facenet.prototxt

name: "FaceNet"
layer {
  name: "facenet"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    scale: 0.00390625
  }
  data_param {
    source: "/home/xubinbin/caffe/tmp_train_lmdb/"
    batch_size: 64
    backend: LMDB
  }
}
layer {
  name: "facenet"
  type: "Data"
  top: "data"
  top: "label"
  include {
    phase: TEST
  }
  transform_param {
    scale: 0.00390625
  }
  data_param {
    source: "/home/xubinbin/caffe/tmp_test_lmdb/"
    batch_size: 64
    backend: LMDB
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 2
    pad: 3 
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
    name: "rnorm1"
    type: "LRN"
    bottom: "pool1"
    top: "rnorm1"
    lrn_param {
        local_size: 5
        alpha: 1.0
        beta: 0.75
    }
}
layer {
  name: "conv2a"
  type: "Convolution"
  bottom: "rnorm1"
  top: "conv2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
        type: "constant"
    }
  }
}

layer {
  name: "conv2"
  type: "Convolution"
  bottom: "conv2a"
  top: "conv2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 192
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
    name: "rnorm2"
    type: "LRN"
    bottom: "conv2"
    top: "rnorm2"
    lrn_param {
        local_size: 5
        alpha: 1.0
        beta: 0.75
    }
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "rnorm2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 1
  }
}

layer {
  name: "conv3a"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 192
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "conv3"
  type: "Convolution"
  bottom: "conv3a"
  top: "conv3"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 384
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "pool3"
  type: "Pooling"
  bottom: "conv3"
  top: "pool3"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    #pad: 1
  }
}

layer {
  name: "conv4a"
  type: "Convolution"
  bottom: "pool3"
  top: "conv4a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 384
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv4a"
  top: "conv4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "conv5a"
  type: "Convolution"
  bottom: "conv4"
  top: "conv5a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "conv5"
  type: "Convolution"
  bottom: "conv5a"
  top: "conv5"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "conv6a"
  type: "Convolution"
  bottom: "conv5"
  top: "conv6a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 256
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "conv6"
  type: "Convolution"
  bottom: "conv6a"
  top: "conv6"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "pool4"
  type: "Pooling"
  bottom: "conv6"
  top: "pool4"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    #pad: 1
  }
}

layer {
  name: "fc1a"
  type: "InnerProduct"
  bottom: "pool4"
  top: "fc1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "fc1b"
  type: "InnerProduct"
  bottom: "pool4"
  top: "fc1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
		std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}


layer {
  name: "maxout1"
  type: "Eltwise"
  bottom: "fc1a"
  bottom: "fc1b"
  top: "maxout1"
  eltwise_param {
    operation:MAX
  }
}

layer {
  name: "fc2a"
  type: "InnerProduct"
  bottom: "maxout1"
  top: "fc2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "fc2b"
  type: "InnerProduct"
  bottom: "maxout1"
  top: "fc2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
	  std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}


layer {
  name: "maxout2"
  type: "Eltwise"
  bottom: "fc2a"
  bottom: "fc2b"
  top: "maxout2"
  eltwise_param {
    operation:MAX
  }
}

layer {
  name: "fc7128"
  type: "InnerProduct"
  bottom: "maxout2"
  top: "fc7128"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  inner_product_param {
    num_output: 128
    weight_filler {
      type: "gaussian"
	  std: 0.1
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "l2"
  type: "Normalization"
  bottom: "fc7128"
  top: "l2"
    normalization_param {
        norm: L2
    }
}

layer {
  name: "loss"
  type: "TripletLoss"
  bottom: "l2"
#  bottom: "fc7128"
  bottom: "label"
  top: "loss"
  triplet_loss_param {
	alpha: 0.8
  }
}