mirror of https://github.com/AlexeyAB/darknet.git
1025 lines
10 KiB
INI
1025 lines
10 KiB
INI
[net]
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# Testing
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#batch=1
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#subdivisions=1
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# Training
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batch=8
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subdivisions=1
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width=640
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height=640
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channels=3
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momentum=0.9
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decay=0.0005
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angle=0
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saturation = 1.5
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exposure = 1.5
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hue=.1
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learning_rate=0.00261
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burn_in=1000
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max_batches = 2000200
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policy=steps
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steps=1600000,1800000
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scales=.1,.1
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# 0
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[convolutional]
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batch_normalize=1
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filters=32
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size=3
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stride=1
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pad=1
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activation=swish
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# 1
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=2
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=swish
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# 3
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=2
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=64
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-2
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[convolutional]
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batch_normalize=1
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filters=64
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=64
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size=3
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stride=1
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pad=1
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activation=swish
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[route]
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layers = -1,-3,-5,-7
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# 12
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-3
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[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=2
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pad=1
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activation=swish
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# 18
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[route]
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layers = -1,-4
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[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-2
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[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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[route]
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layers = -1,-3,-5,-7
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# 27
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-3
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=2
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pad=1
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activation=swish
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# 33
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[route]
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layers = -1,-4
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-2
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[route]
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layers = -1,-3,-5,-7
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# 42
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[convolutional]
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batch_normalize=1
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filters=1024
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size=1
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stride=1
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pad=1
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activation=swish
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[maxpool]
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size=2
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stride=2
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-3
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=512
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size=3
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stride=2
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pad=1
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activation=swish
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# 48
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[route]
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layers = -1,-4
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-2
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=256
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size=3
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stride=1
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pad=1
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activation=swish
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[route]
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layers = -1,-3,-5,-7
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# 57
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[convolutional]
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batch_normalize=1
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filters=1024
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size=1
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stride=1
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pad=1
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activation=swish
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##################################
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### SPPCSP ###
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers = -2
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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size=3
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stride=1
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pad=1
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filters=512
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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### SPP ###
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[maxpool]
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stride=1
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size=5
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[route]
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layers=-2
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[maxpool]
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stride=1
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size=9
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[route]
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layers=-4
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[maxpool]
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stride=1
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size=13
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[route]
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layers=-6,-5,-3,-1
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### End SPP ###
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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size=3
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stride=1
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pad=1
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filters=512
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activation=swish
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[route]
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layers = -1, -13
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# 72
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[convolutional]
