Remote Machine Learning

To alleviate performance issues on low-memory systems like the Raspberry Pi, you may also host Immich's machine-learning container on a more powerful system (e.g. your laptop or desktop computer):

• Set the URL in Machine Learning Settings on the Admin Settings page to point to the designated ML system, e.g. http://workstation:3003.
• Copy the following docker-compose.yml to your ML system.
  • If using hardware acceleration, the hwaccel.ml.yml file also needs to be added
• Start the container by running docker compose up -d.

info

Smart Search and Face Detection will use this feature, but Facial Recognition is handled in the server.

danger

When using remote machine learning, the thumbnails are sent to the remote machine learning container. Use this option carefully when running this on a public computer or a paid processing cloud.

name: immich_remote_ml

services:
  immich-machine-learning:
    container_name: immich_machine_learning
    # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
    # Example tag: ${IMMICH_VERSION:-release}-cuda
    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
    # extends:
    #   file: hwaccel.ml.yml
    #   service: # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
    volumes:
      - model-cache:/cache
    restart: always
    ports:
      - 3003:3003

volumes:
  model-cache:

Please note that version mismatches between both hosts may cause instabilities and bugs, so make sure to always perform updates together.

caution

As an internal service, the machine learning container has no security measures whatsoever. Please be mindful of where it's deployed and who can access it.