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+ input: "data"
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+ input_shape {
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+ dim: 1
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+ dim: 3
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+ dim: 300
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+ dim: 300
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+ }
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+
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+ layer {
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+ name: "data_bn"
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+ type: "BatchNorm"
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+ bottom: "data"
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+ top: "data_bn"
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ }
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+ layer {
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+ name: "data_scale"
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+ type: "Scale"
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+ bottom: "data_bn"
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+ top: "data_bn"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ param {
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+ lr_mult: 2.0
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+ decay_mult: 1.0
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+ }
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+ scale_param {
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+ bias_term: true
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+ }
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+ }
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+ layer {
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+ name: "conv1_h"
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+ type: "Convolution"
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+ bottom: "data_bn"
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+ top: "conv1_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ param {
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+ lr_mult: 2.0
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+ decay_mult: 1.0
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+ }
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+ convolution_param {
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+ num_output: 32
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+ pad: 3
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+ kernel_size: 7
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+ stride: 2
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+ weight_filler {
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+ type: "msra"
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+ variance_norm: FAN_OUT
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+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "conv1_bn_h"
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+ type: "BatchNorm"
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+ bottom: "conv1_h"
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+ top: "conv1_h"
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ }
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+ layer {
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+ name: "conv1_scale_h"
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+ type: "Scale"
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+ bottom: "conv1_h"
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+ top: "conv1_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ param {
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+ lr_mult: 2.0
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+ decay_mult: 1.0
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+ }
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+ scale_param {
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+ bias_term: true
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+ }
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+ }
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+ layer {
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+ name: "conv1_relu"
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+ type: "ReLU"
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+ bottom: "conv1_h"
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+ top: "conv1_h"
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+ }
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+ layer {
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+ name: "conv1_pool"
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+ type: "Pooling"
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+ bottom: "conv1_h"
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+ top: "conv1_pool"
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+ pooling_param {
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+ kernel_size: 3
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+ stride: 2
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+ }
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+ }
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+ layer {
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+ name: "layer_64_1_conv1_h"
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+ type: "Convolution"
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+ bottom: "conv1_pool"
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+ top: "layer_64_1_conv1_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ convolution_param {
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+ num_output: 32
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+ bias_term: false
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+ pad: 1
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+ kernel_size: 3
