I then converted the .tlt model to .etlt followed by conversion to an engine file using tlt-converter.
i know i can use deepstream directly but that’s not my goal here, i want to run inference on python.
I used the following code i attached for inference.
I can parse the bounding boxes just fine, I don’t, however understand how to parse the masks.
i know that the masks resolution is 28x28 and i used PeopleSegNet before and i was able to parse the masks by reshaping the output to (100,2,28,28) but the output this time has dimensions of 7134400 which i don’t know what to reshape it to.
Maybe i am missing something.
Any help would be appreciated
• Hardware: Jetson Xavier AGX
• Network Type: Mask_rcnn
• TLT Version: 3.0
• TensorRT Version: TensorRT 7.1.3
TRT_infer.py (3.5 KB)