Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
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Updated
Jun 13, 2024 - Python
Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
a napari plugin for labeling and refining keypoint data within DeepLabCut projects
Deep learning-driven multi animal tracking and pose estimation add-on for Blender
[NeurIPS 2023] We turn natural language descriptions of behaviors into machine-executable code
[ICCV 2023] "Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity"
Docker image to get DeepLabCutCore running on cloud GPUs.
🐜🐀🐒🚶 A toolkit for robust markerless 3D pose estimation
PoseModel: An Open-Source Toolkit for Accurate and Robust Automated Behavioral Latent Embedding
[Cell 2024]: Code for Task-driven neural network models predict neural dynamics of proprioception by Marin Vargas* and Bisi* et al.
I created this notebook to help me with behavioral neuroscience experiments. It calculates the average positions and velocities of two body parts (for better accuracy), and creates visualizations such as GIFs and streamline plots to represent the motion and flow of movement.
Toolbox for using multiple cameras from intrinsic calculations to reconstructing kinematics
DLC2Action is an action segmentation package that makes running and tracking of machine learning experiments easy.
This repository contains notebooks and resources for the workshop taking place in March 2024 at the Leibniz Institute for Neurobiology in Magdeburg.
Tools for machine learning of animal behavior
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.
In this repository we store and share scripts, data, training models, etc used for tracking or evaluating behavioural videos via DLC, SIMBA and other potential ML tools.
SDK for running DeepLabCut on a live video stream
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.
DLClibrary is a lightweight library supporting universal functions for the DeepLabCut ecosystem.
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