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name: "autocolorize"
input: "data"
input_dim: 1
input_dim: 1
input_dim: 514
input_dim: 514
layer {
name: "data"
type: "Input"
top: "data"
input_param {
shape: {
dim: 1
dim: 1
dim: 514
dim: 514
}
}
}
layer {
bottom: "data"
top: "conv1_1"
name: "conv1_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv1_1"
type: "ReLU"
bottom: "conv1_1"
top: "conv1_1"
}
layer {
bottom: "conv1_1"
top: "conv1_2"
name: "conv1_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv1_2"
type: "ReLU"
bottom: "conv1_2"
top: "conv1_2"
}
layer {
bottom: "conv1_2"
top: "pool1"
name: "pool1"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
bottom: "pool1"
top: "conv2_1"
name: "conv2_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv2_1"
type: "ReLU"
bottom: "conv2_1"
top: "conv2_1"
}
layer {
bottom: "conv2_1"
top: "conv2_2"
name: "conv2_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv2_2"
type: "ReLU"
bottom: "conv2_2"
top: "conv2_2"
}
layer {
bottom: "conv2_2"
top: "pool2"
name: "pool2"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
bottom: "pool2"
top: "conv3_1"
name: "conv3_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv3_1"
type: "ReLU"
bottom: "conv3_1"
top: "conv3_1"
}
layer {
bottom: "conv3_1"
top: "conv3_2"
name: "conv3_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv3_2"
type: "ReLU"
bottom: "conv3_2"
top: "conv3_2"
}
layer {
bottom: "conv3_2"
top: "conv3_3"
name: "conv3_3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv3_3"
type: "ReLU"
bottom: "conv3_3"
top: "conv3_3"
}
layer {
bottom: "conv3_3"
top: "pool3"
name: "pool3"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
bottom: "pool3"
top: "conv4_1"
name: "conv4_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv4_1"
type: "ReLU"
bottom: "conv4_1"
top: "conv4_1"
}
layer {
bottom: "conv4_1"
top: "conv4_2"
name: "conv4_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv4_2"
type: "ReLU"
bottom: "conv4_2"
top: "conv4_2"
}
layer {
bottom: "conv4_2"
top: "conv4_3"
name: "conv4_3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv4_3"
type: "ReLU"
bottom: "conv4_3"
top: "conv4_3"
}
layer {
bottom: "conv4_3"
top: "pool4"
name: "pool4"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
bottom: "pool4"
top: "conv5_1"
name: "conv5_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv5_1"
type: "ReLU"
bottom: "conv5_1"
top: "conv5_1"
}
layer {
bottom: "conv5_1"
top: "conv5_2"
name: "conv5_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv5_2"
type: "ReLU"
bottom: "conv5_2"
top: "conv5_2"
}
layer {
bottom: "conv5_2"
top: "conv5_3"
name: "conv5_3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 512
pad: 1
kernel_size: 3
}
}
layer {
name: "relu_conv5_3"
type: "ReLU"
bottom: "conv5_3"
top: "conv5_3"
}
layer {
bottom: "conv5_3"
top: "pool5"
name: "pool5"
type: "Pooling"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
bottom: "pool5"
top: "fc6"
name: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 4096
pad: 3
kernel_size: 7
}
}
layer {
name: "relu_fc6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "dropout_fc6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
bottom: "fc6"
top: "fc7"
name: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 4096
pad: 0
kernel_size: 1
}
}
layer {
name: "relu_fc7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "dropout_fc7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "data_full"
type: "Pooling"
bottom: "data" top: "data_full"
pooling_param {
kernel_size: 4 stride: 4
pool: AVE
pad: 0
}
}
layer {
name: "conv1_1_full"
type: "Pooling"
bottom: "conv1_1" top: "conv1_1_full"
pooling_param {
kernel_size: 4 stride: 4
