person-detection-retail-0001.prototxt

name: "PVANet + R-FCN"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 544
      dim: 992
    }
  }
}
layer {
  name: "im_info"
  type: "Input"
  top: "im_info"
  input_param {
    shape {
      dim: 1
      dim: 6
    }
  }
}
layer {
  name: "conv1_1/conv"
  type: "Convolution"
  bottom: "data"
  top: "conv1_1/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 16
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 3
    pad_w: 3
    kernel_h: 7
    kernel_w: 7
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "conv1_1/neg"
  type: "Power"
  bottom: "conv1_1/conv"
  top: "conv1_1/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv1_1/concat"
  type: "Concat"
  bottom: "conv1_1/conv"
  bottom: "conv1_1/neg"
  top: "conv1_1"
}
layer {
  name: "conv1_1/scale"
  type: "Scale"
  bottom: "conv1_1"
  top: "conv1_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv1_1/relu"
  type: "ReLU"
  bottom: "conv1_1"
  top: "conv1_1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1_1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "conv2_1/1/conv"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2_1/1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv2_1/1/relu"
  type: "ReLU"
  bottom: "conv2_1/1"
  top: "conv2_1/1"
}
layer {
  name: "conv2_1/2/conv"
  type: "Convolution"
  bottom: "conv2_1/1"
  top: "conv2_1/2/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv2_1/2/neg"
  type: "Power"
  bottom: "conv2_1/2/conv"
  top: "conv2_1/2/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv2_1/2/concat"
  type: "Concat"
  bottom: "conv2_1/2/conv"
  bottom: "conv2_1/2/neg"
  top: "conv2_1/2"
}
layer {
  name: "conv2_1/2/scale"
  type: "Scale"
  bottom: "conv2_1/2"
  top: "conv2_1/2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv2_1/2/relu"
  type: "ReLU"
  bottom: "conv2_1/2"
  top: "conv2_1/2"
}
layer {
  name: "conv2_1/3/conv"
  type: "Convolution"
  bottom: "conv2_1/2"
  top: "conv2_1/3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv2_1/proj"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2_1/proj"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 64
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv2_1"
  type: "Eltwise"
  bottom: "conv2_1/3"
  bottom: "conv2_1/proj"
  top: "conv2_1"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv2_2/1/conv"
  type: "Convolution"
  bottom: "conv2_1"
  top: "conv2_2/1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv2_2/1/relu"
  type: "ReLU"
  bottom: "conv2_2/1"
  top: "conv2_2/1"
}
layer {
  name: "conv2_2/2/conv"
  type: "Convolution"
  bottom: "conv2_2/1"
  top: "conv2_2/2/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv2_2/2/neg"
  type: "Power"
  bottom: "conv2_2/2/conv"
  top: "conv2_2/2/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv2_2/2/concat"
  type: "Concat"
  bottom: "conv2_2/2/conv"
  bottom: "conv2_2/2/neg"
  top: "conv2_2/2"
}
layer {
  name: "conv2_2/2/scale"
  type: "Scale"
  bottom: "conv2_2/2"
  top: "conv2_2/2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv2_2/2/relu"
  type: "ReLU"
  bottom: "conv2_2/2"
  top: "conv2_2/2"
}
layer {
  name: "conv2_2/3/conv"
  type: "Convolution"
  bottom: "conv2_2/2"
  top: "conv2_2/3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv2_2"
  type: "Eltwise"
  bottom: "conv2_2/3"
  bottom: "conv2_1"
  top: "conv2_2"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv2_3/1/conv"
  type: "Convolution"
  bottom: "conv2_2"
  top: "conv2_3/1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv2_3/1/relu"
  type: "ReLU"
  bottom: "conv2_3/1"
  top: "conv2_3/1"
}
layer {
  name: "conv2_3/2/conv"
  type: "Convolution"
  bottom: "conv2_3/1"
  top: "conv2_3/2/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv2_3/2/neg"
  type: "Power"
  bottom: "conv2_3/2/conv"
  top: "conv2_3/2/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv2_3/2/concat"
  type: "Concat"
  bottom: "conv2_3/2/conv"
  bottom: "conv2_3/2/neg"
