RefineDLC: An advanced post-processing pipeline for DeepLabCut outputs.

ABSTRACT: DeepLabCut has transformed behavioral and locomotor research by enabling markerless pose estimation through deep learning. Despite its broad adoption across species and behaviors, quantitative kinematic analyses remained limited by noisy outputs and the computational expertise required for refinement. To address this issue, we introduce refineDLC, a comprehensive post-processing pipeline that streamlines the conversion of noisy DeepLabCut outputs into robust, analytically reliable kinematic data. The pipeline incorporates essential cleaning steps, including inversion of the y-coordinates for intuitive spatial interpretation, removal of zero-value frames, and exclusion of irrelevant body part labels. It further applies dual-stage filtering based on likelihood scores and positional changes,

SUBMITTER: Klecel W 

PROVIDER: S-EPMC12744387 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature