39 lines
1.3 KiB
YAML
39 lines
1.3 KiB
YAML
# Ultralytics YOLO 🚀, AGPL-3.0 license
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# YOLOv9c object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
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# 618 layers, 25590912 parameters, 104.0 GFLOPs
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# Parameters
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nc: 80 # number of classes
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# GELAN backbone
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backbone:
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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, RepNCSPELAN4, [256, 128, 64, 1]] # 2
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- [-1, 1, ADown, [256]] # 3-P3/8
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- [-1, 1, RepNCSPELAN4, [512, 256, 128, 1]] # 4
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- [-1, 1, ADown, [512]] # 5-P4/16
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- [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]] # 6
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- [-1, 1, ADown, [512]] # 7-P5/32
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- [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]] # 8
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- [-1, 1, SPPELAN, [512, 256]] # 9
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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, 1, RepNCSPELAN4, [512, 512, 256, 1]] # 12
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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, 1, RepNCSPELAN4, [256, 256, 128, 1]] # 15 (P3/8-small)
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- [-1, 1, ADown, [256]]
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- [[-1, 12], 1, Concat, [1]] # cat head P4
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- [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]] # 18 (P4/16-medium)
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- [-1, 1, ADown, [512]]
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- [[-1, 9], 1, Concat, [1]] # cat head P5
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- [-1, 1, RepNCSPELAN4, [512, 512, 256, 1]] # 21 (P5/32-large)
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- [[15, 18, 21], 1, Detect, [nc]] # Detect(P3, P4, P5)
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