DeepLabCut provides a complete workflow for training deep neural networks to estimate poses of animals and humans from video data. The project includes a graphical labeling interface for annotating training data, a model training pipeline using deep learning frameworks, and inference tools for analyzing new videos. Researchers use it to automatically track movement and behavior across a wide range of species without requiring physical markers.