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+ stride: 1
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+ weight_filler {
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+ type: "msra"
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+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "layer_64_1_bn2_h"
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+ type: "BatchNorm"
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+ bottom: "layer_64_1_conv1_h"
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+ top: "layer_64_1_conv1_h"
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ }
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+ layer {
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+ name: "layer_64_1_scale2_h"
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+ type: "Scale"
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+ bottom: "layer_64_1_conv1_h"
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+ top: "layer_64_1_conv1_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ param {
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+ lr_mult: 2.0
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+ decay_mult: 1.0
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+ }
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+ scale_param {
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+ bias_term: true
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+ }
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+ }
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+ layer {
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+ name: "layer_64_1_relu2"
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+ type: "ReLU"
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+ bottom: "layer_64_1_conv1_h"
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+ top: "layer_64_1_conv1_h"
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+ }
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+ layer {
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+ name: "layer_64_1_conv2_h"
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+ type: "Convolution"
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+ bottom: "layer_64_1_conv1_h"
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+ top: "layer_64_1_conv2_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ convolution_param {
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+ num_output: 32
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+ bias_term: false
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+ pad: 1
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+ kernel_size: 3
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+ stride: 1
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+ weight_filler {
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+ type: "msra"
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+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "layer_64_1_sum"
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+ type: "Eltwise"
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+ bottom: "layer_64_1_conv2_h"
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+ bottom: "conv1_pool"
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+ top: "layer_64_1_sum"
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+ }
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+ layer {
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+ name: "layer_128_1_bn1_h"
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+ type: "BatchNorm"
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+ bottom: "layer_64_1_sum"
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+ top: "layer_128_1_bn1_h"
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ }
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+ layer {
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+ name: "layer_128_1_scale1_h"
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+ type: "Scale"
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+ bottom: "layer_128_1_bn1_h"
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+ top: "layer_128_1_bn1_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ param {
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+ lr_mult: 2.0
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+ decay_mult: 1.0
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+ }
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+ scale_param {
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+ bias_term: true
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+ }
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+ }
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+ layer {
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+ name: "layer_128_1_relu1"
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+ type: "ReLU"
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+ bottom: "layer_128_1_bn1_h"
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+ top: "layer_128_1_bn1_h"
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+ }
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+ layer {
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+ name: "layer_128_1_conv1_h"
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+ type: "Convolution"
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+ bottom: "layer_128_1_bn1_h"
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+ top: "layer_128_1_conv1_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ convolution_param {
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+ num_output: 128
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+ bias_term: false
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+ pad: 1
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+ kernel_size: 3
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+ stride: 2
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+ weight_filler {
