mirror of
https://github.com/wassname/PSPNet-Keras-tensorflow.git
synced 2026-09-02 12:00:07 +08:00
3895 lines
57 KiB
Plaintext
3895 lines
57 KiB
Plaintext
#
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input: "data"
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input_dim: 1
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input_dim: 3
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input_dim: 473
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input_dim: 473
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layer {
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name: "conv1_1_3x3_s2"
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type: "Convolution"
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bottom: "data"
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top: "conv1_1_3x3_s2"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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convolution_param {
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num_output: 64
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pad: 1
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kernel_size: 3
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stride: 2
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weight_filler {
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type: "msra"
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}
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bias_term: false
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}
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}
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layer {
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name: "conv1_1_3x3_s2/bn"
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type: "BN"
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bottom: "conv1_1_3x3_s2"
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top: "conv1_1_3x3_s2"
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param {
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lr_mult: 1
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decay_mult: 0
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}
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param {
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|
lr_mult: 1
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|
decay_mult: 0
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|
}
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param {
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|
lr_mult: 0
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|
decay_mult: 0
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}
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|
param {
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|
lr_mult: 0
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|
decay_mult: 0
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|
}
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|
bn_param {
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|
slope_filler {
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type: "constant"
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|
value: 1
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}
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bias_filler {
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type: "constant"
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|
value: 0
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}
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frozen: true
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momentum: 0.95
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}
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}
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layer {
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name: "conv1_1_3x3_s2/relu"
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type: "ReLU"
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bottom: "conv1_1_3x3_s2"
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top: "conv1_1_3x3_s2"
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}
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layer {
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name: "conv1_2_3x3"
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type: "Convolution"
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bottom: "conv1_1_3x3_s2"
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top: "conv1_2_3x3"
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param {
|
|
lr_mult: 1
|
|
decay_mult: 1
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|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 1
|
|
kernel_size: 3
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|
stride: 1
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|
weight_filler {
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|
type: "msra"
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|
}
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|
bias_term: false
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|
}
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|
}
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|
layer {
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name: "conv1_2_3x3/bn"
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|
type: "BN"
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|
bottom: "conv1_2_3x3"
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top: "conv1_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
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}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
