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# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv9c object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
# 618 layers, 25590912 parameters, 104.0 GFLOPs

# 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]] # Detect(P3, P4, P5)