Is busy CPU usage when jetson nano hardware decoding is doing task?

[DaneLLL]

Hi,

@LoveNvidia

You mean is that I don’t use zero-copy memory method? I do duplicated data in memory? How to correct this problem? If is set appsink as gstream elemet, this problem can be solve?

For using appsink in OpenCV, this cannot be eliminated. Optimal pipeline on Jetson Nano is to have NVMM bufffers from source to sink. OpenCV is CPU-based stackand it only accepts CPU buffers in appink.

An optimal solution is to leverage CUDA APIs and tegra_multimedia_api. Please refer to

Nano not using GPU with gstreamer/python. Slow FPS, dropped frames

Hi, Attached a sample for reference. Please follow the steps: 0. Install CUDA, tegra_multimedia_api samples through sdkmanager Down the script [s]https://github.com/AastaNV/JEP/blob/master/script/install_opencv4.1.1_Jetson.sh[/s] JEP/install_opencv4.5.0_Jetson.sh at master · AastaNV/JEP · GitHub Add the option and execute the script to build OCV4.1.1 -D OPENCV_GENERATE_PKGCONFIG=YES Execute $ sudo ldconfig -v Build and run the sample ~/gst_cv_gpumat$ CUDA_VER=10.0 make Compiling: gs…