# parameters
nc: 80  # number of classes
depth_multiple: 1.0  # expand model depth
width_multiple: 1.0  # expand layer channels

# anchors
anchors:
  - [ 19,27,  44,40,  38,94 ]  # P3/8
  - [ 96,68,  86,152,  180,137 ]  # P4/16
  - [ 140,301,  303,264,  238,542 ]  # P5/32
  - [ 436,615,  739,380,  925,792 ]  # P6/64

# CSP-Darknet backbone
backbone:
  # [from, number, module, args]
  [[-1, 1, ReOrg, []],  # 0
   [-1, 1, Conv, [64, 3, 1]],  # 1-P1/2
   [-1, 1, Conv, [128, 3, 2]],  # 2-P2/4
   [-1, 3, BottleneckCSPA, [128]],
   [-1, 1, Conv, [256, 3, 2]],  # 4-P3/8
   [-1, 7, BottleneckCSPA, [256]],
   [-1, 1, Conv, [384, 3, 2]],  # 6-P4/16
   [-1, 7, BottleneckCSPA, [384]],
   [-1, 1, Conv, [512, 3, 2]], # 8-P5/32
   [-1, 3, BottleneckCSPA, [512]],
   [-1, 1, Conv, [640, 3, 2]], # 10-P6/64
   [-1, 3, BottleneckCSPA, [640]],  # 11
  ]

# CSP-Dark-PAN head
head:
  [[-1, 1, SPPCSPC, [320]], # 12
   [-1, 1, Conv, [256, 1, 1]],
   [-1, 1, nn.Upsample, [None, 2, 'nearest']],
   [-6, 1, Conv, [256, 1, 1]], # route backbone P5
   [[-1, -2], 1, Concat, [1]],
   [-1, 3, BottleneckCSPB, [256]], # 17
   [-1, 1, Conv, [192, 1, 1]],
   [-1, 1, nn.Upsample, [None, 2, 'nearest']],
   [-13, 1, Conv, [192, 1, 1]], # route backbone P4
   [[-1, -2], 1, Concat, [1]],
   [-1, 3, BottleneckCSPB, [192]], # 22
   [-1, 1, Conv, [128, 1, 1]],
   [-1, 1, nn.Upsample, [None, 2, 'nearest']],
   [-20, 1, Conv, [128, 1, 1]], # route backbone P3
   [[-1, -2], 1, Concat, [1]],
   [-1, 3, BottleneckCSPB, [128]], # 27
   [-1, 1, Conv, [256, 3, 1]],
   [-2, 1, Conv, [192, 3, 2]],
   [[-1, 22], 1, Concat, [1]],  # cat
   [-1, 3, BottleneckCSPB, [192]], # 31
   [-1, 1, Conv, [384, 3, 1]],
   [-2, 1, Conv, [256, 3, 2]],
   [[-1, 17], 1, Concat, [1]],  # cat
   [-1, 3, BottleneckCSPB, [256]], # 35
   [-1, 1, Conv, [512, 3, 1]],
   [-2, 1, Conv, [320, 3, 2]],
   [[-1, 12], 1, Concat, [1]],  # cat
   [-1, 3, BottleneckCSPB, [320]], # 39
   [-1, 1, Conv, [640, 3, 1]],

   [[28,32,36,40], 1, IDetect, [nc, anchors]],   # Detect(P3, P4, P5, P6)
  ]