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|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
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|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
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momentum: 0.95
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|
}
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|
}
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|
layer {
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name: "conv1_2_3x3/relu"
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|
type: "ReLU"
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bottom: "conv1_2_3x3"
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top: "conv1_2_3x3"
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}
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|
layer {
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name: "conv1_3_3x3"
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type: "Convolution"
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bottom: "conv1_2_3x3"
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top: "conv1_3_3x3"
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|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
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|
num_output: 128
|
|
pad: 1
|
|
kernel_size: 3
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|
stride: 1
|
|
weight_filler {
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|
type: "msra"
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|
}
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|
bias_term: false
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}
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}
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layer {
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name: "conv1_3_3x3/bn"
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|
type: "BN"
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bottom: "conv1_3_3x3"
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top: "conv1_3_3x3"
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|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
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|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
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|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
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|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
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|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
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|
value: 0
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|
}
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|
frozen: true
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|
momentum: 0.95
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|
}
|
|
}
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|
layer {
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|
name: "conv1_3_3x3/relu"
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|
type: "ReLU"
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bottom: "conv1_3_3x3"
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top: "conv1_3_3x3"
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}
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layer {
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name: "pool1_3x3_s2"
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type: "Pooling"
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bottom: "conv1_3_3x3"
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top: "pool1_3x3_s2"
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pooling_param {
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pool: MAX
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kernel_size: 3
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stride: 2
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pad: 1
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}
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|
}
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layer {
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name: "conv2_1_1x1_reduce"
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type: "Convolution"
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bottom: "pool1_3x3_s2"
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top: "conv2_1_1x1_reduce"
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|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 0
|
|
kernel_size: 1
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|
stride: 1
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|
weight_filler {
|
|
type: "msra"
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|
}
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|
bias_term: false
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|
}
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|
}
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|
layer {
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|
name: "conv2_1_1x1_reduce/bn"
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|
type: "BN"
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|
bottom: "conv2_1_1x1_reduce"
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|
top: "conv2_1_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
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|
}
|
|
}
|
|
layer {
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|
name: "conv2_1_1x1_reduce/relu"
|
|
type: "ReLU"
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|
bottom: "conv2_1_1x1_reduce"
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|
