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October 27, 2017 14:33
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| # | |
| input: "data" | |
| input_shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 512 | |
| dim: 512 | |
| } | |
| layer { | |
| name: "data_sub1" | |
| type: "Scale" | |
| bottom: "data" | |
| top: "data_sub1" | |
| } | |
| layer { | |
| name: "data_sub2" | |
| type: "Convolution" | |
| bottom: "data_sub1" | |
| top: "data_sub2" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 3 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 2 | |
| group: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "bilinear" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_1_3x3_s2" | |
| type: "Convolution" | |
| bottom: "data_sub2" | |
| top: "conv1_1_3x3_s2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_1_3x3_s2/relu" | |
| type: "ReLU" | |
| bottom: "conv1_1_3x3_s2" | |
| top: "conv1_1_3x3_s2" | |
| } | |
| layer { | |
| name: "conv1_2_3x3" | |
| type: "Convolution" | |
| bottom: "conv1_1_3x3_s2" | |
| top: "conv1_2_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_2_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv1_2_3x3" | |
| top: "conv1_2_3x3" | |
| } | |
| layer { | |
| name: "conv1_3_3x3" | |
| type: "Convolution" | |
| bottom: "conv1_2_3x3" | |
| top: "conv1_3_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_3_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv1_3_3x3" | |
| top: "conv1_3_3x3" | |
| } | |
| layer { | |
| name: "pool1_3x3_s2" | |
| type: "Pooling" | |
| bottom: "conv1_3_3x3" | |
| top: "pool1_3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "pool1_3x3_s2" | |
| top: "conv2_1_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv2_1_1x1_reduce" | |
| top: "conv2_1_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv2_1_3x3" | |
| type: "Convolution" | |
| bottom: "conv2_1_1x1_reduce" | |
| top: "conv2_1_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv2_1_3x3" | |
| top: "conv2_1_3x3" | |
| } | |
| layer { | |
| name: "conv2_1_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv2_1_3x3" | |
| top: "conv2_1_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_1x1_proj" | |
| type: "Convolution" | |
| bottom: "pool1_3x3_s2" | |
| top: "conv2_1_1x1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1" | |
| type: "Eltwise" | |
| bottom: "conv2_1_1x1_proj" | |
| bottom: "conv2_1_1x1_increase" | |
| top: "conv2_1" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| } | |
| layer { | |
| name: "conv2_2_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv2_1" | |
| top: "conv2_2_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv2_2_1x1_reduce" | |
| top: "conv2_2_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv2_2_3x3" | |
| type: "Convolution" | |
| bottom: "conv2_2_1x1_reduce" | |
| top: "conv2_2_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv2_2_3x3" | |
| top: "conv2_2_3x3" | |
| } | |
| layer { | |
| name: "conv2_2_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv2_2_3x3" | |
| top: "conv2_2_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2" | |
| type: "Eltwise" | |
| bottom: "conv2_1" | |
| bottom: "conv2_2_1x1_increase" | |
| top: "conv2_2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/relu" | |
| type: "ReLU" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| } | |
| layer { | |
| name: "conv2_3_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv2_2" | |
| top: "conv2_3_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv2_3_1x1_reduce" | |
| top: "conv2_3_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv2_3_3x3" | |
| type: "Convolution" | |
| bottom: "conv2_3_1x1_reduce" | |
| top: "conv2_3_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv2_3_3x3" | |
| top: "conv2_3_3x3" | |
| } | |
| layer { | |
| name: "conv2_3_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv2_3_3x3" | |
| top: "conv2_3_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3" | |
| type: "Eltwise" | |
| bottom: "conv2_2" | |
| bottom: "conv2_3_1x1_increase" | |
| top: "conv2_3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/relu" | |
| type: "ReLU" | |
| bottom: "conv2_3" | |
| top: "conv2_3" | |
| } | |
| layer { | |
| name: "conv3_1_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv2_3" | |
| top: "conv3_1_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_1_1x1_reduce" | |
| top: "conv3_1_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv3_1_3x3" | |
| type: "Convolution" | |
| bottom: "conv3_1_1x1_reduce" | |
| top: "conv3_1_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv3_1_3x3" | |
| top: "conv3_1_3x3" | |
| } | |
| layer { | |
| name: "conv3_1_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_1_3x3" | |
| top: "conv3_1_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1_1x1_proj" | |
| type: "Convolution" | |
| bottom: "conv2_3" | |
| top: "conv3_1_1x1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1" | |
| type: "Eltwise" | |
| bottom: "conv3_1_1x1_proj" | |
| bottom: "conv3_1_1x1_increase" | |
| top: "conv3_1" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/relu" | |
| type: "ReLU" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| } | |
| layer { | |
| name: "conv3_1_sub4" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv3_1_sub4" | |
| param { | |
| lr_mult: 0.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 4 | |
| group: 256 | |
| stride: 2 | |
| weight_filler { | |
| type: "bilinear" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_1_sub4" | |
| top: "conv3_2_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_2_1x1_reduce" | |
