Annolid: Annotate, Segment, and Track Anything You Need
This tool addresses the need for efficient and automated video analysis in animal behavior research, though it is incremental as it builds on existing segmentation methods.
Annolid is a software package that tackles the problem of segmenting, labeling, and tracking animals in videos for behavior analysis, achieving resilient, markerless tracking from single annotated frames and enabling automatic segmentation by text command.
Annolid is a deep learning-based software package designed for the segmentation, labeling, and tracking of research targets within video files, focusing primarily on animal behavior analysis. Based on state-of-the-art instance segmentation methods, Annolid now harnesses the Cutie video object segmentation model to achieve resilient, markerless tracking of multiple animals from single annotated frames, even in environments in which they may be partially or entirely concealed by environmental features or by one another. Our integration of Segment Anything and Grounding-DINO strategies additionally enables the automatic masking and segmentation of recognizable animals and objects by text command, removing the need for manual annotation. Annolid's comprehensive approach to object segmentation flexibly accommodates a broad spectrum of behavior analysis applications, enabling the classification of diverse behavioral states such as freezing, digging, pup huddling, and social interactions in addition to the tracking of animals and their body parts.