[net]
batch = 64
subdivisions = 8
width = 416
height = 416
channels = 3
momentum = 0.9
decay = 0.0005
angle = 0
saturation = 1.5
exposure = 1.5
hue = .1

learning_rate = 0.001
max_batches = 40100
policy = steps
steps = -1,100,20000,30000
scales = .1,10,.1,.1

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

[maxpool]
size = 2
stride = 2

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

[maxpool]
size = 2
stride = 2

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

[maxpool]
size = 2
stride = 2

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

[maxpool]
size = 2
stride = 2

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

[maxpool]
size = 2
stride = 2

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

[maxpool]
size = 2
stride = 1

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

###########

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

[convolutional]
size = 1
stride = 1
pad = 1
filters = 40
activation = linear

[region]
anchors = 1.08,1.19,  3.42,4.41,  6.63,11.38,  9.42,5.11,  16.62,10.52
bias_match = 1
classes = 3
coords = 4
num = 5
softmax = 1
jitter = .2
rescore = 1

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

absolute = 1
thresh = .5
random = 1