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November 7, 2017 04:46
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mobilenet0.5.prototxt
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name: "SIMPLIFIED_MOBILENET" | |
# transform_param { | |
# scale: 0.017 | |
# mirror: false | |
# crop_size: 224 | |
# mean_value: [103.94,116.78,123.68] | |
# } | |
input: "data" | |
input_shape { | |
dim: 1 | |
dim: 3 | |
dim: 224 | |
dim: 224 | |
} | |
layer { | |
name: "conv1" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv1/bn" | |
type: "BatchNorm" | |
bottom: "conv1" | |
top: "conv1" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv1/scale" | |
type: "Scale" | |
bottom: "conv1" | |
top: "conv1" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu1" | |
type: "ReLU" | |
bottom: "conv1" | |
top: "conv1" | |
} | |
layer { | |
name: "conv2_1/dw" | |
type: "Convolution" | |
bottom: "conv1" | |
top: "conv2_1/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 16 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv2_1/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv2_1/dw" | |
top: "conv2_1/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv2_1/dw/scale" | |
type: "Scale" | |
bottom: "conv2_1/dw" | |
top: "conv2_1/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_1/dw" | |
type: "ReLU" | |
bottom: "conv2_1/dw" | |
top: "conv2_1/dw" | |
} | |
layer { | |
name: "conv2_1/sep" | |
type: "Convolution" | |
bottom: "conv2_1/dw" | |
top: "conv2_1/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv2_1/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv2_1/sep" | |
top: "conv2_1/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv2_1/sep/scale" | |
type: "Scale" | |
bottom: "conv2_1/sep" | |
top: "conv2_1/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_1/sep" | |
type: "ReLU" | |
bottom: "conv2_1/sep" | |
top: "conv2_1/sep" | |
} | |
layer { | |
name: "conv2_2/dw" | |
type: "Convolution" | |
bottom: "conv2_1/sep" | |
top: "conv2_2/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 32 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv2_2/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv2_2/dw" | |
top: "conv2_2/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv2_2/dw/scale" | |
type: "Scale" | |
bottom: "conv2_2/dw" | |
top: "conv2_2/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_2/dw" | |
type: "ReLU" | |
bottom: "conv2_2/dw" | |
top: "conv2_2/dw" | |
} | |
layer { | |
name: "conv2_2/sep" | |
type: "Convolution" | |
bottom: "conv2_2/dw" | |
top: "conv2_2/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv2_2/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv2_2/sep" | |
top: "conv2_2/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv2_2/sep/scale" | |
type: "Scale" | |
bottom: "conv2_2/sep" | |
top: "conv2_2/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu2_2/sep" | |
type: "ReLU" | |
bottom: "conv2_2/sep" | |
top: "conv2_2/sep" | |
} | |
layer { | |
name: "conv3_1/dw" | |
type: "Convolution" | |
bottom: "conv2_2/sep" | |
top: "conv3_1/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv3_1/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv3_1/dw" | |
top: "conv3_1/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv3_1/dw/scale" | |
type: "Scale" | |
bottom: "conv3_1/dw" | |
top: "conv3_1/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_1/dw" | |
type: "ReLU" | |
bottom: "conv3_1/dw" | |
top: "conv3_1/dw" | |
} | |
layer { | |
name: "conv3_1/sep" | |
type: "Convolution" | |
bottom: "conv3_1/dw" | |
top: "conv3_1/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv3_1/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv3_1/sep" | |
top: "conv3_1/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv3_1/sep/scale" | |
type: "Scale" | |
bottom: "conv3_1/sep" | |
top: "conv3_1/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_1/sep" | |
type: "ReLU" | |
bottom: "conv3_1/sep" | |
top: "conv3_1/sep" | |
} | |
layer { | |
name: "conv3_2/dw" | |
type: "Convolution" | |
bottom: "conv3_1/sep" | |
top: "conv3_2/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 64 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv3_2/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv3_2/dw" | |
top: "conv3_2/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv3_2/dw/scale" | |
type: "Scale" | |
bottom: "conv3_2/dw" | |
top: "conv3_2/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_2/dw" | |
type: "ReLU" | |
bottom: "conv3_2/dw" | |
top: "conv3_2/dw" | |
} | |
layer { | |
name: "conv3_2/sep" | |
type: "Convolution" | |
bottom: "conv3_2/dw" | |
top: "conv3_2/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv3_2/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv3_2/sep" | |
top: "conv3_2/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv3_2/sep/scale" | |
type: "Scale" | |
bottom: "conv3_2/sep" | |
top: "conv3_2/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu3_2/sep" | |
type: "ReLU" | |
bottom: "conv3_2/sep" | |
top: "conv3_2/sep" | |
} | |
layer { | |
name: "conv4_1/dw" | |
type: "Convolution" | |
bottom: "conv3_2/sep" | |
top: "conv4_1/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv4_1/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv4_1/dw" | |
