mirror of https://github.com/AlexeyAB/darknet.git
1010 lines
11 KiB
INI
1010 lines
11 KiB
INI
[net]
|
|
# Training
|
|
batch=120
|
|
subdivisions=4
|
|
# Testing
|
|
#batch=1
|
|
#subdivisions=1
|
|
height=224
|
|
width=224
|
|
channels=3
|
|
momentum=0.9
|
|
decay=0.0005
|
|
max_crop=256
|
|
#mixup=4
|
|
blur=1
|
|
cutmix=1
|
|
mosaic=1
|
|
|
|
burn_in=1000
|
|
#burn_in=100
|
|
learning_rate=0.256
|
|
policy=poly
|
|
power=4
|
|
max_batches=800000
|
|
momentum=0.9
|
|
decay=0.00005
|
|
|
|
angle=7
|
|
hue=.1
|
|
saturation=.75
|
|
exposure=.75
|
|
aspect=.75
|
|
|
|
|
|
### CONV1 - 1 (1)
|
|
# conv1
|
|
[convolutional]
|
|
filters=32
|
|
size=3
|
|
pad=1
|
|
stride=2
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
### CONV2 - MBConv1 - 1 (1)
|
|
# conv2_1_expand
|
|
[convolutional]
|
|
filters=32
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv2_1_dwise
|
|
[convolutional]
|
|
groups=32
|
|
filters=32
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=4 (recommended r=16)
|
|
[convolutional]
|
|
filters=8
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=32
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv2_1_linear
|
|
[convolutional]
|
|
filters=16
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
|
|
### CONV3 - MBConv6 - 1 (2)
|
|
# conv2_2_expand
|
|
[convolutional]
|
|
filters=96
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv2_2_dwise
|
|
[convolutional]
|
|
groups=96
|
|
filters=96
|
|
size=3
|
|
pad=1
|
|
stride=2
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=8 (recommended r=16)
|
|
[convolutional]
|
|
filters=16
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=96
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv2_2_linear
|
|
[convolutional]
|
|
filters=24
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV3 - MBConv6 - 2 (2)
|
|
# conv3_1_expand
|
|
[convolutional]
|
|
filters=144
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv3_1_dwise
|
|
[convolutional]
|
|
groups=144
|
|
filters=144
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=8
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=144
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv3_1_linear
|
|
[convolutional]
|
|
filters=24
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
|
|
### CONV4 - MBConv6 - 1 (2)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_3_1
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_3_2_expand
|
|
[convolutional]
|
|
filters=144
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_3_2_dwise
|
|
[convolutional]
|
|
groups=144
|
|
filters=144
|
|
size=5
|
|
pad=1
|
|
stride=2
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=8
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=144
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_3_2_linear
|
|
[convolutional]
|
|
filters=40
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV4 - MBConv6 - 2 (2)
|
|
# conv_4_1_expand
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_4_1_dwise
|
|
[convolutional]
|
|
groups=192
|
|
filters=192
|
|
size=5
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=16
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_4_1_linear
|
|
[convolutional]
|
|
filters=40
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
|
|
|
|
### CONV5 - MBConv6 - 1 (3)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_4_2
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_4_3_expand
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_4_3_dwise
|
|
[convolutional]
|
|
groups=192
|
|
filters=192
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=16
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_4_3_linear
|
|
[convolutional]
|
|
filters=80
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV5 - MBConv6 - 2 (3)
|
|
# conv_4_4_expand
|
|
[convolutional]
|
|
filters=384
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_4_4_dwise
|
|
[convolutional]
|
|
groups=384
|
|
filters=384
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=24
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=384
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_4_4_linear
|
|
[convolutional]
|
|
filters=80
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV5 - MBConv6 - 3 (3)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_4_4
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_4_5_expand
|
|
[convolutional]
|
|
filters=384
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_4_5_dwise
|
|
[convolutional]
|
|
groups=384
|
|
filters=384
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=24
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=384
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_4_5_linear
|
|
[convolutional]
|
|
filters=80
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
|
