RTSP Stream Handling with C++ on Nvidia Jetson Orin Nano

Issue Overview

Users are experiencing difficulties in implementing a C++ application that utilizes GStreamer to obtain RTSP streams and convert the data into a format suitable for facial recognition algorithms on the Nvidia Jetson Orin Nano Developer Kit. The specific symptoms include:

• Successful retrieval of RTSP data using a GStreamer command, but failure to achieve similar results in a C++ implementation.
• The C++ pipeline is defined but results in logs indicating "Stream format not found, dropping the frame," suggesting issues with data handling or format compatibility.
• Users have attempted to run DeepStream SDK samples but encountered errors related to model deserialization and configuration file issues.

The context of the problem arises during the setup of C++ applications and while attempting to run DeepStream SDK samples. The hardware specifications include the Nvidia Orin Nano Developer Kit, Jetpack version 5.1.3 (L4T 35.5.0), and GStreamer version 1.16.3. The issue appears to be consistent across multiple attempts, significantly impacting users’ ability to process video streams for facial recognition.

Possible Causes

• Hardware Incompatibilities or Defects: The Nvidia Orin Nano may have specific requirements or limitations that are not met by the current configuration or software versions.

• Software Bugs or Conflicts: There may be bugs in the GStreamer or DeepStream SDK versions being used, leading to unexpected behavior during stream processing.

• Configuration Errors: Incorrect pipeline configurations in the C++ code could prevent proper stream handling, particularly regarding format specifications.

• Driver Issues: Incompatibilities between installed drivers (CUDA, cuDNN) and the versions of GStreamer or DeepStream SDK could lead to failures in executing commands.

• Environmental Factors: Insufficient permissions or incorrect environmental settings may hinder execution, especially when accessing hardware resources.

• User Errors or Misconfigurations: Mistakes in setting up the environment or running commands (e.g., incorrect paths or missing files) can lead to failures.

Troubleshooting Steps, Solutions & Fixes

1. Verify Hardware Compatibility:

   • Ensure that the Nvidia Orin Nano Developer Kit meets all requirements for running GStreamer and DeepStream SDK applications.

2. Check Software Versions:

   • Confirm that all software components (Jetpack, CUDA, cuDNN, TensorRT) are compatible with each other and properly installed.
   • Recommended versions:
     • CUDA Driver Version: 11.4
     • TensorRT Version: 8.5
     • cuDNN Version: 8.6

3. Review and Adjust C++ Pipeline:

   • Modify the C++ pipeline definition to ensure it matches working configurations. A sample pipeline is provided below:

     #define RTSP_PIPELINE "rtspsrc location=rtsp://192.168.0.12:8554/test protocols=udp latency=100 ! " \
         "rtph264depay ! h264parse ! nvv4l2decoder ! " \
         "nvvidconv ! " \
         "video/x-raw format=(string)BGRx ! " \
         "videoconvert ! " \
         "video/x-raw format=BGR ! " \
         "appsink name=sink"
     

4. Run GStreamer Commands for Debugging:

   • Test the GStreamer command directly in the terminal to ensure it works as expected:

     gst-launch-1.0 rtspsrc location=rtsp://192.168.0.12:8554/test protocols=udp latency=100 ! rtph264depay ! h264parse ! nvv4l2decoder ! nv3dsink -e
     

5. DeepStream SDK Configuration:

   • If using DeepStream SDK, ensure correct configuration files are being used and that they point to valid model files.
   • Check permissions on model files; consider running commands with sudo if necessary.

6. Resolve Model Deserialization Errors:

   • Review error logs indicating issues with model paths; ensure that all required model files are present and accessible.
   • If errors persist, consider rebuilding the engine from model files as suggested by error messages.

7. Permissions Check:

   • Ensure that all necessary directories and files have appropriate permissions set (e.g., using chmod 777 cautiously).

8. Consult Documentation:

   • Refer to NVIDIA Metropolis documentation for guidance on setting up DeepStream applications correctly.

9. Seek Community Support:

   • If issues remain unresolved, consider reaching out on forums or NVIDIA support channels for additional insights.

10. Best Practices for Future Use:

    • Maintain updated software versions and regularly check compatibility notes from NVIDIA.
    • Document configuration changes and results for easier troubleshooting in future projects.

By following these steps, users can systematically diagnose and resolve issues related to RTSP stream handling in their C++ applications on the Nvidia Jetson Orin Nano platform.