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batch_normalize=1
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filters=512
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size=1
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stride=1
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pad=1
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activation=swish
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### End SPPCSP ###
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[upsample]
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stride=2
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[route]
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layers = 42
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers = -1,-3
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[route]
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layers=-2
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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|
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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|
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[convolutional]
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batch_normalize=1
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filters=128
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size=3
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stride=1
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pad=1
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activation=swish
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[route]
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layers = -1,-2,-3,-4,-5,-7
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# 86
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[convolutional]
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batch_normalize=1
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filters=256
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size=1
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stride=1
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pad=1
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activation=swish
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|
|
|
|
[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=swish
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|
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[upsample]
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stride=2
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|
|
[route]
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layers = 27
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|
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[convolutional]
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|
batch_normalize=1
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filters=128
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size=1
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stride=1
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|
pad=1
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activation=swish
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|
|
[route]
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layers = -1,-3
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|
|
|
|
|
[convolutional]
|
|
batch_normalize=1
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|
filters=128
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|
size=1
|
|
stride=1
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|
pad=1
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activation=swish
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|
|
|
[route]
|
|
layers=-2
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|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=1
|
|
stride=1
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|
pad=1
|
|
activation=swish
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|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=64
|
|
size=3
|
|
stride=1
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|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=64
|
|
size=3
|
|
stride=1
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|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=64
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=64
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
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|
|
|
[route]
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layers = -1,-2,-3,-4,-5,-7
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|
|
# 100
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[convolutional]
|
|
batch_normalize=1
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|
filters=128
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size=1
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|
stride=1
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|
pad=1
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|
activation=swish
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|
|
|
|
|
[maxpool]
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size=2
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stride=2
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|
|
|
[convolutional]
|
|
batch_normalize=1
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|
filters=128
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|
size=1
|
|
stride=1
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|
pad=1
|
|
activation=swish
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|
|
|
[route]
|
|
layers=-3
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|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=1
|
|
stride=1
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|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=3
|
|
stride=2
|
|
pad=1
|
|
activation=swish
|
|
|
|
[route]
|
|
layers = -1,-4,86
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|
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[route]
|
|
layers=-2
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[route]
|
|
layers = -1,-2,-3,-4,-5,-7
|
|
|
|
# 115
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
|
|
[maxpool]
|
|
size=2
|
|
stride=2
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[route]
|
|
layers=-3
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=3
|
|
stride=2
|
|
pad=1
|
|
activation=swish
|
|
|
|
[route]
|
|
layers = -1,-4,72
|
|
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=512
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[route]
|
|
layers=-2
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=512
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
[route]
|
|
layers = -1,-2,-3,-4,-5,-7
|
|
|
|
# 130
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=512
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=swish
|
|
|
|
#############################
|
|
|
|
# ============ End of Neck ============ #
|
|
|
|
# ============ Head ============ #
|
|
|
|
|
|
# P3
|
|
[route]
|
|
layers = 100
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=256
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
filters=255
|
|
#activation=linear
|
|
activation=logistic
|
|
|
|
[yolo]
|
|
mask = 0,1,2
|
|
anchors = 12,16, 19,36, 40,28, 36,75, 76,55, 72,146, 142,110, 192,243, 459,401
|
|
classes=80
|
|
num=9
|
|
jitter=.1
|
|
scale_x_y = 2.0
|
|
objectness_smooth=1
|
|
ignore_thresh = .7
|
|
truth_thresh = 1
|
|
#random=1
|
|
resize=1.5
|
|
iou_thresh=0.2
|
|
iou_normalizer=0.05
|
|
cls_normalizer=0.5
|
|
obj_normalizer=1.0
|
|
iou_loss=ciou
|
|
nms_kind=diounms
|
|
beta_nms=0.6
|
|
new_coords=1
|
|
max_delta=2
|
|
|
|
|
|
# P4
|
|
[route]
|
|
layers = 115
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=512
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
filters=255
|
|
#activation=linear
|
|
activation=logistic
|
|
|
|
[yolo]
|
|
mask = 3,4,5
|
|
anchors = 12,16, 19,36, 40,28, 36,75, 76,55, 72,146, 142,110, 192,243, 459,401
|
|
classes=80
|
|
num=9
|
|
jitter=.1
|
|
scale_x_y = 2.0
|
|
objectness_smooth=1
|
|
ignore_thresh = .7
|
|
truth_thresh = 1
|
|
#random=1
|
|
resize=1.5
|
|
iou_thresh=0.2
|
|
iou_normalizer=0.05
|
|
cls_normalizer=0.5
|
|
obj_normalizer=1.0
|
|
iou_loss=ciou
|
|
nms_kind=diounms
|
|
beta_nms=0.6
|
|
new_coords=1
|
|
max_delta=2
|
|
|
|
|
|
# P5
|
|
[route]
|
|
layers = 130
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=1024
|
|
activation=swish
|
|
|
|
[convolutional]
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
filters=255
|
|
#activation=linear
|
|
activation=logistic
|
|
|
|
[yolo]
|
|
mask = 6,7,8
|
|
anchors = 12,16, 19,36, 40,28, 36,75, 76,55, 72,146, 142,110, 192,243, 459,401
|
|
classes=80
|
|
num=9
|
|
jitter=.1
|
|
scale_x_y = 2.0
|
|
objectness_smooth=1
|
|
ignore_thresh = .7
|
|
truth_thresh = 1
|
|
#random=1
|
|
resize=1.5
|
|
iou_thresh=0.2
|
|
iou_normalizer=0.05
|
|
cls_normalizer=0.5
|
|
obj_normalizer=1.0
|
|
iou_loss=ciou
|
|
nms_kind=diounms
|
|
beta_nms=0.6
|
|
new_coords=1
|
|
max_delta=2
|