pauljerem

+1 @srikar242 could you explain how you resolved the memory issue please? I'm doing exactly the same as you (using YOLOv4 in RT on a Jetson Nano), and having exactly...

So, I figured out from [this post](https://stackoverflow.com/questions/26201172/cuda-too-many-resources-requested-for-launch) that the error relates to CUDA’s maximum number of threads per block being too large. And, according to [this response](https://forums.developer.nvidia.com/t/tiny-yolov4-tensorrt-too-many-resources-requested-for-launch-on-4gb-nano/163962/3) from Nvidia, *config.block_count*,...

I found a solution. The issue can be fixed by adding the following lines at the top of the detect script (before TensorFlow is imported): ``` import os os.environ['CUDA_VISIBLE_DEVICES'] =...