  top: "conv2_3/2"
}
layer {
  name: "conv2_3/2/scale"
  type: "Scale"
  bottom: "conv2_3/2"
  top: "conv2_3/2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv2_3/2/relu"
  type: "ReLU"
  bottom: "conv2_3/2"
  top: "conv2_3/2"
}
layer {
  name: "conv2_3/3/conv"
  type: "Convolution"
  bottom: "conv2_3/2"
  top: "conv2_3/3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv2_3"
  type: "Eltwise"
  bottom: "conv2_3/3"
  bottom: "conv2_2"
  top: "conv2_3"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv3_1/1/conv"
  type: "Convolution"
  bottom: "conv2_3"
  top: "conv3_1/1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv3_1/1/relu"
  type: "ReLU"
  bottom: "conv3_1/1"
  top: "conv3_1/1"
}
layer {
  name: "conv3_1/2/conv"
  type: "Convolution"
  bottom: "conv3_1/1"
  top: "conv3_1/2/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv3_1/2/neg"
  type: "Power"
  bottom: "conv3_1/2/conv"
  top: "conv3_1/2/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv3_1/2/concat"
  type: "Concat"
  bottom: "conv3_1/2/conv"
  bottom: "conv3_1/2/neg"
  top: "conv3_1/2"
}
layer {
  name: "conv3_1/2/scale"
  type: "Scale"
  bottom: "conv3_1/2"
  top: "conv3_1/2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv3_1/2/relu"
  type: "ReLU"
  bottom: "conv3_1/2"
  top: "conv3_1/2"
}
layer {
  name: "conv3_1/3/conv"
  type: "Convolution"
  bottom: "conv3_1/2"
  top: "conv3_1/3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv3_1/proj"
  type: "Convolution"
  bottom: "conv2_3"
  top: "conv3_1/proj"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 128
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv3_1"
  type: "Eltwise"
  bottom: "conv3_1/3"
  bottom: "conv3_1/proj"
  top: "conv3_1"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv3_2/1/conv"
  type: "Convolution"
  bottom: "conv3_1"
  top: "conv3_2/1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv3_2/1/relu"
  type: "ReLU"
  bottom: "conv3_2/1"
  top: "conv3_2/1"
}
layer {
  name: "conv3_2/2/conv"
  type: "Convolution"
  bottom: "conv3_2/1"
  top: "conv3_2/2/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv3_2/2/neg"
  type: "Power"
  bottom: "conv3_2/2/conv"
  top: "conv3_2/2/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv3_2/2/concat"
  type: "Concat"
  bottom: "conv3_2/2/conv"
  bottom: "conv3_2/2/neg"
  top: "conv3_2/2"
}
layer {
  name: "conv3_2/2/scale"
  type: "Scale"
  bottom: "conv3_2/2"
  top: "conv3_2/2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv3_2/2/relu"
  type: "ReLU"
  bottom: "conv3_2/2"
  top: "conv3_2/2"
}
layer {
  name: "conv3_2/3/conv"
  type: "Convolution"
  bottom: "conv3_2/2"
  top: "conv3_2/3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv3_2"
  type: "Eltwise"
  bottom: "conv3_2/3"
  bottom: "conv3_1"
  top: "conv3_2"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv3_3/1/conv"
  type: "Convolution"
  bottom: "conv3_2"
  top: "conv3_3/1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv3_3/1/relu"
  type: "ReLU"
  bottom: "conv3_3/1"
  top: "conv3_3/1"
}
layer {
  name: "conv3_3/2/conv"
  type: "Convolution"
  bottom: "conv3_3/1"
  top: "conv3_3/2/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv3_3/2/neg"
  type: "Power"
  bottom: "conv3_3/2/conv"
  top: "conv3_3/2/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv3_3/2/concat"
  type: "Concat"
  bottom: "conv3_3/2/conv"
  bottom: "conv3_3/2/neg"
  top: "conv3_3/2"
}
layer {
  name: "conv3_3/2/scale"
  type: "Scale"
  bottom: "conv3_3/2"
  top: "conv3_3/2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv3_3/2/relu"
  type: "ReLU"
  bottom: "conv3_3/2"
  top: "conv3_3/2"
}
layer {
  name: "conv3_3/3/conv"
  type: "Convolution"
  bottom: "conv3_3/2"
  top: "conv3_3/3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv3_3"
  type: "Eltwise"
  bottom: "conv3_3/3"
  bottom: "conv3_2"
  top: "conv3_3"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv3_4/1/conv"
  type: "Convolution"
  bottom: "conv3_3"
