Immich Machine Learning

Description / name	Input element
Container Registry
Container Configuration Root Path
Timezone
User ID
Group ID
Immich Machine Learning Host Port
Immich Machine Learning /cache Path
Immich Machine Learning /config Path

Machine learning service for Immich — handles facial recognition, image classification, and semantic search using ONNX models.


Port	`3003`
Registry	`ghcr.io/daemonless/immich-ml`
Daemonless	daemonless/immich-ml
Source	immich-app/immich
Website	immich.app

Version Tags

Tag	Description	Best For
`latest`	Upstream Binary. Built from official release.	Most users — recommended.

Before deploying, ensure your host environment is ready. See the Quick Start Guide for host setup instructions, including the security model for host vs. container privileges.

Deployment

Podman AppJail

Compose CLI Ansible

services:
  immich-ml:
    image: "ghcr.io/daemonless/immich-ml:latest"
    container_name: immich-ml
    environment:
      - MACHINE_LEARNING_HOST=0.0.0.0  # Host to bind to (0.0.0.0)
      - MACHINE_LEARNING_PORT=3003  # Port to bind to (3003)
      - MACHINE_LEARNING_CACHE_FOLDER=/cache  # Path to cache folder (/cache)
      - PUID=1000  # User ID for the application process
      - PGID=1000  # Group ID for the application process
      - TZ=UTC  # Timezone for the container
      - MACHINE_LEARNING_WORKERS=1  # Number of ML worker processes. Keep at 1 on weak / CPU-only hosts.
      - MACHINE_LEARNING_WORKER_TIMEOUT=300  # Gunicorn worker timeout in seconds. Raise on slow CPUs so model loading doesn't time out and cycle the worker.
      - SKIP_CHOWN=true  # Skip the one-time recursive chown of /cache and /config once ownership is recorded in /config/.chown_done (default true). Set false to force a chown on every start.
    volumes:
      - "/path/to/containers/immich-ml/cache:/cache"
      - "/path/to/containers/immich-ml:/config"
    ports:
      - "3003:3003"
    # always (not unless-stopped) so FreeBSD's podman rc.d auto-starts it at boot
    restart: always

podman run -d --name immich-ml \
  -p 3003:3003 \
  -e MACHINE_LEARNING_HOST=0.0.0.0 \
  -e MACHINE_LEARNING_PORT=3003 \
  -e MACHINE_LEARNING_CACHE_FOLDER=/cache \
  -e PUID=1000 \
  -e PGID=1000 \
  -e TZ=UTC \
  -e MACHINE_LEARNING_WORKERS=1 \
  -e MACHINE_LEARNING_WORKER_TIMEOUT=300 \
  -e SKIP_CHOWN=true \
  -v /path/to/containers/immich-ml/cache:/cache \
  -v /path/to/containers/immich-ml:/config \
  ghcr.io/daemonless/immich-ml:latest

- name: Deploy immich-ml
  containers.podman.podman_container:
    name: immich-ml
    image: "ghcr.io/daemonless/immich-ml:latest"
    state: started
    restart_policy: always
    env:
      MACHINE_LEARNING_HOST: "0.0.0.0"
      MACHINE_LEARNING_PORT: "3003"
      MACHINE_LEARNING_CACHE_FOLDER: "/cache"
      PUID: "1000"
      PGID: "1000"
      TZ: "UTC"
      MACHINE_LEARNING_WORKERS: "1"
      MACHINE_LEARNING_WORKER_TIMEOUT: "300"
      SKIP_CHOWN: "true"
    ports:
      - "3003:3003"
    volumes:
      - "/path/to/containers/immich-ml/cache:/cache"
      - "/path/to/containers/immich-ml:/config"

Director CLI

# .env

DIRECTOR_PROJECT=immich-ml
MACHINE_LEARNING_HOST=0.0.0.0
MACHINE_LEARNING_PORT=3003
MACHINE_LEARNING_CACHE_FOLDER=/cache
PUID=1000
PGID=1000
TZ=UTC
MACHINE_LEARNING_WORKERS=1
MACHINE_LEARNING_WORKER_TIMEOUT=300
SKIP_CHOWN=true