top: "conv4_1/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv4_1/dw/scale" | |
type: "Scale" | |
bottom: "conv4_1/dw" | |
top: "conv4_1/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_1/dw" | |
type: "ReLU" | |
bottom: "conv4_1/dw" | |
top: "conv4_1/dw" | |
} | |
layer { | |
name: "conv4_1/sep" | |
type: "Convolution" | |
bottom: "conv4_1/dw" | |
top: "conv4_1/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv4_1/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv4_1/sep" | |
top: "conv4_1/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv4_1/sep/scale" | |
type: "Scale" | |
bottom: "conv4_1/sep" | |
top: "conv4_1/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_1/sep" | |
type: "ReLU" | |
bottom: "conv4_1/sep" | |
top: "conv4_1/sep" | |
} | |
layer { | |
name: "conv4_2/dw" | |
type: "Convolution" | |
bottom: "conv4_1/sep" | |
top: "conv4_2/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 128 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv4_2/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv4_2/dw" | |
top: "conv4_2/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv4_2/dw/scale" | |
type: "Scale" | |
bottom: "conv4_2/dw" | |
top: "conv4_2/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_2/dw" | |
type: "ReLU" | |
bottom: "conv4_2/dw" | |
top: "conv4_2/dw" | |
} | |
layer { | |
name: "conv4_2/sep" | |
type: "Convolution" | |
bottom: "conv4_2/dw" | |
top: "conv4_2/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv4_2/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv4_2/sep" | |
top: "conv4_2/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv4_2/sep/scale" | |
type: "Scale" | |
bottom: "conv4_2/sep" | |
top: "conv4_2/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu4_2/sep" | |
type: "ReLU" | |
bottom: "conv4_2/sep" | |
top: "conv4_2/sep" | |
} | |
layer { | |
name: "conv5_1/dw" | |
type: "Convolution" | |
bottom: "conv4_2/sep" | |
top: "conv5_1/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_1/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv5_1/dw" | |
top: "conv5_1/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_1/dw/scale" | |
type: "Scale" | |
bottom: "conv5_1/dw" | |
top: "conv5_1/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_1/dw" | |
type: "ReLU" | |
bottom: "conv5_1/dw" | |
top: "conv5_1/dw" | |
} | |
layer { | |
name: "conv5_1/sep" | |
type: "Convolution" | |
bottom: "conv5_1/dw" | |
top: "conv5_1/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_1/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv5_1/sep" | |
top: "conv5_1/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_1/sep/scale" | |
type: "Scale" | |
bottom: "conv5_1/sep" | |
top: "conv5_1/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_1/sep" | |
type: "ReLU" | |
bottom: "conv5_1/sep" | |
top: "conv5_1/sep" | |
} | |
layer { | |
name: "conv5_2/dw" | |
type: "Convolution" | |
bottom: "conv5_1/sep" | |
top: "conv5_2/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_2/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv5_2/dw" | |
top: "conv5_2/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_2/dw/scale" | |
type: "Scale" | |
bottom: "conv5_2/dw" | |
top: "conv5_2/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_2/dw" | |
type: "ReLU" | |
bottom: "conv5_2/dw" | |
top: "conv5_2/dw" | |
} | |
layer { | |
name: "conv5_2/sep" | |
type: "Convolution" | |
bottom: "conv5_2/dw" | |
top: "conv5_2/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_2/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv5_2/sep" | |
top: "conv5_2/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_2/sep/scale" | |
type: "Scale" | |
bottom: "conv5_2/sep" | |
top: "conv5_2/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_2/sep" | |
type: "ReLU" | |
bottom: "conv5_2/sep" | |
top: "conv5_2/sep" | |
} | |
layer { | |
name: "conv5_3/dw" | |
type: "Convolution" | |
bottom: "conv5_2/sep" | |
top: "conv5_3/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_3/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv5_3/dw" | |
top: "conv5_3/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_3/dw/scale" | |
type: "Scale" | |
bottom: "conv5_3/dw" | |
top: "conv5_3/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_3/dw" | |
type: "ReLU" | |
bottom: "conv5_3/dw" | |
top: "conv5_3/dw" | |
} | |
layer { | |
name: "conv5_3/sep" | |
type: "Convolution" | |
bottom: "conv5_3/dw" | |
top: "conv5_3/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_3/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv5_3/sep" | |
top: "conv5_3/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_3/sep/scale" | |
type: "Scale" | |
bottom: "conv5_3/sep" | |
top: "conv5_3/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_3/sep" | |
type: "ReLU" | |
bottom: "conv5_3/sep" | |
top: "conv5_3/sep" | |
} | |
layer { | |
name: "conv5_4/dw" | |
type: "Convolution" | |
bottom: "conv5_3/sep" | |
top: "conv5_4/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_4/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv5_4/dw" | |
top: "conv5_4/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_4/dw/scale" | |
type: "Scale" | |
bottom: "conv5_4/dw" | |
