A real-time lightweight object detector (RLOD) network
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A real-time lightweight object detector (RLOD) for the mobile embedded platform is proposed for underwater manipulation. Do the following to see the detailed network.
1、Copy the following codes and paste it into http://ethereon.github.io/netscope/#/editor. （Google Chrome should be used.）
2、 Push Shift+Enter to update the visualization.
name: "MobDenseNet-DSSD"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 416
dim: 416
}
layer {
name: "conv1_0"
type: "Convolution"
bottom: "data"
top: "conv1_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv1_0/relu"
type: "ReLU"
bottom: "conv1_0"
top: "conv1_0"
}
layer {
name: "conv1_1/expand"
type: "Convolution"
bottom: "conv1_0"
top: "conv1_1/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv1_1/expand/relu"
type: "ReLU"
bottom: "conv1_1/expand"
top: "conv1_1/expand"
}
layer {
name: "conv1_1/depthwise"
type: "DepthwiseConvolution"
bottom: "conv1_1/expand"
top: "conv1_1/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
pad: 1
kernel_size: 3
group: 32
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv1_1/depthwise/relu"
type: "ReLU"
bottom: "conv1_1/depthwise"
top: "conv1_1/depthwise"
}
layer {
name: "conv1_1/project"
type: "Convolution"
bottom: "conv1_1/depthwise"
top: "conv1_1/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv1_1/sum"
type: "Eltwise"
bottom: "conv1_0"
bottom: "conv1_1/project"
top: "conv1_1"
}
layer {
name: "pooling2_0"
type: "Pooling"
bottom: "conv1_1"
top: "pooling2_0"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling2_0/scale_relu"
type: "Scale"
bottom: "pooling2_0"
top: "pooling2_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling2_0/relu"
type: "ReLU"
bottom: "pooling2_0/relu"
top: "pooling2_0/relu"
}
layer {
name: "conv2_0/expand"
type: "Convolution"
bottom: "pooling2_0/relu"
top: "conv2_0/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv2_0/expand/relu"
type: "ReLU"
bottom: "conv2_0/expand"
top: "conv2_0/expand"
}
layer {
name: "conv2_0/depthwise"
type: "DepthwiseConvolution"
bottom: "conv2_0/expand"
top: "conv2_0/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv2_0/depthwise/relu"
type: "ReLU"
bottom: "conv2_0/depthwise"
top: "conv2_0/depthwise"
}
layer {
name: "conv2_0/project"
type: "Convolution"
bottom: "conv2_0/depthwise"
top: "conv2_0/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat2_0"
type: "Concat"
bottom: "conv2_0/project"
bottom: "pooling2_0"
top: "concat2_0"
concat_param {
axis: 1
}
}
layer {
name: "concat2_0/scale_relu"
type: "Scale"
bottom: "concat2_0"
top: "concat2_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat2_0/relu"
type: "ReLU"
bottom: "concat2_0/relu"
top: "concat2_0/relu"
}
layer {
name: "conv2_1/expand"
type: "Convolution"
bottom: "concat2_0/relu"
top: "conv2_1/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv2_1/expand/relu"
type: "ReLU"
bottom: "conv2_1/expand"
top: "conv2_1/expand"
}
layer {
name: "conv2_1/depthwise"
type: "DepthwiseConvolution"
bottom: "conv2_1/expand"
top: "conv2_1/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv2_1/depthwise/relu"
type: "ReLU"
bottom: "conv2_1/depthwise"
top: "conv2_1/depthwise"
}
layer {
name: "conv2_1/project"
type: "Convolution"
bottom: "conv2_1/depthwise"
top: "conv2_1/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat2_1"
type: "Concat"
bottom: "conv2_1/project"
bottom: "concat2_0"
top: "concat2_1"
concat_param {
axis: 1
}
}
layer {
name: "concat2_1/scale_relu"
type: "Scale"
bottom: "concat2_1"
top: "concat2_1/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat2_1/relu"
type: "ReLU"
bottom: "concat2_1/relu"
top: "concat2_1/relu"
}
layer {
name: "conv2_2/expand"
type: "Convolution"
bottom: "concat2_1/relu"
top: "conv2_2/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv2_2/expand/relu"
type: "ReLU"
bottom: "conv2_2/expand"
top: "conv2_2/expand"
}
layer {
name: "conv2_2/depthwise"
type: "DepthwiseConvolution"
bottom: "conv2_2/expand"
top: "conv2_2/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv2_2/depthwise/relu"
type: "ReLU"
bottom: "conv2_2/depthwise"
top: "conv2_2/depthwise"
}
layer {
name: "conv2_2/project"
type: "Convolution"
bottom: "conv2_2/depthwise"
top: "conv2_2/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat2_2"
type: "Concat"
bottom: "conv2_2/project"
bottom: "concat2_1"
top: "concat2_2"
concat_param {
axis: 1
}
}
layer {
name: "concat2_2/scale_relu"
type: "Scale"
bottom: "concat2_2"
top: "concat2_2/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat2_2/relu"
type: "ReLU"
bottom: "concat2_2/relu"
top: "concat2_2/relu"
}
layer {
name: "transition2_0"
type: "Convolution"
bottom: "concat2_2/relu"
top: "transition2_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "pooling3_0"
type: "Pooling"
bottom: "transition2_0"
top: "pooling3_0"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling3_0/scale_relu"
type: "Scale"
bottom: "pooling3_0"
top: "pooling3_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling3_0/relu"
type: "ReLU"
bottom: "pooling3_0/relu"
top: "pooling3_0/relu"
}
layer {
name: "conv3_0/expand"
type: "Convolution"
bottom: "pooling3_0/relu"
top: "conv3_0/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_0/expand/relu"
type: "ReLU"
bottom: "conv3_0/expand"
top: "conv3_0/expand"
}
layer {
name: "conv3_0/depthwise"
type: "DepthwiseConvolution"
bottom: "conv3_0/expand"
