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Open Source Computer Vision Library
https://opencv.org/
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3102 lines
44 KiB
3102 lines
44 KiB
7 years ago
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name: "MobileNet-SSD"
|
||
|
input: "data"
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||
|
input_shape {
|
||
|
dim: 1
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||
|
dim: 3
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||
|
dim: 300
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||
|
dim: 300
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv0"
|
||
|
type: "Convolution"
|
||
|
bottom: "data"
|
||
|
top: "conv0"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 32
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv0/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv0"
|
||
|
top: "conv0"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv0/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv0"
|
||
|
top: "conv0"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv0/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv0"
|
||
|
top: "conv0"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv0"
|
||
|
top: "conv1/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 32
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 32
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv1/dw"
|
||
|
top: "conv1/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv1/dw"
|
||
|
top: "conv1/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv1/dw"
|
||
|
top: "conv1/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv1/dw"
|
||
|
top: "conv1"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 64
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv1"
|
||
|
top: "conv1"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv1"
|
||
|
top: "conv1"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv1/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv1"
|
||
|
top: "conv1"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv1"
|
||
|
top: "conv2/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 64
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
group: 64
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv2/dw"
|
||
|
top: "conv2/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv2/dw"
|
||
|
top: "conv2/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv2/dw"
|
||
|
top: "conv2/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv2/dw"
|
||
|
top: "conv2"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 128
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv2"
|
||
|
top: "conv2"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv2"
|
||
|
top: "conv2"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv2/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv2"
|
||
|
top: "conv2"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv2"
|
||
|
top: "conv3/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 128
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 128
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv3/dw"
|
||
|
top: "conv3/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv3/dw"
|
||
|
top: "conv3/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv3/dw"
|
||
|
top: "conv3/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv3/dw"
|
||
|
top: "conv3"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 128
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv3"
|
||
|
top: "conv3"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv3"
|
||
|
top: "conv3"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv3/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv3"
|
||
|
top: "conv3"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv3"
|
||
|
top: "conv4/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 128
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
group: 128
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv4/dw"
|
||
|
top: "conv4/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv4/dw"
|
||
|
top: "conv4/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv4/dw"
|
||
|
top: "conv4/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv4/dw"
|
||
|
top: "conv4"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 256
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv4"
|
||
|
top: "conv4"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv4"
|
||
|
top: "conv4"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv4/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv4"
|
||
|
top: "conv4"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv4"
|
||
|
top: "conv5/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 256
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 256
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv5/dw"
|
||
|
top: "conv5/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv5/dw"
|
||
|
top: "conv5/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv5/dw"
|
||
|
top: "conv5/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv5/dw"
|
||
|
top: "conv5"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 256
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv5"
|
||
|
top: "conv5"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv5"
|
||
|
top: "conv5"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv5/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv5"
|
||
|
top: "conv5"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv5"
|
||
|
top: "conv6/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 256
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
group: 256
