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モデル更新

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lltcggie 2016-07-03 17:11:57 +09:00
parent 48b8cab0c0
commit ebc71b317c
5 changed files with 572 additions and 5 deletions
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5
bin/models/upconv_7_anime_style_art_rgb/info.json
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@ -1 +1,4 @@
{"name":"UpRGB","arch_name":"upconv_7","channels":3,"resize":true,"scale_factor":2,"offset":12} {"name":"UpRGB","arch_name":"upconv_7","has_noise_scale":true,"channels":3,
"scale_factor":2,"offset":14,
"scale_factor_noise":1,"offset_noise":7
}

188
bin/models/upconv_7_anime_style_art_rgb/noise1_scale2.0x_model.prototxt Normal file
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@ -0,0 +1,188 @@
name: "upconv_7"
layer {
name: "input"
type: "Input"
top: "input"
input_param { shape: { dim: 1 dim: 3 dim: 142 dim: 142 } }
}
layer {
name: "conv1_layer"
type: "Convolution"
bottom: "input"
top: "conv1"
convolution_param {
num_output: 16
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv1_relu_layer"
type: "ReLU"
bottom: "conv1"
top: "conv1"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv2_layer"
type: "Convolution"
bottom: "conv1"
top: "conv2"
convolution_param {
num_output: 32
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv2_relu_layer"
type: "ReLU"
bottom: "conv2"
top: "conv2"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv3_layer"
type: "Convolution"
bottom: "conv2"
top: "conv3"
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv3_relu_layer"
type: "ReLU"
bottom: "conv3"
top: "conv3"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv4_layer"
type: "Convolution"
bottom: "conv3"
top: "conv4"
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv4_relu_layer"
type: "ReLU"
bottom: "conv4"
top: "conv4"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv5_layer"
type: "Convolution"
bottom: "conv4"
top: "conv5"
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv5_relu_layer"
type: "ReLU"
bottom: "conv5"
top: "conv5"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv6_layer"
type: "Convolution"
bottom: "conv5"
top: "conv6"
convolution_param {
num_output: 256
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv6_relu_layer"
type: "ReLU"
bottom: "conv6"
top: "conv6"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv7_layer"
type: "Deconvolution"
bottom: "conv6"
top: "conv7"
convolution_param {
num_output: 3
kernel_size: 4
stride: 2
pad: 3
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "target"
type: "MemoryData"
top: "target"
top: "dummy_label2"
memory_data_param {
batch_size: 1
channels: 3
height: 142
width: 142
}
include: { phase: TRAIN }
}
layer {
name: "loss"
type: "EuclideanLoss"
bottom: "conv7"
bottom: "target"
top: "loss"
include: { phase: TRAIN }
}

188
bin/models/upconv_7_anime_style_art_rgb/noise2_scale2.0x_model.prototxt Normal file
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@ -0,0 +1,188 @@
name: "upconv_7"
layer {
name: "input"
type: "Input"
top: "input"
input_param { shape: { dim: 1 dim: 3 dim: 142 dim: 142 } }
}
layer {
name: "conv1_layer"
type: "Convolution"
bottom: "input"
top: "conv1"
convolution_param {
num_output: 16
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv1_relu_layer"
type: "ReLU"
bottom: "conv1"
top: "conv1"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv2_layer"
type: "Convolution"
bottom: "conv1"
top: "conv2"
convolution_param {
num_output: 32
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv2_relu_layer"
type: "ReLU"
bottom: "conv2"
top: "conv2"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv3_layer"
type: "Convolution"
bottom: "conv2"
top: "conv3"
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv3_relu_layer"
type: "ReLU"
bottom: "conv3"
top: "conv3"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv4_layer"
type: "Convolution"
bottom: "conv3"
top: "conv4"
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv4_relu_layer"
type: "ReLU"
bottom: "conv4"
top: "conv4"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv5_layer"
type: "Convolution"
bottom: "conv4"
top: "conv5"
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv5_relu_layer"
type: "ReLU"
bottom: "conv5"
top: "conv5"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv6_layer"
type: "Convolution"
bottom: "conv5"
top: "conv6"
convolution_param {
num_output: 256
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv6_relu_layer"
type: "ReLU"
bottom: "conv6"
top: "conv6"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv7_layer"
type: "Deconvolution"
bottom: "conv6"
top: "conv7"
convolution_param {
num_output: 3
kernel_size: 4
stride: 2
pad: 3
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "target"
type: "MemoryData"
top: "target"
top: "dummy_label2"
memory_data_param {
batch_size: 1
channels: 3
height: 142
width: 142
}
include: { phase: TRAIN }
}
layer {
name: "loss"
type: "EuclideanLoss"
bottom: "conv7"
bottom: "target"
top: "loss"
include: { phase: TRAIN }
}

