-
-
Save pyrolitic/ad2eed3fb83a5f4c200bb99cfa364590 to your computer and use it in GitHub Desktop.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: "DBN_DBN_128x128_train" | |
| layer { | |
| name: "data" | |
| type: "ImageData" | |
| top: "data" | |
| transform_param { | |
| scale: 0.00390625 | |
| crop_size: 128 | |
| } | |
| image_data_param { | |
| source: "/home/caffemaker/caffe/dataset/blurred+sharp/train.txt" | |
| batch_size: 48 | |
| new_height: 128 | |
| new_width: 128 | |
| label: false | |
| } | |
| } | |
| layer { | |
| name: "label" | |
| type: "ImageData" | |
| top: "label" | |
| transform_param { | |
| scale: 0.00390625 | |
| crop_size: 128 | |
| } | |
| image_data_param { | |
| source: "/home/caffemaker/caffe/dataset/blurred+sharp/train_label.txt" | |
| batch_size: 48 | |
| new_height: 128 | |
| new_width: 128 | |
| label: false | |
| } | |
| } | |
| layer { | |
| name: "flat_conv0" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "flat_conv0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 2 | |
| kernel_size: 5 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv0_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv0" | |
| top: "flat_conv0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv0_scale" | |
| type: "Scale" | |
| bottom: "flat_conv0" | |
| top: "flat_conv0" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv0_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv0" | |
| top: "flat_conv0" | |
| } | |
| layer { | |
| name: "down_conv1" | |
| type: "Convolution" | |
| bottom: "flat_conv0" | |
| top: "down_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "down_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "down_conv1" | |
| top: "down_conv1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "down_conv1_scale" | |
| type: "Scale" | |
| bottom: "down_conv1" | |
| top: "down_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "down_conv1_relu" | |
| type: "ReLU" | |
| bottom: "down_conv1" | |
| top: "down_conv1" | |
| } | |
| layer { | |
| name: "flat_conv1_1" | |
| type: "Convolution" | |
| bottom: "down_conv1" | |
| top: "flat_conv1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv1_1_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv1_1" | |
| top: "flat_conv1_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv1_1_scale" | |
| type: "Scale" | |
| bottom: "flat_conv1_1" | |
| top: "flat_conv1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv1_1_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv1_1" | |
| top: "flat_conv1_1" | |
| } | |
| layer { | |
| name: "flat_conv1_2" | |
| type: "Convolution" | |
| bottom: "flat_conv1_1" | |
| top: "flat_conv1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv1_2_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv1_2" | |
| top: "flat_conv1_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv1_2_scale" | |
| type: "Scale" | |
| bottom: "flat_conv1_2" | |
| top: "flat_conv1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv1_2_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv1_2" | |
| top: "flat_conv1_2" | |
| } | |
| layer { | |
| name: "down_conv2" | |
| type: "Convolution" | |
| bottom: "flat_conv1_2" | |
| top: "down_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "down_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "down_conv2" | |
| top: "down_conv2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "down_conv2_scale" | |
| type: "Scale" | |
| bottom: "down_conv2" | |
| top: "down_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "down_conv2_relu" | |
| type: "ReLU" | |
| bottom: "down_conv2" | |
| top: "down_conv2" | |
| } | |
| layer { | |
| name: "flat_conv2_1" | |
| type: "Convolution" | |
| bottom: "down_conv2" | |
| top: "flat_conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_1_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv2_1" | |
| top: "flat_conv2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_1_scale" | |
| type: "Scale" | |
| bottom: "flat_conv2_1" | |
| top: "flat_conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_1_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv2_1" | |
| top: "flat_conv2_1" | |
| } | |
| layer { | |
| name: "flat_conv2_2" | |
| type: "Convolution" | |
| bottom: "flat_conv2_1" | |
| top: "flat_conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_2_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv2_2" | |
| top: "flat_conv2_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_2_scale" | |
| type: "Scale" | |
| bottom: "flat_conv2_2" | |
