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58 lines
1.9 KiB
58 lines
1.9 KiB
2 years ago
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# Ultralytics YOLO 🚀, GPL-3.0 license
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# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
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# Parameters
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nc: 1 # number of classes
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kpt_shape: [17, 3] # number of keypoints, number of dims (2 for x,y or 3 for x,y,visible)
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scales: # model compound scaling constants, i.e. 'model=yolov8n-p6.yaml' will call yolov8-p6.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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s: [0.33, 0.50, 1024]
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m: [0.67, 0.75, 768]
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l: [1.00, 1.00, 512]
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x: [1.00, 1.25, 512]
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# YOLOv8.0x6 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, 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, Conv, [512, 3, 2]] # 5-P4/16
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- [-1, 6, C2f, [512, True]]
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- [-1, 1, Conv, [768, 3, 2]] # 7-P5/32
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- [-1, 3, C2f, [768, True]]
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- [-1, 1, Conv, [1024, 3, 2]] # 9-P6/64
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- [-1, 3, C2f, [1024, True]]
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- [-1, 1, SPPF, [1024, 5]] # 11
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# YOLOv8.0x6 head
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head:
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- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
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- [[-1, 8], 1, Concat, [1]] # cat backbone P5
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- [-1, 3, C2, [768, False]] # 14
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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, C2, [512, False]] # 17
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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, C2, [256, False]] # 20 (P3/8-small)
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- [-1, 1, Conv, [256, 3, 2]]
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- [[-1, 17], 1, Concat, [1]] # cat head P4
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- [-1, 3, C2, [512, False]] # 23 (P4/16-medium)
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- [-1, 1, Conv, [512, 3, 2]]
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- [[-1, 14], 1, Concat, [1]] # cat head P5
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- [-1, 3, C2, [768, False]] # 26 (P5/32-large)
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- [-1, 1, Conv, [768, 3, 2]]
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- [[-1, 11], 1, Concat, [1]] # cat head P6
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- [-1, 3, C2, [1024, False]] # 29 (P6/64-xlarge)
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- [[20, 23, 26, 29], 1, Pose, [nc, kpt_shape]] # Pose(P3, P4, P5, P6)
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