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pre-res200-cysu.prototxt
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| name: "ResNet_200" | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| top: 'gt_boxes' | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: true | |
| crop_size: 224 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| force_color: true | |
| } | |
| data_param { | |
| source: "examples/imagenet/ilsvrc12_train_lmdb" | |
| batch_size: 32 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mirror: false | |
| crop_size: 224 | |
| mean_value: 104 | |
| mean_value: 117 | |
| mean_value: 123 | |
| force_color: true | |
| } | |
| data_param { | |
| source: "examples/imagenet/ilsvrc12_val_lmdb" | |
| batch_size: 25 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "conv1_scale" | |
| type: "Scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2_res1_proj" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv2_res1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res1_conv1" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv2_res1_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res1_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res1_conv1" | |
| top: "conv2_res1_conv1" | |
| } | |
| layer { | |
| name: "conv2_res1_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv2_res1_conv1" | |
| top: "conv2_res1_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res1_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res1_conv1" | |
| top: "conv2_res1_conv1" | |
| } | |
| layer { | |
| name: "conv2_res1_conv2" | |
| type: "Convolution" | |
| bottom: "conv2_res1_conv1" | |
| top: "conv2_res1_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res1_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res1_conv2" | |
| top: "conv2_res1_conv2" | |
| } | |
| layer { | |
| name: "conv2_res1_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv2_res1_conv2" | |
| top: "conv2_res1_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res1_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res1_conv2" | |
| top: "conv2_res1_conv2" | |
| } | |
| layer { | |
| name: "conv2_res1_conv3" | |
| type: "Convolution" | |
| bottom: "conv2_res1_conv2" | |
| top: "conv2_res1_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res1" | |
| type: "Eltwise" | |
| bottom: "conv2_res1_proj" | |
| bottom: "conv2_res1_conv3" | |
| top: "conv2_res1" | |
| } | |
| layer { | |
| name: "conv2_res2_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res1" | |
| top: "conv2_res2_pre" | |
| } | |
| layer { | |
| name: "conv2_res2_pre_scale" | |
| type: "Scale" | |
| bottom: "conv2_res2_pre" | |
| top: "conv2_res2_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res2_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res2_pre" | |
| top: "conv2_res2_pre" | |
| } | |
| layer { | |
| name: "conv2_res2_conv1" | |
| type: "Convolution" | |
| bottom: "conv2_res2_pre" | |
| top: "conv2_res2_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res2_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res2_conv1" | |
| top: "conv2_res2_conv1" | |
| } | |
| layer { | |
| name: "conv2_res2_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv2_res2_conv1" | |
| top: "conv2_res2_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res2_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res2_conv1" | |
| top: "conv2_res2_conv1" | |
| } | |
| layer { | |
| name: "conv2_res2_conv2" | |
| type: "Convolution" | |
| bottom: "conv2_res2_conv1" | |
| top: "conv2_res2_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res2_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res2_conv2" | |
| top: "conv2_res2_conv2" | |
| } | |
| layer { | |
| name: "conv2_res2_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv2_res2_conv2" | |
| top: "conv2_res2_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res2_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res2_conv2" | |
| top: "conv2_res2_conv2" | |
| } | |
| layer { | |
| name: "conv2_res2_conv3" | |
| type: "Convolution" | |
| bottom: "conv2_res2_conv2" | |
| top: "conv2_res2_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res2" | |
| type: "Eltwise" | |
| bottom: "conv2_res1" | |
| bottom: "conv2_res2_conv3" | |
| top: "conv2_res2" | |
| } | |
| layer { | |
| name: "conv2_res3_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res2" | |
| top: "conv2_res3_pre" | |
| } | |
| layer { | |
| name: "conv2_res3_pre_scale" | |
| type: "Scale" | |
| bottom: "conv2_res3_pre" | |
| top: "conv2_res3_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res3_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res3_pre" | |
| top: "conv2_res3_pre" | |
| } | |
| layer { | |
| name: "conv2_res3_conv1" | |
| type: "Convolution" | |
| bottom: "conv2_res3_pre" | |
| top: "conv2_res3_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res3_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res3_conv1" | |
| top: "conv2_res3_conv1" | |
| } | |
| layer { | |
| name: "conv2_res3_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv2_res3_conv1" | |
| top: "conv2_res3_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res3_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res3_conv1" | |
| top: "conv2_res3_conv1" | |
| } | |
| layer { | |
| name: "conv2_res3_conv2" | |
| type: "Convolution" | |
| bottom: "conv2_res3_conv1" | |
| top: "conv2_res3_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res3_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res3_conv2" | |
| top: "conv2_res3_conv2" | |
| } | |
| layer { | |
| name: "conv2_res3_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv2_res3_conv2" | |
| top: "conv2_res3_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res3_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv2_res3_conv2" | |
| top: "conv2_res3_conv2" | |
| } | |
| layer { | |
| name: "conv2_res3_conv3" | |
| type: "Convolution" | |
| bottom: "conv2_res3_conv2" | |
| top: "conv2_res3_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_res3" | |
| type: "Eltwise" | |
| bottom: "conv2_res2" | |
| bottom: "conv2_res3_conv3" | |
| top: "conv2_res3" | |
| } | |
| layer { | |
| name: "conv3_res1_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_res3" | |
| top: "conv3_res1_pre" | |
| } | |
| layer { | |
| name: "conv3_res1_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res1_pre" | |
| top: "conv3_res1_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res1_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res1_pre" | |
| top: "conv3_res1_pre" | |
| } | |
| layer { | |
| name: "conv3_res1_proj" | |
| type: "Convolution" | |
| bottom: "conv3_res1_pre" | |
| top: "conv3_res1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res1_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res1_pre" | |
| top: "conv3_res1_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res1_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res1_conv1" | |
| top: "conv3_res1_conv1" | |
| } | |
| layer { | |
| name: "conv3_res1_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res1_conv1" | |
| top: "conv3_res1_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res1_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res1_conv1" | |
| top: "conv3_res1_conv1" | |
| } | |
| layer { | |
| name: "conv3_res1_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res1_conv1" | |
| top: "conv3_res1_conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res1_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res1_conv2" | |
| top: "conv3_res1_conv2" | |
| } | |
| layer { | |
| name: "conv3_res1_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res1_conv2" | |
| top: "conv3_res1_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res1_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res1_conv2" | |
| top: "conv3_res1_conv2" | |
| } | |
| layer { | |
| name: "conv3_res1_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res1_conv2" | |
| top: "conv3_res1_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res1" | |
| type: "Eltwise" | |
| bottom: "conv3_res1_proj" | |
| bottom: "conv3_res1_conv3" | |
| top: "conv3_res1" | |
| } | |
| layer { | |
| name: "conv3_res2_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res1" | |
| top: "conv3_res2_pre" | |
| } | |
| layer { | |
| name: "conv3_res2_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res2_pre" | |
| top: "conv3_res2_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res2_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res2_pre" | |
| top: "conv3_res2_pre" | |
| } | |
| layer { | |
| name: "conv3_res2_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res2_pre" | |
| top: "conv3_res2_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res2_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res2_conv1" | |
| top: "conv3_res2_conv1" | |
| } | |
| layer { | |
| name: "conv3_res2_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res2_conv1" | |
| top: "conv3_res2_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res2_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res2_conv1" | |
| top: "conv3_res2_conv1" | |
| } | |
| layer { | |
| name: "conv3_res2_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res2_conv1" | |
| top: "conv3_res2_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res2_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res2_conv2" | |
| top: "conv3_res2_conv2" | |
| } | |
| layer { | |
| name: "conv3_res2_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res2_conv2" | |
| top: "conv3_res2_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res2_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res2_conv2" | |
| top: "conv3_res2_conv2" | |
| } | |
| layer { | |
| name: "conv3_res2_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res2_conv2" | |
| top: "conv3_res2_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res2" | |
| type: "Eltwise" | |
| bottom: "conv3_res1" | |
| bottom: "conv3_res2_conv3" | |
| top: "conv3_res2" | |
| } | |
| layer { | |
| name: "conv3_res3_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res2" | |
| top: "conv3_res3_pre" | |
| } | |
| layer { | |
| name: "conv3_res3_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res3_pre" | |
| top: "conv3_res3_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res3_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res3_pre" | |
| top: "conv3_res3_pre" | |
| } | |
| layer { | |
| name: "conv3_res3_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res3_pre" | |
| top: "conv3_res3_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res3_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res3_conv1" | |
| top: "conv3_res3_conv1" | |
| } | |
| layer { | |
| name: "conv3_res3_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res3_conv1" | |
| top: "conv3_res3_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res3_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res3_conv1" | |
| top: "conv3_res3_conv1" | |
| } | |
| layer { | |
| name: "conv3_res3_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res3_conv1" | |
| top: "conv3_res3_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res3_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res3_conv2" | |
| top: "conv3_res3_conv2" | |
| } | |
| layer { | |
| name: "conv3_res3_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res3_conv2" | |
| top: "conv3_res3_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res3_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res3_conv2" | |
| top: "conv3_res3_conv2" | |
| } | |
| layer { | |
| name: "conv3_res3_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res3_conv2" | |
| top: "conv3_res3_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res3" | |
| type: "Eltwise" | |
| bottom: "conv3_res2" | |
| bottom: "conv3_res3_conv3" | |
| top: "conv3_res3" | |
| } | |
| layer { | |
| name: "conv3_res4_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res3" | |
| top: "conv3_res4_pre" | |
| } | |
| layer { | |
| name: "conv3_res4_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res4_pre" | |
| top: "conv3_res4_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res4_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res4_pre" | |
| top: "conv3_res4_pre" | |
| } | |
| layer { | |
| name: "conv3_res4_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res4_pre" | |
| top: "conv3_res4_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res4_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res4_conv1" | |
| top: "conv3_res4_conv1" | |
| } | |
| layer { | |
| name: "conv3_res4_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res4_conv1" | |
| top: "conv3_res4_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res4_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res4_conv1" | |
| top: "conv3_res4_conv1" | |
| } | |
| layer { | |
| name: "conv3_res4_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res4_conv1" | |
| top: "conv3_res4_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res4_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res4_conv2" | |
| top: "conv3_res4_conv2" | |
| } | |
| layer { | |
| name: "conv3_res4_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res4_conv2" | |
| top: "conv3_res4_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res4_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res4_conv2" | |
| top: "conv3_res4_conv2" | |
| } | |
| layer { | |
| name: "conv3_res4_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res4_conv2" | |
| top: "conv3_res4_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res4" | |
| type: "Eltwise" | |
| bottom: "conv3_res3" | |
| bottom: "conv3_res4_conv3" | |
| top: "conv3_res4" | |
| } | |
| layer { | |
| name: "conv3_res5_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res4" | |
| top: "conv3_res5_pre" | |
| } | |
| layer { | |
| name: "conv3_res5_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res5_pre" | |
| top: "conv3_res5_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res5_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res5_pre" | |
| top: "conv3_res5_pre" | |
| } | |
| layer { | |
| name: "conv3_res5_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res5_pre" | |
| top: "conv3_res5_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res5_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res5_conv1" | |
| top: "conv3_res5_conv1" | |
| } | |
| layer { | |
| name: "conv3_res5_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res5_conv1" | |
| top: "conv3_res5_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res5_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res5_conv1" | |
| top: "conv3_res5_conv1" | |
| } | |
| layer { | |
| name: "conv3_res5_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res5_conv1" | |
| top: "conv3_res5_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res5_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res5_conv2" | |
| top: "conv3_res5_conv2" | |
| } | |
| layer { | |
| name: "conv3_res5_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res5_conv2" | |
| top: "conv3_res5_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res5_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res5_conv2" | |
| top: "conv3_res5_conv2" | |
| } | |
| layer { | |
| name: "conv3_res5_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res5_conv2" | |
| top: "conv3_res5_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res5" | |
| type: "Eltwise" | |
| bottom: "conv3_res4" | |
| bottom: "conv3_res5_conv3" | |
| top: "conv3_res5" | |
| } | |
| layer { | |
| name: "conv3_res6_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res5" | |
| top: "conv3_res6_pre" | |
| } | |
| layer { | |
| name: "conv3_res6_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res6_pre" | |