top: "conv2_1_1x1_reduce"
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|
}
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|
layer {
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|
name: "conv2_1_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv2_1_1x1_reduce"
|
|
top: "conv2_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 1
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_1_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv2_1_3x3"
|
|
top: "conv2_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_1_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv2_1_3x3"
|
|
top: "conv2_1_3x3"
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|
}
|
|
layer {
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|
name: "conv2_1_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv2_1_3x3"
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|
top: "conv2_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
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|
name: "conv2_1_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv2_1_1x1_increase"
|
|
top: "conv2_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
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|
momentum: 0.95
|
|
}
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|
}
|
|
layer {
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|
name: "conv2_1_1x1_proj"
|
|
type: "Convolution"
|
|
bottom: "pool1_3x3_s2"
|
|
top: "conv2_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_1_1x1_proj/bn"
|
|
type: "BN"
|
|
bottom: "conv2_1_1x1_proj"
|
|
top: "conv2_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
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|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
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|
}
|
|
layer {
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name: "conv2_1"
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|
type: "Eltwise"
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|
bottom: "conv2_1_1x1_proj"
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|
bottom: "conv2_1_1x1_increase"
|
|
top: "conv2_1"
|
|
eltwise_param {
|
|
operation: SUM
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|
}
|
|
}
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|
layer {
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|
name: "conv2_1/relu"
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|
type: "ReLU"
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|
bottom: "conv2_1"
|
|
top: "conv2_1"
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|
}
|
|
layer {
|
|
name: "conv2_2_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv2_1"
|
|
top: "conv2_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_2_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv2_2_1x1_reduce"
|
|
top: "conv2_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_2_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv2_2_1x1_reduce"
|
|
top: "conv2_2_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv2_2_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv2_2_1x1_reduce"
|
|
top: "conv2_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 1
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_2_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv2_2_3x3"
|
|
top: "conv2_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_2_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv2_2_3x3"
|
|
top: "conv2_2_3x3"
|
|
}
|
|
layer {
|
|
name: "conv2_2_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv2_2_3x3"
|
|
top: "conv2_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_2_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv2_2_1x1_increase"
|
|
top: "conv2_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_2"
|
|
type: "Eltwise"
|
|
bottom: "conv2_1"
|
|
bottom: "conv2_2_1x1_increase"
|
|
top: "conv2_2"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_2/relu"
|
|
type: "ReLU"
|
|
bottom: "conv2_2"
|
|
top: "conv2_2"
|
|
}
|
|
layer {
|
|
name: "conv2_3_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv2_2"
|
|
top: "conv2_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_3_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv2_3_1x1_reduce"
|
|
top: "conv2_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_3_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv2_3_1x1_reduce"
|
|
top: "conv2_3_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv2_3_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv2_3_1x1_reduce"
|
|
top: "conv2_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 64
|
|
pad: 1
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_3_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv2_3_3x3"
|
|
top: "conv2_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_3_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv2_3_3x3"
|
|
top: "conv2_3_3x3"
|
|
}
|
|
layer {
|
|
name: "conv2_3_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv2_3_3x3"
|
|
top: "conv2_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_3_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv2_3_1x1_increase"
|
|
top: "conv2_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_3"
|
|
type: "Eltwise"
|
|
bottom: "conv2_2"
|
|
bottom: "conv2_3_1x1_increase"
|
|
top: "conv2_3"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv2_3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv2_3"
|
|
top: "conv2_3"
|
|
}
|
|
layer {
|
|
name: "conv3_1_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv2_3"
|
|
top: "conv3_1_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 2
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv3_1_1x1_reduce"
|
|
top: "conv3_1_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_1_1x1_reduce"
|
|