top: "conv3_0/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_0/depthwise/relu"
type: "ReLU"
bottom: "conv3_0/depthwise"
top: "conv3_0/depthwise"
}
layer {
name: "conv3_0/project"
type: "Convolution"
bottom: "conv3_0/depthwise"
top: "conv3_0/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat3_0"
type: "Concat"
bottom: "conv3_0/project"
bottom: "pooling3_0"
top: "concat3_0"
concat_param {
axis: 1
}
}
layer {
name: "concat3_0/scale_relu"
type: "Scale"
bottom: "concat3_0"
top: "concat3_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat3_0/relu"
type: "ReLU"
bottom: "concat3_0/relu"
top: "concat3_0/relu"
}
layer {
name: "conv3_1/expand"
type: "Convolution"
bottom: "concat3_0/relu"
top: "conv3_1/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_1/expand/relu"
type: "ReLU"
bottom: "conv3_1/expand"
top: "conv3_1/expand"
}
layer {
name: "conv3_1/depthwise"
type: "DepthwiseConvolution"
bottom: "conv3_1/expand"
top: "conv3_1/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_1/depthwise/relu"
type: "ReLU"
bottom: "conv3_1/depthwise"
top: "conv3_1/depthwise"
}
layer {
name: "conv3_1/project"
type: "Convolution"
bottom: "conv3_1/depthwise"
top: "conv3_1/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat3_1"
type: "Concat"
bottom: "conv3_1/project"
bottom: "concat3_0"
top: "concat3_1"
concat_param {
axis: 1
}
}
layer {
name: "concat3_1/scale_relu"
type: "Scale"
bottom: "concat3_1"
top: "concat3_1/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat3_1/relu"
type: "ReLU"
bottom: "concat3_1/relu"
top: "concat3_1/relu"
}
layer {
name: "conv3_2/expand"
type: "Convolution"
bottom: "concat3_1/relu"
top: "conv3_2/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_2/expand/relu"
type: "ReLU"
bottom: "conv3_2/expand"
top: "conv3_2/expand"
}
layer {
name: "conv3_2/depthwise"
type: "DepthwiseConvolution"
bottom: "conv3_2/expand"
top: "conv3_2/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_2/depthwise/relu"
type: "ReLU"
bottom: "conv3_2/depthwise"
top: "conv3_2/depthwise"
}
layer {
name: "conv3_2/project"
type: "Convolution"
bottom: "conv3_2/depthwise"
top: "conv3_2/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat3_2"
type: "Concat"
bottom: "conv3_2/project"
bottom: "concat3_1"
top: "concat3_2"
concat_param {
axis: 1
}
}
layer {
name: "concat3_2/scale_relu"
type: "Scale"
bottom: "concat3_2"
top: "concat3_2/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat3_2/relu"
type: "ReLU"
bottom: "concat3_2/relu"
top: "concat3_2/relu"
}
layer {
name: "conv3_3/expand"
type: "Convolution"
bottom: "concat3_2/relu"
top: "conv3_3/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_3/expand/relu"
type: "ReLU"
bottom: "conv3_3/expand"
top: "conv3_3/expand"
}
layer {
name: "conv3_3/depthwise"
type: "DepthwiseConvolution"
bottom: "conv3_3/expand"
top: "conv3_3/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_3/depthwise/relu"
type: "ReLU"
bottom: "conv3_3/depthwise"
top: "conv3_3/depthwise"
}
layer {
name: "conv3_3/project"
type: "Convolution"
bottom: "conv3_3/depthwise"
top: "conv3_3/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat3_3"
type: "Concat"
bottom: "conv3_3/project"
bottom: "concat3_2"
top: "concat3_3"
concat_param {
axis: 1
}
}
layer {
name: "concat3_3/scale_relu"
type: "Scale"
bottom: "concat3_3"
top: "concat3_3/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat3_3/relu"
type: "ReLU"
bottom: "concat3_3/relu"
top: "concat3_3/relu"
}
layer {
name: "conv3_4/expand"
type: "Convolution"
bottom: "concat3_3/relu"
top: "conv3_4/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_4/expand/relu"
type: "ReLU"
bottom: "conv3_4/expand"
top: "conv3_4/expand"
}
layer {
name: "conv3_4/depthwise"
type: "DepthwiseConvolution"
bottom: "conv3_4/expand"
top: "conv3_4/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_4/depthwise/relu"
type: "ReLU"
bottom: "conv3_4/depthwise"
top: "conv3_4/depthwise"
}
layer {
name: "conv3_4/project"
type: "Convolution"
bottom: "conv3_4/depthwise"
top: "conv3_4/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat3_4"
type: "Concat"
bottom: "conv3_4/project"
bottom: "concat3_3"
top: "concat3_4"
concat_param {
axis: 1
}
}
layer {
name: "concat3_4/scale_relu"
type: "Scale"
bottom: "concat3_4"
top: "concat3_4/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat3_4/relu"
type: "ReLU"
bottom: "concat3_4/relu"
top: "concat3_4/relu"
}
layer {
name: "conv3_5/expand"
type: "Convolution"
bottom: "concat3_4/relu"
top: "conv3_5/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_5/expand/relu"
type: "ReLU"
bottom: "conv3_5/expand"
top: "conv3_5/expand"
}
layer {
name: "conv3_5/depthwise"
type: "DepthwiseConvolution"
bottom: "conv3_5/expand"
top: "conv3_5/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv3_5/depthwise/relu"
type: "ReLU"
bottom: "conv3_5/depthwise"
top: "conv3_5/depthwise"
}
layer {
name: "conv3_5/project"
type: "Convolution"
bottom: "conv3_5/depthwise"
top: "conv3_5/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat3_5"
type: "Concat"
bottom: "conv3_5/project"
bottom: "concat3_4"
top: "concat3_5"
concat_param {
axis: 1
}
}
layer {
name: "concat3_5/scale_relu"
type: "Scale"
bottom: "concat3_5"
top: "concat3_5/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat3_5/relu"
type: "ReLU"
bottom: "concat3_5/relu"
top: "concat3_5/relu"
}
layer {
name: "first"
type: "Convolution"
bottom: "concat3_5/relu"
top: "first"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 320
