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,…
Looks like it picks up parts of the mail thing as a scooter only in a few frames and the score is way below 1% (I set the minimum threshold to 0.01%), here's an example: https://imgur.com/a/9pSTwut
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++.
Thanks!!!
Nice! Let us know if using Studio might be helpful there.
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,…
Looks like it picks up parts of the mail thing as a scooter only in a few frames and the score is way below 1% (I set the minimum threshold to 0.01%), here's an example: https://imgur.com/a/9pSTwut
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++.
Thanks!!!
Nice! Let us know if using Studio might be helpful there.