[TensorRT] ERROR: …/rtSafe/cuda/reformat.cu (925) - Cuda Error in NCHWToNCHHW2: 400 (invalid resource handle)

[AastaLLL]

Hi,

Not sure if I understand your problem correctly.
It seems that you try to run the inference as a kind of callback function from the internet.

Then, a common error is that the CUDA context is refreshed and mixed up with other applications.
Please store the CUDA context before leaving the yolo_detection function and restore it when back.

A similar example can be found in this topic:

How to use TensorRT by the multi-threading package of python

Hi, The sample is ready. The workflow looks like this: Master: create TensorRT engine and buffer, store the created CUDA context. Thread1: restore master’s CUDA context, run inference, destroy its CUDA context. Master: destroy the stored CUDA context. The sample is created with TensorRT default MNIST model. 1. Prepare data $ /usr/src/tensorrt/bin/trtexec --onnx=/usr/src/tensorrt/data/mnist/mnist.onnx --saveEngine=mnist.trt $ cd /usr/src/tensorrt/data/mnist/ $ sudo pip3 install pillow $ pyt…

Thanks.