Comment by joshvm
2 days ago
Well, a small shoutout for my project to facilitate YOLO on the EdgeTPU without any dependencies on Ultralytics. Some contributors helped a bit with more recent versions, but it seems like all you need is to twiddle a few of the input shapes. I say facilitate rather than port because someone else did the hard work actually implementing the converter to tflite.
https://github.com/jveitchmichaelis/edgetpu-yolo
You really do need the model to be defined in Tensorflow though. Channel ordering screws things up in PyTorch and it's not trivial to get round it, otherwise the compiler does all sorts of weird gymnastics to permute for you.
See, this looks great, so now I have to give this a try! Just a quick Q to avoid the pain of trying if it's known not to work, is there a major reason this might not work on a raspberry pi? Thanks for sharing
If you can get the libraries installed then the code should work. The only risk is that Coral is not particularly well maintained and you might need to downgrade to e.g. an older version of Debian. Feel free to post an issue if you run into trouble.