| top: "conv3_res6_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res6_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res6_pre" | |
| top: "conv3_res6_pre" | |
| } | |
| layer { | |
| name: "conv3_res6_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res6_pre" | |
| top: "conv3_res6_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res6_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res6_conv1" | |
| top: "conv3_res6_conv1" | |
| } | |
| layer { | |
| name: "conv3_res6_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res6_conv1" | |
| top: "conv3_res6_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res6_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res6_conv1" | |
| top: "conv3_res6_conv1" | |
| } | |
| layer { | |
| name: "conv3_res6_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res6_conv1" | |
| top: "conv3_res6_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res6_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res6_conv2" | |
| top: "conv3_res6_conv2" | |
| } | |
| layer { | |
| name: "conv3_res6_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res6_conv2" | |
| top: "conv3_res6_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res6_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res6_conv2" | |
| top: "conv3_res6_conv2" | |
| } | |
| layer { | |
| name: "conv3_res6_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res6_conv2" | |
| top: "conv3_res6_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res6" | |
| type: "Eltwise" | |
| bottom: "conv3_res5" | |
| bottom: "conv3_res6_conv3" | |
| top: "conv3_res6" | |
| } | |
| layer { | |
| name: "conv3_res7_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res6" | |
| top: "conv3_res7_pre" | |
| } | |
| layer { | |
| name: "conv3_res7_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res7_pre" | |
| top: "conv3_res7_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res7_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res7_pre" | |
| top: "conv3_res7_pre" | |
| } | |
| layer { | |
| name: "conv3_res7_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res7_pre" | |
| top: "conv3_res7_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res7_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res7_conv1" | |
| top: "conv3_res7_conv1" | |
| } | |
| layer { | |
| name: "conv3_res7_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res7_conv1" | |
| top: "conv3_res7_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res7_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res7_conv1" | |
| top: "conv3_res7_conv1" | |
| } | |
| layer { | |
| name: "conv3_res7_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res7_conv1" | |
| top: "conv3_res7_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res7_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res7_conv2" | |
| top: "conv3_res7_conv2" | |
| } | |
| layer { | |
| name: "conv3_res7_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res7_conv2" | |
| top: "conv3_res7_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res7_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res7_conv2" | |
| top: "conv3_res7_conv2" | |
| } | |
| layer { | |
| name: "conv3_res7_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res7_conv2" | |
| top: "conv3_res7_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res7" | |
| type: "Eltwise" | |
| bottom: "conv3_res6" | |
| bottom: "conv3_res7_conv3" | |
| top: "conv3_res7" | |
| } | |
| layer { | |
| name: "conv3_res8_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res7" | |
| top: "conv3_res8_pre" | |
| } | |
| layer { | |
| name: "conv3_res8_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res8_pre" | |
| top: "conv3_res8_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res8_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res8_pre" | |
| top: "conv3_res8_pre" | |
| } | |
| layer { | |
| name: "conv3_res8_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res8_pre" | |
| top: "conv3_res8_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res8_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res8_conv1" | |
| top: "conv3_res8_conv1" | |
| } | |
| layer { | |
| name: "conv3_res8_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res8_conv1" | |
| top: "conv3_res8_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res8_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res8_conv1" | |
| top: "conv3_res8_conv1" | |
| } | |
| layer { | |
| name: "conv3_res8_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res8_conv1" | |
| top: "conv3_res8_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res8_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res8_conv2" | |
| top: "conv3_res8_conv2" | |
| } | |
| layer { | |
| name: "conv3_res8_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res8_conv2" | |
| top: "conv3_res8_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res8_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res8_conv2" | |
| top: "conv3_res8_conv2" | |
| } | |
| layer { | |
| name: "conv3_res8_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res8_conv2" | |
| top: "conv3_res8_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res8" | |
| type: "Eltwise" | |
| bottom: "conv3_res7" | |
| bottom: "conv3_res8_conv3" | |
| top: "conv3_res8" | |
| } | |
| layer { | |
| name: "conv3_res9_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res8" | |
| top: "conv3_res9_pre" | |
| } | |
| layer { | |
| name: "conv3_res9_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res9_pre" | |
| top: "conv3_res9_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res9_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res9_pre" | |
| top: "conv3_res9_pre" | |
| } | |
| layer { | |
| name: "conv3_res9_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res9_pre" | |
| top: "conv3_res9_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res9_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res9_conv1" | |
| top: "conv3_res9_conv1" | |
| } | |
| layer { | |
| name: "conv3_res9_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res9_conv1" | |
| top: "conv3_res9_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res9_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res9_conv1" | |
| top: "conv3_res9_conv1" | |
| } | |
| layer { | |
| name: "conv3_res9_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res9_conv1" | |
| top: "conv3_res9_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res9_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res9_conv2" | |
| top: "conv3_res9_conv2" | |
| } | |
| layer { | |
| name: "conv3_res9_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res9_conv2" | |
| top: "conv3_res9_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res9_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res9_conv2" | |
| top: "conv3_res9_conv2" | |
| } | |
| layer { | |
| name: "conv3_res9_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res9_conv2" | |
| top: "conv3_res9_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res9" | |
| type: "Eltwise" | |
| bottom: "conv3_res8" | |
| bottom: "conv3_res9_conv3" | |
| top: "conv3_res9" | |
| } | |
| layer { | |
| name: "conv3_res10_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res9" | |
| top: "conv3_res10_pre" | |
| } | |
| layer { | |
| name: "conv3_res10_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res10_pre" | |
| top: "conv3_res10_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res10_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res10_pre" | |
| top: "conv3_res10_pre" | |
| } | |
| layer { | |
| name: "conv3_res10_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res10_pre" | |
| top: "conv3_res10_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res10_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res10_conv1" | |
| top: "conv3_res10_conv1" | |
| } | |
| layer { | |
| name: "conv3_res10_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res10_conv1" | |
| top: "conv3_res10_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res10_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res10_conv1" | |
| top: "conv3_res10_conv1" | |
| } | |
| layer { | |
| name: "conv3_res10_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res10_conv1" | |
| top: "conv3_res10_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res10_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res10_conv2" | |
| top: "conv3_res10_conv2" | |
| } | |
| layer { | |
| name: "conv3_res10_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res10_conv2" | |
| top: "conv3_res10_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res10_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res10_conv2" | |
| top: "conv3_res10_conv2" | |
| } | |
| layer { | |
| name: "conv3_res10_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res10_conv2" | |
| top: "conv3_res10_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res10" | |
| type: "Eltwise" | |
| bottom: "conv3_res9" | |
| bottom: "conv3_res10_conv3" | |
| top: "conv3_res10" | |
| } | |
| layer { | |
| name: "conv3_res11_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res10" | |
| top: "conv3_res11_pre" | |
| } | |
| layer { | |
| name: "conv3_res11_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res11_pre" | |
| top: "conv3_res11_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res11_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res11_pre" | |
| top: "conv3_res11_pre" | |
| } | |
| layer { | |
| name: "conv3_res11_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res11_pre" | |
| top: "conv3_res11_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res11_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res11_conv1" | |
| top: "conv3_res11_conv1" | |
| } | |
| layer { | |
| name: "conv3_res11_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res11_conv1" | |
| top: "conv3_res11_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res11_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res11_conv1" | |
| top: "conv3_res11_conv1" | |
| } | |
| layer { | |
| name: "conv3_res11_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res11_conv1" | |
| top: "conv3_res11_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res11_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res11_conv2" | |
| top: "conv3_res11_conv2" | |
| } | |
| layer { | |
| name: "conv3_res11_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res11_conv2" | |
| top: "conv3_res11_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res11_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res11_conv2" | |
| top: "conv3_res11_conv2" | |
| } | |
| layer { | |
| name: "conv3_res11_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res11_conv2" | |
| top: "conv3_res11_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res11" | |
| type: "Eltwise" | |
| bottom: "conv3_res10" | |
| bottom: "conv3_res11_conv3" | |
| top: "conv3_res11" | |
| } | |
| layer { | |
| name: "conv3_res12_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res11" | |
| top: "conv3_res12_pre" | |
| } | |
| layer { | |
| name: "conv3_res12_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res12_pre" | |
| top: "conv3_res12_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res12_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res12_pre" | |
| top: "conv3_res12_pre" | |
| } | |
| layer { | |
| name: "conv3_res12_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res12_pre" | |
| top: "conv3_res12_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res12_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res12_conv1" | |
| top: "conv3_res12_conv1" | |
| } | |
| layer { | |
| name: "conv3_res12_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res12_conv1" | |
| top: "conv3_res12_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res12_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res12_conv1" | |
| top: "conv3_res12_conv1" | |
| } | |
| layer { | |
| name: "conv3_res12_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res12_conv1" | |
| top: "conv3_res12_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res12_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res12_conv2" | |
| top: "conv3_res12_conv2" | |
| } | |
| layer { | |
| name: "conv3_res12_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res12_conv2" | |
| top: "conv3_res12_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res12_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res12_conv2" | |
| top: "conv3_res12_conv2" | |
| } | |
| layer { | |
| name: "conv3_res12_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res12_conv2" | |
| top: "conv3_res12_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res12" | |
| type: "Eltwise" | |
| bottom: "conv3_res11" | |
| bottom: "conv3_res12_conv3" | |
| top: "conv3_res12" | |
| } | |
| layer { | |
| name: "conv3_res13_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res12" | |
| top: "conv3_res13_pre" | |
| } | |
| layer { | |
| name: "conv3_res13_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res13_pre" | |
| top: "conv3_res13_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res13_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res13_pre" | |
| top: "conv3_res13_pre" | |
| } | |
| layer { | |
| name: "conv3_res13_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res13_pre" | |
| top: "conv3_res13_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res13_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res13_conv1" | |
| top: "conv3_res13_conv1" | |
| } | |
| layer { | |
| name: "conv3_res13_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res13_conv1" | |
| top: "conv3_res13_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res13_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res13_conv1" | |
| top: "conv3_res13_conv1" | |
| } | |
| layer { | |
| name: "conv3_res13_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res13_conv1" | |
| top: "conv3_res13_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res13_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res13_conv2" | |
| top: "conv3_res13_conv2" | |
| } | |
| layer { | |
| name: "conv3_res13_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res13_conv2" | |
| top: "conv3_res13_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res13_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res13_conv2" | |
| top: "conv3_res13_conv2" | |
| } | |
| layer { | |
| name: "conv3_res13_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res13_conv2" | |
| top: "conv3_res13_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res13" | |
| type: "Eltwise" | |
| bottom: "conv3_res12" | |
| bottom: "conv3_res13_conv3" | |
| top: "conv3_res13" | |
| } | |
| layer { | |
| name: "conv3_res14_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res13" | |
| top: "conv3_res14_pre" | |
| } | |
| layer { | |
| name: "conv3_res14_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res14_pre" | |
| top: "conv3_res14_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res14_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res14_pre" | |
| top: "conv3_res14_pre" | |
| } | |
| layer { | |
| name: "conv3_res14_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res14_pre" | |
| top: "conv3_res14_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res14_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res14_conv1" | |
| top: "conv3_res14_conv1" | |
| } | |
| layer { | |
| name: "conv3_res14_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res14_conv1" | |
| top: "conv3_res14_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res14_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res14_conv1" | |
| top: "conv3_res14_conv1" | |
| } | |
| layer { | |
| name: "conv3_res14_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res14_conv1" | |
