User of Frigate here. Seems these are some pretty major differences of what you can do for free with Frigate, but if you use Clearcam, you need to pay for "Clearcam Premium":
- View your live camera feeds remotely.
- Receive notifications on events (objects/people detected).
- View event clips remotely.
- End-to-end encryption on all data.
What neither of the solutions seem to have, is encryption at rest. But I guess others, just like me, rather encrypt the volume/storage itself, instead of leaving it up to applications anyways, so might/might not matter for you.
Where can I find the list of supported GPUs? Frigate been able to handle everything I've tried so far, all from Nvidia and AMD GPUs to even Intel iGPUs.
Maybe my view of frigate and tensorflow (assuming frigate still uses it) is outdated then. I’m referring to tinygrad vs tensorflow when I say GPU support, of course google’s tensorflow is best for google’s TPUs. I’ve had better luck using tinygrad on my personal devices, but I am biased as it’s been a while since I’ve used tensorflow
This would be a good point of differentiation to make on your GitHub page or for a technical audience on your website. Frigate is SOTA in many folks minds, and to show that you are using tinygrad over tensorflow may be a good “modern-ness” signal for that audience.
Edit: another solution in this space shows a list of supported ML runtimes, which would be good info for folks wanting to run on specific hardware. https://github.com/boquila/boquilahub
Supported runtimes list would be nice, but I don't have access to much hardware to test on. I aim to remove most dependencies and support anything that can run tinygrad + ffmpeg
Unless you’re making changes, isn’t it enough to just link back to the original repo?
That said, I’ve also been in the camp that avoids AGPL-except maybe as a way to sell a commercial license while still being "open source," or just to be obnoxious. And honestly, I am still failing to see the upside in being obnoxious for its own sake.
User of Frigate here. Seems these are some pretty major differences of what you can do for free with Frigate, but if you use Clearcam, you need to pay for "Clearcam Premium":
- View your live camera feeds remotely.
- Receive notifications on events (objects/people detected).
- View event clips remotely.
- End-to-end encryption on all data.
What neither of the solutions seem to have, is encryption at rest. But I guess others, just like me, rather encrypt the volume/storage itself, instead of leaving it up to applications anyways, so might/might not matter for you.
The author states elsewhere that the payments are for the use of their server, which can be reconfigured.
Yeah, I'll admit to not having tried Clearcam myself, I was just going by the information from the README as-is.
fewer features, easier setup, with more GPUs supported. (I've not used frigate myself though, only watched videos)
Where can I find the list of supported GPUs? Frigate been able to handle everything I've tried so far, all from Nvidia and AMD GPUs to even Intel iGPUs.
same here -- it's also among one of the only things to support Coral devices and RPi video cores.
I would imagine any GPGPU compute-capable pre-CUDA thing probably won't cut it.
I have used Frigate for years, I think early on it didn't support all of those GPUs. So it might be that said videos are out of date.
Maybe my view of frigate and tensorflow (assuming frigate still uses it) is outdated then. I’m referring to tinygrad vs tensorflow when I say GPU support, of course google’s tensorflow is best for google’s TPUs. I’ve had better luck using tinygrad on my personal devices, but I am biased as it’s been a while since I’ve used tensorflow
This would be a good point of differentiation to make on your GitHub page or for a technical audience on your website. Frigate is SOTA in many folks minds, and to show that you are using tinygrad over tensorflow may be a good “modern-ness” signal for that audience.
Edit: another solution in this space shows a list of supported ML runtimes, which would be good info for folks wanting to run on specific hardware. https://github.com/boquila/boquilahub
Supported runtimes list would be nice, but I don't have access to much hardware to test on. I aim to remove most dependencies and support anything that can run tinygrad + ffmpeg
Sorry, which one are you talking about, frigate or clear cam?
it's AGPL so you have to give anyone that views your camera feeds a copy of the source
Unless you’re making changes, isn’t it enough to just link back to the original repo?
That said, I’ve also been in the camp that avoids AGPL-except maybe as a way to sell a commercial license while still being "open source," or just to be obnoxious. And honestly, I am still failing to see the upside in being obnoxious for its own sake.
It's AGPL because Ultralytics requires it to use YOLO: https://github.com/blakeblackshear/frigate/pull/10717
I'd make it MIT tomorrow if you know a workaround or alternative model