train_utility/docker-compose.yml

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services:
webui:
build:
context: .
image: yolo-train-webui:latest
ports:
# The training API has no built-in user accounts, so expose it locally only.
- "127.0.0.1:8000:8000"
volumes:
- ./datasets:/workspace/datasets
- ./runs:/workspace/runs
- ./models:/workspace/models
- ./models/.config:/root/.config/Ultralytics
environment:
# Optional: tracking URI for external MLflow server (e.g. http://host.docker.internal:5000 or http://your-mlflow-host:5000)
YOLO_WEBUI_MLFLOW_TRACKING_URI: http://host.docker.internal:5000
# Uncomment the block below on Linux with NVIDIA GPU to pass the graphics card into the container:
# deploy:
# resources:
# reservations:
# devices:
# - driver: nvidia
# count: all
# capabilities: [gpu]
ipc: host
restart: unless-stopped