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1789 lines (1785 loc) · 27.4 KB
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input: "data"
input_shape {
dim: 1
dim: 3
dim: 300
dim: 300
}
layer {
name: "data_bn"
type: "BatchNorm"
bottom: "data"
top: "data_bn"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "data_scale"
type: "Scale"
bottom: "data_bn"
top: "data_bn"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv1_h"
type: "Convolution"
bottom: "data_bn"
top: "conv1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
convolution_param {
num_output: 32
pad: 3
kernel_size: 7
stride: 2
weight_filler {
type: "msra"
variance_norm: FAN_OUT
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv1_bn_h"
type: "BatchNorm"
bottom: "conv1_h"
top: "conv1_h"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "conv1_scale_h"
type: "Scale"
bottom: "conv1_h"
top: "conv1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "conv1_relu"
type: "ReLU"
bottom: "conv1_h"
top: "conv1_h"
}
layer {
name: "conv1_pool"
type: "Pooling"
bottom: "conv1_h"
top: "conv1_pool"
pooling_param {
kernel_size: 3
stride: 2
}
}
layer {
name: "layer_64_1_conv1_h"
type: "Convolution"
bottom: "conv1_pool"
top: "layer_64_1_conv1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_64_1_bn2_h"
type: "BatchNorm"
bottom: "layer_64_1_conv1_h"
top: "layer_64_1_conv1_h"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "layer_64_1_scale2_h"
type: "Scale"
bottom: "layer_64_1_conv1_h"
top: "layer_64_1_conv1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "layer_64_1_relu2"
type: "ReLU"
bottom: "layer_64_1_conv1_h"
top: "layer_64_1_conv1_h"
}
layer {
name: "layer_64_1_conv2_h"
type: "Convolution"
bottom: "layer_64_1_conv1_h"
top: "layer_64_1_conv2_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_64_1_sum"
type: "Eltwise"
bottom: "layer_64_1_conv2_h"
bottom: "conv1_pool"
top: "layer_64_1_sum"
}
layer {
name: "layer_128_1_bn1_h"
type: "BatchNorm"
bottom: "layer_64_1_sum"
top: "layer_128_1_bn1_h"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "layer_128_1_scale1_h"
type: "Scale"
bottom: "layer_128_1_bn1_h"
top: "layer_128_1_bn1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "layer_128_1_relu1"
type: "ReLU"
bottom: "layer_128_1_bn1_h"
top: "layer_128_1_bn1_h"
}
layer {
name: "layer_128_1_conv1_h"
type: "Convolution"
bottom: "layer_128_1_bn1_h"
top: "layer_128_1_conv1_h"
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"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_128_1_bn2"
type: "BatchNorm"
bottom: "layer_128_1_conv1_h"
top: "layer_128_1_conv1_h"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "layer_128_1_scale2"
type: "Scale"
bottom: "layer_128_1_conv1_h"
top: "layer_128_1_conv1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "layer_128_1_relu2"
type: "ReLU"
bottom: "layer_128_1_conv1_h"
top: "layer_128_1_conv1_h"
}
layer {
name: "layer_128_1_conv2"
type: "Convolution"
bottom: "layer_128_1_conv1_h"
top: "layer_128_1_conv2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_128_1_conv_expand_h"
type: "Convolution"
bottom: "layer_128_1_bn1_h"
top: "layer_128_1_conv_expand_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_128_1_sum"
type: "Eltwise"
bottom: "layer_128_1_conv2"
bottom: "layer_128_1_conv_expand_h"
top: "layer_128_1_sum"
}
layer {
name: "layer_256_1_bn1"
type: "BatchNorm"
bottom: "layer_128_1_sum"
top: "layer_256_1_bn1"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "layer_256_1_scale1"
type: "Scale"
bottom: "layer_256_1_bn1"
top: "layer_256_1_bn1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "layer_256_1_relu1"
type: "ReLU"
bottom: "layer_256_1_bn1"
top: "layer_256_1_bn1"
}
layer {
name: "layer_256_1_conv1"
type: "Convolution"
bottom: "layer_256_1_bn1"
top: "layer_256_1_conv1"
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"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_256_1_bn2"
type: "BatchNorm"
bottom: "layer_256_1_conv1"
top: "layer_256_1_conv1"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "layer_256_1_scale2"
type: "Scale"
bottom: "layer_256_1_conv1"
top: "layer_256_1_conv1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "layer_256_1_relu2"
type: "ReLU"
bottom: "layer_256_1_conv1"
top: "layer_256_1_conv1"
}
layer {
name: "layer_256_1_conv2"
type: "Convolution"
bottom: "layer_256_1_conv1"
