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vgg-16.cfg
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vgg-16.cfg
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[net]
batch=128
subdivisions=4
height=256
width=256
channels=3
learning_rate=0.00001
momentum=0.9
decay=0.0005
[crop]
crop_height=224
crop_width=224
flip=1
exposure=1
saturation=1
angle=0
[convolutional]
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=64
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=128
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=256
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=256
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=256
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[connected]
output=4096
activation=relu
[dropout]
probability=.5
[connected]
output=4096
activation=relu
[dropout]
probability=.5
[connected]
output=1000
activation=linear
[softmax]
groups=1
[cost]
type=sse