-
Notifications
You must be signed in to change notification settings - Fork 32
/
Copy pathtrain_val.prototxt
165 lines (153 loc) · 8.35 KB
/
train_val.prototxt
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
154
155
156
157
158
159
160
161
162
163
164
name: "HED"
layer {
name: "data"
type: "ImageLabelmapData"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: false
mean_value: 104.00699
mean_value: 116.66877
mean_value: 122.67892
}
image_data_param {
root_folder: "../../data/"
source: "../../data/train_pair.list"
batch_size: 1
shuffle: true
new_height: 0
new_width: 0
}
}
layer {
name: "data"
type: "ImageLabelmapData"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
mirror: false
mean_value: 104.00699
mean_value: 116.66877
mean_value: 122.67892
}
image_data_param {
root_folder: "../../data/"
source: "../../data/val_pair.list"
#Just setup the network. No real online testing
batch_size: 1
shuffle: true
new_height: 0
new_width: 0
}
}
layer { bottom: 'data' top: 'conv1_1' name: 'conv1_1' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 64 pad: 35 kernel_size: 3 } }
layer { bottom: 'conv1_1' top: 'conv1_1' name: 'relu1_1' type: "ReLU" }
layer { bottom: 'conv1_1' top: 'conv1_2' name: 'conv1_2' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 64 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv1_2' top: 'conv1_2' name: 'relu1_2' type: "ReLU" }
layer { name: 'pool1' bottom: 'conv1_2' top: 'pool1' type: "Pooling"
pooling_param { pool: MAX kernel_size: 2 stride: 2 } }
layer { name: 'conv2_1' bottom: 'pool1' top: 'conv2_1' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 128 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv2_1' top: 'conv2_1' name: 'relu2_1' type: "ReLU" }
layer { bottom: 'conv2_1' top: 'conv2_2' name: 'conv2_2' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 128 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv2_2' top: 'conv2_2' name: 'relu2_2' type: "ReLU" }
layer { bottom: 'conv2_2' top: 'pool2' name: 'pool2' type: "Pooling"
pooling_param { pool: MAX kernel_size: 2 stride: 2 } }
layer { bottom: 'pool2' top: 'conv3_1' name: 'conv3_1' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 256 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv3_1' top: 'conv3_1' name: 'relu3_1' type: "ReLU" }
layer { bottom: 'conv3_1' top: 'conv3_2' name: 'conv3_2' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 256 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv3_2' top: 'conv3_2' name: 'relu3_2' type: "ReLU" }
layer { bottom: 'conv3_2' top: 'conv3_3' name: 'conv3_3' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 256 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv3_3' top: 'conv3_3' name: 'relu3_3' type: "ReLU" }
layer { bottom: 'conv3_3' top: 'pool3' name: 'pool3' type: "Pooling"
pooling_param { pool: MAX kernel_size: 2 stride: 2 } }
layer { bottom: 'pool3' top: 'conv4_1' name: 'conv4_1' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv4_1' top: 'conv4_1' name: 'relu4_1' type: "ReLU" }
layer { bottom: 'conv4_1' top: 'conv4_2' name: 'conv4_2' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv4_2' top: 'conv4_2' name: 'relu4_2' type: "ReLU" }
layer { bottom: 'conv4_2' top: 'conv4_3' name: 'conv4_3' type: "Convolution"
param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv4_3' top: 'conv4_3' name: 'relu4_3' type: "ReLU" }
layer { bottom: 'conv4_3' top: 'pool4' name: 'pool4' type: "Pooling"
pooling_param { pool: MAX kernel_size: 2 stride: 2 } }
layer { bottom: 'pool4' top: 'conv5_1' name: 'conv5_1' type: "Convolution"
param { lr_mult: 100 decay_mult: 1 } param { lr_mult: 200 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv5_1' top: 'conv5_1' name: 'relu5_1' type: "ReLU" }