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+ type: "msra"
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+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "layer_128_1_bn2"
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+ type: "BatchNorm"
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+ bottom: "layer_128_1_conv1_h"
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+ top: "layer_128_1_conv1_h"
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ }
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+ layer {
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+ name: "layer_128_1_scale2"
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+ type: "Scale"
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+ bottom: "layer_128_1_conv1_h"
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+ top: "layer_128_1_conv1_h"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ param {
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+ lr_mult: 2.0
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+ decay_mult: 1.0
299
+ }
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+ scale_param {
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+ bias_term: true
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+ }
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+ }
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+ layer {
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+ name: "layer_128_1_relu2"
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+ type: "ReLU"
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+ bottom: "layer_128_1_conv1_h"
308
+ top: "layer_128_1_conv1_h"
309
+ }
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+ layer {
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+ name: "layer_128_1_conv2"
312
+ type: "Convolution"
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+ bottom: "layer_128_1_conv1_h"
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+ top: "layer_128_1_conv2"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
318
+ }
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+ convolution_param {
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+ num_output: 128
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+ bias_term: false
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+ pad: 1
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+ kernel_size: 3
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+ stride: 1
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+ weight_filler {
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+ type: "msra"
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+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "layer_128_1_conv_expand_h"
336
+ type: "Convolution"
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+ bottom: "layer_128_1_bn1_h"
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+ top: "layer_128_1_conv_expand_h"
339
+ param {
340
+ lr_mult: 1.0
341
+ decay_mult: 1.0
342
+ }
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+ convolution_param {
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+ num_output: 128
345
+ bias_term: false
346
+ pad: 0
347
+ kernel_size: 1
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+ stride: 2
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+ weight_filler {
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+ type: "msra"
351
+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
355
+ }
356
+ }
357
+ }
358
+ layer {
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+ name: "layer_128_1_sum"
360
+ type: "Eltwise"
361
+ bottom: "layer_128_1_conv2"
362
+ bottom: "layer_128_1_conv_expand_h"
363
+ top: "layer_128_1_sum"
364
+ }
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+ layer {
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+ name: "layer_256_1_bn1"
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+ type: "BatchNorm"
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+ bottom: "layer_128_1_sum"
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+ top: "layer_256_1_bn1"
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
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+ }
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+ }
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+ layer {
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+ name: "layer_256_1_scale1"
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+ type: "Scale"
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+ bottom: "layer_256_1_bn1"
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+ top: "layer_256_1_bn1"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
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+ }
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+ param {
390
+ lr_mult: 2.0
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+ decay_mult: 1.0
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+ }
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+ scale_param {
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+ bias_term: true
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+ }
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+ }
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+ layer {
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+ name: "layer_256_1_relu1"
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+ type: "ReLU"
400
+ bottom: "layer_256_1_bn1"
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+ top: "layer_256_1_bn1"
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+ }
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+ layer {
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+ name: "layer_256_1_conv1"
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+ type: "Convolution"
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+ bottom: "layer_256_1_bn1"
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+ top: "layer_256_1_conv1"