top: "conv3_1_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv3_1_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv3_1_1x1_reduce"
|
|
top: "conv3_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 1
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv3_1_3x3"
|
|
top: "conv3_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_1_3x3"
|
|
top: "conv3_1_3x3"
|
|
}
|
|
layer {
|
|
name: "conv3_1_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv3_1_3x3"
|
|
top: "conv3_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv3_1_1x1_increase"
|
|
top: "conv3_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1_1x1_proj"
|
|
type: "Convolution"
|
|
bottom: "conv2_3"
|
|
top: "conv3_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 2
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1_1x1_proj/bn"
|
|
type: "BN"
|
|
bottom: "conv3_1_1x1_proj"
|
|
top: "conv3_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1"
|
|
type: "Eltwise"
|
|
bottom: "conv3_1_1x1_proj"
|
|
bottom: "conv3_1_1x1_increase"
|
|
top: "conv3_1"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_1/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_1"
|
|
top: "conv3_1"
|
|
}
|
|
layer {
|
|
name: "conv3_2_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv3_1"
|
|
top: "conv3_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_2_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv3_2_1x1_reduce"
|
|
top: "conv3_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_2_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_2_1x1_reduce"
|
|
top: "conv3_2_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv3_2_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv3_2_1x1_reduce"
|
|
top: "conv3_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 1
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_2_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv3_2_3x3"
|
|
top: "conv3_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_2_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_2_3x3"
|
|
top: "conv3_2_3x3"
|
|
}
|
|
layer {
|
|
name: "conv3_2_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv3_2_3x3"
|
|
top: "conv3_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_2_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv3_2_1x1_increase"
|
|
top: "conv3_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_2"
|
|
type: "Eltwise"
|
|
bottom: "conv3_1"
|
|
bottom: "conv3_2_1x1_increase"
|
|
top: "conv3_2"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_2/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_2"
|
|
top: "conv3_2"
|
|
}
|
|
layer {
|
|
name: "conv3_3_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv3_2"
|
|
top: "conv3_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_3_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv3_3_1x1_reduce"
|
|
top: "conv3_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_3_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_3_1x1_reduce"
|
|
top: "conv3_3_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv3_3_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv3_3_1x1_reduce"
|
|
top: "conv3_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 1
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_3_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv3_3_3x3"
|
|
top: "conv3_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_3_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_3_3x3"
|
|
top: "conv3_3_3x3"
|
|
}
|
|
layer {
|
|
name: "conv3_3_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv3_3_3x3"
|
|
top: "conv3_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_3_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv3_3_1x1_increase"
|
|
top: "conv3_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_3"
|
|
type: "Eltwise"
|
|
bottom: "conv3_2"
|
|
bottom: "conv3_3_1x1_increase"
|
|
top: "conv3_3"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_3"
|
|
top: "conv3_3"
|
|
}
|
|
layer {
|
|
name: "conv3_4_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv3_3"
|
|
top: "conv3_4_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_4_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv3_4_1x1_reduce"
|
|
top: "conv3_4_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_4_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_4_1x1_reduce"
|
|
top: "conv3_4_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv3_4_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv3_4_1x1_reduce"
|
|
top: "conv3_4_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 128
|
|
pad: 1
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_4_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv3_4_3x3"
|
|
top: "conv3_4_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_4_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_4_3x3"
|
|
top: "conv3_4_3x3"
|
|
}
|
|
layer {
|
|
name: "conv3_4_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv3_4_3x3"
|
|
top: "conv3_4_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_4_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv3_4_1x1_increase"
|
|
top: "conv3_4_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_4"
|
|
type: "Eltwise"
|
|
bottom: "conv3_3"
|
|
bottom: "conv3_4_1x1_increase"
|
|
top: "conv3_4"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv3_4/relu"
|
|
type: "ReLU"
|
|
bottom: "conv3_4"
|
|
top: "conv3_4"
|
|
}
|
|
layer {
|
|
name: "conv4_1_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv3_4"
|
|
top: "conv4_1_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv4_1_1x1_reduce"
|
|
top: "conv4_1_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_1_1x1_reduce"
|
|
top: "conv4_1_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv4_1_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv4_1_1x1_reduce"
