Ankle/yolov5_birdproject
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PyCharm reformat (#4209)

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* PyCharm reformat

* YAML reformat

* Markdown reformat
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Glenn Jocher authored and GitHub committed 2021-07-28 23:35:14 +02:00
1 parent 750465edae
commit b60b62e874
38 files changed
+647 -604
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models/hub/yolov3-tiny.yaml
+23 -23
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@@ -3,37 +3,37 @@ nc: 80 # number of classes
depth_multiple: 1.0 # model depth multiple
width_multiple: 1.0 # layer channel multiple
anchors:
- [ 10,14, 23,27, 37,58 ] # P4/16
- [ 81,82, 135,169, 344,319 ] # P5/32
- [10,14, 23,27, 37,58] # P4/16
- [81,82, 135,169, 344,319] # P5/32
# 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, anchors ] ], # Detect(P4, P5)
[[19, 15], 1, Detect, [nc, anchors]], # Detect(P4, P5)
]