Closed WongKinYiu closed 2 years ago
@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
Thanks.
@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.
@WongKinYiu That's really awesome. Thanks for training yolor that surpasses yolov5l at lower complexity. Will add these results.
Regards, Debapriya
❔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.