# yolov2 resnet18.cfg网络

```shell
[net]
# Training
# batch=128
# subdivisions=1

# Testing
batch=48
subdivisions=8

height=384
width=640

channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=0.1

learning_rate=0.01
burn_in=10000
max_batches = 300200
policy=steps
steps=100000,200000,250000
scales=.1,.1,.1


#letter_box=1



[convolutional]
batch_normalize=1
filters=64
size=3
stride=2
pad=1
activation=leaky

[maxpool]
size=2
stride=2


# Residual Block
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3

# Residual Block
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3

[maxpool]
size=2
stride=2

# Strided Residual Block
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=linear

[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3

# Residual Block
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=linear

[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3


[maxpool]
size=2
stride=2

# Strided Residual Block
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=linear

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3

# Residual Block
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=linear

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3

[maxpool]
size=2
stride=2

# Strided Residual Block
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=linear

[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3

# Residual Block
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=linear

[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=linear

[shortcut]
activation=leaky
from=-3

[convolutional]
batch_normalize=1
filters=30
size=1
stride=1
pad=0
activation=linear

[region]
anchors = 0.52,0.61, 1.05,1.12, 1.85,2.05, 4.63,4.49, 7.15,7.56
bias_match=1
classes=1
coords=4
num=5
max_boxes=300
softmax=0
jitter=.3
rescore=1

object_scale=5
noobject_scale=1
class_scale=1
coord_scale=2

absolute=1
thresh = .6
random=0
```