VPI 1.2 very slow to download image from GPU - any tips?

Hello, I am trying to warp two 1080p images using the GPU, then pass them to another non-gpu function

Currently the VPI .cpu function is very slow and does not give me access to results in realtime (able to inspect array), this is taking about 50ms for 2 images - which is slower than openCV cuda

Can I have some advice on how to speed this up so I can process images in realtime?

thank you

cv_backend = vpi.Backend.CUDA

img = cap.read()
img2 = cap2.read()

with cv_backend:
** frame1 = vpi.asimage(img[0:1080, 0:1920,:])**
** frame2 = vpi.asimage(img2[0:1080, 0:1920,:])**

with cv_backend:
** output1 = frame1.perspwarp(hom)**
** output2 = frame2.perspwarp(hom)**

with output1.rlock(), output2.rlock():
** plop1=output1.cpu()**
** plop2=output2.cpu()**

Hi,

Have you maximized the device performance already?
You can find the script to boost VPI performance below:
https://docs.nvidia.com/vpi/algo_performance.html#maxout_clocks

Thanks.

Hello, I just tried that and it didn’t effect the processing time. I was incorrect its actually 70ms for the output to CPU stage, not 50ms as I originally stated

I have the same problem. With CUDA backend, calling VPI.Image.cpu() took ~50ms. Any ideas to improve it?

Hi,

Is the 70ms only used for downloading the output to the CPU?
Or it also includes the time that does the perspective warping?

Thanks.

Hi AastaLLL, I have had to move on to the Xavier for our production (same code), but yes was 50ms-70ms just for the CPU output - I forgot to mention its for 2 images being locked for CPU access being timed here not for 1 - but 25ms+ is still not realtime for us. I still have the Nano set up if there is anything else we can try but if this is a limit of the hardware we can move on

image

I’m closing this topic due to there is no update from you for a period, assuming this issue was resolved.
If still need the support, please open a new topic. Thanks

Hi,

Does the same issue occur on Xavier?

Thanks

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