YOLOR / cfg /yolov4_p7.cfg
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[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 ============ #