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| # Ultralytics YOLO 🚀, AGPL-3.0 license | |
| # YOLOv6 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/models/yolov6 | |
| # Parameters | |
| nc: 80 # number of classes | |
| activation: nn.ReLU() # (optional) model default activation function | |
| scales: # model compound scaling constants, i.e. 'model=yolov6n.yaml' will call yolov8.yaml with scale 'n' | |
| # [depth, width, max_channels] | |
| n: [0.33, 0.25, 1024] | |
| s: [0.33, 0.50, 1024] | |
| m: [0.67, 0.75, 768] | |
| l: [1.00, 1.00, 512] | |
| x: [1.00, 1.25, 512] | |
| # YOLOv6-3.0s backbone | |
| backbone: | |
| # [from, repeats, module, args] | |
| - [-1, 1, Conv, [64, 3, 2]] # 0-P1/2 | |
| - [-1, 1, Conv, [128, 3, 2]] # 1-P2/4 | |
| - [-1, 6, Conv, [128, 3, 1]] | |
| - [-1, 1, Conv, [256, 3, 2]] # 3-P3/8 | |
| - [-1, 12, Conv, [256, 3, 1]] | |
| - [-1, 1, Conv, [512, 3, 2]] # 5-P4/16 | |
| - [-1, 18, Conv, [512, 3, 1]] | |
| - [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32 | |
| - [-1, 6, Conv, [1024, 3, 1]] | |
| - [-1, 1, SPPF, [1024, 5]] # 9 | |
| # YOLOv6-3.0s head | |
| head: | |
| - [-1, 1, Conv, [256, 1, 1]] | |
| - [-1, 1, nn.ConvTranspose2d, [256, 2, 2, 0]] | |
| - [[-1, 6], 1, Concat, [1]] # cat backbone P4 | |
| - [-1, 1, Conv, [256, 3, 1]] | |
| - [-1, 9, Conv, [256, 3, 1]] # 14 | |
| - [-1, 1, Conv, [128, 1, 1]] | |
| - [-1, 1, nn.ConvTranspose2d, [128, 2, 2, 0]] | |
| - [[-1, 4], 1, Concat, [1]] # cat backbone P3 | |
| - [-1, 1, Conv, [128, 3, 1]] | |
| - [-1, 9, Conv, [128, 3, 1]] # 19 | |
| - [-1, 1, Conv, [128, 3, 2]] | |
| - [[-1, 15], 1, Concat, [1]] # cat head P4 | |
| - [-1, 1, Conv, [256, 3, 1]] | |
| - [-1, 9, Conv, [256, 3, 1]] # 23 | |
| - [-1, 1, Conv, [256, 3, 2]] | |
| - [[-1, 10], 1, Concat, [1]] # cat head P5 | |
| - [-1, 1, Conv, [512, 3, 1]] | |
| - [-1, 9, Conv, [512, 3, 1]] # 27 | |
| - [[19, 23, 27], 1, Detect, [nc]] # Detect(P3, P4, P5) | |