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv6/dw"
|
||
|
top: "conv6/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv6/dw"
|
||
|
top: "conv6/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv6/dw"
|
||
|
top: "conv6/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv6/dw"
|
||
|
top: "conv6"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv6"
|
||
|
top: "conv6"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv6"
|
||
|
top: "conv6"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv6/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv6"
|
||
|
top: "conv6"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv6"
|
||
|
top: "conv7/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 512
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv7/dw"
|
||
|
top: "conv7/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv7/dw"
|
||
|
top: "conv7/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv7/dw"
|
||
|
top: "conv7/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv7/dw"
|
||
|
top: "conv7"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv7"
|
||
|
top: "conv7"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv7"
|
||
|
top: "conv7"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv7/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv7"
|
||
|
top: "conv7"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv7"
|
||
|
top: "conv8/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 512
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv8/dw"
|
||
|
top: "conv8/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv8/dw"
|
||
|
top: "conv8/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv8/dw"
|
||
|
top: "conv8/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv8/dw"
|
||
|
top: "conv8"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv8"
|
||
|
top: "conv8"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv8"
|
||
|
top: "conv8"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv8/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv8"
|
||
|
top: "conv8"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv8"
|
||
|
top: "conv9/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 512
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv9/dw"
|
||
|
top: "conv9/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv9/dw"
|
||
|
top: "conv9/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv9/dw"
|
||
|
top: "conv9/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv9/dw"
|
||
|
top: "conv9"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv9"
|
||
|
top: "conv9"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv9"
|
||
|
top: "conv9"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv9/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv9"
|
||
|
top: "conv9"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv9"
|
||
|
top: "conv10/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 512
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv10/dw"
|
||
|
top: "conv10/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv10/dw"
|
||
|
top: "conv10/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv10/dw"
|
||
|
top: "conv10/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv10/dw"
|
||
|
top: "conv10"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv10"
|
||
|
top: "conv10"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv10"
|
||
|
top: "conv10"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv10/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv10"
|
||
|
top: "conv10"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv10"
|
||
|
top: "conv11/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 512
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv11/dw"
|
||
|
top: "conv11/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv11/dw"
|
||
|
top: "conv11/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv11/dw"
|
||
|
top: "conv11/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv11/dw"
|
||
|
top: "conv11"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv11"
|
||
|
top: "conv11"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv11"
|
||
|
top: "conv11"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv11"
|
||
|
top: "conv11"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv11"
|
||
|
top: "conv12/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
group: 512
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv12/dw"
|
||
|
top: "conv12/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv12/dw"
|
||
|
top: "conv12/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv12/dw"
|
||
|
top: "conv12/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv12/dw"
|
||
|
top: "conv12"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 1024
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv12"
|
||
|
top: "conv12"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv12"
|
||
|
top: "conv12"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv12/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv12"
|
||
|
top: "conv12"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13/dw"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv12"
|
||
|
top: "conv13/dw"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 1024
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
group: 1024
|
||
|
engine: CAFFE
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13/dw/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv13/dw"
|
||
|
top: "conv13/dw"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13/dw/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv13/dw"
|
||
|
