Env

• GPU, e.g. NVIDIA Xavier AGX
• OS, e.g. Ubuntu18.04
• Cuda version : 10.2.89
• TensorRT version

About this repo

• which branch/tag/commit are you using? https://github.com/dusty-nv/pytorch-detection
• which model? mobile net ssd

Your problem

I wanted to custom train on a different dataset (eg, doorways detection).

• I see that the train_ssd.py seems to do it, however I have not not been able to realize how to fo it.
• I am new to computer vision, can you guide me how the dataset should look like, I have images (.jpeg) and label (.xml files).
• The folder is structures as \images - > \train and \test . these subfolders have images and labels.
• Do I need to load a model in order to do it, because I see that is the case, however I donot have any model.
• How do I prune my model after I have created one?
• How to convert the .pth file to trt model once I am able to train it.

Thank you.

Hello Dusty, I have checked your training program for detection. Can I know how to run and test the program? Is the program is used for face detection?

Hi @dusty-nv ,

I tried to train a custom SSD w/ mibilenetV2 from this repo and then deploy on a jetson agx xavier through jetson-inference. However, it seems that there is an incompability between onnx and tensorrt.
I obtained this error:

My tensorrt version is 5.1.6.

Could you help me on that?
Thanks!