  top: "conv3_4/1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv3_4/1/relu"
  type: "ReLU"
  bottom: "conv3_4/1"
  top: "conv3_4/1"
}
layer {
  name: "conv3_4/2/conv"
  type: "Convolution"
  bottom: "conv3_4/1"
  top: "conv3_4/2/conv"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv3_4/2/neg"
  type: "Power"
  bottom: "conv3_4/2/conv"
  top: "conv3_4/2/neg"
  power_param {
    power: 1.0
    scale: -1.0
    shift: 0.0
  }
}
layer {
  name: "conv3_4/2/concat"
  type: "Concat"
  bottom: "conv3_4/2/conv"
  bottom: "conv3_4/2/neg"
  top: "conv3_4/2"
}
layer {
  name: "conv3_4/2/scale"
  type: "Scale"
  bottom: "conv3_4/2"
  top: "conv3_4/2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    bias_term: true
  }
}
layer {
  name: "conv3_4/2/relu"
  type: "ReLU"
  bottom: "conv3_4/2"
  top: "conv3_4/2"
}
layer {
  name: "conv3_4/3/conv"
  type: "Convolution"
  bottom: "conv3_4/2"
  top: "conv3_4/3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv3_4"
  type: "Eltwise"
  bottom: "conv3_4/3"
  bottom: "conv3_3"
  top: "conv3_4"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv4_1/incep/0/conv"
  type: "Convolution"
  bottom: "conv3_4"
  top: "conv4_1/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv4_1/incep/0/relu"
  type: "ReLU"
  bottom: "conv4_1/incep/0"
  top: "conv4_1/incep/0"
}
layer {
  name: "conv4_1/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv3_4"
  top: "conv4_1/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv4_1/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv4_1/incep/1_reduce"
  top: "conv4_1/incep/1_reduce"
}
layer {
  name: "conv4_1/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv4_1/incep/1_reduce"
  top: "conv4_1/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_1/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv4_1/incep/1_0"
  top: "conv4_1/incep/1_0"
}
layer {
  name: "conv4_1/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv3_4"
  top: "conv4_1/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv4_1/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv4_1/incep/2_reduce"
  top: "conv4_1/incep/2_reduce"
}
layer {
  name: "conv4_1/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv4_1/incep/2_reduce"
  top: "conv4_1/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_1/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv4_1/incep/2_0"
  top: "conv4_1/incep/2_0"
}
layer {
  name: "conv4_1/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv4_1/incep/2_0"
  top: "conv4_1/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_1/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv4_1/incep/2_1"
  top: "conv4_1/incep/2_1"
}
layer {
  name: "conv4_1/incep/pool"
  type: "Pooling"
  bottom: "conv3_4"
  top: "conv4_1/incep/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "conv4_1/incep/poolproj/conv"
  type: "Convolution"
  bottom: "conv4_1/incep/pool"
  top: "conv4_1/incep/poolproj"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_1/incep/poolproj/relu"
  type: "ReLU"
  bottom: "conv4_1/incep/poolproj"
  top: "conv4_1/incep/poolproj"
}
layer {
  name: "conv4_1/incep"
  type: "Concat"
  bottom: "conv4_1/incep/0"
  bottom: "conv4_1/incep/1_0"
  bottom: "conv4_1/incep/2_1"
  bottom: "conv4_1/incep/poolproj"
  top: "conv4_1/incep"
}
layer {
  name: "conv4_1/out/conv"
  type: "Convolution"
  bottom: "conv4_1/incep"
  top: "conv4_1/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_1/proj"
  type: "Convolution"
  bottom: "conv3_4"
  top: "conv4_1/proj"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 256
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv4_1"
  type: "Eltwise"
  bottom: "conv4_1/out"
  bottom: "conv4_1/proj"
  top: "conv4_1"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv4_2/incep/0/conv"
  type: "Convolution"
  bottom: "conv4_1"
  top: "conv4_2/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_2/incep/0/relu"
  type: "ReLU"
  bottom: "conv4_2/incep/0"
  top: "conv4_2/incep/0"
