darknet/cfg/yolo.cfg

[net]
batch=64
subdivisions=2
height=448
width=448
channels=3
momentum=0.9
decay=0.0005

learning_rate=0.0005
policy=steps
steps=200,400,600,20000,30000
scales=2.5,2,2,.1,.1
max_batches = 40000

[crop]
crop_width=448
crop_height=448
flip=0
angle=0
saturation = 1.5
exposure = 1.5
noadjust=1

[convolutional]
batch_normalize=1
filters=64
size=7
stride=2
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=192
size=3
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

[convolutional]
batch_normalize=1
filters=256
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
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

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=256
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=512
size=1
stride=1
pad=1
activation=leaky

[convolutional]
batch_normalize=1
filters=1024
size=3
stride=1
pad=1
activation=leaky

#######

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

[convolutional]
batch_normalize=1
size=3
stride=2
pad=1
filters=1024
activation=leaky

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

[convolutional]
batch_normalize=1
size=3
stride=1
pad=1
filters=1024
activation=leaky

[local]
size=3
stride=1
pad=1
filters=256
activation=leaky

[dropout]
probability=.5

[connected]
output= 1715
activation=linear

[detection]
classes=20
coords=4
rescore=1
side=7
num=3
softmax=0
sqrt=1
jitter=.2

object_scale=1
noobject_scale=.5
class_scale=1
coord_scale=5
detection exp 2015-05-20 20:06:42 +03:00			`[net]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch=64`
			`subdivisions=2`
detection exp 2015-05-20 20:06:42 +03:00			`height=448`
			`width=448`
			`channels=3`
			`momentum=0.9`
			`decay=0.0005`

what do you even write here? 2016-08-11 21:54:24 +03:00			`learning_rate=0.0005`
stable 2015-09-09 22:48:40 +03:00			`policy=steps`
New YOLO 2015-11-09 22:31:39 +03:00			`steps=200,400,600,20000,30000`
			`scales=2.5,2,2,.1,.1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`max_batches = 40000`
stable 2015-09-09 22:48:40 +03:00
what do you even write here? 2016-08-11 21:54:24 +03:00			`[crop]`
			`crop_width=448`
			`crop_height=448`
			`flip=0`
			`angle=0`
			`saturation = 1.5`
			`exposure = 1.5`
			`noadjust=1`

detection exp 2015-05-20 20:06:42 +03:00			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=64`
			`size=7`
			`stride=2`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`

			`[maxpool]`
			`size=2`
			`stride=2`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=192`
			`size=3`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`stride=1`
detection exp 2015-05-20 20:06:42 +03:00			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`

			`[maxpool]`
			`size=2`
			`stride=2`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=128`
			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=256`
			`size=3`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`stride=1`
detection exp 2015-05-20 20:06:42 +03:00			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`filters=256`
detection exp 2015-05-20 20:06:42 +03:00			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`filters=512`
detection exp 2015-05-20 20:06:42 +03:00			`size=3`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`

			`[maxpool]`
			`size=2`
			`stride=2`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`filters=256`
detection exp 2015-05-20 20:06:42 +03:00			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=512`
			`size=3`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`stride=1`
detection exp 2015-05-20 20:06:42 +03:00			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=256`
			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=512`
			`size=3`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=256`
			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=512`
			`size=3`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=256`
			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=512`
			`size=3`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`filters=512`
detection exp 2015-05-20 20:06:42 +03:00			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`filters=1024`
detection exp 2015-05-20 20:06:42 +03:00			`size=3`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`

			`[maxpool]`
			`size=2`
			`stride=2`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`filters=512`
detection exp 2015-05-20 20:06:42 +03:00			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=1024`
			`size=3`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`stride=1`
detection exp 2015-05-20 20:06:42 +03:00			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=512`
			`size=1`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`filters=1024`
			`size=3`
			`stride=1`
			`pad=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`

			`#######`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`size=3`
			`stride=1`
			`pad=1`
			`filters=1024`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`size=3`
			`stride=2`
			`pad=1`
			`filters=1024`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
detection exp 2015-05-20 20:06:42 +03:00			`size=3`
			`stride=1`
			`pad=1`
			`filters=1024`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
syncing messed something up 2015-06-09 21:17:46 +03:00			`[convolutional]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`batch_normalize=1`
syncing messed something up 2015-06-09 21:17:46 +03:00			`size=3`
			`stride=1`
			`pad=1`
			`filters=1024`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
syncing messed something up 2015-06-09 21:17:46 +03:00
what do you even write here? 2016-08-11 21:54:24 +03:00			`[local]`
			`size=3`
			`stride=1`
			`pad=1`
			`filters=256`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=leaky`
detection exp 2015-05-20 20:06:42 +03:00
what do you even write here? 2016-08-11 21:54:24 +03:00			`[dropout]`
			`probability=.5`

detection exp 2015-05-20 20:06:42 +03:00			`[connected]`
what do you even write here? 2016-08-11 21:54:24 +03:00			`output= 1715`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=linear`
detection exp 2015-05-20 20:06:42 +03:00
New YOLO 2015-11-09 22:31:39 +03:00			`[detection]`
detection exp 2015-05-20 20:06:42 +03:00			`classes=20`
			`coords=4`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`rescore=1`
			`side=7`
what do you even write here? 2016-08-11 21:54:24 +03:00			`num=3`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`softmax=0`
			`sqrt=1`
			`jitter=.2`

			`object_scale=1`
			`noobject_scale=.5`
			`class_scale=1`
			`coord_scale=5`
changes to detection 2015-07-21 00:56:53 +03:00