yolov5/models/hub/yolov3-tiny.yaml

# Parameters
nc: 80  # number of classes
depth_multiple: 1.0  # model depth multiple
width_multiple: 1.0  # layer channel multiple
anchors:
  - [ 10,14, 23,27, 37,58 ]  # P4/16
  - [ 81,82, 135,169, 344,319 ]  # P5/32

# YOLOv3-tiny backbone
backbone:
  # [from, number, module, args]
  [ [ -1, 1, Conv, [ 16, 3, 1 ] ],  # 0
    [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ],  # 1-P1/2
    [ -1, 1, Conv, [ 32, 3, 1 ] ],
    [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ],  # 3-P2/4
    [ -1, 1, Conv, [ 64, 3, 1 ] ],
    [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ],  # 5-P3/8
    [ -1, 1, Conv, [ 128, 3, 1 ] ],
    [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ],  # 7-P4/16
    [ -1, 1, Conv, [ 256, 3, 1 ] ],
    [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ],  # 9-P5/32
    [ -1, 1, Conv, [ 512, 3, 1 ] ],
    [ -1, 1, nn.ZeroPad2d, [ [ 0, 1, 0, 1 ] ] ],  # 11
    [ -1, 1, nn.MaxPool2d, [ 2, 1, 0 ] ],  # 12
  ]

# YOLOv3-tiny head
head:
  [ [ -1, 1, Conv, [ 1024, 3, 1 ] ],
    [ -1, 1, Conv, [ 256, 1, 1 ] ],
    [ -1, 1, Conv, [ 512, 3, 1 ] ],  # 15 (P5/32-large)

    [ -2, 1, Conv, [ 128, 1, 1 ] ],
    [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ],
    [ [ -1, 8 ], 1, Concat, [ 1 ] ],  # cat backbone P4
    [ -1, 1, Conv, [ 256, 3, 1 ] ],  # 19 (P4/16-medium)

    [ [ 19, 15 ], 1, Detect, [ nc, anchors ] ],  # Detect(P4, P5)
  ]