Hi,
I can imagine it is documented somewhere but I could not find it. Installation instructions are very detailed for Nvidia GPU owners (Tensorflow and CUDA), but I did not see any guide on how to use Deeplabcut-GPU with ATI GPUs.
Running one of the examples using the Deeplabcut-CPU is taking already a couple of days…
Thanks in advance, Claudio.
Hi @claudioez because we use CUDA one needs to use NVIDIA GPUs.
I asked a related question here, later CUDA dependence in DLC
However, I found that there exists at least a TensorFlow implementation for Radeon that might resolve the NVIDIA/CUDA dependence if TensorFlow is the only aspect of DLC that relies on Nvidia technology.
[1] https://github.com/ROCmSoftwarePlatform/tensorflow-upstream
[2] https://rocmdocs.amd.com/en/latest/InstallGuide.html
I can’t try this myself because I have neither GPU currently. I am trying to buy an 3000 series NVIDIA card to build a new analysis rig, but they are almost impossible to obtain for a reasonable cost. Learning that DLC can run on Radeon would help improve my options.
Sorry for the the delayed response. Indeed the only aspect of DLC that requires CUDA/NVIDIA is TensorFlow (see here for more details on NVIDIA and TF: https://www.tensorflow.org/install/gpu).
Unfortunately, I have no experience with (trying) to use TF on Radeon cards. But maybe somebody else, has…
The 30x series indeed starts at ~500$, https://www.nvidia.com/en-us/geforce/news/geforce-rtx-3070-out-now/
(they are great cards!). The previous series are still available too, and are a bit cheaper… Perhaps a great alternative is using Google Colaboratory (you can use GPUs for free up to 6h at a time, or get a pro account for 10$ a month: https://colab.research.google.com/signup). Examples for how to use DLC on Colab are here: https://github.com/DeepLabCut/DeepLabCut/tree/master/examples
Sorry that I don’t have a more helpful answer!