name: "Mnet_vA367_extract_hair"
input: "data"
input_dim: 1
input_dim: 6
input_dim: 512
input_dim: 512

layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv_blob1"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm1"
  type: "BatchNorm"
  bottom: "conv_blob1"
  top: "batch_norm_blob1"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale1"
  type: "Scale"
  bottom: "batch_norm_blob1"
  top: "batch_norm_blob1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "batch_norm_blob1"
  top: "relu_blob1"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "relu_blob1"
  top: "conv_blob2"
  convolution_param {
    num_output: 8
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm2"
  type: "BatchNorm"
  bottom: "conv_blob2"
  top: "batch_norm_blob2"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale2"
  type: "Scale"
  bottom: "batch_norm_blob2"
  top: "batch_norm_blob2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "batch_norm_blob2"
  top: "relu_blob2"
}
layer {
  name: "max_pool1"
  type: "Pooling"
  bottom: "relu_blob1"
  top: "max_pool_blob1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "max_pool_blob1"
  top: "conv_blob3"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm3"
  type: "BatchNorm"
  bottom: "conv_blob3"
  top: "batch_norm_blob3"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale3"
  type: "Scale"
  bottom: "batch_norm_blob3"
  top: "batch_norm_blob3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "batch_norm_blob3"
  top: "relu_blob3"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "relu_blob3"
  top: "conv_blob4"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm4"
  type: "BatchNorm"
  bottom: "conv_blob4"
  top: "batch_norm_blob4"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale4"
  type: "Scale"
  bottom: "batch_norm_blob4"
  top: "batch_norm_blob4"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "batch_norm_blob4"
  top: "relu_blob4"
}
layer {
  name: "max_pool2"
  type: "Pooling"
  bottom: "relu_blob3"
  top: "max_pool_blob2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "max_pool_blob2"
  top: "conv_blob5"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm5"
  type: "BatchNorm"
  bottom: "conv_blob5"
  top: "batch_norm_blob5"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale5"
  type: "Scale"
  bottom: "batch_norm_blob5"
  top: "batch_norm_blob5"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "batch_norm_blob5"
  top: "relu_blob5"
}
layer {
  name: "conv6"
  type: "Convolution"
  bottom: "relu_blob5"
  top: "conv_blob6"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm6"
  type: "BatchNorm"
  bottom: "conv_blob6"
  top: "batch_norm_blob6"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale6"
  type: "Scale"
  bottom: "batch_norm_blob6"
  top: "batch_norm_blob6"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "batch_norm_blob6"
  top: "relu_blob6"
}
layer {
  name: "max_pool3"
  type: "Pooling"
  bottom: "relu_blob5"
  top: "max_pool_blob3"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "max_pool_blob3"
  top: "conv_blob7"
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm7"
  type: "BatchNorm"
  bottom: "conv_blob7"
  top: "batch_norm_blob7"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale7"
  type: "Scale"
  bottom: "batch_norm_blob7"
  top: "batch_norm_blob7"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "batch_norm_blob7"
  top: "relu_blob7"
}
layer {
  name: "conv8"
  type: "Convolution"
  bottom: "relu_blob7"
  top: "conv_blob8"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm8"
  type: "BatchNorm"
  bottom: "conv_blob8"
  top: "batch_norm_blob8"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale8"
  type: "Scale"
  bottom: "batch_norm_blob8"
  top: "batch_norm_blob8"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu8"
  type: "ReLU"
  bottom: "batch_norm_blob8"
  top: "relu_blob8"
}
layer {
  name: "max_pool4"
  type: "Pooling"
  bottom: "relu_blob7"
  top: "max_pool_blob4"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv9"
  type: "Convolution"
  bottom: "max_pool_blob4"
  top: "conv_blob9"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm9"
  type: "BatchNorm"
  bottom: "conv_blob9"
  top: "batch_norm_blob9"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale9"
  type: "Scale"
  bottom: "batch_norm_blob9"
  top: "batch_norm_blob9"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu9"
  type: "ReLU"
  bottom: "batch_norm_blob9"
  top: "relu_blob9"
}
layer {
  name: "cat1"
  type: "Concat"
  bottom: "relu_blob9"
  bottom: "max_pool_blob4"
  top: "cat_blob1"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv10"
  type: "Convolution"
  bottom: "cat_blob1"
  top: "conv_blob10"
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm10"
  type: "BatchNorm"
  bottom: "conv_blob10"
  top: "batch_norm_blob10"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale10"
  type: "Scale"
  bottom: "batch_norm_blob10"
  top: "batch_norm_blob10"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu10"
  type: "ReLU"
  bottom: "batch_norm_blob10"
  top: "relu_blob10"
}
layer {
  name: "conv11"
  type: "Convolution"
  bottom: "relu_blob10"
  top: "conv_blob11"
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 2
    kernel_size: 5
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "conv_transpose1"
  type: "Deconvolution"
  bottom: "conv_blob11"
  top: "conv_transpose_blob1"
  convolution_param {
    num_output: 128
    pad: 0
    kernel_size: 2
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  bias_filler{
      type:"constant"
      value:0
  }
  }

