| input: "data"
|
| input_shape {
|
| dim: 1
|
| dim: 3
|
| dim: 300
|
| dim: 300
|
| }
|
|
|
| layer {
|
| name: "data_bn"
|
| type: "BatchNorm"
|
| bottom: "data"
|
| top: "data_bn"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "data_scale"
|
| type: "Scale"
|
| bottom: "data_bn"
|
| top: "data_bn"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "conv1_h"
|
| type: "Convolution"
|
| bottom: "data_bn"
|
| top: "conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 32
|
| pad: 3
|
| kernel_size: 7
|
| stride: 2
|
| weight_filler {
|
| type: "msra"
|
| variance_norm: FAN_OUT
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv1_bn_h"
|
| type: "BatchNorm"
|
| bottom: "conv1_h"
|
| top: "conv1_h"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "conv1_scale_h"
|
| type: "Scale"
|
| bottom: "conv1_h"
|
| top: "conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "conv1_relu"
|
| type: "ReLU"
|
| bottom: "conv1_h"
|
| top: "conv1_h"
|
| }
|
| layer {
|
| name: "conv1_pool"
|
| type: "Pooling"
|
| bottom: "conv1_h"
|
| top: "conv1_pool"
|
| pooling_param {
|
| kernel_size: 3
|
| stride: 2
|
| }
|
| }
|
| layer {
|
| name: "layer_64_1_conv1_h"
|
| type: "Convolution"
|
| bottom: "conv1_pool"
|
| top: "layer_64_1_conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 32
|
| bias_term: false
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_64_1_bn2_h"
|
| type: "BatchNorm"
|
| bottom: "layer_64_1_conv1_h"
|
| top: "layer_64_1_conv1_h"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "layer_64_1_scale2_h"
|
| type: "Scale"
|
| bottom: "layer_64_1_conv1_h"
|
| top: "layer_64_1_conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "layer_64_1_relu2"
|
| type: "ReLU"
|
| bottom: "layer_64_1_conv1_h"
|
| top: "layer_64_1_conv1_h"
|
| }
|
| layer {
|
| name: "layer_64_1_conv2_h"
|
| type: "Convolution"
|
| bottom: "layer_64_1_conv1_h"
|
| top: "layer_64_1_conv2_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 32
|
| bias_term: false
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_64_1_sum"
|
| type: "Eltwise"
|
| bottom: "layer_64_1_conv2_h"
|
| bottom: "conv1_pool"
|
| top: "layer_64_1_sum"
|
| }
|
| layer {
|
| name: "layer_128_1_bn1_h"
|
| type: "BatchNorm"
|
| bottom: "layer_64_1_sum"
|
| top: "layer_128_1_bn1_h"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "layer_128_1_scale1_h"
|
| type: "Scale"
|
| bottom: "layer_128_1_bn1_h"
|
| top: "layer_128_1_bn1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "layer_128_1_relu1"
|
| type: "ReLU"
|
| bottom: "layer_128_1_bn1_h"
|
| top: "layer_128_1_bn1_h"
|
| }
|
| layer {
|
| name: "layer_128_1_conv1_h"
|
| type: "Convolution"
|
| bottom: "layer_128_1_bn1_h"
|
| top: "layer_128_1_conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| bias_term: false
|
| pad: 1
|
| kernel_size: 3
|
| stride: 2
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_128_1_bn2"
|
| type: "BatchNorm"
|
| bottom: "layer_128_1_conv1_h"
|
| top: "layer_128_1_conv1_h"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "layer_128_1_scale2"
|
| type: "Scale"
|
| bottom: "layer_128_1_conv1_h"
|
| top: "layer_128_1_conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "layer_128_1_relu2"
|
| type: "ReLU"
|
| bottom: "layer_128_1_conv1_h"
|
| top: "layer_128_1_conv1_h"
|
| }
|
| layer {
|
| name: "layer_128_1_conv2"
|
| type: "Convolution"
|
| bottom: "layer_128_1_conv1_h"
|
| top: "layer_128_1_conv2"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| bias_term: false
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_128_1_conv_expand_h"
|
| type: "Convolution"
|
| bottom: "layer_128_1_bn1_h"
|
