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Update YOLOv3 and YOLOv5 YAMLs (#7574)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-01-14 20:10:32 +01:00 • committed by GitHub
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51 changed files with 284 additions and 304 deletions
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60
ultralytics/cfg/models/v3/yolov3-spp.yaml
View file

@ -9,40 +9,38 @@ width_multiple: 1.0 # layer channel multiple
# darknet53 backbone
backbone:
# [from, number, module, args]
[[-1, 1, Conv, [32, 3, 1]], # 0
[-1, 1, Conv, [64, 3, 2]], # 1-P1/2
[-1, 1, Bottleneck, [64]],
[-1, 1, Conv, [128, 3, 2]], # 3-P2/4
[-1, 2, Bottleneck, [128]],
[-1, 1, Conv, [256, 3, 2]], # 5-P3/8
[-1, 8, Bottleneck, [256]],
[-1, 1, Conv, [512, 3, 2]], # 7-P4/16
[-1, 8, Bottleneck, [512]],
[-1, 1, Conv, [1024, 3, 2]], # 9-P5/32
[-1, 4, Bottleneck, [1024]], # 10
]
- [-1, 1, Conv, [32, 3, 1]] # 0
- [-1, 1, Conv, [64, 3, 2]] # 1-P1/2
- [-1, 1, Bottleneck, [64]]
- [-1, 1, Conv, [128, 3, 2]] # 3-P2/4
- [-1, 2, Bottleneck, [128]]
- [-1, 1, Conv, [256, 3, 2]] # 5-P3/8
- [-1, 8, Bottleneck, [256]]
- [-1, 1, Conv, [512, 3, 2]] # 7-P4/16
- [-1, 8, Bottleneck, [512]]
- [-1, 1, Conv, [1024, 3, 2]] # 9-P5/32
- [-1, 4, Bottleneck, [1024]] # 10
# YOLOv3-SPP head
head:
[[-1, 1, Bottleneck, [1024, False]],
[-1, 1, SPP, [512, [5, 9, 13]]],
[-1, 1, Conv, [1024, 3, 1]],
[-1, 1, Conv, [512, 1, 1]],
[-1, 1, Conv, [1024, 3, 1]], # 15 (P5/32-large)
- [-1, 1, Bottleneck, [1024, False]]
- [-1, 1, SPP, [512, [5, 9, 13]]]
- [-1, 1, Conv, [1024, 3, 1]]
- [-1, 1, Conv, [512, 1, 1]]
- [-1, 1, Conv, [1024, 3, 1]] # 15 (P5/32-large)
[-2, 1, Conv, [256, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 8], 1, Concat, [1]], # cat backbone P4
[-1, 1, Bottleneck, [512, False]],
[-1, 1, Bottleneck, [512, False]],
[-1, 1, Conv, [256, 1, 1]],
[-1, 1, Conv, [512, 3, 1]], # 22 (P4/16-medium)
- [-2, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 8], 1, Concat, [1]] # cat backbone P4
- [-1, 1, Bottleneck, [512, False]]
- [-1, 1, Bottleneck, [512, False]]
- [-1, 1, Conv, [256, 1, 1]]
- [-1, 1, Conv, [512, 3, 1]] # 22 (P4/16-medium)
[-2, 1, Conv, [128, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 6], 1, Concat, [1]], # cat backbone P3
[-1, 1, Bottleneck, [256, False]],
[-1, 2, Bottleneck, [256, False]], # 27 (P3/8-small)
- [-2, 1, Conv, [128, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 6], 1, Concat, [1]] # cat backbone P3
- [-1, 1, Bottleneck, [256, False]]
- [-1, 2, Bottleneck, [256, False]] # 27 (P3/8-small)
[[27, 22, 15], 1, Detect, [nc]], # Detect(P3, P4, P5)
]
- [[27, 22, 15], 1, Detect, [nc]] # Detect(P3, P4, P5)

