| name: "LtoAB" |
|
|
| layer { |
| name: "data_l" |
| type: "Input" |
| top: "data_l" |
| input_param { |
| shape { dim: 1 dim: 1 dim: 224 dim: 224 } |
| } |
| } |
|
|
| # ***************** |
| # ***** conv1 ***** |
| # ***************** |
| layer { |
| name: "bw_conv1_1" |
| type: "Convolution" |
| bottom: "data_l" |
| top: "conv1_1" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 64 |
| pad: 1 |
| kernel_size: 3 |
| } |
| } |
| layer { |
| name: "relu1_1" |
| type: "ReLU" |
| bottom: "conv1_1" |
| top: "conv1_1" |
| } |
| layer { |
| name: "conv1_2" |
| type: "Convolution" |
| bottom: "conv1_1" |
| top: "conv1_2" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 64 |
| pad: 1 |
| kernel_size: 3 |
| stride: 2 |
| } |
| } |
| layer { |
| name: "relu1_2" |
| type: "ReLU" |
| bottom: "conv1_2" |
| top: "conv1_2" |
| } |
| layer { |
| name: "conv1_2norm" |
| type: "BatchNorm" |
| bottom: "conv1_2" |
| top: "conv1_2norm" |
| batch_norm_param{ } |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| } |
| # ***************** |
| # ***** conv2 ***** |
| # ***************** |
| layer { |
| name: "conv2_1" |
| type: "Convolution" |
| # bottom: "conv1_2" |
| bottom: "conv1_2norm" |
| # bottom: "pool1" |
| top: "conv2_1" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 128 |
| pad: 1 |
| kernel_size: 3 |
| } |
| } |
| layer { |
| name: "relu2_1" |
| type: "ReLU" |
| bottom: "conv2_1" |
| top: "conv2_1" |
| } |
| layer { |
| name: "conv2_2" |
| type: "Convolution" |
| bottom: "conv2_1" |
| top: "conv2_2" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 128 |
| pad: 1 |
| kernel_size: 3 |
| stride: 2 |
| } |
| } |
| layer { |
| name: "relu2_2" |
| type: "ReLU" |
| bottom: "conv2_2" |
| top: "conv2_2" |
| } |
| layer { |
| name: "conv2_2norm" |
| type: "BatchNorm" |
| bottom: "conv2_2" |
| top: "conv2_2norm" |
| batch_norm_param{ } |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| } |
| # ***************** |
| # ***** conv3 ***** |
| # ***************** |
| layer { |
| name: "conv3_1" |
| type: "Convolution" |
| # bottom: "conv2_2" |
| bottom: "conv2_2norm" |
| # bottom: "pool2" |
| top: "conv3_1" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 256 |
| pad: 1 |
| kernel_size: 3 |
| } |
| } |
| layer { |
| name: "relu3_1" |
| type: "ReLU" |
| bottom: "conv3_1" |
| top: "conv3_1" |
| } |
| layer { |
| name: "conv3_2" |
| type: "Convolution" |
| bottom: "conv3_1" |
| top: "conv3_2" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 256 |
| pad: 1 |
| kernel_size: 3 |
| } |
| } |
| layer { |
| name: "relu3_2" |
| type: "ReLU" |
| bottom: "conv3_2" |
| top: "conv3_2" |
| } |
| layer { |
| name: "conv3_3" |
| type: "Convolution" |
| bottom: "conv3_2" |
| top: "conv3_3" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 256 |
| pad: 1 |
| kernel_size: 3 |
| stride: 2 |
| } |
| } |
| layer { |
| name: "relu3_3" |
| type: "ReLU" |
| bottom: "conv3_3" |
| top: "conv3_3" |
| } |
| layer { |
| name: "conv3_3norm" |
| type: "BatchNorm" |
| bottom: "conv3_3" |
| top: "conv3_3norm" |
| batch_norm_param{ } |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| } |
| # ***************** |
| # ***** conv4 ***** |
| # ***************** |
| layer { |
