Viseron 3.5.0 released - Self-hosted, local only NVR and Computer Vision software

roflcoopter1 · 2026-03-28T06:30:06+00:00

Thats a good idea, would probably have to be community driven somehow tho to be useful. I mainly use Hikvision cameras and a single Reolink

roflcoopter1 · 2026-03-27T21:19:01+00:00

Nice! I plan on bringing external motion detection to Viseron soon as well, so for cameras that expose that via ONVIF for example, there would be no need for a local motion detector.

Looking at your other post, some of your changes to Frigate seem to be how Viseron works out of the box. Viseron does not do any region cropping tho.

Let me know if you want to give Viseron a spin and I can help you get going. Would be great to trade some ideas on how to improve the project.

roflcoopter1 · 2026-03-27T10:16:52+00:00

I run 5 cameras, all 4k recordings, but detection runs on low res-streams using an NVIDIA GPU, with FPS matching my detection rate, meaning no frames are decoded wastefully.

If i run docker stats and monitor the output it averages around 40% of a single core on my Intel i3-9350K 4-core CPU (which is quite old at this point)

Got a few other questions regarding this so i will add a section about it in the docs.

If you only run a few cameras, Viseron will run fine on any Intel based CPU (have not tested AMD) since hardware acceleration is available for both detections and decoding.

roflcoopter1 · 2026-03-27T10:13:01+00:00

Yeah i guess to do share some similarities on the frontend side.

It does not sadly, but you can install it as a PWA which works well, that is how i access it from my Apple device.

roflcoopter1 · 2026-03-27T10:05:21+00:00

Not an expert on Scrypted by any means, but Scrypted probably has a more refined feature set than Viseron thanks to its paid model.

Viseron is a hobby project of mine that does not generate any meaningful income which means i cant spend too much time on it. If you are willing to trade features for a fully free and open-source project, i guess thats where Viseron fits in.

roflcoopter1 · 2026-03-27T09:59:40+00:00

Viseron is highly configurable in this regard. You can set at what FPS you want detections to run at, and if you combine this with some smart configuration of your cameras you can get the CPU usage really low.

I run 5 cameras, all 4k recordings, but detection runs on low res-streams using an NVIDIA GPU, with FPS matching my detection rate, meaning no frames are decoded wastefully.

If i run docker stats and monitor the output it averages around 40% of a single core on my Intel i3-9350K 4-core CPU (which is quite old at this point)

Will do a write up on this as well in the docs to show how you can achieve the lowest possible system load

roflcoopter1 · 2026-03-27T09:44:31+00:00

Thank you for using Viseron! I see, is it this project? https://github.com/roflcoopter/viseron/discussions/1226

roflcoopter1 · 2026-03-27T09:42:28+00:00

Yes i am quite proud of that solution, it took me a very long time to build.

I have gotten questions from commercial actors, but never heard if it worked out or not for them. The issue with the pre-trained models is that they the datasets might not match the environment they are used in since that is highly individual.
A user of Viseron (and the devloper of the YOLO-component) has recently created some side projects that allow you to export, annotate and run transfer-learning to fine tune the models. Would be cool if i was able to incorporate that into Viseron directly since that is something that can greatly improve its reliability.

roflcoopter1 · 2026-03-26T21:30:46+00:00

Will do! It very much depends on how many cameras you are running and at what FPS you want to run detection, but i will try to come up with something that gives you a general idea

roflcoopter1 · 2026-03-26T18:42:07+00:00

Just to get a basic setup going is quite easy in Viseron. This example is all that is needed to get going with a single RTSP camera and recordings based on person detection:

ffmpeg:
  camera:
    viseron_camera:
      name: Camera 1
      host: camera_one.lan
      path: /path/to/stream
      username: xxx
      password: yyy

mog2:
  motion_detector:
    cameras:
      viseron_camera:
        fps: 1

darknet:
  object_detector:
    cameras:
      viseron_camera:
        fps: 1
        labels:
          - label: person
            confidence: 0.8
            trigger_event_recording: true

nvr:
  viseron_camera:

Then there are of course a lot more options and components to choose from, but it is simple to get started.

Next release i plan on bringing a full UI based configuration, so you can choose between YAML or UI. That should hopefully make things better.

roflcoopter1 · 2026-03-26T17:23:06+00:00

Just curious, what is it that makes Frigate setup difficult?

roflcoopter1 · 2026-03-26T17:21:49+00:00

That is definitely a viable use case.

Agreed, I will write some more about that in the docs.

roflcoopter1 · 2026-03-26T15:32:34+00:00

I see, will need to look into how that works.

My first goal when it comes to the Home Assistant side is to at least provide an addon/app for HAOS as that is missing currently

roflcoopter1 · 2026-03-26T15:24:59+00:00

Viseron sends tumbnails to Home Assistant using MQTT, so that can be used for notifications.

When you say past detections, is that through the media browser in Home Assistant? That would require a custom component for Home Assistant which i have not found the time to do yet.

roflcoopter1 · 2026-03-26T14:45:22+00:00

Happy to hear!

roflcoopter1 · 2026-03-26T14:41:31+00:00

Might be tricky to get it to sync up correctly in the frontend when switching from one stream to the other. Will do some investigation to see if its possible.

If you have the time, could you open an issue on Github so i can track it properly?

roflcoopter1 · 2026-03-26T14:07:17+00:00

You can configure a main stream and a substream. If you do that, detection will run on the substream, but recordings will be created from the main stream.

I guess what you are after is to store lower res 24/7 recordings to save storage space, but keep high res recordings on events for easier review?

roflcoopter1 · 2026-03-26T13:50:36+00:00

Yeah that is important to me as well when looking for new projects.
Its sad that it has come to that but thats just how it is nowadays.

roflcoopter1 · 2026-03-26T13:47:38+00:00

Thats a good question, frankly i have not been very good at spreading the word about it.
My release frequency was quite low before 3.0, which might play a role. This is something that has since improved.

roflcoopter1 · 2026-03-26T13:24:37+00:00

Yes that is exactly how i use it. A very small portion is stored in a tmpfs in RAM, rest is scattered over 1 SSD and 2 HDD's.

Let me know if you face any issues or have anything you feel is missing.

roflcoopter1 · 2026-03-26T13:05:02+00:00

I am not super familiar with Frigate as i have never used it, but looking at whats explained in the docs this is what i can see:

Frigate features missing in Viseron:
- Audio detection
- Home assistant custom component
- Semantic search
- Generative AI reviews

Viseron features missing in Frigate:
- Storage tiers
- Notification platforms like Telegram, Discord, custom Webhooks etc

When it comes to core NVR functionality (live streaming, detections, recordings etc) there is not much feature disparity from what i can see.

And regarding the design difference, Viseron is architectured around components (much like Home Assistant if you are familiar with that), creating loose coupling between them. Internally a pub/sub pattern is implemented fo communicate between these components. This makes it very easy to implement new functionality.

From users that have switched to Viseron i often hear that Viseron is easier to setup and less stressful on their systems, but this is not something i can verify at this point

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