darknet/cfg/vgg-16.cfg

[net]
# Training
# batch=128
# subdivisions=4

# Testing
batch=1
subdivisions=1

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