layer {
	name: "input"
	type: "Input"
	top: "data" # BGR image from [0,255] ***NOT MEAN CENTERED***
	input_param { shape { dim: 60 dim: 3 dim: 227 dim: 227 } }
}
layer { # Convert to lab
  name: "img_lab"
  type: "ColorConv"
  bottom: "data"
  top: "img_lab"
  propagate_down: false
  color_conv_param {
    input: 0 # BGR
    output: 3 # Lab
  }
}
layer { # 0-center lightness channel
  name: "data_lab"
  type: "Convolution"
  bottom: "img_lab"
  top: "data_lab" # [-50,50]
  propagate_down: false
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  convolution_param {
    kernel_size: 1
    num_output: 3
    group: 3
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  # bottom: "img"
  bottom: "data_lab"
  # bottom: "img_bn"
  top: "conv1"
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  convolution_param {
    num_output: 96
    kernel_size: 11
    stride: 4
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2"
  param {    lr_mult: 0    decay_mult: 0  }
  param {    lr_mult: 0    decay_mult: 0  }
  convolution_param {
    num_output: 256
    pad: 2
    kernel_size: 5
    group: 2
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2"
}
layer {
  name: "pool2"
  type: "Pooling"
  # bottom: "conv2"
  bottom: "conv2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
    # pad: 1
  }
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3"
  # propagate_down: false
  param {    lr_mult: 0    decay_mult: 0  }
  param {    lr_mult: 0    decay_mult: 0  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "conv3"
  top: "conv3"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv3"
  top: "conv4"
  param {    lr_mult: 0    decay_mult: 0  }
  param {    lr_mult: 0    decay_mult: 0  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    group: 2
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "conv4"
  top: "conv4"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "conv4"
  top: "conv5"
  param {    lr_mult: 0    decay_mult: 0  }
  param {    lr_mult: 0    decay_mult: 0  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 2
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "conv5"
  top: "conv5"
}
layer {
  name: "pool5"
  type: "Pooling"
  bottom: "conv5"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "fc6"
  type: "Convolution"
  bottom: "pool5"
  top: "fc6"
  param {    lr_mult: 0    decay_mult: 0  }
  param {    lr_mult: 0    decay_mult: 0  }
  convolution_param {
    kernel_size: 6
    dilation: 2
    pad: 5
    stride: 1
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "fc6"
  top: "fc6"
}
layer {
  name: "fc7"
  type: "Convolution"
  bottom: "fc6"
  top: "fc7"
  param {    lr_mult: 0    decay_mult: 0  }
  param {    lr_mult: 0    decay_mult: 0  }
  convolution_param {
    kernel_size: 1
    stride: 1
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "fc7"
  top: "fc7"
}