cspx-p7-mish_hp.cfg

[net]
# Testing
#batch=1
#subdivisions=1
# Training
batch=64
subdivisions=16
#width=1536
#height=1536
width=896
height=896
channels=3
momentum=0.949
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
burn_in=1000
max_batches = 500500
policy=steps
steps=400000,450000
scales=.1,.1

mosaic=1
letter_box=1

### Start of Backbone ###

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

# Downsample

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

[convolutional]
batch_normalize=1
filters=40
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

# Downsample

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

[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

[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

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

[route]
layers = -1,-13

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

# Downsample

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

[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

[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

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

[route]
layers = -1,-49

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

# Downsample

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

[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

[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

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

[route]
layers = -1,-49

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

# Downsample

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

[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
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

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

[route]
layers = -1,-25

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

# Downsample

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

[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
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

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

[route]
layers = -1,-25

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

# Downsample

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

[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
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

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

[route]
layers = -1,-25

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

### End of backbone ###

### Start of 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

[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

[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

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

### End of CSPSPP ###

### Start of CSPPAN ###

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

[upsample]
stride=2

[route]
layers = 180 ###P6

[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

[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

[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

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

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

[upsample]
stride=2

[route]
layers = 152 ###P5

[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

[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

[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

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

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

[upsample]
stride=2

[route]
layers = 124 ###P4

[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

[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

[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

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

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

[upsample]
stride=2

[route]
layers = 72 ###P3

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

[route]
layers = -1, -3

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

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

[route]
layers = -2

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

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

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

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

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

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

[route]
layers = -1, -8

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

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

[route]
layers = -1, 271 ###S4

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

[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

[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

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

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

[route]
layers = -1, 255 ###S5

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

[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

[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

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

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

[route]
layers = -1, 239 ###S6

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

[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

[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

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

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

[route]
layers = -1, 223 ###S7

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

[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

[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

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

### End of CSPPAN ###

### Start of YOLO ###

[route]
layers = 287 ###

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

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

[sam]
from=-2

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

[convolutional]
size=1
stride=1
pad=1
#filters=340
filters=170
activation=linear

#[route]
#layers=-1

[yolo]
mask = 0,1
anchors = 13,17,  31,25,   24,51, 61,45    61,45,  48,102,  119,96, 97,189,    97,189,  217,184,  171,384, 324,451,    324,451, 545,357, 616,618, 800,800
classes=80
num=16
#jitter=.3
ignore_thresh = .7
truth_thresh = 1
resize=1.5
scale_x_y = 1.05
##iou_thresh=0.213
#cls_normalizer=1.0
#iou_normalizer=0.07

jitter=.1
#objectness_smooth=1
##iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=4.0

iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6

#counters_per_class = 26575, 7113, 44338, 8730, 5154, 6100, 4550, 10038, 10832, 13016, 1883, 1974, 1287, 9787, 10883, 4776, 5507, 6562, 9724, 8171, 5491, 1312, 5296, 5193, 8707, 11531, 12415, 6470, 6214, 2688, 6605, 2665, 6393, 9159, 3300, 3756, 5508, 6143, 4854, 24516, 7914, 20710, 5466, 7810, 6168, 14398, 9603, 5941,  4403, 6561, 7308, 7885, 2908, 5892, 7401, 6466, 38878, 5804, 8585, 4160, 15789,  4157, 5836, 4964, 2273, 5746, 2891, 6411, 1641, 3335, 223, 5624, 2658, 25244, 6320, 6539, 1464, 4775, 198, 1937
#max_delta=3

[route]
layers = 300 ###

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

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

[sam]
from=-2

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

[convolutional]
size=1
stride=1
pad=1
#filters=340
filters=255
activation=linear

[yolo]
mask = 1,2,3
anchors = 13,17,  31,25,   24,51, 61,45    61,45,  48,102,  119,96, 97,189,    97,189,  217,184,  171,384, 324,451,    324,451, 545,357, 616,618, 800,800
classes=80
num=16
#jitter=.3
ignore_thresh = .7
truth_thresh = 1
resize=1.5
scale_x_y = 1.05
##iou_thresh=0.213
#cls_normalizer=1.0
#iou_normalizer=0.07

jitter=.1
#objectness_smooth=1
#iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=1.0

iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6

#counters_per_class = 26575, 7113, 44338, 8730, 5154, 6100, 4550, 10038, 10832, 13016, 1883, 1974, 1287, 9787, 10883, 4776, 5507, 6562, 9724, 8171, 5491, 1312, 5296, 5193, 8707, 11531, 12415, 6470, 6214, 2688, 6605, 2665, 6393, 9159, 3300, 3756, 5508, 6143, 4854, 24516, 7914, 20710, 5466, 7810, 6168, 14398, 9603, 5941,  4403, 6561, 7308, 7885, 2908, 5892, 7401, 6466, 38878, 5804, 8585, 4160, 15789,  4157, 5836, 4964, 2273, 5746, 2891, 6411, 1641, 3335, 223, 5624, 2658, 25244, 6320, 6539, 1464, 4775, 198, 1937
#max_delta=3

