# 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, [16, 3, 2]], # 0-P1/2 # conv down [-1, 1, Conv, [32, 3, 2]], # 1-P2/4 # elan-1 block [-1, 1, ELAN1, [32, 32, 16]], # 2 # avg-conv down [-1, 1, AConv, [64]], # 3-P3/8 # elan-2 block [-1, 1, RepNCSPELAN4, [64, 64, 32, 3]], # 4 # avg-conv down [-1, 1, AConv, [96]], # 5-P4/16 # elan-2 block [-1, 1, RepNCSPELAN4, [96, 96, 48, 3]], # 6 # avg-conv down [-1, 1, AConv, [128]], # 7-P5/32 # elan-2 block [-1, 1, RepNCSPELAN4, [128, 128, 64, 3]], # 8 ] # elan head head: [ # elan-spp block [-1, 1, SPPELAN, [128, 64]], # 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, [96, 96, 48, 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, [64, 64, 32, 3]], # 15 # avg-conv-down merge [-1, 1, AConv, [48]], [[-1, 12], 1, Concat, [1]], # cat head P4 # elan-2 block [-1, 1, RepNCSPELAN4, [96, 96, 48, 3]], # 18 (P4/16-medium) # avg-conv-down merge [-1, 1, AConv, [64]], [[-1, 9], 1, Concat, [1]], # cat head P5 # elan-2 block [-1, 1, RepNCSPELAN4, [128, 128, 64, 3]], # 21 (P5/32-large) # elan-spp block [8, 1, SPPELAN, [128, 64]], # 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, [96, 96, 48, 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, [64, 64, 32, 3]], # 28 # detect [[28, 25, 22, 15, 18, 21], 1, DualDDetect, [nc]], # Detect(P3, P4, P5) ]