DIPLOMAT
Deep Learning-Based Identity Preserving Labeled-Object Multi-Animal Tracking
DIPLOMAT
Deep Learning-Based Identity Preserving Labeled-Object Multi-Animal Tracking
DIPLOMAT
DIPLOMAT provides a multi-animal tracking/pose-estimation interface that (1) reduces identity swaps and body part losses, and (2) simplifies correction of automated tracking errors. After pre-processing a video with a pose estimation tool (currently supporting SLEAP and DeepLabCut packages), DIPLOMAT computes a multi-animal maximum-probability trace to Track multiple animals (and their body parts); it then provides an intuitive and memory/time efficient Interact interface to edit and re-track as needed. DIPLOMAT differs from other multi-animal tracking packages by working directly off of confidence maps instead of running peak detection, allowing for more accurate tracking results.
Here we can make precise adjustments to our model's predicted points and re-run the Viterbi algorithm
Learn more about DIPLOMAT's functionalities through our video guides.
Introduction on how you can track and interact with pose data in DIPLOMAT, leveraging models created through SLEAP or DeepLabCut (DLC).
Overview of the visual settings, continuous labeling, single/multi body part labeling modes, and re-running the Viterbi algorithm
The Tweak Interface allows for fine-tuning to minimize identity swaps and other issues. Explore the tutorial video to learn more.
Tutorial on navigating the Tweak Interface