Precise, pixel-tight Polygon masks for instance, semantic, or panoptic segmentation any object category Clean separation of occluded, overlapping, or stacked objects, with no boundary bleed between instances Delivery in your pipeline's format: COCO JSON, YOLO-seg, Label Studio, CVAT, or custom Optional SAM2/Florence-2-assisted pre-labeling for large batches, always followed by a manual correction pass QA review on every batch before handoff

In this project has 700+ hand-annotated images of stacked, overlapping poker chips across three near-identical color classes A 5-class botanical dataset (flower, fruit, leaf, stem/branch) across 2,000+ images, including thin/sparse structures most annotators get wrong CVAT/Label Studio pipelines built and run for 5,000+ frame labeling batches