input: "data"
input_dim: 1
input_dim: 3
input_dim: 80
input_dim: 80
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 2
    kernel_size: 5
    group: 1
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "conv1_bn"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1_bn"
  batch_norm_param {
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "conv1_bn"
  top: "conv1_bn"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1_bn"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "conv2_a"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2_a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "conv2_a_bn"
  type: "BatchNorm"
  bottom: "conv2_a"
  top: "conv2_a_bn"
  batch_norm_param {
  }
}
layer {
  name: "relu2_a"
  type: "ReLU"
  bottom: "conv2_a_bn"
  top: "conv2_a_bn"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "conv2_a_bn"
  top: "conv2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 32
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "conv2_bn"
  type: "BatchNorm"
  bottom: "conv2"
  top: "conv2_bn"
  batch_norm_param {
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "conv2_bn"
  top: "conv2_bn"
}
layer {
  name: "pool3"
  type: "Pooling"
  bottom: "conv2_bn"
  top: "pool3"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "conv4_a"
  type: "Convolution"
  bottom: "pool3"
  top: "conv4_a"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "conv4_a_bn"
  type: "BatchNorm"
  bottom: "conv4_a"
  top: "conv4_a_bn"
  batch_norm_param {
  }
}
layer {
  name: "relu4_a"
  type: "ReLU"
  bottom: "conv4_a_bn"
  top: "conv4_a_bn"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv4_a_bn"
  top: "conv4"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "conv4_bn"
  type: "BatchNorm"
  bottom: "conv4"
  top: "conv4_bn"
  batch_norm_param {
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "conv4_bn"
  top: "conv4_bn"
}
layer {
  name: "pool6"
  type: "Pooling"
  bottom: "conv4_bn"
  top: "pool6"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "fc1"
  type: "InnerProduct"
  bottom: "pool6"
  top: "fc1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 256
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "fc1_bn"
  type: "BatchNorm"
  bottom: "fc1"
  top: "fc1_bn"
  batch_norm_param {
  }
}
layer {
  name: "relu_fc1"
  type: "ReLU"
  bottom: "fc1_bn"
  top: "fc1_bn"
}
layer {
  name: "fc2"
  type: "InnerProduct"
  bottom: "fc1_bn"
  top: "fc2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 128
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "fc2_bn"
  type: "BatchNorm"
  bottom: "fc2"
  top: "fc2_bn"
  batch_norm_param {
  }
}
layer {
  name: "relu_fc2"
  type: "ReLU"
  bottom: "fc2_bn"
  top: "fc2_bn"
}
layer {
  name: "fc_pose_umd"
  type: "InnerProduct"
  bottom: "fc2_bn"
  top: "fc_pose_umd"
  inner_product_param {
    num_output: 3
  }
}