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "pooling4_0"
type: "Pooling"
bottom: "first"
top: "pooling4_0"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling4_0/scale_relu"
type: "Scale"
bottom: "pooling4_0"
top: "pooling4_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling4_0/relu"
type: "ReLU"
bottom: "pooling4_0/relu"
top: "pooling4_0/relu"
}
layer {
name: "conv4_0/expand"
type: "Convolution"
bottom: "pooling4_0/relu"
top: "conv4_0/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_0/expand/relu"
type: "ReLU"
bottom: "conv4_0/expand"
top: "conv4_0/expand"
}
layer {
name: "conv4_0/depthwise"
type: "DepthwiseConvolution"
bottom: "conv4_0/expand"
top: "conv4_0/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_0/depthwise/relu"
type: "ReLU"
bottom: "conv4_0/depthwise"
top: "conv4_0/depthwise"
}
layer {
name: "conv4_0/project"
type: "Convolution"
bottom: "conv4_0/depthwise"
top: "conv4_0/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat4_0"
type: "Concat"
bottom: "conv4_0/project"
bottom: "pooling4_0"
top: "concat4_0"
concat_param {
axis: 1
}
}
layer {
name: "concat4_0/scale_relu"
type: "Scale"
bottom: "concat4_0"
top: "concat4_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat4_0/relu"
type: "ReLU"
bottom: "concat4_0/relu"
top: "concat4_0/relu"
}
layer {
name: "conv4_1/expand"
type: "Convolution"
bottom: "concat4_0/relu"
top: "conv4_1/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_1/expand/relu"
type: "ReLU"
bottom: "conv4_1/expand"
top: "conv4_1/expand"
}
layer {
name: "conv4_1/depthwise"
type: "DepthwiseConvolution"
bottom: "conv4_1/expand"
top: "conv4_1/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_1/depthwise/relu"
type: "ReLU"
bottom: "conv4_1/depthwise"
top: "conv4_1/depthwise"
}
layer {
name: "conv4_1/project"
type: "Convolution"
bottom: "conv4_1/depthwise"
top: "conv4_1/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat4_1"
type: "Concat"
bottom: "conv4_1/project"
bottom: "concat4_0"
top: "concat4_1"
concat_param {
axis: 1
}
}
layer {
name: "concat4_1/scale_relu"
type: "Scale"
bottom: "concat4_1"
top: "concat4_1/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat4_1/relu"
type: "ReLU"
bottom: "concat4_1/relu"
top: "concat4_1/relu"
}
layer {
name: "conv4_2/expand"
type: "Convolution"
bottom: "concat4_1/relu"
top: "conv4_2/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_2/expand/relu"
type: "ReLU"
bottom: "conv4_2/expand"
top: "conv4_2/expand"
}
layer {
name: "conv4_2/depthwise"
type: "DepthwiseConvolution"
bottom: "conv4_2/expand"
top: "conv4_2/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_2/depthwise/relu"
type: "ReLU"
bottom: "conv4_2/depthwise"
top: "conv4_2/depthwise"
}
layer {
name: "conv4_2/project"
type: "Convolution"
bottom: "conv4_2/depthwise"
top: "conv4_2/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat4_2"
type: "Concat"
bottom: "conv4_2/project"
bottom: "concat4_1"
top: "concat4_2"
concat_param {
axis: 1
}
}
layer {
name: "concat4_2/scale_relu"
type: "Scale"
bottom: "concat4_2"
top: "concat4_2/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat4_2/relu"
type: "ReLU"
bottom: "concat4_2/relu"
top: "concat4_2/relu"
}
layer {
name: "conv4_3/expand"
type: "Convolution"
bottom: "concat4_2/relu"
top: "conv4_3/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_3/expand/relu"
type: "ReLU"
bottom: "conv4_3/expand"
top: "conv4_3/expand"
}
layer {
name: "conv4_3/depthwise"
type: "DepthwiseConvolution"
bottom: "conv4_3/expand"
top: "conv4_3/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_3/depthwise/relu"
type: "ReLU"
bottom: "conv4_3/depthwise"
top: "conv4_3/depthwise"
}
layer {
name: "conv4_3/project"
type: "Convolution"
bottom: "conv4_3/depthwise"
top: "conv4_3/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat4_3"
type: "Concat"
bottom: "conv4_3/project"
bottom: "concat4_2"
top: "concat4_3"
concat_param {
axis: 1
}
}
layer {
name: "concat4_3/scale_relu"
type: "Scale"
bottom: "concat4_3"
top: "concat4_3/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat4_3/relu"
type: "ReLU"
bottom: "concat4_3/relu"
top: "concat4_3/relu"
}
layer {
name: "conv4_4/expand"
type: "Convolution"
bottom: "concat4_3/relu"
top: "conv4_4/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_4/expand/relu"
type: "ReLU"
bottom: "conv4_4/expand"
top: "conv4_4/expand"
}
layer {
name: "conv4_4/depthwise"
type: "DepthwiseConvolution"
bottom: "conv4_4/expand"
top: "conv4_4/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_4/depthwise/relu"
type: "ReLU"
bottom: "conv4_4/depthwise"
top: "conv4_4/depthwise"
}
layer {
name: "conv4_4/project"
type: "Convolution"
bottom: "conv4_4/depthwise"
top: "conv4_4/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat4_4"
type: "Concat"
bottom: "conv4_4/project"
bottom: "concat4_3"
top: "concat4_4"
concat_param {
axis: 1
}
}
layer {
name: "concat4_4/scale_relu"
type: "Scale"
bottom: "concat4_4"
top: "concat4_4/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat4_4/relu"
type: "ReLU"
bottom: "concat4_4/relu"
top: "concat4_4/relu"
}
layer {
name: "conv4_5/expand"
type: "Convolution"
bottom: "concat4_4/relu"
top: "conv4_5/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_5/expand/relu"
type: "ReLU"
bottom: "conv4_5/expand"
top: "conv4_5/expand"
}
layer {
name: "conv4_5/depthwise"
type: "DepthwiseConvolution"
bottom: "conv4_5/expand"
top: "conv4_5/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv4_5/depthwise/relu"
type: "ReLU"
bottom: "conv4_5/depthwise"
