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@MarcoForte
Created July 5, 2017 16:15
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Just for quick visualisation with netscope
name: "RED-Net"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 256
input_dim: 256
# conv1
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "c1"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu1" type: "ReLU" bottom: "c1" top: "c1" }
# conv2
layer {
name: "conv2"
type: "Convolution"
bottom: "c1"
top: "c2"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu2" type: "ReLU" bottom: "c2" top: "c2" }
# conv3
layer {
name: "conv3"
type: "Convolution"
bottom: "c2"
top: "c3"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu3" type: "ReLU" bottom: "c3" top: "c3" }
# conv4
layer {
name: "conv4"
type: "Convolution"
bottom: "c3"
top: "c4"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu4" type: "ReLU" bottom: "c4" top: "c4" }
# conv5
layer {
name: "conv5"
type: "Convolution"
bottom: "c4"
top: "c5"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu5" type: "ReLU" bottom: "c5" top: "c5" }
# conv6
layer {
name: "conv6"
type: "Convolution"
bottom: "c5"
top: "c6"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu6" type: "ReLU" bottom: "c6" top: "c6" }
# conv7
layer {
name: "conv7"
type: "Convolution"
bottom: "c6"
top: "c7"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu7" type: "ReLU" bottom: "c7" top: "c7" }
# conv8
layer {
name: "conv8"
type: "Convolution"
bottom: "c7"
top: "c8"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu8" type: "ReLU" bottom: "c8" top: "c8" }
# conv9
layer {
name: "conv9"
type: "Convolution"
bottom: "c8"
top: "c9"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu9" type: "ReLU" bottom: "c9" top: "c9" }
# conv10
layer {
name: "conv10"
type: "Convolution"
bottom: "c9"
top: "c10"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu10" type: "ReLU" bottom: "c10" top: "c10" }
# conv11
layer {
name: "conv11"
type: "Convolution"
bottom: "c10"
top: "c11"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu11" type: "ReLU" bottom: "c11" top: "c11" }
# conv12
layer {
name: "conv12"
type: "Convolution"
bottom: "c11"
top: "c12"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu12" type: "ReLU" bottom: "c12" top: "c12" }
# conv13
layer {
name: "conv13"
type: "Convolution"
bottom: "c12"
top: "c13"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu13" type: "ReLU" bottom: "c13" top: "c13" }
# conv14
layer {
name: "conv14"
type: "Convolution"
bottom: "c13"
top: "c14"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu14" type: "ReLU" bottom: "c14" top: "c14" }
# conv15
layer {
name: "conv15"
type: "Convolution"
bottom: "c14"
top: "c15"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu15" type: "ReLU" bottom: "c15" top: "c15" }
# deconv1
layer {
name: "deconv1"
type: "Deconvolution"
bottom: "c15"
top: "d1"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu16" type: "ReLU" bottom: "d1" top: "d1" }
# residual1
layer {
name: "residual1"
type: "Eltwise"
bottom: "c14"
bottom: "d1"
top: "d1a"
}
layer { name: "relu17" type: "ReLU" bottom: "d1a" top: "d1a" }
# deconv2
layer {
name: "deconv2"
type: "Deconvolution"
bottom: "d1a"
top: "d2"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu18" type: "ReLU" bottom: "d2" top: "d2" }
# deconv3
layer {
name: "deconv3"
type: "Deconvolution"
bottom: "d2"
top: "d3"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu19" type: "ReLU" bottom: "d3" top: "d3" }
# residual2
layer {
name: "residual2"
type: "Eltwise"
bottom: "c12"
bottom: "d3"
top: "d3a"
}
layer { name: "relu20" type: "ReLU" bottom: "d3a" top: "d3a" }
# deconv4
layer {
name: "deconv4"
type: "Deconvolution"
bottom: "d3a"
top: "d4"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu21" type: "ReLU" bottom: "d4" top: "d4" }
# deconv5
layer {
name: "deconv5"
type: "Deconvolution"
bottom: "d4"
top: "d5"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu22" type: "ReLU" bottom: "d5" top: "d5" }
# residual3
layer {
name: "residual3"
type: "Eltwise"
bottom: "c10"
bottom: "d5"
top: "d5a"
}
layer { name: "relu23" type: "ReLU" bottom: "d5a" top: "d5a" }
# deconv6
layer {
name: "deconv6"
type: "Deconvolution"
bottom: "d5a"
top: "d6"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu24" type: "ReLU" bottom: "d6" top: "d6" }
# deconv7
layer {
name: "deconv7"
type: "Deconvolution"
bottom: "d6"
top: "d7"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu25" type: "ReLU" bottom: "d7" top: "d7" }
# residual4
layer {
name: "residual4"
type: "Eltwise"
bottom: "c8"
bottom: "d7"
top: "d7a"
}
layer { name: "relu26" type: "ReLU" bottom: "d7a" top: "d7a" }
# deconv8
layer {
name: "deconv8"
type: "Deconvolution"
bottom: "d7a"
top: "d8"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu27" type: "ReLU" bottom: "d8" top: "d8" }
# deconv9
layer {
name: "deconv9"
type: "Deconvolution"
bottom: "d8"
top: "d9"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu28" type: "ReLU" bottom: "d9" top: "d9" }
# residual5
layer {
name: "residual5"
type: "Eltwise"
bottom: "c6"
bottom: "d9"
top: "d9a"
}
layer { name: "relu29" type: "ReLU" bottom: "d9a" top: "d9a" }
# deconv10
layer {
name: "deconv10"
type: "Deconvolution"
bottom: "d9a"
top: "d10"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu30" type: "ReLU" bottom: "d10" top: "d10" }
# deconv11
layer {
name: "deconv11"
type: "Deconvolution"
bottom: "d10"
top: "d11"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu31" type: "ReLU" bottom: "d11" top: "d11" }
# residual6
layer {
name: "residual6"
type: "Eltwise"
bottom: "c4"
bottom: "d11"
top: "d11a"
}
layer { name: "relu32" type: "ReLU" bottom: "d11a" top: "d11a" }
# deconv12
layer {
name: "deconv12"
type: "Deconvolution"
bottom: "d11a"
top: "d12"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu33" type: "ReLU" bottom: "d12" top: "d12" }
# deconv13
layer {
name: "deconv13"
type: "Deconvolution"
bottom: "d12"
top: "d13"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu34" type: "ReLU" bottom: "d13" top: "d13" }
# residual7
layer {
name: "residual7"
type: "Eltwise"
bottom: "c2"
bottom: "d13"
top: "d13a"
}
layer { name: "relu35" type: "ReLU" bottom: "d13a" top: "d13a" }
# deconv14
layer {
name: "deconv14"
type: "Deconvolution"
bottom: "d13a"
top: "d14"
convolution_param { num_output: 128 kernel_size: 3 stride: 1 pad: 1 }
}
layer { name: "relu36" type: "ReLU" bottom: "d14" top: "d14" }
# deconv15
layer {
name: "deconv15"
type: "Deconvolution"
bottom: "d14"
top: "d15"
convolution_param { num_output: 3 kernel_size: 3 stride: 1 pad: 1 }
}
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