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+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
411
+ }
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+ convolution_param {
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+ num_output: 256
414
+ bias_term: false
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+ pad: 1
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+ kernel_size: 3
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+ stride: 2
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+ weight_filler {
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+ type: "msra"
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+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "layer_256_1_bn2"
429
+ type: "BatchNorm"
430
+ bottom: "layer_256_1_conv1"
431
+ top: "layer_256_1_conv1"
432
+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
436
+ lr_mult: 0.0
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+ }
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+ param {
439
+ lr_mult: 0.0
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+ }
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+ }
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+ layer {
443
+ name: "layer_256_1_scale2"
444
+ type: "Scale"
445
+ bottom: "layer_256_1_conv1"
446
+ top: "layer_256_1_conv1"
447
+ param {
448
+ lr_mult: 1.0
449
+ decay_mult: 1.0
450
+ }
451
+ param {
452
+ lr_mult: 2.0
453
+ decay_mult: 1.0
454
+ }
455
+ scale_param {
456
+ bias_term: true
457
+ }
458
+ }
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+ layer {
460
+ name: "layer_256_1_relu2"
461
+ type: "ReLU"
462
+ bottom: "layer_256_1_conv1"
463
+ top: "layer_256_1_conv1"
464
+ }
465
+ layer {
466
+ name: "layer_256_1_conv2"
467
+ type: "Convolution"
468
+ bottom: "layer_256_1_conv1"
469
+ top: "layer_256_1_conv2"
470
+ param {
471
+ lr_mult: 1.0
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+ decay_mult: 1.0
473
+ }
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+ convolution_param {
475
+ num_output: 256
476
+ bias_term: false
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+ pad: 1
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+ kernel_size: 3
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+ stride: 1
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+ weight_filler {
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+ type: "msra"
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+ }
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+ bias_filler {
484
+ type: "constant"
485
+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "layer_256_1_conv_expand"
491
+ type: "Convolution"
492
+ bottom: "layer_256_1_bn1"
493
+ top: "layer_256_1_conv_expand"
494
+ param {
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+ lr_mult: 1.0
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+ decay_mult: 1.0
497
+ }
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+ convolution_param {
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+ num_output: 256
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+ bias_term: false
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+ pad: 0
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+ kernel_size: 1
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+ stride: 2
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+ weight_filler {
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+ type: "msra"
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+ }
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+ bias_filler {
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+ type: "constant"
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+ value: 0.0
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+ }
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+ }
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+ }
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+ layer {
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+ name: "layer_256_1_sum"
515
+ type: "Eltwise"
516
+ bottom: "layer_256_1_conv2"
517
+ bottom: "layer_256_1_conv_expand"
518
+ top: "layer_256_1_sum"
519
+ }
520
+ layer {
521
+ name: "layer_512_1_bn1"
522
+ type: "BatchNorm"
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+ bottom: "layer_256_1_sum"
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+ top: "layer_512_1_bn1"
525
+ param {
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+ lr_mult: 0.0
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+ }
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+ param {
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+ lr_mult: 0.0
530
+ }
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+ param {
532
+ lr_mult: 0.0
533
+ }
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+ }
535
+ layer {
536
+ name: "layer_512_1_scale1"
537
+ type: "Scale"
538
+ bottom: "layer_512_1_bn1"
539
+ top: "layer_512_1_bn1"
540
+ param {
541
+ lr_mult: 1.0
542
+ decay_mult: 1.0
543
+ }
544
+ param {
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+ lr_mult: 2.0
546
+ decay_mult: 1.0
547
+ }
548
+ scale_param {
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+ bias_term: true
550
+ }
551
+ }
552
+ layer {
553
+ name: "layer_512_1_relu1"
554
+ type: "ReLU"
555
+ bottom: "layer_512_1_bn1"
556
+ top: "layer_512_1_bn1"
557
+ }
558
+ layer {
559
+ name: "layer_512_1_conv1_h"
560
+ type: "Convolution"
561
+ bottom: "layer_512_1_bn1"
562
+ top: "layer_512_1_conv1_h"
563
+ param {
564
+ lr_mult: 1.0
565
+ decay_mult: 1.0
566
+ }
567
+ convolution_param {
568
+ num_output: 128
569
+ bias_term: false
570
+ pad: 1
571
+ kernel_size: 3
572
+ stride: 1 # 2
573
+ weight_filler {
574
+ type: "msra"
575
+ }
576
+ bias_filler {
577
+ type: "constant"
578
+ value: 0.0
579
+ }
580
+ }
581
+ }
582
+ layer {
583
+ name: "layer_512_1_bn2_h"
584
+ type: "BatchNorm"
585
+ bottom: "layer_512_1_conv1_h"
586
+ top: "layer_512_1_conv1_h"
587
+ param {
588
+ lr_mult: 0.0
589
+ }
590
+ param {
