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Open Source Computer Vision Library
https://opencv.org/
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503 lines
6.7 KiB
503 lines
6.7 KiB
8 years ago
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#
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# This prototxt is based on voc-fcn32s/val.prototxt file from
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# https://github.com/shelhamer/fcn.berkeleyvision.org, which is distributed under
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# Caffe (BSD) license:
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# http://caffe.berkeleyvision.org/model_zoo.html#bvlc-model-license
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#
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name: "voc-fcn32s"
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input: "data"
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input_dim: 1
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input_dim: 3
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input_dim: 500
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input_dim: 500
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layer {
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name: "conv1_1"
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type: "Convolution"
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bottom: "data"
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top: "conv1_1"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 64
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pad: 100
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "relu1_1"
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type: "ReLU"
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bottom: "conv1_1"
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top: "conv1_1"
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}
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layer {
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name: "conv1_2"
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type: "Convolution"
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bottom: "conv1_1"
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top: "conv1_2"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 64
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pad: 1
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "relu1_2"
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type: "ReLU"
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bottom: "conv1_2"
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top: "conv1_2"
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}
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layer {
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name: "pool1"
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type: "Pooling"
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bottom: "conv1_2"
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top: "pool1"
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pooling_param {
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pool: MAX
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kernel_size: 2
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stride: 2
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}
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}
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layer {
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name: "conv2_1"
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type: "Convolution"
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bottom: "pool1"
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top: "conv2_1"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 128
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pad: 1
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "relu2_1"
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type: "ReLU"
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bottom: "conv2_1"
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top: "conv2_1"
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}
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layer {
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name: "conv2_2"
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|
type: "Convolution"
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bottom: "conv2_1"
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top: "conv2_2"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 128
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pad: 1
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "relu2_2"
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type: "ReLU"
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bottom: "conv2_2"
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top: "conv2_2"
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}
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layer {
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name: "pool2"
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type: "Pooling"
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bottom: "conv2_2"
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top: "pool2"
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pooling_param {
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pool: MAX
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kernel_size: 2
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stride: 2
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}
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}
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layer {
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name: "conv3_1"
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type: "Convolution"
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bottom: "pool2"
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top: "conv3_1"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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|
decay_mult: 0
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}
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|
convolution_param {
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num_output: 256
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pad: 1
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kernel_size: 3
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|
stride: 1
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}
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}
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layer {
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name: "relu3_1"
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type: "ReLU"
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bottom: "conv3_1"
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top: "conv3_1"
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}
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layer {
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name: "conv3_2"
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|
type: "Convolution"
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|
bottom: "conv3_1"
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|
top: "conv3_2"
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|
param {
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|
lr_mult: 1
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|
decay_mult: 1
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}
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|
param {
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|
lr_mult: 2
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|
decay_mult: 0
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|
}
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|
convolution_param {
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|
num_output: 256
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pad: 1
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kernel_size: 3
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|
stride: 1
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}
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}
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|
layer {
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name: "relu3_2"
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type: "ReLU"
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bottom: "conv3_2"
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top: "conv3_2"
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}
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layer {
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name: "conv3_3"
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type: "Convolution"
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bottom: "conv3_2"
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top: "conv3_3"
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param {
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|
lr_mult: 1
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|
decay_mult: 1
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}
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|
param {
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|
lr_mult: 2
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|
decay_mult: 0
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}
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|
convolution_param {
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|
num_output: 256
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pad: 1
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kernel_size: 3
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|
stride: 1
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}
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}
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layer {
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name: "relu3_3"
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type: "ReLU"
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bottom: "conv3_3"
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top: "conv3_3"
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}
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layer {
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name: "pool3"
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type: "Pooling"
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bottom: "conv3_3"
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top: "pool3"
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pooling_param {
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pool: MAX
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kernel_size: 2
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stride: 2
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}
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}
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layer {
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name: "conv4_1"
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type: "Convolution"
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bottom: "pool3"
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top: "conv4_1"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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|
decay_mult: 0
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}
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|
convolution_param {
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num_output: 512
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pad: 1
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "relu4_1"
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type: "ReLU"
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bottom: "conv4_1"
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top: "conv4_1"
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}
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layer {
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name: "conv4_2"
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|
type: "Convolution"
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bottom: "conv4_1"
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top: "conv4_2"
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|
param {
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|
lr_mult: 1
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|
decay_mult: 1
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}
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|
param {
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|
lr_mult: 2
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|
decay_mult: 0
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}
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|
convolution_param {
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num_output: 512
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pad: 1
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "relu4_2"
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|
type: "ReLU"
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bottom: "conv4_2"
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top: "conv4_2"
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}
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|
layer {
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name: "conv4_3"
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|
type: "Convolution"
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|
bottom: "conv4_2"
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top: "conv4_3"
