martabal/immich

Immich is a high performance self-hosted photo and video backup solution.

What is it ?

This repo is a fork of the official AIO image for Immich. Its main goal is to provide docker images with pre-installed machine learning support for CUDA and openvino.

Supported Architectures

This image supports the following architectures:

Architecture	Available
x86-64	✅
arm64	✅
armhf	❌

Version Tags

This image offers different versions via tags. Be cautious when using unstable or development tags, and read their descriptions carefully.

Tag	Available	Description
latest	✅	Latest Immich release with an Ubuntu base.
openvino	✅	Latest Immich release with an Ubuntu base and support for openvino for machine-learning acceleration.
cuda	✅	Latest Immich release with an Ubuntu base and support for cuda for machine-learning acceleration.
noml	✅	Latest Immich release with an Ubuntu base. Machine-learning is completely removed, making it still compatible with hardware accelaration.

Application Setup

The WebUI can be accessed at http://your-ip:8080 Follow the wizard to set up Immich.

To use Immich, you need to have PostgreSQL 14/15/16 server with pgvecto.rs set up externally, and Redis set up externally or within the container using a docker mod.

To use a SSL connection to your PostgreSQL database, include a PostgreSQL URL in the DB_URL environment variable.

Hardware Acceleration for videos

Intel - QSV/VAAPI

To use Intel Quicksync hardware acceleration:

• Ensure your container has access to the /dev/dri video device.

• Add the device to your container by including the following option in your Docker run command:

  • Docker run:

    docker run --device=/dev/dri:/dev/dri ...

  • Docker compose:

  services:
    immich:
      image: ghcr.io/martabal/immich:latest
      ...
      devices:
        - "/dev/dri:/dev/dri"

Nvidia - NVENC/VAAPI

To use Nvidia hardware acceleration:

• First, install the Nvidia container runtime on your host machine. Follow the [installation instructions here](https://github.com/NVIDIA/ nvidia-docker).

• After installing nvidia-docker2, recreate or create a new Docker container using the Nvidia runtime. This can be done in two ways:

• Add both --runtime=nvidia and NVIDIA_VISIBLE_DEVICES=all to your Docker run command. Replace all with a specific GPU's UUID if needed. Example:

  • Docker run:

    docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all

  • Docker compose:

  services:
    immich:
      image: ghcr.io/martabal/immich:latest
      ...
      runtime: nvidia
      environment:
        ...
        - NVIDIA_VISIBLE_DEVICES=all

• Alternatively, use --gpus=all in your Docker run command. Example:

  • Docker run:

    docker run --gpus=all ...

  • Docker compose:

  services:
    immich:
      image: ghcr.io/martabal/immich:latest
      ...
      deploy:
        resources:
          reservations:
            devices:
              - driver: nvidia
                count: 1
                capabilities:
                  - gpu

Machine-learning acceleration

Intel - OpenVINO

To use OpenVINO:

• Make sure your CPU supports OpenVINO

• Add a new path -p /dev/bus/usb:/dev/bus/usb and add --device=/dev/dri --device-cgroup-rule='c 189:* rmw' in your Docker run command. Example:

  • Docker run:

    docker run --device=/dev/dri --device-cgroup-rule='c 189:* rmw' -p /dev/bus/usb:/dev/bus/usb ...

  • Docker compose:

  services:
    immich:
      image: ghcr.io/martabal/immich:latest
      ...
      device_cgroup_rules:
        - 'c 189:* rmw'
      devices:
        - /dev/dri:/dev/dri
      volumes:
        ...
        - /dev/bus/usb:/dev/bus/usb

Nvidia - CUDA

For Nvidia GPUs with Nvidia/CUDA hardware acceleration, use the same commands used for video transcoding.

Import your existing libraries into Immich

• Mount your existing library folder to /import
• In your administration settings, go to "External Libraries", add a library owner, and set the import paths starting (it must start with /import)

Usage

Example snippets to start creating a container:

Docker Compose

services:
  immich:
    image: ghcr.io/martabal/immich:latest
    container_name: immich
    environment:
      - PUID=1000
      - PGID=1000
      - TZ=Etc/UTC
      - DB_HOSTNAME=192.168.1.x
      - DB_USERNAME=postgres
      - DB_PASSWORD=postgres
      - DB_DATABASE_NAME=immich
      - REDIS_HOSTNAME=192.168.1.x
      - DB_PORT=5432 #optional
      - REDIS_PORT=6379 #optional
      - REDIS_PASSWORD= #optional
      - MACHINE_LEARNING_HOST=0.0.0.0 #optional
      - MACHINE_LEARNING_PORT=3003 #optional
      - MACHINE_LEARNING_WORKERS=1 #optional
      - MACHINE_LEARNING_WORKER_TIMEOUT=120 #optional
    volumes:
      - path_to_appdata:/config
      - path_to_photos:/photos
      - path_to_imports:/import:ro #optional
    ports:
      - 8080:8080
    restart: unless-stopped
  # This container requires an external application to be run separately to be run separately.
  # By default, ports for the databases are opened, be careful when deploying it
  # Redis:
  redis:
    image: redis
    ports:
      - 6379:6379
    container_name: redis
  # PostgreSQL 14:
  postgres14:
    image: tensorchord/pgvecto-rs:pg14-v0.2.0
    ports:
      - 5432:5432
    container_name: postgres14
    environment:
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: postgres
      POSTGRES_DB: immich
    volumes:
      - path_to_postgres:/var/lib/postgresql/data

