@simon_dg posted a new topic, subject "Docker libv4l2: error getting capabilities". It read:

   #  Docker libv4l2: error getting capabilities
    
      * **Hardware Platform (Jetson / GPU)**
    
        * Ubuntu 18.04
    
        * Jetpack 4.6.1 R32.7.1
    [code]         cat /etc/nv_tegra_release
            R32 (release), REVISION: 7.1, GCID: 29818004, BOARD: t186ref, EABI: aarch64, DATE: Sat Feb 19 17:07:00 UTC 202
            
    [/code]
    
      * **Issue Type: bug**
    
    Running a GStreamer decoding pipeline fails in docker but succeeds on the host.
    
    The following GStreamer pipeline, decodes a h264 stream and saves it to the local file system.
    
    On the host it seems to work flawless
    [code]     $ gst-launch-1.0 videotestsrc num-buffers=100 ! 'video/x-raw, format=UYVY, width=1920, height=1080, framerate=60/1' ! nvvidconv ! 'video/x-raw(memory:NVMM), format=NV12' ! nvv4l2h264enc ! 'video/x-h264, stream-format=(string)byte-stream' ! h264parse ! nvv4l2decoder ! filesink location=/tmp/h264.test
        Setting pipeline to PAUSED ...
        Opening in BLOCKING MODE
        Opening in BLOCKING MODE
        Pipeline is PREROLLING ...
        NvMMLiteOpen : Block : BlockType = 261
        NVMEDIA: Reading vendor.tegra.display-size : status: 6
        NvMMLiteBlockCreate : Block : BlockType = 261
        Redistribute latency...
        NvMMLiteOpen : Block : BlockType = 4
        ===== NVMEDIA: NVENC =====
        NvMMLiteBlockCreate : Block : BlockType = 4
        H264: Profile = 66, Level = 0
        
    [/code]
    
    When we try to run the same pipeline in the l4t-base container the library files aren't loaded properly. The pipeline fails and reports it isn't able query the decoding device capabilities.
    [code]     docker run --rm --network=host --runtime=nvidia --privileged  nvcr.io/nvidia/l4t-base:r32.7.1  gst-launch-1.0 videotestsrc num-buffers=100 ! 'video/x-raw, format=UYVY, width=1920, height=1080, framerate=60/1' ! nvvidconv ! 'video/x-raw(memory:NVMM), format=NV12' ! nvv4l2h264enc ! 'video/x-h264, stream-format=(string)byte-stream' ! h264parse ! nvv4l2decoder ! filesink location=/tmp/h264.test
        (Argus) Error FileOperationFailed: Connecting to nvargus-daemon failed: No such file or directory (in src/rpc/socket/client/SocketClientDispatch.cpp, function openSocketConnection(), line 205)
        (Argus) Error FileOperationFailed: Cannot create camera provider (in src/rpc/socket/client/SocketClientDispatch.cpp, function createCameraProvider(), line 106)
        Setting pipeline to PAUSED ...
        Failed to query video capabilities: Inappropriate ioctl for device
        libv4l2: error getting capabilities: Inappropriate ioctl for device
        ERROR: Pipeline doesn't want to pause.
        ERROR: from element /GstPipeline:pipeline0/nvv4l2decoder:nvv4l2decoder0: Error getting capabilities for device '/dev/nvhost-nvdec': It isn't a v4l2 driver. Check if it is a v4l1 driver.
        Additional debug info:
        /dvs/git/dirty/git-master_linux/3rdparty/gst/gst-v4l2/gst-v4l2/v4l2_calls.c(97): gst_v4l2_get_capabilities (): /GstPipeline:pipeline0/nvv4l2decoder:nvv4l2decoder0:
        system error: Inappropriate ioctl for device
        Setting pipeline to NULL ...
        Freeing pipeline ...
        