| top: "layer_128_1_conv_expand_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| bias_term: false
|
| pad: 0
|
| kernel_size: 1
|
| stride: 2
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_128_1_sum"
|
| type: "Eltwise"
|
| bottom: "layer_128_1_conv2"
|
| bottom: "layer_128_1_conv_expand_h"
|
| top: "layer_128_1_sum"
|
| }
|
| layer {
|
| name: "layer_256_1_bn1"
|
| type: "BatchNorm"
|
| bottom: "layer_128_1_sum"
|
| top: "layer_256_1_bn1"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "layer_256_1_scale1"
|
| type: "Scale"
|
| bottom: "layer_256_1_bn1"
|
| top: "layer_256_1_bn1"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "layer_256_1_relu1"
|
| type: "ReLU"
|
| bottom: "layer_256_1_bn1"
|
| top: "layer_256_1_bn1"
|
| }
|
| layer {
|
| name: "layer_256_1_conv1"
|
| type: "Convolution"
|
| bottom: "layer_256_1_bn1"
|
| top: "layer_256_1_conv1"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 256
|
| bias_term: false
|
| pad: 1
|
| kernel_size: 3
|
| stride: 2
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_256_1_bn2"
|
| type: "BatchNorm"
|
| bottom: "layer_256_1_conv1"
|
| top: "layer_256_1_conv1"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "layer_256_1_scale2"
|
| type: "Scale"
|
| bottom: "layer_256_1_conv1"
|
| top: "layer_256_1_conv1"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "layer_256_1_relu2"
|
| type: "ReLU"
|
| bottom: "layer_256_1_conv1"
|
| top: "layer_256_1_conv1"
|
| }
|
| layer {
|
| name: "layer_256_1_conv2"
|
| type: "Convolution"
|
| bottom: "layer_256_1_conv1"
|
| top: "layer_256_1_conv2"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 256
|
| bias_term: false
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_256_1_conv_expand"
|
| type: "Convolution"
|
| bottom: "layer_256_1_bn1"
|
| top: "layer_256_1_conv_expand"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 256
|
| bias_term: false
|
| pad: 0
|
| kernel_size: 1
|
| stride: 2
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_256_1_sum"
|
| type: "Eltwise"
|
| bottom: "layer_256_1_conv2"
|
| bottom: "layer_256_1_conv_expand"
|
| top: "layer_256_1_sum"
|
| }
|
| layer {
|
| name: "layer_512_1_bn1"
|
| type: "BatchNorm"
|
| bottom: "layer_256_1_sum"
|
| top: "layer_512_1_bn1"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "layer_512_1_scale1"
|
| type: "Scale"
|
| bottom: "layer_512_1_bn1"
|
| top: "layer_512_1_bn1"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "layer_512_1_relu1"
|
| type: "ReLU"
|
| bottom: "layer_512_1_bn1"
|
| top: "layer_512_1_bn1"
|
| }
|
| layer {
|
| name: "layer_512_1_conv1_h"
|
| type: "Convolution"
|
| bottom: "layer_512_1_bn1"
|
| top: "layer_512_1_conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| bias_term: false
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1 # 2
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_512_1_bn2_h"
|
| type: "BatchNorm"
|
| bottom: "layer_512_1_conv1_h"
|
| top: "layer_512_1_conv1_h"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "layer_512_1_scale2_h"
|
| type: "Scale"
|
| bottom: "layer_512_1_conv1_h"
|
| top: "layer_512_1_conv1_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "layer_512_1_relu2"
|
| type: "ReLU"
|
| bottom: "layer_512_1_conv1_h"
|
| top: "layer_512_1_conv1_h"
|
| }
|
| layer {
|
| name: "layer_512_1_conv2_h"
|
| type: "Convolution"
|
| bottom: "layer_512_1_conv1_h"
|
| top: "layer_512_1_conv2_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 256
|
| bias_term: false
|
| pad: 2 # 1
|
| kernel_size: 3
|
| stride: 1
|
| dilation: 2
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_512_1_conv_expand_h"
|
| type: "Convolution"