|
|
top: "conv4_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 2
|
|
dilation: 2
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv4_1_3x3"
|
|
top: "conv4_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_1_3x3"
|
|
top: "conv4_1_3x3"
|
|
}
|
|
layer {
|
|
name: "conv4_1_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv4_1_3x3"
|
|
top: "conv4_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv4_1_1x1_increase"
|
|
top: "conv4_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1_1x1_proj"
|
|
type: "Convolution"
|
|
bottom: "conv3_4"
|
|
top: "conv4_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1_1x1_proj/bn"
|
|
type: "BN"
|
|
bottom: "conv4_1_1x1_proj"
|
|
top: "conv4_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1"
|
|
type: "Eltwise"
|
|
bottom: "conv4_1_1x1_proj"
|
|
bottom: "conv4_1_1x1_increase"
|
|
top: "conv4_1"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_1/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_1"
|
|
top: "conv4_1"
|
|
}
|
|
layer {
|
|
name: "conv4_2_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv4_1"
|
|
top: "conv4_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv4_2_1x1_reduce"
|
|
top: "conv4_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_2_1x1_reduce"
|
|
top: "conv4_2_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv4_2_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv4_2_1x1_reduce"
|
|
top: "conv4_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 2
|
|
dilation: 2
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv4_2_3x3"
|
|
top: "conv4_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_2_3x3"
|
|
top: "conv4_2_3x3"
|
|
}
|
|
layer {
|
|
name: "conv4_2_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv4_2_3x3"
|
|
top: "conv4_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv4_2_1x1_increase"
|
|
top: "conv4_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2"
|
|
type: "Eltwise"
|
|
bottom: "conv4_1"
|
|
bottom: "conv4_2_1x1_increase"
|
|
top: "conv4_2"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_2/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_2"
|
|
top: "conv4_2"
|
|
}
|
|
layer {
|
|
name: "conv4_3_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv4_2"
|
|
top: "conv4_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_3_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv4_3_1x1_reduce"
|
|
top: "conv4_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_3_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_3_1x1_reduce"
|
|
top: "conv4_3_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv4_3_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv4_3_1x1_reduce"
|
|
top: "conv4_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 2
|
|
dilation: 2
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_3_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv4_3_3x3"
|
|
top: "conv4_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_3_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_3_3x3"
|
|
top: "conv4_3_3x3"
|
|
}
|
|
layer {
|
|
name: "conv4_3_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv4_3_3x3"
|
|
top: "conv4_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_3_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv4_3_1x1_increase"
|
|
top: "conv4_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_3"
|
|
type: "Eltwise"
|
|
bottom: "conv4_2"
|
|
bottom: "conv4_3_1x1_increase"
|
|
top: "conv4_3"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_3"
|
|
top: "conv4_3"
|
|
}
|
|
layer {
|
|
name: "conv4_4_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv4_3"
|
|
top: "conv4_4_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_4_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv4_4_1x1_reduce"
|
|
top: "conv4_4_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_4_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_4_1x1_reduce"
|
|
top: "conv4_4_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv4_4_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv4_4_1x1_reduce"
|
|
top: "conv4_4_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 2
|
|
dilation: 2
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_4_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv4_4_3x3"
|
|
top: "conv4_4_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_4_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_4_3x3"
|
|
top: "conv4_4_3x3"
|
|
}
|
|
layer {
|
|
name: "conv4_4_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv4_4_3x3"
|
|
top: "conv4_4_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_4_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv4_4_1x1_increase"
|
|
top: "conv4_4_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_4"
|
|
type: "Eltwise"
|
|
bottom: "conv4_3"
|
|
bottom: "conv4_4_1x1_increase"
|
|
top: "conv4_4"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_4/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_4"
|
|
top: "conv4_4"
|
|
}
|
|
layer {
|
|
name: "conv4_5_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv4_4"
|
|
top: "conv4_5_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_5_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv4_5_1x1_reduce"
|
|
top: "conv4_5_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_5_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_5_1x1_reduce"
|
|
top: "conv4_5_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv4_5_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv4_5_1x1_reduce"
|
|
top: "conv4_5_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 2
|
|
dilation: 2
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_5_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv4_5_3x3"
|
|
