^ probably not, since they use detectron2, but given the labeled images are really the core part of this, there’s no reason you can’t use them on a different mode that is compatible.
Yeah the labels are loaded into the Detectron2 format from the 3D annotations json at train time, we plan to add similar data loading for YOLOv3 etc soon. Starting out with Detectron2 was mainly for POC/demo purposes, the idea in the future is to be able to feed the data anywhere it might be needed.
I don't know the specifics of that camera/its software, but the trained models are saved as TorchScript (https://pytorch.org/docs/stable/jit.html) which can be used very flexibly in python/C++.
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Looks great! Very innovative approach. Are the generated models compatible with OpenCV OAK camera?
https://github.com/facebookresearch/detectron2/issues/1602
^ probably not, since they use detectron2, but given the labeled images are really the core part of this, there’s no reason you can’t use them on a different mode that is compatible.
Yeah the labels are loaded into the Detectron2 format from the 3D annotations json at train time, we plan to add similar data loading for YOLOv3 etc soon. Starting out with Detectron2 was mainly for POC/demo purposes, the idea in the future is to be able to feed the data anywhere it might be needed.
I don't know the specifics of that camera/its software, but the trained models are saved as TorchScript (https://pytorch.org/docs/stable/jit.html) which can be used very flexibly in python/C++.