darknet/cfg/darknet53_448_xnor.cfg

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2019-06-23 00:17:41 +08:00
[net]
# Training - start training with darknet53.weights
batch=120
subdivisions=20
# Testing
#batch=1
#subdivisions=1
height=448
width=448
channels=3
min_crop=448
max_crop=512
burn_in=1000
learning_rate=0.1
policy=poly
power=4
max_batches=100000
momentum=0.9
decay=0.0005
[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky
# Downsample
[convolutional]
xnor=1
batch_normalize=1
filters=64
size=3
stride=2
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
# Downsample
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=3
stride=2
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
# Downsample
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=2
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
# Downsample
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=2
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
# Downsample
[convolutional]
xnor=1
batch_normalize=1
filters=1024
size=3
stride=2
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
xnor=1
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
[convolutional]
xnor=1
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
[shortcut]
from=-3
activation=linear
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
[avgpool]
[convolutional]
filters=1000
size=1
stride=1
pad=1
activation=linear
[softmax]
groups=1