}
layer {
  name: "conv4_2/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv4_1"
  top: "conv4_2/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_2/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv4_2/incep/1_reduce"
  top: "conv4_2/incep/1_reduce"
}
layer {
  name: "conv4_2/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv4_2/incep/1_reduce"
  top: "conv4_2/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_2/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv4_2/incep/1_0"
  top: "conv4_2/incep/1_0"
}
layer {
  name: "conv4_2/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv4_1"
  top: "conv4_2/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_2/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv4_2/incep/2_reduce"
  top: "conv4_2/incep/2_reduce"
}
layer {
  name: "conv4_2/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv4_2/incep/2_reduce"
  top: "conv4_2/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_2/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv4_2/incep/2_0"
  top: "conv4_2/incep/2_0"
}
layer {
  name: "conv4_2/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv4_2/incep/2_0"
  top: "conv4_2/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_2/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv4_2/incep/2_1"
  top: "conv4_2/incep/2_1"
}
layer {
  name: "conv4_2/incep"
  type: "Concat"
  bottom: "conv4_2/incep/0"
  bottom: "conv4_2/incep/1_0"
  bottom: "conv4_2/incep/2_1"
  top: "conv4_2/incep"
}
layer {
  name: "conv4_2/out/conv"
  type: "Convolution"
  bottom: "conv4_2/incep"
  top: "conv4_2/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_2"
  type: "Eltwise"
  bottom: "conv4_2/out"
  bottom: "conv4_1"
  top: "conv4_2"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv4_3/incep/0/conv"
  type: "Convolution"
  bottom: "conv4_2"
  top: "conv4_3/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_3/incep/0/relu"
  type: "ReLU"
  bottom: "conv4_3/incep/0"
  top: "conv4_3/incep/0"
}
layer {
  name: "conv4_3/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv4_2"
  top: "conv4_3/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_3/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv4_3/incep/1_reduce"
  top: "conv4_3/incep/1_reduce"
}
layer {
  name: "conv4_3/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv4_3/incep/1_reduce"
  top: "conv4_3/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_3/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv4_3/incep/1_0"
  top: "conv4_3/incep/1_0"
}
layer {
  name: "conv4_3/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv4_2"
  top: "conv4_3/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_3/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv4_3/incep/2_reduce"
  top: "conv4_3/incep/2_reduce"
}
layer {
  name: "conv4_3/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv4_3/incep/2_reduce"
  top: "conv4_3/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_3/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv4_3/incep/2_0"
  top: "conv4_3/incep/2_0"
}
layer {
  name: "conv4_3/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv4_3/incep/2_0"
  top: "conv4_3/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_3/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv4_3/incep/2_1"
  top: "conv4_3/incep/2_1"
}
layer {
  name: "conv4_3/incep"
  type: "Concat"
  bottom: "conv4_3/incep/0"
  bottom: "conv4_3/incep/1_0"
  bottom: "conv4_3/incep/2_1"
  top: "conv4_3/incep"
}
layer {
  name: "conv4_3/out/conv"
  type: "Convolution"
  bottom: "conv4_3/incep"
  top: "conv4_3/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_3"
  type: "Eltwise"
  bottom: "conv4_3/out"
  bottom: "conv4_2"
  top: "conv4_3"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv4_4/incep/0/conv"
  type: "Convolution"
  bottom: "conv4_3"
  top: "conv4_4/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_4/incep/0/relu"
  type: "ReLU"
  bottom: "conv4_4/incep/0"
