Real-time instance segmentation models ranked by mask mAP on COCO val2017. Each run also records box mAP; masks are scored with COCO segm evaluation at source resolution.
| Model | Family | mAP@50-95 (%) | Latency (ms) | FPS | Params (M) |
|---|---|---|---|---|---|
| rfdetr-seg-n | rfdetr | 40.4 | 28.5 | 35.1 | 33.6 |
LibreYOLO has the best catalogue of state-of-the-art detectors, all behind one MIT-licensed Python API.
from libreyolo import LibreYOLO, SAMPLE_IMAGE
# LibreYOLO has the best catalogue of state-of-the-art models.
model = LibreYOLO("LibreRFDETRl.pt") # RF-DETR-L (transformer flagship)
results = model(SAMPLE_IMAGE, save=True) # run inference, save the annotated image
# Swap in any other model, same one-line API (weights auto-download):
# LibreYOLO("LibreYOLO9c.pt") # YOLO9-C
# LibreYOLO("LibreYOLOXx.pt") # YOLOX-X
# LibreYOLO("LibreDFINEx.pt") # D-FINE-X
# LibreYOLO("LibreRTDETRr50.pt") # RT-DETR-R50