44
ultralytics/cfg/models/v3/yolov3-tiny.yaml
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@ -9,31 +9,29 @@ width_multiple: 1.0 # layer channel multiple
# YOLOv3-tiny backbone
backbone:
# [from, number, module, args]
[[-1, 1, Conv, [16, 3, 1]], # 0
[-1, 1, nn.MaxPool2d, [2, 2, 0]], # 1-P1/2
[-1, 1, Conv, [32, 3, 1]],
[-1, 1, nn.MaxPool2d, [2, 2, 0]], # 3-P2/4
[-1, 1, Conv, [64, 3, 1]],
[-1, 1, nn.MaxPool2d, [2, 2, 0]], # 5-P3/8
[-1, 1, Conv, [128, 3, 1]],
[-1, 1, nn.MaxPool2d, [2, 2, 0]], # 7-P4/16
[-1, 1, Conv, [256, 3, 1]],
[-1, 1, nn.MaxPool2d, [2, 2, 0]], # 9-P5/32
[-1, 1, Conv, [512, 3, 1]],
[-1, 1, nn.ZeroPad2d, [[0, 1, 0, 1]]], # 11
[-1, 1, nn.MaxPool2d, [2, 1, 0]], # 12
]
- [-1, 1, Conv, [16, 3, 1]] # 0
- [-1, 1, nn.MaxPool2d, [2, 2, 0]] # 1-P1/2
- [-1, 1, Conv, [32, 3, 1]]
- [-1, 1, nn.MaxPool2d, [2, 2, 0]] # 3-P2/4
- [-1, 1, Conv, [64, 3, 1]]
- [-1, 1, nn.MaxPool2d, [2, 2, 0]] # 5-P3/8
- [-1, 1, Conv, [128, 3, 1]]
- [-1, 1, nn.MaxPool2d, [2, 2, 0]] # 7-P4/16
- [-1, 1, Conv, [256, 3, 1]]
- [-1, 1, nn.MaxPool2d, [2, 2, 0]] # 9-P5/32
- [-1, 1, Conv, [512, 3, 1]]
- [-1, 1, nn.ZeroPad2d, [[0, 1, 0, 1]]] # 11
- [-1, 1, nn.MaxPool2d, [2, 1, 0]] # 12
# YOLOv3-tiny head
head:
[[-1, 1, Conv, [1024, 3, 1]],
[-1, 1, Conv, [256, 1, 1]],
[-1, 1, Conv, [512, 3, 1]], # 15 (P5/32-large)
- [-1, 1, Conv, [1024, 3, 1]]
- [-1, 1, Conv, [256, 1, 1]]
- [-1, 1, Conv, [512, 3, 1]] # 15 (P5/32-large)
[-2, 1, Conv, [128, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 8], 1, Concat, [1]], # cat backbone P4
[-1, 1, Conv, [256, 3, 1]], # 19 (P4/16-medium)
- [-2, 1, Conv, [128, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 8], 1, Concat, [1]] # cat backbone P4
- [-1, 1, Conv, [256, 3, 1]] # 19 (P4/16-medium)
[[19, 15], 1, Detect, [nc]], # Detect(P4, P5)
]
- [[19, 15], 1, Detect, [nc]] # Detect(P4, P5)

60
ultralytics/cfg/models/v3/yolov3.yaml
View file

@ -9,40 +9,38 @@ width_multiple: 1.0 # layer channel multiple
# darknet53 backbone
backbone:
# [from, number, module, args]
[[-1, 1, Conv, [32, 3, 1]], # 0
[-1, 1, Conv, [64, 3, 2]], # 1-P1/2
[-1, 1, Bottleneck, [64]],
[-1, 1, Conv, [128, 3, 2]], # 3-P2/4
[-1, 2, Bottleneck, [128]],
[-1, 1, Conv, [256, 3, 2]], # 5-P3/8
[-1, 8, Bottleneck, [256]],
[-1, 1, Conv, [512, 3, 2]], # 7-P4/16
[-1, 8, Bottleneck, [512]],
[-1, 1, Conv, [1024, 3, 2]], # 9-P5/32
[-1, 4, Bottleneck, [1024]], # 10
]
- [-1, 1, Conv, [32, 3, 1]] # 0
- [-1, 1, Conv, [64, 3, 2]] # 1-P1/2
- [-1, 1, Bottleneck, [64]]
- [-1, 1, Conv, [128, 3, 2]] # 3-P2/4
- [-1, 2, Bottleneck, [128]]
- [-1, 1, Conv, [256, 3, 2]] # 5-P3/8
- [-1, 8, Bottleneck, [256]]
- [-1, 1, Conv, [512, 3, 2]] # 7-P4/16
- [-1, 8, Bottleneck, [512]]
- [-1, 1, Conv, [1024, 3, 2]] # 9-P5/32
- [-1, 4, Bottleneck, [1024]] # 10
# YOLOv3 head
head:
[[-1, 1, Bottleneck, [1024, False]],
[-1, 1, Conv, [512, 1, 1]],
[-1, 1, Conv, [1024, 3, 1]],
[-1, 1, Conv, [512, 1, 1]],
[-1, 1, Conv, [1024, 3, 1]], # 15 (P5/32-large)
- [-1, 1, Bottleneck, [1024, False]]
- [-1, 1, Conv, [512, 1, 1]]
- [-1, 1, Conv, [1024, 3, 1]]
- [-1, 1, Conv, [512, 1, 1]]
- [-1, 1, Conv, [1024, 3, 1]] # 15 (P5/32-large)
[-2, 1, Conv, [256, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 8], 1, Concat, [1]], # cat backbone P4
[-1, 1, Bottleneck, [512, False]],
[-1, 1, Bottleneck, [512, False]],
[-1, 1, Conv, [256, 1, 1]],
[-1, 1, Conv, [512, 3, 1]], # 22 (P4/16-medium)
- [-2, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 8], 1, Concat, [1]] # cat backbone P4
- [-1, 1, Bottleneck, [512, False]]
- [-1, 1, Bottleneck, [512, False]]
- [-1, 1, Conv, [256, 1, 1]]
- [-1, 1, Conv, [512, 3, 1]] # 22 (P4/16-medium)
[-2, 1, Conv, [128, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 6], 1, Concat, [1]], # cat backbone P3
[-1, 1, Bottleneck, [256, False]],
[-1, 2, Bottleneck, [256, False]], # 27 (P3/8-small)
- [-2, 1, Conv, [128, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 6], 1, Concat, [1]] # cat backbone P3
- [-1, 1, Bottleneck, [256, False]]
- [-1, 2, Bottleneck, [256, False]] # 27 (P3/8-small)
[[27, 22, 15], 1, Detect, [nc]], # Detect(P3, P4, P5)
]
- [[27, 22, 15], 1, Detect, [nc]] # Detect(P3, P4, P5)

