Jetson Nano Youtube Tutorial Failing

🤝 Community Help
1

I’ve been following the “set up inference server” roboflow tutorial (X9jt8qb_igo) to the letter, trying to get local inferencing from a roboflow model working on the jetson nano dev kit.

I setup things OK on the jetson nano 4GB using JetPack 4.6.1, and have the local inference server running on the jetson with docker with the following command:

docker run --net=host --gpus all roboflow/inference-server:jetson

The server appears to run OK. In another terminal, I’m trying to run a test inference on a local image using the following command (from the tutorial):

base64 1689278366.jpg | curl -d @- “http://127.0.0.1:9001/jsi/8?api_key=VLOziA70pvIDNWDTQ66H”

Initially, on the device I see that it can load the model OK, but then I get an impassable error.

image.png

Can someone please assist with this issue or attempt to reproduce it? As-is, the getting started tutorial does not work out of the box as a result with the jetson nano.

2

Might be connected to my issue?

3

Hey, @Charles_Modrich, sorry to hear of the troubles. Which tutorial are you following? Is it this YouTube video?

4

@josephofiowa

Charlie’s team member here. Yes, that video and blog post / how-to.

Since the image of the error doesn’t seem to be working on the original post:

image-4
image-4926Ă—88 5.98 KB

5

Hi Joesph! Any thoughts on this one? Happy to test with your team to update the documentation for others.

6

@NickJSI As mentioned above, your issue might be the same as ours. You got the same error message we got when following the written docs on a Jetson Nano trying to deploy Roboflow 3.0 models.

According to the answer of @Paul (Error deploying custom trained model on NVIDIA Jetson Xavier - #15 by Paul) you could follow the new documentation (NVIDIA Jetson - Roboflow Docs), but I have bumped into quota issues that might be also the case for you and will require someone from roboflow to solve.

7

Wanted to update this thread that there are new docs and new Jetson images that should resolve this issue.

Docs:

New Docker Images: