Skip to content

Instantly share code, notes, and snippets.

@eric612

eric612/gist:5f45b2841dd1ce7e78fe455c3e646b99

Created March 11, 2019 03:48
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save eric612/5f45b2841dd1ce7e78fe455c3e646b99 to your computer and use it in GitHub Desktop.
Save eric612/5f45b2841dd1ce7e78fe455c3e646b99 to your computer and use it in GitHub Desktop.
Download ZIP
Model
Raw
gistfile1.txt
name: "model"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 480
dim: 352
}
layer {
name: "conv0"
type: "Convolution"
bottom: "data"
top: "conv0"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
stride: 2
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv0/bn"
type: "BatchNorm"
bottom: "conv0"
top: "conv0"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv0/scale"
type: "Scale"
bottom: "conv0"
top: "conv0"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv0/relu"
type: "ReLU"
bottom: "conv0"
top: "conv0"
}
layer {
name: "conv1/dw"
type: "DepthwiseConvolution"
bottom: "conv0"
top: "conv1/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 32
bias_term: false
pad: 1
kernel_size: 3
group: 32
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv1/dw/bn"
type: "BatchNorm"
bottom: "conv1/dw"
top: "conv1/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv1/dw/scale"
type: "Scale"
bottom: "conv1/dw"
top: "conv1/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv1/dw/relu"
type: "ReLU"
bottom: "conv1/dw"
top: "conv1/dw"
}
layer {
name: "conv1"
type: "Convolution"
bottom: "conv1/dw"
top: "conv1"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 64
bias_term: false
kernel_size: 1
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"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv1/relu"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "conv2/dw"
type: "DepthwiseConvolution"
bottom: "conv1"
top: "conv2/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 64
bias_term: false
pad: 1
kernel_size: 3
stride: 2
group: 64
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2/dw/bn"
type: "BatchNorm"
bottom: "conv2/dw"
top: "conv2/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/dw/scale"
type: "Scale"
bottom: "conv2/dw"
top: "conv2/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv2/dw/relu"
type: "ReLU"
bottom: "conv2/dw"
top: "conv2/dw"
}
layer {
name: "conv2"
type: "Convolution"
bottom: "conv2/dw"
top: "conv2"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv2/bn"
type: "BatchNorm"
bottom: "conv2"
top: "conv2"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv2/scale"
type: "Scale"
bottom: "conv2"
top: "conv2"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv2/relu"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "conv3/dw"
type: "DepthwiseConvolution"
bottom: "conv2"
top: "conv3/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3/dw/bn"
type: "BatchNorm"
bottom: "conv3/dw"
top: "conv3/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/dw/scale"
type: "Scale"
bottom: "conv3/dw"
top: "conv3/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv3/dw/relu"
type: "ReLU"
bottom: "conv3/dw"
top: "conv3/dw"
}
layer {
name: "conv3"
type: "Convolution"
bottom: "conv3/dw"
top: "conv3"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv3/bn"
type: "BatchNorm"
bottom: "conv3"
top: "conv3"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv3/scale"
type: "Scale"
bottom: "conv3"
top: "conv3"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv3/relu"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4/dw"
type: "DepthwiseConvolution"
bottom: "conv3"
top: "conv4/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 128
bias_term: false
pad: 1
kernel_size: 3
stride: 2
group: 128
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4/dw/bn"
type: "BatchNorm"
bottom: "conv4/dw"
top: "conv4/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/dw/scale"
type: "Scale"
bottom: "conv4/dw"
top: "conv4/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv4/dw/relu"
type: "ReLU"
bottom: "conv4/dw"
top: "conv4/dw"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv4/dw"
top: "conv4"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv4/bn"
type: "BatchNorm"
bottom: "conv4"
top: "conv4"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv4/scale"
type: "Scale"
bottom: "conv4"
top: "conv4"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv4/relu"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5/dw"
type: "DepthwiseConvolution"
bottom: "conv4"
top: "conv5/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5/dw/bn"
type: "BatchNorm"
bottom: "conv5/dw"
top: "conv5/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/dw/scale"
type: "Scale"
bottom: "conv5/dw"
top: "conv5/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv5/dw/relu"
type: "ReLU"
bottom: "conv5/dw"
top: "conv5/dw"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv5/dw"
top: "conv5"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv5/bn"
type: "BatchNorm"
bottom: "conv5"
top: "conv5"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv5/scale"
type: "Scale"
bottom: "conv5"
top: "conv5"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv5/relu"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "conv6/dw"
type: "DepthwiseConvolution"
bottom: "conv5"
top: "conv6/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
stride: 2
group: 256
engine: CAFFE
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"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv6/dw/relu"
type: "ReLU"
bottom: "conv6/dw"
top: "conv6/dw"
}
layer {
name: "conv6"
type: "Convolution"
bottom: "conv6/dw"
top: "conv6"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv6/bn"
type: "BatchNorm"
bottom: "conv6"
top: "conv6"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv6/scale"
type: "Scale"
bottom: "conv6"
top: "conv6"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv6/relu"
type: "ReLU"
bottom: "conv6"
top: "conv6"
}
layer {
name: "conv7/dw"
type: "DepthwiseConvolution"
bottom: "conv6"
top: "conv7/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv7/dw/bn"
type: "BatchNorm"
bottom: "conv7/dw"
top: "conv7/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv7/dw/scale"
type: "Scale"
bottom: "conv7/dw"
top: "conv7/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv7/dw/relu"
type: "ReLU"
bottom: "conv7/dw"
top: "conv7/dw"
}
layer {
name: "conv7"
type: "Convolution"
bottom: "conv7/dw"
top: "conv7"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv7/bn"
type: "BatchNorm"
bottom: "conv7"
top: "conv7"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv7/scale"
type: "Scale"
bottom: "conv7"
top: "conv7"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv7/relu"
type: "ReLU"
bottom: "conv7"
top: "conv7"
}
layer {
name: "conv8/dw"
type: "DepthwiseConvolution"
bottom: "conv7"
top: "conv8/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv8/dw/bn"
type: "BatchNorm"
bottom: "conv8/dw"
top: "conv8/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv8/dw/scale"
type: "Scale"
bottom: "conv8/dw"
top: "conv8/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv8/dw/relu"
type: "ReLU"
bottom: "conv8/dw"
top: "conv8/dw"
}
layer {
name: "conv8"
type: "Convolution"
bottom: "conv8/dw"
top: "conv8"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv8/bn"
type: "BatchNorm"
bottom: "conv8"
top: "conv8"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv8/scale"
type: "Scale"
bottom: "conv8"
top: "conv8"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv8/relu"
type: "ReLU"
bottom: "conv8"
top: "conv8"
}
layer {
name: "conv9/dw"
type: "DepthwiseConvolution"
bottom: "conv8"
top: "conv9/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv9/dw/bn"
type: "BatchNorm"
bottom: "conv9/dw"
top: "conv9/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv9/dw/scale"
type: "Scale"
bottom: "conv9/dw"
top: "conv9/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv9/dw/relu"
type: "ReLU"
bottom: "conv9/dw"
top: "conv9/dw"
}
layer {
name: "conv9"
type: "Convolution"
bottom: "conv9/dw"
top: "conv9"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv9/bn"
type: "BatchNorm"
bottom: "conv9"
top: "conv9"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv9/scale"
type: "Scale"
bottom: "conv9"
top: "conv9"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv9/relu"
type: "ReLU"
bottom: "conv9"
top: "conv9"
}
layer {
name: "conv10/dw"
type: "DepthwiseConvolution"
bottom: "conv9"
top: "conv10/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv10/dw/bn"
type: "BatchNorm"
bottom: "conv10/dw"
top: "conv10/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv10/dw/scale"
