[net]
batch=64
subdivisions=8
width=1536
height=1536
channels=3
momentum=0.949
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.00261
burn_in=1000
max_batches = 500500
policy=steps
steps=400000,450000
scales=.1,.1

mosaic=1


# ============ Backbone ============ #

# Stem 

# 0
[convolutional]
batch_normalize=1
filters=40
size=3
stride=1
pad=1
activation=mish


# P1

# Downsample

[convolutional]
batch_normalize=1
filters=80
size=3
stride=2
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=40
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=40
size=1
stride=1
pad=1
activation=mish

# Residual Block

[convolutional]
batch_normalize=1
filters=40
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=40
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

# Transition first

[convolutional]
batch_normalize=1
filters=40
size=1
stride=1
pad=1
activation=mish

# Merge [-1, -(3k+4)]

[route]
layers = -1,-7

# Transition last

# 10 (previous+7+3k)
[convolutional]
batch_normalize=1
filters=80
size=1
stride=1
pad=1
activation=mish


# P2

# Downsample

[convolutional]
batch_normalize=1
filters=160
size=3
stride=2
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=80
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=80
size=1
stride=1
pad=1
activation=mish

# Residual Block

[convolutional]
batch_normalize=1
filters=80
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=80
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=80
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=80
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=80
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=80
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

# Transition first

[convolutional]
batch_normalize=1
filters=80
size=1
stride=1
pad=1
activation=mish

# Merge [-1, -(3k+4)]

[route]
layers = -1,-13

# Transition last

# 26 (previous+7+3k)
[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish


# P3

# Downsample

[convolutional]
batch_normalize=1
filters=320
size=3
stride=2
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

# Residual Block

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

# Transition first

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

# Merge [-1, -(3k+4)]

[route]
layers = -1,-49

# Transition last

# 78 (previous+7+3k)
[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish


# P4

# Downsample

[convolutional]
batch_normalize=1
filters=640
size=3
stride=2
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

# Residual Block

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

# Transition first

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

# Merge [-1, -(3k+4)]

[route]
layers = -1,-49

# Transition last

# 130 (previous+7+3k)
[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish


# P5

# Downsample

[convolutional]
batch_normalize=1
filters=1280
size=3
stride=2
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Residual Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

# Transition first

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Merge [-1, -(3k+4)]

[route]
layers = -1,-25

# Transition last

# 158 (previous+7+3k)
[convolutional]
batch_normalize=1
filters=1280
size=1
stride=1
pad=1
activation=mish


# P6

# Downsample

[convolutional]
batch_normalize=1
filters=1280
size=3
stride=2
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Residual Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

# Transition first

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Merge [-1, -(3k+4)]

[route]
layers = -1,-25

# Transition last

# 186 (previous+7+3k)
[convolutional]
batch_normalize=1
filters=1280
size=1
stride=1
pad=1
activation=mish


# P7

# Downsample

[convolutional]
batch_normalize=1
filters=1280
size=3
stride=2
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Residual Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=3
stride=1
pad=1
activation=mish

[shortcut]
from=-3
activation=linear

# Transition first

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Merge [-1, -(3k+4)]

[route]
layers = -1,-25

# Transition last

# 214 (previous+7+3k)
[convolutional]
batch_normalize=1
filters=1280
size=1
stride=1
pad=1
activation=mish

# ============ End of Backbone ============ #

# ============ Neck ============ #

# CSPSPP

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

### SPP ###
[maxpool]
stride=1
size=5

[route]
layers=-2

[maxpool]
stride=1
size=9

[route]
layers=-4

[maxpool]
stride=1
size=13

[route]
layers=-1,-3,-5,-6
### End SPP ###

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[route]
layers = -1, -13

# 229 (previous+6+5+2k)
[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# End of CSPSPP


# FPN-6

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[upsample]
stride=2

[route]
layers = 186

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -1, -3

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

# Merge [-1, -(2k+2)]

[route]
layers = -1, -8

# Transition last

# 245 (previous+6+4+2k)
[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish


# FPN-5

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[upsample]
stride=2

[route]
layers = 158

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -1, -3

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

# Merge [-1, -(2k+2)]

[route]
layers = -1, -8

# Transition last

# 261 (previous+6+4+2k)
[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish


# FPN-4

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[upsample]
stride=2

[route]
layers = 130

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[route]
layers = -1, -3

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=320
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=320
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=320
activation=mish

# Merge [-1, -(2k+2)]

[route]
layers = -1, -8

# Transition last

# 277 (previous+6+4+2k)
[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish


# FPN-3

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[upsample]
stride=2

[route]
layers = 78

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[route]
layers = -1, -3

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=160
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=160
activation=mish

