Hello AI World ‘killed’ on Orin Nano 4gb

Issue Overview

Users have reported that when attempting to run the example Python code for object detection from the "Hello AI World" project on the Nvidia Jetson Orin Nano 4GB development kit, the process is unexpectedly terminated with a "Killed" message. This issue occurs shortly after initiating the script, typically within 30 seconds of execution. The specific command used is:

$ python3 myDetectNetPythonCode.py > log.txt

The environment consists of JetPack version 5.1.3-b29. The symptoms indicate a potential resource limitation, likely related to memory usage, as suggested by community feedback. The problem consistently affects users attempting to run similar detection scripts, impacting their ability to utilize the development kit effectively for AI applications.

Possible Causes

1. Memory Limitations: The most common cause for the "Killed" message is running out of available memory (RAM). The Jetson Orin Nano 4GB may not have sufficient resources to handle the operations required by the detection model.
2. Configuration Errors: Incorrect setup or parameters in the Python script could lead to excessive resource consumption.
3. Driver Issues: Outdated or incompatible drivers may hinder performance and lead to crashes.
4. Environmental Factors: Overheating due to inadequate cooling could cause the system to terminate processes to protect hardware.
5. User Errors: Misconfigurations in camera input or other parameters might contribute to excessive resource usage.

Troubleshooting Steps, Solutions & Fixes

1. Create Swap Memory:

   • To alleviate memory constraints, create swap space on your device:

     sudo fallocate -l 2G /swapfile
     sudo chmod 600 /swapfile
     sudo mkswap /swapfile
     sudo swapon /swapfile
     

   • Verify that swap is active:

     sudo swapon --show
     

2. Monitor System Resources:

   • Use htop or free -h to monitor RAM and swap usage while running your script.
   • Install htop if not available:

     sudo apt install htop
     

3. Optimize Code:

   • Review your Python script for potential optimizations, such as reducing image resolution or adjusting detection thresholds.

4. Update Drivers and JetPack:

   • Ensure you are using the latest drivers and JetPack version compatible with your hardware.
   • Check for updates using SDK Manager.

5. Test with Different Configurations:

   • Try running the script with different camera inputs or configurations to isolate the issue further.
   • For instance, test with a static image instead of live camera feed.

6. Check for Overheating:

   • Ensure that your development kit has adequate cooling and is not overheating during operation.

7. Review Logs:

   • Inspect log.txt for any additional error messages that could provide insight into the failure.

8. Community Solutions:

   • Engage with community forums for additional insights; many users have shared successful workarounds and solutions.

9. Documentation and Resources:

   • Refer to Nvidia’s official documentation for Jetson Orin Nano for any specific guidelines or updates related to your issues.

10. Best Practices:

    • Regularly monitor system performance and manage resources effectively to prevent similar issues in future projects.

By following these steps, users can diagnose and potentially resolve the "Killed" issue when running detection scripts on the Nvidia Jetson Orin Nano 4GB development kit.