  top: "conv4_4/incep/0"
}
layer {
  name: "conv4_4/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv4_3"
  top: "conv4_4/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_4/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv4_4/incep/1_reduce"
  top: "conv4_4/incep/1_reduce"
}
layer {
  name: "conv4_4/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv4_4/incep/1_reduce"
  top: "conv4_4/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_4/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv4_4/incep/1_0"
  top: "conv4_4/incep/1_0"
}
layer {
  name: "conv4_4/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv4_3"
  top: "conv4_4/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 24
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_4/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv4_4/incep/2_reduce"
  top: "conv4_4/incep/2_reduce"
}
layer {
  name: "conv4_4/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv4_4/incep/2_reduce"
  top: "conv4_4/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_4/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv4_4/incep/2_0"
  top: "conv4_4/incep/2_0"
}
layer {
  name: "conv4_4/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv4_4/incep/2_0"
  top: "conv4_4/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 48
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv4_4/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv4_4/incep/2_1"
  top: "conv4_4/incep/2_1"
}
layer {
  name: "conv4_4/incep"
  type: "Concat"
  bottom: "conv4_4/incep/0"
  bottom: "conv4_4/incep/1_0"
  bottom: "conv4_4/incep/2_1"
  top: "conv4_4/incep"
}
layer {
  name: "conv4_4/out/conv"
  type: "Convolution"
  bottom: "conv4_4/incep"
  top: "conv4_4/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv4_4"
  type: "Eltwise"
  bottom: "conv4_4/out"
  bottom: "conv4_3"
  top: "conv4_4"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv5_1/incep/0/conv"
  type: "Convolution"
  bottom: "conv4_4"
  top: "conv5_1/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv5_1/incep/0/relu"
  type: "ReLU"
  bottom: "conv5_1/incep/0"
  top: "conv5_1/incep/0"
}
layer {
  name: "conv5_1/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv4_4"
  top: "conv5_1/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 96
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv5_1/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv5_1/incep/1_reduce"
  top: "conv5_1/incep/1_reduce"
}
layer {
  name: "conv5_1/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv5_1/incep/1_reduce"
  top: "conv5_1/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 192
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_1/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv5_1/incep/1_0"
  top: "conv5_1/incep/1_0"
}
layer {
  name: "conv5_1/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv4_4"
  top: "conv5_1/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv5_1/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv5_1/incep/2_reduce"
  top: "conv5_1/incep/2_reduce"
}
layer {
  name: "conv5_1/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv5_1/incep/2_reduce"
  top: "conv5_1/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_1/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv5_1/incep/2_0"
  top: "conv5_1/incep/2_0"
}
layer {
  name: "conv5_1/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv5_1/incep/2_0"
  top: "conv5_1/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_1/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv5_1/incep/2_1"
  top: "conv5_1/incep/2_1"
}
layer {
  name: "conv5_1/incep/pool"
  type: "Pooling"
  bottom: "conv4_4"
  top: "conv5_1/incep/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "conv5_1/incep/poolproj/conv"
  type: "Convolution"
  bottom: "conv5_1/incep/pool"
  top: "conv5_1/incep/poolproj"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_1/incep/poolproj/relu"
  type: "ReLU"
  bottom: "conv5_1/incep/poolproj"
