lane.prototxt

layer {
  name: "input"
  type: "Input"
  top: "input"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 288
      dim: 800
    }
  }
}
layer {
  name: "127"
  type: "Convolution"
  bottom: "input"
  top: "127"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 3
    pad_w: 3
    kernel_h: 7
    kernel_w: 7
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "128_bn"
  type: "BatchNorm"
  bottom: "127"
  top: "128"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "128"
  type: "Scale"
  bottom: "128"
  top: "128"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "129"
  type: "ReLU"
  bottom: "128"
  top: "129"
}
layer {
  name: "130"
  type: "Pooling"
  bottom: "129"
  top: "130"
  pooling_param {
    pool: MAX
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    pad_h: 0
    pad_w: 0
  }
}
layer {
  name: "131"
  type: "Convolution"
  bottom: "130"
  top: "131"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "132_bn"
  type: "BatchNorm"
  bottom: "131"
  top: "132"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "132"
  type: "Scale"
  bottom: "132"
  top: "132"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "133"
  type: "ReLU"
  bottom: "132"
  top: "133"
}
layer {
  name: "134"
  type: "Convolution"
  bottom: "133"
  top: "134"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "135_bn"
  type: "BatchNorm"
  bottom: "134"
  top: "135"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "135"
  type: "Scale"
  bottom: "135"
  top: "135"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "136"
  type: "Eltwise"
  bottom: "135"
  bottom: "130"
  top: "136"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "137"
  type: "ReLU"
  bottom: "136"
  top: "137"
}
layer {
  name: "138"
  type: "Convolution"
  bottom: "137"
  top: "138"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "139_bn"
  type: "BatchNorm"
  bottom: "138"
  top: "139"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "139"
  type: "Scale"
  bottom: "139"
  top: "139"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "140"
  type: "ReLU"
  bottom: "139"
  top: "140"
}
layer {
  name: "141"
  type: "Convolution"
  bottom: "140"
  top: "141"
  convolution_param {
    num_output: 64
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "142_bn"
  type: "BatchNorm"
  bottom: "141"
  top: "142"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "142"
  type: "Scale"
  bottom: "142"
  top: "142"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "143"
  type: "Eltwise"
  bottom: "142"
  bottom: "137"
  top: "143"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "144"
  type: "ReLU"
  bottom: "143"
  top: "144"
}
layer {
  name: "145"
  type: "Convolution"
  bottom: "144"
  top: "145"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "146_bn"
  type: "BatchNorm"
  bottom: "145"
  top: "146"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "146"
  type: "Scale"
  bottom: "146"
  top: "146"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "147"
  type: "ReLU"
  bottom: "146"
  top: "147"
}
layer {
  name: "148"
  type: "Convolution"
  bottom: "147"
  top: "148"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "149_bn"
  type: "BatchNorm"
  bottom: "148"
  top: "149"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "149"
  type: "Scale"
  bottom: "149"
  top: "149"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "150"
  type: "Convolution"
  bottom: "144"
  top: "150"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "151_bn"
  type: "BatchNorm"
  bottom: "150"
  top: "151"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "151"
  type: "Scale"
  bottom: "151"
  top: "151"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "152"
  type: "Eltwise"
  bottom: "149"
  bottom: "151"
  top: "152"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "153"
  type: "ReLU"
  bottom: "152"
  top: "153"
}
layer {
  name: "154"
  type: "Convolution"
  bottom: "153"
  top: "154"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "155_bn"
  type: "BatchNorm"
  bottom: "154"
  top: "155"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "155"
  type: "Scale"
  bottom: "155"
  top: "155"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "156"
  type: "ReLU"
  bottom: "155"
  top: "156"
}
layer {
  name: "157"
  type: "Convolution"
  bottom: "156"
  top: "157"
  convolution_param {
    num_output: 128
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "158_bn"
  type: "BatchNorm"
  bottom: "157"
  top: "158"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "158"
  type: "Scale"
  bottom: "158"
  top: "158"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "159"
  type: "Eltwise"
  bottom: "158"
  bottom: "153"
  top: "159"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "160"
  type: "ReLU"
  bottom: "159"
  top: "160"
}
layer {
  name: "161"
  type: "Convolution"
  bottom: "160"
  top: "161"
  convolution_param {
    num_output: 256
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "162_bn"
  type: "BatchNorm"
  bottom: "161"
  top: "162"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "162"
  type: "Scale"
  bottom: "162"
  top: "162"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "163"
