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deploy_FFInception-5
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name: "FFInception-5" | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 112 | |
input_dim: 112 | |
################################## | |
layer { | |
name: "conv1" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 5 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1" | |
type: "PReLU" | |
bottom: "conv1" | |
top: "conv1" | |
} | |
layer { | |
name: "conv1_1" | |
type: "Convolution" | |
bottom: "conv1" | |
top: "conv1_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1_1" | |
type: "PReLU" | |
bottom: "conv1_1" | |
top: "conv1_1" | |
} | |
layer { | |
name: "conv1_2" | |
type: "Convolution" | |
bottom: "conv1_1" | |
top: "conv1_2" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 8 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1_2" | |
type: "PReLU" | |
bottom: "conv1_2" | |
top: "conv1_2" | |
} | |
layer { | |
name: "conv1_3" | |
type: "Convolution" | |
bottom: "conv1_2" | |
top: "conv1_3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 4 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1_3" | |
type: "PReLU" | |
bottom: "conv1_3" | |
top: "conv1_3" | |
} | |
layer { | |
name: "conv1_4" | |
type: "Convolution" | |
bottom: "conv1_3" | |
top: "conv1_4" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 4 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1_4" | |
type: "PReLU" | |
bottom: "conv1_4" | |
top: "conv1_4" | |
} | |
layer{ | |
name: "concat1" | |
type: "Concat" | |
bottom: "conv1" | |
bottom: "conv1_1" | |
bottom: "conv1_2" | |
bottom: "conv1_3" | |
bottom: "conv1_4" | |
top: "concat1" | |
concat_param{ | |
axis:1 | |
} | |
} | |
layer { | |
name: "conv2" | |
type: "Convolution" | |
bottom: "concat1" | |
top: "conv2" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2" | |
type: "PReLU" | |
bottom: "conv2" | |
top: "conv2" | |
} | |
layer { | |
name: "conv2_1" | |
type: "Convolution" | |
bottom: "conv2" | |
top: "conv2_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_1" | |
type: "PReLU" | |
bottom: "conv2_1" | |
top: "conv2_1" | |
} | |
layer { | |
name: "conv2_2" | |
type: "Convolution" | |
bottom: "conv2_1" | |
top: "conv2_2" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_2" | |
type: "PReLU" | |
bottom: "conv2_2" | |
top: "conv2_2" | |
} | |
layer { | |
name: "conv2_3" | |
type: "Convolution" | |
bottom: "conv2_2" | |
top: "conv2_3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 8 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_3" | |
type: "PReLU" | |
bottom: "conv2_3" | |
top: "conv2_3" | |
} | |
layer { | |
name: "conv2_4" | |
type: "Convolution" | |
bottom: "conv2_3" | |
top: "conv2_4" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 8 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_4" | |
type: "PReLU" | |
bottom: "conv2_4" | |
top: "conv2_4" | |
} | |
layer{ | |
name: "concat2" | |
type: "Concat" | |
bottom: "conv2" | |
bottom: "conv2_1" | |
bottom: "conv2_2" | |
bottom: "conv2_3" | |
bottom: "conv2_4" | |
top: "concat2" | |
concat_param{ | |
axis:1 | |
} | |
} | |
layer { | |
name: "conv3" | |
type: "Convolution" | |
bottom: "concat2" | |
top: "conv3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3" | |
type: "PReLU" | |
bottom: "conv3" | |
top: "conv3" | |
} | |
layer { | |
name: "conv3_1" | |
type: "Convolution" | |
bottom: "conv3" | |
top: "conv3_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_1" | |
type: "PReLU" | |
bottom: "conv3_1" | |
top: "conv3_1" | |
} | |
layer { | |
name: "conv3_2" | |
type: "Convolution" | |
bottom: "conv3_1" | |
top: "conv3_2" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_2" | |
type: "PReLU" | |
bottom: "conv3_2" | |
top: "conv3_2" | |
} | |
layer { | |
name: "conv3_3" | |
type: "Convolution" | |
bottom: "conv3_2" | |
top: "conv3_3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_3" | |
type: "PReLU" | |
bottom: "conv3_3" | |
top: "conv3_3" | |
} | |
layer { | |
name: "conv3_4" | |
type: "Convolution" | |
bottom: "conv3_3" | |
top: "conv3_4" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 16 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_4" | |
type: "PReLU" | |
bottom: "conv3_4" | |
top: "conv3_4" | |
} | |
layer{ | |
name: "concat3" | |
type: "Concat" | |
bottom: "conv3" | |
bottom: "conv3_1" | |
bottom: "conv3_2" | |
bottom: "conv3_3" | |
bottom: "conv3_4" | |
top: "concat3" | |
concat_param{ | |
axis:1 | |
} | |
} | |
layer { | |
name: "conv4" | |
type: "Convolution" | |
bottom: "concat3" | |
top: "conv4" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 256 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4" | |
type: "PReLU" | |
bottom: "conv4" | |
top: "conv4" | |
} | |
layer { | |
name: "conv4_1" | |
type: "Convolution" | |
bottom: "conv4" | |
top: "conv4_1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 128 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_1" | |
type: "PReLU" | |
bottom: "conv4_1" | |
top: "conv4_1" | |
} | |
layer { | |
name: "conv4_2" | |
type: "Convolution" | |
bottom: "conv4_1" | |
top: "conv4_2" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 64 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_2" | |
type: "PReLU" | |
bottom: "conv4_2" | |
top: "conv4_2" | |
} | |
layer { | |
name: "conv4_3" | |
type: "Convolution" | |
bottom: "conv4_2" | |
top: "conv4_3" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_3" | |
type: "PReLU" | |
bottom: "conv4_3" | |
top: "conv4_3" | |
} | |
layer { | |
name: "conv4_4" | |
type: "Convolution" | |
bottom: "conv4_3" | |
top: "conv4_4" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 32 | |
kernel_size: 3 | |
stride: 1 | |
pad: 1 | |
weight_filler { | |
type: "gaussian" | |
std: 0.01 | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_4" | |
type: "PReLU" | |
bottom: "conv4_4" | |
top: "conv4_4" | |
} | |
layer{ | |
name: "concat4" | |
type: "Concat" | |
bottom: "conv4" | |
bottom: "conv4_1" | |
bottom: "conv4_2" | |
bottom: "conv4_3" | |
bottom: "conv4_4" | |
top: "concat4" | |
concat_param{ | |
axis:1 | |
} | |
} | |
layer { | |
name: "fc5" | |
type: "InnerProduct" | |
bottom: "concat4" | |
top: "fc5" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
inner_product_param { | |
num_output: 128 | |
weight_filler { | |
type: "xavier" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} |
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