[route]
layers = 313 ###

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

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

[sam]
from=-2

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

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

[yolo]
mask = 4,5,6,7
anchors = 13,17,  31,25,   24,51, 61,45    61,45,  48,102,  119,96, 97,189,    97,189,  217,184,  171,384, 324,451,    324,451, 545,357, 616,618, 800,800
classes=80
num=16
#jitter=.3
ignore_thresh = .7
truth_thresh = 1
resize=1.5
scale_x_y = 1.05
##iou_thresh=0.213
#cls_normalizer=1.0
#iou_normalizer=0.07

jitter=.1
objectness_smooth=1
#iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=0.5

iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6

counters_per_class = 26575, 7113, 44338, 8730, 5154, 6100, 4550, 10038, 10832, 13016, 1883, 1974, 1287, 9787, 10883, 4776, 5507, 6562, 9724, 8171, 5491, 1312, 5296, 5193, 8707, 11531, 12415, 6470, 6214, 2688, 6605, 2665, 6393, 9159, 3300, 3756, 5508, 6143, 4854, 24516, 7914, 20710, 5466, 7810, 6168, 14398, 9603, 5941,  4403, 6561, 7308, 7885, 2908, 5892, 7401, 6466, 38878, 5804, 8585, 4160, 15789,  4157, 5836, 4964, 2273, 5746, 2891, 6411, 1641, 3335, 223, 5624, 2658, 25244, 6320, 6539, 1464, 4775, 198, 1937
max_delta=3

[route]
layers = 326 ###

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

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

[sam]
from=-2

[convolutional]
batch_normalize=1
size=1
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,  31,25,   24,51, 61,45    61,45,  48,102,  119,96, 97,189,    97,189,  217,184,  171,384, 324,451,    324,451, 545,357, 616,618, 800,800
classes=80
num=16
#jitter=.3
ignore_thresh = .7
truth_thresh = 1
resize=1.5
scale_x_y = 1.05
##iou_thresh=0.213
#cls_normalizer=1.0
#iou_normalizer=0.07

jitter=.1
objectness_smooth=1
#iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=0.4

iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6

counters_per_class = 26575, 7113, 44338, 8730, 5154, 6100, 4550, 10038, 10832, 13016, 1883, 1974, 1287, 9787, 10883, 4776, 5507, 6562, 9724, 8171, 5491, 1312, 5296, 5193, 8707, 11531, 12415, 6470, 6214, 2688, 6605, 2665, 6393, 9159, 3300, 3756, 5508, 6143, 4854, 24516, 7914, 20710, 5466, 7810, 6168, 14398, 9603, 5941,  4403, 6561, 7308, 7885, 2908, 5892, 7401, 6466, 38878, 5804, 8585, 4160, 15789,  4157, 5836, 4964, 2273, 5746, 2891, 6411, 1641, 3335, 223, 5624, 2658, 25244, 6320, 6539, 1464, 4775, 198, 1937
max_delta=3

[route]
layers = 339 ###

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

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

[sam]
from=-2

[convolutional]
batch_normalize=1
size=1
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,  31,25,   24,51, 61,45    61,45,  48,102,  119,96, 97,189,    97,189,  217,184,  171,384, 324,451,    324,451, 545,357, 616,618, 800,800
classes=80
num=16
#jitter=.3
ignore_thresh = .7
truth_thresh = 1
resize=1.5
scale_x_y = 1.05
##iou_thresh=0.213
#cls_normalizer=1.0
#iou_normalizer=0.07

jitter=.1
objectness_smooth=1
#iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=0.1

iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6

#counters_per_class = 26575, 7113, 44338, 8730, 5154, 6100, 4550, 10038, 10832, 13016, 1883, 1974, 1287, 9787, 10883, 4776, 5507, 6562, 9724, 8171, 5491, 1312, 5296, 5193, 8707, 11531, 12415, 6470, 6214, 2688, 6605, 2665, 6393, 9159, 3300, 3756, 5508, 6143, 4854, 24516, 7914, 20710, 5466, 7810, 6168, 14398, 9603, 5941,  4403, 6561, 7308, 7885, 2908, 5892, 7401, 6466, 38878, 5804, 8585, 4160, 15789,  4157, 5836, 4964, 2273, 5746, 2891, 6411, 1641, 3335, 223, 5624, 2658, 25244, 6320, 6539, 1464, 4775, 198, 1937
max_delta=3

### End of YOLO ###