deploy.prototxt

name: "VGG_FACE_16_layer"
input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 218
  dim: 178
}
layer {
  bottom: "data"
  top: "conv1"
  name: "conv1"
  type: "Convolution"
  convolution_param {
    num_output: 16
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv1"
 top: "bn_conv1"
 name: "bn_conv1"
 type: "BatchNorm"
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "bn_conv1"
  top: "bn_conv1"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv1"
  top: "pool1"
  name: "pool1"
  type: "Pooling"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  bottom: "pool1"
  top: "conv2"
  name: "conv2"
  type: "Convolution"
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv2"
 top: "bn_conv2"
 name: "bn_conv2"
 type: "BatchNorm"
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "bn_conv2"
  top: "bn_conv2"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv2"
  top: "pool2"
  name: "pool2"
  type: "Pooling"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  bottom: "pool2"
  top: "conv3"
  name: "conv3"
  type: "Convolution"
  convolution_param {
    num_output: 16
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv3"
 top: "bn_conv3"
 name: "bn_conv3"
 type: "BatchNorm"
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "bn_conv3"
  top: "bn_conv3"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv3"
  top: "pool3"
  name: "pool3"
  type: "Pooling"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  bottom: "pool3"
  top: "conv4_1"
  name: "conv4_1"
  type: "Convolution"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv4_1"
 top: "bn_conv4_1"
 name: "bn_conv4_1"
 type: "BatchNorm"
}
layer {
  name: "relu4_1"
  type: "ReLU"
  bottom: "bn_conv4_1"
  top: "bn_conv4_1"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv4_1"
  top: "conv4_2"
  name: "conv4_2"
  type: "Convolution"
  convolution_param {
    num_output: 16
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv4_2"
 top: "bn_conv4_2"
 name: "bn_conv4_2"
 type: "BatchNorm"
}
layer {
  name: "relu4_2"
  type: "ReLU"
  bottom: "bn_conv4_2"
  top: "bn_conv4_2"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv4_2"
  top: "conv4_3"
  name: "conv4_3"
  type: "Convolution"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv4_3"
 top: "bn_conv4_3"
 name: "bn_conv4_3"
 type: "BatchNorm"
}
layer {
  name: "relu4_3"
  type: "ReLU"
  bottom: "bn_conv4_3"
  top: "bn_conv4_3"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv4_3"
  top: "pool4"
  name: "pool4"
  type: "Pooling"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}


layer {
  bottom: "pool4"
  top: "conv5_1"
  name: "conv5_1"
  type: "Convolution"
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv5_1"
 top: "bn_conv5_1"
 name: "bn_conv5_1"
 type: "BatchNorm"
}
layer {
  name: "relu5_1"
  type: "ReLU"
  bottom: "bn_conv5_1"
  top: "bn_conv5_1"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv5_1"
  top: "conv5_2"
  name: "conv5_2"
  type: "Convolution"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv5_2"
 top: "bn_conv5_2"
 name: "bn_conv5_2"
 type: "BatchNorm"
}
layer {
  name: "relu5_2"
  type: "ReLU"
  bottom: "bn_conv5_2"
  top: "bn_conv5_2"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv5_2"
  top: "conv5_3"
  name: "conv5_3"
  type: "Convolution"
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv5_3"
 top: "bn_conv5_3"
 name: "bn_conv5_3"
 type: "BatchNorm"
}
layer {
  name: "relu5_3"
  type: "ReLU"
  bottom: "bn_conv5_3"
  top: "bn_conv5_3"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv5_3"
  top: "conv5_4"
  name: "conv5_4"
  type: "Convolution"
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv5_4"
 top: "bn_conv5_4"
 name: "bn_conv5_4"
 type: "BatchNorm"
}
layer {
  name: "relu5_4"
  type: "ReLU"
  bottom: "bn_conv5_4"
  top: "bn_conv5_4"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv5_4"
  top: "pool5"
  name: "pool5"
  type: "Pooling"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer {
  bottom: "pool5"
  top: "conv6_1"
  name: "conv6_1"
  type: "Convolution"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv6_1"
 top: "bn_conv6_1"
 name: "bn_conv6_1"
 type: "BatchNorm"
}
layer {
  name: "relu6_1"
  type: "ReLU"
  bottom: "bn_conv6_1"
  top: "bn_conv6_1"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv6_1"
  top: "conv6_2"
  name: "conv6_2"
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv6_2"
 top: "bn_conv6_2"
 name: "bn_conv6_2"
 type: "BatchNorm"
}
layer {
  name: "relu6_2"
  type: "ReLU"
  bottom: "bn_conv6_2"
  top: "bn_conv6_2"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv6_2"
  top: "conv6_3"
  name: "conv6_3"
  type: "Convolution"
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv6_3"
 top: "bn_conv6_3"
 name: "bn_conv6_3"
 type: "BatchNorm"
}
layer {
  name: "relu6_3"
  type: "ReLU"
  bottom: "bn_conv6_3"
  top: "bn_conv6_3"
  relu_param{
    negative_slope: 0.1
  }
}
layer {
  bottom: "bn_conv6_3"
  top: "conv6_4"
  name: "conv6_4"
  type: "Convolution"
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv6_4"
 top: "bn_conv6_4"
 name: "bn_conv6_4"
 type: "BatchNorm"
}
layer {
  name: "relu6_4"
  type: "ReLU"
  bottom: "bn_conv6_4"
  top: "bn_conv6_4"
  relu_param{
    negative_slope: 0.1
  }
}

layer {
  bottom: "bn_conv6_4"
  top: "conv7"
  name: "conv7"
  type: "Convolution"
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv7"
 top: "bn_conv7"
 name: "bn_conv7"
 type: "BatchNorm"
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "bn_conv7"
  top: "bn_conv7"
  relu_param{
    negative_slope: 0.1
  }
}

layer {
  bottom: "bn_conv7"
  top: "conv8"
  name: "conv8"
  type: "Convolution"
  convolution_param {
    num_output: 1000
    pad: 1
    kernel_size: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
 bottom: "conv8"
 top: "bn_conv8"
 name: "bn_conv8"
 type: "BatchNorm"
}
layer {
  name: "relu8"
  type: "ReLU"
  bottom: "bn_conv8"
  top: "bn_conv8"
  relu_param{
    negative_slope: 0.1
  }
}


layer {
  bottom: "bn_conv8"
  top: "global_pool8_max"
  name: "global_pool8_max"
  type: "Pooling"
  pooling_param{
    pool: MAX
    global_pooling: true
  }
}
layer {
  bottom: "global_pool8_max"
  top: "norm_conv8_max"
  type: "Normalize"
  name: "norm_conv8_max"
}
layer {
  bottom: "bn_conv8"
  top: "global_pool8_ave" 
  name: "global_pool8_ave"
  type: "Pooling"
  pooling_param{
    pool: AVE
    global_pooling: true
  }
}
layer {
  bottom: "global_pool8_ave"
  top: "norm_conv8_ave"
  type: "Normalize"
  name: "norm_conv8_ave"
}

layer {
  bottom: "norm_conv8_max"
  bottom: "norm_conv8_ave"
  top: "concat_data"
  name: "concat_data"
  type: "Concat"
}

layer {
  bottom: "concat_data"
  top: "moon-fc"
  name: "moon-fc"
  type: "InnerProduct"
  inner_product_param {
    num_output: 40
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}