[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=160
activation=mish

# Merge [-1, -(2k+2)]

[route]
layers = -1, -8

# Transition last

# 293 (previous+6+4+2k)
[convolutional]
batch_normalize=1
filters=160
size=1
stride=1
pad=1
activation=mish


# PAN-4

[convolutional]
batch_normalize=1
size=3
stride=2
pad=1
filters=320
activation=mish

[route]
layers = -1, 277

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=320
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=320
activation=mish

[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=320
activation=mish

[route]
layers = -1,-8

# Transition last

# 306 (previous+3+4+2k)
[convolutional]
batch_normalize=1
filters=320
size=1
stride=1
pad=1
activation=mish


# PAN-5

[convolutional]
batch_normalize=1
size=3
stride=2
pad=1
filters=640
activation=mish

[route]
layers = -1, 261

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[route]
layers = -1,-8

# Transition last

# 319 (previous+3+4+2k)
[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish


# PAN-6

[convolutional]
batch_normalize=1
size=3
stride=2
pad=1
filters=640
activation=mish

[route]
layers = -1, 245

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[route]
layers = -1,-8

# Transition last

# 332 (previous+3+4+2k)
[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish


# PAN-7

[convolutional]
batch_normalize=1
size=3
stride=2
pad=1
filters=640
activation=mish

[route]
layers = -1, 229

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# Split

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[route]
layers = -2

# Plain Block

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[route]
layers = -1,-8

# Transition last

# 345 (previous+3+4+2k)
[convolutional]
batch_normalize=1
filters=640
size=1
stride=1
pad=1
activation=mish

# ============ End of Neck ============ #

# ============ Head ============ #

# YOLO-3

[route]
layers = 293

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=320
activation=mish

[convolutional]
size=1
stride=1
pad=1
filters=340
activation=linear

[yolo]
mask = 0,1,2,3
anchors = 13,17,  22,25,  27,66, 55,41,  57,88,  112,69,  69,177,  136,138,  136,138,  287,114,  134,275,  268,248,  268,248,  232,504, 445,416,  640,640,  812,393,  477,808,  1070,908,  1408,1408
classes=80
num=20
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1
scale_x_y = 1.05
iou_thresh=0.213
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6


# YOLO-4

[route]
layers = 306

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=640
activation=mish

[convolutional]
size=1
stride=1
pad=1
filters=340
activation=linear

[yolo]
mask = 4,5,6,7
anchors = 13,17,  22,25,  27,66, 55,41,  57,88,  112,69,  69,177,  136,138,  136,138,  287,114,  134,275,  268,248,  268,248,  232,504, 445,416,  640,640,  812,393,  477,808,  1070,908,  1408,1408
classes=80
num=20
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1
scale_x_y = 1.05
iou_thresh=0.213
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6


# YOLO-5

[route]
layers = 319

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1280
activation=mish

[convolutional]
size=1
stride=1
pad=1
filters=340
activation=linear

[yolo]
mask = 8,9,10,11
anchors = 13,17,  22,25,  27,66, 55,41,  57,88,  112,69,  69,177,  136,138,  136,138,  287,114,  134,275,  268,248,  268,248,  232,504, 445,416,  640,640,  812,393,  477,808,  1070,908,  1408,1408
classes=80
num=20
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1
scale_x_y = 1.05
iou_thresh=0.213
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6


# YOLO-6

[route]
layers = 332

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1280
activation=mish

[convolutional]
size=1
stride=1
pad=1
filters=340
activation=linear

[yolo]
mask = 12,13,14,15
anchors = 13,17,  22,25,  27,66, 55,41,  57,88,  112,69,  69,177,  136,138,  136,138,  287,114,  134,275,  268,248,  268,248,  232,504, 445,416,  640,640,  812,393,  477,808,  1070,908,  1408,1408
classes=80
num=20
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1
scale_x_y = 1.05
iou_thresh=0.213
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6


# YOLO-7

[route]
layers = 345

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1280
activation=mish

[convolutional]
size=1
stride=1
pad=1
filters=340
activation=linear

[yolo]
mask = 16,17,18,19
anchors = 13,17,  22,25,  27,66, 55,41,  57,88,  112,69,  69,177,  136,138,  136,138,  287,114,  134,275,  268,248,  268,248,  232,504, 445,416,  640,640,  812,393,  477,808,  1070,908,  1408,1408
classes=80
num=20
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1
scale_x_y = 1.05
iou_thresh=0.213
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6

# ============ End of Head ============ #