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|
param {
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||
|
lr_mult: 1
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|
decay_mult: 1
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}
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|
param {
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|
lr_mult: 2
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|
decay_mult: 0
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}
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|
convolution_param {
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|
num_output: 512
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|
pad: 1
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "relu4_3"
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|
type: "ReLU"
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bottom: "conv4_3"
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top: "conv4_3"
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}
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layer {
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name: "pool4"
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|
type: "Pooling"
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|
bottom: "conv4_3"
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top: "pool4"
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|
pooling_param {
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||
|
pool: MAX
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|
kernel_size: 2
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|
stride: 2
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}
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}
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layer {
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name: "conv5_1"
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|
type: "Convolution"
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|
bottom: "pool4"
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top: "conv5_1"
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|
param {
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lr_mult: 1
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decay_mult: 1
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}
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|
param {
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|
lr_mult: 2
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|
decay_mult: 0
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}
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|
convolution_param {
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|
num_output: 512
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pad: 1
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kernel_size: 3
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|
stride: 1
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}
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}
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layer {
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name: "relu5_1"
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type: "ReLU"
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bottom: "conv5_1"
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top: "conv5_1"
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}
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layer {
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name: "conv5_2"
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|
type: "Convolution"
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bottom: "conv5_1"
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top: "conv5_2"
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|
param {
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|
lr_mult: 1
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|
decay_mult: 1
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}
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|
param {
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lr_mult: 2
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decay_mult: 0
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}
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|
convolution_param {
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|
num_output: 512
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pad: 1
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kernel_size: 3
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|
stride: 1
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}
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}
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layer {
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name: "relu5_2"
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type: "ReLU"
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bottom: "conv5_2"
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top: "conv5_2"
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}
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layer {
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name: "conv5_3"
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type: "Convolution"
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bottom: "conv5_2"
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top: "conv5_3"
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param {
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|
lr_mult: 1
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decay_mult: 1
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}
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param {
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|
lr_mult: 2
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|
decay_mult: 0
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}
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||
|
convolution_param {
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||
|
num_output: 512
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pad: 1
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kernel_size: 3
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|
stride: 1
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}
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}
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layer {
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name: "relu5_3"
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|
type: "ReLU"
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bottom: "conv5_3"
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top: "conv5_3"
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}
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|
layer {
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|
name: "pool5"
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|
type: "Pooling"
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|
bottom: "conv5_3"
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|
top: "pool5"
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|
pooling_param {
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||
|
pool: MAX
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|
kernel_size: 2
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stride: 2
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}
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}
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layer {
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name: "fc6"
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type: "Convolution"
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bottom: "pool5"
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|
top: "fc6"
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param {
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|
lr_mult: 1
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decay_mult: 1
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}
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|
param {
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|
lr_mult: 2
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|
decay_mult: 0
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||
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}
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||
|
convolution_param {
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||
|
num_output: 4096
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|
pad: 0
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kernel_size: 7
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stride: 1
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}
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}
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layer {
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name: "relu6"
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type: "ReLU"
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bottom: "fc6"
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top: "fc6"
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}
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|
layer {
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name: "fc7"
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|
type: "Convolution"
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|
bottom: "fc6"
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|
top: "fc7"
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||
|
param {
|
||
|
lr_mult: 1
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||
|
decay_mult: 1
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||
|
}
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||
|
param {
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||
|
lr_mult: 2
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||
|
decay_mult: 0
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||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 4096
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||
|
pad: 0
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||
|
kernel_size: 1
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||
|
stride: 1
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||
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}
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||
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}
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||
|
layer {
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||
|
name: "relu7"
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||
|
type: "ReLU"
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||
|
bottom: "fc7"
|
||
|
top: "fc7"
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||
|
}
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|
layer {
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||
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name: "score_fr"
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||
|
type: "Convolution"
|
||
|
bottom: "fc7"
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||
|
top: "score_fr"
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||
|
param {
|
||
|
lr_mult: 1
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||
|
decay_mult: 1
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||
|
}
|
||
|
param {
|
||
|
lr_mult: 2
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||
|
decay_mult: 0
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||
|
}
|
||
|
convolution_param {
|
||
|
num_output: 21
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|
pad: 0
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|
kernel_size: 1
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}
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}
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|
layer {
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||
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name: "upscore"
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||
|
type: "Deconvolution"
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||
|
bottom: "score_fr"
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||
|
top: "upscore"
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||
|
param {
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||
|
lr_mult: 0
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|
}
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||
|
convolution_param {
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||
|
num_output: 21
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|
bias_term: false
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||
|
kernel_size: 64
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|
stride: 32
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|
}
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||
|
}
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|
layer {
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||
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name: "score"
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||
|
type: "Crop"
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||
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bottom: "upscore"
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||
|
bottom: "data"
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||
|
top: "score"
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||
|
crop_param {
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||
|
axis: 2
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||
|
offset: 19
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||
|
}
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||
|
}
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