    [/code]
    
    When we run the same command with a `sleep 1 &&` it does seem to work properly, why does this approach solve the previous issue? We would like to avoid running the container in this way, is this a possibility?
    [code]     docker run --rm --network=host --runtime=nvidia --privileged  nvcr.io/nvidia/l4t-base:r32.7.1 sleep 1 &&   gst-launch-1.0 videotestsrc num-buffers=100 ! 'video/x-raw, format=UYVY, width=1920, height=1080, framerate=60/1' ! nvvidconv ! 'video/x-raw(memory:NVMM), format=NV12' ! nvv4l2h264enc ! 'video/x-h264, stream-format=(string)byte-stream' ! h264parse ! nvv4l2decoder ! filesink location=/tmp/h264.test
        Setting pipeline to PAUSED ...
        Opening in BLOCKING MODE
        Opening in BLOCKING MODE
        Pipeline is PREROLLING ...
        NvMMLiteOpen : Block : BlockType = 261
        NVMEDIA: Reading vendor.tegra.display-size : status: 6
        NvMMLiteBlockCreate : Block : BlockType = 261
        Redistribute latency...
        NvMMLiteOpen : Block : BlockType = 4
        ===== NVMEDIA: NVENC =====
        NvMMLiteBlockCreate : Block : BlockType = 4
        H264: Profile = 66, Level = 0
        ^Chandling interrupt.
        Interrupt: Stopping pipeline ...
        ERROR: pipeline doesn't want to preroll.
        Setting pipeline to NULL ...
        
    [/code]

To which @ward.van.driessche (Ward Van Driessche) replied

    Noticed a very similar issue. Any updates?

Then @Amycao said

    The second command, the last part gst command actually run on your host, not within container.  
    docker run --rm --network=host --runtime=nvidia --privileged nvcr.io/nvidia/l4t-base:r32.7.1 sleep 1 && gst-launch-1.0 videotestsrc num-buffers=100 ! ‘video/x-raw, format=UYVY, width=1920, height=1080, framerate=60/1' ! nvvidconv ! ‘video/x-raw(memory:NVMM), format=NV12' ! nvv4l2h264enc ! ‘video/x-h264, stream-format=(string)byte-stream' ! h264parse ! nvv4l2decoder ! filesink location=/tmp/h264.test

After which, @Amycao added

    Please use docker container based on compatible JP version and DS version.  
    https://docs.nvidia.com/metropolis/deepstream/6.0.1/dev-guide/text/DS_docker_containers.html#a-docker-container-for-jetson

@simon_dg replied

    Hi @Amycao , Running the pipeline with the deepstream-l4t:6.0.1-base image results in the same issue.
    [code] 
        (Argus) Error FileOperationFailed: Connecting to nvargus-daemon failed: No such file or directory (in src/rpc/socket/client/SocketClientDispatch.cpp, function openSocketConnection(), line 205)
        
        (Argus) Error FileOperationFailed: Cannot create camera provider (in src/rpc/socket/client/SocketClientDispatch.cpp, function createCameraProvider(), line 106)
        
        (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.940: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_deepstream_bins.so': libnvparsers.so.8: cannot open shared object file: No such file or directory
        
        (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.958: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_inferaudio.so': libcufft.so.10: cannot open shared object file: No such file or directory
        
        (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.962: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_infer.so': libnvparsers.so.8: cannot open shared object file: No such file or directory
        
        (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.970: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_udp.so': librivermax.so.0: cannot open shared object file: No such file or directory
        
        (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.985: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_inferserver.so': libtritonserver.so: cannot open shared object file: No such file or directory
        
        (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:43.037: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_osd.so': libnvinfer.so.8: cannot open shared object file: No such file or directory
        
        Setting pipeline to PAUSED ...
        
        Failed to query video capabilities: Inappropriate ioctl for device
        
        libv4l2: error getting capabilities: Inappropriate ioctl for device
        
        ERROR: Pipeline doesn't want to pause.
        
