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@ -11,13 +11,17 @@ Network|COCO mAP(0.5)|Resolution|Run Time(4xCore)|Run Time(1xCore)|FLOPs(G)|Para
[Yolo-FastestV1.1](https://github.com/dog-qiuqiu/Yolo-Fastest/tree/master/ModelZoo/yolo-fastest-1.1_coco)|24.40 %|320X320|26.60 ms|75.74 ms|0.252|0.35M
[Yolo-FastestV2](https://github.com/dog-qiuqiu/Yolo-FastestV2/tree/main/modelzoo)|24.10 %|352X352|23.8 ms|68.9 ms|0.212|0.25M
FastestDet|27.8%|512X512|21.51ms|34.62ms|*|0.25M
* ***Test platform RK3568 CPU，Based on [NCNN](https://github.com/Tencent/ncnn)***
# Improvement
* Anchor-Free
* Single scale detector head
* Cross grid multiple candidate targets
* Dynamic positive and negative sample allocation
# Multi-platform benchmark
Equipment|Computing backend|System|Framework|Run time(Single core)|Run time(Multi core)
:---:|:---:|:---:|:---:|:---:|:---:
Radxa rock3a|RK3568(arm-cpu)|Linux(aarch64)|ncnn|34.62ms|21.51ms
AMD|R5-5600(X86-cpu)|Linux(amd64)|ncnn|2.16ms|1.73ms
# How to use
## Dependent installation
* PiP(Note pytorch CUDA version selection)