docker-compose.yml

services:
  friendlysplat:
    # Image name (can also be built from Dockerfile below)
    image: friendlysplat:latest
    build:
      context: .                     # Build context: current directory
      dockerfile: Dockerfile         # Use this Dockerfile to build the image
    container_name: friendlysplat_dev

    shm_size: "8gb"                  # Increase shared memory to avoid PyTorch DataLoader crashes

    deploy:
    # GPU reservation for multi-node Docker Swarm / production deployment
    # Note: This is ignored by `docker-compose up` on a single machine
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu, utility, compute]

    # Enable NVIDIA GPU support
    runtime: nvidia
    environment:
      - NVIDIA_VISIBLE_DEVICES=all   # Expose all GPUs to the container
      - DEBIAN_FRONTEND=noninteractive

    # Mount local directories to container for development and data persistence
    volumes:
    # Update volumes if your dataset or results use different directories
      - ./data:/app/FriendlySplat/data          # Local dataset directory
      - ./outputs:/app/FriendlySplat/outputs    # Directory to store results
      - .:/app/FriendlySplat                    # Mount project code for hot-reload

    # Map container ports to host (for viewer / web interface)
    ports:
      - "8080:8080"                             # Access viewer at http://localhost:8080

    # Keep container interactive (useful for `docker-compose exec`)
    tty: false
    stdin_open: false

    # Notes:
    # - Adjust volume paths if your datasets or checkpoints are in different directories.
    # - Expose additional ports if using other services or viewers.
    # - Use `docker-compose up -d` for detached mode in production/development.