🙋♀️ DeepLabCut™ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks.
- The main code repository is here. Contains code for all necessary steps to do pose estimation incl. GUI.
- 👩💻 Read the documentation for how to get started and how to use DeepLabCut.
We also have several related code repositories that may be of interest:
- DLC-Live! & DLC-Live! GUI -- export your trained DeepLabCut model and run it for live analysis. Consider using our easy GUI to do so.
- DLCUtils -- this repo hosts some code and key links to helper packages that input the outputs of DeepLabCut for downstream analysis.
- DLC Workshop & Educational Materials -- learn about how to use and develop with DeepLabCut!
- DLC2Kinematics -- use this code to load DeepLabCut (H5) files for movement analysis, dev. by MW Mathis Lab.
- DLC2Action -- for action segmentation based on pose estimation data, dev. by A Mathis Group.
- CEBRA -- use this code to load DeepLabCut (H5) files for advnced nonlinear embedding analysis and joint modeling, dev. by MW Mathis Lab.
🌈 Contribution guidelines to this project can be found here!
🍿 Find more resources, our papers, and examples on the main website!
🧙 Check out the repos below to find helper code, additional tools, and more!