top: "layer_256_1_conv2"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_256_1_conv_expand"
type: "Convolution"
bottom: "layer_256_1_bn1"
top: "layer_256_1_conv_expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_256_1_sum"
type: "Eltwise"
bottom: "layer_256_1_conv2"
bottom: "layer_256_1_conv_expand"
top: "layer_256_1_sum"
}
layer {
name: "layer_512_1_bn1"
type: "BatchNorm"
bottom: "layer_256_1_sum"
top: "layer_512_1_bn1"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "layer_512_1_scale1"
type: "Scale"
bottom: "layer_512_1_bn1"
top: "layer_512_1_bn1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "layer_512_1_relu1"
type: "ReLU"
bottom: "layer_512_1_bn1"
top: "layer_512_1_bn1"
}
layer {
name: "layer_512_1_conv1_h"
type: "Convolution"
bottom: "layer_512_1_bn1"
top: "layer_512_1_conv1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 1 # 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_512_1_bn2_h"
type: "BatchNorm"
bottom: "layer_512_1_conv1_h"
top: "layer_512_1_conv1_h"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "layer_512_1_scale2_h"
type: "Scale"
bottom: "layer_512_1_conv1_h"
top: "layer_512_1_conv1_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "layer_512_1_relu2"
type: "ReLU"
bottom: "layer_512_1_conv1_h"
top: "layer_512_1_conv1_h"
}
layer {
name: "layer_512_1_conv2_h"
type: "Convolution"
bottom: "layer_512_1_conv1_h"
top: "layer_512_1_conv2_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 2 # 1
kernel_size: 3
stride: 1
dilation: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_512_1_conv_expand_h"
type: "Convolution"
bottom: "layer_512_1_bn1"
top: "layer_512_1_conv_expand_h"
param {
lr_mult: 1.0
decay_mult: 1.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 1
stride: 1 # 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "layer_512_1_sum"
type: "Eltwise"
bottom: "layer_512_1_conv2_h"
bottom: "layer_512_1_conv_expand_h"
top: "layer_512_1_sum"
}
layer {
name: "last_bn_h"
type: "BatchNorm"
bottom: "layer_512_1_sum"
top: "layer_512_1_sum"
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
param {
lr_mult: 0.0
}
}
layer {
name: "last_scale_h"
type: "Scale"
bottom: "layer_512_1_sum"
top: "layer_512_1_sum"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 1.0
}
scale_param {
bias_term: true
}
}
layer {
name: "last_relu"
type: "ReLU"
bottom: "layer_512_1_sum"
top: "fc7"
}
layer {
name: "conv6_1_h"
type: "Convolution"
bottom: "fc7"
top: "conv6_1_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv6_1_relu"
type: "ReLU"
bottom: "conv6_1_h"
top: "conv6_1_h"
}
layer {
name: "conv6_2_h"
type: "Convolution"
bottom: "conv6_1_h"
top: "conv6_2_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv6_2_relu"
type: "ReLU"
bottom: "conv6_2_h"
top: "conv6_2_h"
}
layer {
name: "conv7_1_h"
type: "Convolution"
bottom: "conv6_2_h"
top: "conv7_1_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv7_1_relu"
type: "ReLU"
bottom: "conv7_1_h"
top: "conv7_1_h"
}
layer {
name: "conv7_2_h"
type: "Convolution"
bottom: "conv7_1_h"
top: "conv7_2_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv7_2_relu"
type: "ReLU"
bottom: "conv7_2_h"
top: "conv7_2_h"
}
layer {
name: "conv8_1_h"
type: "Convolution"
bottom: "conv7_2_h"
top: "conv8_1_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv8_1_relu"
type: "ReLU"
bottom: "conv8_1_h"
top: "conv8_1_h"
}
layer {
name: "conv8_2_h"
type: "Convolution"
bottom: "conv8_1_h"
top: "conv8_2_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv8_2_relu"
type: "ReLU"
bottom: "conv8_2_h"
top: "conv8_2_h"
}
layer {
name: "conv9_1_h"
type: "Convolution"
bottom: "conv8_2_h"
top: "conv9_1_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 0
kernel_size: 1
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv9_1_relu"
type: "ReLU"
bottom: "conv9_1_h"
top: "conv9_1_h"
}
layer {
name: "conv9_2_h"
type: "Convolution"
bottom: "conv9_1_h"
top: "conv9_2_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
stride: 1
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv9_2_relu"
type: "ReLU"
bottom: "conv9_2_h"
top: "conv9_2_h"
}
layer {
name: "conv4_3_norm"
type: "Normalize"
bottom: "layer_256_1_bn1"
top: "conv4_3_norm"
norm_param {
across_spatial: false
scale_filler {
type: "constant"
value: 20
}
channel_shared: false
}
}
layer {
name: "conv4_3_norm_mbox_loc"
type: "Convolution"
bottom: "conv4_3_norm"
top: "conv4_3_norm_mbox_loc"
param {
lr_mult: 1
decay_mult: 1