591
+ lr_mult: 0.0
592
+ }
593
+ param {
594
+ lr_mult: 0.0
595
+ }
596
+ }
597
+ layer {
598
+ name: "layer_512_1_scale2_h"
599
+ type: "Scale"
600
+ bottom: "layer_512_1_conv1_h"
601
+ top: "layer_512_1_conv1_h"
602
+ param {
603
+ lr_mult: 1.0
604
+ decay_mult: 1.0
605
+ }
606
+ param {
607
+ lr_mult: 2.0
608
+ decay_mult: 1.0
609
+ }
610
+ scale_param {
611
+ bias_term: true
612
+ }
613
+ }
614
+ layer {
615
+ name: "layer_512_1_relu2"
616
+ type: "ReLU"
617
+ bottom: "layer_512_1_conv1_h"
618
+ top: "layer_512_1_conv1_h"
619
+ }
620
+ layer {
621
+ name: "layer_512_1_conv2_h"
622
+ type: "Convolution"
623
+ bottom: "layer_512_1_conv1_h"
624
+ top: "layer_512_1_conv2_h"
625
+ param {
626
+ lr_mult: 1.0
627
+ decay_mult: 1.0
628
+ }
629
+ convolution_param {
630
+ num_output: 256
631
+ bias_term: false
632
+ pad: 2 # 1
633
+ kernel_size: 3
634
+ stride: 1
635
+ dilation: 2
636
+ weight_filler {
637
+ type: "msra"
638
+ }
639
+ bias_filler {
640
+ type: "constant"
641
+ value: 0.0
642
+ }
643
+ }
644
+ }
645
+ layer {
646
+ name: "layer_512_1_conv_expand_h"
647
+ type: "Convolution"
648
+ bottom: "layer_512_1_bn1"
649
+ top: "layer_512_1_conv_expand_h"
650
+ param {
651
+ lr_mult: 1.0
652
+ decay_mult: 1.0
653
+ }
654
+ convolution_param {
655
+ num_output: 256
656
+ bias_term: false
657
+ pad: 0
658
+ kernel_size: 1
659
+ stride: 1 # 2
660
+ weight_filler {
661
+ type: "msra"
662
+ }
663
+ bias_filler {
664
+ type: "constant"
665
+ value: 0.0
666
+ }
667
+ }
668
+ }
669
+ layer {
670
+ name: "layer_512_1_sum"
671
+ type: "Eltwise"
672
+ bottom: "layer_512_1_conv2_h"
673
+ bottom: "layer_512_1_conv_expand_h"
674
+ top: "layer_512_1_sum"
675
+ }
676
+ layer {
677
+ name: "last_bn_h"
678
+ type: "BatchNorm"
679
+ bottom: "layer_512_1_sum"
680
+ top: "layer_512_1_sum"
681
+ param {
682
+ lr_mult: 0.0
683
+ }
684
+ param {
685
+ lr_mult: 0.0
686
+ }
687
+ param {
688
+ lr_mult: 0.0
689
+ }
690
+ }
691
+ layer {
692
+ name: "last_scale_h"
693
+ type: "Scale"
694
+ bottom: "layer_512_1_sum"
695
+ top: "layer_512_1_sum"
696
+ param {
697
+ lr_mult: 1.0
698
+ decay_mult: 1.0
699
+ }
700
+ param {
701
+ lr_mult: 2.0
702
+ decay_mult: 1.0
703
+ }
704
+ scale_param {
705
+ bias_term: true
706
+ }
707
+ }
708
+ layer {
709
+ name: "last_relu"
710
+ type: "ReLU"
711
+ bottom: "layer_512_1_sum"
712
+ top: "fc7"
713
+ }
714
+
715
+ layer {
716
+ name: "conv6_1_h"
717
+ type: "Convolution"
718
+ bottom: "fc7"
719
+ top: "conv6_1_h"
720
+ param {
721
+ lr_mult: 1
722
+ decay_mult: 1
723
+ }
724
+ param {
725
+ lr_mult: 2
726
+ decay_mult: 0
727
+ }
728
+ convolution_param {
729
+ num_output: 128
730
+ pad: 0
731
+ kernel_size: 1
732
+ stride: 1
733
+ weight_filler {
734
+ type: "xavier"
735
+ }
736
+ bias_filler {
737
+ type: "constant"
738
+ value: 0
739
+ }
740
+ }
741
+ }
742
+ layer {
743
+ name: "conv6_1_relu"
744
+ type: "ReLU"
745
+ bottom: "conv6_1_h"
746
+ top: "conv6_1_h"
747
+ }
748
+ layer {
749
+ name: "conv6_2_h"
750
+ type: "Convolution"
751
+ bottom: "conv6_1_h"
752
+ top: "conv6_2_h"
753
+ param {
754
+ lr_mult: 1
755
+ decay_mult: 1
756
+ }
757
+ param {
758
+ lr_mult: 2
759
+ decay_mult: 0
760
+ }
761
+ convolution_param {
762
+ num_output: 256
763
+ pad: 1
764
+ kernel_size: 3
765
+ stride: 2
766
+ weight_filler {
767
+ type: "xavier"
768
+ }
769
+ bias_filler {
770
+ type: "constant"
771
+ value: 0
772
+ }
773
+ }
774
+ }
775
+ layer {
776
+ name: "conv6_2_relu"
777
+ type: "ReLU"
778
+ bottom: "conv6_2_h"
779
+ top: "conv6_2_h"
780
+ }
781
+ layer {
782
+ name: "conv7_1_h"
783
+ type: "Convolution"
784
+ bottom: "conv6_2_h"
785
+ top: "conv7_1_h"
786
+ param {
787
+ lr_mult: 1
788
+ decay_mult: 1
789
+ }
790
+ param {
791
+ lr_mult: 2
792
+ decay_mult: 0
793
+ }
794
+ convolution_param {
795
+ num_output: 64
796
+ pad: 0
797
+ kernel_size: 1
798
+ stride: 1
799
+ weight_filler {
800
+ type: "xavier"
801
+ }
802
+ bias_filler {
803
+ type: "constant"
804
+ value: 0
805
+ }
806
+ }
807
+ }
808
+ layer {
809
+ name: "conv7_1_relu"
810
+ type: "ReLU"
811
+ bottom: "conv7_1_h"
812
+ top: "conv7_1_h"
813
+ }
814
+ layer {
815
+ name: "conv7_2_h"
816
+ type: "Convolution"
817
+ bottom: "conv7_1_h"
818
+ top: "conv7_2_h"
819
+ param {
820
+ lr_mult: 1
821
+ decay_mult: 1
822
+ }
823
+ param {
824
+ lr_mult: 2
825
+ decay_mult: 0
826
+ }
827
+ convolution_param {
828
+ num_output: 128
829
+ pad: 1
830
+ kernel_size: 3
831
+ stride: 2
832
+ weight_filler {
833
+ type: "xavier"
834
+ }
835
+ bias_filler {
836
+ type: "constant"
837
+ value: 0
838
+ }
839
+ }
840
+ }
841
+ layer {
842
+ name: "conv7_2_relu"
843
+ type: "ReLU"
844
+ bottom: "conv7_2_h"
845
+ top: "conv7_2_h"
846
+ }
847
+ layer {
848
+ name: "conv8_1_h"
849
+ type: "Convolution"
850
+ bottom: "conv7_2_h"
851
+ top: "conv8_1_h"
852
+ param {
853
+ lr_mult: 1
854
+ decay_mult: 1
855
+ }
856
+ param {
857
+ lr_mult: 2
858
+ decay_mult: 0
859
+ }
860
+ convolution_param {
861
+ num_output: 64
862
+ pad: 0
863
+ kernel_size: 1
864
+ stride: 1
865
+ weight_filler {
866
+ type: "xavier"
867
+ }
868
+ bias_filler {
869
+ type: "constant"
870
+ value: 0
871
+ }
872
+ }
873
+ }
874
+ layer {
875
+ name: "conv8_1_relu"
876
+ type: "ReLU"
877
+ bottom: "conv8_1_h"
878
+ top: "conv8_1_h"
879
+ }
880
+ layer {
881
+ name: "conv8_2_h"
882
+ type: "Convolution"
883
+ bottom: "conv8_1_h"
884
+ top: "conv8_2_h"
885
+ param {
886
+ lr_mult: 1
887
+ decay_mult: 1
888
+ }
889
+ param {
890
+ lr_mult: 2
891
+ decay_mult: 0
892
+ }
893
+ convolution_param {
894
+ num_output: 128
895
+ pad: 1
896
+ kernel_size: 3
897
+ stride: 1
898
+ weight_filler {
899
+ type: "xavier"
900
+ }
901
+ bias_filler {
902
+ type: "constant"
903
+ value: 0
904
+ }
905
+ }
906
+ }
907
+ layer {
908
+ name: "conv8_2_relu"
909
+ type: "ReLU"
910
+ bottom: "conv8_2_h"
911
+ top: "conv8_2_h"
912
+ }
913
+ layer {
914
+ name: "conv9_1_h"
915
+ type: "Convolution"
916
+ bottom: "conv8_2_h"
917
+ top: "conv9_1_h"
918
+ param {
919
+ lr_mult: 1
920
+ decay_mult: 1
921
+ }