  top: "conv5_1/incep/poolproj"
}
layer {
  name: "conv5_1/incep"
  type: "Concat"
  bottom: "conv5_1/incep/0"
  bottom: "conv5_1/incep/1_0"
  bottom: "conv5_1/incep/2_1"
  bottom: "conv5_1/incep/poolproj"
  top: "conv5_1/incep"
}
layer {
  name: "conv5_1/out/conv"
  type: "Convolution"
  bottom: "conv5_1/incep"
  top: "conv5_1/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 384
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_1/proj"
  type: "Convolution"
  bottom: "conv4_4"
  top: "conv5_1/proj"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 384
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    engine: CAFFE
  }
}
layer {
  name: "conv5_1"
  type: "Eltwise"
  bottom: "conv5_1/out"
  bottom: "conv5_1/proj"
  top: "conv5_1"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv5_2/incep/0/conv"
  type: "Convolution"
  bottom: "conv5_1"
  top: "conv5_2/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_2/incep/0/relu"
  type: "ReLU"
  bottom: "conv5_2/incep/0"
  top: "conv5_2/incep/0"
}
layer {
  name: "conv5_2/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv5_1"
  top: "conv5_2/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 96
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_2/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv5_2/incep/1_reduce"
  top: "conv5_2/incep/1_reduce"
}
layer {
  name: "conv5_2/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv5_2/incep/1_reduce"
  top: "conv5_2/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 192
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_2/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv5_2/incep/1_0"
  top: "conv5_2/incep/1_0"
}
layer {
  name: "conv5_2/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv5_1"
  top: "conv5_2/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_2/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv5_2/incep/2_reduce"
  top: "conv5_2/incep/2_reduce"
}
layer {
  name: "conv5_2/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv5_2/incep/2_reduce"
  top: "conv5_2/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_2/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv5_2/incep/2_0"
  top: "conv5_2/incep/2_0"
}
layer {
  name: "conv5_2/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv5_2/incep/2_0"
  top: "conv5_2/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_2/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv5_2/incep/2_1"
  top: "conv5_2/incep/2_1"
}
layer {
  name: "conv5_2/incep"
  type: "Concat"
  bottom: "conv5_2/incep/0"
  bottom: "conv5_2/incep/1_0"
  bottom: "conv5_2/incep/2_1"
  top: "conv5_2/incep"
}
layer {
  name: "conv5_2/out/conv"
  type: "Convolution"
  bottom: "conv5_2/incep"
  top: "conv5_2/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 384
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_2"
  type: "Eltwise"
  bottom: "conv5_2/out"
  bottom: "conv5_1"
  top: "conv5_2"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv5_3/incep/0/conv"
  type: "Convolution"
  bottom: "conv5_2"
  top: "conv5_3/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_3/incep/0/relu"
  type: "ReLU"
  bottom: "conv5_3/incep/0"
  top: "conv5_3/incep/0"
}
layer {
  name: "conv5_3/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv5_2"
  top: "conv5_3/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 96
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_3/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv5_3/incep/1_reduce"
  top: "conv5_3/incep/1_reduce"
}
layer {
  name: "conv5_3/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv5_3/incep/1_reduce"
  top: "conv5_3/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 192
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_3/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv5_3/incep/1_0"
  top: "conv5_3/incep/1_0"
}
layer {
  name: "conv5_3/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv5_2"