top: "conv4_5/depthwise"
}
layer {
name: "conv4_5/project"
type: "Convolution"
bottom: "conv4_5/depthwise"
top: "conv4_5/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat4_5"
type: "Concat"
bottom: "conv4_5/project"
bottom: "concat4_4"
top: "concat4_5"
concat_param {
axis: 1
}
}
layer {
name: "concat4_5/scale_relu"
type: "Scale"
bottom: "concat4_5"
top: "concat4_5/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat4_5/relu"
type: "ReLU"
bottom: "concat4_5/relu"
top: "concat4_5/relu"
}
layer {
name: "transition4_0"
type: "Convolution"
bottom: "concat4_5/relu"
top: "transition4_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "pooling4_1"
type: "Pooling"
bottom: "first"
top: "pooling4_1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling4_1/scale_relu"
type: "Scale"
bottom: "pooling4_1"
top: "pooling4_1/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling4_1/relu"
type: "ReLU"
bottom: "pooling4_1/relu"
top: "pooling4_1/relu"
}
layer {
name: "transition4_1"
type: "Convolution"
bottom: "pooling4_1/relu"
top: "transition4_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "second"
type: "Concat"
bottom: "transition4_1"
bottom: "transition4_0"
top: "second"
concat_param {
axis: 1
}
}
layer {
name: "second/scale_relu"
type: "Scale"
bottom: "second"
top: "second/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "second/relu"
type: "ReLU"
bottom: "second/relu"
top: "second/relu"
}
layer {
name: "pooling5_0"
type: "Pooling"
bottom: "second/relu"
top: "pooling5_0"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling5_0/scale_relu"
type: "Scale"
bottom: "pooling5_0"
top: "pooling5_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling5_0/relu"
type: "ReLU"
bottom: "pooling5_0/relu"
top: "pooling5_0/relu"
}
layer {
name: "conv5_0/expand"
type: "Convolution"
bottom: "pooling5_0/relu"
top: "conv5_0/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_0/expand/relu"
type: "ReLU"
bottom: "conv5_0/expand"
top: "conv5_0/expand"
}
layer {
name: "conv5_0/depthwise"
type: "DepthwiseConvolution"
bottom: "conv5_0/expand"
top: "conv5_0/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_0/depthwise/relu"
type: "ReLU"
bottom: "conv5_0/depthwise"
top: "conv5_0/depthwise"
}
layer {
name: "conv5_0/project"
type: "Convolution"
bottom: "conv5_0/depthwise"
top: "conv5_0/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat5_0"
type: "Concat"
bottom: "conv5_0/project"
bottom: "pooling5_0"
top: "concat5_0"
concat_param {
axis: 1
}
}
layer {
name: "concat5_0/scale_relu"
type: "Scale"
bottom: "concat5_0"
top: "concat5_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat5_0/relu"
type: "ReLU"
bottom: "concat5_0/relu"
top: "concat5_0/relu"
}
layer {
name: "conv5_1/expand"
type: "Convolution"
bottom: "concat5_0/relu"
top: "conv5_1/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_1/expand/relu"
type: "ReLU"
bottom: "conv5_1/expand"
top: "conv5_1/expand"
}
layer {
name: "conv5_1/depthwise"
type: "DepthwiseConvolution"
bottom: "conv5_1/expand"
top: "conv5_1/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_1/depthwise/relu"
type: "ReLU"
bottom: "conv5_1/depthwise"
top: "conv5_1/depthwise"
}
layer {
name: "conv5_1/project"
type: "Convolution"
bottom: "conv5_1/depthwise"
top: "conv5_1/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat5_1"
type: "Concat"
bottom: "conv5_1/project"
bottom: "concat5_0"
top: "concat5_1"
concat_param {
axis: 1
}
}
layer {
name: "concat5_1/scale_relu"
type: "Scale"
bottom: "concat5_1"
top: "concat5_1/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat5_1/relu"
type: "ReLU"
bottom: "concat5_1/relu"
top: "concat5_1/relu"
}
layer {
name: "conv5_2/expand"
type: "Convolution"
bottom: "concat5_1/relu"
top: "conv5_2/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_2/expand/relu"
type: "ReLU"
bottom: "conv5_2/expand"
top: "conv5_2/expand"
}
layer {
name: "conv5_2/depthwise"
type: "DepthwiseConvolution"
bottom: "conv5_2/expand"
top: "conv5_2/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_2/depthwise/relu"
type: "ReLU"
bottom: "conv5_2/depthwise"
top: "conv5_2/depthwise"
}
layer {
name: "conv5_2/project"
type: "Convolution"
bottom: "conv5_2/depthwise"
top: "conv5_2/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat5_2"
type: "Concat"
bottom: "conv5_2/project"
bottom: "concat5_1"
top: "concat5_2"
concat_param {
axis: 1
}
}
layer {
name: "concat5_2/scale_relu"
type: "Scale"
bottom: "concat5_2"
top: "concat5_2/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat5_2/relu"
type: "ReLU"
bottom: "concat5_2/relu"
top: "concat5_2/relu"
}
layer {
name: "conv5_3/expand"
type: "Convolution"
bottom: "concat5_2/relu"
top: "conv5_3/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_3/expand/relu"
type: "ReLU"
bottom: "conv5_3/expand"
top: "conv5_3/expand"
}
layer {
name: "conv5_3/depthwise"
type: "DepthwiseConvolution"
bottom: "conv5_3/expand"
top: "conv5_3/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_3/depthwise/relu"
type: "ReLU"
bottom: "conv5_3/depthwise"
top: "conv5_3/depthwise"
}
layer {
name: "conv5_3/project"
type: "Convolution"
bottom: "conv5_3/depthwise"
top: "conv5_3/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat5_3"
type: "Concat"
bottom: "conv5_3/project"
bottom: "concat5_2"
top: "concat5_3"
concat_param {
axis: 1
}
}
layer {
name: "concat5_3/scale_relu"
type: "Scale"
bottom: "concat5_3"
top: "concat5_3/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat5_3/relu"