|
| bottom: "layer_512_1_bn1"
|
| top: "layer_512_1_conv_expand_h"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| convolution_param {
|
| num_output: 256
|
| bias_term: false
|
| pad: 0
|
| kernel_size: 1
|
| stride: 1 # 2
|
| weight_filler {
|
| type: "msra"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0.0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "layer_512_1_sum"
|
| type: "Eltwise"
|
| bottom: "layer_512_1_conv2_h"
|
| bottom: "layer_512_1_conv_expand_h"
|
| top: "layer_512_1_sum"
|
| }
|
| layer {
|
| name: "last_bn_h"
|
| type: "BatchNorm"
|
| bottom: "layer_512_1_sum"
|
| top: "layer_512_1_sum"
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| param {
|
| lr_mult: 0.0
|
| }
|
| }
|
| layer {
|
| name: "last_scale_h"
|
| type: "Scale"
|
| bottom: "layer_512_1_sum"
|
| top: "layer_512_1_sum"
|
| param {
|
| lr_mult: 1.0
|
| decay_mult: 1.0
|
| }
|
| param {
|
| lr_mult: 2.0
|
| decay_mult: 1.0
|
| }
|
| scale_param {
|
| bias_term: true
|
| }
|
| }
|
| layer {
|
| name: "last_relu"
|
| type: "ReLU"
|
| bottom: "layer_512_1_sum"
|
| top: "fc7"
|
| }
|
|
|
| layer {
|
| name: "conv6_1_h"
|
| type: "Convolution"
|
| bottom: "fc7"
|
| top: "conv6_1_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| pad: 0
|
| kernel_size: 1
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv6_1_relu"
|
| type: "ReLU"
|
| bottom: "conv6_1_h"
|
| top: "conv6_1_h"
|
| }
|
| layer {
|
| name: "conv6_2_h"
|
| type: "Convolution"
|
| bottom: "conv6_1_h"
|
| top: "conv6_2_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 256
|
| pad: 1
|
| kernel_size: 3
|
| stride: 2
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_relu"
|
| type: "ReLU"
|
| bottom: "conv6_2_h"
|
| top: "conv6_2_h"
|
| }
|
| layer {
|
| name: "conv7_1_h"
|
| type: "Convolution"
|
| bottom: "conv6_2_h"
|
| top: "conv7_1_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 64
|
| pad: 0
|
| kernel_size: 1
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv7_1_relu"
|
| type: "ReLU"
|
| bottom: "conv7_1_h"
|
| top: "conv7_1_h"
|
| }
|
| layer {
|
| name: "conv7_2_h"
|
| type: "Convolution"
|
| bottom: "conv7_1_h"
|
| top: "conv7_2_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| pad: 1
|
| kernel_size: 3
|
| stride: 2
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_relu"
|
| type: "ReLU"
|
| bottom: "conv7_2_h"
|
| top: "conv7_2_h"
|
| }
|
| layer {
|
| name: "conv8_1_h"
|
| type: "Convolution"
|
| bottom: "conv7_2_h"
|
| top: "conv8_1_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 64
|
| pad: 0
|
| kernel_size: 1
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv8_1_relu"
|
| type: "ReLU"
|
| bottom: "conv8_1_h"
|
| top: "conv8_1_h"
|
| }
|
| layer {
|
| name: "conv8_2_h"
|
| type: "Convolution"
|
| bottom: "conv8_1_h"
|
| top: "conv8_2_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_relu"
|
| type: "ReLU"
|
| bottom: "conv8_2_h"
|
| top: "conv8_2_h"
|
| }
|
| layer {
|
| name: "conv9_1_h"
|
| type: "Convolution"
|
| bottom: "conv8_2_h"
|
| top: "conv9_1_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 64
|
| pad: 0
|
| kernel_size: 1
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv9_1_relu"
|
| type: "ReLU"
|
| bottom: "conv9_1_h"
|
| top: "conv9_1_h"
|
| }
|
| layer {
|
| name: "conv9_2_h"
|
| type: "Convolution"
|
| bottom: "conv9_1_h"
|
| top: "conv9_2_h"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 128
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_relu"
|
| type: "ReLU"
|
| bottom: "conv9_2_h"
|
| top: "conv9_2_h"
|
| }
|
| layer {
|
| name: "conv4_3_norm"
|
| type: "Normalize"
|
| bottom: "layer_256_1_bn1"
|
| top: "conv4_3_norm"