        ERROR: from element /GstPipeline:pipeline0/nvv4l2decoder:nvv4l2decoder0: Error getting capabilities for device '/dev/nvhost-nvdec': It isn't a v4l2 driver. Check if it is a v4l1 driver.
        
        Additional debug info:
        
        /dvs/git/dirty/git-master_linux/3rdparty/gst/gst-v4l2/gst-v4l2/v4l2_calls.c(97): gst_v4l2_get_capabilities (): /GstPipeline:pipeline0/nvv4l2decoder:nvv4l2decoder0:
        
        system error: Inappropriate ioctl for device
        
        Setting pipeline to NULL ...
        
        Freeing pipeline `...`
        
        
    [/code]

So @Amycao replied

    simon_dg:
    
    > 
    [code]
    >     (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.940: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_deepstream_bins.so': libnvparsers.so.8: cannot open shared object file: No such file or directory
    >     
    >     (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.958: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_inferaudio.so': libcufft.so.10: cannot open shared object file: No such file or directory
    >     
    >     (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.962: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_infer.so': libnvparsers.so.8: cannot open shared object file: No such file or directory
    >     
    >     (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.970: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_udp.so': librivermax.so.0: cannot open shared object file: No such file or directory
    >     
    >     (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:42.985: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_inferserver.so': libtritonserver.so: cannot open shared object file: No such file or directory
    >     
    >     (gst-plugin-scanner:21): GStreamer-WARNING **: 07:58:43.037: Failed to load plugin '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_osd.so': libnvinfer.so.8: cannot open shared object file: No such file or directory
    >     
    [/code]
    
    Can you find the library libnvinfer.so.8, libnvparsers.so.8, libcufft.so.10 within container?

To which @simon_dg replied

    @Amycao  
    The library files are not available within the container
    [code] 
        nvidia-docker run --network=host -it --runtime=nvidia nvcr.io/nvidia/deepstream-l4t:6.0.1-base /bin/bash
        
        /opt/nvidia/deepstream/deepstream-6.0# find / -name libnvinfer.so.8
        
        /opt/nvidia/deepstream/deepstream-6.0# find / -name libnvparsers.so.8
        
        /opt/nvidia/deepstream/deepstream-6.0# find / -name libcufft.so.10
        
        
    [/code]
    
    On the host I do find the files, stored on the following paths:
    [code] 
        /usr/local/cuda-10.2/targets/aarch64-linux/lib/libcufft.so.10
        
        /usr/lib/aarch64-linux-gnu/libnvparsers.so.8
        
        /usr/lib/aarch64-linux-gnu/libnvinfer.so.8
        
    [/code]

To which @Amycao replied

    How about this?  
    docker run --network=host -it --runtime=nvidia nvcr.io/nvidia/deepstream-l4t:6.0.1-base /bin/bash

To which @ward.van.driessche (Ward Van Driessche) replied

    Cannot find those files either:
    [code] 
        $ docker run --network=host -it --runtime=nvidia nvcr.io/nvidia/deepstream-l4t:6.0.1-base /bin/bash
        /opt/nvidia/deepstream/deepstream-6.0# find / -name libnvinfer.so.8
        /opt/nvidia/deepstream/deepstream-6.0# find / -name libnvparsers.so.8
        /opt/nvidia/deepstream/deepstream-6.0# find / -name libcufft.so.10
        
    [/code]

Then @simon_dg said

    Any updates?