70
ultralytics/cfg/models/v5/yolov5-p6.yaml
View file

@ -14,48 +14,46 @@ scales: # model compound scaling constants, i.e. 'model=yolov5n-p6.yaml' will ca
# YOLOv5 v6.0 backbone
backbone:
# [from, number, module, args]
[[-1, 1, Conv, [64, 6, 2, 2]], # 0-P1/2
[-1, 1, Conv, [128, 3, 2]], # 1-P2/4
[-1, 3, C3, [128]],
[-1, 1, Conv, [256, 3, 2]], # 3-P3/8
[-1, 6, C3, [256]],
[-1, 1, Conv, [512, 3, 2]], # 5-P4/16
[-1, 9, C3, [512]],
[-1, 1, Conv, [768, 3, 2]], # 7-P5/32
[-1, 3, C3, [768]],
[-1, 1, Conv, [1024, 3, 2]], # 9-P6/64
[-1, 3, C3, [1024]],
[-1, 1, SPPF, [1024, 5]], # 11
]
- [-1, 1, Conv, [64, 6, 2, 2]] # 0-P1/2
- [-1, 1, Conv, [128, 3, 2]] # 1-P2/4
- [-1, 3, C3, [128]]
- [-1, 1, Conv, [256, 3, 2]] # 3-P3/8
- [-1, 6, C3, [256]]
- [-1, 1, Conv, [512, 3, 2]] # 5-P4/16
- [-1, 9, C3, [512]]
- [-1, 1, Conv, [768, 3, 2]] # 7-P5/32
- [-1, 3, C3, [768]]
- [-1, 1, Conv, [1024, 3, 2]] # 9-P6/64
- [-1, 3, C3, [1024]]
- [-1, 1, SPPF, [1024, 5]] # 11
# YOLOv5 v6.0 head
head:
[[-1, 1, Conv, [768, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 8], 1, Concat, [1]], # cat backbone P5
[-1, 3, C3, [768, False]], # 15
- [-1, 1, Conv, [768, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 8], 1, Concat, [1]] # cat backbone P5
- [-1, 3, C3, [768, False]] # 15
[-1, 1, Conv, [512, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 6], 1, Concat, [1]], # cat backbone P4
[-1, 3, C3, [512, False]], # 19
- [-1, 1, Conv, [512, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C3, [512, False]] # 19
[-1, 1, Conv, [256, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 4], 1, Concat, [1]], # cat backbone P3
[-1, 3, C3, [256, False]], # 23 (P3/8-small)
- [-1, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C3, [256, False]] # 23 (P3/8-small)
[-1, 1, Conv, [256, 3, 2]],
[[-1, 20], 1, Concat, [1]], # cat head P4
[-1, 3, C3, [512, False]], # 26 (P4/16-medium)
- [-1, 1, Conv, [256, 3, 2]]
- [[-1, 20], 1, Concat, [1]] # cat head P4
- [-1, 3, C3, [512, False]] # 26 (P4/16-medium)
[-1, 1, Conv, [512, 3, 2]],
[[-1, 16], 1, Concat, [1]], # cat head P5
[-1, 3, C3, [768, False]], # 29 (P5/32-large)
- [-1, 1, Conv, [512, 3, 2]]
- [[-1, 16], 1, Concat, [1]] # cat head P5
- [-1, 3, C3, [768, False]] # 29 (P5/32-large)
[-1, 1, Conv, [768, 3, 2]],
[[-1, 12], 1, Concat, [1]], # cat head P6
[-1, 3, C3, [1024, False]], # 32 (P6/64-xlarge)
- [-1, 1, Conv, [768, 3, 2]]
- [[-1, 12], 1, Concat, [1]] # cat head P6
- [-1, 3, C3, [1024, False]] # 32 (P6/64-xlarge)
[[23, 26, 29, 32], 1, Detect, [nc]], # Detect(P3, P4, P5, P6)
]
- [[23, 26, 29, 32], 1, Detect, [nc]] # Detect(P3, P4, P5, P6)

