mirror of
https://github.com/pjreddie/darknet.git
synced 2023-08-10 21:13:14 +03:00
212 lines
2.2 KiB
INI
212 lines
2.2 KiB
INI
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[net]
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batch=1
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subdivisions=1
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height=416
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width=416
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channels=3
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momentum=0.9
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decay=0.0005
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learning_rate=0.00001
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max_batches = 242200
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policy=steps
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steps=500,200000,240000
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scales=10,.1,.1
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hue=.1
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saturation=.75
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exposure=.75
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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=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=64
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size=3
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stride=1
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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=3
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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=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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[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=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=256
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size=3
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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=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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stride=1
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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=512
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size=3
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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=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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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=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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stride=1
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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=1024
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size=3
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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=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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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=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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stride=1
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pad=1
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activation=leaky
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[convolutional]
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filters=28269
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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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[region]
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anchors = 0.77871, 1.14074, 3.00525, 4.31277, 9.22725, 9.61974
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bias_match=1
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classes=9418
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coords=4
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num=3
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softmax=1
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jitter=.2
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rescore=1
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object_scale=5
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noobject_scale=1
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class_scale=1
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coord_scale=1
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thresh = .6
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absolute=1
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random=1
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tree=data/9k.tree
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map = data/coco9k.map
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