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| # Ultralytics YOLO 🚀, AGPL-3.0 license | |
| # YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect | |
| # 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] | |
| m: [0.67, 0.75, 768] # YOLOv8m summary: 295 layers, 25902640 parameters, 25902624 gradients, 79.3 GFLOPs | |
| # YOLOv8.0n 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, 3, C2f, [128, True]] | |
| - [-1, 1, Conv, [256, 3, 2]] # 3-P3/8 | |
| - [-1, 6, C2f, [256, True]] | |
| - [-1, 1, SCDown, [512, 3, 2]] # 5-P4/16 | |
| - [-1, 6, C2f, [512, True]] | |
| - [-1, 1, SCDown, [1024, 3, 2]] # 7-P5/32 | |
| - [-1, 3, C2fCIB, [1024, True]] | |
| - [-1, 1, SPPF, [1024, 5]] # 9 | |
| - [-1, 1, PSA, [1024]] # 10 | |
| # YOLOv8.0n head | |
| head: | |
| - [-1, 1, nn.Upsample, [None, 2, "nearest"]] | |
| - [[-1, 6], 1, Concat, [1]] # cat backbone P4 | |
| - [-1, 3, C2f, [512]] # 13 | |
| - [-1, 1, nn.Upsample, [None, 2, "nearest"]] | |
| - [[-1, 4], 1, Concat, [1]] # cat backbone P3 | |
| - [-1, 3, C2f, [256]] # 16 (P3/8-small) | |
| - [-1, 1, Conv, [256, 3, 2]] | |
| - [[-1, 13], 1, Concat, [1]] # cat head P4 | |
| - [-1, 3, C2fCIB, [512, True]] # 19 (P4/16-medium) | |
| - [-1, 1, SCDown, [512, 3, 2]] | |
| - [[-1, 10], 1, Concat, [1]] # cat head P5 | |
| - [-1, 3, C2fCIB, [1024, True]] # 22 (P5/32-large) | |
| - [[16, 19, 22], 1, v10Detect, [nc]] # Detect(P3, P4, P5) | |