CSI Camera Fails to Load on Nvidia Jetson Orin Nano Dev Board

Issue Overview

Users are experiencing issues with the Nvidia Jetson Orin Nano Dev board when attempting to use two IMX 219 cameras within the jetson-inference Docker container. The primary symptoms include failure to load the cameras, as indicated by error messages related to GStreamer plugins and the inability to create camera pipelines. Specifically, users see warnings such as "Failed to load plugin" and "gstCamera failed to create device csi://0" and "csi://1," indicating that the nvarguscamerasrc element is not found. This problem occurs during the setup phase when users try to access the cameras after starting the Docker container. The hardware used includes the Jetson Orin Nano with L4T R35.3.1 and GStreamer version 1.16.3, and it has been noted that the cameras function correctly outside of the container environment. The issue appears consistently, impacting user experience by preventing camera access for applications relying on visual input.

Possible Causes

• Hardware Incompatibility: There may be incompatibilities between the IMX 219 cameras and the Jetson Orin Nano or its configuration.
• Software Bugs: The issue could stem from bugs in the jetson-inference container or GStreamer itself.
• Configuration Errors: Incorrect settings in Docker or the environment may lead to failures in loading necessary plugins.
• Driver Issues: Missing or outdated drivers for GStreamer or camera support could prevent proper functionality.
• Environmental Factors: Insufficient memory allocation or improper power supply might affect camera initialization.
• User Misconfiguration: Users might not be setting up their environment correctly, particularly with respect to environmental variables like LD_PRELOAD.

Troubleshooting Steps, Solutions & Fixes

1. Restart Container:

   • Exit and restart the jetson-inference container.

2. Set Environment Variable:

   • Before attempting to access the cameras, run:

     export LD_PRELOAD=/lib/aarch64-linux-gnu/libGLdispatch.so.0
     

3. Clear GStreamer Cache:

   • Run the following command to clear any cached plugins:

     rm -rf /root/.cache/gstreamer-1.0
     

4. Check Plugin Availability:

   • After setting the environment variable and clearing cache, check for available GStreamer elements:

     gst-inspect-1.0 | grep nv
     

   • Ensure that nvarguscamerasrc is listed.

5. Modify Dockerfile (if applicable):

   • To automate the process of setting LD_PRELOAD, modify your Dockerfile by adding:

     ENV LD_PRELOAD=/lib/aarch64-linux-gnu/libGLdispatch.so.0
     

   • Rebuild your Docker container after making changes.

6. Run Command with Environment Variable:

   • Alternatively, modify your docker/run.sh script to include:

     --env LD_PRELOAD=/usr/lib/aarch64-linux-gnu/libgomp.so.1:/lib/aarch64-linux-gnu/libGLdispatch.so.0
     

   • This ensures that every time you run the container, it has access to the necessary libraries.

7. Testing Different Configurations:

   • If issues persist, try testing with different camera setups or configurations to isolate whether it’s a hardware-specific issue.

8. Documentation & Updates:

   • Regularly check for updates on relevant documentation from Nvidia regarding Jetson Orin Nano and jetson-inference.
   • Ensure that all drivers and software packages are up-to-date.

9. Community Support:

   • Engage with community forums for additional support or similar experiences shared by other users.

By following these steps, users should be able to diagnose and potentially resolve issues related to using IMX 219 cameras with the Nvidia Jetson Orin Nano Dev board effectively.