type: "Scale"
bottom: "conv10/dw"
top: "conv10/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv10/dw/relu"
type: "ReLU"
bottom: "conv10/dw"
top: "conv10/dw"
}
layer {
name: "conv10"
type: "Convolution"
bottom: "conv10/dw"
top: "conv10"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv10/bn"
type: "BatchNorm"
bottom: "conv10"
top: "conv10"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv10/scale"
type: "Scale"
bottom: "conv10"
top: "conv10"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv10/relu"
type: "ReLU"
bottom: "conv10"
top: "conv10"
}
layer {
name: "conv11/dw"
type: "DepthwiseConvolution"
bottom: "conv10"
top: "conv11/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv11/dw/bn"
type: "BatchNorm"
bottom: "conv11/dw"
top: "conv11/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv11/dw/scale"
type: "Scale"
bottom: "conv11/dw"
top: "conv11/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv11/dw/relu"
type: "ReLU"
bottom: "conv11/dw"
top: "conv11/dw"
}
layer {
name: "conv11"
type: "Convolution"
bottom: "conv11/dw"
top: "conv11"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv11/bn"
type: "BatchNorm"
bottom: "conv11"
top: "conv11"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv11/scale"
type: "Scale"
bottom: "conv11"
top: "conv11"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv11/relu"
type: "ReLU"
bottom: "conv11"
top: "conv11"
}
layer {
name: "conv12/dw"
type: "DepthwiseConvolution"
bottom: "conv11"
top: "conv12/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
stride: 2
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv12/dw/bn"
type: "BatchNorm"
bottom: "conv12/dw"
top: "conv12/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv12/dw/scale"
type: "Scale"
bottom: "conv12/dw"
top: "conv12/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv12/dw/relu"
type: "ReLU"
bottom: "conv12/dw"
top: "conv12/dw"
}
layer {
name: "conv12"
type: "Convolution"
bottom: "conv12/dw"
top: "conv12"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv12/bn"
type: "BatchNorm"
bottom: "conv12"
top: "conv12"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv12/scale"
type: "Scale"
bottom: "conv12"
top: "conv12"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv12/relu"
type: "ReLU"
bottom: "conv12"
top: "conv12"
}
layer {
name: "conv13/dw"
type: "DepthwiseConvolution"
bottom: "conv12"
top: "conv13/dw"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 1
kernel_size: 3
group: 1024
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv13/dw/bn"
type: "BatchNorm"
bottom: "conv13/dw"
top: "conv13/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv13/dw/scale"
type: "Scale"
bottom: "conv13/dw"
top: "conv13/dw"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv13/dw/relu"
type: "ReLU"
bottom: "conv13/dw"
top: "conv13/dw"
}
layer {
name: "conv13"
type: "Convolution"
bottom: "conv13/dw"
top: "conv13"
param {
lr_mult: 0.1
decay_mult: 0.1
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv13/bn"
type: "BatchNorm"
bottom: "conv13"
top: "conv13"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv13/scale"
type: "Scale"
bottom: "conv13"
top: "conv13"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv13/relu"
type: "ReLU"
bottom: "conv13"
top: "conv13"
}
layer {
name: "conv15/dw"
type: "DepthwiseConvolution"
bottom: "conv13"
top: "conv15/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
pad: 1
kernel_size: 3
group: 1024
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv15/dw/bn"
type: "BatchNorm"
bottom: "conv15/dw"
top: "conv15/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv15/dw/scale"
type: "Scale"
bottom: "conv15/dw"
top: "conv15/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv15/dw/relu"
type: "ReLU"
bottom: "conv15/dw"
top: "conv15/dw"
}
layer {
name: "conv15"
type: "Convolution"
bottom: "conv15/dw"
top: "conv15"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 1024
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv15/bn"
type: "BatchNorm"
bottom: "conv15"
top: "conv15"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv15/scale"
type: "Scale"
bottom: "conv15"
top: "conv15"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv15/relu"
type: "ReLU"
bottom: "conv15"
top: "conv15"
}
layer {
name: "upsample"