  top: "conv5_3/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_3/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv5_3/incep/2_reduce"
  top: "conv5_3/incep/2_reduce"
}
layer {
  name: "conv5_3/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv5_3/incep/2_reduce"
  top: "conv5_3/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_3/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv5_3/incep/2_0"
  top: "conv5_3/incep/2_0"
}
layer {
  name: "conv5_3/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv5_3/incep/2_0"
  top: "conv5_3/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_3/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv5_3/incep/2_1"
  top: "conv5_3/incep/2_1"
}
layer {
  name: "conv5_3/incep"
  type: "Concat"
  bottom: "conv5_3/incep/0"
  bottom: "conv5_3/incep/1_0"
  bottom: "conv5_3/incep/2_1"
  top: "conv5_3/incep"
}
layer {
  name: "conv5_3/out/conv"
  type: "Convolution"
  bottom: "conv5_3/incep"
  top: "conv5_3/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 384
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_3"
  type: "Eltwise"
  bottom: "conv5_3/out"
  bottom: "conv5_2"
  top: "conv5_3"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "conv5_4/incep/0/conv"
  type: "Convolution"
  bottom: "conv5_3"
  top: "conv5_4/incep/0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_4/incep/0/relu"
  type: "ReLU"
  bottom: "conv5_4/incep/0"
  top: "conv5_4/incep/0"
}
layer {
  name: "conv5_4/incep/1_reduce/conv"
  type: "Convolution"
  bottom: "conv5_3"
  top: "conv5_4/incep/1_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 96
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_4/incep/1_reduce/relu"
  type: "ReLU"
  bottom: "conv5_4/incep/1_reduce"
  top: "conv5_4/incep/1_reduce"
}
layer {
  name: "conv5_4/incep/1_0/conv"
  type: "Convolution"
  bottom: "conv5_4/incep/1_reduce"
  top: "conv5_4/incep/1_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 192
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_4/incep/1_0/relu"
  type: "ReLU"
  bottom: "conv5_4/incep/1_0"
  top: "conv5_4/incep/1_0"
}
layer {
  name: "conv5_4/incep/2_reduce/conv"
  type: "Convolution"
  bottom: "conv5_3"
  top: "conv5_4/incep/2_reduce"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_4/incep/2_reduce/relu"
  type: "ReLU"
  bottom: "conv5_4/incep/2_reduce"
  top: "conv5_4/incep/2_reduce"
}
layer {
  name: "conv5_4/incep/2_0/conv"
  type: "Convolution"
  bottom: "conv5_4/incep/2_reduce"
  top: "conv5_4/incep/2_0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_4/incep/2_0/relu"
  type: "ReLU"
  bottom: "conv5_4/incep/2_0"
  top: "conv5_4/incep/2_0"
}
layer {
  name: "conv5_4/incep/2_1/conv"
  type: "Convolution"
  bottom: "conv5_4/incep/2_0"
  top: "conv5_4/incep/2_1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv5_4/incep/2_1/relu"
  type: "ReLU"
  bottom: "conv5_4/incep/2_1"
  top: "conv5_4/incep/2_1"
}
layer {
  name: "conv5_4/incep"
  type: "Concat"
  bottom: "conv5_4/incep/0"
  bottom: "conv5_4/incep/1_0"
  bottom: "conv5_4/incep/2_1"
  top: "conv5_4/incep"
}
layer {
  name: "conv5_4/out/conv"
  type: "Convolution"
  bottom: "conv5_4/incep"
  top: "conv5_4/out"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 384
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    engine: CAFFE
  }
}
layer {
  name: "conv5_4"
  type: "Eltwise"
  bottom: "conv5_4/out"
  bottom: "conv5_3"
  top: "conv5_4"
  eltwise_param {
    operation: SUM
    coeff: 1.0
    coeff: 1.0
  }
}
layer {
  name: "downsample"
  type: "Pooling"
  bottom: "conv3_4"
  top: "downsample"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    pad: 0
  }
}
layer {
  name: "upsample"
  type: "Deconvolution"
  bottom: "conv5_4"
  top: "upsample"
  param {
    lr_mult: 0.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 384
    bias_term: false
    pad: 1
    kernel_size: 4
    group: 384
    stride: 2
    weight_filler {
      type: "bilinear"
    }
  }
}
layer {
  name: "concat"
  type: "Concat"
  bottom: "downsample"
