-a0d4-8a3542a4b35e.png\" title=\"Hey everyone!\" width=\"180\" />","github_created_at":"2019-06-19T02:00:44+00:00","created_at":"2026-07-15T11:20:36.236367+00:00","updated_at":"2026-09-20T05:21:27.92567+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"}],"tags":[{"slug":"annotation","name":"annotation"},{"slug":"computer-vision","name":"computer-vision"},{"slug":"image-classification","name":"image-classification"},{"slug":"labeling-tool","name":"labeling-tool"},{"slug":"semantic-segmentation","name":"semantic-segmentation"},{"slug":"text-annotation","name":"text-annotation"}],"trust":{"provenance":{"is_fork":false,"github_id":192640529,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T05:21:25.398Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":1,"days_since_push":1,"last_release_at":"2026-09-18T00:12:05Z","stars_delta_30d":239,"open_issues_delta_30d":27},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-15T11:20:38.967Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T05:21:26.458Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-20T05:21:26.458Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-09-20T05:21:26.458Z"},"languages":{"value":["typescript","python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-20T05:21:26.458Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-20T05:21:26.458Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-20T05:21:26.458Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["For projects needing multi-type annotations including images, texts, and more","When a Dockerized setup simplifies deployment","To maintain production readiness with PostgreSQL support via Docker Compose"],"when_not_to_use":["If your project strictly requires on-premise database solutions without Docker support","For tasks where real-time collaboration annotations are non-negotiable features","When the need for minimal setup overrides advanced configuration options"],"source":"enrich:decision_facts","observed_at":"2026-07-17T12:47:20.380Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Label Studio is an annotation tool supporting multiple data types with standardized output for machine learning projects."}]}}