#Remote Machine Learning

1 messages · Page 1 of 1 (latest)

crimson vector
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Currently I have the Immich server running on a Synology NAS. And the ML on my PC.

Because I've just started and wanted to implement all my pictures I decided the PC with ML would speed things up.
My Syn NAS is running at 99% CPU and my PC only at 13%.

In attachment is the data from docker on my PC. All looks good but it's only using 2.13 GB RAM
CPU 0.2-0.6%

nova impBOT
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:wave: Hey @crimson vector,

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

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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 ;)

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GitHub

High performance self-hosted photo and video management solution. - Issues · immich-app/immich

crimson vector
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Do I also need an env file on the Machine Learning side?

solid talon
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Nope

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If it's accessible, then it should download the required model upon request

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If required

crimson vector
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I see it loading the ViT-B-32__openai model.
I just don't see it using my PC's CPU power instead of the Synology CPU.

solid talon
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Pause all other jobs on the Synology. You're likely IOPS bound

crimson vector
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Nothing else is currently running on my Synology. I stopped all other docker containers

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Does the Generate Thumbnails go through my PC? Or are those only possible to generate on my Synology?

solid talon
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Those are on the Synology

crimson vector
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Because I think everything is working fine, but it's just all stuck on the Thumbnails and waiting for that to be done so it can go into Smart Search and Face Detection

crimson vector
solid talon
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Library, metadata, and thumbnails are on the Synology. What's the Synology's cpu? Likely not maxed?

crimson vector
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The spike is when I resumed everything.

solid talon
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Right now wait a minute and see if it stays high. You can disable all jobs except those 3

crimson vector
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Can I do the main server on my PC and link it to my Synology server via a Network location map.

solid talon
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I'm guessing the difference will be negligible if you're running SHR, but I could be wrong. It didn't make a difference in my case but I have SMR drives unfortunately

solid talon
crimson vector
solid talon
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Correct, because that won't change. SSD will change a lot

crimson vector
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It all seems fine, I have Face Detection on and Smart Search (both not influecing the CPU of the NAS) and I see movement in Docker on desktop. So all fine, it was like you said the bottleneck of the NAS with the thumbnails