53
ultralytics/cfg/models/v5/yolov5.yaml
View file

@ -14,37 +14,36 @@ scales: # model compound scaling constants, i.e. 'model=yolov5n.yaml' will call
# YOLOv5 v6.0 backbone
backbone:
# [from, number, module, args]
[[-1, 1, Conv, [64, 6, 2, 2]], # 0-P1/2
[-1, 1, Conv, [128, 3, 2]], # 1-P2/4
[-1, 3, C3, [128]],
[-1, 1, Conv, [256, 3, 2]], # 3-P3/8
[-1, 6, C3, [256]],
[-1, 1, Conv, [512, 3, 2]], # 5-P4/16
[-1, 9, C3, [512]],
[-1, 1, Conv, [1024, 3, 2]], # 7-P5/32
[-1, 3, C3, [1024]],
[-1, 1, SPPF, [1024, 5]], # 9
]
- [-1, 1, Conv, [64, 6, 2, 2]] # 0-P1/2
- [-1, 1, Conv, [128, 3, 2]] # 1-P2/4
- [-1, 3, C3, [128]]
- [-1, 1, Conv, [256, 3, 2]] # 3-P3/8
- [-1, 6, C3, [256]]
- [-1, 1, Conv, [512, 3, 2]] # 5-P4/16
- [-1, 9, C3, [512]]
- [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32
- [-1, 3, C3, [1024]]
- [-1, 1, SPPF, [1024, 5]] # 9
# YOLOv5 v6.0 head
head:
[[-1, 1, Conv, [512, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 6], 1, Concat, [1]], # cat backbone P4
[-1, 3, C3, [512, False]], # 13
- [-1, 1, Conv, [512, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 6], 1, Concat, [1]] # cat backbone P4
- [-1, 3, C3, [512, False]] # 13
[-1, 1, Conv, [256, 1, 1]],
[-1, 1, nn.Upsample, [None, 2, 'nearest']],
[[-1, 4], 1, Concat, [1]], # cat backbone P3
[-1, 3, C3, [256, False]], # 17 (P3/8-small)
- [-1, 1, Conv, [256, 1, 1]]
- [-1, 1, nn.Upsample, [None, 2, 'nearest']]
- [[-1, 4], 1, Concat, [1]] # cat backbone P3
- [-1, 3, C3, [256, False]] # 17 (P3/8-small)
[-1, 1, Conv, [256, 3, 2]],
[[-1, 14], 1, Concat, [1]], # cat head P4
[-1, 3, C3, [512, False]], # 20 (P4/16-medium)
- [-1, 1, Conv, [256, 3, 2]]
- [[-1, 14], 1, Concat, [1]] # cat head P4
- [-1, 3, C3, [512, False]] # 20 (P4/16-medium)
[-1, 1, Conv, [512, 3, 2]],
[[-1, 10], 1, Concat, [1]], # cat head P5
[-1, 3, C3, [1024, False]], # 23 (P5/32-large)
- [-1, 1, Conv, [512, 3, 2]]
- [[-1, 10], 1, Concat, [1]] # cat head P5
- [-1, 3, C3, [1024, False]] # 23 (P5/32-large)
[[17, 20, 23], 1, Detect, [nc]], # Detect(P3, P4, P5)
]
- [[17, 20, 23], 1, Detect, [nc]] # Detect(P3, P4, P5)