Hi,
On Jetson platforms, we would suggest try VPI. Please check explanation in this topic:
Trying to get OpenCV (built with CUDA) working with FFMPEG - #6 by DaneLLLFor
cv::resize, it is supported in hardware converter VIC. Please try nvvidconv plugin in gstreamer, or NvBufferTransform() in jetson_multimedia_api.
Yeah, but VPI doesn’t and in the near future will not support most of the OpenCV algorithms. And I think Nvidia made most of the CUDA backend for OpenCV anyway. And previously someone from NVidia said that they cannot compile OpenCV + CUDA for Jetpack because of some compatibility reason, but as far as I know recompiling OpenCV + CUDA works fine out of the box.
Most people will do that anyway, because it is usually required for efficient DNN pre and post-processing. So the only reason you might not want do to it now is because you don’t have the storage space for extra few hundred mb. Jetson have very little storage and that is a constant pain.
But wait a second Dalus, are you sure there’s no OpenCL support? Some time back I had this thread regarding the up-sampling performance:
OpenCV has a lot of backends, so it is possible it switched to multi-core. But threading is usually done also for regular cv::Mat - not sure why cv::UMat made a difference there. I have also done per-pixel processing with OpenMP on Jetson and that seemed to work fine.
I suggest recompiling OpenCV with CUDA and using that. And if possible then try VPI.