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# YOLOv9
# parameters
nc: 80 # number of classes
depth_multiple: 1.0 # model depth multiple
width_multiple: 1.0 # layer channel multiple
#activation: nn.LeakyReLU(0.1)
#activation: nn.ReLU()
# anchors
anchors: 3
# gelan backbone
backbone:
[
# conv down
[-1, 1, Conv, [32, 3, 2]], # 0-P1/2
# conv down
[-1, 1, Conv, [64, 3, 2]], # 1-P2/4
# elan-1 block
[-1, 1, ELAN1, [64, 64, 32]], # 2
# avg-conv down
[-1, 1, AConv, [128]], # 3-P3/8
# elan-2 block
[-1, 1, RepNCSPELAN4, [128, 128, 64, 3]], # 4
# avg-conv down
[-1, 1, AConv, [192]], # 5-P4/16
# elan-2 block
[-1, 1, RepNCSPELAN4, [192, 192, 96, 3]], # 6
# avg-conv down
[-1, 1, AConv, [256]], # 7-P5/32
# elan-2 block
[-1, 1, RepNCSPELAN4, [256, 256, 128, 3]], # 8
]
# elan head
head:
[
# elan-spp block
[-1, 1, SPPELAN, [256, 128]], # 9
# up-concat merge
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 6], 1, Concat, [1]], # cat backbone P4
# elan-2 block
[-1, 1, RepNCSPELAN4, [192, 192, 96, 3]], # 12
# up-concat merge
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 4], 1, Concat, [1]], # cat backbone P3
# elan-2 block
[-1, 1, RepNCSPELAN4, [128, 128, 64, 3]], # 15
# avg-conv-down merge
[-1, 1, AConv, [96]],
[[-1, 12], 1, Concat, [1]], # cat head P4
# elan-2 block
[-1, 1, RepNCSPELAN4, [192, 192, 96, 3]], # 18 (P4/16-medium)
# avg-conv-down merge
[-1, 1, AConv, [128]],
[[-1, 9], 1, Concat, [1]], # cat head P5
# elan-2 block
[-1, 1, RepNCSPELAN4, [256, 256, 128, 3]], # 21 (P5/32-large)
# elan-spp block
[8, 1, SPPELAN, [256, 128]], # 22
# up-concat merge
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 6], 1, Concat, [1]], # cat backbone P4
# elan-2 block
[-1, 1, RepNCSPELAN4, [192, 192, 96, 3]], # 25
# up-concat merge
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 4], 1, Concat, [1]], # cat backbone P3
# elan-2 block
[-1, 1, RepNCSPELAN4, [128, 128, 64, 3]], # 28
# detect
[[28, 25, 22, 15, 18, 21], 1, DualDDetect, [nc]], # Detect(P3, P4, P5)
]
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