Protocol for Tracking and Automated Behavioral Quantification in Drosophila melanogaster

To develop an open-source analytical tool that overcomes the limitations of traditional centroid-based tracking methods, we present a protocol to accurately analyze social interactions in freely behaving Drosophila pairs. Specifically, this protocol is inspired by the high-resolution network (HRNet) framework to simultaneously track five anatomical key points-head, thorax, abdomen, and left and right wing tips -aiming to generate high-resolution coordinate data for subsequent quantitative analysis of social behaviors. This protocol provides a complete workflow based on Python and a graphical user interface (GUI) we designed, including dataset construction, model training, and automated coordinate extraction, along with integrated modules for generating spatial occupancy heatmaps, locomotor trajectories, and social interaction ratios in flies. To validate this framework, it was tested by using two widely used strains, w1118 and Canton-S (CS). Our results demonstrated the stability of key-point detection and revealed genotype-specific differences in spatial utilization and locomotive structure. This methodology provides a scalable foundation for quantitative ethology and automated analysis of social interactions in Drosophila, while reducing manual annotation effort and improving reproducibility.