So @Amycao replied

    How about your docker version?  
    dpkg -l|grep docker

To which @ward.van.driessche (Ward Van Driessche) replied

    [code]
        ii  docker                                     1.5-1build1                                arm64        System tray for KDE3/GNOME2 docklet applications
        ii  docker.io                                  20.10.7-0ubuntu5~18.04.3                   arm64        Linux container runtime
        ii  nvidia-docker2                             2.11.0-1                                   all          nvidia-docker CLI wrapper
        
    [/code]

After which, @Amycao added

    This comes with JP 4.6.1. please run nvidia-docker run --rm -it IMAGE ID, if not work, please try to reinstall it to see if works.  
    ubuntu@ubuntu-All-Series:~/Downloads/nvidia/sdkm_downloads$ ls |grep -E ‘container|docker'  
    libnvidia-container0_0.10.0+jetpack_arm64.deb  
    libnvidia-container1_1.7.0-1_arm64.deb  
    libnvidia-container-tools_1.7.0-1_arm64.deb  
    nvidia-container-csv-cuda_10.2.460-1_arm64.deb  
    nvidia-container-csv-cudnn_30.255.87.135-1+cuda10.2_arm64.deb  
    nvidia-container-csv-tensorrt_30.255.87.135-1+cuda10.2_arm64.deb  
    nvidia-container-csv-visionworks_30.170-34-9794_arm64.deb  
    nvidia-container-runtime_3.7.0-1_all.deb  
    nvidia-container-toolkit_1.7.0-1_arm64.deb  
    nvidia-docker2_2.8.0-1_all.deb

So @ward.van.driessche (Ward Van Driessche) replied

    Hi Amycao. Could you please provide instructions on how to reinstall `nvidia-docker` instead of listing your downloads?

@ward.van.driessche (Ward Van Driessche) replied

    I have downloaded
    
      * `https://repo.download.nvidia.com/jetson/common/pool/main/n/nvidia-container-toolkit/nvidia-container-toolkit_1.7.0-1_arm64.deb`
    
      * `https://repo.download.nvidia.com/jetson/common/pool/main/n/nvidia-docker2/nvidia-docker2_2.8.0-1_all.deb`
    
    
    
    
    And installed both with `sudo dpkg -i <.deb>` and now everything seems to work but I don't understand how. Could you read through the steps below?
    
    Steps to reproduce:
    
      * 
    
    [code] 
        $ sudo apt-get autoremove nvidia-container-toolkit
        Reading package lists... Done
        Building dependency tree
        Reading state information... Done
        The following packages will be REMOVED:
          nvidia-container-runtime nvidia-container-toolkit nvidia-container-toolkit-base nvidia-docker2
        0 upgraded, 0 newly installed, 4 to remove and 162 not upgraded.
        After this operation, 9.654 kB disk space will be freed.
        Do you want to continue? [Y/n] y
        (Reading database ... 178374 files and directories currently installed.)
        Removing nvidia-container-runtime (3.11.0-1) ...
        Removing nvidia-docker2 (2.11.0-1) ...
        Removing nvidia-container-toolkit (1.11.0-1) ...
        Removing nvidia-container-toolkit-base (1.11.0-1) ...
        
    [/code]
    
      * 
    
    [code] 
        $ sudo dpkg -i nvidia-container-toolkit_1.7.0-1_arm64.deb
        Selecting previously unselected package nvidia-container-toolkit.
        (Reading database ... 178355 files and directories currently installed.)
        Preparing to unpack nvidia-container-toolkit_1.7.0-1_arm64.deb ...
        Unpacking nvidia-container-toolkit (1.7.0-1) ...
        Setting up nvidia-container-toolkit (1.7.0-1) ...
        Installing new version of config file /etc/nvidia-container-runtime/config.toml ...
        
    [/code]
    
      * 
    
    [code] 
        $ sudo dpkg -i nvidia-docker2_2.8.0-1_all.deb
        Selecting previously unselected package nvidia-docker2.
        (Reading database ... 178361 files and directories currently installed.)
        Preparing to unpack nvidia-docker2_2.8.0-1_all.deb ...
        Unpacking nvidia-docker2 (2.8.0-1) ...
        Setting up nvidia-docker2 (2.8.0-1) ...
        