| top: "conv3_res14_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res14_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res14_conv2" | |
| top: "conv3_res14_conv2" | |
| } | |
| layer { | |
| name: "conv3_res14_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res14_conv2" | |
| top: "conv3_res14_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res14_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res14_conv2" | |
| top: "conv3_res14_conv2" | |
| } | |
| layer { | |
| name: "conv3_res14_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res14_conv2" | |
| top: "conv3_res14_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res14" | |
| type: "Eltwise" | |
| bottom: "conv3_res13" | |
| bottom: "conv3_res14_conv3" | |
| top: "conv3_res14" | |
| } | |
| layer { | |
| name: "conv3_res15_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res14" | |
| top: "conv3_res15_pre" | |
| } | |
| layer { | |
| name: "conv3_res15_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res15_pre" | |
| top: "conv3_res15_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res15_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res15_pre" | |
| top: "conv3_res15_pre" | |
| } | |
| layer { | |
| name: "conv3_res15_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res15_pre" | |
| top: "conv3_res15_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res15_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res15_conv1" | |
| top: "conv3_res15_conv1" | |
| } | |
| layer { | |
| name: "conv3_res15_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res15_conv1" | |
| top: "conv3_res15_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res15_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res15_conv1" | |
| top: "conv3_res15_conv1" | |
| } | |
| layer { | |
| name: "conv3_res15_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res15_conv1" | |
| top: "conv3_res15_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res15_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res15_conv2" | |
| top: "conv3_res15_conv2" | |
| } | |
| layer { | |
| name: "conv3_res15_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res15_conv2" | |
| top: "conv3_res15_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res15_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res15_conv2" | |
| top: "conv3_res15_conv2" | |
| } | |
| layer { | |
| name: "conv3_res15_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res15_conv2" | |
| top: "conv3_res15_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res15" | |
| type: "Eltwise" | |
| bottom: "conv3_res14" | |
| bottom: "conv3_res15_conv3" | |
| top: "conv3_res15" | |
| } | |
| layer { | |
| name: "conv3_res16_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res15" | |
| top: "conv3_res16_pre" | |
| } | |
| layer { | |
| name: "conv3_res16_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res16_pre" | |
| top: "conv3_res16_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res16_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res16_pre" | |
| top: "conv3_res16_pre" | |
| } | |
| layer { | |
| name: "conv3_res16_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res16_pre" | |
| top: "conv3_res16_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res16_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res16_conv1" | |
| top: "conv3_res16_conv1" | |
| } | |
| layer { | |
| name: "conv3_res16_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res16_conv1" | |
| top: "conv3_res16_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res16_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res16_conv1" | |
| top: "conv3_res16_conv1" | |
| } | |
| layer { | |
| name: "conv3_res16_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res16_conv1" | |
| top: "conv3_res16_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res16_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res16_conv2" | |
| top: "conv3_res16_conv2" | |
| } | |
| layer { | |
| name: "conv3_res16_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res16_conv2" | |
| top: "conv3_res16_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res16_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res16_conv2" | |
| top: "conv3_res16_conv2" | |
| } | |
| layer { | |
| name: "conv3_res16_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res16_conv2" | |
| top: "conv3_res16_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res16" | |
| type: "Eltwise" | |
| bottom: "conv3_res15" | |
| bottom: "conv3_res16_conv3" | |
| top: "conv3_res16" | |
| } | |
| layer { | |
| name: "conv3_res17_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res16" | |
| top: "conv3_res17_pre" | |
| } | |
| layer { | |
| name: "conv3_res17_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res17_pre" | |
| top: "conv3_res17_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res17_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res17_pre" | |
| top: "conv3_res17_pre" | |
| } | |
| layer { | |
| name: "conv3_res17_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res17_pre" | |
| top: "conv3_res17_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res17_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res17_conv1" | |
| top: "conv3_res17_conv1" | |
| } | |
| layer { | |
| name: "conv3_res17_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res17_conv1" | |
| top: "conv3_res17_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res17_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res17_conv1" | |
| top: "conv3_res17_conv1" | |
| } | |
| layer { | |
| name: "conv3_res17_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res17_conv1" | |
| top: "conv3_res17_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res17_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res17_conv2" | |
| top: "conv3_res17_conv2" | |
| } | |
| layer { | |
| name: "conv3_res17_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res17_conv2" | |
| top: "conv3_res17_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res17_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res17_conv2" | |
| top: "conv3_res17_conv2" | |
| } | |
| layer { | |
| name: "conv3_res17_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res17_conv2" | |
| top: "conv3_res17_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res17" | |
| type: "Eltwise" | |
| bottom: "conv3_res16" | |
| bottom: "conv3_res17_conv3" | |
| top: "conv3_res17" | |
| } | |
| layer { | |
| name: "conv3_res18_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res17" | |
| top: "conv3_res18_pre" | |
| } | |
| layer { | |
| name: "conv3_res18_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res18_pre" | |
| top: "conv3_res18_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res18_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res18_pre" | |
| top: "conv3_res18_pre" | |
| } | |
| layer { | |
| name: "conv3_res18_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res18_pre" | |
| top: "conv3_res18_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res18_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res18_conv1" | |
| top: "conv3_res18_conv1" | |
| } | |
| layer { | |
| name: "conv3_res18_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res18_conv1" | |
| top: "conv3_res18_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res18_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res18_conv1" | |
| top: "conv3_res18_conv1" | |
| } | |
| layer { | |
| name: "conv3_res18_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res18_conv1" | |
| top: "conv3_res18_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res18_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res18_conv2" | |
| top: "conv3_res18_conv2" | |
| } | |
| layer { | |
| name: "conv3_res18_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res18_conv2" | |
| top: "conv3_res18_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res18_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res18_conv2" | |
| top: "conv3_res18_conv2" | |
| } | |
| layer { | |
| name: "conv3_res18_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res18_conv2" | |
| top: "conv3_res18_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res18" | |
| type: "Eltwise" | |
| bottom: "conv3_res17" | |
| bottom: "conv3_res18_conv3" | |
| top: "conv3_res18" | |
| } | |
| layer { | |
| name: "conv3_res19_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res18" | |
| top: "conv3_res19_pre" | |
| } | |
| layer { | |
| name: "conv3_res19_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res19_pre" | |
| top: "conv3_res19_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res19_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res19_pre" | |
| top: "conv3_res19_pre" | |
| } | |
| layer { | |
| name: "conv3_res19_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res19_pre" | |
| top: "conv3_res19_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res19_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res19_conv1" | |
| top: "conv3_res19_conv1" | |
| } | |
| layer { | |
| name: "conv3_res19_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res19_conv1" | |
| top: "conv3_res19_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res19_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res19_conv1" | |
| top: "conv3_res19_conv1" | |
| } | |
| layer { | |
| name: "conv3_res19_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res19_conv1" | |
| top: "conv3_res19_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res19_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res19_conv2" | |
| top: "conv3_res19_conv2" | |
| } | |
| layer { | |
| name: "conv3_res19_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res19_conv2" | |
| top: "conv3_res19_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res19_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res19_conv2" | |
| top: "conv3_res19_conv2" | |
| } | |
| layer { | |
| name: "conv3_res19_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res19_conv2" | |
| top: "conv3_res19_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res19" | |
| type: "Eltwise" | |
| bottom: "conv3_res18" | |
| bottom: "conv3_res19_conv3" | |
| top: "conv3_res19" | |
| } | |
| layer { | |
| name: "conv3_res20_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res19" | |
| top: "conv3_res20_pre" | |
| } | |
| layer { | |
| name: "conv3_res20_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res20_pre" | |
| top: "conv3_res20_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res20_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res20_pre" | |
| top: "conv3_res20_pre" | |
| } | |
| layer { | |
| name: "conv3_res20_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res20_pre" | |
| top: "conv3_res20_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res20_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res20_conv1" | |
| top: "conv3_res20_conv1" | |
| } | |
| layer { | |
| name: "conv3_res20_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res20_conv1" | |
| top: "conv3_res20_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res20_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res20_conv1" | |
| top: "conv3_res20_conv1" | |
| } | |
| layer { | |
| name: "conv3_res20_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res20_conv1" | |
| top: "conv3_res20_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res20_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res20_conv2" | |
| top: "conv3_res20_conv2" | |
| } | |
| layer { | |
| name: "conv3_res20_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res20_conv2" | |
| top: "conv3_res20_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res20_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res20_conv2" | |
| top: "conv3_res20_conv2" | |
| } | |
| layer { | |
| name: "conv3_res20_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res20_conv2" | |
| top: "conv3_res20_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res20" | |
| type: "Eltwise" | |
| bottom: "conv3_res19" | |
| bottom: "conv3_res20_conv3" | |
| top: "conv3_res20" | |
| } | |
| layer { | |
| name: "conv3_res21_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res20" | |
| top: "conv3_res21_pre" | |
| } | |
| layer { | |
| name: "conv3_res21_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res21_pre" | |
| top: "conv3_res21_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res21_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res21_pre" | |
| top: "conv3_res21_pre" | |
| } | |
| layer { | |
| name: "conv3_res21_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res21_pre" | |
| top: "conv3_res21_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res21_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res21_conv1" | |
| top: "conv3_res21_conv1" | |
| } | |
| layer { | |
| name: "conv3_res21_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res21_conv1" | |
| top: "conv3_res21_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res21_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res21_conv1" | |
| top: "conv3_res21_conv1" | |
| } | |
| layer { | |
| name: "conv3_res21_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res21_conv1" | |
| top: "conv3_res21_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res21_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res21_conv2" | |
| top: "conv3_res21_conv2" | |
| } | |
| layer { | |
| name: "conv3_res21_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res21_conv2" | |
| top: "conv3_res21_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res21_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res21_conv2" | |
| top: "conv3_res21_conv2" | |
| } | |
| layer { | |
| name: "conv3_res21_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res21_conv2" | |
| top: "conv3_res21_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res21" | |
| type: "Eltwise" | |
| bottom: "conv3_res20" | |
| bottom: "conv3_res21_conv3" | |
| top: "conv3_res21" | |
| } | |
| layer { | |
| name: "conv3_res22_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res21" | |
| top: "conv3_res22_pre" | |
| } | |
| layer { | |
| name: "conv3_res22_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res22_pre" | |
| top: "conv3_res22_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res22_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res22_pre" | |
| top: "conv3_res22_pre" | |
| } | |
| layer { | |
| name: "conv3_res22_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res22_pre" | |
| top: "conv3_res22_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res22_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res22_conv1" | |
| top: "conv3_res22_conv1" | |
| } | |
| layer { | |
| name: "conv3_res22_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res22_conv1" | |
| top: "conv3_res22_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res22_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res22_conv1" | |
| top: "conv3_res22_conv1" | |
| } | |
| layer { | |
| name: "conv3_res22_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res22_conv1" | |
| top: "conv3_res22_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res22_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res22_conv2" | |
| top: "conv3_res22_conv2" | |
| } | |
| layer { | |
| name: "conv3_res22_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res22_conv2" | |
| top: "conv3_res22_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res22_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res22_conv2" | |
| top: "conv3_res22_conv2" | |
| } | |
| layer { | |
| name: "conv3_res22_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res22_conv2" | |
| top: "conv3_res22_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res22" | |
| type: "Eltwise" | |