922
+ param {
923
+ lr_mult: 2
924
+ decay_mult: 0
925
+ }
926
+ convolution_param {
927
+ num_output: 64
928
+ pad: 0
929
+ kernel_size: 1
930
+ stride: 1
931
+ weight_filler {
932
+ type: "xavier"
933
+ }
934
+ bias_filler {
935
+ type: "constant"
936
+ value: 0
937
+ }
938
+ }
939
+ }
940
+ layer {
941
+ name: "conv9_1_relu"
942
+ type: "ReLU"
943
+ bottom: "conv9_1_h"
944
+ top: "conv9_1_h"
945
+ }
946
+ layer {
947
+ name: "conv9_2_h"
948
+ type: "Convolution"
949
+ bottom: "conv9_1_h"
950
+ top: "conv9_2_h"
951
+ param {
952
+ lr_mult: 1
953
+ decay_mult: 1
954
+ }
955
+ param {
956
+ lr_mult: 2
957
+ decay_mult: 0
958
+ }
959
+ convolution_param {
960
+ num_output: 128
961
+ pad: 1
962
+ kernel_size: 3
963
+ stride: 1
964
+ weight_filler {
965
+ type: "xavier"
966
+ }
967
+ bias_filler {
968
+ type: "constant"
969
+ value: 0
970
+ }
971
+ }
972
+ }
973
+ layer {
974
+ name: "conv9_2_relu"
975
+ type: "ReLU"
976
+ bottom: "conv9_2_h"
977
+ top: "conv9_2_h"
978
+ }
979
+ layer {
980
+ name: "conv4_3_norm"
981
+ type: "Normalize"
982
+ bottom: "layer_256_1_bn1"
983
+ top: "conv4_3_norm"
984
+ norm_param {
985
+ across_spatial: false
986
+ scale_filler {
987
+ type: "constant"
988
+ value: 20
989
+ }
990
+ channel_shared: false
991
+ }
992
+ }
993
+ layer {
994
+ name: "conv4_3_norm_mbox_loc"
995
+ type: "Convolution"
996
+ bottom: "conv4_3_norm"
997
+ top: "conv4_3_norm_mbox_loc"
998
+ param {
999
+ lr_mult: 1
1000
+ decay_mult: 1
1001
+ }
1002
+ param {
1003
+ lr_mult: 2
1004
+ decay_mult: 0
1005
+ }
1006
+ convolution_param {
1007
+ num_output: 16
1008
+ pad: 1
1009
+ kernel_size: 3
1010
+ stride: 1
1011
+ weight_filler {
1012
+ type: "xavier"
1013
+ }
1014
+ bias_filler {
1015
+ type: "constant"
1016
+ value: 0
1017
+ }
1018
+ }
1019
+ }
1020
+ layer {
1021
+ name: "conv4_3_norm_mbox_loc_perm"
1022
+ type: "Permute"
1023
+ bottom: "conv4_3_norm_mbox_loc"
1024
+ top: "conv4_3_norm_mbox_loc_perm"
1025
+ permute_param {
1026
+ order: 0
1027
+ order: 2
1028
+ order: 3
1029
+ order: 1
1030
+ }
1031
+ }
1032
+ layer {
1033
+ name: "conv4_3_norm_mbox_loc_flat"
1034
+ type: "Flatten"
1035
+ bottom: "conv4_3_norm_mbox_loc_perm"
1036
+ top: "conv4_3_norm_mbox_loc_flat"
1037
+ flatten_param {
1038
+ axis: 1
1039
+ }
1040
+ }
1041
+ layer {
1042
+ name: "conv4_3_norm_mbox_conf"
1043
+ type: "Convolution"
1044
+ bottom: "conv4_3_norm"
1045
+ top: "conv4_3_norm_mbox_conf"
1046
+ param {
1047
+ lr_mult: 1
1048
+ decay_mult: 1
1049
+ }
1050
+ param {
1051
+ lr_mult: 2
1052
+ decay_mult: 0
1053
+ }
1054
+ convolution_param {
1055
+ num_output: 8 # 84
1056
+ pad: 1
1057
+ kernel_size: 3
1058
+ stride: 1
1059
+ weight_filler {
1060
+ type: "xavier"
1061
+ }
1062
+ bias_filler {
1063
+ type: "constant"
1064
+ value: 0
1065
+ }
1066
+ }
1067
+ }
1068
+ layer {
1069
+ name: "conv4_3_norm_mbox_conf_perm"
1070
+ type: "Permute"
1071
+ bottom: "conv4_3_norm_mbox_conf"
1072
+ top: "conv4_3_norm_mbox_conf_perm"
1073
+ permute_param {
1074
+ order: 0
1075
+ order: 2
1076
+ order: 3
1077
+ order: 1
1078
+ }
1079
+ }
1080
+ layer {
1081
+ name: "conv4_3_norm_mbox_conf_flat"
1082
+ type: "Flatten"
1083
+ bottom: "conv4_3_norm_mbox_conf_perm"
1084
+ top: "conv4_3_norm_mbox_conf_flat"
1085
+ flatten_param {
1086
+ axis: 1
1087
+ }
1088
+ }
1089
+ layer {
1090
+ name: "conv4_3_norm_mbox_priorbox"
1091
+ type: "PriorBox"
1092
+ bottom: "conv4_3_norm"
1093
+ bottom: "data"
1094
+ top: "conv4_3_norm_mbox_priorbox"
1095
+ prior_box_param {
1096
+ min_size: 30.0
1097
+ max_size: 60.0
1098
+ aspect_ratio: 2
1099
+ flip: true
1100
+ clip: false
1101
+ variance: 0.1
1102
+ variance: 0.1
1103
+ variance: 0.2
1104
+ variance: 0.2
1105
+ step: 8
1106
+ offset: 0.5
1107
+ }
1108
+ }
1109
+ layer {
1110
+ name: "fc7_mbox_loc"
1111
+ type: "Convolution"
1112
+ bottom: "fc7"
1113
+ top: "fc7_mbox_loc"
1114
+ param {
1115
+ lr_mult: 1
1116
+ decay_mult: 1
1117
+ }
1118
+ param {
1119
+ lr_mult: 2
1120
+ decay_mult: 0
1121
+ }
1122
+ convolution_param {
1123
+ num_output: 24
1124
+ pad: 1
1125
+ kernel_size: 3
1126
+ stride: 1
1127
+ weight_filler {
1128
+ type: "xavier"
1129
+ }
1130
+ bias_filler {
1131
+ type: "constant"
1132
+ value: 0
1133
+ }
1134
+ }
1135
+ }
1136
+ layer {
1137
+ name: "fc7_mbox_loc_perm"
1138
+ type: "Permute"
1139
+ bottom: "fc7_mbox_loc"
1140
+ top: "fc7_mbox_loc_perm"
1141
+ permute_param {
1142
+ order: 0
1143
+ order: 2
1144
+ order: 3
1145
+ order: 1
1146
+ }
1147
+ }
1148
+ layer {
1149
+ name: "fc7_mbox_loc_flat"
1150
+ type: "Flatten"
1151
+ bottom: "fc7_mbox_loc_perm"
1152
+ top: "fc7_mbox_loc_flat"
1153
+ flatten_param {
1154
+ axis: 1
1155
+ }
1156
+ }
1157
+ layer {
1158
+ name: "fc7_mbox_conf"
1159
+ type: "Convolution"
1160
+ bottom: "fc7"
1161
+ top: "fc7_mbox_conf"
1162
+ param {
1163
+ lr_mult: 1
1164
+ decay_mult: 1
1165
+ }
1166
+ param {
1167
+ lr_mult: 2
1168
+ decay_mult: 0
1169
+ }
1170
+ convolution_param {
1171
+ num_output: 12 # 126
1172
+ pad: 1
1173
+ kernel_size: 3
1174
+ stride: 1
1175
+ weight_filler {
1176
+ type: "xavier"
1177
+ }
1178
+ bias_filler {
1179
+ type: "constant"
1180
+ value: 0
1181
+ }
1182
+ }
1183
+ }
1184
+ layer {
1185
+ name: "fc7_mbox_conf_perm"
1186
+ type: "Permute"
1187
+ bottom: "fc7_mbox_conf"
1188
+ top: "fc7_mbox_conf_perm"
1189
+ permute_param {
1190
+ order: 0
1191
+ order: 2
1192
+ order: 3
1193
+ order: 1
1194
+ }
1195
+ }
1196
+ layer {
1197
+ name: "fc7_mbox_conf_flat"
1198
+ type: "Flatten"
1199
+ bottom: "fc7_mbox_conf_perm"
1200
+ top: "fc7_mbox_conf_flat"
1201
+ flatten_param {
1202
+ axis: 1
1203
+ }
1204
+ }
1205
+ layer {
1206
+ name: "fc7_mbox_priorbox"
1207
+ type: "PriorBox"
1208
+ bottom: "fc7"
1209
+ bottom: "data"
1210
+ top: "fc7_mbox_priorbox"
1211
+ prior_box_param {
1212
+ min_size: 60.0
1213
+ max_size: 111.0
1214
+ aspect_ratio: 2
1215
+ aspect_ratio: 3
1216
+ flip: true
1217
+ clip: false
1218
+ variance: 0.1
1219
+ variance: 0.1
1220
+ variance: 0.2
1221
+ variance: 0.2
1222
+ step: 16
1223
+ offset: 0.5
1224
+ }
