Issues running VPI on Orin Nano

Issue Overview

Users are experiencing crashes when attempting to run the Vision Programming Interface (VPI) on the Nvidia Jetson Orin Nano development kit through Python. The specific error message encountered is:

double free or corruption (out)
Aborted (core dumped)

This issue occurs during the execution of the following code snippet:

import vpi
i = vpi.Image((64,64), vpi.Format.RGB8)

The problem has been reported consistently across different setups, indicating that it may not be an isolated incident. Users have noted that the error also occurs when running a similar program written in C, suggesting a potential issue with the VPI library itself.

The context of the problem includes:

• Hardware: Nvidia Jetson Orin Nano development kit
• Software: Python 3.8.10, VPI library (specific version not mentioned)
• Frequency: The issue appears to be reproducible under certain conditions, particularly when using SSH sessions with X forwarding enabled.
• Impact: This problem significantly affects the user experience by preventing the execution of applications that rely on VPI, thereby limiting functionality and usability.

Possible Causes

Several potential causes for this issue have been identified:

• Software Bugs or Conflicts: There may be bugs within the VPI library that lead to memory management issues, such as double freeing memory.

• Configuration Errors: Improper configuration during installation or setup could lead to compatibility issues with the VPI library.

• Driver Issues: Outdated or incompatible drivers may cause instability when running applications that utilize hardware acceleration.

• Environmental Factors: Running applications over SSH with X forwarding enabled can introduce complications that lead to crashes.

• User Errors or Misconfigurations: Incorrect usage patterns, such as trying to run graphical applications over SSH without proper configuration, can result in errors.

Troubleshooting Steps, Solutions & Fixes

To diagnose and resolve the issue with running VPI on the Orin Nano, follow these steps:

1. Verify VPI Installation:

   • Ensure that VPI is correctly installed. You can reinstall it using SDK Manager.
   • Confirm that you have included all necessary components during installation.

2. Test in Different Environments:

   • Run your Python code directly on the Orin Nano terminal instead of through an SSH session. If it works locally but fails over SSH, this indicates an environmental issue.

3. Disable X Forwarding:

   • If you are using SSH with X forwarding enabled, disable it and test your application again. This has been shown to resolve crashes for some users.
   • To disable X forwarding in your SSH session, use the command:

     ssh -x user@hostname
     

4. Check for Driver Updates:

   • Ensure that your system has the latest drivers installed. You can check for updates through SDK Manager or Nvidia’s official site.

5. Run Diagnostic Commands:

   • Use commands like dmesg or journalctl to check for any system logs that might provide additional insights into crashes or errors related to memory management.

6. Test Different Code Versions:

   • Experiment with variations of your code to see if specific parameters or configurations trigger the error consistently.

7. Monitor System Resources:

   • Check system resource usage (CPU, memory) while running your application to ensure there are no resource constraints leading to crashes.

8. Consult Documentation:

   • Review Nvidia’s documentation for VPI and Jetson Orin Nano for any known issues or additional troubleshooting steps.

9. Community Support:

   • If issues persist after trying these solutions, consider reaching out to community forums for additional support and sharing your experiences for further assistance.

By following these troubleshooting steps and solutions, users should be able to address the issues they are facing with VPI on their Nvidia Jetson Orin Nano development kits effectively.