| bottom: "conv3_res21" | |
| bottom: "conv3_res22_conv3" | |
| top: "conv3_res22" | |
| } | |
| layer { | |
| name: "conv3_res23_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res22" | |
| top: "conv3_res23_pre" | |
| } | |
| layer { | |
| name: "conv3_res23_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res23_pre" | |
| top: "conv3_res23_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res23_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res23_pre" | |
| top: "conv3_res23_pre" | |
| } | |
| layer { | |
| name: "conv3_res23_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res23_pre" | |
| top: "conv3_res23_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res23_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res23_conv1" | |
| top: "conv3_res23_conv1" | |
| } | |
| layer { | |
| name: "conv3_res23_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res23_conv1" | |
| top: "conv3_res23_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res23_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res23_conv1" | |
| top: "conv3_res23_conv1" | |
| } | |
| layer { | |
| name: "conv3_res23_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res23_conv1" | |
| top: "conv3_res23_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res23_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res23_conv2" | |
| top: "conv3_res23_conv2" | |
| } | |
| layer { | |
| name: "conv3_res23_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res23_conv2" | |
| top: "conv3_res23_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res23_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res23_conv2" | |
| top: "conv3_res23_conv2" | |
| } | |
| layer { | |
| name: "conv3_res23_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res23_conv2" | |
| top: "conv3_res23_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res23" | |
| type: "Eltwise" | |
| bottom: "conv3_res22" | |
| bottom: "conv3_res23_conv3" | |
| top: "conv3_res23" | |
| } | |
| layer { | |
| name: "conv3_res24_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res23" | |
| top: "conv3_res24_pre" | |
| } | |
| layer { | |
| name: "conv3_res24_pre_scale" | |
| type: "Scale" | |
| bottom: "conv3_res24_pre" | |
| top: "conv3_res24_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res24_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res24_pre" | |
| top: "conv3_res24_pre" | |
| } | |
| layer { | |
| name: "conv3_res24_conv1" | |
| type: "Convolution" | |
| bottom: "conv3_res24_pre" | |
| top: "conv3_res24_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res24_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res24_conv1" | |
| top: "conv3_res24_conv1" | |
| } | |
| layer { | |
| name: "conv3_res24_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv3_res24_conv1" | |
| top: "conv3_res24_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res24_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res24_conv1" | |
| top: "conv3_res24_conv1" | |
| } | |
| layer { | |
| name: "conv3_res24_conv2" | |
| type: "Convolution" | |
| bottom: "conv3_res24_conv1" | |
| top: "conv3_res24_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res24_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res24_conv2" | |
| top: "conv3_res24_conv2" | |
| } | |
| layer { | |
| name: "conv3_res24_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv3_res24_conv2" | |
| top: "conv3_res24_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res24_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv3_res24_conv2" | |
| top: "conv3_res24_conv2" | |
| } | |
| layer { | |
| name: "conv3_res24_conv3" | |
| type: "Convolution" | |
| bottom: "conv3_res24_conv2" | |
| top: "conv3_res24_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_res24" | |
| type: "Eltwise" | |
| bottom: "conv3_res23" | |
| bottom: "conv3_res24_conv3" | |
| top: "conv3_res24" | |
| } | |
| layer { | |
| name: "conv4_res1_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_res24" | |
| top: "conv4_res1_pre" | |
| } | |
| layer { | |
| name: "conv4_res1_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res1_pre" | |
| top: "conv4_res1_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res1_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res1_pre" | |
| top: "conv4_res1_pre" | |
| } | |
| layer { | |
| name: "conv4_res1_proj" | |
| type: "Convolution" | |
| bottom: "conv4_res1_pre" | |
| top: "conv4_res1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res1_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res1_pre" | |
| top: "conv4_res1_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res1_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res1_conv1" | |
| top: "conv4_res1_conv1" | |
| } | |
| layer { | |
| name: "conv4_res1_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res1_conv1" | |
| top: "conv4_res1_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res1_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res1_conv1" | |
| top: "conv4_res1_conv1" | |
| } | |
| layer { | |
| name: "conv4_res1_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res1_conv1" | |
| top: "conv4_res1_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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res1_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res1_conv2" | |
| top: "conv4_res1_conv2" | |
| } | |
| layer { | |
| name: "conv4_res1_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res1_conv2" | |
| top: "conv4_res1_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res1_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res1_conv2" | |
| top: "conv4_res1_conv2" | |
| } | |
| layer { | |
| name: "conv4_res1_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res1_conv2" | |
| top: "conv4_res1_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res1" | |
| type: "Eltwise" | |
| bottom: "conv4_res1_proj" | |
| bottom: "conv4_res1_conv3" | |
| top: "conv4_res1" | |
| } | |
| layer { | |
| name: "conv4_res2_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res1" | |
| top: "conv4_res2_pre" | |
| } | |
| layer { | |
| name: "conv4_res2_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res2_pre" | |
| top: "conv4_res2_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res2_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res2_pre" | |
| top: "conv4_res2_pre" | |
| } | |
| layer { | |
| name: "conv4_res2_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res2_pre" | |
| top: "conv4_res2_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res2_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res2_conv1" | |
| top: "conv4_res2_conv1" | |
| } | |
| layer { | |
| name: "conv4_res2_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res2_conv1" | |
| top: "conv4_res2_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res2_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res2_conv1" | |
| top: "conv4_res2_conv1" | |
| } | |
| layer { | |
| name: "conv4_res2_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res2_conv1" | |
| top: "conv4_res2_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res2_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res2_conv2" | |
| top: "conv4_res2_conv2" | |
| } | |
| layer { | |
| name: "conv4_res2_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res2_conv2" | |
| top: "conv4_res2_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res2_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res2_conv2" | |
| top: "conv4_res2_conv2" | |
| } | |
| layer { | |
| name: "conv4_res2_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res2_conv2" | |
| top: "conv4_res2_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res2" | |
| type: "Eltwise" | |
| bottom: "conv4_res1" | |
| bottom: "conv4_res2_conv3" | |
| top: "conv4_res2" | |
| } | |
| layer { | |
| name: "conv4_res3_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res2" | |
| top: "conv4_res3_pre" | |
| } | |
| layer { | |
| name: "conv4_res3_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res3_pre" | |
| top: "conv4_res3_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res3_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res3_pre" | |
| top: "conv4_res3_pre" | |
| } | |
| layer { | |
| name: "conv4_res3_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res3_pre" | |
| top: "conv4_res3_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res3_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res3_conv1" | |
| top: "conv4_res3_conv1" | |
| } | |
| layer { | |
| name: "conv4_res3_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res3_conv1" | |
| top: "conv4_res3_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res3_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res3_conv1" | |
| top: "conv4_res3_conv1" | |
| } | |
| layer { | |
| name: "conv4_res3_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res3_conv1" | |
| top: "conv4_res3_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res3_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res3_conv2" | |
| top: "conv4_res3_conv2" | |
| } | |
| layer { | |
| name: "conv4_res3_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res3_conv2" | |
| top: "conv4_res3_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res3_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res3_conv2" | |
| top: "conv4_res3_conv2" | |
| } | |
| layer { | |
| name: "conv4_res3_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res3_conv2" | |
| top: "conv4_res3_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res3" | |
| type: "Eltwise" | |
| bottom: "conv4_res2" | |
| bottom: "conv4_res3_conv3" | |
| top: "conv4_res3" | |
| } | |
| layer { | |
| name: "conv4_res4_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res3" | |
| top: "conv4_res4_pre" | |
| } | |
| layer { | |
| name: "conv4_res4_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res4_pre" | |
| top: "conv4_res4_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res4_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res4_pre" | |
| top: "conv4_res4_pre" | |
| } | |
| layer { | |
| name: "conv4_res4_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res4_pre" | |
| top: "conv4_res4_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res4_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res4_conv1" | |
| top: "conv4_res4_conv1" | |
| } | |
| layer { | |
| name: "conv4_res4_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res4_conv1" | |
| top: "conv4_res4_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res4_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res4_conv1" | |
| top: "conv4_res4_conv1" | |
| } | |
| layer { | |
| name: "conv4_res4_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res4_conv1" | |
| top: "conv4_res4_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res4_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res4_conv2" | |
| top: "conv4_res4_conv2" | |
| } | |
| layer { | |
| name: "conv4_res4_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res4_conv2" | |
| top: "conv4_res4_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res4_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res4_conv2" | |
| top: "conv4_res4_conv2" | |
| } | |
| layer { | |
| name: "conv4_res4_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res4_conv2" | |
| top: "conv4_res4_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res4" | |
| type: "Eltwise" | |
| bottom: "conv4_res3" | |
| bottom: "conv4_res4_conv3" | |
| top: "conv4_res4" | |
| } | |
| layer { | |
| name: "conv4_res5_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res4" | |
| top: "conv4_res5_pre" | |
| } | |
| layer { | |
| name: "conv4_res5_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res5_pre" | |
| top: "conv4_res5_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res5_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res5_pre" | |
| top: "conv4_res5_pre" | |
| } | |
| layer { | |
| name: "conv4_res5_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res5_pre" | |
| top: "conv4_res5_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res5_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res5_conv1" | |
| top: "conv4_res5_conv1" | |
| } | |
| layer { | |
| name: "conv4_res5_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res5_conv1" | |
| top: "conv4_res5_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res5_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res5_conv1" | |
| top: "conv4_res5_conv1" | |
| } | |
| layer { | |
| name: "conv4_res5_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res5_conv1" | |
| top: "conv4_res5_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res5_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res5_conv2" | |
| top: "conv4_res5_conv2" | |
| } | |
| layer { | |
| name: "conv4_res5_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res5_conv2" | |
| top: "conv4_res5_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res5_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res5_conv2" | |
| top: "conv4_res5_conv2" | |
| } | |
| layer { | |
| name: "conv4_res5_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res5_conv2" | |
| top: "conv4_res5_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res5" | |
| type: "Eltwise" | |
| bottom: "conv4_res4" | |
| bottom: "conv4_res5_conv3" | |
| top: "conv4_res5" | |
| } | |
| layer { | |
| name: "conv4_res6_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res5" | |
| top: "conv4_res6_pre" | |
| } | |
| layer { | |
| name: "conv4_res6_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res6_pre" | |
| top: "conv4_res6_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res6_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res6_pre" | |
| top: "conv4_res6_pre" | |
| } | |
| layer { | |
| name: "conv4_res6_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res6_pre" | |
| top: "conv4_res6_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res6_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res6_conv1" | |
| top: "conv4_res6_conv1" | |
| } | |
| layer { | |
| name: "conv4_res6_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res6_conv1" | |
| top: "conv4_res6_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res6_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res6_conv1" | |
| top: "conv4_res6_conv1" | |
| } | |
| layer { | |
| name: "conv4_res6_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res6_conv1" | |
| top: "conv4_res6_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res6_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res6_conv2" | |
| top: "conv4_res6_conv2" | |
| } | |
| layer { | |
| name: "conv4_res6_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res6_conv2" | |
| top: "conv4_res6_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res6_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res6_conv2" | |
| top: "conv4_res6_conv2" | |
| } | |
| layer { | |
| name: "conv4_res6_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res6_conv2" | |
| top: "conv4_res6_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res6" | |
| type: "Eltwise" | |
| bottom: "conv4_res5" | |
| bottom: "conv4_res6_conv3" | |
| top: "conv4_res6" | |
| } | |
| layer { | |
| name: "conv4_res7_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res6" | |
| top: "conv4_res7_pre" | |
| } | |
| layer { | |
| name: "conv4_res7_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res7_pre" | |
| top: "conv4_res7_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res7_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res7_pre" | |
| top: "conv4_res7_pre" | |
| } | |
| layer { | |
| name: "conv4_res7_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res7_pre" | |
| top: "conv4_res7_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res7_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res7_conv1" | |
