Open World Object segmentor

I’m developing a lightweight, real-time open-world segmentation system that decomposes images into fine primitive regions rather than trying to predict final object masks in one step. The key idea is to consistently over-segment the scene, because small regions can always be grouped later, while under-segmented objects are much harder to fix once information has been lost. This makes the system a stronger foundation for downstream object formation and open-world perception than methods that may inconsistently merge object parts too early. The long-term goal is a fast, practical alternative to large segmentation models like SAM for real-time use.