top: "conv4_5_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_5_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_5_3x3"
|
|
top: "conv4_5_3x3"
|
|
}
|
|
layer {
|
|
name: "conv4_5_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv4_5_3x3"
|
|
top: "conv4_5_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_5_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv4_5_1x1_increase"
|
|
top: "conv4_5_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_5"
|
|
type: "Eltwise"
|
|
bottom: "conv4_4"
|
|
bottom: "conv4_5_1x1_increase"
|
|
top: "conv4_5"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_5/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_5"
|
|
top: "conv4_5"
|
|
}
|
|
layer {
|
|
name: "conv4_6_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv4_5"
|
|
top: "conv4_6_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_6_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv4_6_1x1_reduce"
|
|
top: "conv4_6_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_6_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_6_1x1_reduce"
|
|
top: "conv4_6_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv4_6_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv4_6_1x1_reduce"
|
|
top: "conv4_6_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 256
|
|
pad: 2
|
|
dilation: 2
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_6_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv4_6_3x3"
|
|
top: "conv4_6_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_6_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_6_3x3"
|
|
top: "conv4_6_3x3"
|
|
}
|
|
layer {
|
|
name: "conv4_6_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv4_6_3x3"
|
|
top: "conv4_6_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 1024
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_6_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv4_6_1x1_increase"
|
|
top: "conv4_6_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_6"
|
|
type: "Eltwise"
|
|
bottom: "conv4_5"
|
|
bottom: "conv4_6_1x1_increase"
|
|
top: "conv4_6"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv4_6/relu"
|
|
type: "ReLU"
|
|
bottom: "conv4_6"
|
|
top: "conv4_6"
|
|
}
|
|
layer {
|
|
name: "conv5_1_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv4_6"
|
|
top: "conv5_1_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv5_1_1x1_reduce"
|
|
top: "conv5_1_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_1_1x1_reduce"
|
|
top: "conv5_1_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv5_1_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv5_1_1x1_reduce"
|
|
top: "conv5_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 4
|
|
dilation: 4
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv5_1_3x3"
|
|
top: "conv5_1_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_1_3x3"
|
|
top: "conv5_1_3x3"
|
|
}
|
|
layer {
|
|
name: "conv5_1_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv5_1_3x3"
|
|
top: "conv5_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 2048
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv5_1_1x1_increase"
|
|
top: "conv5_1_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1_1x1_proj"
|
|
type: "Convolution"
|
|
bottom: "conv4_6"
|
|
top: "conv5_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 2048
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1_1x1_proj/bn"
|
|
type: "BN"
|
|
bottom: "conv5_1_1x1_proj"
|
|
top: "conv5_1_1x1_proj"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1"
|
|
type: "Eltwise"
|
|
bottom: "conv5_1_1x1_proj"
|
|
bottom: "conv5_1_1x1_increase"
|
|
top: "conv5_1"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_1/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_1"
|
|
top: "conv5_1"
|
|
}
|
|
layer {
|
|
name: "conv5_2_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv5_1"
|
|
top: "conv5_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv5_2_1x1_reduce"
|
|
top: "conv5_2_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_2_1x1_reduce"
|
|
top: "conv5_2_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv5_2_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv5_2_1x1_reduce"
|
|
top: "conv5_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 4
|
|
dilation: 4
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv5_2_3x3"
|
|
top: "conv5_2_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_2_3x3"
|
|
top: "conv5_2_3x3"
|
|
}
|
|
layer {
|
|
name: "conv5_2_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv5_2_3x3"
|
|
top: "conv5_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 2048
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv5_2_1x1_increase"
|
|
top: "conv5_2_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2"
|
|
type: "Eltwise"
|
|
bottom: "conv5_1"
|
|
bottom: "conv5_2_1x1_increase"
|
|
top: "conv5_2"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_2/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_2"
|
|
top: "conv5_2"
|
|
}
|
|
layer {
|
|
name: "conv5_3_1x1_reduce"
|
|
type: "Convolution"
|
|
bottom: "conv5_2"
|
|
top: "conv5_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_1x1_reduce/bn"
|
|
type: "BN"
|
|
bottom: "conv5_3_1x1_reduce"
|
|
top: "conv5_3_1x1_reduce"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_1x1_reduce/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_3_1x1_reduce"
|
|
top: "conv5_3_1x1_reduce"
|
|
}
|
|
layer {
|
|
name: "conv5_3_3x3"
|
|
type: "Convolution"
|
|
bottom: "conv5_3_1x1_reduce"
|
|
top: "conv5_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
pad: 4
|
|
dilation: 4
|
|
kernel_size: 3
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_3x3/bn"
|
|
type: "BN"
|
|
bottom: "conv5_3_3x3"
|
|
top: "conv5_3_3x3"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_3x3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_3_3x3"