Docker CLI (Click here for more info)

docker run -d \
  --name=immich \
  -e PUID=1000 \
  -e PGID=1000 \
  -e TZ=Etc/UTC \
  -e DB_HOSTNAME=192.168.1.x \
  -e DB_USERNAME=postgres \
  -e DB_PASSWORD=postgres \
  -e DB_DATABASE_NAME=immich \
  -e REDIS_HOSTNAME=192.168.1.x \
  -e DB_PORT=5432 `#optional` \
  -e REDIS_PORT=6379 `#optional` \
  -e REDIS_PASSWORD= `#optional` \
  -e MACHINE_LEARNING_HOST=0.0.0.0 `#optional` \
  -e MACHINE_LEARNING_PORT=3003 `#optional` \
  -e MACHINE_LEARNING_WORKERS=1 `#optional` \
  -e MACHINE_LEARNING_WORKER_TIMEOUT=120 `#optional` \
  -p 8080:8080 \
  -v path_to_appdata:/config \
  -v path_to_photos:/photos \
  -v path_to_imports:/import:ro `#optional` \
  --restart unless-stopped \
  ghcr.io/martabal/immich:latest

# This container requires an external application to be run separately.
# By default, ports for the databases are opened, be careful when deploying it
# Redis:
docker run -d \
  --name=redis \
  -p 6379:6379 \
  redis

# PostgreSQL 14:
docker run -d \
  --name=postgres14 \
  -e POSTGRES_USER=postgres \
  -e POSTGRES_PASSWORD=postgres \
  -e POSTGRES_DB=immich \
  -v path_to_postgres:/var/lib/postgresql/data \
  -p 5432:5432 \
  tensorchord/pgvecto-rs:pg14-v0.2.0

Variables

To configure the container, pass variables at runtime using the format <external>:<internal>. For instance, -p 8080:80 exposes port 80 inside the container, making it accessible outside the container via the host's IP on port 8080.

Variable	Description
-p 8080	WebUI Port
-e PUID=1000	UID for permissions - see below for explanation
-e PGID=1000	GID for permissions - see below for explanation
-e TZ=Etc/UTC	Specify a timezone to use, see this list.
-e DB_HOSTNAME=192.168.1.x	PostgreSQL Host
-e DB_USERNAME=postgres	PostgreSQL Username
-e DB_PASSWORD=postgres	PostgreSQL Password
-e DB_DATABASE_NAME=immich	PostgreSQL Database Name
-e REDIS_HOSTNAME=192.168.1.x	Redis Hostname
-e DB_PORT=5432	PostgreSQL Port
-e REDIS_PORT=6379	Redis Port
-e REDIS_PASSWORD=	Redis password
-e MACHINE_LEARNING_HOST=0.0.0.0	Immich machine-learning host
-e MACHINE_LEARNING_PORT=3003	Immich machine-learning port
-e MACHINE_LEARNING_WORKERS=1	Machine learning workers
-e MACHINE_LEARNING_WORKER_TIMEOUT=120	Machine learning worker timeout
-v /config	Contains machine learning models (~1.5GB with default models)
-v /photos	Contains all the photos uploaded to Immich
-v /import:ro	This folder will be periodically scanned, contents will be automatically imported into Immich

Umask for running applications

The image allow overriding the default umask setting for services started within the containers using the optional -e UMASK=022 option. Note that umask works differently than chmod and subtracts permissions based on its value, not adding. For more information, please refer to the Wikipedia article on umask here.

User / Group Identifiers

To avoid permissions issues when using volumes (-v flags) between the host OS and the container, you can specify the user (PUID) and group (PGID). Make sure that the volume directories on the host are owned by the same user you specify, and the issues will disappear.

Example: PUID=1000 and PGID=1000. To find your PUID and PGID, run id user.

  $ id username
    uid=1000(dockeruser) gid=1000(dockergroup) groups=1000(dockergroup)

Updating the Container

Check the Application Setup section for recommendations for the specific image.

Instructions for updating the container:

Via Docker Compose

• Update all images: docker-compose pull or update a single image: docker-compose pull immich
• Let compose update all containers as necessary: docker-compose up -d or update a single container: docker-compose up -d immich
• You can also remove the old dangling images: docker image prune

Via Docker Run

• Update the image: docker pull ghcr.io/martabal/immich:latest
• Stop the running container: docker stop immich
• Delete the container: docker rm immich
• Recreate a new container with the same docker run parameters as instructed above (if mapped correctly to a host folder, your /config folder and settings will be preserved)
• You can also remove the old dangling images: docker image prune