add yolo v10 and modify pipeline
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# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
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# Parameters
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nc: 1000 # number of classes
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nc: 1000 # number of classes
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scales: # model compound scaling constants, i.e. 'model=yolov8n-cls.yaml' will call yolov8-cls.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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@ -14,16 +14,16 @@ scales: # model compound scaling constants, i.e. 'model=yolov8n-cls.yaml' will c
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# YOLOv8.0n 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, 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, 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, 1, Conv, [512, 3, 2]] # 5-P4/16
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- [-1, 6, C2f, [512, True]]
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- [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32
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- [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32
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- [-1, 3, C2f, [1024, True]]
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# YOLOv8.0n head
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head:
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- [-1, 1, Classify, [nc]] # Classify
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- [-1, 1, Classify, [nc]] # Classify
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