43 lines
1.4 KiB
YAML
43 lines
1.4 KiB
YAML
# Ultralytics YOLO 🚀, AGPL-3.0 license
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# YOLOv10 object detection model. For Usage examples see https://docs.ultralytics.com/tasks/detect
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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=yolov10n.yaml' will call yolov10.yaml with scale 'n'
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# [depth, width, max_channels]
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n: [0.33, 0.25, 1024]
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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, 3, C2f, [128, True]]
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- [-1, 1, Conv, [256, 3, 2]] # 3-P3/8
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- [-1, 6, C2f, [256, True]]
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- [-1, 1, SCDown, [512, 3, 2]] # 5-P4/16
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- [-1, 6, C2f, [512, True]]
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- [-1, 1, SCDown, [1024, 3, 2]] # 7-P5/32
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- [-1, 3, C2f, [1024, True]]
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- [-1, 1, SPPF, [1024, 5]] # 9
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- [-1, 1, PSA, [1024]] # 10
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# YOLOv10.0n 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, 3, C2f, [512]] # 13
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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, 3, C2f, [256]] # 16 (P3/8-small)
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- [-1, 1, Conv, [256, 3, 2]]
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- [[-1, 13], 1, Concat, [1]] # cat head P4
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- [-1, 3, C2f, [512]] # 19 (P4/16-medium)
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- [-1, 1, SCDown, [512, 3, 2]]
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- [[-1, 10], 1, Concat, [1]] # cat head P5
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- [-1, 3, C2fCIB, [1024, True, True]] # 22 (P5/32-large)
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- [[16, 19, 22], 1, v10Detect, [nc]] # Detect(P3, P4, P5)
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