DLI "Getting Started with AI on Jetson Nano" Course Environment Container question

Autonomous Machines Jetson & Embedded Systems Jetson Nano
#1

Hello,all .
I am a fresh to Jetson Nano and I am following the course of Getting Started with AI then I am doing the Download Docker And Start JupyterLab.
but I have a problem that stop my going on
after I input :

sudo docker run --runtime nvidia -it --rm --network host
–volume ~/nvdli-data:/nvdli-nano/data
–device /dev/video0
nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.4.4

it shows error : Error response from daemon: OCI runtime create failed: container_linux.go:349: starting container process caused “process_linux.go:449: container init caused “process_linux.go:432: running prestart hook 0 caused \“error running hook: exit status 1, stdout: , stderr: exec command: [/usr/bin/nvidia-container-cli --load-kmods configure --ldconfig=@/sbin/ldconfig.real --device=all --compute --compat32 --graphics --utility --video --display --pid=14372 /var/lib/docker/overlay2/f2fa6a5ca1a7130a24b0a24ebbc38c8340437718ca5ed3e2a6aad2a125152c65/merged]\\nnvidia-container-cli: mount error: file creation failed: /var/lib/docker/overlay2/f2fa6a5ca1a7130a24b0a24ebbc38c8340437718ca5ed3e2a6aad2a125152c65/merged/usr/lib/libvisionworks.so: file exists\\n\”””: unknown

Does anyone can help me ? thanks very much .

#2

Hello all,
I have an error at a similar point of the setup (I’m using the rasperry camera):

after ```
echo “sudo docker run --runtime nvidia -it --rm --network host
–volume ~/nvdli-data:/nvdli-nano/data
–device /dev/video0
nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.4.4” > docker_dli_run.sh
chmod +x docker_dli_run.sh
./docker_dli_run.sh

I got the message:
 "docker: Error response from daemon: error gathering device information while adding custom device "/dev/video0": no such file or directory."

Does anybody have an idea? Many thanks in advance!
#3

Hi @qys1988, do you know which version of JetPack you flashed your Nano with? On your Jetson can you run cat /etc/nv_tegra_release. That version reported should be the same as the L4T version in the container’s tag. For example, currently you are trying to run the JetPack 4.4.1 container.

#4

Hi @maxeuropa, first can you confirm that you get a camera feed outside of the container? If you have a display attached to your Jetson, you can run nvgstcapture-1.0, and it should show the camera feed.

If you run ls /dev/video* does it show any devices? If not, than your CSI camera is probably not being detected.

Also, you don’t need to mount a /dev/video device for CSI camera, instead you should have this line:

-v /tmp/argus_socket:/tmp/argus_socket
1 Like
#5

thank you, dusty_nv! It doesn’t detect the camera - seems to be a hardware issue from the cable or camera or so… however, when I’m neglecting the camera line, the container with Jupyter starts.

#6

I have another question: I startet the docker without the video line (because I have to have problems with the hardware). In the JupyterLab File Browser, I can only find the files of the first tutorial, not of the course “Getting Started with DeepStream for Video Analytics on Jetson Nano”
Can you tell me, how I can get the files from this course? (I accessed the JupyterLab from this course).

#7

Thanks @dusty_nv
I do as you said it shows:
R32 (release), REVISION: 3.1, GCID: 18186506, BOARD: t210ref, EABI: aarch64, DATE: Tue Dec 10 06:58:34 UTC 2019

#8

Hi @maxeuropa, “Getting Started with DeepStream for Video Analytics on Jetson Nano” is a different DLI course with it’s own contents. I believe the DeepStream course is using it’s own SD card image. You would download it through the DLI course page.

#9

OK thanks @qys1988, you are running JetPack 4.3 (L4T R32.3.1). To run this container, you need to use JetPack 4.4 or newer. I recommend that you re-flash your SD card with the latest JetPack 4.4.1 image found here:

After flashing JetPack 4.4.1 (L4T R32.4.4), you will be able to run this container:

nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.4.4

#10

Thanks very much @dusty_nv
I have solved the problem as you said . That is very helpful for me .