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separate pytwrpper from predictorWrappery
[trackerpp.git]
/
resources
/
yolov3-tiny.cfg
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[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=2
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width=416
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height=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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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=0.001
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burn_in=1000
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max_batches = 500200
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policy=steps
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steps=400000,450000
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scales=.1,.1
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[convolutional]
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batch_normalize=1
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filters=16
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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=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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[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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[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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[maxpool]
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size=2
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stride=1
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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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###########
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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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size=1
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stride=1
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pad=1
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filters=255
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activation=linear
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[yolo]
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mask = 3,4,5
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anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
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classes=80
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num=6
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jitter=.3
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ignore_thresh = .7
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truth_thresh = 1
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random=1
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[route]
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layers = -4
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[convolutional]
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batch_normalize=1
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filters=128
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size=1
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stride=1
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pad=1
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activation=leaky
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[upsample]
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stride=2
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[route]
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layers = -1, 8
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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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size=1
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stride=1
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pad=1
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filters=255
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activation=linear
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[yolo]
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mask = 1,2,3
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anchors = 10,14, 23,27, 37,58, 81,82, 135,169, 344,319
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classes=80
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num=6
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jitter=.3
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ignore_thresh = .7
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truth_thresh = 1
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random=1