Updated cfg-files for new weights-files

This commit is contained in:
AlexeyAB
2017-04-07 18:06:56 +03:00
parent 9c63bd33ad
commit e5ab66d7a7
7 changed files with 95 additions and 39 deletions

View File

@ -1,6 +1,6 @@
darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -i 0 -thresh 0.1
darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights -i 0 -thresh 0.2
pause

View File

@ -12,7 +12,7 @@ exposure = 1.5
hue=.1
learning_rate=0.001
max_batches = 40100
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

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@ -1,6 +1,10 @@
[net]
batch=64
subdivisions=8
# Testing
batch=1
subdivisions=1
# Training
# batch=64
# subdivisions=8
height=416
width=416
channels=3
@ -11,11 +15,12 @@ saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.0001
max_batches = 45000
learning_rate=0.001
burn_in=1000
max_batches = 80200
policy=steps
steps=100,25000,35000
scales=10,.1,.1
steps=40000,60000
scales=.1,.1
[convolutional]
batch_normalize=1
@ -203,11 +208,19 @@ 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,-3
layers=-1,-4
[convolutional]
batch_normalize=1
@ -224,14 +237,15 @@ pad=1
filters=125
activation=linear
[region]
anchors = 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52
anchors = 1.3221, 1.73145, 3.19275, 4.00944, 5.05587, 8.09892, 9.47112, 4.84053, 11.2364, 10.0071
bias_match=1
classes=20
coords=4
num=5
softmax=1
jitter=.2
jitter=.3
rescore=1
object_scale=5
@ -241,4 +255,4 @@ coord_scale=1
absolute=1
thresh = .6
random=0
random=1

View File

@ -1,8 +1,12 @@
[net]
# Testing
batch=1
subdivisions=1
width=416
# Training
# batch=64
# subdivisions=8
height=416
width=416
channels=3
momentum=0.9
decay=0.0005
@ -12,10 +16,11 @@ exposure = 1.5
hue=.1
learning_rate=0.001
max_batches = 120000
burn_in=1000
max_batches = 500200
policy=steps
steps=-1,100,80000,100000
scales=.1,10,.1,.1
steps=400000,450000
scales=.1,.1
[convolutional]
batch_normalize=1
@ -203,11 +208,19 @@ 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,-3
layers=-1,-4
[convolutional]
batch_normalize=1
@ -224,14 +237,15 @@ pad=1
filters=425
activation=linear
[region]
anchors = 0.738768,0.874946, 2.42204,2.65704, 4.30971,7.04493, 10.246,4.59428, 12.6868,11.8741
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=.2
jitter=.3
rescore=1
object_scale=5
@ -241,4 +255,4 @@ coord_scale=1
absolute=1
thresh = .6
random=0
random=1

View File

@ -12,7 +12,7 @@ exposure = 1.5
hue=.1
learning_rate=0.001
max_batches = 40100
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

View File

@ -1,6 +1,10 @@
[net]
batch=64
subdivisions=8
# Testing
batch=1
subdivisions=1
# Training
# batch=64
# subdivisions=8
height=416
width=416
channels=3
@ -11,11 +15,12 @@ saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.0001
max_batches = 45000
learning_rate=0.001
burn_in=1000
max_batches = 80200
policy=steps
steps=100,25000,35000
scales=10,.1,.1
steps=40000,60000
scales=.1,.1
[convolutional]
batch_normalize=1
@ -203,11 +208,19 @@ 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,-3
layers=-1,-4
[convolutional]
batch_normalize=1
@ -224,14 +237,15 @@ pad=1
filters=125
activation=linear
[region]
anchors = 1.08,1.19, 3.42,4.41, 6.63,11.38, 9.42,5.11, 16.62,10.52
anchors = 1.3221, 1.73145, 3.19275, 4.00944, 5.05587, 8.09892, 9.47112, 4.84053, 11.2364, 10.0071
bias_match=1
classes=20
coords=4
num=5
softmax=1
jitter=.2
jitter=.3
rescore=1
object_scale=5
@ -241,4 +255,4 @@ coord_scale=1
absolute=1
thresh = .6
random=0
random=1

View File

@ -1,8 +1,12 @@
[net]
# Testing
batch=1
subdivisions=1
width=416
# Training
# batch=64
# subdivisions=8
height=416
width=416
channels=3
momentum=0.9
decay=0.0005
@ -12,10 +16,11 @@ exposure = 1.5
hue=.1
learning_rate=0.001
max_batches = 120000
burn_in=1000
max_batches = 500200
policy=steps
steps=-1,100,80000,100000
scales=.1,10,.1,.1
steps=400000,450000
scales=.1,.1
[convolutional]
batch_normalize=1
@ -203,11 +208,19 @@ 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,-3
layers=-1,-4
[convolutional]
batch_normalize=1
@ -224,14 +237,15 @@ pad=1
filters=425
activation=linear
[region]
anchors = 0.738768,0.874946, 2.42204,2.65704, 4.30971,7.04493, 10.246,4.59428, 12.6868,11.8741
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=.2
jitter=.3
rescore=1
object_scale=5
@ -241,4 +255,4 @@ coord_scale=1
absolute=1
thresh = .6
random=0
random=1