Updated cfg-files for new weights-files

AlexeyAB

2017-04-07 e5ab66d7a770c3861cb93e3fca0079d34b5a26d4

Updated cfg-files for new weights-files

 build/darknet/x64/darknet_voc.cmd

@@ -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

 build/darknet/x64/tiny-yolo-voc.cfg

@@ -12,7 +12,7 @@
hue=.1

learning_rate=0.001
max_batches = 40100
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

 build/darknet/x64/yolo-voc.cfg

@@ -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 @@
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 @@
[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 @@
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 @@

absolute=1
thresh = .6
random=0
random=1

 build/darknet/x64/yolo.cfg

@@ -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 @@
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 @@
[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 @@
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 @@

absolute=1
thresh = .6
random=0
random=1

 cfg/tiny-yolo-voc.cfg

@@ -12,7 +12,7 @@
hue=.1

learning_rate=0.001
max_batches = 40100
max_batches = 40200
policy=steps
steps=-1,100,20000,30000
scales=.1,10,.1,.1

 cfg/yolo-voc.cfg

@@ -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 @@
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 @@
[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 @@
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 @@

absolute=1
thresh = .6
random=0
random=1

 cfg/yolo.cfg

@@ -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 @@
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 @@
[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 @@
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 @@

absolute=1
thresh = .6
random=0
random=1