DeepLabCut is an open-source AI/ML library built on TensorFlow/PyTorch for markerless pose estimation. It provides tools, pre-trained models, and flexible APIs to create, train, and evaluate deep learning models for tracking body parts in videos. DeepLabCut runs via CLI, making it lightweight and easy to use for research, experimentation, and production workflows.

Features of DeepLabCut:

AI-powered pose estimation and video analysis using deep learning.
Command-line interface for simple and fast usage.
Support for multiple tasks like animal and human movement tracking.
Lightweight and does not require a web server.
Integration with Python projects for automated workflows.
High-quality pre-trained models suitable for research and production.
Open-source and extensible for custom behavioral analysis applications.

To check DeepLabCut version:

$ cd /opt/deeplabcut

$ source /opt/deeplabcut/dlc-venv/bin/activate

$ python -m deeplabcut --version

Disclaimer: DeepLabCut is open-source software provided under the Apache 2.0 License. It is offered "as is," without any warranty, express or implied. Users are responsible for ensuring the ethical and legal use of DeepLabCut in their projects.

DeepLabCutbCloud LLC

DeepLabCut

bCloud LLC

DeepLabCut

bCloud LLC

DeepLabCut
bCloud LLC