188
bin/models/upconv_7_anime_style_art_rgb/noise3_scale2.0x_model.prototxt Normal file
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@ -0,0 +1,188 @@
name: "upconv_7"
layer {
name: "input"
type: "Input"
top: "input"
input_param { shape: { dim: 1 dim: 3 dim: 142 dim: 142 } }
}
layer {
name: "conv1_layer"
type: "Convolution"
bottom: "input"
top: "conv1"
convolution_param {
num_output: 16
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv1_relu_layer"
type: "ReLU"
bottom: "conv1"
top: "conv1"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv2_layer"
type: "Convolution"
bottom: "conv1"
top: "conv2"
convolution_param {
num_output: 32
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv2_relu_layer"
type: "ReLU"
bottom: "conv2"
top: "conv2"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv3_layer"
type: "Convolution"
bottom: "conv2"
top: "conv3"
convolution_param {
num_output: 64
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv3_relu_layer"
type: "ReLU"
bottom: "conv3"
top: "conv3"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv4_layer"
type: "Convolution"
bottom: "conv3"
top: "conv4"
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv4_relu_layer"
type: "ReLU"
bottom: "conv4"
top: "conv4"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv5_layer"
type: "Convolution"
bottom: "conv4"
top: "conv5"
convolution_param {
num_output: 128
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv5_relu_layer"
type: "ReLU"
bottom: "conv5"
top: "conv5"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv6_layer"
type: "Convolution"
bottom: "conv5"
top: "conv6"
convolution_param {
num_output: 256
kernel_size: 3
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "conv6_relu_layer"
type: "ReLU"
bottom: "conv6"
top: "conv6"
relu_param {
negative_slope: 0.1
}
}
layer {
name: "conv7_layer"
type: "Deconvolution"
bottom: "conv6"
top: "conv7"
convolution_param {
num_output: 3
kernel_size: 4
stride: 2
pad: 3
weight_filler {
type: "gaussian"
std: 0.01
}
}
}
layer {
name: "target"
type: "MemoryData"
top: "target"
top: "dummy_label2"
memory_data_param {
batch_size: 1
channels: 3
height: 142
width: 142
}
include: { phase: TRAIN }
}
layer {
name: "loss"
type: "EuclideanLoss"
bottom: "conv7"
bottom: "target"
top: "loss"
include: { phase: TRAIN }
}

8
bin/models/upconv_7_anime_style_art_rgb/scale2.0x_model.prototxt
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@ -11,7 +11,7 @@ layer {
bottom: "input" bottom: "input"
top: "conv1" top: "conv1"
convolution_param { convolution_param {
num_output: 32 num_output: 16
kernel_size: 3 kernel_size: 3
stride: 1 stride: 1
weight_filler { weight_filler {
@ -83,7 +83,7 @@ layer {
bottom: "conv3" bottom: "conv3"
top: "conv4" top: "conv4"
convolution_param { convolution_param {
num_output: 64 num_output: 128
kernel_size: 3 kernel_size: 3
stride: 1 stride: 1
weight_filler { weight_filler {
@ -131,7 +131,7 @@ layer {
bottom: "conv5" bottom: "conv5"
top: "conv6" top: "conv6"
convolution_param { convolution_param {
num_output: 128 num_output: 256
kernel_size: 3 kernel_size: 3
stride: 1 stride: 1
weight_filler { weight_filler {
@ -158,7 +158,7 @@ layer {
num_output: 3 num_output: 3
kernel_size: 4 kernel_size: 4
stride: 2 stride: 2
pad: 1 pad: 3
weight_filler { weight_filler {
type: "gaussian" type: "gaussian"
std: 0.01 std: 0.01