darknet/cfg/yolo-tiny.cfg

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2015-11-10 00:26:21 +03:00
[net]
batch=64
subdivisions=64
height=448
width=448
channels=3
momentum=0.9
decay=0.0005
learning_rate=0.0001
policy=steps
steps=20,40,60,80,20000,30000
scales=5,5,2,2,.1,.1
max_batches = 40000
[crop]
crop_width=448
crop_height=448
flip=0
angle=0
saturation = 1.5
exposure = 1.5
[convolutional]
filters=16
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
filters=32
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
filters=64
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
filters=128
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
filters=256
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=leaky
[maxpool]
size=2
stride=2
[convolutional]
filters=1024
size=3
stride=1
pad=1
activation=leaky
[convolutional]
filters=1024
size=3
stride=1
pad=1
activation=leaky
[convolutional]
filters=1024
size=3
stride=1
pad=1
activation=leaky
[connected]
output=256
activation=linear
[connected]
output=4096
activation=leaky
[dropout]
probability=.5
[connected]
output= 1470
activation=linear
[detection]
classes=20
coords=4
rescore=1
side=7
num=2
softmax=0
sqrt=1
jitter=.2
object_scale=1
noobject_scale=.5
class_scale=1
coord_scale=5