mirror of https://github.com/AlexeyAB/darknet.git
1177 lines
12 KiB
INI
1177 lines
12 KiB
INI
[net]
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batch=64
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subdivisions=8
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# Training
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#width=512
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#height=512
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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=0.0013
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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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mosaic=1
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letter_box=1
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ema_alpha=0.9998
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#optimized_memory=1
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#:104x104 54:52x52 85:26x26 104:13x13 for 416
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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=mish
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# Downsample
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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=mish
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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=mish
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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=mish
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[convolutional]
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batch_normalize=1
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filters=32
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size=1
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stride=1
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pad=1
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activation=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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[route]
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layers = -1,-7
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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=mish
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# Downsample
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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=mish
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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=mish
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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=mish
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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[route]
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layers = -1,-10
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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=mish
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# Downsample
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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=mish
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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=mish
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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=mish
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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[route]
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layers = -1,-28
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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=mish
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# Downsample
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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=mish
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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=mish
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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=mish
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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[route]
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layers = -1,-28
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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=mish
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# Downsample
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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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stride=2
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pad=1
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activation=mish
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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=mish
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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=mish
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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=mish
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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=1
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pad=1
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activation=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=1
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pad=1
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activation=mish
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|
|
[shortcut]
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from=-3
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activation=linear
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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=mish
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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=1
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pad=1
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activation=mish
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[shortcut]
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from=-3
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activation=linear
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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=mish
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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=1
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pad=1
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activation=mish
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|
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[shortcut]
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from=-3
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activation=linear
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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=mish
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|
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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=1024
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size=1
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stride=1
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pad=1
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activation=mish
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|
|
##########################
|
|
|
|
[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
|
|
|
|
### SPP ###
|
|
[maxpool]
|
|
stride=1
|
|
size=5
|
|
|
|
[route]
|
|
layers=-2
|
|
|
|
[maxpool]
|
|
stride=1
|
|
size=9
|
|
|
|
[route]
|
|
layers=-4
|
|
|
|
[maxpool]
|
|
stride=1
|
|
size=13
|
|
|
|
[route]
|
|
layers=-1,-3,-5,-6
|
|
### End SPP ###
|
|
|
|
[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
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[upsample]
|
|
stride=2
|
|
|
|
[route]
|
|
layers = 85
|
|
|
|
[convolutional]
|
|
batch_normalize=1
|
|
filters=256
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[route]
|
|
layers = -1, -3
|
|
|
|
[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
|
|
filters=128
|
|
size=1
|
|
stride=1
|
|
pad=1
|
|
activation=leaky
|
|
|
|
[upsample]
|
|
stride=2
|
|
|
|
[route]
|
|
layers = 54
|
|
|
|
[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=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=0.4
|
|
iou_loss=ciou
|
|
nms_kind=diounms
|
|
beta_nms=0.6
|
|
new_coords=1
|
|
max_delta=2
|
|
|
|
|
|
[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=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=0.4
|
|
iou_loss=ciou
|
|
nms_kind=diounms
|
|
beta_nms=0.6
|
|
new_coords=1
|
|
max_delta=2
|
|
|
|
|
|
[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=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=0.4
|
|
iou_loss=ciou
|
|
nms_kind=diounms
|
|
beta_nms=0.6
|
|
new_coords=1
|
|
max_delta=2
|