[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 = 125

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 = 20

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