Hello,
I am trying to make a custom docker image for the mpv video player application on jetson nano.
Here is the docker file which built the image…
Dockerfile (3.0 KB)
When I run as follows,
docker run --rm --privileged --runtime=nvidia -e DISPLAY=unix$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix -v /dev:/dev -v /run:/run -v /etc/machine-id:/etc/machine-id --ipc=host --device /dev/dri --group-add video mpv-nvmpi-nvv4l2dec
docker: Error response from daemon: OCI runtime create failed: json: cannot unmarshal object into Go struct field Process.capabilities of type string: unknown.
Hi @rreddy78, does it work if you remove the FROM docker.io/arm64v8/ubuntu:bionic statement from your Dockerfile? Also, is the version of L4T that you are running indeed L4T R32.5.1? You can check this with cat /etc/nv_tegra_release
Can you also check that you can run the l4t-base container as expected with this command?
sudo docker run -it --rm --net=host --runtime nvidia nvcr.io/nvidia/l4t-base:r32.5.1
Yes.
cat /etc/nv_tegra_release# R32 (release), REVISION: 5.1, GCID: 26202423, BOARD: t210ref, EABI: aarch64, DATE: Fri Feb 19 16:45:52 UTC 2021
sudo docker run -it --rm --net=host --runtime nvidia nvcr.io/nvidia/l4t-base:r32.5.1
[sudo] password for rreddy78:
Unable to find image ‘nvcr.io/nvidia/l4t-base:r32.5.1’ locally
docker: Error response from daemon: manifest for nvcr.io/nvidia/l4t-base:r32.5.1 not found: manifest unknown: manifest unknown.
See ‘docker run --help’.
Initially I didnt have the nvcr.io line and it built correctly. So for some reason its unable to find the nvcr
Woops, sorry I should have said nvcr.io/nvidia/l4t-base:r32.5.0 instead.
L4T R32.5.1 uses the same l4t-base container as R32.5.0, because there weren’t changes to the BSP between those releases of L4T. So try nvcr.io/nvidia/l4t-base:r32.5.0 instead (even if you are on R32.5.1 in this case). You would also want to change this to r32.5.0 in your Dockerfile.
Yes. indeed this time it downloads correctly, but there is still an error as follows
sudo docker run -it --rm --net=host --runtime nvidia nvcr.io/nvidia/l4t-base:r32.5.0
docker: Error response from daemon: OCI runtime create failed: flag provided but not defined: -console-socket: unknown.
Also one more Qn: Do I or do i not need the FROM docker.io/arm64v8/ubuntu:bionic line ?
If i remove the --runtime=nvidia then it fails with missing libraries
docker run --rm --privileged -e DISPLAY=unix$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix -v /dev:/dev -v /run:/run -v /etc/machine-id:/etc/machine-id --ipc=host --device /dev/dri --group-add video mpv-nvmpi-nvv4l2dec
/usr/bin/mpv: error while loading shared libraries: libnvbuf_utils.so.1.0.0: cannot open shared object file: No such file or directory.
You don’t need that line. You should just have FROM nvcr.io/nvidia/l4t-base:r32.5.0
It seems there is something corrupted or messed up with your docker runtimes. Usually the easiest / most sure-fire way to fix this would be to reflash your SD card. If you don’t want to do that, you can try uninstalling/re-installing the nvidia-container packages:
sudo dpkg-query -l | grep nvidia
ii libnvidia-container-tools 0.9.0~beta.1 arm64 NVIDIA container runtime library (command-line tools)
ii libnvidia-container0:arm64 0.9.0~beta.1 arm64 NVIDIA container runtime library
ii nvidia-container-csv-cuda 10.2.89-1 arm64 Jetpack CUDA CSV file
ii nvidia-container-csv-cudnn 8.0.0.180-1+cuda10.2 arm64 Jetpack CUDNN CSV file
ii nvidia-container-csv-tensorrt 7.1.3.0-1+cuda10.2 arm64 Jetpack TensorRT CSV file
ii nvidia-container-csv-visionworks 1.6.0.501 arm64 Jetpack VisionWorks CSV file
ii nvidia-container-runtime 3.1.0-1 arm64 NVIDIA container runtime
ii nvidia-container-toolkit 1.0.1-1 arm64 NVIDIA container runtime hook
ii nvidia-docker2
Thanks for the suggestion. Reinstalling did not solve it. Also I see errors in dockerd for the same reason.
