High Glass-to-Glass latency in Nvidia AGX Orin

Robotics & Edge Computing Jetson Systems Jetson AGX Orin
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Hi Nvidia Team,

We are using Nvidia AGX Orin Development Kit (64 GB) along with e-CAM82_CUOAGX (IMX485) camera module.

& getting ~100 ms glass-to-glass latency.

Setup:
Nvidia AGX Orin Development Kit (64 GB) + e-CAM82_CUOAGX (4-lane CSI)

=> sudo nvpmodel -m 0
=> sudo jetson_clocks
=> sudo ./max-isp-vi-clks.sh

GStreamer Pipeline:
gst-launch-1.0 nvarguscamerasrc ! ‘video/x-raw(memory:NVMM), width=(int)3840, height=(int)2160, format=(string)NV12, framerate=(fraction)30/1’ ! queue ! nv3dsink sync = false

We have also tried with v4l2-ctl (low_latency_mode = 1), But with that framerate is dropped to 30fps.

Is there any other optimization to be made to reduce this latency to the lowest possible?

Our requirement to is get around ~30 - 40ms of glass-to-glass latency.
Please suggest possible steps to reduce this latency.

Additionally could anyone please answer the below queries?

  1. what is the expected latency of nvarguscamerasrc element?
  2. what impact does low_latency_mode bring & why framerate is dropped after some time in this mode.

Thanks & Regards,
Kaushal

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hello kaushal.dekivadia,

it looks it’s already close to our G2G latency evaluation. please see-also Topic 273184.

FYI,
this flag only works for TX2 and before. it doesn’t works with Orin’s VI driver. (i.e. vi5_fops.c)

you may consider other approach as it’s not doable via nvarguscamerasrc plugin.

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Hi Jerry,

Thanks for your prompt reply.

Is there anything that we can change in the nvarguscamerasrc code so that it can reduce the buffer time?
or can we disable 3A in nvarguscamerasrc?

As latency is very critical in our product and we know that Nvidia Jetson Orin should be capable of that.

can you please share any other approach that we can get reduce latency with the IMX485 camera module (RAW10 Bayer)?

Thanks & Regards,
Kaushal

6

hello kaushal.dekivadia,

FYI, 100ms is expected glass-to-glass latency.
you may try below sample for getting frame data earlier, but, it’ll consumes GPU resources to demosaic.
for instance, /usr/src/jetson_multimedia_api/argus/samples/cudaBayerDemosaic

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