type: "Deconvolution"
bottom: "conv15"
top: "upsample"
param { lr_mult: 1 decay_mult: 1 }
convolution_param {
num_output: 512
group: 512
kernel_size: 2 stride: 2 pad: 0
weight_filler: { type: "bilinear" }
bias_term: false
}
}
layer {
name: "conv16/dw"
type: "DepthwiseConvolution"
bottom: "upsample"
top: "conv16/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv16/dw/bn"
type: "BatchNorm"
bottom: "conv16/dw"
top: "conv16/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv16/dw/scale"
type: "Scale"
bottom: "conv16/dw"
top: "conv16/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv16/dw/relu"
type: "ReLU"
bottom: "conv16/dw"
top: "conv16/dw"
}
layer {
name: "conv16"
type: "Convolution"
bottom: "conv16/dw"
top: "conv16"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv16/bn"
type: "BatchNorm"
bottom: "conv16"
top: "conv16"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv16/scale"
type: "Scale"
bottom: "conv16"
top: "conv16"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv16/relu"
type: "ReLU"
bottom: "conv16"
top: "conv16"
}
layer {
name: "conv17/dw"
type: "DepthwiseConvolution"
bottom: "conv11"
top: "conv17/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv17/dw/bn"
type: "BatchNorm"
bottom: "conv17/dw"
top: "conv17/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv17/dw/scale"
type: "Scale"
bottom: "conv17/dw"
top: "conv17/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv17/dw/relu"
type: "ReLU"
bottom: "conv17/dw"
top: "conv17/dw"
}
layer {
name: "conv17"
type: "Convolution"
bottom: "conv17/dw"
top: "conv17"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv17/bn"
type: "BatchNorm"
bottom: "conv17"
top: "conv17"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv17/scale"
type: "Scale"
bottom: "conv17"
top: "conv17"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv17/relu"
type: "ReLU"
bottom: "conv17"
top: "conv17"
}
layer {
name: "conv17/sum"
type: "Eltwise"
bottom: "conv16"
bottom: "conv17"
top: "conv17/sum"
}
layer {
name: "conv18/dw"
type: "DepthwiseConvolution"
bottom: "conv17/sum"
top: "conv18/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
pad: 1
kernel_size: 3
group: 512
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv18/dw/bn"
type: "BatchNorm"
bottom: "conv18/dw"
top: "conv18/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv18/dw/scale"
type: "Scale"
bottom: "conv18/dw"
top: "conv18/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv18/dw/relu"
type: "ReLU"
bottom: "conv18/dw"
top: "conv18/dw"
}
layer {
name: "conv18"
type: "Convolution"
bottom: "conv18/dw"
top: "conv18"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv18/bn"
type: "BatchNorm"
bottom: "conv18"
top: "conv18"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv18/scale"
type: "Scale"
bottom: "conv18"
top: "conv18"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv18/relu"
type: "ReLU"
bottom: "conv18"
top: "conv18"
}
layer {
name: "upsample2"
type: "Deconvolution"
bottom: "conv18"
top: "upsample2"
param { lr_mult: 1 decay_mult: 1 }
convolution_param {
num_output: 256
group: 256
kernel_size: 2 stride: 2 pad: 0
weight_filler: { type: "bilinear" }
bias_term: false
}
}
layer {
name: "conv19/dw"
type: "DepthwiseConvolution"
bottom: "upsample2"
top: "conv19/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv19/dw/bn"
type: "BatchNorm"
bottom: "conv19/dw"
top: "conv19/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv19/dw/scale"
type: "Scale"
bottom: "conv19/dw"
top: "conv19/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv19/dw/relu"
type: "ReLU"
bottom: "conv19/dw"
top: "conv19/dw"
}
layer {
name: "conv19"
type: "Convolution"
bottom: "conv19/dw"
top: "conv19"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv19/bn"
type: "BatchNorm"
bottom: "conv19"
top: "conv19"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv19/scale"
type: "Scale"
bottom: "conv19"
top: "conv19"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv19/relu"
type: "ReLU"
bottom: "conv19"
top: "conv19"
}
layer {
name: "conv20/dw"
type: "DepthwiseConvolution"
bottom: "conv5"
top: "conv20/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv20/dw/bn"
type: "BatchNorm"
bottom: "conv20/dw"
top: "conv20/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv20/dw/scale"
type: "Scale"
bottom: "conv20/dw"
