yolov5s.yaml

# YOLOv5 🚀 by Ultralytics, GPL-3.0 license

# Parameters
nc: 80  # number of classes
depth_multiple: 0.33  # model depth multiple
width_multiple: 0.50  # layer channel multiple
anchors:
  - [ 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]  # 3, 256, 256
  [ [ -1, 1, Conv, [ 64, 6, 2, 2 ] ],  # 0-P1/2  32, 128, 128
    [ -1, 1, Conv, [ 128, 3, 2 ] ],  # 1-P2/4  64, 64, 64
    [ -1, 3, C3, [ 128 ] ],
    [ -1, 1, Conv, [ 256, 3, 2 ] ],  # 3-P3/8  128, 32, 32
    [ -1, 6, C3, [ 256 ] ],
    [ -1, 1, Conv, [ 512, 3, 2 ] ],  # 5-P4/16  256, 16, 16
    [ -1, 9, C3, [ 512 ] ],
    [ -1, 1, Conv, [ 1024, 3, 2 ] ],  # 7-P5/32  512, 8, 8
    [ -1, 3, C3, [ 1024 ] ],
    [ -1, 1, SPPF, [ 1024, 5 ] ],  # 9
  ]

# YOLOv5 v6.0 head
head:
  [ [ -1, 1, Conv, [ 512, 1, 1 ] ],  # 256, 8, 8
    [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],  # 256, 16, 16
    [ [ -1, 6 ], 1, Concat, [ 1 ] ],  # cat backbone P4  512, 16, 16
    [ -1, 3, C3, [ 512, False ] ],  # 13  256, 16, 16

    [ -1, 1, Conv, [ 256, 1, 1 ] ],  # 128, 16, 16
    [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],  # 128, 32, 32
    [ [ -1, 4 ], 1, Concat, [ 1 ] ],  # cat backbone P3  256, 32, 32
    [ -1, 3, C3, [ 256, False ] ],  # 17 (P3/8-small)  128, 32, 32

    [ -1, 1, Conv, [ 256, 3, 2 ] ],  # 128, 16, 16
    [ [ -1, 14 ], 1, Concat, [ 1 ] ],  # cat head P4  256, 16, 16
    [ -1, 3, C3, [ 512, False ] ],  # 20 (P4/16-medium)  256, 16, 16

    [ -1, 1, Conv, [ 512, 3, 2 ] ],  # 256, 8, 8
    [ [ -1, 10 ], 1, Concat, [ 1 ] ],  # cat head P5  512, 8, 8
    [ -1, 3, C3, [ 1024, False ] ],  # 23 (P5/32-large)  512, 8, 8

    [ [ 17, 20, 23 ], 1, Detect, [ nc, anchors ] ],  # Detect(P3, P4, P5)
  ]