vgg-16.cfg
1.38 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
[net]
batch=128
subdivisions=4
height=256
width=256
channels=3
learning_rate=0.00001
momentum=0.9
decay=0.0005
[crop]
crop_height=224
crop_width=224
flip=1
exposure=1
saturation=1
angle=0
[convolutional]
filters=64
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=64
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=128
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=128
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=256
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=256
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=256
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[convolutional]
filters=512
size=3
stride=1
pad=1
activation=relu
[maxpool]
size=2
stride=2
[connected]
output=4096
activation=relu
[dropout]
probability=.5
[connected]
output=4096
activation=relu
[dropout]
probability=.5
[connected]
output=1000
activation=linear
[softmax]
groups=1
[cost]
type=sse