| | 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
|
| | }
|
| | }
|
| |
|
