mirror of https://github.com/AlexeyAB/darknet.git
1043 lines
11 KiB
INI
1043 lines
11 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=64
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subdivisions=8
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width=608
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height=608
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channels=3
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momentum=0.949
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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 = 500500
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policy=steps
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steps=400000,450000
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scales=.1,.1
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#cutmix=1
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mosaic=1
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#19:104x104 38:52x52 65:26x26 80:13x13 for 416
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[convolutional]
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batch_normalize=1
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filters=64
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size=7
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stride=2
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pad=1
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activation=leaky
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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=leaky
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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=leaky
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# 1-1
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 1-2
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 1-3
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 1-T
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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=leaky
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[route]
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layers = -1,-16
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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=leaky
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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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groups=32
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stride=2
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pad=1
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activation=leaky
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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=linear
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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=linear
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# 2-1
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 2-2
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 2-3
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 2-T
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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=leaky
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[route]
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layers = -1,-16
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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=leaky
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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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groups=32
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stride=2
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pad=1
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activation=leaky
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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=linear
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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=linear
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# 3-1
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 3-2
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 3-3
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 3-4
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 3-5
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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=leaky
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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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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 3-T
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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=leaky
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[route]
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layers = -1,-24
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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=leaky
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[convolutional]
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batch_normalize=1
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filters=1024
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size=3
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groups=32
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stride=2
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pad=1
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activation=leaky
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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=leaky
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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=1024
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size=1
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stride=1
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pad=1
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activation=leaky
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# 4-1
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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=leaky
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[convolutional]
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batch_normalize=1
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filters=1024
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size=3
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groups=32
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stride=1
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pad=1
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activation=leaky
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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=linear
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[shortcut]
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from=-4
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activation=leaky
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# 4-2
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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=leaky
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[convolutional]
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batch_normalize=1
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filters=1024
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size=3
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groups=32
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stride=1
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pad=1
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activation=leaky
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|
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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=linear
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|
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[shortcut]
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from=-4
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activation=leaky
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# 4-T
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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=leaky
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|
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[route]
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layers = -1,-12
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[convolutional]
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batch_normalize=1
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filters=2048
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size=1
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stride=1
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pad=1
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activation=leaky
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##########################
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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=leaky
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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=1024
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activation=leaky
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|
|
|
[convolutional]
|
|
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=leaky
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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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|
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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=-1,-3,-5,-6
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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=leaky
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|
|
|
[convolutional]
|
|
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=1024
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|
activation=leaky
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|
|
|
[convolutional]
|
|
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=leaky
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|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
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=leaky
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|
|
|
[upsample]
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stride=2
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|
|
|
[route]
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|
layers = 65
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|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
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|
size=1
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|
stride=1
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|
pad=1
|
|
activation=leaky
|
|
|
|
[route]
|
|
layers = -1, -3
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|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
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|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=512
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=512
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[upsample]
|
|
stride=2
|
|
|
|
[route]
|
|
layers = 38
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[route]
|
|
layers = -1, -3
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=256
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=256
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=128
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
##########################
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=256
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
filters=255
|
|
activation=linear
|
|
|
|
|
|
[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=.3
|
|
ignore_thresh = .7
|
|
truth_thresh = 1
|
|
scale_x_y = 1.2
|
|
iou_thresh=0.213
|
|
cls_normalizer=1.0
|
|
iou_normalizer=0.07
|
|
iou_loss=ciou
|
|
nms_kind=greedynms
|
|
beta_nms=0.6
|
|
|
|
[route]
|
|
layers = -4
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=2
|
|
pad=1
|
|
filters=256
|
|
activation=leaky
|
|
|
|
[route]
|
|
layers = -1, -16
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=512
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=512
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=512
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
filters=255
|
|
activation=linear
|
|
|
|
|
|
[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=.3
|
|
ignore_thresh = .7
|
|
truth_thresh = 1
|
|
scale_x_y = 1.1
|
|
iou_thresh=0.213
|
|
cls_normalizer=1.0
|
|
iou_normalizer=0.07
|
|
iou_loss=ciou
|
|
nms_kind=greedynms
|
|
beta_nms=0.6
|
|
|
|
|
|
[route]
|
|
layers = -4
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=2
|
|
pad=1
|
|
filters=512
|
|
activation=leaky
|
|
|
|
[route]
|
|
layers = -1, -37
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=512
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=1024
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=512
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=1024
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=512
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
filters=1024
|
|
activation=leaky
|
|
|
|
[convolutional]
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
filters=255
|
|
activation=linear
|
|
|
|
|
|
[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=.3
|
|
ignore_thresh = .7
|
|
truth_thresh = 1
|
|
random=1
|
|
scale_x_y = 1.05
|
|
iou_thresh=0.213
|
|
cls_normalizer=1.0
|
|
iou_normalizer=0.07
|
|
iou_loss=ciou
|
|
nms_kind=greedynms
|
|
beta_nms=0.6
|
|
|