[net]
# Training
batch=128
subdivisions=4

# Testing
# batch=1
# subdivisions=1

height=256
width=256
channels=3
min_crop=128
max_crop=448

burn_in=1000
learning_rate=0.1
policy=poly
power=4
max_batches=800000
momentum=0.9
decay=0.0005

angle=7
hue=.1
saturation=.75
exposure=.75
aspect=.75



### stem network ###
#				# 0
[convolutional]
batch_normalize=1
filters=64
size=7
stride=2
pad=1
activation=leaky
#				# 1
[maxpool]
size=2
stride=2
#				# 2 b1 1sr gray rectangle block
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
#				# 3
[convolutional]
batch_normalize=1
filters=64
groups=2
size=3
stride=1
pad=1
activation=leaky
#				# 4
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=linear
#				# 5 b1
[shortcut]
from=-4
activation=leaky
#				# 6 b2 2nd gray rectangle block
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
#				# 7
[convolutional]
batch_normalize=1
filters=64
groups=2
size=3
stride=1
pad=1
activation=leaky
#				# 8
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=linear
#				# 9 b2
[shortcut]
from=-4
activation=leaky
#				# 10 b3 3rd gray rectangle block
#				# from b1,b2
[shortcut]
from=-5
activation=linear
#				# 11 bottleneck block
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
#				# 12
[convolutional]
batch_normalize=1
filters=64
groups=2
size=3
stride=1
pad=1
activation=leaky
#				# 13
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=linear
#				# 14 b3
[shortcut]
from=-4
activation=leaky

#				# 15 b4 green diamond block
#				# from b1 
[route]
layers=5
#				# 16
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
#				# 17
[convolutional]
batch_normalize=1
filters=128
groups=4
size=3
stride=2
pad=1
activation=leaky
#				# 18
[maxpool]
stride=2
size=2
#				# 19
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 20 from b2 
[route]
layers=9
#				# 21
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
#				# 22
[convolutional]
batch_normalize=1
filters=128
groups=4
size=3
stride=2
pad=1
activation=leaky
#				# 23
[maxpool]
stride=2
size=2
#				# 24
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 25 residual block
[shortcut]
from=-6
activation=linear
#				# 26
[convolutional]
batch_normalize=1
filters=1024
groups=16
size=3
stride=1
pad=1
activation=leaky
#				# 27
[convolutional]
batch_normalize=1
filters=1024
groups=16
size=3
stride=1
pad=1
activation=linear
#				# 28 b4
[shortcut]
from=-3
activation=leaky
#				# 29 b5 1st yellow rectangle block
#				# from b4
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
#				# 30
[upsample]
stride=2
#				# 31
[convolutional]
batch_normalize=1
filters=512
groups=4
size=1
stride=1
pad=1
activation=leaky
#				# 32 from b3
[route]
layers=14
#				# 33
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
#				# 34
[convolutional]
batch_normalize=1
filters=128
groups=4
size=3
stride=2
pad=1
activation=leaky
#				# 35
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
#				# 36 bottleneck block
[shortcut]
from=-5
activation=linear
#				# 37
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
#				# 38
[convolutional]
batch_normalize=1
filters=128
groups=4
size=3
stride=1
pad=1
activation=leaky
#				# 39
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=linear
#				# 40 b5
[shortcut]
from=-4
activation=leaky
#				# 41 b6 1st green rectangle block
#				# from b5
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
#				# 42
[convolutional]
batch_normalize=1
filters=256
groups=8
size=3
stride=2
pad=1
activation=leaky
#				# 43
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 44 from b3
[route]
layers=14
#				# 45
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
#				# 46
[convolutional]
batch_normalize=1
filters=128
groups=4
size=3
stride=2
pad=1
activation=leaky
#				# 47
[maxpool]
stride=2
size=2
#				# 48
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 49 bottleneck
[shortcut]
from=-6
activation=linear
#				# 50
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
#				# 51
[convolutional]
batch_normalize=1
filters=256
groups=16
size=3
stride=1
pad=1
activation=leaky
#				# 52
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=linear
#				# 53 b6
[shortcut]
from=-4
activation=leaky
#				# 54 b7 red diamond block
#				# from b6
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
#				# 55
[convolutional]
batch_normalize=1
filters=512
groups=8
size=3
stride=2
pad=1
activation=leaky
#				# 56
[maxpool]
stride=2
size=2
#				# 57
[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=leaky
#				# 58 from b4
[route]
layers=28
#				# 59
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
#				# 60
[convolutional]
batch_normalize=1
filters=512
groups=8
size=3
stride=2
pad=1
activation=leaky
#				# 61
[maxpool]
stride=2
size=2
#				# 62
[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=leaky
#				# 63 residual
[shortcut]
from=-6
activation=linear
#				# 64
[convolutional]
batch_normalize=1
filters=2048
groups=64
size=3
stride=1
pad=1
activation=leaky
#				# 65
[convolutional]
batch_normalize=1
filters=2048
groups=64
size=3
stride=1
pad=1
activation=linear
#				# 66 b7
[shortcut]
from=-3
activation=leaky
#				# 67 b8 2nd green rectangle block
#				# from b6
[route]
layers=53
#				# 68 from b4
[shortcut]
from=28
activation=linear
#				# 69 bottleneck block
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
#				# 70
[convolutional]
batch_normalize=1
filters=256
groups=16
size=3
stride=1
pad=1
activation=leaky
#				# 71
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=linear
#				# 72 b8 ccc
[shortcut]
from=-4
activation=leaky
#				# 73 b9 blue diamond block
#				# from b8
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
#				# 74
[convolutional]
batch_normalize=1
filters=512
groups=16
size=3
stride=2
pad=1
activation=leaky
#				# 75
[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=leaky
#				# 76 from b7
[route]
layers=66
#				# 77
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 78
[upsample]
stride=2
#				# 79
[convolutional]
batch_normalize=1
filters=2048
groups=4
size=1
stride=1
pad=1
activation=leaky
#				# 80 residual block
[shortcut]
from=-5
activation=linear
#				# 81
[convolutional]
batch_normalize=1
filters=2048
groups=64
size=3
stride=1
pad=1
activation=leaky
#				# 82
[convolutional]
batch_normalize=1
filters=2048
groups=64
size=3
stride=1
pad=1
activation=linear
#				# 83 b9 ccc
[shortcut]
from=-3
activation=leaky
#				# 84 b10 gray2 diamond block
#				# from b9
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 85
[convolutional]
batch_normalize=1
filters=1024
groups=16
size=3
stride=2
pad=1
activation=leaky
#				# 86
[maxpool]
size=2
stride=2
#				# 87
[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=leaky
#				# 88 from b7
[route]
layers=66
#				# 89
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 90
[convolutional]
batch_normalize=1
filters=1024
groups=16
size=3
stride=2
pad=1
activation=leaky
#				# 91
[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=leaky
#				# 92 residual block
[shortcut]
from=-5
activation=linear
#				# 93
[convolutional]
batch_normalize=1
filters=2048
groups=64
size=3
stride=1
pad=1
activation=leaky
#				# 94
[convolutional]
batch_normalize=1
filters=2048
groups=64
size=3
stride=1
pad=1
activation=linear
#				# 95 b10
[shortcut]
from=-3
activation=leaky
#				# 96 b11 1st blue rectangle block
#				# from b10
[convolutional]
batch_normalize=1
filters=1024
size=1
stride=1
pad=1
activation=leaky
#				# 97
[upsample]
stride=4
#				# 98
[convolutional]
batch_normalize=1
filters=2048
groups=4
size=1
stride=1
pad=1
activation=leaky
#				# 99 from b9
[shortcut]
from=83
activation=linear
#				# 100 bottleneck block
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
#				# 101
[convolutional]
batch_normalize=1
filters=512
groups=16
size=3
stride=1
pad=1
activation=leaky
#				# 102
[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=linear
#				# 103 b11
[shortcut]
from=-4
activation=leaky
#				# 104 b12 2nd blue rectangle block
#				# from b11,b9
[shortcut]
from=83
activation=linear
#				# 105 bottleneck block
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
#				# 106
[convolutional]
batch_normalize=1
filters=512
groups=16
size=3
stride=1
pad=1
activation=leaky
#				# 107
[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=linear
#				# 108 b12 ccc
[shortcut]
from=-4
activation=leaky
#				# 109 b13 3rd green rectangle block output
#				# from b11


[convolutional]
batch_normalize=1
filters=2048
size=1
stride=1
pad=1
activation=leaky

[avgpool]

[convolutional]
filters=1000
size=1
stride=1
pad=1
activation=linear

[softmax]
groups=1