    [/code]
    
      * Checking versions:
    
    
    [code] 
        $ dpkg -l|grep -E 'container|docker'
        ii  containerd                                 1.5.5-0ubuntu3~18.04.1                     arm64        daemon to control runC
        ii  docker                                     1.5-1build1                                arm64        System tray for KDE3/GNOME2 docklet applications
        ii  docker.io                                  20.10.7-0ubuntu5~18.04.3                   arm64        Linux container runtime
        ii  libavformat57:arm64                        7:3.4.8-0ubuntu0.2                         arm64        FFmpeg library with (de)muxers for multimedia containers - runtime files
        ii  libkf5wallet-bin                           5.44.0-0ubuntu1                            arm64        Secure and unified container for user passwords.
        ii  libkf5wallet-data                          5.44.0-0ubuntu1                            all          Secure and unified container for user passwords.
        ii  libkf5wallet5:arm64                        5.44.0-0ubuntu1                            arm64        Secure and unified container for user passwords.
        ii  libkwalletbackend5-5:arm64                 5.44.0-0ubuntu1                            arm64        Secure and unified container for user passwords.
        ii  libmatroska6v5:arm64                       1.4.8-1.1                                  arm64        extensible open standard audio/video container format (shared library)
        ii  libnvidia-container-tools                  1.11.0-1                                   arm64        NVIDIA container runtime library (command-line tools)
        ii  libnvidia-container0:arm64                 0.10.0+jetpack                             arm64        NVIDIA container runtime library
        ii  libnvidia-container1:arm64                 1.11.0-1                                   arm64        NVIDIA container runtime library
        ii  nvidia-container-csv-cuda                  10.2.460-1                                 arm64        Jetpack CUDA CSV file
        ii  nvidia-container-csv-cudnn                 30.255.87.135-1+cuda10.2                        arm64        Jetpack CUDNN CSV file
        ii  nvidia-container-csv-tensorrt              30.255.87.135-1+cuda10.2                         arm64        Jetpack TensorRT CSV file
        ii  nvidia-container-csv-visionworks           30.170-34-9794                                  arm64        Jetpack VisionWorks CSV file
        ii  nvidia-container-toolkit                   1.7.0-1                                    arm64        NVIDIA container runtime hook
        rc  nvidia-container-toolkit-base              1.11.0-1                                   arm64        NVIDIA Container Toolkit Base
        ii  nvidia-docker2                             2.8.0-1                                    all          nvidia-docker CLI wrapper
        
    [/code]
    
      * Testing pipeline (working):
    
    
    [code] 
        $ docker run --rm --network=host --runtime=nvidia --privileged  nvcr.io/nvidia/l4t-base:r32.7.1  gst-launch-1.0 videotestsrc num-buffers=100 ! 'video/x-raw, format=UYVY, width=1920, height=1080, framerate=60/1' ! nvvidconv ! 'video/x-raw(memory:NVMM), format=NV12' ! nvv4l2h264enc ! 'video/x-h264, stream-format=(string)byte-stream' ! h264parse ! nvv4l2decoder ! filesink location=/tmp/h264.test
        (Argus) Error FileOperationFailed: Connecting to nvargus-daemon failed: No such file or directory (in src/rpc/socket/client/SocketClientDispatch.cpp, function openSocketConnection(), line 205)
        (Argus) Error FileOperationFailed: Cannot create camera provider (in src/rpc/socket/client/SocketClientDispatch.cpp, function createCameraProvider(), line 106)
        Setting pipeline to PAUSED ...
        Opening in BLOCKING MODE
        Opening in BLOCKING MODE
        Pipeline is PREROLLING ...
        NvMMLiteOpen : Block : BlockType = 261
        NVMEDIA: Reading vendor.tegra.display-size : status: 6
        NvMMLiteBlockCreate : Block : BlockType = 261
        NvMMLiteOpen : Block : BlockType = 4
        Redistribute latency...
        ===== NVMEDIA: NVENC =====
        NvMMLiteBlockCreate : Block : BlockType = 4
        H264: Profile = 66, Level = 0
        
