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yolo-lightnet

Object Detection
darknet
yolo
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yolo-lightnet / head_body /lightnet-head_body-1024x768.cfg
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[net]
batch=256
subdivisions=16
width=1024
height=768
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=50
max_batches = 2000
policy=steps
steps=100,400,800,1600
scales=.5,.5,.5,.5
gaussian_noise=1
flip=1
##sparse=1 : 2:4 structured sparsity
[convolutional]
batch_normalize=1
filters=32
size=3
stride=2
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=2
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=2
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=2
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=3
stride=2
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
[convolutional]
#sparse=1
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=relu
##################################
### ASPPCSP ###
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
[route]
layers = -2
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
### ASPP ###
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
dilation=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
dilation=3
activation=relu
[route]
layers=-4
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
dilation=5
activation=relu
[route]
layers=-1,-3,-5,-6
### End ASPP ###
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
[route]
layers = -10,-1
# 44
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
### End ASPPCSP ###
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[upsample]
stride=2
[route]
layers = 30
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[route]
layers = -1,-3
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
# 56
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[upsample]
stride=2
[route]
layers = 20
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[route]
layers = -1,-3
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
size=3
stride=2
pad=1
filters=128
activation=relu
[route]
layers = -1,67
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
size=3
stride=2
pad=1
filters=256
activation=relu
[route]
layers = -1,53
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[route]
layers=-2
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
#sparse=1
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=relu
[route]
layers = -1,-3,-5,-7
[convolutional]
#sparse=1
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=relu
#############################
# ============ End of Neck ============ #
# ============ Head ============ #
# P3
[route]
layers = 80
[convolutional]
#sparse=1
batch_normalize=1
size=3
stride=1
pad=1
filters=128
activation=relu
[convolutional]
##sparse=1
size=1
stride=1
pad=1
filters=21
#activation=linear
activation=logistic
[yolo]
mask = 0,1,2
anchors = 8, 11, 20, 31, 34, 66, 64, 93, 54,184, 120,174, 97,334, 176,448, 344,564
classes=2
num=9
jitter=.3
scale_x_y = 2.0
ignore_thresh = .5
truth_thresh = 1
#random=1
resize=1.5
new_coords=1
iou_normalizer=0.05
# iou_loss=ciou
# P4
[route]
layers = 91
[convolutional]
#sparse=1
batch_normalize=1
size=3
stride=1
pad=1
filters=256
activation=relu
[convolutional]
##sparse=1
size=1
stride=1
pad=1
filters=21
#activation=linear
activation=logistic
[yolo]
mask = 3,4,5
anchors = 8, 11, 20, 31, 34, 66, 64, 93, 54,184, 120,174, 97,334, 176,448, 344,564
classes=2
num=9
jitter=.3
scale_x_y = 2.0
ignore_thresh = .5
truth_thresh = 1
resize=1.5
new_coords=1
iou_normalizer=0.05
# iou_loss=ciou
# P5
[route]
layers = 102
[convolutional]
#sparse=1
batch_normalize=1
size=3
stride=1
pad=1
filters=512
activation=relu
[convolutional]
##sparse=1
size=1
stride=1
pad=1
filters=21
#activation=linear
activation=logistic
[yolo]
mask = 6,7,8
anchors = 8, 11, 20, 31, 34, 66, 64, 93, 54,184, 120,174, 97,334, 176,448, 344,564
classes=2
num=9
jitter=.3
scale_x_y = 2.0
ignore_thresh = .7
truth_thresh = 1
resize=1.5
new_coords=1
iou_normalizer=0.05
iou_loss=ciou