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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Vivek Malvi <vivekmalvi@raoinformationtechnology.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: iscyy <wenvoi@163.com> Co-authored-by: Laughing-q <1185102784@qq.com> Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com> Co-authored-by: Prince kumar <85225054+prince0310@users.noreply.github.com>
26 lines
882 B
YAML
26 lines
882 B
YAML
# Ultralytics YOLO 🚀, AGPL-3.0 license
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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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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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s: [0.33, 0.50, 1024]
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m: [0.67, 0.75, 1024]
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l: [1.00, 1.00, 1024]
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x: [1.00, 1.25, 1024]
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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, ResNetLayer, [3, 64, 1, True, 1]] # 0-P1/2
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- [-1, 1, ResNetLayer, [64, 64, 1, False, 3]] # 1-P2/4
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- [-1, 1, ResNetLayer, [256, 128, 2, False, 4]] # 2-P3/8
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- [-1, 1, ResNetLayer, [512, 256, 2, False, 6]] # 3-P4/16
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- [-1, 1, ResNetLayer, [1024, 512, 2, False, 3]] # 4-P5/32
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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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