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darknet
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darknet/cfg/yolov7-tiny.cfg

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[net]
# Testing
#batch=1
#subdivisions=1
# Training
batch=64
subdivisions=1
width=416
height=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.00261
burn_in=1000
max_batches = 2000200
policy=steps
steps=1600000,1800000
scales=.1,.1
# 0
[convolutional]
batch_normalize=1
filters=32
size=3
stride=2
pad=1
activation=leaky
# 1
[convolutional]
batch_normalize=1
filters=64
size=3
stride=2
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 8
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 16
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 24
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 32
[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky
##################################
### SPPCSP ###
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
[route]
layers = -2
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
### 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=256
size=1
stride=1
pad=1
activation=leaky
[route]
layers = -10,-1
# 44
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
### End SPPCSP ###
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[upsample]
stride=2
[route]
layers = 24
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[route]
layers = -1,-3
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 56
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[upsample]
stride=2
[route]
layers = 16
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[route]
layers = -1,-3
[convolutional]
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=32
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 68
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
##########################
[convolutional]
batch_normalize=1
size=3
stride=2
pad=1
filters=128
activation=leaky
[route]
layers = -1,56
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=64
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 77
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
size=3
stride=2
pad=1
filters=256
activation=leaky
[route]
layers = -1,44
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[route]
layers=-2
[convolutional]
batch_normalize=1
filters=128
size=1
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[convolutional]
batch_normalize=1
filters=128
size=3
stride=1
pad=1
activation=leaky
[route]
layers = -5,-3,-2,-1
# 86
[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky
#############################
# ============ End of Neck ============ #
# ============ Head ============ #
# P3
[route]
layers = 68
[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=128
activation=leaky
[convolutional]
size=1
stride=1
pad=1
filters=255
#activation=linear
activation=logistic
[yolo]
mask = 0,1,2
anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
classes=80
num=9
jitter=.1
scale_x_y = 2.0
objectness_smooth=1
ignore_thresh = .7
truth_thresh = 1
#random=1
resize=1.5
iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=1.0
iou_loss=ciou
nms_kind=diounms
beta_nms=0.6
new_coords=1
max_delta=2
# P4
[route]
layers = 77
[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=256
activation=leaky
[convolutional]
size=1
stride=1
pad=1
filters=255
#activation=linear
activation=logistic
[yolo]
mask = 3,4,5
anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
classes=80
num=9
jitter=.1
scale_x_y = 2.0
objectness_smooth=1
ignore_thresh = .7
truth_thresh = 1
#random=1
resize=1.5
iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=1.0
iou_loss=ciou
nms_kind=diounms
beta_nms=0.6
new_coords=1
max_delta=2
# P5
[route]
layers = 86
[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=512
activation=leaky
[convolutional]
size=1
stride=1
pad=1
filters=255
#activation=linear
activation=logistic
[yolo]
mask = 6,7,8
anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
classes=80
num=9
jitter=.1
scale_x_y = 2.0
objectness_smooth=1
ignore_thresh = .7
truth_thresh = 1
#random=1
resize=1.5
iou_thresh=0.2
iou_normalizer=0.05
cls_normalizer=0.5
obj_normalizer=1.0
iou_loss=ciou
nms_kind=diounms
beta_nms=0.6
new_coords=1
max_delta=2
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