| top: "conv4_res7_conv1" | |
| } | |
| layer { | |
| name: "conv4_res7_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res7_conv1" | |
| top: "conv4_res7_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res7_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res7_conv1" | |
| top: "conv4_res7_conv1" | |
| } | |
| layer { | |
| name: "conv4_res7_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res7_conv1" | |
| top: "conv4_res7_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res7_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res7_conv2" | |
| top: "conv4_res7_conv2" | |
| } | |
| layer { | |
| name: "conv4_res7_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res7_conv2" | |
| top: "conv4_res7_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res7_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res7_conv2" | |
| top: "conv4_res7_conv2" | |
| } | |
| layer { | |
| name: "conv4_res7_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res7_conv2" | |
| top: "conv4_res7_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res7" | |
| type: "Eltwise" | |
| bottom: "conv4_res6" | |
| bottom: "conv4_res7_conv3" | |
| top: "conv4_res7" | |
| } | |
| layer { | |
| name: "conv4_res8_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res7" | |
| top: "conv4_res8_pre" | |
| } | |
| layer { | |
| name: "conv4_res8_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res8_pre" | |
| top: "conv4_res8_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res8_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res8_pre" | |
| top: "conv4_res8_pre" | |
| } | |
| layer { | |
| name: "conv4_res8_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res8_pre" | |
| top: "conv4_res8_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res8_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res8_conv1" | |
| top: "conv4_res8_conv1" | |
| } | |
| layer { | |
| name: "conv4_res8_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res8_conv1" | |
| top: "conv4_res8_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res8_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res8_conv1" | |
| top: "conv4_res8_conv1" | |
| } | |
| layer { | |
| name: "conv4_res8_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res8_conv1" | |
| top: "conv4_res8_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res8_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res8_conv2" | |
| top: "conv4_res8_conv2" | |
| } | |
| layer { | |
| name: "conv4_res8_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res8_conv2" | |
| top: "conv4_res8_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res8_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res8_conv2" | |
| top: "conv4_res8_conv2" | |
| } | |
| layer { | |
| name: "conv4_res8_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res8_conv2" | |
| top: "conv4_res8_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res8" | |
| type: "Eltwise" | |
| bottom: "conv4_res7" | |
| bottom: "conv4_res8_conv3" | |
| top: "conv4_res8" | |
| } | |
| layer { | |
| name: "conv4_res9_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res8" | |
| top: "conv4_res9_pre" | |
| } | |
| layer { | |
| name: "conv4_res9_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res9_pre" | |
| top: "conv4_res9_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res9_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res9_pre" | |
| top: "conv4_res9_pre" | |
| } | |
| layer { | |
| name: "conv4_res9_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res9_pre" | |
| top: "conv4_res9_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res9_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res9_conv1" | |
| top: "conv4_res9_conv1" | |
| } | |
| layer { | |
| name: "conv4_res9_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res9_conv1" | |
| top: "conv4_res9_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res9_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res9_conv1" | |
| top: "conv4_res9_conv1" | |
| } | |
| layer { | |
| name: "conv4_res9_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res9_conv1" | |
| top: "conv4_res9_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res9_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res9_conv2" | |
| top: "conv4_res9_conv2" | |
| } | |
| layer { | |
| name: "conv4_res9_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res9_conv2" | |
| top: "conv4_res9_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res9_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res9_conv2" | |
| top: "conv4_res9_conv2" | |
| } | |
| layer { | |
| name: "conv4_res9_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res9_conv2" | |
| top: "conv4_res9_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res9" | |
| type: "Eltwise" | |
| bottom: "conv4_res8" | |
| bottom: "conv4_res9_conv3" | |
| top: "conv4_res9" | |
| } | |
| layer { | |
| name: "conv4_res10_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res9" | |
| top: "conv4_res10_pre" | |
| } | |
| layer { | |
| name: "conv4_res10_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res10_pre" | |
| top: "conv4_res10_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res10_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res10_pre" | |
| top: "conv4_res10_pre" | |
| } | |
| layer { | |
| name: "conv4_res10_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res10_pre" | |
| top: "conv4_res10_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res10_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res10_conv1" | |
| top: "conv4_res10_conv1" | |
| } | |
| layer { | |
| name: "conv4_res10_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res10_conv1" | |
| top: "conv4_res10_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res10_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res10_conv1" | |
| top: "conv4_res10_conv1" | |
| } | |
| layer { | |
| name: "conv4_res10_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res10_conv1" | |
| top: "conv4_res10_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res10_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res10_conv2" | |
| top: "conv4_res10_conv2" | |
| } | |
| layer { | |
| name: "conv4_res10_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res10_conv2" | |
| top: "conv4_res10_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res10_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res10_conv2" | |
| top: "conv4_res10_conv2" | |
| } | |
| layer { | |
| name: "conv4_res10_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res10_conv2" | |
| top: "conv4_res10_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res10" | |
| type: "Eltwise" | |
| bottom: "conv4_res9" | |
| bottom: "conv4_res10_conv3" | |
| top: "conv4_res10" | |
| } | |
| layer { | |
| name: "conv4_res11_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res10" | |
| top: "conv4_res11_pre" | |
| } | |
| layer { | |
| name: "conv4_res11_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res11_pre" | |
| top: "conv4_res11_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res11_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res11_pre" | |
| top: "conv4_res11_pre" | |
| } | |
| layer { | |
| name: "conv4_res11_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res11_pre" | |
| top: "conv4_res11_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res11_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res11_conv1" | |
| top: "conv4_res11_conv1" | |
| } | |
| layer { | |
| name: "conv4_res11_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res11_conv1" | |
| top: "conv4_res11_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res11_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res11_conv1" | |
| top: "conv4_res11_conv1" | |
| } | |
| layer { | |
| name: "conv4_res11_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res11_conv1" | |
| top: "conv4_res11_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res11_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res11_conv2" | |
| top: "conv4_res11_conv2" | |
| } | |
| layer { | |
| name: "conv4_res11_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res11_conv2" | |
| top: "conv4_res11_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res11_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res11_conv2" | |
| top: "conv4_res11_conv2" | |
| } | |
| layer { | |
| name: "conv4_res11_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res11_conv2" | |
| top: "conv4_res11_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res11" | |
| type: "Eltwise" | |
| bottom: "conv4_res10" | |
| bottom: "conv4_res11_conv3" | |
| top: "conv4_res11" | |
| } | |
| layer { | |
| name: "conv4_res12_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res11" | |
| top: "conv4_res12_pre" | |
| } | |
| layer { | |
| name: "conv4_res12_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res12_pre" | |
| top: "conv4_res12_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res12_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res12_pre" | |
| top: "conv4_res12_pre" | |
| } | |
| layer { | |
| name: "conv4_res12_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res12_pre" | |
| top: "conv4_res12_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res12_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res12_conv1" | |
| top: "conv4_res12_conv1" | |
| } | |
| layer { | |
| name: "conv4_res12_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res12_conv1" | |
| top: "conv4_res12_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res12_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res12_conv1" | |
| top: "conv4_res12_conv1" | |
| } | |
| layer { | |
| name: "conv4_res12_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res12_conv1" | |
| top: "conv4_res12_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res12_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res12_conv2" | |
| top: "conv4_res12_conv2" | |
| } | |
| layer { | |
| name: "conv4_res12_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res12_conv2" | |
| top: "conv4_res12_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res12_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res12_conv2" | |
| top: "conv4_res12_conv2" | |
| } | |
| layer { | |
| name: "conv4_res12_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res12_conv2" | |
| top: "conv4_res12_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res12" | |
| type: "Eltwise" | |
| bottom: "conv4_res11" | |
| bottom: "conv4_res12_conv3" | |
| top: "conv4_res12" | |
| } | |
| layer { | |
| name: "conv4_res13_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res12" | |
| top: "conv4_res13_pre" | |
| } | |
| layer { | |
| name: "conv4_res13_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res13_pre" | |
| top: "conv4_res13_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res13_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res13_pre" | |
| top: "conv4_res13_pre" | |
| } | |
| layer { | |
| name: "conv4_res13_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res13_pre" | |
| top: "conv4_res13_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res13_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res13_conv1" | |
| top: "conv4_res13_conv1" | |
| } | |
| layer { | |
| name: "conv4_res13_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res13_conv1" | |
| top: "conv4_res13_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res13_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res13_conv1" | |
| top: "conv4_res13_conv1" | |
| } | |
| layer { | |
| name: "conv4_res13_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res13_conv1" | |
| top: "conv4_res13_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res13_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res13_conv2" | |
| top: "conv4_res13_conv2" | |
| } | |
| layer { | |
| name: "conv4_res13_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res13_conv2" | |
| top: "conv4_res13_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res13_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res13_conv2" | |
| top: "conv4_res13_conv2" | |
| } | |
| layer { | |
| name: "conv4_res13_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res13_conv2" | |
| top: "conv4_res13_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res13" | |
| type: "Eltwise" | |
| bottom: "conv4_res12" | |
| bottom: "conv4_res13_conv3" | |
| top: "conv4_res13" | |
| } | |
| layer { | |
| name: "conv4_res14_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res13" | |
| top: "conv4_res14_pre" | |
| } | |
| layer { | |
| name: "conv4_res14_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res14_pre" | |
| top: "conv4_res14_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res14_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res14_pre" | |
| top: "conv4_res14_pre" | |
| } | |
| layer { | |
| name: "conv4_res14_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res14_pre" | |
| top: "conv4_res14_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res14_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res14_conv1" | |
| top: "conv4_res14_conv1" | |
| } | |
| layer { | |
| name: "conv4_res14_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res14_conv1" | |
| top: "conv4_res14_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res14_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res14_conv1" | |
| top: "conv4_res14_conv1" | |
| } | |
| layer { | |
| name: "conv4_res14_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res14_conv1" | |
| top: "conv4_res14_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res14_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res14_conv2" | |
| top: "conv4_res14_conv2" | |
| } | |
| layer { | |
| name: "conv4_res14_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res14_conv2" | |
| top: "conv4_res14_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res14_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res14_conv2" | |
| top: "conv4_res14_conv2" | |
| } | |
| layer { | |
| name: "conv4_res14_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res14_conv2" | |
| top: "conv4_res14_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res14" | |
| type: "Eltwise" | |
| bottom: "conv4_res13" | |
| bottom: "conv4_res14_conv3" | |
| top: "conv4_res14" | |
| } | |
| layer { | |
| name: "conv4_res15_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res14" | |
| top: "conv4_res15_pre" | |
| } | |
| layer { | |
| name: "conv4_res15_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res15_pre" | |
| top: "conv4_res15_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res15_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res15_pre" | |
| top: "conv4_res15_pre" | |
| } | |
| layer { | |
| name: "conv4_res15_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res15_pre" | |
| top: "conv4_res15_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res15_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res15_conv1" | |
| top: "conv4_res15_conv1" | |
| } | |
| layer { | |
| name: "conv4_res15_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res15_conv1" | |
| top: "conv4_res15_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res15_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res15_conv1" | |
| top: "conv4_res15_conv1" | |
| } | |
| layer { | |
| name: "conv4_res15_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res15_conv1" | |
| top: "conv4_res15_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res15_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res15_conv2" | |
| top: "conv4_res15_conv2" | |
| } | |
| layer { | |
| name: "conv4_res15_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res15_conv2" | |
