Note: typical constraint is RAM and changes to the EdgeTPU compiler which now fails to convert larger models. Previously (version 15?) it would delegate layers to the CPU, but now it just doesn't work at all for large input sizes.
Also while it works, I think it's unlikely to be much better than a well trained mobilenet SSD. The advantage is you can train in pytorch and go from there, training quantised/edge models in Tensorflow is tricky.
Note: typical constraint is RAM and changes to the EdgeTPU compiler which now fails to convert larger models. Previously (version 15?) it would delegate layers to the CPU, but now it just doesn't work at all for large input sizes.
Also while it works, I think it's unlikely to be much better than a well trained mobilenet SSD. The advantage is you can train in pytorch and go from there, training quantised/edge models in Tensorflow is tricky.