PyTorch Object Detection :: meituan/YOLOv6

MT-YOLOv6

The YOLOv6 repository was published June 2022 by Meituan, and it claims new state-of-the-art performance on the COCO dataset benchmark. We'll leave it to the community to determine if this name is the best representation for the architecture.

https://blog.roboflow.com/yolov6/

In any case, it's clear MT-YOLOv6 (hereafter YOLOv6 for brevity) is popular. In a couple short weeks, the repo has attracted over 2,000+ stars and 300+ forks.

YOLOv6 claims to set a new state-of-the-art performance on the COCO dataset benchmark. As the authors detail, YOLOv6-s achieves 43.1 mAP on COCO val2017 dataset (with 520 FPS on T4 using TensorRT FP16 for bs32 inference).

(For point of comparison, YOLOv5-s achieves 37.4 mAP @ 0.95% on the same COCO benchmark.)
The YOLOv6 repository authors published the below evaluation graphic, demonstrating YOLOv6 outperforming YOLOv5 and YOLOX at similar sizes.