About GMACs reported in the YOLO-Pose paper

[WongKinYiu]

❔Question

Why the GMACs of other methods reported in this paper are doubled when compare with GFLOPs reported in original papers.

Usually, FLOPs may = MACs or = 2 * MACs when use different definition. I have not checked which one is reported in the original paper, but it won't be MACs / 2.

[debapriyamaji]

@WongKinYiu ,

By definition, FLOPs = 2 * MACs. For other bottom-up approaches, all reported results are with flip-test. That's why the complexity is doubled.

Regards, Debapriya

[WongKinYiu]

Thanks.

[WongKinYiu]

@debapriyamaji

add yolor support.

Dataset	Model Name	Input Size	#Params	GMACS	AP[0.5:0.95]%	AP50%	AP75%
COCO	Yolov5m6_pose_960	960x960	41.4M	66.3	67.4	89.1	73.7
COCO	Yolorp6_pose_960	960x960	41.6M	100.6	70.4	90.3	78.1
COCO	Yolov5l6_pose_960	960x960	87.0M	145.6	69.4	90.2	76.1

Thanks for your great repo.

[debapriyamaji]

@WongKinYiu That's really awesome. Thanks for training yolor that surpasses yolov5l at lower complexity. Will add these results.

Regards, Debapriya