top: "conv5_4/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_4/dw" | |
type: "ReLU" | |
bottom: "conv5_4/dw" | |
top: "conv5_4/dw" | |
} | |
layer { | |
name: "conv5_4/sep" | |
type: "Convolution" | |
bottom: "conv5_4/dw" | |
top: "conv5_4/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_4/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv5_4/sep" | |
top: "conv5_4/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_4/sep/scale" | |
type: "Scale" | |
bottom: "conv5_4/sep" | |
top: "conv5_4/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_4/sep" | |
type: "ReLU" | |
bottom: "conv5_4/sep" | |
top: "conv5_4/sep" | |
} | |
layer { | |
name: "conv5_5/dw" | |
type: "Convolution" | |
bottom: "conv5_4/sep" | |
top: "conv5_5/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_5/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv5_5/dw" | |
top: "conv5_5/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_5/dw/scale" | |
type: "Scale" | |
bottom: "conv5_5/dw" | |
top: "conv5_5/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_5/dw" | |
type: "ReLU" | |
bottom: "conv5_5/dw" | |
top: "conv5_5/dw" | |
} | |
layer { | |
name: "conv5_5/sep" | |
type: "Convolution" | |
bottom: "conv5_5/dw" | |
top: "conv5_5/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_5/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv5_5/sep" | |
top: "conv5_5/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_5/sep/scale" | |
type: "Scale" | |
bottom: "conv5_5/sep" | |
top: "conv5_5/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_5/sep" | |
type: "ReLU" | |
bottom: "conv5_5/sep" | |
top: "conv5_5/sep" | |
} | |
layer { | |
name: "conv5_6/dw" | |
type: "Convolution" | |
bottom: "conv5_5/sep" | |
top: "conv5_6/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 256 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 2 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_6/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv5_6/dw" | |
top: "conv5_6/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_6/dw/scale" | |
type: "Scale" | |
bottom: "conv5_6/dw" | |
top: "conv5_6/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_6/dw" | |
type: "ReLU" | |
bottom: "conv5_6/dw" | |
top: "conv5_6/dw" | |
} | |
layer { | |
name: "conv5_6/sep" | |
type: "Convolution" | |
bottom: "conv5_6/dw" | |
top: "conv5_6/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv5_6/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv5_6/sep" | |
top: "conv5_6/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv5_6/sep/scale" | |
type: "Scale" | |
bottom: "conv5_6/sep" | |
top: "conv5_6/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu5_6/sep" | |
type: "ReLU" | |
bottom: "conv5_6/sep" | |
top: "conv5_6/sep" | |
} | |
layer { | |
name: "conv6/dw" | |
type: "Convolution" | |
bottom: "conv5_6/sep" | |
top: "conv6/dw" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 1 | |
kernel_size: 3 | |
group: 4 | |
#engine: CAFFE | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv6/dw/bn" | |
type: "BatchNorm" | |
bottom: "conv6/dw" | |
top: "conv6/dw" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv6/dw/scale" | |
type: "Scale" | |
bottom: "conv6/dw" | |
top: "conv6/dw" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu6/dw" | |
type: "ReLU" | |
bottom: "conv6/dw" | |
top: "conv6/dw" | |
} | |
layer { | |
name: "conv6/sep" | |
type: "Convolution" | |
bottom: "conv6/dw" | |
top: "conv6/sep" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
convolution_param { | |
num_output: 512 | |
bias_term: false | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
weight_filler { | |
type: "msra" | |
} | |
} | |
} | |
layer { | |
name: "conv6/sep/bn" | |
type: "BatchNorm" | |
bottom: "conv6/sep" | |
top: "conv6/sep" | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
param { | |
lr_mult: 0 | |
decay_mult: 0 | |
} | |
} | |
layer { | |
name: "conv6/sep/scale" | |
type: "Scale" | |
bottom: "conv6/sep" | |
top: "conv6/sep" | |
scale_param { | |
filler { | |
value: 1 | |
} | |
bias_term: true | |
bias_filler { | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "relu6/sep" | |
type: "ReLU" | |
bottom: "conv6/sep" | |
top: "conv6/sep" | |
} | |
layer { | |
name: "pool6" | |
type: "Pooling" | |
bottom: "conv6/sep" | |
top: "pool6" | |
pooling_param { | |
pool: AVE | |
global_pooling: true | |
} | |
} | |
layer { | |
name: "fc7" | |
type: "Convolution" | |
bottom: "pool6" | |
top: "fc7" | |
param { | |
lr_mult: 1 | |
decay_mult: 1 | |
} | |
param { | |
lr_mult: 2 | |
decay_mult: 0 | |
} | |
convolution_param { | |
num_output: 1000 | |
kernel_size: 1 | |
weight_filler { | |
type: "msra" | |
} | |
bias_filler { | |
type: "constant" | |
value: 0 | |
} | |
} | |
} | |
layer { | |
name: "loss" | |
type: "SoftmaxWithLoss" | |
bottom: "fc7" | |
bottom: "label" | |
top: "loss" | |
} | |
layer { | |
name: "accuracy_top1" | |
type: "Accuracy" | |
bottom: "fc7" | |
bottom: "label" | |
top: "accuracy_top1" | |
include { | |
phase: TEST | |
} | |
} | |
layer { | |
name: "accuracy_top5" | |
type: "Accuracy" | |
bottom: "fc7" | |
bottom: "label" | |
top: "accuracy_top5" | |
include { | |
phase: TEST | |
} | |
accuracy_param { | |
top_k: 5 | |
} | |
} |
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