| top: "flat_conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_2_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv2_2" | |
| top: "flat_conv2_2" | |
| } | |
| layer { | |
| name: "flat_conv2_3" | |
| type: "Convolution" | |
| bottom: "flat_conv2_2" | |
| top: "flat_conv2_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_3_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv2_3" | |
| top: "flat_conv2_3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_3_scale" | |
| type: "Scale" | |
| bottom: "flat_conv2_3" | |
| top: "flat_conv2_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv2_3_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv2_3" | |
| top: "flat_conv2_3" | |
| } | |
| layer { | |
| name: "down_conv3" | |
| type: "Convolution" | |
| bottom: "flat_conv2_3" | |
| top: "down_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "down_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "down_conv3" | |
| top: "down_conv3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "down_conv3_scale" | |
| type: "Scale" | |
| bottom: "down_conv3" | |
| top: "down_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "down_conv3_relu" | |
| type: "ReLU" | |
| bottom: "down_conv3" | |
| top: "down_conv3" | |
| } | |
| layer { | |
| name: "flat_conv3_1" | |
| type: "Convolution" | |
| bottom: "down_conv3" | |
| top: "flat_conv3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_1_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv3_1" | |
| top: "flat_conv3_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_1_scale" | |
| type: "Scale" | |
| bottom: "flat_conv3_1" | |
| top: "flat_conv3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_1_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv3_1" | |
| top: "flat_conv3_1" | |
| } | |
| layer { | |
| name: "flat_conv3_2" | |
| type: "Convolution" | |
| bottom: "flat_conv3_1" | |
| top: "flat_conv3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_2_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv3_2" | |
| top: "flat_conv3_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_2_scale" | |
| type: "Scale" | |
| bottom: "flat_conv3_2" | |
| top: "flat_conv3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_2_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv3_2" | |
| top: "flat_conv3_2" | |
| } | |
| layer { | |
| name: "flat_conv3_3" | |
| type: "Convolution" | |
| bottom: "flat_conv3_2" | |
| top: "flat_conv3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_3_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv3_3" | |
| top: "flat_conv3_3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_3_scale" | |
| type: "Scale" | |
| bottom: "flat_conv3_3" | |
| top: "flat_conv3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv3_3_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv3_3" | |
| top: "flat_conv3_3" | |
| } | |
| layer { | |
| name: "up_conv1" | |
| type: "Deconvolution" | |
| bottom: "flat_conv3_3" | |
| top: "up_conv1" | |
| param { | |
| lr_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "up_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "up_conv1" | |
| top: "up_conv1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "up_conv1_scale" | |
| type: "Scale" | |
| bottom: "up_conv1" | |
| top: "up_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "up1_eltwise" | |
| type: "Eltwise" | |
| bottom: "up_conv1" | |
| bottom: "flat_conv2_3" | |
| top: "up1_eltwise" | |
| } | |
| layer { | |
| name: "up1_eltwise_relu" | |
| type: "ReLU" | |
| bottom: "up1_eltwise" | |
| top: "up1_eltwise" | |
| } | |
| layer { | |
| name: "flat_conv4_1" | |
| type: "Convolution" | |
| bottom: "up1_eltwise" | |
| top: "flat_conv4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_1_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv4_1" | |
| top: "flat_conv4_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_1_scale" | |
| type: "Scale" | |
| bottom: "flat_conv4_1" | |
| top: "flat_conv4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_1_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv4_1" | |
| top: "flat_conv4_1" | |
| } | |
| layer { | |
| name: "flat_conv4_2" | |
| type: "Convolution" | |
| bottom: "flat_conv4_1" | |
| top: "flat_conv4_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_2_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv4_2" | |
| top: "flat_conv4_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_2_scale" | |
| type: "Scale" | |
| bottom: "flat_conv4_2" | |
| top: "flat_conv4_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_2_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv4_2" | |
| top: "flat_conv4_2" | |
| } | |
| layer { | |
