Features
- Release YOLOv6-Segmentation models at full scales
- Achieve the state-of-the-art accuracy in Real-time Instance Segmentation.
Performance of YOLOv6-seg models
| Model | Size | mAPbox 50-95 |
mAPmask 50-95 |
SpeedT4 trt fp16 b1 (fps) |
Params (M) |
FLOPs (G) |
|---|---|---|---|---|---|---|
| YOLOv6-N | 640 | 35.3 | 31.2 | 645 | 4.9 | 7.0 |
| YOLOv6-S | 640 | 44.0 | 38.0 | 292 | 19.6 | 27.7 |
| YOLOv6-M | 640 | 48.2 | 41.3 | 148 | 37.1 | 54.3 |
| YOLOv6-L | 640 | 51.1 | 43.7 | 93 | 63.6 | 95.5 |
| YOLOv6-X | 640 | 52.2 | 44.8 | 47 | 119.1 | 175.5 |
Table Notes
- All checkpoints are trained from scratch on COCO for 300 epochs without distillation.
- Results of the mAP and speed are evaluated on COCO val2017 dataset with the input resolution of 640×640.
- Speed is tested with TensorRT 8.5 on T4 without post-processing.