top: "conv13/dw"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13/dw/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv13/dw"
|
||
|
top: "conv13/dw"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv13/dw"
|
||
|
top: "conv13"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 1024
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv13"
|
||
|
top: "conv13"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv13"
|
||
|
top: "conv13"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv13"
|
||
|
top: "conv13"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_1"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv13"
|
||
|
top: "conv14_1"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 256
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_1/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv14_1"
|
||
|
top: "conv14_1"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_1/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv14_1"
|
||
|
top: "conv14_1"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_1/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv14_1"
|
||
|
top: "conv14_1"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv14_1"
|
||
|
top: "conv14_2"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 512
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv14_2"
|
||
|
top: "conv14_2"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv14_2"
|
||
|
top: "conv14_2"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv14_2"
|
||
|
top: "conv14_2"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_1"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv14_2"
|
||
|
top: "conv15_1"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 128
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_1/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv15_1"
|
||
|
top: "conv15_1"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_1/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv15_1"
|
||
|
top: "conv15_1"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_1/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv15_1"
|
||
|
top: "conv15_1"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv15_1"
|
||
|
top: "conv15_2"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 256
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv15_2"
|
||
|
top: "conv15_2"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv15_2"
|
||
|
top: "conv15_2"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv15_2"
|
||
|
top: "conv15_2"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_1"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv15_2"
|
||
|
top: "conv16_1"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 128
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_1/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv16_1"
|
||
|
top: "conv16_1"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_1/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv16_1"
|
||
|
top: "conv16_1"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_1/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv16_1"
|
||
|
top: "conv16_1"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv16_1"
|
||
|
top: "conv16_2"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 256
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv16_2"
|
||
|
top: "conv16_2"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv16_2"
|
||
|
top: "conv16_2"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv16_2"
|
||
|
top: "conv16_2"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_1"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv16_2"
|
||
|
top: "conv17_1"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 64
|
||
|
bias_term: false
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_1/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv17_1"
|
||
|
top: "conv17_1"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_1/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv17_1"
|
||
|
top: "conv17_1"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_1/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv17_1"
|
||
|
top: "conv17_1"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv17_1"
|
||
|
top: "conv17_2"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 128
|
||
|
bias_term: false
|
||
|
pad: 1
|
||
|
kernel_size: 3
|
||
|
stride: 2
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2/bn"
|
||
|
type: "BatchNorm"
|
||
|
bottom: "conv17_2"
|
||
|
top: "conv17_2"
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0
|
||
|
decay_mult: 0
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2/scale"
|
||
|
type: "Scale"
|
||
|
bottom: "conv17_2"
|
||
|
top: "conv17_2"
|
||
|
param {
|
||
|
lr_mult: 0.1
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 0.2
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
scale_param {
|
||
|
filler {
|
||
|
value: 1
|
||
|
}
|
||
|
bias_term: true
|
||
|
bias_filler {
|
||
|
value: 0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2/relu"
|
||
|
type: "ReLU"
|
||
|
bottom: "conv17_2"
|
||
|
top: "conv17_2"
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11_mbox_loc"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv11"
|
||
|
top: "conv11_mbox_loc"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 12
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11_mbox_loc_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv11_mbox_loc"
|
||
|
top: "conv11_mbox_loc_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11_mbox_loc_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv11_mbox_loc_perm"
|
||
|