| top: "conv4_res15_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res15_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res15_conv2" | |
| top: "conv4_res15_conv2" | |
| } | |
| layer { | |
| name: "conv4_res15_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res15_conv2" | |
| top: "conv4_res15_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res15" | |
| type: "Eltwise" | |
| bottom: "conv4_res14" | |
| bottom: "conv4_res15_conv3" | |
| top: "conv4_res15" | |
| } | |
| layer { | |
| name: "conv4_res16_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res15" | |
| top: "conv4_res16_pre" | |
| } | |
| layer { | |
| name: "conv4_res16_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res16_pre" | |
| top: "conv4_res16_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res16_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res16_pre" | |
| top: "conv4_res16_pre" | |
| } | |
| layer { | |
| name: "conv4_res16_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res16_pre" | |
| top: "conv4_res16_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res16_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res16_conv1" | |
| top: "conv4_res16_conv1" | |
| } | |
| layer { | |
| name: "conv4_res16_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res16_conv1" | |
| top: "conv4_res16_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res16_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res16_conv1" | |
| top: "conv4_res16_conv1" | |
| } | |
| layer { | |
| name: "conv4_res16_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res16_conv1" | |
| top: "conv4_res16_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res16_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res16_conv2" | |
| top: "conv4_res16_conv2" | |
| } | |
| layer { | |
| name: "conv4_res16_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res16_conv2" | |
| top: "conv4_res16_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res16_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res16_conv2" | |
| top: "conv4_res16_conv2" | |
| } | |
| layer { | |
| name: "conv4_res16_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res16_conv2" | |
| top: "conv4_res16_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res16" | |
| type: "Eltwise" | |
| bottom: "conv4_res15" | |
| bottom: "conv4_res16_conv3" | |
| top: "conv4_res16" | |
| } | |
| layer { | |
| name: "conv4_res17_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res16" | |
| top: "conv4_res17_pre" | |
| } | |
| layer { | |
| name: "conv4_res17_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res17_pre" | |
| top: "conv4_res17_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res17_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res17_pre" | |
| top: "conv4_res17_pre" | |
| } | |
| layer { | |
| name: "conv4_res17_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res17_pre" | |
| top: "conv4_res17_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res17_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res17_conv1" | |
| top: "conv4_res17_conv1" | |
| } | |
| layer { | |
| name: "conv4_res17_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res17_conv1" | |
| top: "conv4_res17_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res17_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res17_conv1" | |
| top: "conv4_res17_conv1" | |
| } | |
| layer { | |
| name: "conv4_res17_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res17_conv1" | |
| top: "conv4_res17_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res17_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res17_conv2" | |
| top: "conv4_res17_conv2" | |
| } | |
| layer { | |
| name: "conv4_res17_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res17_conv2" | |
| top: "conv4_res17_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res17_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res17_conv2" | |
| top: "conv4_res17_conv2" | |
| } | |
| layer { | |
| name: "conv4_res17_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res17_conv2" | |
| top: "conv4_res17_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res17" | |
| type: "Eltwise" | |
| bottom: "conv4_res16" | |
| bottom: "conv4_res17_conv3" | |
| top: "conv4_res17" | |
| } | |
| layer { | |
| name: "conv4_res18_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res17" | |
| top: "conv4_res18_pre" | |
| } | |
| layer { | |
| name: "conv4_res18_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res18_pre" | |
| top: "conv4_res18_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res18_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res18_pre" | |
| top: "conv4_res18_pre" | |
| } | |
| layer { | |
| name: "conv4_res18_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res18_pre" | |
| top: "conv4_res18_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res18_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res18_conv1" | |
| top: "conv4_res18_conv1" | |
| } | |
| layer { | |
| name: "conv4_res18_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res18_conv1" | |
| top: "conv4_res18_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res18_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res18_conv1" | |
| top: "conv4_res18_conv1" | |
| } | |
| layer { | |
| name: "conv4_res18_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res18_conv1" | |
| top: "conv4_res18_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res18_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res18_conv2" | |
| top: "conv4_res18_conv2" | |
| } | |
| layer { | |
| name: "conv4_res18_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res18_conv2" | |
| top: "conv4_res18_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res18_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res18_conv2" | |
| top: "conv4_res18_conv2" | |
| } | |
| layer { | |
| name: "conv4_res18_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res18_conv2" | |
| top: "conv4_res18_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res18" | |
| type: "Eltwise" | |
| bottom: "conv4_res17" | |
| bottom: "conv4_res18_conv3" | |
| top: "conv4_res18" | |
| } | |
| layer { | |
| name: "conv4_res19_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res18" | |
| top: "conv4_res19_pre" | |
| } | |
| layer { | |
| name: "conv4_res19_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res19_pre" | |
| top: "conv4_res19_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res19_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res19_pre" | |
| top: "conv4_res19_pre" | |
| } | |
| layer { | |
| name: "conv4_res19_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res19_pre" | |
| top: "conv4_res19_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res19_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res19_conv1" | |
| top: "conv4_res19_conv1" | |
| } | |
| layer { | |
| name: "conv4_res19_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res19_conv1" | |
| top: "conv4_res19_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res19_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res19_conv1" | |
| top: "conv4_res19_conv1" | |
| } | |
| layer { | |
| name: "conv4_res19_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res19_conv1" | |
| top: "conv4_res19_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res19_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res19_conv2" | |
| top: "conv4_res19_conv2" | |
| } | |
| layer { | |
| name: "conv4_res19_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res19_conv2" | |
| top: "conv4_res19_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res19_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res19_conv2" | |
| top: "conv4_res19_conv2" | |
| } | |
| layer { | |
| name: "conv4_res19_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res19_conv2" | |
| top: "conv4_res19_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res19" | |
| type: "Eltwise" | |
| bottom: "conv4_res18" | |
| bottom: "conv4_res19_conv3" | |
| top: "conv4_res19" | |
| } | |
| layer { | |
| name: "conv4_res20_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res19" | |
| top: "conv4_res20_pre" | |
| } | |
| layer { | |
| name: "conv4_res20_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res20_pre" | |
| top: "conv4_res20_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res20_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res20_pre" | |
| top: "conv4_res20_pre" | |
| } | |
| layer { | |
| name: "conv4_res20_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res20_pre" | |
| top: "conv4_res20_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res20_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res20_conv1" | |
| top: "conv4_res20_conv1" | |
| } | |
| layer { | |
| name: "conv4_res20_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res20_conv1" | |
| top: "conv4_res20_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res20_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res20_conv1" | |
| top: "conv4_res20_conv1" | |
| } | |
| layer { | |
| name: "conv4_res20_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res20_conv1" | |
| top: "conv4_res20_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res20_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res20_conv2" | |
| top: "conv4_res20_conv2" | |
| } | |
| layer { | |
| name: "conv4_res20_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res20_conv2" | |
| top: "conv4_res20_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res20_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res20_conv2" | |
| top: "conv4_res20_conv2" | |
| } | |
| layer { | |
| name: "conv4_res20_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res20_conv2" | |
| top: "conv4_res20_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res20" | |
| type: "Eltwise" | |
| bottom: "conv4_res19" | |
| bottom: "conv4_res20_conv3" | |
| top: "conv4_res20" | |
| } | |
| layer { | |
| name: "conv4_res21_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res20" | |
| top: "conv4_res21_pre" | |
| } | |
| layer { | |
| name: "conv4_res21_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res21_pre" | |
| top: "conv4_res21_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res21_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res21_pre" | |
| top: "conv4_res21_pre" | |
| } | |
| layer { | |
| name: "conv4_res21_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res21_pre" | |
| top: "conv4_res21_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res21_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res21_conv1" | |
| top: "conv4_res21_conv1" | |
| } | |
| layer { | |
| name: "conv4_res21_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res21_conv1" | |
| top: "conv4_res21_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res21_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res21_conv1" | |
| top: "conv4_res21_conv1" | |
| } | |
| layer { | |
| name: "conv4_res21_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res21_conv1" | |
| top: "conv4_res21_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res21_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res21_conv2" | |
| top: "conv4_res21_conv2" | |
| } | |
| layer { | |
| name: "conv4_res21_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res21_conv2" | |
| top: "conv4_res21_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res21_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res21_conv2" | |
| top: "conv4_res21_conv2" | |
| } | |
| layer { | |
| name: "conv4_res21_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res21_conv2" | |
| top: "conv4_res21_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res21" | |
| type: "Eltwise" | |
| bottom: "conv4_res20" | |
| bottom: "conv4_res21_conv3" | |
| top: "conv4_res21" | |
| } | |
| layer { | |
| name: "conv4_res22_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res21" | |
| top: "conv4_res22_pre" | |
| } | |
| layer { | |
| name: "conv4_res22_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res22_pre" | |
| top: "conv4_res22_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res22_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res22_pre" | |
| top: "conv4_res22_pre" | |
| } | |
| layer { | |
| name: "conv4_res22_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res22_pre" | |
| top: "conv4_res22_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res22_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res22_conv1" | |
| top: "conv4_res22_conv1" | |
| } | |
| layer { | |
| name: "conv4_res22_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res22_conv1" | |
| top: "conv4_res22_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res22_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res22_conv1" | |
| top: "conv4_res22_conv1" | |
| } | |
| layer { | |
| name: "conv4_res22_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res22_conv1" | |
| top: "conv4_res22_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res22_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res22_conv2" | |
| top: "conv4_res22_conv2" | |
| } | |
| layer { | |
| name: "conv4_res22_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res22_conv2" | |
| top: "conv4_res22_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res22_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res22_conv2" | |
| top: "conv4_res22_conv2" | |
| } | |
| layer { | |
| name: "conv4_res22_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res22_conv2" | |
| top: "conv4_res22_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res22" | |
| type: "Eltwise" | |
| bottom: "conv4_res21" | |
| bottom: "conv4_res22_conv3" | |
| top: "conv4_res22" | |
| } | |
| layer { | |
| name: "conv4_res23_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res22" | |
| top: "conv4_res23_pre" | |
| } | |
| layer { | |
| name: "conv4_res23_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res23_pre" | |
| top: "conv4_res23_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res23_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res23_pre" | |
| top: "conv4_res23_pre" | |
| } | |
| layer { | |
| name: "conv4_res23_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res23_pre" | |
| top: "conv4_res23_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res23_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res23_conv1" | |
| top: "conv4_res23_conv1" | |
| } | |
| layer { | |
| name: "conv4_res23_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res23_conv1" | |
| top: "conv4_res23_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res23_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res23_conv1" | |
| top: "conv4_res23_conv1" | |
| } | |
| layer { | |
| name: "conv4_res23_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res23_conv1" | |
| top: "conv4_res23_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res23_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res23_conv2" | |
| top: "conv4_res23_conv2" | |
| } | |
| layer { | |
| name: "conv4_res23_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res23_conv2" | |
| top: "conv4_res23_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res23_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res23_conv2" | |
| top: "conv4_res23_conv2" | |
| } | |
| layer { | |
| name: "conv4_res23_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res23_conv2" | |
| top: "conv4_res23_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res23" | |
| type: "Eltwise" | |
| bottom: "conv4_res22" | |
| bottom: "conv4_res23_conv3" | |
| top: "conv4_res23" | |
| } | |
| layer { | |
| name: "conv4_res24_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res23" | |
| top: "conv4_res24_pre" | |
| } | |
| layer { | |
| name: "conv4_res24_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res24_pre" | |