pool: AVE
pad: 0
}
}
layer {
name: "conv1_2_full"
type: "Pooling"
bottom: "conv1_2" top: "conv1_2_full"
pooling_param {
kernel_size: 4 stride: 4
pool: AVE
pad: 0
}
}
layer {
name: "conv2_1_full"
type: "Pooling"
bottom: "conv2_1" top: "conv2_1_full"
pooling_param {
kernel_size: 2 stride: 2
pool: AVE
pad: 0
}
}
layer {
name: "conv2_2_full"
type: "Pooling"
bottom: "conv2_2" top: "conv2_2_full"
pooling_param {
kernel_size: 2 stride: 2
pool: AVE
pad: 0
}
}
# conv4_1 upsampling
layer {
name: "conv4_1_reshaped" type: "Reshape"
bottom: "conv4_1" top: "conv4_1_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "conv4_1_full_reshaped"
type: "Deconvolution"
bottom: "conv4_1_reshaped" top: "conv4_1_full_reshaped"
convolution_param {
kernel_size: 4 stride: 2
num_output: 1 group: 1
pad: 1
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "conv4_1_full" type: "Reshape"
bottom: "conv4_1_full_reshaped" top: "conv4_1_full"
reshape_param {
shape { dim: -1 dim: 512 }
axis: 0
num_axes: 2
}
}
# conv4_2 upsampling
layer {
name: "conv4_2_reshaped" type: "Reshape"
bottom: "conv4_2" top: "conv4_2_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "conv4_2_full_reshaped"
type: "Deconvolution"
bottom: "conv4_2_reshaped" top: "conv4_2_full_reshaped"
convolution_param {
kernel_size: 4 stride: 2
num_output: 1 group: 1
pad: 1
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "conv4_2_full" type: "Reshape"
bottom: "conv4_2_full_reshaped" top: "conv4_2_full"
reshape_param {
shape { dim: -1 dim: 512 }
axis: 0
num_axes: 2
}
}
# conv4_3 upsampling
layer {
name: "conv4_3_reshaped" type: "Reshape"
bottom: "conv4_3" top: "conv4_3_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "conv4_3_full_reshaped"
type: "Deconvolution"
bottom: "conv4_3_reshaped" top: "conv4_3_full_reshaped"
convolution_param {
kernel_size: 4 stride: 2
num_output: 1 group: 1
pad: 1
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "conv4_3_full" type: "Reshape"
bottom: "conv4_3_full_reshaped" top: "conv4_3_full"
reshape_param {
shape { dim: -1 dim: 512 }
axis: 0
num_axes: 2
}
}
# conv5_1 upsampling
layer {
name: "conv5_1_reshaped" type: "Reshape"
bottom: "conv5_1" top: "conv5_1_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "conv5_1_full_reshaped"
type: "Deconvolution"
bottom: "conv5_1_reshaped" top: "conv5_1_full_reshaped"
convolution_param {
kernel_size: 8 stride: 4
num_output: 1 group: 1
pad: 2
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "conv5_1_full" type: "Reshape"
bottom: "conv5_1_full_reshaped" top: "conv5_1_full"
reshape_param {
shape { dim: -1 dim: 512 }
axis: 0
num_axes: 2
}
}
# conv5_2 upsampling
layer {
name: "conv5_2_reshaped" type: "Reshape"
bottom: "conv5_2" top: "conv5_2_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "conv5_2_full_reshaped"
type: "Deconvolution"
bottom: "conv5_2_reshaped" top: "conv5_2_full_reshaped"
convolution_param {
kernel_size: 8 stride: 4
num_output: 1 group: 1
pad: 2
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "conv5_2_full" type: "Reshape"
bottom: "conv5_2_full_reshaped" top: "conv5_2_full"
reshape_param {
shape { dim: -1 dim: 512 }
axis: 0
num_axes: 2
}
}
# conv5_3 upsampling
layer {
name: "conv5_3_reshaped" type: "Reshape"
bottom: "conv5_3" top: "conv5_3_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "conv5_3_full_reshaped"
type: "Deconvolution"
bottom: "conv5_3_reshaped" top: "conv5_3_full_reshaped"
convolution_param {
kernel_size: 8 stride: 4
num_output: 1 group: 1
pad: 2
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "conv5_3_full" type: "Reshape"
bottom: "conv5_3_full_reshaped" top: "conv5_3_full"
reshape_param {
shape { dim: -1 dim: 512 }