  type: "ReLU"
  bottom: "162"
  top: "163"
}
layer {
  name: "164"
  type: "Convolution"
  bottom: "163"
  top: "164"
  convolution_param {
    num_output: 256
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "165_bn"
  type: "BatchNorm"
  bottom: "164"
  top: "165"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "165"
  type: "Scale"
  bottom: "165"
  top: "165"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "166"
  type: "Convolution"
  bottom: "160"
  top: "166"
  convolution_param {
    num_output: 256
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "167_bn"
  type: "BatchNorm"
  bottom: "166"
  top: "167"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "167"
  type: "Scale"
  bottom: "167"
  top: "167"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "168"
  type: "Eltwise"
  bottom: "165"
  bottom: "167"
  top: "168"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "169"
  type: "ReLU"
  bottom: "168"
  top: "169"
}
layer {
  name: "170"
  type: "Convolution"
  bottom: "169"
  top: "170"
  convolution_param {
    num_output: 256
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "171_bn"
  type: "BatchNorm"
  bottom: "170"
  top: "171"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "171"
  type: "Scale"
  bottom: "171"
  top: "171"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "172"
  type: "ReLU"
  bottom: "171"
  top: "172"
}
layer {
  name: "173"
  type: "Convolution"
  bottom: "172"
  top: "173"
  convolution_param {
    num_output: 256
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "174_bn"
  type: "BatchNorm"
  bottom: "173"
  top: "174"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "174"
  type: "Scale"
  bottom: "174"
  top: "174"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "175"
  type: "Eltwise"
  bottom: "174"
  bottom: "169"
  top: "175"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "176"
  type: "ReLU"
  bottom: "175"
  top: "176"
}
layer {
  name: "177"
  type: "Convolution"
  bottom: "176"
  top: "177"
  convolution_param {
    num_output: 512
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "178_bn"
  type: "BatchNorm"
  bottom: "177"
  top: "178"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "178"
  type: "Scale"
  bottom: "178"
  top: "178"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "179"
  type: "ReLU"
  bottom: "178"
  top: "179"
}
layer {
  name: "180"
  type: "Convolution"
  bottom: "179"
  top: "180"
  convolution_param {
    num_output: 512
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "181_bn"
  type: "BatchNorm"
  bottom: "180"
  top: "181"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "181"
  type: "Scale"
  bottom: "181"
  top: "181"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "182"
  type: "Convolution"
  bottom: "176"
  top: "182"
  convolution_param {
    num_output: 512
    bias_term: false
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
    dilation: 1
  }
}
layer {
  name: "183_bn"
  type: "BatchNorm"
  bottom: "182"
  top: "183"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "183"
  type: "Scale"
  bottom: "183"
  top: "183"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "184"
  type: "Eltwise"
  bottom: "181"
  bottom: "183"
  top: "184"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "185"
  type: "ReLU"
  bottom: "184"
  top: "185"
}
layer {
  name: "186"
  type: "Convolution"
  bottom: "185"
  top: "186"
  convolution_param {
    num_output: 512
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "187_bn"
  type: "BatchNorm"
  bottom: "186"
  top: "187"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "187"
  type: "Scale"
  bottom: "187"
  top: "187"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "188"
  type: "ReLU"
  bottom: "187"
  top: "188"
}
layer {
  name: "189"
  type: "Convolution"
  bottom: "188"
  top: "189"
  convolution_param {
    num_output: 512
    bias_term: false
    group: 1
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "190_bn"
  type: "BatchNorm"
  bottom: "189"
  top: "190"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "190"
  type: "Scale"
  bottom: "190"
  top: "190"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "191"
  type: "Eltwise"
  bottom: "190"
  bottom: "185"
  top: "191"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "192"
  type: "ReLU"
  bottom: "191"
  top: "192"
}
layer {
  name: "193"
  type: "Convolution"
  bottom: "192"
  top: "193"
  convolution_param {
    num_output: 8
    bias_term: true
    group: 1
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
    dilation: 1
  }
}
layer {
  name: "195"
  type: "Flatten"
  bottom: "193"
  top: "195"
}
layer {
  name: "196"
  type: "InnerProduct"
  bottom: "195"
  top: "196"
  inner_product_param {
    num_output: 2048
    bias_term: true
  }
}
layer {
  name: "197"
  type: "ReLU"
  bottom: "196"
  top: "197"
}
layer {
  name: "198"
  type: "InnerProduct"
  bottom: "197"
  top: "198"
  inner_product_param {
    num_output: 14472
    bias_term: true
  }
}
layer {
  name: "output"
  type: "Reshape"
  bottom: "198"
  top: "output"
  reshape_param {
    shape {
      dim: -1
      dim: 201
      dim: 18
      dim: 4
    }
  }
}