轻量化YOLOv5s网络车底危险物识别算法
金鑫,庄建军,徐子恒
Lightweight YOLOv5s network-based algorithm for identifying hazardous objects under vehicles
Xin JIN,Jian-jun ZHUANG,Zi-heng XU
表 1
Backbone网络结构参数
Tab.1
Structure parameters of Backbone network
序号
模块重复次数
模块名
参数配置
输出大小
0
1
Focus
[3, 32, 3]
32×320×320
1
1
S-(2)
[32, 64, 2]
64×160×160
2
1
S-(1)
[64, 64, 1]
64×160×160
3
1
S-(2)
[64, 128, 2]
128×80×80
4
3
S-(1)
[128, 128, 1]
128×80×80
5
1
S-(2)
[128, 256, 2]
256×40×40
6
3
S-(1)
[256, 256, 1]
256×40×40
7
1
S-(2)
[256, 512, 2]
512×20×20
8
1
SPPF
[512, 512, [5, 5, 5]]
512×20×20
9
1
S-(1)
[512, 512, 1]
512×20×20