darknet/cfg/yolov1/yolo-small.cfg

240 lines
2.3 KiB
INI
Raw Normal View History

2015-07-12 08:52:43 +03:00
[net]
batch=64
2015-11-10 00:26:21 +03:00
subdivisions=64
2015-07-12 08:52:43 +03:00
height=448
width=448
channels=3
momentum=0.9
decay=0.0005
2015-11-10 00:12:08 +03:00
learning_rate=0.001
policy=steps
steps=200,400,600,20000,30000
scales=2.5,2,2,.1,.1
max_batches = 40000
2015-07-12 08:52:43 +03:00
[crop]
crop_width=448
crop_height=448
flip=0
angle=0
2015-11-10 00:12:08 +03:00
saturation = 1.5
exposure = 1.5
2015-07-12 08:52:43 +03:00
[convolutional]
filters=64
size=7
stride=2
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
[maxpool]
size=2
stride=2
2015-07-12 08:52:43 +03:00
[convolutional]
filters=192
size=3
2015-11-10 00:12:08 +03:00
stride=1
2015-07-12 08:52:43 +03:00
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
[maxpool]
size=2
stride=2
2015-07-12 08:52:43 +03:00
[convolutional]
filters=128
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=256
size=3
2015-11-10 00:12:08 +03:00
stride=1
2015-07-12 08:52:43 +03:00
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
2015-11-10 00:12:08 +03:00
filters=256
2015-07-12 08:52:43 +03:00
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
2015-11-10 00:12:08 +03:00
filters=512
2015-07-12 08:52:43 +03:00
size=3
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
[maxpool]
size=2
stride=2
2015-07-12 08:52:43 +03:00
[convolutional]
2015-11-10 00:12:08 +03:00
filters=256
2015-07-12 08:52:43 +03:00
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=512
size=3
2015-11-10 00:12:08 +03:00
stride=1
2015-07-12 08:52:43 +03:00
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=256
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=512
size=3
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=256
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=512
size=3
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=256
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=512
size=3
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
2015-11-10 00:12:08 +03:00
filters=512
2015-07-12 08:52:43 +03:00
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
2015-11-10 00:12:08 +03:00
filters=1024
2015-07-12 08:52:43 +03:00
size=3
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
[maxpool]
size=2
stride=2
2015-07-12 08:52:43 +03:00
[convolutional]
2015-11-10 00:12:08 +03:00
filters=512
2015-07-12 08:52:43 +03:00
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=1024
size=3
2015-11-10 00:12:08 +03:00
stride=1
2015-07-12 08:52:43 +03:00
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=512
size=1
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
filters=1024
size=3
stride=1
pad=1
2015-11-10 00:12:08 +03:00
activation=leaky
#######
2015-07-12 08:52:43 +03:00
[convolutional]
size=3
stride=1
pad=1
filters=1024
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
size=3
stride=2
pad=1
filters=1024
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
size=3
stride=1
pad=1
filters=1024
2015-11-10 00:12:08 +03:00
activation=leaky
2015-07-12 08:52:43 +03:00
[convolutional]
size=3
stride=1
pad=1
2015-11-10 00:12:08 +03:00
filters=1024
activation=leaky
[connected]
output=512
activation=leaky
2015-07-12 08:52:43 +03:00
[connected]
2015-11-10 00:12:08 +03:00
output=4096
activation=leaky
2015-07-12 08:52:43 +03:00
[dropout]
probability=.5
[connected]
2015-11-10 00:12:08 +03:00
output= 1470
activation=linear
2015-07-12 08:52:43 +03:00
[detection]
classes=20
coords=4
rescore=1
2015-11-10 00:12:08 +03:00
side=7
num=2
softmax=0
sqrt=1
jitter=.2
object_scale=1
noobject_scale=.5
class_scale=1
coord_scale=5
2015-07-21 01:11:01 +03:00