I started tinkering with frigate and saw the option to use a coral ai device to process the video feeds for object recognition.
So, I started checking a bit more what else could be done with the device, and everything listed in the site is related to human recognition (poses, faces, parts) or voice recognition.
In some part I read stable diffusion or LLMs are not an option since they require a lot of ram which these kind of devices lack.
What other good/interesting uses can these devices have? What are some of your deployed services using these devices for?
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Yeah, they are mostly designed for classification and inference tasks; given a piece of input data, decide which of these categories it belongs to - the sort of things you are going to want to do in near real time, where it isn’t really practical to ship off to a data centre somewhere for processing.
I started using Frigate and thought about going the Coral route but realized you didn’t need them if you have a relatively recent Intel CPU (6th gen or newer) as OpenVino with the iGPU is pretty much on par https://github.com/blakeblackshear/frigate/discussions/5742 .
A lot of the newer SBCs are being shipped with integrated NPUs/TPUs now as well. I would get a Coral if I were to use an older SBC or RPi or older PC as a camera server for object detection. Currently I have an ESP32-CAM watching a bird feeder but that feed goes to a modern server for bird species recognition but I could see a Coral as an option.
They’re a great use for that otherwise useless “Wi-Fi slot” on a wired machine. Not too expensive either. So if you’re using your iGPU to transcode videos, it won’t interfere with your Frigate or Immich workload. And they’re supposed to be energy efficient too.
They are generally used for speech recognition and image classification, sometimes in a BAD way, like face recognition in surveillance cameras.
I mean that’s not inherently bad, what you do with that data could be though.