# appjail-director.yml

options:
  - virtualnet: ':<random> default'
  - nat:
services:
  immich-ml:
    name: immich_ml
    options:
      - container: 'boot args:--pull'
      - expose: '3003:3003 proto:tcp'
    oci:
      user: root
      environment:
        - MACHINE_LEARNING_HOST: !ENV '${MACHINE_LEARNING_HOST}'
        - MACHINE_LEARNING_PORT: !ENV '${MACHINE_LEARNING_PORT}'
        - MACHINE_LEARNING_CACHE_FOLDER: !ENV '${MACHINE_LEARNING_CACHE_FOLDER}'
        - PUID: !ENV '${PUID}'
        - PGID: !ENV '${PGID}'
        - TZ: !ENV '${TZ}'
        - MACHINE_LEARNING_WORKERS: !ENV '${MACHINE_LEARNING_WORKERS}'
        - MACHINE_LEARNING_WORKER_TIMEOUT: !ENV '${MACHINE_LEARNING_WORKER_TIMEOUT}'
        - SKIP_CHOWN: !ENV '${SKIP_CHOWN}'
    volumes:
      - IMMICH_ML_CACHE_PATH: /cache
      - IMMICH_ML_CONFIG_PATH: /config
volumes:
  IMMICH_ML_CACHE_PATH:
    device: '/path/to/containers/immich-ml/cache'
  IMMICH_ML_CONFIG_PATH:
    device: '/path/to/containers/immich-ml'

# Makejail

ARG tag=latest

OPTION overwrite=force
OPTION from=ghcr.io/daemonless/immich-ml:${tag}

appjail oci run -Pd \
  -o overwrite=force \
  -o container="args:--pull" \
  -o virtualnet=":<random> default" \
  -o nat \
  -o expose="3003:3003 proto:tcp" \
  -e MACHINE_LEARNING_HOST=0.0.0.0 \
  -e MACHINE_LEARNING_PORT=3003 \
  -e MACHINE_LEARNING_CACHE_FOLDER=/cache \
  -e PUID=1000 \
  -e PGID=1000 \
  -e TZ=UTC \
  -e MACHINE_LEARNING_WORKERS=1 \
  -e MACHINE_LEARNING_WORKER_TIMEOUT=300 \
  -e SKIP_CHOWN=true \
  -o fstab="/path/to/containers/immich-ml/cache /cache <pseudofs>" \
  -o fstab="/path/to/containers/immich-ml /config <pseudofs>" \
  ghcr.io/daemonless/immich-ml:latest immich-ml

Interactive Configuration

Parameters

Environment Variables

Variable	Default	Description
`MACHINE_LEARNING_HOST`	`0.0.0.0`	Host to bind to (0.0.0.0)
`MACHINE_LEARNING_PORT`	`3003`	Port to bind to (3003)
`MACHINE_LEARNING_CACHE_FOLDER`	`/cache`	Path to cache folder (/cache)
`PUID`	`1000`	User ID for the application process
`PGID`	`1000`	Group ID for the application process
`TZ`	`UTC`	Timezone for the container
`MACHINE_LEARNING_WORKERS`	`1`	Number of ML worker processes. Keep at 1 on weak / CPU-only hosts.
`MACHINE_LEARNING_WORKER_TIMEOUT`	`300`	Gunicorn worker timeout in seconds. Raise on slow CPUs so model loading doesn't time out and cycle the worker.
`SKIP_CHOWN`	`true`	Skip the one-time recursive chown of /cache and /config once ownership is recorded in /config/.chown_done (default true). Set false to force a chown on every start.

Volumes

Path	Description
`/cache`	Model cache (HuggingFace ONNX models). Use a persistent volume to avoid re-downloading models.
`/config`	Gunicorn HOME and the .chown_done ownership marker. Must be a persistent volume (the chown-skip relies on it).

Ports

Port	Protocol	Description
`3003`	TCP	ML API

This image is part of the Immich Stack.

Low-power / CPU-only hosts

On weak or CPU-only machines, model loading can be slow and the worker may time out during startup (repeated healthy/unhealthy cycles). Raise the timeout and pin the numeric libraries to a single thread to avoid thrashing:

environment:
  MACHINE_LEARNING_WORKERS: "1"
  MACHINE_LEARNING_WORKER_TIMEOUT: "300"
  MACHINE_LEARNING_MODEL_INTER_OP_THREADS: "1"
  MACHINE_LEARNING_MODEL_INTRA_OP_THREADS: "1"
  MACHINE_LEARNING_REQUEST_THREADS: "1"
  OMP_NUM_THREADS: "1"
  OPENBLAS_NUM_THREADS: "1"
  MKL_NUM_THREADS: "1"

Persistent volumes

Mount both /config and /cache as persistent volumes. The one-time recursive chown is skipped on later starts via a /config/.chown_done marker — without a persistent /config, the marker is lost and the chown re-runs every start, so SKIP_CHOWN=true only takes effect once /config persists the marker.

Implementation Details

Architectures: amd64
User: bsd (UID/GID set via PUID/PGID). Defaults to 1000:1000.
Base: Built on ghcr.io/daemonless/base (FreeBSD 15.1).

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