| name: "flat_conv4_3" | |
| type: "Convolution" | |
| bottom: "flat_conv4_2" | |
| top: "flat_conv4_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_3_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv4_3" | |
| top: "flat_conv4_3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_3_scale" | |
| type: "Scale" | |
| bottom: "flat_conv4_3" | |
| top: "flat_conv4_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv4_3_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv4_3" | |
| top: "flat_conv4_3" | |
| } | |
| layer { | |
| name: "up_conv2" | |
| type: "Deconvolution" | |
| bottom: "flat_conv4_3" | |
| top: "up_conv2" | |
| param { | |
| lr_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "up_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "up_conv2" | |
| top: "up_conv2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "up_conv2_scale" | |
| type: "Scale" | |
| bottom: "up_conv2" | |
| top: "up_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "up2_eltwise" | |
| type: "Eltwise" | |
| bottom: "up_conv2" | |
| bottom: "flat_conv1_2" | |
| top: "up2_eltwise" | |
| } | |
| layer { | |
| name: "up2_eltwise_relu" | |
| type: "ReLU" | |
| bottom: "up2_eltwise" | |
| top: "up2_eltwise" | |
| } | |
| layer { | |
| name: "flat_conv5_1" | |
| type: "Convolution" | |
| bottom: "up2_eltwise" | |
| top: "flat_conv5_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv5_1_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv5_1" | |
| top: "flat_conv5_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv5_1_scale" | |
| type: "Scale" | |
| bottom: "flat_conv5_1" | |
| top: "flat_conv5_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv5_1_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv5_1" | |
| top: "flat_conv5_1" | |
| } | |
| layer { | |
| name: "flat_conv5_2" | |
| type: "Convolution" | |
| bottom: "flat_conv5_1" | |
| top: "flat_conv5_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv5_2_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv5_2" | |
| top: "flat_conv5_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv5_2_scale" | |
| type: "Scale" | |
| bottom: "flat_conv5_2" | |
| top: "flat_conv5_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv5_2_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv5_2" | |
| top: "flat_conv5_2" | |
| } | |
| layer { | |
| name: "up_conv3" | |
| type: "Deconvolution" | |
| bottom: "flat_conv5_2" | |
| top: "up_conv3" | |
| param { | |
| lr_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 4 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "up_conv3_bn" | |
| type: "BatchNorm" | |
| bottom: "up_conv3" | |
| top: "up_conv3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "up_conv3_scale" | |
| type: "Scale" | |
| bottom: "up_conv3" | |
| top: "up_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "up3_eltwise" | |
| type: "Eltwise" | |
| bottom: "up_conv3" | |
| bottom: "flat_conv0" | |
| top: "up3_eltwise" | |
| } | |
| layer { | |
| name: "up3_eltwise_relu" | |
| type: "ReLU" | |
| bottom: "up3_eltwise" | |
| top: "up3_eltwise" | |
| } | |
| layer { | |
| name: "flat_conv6_1" | |
| type: "Convolution" | |
| bottom: "up3_eltwise" | |
| top: "flat_conv6_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv6_1_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv6_1" | |
| top: "flat_conv6_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv6_1_scale" | |
| type: "Scale" | |
| bottom: "flat_conv6_1" | |
| top: "flat_conv6_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv6_1_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv6_1" | |
| top: "flat_conv6_1" | |
| } | |
| layer { | |
| name: "flat_conv6_2" | |
| type: "Convolution" | |
| bottom: "flat_conv6_1" | |
| top: "flat_conv6_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 3 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv6_2_bn" | |
| type: "BatchNorm" | |
| bottom: "flat_conv6_2" | |
| top: "flat_conv6_2" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| eps: 0.001 | |
| } | |
| } | |
| layer { | |
| name: "flat_conv6_2_scale" | |
| type: "Scale" | |
| bottom: "flat_conv6_2" | |
| top: "flat_conv6_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| filler { | |
| type: "constant" | |
| value: 1.0 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "flat_conv6_2_relu" | |
| type: "ReLU" | |
| bottom: "flat_conv6_2" | |
| top: "flat_conv6_2" | |
| } | |
| layer { | |
| name: "loss" | |
| type: "EuclideanLoss" | |
| bottom: "flat_conv6_2" | |
| bottom: "label" | |
| top: "loss" | |
| } | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment