[net]
# Testing
#batch=1
#subdivisions=1
# Training
batch=16
subdivisions=1
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
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1

# 0
[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

# 1
# Downsample
# res1模块，一个CBL加上一个残差连接（一个残差连接包括两个CBL）
[convolutional]
batch_normalize=1
filters=64
size=3
stride=2
pad=1
activation=leaky

# 2
[convolutional]
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=leaky

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

# 4
[shortcut]
from=-3
activation=linear

# 5
# Downsample
# res2模块，一个CBL加上两个残差连接 
[convolutional]
batch_normalize=1
filters=128
size=3
stride=2
pad=1
activation=leaky

# 6
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky

# 7
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

# 8
[shortcut]
from=-3
activation=linear

# 9
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky

# 10
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky

# 11
[shortcut]
from=-3
activation=linear

# 12
# Downsample
# 第三个res模块，res8，一个CBL加上8个残差连接
[convolutional]
batch_normalize=1
filters=256
size=3
stride=2
pad=1
activation=leaky

# 13
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 14
# 在res8中，将每个残差连接的第二个CBL模块的卷积变为深度可分离卷积
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 14
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky

# 15
[shortcut]
#from=-3 普通卷积变成了深度可分离卷积，多了一层
from=-3
activation=linear

# 16
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 17
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky

# 17
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 18
[shortcut]
from=-3
activation=linear

# 19
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 20
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky

# 20
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 21
[shortcut]
from=-3
activation=linear

# 22
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 23
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky

# 23
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 24
[shortcut]
from=-3
activation=linear

# 25
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 26
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky

# 26
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 27
[shortcut]
from=-3
activation=linear

# 28
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 29
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky

# 29
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 30
[shortcut]
from=-3
activation=linear

# 31
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 32
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky
# 32
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 33
[shortcut]
from=-3
activation=linear

# 34
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky

# 35
# [convolutional]
# batch_normalize=1
# filters=256
# size=3
# stride=1
# pad=1
# activation=leaky
# 35
[ds_conv]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

# 36
[shortcut]
from=-3
activation=linear

# Downsample
# 第四个res模块，res8

# 37
[convolutional]
batch_normalize=1
filters=512
size=3
stride=2
pad=1
activation=leaky

# 38
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 39
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 39
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 40
[shortcut]
from=-3
activation=linear

# 41
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 42
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 42
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 43
[shortcut]
from=-3
activation=linear

# 44
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 45
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 45
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 46
[shortcut]
from=-3
activation=linear

# 47
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 48
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 48
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 49
[shortcut]
from=-3
activation=linear

# 50
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 51
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 51
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 52
[shortcut]
from=-3
activation=linear

# 53
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 54
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 54
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 55
[shortcut]
from=-3
activation=linear

# 56
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 57
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 57
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 57
[shortcut]
from=-3
activation=linear

# 58
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

# 59
# [convolutional]
# batch_normalize=1
# filters=512
# size=3
# stride=1
# pad=1
# activation=leaky
# 59
[ds_conv]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

# 60
[shortcut]
from=-3
activation=linear

# Downsample
# 第五个res模块，res4

# 61
[convolutional]
batch_normalize=1
filters=1024
size=3
stride=2
pad=1
activation=leaky

# 62
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

# 63
[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
# 63
# [ds_conv]
# batch_normalize=1
# filters=1024
# size=3
# stride=1
# pad=1
# activation=leaky

# 64
[shortcut]
from=-3
activation=linear

# 65
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

# 66
[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
# 66
# [ds_conv]
# batch_normalize=1
# filters=1024
# size=3
# stride=1
# pad=1
# activation=leaky

# 67
[shortcut]
from=-3
activation=linear

# 68
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

# 69
[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
# 69
# [ds_conv]
# batch_normalize=1
# filters=1024
# size=3
# stride=1
# pad=1
# activation=leaky

# 70
[shortcut]
from=-3
activation=linear

# 71
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

# 72
[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky
# 72
# [ds_conv]
# batch_normalize=1
# filters=1024
# size=3
# stride=1
# pad=1
# activation=leaky

# 73
[shortcut]
from=-3
activation=linear

######################

# 74
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

# 75
[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

# 76
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

# 77
[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

# 78
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

# 79
[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

# 80
[convolutional]
size=1
stride=1
pad=1
filters=18 
activation=linear


[yolo]
mask = 6,7,8
anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
classes=1
num=9
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1


[route]
layers = -4

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

[upsample]
stride=2

[route]
layers = -1, 61



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

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

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

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

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

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

[convolutional]
size=1
stride=1
pad=1
filters=18 
activation=linear


[yolo]
mask = 3,4,5
anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
classes=1
num=9
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1



[route]
layers = -4

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

[upsample]
stride=2

[route]
layers = -1, 36



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

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

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

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

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

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

[convolutional]
size=1
stride=1
pad=1
filters=18
activation=linear


[yolo]
mask = 0,1,2
anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
classes=1
num=9
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1