49 lines
1.9 KiB
YAML
49 lines
1.9 KiB
YAML
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
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# YOLO12-seg instance segmentation model with P3/8 - P5/32 outputs
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# Model docs: https://docs.ultralytics.com/models/yolo12
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# Task docs: https://docs.ultralytics.com/tasks/segment
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# Parameters
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nc: 80 # number of classes
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scales: # model compound scaling constants, i.e. 'model=yolo12n-seg.yaml' will call yolo12-seg.yaml with scale 'n'
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# [depth, width, max_channels]
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n: [0.50, 0.25, 1024] # summary: 294 layers, 2,855,056 parameters, 2,855,040 gradients, 10.6 GFLOPs
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s: [0.50, 0.50, 1024] # summary: 294 layers, 9,938,592 parameters, 9,938,576 gradients, 35.7 GFLOPs
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m: [0.50, 1.00, 512] # summary: 314 layers, 22,505,376 parameters, 22,505,360 gradients, 123.5 GFLOPs
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l: [1.00, 1.00, 512] # summary: 510 layers, 28,756,992 parameters, 28,756,976 gradients, 145.1 GFLOPs
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x: [1.00, 1.50, 512] # summary: 510 layers, 64,387,264 parameters, 64,387,248 gradients, 324.6 GFLOPs
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# YOLO12n backbone
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backbone:
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# [from, repeats, module, args]
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- [-1, 1, Conv, [64, 3, 2]] # 0-P1/2
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- [-1, 1, Conv, [128, 3, 2]] # 1-P2/4
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- [-1, 2, C3k2, [256, False, 0.25]]
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- [-1, 1, Conv, [256, 3, 2]] # 3-P3/8
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- [-1, 2, C3k2, [512, False, 0.25]]
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- [-1, 1, Conv, [512, 3, 2]] # 5-P4/16
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- [-1, 4, A2C2f, [512, True, 4]]
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- [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32
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- [-1, 4, A2C2f, [1024, True, 1]] # 8
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# YOLO12n head
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head:
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- [-1, 1, nn.Upsample, [None, 2, "nearest"]]
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- [[-1, 6], 1, Concat, [1]] # cat backbone P4
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- [-1, 2, A2C2f, [512, False, -1]] # 11
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- [-1, 1, nn.Upsample, [None, 2, "nearest"]]
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- [[-1, 4], 1, Concat, [1]] # cat backbone P3
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- [-1, 2, A2C2f, [256, False, -1]] # 14
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- [-1, 1, Conv, [256, 3, 2]]
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- [[-1, 11], 1, Concat, [1]] # cat head P4
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- [-1, 2, A2C2f, [512, False, -1]] # 17
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- [-1, 1, Conv, [512, 3, 2]]
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- [[-1, 8], 1, Concat, [1]] # cat head P5
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- [-1, 2, C3k2, [1024, True]] # 20 (P5/32-large)
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- [[14, 17, 20], 1, Segment, [nc, 32, 256]] # Detect(P3, P4, P5)
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