𝗗𝗲𝗽𝗹𝗼𝘆 𝗟𝗮𝗯𝗲𝗹 𝗦𝘁𝘂𝗱𝗶𝗼 𝗼𝗻 𝗨𝗯𝘂𝗻𝘁𝘂 𝟮𝟰.𝟬𝟰
Label Studio helps you label text, images, audio, and video. You can use it for machine learning workflows and team collaboration.
This guide shows you how to deploy Label Studio using Docker Compose and Traefik. Traefik provides automatic HTTPS for your domain.
Follow these steps to set it up.
- Prepare your directory
Run these commands to create a folder for your project:
$ mkdir ~/labelstudio $ cd ~/labelstudio
- Set your environment variables
Create a .env file:
$ nano .env
Add your domain and email:
DOMAIN=labelstudio.example.com LETSENCRYPT_EMAIL=admin@example.com
- Create the Docker Compose file
Create a file named docker-compose.yaml:
$ nano docker-compose.yaml
Paste this configuration:
services: traefik: image: traefik:v3.6 container_name: traefik command: - "--providers.docker=true" - "--providers.docker.exposedbydefault=false" - "--entrypoints.web.address=:80" - "--entrypoints.websecure.address=:443" - "--entrypoints.web.http.redirections.entrypoint.to=websecure" - "--entrypoints.web.http.redirections.entrypoint.scheme=https" - "--certificatesresolvers.letsencrypt.acme.httpchallenge=true" - "--certificatesresolvers.letsencrypt.acme.httpchallenge.entrypoint=web" - "--certificatesresolvers.letsencrypt.acme.email=${LETSENCRYPT_EMAIL}" - "--certificatesresolvers.letsencrypt.acme.storage=/letsencrypt/acme.json" ports: - "80:80" - "443:443" volumes: - "./letsencrypt:/letsencrypt" - "/var/run/docker.sock:/var/run/docker.sock:ro" restart: unless-stopped
labelstudio:
image: heartexlabs/label-studio:1.23.0
container_name: labelstudio
expose:
- "8080"
environment:
- DJANGO_ALLOWED_HOSTS=${DOMAIN}
- CSRF_TRUSTED_ORIGINS=https://${DOMAIN}
- USE_X_FORWARDED_HOST=true
- SECURE_PROXY_SSL_HEADER=HTTP_X_FORWARDED_PROTO,https
volumes:
- ./data:/label-studio/data
labels:
- "traefik.enable=true"
- "traefik.http.routers.labelstudio.rule=Host(${DOMAIN})"
- "traefik.http.routers.labelstudio.entrypoints=websecure"
- "traefik.http.routers.labelstudio.tls.certresolver=letsencrypt"
- "traefik.http.services.labelstudio.loadbalancer.server.port=8080"
restart: unless-stopped
- Configurar permisos e iniciar
Crea la carpeta de datos:
$ mkdir data $ sudo chown :0 data
Ejecuta los servicios:
$ docker compose up -d
- Verificar la configuración
Comprueba si tus contenedores se están ejecutando:
$ docker compose ps
Accede a tu herramienta en https://labelstudio.example.com. Regístrate para crear tu cuenta de administrador.
Próximos pasos para tu proyecto:
- Conecta backends de ML como PyTorch para el aprendizaje activo.
- Invita a miembros del equipo con roles específicos.
- Exporta tus datos en formatos como JSON, CSV o YOLO.
Fuente: https://dev.to/vultr/deploying-label-studio-open-source-data-labeling-platform-on-ubuntu-2404-5bd0
Comunidad de aprendizaje opcional: https://t.me/GyaanSetuAi