|
|
top: "conv5_3_3x3"
|
|
}
|
|
layer {
|
|
name: "conv5_3_1x1_increase"
|
|
type: "Convolution"
|
|
bottom: "conv5_3_3x3"
|
|
top: "conv5_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 2048
|
|
pad: 0
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_1x1_increase/bn"
|
|
type: "BN"
|
|
bottom: "conv5_3_1x1_increase"
|
|
top: "conv5_3_1x1_increase"
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 1
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3"
|
|
type: "Eltwise"
|
|
bottom: "conv5_2"
|
|
bottom: "conv5_3_1x1_increase"
|
|
top: "conv5_3"
|
|
eltwise_param {
|
|
operation: SUM
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_3"
|
|
top: "conv5_3"
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool1"
|
|
type: "Pooling"
|
|
bottom: "conv5_3"
|
|
top: "conv5_3_pool1"
|
|
pooling_param {
|
|
pool: AVE
|
|
kernel_size: 60
|
|
stride: 60
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool1_conv"
|
|
type: "Convolution"
|
|
bottom: "conv5_3_pool1"
|
|
top: "conv5_3_pool1_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool1_conv/bn"
|
|
type: "BN"
|
|
bottom: "conv5_3_pool1_conv"
|
|
top: "conv5_3_pool1_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool1_conv/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_3_pool1_conv"
|
|
top: "conv5_3_pool1_conv"
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool1_interp"
|
|
type: "Interp"
|
|
bottom: "conv5_3_pool1_conv"
|
|
top: "conv5_3_pool1_interp"
|
|
interp_param {
|
|
height: 60
|
|
width: 60
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool2"
|
|
type: "Pooling"
|
|
bottom: "conv5_3"
|
|
top: "conv5_3_pool2"
|
|
pooling_param {
|
|
pool: AVE
|
|
kernel_size: 30
|
|
stride: 30
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool2_conv"
|
|
type: "Convolution"
|
|
bottom: "conv5_3_pool2"
|
|
top: "conv5_3_pool2_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool2_conv/bn"
|
|
type: "BN"
|
|
bottom: "conv5_3_pool2_conv"
|
|
top: "conv5_3_pool2_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool2_conv/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_3_pool2_conv"
|
|
top: "conv5_3_pool2_conv"
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool2_interp"
|
|
type: "Interp"
|
|
bottom: "conv5_3_pool2_conv"
|
|
top: "conv5_3_pool2_interp"
|
|
interp_param {
|
|
height: 60
|
|
width: 60
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool3"
|
|
type: "Pooling"
|
|
bottom: "conv5_3"
|
|
top: "conv5_3_pool3"
|
|
pooling_param {
|
|
pool: AVE
|
|
kernel_size: 20
|
|
stride: 20
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool3_conv"
|
|
type: "Convolution"
|
|
bottom: "conv5_3_pool3"
|
|
top: "conv5_3_pool3_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool3_conv/bn"
|
|
type: "BN"
|
|
bottom: "conv5_3_pool3_conv"
|
|
top: "conv5_3_pool3_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool3_conv/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_3_pool3_conv"
|
|
top: "conv5_3_pool3_conv"
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool3_interp"
|
|
type: "Interp"
|
|
bottom: "conv5_3_pool3_conv"
|
|
top: "conv5_3_pool3_interp"
|
|
interp_param {
|
|
height: 60
|
|
width: 60
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool6"
|
|
type: "Pooling"
|
|
bottom: "conv5_3"
|
|
top: "conv5_3_pool6"
|
|
pooling_param {
|
|
pool: AVE
|
|
kernel_size: 10
|
|
stride: 10
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool6_conv"
|
|
type: "Convolution"
|
|
bottom: "conv5_3_pool6"
|
|
top: "conv5_3_pool6_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool6_conv/bn"
|
|
type: "BN"
|
|
bottom: "conv5_3_pool6_conv"
|
|
top: "conv5_3_pool6_conv"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool6_conv/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_3_pool6_conv"
|
|
top: "conv5_3_pool6_conv"
|
|
}
|
|
layer {
|
|
name: "conv5_3_pool6_interp"
|
|
type: "Interp"
|
|
bottom: "conv5_3_pool6_conv"
|
|
top: "conv5_3_pool6_interp"
|
|
interp_param {
|
|
height: 60
|
|
width: 60
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_3_concat"
|
|
type: "Concat"
|
|
bottom: "conv5_3"
|
|
bottom: "conv5_3_pool6_interp"
|
|
bottom: "conv5_3_pool3_interp"
|
|
bottom: "conv5_3_pool2_interp"
|
|
bottom: "conv5_3_pool1_interp"
|
|
top: "conv5_3_concat"
|
|
}
|
|
layer {
|
|
name: "conv5_4"
|
|
type: "Convolution"
|
|
bottom: "conv5_3_concat"
|
|
top: "conv5_4"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 512
|
|
kernel_size: 3
|
|
stride: 1
|
|
pad: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
bias_term: false
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_4/bn"
|
|
type: "BN"
|
|
bottom: "conv5_4"
|
|
top: "conv5_4"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 0
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 0
|
|
decay_mult: 0
|
|
}
|
|
bn_param {
|
|
slope_filler {
|
|
type: "constant"
|
|
value: 1
|
|
}
|
|
bias_filler {
|
|
type: "constant"
|
|
value: 0
|
|
}
|
|
frozen: true
|
|
momentum: 0.95
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv5_4/relu"
|
|
type: "ReLU"
|
|
bottom: "conv5_4"
|
|
top: "conv5_4"
|
|
}
|
|
layer {
|
|
name: "conv5_4/dropout"
|
|
type: "Dropout"
|
|
bottom: "conv5_4"
|
|
top: "conv5_4"
|
|
dropout_param {
|
|
dropout_ratio: 0.1
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv6"
|
|
type: "Convolution"
|
|
bottom: "conv5_4"
|
|
top: "conv6"
|
|
param {
|
|
lr_mult: 10
|
|
decay_mult: 1
|
|
}
|
|
param {
|
|
lr_mult: 20
|
|
decay_mult: 1
|
|
}
|
|
convolution_param {
|
|
num_output: 150
|
|
kernel_size: 1
|
|
stride: 1
|
|
weight_filler {
|
|
type: "msra"
|
|
}
|
|
}
|
|
}
|
|
layer {
|
|
name: "conv6_interp"
|
|
type: "Interp"
|
|
bottom: "conv6"
|
|
top: "conv6_interp"
|
|
interp_param {
|
|
zoom_factor: 8
|
|
}
|
|
}
|