1225
+ }
1226
+ layer {
1227
+ name: "conv6_2_mbox_loc"
1228
+ type: "Convolution"
1229
+ bottom: "conv6_2_h"
1230
+ top: "conv6_2_mbox_loc"
1231
+ param {
1232
+ lr_mult: 1
1233
+ decay_mult: 1
1234
+ }
1235
+ param {
1236
+ lr_mult: 2
1237
+ decay_mult: 0
1238
+ }
1239
+ convolution_param {
1240
+ num_output: 24
1241
+ pad: 1
1242
+ kernel_size: 3
1243
+ stride: 1
1244
+ weight_filler {
1245
+ type: "xavier"
1246
+ }
1247
+ bias_filler {
1248
+ type: "constant"
1249
+ value: 0
1250
+ }
1251
+ }
1252
+ }
1253
+ layer {
1254
+ name: "conv6_2_mbox_loc_perm"
1255
+ type: "Permute"
1256
+ bottom: "conv6_2_mbox_loc"
1257
+ top: "conv6_2_mbox_loc_perm"
1258
+ permute_param {
1259
+ order: 0
1260
+ order: 2
1261
+ order: 3
1262
+ order: 1
1263
+ }
1264
+ }
1265
+ layer {
1266
+ name: "conv6_2_mbox_loc_flat"
1267
+ type: "Flatten"
1268
+ bottom: "conv6_2_mbox_loc_perm"
1269
+ top: "conv6_2_mbox_loc_flat"
1270
+ flatten_param {
1271
+ axis: 1
1272
+ }
1273
+ }
1274
+ layer {
1275
+ name: "conv6_2_mbox_conf"
1276
+ type: "Convolution"
1277
+ bottom: "conv6_2_h"
1278
+ top: "conv6_2_mbox_conf"
1279
+ param {
1280
+ lr_mult: 1
1281
+ decay_mult: 1
1282
+ }
1283
+ param {
1284
+ lr_mult: 2
1285
+ decay_mult: 0
1286
+ }
1287
+ convolution_param {
1288
+ num_output: 12 # 126
1289
+ pad: 1
1290
+ kernel_size: 3
1291
+ stride: 1
1292
+ weight_filler {
1293
+ type: "xavier"
1294
+ }
1295
+ bias_filler {
1296
+ type: "constant"
1297
+ value: 0
1298
+ }
1299
+ }
1300
+ }
1301
+ layer {
1302
+ name: "conv6_2_mbox_conf_perm"
1303
+ type: "Permute"
1304
+ bottom: "conv6_2_mbox_conf"
1305
+ top: "conv6_2_mbox_conf_perm"
1306
+ permute_param {
1307
+ order: 0
1308
+ order: 2
1309
+ order: 3
1310
+ order: 1
1311
+ }
1312
+ }
1313
+ layer {
1314
+ name: "conv6_2_mbox_conf_flat"
1315
+ type: "Flatten"
1316
+ bottom: "conv6_2_mbox_conf_perm"
1317
+ top: "conv6_2_mbox_conf_flat"
1318
+ flatten_param {
1319
+ axis: 1
1320
+ }
1321
+ }
1322
+ layer {
1323
+ name: "conv6_2_mbox_priorbox"
1324
+ type: "PriorBox"
1325
+ bottom: "conv6_2_h"
1326
+ bottom: "data"
1327
+ top: "conv6_2_mbox_priorbox"
1328
+ prior_box_param {
1329
+ min_size: 111.0
1330
+ max_size: 162.0
1331
+ aspect_ratio: 2
1332
+ aspect_ratio: 3
1333
+ flip: true
1334
+ clip: false
1335
+ variance: 0.1
1336
+ variance: 0.1
1337
+ variance: 0.2
1338
+ variance: 0.2
1339
+ step: 32
1340
+ offset: 0.5
1341
+ }
1342
+ }
1343
+ layer {
1344
+ name: "conv7_2_mbox_loc"
1345
+ type: "Convolution"
1346
+ bottom: "conv7_2_h"
1347
+ top: "conv7_2_mbox_loc"
1348
+ param {
1349
+ lr_mult: 1
1350
+ decay_mult: 1
1351
+ }
1352
+ param {
1353
+ lr_mult: 2
1354
+ decay_mult: 0
1355
+ }
1356
+ convolution_param {
1357
+ num_output: 24
1358
+ pad: 1
1359
+ kernel_size: 3
1360
+ stride: 1
1361
+ weight_filler {
1362
+ type: "xavier"
1363
+ }
1364
+ bias_filler {
1365
+ type: "constant"
1366
+ value: 0
1367
+ }
1368
+ }
1369
+ }
1370
+ layer {
1371
+ name: "conv7_2_mbox_loc_perm"
1372
+ type: "Permute"
1373
+ bottom: "conv7_2_mbox_loc"
1374
+ top: "conv7_2_mbox_loc_perm"
1375
+ permute_param {
1376
+ order: 0
1377
+ order: 2
1378
+ order: 3
1379
+ order: 1
1380
+ }
1381
+ }
1382
+ layer {
1383
+ name: "conv7_2_mbox_loc_flat"
1384
+ type: "Flatten"
1385
+ bottom: "conv7_2_mbox_loc_perm"
1386
+ top: "conv7_2_mbox_loc_flat"
1387
+ flatten_param {
1388
+ axis: 1
1389
+ }
1390
+ }
1391
+ layer {
1392
+ name: "conv7_2_mbox_conf"
1393
+ type: "Convolution"
1394
+ bottom: "conv7_2_h"
1395
+ top: "conv7_2_mbox_conf"
1396
+ param {
1397
+ lr_mult: 1
1398
+ decay_mult: 1
1399
+ }
1400
+ param {
1401
+ lr_mult: 2
1402
+ decay_mult: 0
1403
+ }
1404
+ convolution_param {
1405
+ num_output: 12 # 126
1406
+ pad: 1
1407
+ kernel_size: 3
1408
+ stride: 1
1409
+ weight_filler {
1410
+ type: "xavier"
1411
+ }
1412
+ bias_filler {
1413
+ type: "constant"
1414
+ value: 0
1415
+ }
1416
+ }
1417
+ }
1418
+ layer {
1419
+ name: "conv7_2_mbox_conf_perm"
1420
+ type: "Permute"
1421
+ bottom: "conv7_2_mbox_conf"
1422
+ top: "conv7_2_mbox_conf_perm"
1423
+ permute_param {
1424
+ order: 0
1425
+ order: 2
1426
+ order: 3
1427
+ order: 1
1428
+ }
1429
+ }
1430
+ layer {
1431
+ name: "conv7_2_mbox_conf_flat"
1432
+ type: "Flatten"
1433
+ bottom: "conv7_2_mbox_conf_perm"
1434
+ top: "conv7_2_mbox_conf_flat"
1435
+ flatten_param {
1436
+ axis: 1
1437
+ }
1438
+ }
1439
+ layer {
1440
+ name: "conv7_2_mbox_priorbox"
1441
+ type: "PriorBox"
1442
+ bottom: "conv7_2_h"
1443
+ bottom: "data"
1444
+ top: "conv7_2_mbox_priorbox"
1445
+ prior_box_param {
1446
+ min_size: 162.0
1447
+ max_size: 213.0
1448
+ aspect_ratio: 2
1449
+ aspect_ratio: 3
1450
+ flip: true
1451
+ clip: false
1452
+ variance: 0.1
1453
+ variance: 0.1
1454
+ variance: 0.2
1455
+ variance: 0.2
1456
+ step: 64
1457
+ offset: 0.5
1458
+ }
1459
+ }
1460
+ layer {
1461
+ name: "conv8_2_mbox_loc"
1462
+ type: "Convolution"
1463
+ bottom: "conv8_2_h"
1464
+ top: "conv8_2_mbox_loc"
1465
+ param {
1466
+ lr_mult: 1
1467
+ decay_mult: 1
1468
+ }
1469
+ param {
1470
+ lr_mult: 2
1471
+ decay_mult: 0
1472
+ }
1473
+ convolution_param {
1474
+ num_output: 16
1475
+ pad: 1
1476
+ kernel_size: 3
1477
+ stride: 1
1478
+ weight_filler {
1479
+ type: "xavier"
1480
+ }
1481
+ bias_filler {
1482
+ type: "constant"
1483
+ value: 0
1484
+ }
1485
+ }
1486
+ }
1487
+ layer {
1488
+ name: "conv8_2_mbox_loc_perm"
1489
+ type: "Permute"
1490
+ bottom: "conv8_2_mbox_loc"
1491
+ top: "conv8_2_mbox_loc_perm"
1492
+ permute_param {
1493
+ order: 0
1494
+ order: 2
1495
+ order: 3
1496
+ order: 1
1497
+ }
1498
+ }
1499
+ layer {
1500
+ name: "conv8_2_mbox_loc_flat"
1501
+ type: "Flatten"
1502
+ bottom: "conv8_2_mbox_loc_perm"
1503
+ top: "conv8_2_mbox_loc_flat"
1504
+ flatten_param {
1505
+ axis: 1
1506
+ }
1507
+ }
1508
+ layer {
1509
+ name: "conv8_2_mbox_conf"
1510
+ type: "Convolution"
1511
+ bottom: "conv8_2_h"
1512
+ top: "conv8_2_mbox_conf"
1513
+ param {
1514
+ lr_mult: 1
1515
+ decay_mult: 1
1516
+ }
1517
+ param {
1518
+ lr_mult: 2
1519
+ decay_mult: 0
1520
+ }
1521
