Tiny Yolo V3 TensorRT conversion low fps

AI & Data Science Deep Learning (Training & Inference) TensorRT
#1

Hi,

I am getting 6fps (for 608x608) in darknet at jetson Nano. After converting it to tensorrt, I am getting 800 ms as inference time and 110 ms (for 608x608) as post processing (i.e. Yolo layer nms operation) time. So, I can say that I am getting the same performance in both the cases. Can I reduce the post processing time? so that performance can be enhanced. I am using the sample tensorrt code (yolo to onnx and onnx to tensorrt).

#2

Can I get any response? Admin Team. Any help??

#3

Hi,
The pre and post-processing steps depend strongly on the particular application.
TensorRT is a high performance neural network inference optimizer and runtime engine.

Please refer to below link for optimizing python performance.
https://docs.nvidia.com/deeplearning/sdk/tensorrt-best-practices/index.html#optimize-python

Thanks