TensorRT_Transform/models/yolov5m_s.yaml

58 lines
1.6 KiB
YAML

# parameters
nc: 80 # number of classes
depth_multiple: 0.67 # model depth multiple
width_multiple: 0.75 # layer channel multiple
# anchors
anchors:
- [5,6, 8,14, 15,11] #P2/4
- [10,13, 16,30, 33,23] # P3/8
- [30,61, 62,45, 59,119] # P4/16
# YOLOv5 backbone
backbone:
# [from, number, module, args]
[[-1, 1, Focus, [64, 3]], # 0-P1/2
[-1, 1, Conv, [128, 3, 2]], # 1-P2/4
[-1, 3, C3, [128]], #160*160
[-1, 1, Conv, [256, 3, 2]], # 3-P3/8
[-1, 9, C3, [256]], #80*80
[-1, 1, Conv, [512, 3, 2]], # 5-P4/16
[-1, 9, C3, [512]], #40*40
[-1, 1, Conv, [1024, 3, 2]], # 7-P5/32
[-1, 1, SPP, [1024, [5, 9, 13]]],
[-1, 3, C3, [1024, False]], # 9 20*20
]
# YOLOv5 head
head:
[[-1, 1, Conv, [512, 1, 1]], #20*20
[-1, 1, nn.Upsample, [None, 2, 'nearest']], #40*40
[[-1, 6], 1, Concat, [1]], # cat backbone P4 40*40
[-1, 3, C3, [512, False]], # 13 40*40
[-1, 1, Conv, [512, 1, 1]], #40*40
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 4], 1, Concat, [1]], # cat backbone P3 80*80
[-1, 3, C3, [512, False]], # 17 (P3/8-small) 80*80
[-1, 1, Conv, [256, 1, 1]], #18 80*80
[-1, 1, nn.Upsample, [None, 2, 'nearest']], #19 160*160
[[-1, 2], 1, Concat, [1]], #20 cat backbone p2 160*160
[-1, 3, C3, [256, False]], #21 160*160
[-1, 1, Conv, [256, 3, 2]], #22 80*80
[[-1, 18], 1, Concat, [1]], #23 80*80
[-1, 3, C3, [256, False]], #24 80*80
[-1, 1, Conv, [512, 3, 2]], #25 40*40
[[-1, 14], 1, Concat, [1]], # 26 cat head P4 40*40
[-1, 3, C3, [1024, False]], # 27 (P4/16-medium) 40*40
[[21, 24, 27], 1, Detect, [nc, anchors]], # Detect(p2, P3, P4)
]