Open thomashopkins32 opened 1 year ago
Double-checked and it is accurate. The problem with using mAP as a metric with the UNet architecture is that I have to run a connected components analysis which is very expensive. Since I have a limited training budget (and the competition is over...) I can use a simpler metric like mean IoU over the whole image. This should speed up validation significantly and allow me to train for longer.
UNet apparently isn't meant for instance segmentation but semantic segmentation (I have to double check that this is accurate).
I should try a different model that was built for instance segmentation once I have squeezed out performance on UNet to the best of my ability.