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yolox-darknet53.yaml
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__BASE__: [
'../coco.yaml',
'./hyp.scratch.yaml',
'./yolox-s.yaml'
]
# difference with s
# 1. backbone
# 2. depth and width
network:
depth_multiple: 1.0
width_multiple: 1.0
backbone:
# [from, number, module, args]
[
[ -1, 1, ConvNormAct, [ 32, 3, 1, act=nn.LeakyReLU(0.1) ] ], # 0, stem.0,
[ -1, 1, ConvNormAct, [ 64, 3, 2, act=nn.LeakyReLU(0.1) ] ], # 1, stem.1, /2
[ -1, 1, Bottleneck, [ 64, act=nn.LeakyReLU(0.1) ] ], # 2, stem.2,
[ -1, 1, ConvNormAct, [ 128, 3, 2, act=nn.LeakyReLU(0.1) ] ], # 3, dark2.0, /4
[ -1, 2, Bottleneck, [ 128, act=nn.LeakyReLU(0.1) ] ], # 4, dark2.1,
[ -1, 1, ConvNormAct, [ 256, 3, 2, act=nn.LeakyReLU(0.1) ] ], # 5, dark3.0, /8
[ -1, 8, Bottleneck, [ 256, act=nn.LeakyReLU(0.1) ] ], # 6, dark3.1,
[ -1, 1, ConvNormAct, [ 512, 3, 2, act=nn.LeakyReLU(0.1) ] ], # 7, dark4.0, /16
[ -1, 8, Bottleneck, [ 512, act=nn.LeakyReLU(0.1) ] ], # 8, dark4.1,
[ -1, 1, ConvNormAct, [ 1024, 3, 2, act=nn.LeakyReLU(0.1) ] ], # 9, dark5.0, /32
[ -1, 4, Bottleneck, [ 1024, act=nn.LeakyReLU(0.1) ] ], # 10, dark5.1,
[ -1, 1, ConvNormAct, [ 512, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 11, dark5.2,
[ -1, 1, ConvNormAct, [ 1024, 3, 1, act=nn.LeakyReLU(0.1) ] ], # 12, dark5.3,
[ -1, 1, SPPF, [ 512, act=nn.LeakyReLU(0.1) ] ], # 13, dark5.4
[ -1, 1, ConvNormAct, [ 1024, 3, 1, act=nn.LeakyReLU(0.1) ] ], # 14, dark5.5
[ -1, 1, ConvNormAct, [ 512, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 15, dark5.6 (small)
]
head:
[
[ -1, 1, ConvNormAct, [ 256, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 16, out1_cbl,
[ -1, 1, Upsample, [ None, 2, 'nearest' ] ], # 17, upsample0, /16
[ [ -1, 8 ], 1, Concat, [ 1 ] ], # 18, concat,
[ -1, 1, ConvNormAct, [ 256, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 19, out1.0,
[ -1, 1, ConvNormAct, [ 512, 3, 1, act=nn.LeakyReLU(0.1) ] ], # 20, out1.1,
[ -1, 1, ConvNormAct, [ 256, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 21, out1.2,
[ -1, 1, ConvNormAct, [ 512, 3, 1, act=nn.LeakyReLU(0.1) ] ], # 22, out1.3,
[ -1, 1, ConvNormAct, [ 256, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 23, out1.4, (middle)
[ -1, 1, ConvNormAct, [ 128, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 24, out2_cbl,
[ -1, 1, Upsample, [ None, 2, 'nearest' ] ], # 25, upsample1, /8
[ [ -1, 6 ], 1, Concat, [ 1 ] ], # 26, concat,
[ -1, 1, ConvNormAct, [ 128, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 27, out2.0,
[ -1, 1, ConvNormAct, [ 256, 3, 1, act=nn.LeakyReLU(0.1) ] ], # 28, out2.1,
[ -1, 1, ConvNormAct, [ 128, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 29, out2.2,
[ -1, 1, ConvNormAct, [ 256, 3, 1, act=nn.LeakyReLU(0.1) ] ], # 30, out2.3,
[ -1, 1, ConvNormAct, [ 128, 1, 1, act=nn.LeakyReLU(0.1) ] ], # 31, out2.4, (large)
[ [ 31, 23, 15 ], 1, YOLOXHead, [ nc, stride, is_standard_backbone=False, act=nn.LeakyReLU(0.1) ] ], # 32, detection head
]