Semantic segmentation on PX2 with a model pretrained on Cityscapes

Dear all,
I would like to do semantic segmentation (i.e. run inference) with a neural network trained on Cityscapes such as MobileNet-v3 or Xception_71 [1]. I use PX2 (AutoChaffeur, Ubuntu 16.04, AArch64), so I can only use C++ API rather than Python API, as the latter is just not available. Obviously, I would also need to use TensorRT for my task. I had been wondering if somebody could suggest some particular tutorials I should follow; I know that there’s quite a lot of them on NVIDIA website, but it is precisely this abundance of information that makes me feel a bit at loss… Thanks a lot in advance!


Dear shader2020,
We have provided DLI lab at GTC on this earlier but it is not available in public domain. If you already have a trained model, you can take a look at TensorRT samples on optimizing your model furthur. Let us know if you face any issues. Also, note that the last release on DRIVE PX 2 has TensorRT 4.0 and all the releases now are targetted towards to DRIVE AGX platform. If possible consider upgrading to DRIVE AGX platform to get latest SW stack.

Dear SivaRamaKrishna,
Thanks a lot!