What exactly does -console-socket unknown means here in this context ?
rreddy78@jetson-nano:~$ sudo systemctl status docker.service
● docker.service - Docker Application Container Engine
Loaded: loaded (/lib/systemd/system/docker.service; disabled; vendor preset: enabled)
Active: active (running) since Sat 2021-03-27 08:55:44 IST; 4min 32s ago
Docs: https://docs.docker.com
Main PID: 10989 (dockerd)
Tasks: 25
CGroup: /system.slice/docker.service
└─10989 /usr/bin/dockerd -H fd:// --containerd=/run/containerd/containerd.sock
Mar 27 08:55:44 jetson-nano systemd[1]: Started Docker Application Container Engine.
Mar 27 08:55:45 jetson-nano dockerd[10989]: time="2021-03-27T08:55:45.084708892+05:30" level=error msg="stream copy error: reading from a closed fifo"
Mar 27 08:55:45 jetson-nano dockerd[10989]: time="2021-03-27T08:55:45.169028188+05:30" level=error msg="6fd85380a816a522f5735a49fb5d0540709c803c57addbf21dadc4523640f14
Mar 27 08:55:45 jetson-nano dockerd[10989]: time="2021-03-27T08:55:45.194686837+05:30" level=error msg="Handler for POST /v1.40/containers/6fd85380a816a522f5735a49fb5d
Mar 27 08:55:50 jetson-nano dockerd[10989]: time="2021-03-27T08:55:50.714210147+05:30" level=error msg="stream copy error: reading from a closed fifo"
Mar 27 08:55:50 jetson-nano dockerd[10989]: time="2021-03-27T08:55:50.799201937+05:30" level=error msg="5820be743b074e8ab4970b1e7d331f71092a43d3924b922db50e399eabc2537
Mar 27 08:55:50 jetson-nano dockerd[10989]: time="2021-03-27T08:55:50.823934967+05:30" level=error msg="Handler for POST /v1.40/containers/5820be743b074e8ab4970b1e7d33
Mar 27 08:56:17 jetson-nano dockerd[10989]: time="2021-03-27T08:56:17.141412383+05:30" level=error msg="stream copy error: reading from a closed fifo"
Mar 27 08:56:17 jetson-nano dockerd[10989]: time="2021-03-27T08:56:17.221597031+05:30" level=error msg="a8b8aac49527c7a88a4cc63fd593010c5cef4abcc917790f58e0f01c82b6716
Mar 27 08:56:17 jetson-nano dockerd[10989]: time="2021-03-27T08:56:17.263620751+05:30" level=error msg="Handler for POST /v1.40/containers/a8b8aac49527c7a88a4cc63fd593
When I remove the -it flag there is a different error:
sudo docker run --rm --net=host --runtime nvidia nvcr.io/nvidia/l4t-base:r32.5.0
docker: Error response from daemon: OCI runtime create failed: json: cannot unmarshal object into Go struct field Process.capabilities of type string: unknown.
Hi @rreddy78, I’m not sure what that error means, I haven’t seen it before. At this point I recommend backing up your work and re-flashing your SD card with a fresh JetPack image.
Ok. So now I try this after a fresh install (and a Ubuntu 20.04 at that) and its working!
Needed a bit of work to get it working, but mpv is running file in the Docker alright including HW decoding and sound.
Only issue with Docker running is this:
A host directory needs to be bound into the container with the same path and only then will the drag and drop work.
Here I attach the Docker file :
Dockerfile (3.1 KB)
Sample run command is this:
cat run-mpv-docker.sh
xhost +
docker run -it --net=host --ipc=host --privileged --runtime nvidia -e DISPLAY=$DISPLAY -e DBUS_SESSION_BUS_ADDRESS=$DBUS_S
ESSION_BUS_ADDRESS -v $XDG_RUNTIME_DIR:$XDG_RUNTIME_DIR -v /tmp/.X11-unix:/tmp/.X11-unix -v /dev:/dev -v /run:/run -v /home/
docker_tmp:/home/docker_tmp -v /etc/machine-id:/etc/machine-id --device /dev/snd --device /dev/nvhost-nvdec --group-add vid
eo rreddy78/mpv-docker:latest
A Docker file for the vlc:
Dockerfile (4.9 KB)