Hello all!
I just want to clarify the usage of TF2+ with DLC. The original blog post states, that only DLC 2.1.8.2 is up to date with TF2+, but that a project created in DLC 2.1.9 is fine. Would this scenario work then:
- Install DLC 2.1.9 with the supplied conda environment
- Within this environment install dlc-core: pip install git+https://github.com/DeepLabCut/DeepLabCut-core.git@tf2.2alpha
- and the latest tensorflow (I have CUDA11 installed): pip install tensorflow==2.4
- Create a project and label videos with DLC 2.1.9 (import deeplabcut as dlc)
- Create a training dataset, train, evaluate and analyze new videos with dlc-core (import deeplabcut-core as dlc)
- For refining and extracting outliers, go back to DLC 2.1.9 (import deeplabcut as dlc)
- Repeat
Additionally, the DLC website states that only CUDA10 or lower is supported. I have already been running DLC 2.1 and DLC 2.2b8 with tensorflow 1.13.1 and CUDA 11 and I seemed to have not experienced any issues. Am I missing something and should roll down my CUDA to 10? CUDA 11 was automatically installed as part of my NVIDIA GPU driver update.
I thank you kindly for your awesome support!