layer { bottom: 'conv5_1' top: 'conv5_2' name: 'conv5_2' type: "Convolution"
param { lr_mult: 100 decay_mult: 1 } param { lr_mult: 200 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv5_2' top: 'conv5_2' name: 'relu5_2' type: "ReLU" }
layer { bottom: 'conv5_2' top: 'conv5_3' name: 'conv5_3' type: "Convolution"
param { lr_mult: 100 decay_mult: 1 } param { lr_mult: 200 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 512 pad: 1 kernel_size: 3 } }
layer { bottom: 'conv5_3' top: 'conv5_3' name: 'relu5_3' type: "ReLU" }
## DSN conv 1 ###
layer { name: 'score-dsn1' type: "Convolution" bottom: 'conv1_2' top: 'score-dsn1-up'
param { lr_mult: 0.01 decay_mult: 1 } param { lr_mult: 0.02 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 1 kernel_size: 1 } }
layer { type: "Crop" name: 'crop' bottom: 'score-dsn1-up' bottom: 'data' top: 'upscore-dsn1' }
### DSN conv 2 ###
layer { name: 'score-dsn2' type: "Convolution" bottom: 'conv2_2' top: 'score-dsn2'
param { lr_mult: 0.01 decay_mult: 1 } param { lr_mult: 0.02 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 1 kernel_size: 1 } }
layer { type: "Deconvolution" name: 'upsample_2' bottom: 'score-dsn2' top: 'score-dsn2-up'
param { lr_mult: 0 decay_mult: 1 } param { lr_mult: 0 decay_mult: 0}
convolution_param { kernel_size: 4 stride: 2 num_output: 1 } }
layer { type: "Crop" name: 'crop' bottom: 'score-dsn2-up' bottom: 'data' top: 'upscore-dsn2' }
### DSN conv 3 ###
layer { name: 'score-dsn3' type: "Convolution" bottom: 'conv3_3' top: 'score-dsn3'
param { lr_mult: 0.01 decay_mult: 1 } param { lr_mult: 0.02 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 1 kernel_size: 1 } }
layer { type: "Deconvolution" name: 'upsample_4' bottom: 'score-dsn3' top: 'score-dsn3-up'
param { lr_mult: 0 decay_mult: 1 } param { lr_mult: 0 decay_mult: 0}
convolution_param { kernel_size: 8 stride: 4 num_output: 1 } }
layer { type: "Crop" name: 'crop' bottom: 'score-dsn3-up' bottom: 'data' top: 'upscore-dsn3' }
###DSN conv 4###
layer { name: 'score-dsn4' type: "Convolution" bottom: 'conv4_3' top: 'score-dsn4'
param { lr_mult: 0.01 decay_mult: 1 } param { lr_mult: 0.02 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 1 kernel_size: 1 } }
layer { type: "Deconvolution" name: 'upsample_8' bottom: 'score-dsn4' top: 'score-dsn4-up'
param { lr_mult: 0 decay_mult: 1 } param { lr_mult: 0 decay_mult: 0}
convolution_param { kernel_size: 16 stride: 8 num_output: 1 } }
layer { type: "Crop" name: 'crop' bottom: 'score-dsn4-up' bottom: 'data' top: 'upscore-dsn4' }
###DSN conv 5###
layer { name: 'score-dsn5' type: "Convolution" bottom: 'conv5_3' top: 'score-dsn5'
param { lr_mult: 0.01 decay_mult: 1 } param { lr_mult: 0.02 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 1 kernel_size: 1 } }
layer { type: "Deconvolution" name: 'upsample_16' bottom: 'score-dsn5' top: 'score-dsn5-up'
param { lr_mult: 0 decay_mult: 1 } param { lr_mult: 0 decay_mult: 0}
convolution_param { kernel_size: 32 stride: 16 num_output: 1 } }
layer { type: "Crop" name: 'crop' bottom: 'score-dsn5-up' bottom: 'data' top: 'upscore-dsn5' }
### Concat and multiscale weight layer ###
layer { name: "concat" bottom: "upscore-dsn1" bottom: "upscore-dsn2" bottom: "upscore-dsn3"
bottom: "upscore-dsn4" bottom: "upscore-dsn5" top: "concat-upscore" type: "Concat"
concat_param { concat_dim: 1} }
layer { name: 'new-score-weighting' type: "Convolution" bottom: 'concat-upscore' top: 'upscore-fuse'
param { lr_mult: 0.001 decay_mult: 1 } param { lr_mult: 0.002 decay_mult: 0}
convolution_param { engine: CAFFE num_output: 1 kernel_size: 1 weight_filler {type: "constant" value: 0.2} } }
layer { type: "SigmoidCrossEntropyLoss" bottom: "upscore-fuse" bottom: "label" top:"fuse_loss" loss_weight: 1}