@hry7999 you either need to build torchvision from source (like under the Installation section of this post) or use a jetson-container with torchvision in it. The containers for JetPack 5.1.2 / L4T R35.4 are compatible with JetPack 5.1.3, you don’t need them to match exactly (or you can rebuild them if desired)
Related topics
| Topic | Replies | Views | Activity | |
|---|---|---|---|---|
| What is the compatible torchvision version for torch-1.14.0a0+44dac51c.nv23.2 installed on AGX ORIN( Ubuntu-22.04, JP-5.1/5.0, Python-3.8, CUDA-11.4) | 19 | 3949 | May 11, 2023 | |
| Torch and torchvision versions are not compatible | 9 | 6725 | September 11, 2023 | |
| Torchvision on Jetson AGX Orin DevKit | 7 | 3242 | June 2, 2023 | |
| Incompatibility between PyTorch and Torchvision for Jetpack 5.1.2 on AGX Orin | 7 | 437 | October 4, 2024 | |
| What is proper version of torchvision for torch 2.0.0+nv23.5 | 5 | 2942 | August 1, 2023 | |
| PyTorch and torchvision on Jetson Orin | 4 | 5060 | April 25, 2023 | |
| Can't find compatible torchvision version for torch for jetpack 5.1 | 6 | 1720 | December 12, 2023 | |
| Torch and Torchvision are not compatible | 5 | 139 | November 19, 2024 | |
| Pytorch compatibility issues (torch 2.0.0+nv23.5 && torchvision 0.15.1) | 10 | 18701 | June 13, 2023 | |
| Torchvision Version for Jetpack 6.1 on Jetson Orin AGX | 0 | 122 | December 7, 2024 |