sphereface_model.prototxt

name: "SpherefaceNet-20"
layer {
  name: "data"
  type: "ImageData"
  top: "data"
  top: "label"
  transform_param {
    mean_value: 127.5
    mean_value: 127.5
    mean_value: 127.5
    scale: 0.0078125
    mirror: true
  }
  image_data_param {
    source: "data/CASIA-WebFace-112X96.txt"
    batch_size: 256
    shuffle: true
  }
}
############## CNN Architecture ###############
layer {
  name: "conv1_1"
  type: "Convolution"
  bottom: "data"
  top: "conv1_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1_1"
  type: "PReLU"
  bottom: "conv1_1"
  top: "conv1_1"
}
layer {
  name: "conv1_2"
  type: "Convolution"
  bottom: "conv1_1"
  top: "conv1_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1_2"
  type: "PReLU"
  bottom: "conv1_2"
  top: "conv1_2"
}
layer {
  name: "conv1_3"
  type: "Convolution"
  bottom: "conv1_2"
  top: "conv1_3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1_3"
  type: "PReLU"
  bottom: "conv1_3"
  top: "conv1_3"
}
layer {
  name: "res1_3"
  type: "Eltwise"
  bottom: "conv1_1"
  bottom: "conv1_3"
  top: "res1_3"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "conv2_1"
  type: "Convolution"
  bottom: "res1_3"
  top: "conv2_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_1"
  type: "PReLU"
  bottom: "conv2_1"
  top: "conv2_1"
}
layer {
  name: "conv2_2"
  type: "Convolution"
  bottom: "conv2_1"
  top: "conv2_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_2"
  type: "PReLU"
  bottom: "conv2_2"
  top: "conv2_2"
}
layer {
  name: "conv2_3"
  type: "Convolution"
  bottom: "conv2_2"
  top: "conv2_3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_3"
  type: "PReLU"
  bottom: "conv2_3"
  top: "conv2_3"
}
layer {
  name: "res2_3"
  type: "Eltwise"
  bottom: "conv2_1"
  bottom: "conv2_3"
  top: "res2_3"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "conv2_4"
  type: "Convolution"
  bottom: "res2_3"
  top: "conv2_4"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_4"
  type: "PReLU"
  bottom: "conv2_4"
  top: "conv2_4"
}
layer {
  name: "conv2_5"
  type: "Convolution"
  bottom: "conv2_4"
  top: "conv2_5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_5"
  type: "PReLU"
  bottom: "conv2_5"
  top: "conv2_5"
}
layer {
  name: "res2_5"
  type: "Eltwise"
  bottom: "res2_3"
  bottom: "conv2_5"
  top: "res2_5"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "conv3_1"
  type: "Convolution"
  bottom: "res2_5"
  top: "conv3_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_1"
  type: "PReLU"
  bottom: "conv3_1"
  top: "conv3_1"
}
layer {
  name: "conv3_2"
  type: "Convolution"
  bottom: "conv3_1"
  top: "conv3_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_2"
  type: "PReLU"
  bottom: "conv3_2"
  top: "conv3_2"
}
layer {
  name: "conv3_3"
  type: "Convolution"
  bottom: "conv3_2"
  top: "conv3_3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_3"
  type: "PReLU"
  bottom: "conv3_3"
  top: "conv3_3"
}
layer {
  name: "res3_3"
  type: "Eltwise"
  bottom: "conv3_1"
  bottom: "conv3_3"
  top: "res3_3"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "conv3_4"
  type: "Convolution"
  bottom: "res3_3"
  top: "conv3_4"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_4"
  type: "PReLU"
  bottom: "conv3_4"
  top: "conv3_4"
}
layer {
  name: "conv3_5"
  type: "Convolution"
  bottom: "conv3_4"
  top: "conv3_5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_5"
  type: "PReLU"
  bottom: "conv3_5"
  top: "conv3_5"
}
layer {
  name: "res3_5"
  type: "Eltwise"
  bottom: "res3_3"
  bottom: "conv3_5"
  top: "res3_5"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "conv3_6"
  type: "Convolution"
  bottom: "res3_5"
  top: "conv3_6"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_6"
  type: "PReLU"
  bottom: "conv3_6"
  top: "conv3_6"
}
layer {
  name: "conv3_7"
  type: "Convolution"
  bottom: "conv3_6"
  top: "conv3_7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_7"
  type: "PReLU"
  bottom: "conv3_7"
  top: "conv3_7"
}
layer {
  name: "res3_7"
  type: "Eltwise"
  bottom: "res3_5"
  bottom: "conv3_7"
  top: "res3_7"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "conv3_8"
  type: "Convolution"
  bottom: "res3_7"
  top: "conv3_8"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_8"
  type: "PReLU"
  bottom: "conv3_8"
  top: "conv3_8"
}
layer {
  name: "conv3_9"
  type: "Convolution"
  bottom: "conv3_8"
  top: "conv3_9"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_9"
  type: "PReLU"
  bottom: "conv3_9"
  top: "conv3_9"
}
layer {
  name: "res3_9"
  type: "Eltwise"
  bottom: "res3_7"
  bottom: "conv3_9"
  top: "res3_9"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "conv4_1"
  type: "Convolution"
  bottom: "res3_9"
  top: "conv4_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 2
    pad: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu4_1"
  type: "PReLU"
  bottom: "conv4_1"
  top: "conv4_1"
}
layer {
  name: "conv4_2"
  type: "Convolution"
  bottom: "conv4_1"
  top: "conv4_2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu4_2"
  type: "PReLU"
  bottom: "conv4_2"
  top: "conv4_2"
}
layer {
  name: "conv4_3"
  type: "Convolution"
  bottom: "conv4_2"
  top: "conv4_3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu4_3"
  type: "PReLU"
  bottom: "conv4_3"
  top: "conv4_3"
}
layer {
  name: "res4_3"
  type: "Eltwise"
  bottom: "conv4_1"
  bottom: "conv4_3"
  top: "res4_3"
  eltwise_param { 
    operation: 1
  }
}
layer {
  name: "fc5"
  type: "InnerProduct"
  bottom: "res4_3"
  top: "fc5"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 512
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
############### A-Softmax Loss ##############
layer {
  name: "fc6"
  type: "MarginInnerProduct"
  bottom: "fc5"
  bottom: "label"
  top: "fc6"
  top: "lambda"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  margin_inner_product_param {
    num_output: 10572
    type: QUADRUPLE
    weight_filler {
      type: "xavier"
    }
    base: 1000
    gamma: 0.12
    power: 1
    lambda_min: 5
    iteration: 0
  }
}
layer {
  name: "softmax_loss"
  type: "SoftmaxWithLoss"
  bottom: "fc6"
  bottom: "label"
  top: "softmax_loss"
}