|
| norm_param {
|
| across_spatial: false
|
| scale_filler {
|
| type: "constant"
|
| value: 20
|
| }
|
| channel_shared: false
|
| }
|
| }
|
| layer {
|
| name: "conv4_3_norm_mbox_loc"
|
| type: "Convolution"
|
| bottom: "conv4_3_norm"
|
| top: "conv4_3_norm_mbox_loc"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 16
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv4_3_norm_mbox_loc_perm"
|
| type: "Permute"
|
| bottom: "conv4_3_norm_mbox_loc"
|
| top: "conv4_3_norm_mbox_loc_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv4_3_norm_mbox_loc_flat"
|
| type: "Flatten"
|
| bottom: "conv4_3_norm_mbox_loc_perm"
|
| top: "conv4_3_norm_mbox_loc_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv4_3_norm_mbox_conf"
|
| type: "Convolution"
|
| bottom: "conv4_3_norm"
|
| top: "conv4_3_norm_mbox_conf"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 8 # 84
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv4_3_norm_mbox_conf_perm"
|
| type: "Permute"
|
| bottom: "conv4_3_norm_mbox_conf"
|
| top: "conv4_3_norm_mbox_conf_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv4_3_norm_mbox_conf_flat"
|
| type: "Flatten"
|
| bottom: "conv4_3_norm_mbox_conf_perm"
|
| top: "conv4_3_norm_mbox_conf_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv4_3_norm_mbox_priorbox"
|
| type: "PriorBox"
|
| bottom: "conv4_3_norm"
|
| bottom: "data"
|
| top: "conv4_3_norm_mbox_priorbox"
|
| prior_box_param {
|
| min_size: 30.0
|
| max_size: 60.0
|
| aspect_ratio: 2
|
| flip: true
|
| clip: false
|
| variance: 0.1
|
| variance: 0.1
|
| variance: 0.2
|
| variance: 0.2
|
| step: 8
|
| offset: 0.5
|
| }
|
| }
|
| layer {
|
| name: "fc7_mbox_loc"
|
| type: "Convolution"
|
| bottom: "fc7"
|
| top: "fc7_mbox_loc"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 24
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "fc7_mbox_loc_perm"
|
| type: "Permute"
|
| bottom: "fc7_mbox_loc"
|
| top: "fc7_mbox_loc_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "fc7_mbox_loc_flat"
|
| type: "Flatten"
|
| bottom: "fc7_mbox_loc_perm"
|
| top: "fc7_mbox_loc_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "fc7_mbox_conf"
|
| type: "Convolution"
|
| bottom: "fc7"
|
| top: "fc7_mbox_conf"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 12 # 126
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "fc7_mbox_conf_perm"
|
| type: "Permute"
|
| bottom: "fc7_mbox_conf"
|
| top: "fc7_mbox_conf_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "fc7_mbox_conf_flat"
|
| type: "Flatten"
|
| bottom: "fc7_mbox_conf_perm"
|
| top: "fc7_mbox_conf_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "fc7_mbox_priorbox"
|
| type: "PriorBox"
|
| bottom: "fc7"
|
| bottom: "data"
|
| top: "fc7_mbox_priorbox"
|
| prior_box_param {
|
| min_size: 60.0
|
| max_size: 111.0
|
| aspect_ratio: 2
|
| aspect_ratio: 3
|
| flip: true
|
| clip: false
|
| variance: 0.1
|
| variance: 0.1
|
| variance: 0.2
|
| variance: 0.2
|
| step: 16
|
| offset: 0.5
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_mbox_loc"
|
| type: "Convolution"
|
| bottom: "conv6_2_h"
|
| top: "conv6_2_mbox_loc"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 24
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_mbox_loc_perm"
|
| type: "Permute"
|
| bottom: "conv6_2_mbox_loc"
|
| top: "conv6_2_mbox_loc_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_mbox_loc_flat"
|
| type: "Flatten"
|
| bottom: "conv6_2_mbox_loc_perm"
|
| top: "conv6_2_mbox_loc_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_mbox_conf"
|
| type: "Convolution"
|
| bottom: "conv6_2_h"
|
| top: "conv6_2_mbox_conf"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 12 # 126
