darknet/cfg/yolov1/tiny-yolo.cfg

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[net]
batch=64
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subdivisions=2
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height=448
width=448
channels=3
momentum=0.9
decay=0.0005
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saturation=.75
exposure=.75
hue = .1
learning_rate=0.0005
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policy=steps
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steps=200,400,600,800,20000,30000
scales=2.5,2,2,2,.1,.1
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max_batches = 40000
[convolutional]
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batch_normalize=1
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filters=16
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
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batch_normalize=1
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filters=32
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
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batch_normalize=1
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filters=64
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
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batch_normalize=1
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filters=128
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
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batch_normalize=1
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filters=256
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
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batch_normalize=1
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filters=512
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
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batch_normalize=1
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size=3
stride=1
pad=1
filters=1024
activation=leaky
[convolutional]
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batch_normalize=1
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size=3
stride=1
pad=1
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filters=256
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activation=leaky
[connected]
output= 1470
activation=linear
[detection]
classes=20
coords=4
rescore=1
side=7
num=2
softmax=0
sqrt=1
jitter=.2
object_scale=1
noobject_scale=.5
class_scale=1
coord_scale=5