type: "ReLU"
bottom: "concat5_3/relu"
top: "concat5_3/relu"
}
layer {
name: "conv5_4/expand"
type: "Convolution"
bottom: "concat5_3/relu"
top: "conv5_4/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_4/expand/relu"
type: "ReLU"
bottom: "conv5_4/expand"
top: "conv5_4/expand"
}
layer {
name: "conv5_4/depthwise"
type: "DepthwiseConvolution"
bottom: "conv5_4/expand"
top: "conv5_4/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_4/depthwise/relu"
type: "ReLU"
bottom: "conv5_4/depthwise"
top: "conv5_4/depthwise"
}
layer {
name: "conv5_4/project"
type: "Convolution"
bottom: "conv5_4/depthwise"
top: "conv5_4/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat5_4"
type: "Concat"
bottom: "conv5_4/project"
bottom: "concat5_3"
top: "concat5_4"
concat_param {
axis: 1
}
}
layer {
name: "concat5_4/scale_relu"
type: "Scale"
bottom: "concat5_4"
top: "concat5_4/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat5_4/relu"
type: "ReLU"
bottom: "concat5_4/relu"
top: "concat5_4/relu"
}
layer {
name: "conv5_5/expand"
type: "Convolution"
bottom: "concat5_4/relu"
top: "conv5_5/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_5/expand/relu"
type: "ReLU"
bottom: "conv5_5/expand"
top: "conv5_5/expand"
}
layer {
name: "conv5_5/depthwise"
type: "DepthwiseConvolution"
bottom: "conv5_5/expand"
top: "conv5_5/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv5_5/depthwise/relu"
type: "ReLU"
bottom: "conv5_5/depthwise"
top: "conv5_5/depthwise"
}
layer {
name: "conv5_5/project"
type: "Convolution"
bottom: "conv5_5/depthwise"
top: "conv5_5/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "concat5_5"
type: "Concat"
bottom: "conv5_5/project"
bottom: "concat5_4"
top: "concat5_5"
concat_param {
axis: 1
}
}
layer {
name: "concat5_5/scale_relu"
type: "Scale"
bottom: "concat5_5"
top: "concat5_5/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "concat5_5/relu"
type: "ReLU"
bottom: "concat5_5/relu"
top: "concat5_5/relu"
}
layer {
name: "transition5_0"
type: "Convolution"
bottom: "concat5_5/relu"
top: "transition5_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "pooling5_1"
type: "Pooling"
bottom: "second"
top: "pooling5_1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling5_1/scale_relu"
type: "Scale"
bottom: "pooling5_1"
top: "pooling5_1/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling5_1/relu"
type: "ReLU"
bottom: "pooling5_1/relu"
top: "pooling5_1/relu"
}
layer {
name: "transition5_1"
type: "Convolution"
bottom: "pooling5_1/relu"
top: "transition5_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "third"
type: "Concat"
bottom: "transition5_1"
bottom: "transition5_0"
top: "third"
concat_param {
axis: 1
}
}
layer {
name: "third/scale_relu"
type: "Scale"
bottom: "third"
top: "third/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "third/relu"
type: "ReLU"
bottom: "third/relu"
top: "third/relu"
}
layer {
name: "conv6/expand"
type: "Convolution"
bottom: "third/relu"
top: "conv6/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv6/expand/relu"
type: "ReLU"
bottom: "conv6/expand"
top: "conv6/expand"
}
layer {
name: "conv6/depthwise"
type: "DepthwiseConvolution"
bottom: "conv6/expand"
top: "conv6/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv6/depthwise/relu"
type: "ReLU"
bottom: "conv6/depthwise"
top: "conv6/depthwise"
}
layer {
name: "conv6/project"
type: "Convolution"
bottom: "conv6/depthwise"
top: "conv6/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "pooling6_0"
type: "Pooling"
bottom: "third"
top: "pooling6_0"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling6_0/scale_relu"
type: "Scale"
bottom: "pooling6_0"
top: "pooling6_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling6_0/relu"
type: "ReLU"
bottom: "pooling6_0/relu"
top: "pooling6_0/relu"
}
layer {
name: "transition6_0"
type: "Convolution"
bottom: "pooling6_0/relu"
top: "transition6_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fourth"
type: "Concat"
bottom: "transition6_0"
bottom: "conv6/project"
top: "fourth"
concat_param {
axis: 1
}
}
layer {
name: "fourth/scale_relu"
type: "Scale"
bottom: "fourth"
top: "fourth/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "fourth/relu"
type: "ReLU"
bottom: "fourth/relu"
top: "fourth/relu"
}
layer {
name: "conv7/expand"
type: "Convolution"
bottom: "fourth/relu"
top: "conv7/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv7/expand/relu"
type: "ReLU"
bottom: "conv7/expand"
top: "conv7/expand"
}
layer {
name: "conv7/depthwise"
type: "DepthwiseConvolution"
bottom: "conv7/expand"
top: "conv7/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv7/depthwise/relu"
type: "ReLU"
bottom: "conv7/depthwise"
top: "conv7/depthwise"
}
layer {
name: "conv7/project"
type: "Convolution"
bottom: "conv7/depthwise"
top: "conv7/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "pooling7_0"
type: "Pooling"
bottom: "fourth"
top: "pooling7_0"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling7_0/scale_relu"
type: "Scale"
bottom: "pooling7_0"
top: "pooling7_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling7_0/relu"
type: "ReLU"
bottom: "pooling7_0/relu"
top: "pooling7_0/relu"
}
layer {
name: "transition7_0"
type: "Convolution"
bottom: "pooling7_0/relu"
top: "transition7_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fifth"
type: "Concat"
bottom: "transition7_0"
bottom: "conv7/project"
top: "fifth"
concat_param {
axis: 1
}
}
layer {
name: "fifth/scale_relu"
type: "Scale"
bottom: "fifth"