  bottom: "conv4_4"
  bottom: "upsample"
  top: "concat"
  concat_param {
    axis: 1
  }
}
layer {
  name: "convf_rpn"
  type: "Convolution"
  bottom: "concat"
  top: "convf_rpn"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "reluf_rpn"
  type: "ReLU"
  bottom: "convf_rpn"
  top: "convf_rpn"
}
layer {
  name: "convf_2"
  type: "Convolution"
  bottom: "concat"
  top: "convf_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.1
    }
  }
}
layer {
  name: "reluf_2"
  type: "ReLU"
  bottom: "convf_2"
  top: "convf_2"
}
layer {
  name: "concat_convf"
  type: "Concat"
  bottom: "convf_rpn"
  bottom: "convf_2"
  top: "convf"
  concat_param {
    axis: 1
  }
}
layer {
  name: "rpn_conv1"
  type: "Convolution"
  bottom: "convf_rpn"
  top: "rpn_conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "rpn_relu1"
  type: "ReLU"
  bottom: "rpn_conv1"
  top: "rpn_conv1"
}
layer {
  name: "rpn_cls_score"
  type: "Convolution"
  bottom: "rpn_conv1"
  top: "rpn_cls_score"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 12
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "rpn_bbox_pred"
  type: "Convolution"
  bottom: "rpn_conv1"
  top: "rpn_bbox_pred"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 24
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "rpn_cls_score_reshape"
  type: "Reshape"
  bottom: "rpn_cls_score"
  top: "rpn_cls_score_reshape"
  reshape_param {
    shape {
      dim: 0
      dim: 2
      dim: -1
      dim: 0
    }
  }
}
layer {
  name: "rpn_cls_prob"
  type: "Softmax"
  bottom: "rpn_cls_score_reshape"
  top: "rpn_cls_prob"
}
layer {
  name: "rpn_cls_prob_reshape"
  type: "Reshape"
  bottom: "rpn_cls_prob"
  top: "rpn_cls_prob_reshape"
  reshape_param {
    shape {
      dim: 0
      dim: 12
      dim: -1
      dim: 0
    }
  }
}
layer {
  name: "proposal"
  type: "Proposal"
  bottom: "rpn_cls_prob_reshape"
  bottom: "rpn_bbox_pred"
  bottom: "im_info"
  top: "rois"
  proposal_param {
    feat_stride: 16
    base_size: 16
    min_size: 16
    ratio: 2.669
    scale: 4.0
    scale: 6.0
    scale: 9.0
    scale: 16.0
    scale: 24.0
    scale: 32.0
    pre_nms_topn: 6000
    post_nms_topn: 200
    nms_thresh: 0.6
  }
}
layer {
  name: "detector/bbox/bbox"
  type: "Convolution"
  bottom: "convf"
  top: "detector/bbox/bbox"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 392
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "detector/bbox/ps_roi_pooling"
  type: "PSROIPooling"
  bottom: "detector/bbox/bbox"
  bottom: "rois"
  top: "detector/bbox/ps_roi_pooling"
  psroi_pooling_param {
    spatial_scale: 0.0625
    output_dim: 8
    group_size: 7
  }
}
layer {
  name: "detector/bbox/ave_pred"
  type: "Pooling"
  bottom: "detector/bbox/ps_roi_pooling"
  top: "detector/bbox/ave_pred"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 7
  }
}
layer {
  name: "bbox_pred_reshape"
  type: "Reshape"
  bottom: "detector/bbox/ave_pred"
  top: "bbox_pred"
  reshape_param {
    shape {
      dim: -1
      dim: 8
    }
  }
}
layer {
  name: "detector/cls/cls"
  type: "Convolution"
  bottom: "convf"
  top: "detector/cls/cls"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 98
    pad: 0
    kernel_size: 1
    stride: 1
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
  }
}
layer {
  name: "detector/cls/ps_roi_pooling"
  type: "PSROIPooling"
  bottom: "detector/cls/cls"
  bottom: "rois"
  top: "detector/cls/ps_roi_pooling"
  psroi_pooling_param {
    spatial_scale: 0.0625
    output_dim: 2
    group_size: 7
  }
}
layer {
  name: "detector/cls/ave_pred"
  type: "Pooling"
  bottom: "detector/cls/ps_roi_pooling"
  top: "detector/cls/ave_pred"
  pooling_param {
    pool: AVE
    kernel_size: 7
    stride: 7
  }
}
layer {
  name: "cls_prob"
  type: "Softmax"
  bottom: "detector/cls/ave_pred"
  top: "cls_prob_pre"
}
layer {
  name: "cls_prob_reshape"
  type: "Reshape"
  bottom: "cls_prob_pre"
  top: "cls_prob"
  reshape_param {
    shape {
      dim: -1
      dim: 2
    }
  }
}