Resolving video capture error in Docker container after restarting nvargus-daemon

Issue Overview

Users of the Nvidia Jetson Orin Nano Dev board have reported experiencing a video capture error when attempting to use the nvarguscamerasrc GStreamer element within a Docker container after restarting the nvargus-daemon. The symptoms of this issue include:

• An error message indicating failure to connect to the nvargus-daemon, specifically:
  • Error FileOperationFailed: Connecting to nvargus-daemon failed: Connection refused
  • Error FileOperationFailed: Cannot create camera provider
• This issue arises after executing the command sudo systemctl restart nvargus-daemon.service on the host machine.
• While video capture works correctly on the host side, executing the same pipeline within the Docker container results in failure.
• Users have noted that recreating the Docker container temporarily resolves the issue, allowing video capture to resume without errors. However, this is not a viable solution for applications requiring continuous operation.

The context of this problem typically involves users needing to restart the nvargus-daemon due to intermittent camera failures during extended usage, which can occur anywhere from one hour to 48 hours into operation. This situation necessitates a solution that allows for minimal disruption while maintaining video capture functionality within Docker.

Possible Causes

Several potential causes for this issue have been identified:

• Hardware Incompatibilities or Defects: Issues with camera hardware or connections may lead to communication failures with the daemon.

• Software Bugs or Conflicts: Bugs in either the GStreamer framework or the nvargus-daemon may prevent proper operation after a restart.

• Configuration Errors: Incorrect Docker configurations may lead to problems accessing necessary resources, such as sockets for communication with nvargus-daemon.

• Driver Issues: Outdated or incompatible drivers could hinder proper functioning of camera operations within Docker.

• Environmental Factors: Power supply issues or temperature fluctuations could affect device performance and stability.

• User Errors or Misconfigurations: Incorrectly configured Docker run commands may lead to insufficient permissions or resource access.

Each of these causes could contribute to the observed problem, particularly in how Docker containers interact with system-level services like nvargus-daemon.

Troubleshooting Steps, Solutions & Fixes

To address the video capture error within a Docker container after restarting nvargus-daemon, users can follow these troubleshooting steps and solutions:

1. Check Docker Run Command:

   • Ensure that the Docker container is run with appropriate permissions and configurations. Use the following command to mount /tmp instead of /tmp/argus_socket:

     docker run -dit --gpus all --privileged -e DISPLAY=$DISPLAY -v /tmp/:/tmp/ --network=host --name=xxxx
     

2. Verify Daemon Status:

   • Before running your GStreamer pipeline, check if the nvargus-daemon is active:

     sudo systemctl status nvargus-daemon.service
     

3. Inspect Logs for Errors:

   • Review the logs of nvargus-daemon for any errors that may provide insight into what went wrong during operation:

     journalctl -u nvargus-daemon.service
     

4. Test Outside Docker:

   • Confirm that video capture works correctly outside of Docker using:

     gst-launch-1.0 nvarguscamerasrc ! fakesink
     

5. Recreate Container as a Last Resort:

   • If errors persist and immediate resolution is required, consider recreating the Docker container as a temporary workaround.

6. Update Drivers and Software:

   • Ensure that all relevant software packages and drivers are up-to-date to minimize compatibility issues.

7. Monitor System Resources:

   • Keep an eye on system resources (CPU, memory) while running applications in Docker to ensure they are not being exhausted.

8. Best Practices for Future Prevention:

   • Regularly restart services and containers during scheduled maintenance windows rather than during active use.
   • Consider implementing logging within your application to catch errors early before they escalate into service interruptions.

By following these steps, users can effectively troubleshoot and potentially resolve issues related to video capture within Docker containers on Nvidia Jetson Orin Nano devices.