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_mbox_conf_perm"
|
| type: "Permute"
|
| bottom: "conv6_2_mbox_conf"
|
| top: "conv6_2_mbox_conf_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_mbox_conf_flat"
|
| type: "Flatten"
|
| bottom: "conv6_2_mbox_conf_perm"
|
| top: "conv6_2_mbox_conf_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv6_2_mbox_priorbox"
|
| type: "PriorBox"
|
| bottom: "conv6_2_h"
|
| bottom: "data"
|
| top: "conv6_2_mbox_priorbox"
|
| prior_box_param {
|
| min_size: 111.0
|
| max_size: 162.0
|
| aspect_ratio: 2
|
| aspect_ratio: 3
|
| flip: true
|
| clip: false
|
| variance: 0.1
|
| variance: 0.1
|
| variance: 0.2
|
| variance: 0.2
|
| step: 32
|
| offset: 0.5
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_mbox_loc"
|
| type: "Convolution"
|
| bottom: "conv7_2_h"
|
| top: "conv7_2_mbox_loc"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 24
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_mbox_loc_perm"
|
| type: "Permute"
|
| bottom: "conv7_2_mbox_loc"
|
| top: "conv7_2_mbox_loc_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_mbox_loc_flat"
|
| type: "Flatten"
|
| bottom: "conv7_2_mbox_loc_perm"
|
| top: "conv7_2_mbox_loc_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_mbox_conf"
|
| type: "Convolution"
|
| bottom: "conv7_2_h"
|
| top: "conv7_2_mbox_conf"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 12 # 126
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_mbox_conf_perm"
|
| type: "Permute"
|
| bottom: "conv7_2_mbox_conf"
|
| top: "conv7_2_mbox_conf_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_mbox_conf_flat"
|
| type: "Flatten"
|
| bottom: "conv7_2_mbox_conf_perm"
|
| top: "conv7_2_mbox_conf_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv7_2_mbox_priorbox"
|
| type: "PriorBox"
|
| bottom: "conv7_2_h"
|
| bottom: "data"
|
| top: "conv7_2_mbox_priorbox"
|
| prior_box_param {
|
| min_size: 162.0
|
| max_size: 213.0
|
| aspect_ratio: 2
|
| aspect_ratio: 3
|
| flip: true
|
| clip: false
|
| variance: 0.1
|
| variance: 0.1
|
| variance: 0.2
|
| variance: 0.2
|
| step: 64
|
| offset: 0.5
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_mbox_loc"
|
| type: "Convolution"
|
| bottom: "conv8_2_h"
|
| top: "conv8_2_mbox_loc"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 16
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_mbox_loc_perm"
|
| type: "Permute"
|
| bottom: "conv8_2_mbox_loc"
|
| top: "conv8_2_mbox_loc_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_mbox_loc_flat"
|
| type: "Flatten"
|
| bottom: "conv8_2_mbox_loc_perm"
|
| top: "conv8_2_mbox_loc_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_mbox_conf"
|
| type: "Convolution"
|
| bottom: "conv8_2_h"
|
| top: "conv8_2_mbox_conf"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 8 # 84
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_mbox_conf_perm"
|
| type: "Permute"
|
| bottom: "conv8_2_mbox_conf"
|
| top: "conv8_2_mbox_conf_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_mbox_conf_flat"
|
| type: "Flatten"
|
| bottom: "conv8_2_mbox_conf_perm"
|
| top: "conv8_2_mbox_conf_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv8_2_mbox_priorbox"
|
| type: "PriorBox"
|
| bottom: "conv8_2_h"
|
| bottom: "data"
|
| top: "conv8_2_mbox_priorbox"
|
| prior_box_param {
|
| min_size: 213.0
|
| max_size: 264.0
|
| aspect_ratio: 2
|
| flip: true
|
| clip: false
|
| variance: 0.1
|
| variance: 0.1
|
| variance: 0.2
|
| variance: 0.2
|
| step: 100
|
| offset: 0.5
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_mbox_loc"
|
| type: "Convolution"
|