| top: "conv4_res24_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res24_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res24_pre" | |
| top: "conv4_res24_pre" | |
| } | |
| layer { | |
| name: "conv4_res24_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res24_pre" | |
| top: "conv4_res24_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res24_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res24_conv1" | |
| top: "conv4_res24_conv1" | |
| } | |
| layer { | |
| name: "conv4_res24_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res24_conv1" | |
| top: "conv4_res24_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res24_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res24_conv1" | |
| top: "conv4_res24_conv1" | |
| } | |
| layer { | |
| name: "conv4_res24_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res24_conv1" | |
| top: "conv4_res24_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res24_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res24_conv2" | |
| top: "conv4_res24_conv2" | |
| } | |
| layer { | |
| name: "conv4_res24_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res24_conv2" | |
| top: "conv4_res24_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res24_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res24_conv2" | |
| top: "conv4_res24_conv2" | |
| } | |
| layer { | |
| name: "conv4_res24_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res24_conv2" | |
| top: "conv4_res24_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res24" | |
| type: "Eltwise" | |
| bottom: "conv4_res23" | |
| bottom: "conv4_res24_conv3" | |
| top: "conv4_res24" | |
| } | |
| layer { | |
| name: "conv4_res25_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res24" | |
| top: "conv4_res25_pre" | |
| } | |
| layer { | |
| name: "conv4_res25_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res25_pre" | |
| top: "conv4_res25_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res25_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res25_pre" | |
| top: "conv4_res25_pre" | |
| } | |
| layer { | |
| name: "conv4_res25_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res25_pre" | |
| top: "conv4_res25_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res25_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res25_conv1" | |
| top: "conv4_res25_conv1" | |
| } | |
| layer { | |
| name: "conv4_res25_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res25_conv1" | |
| top: "conv4_res25_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res25_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res25_conv1" | |
| top: "conv4_res25_conv1" | |
| } | |
| layer { | |
| name: "conv4_res25_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res25_conv1" | |
| top: "conv4_res25_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res25_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res25_conv2" | |
| top: "conv4_res25_conv2" | |
| } | |
| layer { | |
| name: "conv4_res25_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res25_conv2" | |
| top: "conv4_res25_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res25_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res25_conv2" | |
| top: "conv4_res25_conv2" | |
| } | |
| layer { | |
| name: "conv4_res25_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res25_conv2" | |
| top: "conv4_res25_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res25" | |
| type: "Eltwise" | |
| bottom: "conv4_res24" | |
| bottom: "conv4_res25_conv3" | |
| top: "conv4_res25" | |
| } | |
| layer { | |
| name: "conv4_res26_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res25" | |
| top: "conv4_res26_pre" | |
| } | |
| layer { | |
| name: "conv4_res26_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res26_pre" | |
| top: "conv4_res26_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res26_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res26_pre" | |
| top: "conv4_res26_pre" | |
| } | |
| layer { | |
| name: "conv4_res26_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res26_pre" | |
| top: "conv4_res26_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res26_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res26_conv1" | |
| top: "conv4_res26_conv1" | |
| } | |
| layer { | |
| name: "conv4_res26_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res26_conv1" | |
| top: "conv4_res26_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res26_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res26_conv1" | |
| top: "conv4_res26_conv1" | |
| } | |
| layer { | |
| name: "conv4_res26_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res26_conv1" | |
| top: "conv4_res26_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res26_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res26_conv2" | |
| top: "conv4_res26_conv2" | |
| } | |
| layer { | |
| name: "conv4_res26_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res26_conv2" | |
| top: "conv4_res26_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res26_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res26_conv2" | |
| top: "conv4_res26_conv2" | |
| } | |
| layer { | |
| name: "conv4_res26_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res26_conv2" | |
| top: "conv4_res26_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res26" | |
| type: "Eltwise" | |
| bottom: "conv4_res25" | |
| bottom: "conv4_res26_conv3" | |
| top: "conv4_res26" | |
| } | |
| layer { | |
| name: "conv4_res27_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res26" | |
| top: "conv4_res27_pre" | |
| } | |
| layer { | |
| name: "conv4_res27_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res27_pre" | |
| top: "conv4_res27_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res27_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res27_pre" | |
| top: "conv4_res27_pre" | |
| } | |
| layer { | |
| name: "conv4_res27_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res27_pre" | |
| top: "conv4_res27_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res27_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res27_conv1" | |
| top: "conv4_res27_conv1" | |
| } | |
| layer { | |
| name: "conv4_res27_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res27_conv1" | |
| top: "conv4_res27_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res27_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res27_conv1" | |
| top: "conv4_res27_conv1" | |
| } | |
| layer { | |
| name: "conv4_res27_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res27_conv1" | |
| top: "conv4_res27_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res27_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res27_conv2" | |
| top: "conv4_res27_conv2" | |
| } | |
| layer { | |
| name: "conv4_res27_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res27_conv2" | |
| top: "conv4_res27_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res27_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res27_conv2" | |
| top: "conv4_res27_conv2" | |
| } | |
| layer { | |
| name: "conv4_res27_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res27_conv2" | |
| top: "conv4_res27_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res27" | |
| type: "Eltwise" | |
| bottom: "conv4_res26" | |
| bottom: "conv4_res27_conv3" | |
| top: "conv4_res27" | |
| } | |
| layer { | |
| name: "conv4_res28_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res27" | |
| top: "conv4_res28_pre" | |
| } | |
| layer { | |
| name: "conv4_res28_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res28_pre" | |
| top: "conv4_res28_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res28_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res28_pre" | |
| top: "conv4_res28_pre" | |
| } | |
| layer { | |
| name: "conv4_res28_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res28_pre" | |
| top: "conv4_res28_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res28_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res28_conv1" | |
| top: "conv4_res28_conv1" | |
| } | |
| layer { | |
| name: "conv4_res28_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res28_conv1" | |
| top: "conv4_res28_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res28_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res28_conv1" | |
| top: "conv4_res28_conv1" | |
| } | |
| layer { | |
| name: "conv4_res28_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res28_conv1" | |
| top: "conv4_res28_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res28_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res28_conv2" | |
| top: "conv4_res28_conv2" | |
| } | |
| layer { | |
| name: "conv4_res28_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res28_conv2" | |
| top: "conv4_res28_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res28_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res28_conv2" | |
| top: "conv4_res28_conv2" | |
| } | |
| layer { | |
| name: "conv4_res28_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res28_conv2" | |
| top: "conv4_res28_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res28" | |
| type: "Eltwise" | |
| bottom: "conv4_res27" | |
| bottom: "conv4_res28_conv3" | |
| top: "conv4_res28" | |
| } | |
| layer { | |
| name: "conv4_res29_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res28" | |
| top: "conv4_res29_pre" | |
| } | |
| layer { | |
| name: "conv4_res29_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res29_pre" | |
| top: "conv4_res29_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res29_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res29_pre" | |
| top: "conv4_res29_pre" | |
| } | |
| layer { | |
| name: "conv4_res29_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res29_pre" | |
| top: "conv4_res29_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res29_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res29_conv1" | |
| top: "conv4_res29_conv1" | |
| } | |
| layer { | |
| name: "conv4_res29_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res29_conv1" | |
| top: "conv4_res29_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res29_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res29_conv1" | |
| top: "conv4_res29_conv1" | |
| } | |
| layer { | |
| name: "conv4_res29_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res29_conv1" | |
| top: "conv4_res29_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res29_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res29_conv2" | |
| top: "conv4_res29_conv2" | |
| } | |
| layer { | |
| name: "conv4_res29_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res29_conv2" | |
| top: "conv4_res29_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res29_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res29_conv2" | |
| top: "conv4_res29_conv2" | |
| } | |
| layer { | |
| name: "conv4_res29_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res29_conv2" | |
| top: "conv4_res29_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res29" | |
| type: "Eltwise" | |
| bottom: "conv4_res28" | |
| bottom: "conv4_res29_conv3" | |
| top: "conv4_res29" | |
| } | |
| layer { | |
| name: "conv4_res30_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res29" | |
| top: "conv4_res30_pre" | |
| } | |
| layer { | |
| name: "conv4_res30_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res30_pre" | |
| top: "conv4_res30_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res30_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res30_pre" | |
| top: "conv4_res30_pre" | |
| } | |
| layer { | |
| name: "conv4_res30_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res30_pre" | |
| top: "conv4_res30_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res30_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res30_conv1" | |
| top: "conv4_res30_conv1" | |
| } | |
| layer { | |
| name: "conv4_res30_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res30_conv1" | |
| top: "conv4_res30_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res30_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res30_conv1" | |
| top: "conv4_res30_conv1" | |
| } | |
| layer { | |
| name: "conv4_res30_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res30_conv1" | |
| top: "conv4_res30_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res30_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res30_conv2" | |
| top: "conv4_res30_conv2" | |
| } | |
| layer { | |
| name: "conv4_res30_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res30_conv2" | |
| top: "conv4_res30_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res30_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res30_conv2" | |
| top: "conv4_res30_conv2" | |
| } | |
| layer { | |
| name: "conv4_res30_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res30_conv2" | |
| top: "conv4_res30_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res30" | |
| type: "Eltwise" | |
| bottom: "conv4_res29" | |
| bottom: "conv4_res30_conv3" | |
| top: "conv4_res30" | |
| } | |
| layer { | |
| name: "conv4_res31_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res30" | |
| top: "conv4_res31_pre" | |
| } | |
| layer { | |
| name: "conv4_res31_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res31_pre" | |
| top: "conv4_res31_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res31_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res31_pre" | |
| top: "conv4_res31_pre" | |
| } | |
| layer { | |
| name: "conv4_res31_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res31_pre" | |
| top: "conv4_res31_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res31_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res31_conv1" | |
| top: "conv4_res31_conv1" | |
| } | |
| layer { | |
| name: "conv4_res31_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res31_conv1" | |
| top: "conv4_res31_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res31_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res31_conv1" | |
| top: "conv4_res31_conv1" | |
| } | |
| layer { | |
| name: "conv4_res31_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res31_conv1" | |
| top: "conv4_res31_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res31_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res31_conv2" | |
| top: "conv4_res31_conv2" | |
| } | |
| layer { | |
| name: "conv4_res31_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res31_conv2" | |
| top: "conv4_res31_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res31_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res31_conv2" | |
| top: "conv4_res31_conv2" | |
| } | |
| layer { | |
| name: "conv4_res31_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res31_conv2" | |
| top: "conv4_res31_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res31" | |
| type: "Eltwise" | |
| bottom: "conv4_res30" | |
| bottom: "conv4_res31_conv3" | |
| top: "conv4_res31" | |
| } | |
| layer { | |
| name: "conv4_res32_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res31" | |
| top: "conv4_res32_pre" | |
| } | |
| layer { | |
| name: "conv4_res32_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res32_pre" | |
| top: "conv4_res32_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res32_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res32_pre" | |
| top: "conv4_res32_pre" | |
| } | |
| layer { | |
| name: "conv4_res32_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res32_pre" | |
| top: "conv4_res32_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res32_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res32_conv1" | |
| top: "conv4_res32_conv1" | |
| } | |
| layer { | |
| name: "conv4_res32_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res32_conv1" | |
| top: "conv4_res32_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res32_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res32_conv1" | |
