# YOLOv9

# parameters
nc: 80  # number of classes

# gelan backbone
backbone:
  - [-1, 1, Conv, [64, 3, 2]]  # 0-P1/2
  - [-1, 1, Conv, [128, 3, 2]]  # 1-P2/4
  - [-1, 1, RepNCSPELAN4, [256, 128, 64, 1]]  # 2
  - [-1, 1, ADown, [256]]  # 3-P3/8
  - [-1, 1, RepNCSPELAN4, [512, 256, 128, 1]]  # 4
  - [-1, 1, ADown, [512]]  # 5-P4/16
  - [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]]  # 6
  - [-1, 1, ADown, [512]]  # 7-P5/32
  - [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]]  # 8
  - [-1, 1, SPPELAN, [512, 256]]  # 9

head:
  - [-1, 1, nn.Upsample, [None, 2, 'nearest']]
  - [[-1, 6], 1, Concat, [1]]  # cat backbone P4
  - [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]]  # 12

  - [-1, 1, nn.Upsample, [None, 2, 'nearest']]
  - [[-1, 4], 1, Concat, [1]]  # cat backbone P3
  - [-1, 1, RepNCSPELAN4, [256, 256, 128, 1]]  # 15 (P3/8-small)

  - [-1, 1, ADown, [256]]
  - [[-1, 12], 1, Concat, [1]]  # cat head P4
  - [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]]  # 18 (P4/16-medium)

  - [-1, 1, ADown, [512]]
  - [[-1, 9], 1, Concat, [1]]  # cat head P5
  - [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]]  # 21 (P5/32-large)

  - [[15, 18, 21], 1, Detect, [nc]]  # DDetect(P3, P4, P5)