Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
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Updated
Aug 26, 2024 - Python
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
🐜🐀🐒🚶 A toolkit for robust markerless 3D pose estimation
Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.
SDK for running DeepLabCut on a live video stream
a napari plugin for labeling and refining keypoint data within DeepLabCut projects
GUI to run DeepLabCut on live video feed
Headless DeepLabCut (no GUI support)
Closed-loop behavioral experiment toolkit using pose estimation of body parts.
We turn natural language descriptions of behaviors into machine-executable code
Utilities to convert DeepLabCut (DLC), output to/from Neurodata Without Borders (NWB) format.
[ICCV 2023] "Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity"
Toolbox for using multiple cameras from intrinsic calculations to reconstructing kinematics
replicAnt - generating annotated images of animals in complex environments with Unreal Engine
DLClibrary is a lightweight library supporting universal functions for the DeepLabCut ecosystem.
Fully automated (rodent) limb motion analysis toolbox for behavioral analysis with bodypart coordinate data, building upon markerless pose estimation.
Deep learning-driven multi animal tracking and pose estimation add-on for Blender
An alpha playground for a web-based labeling tool for DLC
A python toolbox for locating and exporting brain regions from mouse brain images.
Simple vispy-based frame-by-frame behavior annotation GUI. Also can display DeepLabCut poses within videos during annotation.
Edit DeepLabCut labels from HDF files. Save edited files in both HDF and MATLAB file formats.
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