VGG_VOC0712_SSD_300x300_deploy

name: “VGG_VOC0712_SSD_300x300_deploy”
input: “data”
input_shape {
dim: 1
dim: 3
dim: 300
dim: 300
}
layer {
name: “conv1_1”
type: “Convolution”
bottom: “data”
top: “conv1_1”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu1_1”
type: “ReLU”
bottom: “conv1_1”
top: “conv1_1”
}
layer {
name: “conv1_2”
type: “Convolution”
bottom: “conv1_1”
top: “conv1_2”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu1_2”
type: “ReLU”
bottom: “conv1_2”
top: “conv1_2”
}
layer {
name: “pool1”
type: “Pooling”
bottom: “conv1_2”
top: “pool1”
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: “conv2_1”
type: “Convolution”
bottom: “pool1”
top: “conv2_1”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu2_1”
type: “ReLU”
bottom: “conv2_1”
top: “conv2_1”
}
layer {
name: “conv2_2”
type: “Convolution”
bottom: “conv2_1”
top: “conv2_2”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu2_2”
type: “ReLU”
bottom: “conv2_2”
top: “conv2_2”
}
layer {
name: “pool2”
type: “Pooling”
bottom: “conv2_2”
top: “pool2”
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: “conv3_1”
type: “Convolution”
bottom: “pool2”
top: “conv3_1”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu3_1”
type: “ReLU”
bottom: “conv3_1”
top: “conv3_1”
}
layer {
name: “conv3_2”
type: “Convolution”
bottom: “conv3_1”
top: “conv3_2”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu3_2”
type: “ReLU”
bottom: “conv3_2”
top: “conv3_2”
}
layer {
name: “conv3_3”
type: “Convolution”
bottom: “conv3_2”
top: “conv3_3”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu3_3”
type: “ReLU”
bottom: “conv3_3”
top: “conv3_3”
}
layer {
name: “pool3”
type: “Pooling”
bottom: “conv3_3”
top: “pool3”
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: “conv4_1”
type: “Convolution”
bottom: “pool3”
top: “conv4_1”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu4_1”
type: “ReLU”
bottom: “conv4_1”
top: “conv4_1”
}
layer {
name: “conv4_2”
type: “Convolution”
bottom: “conv4_1”
top: “conv4_2”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: “xavier”
}
bias_filler {
type: “constant”
value: 0.0
}
}
}
layer {
name: “relu4_2”
type: “ReLU”
bottom: “conv4_2”
top: “conv4_2”
}
layer {
name: “conv4_3”
type: “Convolution”
bottom: “conv4_2”
top: “conv4_3”
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
weight_filler {
type: “xavie