Immich•4mo ago

Does my machine support machine learning using openvino?

I see docs said

https://v1.124.2.archive.immich.app/docs/features/ml-hardware-acceleration#openvino The server must have a discrete GPU, i.e. Iris Xe or Arc. Expect issues when attempting to use integrated graphics.

But as far as I know, Iris XE is not a discrete GPU, it's integrated together in intel CPUs. How can I know my immich instance on "11th Gen Intel® Core™ i7-1165G7 @ 2.80GHz" is processing machine learning with openvino. here is my docker-compose settings

#
# WARNING: Make sure to use the docker-compose.yml of the current release:
#
# https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml
#
# The compose file on main may not be compatible with the latest release.
#

name: immich

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: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
    #   file: hwaccel.ml.yml
    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
    volumes:
      - /mnt/user/tempo/immich:/cache
      - /dev/bus/usb:/dev/bus/usb
    env_file:
      - .env
    device_cgroup_rules:
      - 'c 189:* rmw'
    devices:
      - /dev/dri:/dev/dri
    restart: always
    healthcheck:
      disable: false

#
# WARNING: Make sure to use the docker-compose.yml of the current release:
#
# https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml
#
# The compose file on main may not be compatible with the latest release.
#

name: immich

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: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
    #   file: hwaccel.ml.yml
    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
    volumes:
      - /mnt/user/tempo/immich:/cache
      - /dev/bus/usb:/dev/bus/usb
    env_file:
      - .env
    device_cgroup_rules:
      - 'c 189:* rmw'
    devices:
      - /dev/dri:/dev/dri
    restart: always
    healthcheck:
      disable: false

Hardware-Accelerated Machine Learning | Immich

This feature allows you to use a GPU to accelerate machine learning tasks, such as Smart Search and Facial Recognition, while reducing CPU load.

7 Replies

Immich•4mo ago

:wave: Hey @latel, Thanks for reaching out to us. Please carefully read this message and follow the recommended actions. This will help us be more effective in our support effort and leave more time for building Immich :immich:. References - Container Logs: docker compose logs docs - Container Status: docker ps -a docs - Reverse Proxy: https://immich.app/docs/administration/reverse-proxy - Code Formatting https://support.discord.com/hc/en-us/articles/210298617-Markdown-Text-101-Chat-Formatting-Bold-Italic-Underline#h_01GY0DAKGXDEHE263BCAYEGFJA

Immich•4mo ago

Checklist I have... 1. :blue_square: verified I'm on the latest release(note that mobile app releases may take some time). 2. :blue_square: read applicable release notes. 3. :blue_square: reviewed the FAQs for known issues. 4. :blue_square: reviewed Github for known issues. 5. :blue_square: tried accessing Immich via local ip (without a custom reverse proxy). 6. :blue_square: uploaded the relevant information (see below). 7. :blue_square: tried an incognito window, disabled extensions, cleared mobile app cache, logged out and back in, different browsers, etc. as applicable (an item can be marked as "complete" by reacting with the appropriate number) Information In order to be able to effectively help you, we need you to provide clear information to show what the problem is. The exact details needed vary per case, but here is a list of things to consider: - Your docker-compose.yml and .env files. - Logs from all the containers and their status (see above). - All the troubleshooting steps you've tried so far. - Any recent changes you've made to Immich or your system. - Details about your system (both software/OS and hardware). - Details about your storage (filesystems, type of disks, output of commands like fdisk -l and df -h). - The version of the Immich server, mobile app, and other relevant pieces. - Any other information that you think might be relevant. Please paste files and logs with proper code formatting, and especially avoid blurry screenshots. Without the right information we can't work out what the problem is. Help us help you ;) If this ticket can be closed you can use the /close command, and re-open it later if needed.

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Athul•4mo ago

hey Latel, to check whether immich is using any specific hardware, the general idea is to run some ml-tasks and monitor your system usage for that device. If you're on windows, taskmanager should list your XE gpu and show it's real-time usage. ML tasks should give a noticeable spike. For starting an ml task, you can run a facial scanning job in the "jobs" section in Immich as admin.

Tempest•4mo ago

 # Example tag: ${IMMICH_VERSION:-release}-cuda
    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}

 # Example tag: ${IMMICH_VERSION:-release}-cuda
    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}

You need to specify a hwa container type if you want to use hwa.

sogan•4mo ago

But as far as I know, Iris XE is not a discrete GPU, it's integrated together in intel CPUs.

It actually depends on the model. Iris Xe MAX is a dGPU series. I’m not sure but other Xe models might also use a dGPU driver, or at least I remember seeing something along those lines in their docs In general you’re free to try using OpenVINO. It’s just historically been more problematic for iGPUs Especially older models

latelOP•4mo ago

I do not see any falling back to CPU like errors, so I guess it's working.

Immich•4mo ago

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Does my machine support machine learning using openvino?

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