|
### CONV6 - MBConv6 - 1 (3)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_4_6
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_4_7_expand
|
|
[convolutional]
|
|
filters=384
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_4_7_dwise
|
|
[convolutional]
|
|
groups=384
|
|
filters=384
|
|
size=5
|
|
pad=1
|
|
stride=2
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=24
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=384
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_4_7_linear
|
|
[convolutional]
|
|
filters=112
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV6 - MBConv6 - 2 (3)
|
|
# conv_5_1_expand
|
|
[convolutional]
|
|
filters=576
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_5_1_dwise
|
|
[convolutional]
|
|
groups=576
|
|
filters=576
|
|
size=5
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=32
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=576
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_5_1_linear
|
|
[convolutional]
|
|
filters=112
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV6 - MBConv6 - 3 (3)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_5_1
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_5_2_expand
|
|
[convolutional]
|
|
filters=576
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_5_2_dwise
|
|
[convolutional]
|
|
groups=576
|
|
filters=576
|
|
size=5
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=32
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=576
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_5_2_linear
|
|
[convolutional]
|
|
filters=112
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV7 - MBConv6 - 1 (4)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_5_2
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_5_3_expand
|
|
[convolutional]
|
|
filters=576
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_5_3_dwise
|
|
[convolutional]
|
|
groups=576
|
|
filters=576
|
|
size=5
|
|
pad=1
|
|
stride=2
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=32
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=576
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_5_3_linear
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV7 - MBConv6 - 2 (4)
|
|
# conv_6_1_expand
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_6_1_dwise
|
|
[convolutional]
|
|
groups=960
|
|
filters=960
|
|
size=5
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=64
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_6_1_linear
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV7 - MBConv6 - 3 (4)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_6_1
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_6_2_expand
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_6_2_dwise
|
|
[convolutional]
|
|
groups=960
|
|
filters=960
|
|
size=5
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=64
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_6_2_linear
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV7 - MBConv6 - 4 (4)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_6_1
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_6_2_expand
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_6_2_dwise
|
|
[convolutional]
|
|
groups=960
|
|
filters=960
|
|
size=5
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=64
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_6_2_linear
|
|
[convolutional]
|
|
filters=192
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
|
|
### CONV8 - MBConv6 - 1 (1)
|
|
# dropout only before residual connection
|
|
[dropout]
|
|
probability=.2
|
|
|
|
# block_6_2
|
|
[shortcut]
|
|
from=-9
|
|
activation=linear
|
|
|
|
# conv_6_3_expand
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
# conv_6_3_dwise
|
|
[convolutional]
|
|
groups=960
|
|
filters=960
|
|
size=3
|
|
stride=1
|
|
pad=1
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
#squeeze-n-excitation
|
|
[avgpool]
|
|
|
|
# squeeze ratio r=16 (recommended r=16)
|
|
[convolutional]
|
|
filters=64
|
|
size=1
|
|
stride=1
|
|
activation=swish
|
|
|
|
# excitation
|
|
[convolutional]
|
|
filters=960
|
|
size=1
|
|
stride=1
|
|
activation=logistic
|
|
|
|
# multiply channels
|
|
[scale_channels]
|
|
from=-4
|
|
|
|
|
|
# conv_6_3_linear
|
|
[convolutional]
|
|
filters=320
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=linear
|
|
|
|
|
|
### CONV9 - Conv2d 1x1
|
|
# conv_6_4
|
|
[convolutional]
|
|
filters=1280
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
batch_normalize=1
|
|
activation=swish
|
|
|
|
|
|
[avgpool]
|
|
|
|
[dropout]
|
|
probability=.2
|
|
|
|
[convolutional]
|
|
filters=1000
|
|
size=1
|
|
stride=1
|
|
pad=0
|
|
activation=linear
|
|
|
|
[softmax]
|
|
groups=1
|
|
|
|
#[cost]
|
|
#type=sse
|
|
|