}
layer {
  name: "cat2"
  type: "Concat"
  bottom: "relu_blob8"
  bottom: "conv_transpose_blob1"
  top: "cat_blob2"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "cat_blob2"
  top: "conv_blob12"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm11"
  type: "BatchNorm"
  bottom: "conv_blob12"
  top: "batch_norm_blob11"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale11"
  type: "Scale"
  bottom: "batch_norm_blob11"
  top: "batch_norm_blob11"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu11"
  type: "ReLU"
  bottom: "batch_norm_blob11"
  top: "relu_blob11"
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "relu_blob11"
  top: "conv_blob13"
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 2
    kernel_size: 5
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "conv_transpose2"
  type: "Deconvolution"
  bottom: "conv_blob13"
  top: "conv_transpose_blob2"
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 2
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  bias_filler{
      type:"constant"
      value:0
  }
  }

}
layer {
  name: "cat3"
  type: "Concat"
  bottom: "relu_blob6"
  bottom: "conv_transpose_blob2"
  top: "cat_blob3"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv14"
  type: "Convolution"
  bottom: "cat_blob3"
  top: "conv_blob14"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm12"
  type: "BatchNorm"
  bottom: "conv_blob14"
  top: "batch_norm_blob12"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale12"
  type: "Scale"
  bottom: "batch_norm_blob12"
  top: "batch_norm_blob12"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu12"
  type: "ReLU"
  bottom: "batch_norm_blob12"
  top: "relu_blob12"
}
layer {
  name: "conv15"
  type: "Convolution"
  bottom: "relu_blob12"
  top: "conv_blob15"
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 2
    kernel_size: 5
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "conv_transpose3"
  type: "Deconvolution"
  bottom: "conv_blob15"
  top: "conv_transpose_blob3"
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 2
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  bias_filler{
      type:"constant"
      value:0
  }
  }

}
layer {
  name: "cat4"
  type: "Concat"
  bottom: "relu_blob4"
  bottom: "conv_transpose_blob3"
  top: "cat_blob4"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv16"
  type: "Convolution"
  bottom: "cat_blob4"
  top: "conv_blob16"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "batch_norm13"
  type: "BatchNorm"
  bottom: "conv_blob16"
  top: "batch_norm_blob13"
  batch_norm_param {
    use_global_stats: true
    eps: 9.999999747378752e-06
  }
}
layer {
  name: "bn_scale13"
  type: "Scale"
  bottom: "batch_norm_blob13"
  top: "batch_norm_blob13"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu13"
  type: "ReLU"
  bottom: "batch_norm_blob13"
  top: "relu_blob13"
}
layer {
  name: "conv17"
  type: "Convolution"
  bottom: "relu_blob13"
  top: "conv_blob17"
  convolution_param {
    num_output: 16
    bias_term: false
    pad: 2
    kernel_size: 5
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}
layer {
  name: "conv_transpose4"
  type: "Deconvolution"
  bottom: "conv_blob17"
  top: "conv_transpose_blob4"
  convolution_param {
    num_output: 16
    pad: 0
    kernel_size: 2
    stride: 2
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  bias_filler{
      type:"constant"
      value:0
  }
  }

}
layer {
  name: "cat5"
  type: "Concat"
  bottom: "relu_blob2"
  bottom: "conv_transpose_blob4"
  top: "cat_blob5"
  concat_param {
    axis: 1
  }
}
layer {
  name: "conv18"
  type: "Convolution"
  bottom: "cat_blob5"
  top: "output"
  convolution_param {
    num_output: 1
    bias_term: false
    pad: 2
    kernel_size: 5
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    dilation: 1
  }
}