| top: "conv3_2_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv3_2_3x3" | |
| type: "Convolution" | |
| bottom: "conv3_2_1x1_reduce" | |
| top: "conv3_2_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv3_2_3x3" | |
| top: "conv3_2_3x3" | |
| } | |
| layer { | |
| name: "conv3_2_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_2_3x3" | |
| top: "conv3_2_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2" | |
| type: "Eltwise" | |
| bottom: "conv3_1_sub4" | |
| bottom: "conv3_2_1x1_increase" | |
| top: "conv3_2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/relu" | |
| type: "ReLU" | |
| bottom: "conv3_2" | |
| top: "conv3_2" | |
| } | |
| layer { | |
| name: "conv3_3_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_2" | |
| top: "conv3_3_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_3_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_3_1x1_reduce" | |
| top: "conv3_3_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv3_3_3x3" | |
| type: "Convolution" | |
| bottom: "conv3_3_1x1_reduce" | |
| top: "conv3_3_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_3_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv3_3_3x3" | |
| top: "conv3_3_3x3" | |
| } | |
| layer { | |
| name: "conv3_3_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_3_3x3" | |
| top: "conv3_3_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_3" | |
| type: "Eltwise" | |
| bottom: "conv3_2" | |
| bottom: "conv3_3_1x1_increase" | |
| top: "conv3_3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/relu" | |
| type: "ReLU" | |
| bottom: "conv3_3" | |
| top: "conv3_3" | |
| } | |
| layer { | |
| name: "conv3_4_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_3" | |
| top: "conv3_4_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_4_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_4_1x1_reduce" | |
| top: "conv3_4_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv3_4_3x3" | |
| type: "Convolution" | |
| bottom: "conv3_4_1x1_reduce" | |
| top: "conv3_4_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_4_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv3_4_3x3" | |
| top: "conv3_4_3x3" | |
| } | |
| layer { | |
| name: "conv3_4_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_4_3x3" | |
| top: "conv3_4_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_4" | |
| type: "Eltwise" | |
| bottom: "conv3_3" | |
| bottom: "conv3_4_1x1_increase" | |
| top: "conv3_4" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/relu" | |
| type: "ReLU" | |
| bottom: "conv3_4" | |
| top: "conv3_4" | |
| } | |
| layer { | |
| name: "conv4_1_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_4" | |
| top: "conv4_1_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1_1x1_reduce" | |
| top: "conv4_1_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv4_1_3x3" | |
| type: "Convolution" | |
| bottom: "conv4_1_1x1_reduce" | |
| top: "conv4_1_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1_3x3" | |
| top: "conv4_1_3x3" | |
| } | |
| layer { | |
| name: "conv4_1_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_1_3x3" | |
| top: "conv4_1_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1_1x1_proj" | |
| type: "Convolution" | |
| bottom: "conv3_4" | |
| top: "conv4_1_1x1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1" | |
| type: "Eltwise" | |
| bottom: "conv4_1_1x1_proj" | |
| bottom: "conv4_1_1x1_increase" | |
| top: "conv4_1" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| } | |
| layer { | |
| name: "conv4_2_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv4_2_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2_1x1_reduce" | |
| top: "conv4_2_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv4_2_3x3" | |
| type: "Convolution" | |
| bottom: "conv4_2_1x1_reduce" | |
| top: "conv4_2_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2_3x3" | |
| top: "conv4_2_3x3" | |
| } | |
| layer { | |
| name: "conv4_2_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_2_3x3" | |
| top: "conv4_2_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2" | |
| type: "Eltwise" | |
| bottom: "conv4_1" | |
| bottom: "conv4_2_1x1_increase" | |
| top: "conv4_2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| } | |
| layer { | |
| name: "conv4_3_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_2" | |
| top: "conv4_3_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3_1x1_reduce" | |
| top: "conv4_3_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv4_3_3x3" | |
| type: "Convolution" | |
| bottom: "conv4_3_1x1_reduce" | |
| top: "conv4_3_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3_3x3" | |
| top: "conv4_3_3x3" | |
| } | |
| layer { | |
| name: "conv4_3_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_3_3x3" | |
| top: "conv4_3_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3" | |
| type: "Eltwise" | |
| bottom: "conv4_2" | |
| bottom: "conv4_3_1x1_increase" | |
| top: "conv4_3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3" | |
| top: "conv4_3" | |
| } | |
| layer { | |
| name: "conv4_4_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_3" | |
| top: "conv4_4_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4_1x1_reduce" | |
| top: "conv4_4_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv4_4_3x3" | |
| type: "Convolution" | |
| bottom: "conv4_4_1x1_reduce" | |
| top: "conv4_4_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4_3x3" | |
| top: "conv4_4_3x3" | |
| } | |
| layer { | |
| name: "conv4_4_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_4_3x3" | |