top: "conv20/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv20/dw/relu"
type: "ReLU"
bottom: "conv20/dw"
top: "conv20/dw"
}
layer {
name: "conv20"
type: "Convolution"
bottom: "conv20/dw"
top: "conv20"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv20/bn"
type: "BatchNorm"
bottom: "conv20"
top: "conv20"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv20/scale"
type: "Scale"
bottom: "conv20"
top: "conv20"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv20/relu"
type: "ReLU"
bottom: "conv20"
top: "conv20"
}
layer {
name: "conv20/sum"
type: "Eltwise"
bottom: "conv19"
bottom: "conv20"
top: "conv20/sum"
}
layer {
name: "conv21/dw"
type: "DepthwiseConvolution"
bottom: "conv20/sum"
top: "conv21/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv21/dw/bn"
type: "BatchNorm"
bottom: "conv21/dw"
top: "conv21/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv21/dw/scale"
type: "Scale"
bottom: "conv21/dw"
top: "conv21/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv21/dw/relu"
type: "ReLU"
bottom: "conv21/dw"
top: "conv21/dw"
}
layer {
name: "conv21"
type: "Convolution"
bottom: "conv21/dw"
top: "conv21"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 512
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv21/bn"
type: "BatchNorm"
bottom: "conv21"
top: "conv21"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv21/scale"
type: "Scale"
bottom: "conv21"
top: "conv21"
param {
lr_mult: 0.1
decay_mult: 0.0
}
param {
lr_mult: 0.2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv21/relu"
type: "ReLU"
bottom: "conv21"
top: "conv21"
}
layer {
name: "conv22"
type: "Convolution"
bottom: "conv15"
top: "conv22"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 18
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "conv23"
type: "Convolution"
bottom: "conv18"
top: "conv23"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 18
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "conv24"
type: "Convolution"
bottom: "conv21"
top: "conv24"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 18
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "detection_out"
type: "Yolov3DetectionOutput"
bottom: "conv22"
bottom: "conv23"
bottom: "conv24"
top: "detection_out"
yolov3_detection_output_param {
confidence_threshold: 0.3
nms_threshold: 0.45
num_classes: 1
#10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
biases: 4
biases: 7
biases: 6
biases: 13
biases: 8
biases: 21
biases: 18
biases: 16
biases: 12
biases: 33
biases: 20
biases: 47
biases: 30
biases: 71
biases: 46
biases: 112
biases: 78
biases: 193
mask:6
mask:7
mask:8
mask:3
mask:4
mask:5
mask:0
mask:1
mask:2
anchors_scale:32
anchors_scale:16
anchors_scale:8
mask_group_num:3
}
}
layer {
name: "conv25/dw"
type: "DepthwiseConvolution"
bottom: "conv20/sum"
top: "conv25/dw"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
pad: 1
kernel_size: 3
group: 256
engine: CAFFE
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv25/dw/bn"
type: "BatchNorm"
bottom: "conv25/dw"
top: "conv25/dw"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv25/dw/scale"
type: "Scale"
bottom: "conv25/dw"
top: "conv25/dw"
param {
lr_mult: 1
decay_mult: 0.0
}
param {
lr_mult: 2
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv25/dw/relu"
type: "ReLU"
bottom: "conv25/dw"
top: "conv25/dw"
}
layer {
name: "conv25"
type: "Convolution"
bottom: "conv25/dw"
top: "conv25"
param {
lr_mult: 1
decay_mult: 1
}
convolution_param {
num_output: 256
bias_term: false
kernel_size: 1
weight_filler {
type: "msra"
}
}
}
layer {
name: "conv25/bn"
type: "BatchNorm"
bottom: "conv25"
top: "conv25"
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
}
layer {
name: "conv25/scale"
type: "Scale"
bottom: "conv25"
top: "conv25"
param {
lr_mult: 1.0
decay_mult: 0.0
}
param {
lr_mult: 2.0
decay_mult: 0.0
}
scale_param {
filler {
value: 1
}
bias_term: true
bias_filler {
value: 0
}
}
}
layer {
name: "conv25/relu"
type: "ReLU"
bottom: "conv25"
top: "conv25"
}
layer {
name: "conv26"
type: "Convolution"
bottom: "conv25"
top: "conv26"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 3 # channel = class
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_filler {
value: 0
}
}
}
layer {
name: "sigmoid"
bottom: "conv26"
top: "sigmoid"
type: "Sigmoid"
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment