# Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Employs Ghost convolutions and modules proposed in Huawei's GhostNet in https://arxiv.org/abs/1911.11907v2

# Parameters
nc: 80 # number of classes
scales: # model compound scaling constants, i.e. 'model=yolov8n.yaml' will call yolov8.yaml with scale 'n'
  # [depth, width, max_channels]
  n: [0.33, 0.25, 1024] # YOLOv8n-ghost summary: 403 layers,  1865316 parameters,  1865300 gradients,   5.8 GFLOPs
  s: [0.33, 0.50, 1024] # YOLOv8s-ghost summary: 403 layers,  5960072 parameters,  5960056 gradients,  16.4 GFLOPs
  m: [0.67, 0.75, 768] # YOLOv8m-ghost summary: 603 layers, 10336312 parameters, 10336296 gradients,  32.7 GFLOPs
  l: [1.00, 1.00, 512] # YOLOv8l-ghost summary: 803 layers, 14277872 parameters, 14277856 gradients,  53.7 GFLOPs
  x: [1.00, 1.25, 512] # YOLOv8x-ghost summary: 803 layers, 22229308 parameters, 22229292 gradients,  83.3 GFLOPs

# YOLOv8.0n-ghost backbone
backbone:
  # [from, repeats, module, args]
  - [-1, 1, Conv, [64, 3, 2]] # 0-P1/2
  - [-1, 1, GhostConv, [128, 3, 2]] # 1-P2/4
  - [-1, 3, C3Ghost, [128, True]]
  - [-1, 1, GhostConv, [256, 3, 2]] # 3-P3/8
  - [-1, 6, C3Ghost, [256, True]]
  - [-1, 1, GhostConv, [512, 3, 2]] # 5-P4/16
  - [-1, 6, C3Ghost, [512, True]]
  - [-1, 1, GhostConv, [1024, 3, 2]] # 7-P5/32
  - [-1, 3, C3Ghost, [1024, True]]
  - [-1, 1, SPPF, [1024, 5]] # 9

# YOLOv8.0n head
head:
  - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
  - [[-1, 6], 1, Concat, [1]] # cat backbone P4
  - [-1, 3, C3Ghost, [512]] # 12

  - [-1, 1, nn.Upsample, [None, 2, "nearest"]]
  - [[-1, 4], 1, Concat, [1]] # cat backbone P3
  - [-1, 3, C3Ghost, [256]] # 15 (P3/8-small)

  - [-1, 1, GhostConv, [256, 3, 2]]
  - [[-1, 12], 1, Concat, [1]] # cat head P4
  - [-1, 3, C3Ghost, [512]] # 18 (P4/16-medium)

  - [-1, 1, GhostConv, [512, 3, 2]]
  - [[-1, 9], 1, Concat, [1]] # cat head P5
  - [-1, 3, C3Ghost, [1024]] # 21 (P5/32-large)

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