| name: "conv4_1" |
| type: "Convolution" |
| # bottom: "conv3_3" |
| bottom: "conv3_3norm" |
| # bottom: "pool3" |
| top: "conv4_1" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| stride: 1 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu4_1" |
| type: "ReLU" |
| bottom: "conv4_1" |
| top: "conv4_1" |
| } |
| layer { |
| name: "conv4_2" |
| type: "Convolution" |
| bottom: "conv4_1" |
| top: "conv4_2" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| stride: 1 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu4_2" |
| type: "ReLU" |
| bottom: "conv4_2" |
| top: "conv4_2" |
| } |
| layer { |
| name: "conv4_3" |
| type: "Convolution" |
| bottom: "conv4_2" |
| top: "conv4_3" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| stride: 1 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu4_3" |
| type: "ReLU" |
| bottom: "conv4_3" |
| top: "conv4_3" |
| } |
| layer { |
| name: "conv4_3norm" |
| type: "BatchNorm" |
| bottom: "conv4_3" |
| top: "conv4_3norm" |
| batch_norm_param{ } |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| } |
| # ***************** |
| # ***** conv5 ***** |
| # ***************** |
| layer { |
| name: "conv5_1" |
| type: "Convolution" |
| # bottom: "conv4_3" |
| bottom: "conv4_3norm" |
| # bottom: "pool4" |
| top: "conv5_1" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| stride: 1 |
| pad: 2 |
| dilation: 2 |
| } |
| } |
| layer { |
| name: "relu5_1" |
| type: "ReLU" |
| bottom: "conv5_1" |
| top: "conv5_1" |
| } |
| layer { |
| name: "conv5_2" |
| type: "Convolution" |
| bottom: "conv5_1" |
| top: "conv5_2" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| stride: 1 |
| pad: 2 |
| dilation: 2 |
| } |
| } |
| layer { |
| name: "relu5_2" |
| type: "ReLU" |
| bottom: "conv5_2" |
| top: "conv5_2" |
| } |
| layer { |
| name: "conv5_3" |
| type: "Convolution" |
| bottom: "conv5_2" |
| top: "conv5_3" |
| # param {lr_mult: 0 decay_mult: 0} |
| # param {lr_mult: 0 decay_mult: 0} |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| stride: 1 |
| pad: 2 |
| dilation: 2 |
| } |
| } |
| layer { |
| name: "relu5_3" |
| type: "ReLU" |
| bottom: "conv5_3" |
| top: "conv5_3" |
| } |
| layer { |
| name: "conv5_3norm" |
| type: "BatchNorm" |
| bottom: "conv5_3" |
| top: "conv5_3norm" |
| batch_norm_param{ } |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| } |
| # ***************** |
| # ***** conv6 ***** |
| # ***************** |
| layer { |
| name: "conv6_1" |
| type: "Convolution" |
| bottom: "conv5_3norm" |
| top: "conv6_1" |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| pad: 2 |
| dilation: 2 |
| } |
| } |
| layer { |
| name: "relu6_1" |
| type: "ReLU" |
| bottom: "conv6_1" |
| top: "conv6_1" |
| } |
| layer { |
| name: "conv6_2" |
| type: "Convolution" |
| bottom: "conv6_1" |
| top: "conv6_2" |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| pad: 2 |
| dilation: 2 |
| } |
| } |
| layer { |
| name: "relu6_2" |
| type: "ReLU" |
| bottom: "conv6_2" |
| top: "conv6_2" |
| } |
| layer { |
| name: "conv6_3" |
| type: "Convolution" |
| bottom: "conv6_2" |
| top: "conv6_3" |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| pad: 2 |
| dilation: 2 |
| } |
| } |
| layer { |
| name: "relu6_3" |