| bottom: "conv9_2_h"
|
| top: "conv9_2_mbox_loc"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 16
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_mbox_loc_perm"
|
| type: "Permute"
|
| bottom: "conv9_2_mbox_loc"
|
| top: "conv9_2_mbox_loc_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_mbox_loc_flat"
|
| type: "Flatten"
|
| bottom: "conv9_2_mbox_loc_perm"
|
| top: "conv9_2_mbox_loc_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_mbox_conf"
|
| type: "Convolution"
|
| bottom: "conv9_2_h"
|
| top: "conv9_2_mbox_conf"
|
| param {
|
| lr_mult: 1
|
| decay_mult: 1
|
| }
|
| param {
|
| lr_mult: 2
|
| decay_mult: 0
|
| }
|
| convolution_param {
|
| num_output: 8 # 84
|
| pad: 1
|
| kernel_size: 3
|
| stride: 1
|
| weight_filler {
|
| type: "xavier"
|
| }
|
| bias_filler {
|
| type: "constant"
|
| value: 0
|
| }
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_mbox_conf_perm"
|
| type: "Permute"
|
| bottom: "conv9_2_mbox_conf"
|
| top: "conv9_2_mbox_conf_perm"
|
| permute_param {
|
| order: 0
|
| order: 2
|
| order: 3
|
| order: 1
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_mbox_conf_flat"
|
| type: "Flatten"
|
| bottom: "conv9_2_mbox_conf_perm"
|
| top: "conv9_2_mbox_conf_flat"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "conv9_2_mbox_priorbox"
|
| type: "PriorBox"
|
| bottom: "conv9_2_h"
|
| bottom: "data"
|
| top: "conv9_2_mbox_priorbox"
|
| prior_box_param {
|
| min_size: 264.0
|
| max_size: 315.0
|
| aspect_ratio: 2
|
| flip: true
|
| clip: false
|
| variance: 0.1
|
| variance: 0.1
|
| variance: 0.2
|
| variance: 0.2
|
| step: 300
|
| offset: 0.5
|
| }
|
| }
|
| layer {
|
| name: "mbox_loc"
|
| type: "Concat"
|
| bottom: "conv4_3_norm_mbox_loc_flat"
|
| bottom: "fc7_mbox_loc_flat"
|
| bottom: "conv6_2_mbox_loc_flat"
|
| bottom: "conv7_2_mbox_loc_flat"
|
| bottom: "conv8_2_mbox_loc_flat"
|
| bottom: "conv9_2_mbox_loc_flat"
|
| top: "mbox_loc"
|
| concat_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "mbox_conf"
|
| type: "Concat"
|
| bottom: "conv4_3_norm_mbox_conf_flat"
|
| bottom: "fc7_mbox_conf_flat"
|
| bottom: "conv6_2_mbox_conf_flat"
|
| bottom: "conv7_2_mbox_conf_flat"
|
| bottom: "conv8_2_mbox_conf_flat"
|
| bottom: "conv9_2_mbox_conf_flat"
|
| top: "mbox_conf"
|
| concat_param {
|
| axis: 1
|
| }
|
| }
|
| layer {
|
| name: "mbox_priorbox"
|
| type: "Concat"
|
| bottom: "conv4_3_norm_mbox_priorbox"
|
| bottom: "fc7_mbox_priorbox"
|
| bottom: "conv6_2_mbox_priorbox"
|
| bottom: "conv7_2_mbox_priorbox"
|
| bottom: "conv8_2_mbox_priorbox"
|
| bottom: "conv9_2_mbox_priorbox"
|
| top: "mbox_priorbox"
|
| concat_param {
|
| axis: 2
|
| }
|
| }
|
|
|
| layer {
|
| name: "mbox_conf_reshape"
|
| type: "Reshape"
|
| bottom: "mbox_conf"
|
| top: "mbox_conf_reshape"
|
| reshape_param {
|
| shape {
|
| dim: 0
|
| dim: -1
|
| dim: 2
|
| }
|
| }
|
| }
|
| layer {
|
| name: "mbox_conf_softmax"
|
| type: "Softmax"
|
| bottom: "mbox_conf_reshape"
|
| top: "mbox_conf_softmax"
|
| softmax_param {
|
| axis: 2
|
| }
|
| }
|
| layer {
|
| name: "mbox_conf_flatten"
|
| type: "Flatten"
|
| bottom: "mbox_conf_softmax"
|
| top: "mbox_conf_flatten"
|
| flatten_param {
|
| axis: 1
|
| }
|
| }
|
|
|
| layer {
|
| name: "detection_out"
|
| type: "DetectionOutput"
|
| bottom: "mbox_loc"
|
| bottom: "mbox_conf_flatten"
|
| bottom: "mbox_priorbox"
|
| top: "detection_out"
|
| include {
|
| phase: TEST
|
| }
|
| detection_output_param {
|
| num_classes: 2
|
| share_location: true
|
| background_label_id: 0
|
| nms_param {
|
| nms_threshold: 0.3
|
| top_k: 400
|
| }
|
| code_type: CENTER_SIZE
|
| keep_top_k: 200
|
| confidence_threshold: 0.01
|
| }
|
| }
|
|
|