    [/code]
    
    However, if I now upgrade the above mentioned packages everything **_still_** works:
    
      * Upgrade `nvidia-containter-toolkit`:
    
    
    [code] 
        $ sudo apt-get install nvidia-container-toolkit
        Reading package lists... Done
        Building dependency tree
        Reading state information... Done
        The following additional packages will be installed:
          nvidia-container-toolkit-base
        The following NEW packages will be installed:
          nvidia-container-toolkit-base
        The following packages will be upgraded:
          nvidia-container-toolkit
        1 upgraded, 1 newly installed, 0 to remove and 163 not upgraded.
        Need to get 2.239 kB of archives.
        After this operation, 5.281 kB of additional disk space will be used.
        Do you want to continue? [Y/n] y
        Get:1 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/arm64  nvidia-container-toolkit 1.11.0-1 [635 kB]
        Get:2 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/arm64  nvidia-container-toolkit-base 1.11.0-1 [1.603 kB]
        Fetched 2.239 kB in 7s (326 kB/s)
        debconf: delaying package configuration, since apt-utils is not installed
        (Reading database ... 178366 files and directories currently installed.)
        Preparing to unpack .../nvidia-container-toolkit_1.11.0-1_arm64.deb ...
        Unpacking nvidia-container-toolkit (1.11.0-1) over (1.7.0-1) ...
        Selecting previously unselected package nvidia-container-toolkit-base.
        Preparing to unpack .../nvidia-container-toolkit-base_1.11.0-1_arm64.deb ...
        Unpacking nvidia-container-toolkit-base (1.11.0-1) ...
        Setting up nvidia-container-toolkit-base (1.11.0-1) ...
        Installing new version of config file /etc/nvidia-container-runtime/config.toml ...
        Setting up nvidia-container-toolkit (1.11.0-1) ...
        
    [/code]
    
      * Upgrading `nvidia-docker2`:
    
    
    [code] 
        $ sudo apt-get install nvidia-docker2
        Reading package lists... Done
        Building dependency tree
        Reading state information... Done
        The following packages will be upgraded:
          nvidia-docker2
        1 upgraded, 0 newly installed, 0 to remove and 162 not upgraded.
        Need to get 0 B/5.544 B of archives.
        After this operation, 0 B of additional disk space will be used.
        debconf: delaying package configuration, since apt-utils is not installed
        (Reading database ... 178370 files and directories currently installed.)
        Preparing to unpack .../nvidia-docker2_2.11.0-1_all.deb ...
        Unpacking nvidia-docker2 (2.11.0-1) over (2.8.0-1) ...
        Setting up nvidia-docker2 (2.11.0-1) ...
        
    [/code]
    
      * Check versions:
    