top: "fifth/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "fifth/relu"
type: "ReLU"
bottom: "fifth/relu"
top: "fifth/relu"
}
layer {
name: "conv8/expand"
type: "Convolution"
bottom: "fifth/relu"
top: "conv8/expand"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv8/expand/relu"
type: "ReLU"
bottom: "conv8/expand"
top: "conv8/expand"
}
layer {
name: "conv8/depthwise"
type: "DepthwiseConvolution"
bottom: "conv8/expand"
top: "conv8/depthwise"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
group: 128
stride: 2
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "conv8/depthwise/relu"
type: "ReLU"
bottom: "conv8/depthwise"
top: "conv8/depthwise"
}
layer {
name: "conv8/project"
type: "Convolution"
bottom: "conv8/depthwise"
top: "conv8/project"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "pooling8_0"
type: "Pooling"
bottom: "fifth"
top: "pooling8_0"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling8_0/scale_relu"
type: "Scale"
bottom: "pooling8_0"
top: "pooling8_0/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "pooling8_0/relu"
type: "ReLU"
bottom: "pooling8_0/relu"
top: "pooling8_0/relu"
}
layer {
name: "transition8_0"
type: "Convolution"
bottom: "pooling8_0/relu"
top: "transition8_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sixth"
type: "Concat"
bottom: "transition8_0"
bottom: "conv8/project"
top: "sixth"
concat_param {
axis: 1
}
}
layer {
name: "sixth/scale_relu"
type: "Scale"
bottom: "sixth"
top: "sixth/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "sixth/relu"
type: "ReLU"
bottom: "sixth/relu"
top: "sixth/relu"
}
layer {
name: "upsampling1"
type: "Deconvolution"
bottom: "sixth/relu"
top: "upsampling1"
param {
lr_mult: 0.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 0
kernel_size: 2
group: 256
stride: 2
weight_filler {
type: "bilinear"
}
dilation: 1
}
}
layer {
name: "upsampling1/scale_relu"
type: "Scale"
bottom: "upsampling1"
top: "upsampling1/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "upsampling1/relu"
type: "ReLU"
bottom: "upsampling1/relu"
top: "upsampling1/relu"
}
layer {
name: "transition9_0"
type: "Convolution"
bottom: "upsampling1/relu"
top: "transition9_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "transition9_1"
type: "Convolution"
bottom: "fifth"
top: "transition9_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "comb_fifth"
type: "Concat"
bottom: "transition9_1"
bottom: "transition9_0"
top: "comb_fifth"
concat_param {
axis: 1
}
}
layer {
name: "comb_fifth/scale_relu"
type: "Scale"
bottom: "comb_fifth"
top: "comb_fifth/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "comb_fifth/relu"
type: "ReLU"
bottom: "comb_fifth/relu"
top: "comb_fifth/relu"
}
layer {
name: "upsampling2"
type: "Deconvolution"
bottom: "comb_fifth/relu"
top: "upsampling2"
param {
lr_mult: 0.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
stride: 2
weight_filler {
type: "bilinear"
}
dilation: 1
}
}
layer {
name: "upsampling2/scale_relu"
type: "Scale"
bottom: "upsampling2"
top: "upsampling2/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "upsampling2/relu"
type: "ReLU"
bottom: "upsampling2/relu"
top: "upsampling2/relu"
}
layer {
name: "transition10_0"
type: "Convolution"
bottom: "upsampling2/relu"
top: "transition10_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "transition10_1"
type: "Convolution"
bottom: "fourth"
top: "transition10_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "comb_fourth"
type: "Concat"
bottom: "transition10_1"
bottom: "transition10_0"
top: "comb_fourth"
concat_param {
axis: 1
}
}
layer {
name: "comb_fourth/scale_relu"
type: "Scale"
bottom: "comb_fourth"
top: "comb_fourth/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "comb_fourth/relu"
type: "ReLU"
bottom: "comb_fourth/relu"
top: "comb_fourth/relu"
}
layer {
name: "upsampling3"
type: "Deconvolution"
bottom: "comb_fourth/relu"
top: "upsampling3"
param {
lr_mult: 0.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
stride: 2
weight_filler {
type: "bilinear"
}
dilation: 1
}
}
layer {
name: "upsampling3/scale_relu"
type: "Scale"
bottom: "upsampling3"
top: "upsampling3/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "upsampling3/relu"
type: "ReLU"
bottom: "upsampling3/relu"
top: "upsampling3/relu"
}
layer {
name: "transition11_0"
type: "Convolution"
bottom: "upsampling3/relu"
top: "transition11_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "transition11_1"
type: "Convolution"
bottom: "third"
top: "transition11_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "comb_third"
type: "Concat"
bottom: "transition11_1"
bottom: "transition11_0"
top: "comb_third"
concat_param {
axis: 1
}
}
layer {
name: "comb_third/scale_relu"
type: "Scale"
bottom: "comb_third"
top: "comb_third/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "comb_third/relu"
type: "ReLU"
bottom: "comb_third/relu"
top: "comb_third/relu"
}
layer {
name: "upsampling4"
type: "Deconvolution"
bottom: "comb_third/relu"
top: "upsampling4"
param {
lr_mult: 0.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 2
group: 512
stride: 2
weight_filler {
type: "bilinear"
}
dilation: 1
}
}
layer {
name: "upsampling4/scale_relu"
type: "Scale"
bottom: "upsampling4"
top: "upsampling4/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "upsampling4/relu"
type: "ReLU"
bottom: "upsampling4/relu"
top: "upsampling4/relu"
}
layer {
name: "transition12_0"
type: "Convolution"
bottom: "upsampling4/relu"
top: "transition12_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "transition12_1"