top: "conv11_mbox_loc_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11_mbox_conf"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv11"
|
||
|
top: "conv11_mbox_conf"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 63
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11_mbox_conf_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv11_mbox_conf"
|
||
|
top: "conv11_mbox_conf_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11_mbox_conf_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv11_mbox_conf_perm"
|
||
|
top: "conv11_mbox_conf_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv11_mbox_priorbox"
|
||
|
type: "PriorBox"
|
||
|
bottom: "conv11"
|
||
|
bottom: "data"
|
||
|
top: "conv11_mbox_priorbox"
|
||
|
prior_box_param {
|
||
|
min_size: 60.0
|
||
|
aspect_ratio: 2.0
|
||
|
flip: true
|
||
|
clip: false
|
||
|
variance: 0.1
|
||
|
variance: 0.1
|
||
|
variance: 0.2
|
||
|
variance: 0.2
|
||
|
offset: 0.5
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13_mbox_loc"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv13"
|
||
|
top: "conv13_mbox_loc"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 24
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13_mbox_loc_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv13_mbox_loc"
|
||
|
top: "conv13_mbox_loc_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13_mbox_loc_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv13_mbox_loc_perm"
|
||
|
top: "conv13_mbox_loc_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13_mbox_conf"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv13"
|
||
|
top: "conv13_mbox_conf"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 126
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13_mbox_conf_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv13_mbox_conf"
|
||
|
top: "conv13_mbox_conf_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13_mbox_conf_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv13_mbox_conf_perm"
|
||
|
top: "conv13_mbox_conf_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv13_mbox_priorbox"
|
||
|
type: "PriorBox"
|
||
|
bottom: "conv13"
|
||
|
bottom: "data"
|
||
|
top: "conv13_mbox_priorbox"
|
||
|
prior_box_param {
|
||
|
min_size: 105.0
|
||
|
max_size: 150.0
|
||
|
aspect_ratio: 2.0
|
||
|
aspect_ratio: 3.0
|
||
|
flip: true
|
||
|
clip: false
|
||
|
variance: 0.1
|
||
|
variance: 0.1
|
||
|
variance: 0.2
|
||
|
variance: 0.2
|
||
|
offset: 0.5
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2_mbox_loc"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv14_2"
|
||
|
top: "conv14_2_mbox_loc"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 24
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2_mbox_loc_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv14_2_mbox_loc"
|
||
|
top: "conv14_2_mbox_loc_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2_mbox_loc_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv14_2_mbox_loc_perm"
|
||
|
top: "conv14_2_mbox_loc_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2_mbox_conf"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv14_2"
|
||
|
top: "conv14_2_mbox_conf"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 126
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2_mbox_conf_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv14_2_mbox_conf"
|
||
|
top: "conv14_2_mbox_conf_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2_mbox_conf_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv14_2_mbox_conf_perm"
|
||
|
top: "conv14_2_mbox_conf_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv14_2_mbox_priorbox"
|
||
|
type: "PriorBox"
|
||
|
bottom: "conv14_2"
|
||
|
bottom: "data"
|
||
|
top: "conv14_2_mbox_priorbox"
|
||
|
prior_box_param {
|
||
|
min_size: 150.0
|
||
|
max_size: 195.0
|
||
|
aspect_ratio: 2.0
|
||
|
aspect_ratio: 3.0
|
||
|
flip: true
|
||
|
clip: false
|
||
|
variance: 0.1
|
||
|
variance: 0.1
|
||
|
variance: 0.2
|
||
|
variance: 0.2
|
||
|
offset: 0.5
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2_mbox_loc"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv15_2"
|
||
|
top: "conv15_2_mbox_loc"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 24
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2_mbox_loc_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv15_2_mbox_loc"
|
||
|
top: "conv15_2_mbox_loc_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2_mbox_loc_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv15_2_mbox_loc_perm"
|
||
|
top: "conv15_2_mbox_loc_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2_mbox_conf"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv15_2"
|
||
|
top: "conv15_2_mbox_conf"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 126
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2_mbox_conf_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv15_2_mbox_conf"
|
||
|
top: "conv15_2_mbox_conf_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2_mbox_conf_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv15_2_mbox_conf_perm"
|
||
|
top: "conv15_2_mbox_conf_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv15_2_mbox_priorbox"
|
||
|
type: "PriorBox"
|
||
|
bottom: "conv15_2"
|
||
|
bottom: "data"
|
||
|
top: "conv15_2_mbox_priorbox"
|
||
|
prior_box_param {
|
||
|
min_size: 195.0
|
||
|
max_size: 240.0
|
||
|
aspect_ratio: 2.0
|
||
|
aspect_ratio: 3.0
|
||
|
flip: true
|
||
|
clip: false
|
||
|
variance: 0.1
|
||
|
variance: 0.1
|
||
|
variance: 0.2
|
||
|
variance: 0.2
|
||
|
offset: 0.5
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2_mbox_loc"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv16_2"
