deeplabcut

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.

Workshop material for using DeepLabCut

SDK for running DeepLabCut on a live video stream

Various scripts to support deeplabcut and what to do afterwards!

a module for kinematic analysis of deeplabcut outputs

Docker container for running DeepLabCut 2.0+ (linux support only)

Closed-loop behavioral experiment toolkit using pose estimation of body parts.

Headless DeepLabCut (no GUI support)

Toolbox for using multiple cameras from intrinsic calculations to reconstructing kinematics

GUI to run DeepLabCut on live video feed

A Primer on Motion Capture with Deep Learning:Principles, Pitfalls and Perspectives

An alpha playground for a web-based labeling tool for DLC

Dockerfile for DeepLabCut 2.0 (https://github.com/AlexEMG/DeepLabCut)

Inofficial docker images for DeepLabCut (experimental)

Function for converting DLTdv tracking files into labeled training data for DeepLabCut pose estimation package

cookiecutter template for DeepLabCut project

A python toolbox for locating and exporting brain regions from mouse brain images.

This is a collabration of Pose-Estimation done on Deeplabcut for Gait Analysis of the Limb for computing joint angle used for Rehabilliation.

Real-time tracking and behavioural reinforcement toolbox for DeepLabCut to accompany Forys, Xiao, Gupta, and Murphy (2020).

Edit DeepLabCut labels from HDF files. Save edited files in both HDF and MATLAB file formats.

Designed to making setting up a markerless pose estimation of user-defined features with deep learning for all animals, including humans

Docker image to get DeepLabCutCore running on cloud GPUs.

Fully automated (rodent) limb motion analysis toolbox for behavioral analysis with bodypart coordinate data, building upon markerless pose estimation.