type: "Convolution"
bottom: "second"
top: "transition12_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "comb_second"
type: "Concat"
bottom: "transition12_1"
bottom: "transition12_0"
top: "comb_second"
concat_param {
axis: 1
}
}
layer {
name: "comb_second/scale_relu"
type: "Scale"
bottom: "comb_second"
top: "comb_second/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "comb_second/relu"
type: "ReLU"
bottom: "comb_second/relu"
top: "comb_second/relu"
}
layer {
name: "upsampling5"
type: "Deconvolution"
bottom: "comb_second/relu"
top: "upsampling5"
param {
lr_mult: 0.0
decay_mult: 0.0
}
convolution_param {
num_output: 512
bias_term: false
pad: 0
kernel_size: 2
group: 512
stride: 2
weight_filler {
type: "bilinear"
}
dilation: 1
}
}
layer {
name: "upsampling5/scale_relu"
type: "Scale"
bottom: "upsampling5"
top: "upsampling5/relu"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1.0
}
bias_term: true
bias_filler {
value: 0.0
}
}
}
layer {
name: "upsampling5/relu"
type: "ReLU"
bottom: "upsampling5/relu"
top: "upsampling5/relu"
}
layer {
name: "transition13_0"
type: "Convolution"
bottom: "upsampling5/relu"
top: "transition13_0"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "transition13_1"
type: "Convolution"
bottom: "first"
top: "transition13_1"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "comb_first"
type: "Concat"
bottom: "transition13_1"
bottom: "transition13_0"
top: "comb_first"
concat_param {
axis: 1
}
}
layer {
name: "first_norm"
type: "Normalize"
bottom: "comb_first"
top: "first_norm"
norm_param {
across_spatial: false
scale_filler {
type: "constant"
value: 20.0
}
channel_shared: false
}
}
layer {
name: "second_norm"
type: "Normalize"
bottom: "comb_second"
top: "second_norm"
norm_param {
across_spatial: false
scale_filler {
type: "constant"
value: 20.0
}
channel_shared: false
}
}
layer {
name: "third_norm"
type: "Normalize"
bottom: "comb_third"
top: "third_norm"
norm_param {
across_spatial: false
scale_filler {
type: "constant"
value: 20.0
}
channel_shared: false
}
}
layer {
name: "fourth_norm"
type: "Normalize"
bottom: "comb_fourth"
top: "fourth_norm"
norm_param {
across_spatial: false
scale_filler {
type: "constant"
value: 20.0
}
channel_shared: false
}
}
layer {
name: "fifth_norm"
type: "Normalize"
bottom: "comb_fifth"
top: "fifth_norm"
norm_param {
across_spatial: false
scale_filler {
type: "constant"
value: 20.0
}
channel_shared: false
}
}
layer {
name: "sixth_norm"
type: "Normalize"
bottom: "sixth"
top: "sixth_norm"
norm_param {
across_spatial: false
scale_filler {
type: "constant"
value: 20.0
}
channel_shared: false
}
}
layer {
name: "first_norm_mbox_loc"
type: "Convolution"
bottom: "first_norm"
top: "first_norm_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "first_norm_mbox_loc_perm"
type: "Permute"
bottom: "first_norm_mbox_loc"
top: "first_norm_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "first_norm_mbox_loc_flat"
type: "Flatten"
bottom: "first_norm_mbox_loc_perm"
top: "first_norm_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "first_norm_mbox_conf"
type: "Convolution"
bottom: "first_norm"
top: "first_norm_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 20
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "first_norm_mbox_conf_perm"
type: "Permute"
bottom: "first_norm_mbox_conf"
top: "first_norm_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "first_norm_mbox_conf_flat"
type: "Flatten"
bottom: "first_norm_mbox_conf_perm"
top: "first_norm_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "first_norm_mbox_priorbox"
type: "PriorBox"
bottom: "first_norm"
bottom: "data"
top: "first_norm_mbox_priorbox"
prior_box_param {
min_size: 41.6
max_size: 61.1
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: "second_norm_mbox_loc"
type: "Convolution"
bottom: "second_norm"
top: "second_norm_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "second_norm_mbox_loc_perm"
type: "Permute"
bottom: "second_norm_mbox_loc"
top: "second_norm_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "second_norm_mbox_loc_flat"
type: "Flatten"
bottom: "second_norm_mbox_loc_perm"
top: "second_norm_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "second_norm_mbox_conf"
type: "Convolution"
bottom: "second_norm"
top: "second_norm_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 30
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "second_norm_mbox_conf_perm"
type: "Permute"
bottom: "second_norm_mbox_conf"
top: "second_norm_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "second_norm_mbox_conf_flat"
type: "Flatten"
bottom: "second_norm_mbox_conf_perm"
top: "second_norm_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "second_norm_mbox_priorbox"
type: "PriorBox"
bottom: "second_norm"
bottom: "data"
top: "second_norm_mbox_priorbox"
prior_box_param {
min_size: 61.1
max_size: 89.6
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: "third_norm_mbox_loc"
type: "Convolution"
bottom: "third_norm"
top: "third_norm_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "third_norm_mbox_loc_perm"
type: "Permute"
bottom: "third_norm_mbox_loc"
top: "third_norm_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "third_norm_mbox_loc_flat"
type: "Flatten"
bottom: "third_norm_mbox_loc_perm"
top: "third_norm_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "third_norm_mbox_conf"
type: "Convolution"
bottom: "third_norm"
top: "third_norm_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 30
