# YOLOv5 🚀 by Ultralytics, GPL-3.0 license # Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple anchors: 4 # - [10,13, 16,30, 33,23] # P3/8 # - [30,61, 62,45, 59,119] # P4/16 # - [116,90, 156,198, 373,326] # P5/32 # YOLOv5 v6.0 backbone backbone: # [from, number, module, args] [[-1, 1, Conv, [64, 6, 2, 2]], # 0-P1/2 [-1, 1, Conv, [128, 3, 2]], # 1-P2/4 [-1, 3, C3, [128]], [-1, 1, Conv, [256, 3, 2]], # 3-P3/8 [-1, 6, C3, [256]], [-1, 1, Conv, [512, 3, 2]], # 5-P4/16 [-1, 9, C3, [512]], [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32 [-1, 3, C3TR, [1024]], [-1, 1, SPPF, [1024, 5]], # 9 ] # YOLOv5 v6.0 head head: [[-1, 1, Conv, [512, 1, 1]], [-1, 1, nn.Upsample, [None, 2, 'nearest']], [[-1, 6], 1, Concat, [1]], # cat backbone P4 [-1, 3, C3, [512, False]], # 13 [-1, 1, Conv, [256, 1, 1]], [-1, 1, nn.Upsample, [None, 2, 'nearest']], [[-1, 4], 1, Concat, [1]], # cat backbone P3 [-1, 3, C3, [256, False]], # 17 (P3/8-small) [ -1, 1, Conv, [ 128, 1, 1 ] ], [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], [ [ -1, 2 ], 1, Concat, [ 1 ] ], # cat backbone P2 [-1, 1, SPP, [128, [5, 9, 13]]], [ -1, 3, C3, [ 128, False ] ], # (P2/4-xsmall) [-1, 1, CBAM, [128]], # 23 [ -1, 1, Conv, [ 128, 3, 2 ] ], [ [ -1, 18, 4], 1, Concat, [ 1 ] ], # cat head P3 [-1, 1, SPP, [256, [5, 9, 13]]], [ -1, 3, C3, [ 256, False ] ], # (P3/8-small) [-1, 1, CBAM, [256]], # 28 [-1, 1, Conv, [256, 3, 2]], [[-1, 14, 6], 1, Concat, [1]], # cat head P4 [-1, 1, SPP, [512, [3, 7, 11]]], [-1, 3, C3, [512, False]], # (P4/16-medium) [-1, 1, CBAM, [512]], # 33 [-1, 1, Conv, [512, 3, 2]], [[-1, 10], 1, Concat, [1]], # cat head P5 [-1, 1, SPP, [1024, [3, 5, 7]]], [-1, 3, C3TR, [1024, False]], # (P5/32-large) [-1, 1, CBAM, [1024]], # 38 [[23, 28, 33, 38], 1, Detect, [nc,anchors]], # Detect(P2, P3, P4, P5) ]