| top: "conv4_res32_conv1" | |
| } | |
| layer { | |
| name: "conv4_res32_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res32_conv1" | |
| top: "conv4_res32_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res32_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res32_conv2" | |
| top: "conv4_res32_conv2" | |
| } | |
| layer { | |
| name: "conv4_res32_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res32_conv2" | |
| top: "conv4_res32_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res32_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res32_conv2" | |
| top: "conv4_res32_conv2" | |
| } | |
| layer { | |
| name: "conv4_res32_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res32_conv2" | |
| top: "conv4_res32_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res32" | |
| type: "Eltwise" | |
| bottom: "conv4_res31" | |
| bottom: "conv4_res32_conv3" | |
| top: "conv4_res32" | |
| } | |
| layer { | |
| name: "conv4_res33_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res32" | |
| top: "conv4_res33_pre" | |
| } | |
| layer { | |
| name: "conv4_res33_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res33_pre" | |
| top: "conv4_res33_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res33_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res33_pre" | |
| top: "conv4_res33_pre" | |
| } | |
| layer { | |
| name: "conv4_res33_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res33_pre" | |
| top: "conv4_res33_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res33_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res33_conv1" | |
| top: "conv4_res33_conv1" | |
| } | |
| layer { | |
| name: "conv4_res33_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res33_conv1" | |
| top: "conv4_res33_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res33_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res33_conv1" | |
| top: "conv4_res33_conv1" | |
| } | |
| layer { | |
| name: "conv4_res33_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res33_conv1" | |
| top: "conv4_res33_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res33_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res33_conv2" | |
| top: "conv4_res33_conv2" | |
| } | |
| layer { | |
| name: "conv4_res33_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res33_conv2" | |
| top: "conv4_res33_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res33_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res33_conv2" | |
| top: "conv4_res33_conv2" | |
| } | |
| layer { | |
| name: "conv4_res33_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res33_conv2" | |
| top: "conv4_res33_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res33" | |
| type: "Eltwise" | |
| bottom: "conv4_res32" | |
| bottom: "conv4_res33_conv3" | |
| top: "conv4_res33" | |
| } | |
| layer { | |
| name: "conv4_res34_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res33" | |
| top: "conv4_res34_pre" | |
| } | |
| layer { | |
| name: "conv4_res34_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res34_pre" | |
| top: "conv4_res34_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res34_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res34_pre" | |
| top: "conv4_res34_pre" | |
| } | |
| layer { | |
| name: "conv4_res34_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res34_pre" | |
| top: "conv4_res34_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res34_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res34_conv1" | |
| top: "conv4_res34_conv1" | |
| } | |
| layer { | |
| name: "conv4_res34_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res34_conv1" | |
| top: "conv4_res34_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res34_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res34_conv1" | |
| top: "conv4_res34_conv1" | |
| } | |
| layer { | |
| name: "conv4_res34_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res34_conv1" | |
| top: "conv4_res34_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res34_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res34_conv2" | |
| top: "conv4_res34_conv2" | |
| } | |
| layer { | |
| name: "conv4_res34_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res34_conv2" | |
| top: "conv4_res34_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res34_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res34_conv2" | |
| top: "conv4_res34_conv2" | |
| } | |
| layer { | |
| name: "conv4_res34_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res34_conv2" | |
| top: "conv4_res34_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res34" | |
| type: "Eltwise" | |
| bottom: "conv4_res33" | |
| bottom: "conv4_res34_conv3" | |
| top: "conv4_res34" | |
| } | |
| layer { | |
| name: "conv4_res35_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res34" | |
| top: "conv4_res35_pre" | |
| } | |
| layer { | |
| name: "conv4_res35_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res35_pre" | |
| top: "conv4_res35_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res35_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res35_pre" | |
| top: "conv4_res35_pre" | |
| } | |
| layer { | |
| name: "conv4_res35_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res35_pre" | |
| top: "conv4_res35_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res35_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res35_conv1" | |
| top: "conv4_res35_conv1" | |
| } | |
| layer { | |
| name: "conv4_res35_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res35_conv1" | |
| top: "conv4_res35_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res35_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res35_conv1" | |
| top: "conv4_res35_conv1" | |
| } | |
| layer { | |
| name: "conv4_res35_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res35_conv1" | |
| top: "conv4_res35_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res35_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res35_conv2" | |
| top: "conv4_res35_conv2" | |
| } | |
| layer { | |
| name: "conv4_res35_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res35_conv2" | |
| top: "conv4_res35_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res35_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res35_conv2" | |
| top: "conv4_res35_conv2" | |
| } | |
| layer { | |
| name: "conv4_res35_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res35_conv2" | |
| top: "conv4_res35_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res35" | |
| type: "Eltwise" | |
| bottom: "conv4_res34" | |
| bottom: "conv4_res35_conv3" | |
| top: "conv4_res35" | |
| } | |
| layer { | |
| name: "conv4_res36_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res35" | |
| top: "conv4_res36_pre" | |
| } | |
| layer { | |
| name: "conv4_res36_pre_scale" | |
| type: "Scale" | |
| bottom: "conv4_res36_pre" | |
| top: "conv4_res36_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res36_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res36_pre" | |
| top: "conv4_res36_pre" | |
| } | |
| layer { | |
| name: "conv4_res36_conv1" | |
| type: "Convolution" | |
| bottom: "conv4_res36_pre" | |
| top: "conv4_res36_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res36_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res36_conv1" | |
| top: "conv4_res36_conv1" | |
| } | |
| layer { | |
| name: "conv4_res36_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv4_res36_conv1" | |
| top: "conv4_res36_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res36_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res36_conv1" | |
| top: "conv4_res36_conv1" | |
| } | |
| layer { | |
| name: "conv4_res36_conv2" | |
| type: "Convolution" | |
| bottom: "conv4_res36_conv1" | |
| top: "conv4_res36_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res36_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res36_conv2" | |
| top: "conv4_res36_conv2" | |
| } | |
| layer { | |
| name: "conv4_res36_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv4_res36_conv2" | |
| top: "conv4_res36_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res36_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv4_res36_conv2" | |
| top: "conv4_res36_conv2" | |
| } | |
| layer { | |
| name: "conv4_res36_conv3" | |
| type: "Convolution" | |
| bottom: "conv4_res36_conv2" | |
| top: "conv4_res36_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_res36" | |
| type: "Eltwise" | |
| bottom: "conv4_res35" | |
| bottom: "conv4_res36_conv3" | |
| top: "conv4_res36" | |
| } | |
| layer { | |
| name: "conv5_res1_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_res36" | |
| top: "conv5_res1_pre" | |
| } | |
| layer { | |
| name: "conv5_res1_pre_scale" | |
| type: "Scale" | |
| bottom: "conv5_res1_pre" | |
| top: "conv5_res1_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res1_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res1_pre" | |
| top: "conv5_res1_pre" | |
| } | |
| layer { | |
| name: "conv5_res1_proj" | |
| type: "Convolution" | |
| bottom: "conv5_res1_pre" | |
| top: "conv5_res1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res1_conv1" | |
| type: "Convolution" | |
| bottom: "conv5_res1_pre" | |
| top: "conv5_res1_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res1_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res1_conv1" | |
| top: "conv5_res1_conv1" | |
| } | |
| layer { | |
| name: "conv5_res1_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv5_res1_conv1" | |
| top: "conv5_res1_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res1_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res1_conv1" | |
| top: "conv5_res1_conv1" | |
| } | |
| layer { | |
| name: "conv5_res1_conv2" | |
| type: "Convolution" | |
| bottom: "conv5_res1_conv1" | |
| top: "conv5_res1_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res1_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res1_conv2" | |
| top: "conv5_res1_conv2" | |
| } | |
| layer { | |
| name: "conv5_res1_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv5_res1_conv2" | |
| top: "conv5_res1_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res1_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res1_conv2" | |
| top: "conv5_res1_conv2" | |
| } | |
| layer { | |
| name: "conv5_res1_conv3" | |
| type: "Convolution" | |
| bottom: "conv5_res1_conv2" | |
| top: "conv5_res1_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res1" | |
| type: "Eltwise" | |
| bottom: "conv5_res1_proj" | |
| bottom: "conv5_res1_conv3" | |
| top: "conv5_res1" | |
| } | |
| layer { | |
| name: "conv5_res2_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res1" | |
| top: "conv5_res2_pre" | |
| } | |
| layer { | |
| name: "conv5_res2_pre_scale" | |
| type: "Scale" | |
| bottom: "conv5_res2_pre" | |
| top: "conv5_res2_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res2_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res2_pre" | |
| top: "conv5_res2_pre" | |
| } | |
| layer { | |
| name: "conv5_res2_conv1" | |
| type: "Convolution" | |
| bottom: "conv5_res2_pre" | |
| top: "conv5_res2_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res2_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res2_conv1" | |
| top: "conv5_res2_conv1" | |
| } | |
| layer { | |
| name: "conv5_res2_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv5_res2_conv1" | |
| top: "conv5_res2_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res2_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res2_conv1" | |
| top: "conv5_res2_conv1" | |
| } | |
| layer { | |
| name: "conv5_res2_conv2" | |
| type: "Convolution" | |
| bottom: "conv5_res2_conv1" | |
| top: "conv5_res2_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res2_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res2_conv2" | |
| top: "conv5_res2_conv2" | |
| } | |
| layer { | |
| name: "conv5_res2_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv5_res2_conv2" | |
| top: "conv5_res2_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res2_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res2_conv2" | |
| top: "conv5_res2_conv2" | |
| } | |
| layer { | |
| name: "conv5_res2_conv3" | |
| type: "Convolution" | |
| bottom: "conv5_res2_conv2" | |
| top: "conv5_res2_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res2" | |
| type: "Eltwise" | |
| bottom: "conv5_res1" | |
| bottom: "conv5_res2_conv3" | |
| top: "conv5_res2" | |
| } | |
| layer { | |
| name: "conv5_res3_pre_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res2" | |
| top: "conv5_res3_pre" | |
| } | |
| layer { | |
| name: "conv5_res3_pre_scale" | |
| type: "Scale" | |
| bottom: "conv5_res3_pre" | |
| top: "conv5_res3_pre" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res3_pre_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res3_pre" | |
| top: "conv5_res3_pre" | |
| } | |
| layer { | |
| name: "conv5_res3_conv1" | |
| type: "Convolution" | |
| bottom: "conv5_res3_pre" | |
| top: "conv5_res3_conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res3_conv1_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res3_conv1" | |
| top: "conv5_res3_conv1" | |
| } | |
| layer { | |
| name: "conv5_res3_conv1_scale" | |
| type: "Scale" | |
| bottom: "conv5_res3_conv1" | |
| top: "conv5_res3_conv1" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res3_conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res3_conv1" | |
| top: "conv5_res3_conv1" | |
| } | |
| layer { | |
| name: "conv5_res3_conv2" | |
| type: "Convolution" | |
| bottom: "conv5_res3_conv1" | |
| top: "conv5_res3_conv2" | |
| 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: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res3_conv2_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res3_conv2" | |
| top: "conv5_res3_conv2" | |
| } | |
| layer { | |
| name: "conv5_res3_conv2_scale" | |
| type: "Scale" | |
| bottom: "conv5_res3_conv2" | |
| top: "conv5_res3_conv2" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res3_conv2_relu" | |
| type: "ReLU" | |
| bottom: "conv5_res3_conv2" | |
| top: "conv5_res3_conv2" | |
| } | |
| layer { | |
| name: "conv5_res3_conv3" | |
| type: "Convolution" | |
| bottom: "conv5_res3_conv2" | |
| top: "conv5_res3_conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_res3" | |
| type: "Eltwise" | |
| bottom: "conv5_res2" | |
| bottom: "conv5_res3_conv3" | |
| top: "conv5_res3" | |
| } | |
| layer { | |
| name: "conv5_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_res3" | |
| top: "conv5" | |
| } | |
| layer { | |
| name: "conv5_scale" | |
| type: "Scale" | |
| bottom: "conv5" | |
| top: "conv5" | |
| scale_param { | |
| filler { | |
| value: 1 | |
| } | |
| bias_term: true | |
| bias_filler { | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_relu" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| } | |
| layer { | |
| name: "pool5" | |
| type: "Pooling" | |
| bottom: "conv5" | |
| top: "pool5" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 7 | |
| stride: 1 | |
| pad: 0 | |
| } | |
| } | |
| layer { | |
| name: "fc" | |
| type: "InnerProduct" | |
| bottom: "pool5" | |
| top: "fc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 1000 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "fc" | |
| bottom: "label" | |
| bottom: 'gt_boxes' | |
| top: "loss" | |
| } | |
| layer { | |
| name: "accuracy_top1" | |
| type: "Accuracy" | |
| bottom: "fc" | |
| bottom: "label" | |
| bottom: 'gt_boxes' | |
| top: "accuracy_top1" | |
| include { | |
| phase: TEST | |
| } | |
| accuracy_param { | |
| top_k: 1 | |
| } | |
| } | |
| layer { | |
| name: "accuracy_top5" | |
| type: "Accuracy" | |
| bottom: "fc" | |
| bottom: "label" | |
| top: "accuracy_top5" | |
| include { | |
| phase: TEST | |
| } | |
| accuracy_param { | |
| top_k: 5 | |
| } | |
| } |
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