| top: "conv4_4_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4" | |
| type: "Eltwise" | |
| bottom: "conv4_3" | |
| bottom: "conv4_4_1x1_increase" | |
| top: "conv4_4" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4" | |
| top: "conv4_4" | |
| } | |
| layer { | |
| name: "conv4_5_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_4" | |
| top: "conv4_5_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_5_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_5_1x1_reduce" | |
| top: "conv4_5_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv4_5_3x3" | |
| type: "Convolution" | |
| bottom: "conv4_5_1x1_reduce" | |
| top: "conv4_5_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_5_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_5_3x3" | |
| top: "conv4_5_3x3" | |
| } | |
| layer { | |
| name: "conv4_5_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_5_3x3" | |
| top: "conv4_5_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_5" | |
| type: "Eltwise" | |
| bottom: "conv4_4" | |
| bottom: "conv4_5_1x1_increase" | |
| top: "conv4_5" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_5/relu" | |
| type: "ReLU" | |
| bottom: "conv4_5" | |
| top: "conv4_5" | |
| } | |
| layer { | |
| name: "conv4_6_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_5" | |
| top: "conv4_6_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_6_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_6_1x1_reduce" | |
| top: "conv4_6_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv4_6_3x3" | |
| type: "Convolution" | |
| bottom: "conv4_6_1x1_reduce" | |
| top: "conv4_6_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_6_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_6_3x3" | |
| top: "conv4_6_3x3" | |
| } | |
| layer { | |
| name: "conv4_6_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_6_3x3" | |
| top: "conv4_6_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_6" | |
| type: "Eltwise" | |
| bottom: "conv4_5" | |
| bottom: "conv4_6_1x1_increase" | |
| top: "conv4_6" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_6/relu" | |
| type: "ReLU" | |
| bottom: "conv4_6" | |
| top: "conv4_6" | |
| } | |
| layer { | |
| name: "conv5_1_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_6" | |
| top: "conv5_1_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1_1x1_reduce" | |
| top: "conv5_1_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv5_1_3x3" | |
| type: "Convolution" | |
| bottom: "conv5_1_1x1_reduce" | |
| top: "conv5_1_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 4 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 4 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1_3x3" | |
| top: "conv5_1_3x3" | |
| } | |
| layer { | |
| name: "conv5_1_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv5_1_3x3" | |
| top: "conv5_1_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1_1x1_proj" | |
| type: "Convolution" | |
| bottom: "conv4_6" | |
| top: "conv5_1_1x1_proj" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1" | |
| type: "Eltwise" | |
| bottom: "conv5_1_1x1_proj" | |
| bottom: "conv5_1_1x1_increase" | |
| top: "conv5_1" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1" | |
| top: "conv5_1" | |
| } | |
| layer { | |
| name: "conv5_2_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv5_2_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_2_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2_1x1_reduce" | |
| top: "conv5_2_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv5_2_3x3" | |
| type: "Convolution" | |
| bottom: "conv5_2_1x1_reduce" | |
| top: "conv5_2_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 4 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 4 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2_3x3" | |
| top: "conv5_2_3x3" | |
| } | |
| layer { | |
| name: "conv5_2_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv5_2_3x3" | |
| top: "conv5_2_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_2" | |
| type: "Eltwise" | |
| bottom: "conv5_1" | |
| bottom: "conv5_2_1x1_increase" | |
| top: "conv5_2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2" | |
| top: "conv5_2" | |
| } | |
| layer { | |
| name: "conv5_3_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv5_2" | |
| top: "conv5_3_1x1_reduce" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_3_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3_1x1_reduce" | |
| top: "conv5_3_1x1_reduce" | |
| } | |
| layer { | |
| name: "conv5_3_3x3" | |
| type: "Convolution" | |
| bottom: "conv5_3_1x1_reduce" | |
| top: "conv5_3_3x3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 4 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| dilation: 4 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3_3x3/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3_3x3" | |
| top: "conv5_3_3x3" | |
| } | |
| layer { | |
| name: "conv5_3_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv5_3_3x3" | |
| top: "conv5_3_1x1_increase" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_3" | |
| type: "Eltwise" | |
| bottom: "conv5_2" | |
| bottom: "conv5_3_1x1_increase" | |
| top: "conv5_3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3" | |
| top: "conv5_3" | |
| } | |
| layer { | |
| name: "conv5_3_pool1" | |
| type: "Pooling" | |
| bottom: "conv5_3" | |
| top: "conv5_3_pool1" | |
| pooling_param { | |
| pool: AVE | |
| kernel_h: 33 | |
| kernel_w: 65 | |
| stride_h: 33 | |
| stride_w: 65 | |
| } | |
| } |
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