Installing Compatible TorchVision for JetPack 6.1 on Nvidia Jetson Orin Nano

Issue Overview

Users have reported difficulties in finding a compatible version of TorchVision to install alongside Torch after setting up JetPack 6.1 on the Nvidia Jetson Orin Nano. The main symptoms include:

• Inability to locate a compatible TorchVision package.
• Confusion regarding installation procedures.
• Users have successfully installed Torch but are left without guidance on TorchVision, impacting their ability to run specific applications that depend on this library.

The issue primarily occurs during the setup phase, specifically after installing JetPack 6.1. This problem has been noted by multiple users, indicating a lack of clear documentation or available resources for the installation of TorchVision that matches the version of Torch provided in the Nvidia repository.

Possible Causes

Several potential causes for this issue have been identified:

• Lack of Official Packages: There may not be an official pre-built package for TorchVision compatible with JetPack 6.1.
• Version Mismatch: The installed version of Torch may not align with any available TorchVision versions, leading to compatibility issues.
• Installation Source: Users may be directed to outdated or incorrect sources for installation, complicating the process further.
• Documentation Gaps: Insufficient documentation from Nvidia regarding the installation process can lead to confusion and frustration among users.

Troubleshooting Steps, Solutions & Fixes

To resolve the issue of installing a compatible version of TorchVision, users can follow these steps:

1. Building from Source:

   • Since no pre-built packages are available, building TorchVision from source is recommended. Follow these steps:

     # Install necessary dependencies
     sudo apt-get install python3-pip libjpeg-dev libpng-dev libtiff-dev
     
     # Clone the TorchVision repository
     git clone https://github.com/pytorch/vision.git
     cd vision
     
     # Check out the compatible version (replace with actual version if known)
     git checkout tags/v0.12.0
     
     # Install using pip
     python3 setup.py install
     

2. Check Compatibility:

   • Ensure that the installed version of Torch matches the requirements of the TorchVision version you are building. You can check your currently installed version of Torch with:

     python3 -c "import torch; print(torch.__version__)"
     

3. Consult Documentation:

   • Review any available documentation on Nvidia’s developer forums or GitHub repositories for updates or additional instructions regarding installation.

4. Community Support:

   • Engage with community forums such as Nvidia’s Developer Forums or Reddit’s r/JetsonNano for shared experiences and solutions from other users who may have faced similar issues.

5. Future Prevention:

   • Regularly check for updates from Nvidia regarding JetPack and associated libraries to ensure compatibility and access to new features or fixes.

By following these steps, users should be able to successfully install a compatible version of TorchVision for their JetPack 6.1 setup on the Nvidia Jetson Orin Nano.