Thanks so much,
Except the memory copy, another concern is OpenCV is CPU-based framework and would be better to use platforms with better CPU capability.
Ok you right the opencv is CPU base, but the main processing is done in GPU.
1- In the above workflow of deepstream, As you see, the Batching of Images is done on CPU before feed to DNN, So, we need to copy from GPU memory into CPU memory, right? I want to know, What’s main difference between above workflow and opencv solution? In both solution, we need copied the decoded of images into CPU, and then do process.
You right the opencv has coping data from GPU mem to CPU mem, that’s bottleneck, but In the deepstream has also Coping GPU mem into CPU mem before feeded into DNN.
No, it means the element can do video/x-raw to video/x-
raw(memory:NVMM) or video/x-raw(memory:NVMM) to video/x-raw conversion.
2- Conversion from video/x-raw(memory:NVMM) to video/x-raw is occurred from GPU memory into CPU memory?
3- Jetson nano has capability of encoding 8-1080 @3O fps, I want to know is it possible to encode 16-1080 @15 fps?