mirror of https://github.com/AlexeyAB/darknet.git
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
1008 lines
11 KiB
1008 lines
11 KiB
[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 |
|
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 |
|
|
|
|