• What platforms are supported?

Windows, Linux, and MacOS are all supported. Currently Python 3.6.x is supported, thus we highly recommend using the supplied Anaconda Environments for an easy install: https://github.com/AlexEMG/DeepLabCut/blob/master/docs/installation.md

Linux is the easiest to use, fastest, and a popular choice with deep learning researchers. In Linux, simply open terminal to get started.

Windows, you need to be sure you have a few extra things set up (like GitBash, and use the Anaconda Prompt!). For example, in the start menu you can search Anaconda, then select "Anaconda Prompt" with a RIGHT CLICK to open as admin.

• How do I know which version of DeepLabCut is installed?

open the terminal, activate your env (if used), type ipython or 'pythonw' (MacOS) then import deeplabcut then deeplabcut.__version__

• What computer hardware is required?

Any NVIDIA GPU card with more (or equal) than 8 GB memory should be sufficient to run DeepLabCut (at least with the ResNet-50). No server or supercomputer is required. These cards can also be installed in standard workstations if they have enough power supply and space. For reference, we use Dell Precision 79xx series towers with 32GB of memory and NVIDIA GeForce GTX 1080 Ti, 2080 Ti, TITAN Xp, or TITAN RTX graphics cards.

• Windows + Docker support?

https://github.com/NVIDIA/nvidia-docker/wiki/Frequently-Asked-Questions#is-microsoft-windows-supported

• Demo videos?:

https://www.youtube.com/channel/UC2HEbWpC_1v6i9RnDMy-dfA/featured?view_as=subscriber

Please also see the Troubleshooting Tips page, and check out the forum: https://forum.image.sc/tags/deeplabcut