darknet/cfg/yolo.cfg

[net]
# Testing
batch=1
subdivisions=1
# Training
# batch=64
# subdivisions=8
height=416
width=416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1

learning_rate=0.001
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1

[convolutional]
batch_normalize=1
filters=32
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

[convolutional]
batch_normalize=1
filters=64
size=3
stride=1
pad=1
activation=leaky

[maxpool]
size=2
stride=2

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

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

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

[maxpool]
size=2
stride=2

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

[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

[maxpool]
size=2
stride=2

[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

[maxpool]
size=2
stride=2

[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
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=1
pad=1
filters=1024
activation=leaky

[route]
layers=-9

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

[reorg]
stride=2

[route]
layers=-1,-4

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

[convolutional]
size=1
stride=1
pad=1
filters=425
activation=linear


[region]
anchors =  0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828
bias_match=1
classes=80
coords=4
num=5
softmax=1
jitter=.3
rescore=1

object_scale=5
noobject_scale=1
class_scale=1
coord_scale=1

absolute=1
thresh = .6
random=1
detection exp 2015-05-20 20:06:42 +03:00			`[net]`
opencv is hell. this is why we can't have nice things. 2017-03-30 06:27:54 +03:00			`# Testing`
			`batch=1`
			`subdivisions=1`
			`# Training`
			`# batch=64`
			`# subdivisions=8`
fixes 2017-03-27 10:01:27 +03:00			`height=416`
			`width=416`
detection exp 2015-05-20 20:06:42 +03:00			`channels=3`
			`momentum=0.9`
			`decay=0.0005`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`angle=0`
			`saturation = 1.5`
			`exposure = 1.5`
updates and things 2016-09-02 02:48:41 +03:00			`hue=.1`
detection exp 2015-05-20 20:06:42 +03:00
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`learning_rate=0.001`
:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00			`burn_in=1000`
			`max_batches = 500200`
stable 2015-09-09 22:48:40 +03:00			`policy=steps`
:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00			`steps=400000,450000`
			`scales=.1,.1`
stable 2015-09-09 22:48:40 +03:00
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`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`filters=32`
			`size=3`
			`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`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`filters=64`
detection exp 2015-05-20 20:06:42 +03:00			`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=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`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`filters=64`
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`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`filters=128`
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`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`size=3`
detection exp 2015-05-20 20:06:42 +03:00			`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`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`filters=128`
			`size=1`
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`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`size=3`
detection exp 2015-05-20 20:06:42 +03:00			`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
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`[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=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
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`[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=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`

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`

:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00
CVPR Experiments 2015-11-04 06:23:17 +03:00			`#######`
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=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
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`[route]`
			`layers=-9`

:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00			`[convolutional]`
			`batch_normalize=1`
			`size=1`
			`stride=1`
			`pad=1`
			`filters=64`
			`activation=leaky`

:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`[reorg]`
			`stride=2`

			`[route]`
:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00			`layers=-1,-4`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +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
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`[convolutional]`
			`size=1`
what do you even write here? 2016-08-11 21:54:24 +03:00			`stride=1`
			`pad=1`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`filters=425`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`activation=linear`
detection exp 2015-05-20 20:06:42 +03:00
:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`[region]`
:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00			`anchors = 0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7.88282, 3.52778, 9.77052, 9.16828`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`bias_match=1`
			`classes=80`
detection exp 2015-05-20 20:06:42 +03:00			`coords=4`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`num=5`
			`softmax=1`
:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00			`jitter=.3`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`rescore=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`object_scale=5`
			`noobject_scale=1`
CVPR Experiments 2015-11-04 06:23:17 +03:00			`class_scale=1`
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`coord_scale=1`
changes to detection 2015-07-21 00:56:53 +03:00
:fire: :fire: yolo v2 :fire: :fire: 2016-11-17 23:18:19 +03:00			`absolute=1`
			`thresh = .6`
:eyeofthetiger::noseofthetiger::eyeofthetiger2: 2017-03-27 09:42:30 +03:00			`random=1`