Jetson Nano - Using Pi NoIR camera V2 with the detectnet-camera example shuts down the board

I have a Jetson Nano board, and I want to run the Live Object Detection through the Camera feed.

I am following this guide:

https://github.com/dusty-nv/jetson-inference/blob/master/docs/detectnet-camera-2.md

The various examples of detectnet-console works just fine. But when I run the detectnet-camera for the first time, the framerate was super slow, UI indicates 1fps but I suspect it to be slower than that because it wasn’t registering any movements until much later.

And I had to eventually shut it down and let it rest, but when I tried detectnet-camera again, it just turned to the board off.

Now, I’m not sure how to proceed. I was really looking forward to making the object detection and the human pose estimation work. But it seems like I am stopped even before I get to start.

Are you able to run the live image recognition (imagenet-camera) first? Or do you only have problem with detectnet-camera?

Also, to check there are no problems with camera feed, please try running nvgstcapture viewer beforehand.

If the board powers off, try running “sudo nvpmodel -m 1” to set it in 5W mode. If it doesn’t shut down any more after that, this would point to a power supply issue.

imagenet-camera works well. I was getting around 15FPS, but when I tried to run detectnet-camera, I think it hanged/taking a really long time to process images.

I’ve also ran “nvgstcapture”, and it shows the feed just fine.

When I inspect the logs of both imagenet-camera and detectnet-camera, there’s a line that’s distinctly different:

with imagenet-camera:

imagenet-camera: camera open for streaming
GST_ARGUS: Creating output stream

with detectnet-camera:

detectnet-camera: failed to capture frame
detectnet-camera: failed to convert from NV12 to RGBA

EDIT:
Okay this is rather odd. After rebooting the Jetson Nano, and still using a 5V 2A Samsung Charger, imagenet-camera ran at 15fps, and then detectnet-camera ran at 5fps. The camera feed was decent, but the detection was lagging behind. I’m not sure what exactly changed here but it’s working now…