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@AlexEMG @MMathisLab

Got Behavior? Get Poses ... DLC LIVE!

This document is an outline of resources for a course for those wanting to learn to use Python and DeepLabCut (while responsibly isolating due to COVID-19!). We expect it to take roughly 1-2 weeks to get through if you do it rigorously. To get the basics, it should take 1-2 days.

CLICK HERE to launch the interactive graphic to get started! (mini preview below) Or, jump in below!

You can also chat with one another on Gitter or Twitter: Gitter Twitter Follow


You need: Anaconda for python3 and DeepLabCut installed (CPU version)


The basics of computing in Python, terminal, and overview of DLC:


  • REVIEW PAPER: The state of animal pose estimation w/ deep learning i.e. "Deep learning tools for the measurement of animal behavior in neuroscience" arXiv & published version

  • NEW! REVIEW PAPER: A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives

  • WATCH: There are a lot of docs... where to begin: Video Tutorial!

Module 1: getting started on data

What you need: any videos where you can see the animals/objects, etc. You can use our demo videos, grab some from the internet, or use whatever older data you have. Any camera, color/monochrome, etc will work. Find diverse videos, and label what you want to track well :)

  • IF YOU ARE PART OF THE COURSE: you will be contributing to the DLC Model Zoo 😄

💜 NOTE: if you want to contribute back to community-science, please get in touch with us as we have a LOT of data we want to label to be able to share back with everyone; So, if you want to help sign up here (labeling can be on data we provide or possibly yours): 💜

Module 2: Neural Networks


Before you create a training/test set, please read/watch:

Module 3: Evalution of network performance

Module 4: Scaling your analysis to many new videos

Once you have good networks, you can deploy them. You can create "cron jobs" to run a timed analysis script, for example. We run this daily on new videos collected in the lab. Check out a simple script to get started, and read more below:

Module 5: Got Poses? Now what ...

Pose estimation took away the painful part of digitizing your data, but now what? There is a rich set of tools out there to help you create your own custom analysis, or use others (and edit them to your needs). Check out more below:

compiled and edited by Mackenzie Mathis