axis: 0
num_axes: 2
}
}
# fc6 upsampling
layer {
name: "fc6_reshaped" type: "Reshape"
bottom: "fc6" top: "fc6_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "fc6_full_reshaped"
type: "Deconvolution"
bottom: "fc6_reshaped" top: "fc6_full_reshaped"
convolution_param {
kernel_size: 16 stride: 8
num_output: 1 group: 1
pad: 4
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "fc6_full" type: "Reshape"
bottom: "fc6_full_reshaped" top: "fc6_full"
reshape_param {
shape { dim: -1 dim: 4096 }
axis: 0
num_axes: 2
}
}
# fc7 upsampling
layer {
name: "fc7_reshaped" type: "Reshape"
bottom: "fc7" top: "fc7_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "fc7_full_reshaped"
type: "Deconvolution"
bottom: "fc7_reshaped" top: "fc7_full_reshaped"
convolution_param {
kernel_size: 16 stride: 8
num_output: 1 group: 1
pad: 4
weight_filler: { type: "bilinear" } bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "fc7_full" type: "Reshape"
bottom: "fc7_full_reshaped" top: "fc7_full"
reshape_param {
shape { dim: -1 dim: 4096 }
axis: 0
num_axes: 2
}
}
layer {
name: "dense_hypercolumn"
type: "Concat"
bottom: "data_full"
bottom: "conv1_1_full"
bottom: "conv1_2_full"
bottom: "conv2_1_full"
bottom: "conv2_2_full"
bottom: "conv3_1"
bottom: "conv3_2"
bottom: "conv3_3"
bottom: "conv4_1_full"
bottom: "conv4_2_full"
bottom: "conv4_3_full"
bottom: "conv5_1_full"
bottom: "conv5_2_full"
bottom: "conv5_3_full"
bottom: "fc6_full"
bottom: "fc7_full"
top: "dense_hypercolumn"
concat_param {
axis: 1
}
}
layer {
bottom: "dense_hypercolumn"
top: "h_fc1"
name: "h_fc1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 1024
pad: 0
kernel_size: 1
}
}
layer {
name: "relu_h_fc1"
type: "ReLU"
bottom: "h_fc1"
top: "h_fc1"
}
layer {
bottom: "h_fc1"
top: "prediction_h"
name: "prediction_h"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
}
}
layer {
bottom: "h_fc1"
top: "prediction_c"
name: "prediction_c"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
type: "Convolution"
convolution_param {
num_output: 32
pad: 0
kernel_size: 1
}
}
layer {
name: "prediction_h_softmax"
type: "Softmax"
bottom: "prediction_h"
top: "prediction_h_softmax"
}
layer {
name: "prediction_c_softmax"
type: "Softmax"
bottom: "prediction_c"
top: "prediction_c_softmax"
}
# prediction_h upsample
layer {
name: "prediction_h_softmax_reshaped" type: "Reshape"
bottom: "prediction_h_softmax" top: "prediction_h_softmax_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "prediction_h_full_reshaped"
type: "Deconvolution"
bottom: "prediction_h_softmax_reshaped"
top: "prediction_h_full_reshaped"
convolution_param {
kernel_size: 8 stride: 4
num_output: 1 group: 1
pad: 2
weight_filler: { type: "bilinear" }
bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "prediction_h_full" type: "Reshape"
bottom: "prediction_h_full_reshaped" top: "prediction_h_full"
reshape_param {
shape { dim: -1 dim: 32 }
axis: 0
num_axes: 2
}
}
# prediction_c upsample
layer {
name: "prediction_c_softmax_reshaped" type: "Reshape"
bottom: "prediction_c_softmax" top: "prediction_c_softmax_reshaped"
reshape_param {
shape { dim: -1 dim: 1 }
axis: 0
num_axes: 2
}
}
layer {
name: "prediction_c_full_reshaped"
type: "Deconvolution"
bottom: "prediction_c_softmax_reshaped"
top: "prediction_c_full_reshaped"
convolution_param {
kernel_size: 8 stride: 4
num_output: 1 group: 1
pad: 2
weight_filler: { type: "bilinear" }
bias_term: false
}
param { lr_mult: 0 decay_mult: 0 }
}
layer {
name: "prediction_c_full" type: "Reshape"
bottom: "prediction_c_full_reshaped" top: "prediction_c_full"
reshape_param {
shape { dim: -1 dim: 32 }
axis: 0
num_axes: 2
}
}
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