[net]
batch=1
subdivisions=1
height=448
width=448
channels=3
momentum=0.9
decay=0.0005

learning_rate=0.0001
policy=steps
steps=20,40,60,80,20000,30000
scales=5,5,2,2,.1,.1
max_batches = 40000

[convolutional]
batch_normalize=1
filters=16
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[batchnorm]

[convolutional]
xnor = 1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[batchnorm]

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

[maxpool]
size=2
stride=2

[batchnorm]

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

[maxpool]
size=2
stride=2

[batchnorm]

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

[maxpool]
size=2
stride=2

[batchnorm]

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

[maxpool]
size=2
stride=2

[batchnorm]

[convolutional]
xnor = 1
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

[batchnorm]

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

[connected]
output= 1470
activation=linear

[detection]
classes=20
coords=4
rescore=1
side=7
num=2
softmax=0
sqrt=1
jitter=.2

object_scale=1
noobject_scale=.5
class_scale=1
coord_scale=5