    
    [code] 
        $ dpkg -l|grep -E 'container|docker'
        ii  containerd                                 1.5.5-0ubuntu3~18.04.1                     arm64        daemon to control runC
        ii  docker                                     1.5-1build1                                arm64        System tray for KDE3/GNOME2 docklet applications
        ii  docker.io                                  20.10.7-0ubuntu5~18.04.3                   arm64        Linux container runtime
        ii  libavformat57:arm64                        7:3.4.8-0ubuntu0.2                         arm64        FFmpeg library with (de)muxers for multimedia containers - runtime files
        ii  libkf5wallet-bin                           5.44.0-0ubuntu1                            arm64        Secure and unified container for user passwords.
        ii  libkf5wallet-data                          5.44.0-0ubuntu1                            all          Secure and unified container for user passwords.
        ii  libkf5wallet5:arm64                        5.44.0-0ubuntu1                            arm64        Secure and unified container for user passwords.
        ii  libkwalletbackend5-5:arm64                 5.44.0-0ubuntu1                            arm64        Secure and unified container for user passwords.
        ii  libmatroska6v5:arm64                       1.4.8-1.1                                  arm64        extensible open standard audio/video container format (shared library)
        ii  libnvidia-container-tools                  1.11.0-1                                   arm64        NVIDIA container runtime library (command-line tools)
        ii  libnvidia-container0:arm64                 0.10.0+jetpack                             arm64        NVIDIA container runtime library
        ii  libnvidia-container1:arm64                 1.11.0-1                                   arm64        NVIDIA container runtime library
        ii  nvidia-container-csv-cuda                  10.2.460-1                                 arm64        Jetpack CUDA CSV file
        ii  nvidia-container-csv-cudnn                 30.255.87.135-1+cuda10.2                        arm64        Jetpack CUDNN CSV file
        ii  nvidia-container-csv-tensorrt              30.255.87.135-1+cuda10.2                         arm64        Jetpack TensorRT CSV file
        ii  nvidia-container-csv-visionworks           30.170-34-9794                                  arm64        Jetpack VisionWorks CSV file
        ii  nvidia-container-toolkit                   1.11.0-1                                   arm64        NVIDIA Container toolkit
        ii  nvidia-container-toolkit-base              1.11.0-1                                   arm64        NVIDIA Container Toolkit Base
        ii  nvidia-docker2                             2.11.0-1                                   all          nvidia-docker CLI wrapper
        
    [/code]
    
      * Running pipeline (working):
    
    
    [code] 
        $ docker run --rm --network=host --runtime=nvidia --privileged  nvcr.io/nvidia/l4t-base:r32.7.1  gst-launch-1.0 videotestsrc num-buffers=100 ! 'video/x-raw, format=UYVY, width=1920, height=1080, framerate=60/1' ! nvvidconv ! 'video/x-raw(memory:NVMM), format=NV12' ! nvv4l2h264enc ! 'video/x-h264, stream-format=(string)byte-stream' ! h264parse ! nvv4l2decoder ! filesink location=/tmp/h264.test
        (Argus) Error FileOperationFailed: Connecting to nvargus-daemon failed: No such file or directory (in src/rpc/socket/client/SocketClientDispatch.cpp, function openSocketConnection(), line 205)
        (Argus) Error FileOperationFailed: Cannot create camera provider (in src/rpc/socket/client/SocketClientDispatch.cpp, function createCameraProvider(), line 106)
        Setting pipeline to PAUSED ...
        Opening in BLOCKING MODE
        Opening in BLOCKING MODE
        Pipeline is PREROLLING ...
        NvMMLiteOpen : Block : BlockType = 261
        NVMEDIA: Reading vendor.tegra.display-size : status: 6
        NvMMLiteBlockCreate : Block : BlockType = 261
        NvMMLiteOpen : Block : BlockType = 4
        ===== NVMEDIA: NVENC =====
        Redistribute latency...
        NvMMLiteBlockCreate : Block : BlockType = 4
        H264: Profile = 66, Level = 0
        
    [/code]
    
    In short: we seem to have fixed it (thanks!) but we don't know exactly how we fixed it, making it hard to prevent this from happening further in the future. Could you check what could have possibly gone wrong in the original setup?

To which @Amycao replied

    i am not sure what could gone wrong in your original setup. but suggest you flash with whole JP version next time, it will not have this version issue.


{'source': 'discourse', 'url': 'https://forums.developer.nvidia.com/t/docker-libv4l2-error-getting-capabilities/227168', 'title': 'Docker libv4l2: error getting capabilities', 'views': 235, 'has_accepted_answer': False, 'word_count': 3354, 'like_count': 3, 'reply_count': 13, 'participant_count': 3, 'posts': 16, 'tags': '', 'author': '@simon_dg', 'participants': '@simon_dg, @ward.van.driessche (Ward Van Driessche), @Amycao', 'image_url': [None], 'created_at': '2022-09-06T11:13:07.090Z', 'last_posted_at': '2022-10-08T05:27:31.503Z'}