+ convolution_param {
1522
+ num_output: 8 # 84
1523
+ pad: 1
1524
+ kernel_size: 3
1525
+ stride: 1
1526
+ weight_filler {
1527
+ type: "xavier"
1528
+ }
1529
+ bias_filler {
1530
+ type: "constant"
1531
+ value: 0
1532
+ }
1533
+ }
1534
+ }
1535
+ layer {
1536
+ name: "conv8_2_mbox_conf_perm"
1537
+ type: "Permute"
1538
+ bottom: "conv8_2_mbox_conf"
1539
+ top: "conv8_2_mbox_conf_perm"
1540
+ permute_param {
1541
+ order: 0
1542
+ order: 2
1543
+ order: 3
1544
+ order: 1
1545
+ }
1546
+ }
1547
+ layer {
1548
+ name: "conv8_2_mbox_conf_flat"
1549
+ type: "Flatten"
1550
+ bottom: "conv8_2_mbox_conf_perm"
1551
+ top: "conv8_2_mbox_conf_flat"
1552
+ flatten_param {
1553
+ axis: 1
1554
+ }
1555
+ }
1556
+ layer {
1557
+ name: "conv8_2_mbox_priorbox"
1558
+ type: "PriorBox"
1559
+ bottom: "conv8_2_h"
1560
+ bottom: "data"
1561
+ top: "conv8_2_mbox_priorbox"
1562
+ prior_box_param {
1563
+ min_size: 213.0
1564
+ max_size: 264.0
1565
+ aspect_ratio: 2
1566
+ flip: true
1567
+ clip: false
1568
+ variance: 0.1
1569
+ variance: 0.1
1570
+ variance: 0.2
1571
+ variance: 0.2
1572
+ step: 100
1573
+ offset: 0.5
1574
+ }
1575
+ }
1576
+ layer {
1577
+ name: "conv9_2_mbox_loc"
1578
+ type: "Convolution"
1579
+ bottom: "conv9_2_h"
1580
+ top: "conv9_2_mbox_loc"
1581
+ param {
1582
+ lr_mult: 1
1583
+ decay_mult: 1
1584
+ }
1585
+ param {
1586
+ lr_mult: 2
1587
+ decay_mult: 0
1588
+ }
1589
+ convolution_param {
1590
+ num_output: 16
1591
+ pad: 1
1592
+ kernel_size: 3
1593
+ stride: 1
1594
+ weight_filler {
1595
+ type: "xavier"
1596
+ }
1597
+ bias_filler {
1598
+ type: "constant"
1599
+ value: 0
1600
+ }
1601
+ }
1602
+ }
1603
+ layer {
1604
+ name: "conv9_2_mbox_loc_perm"
1605
+ type: "Permute"
1606
+ bottom: "conv9_2_mbox_loc"
1607
+ top: "conv9_2_mbox_loc_perm"
1608
+ permute_param {
1609
+ order: 0
1610
+ order: 2
1611
+ order: 3
1612
+ order: 1
1613
+ }
1614
+ }
1615
+ layer {
1616
+ name: "conv9_2_mbox_loc_flat"
1617
+ type: "Flatten"
1618
+ bottom: "conv9_2_mbox_loc_perm"
1619
+ top: "conv9_2_mbox_loc_flat"
1620
+ flatten_param {
1621
+ axis: 1
1622
+ }
1623
+ }
1624
+ layer {
1625
+ name: "conv9_2_mbox_conf"
1626
+ type: "Convolution"
1627
+ bottom: "conv9_2_h"
1628
+ top: "conv9_2_mbox_conf"
1629
+ param {
1630
+ lr_mult: 1
1631
+ decay_mult: 1
1632
+ }
1633
+ param {
1634
+ lr_mult: 2
1635
+ decay_mult: 0
1636
+ }
1637
+ convolution_param {
1638
+ num_output: 8 # 84
1639
+ pad: 1
1640
+ kernel_size: 3
1641
+ stride: 1
1642
+ weight_filler {
1643
+ type: "xavier"
1644
+ }
1645
+ bias_filler {
1646
+ type: "constant"
1647
+ value: 0
1648
+ }
1649
+ }
1650
+ }
1651
+ layer {
1652
+ name: "conv9_2_mbox_conf_perm"
1653
+ type: "Permute"
1654
+ bottom: "conv9_2_mbox_conf"
1655
+ top: "conv9_2_mbox_conf_perm"
1656
+ permute_param {
1657
+ order: 0
1658
+ order: 2
1659
+ order: 3
1660
+ order: 1
1661
+ }
1662
+ }
1663
+ layer {
1664
+ name: "conv9_2_mbox_conf_flat"
1665
+ type: "Flatten"
1666
+ bottom: "conv9_2_mbox_conf_perm"
1667
+ top: "conv9_2_mbox_conf_flat"
1668
+ flatten_param {
1669
+ axis: 1
1670
+ }
1671
+ }
1672
+ layer {
1673
+ name: "conv9_2_mbox_priorbox"
1674
+ type: "PriorBox"
1675
+ bottom: "conv9_2_h"
1676
+ bottom: "data"
1677
+ top: "conv9_2_mbox_priorbox"
1678
+ prior_box_param {
1679
+ min_size: 264.0
1680
+ max_size: 315.0
1681
+ aspect_ratio: 2
1682
+ flip: true
1683
+ clip: false
1684
+ variance: 0.1
1685
+ variance: 0.1
1686
+ variance: 0.2
1687
+ variance: 0.2
1688
+ step: 300
1689
+ offset: 0.5
1690
+ }
1691
+ }
1692
+ layer {
1693
+ name: "mbox_loc"
1694
+ type: "Concat"
1695
+ bottom: "conv4_3_norm_mbox_loc_flat"
1696
+ bottom: "fc7_mbox_loc_flat"
1697
+ bottom: "conv6_2_mbox_loc_flat"
1698
+ bottom: "conv7_2_mbox_loc_flat"
1699
+ bottom: "conv8_2_mbox_loc_flat"
1700
+ bottom: "conv9_2_mbox_loc_flat"
1701
+ top: "mbox_loc"
1702
+ concat_param {
1703
+ axis: 1
1704
+ }
1705
+ }
1706
+ layer {
1707
+ name: "mbox_conf"
1708
+ type: "Concat"
1709
+ bottom: "conv4_3_norm_mbox_conf_flat"
1710
+ bottom: "fc7_mbox_conf_flat"
1711
+ bottom: "conv6_2_mbox_conf_flat"
1712
+ bottom: "conv7_2_mbox_conf_flat"
1713
+ bottom: "conv8_2_mbox_conf_flat"
1714
+ bottom: "conv9_2_mbox_conf_flat"
1715
+ top: "mbox_conf"
1716
+ concat_param {
1717
+ axis: 1
1718
+ }
1719
+ }
1720
+ layer {
1721
+ name: "mbox_priorbox"
1722
+ type: "Concat"
1723
+ bottom: "conv4_3_norm_mbox_priorbox"
1724
+ bottom: "fc7_mbox_priorbox"
1725
+ bottom: "conv6_2_mbox_priorbox"
1726
+ bottom: "conv7_2_mbox_priorbox"
1727
+ bottom: "conv8_2_mbox_priorbox"
1728
+ bottom: "conv9_2_mbox_priorbox"
1729
+ top: "mbox_priorbox"
1730
+ concat_param {
1731
+ axis: 2
1732
+ }
1733
+ }
1734
+
1735
+ layer {
1736
+ name: "mbox_conf_reshape"
1737
+ type: "Reshape"
1738
+ bottom: "mbox_conf"
1739
+ top: "mbox_conf_reshape"
1740
+ reshape_param {
1741
+ shape {
1742
+ dim: 0
1743
+ dim: -1
1744
+ dim: 2
1745
+ }
1746
+ }
1747
+ }
1748
+ layer {
1749
+ name: "mbox_conf_softmax"
1750
+ type: "Softmax"
1751
+ bottom: "mbox_conf_reshape"
1752
+ top: "mbox_conf_softmax"
1753
+ softmax_param {
1754
+ axis: 2
1755
+ }
1756
+ }
1757
+ layer {
1758
+ name: "mbox_conf_flatten"
1759
+ type: "Flatten"
1760
+ bottom: "mbox_conf_softmax"
1761
+ top: "mbox_conf_flatten"
1762
+ flatten_param {
1763
+ axis: 1
1764
+ }
1765
+ }
1766
+
1767
+ layer {
1768
+ name: "detection_out"
1769
+ type: "DetectionOutput"
1770
+ bottom: "mbox_loc"
1771
+ bottom: "mbox_conf_flatten"
1772
+ bottom: "mbox_priorbox"
1773
+ top: "detection_out"
1774
+ include {
1775
+ phase: TEST
1776
+ }
1777
+ detection_output_param {
1778
+ num_classes: 2
1779
+ share_location: true
1780
+ background_label_id: 0
1781
+ nms_param {
1782
+ nms_threshold: 0.45
1783
+ top_k: 400
1784
+ }
1785
+ code_type: CENTER_SIZE
1786
+ keep_top_k: 200
1787
+ confidence_threshold: 0.01
1788
+ }
1789
+ }
face_detector/res10_300x300_ssd_iter_140000.caffemodel ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2a56a11a57a4a295956b0660b4a3d76bbdca2206c4961cea8efe7d95c7cb2f2d
3
+ size 10666211