Neural Net accuracy scales with the amount of compute you have available at inference time, and for vision models it is largely the amount of compute you need

Neural Net accuracy scales with the amount of compute you have available at inference time, and for vision models it is largely the amount of compute you need (NLP models often require a lot of memory too), so while you could probably squeeze something onto a raspberry pi, you would probably have to sacrifice frames per second and overall performance. I think for a hobby project bundling an accelerator is the right choice so that hobbyists don't have to worry so much about performance. The same way that a raspberry pi really is overkill for almost everything people do with them since you could do the same with a microcontroller with no OS, someone could probably squeeze something onto a raspberry pi without the accelerator, but that's going to be far harder than just getting started with the high level APIs.