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "third_norm_mbox_conf_perm"
type: "Permute"
bottom: "third_norm_mbox_conf"
top: "third_norm_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "third_norm_mbox_conf_flat"
type: "Flatten"
bottom: "third_norm_mbox_conf_perm"
top: "third_norm_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "third_norm_mbox_priorbox"
type: "PriorBox"
bottom: "third_norm"
bottom: "data"
top: "third_norm_mbox_priorbox"
prior_box_param {
min_size: 89.6
max_size: 131.6
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: "fourth_norm_mbox_loc"
type: "Convolution"
bottom: "fourth_norm"
top: "fourth_norm_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 24
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fourth_norm_mbox_loc_perm"
type: "Permute"
bottom: "fourth_norm_mbox_loc"
top: "fourth_norm_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fourth_norm_mbox_loc_flat"
type: "Flatten"
bottom: "fourth_norm_mbox_loc_perm"
top: "fourth_norm_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fourth_norm_mbox_conf"
type: "Convolution"
bottom: "fourth_norm"
top: "fourth_norm_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 30
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fourth_norm_mbox_conf_perm"
type: "Permute"
bottom: "fourth_norm_mbox_conf"
top: "fourth_norm_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fourth_norm_mbox_conf_flat"
type: "Flatten"
bottom: "fourth_norm_mbox_conf_perm"
top: "fourth_norm_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fourth_norm_mbox_priorbox"
type: "PriorBox"
bottom: "fourth_norm"
bottom: "data"
top: "fourth_norm_mbox_priorbox"
prior_box_param {
min_size: 131.6
max_size: 193.1
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: "fifth_norm_mbox_loc"
type: "Convolution"
bottom: "fifth_norm"
top: "fifth_norm_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fifth_norm_mbox_loc_perm"
type: "Permute"
bottom: "fifth_norm_mbox_loc"
top: "fifth_norm_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fifth_norm_mbox_loc_flat"
type: "Flatten"
bottom: "fifth_norm_mbox_loc_perm"
top: "fifth_norm_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fifth_norm_mbox_conf"
type: "Convolution"
bottom: "fifth_norm"
top: "fifth_norm_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 20
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "fifth_norm_mbox_conf_perm"
type: "Permute"
bottom: "fifth_norm_mbox_conf"
top: "fifth_norm_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "fifth_norm_mbox_conf_flat"
type: "Flatten"
bottom: "fifth_norm_mbox_conf_perm"
top: "fifth_norm_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "fifth_norm_mbox_priorbox"
type: "PriorBox"
bottom: "fifth_norm"
bottom: "data"
top: "fifth_norm_mbox_priorbox"
prior_box_param {
min_size: 193.1
max_size: 283.4
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: "sixth_norm_mbox_loc"
type: "Convolution"
bottom: "sixth_norm"
top: "sixth_norm_mbox_loc"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 16
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sixth_norm_mbox_loc_perm"
type: "Permute"
bottom: "sixth_norm_mbox_loc"
top: "sixth_norm_mbox_loc_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "sixth_norm_mbox_loc_flat"
type: "Flatten"
bottom: "sixth_norm_mbox_loc_perm"
top: "sixth_norm_mbox_loc_flat"
flatten_param {
axis: 1
}
}
layer {
name: "sixth_norm_mbox_conf"
type: "Convolution"
bottom: "sixth_norm"
top: "sixth_norm_mbox_conf"
param {
lr_mult: 1.0
decay_mult: 1.0
}
param {
lr_mult: 1.0
decay_mult: 0.0
}
convolution_param {
num_output: 20
pad: 1
kernel_size: 3
weight_filler {
type: "msra"
}
bias_filler {
type: "constant"
value: 0.0
}
}
}
layer {
name: "sixth_norm_mbox_conf_perm"
type: "Permute"
bottom: "sixth_norm_mbox_conf"
top: "sixth_norm_mbox_conf_perm"
permute_param {
order: 0
order: 2
order: 3
order: 1
}
}
layer {
name: "sixth_norm_mbox_conf_flat"
type: "Flatten"
bottom: "sixth_norm_mbox_conf_perm"
top: "sixth_norm_mbox_conf_flat"
flatten_param {
axis: 1
}
}
layer {
name: "sixth_norm_mbox_priorbox"
type: "PriorBox"
bottom: "sixth_norm"
bottom: "data"
top: "sixth_norm_mbox_priorbox"
prior_box_param {
min_size: 283.4
max_size: 416.0
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: "mbox_loc"
type: "Concat"
bottom: "first_norm_mbox_loc_flat"
bottom: "second_norm_mbox_loc_flat"
bottom: "third_norm_mbox_loc_flat"
bottom: "fourth_norm_mbox_loc_flat"
bottom: "fifth_norm_mbox_loc_flat"
bottom: "sixth_norm_mbox_loc_flat"
top: "mbox_loc"
concat_param {
axis: 1
}
}
layer {
name: "mbox_conf"
type: "Concat"
bottom: "first_norm_mbox_conf_flat"
bottom: "second_norm_mbox_conf_flat"
bottom: "third_norm_mbox_conf_flat"
bottom: "fourth_norm_mbox_conf_flat"
bottom: "fifth_norm_mbox_conf_flat"
bottom: "sixth_norm_mbox_conf_flat"
top: "mbox_conf"
concat_param {
axis: 1
}
}
layer {
name: "mbox_priorbox"
type: "Concat"
bottom: "first_norm_mbox_priorbox"
bottom: "second_norm_mbox_priorbox"
bottom: "third_norm_mbox_priorbox"
bottom: "fourth_norm_mbox_priorbox"
bottom: "fifth_norm_mbox_priorbox"
bottom: "sixth_norm_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: 5
}
}
}
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: 5
share_location: true
background_label_id: 0
nms_param {
nms_threshold: 0.25
top_k: 400
}
code_type: CENTER_SIZE
keep_top_k: 200
confidence_threshold: 0.91
}
}
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