|
||
|
top: "conv16_2_mbox_loc"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 24
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2_mbox_loc_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv16_2_mbox_loc"
|
||
|
top: "conv16_2_mbox_loc_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2_mbox_loc_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv16_2_mbox_loc_perm"
|
||
|
top: "conv16_2_mbox_loc_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2_mbox_conf"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv16_2"
|
||
|
top: "conv16_2_mbox_conf"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 126
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2_mbox_conf_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv16_2_mbox_conf"
|
||
|
top: "conv16_2_mbox_conf_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2_mbox_conf_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv16_2_mbox_conf_perm"
|
||
|
top: "conv16_2_mbox_conf_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv16_2_mbox_priorbox"
|
||
|
type: "PriorBox"
|
||
|
bottom: "conv16_2"
|
||
|
bottom: "data"
|
||
|
top: "conv16_2_mbox_priorbox"
|
||
|
prior_box_param {
|
||
|
min_size: 240.0
|
||
|
max_size: 285.0
|
||
|
aspect_ratio: 2.0
|
||
|
aspect_ratio: 3.0
|
||
|
flip: true
|
||
|
clip: false
|
||
|
variance: 0.1
|
||
|
variance: 0.1
|
||
|
variance: 0.2
|
||
|
variance: 0.2
|
||
|
offset: 0.5
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2_mbox_loc"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv17_2"
|
||
|
top: "conv17_2_mbox_loc"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 24
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2_mbox_loc_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv17_2_mbox_loc"
|
||
|
top: "conv17_2_mbox_loc_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2_mbox_loc_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv17_2_mbox_loc_perm"
|
||
|
top: "conv17_2_mbox_loc_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2_mbox_conf"
|
||
|
type: "Convolution"
|
||
|
bottom: "conv17_2"
|
||
|
top: "conv17_2_mbox_conf"
|
||
|
param {
|
||
|
lr_mult: 1.0
|
||
|
decay_mult: 1.0
|
||
|
}
|
||
|
param {
|
||
|
lr_mult: 2.0
|
||
|
decay_mult: 0.0
|
||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 126
|
||
|
kernel_size: 1
|
||
|
weight_filler {
|
||
|
type: "msra"
|
||
|
}
|
||
|
bias_filler {
|
||
|
type: "constant"
|
||
|
value: 0.0
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2_mbox_conf_perm"
|
||
|
type: "Permute"
|
||
|
bottom: "conv17_2_mbox_conf"
|
||
|
top: "conv17_2_mbox_conf_perm"
|
||
|
permute_param {
|
||
|
order: 0
|
||
|
order: 2
|
||
|
order: 3
|
||
|
order: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2_mbox_conf_flat"
|
||
|
type: "Flatten"
|
||
|
bottom: "conv17_2_mbox_conf_perm"
|
||
|
top: "conv17_2_mbox_conf_flat"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "conv17_2_mbox_priorbox"
|
||
|
type: "PriorBox"
|
||
|
bottom: "conv17_2"
|
||
|
bottom: "data"
|
||
|
top: "conv17_2_mbox_priorbox"
|
||
|
prior_box_param {
|
||
|
min_size: 285.0
|
||
|
max_size: 300.0
|
||
|
aspect_ratio: 2.0
|
||
|
aspect_ratio: 3.0
|
||
|
flip: true
|
||
|
clip: false
|
||
|
variance: 0.1
|
||
|
variance: 0.1
|
||
|
variance: 0.2
|
||
|
variance: 0.2
|
||
|
offset: 0.5
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "mbox_loc"
|
||
|
type: "Concat"
|
||
|
bottom: "conv11_mbox_loc_flat"
|
||
|
bottom: "conv13_mbox_loc_flat"
|
||
|
bottom: "conv14_2_mbox_loc_flat"
|
||
|
bottom: "conv15_2_mbox_loc_flat"
|
||
|
bottom: "conv16_2_mbox_loc_flat"
|
||
|
bottom: "conv17_2_mbox_loc_flat"
|
||
|
top: "mbox_loc"
|
||
|
concat_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "mbox_conf"
|
||
|
type: "Concat"
|
||
|
bottom: "conv11_mbox_conf_flat"
|
||
|
bottom: "conv13_mbox_conf_flat"
|
||
|
bottom: "conv14_2_mbox_conf_flat"
|
||
|
bottom: "conv15_2_mbox_conf_flat"
|
||
|
bottom: "conv16_2_mbox_conf_flat"
|
||
|
bottom: "conv17_2_mbox_conf_flat"
|
||
|
top: "mbox_conf"
|
||
|
concat_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "mbox_priorbox"
|
||
|
type: "Concat"
|
||
|
bottom: "conv11_mbox_priorbox"
|
||
|
bottom: "conv13_mbox_priorbox"
|
||
|
bottom: "conv14_2_mbox_priorbox"
|
||
|
bottom: "conv15_2_mbox_priorbox"
|
||
|
bottom: "conv16_2_mbox_priorbox"
|
||
|
bottom: "conv17_2_mbox_priorbox"
|
||
|
top: "mbox_priorbox"
|
||
|
concat_param {
|
||
|
axis: 2
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "mbox_conf_reshape"
|
||
|
type: "Reshape"
|
||
|
bottom: "mbox_conf"
|
||
|
top: "mbox_conf_reshape"
|
||
|
reshape_param {
|
||
|
shape {
|
||
|
dim: 0
|
||
|
dim: -1
|
||
|
dim: 21
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "mbox_conf_softmax"
|
||
|
type: "Softmax"
|
||
|
bottom: "mbox_conf_reshape"
|
||
|
top: "mbox_conf_softmax"
|
||
|
softmax_param {
|
||
|
axis: 2
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "mbox_conf_flatten"
|
||
|
type: "Flatten"
|
||
|
bottom: "mbox_conf_softmax"
|
||
|
top: "mbox_conf_flatten"
|
||
|
flatten_param {
|
||
|
axis: 1
|
||
|
}
|
||
|
}
|
||
|
layer {
|
||
|
name: "detection_out"
|
||
|
type: "DetectionOutput"
|
||
|
bottom: "mbox_loc"
|
||
|
bottom: "mbox_conf_flatten"
|
||
|
bottom: "mbox_priorbox"
|
||
|
top: "detection_out"
|
||
|
include {
|
||
|
phase: TEST
|
||
|
}
|
||
|
detection_output_param {
|
||
|
num_classes: 21
|
||
|
share_location: true
|
||
|
background_label_id: 0
|
||
|
nms_param {
|
||
|
nms_threshold: 0.45
|
||
|
top_k: 100
|
||
|
}
|
||
|
code_type: CENTER_SIZE
|
||
|
keep_top_k: 100
|
||
|
confidence_threshold: 0.25
|
||
|
}
|
||
|
}
|