| type: "ReLU" |
| bottom: "conv6_3" |
| top: "conv6_3" |
| } |
| layer { |
| name: "conv6_3norm" |
| type: "BatchNorm" |
| bottom: "conv6_3" |
| top: "conv6_3norm" |
| batch_norm_param{ } |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| } |
| # ***************** |
| # ***** conv7 ***** |
| # ***************** |
| layer { |
| name: "conv7_1" |
| type: "Convolution" |
| bottom: "conv6_3norm" |
| top: "conv7_1" |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu7_1" |
| type: "ReLU" |
| bottom: "conv7_1" |
| top: "conv7_1" |
| } |
| layer { |
| name: "conv7_2" |
| type: "Convolution" |
| bottom: "conv7_1" |
| top: "conv7_2" |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu7_2" |
| type: "ReLU" |
| bottom: "conv7_2" |
| top: "conv7_2" |
| } |
| layer { |
| name: "conv7_3" |
| type: "Convolution" |
| bottom: "conv7_2" |
| top: "conv7_3" |
| convolution_param { |
| num_output: 512 |
| kernel_size: 3 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu7_3" |
| type: "ReLU" |
| bottom: "conv7_3" |
| top: "conv7_3" |
| } |
| layer { |
| name: "conv7_3norm" |
| type: "BatchNorm" |
| bottom: "conv7_3" |
| top: "conv7_3norm" |
| batch_norm_param{ } |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| param {lr_mult: 0 decay_mult: 0} |
| } |
| # ***************** |
| # ***** conv8 ***** |
| # ***************** |
| layer { |
| name: "conv8_1" |
| type: "Deconvolution" |
| bottom: "conv7_3norm" |
| top: "conv8_1" |
| convolution_param { |
| num_output: 256 |
| kernel_size: 4 |
| pad: 1 |
| dilation: 1 |
| stride: 2 |
| } |
| } |
| layer { |
| name: "relu8_1" |
| type: "ReLU" |
| bottom: "conv8_1" |
| top: "conv8_1" |
| } |
| layer { |
| name: "conv8_2" |
| type: "Convolution" |
| bottom: "conv8_1" |
| top: "conv8_2" |
| convolution_param { |
| num_output: 256 |
| kernel_size: 3 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu8_2" |
| type: "ReLU" |
| bottom: "conv8_2" |
| top: "conv8_2" |
| } |
| layer { |
| name: "conv8_3" |
| type: "Convolution" |
| bottom: "conv8_2" |
| top: "conv8_3" |
| convolution_param { |
| num_output: 256 |
| kernel_size: 3 |
| pad: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "relu8_3" |
| type: "ReLU" |
| bottom: "conv8_3" |
| top: "conv8_3" |
| } |
| # ******************* |
| # ***** Softmax ***** |
| # ******************* |
| layer { |
| name: "conv8_313" |
| type: "Convolution" |
| bottom: "conv8_3" |
| top: "conv8_313" |
| convolution_param { |
| num_output: 313 |
| kernel_size: 1 |
| stride: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "conv8_313_rh" |
| type: "Scale" |
| bottom: "conv8_313" |
| top: "conv8_313_rh" |
| scale_param { |
| bias_term: false |
| filler { type: 'constant' value: 2.606 } |
| } |
| } |
| layer { |
| name: "class8_313_rh" |
| type: "Softmax" |
| bottom: "conv8_313_rh" |
| top: "class8_313_rh" |
| } |
| # ******************** |
| # ***** Decoding ***** |
| # ******************** |
| layer { |
| name: "class8_ab" |
| type: "Convolution" |
| bottom: "class8_313_rh" |
| top: "class8_ab" |
| convolution_param { |
| num_output: 2 |
| kernel_size: 1 |
| stride: 1 |
| dilation: 1 |
| } |
| } |
| layer { |
| name: "Silence" |
| type: "Silence" |
| bottom: "class8_ab" |
| } |
