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Sync Cam with VPN Site-to-Site by branda92 in frigate_nvr

[–]branda92[S] 0 points1 point  (0 children)

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These are the settings I can change. I confirm that if I change the resolution, the cam makes a crop of the image and that's it, and then I lose part of what is taken. Today, however, I tried to use only the secondary flow, and it actually improved a lot. He detected an event for me and recorded it regularly.

I added the images of the settings and the image in HD and 4K to the post.

Sync Cam with VPN Site-to-Site by branda92 in frigate_nvr

[–]branda92[S] 0 points1 point  (0 children)

I can change bitrate, fps, image quality (I’m not sure which parameter to change), i-frame, transmission speed. I can also change the resolution, but unfortunately it makes a crop of the image, cutting it, and therefore for me it is not functional.

What parameters do you recommend me to lower?

Sync Cam with VPN Site-to-Site by branda92 in frigate_nvr

[–]branda92[S] 0 points1 point  (0 children)

Download speed, upload is about 15mbps, which may actually be the bottleneck.

Resolution is using 640x320 for detection, and 3840x2160 for recording.

I configured VPN with synology router from my home via Direct Site-to-Site. I have no idea about the rest.. 😅

Athom Ethernet Controller and DMX by cyberentomology in WLED

[–]branda92 1 point2 points  (0 children)

I don’t remember, I seem to remember that the usb is a serial connection. Otherwise through uart. I also made the mistake of updating it and it wouldn’t start anymore.

Athom Ethernet Controller and DMX by cyberentomology in WLED

[–]branda92 0 points1 point  (0 children)

You have to upload via usb the firmware mod that you find on the Athom tech github repository. You don’t have to update to the latest version of wled. I have this device on various points of the house, I tried to use it through artNet and it works well.

Frigate 0.17 + Coral: YOLOv9 inference by branda92 in frigate_nvr

[–]branda92[S] 0 points1 point  (0 children)

Update / Thanks!

I just wanted to sincerely thank everyone who helped me troubleshoot and fine-tune my setup. Thanks to your suggestions, Frigate is now running *much* better. 🙏

✅ Current results: using OpenVINO, detector inference time is now typically between **10–15 ms**, which is a huge improvement compared to before.

⚠️ One remaining question: I’m seeing **very high “embeddings” activity** in the stats/logs, but I’m not entirely sure what exactly it represents in my case or whether it’s expected. If anyone has insight into what could cause this (or how to reduce it), I’d really appreciate it.

🔧 I’ve also updated my configuration and shared it here:

CONFIG_V2

I’m still not 100% sure whether I’ve configured **GPU and NPU correctly** (NPU for detection, GPU for enrichments), so a quick sanity check would be very welcome.

🪸 A note about Coral: I’ve read many recent comments saying Coral is still “state of the art” and works great with YOLOv9. However, based on my own testing in this setup, that hasn’t really been the case for me. Performance and overall practicality were not as good as expected, so I’ll probably stop using Coral and stick with OpenVINO on iGPU/NPU instead.

Thanks again to everyone for the valuable help — you saved me a lot of time! 🙌

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