colorization_deploy_v1.prototxt

name: "LtoAB"
input: "data_l"
input_shape {
  dim: 1
  dim: 1
  dim: 224
  dim: 224
}
input: "Trecip" # reciprocal of annealing temperature T
input_shape {
  dim: 1
  dim: 313
  dim: 56
  dim: 56
}
force_backward: true
# *****************
# ***** conv1 *****
# *****************
layer {
  name: "bw_conv1_1"
  type: "Convolution"
  bottom: "data_l"
  top: "conv1_1"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu1_1"
  type: "ReLU"
  bottom: "conv1_1"
  top: "conv1_1"
}
layer {
  name: "conv1_2"
  type: "Convolution"
  bottom: "conv1_1"
  top: "conv1_2"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "relu1_2"
  type: "ReLU"
  bottom: "conv1_2"
  top: "conv1_2"
}
layer {
  name: "conv1_2norm"
  type: "BatchNorm"
  bottom: "conv1_2"
  top: "conv1_2norm"
  batch_norm_param{ }
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
}
# *****************
# ***** conv2 *****
# *****************
layer {
  name: "conv2_1"
  type: "Convolution"
  # bottom: "conv1_2"
  bottom: "conv1_2norm"
  # bottom: "pool1"
  top: "conv2_1"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu2_1"
  type: "ReLU"
  bottom: "conv2_1"
  top: "conv2_1"
}
layer {
  name: "conv2_2"
  type: "Convolution"
  bottom: "conv2_1"
  top: "conv2_2"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "relu2_2"
  type: "ReLU"
  bottom: "conv2_2"
  top: "conv2_2"
}
layer {
  name: "conv2_2norm"
  type: "BatchNorm"
  bottom: "conv2_2"
  top: "conv2_2norm"
  batch_norm_param{ }
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
}
# *****************
# ***** conv3 *****
# *****************
layer {
  name: "conv3_1"
  type: "Convolution"
  # bottom: "conv2_2"
  bottom: "conv2_2norm"
  # bottom: "pool2"
  top: "conv3_1"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu3_1"
  type: "ReLU"
  bottom: "conv3_1"
  top: "conv3_1"
}
layer {
  name: "conv3_2"
  type: "Convolution"
  bottom: "conv3_1"
  top: "conv3_2"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
  }
}
layer {
  name: "relu3_2"
  type: "ReLU"
  bottom: "conv3_2"
  top: "conv3_2"
}
layer {
  name: "conv3_3"
  type: "Convolution"
  bottom: "conv3_2"
  top: "conv3_3"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "relu3_3"
  type: "ReLU"
  bottom: "conv3_3"
  top: "conv3_3"
}
layer {
  name: "conv3_3norm"
  type: "BatchNorm"
  bottom: "conv3_3"
  top: "conv3_3norm"
  batch_norm_param{ }
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
}
# *****************
# ***** conv4 *****
# *****************
layer {
  name: "conv4_1"
  type: "Convolution"
  # bottom: "conv3_3"
  bottom: "conv3_3norm"
  # bottom: "pool3"
  top: "conv4_1"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu4_1"
  type: "ReLU"
  bottom: "conv4_1"
  top: "conv4_1"
}
layer {
  name: "conv4_2"
  type: "Convolution"
  bottom: "conv4_1"
  top: "conv4_2"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu4_2"
  type: "ReLU"
  bottom: "conv4_2"
  top: "conv4_2"
}
layer {
  name: "conv4_3"
  type: "Convolution"
  bottom: "conv4_2"
  top: "conv4_3"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu4_3"
  type: "ReLU"
  bottom: "conv4_3"
  top: "conv4_3"
}
layer {
  name: "conv4_3norm"
  type: "BatchNorm"
  bottom: "conv4_3"
  top: "conv4_3norm"
  batch_norm_param{ }
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
}
# *****************
# ***** conv5 *****
# *****************
layer {
  name: "conv5_1"
  type: "Convolution"
  # bottom: "conv4_3"
  bottom: "conv4_3norm"
  # bottom: "pool4"
  top: "conv5_1"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0}   
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 2
    dilation: 2
  }
}
layer {
  name: "relu5_1"
  type: "ReLU"
  bottom: "conv5_1"
  top: "conv5_1"
}
layer {
  name: "conv5_2"
  type: "Convolution"
  bottom: "conv5_1"
  top: "conv5_2"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 2
    dilation: 2
  }
}
layer {
  name: "relu5_2"
  type: "ReLU"
  bottom: "conv5_2"
  top: "conv5_2"
}
layer {
  name: "conv5_3"
  type: "Convolution"
  bottom: "conv5_2"
  top: "conv5_3"
  # param {lr_mult: 0 decay_mult: 0} 
  # param {lr_mult: 0 decay_mult: 0} 
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 2
    dilation: 2
  }
}
layer {
  name: "relu5_3"
  type: "ReLU"
  bottom: "conv5_3"
  top: "conv5_3"
}
layer {
  name: "conv5_3norm"
  type: "BatchNorm"
  bottom: "conv5_3"
  top: "conv5_3norm"
  batch_norm_param{ }
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
}
# *****************
# ***** conv6 *****
# *****************
layer {
  name: "conv6_1"
  type: "Convolution"
  bottom: "conv5_3norm"
  top: "conv6_1"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 2
    dilation: 2
  }
}
layer {
  name: "relu6_1"
  type: "ReLU"
  bottom: "conv6_1"
  top: "conv6_1"
}
layer {
  name: "conv6_2"
  type: "Convolution"
  bottom: "conv6_1"
  top: "conv6_2"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 2
    dilation: 2
  }
}
layer {
  name: "relu6_2"
  type: "ReLU"
  bottom: "conv6_2"
  top: "conv6_2"
}
layer {
  name: "conv6_3"
  type: "Convolution"
  bottom: "conv6_2"
  top: "conv6_3"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 2
    dilation: 2
  }
}
layer {
  name: "relu6_3"
  type: "ReLU"
  bottom: "conv6_3"
  top: "conv6_3"
}
layer {
  name: "conv6_3norm"
  type: "BatchNorm"
  bottom: "conv6_3"
  top: "conv6_3norm"
  batch_norm_param{ }
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
}
# *****************
# ***** conv7 *****
# *****************
layer {
  name: "conv7_1"
  type: "Convolution"
  bottom: "conv6_3norm"
  top: "conv7_1"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu7_1"
  type: "ReLU"
  bottom: "conv7_1"
  top: "conv7_1"
}
layer {
  name: "conv7_2"
  type: "Convolution"
  bottom: "conv7_1"
  top: "conv7_2"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu7_2"
  type: "ReLU"
  bottom: "conv7_2"
  top: "conv7_2"
}
layer {
  name: "conv7_3"
  type: "Convolution"
  bottom: "conv7_2"
  top: "conv7_3"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu7_3"
  type: "ReLU"
  bottom: "conv7_3"
  top: "conv7_3"
}
layer {
  name: "conv7_3norm"
  type: "BatchNorm"
  bottom: "conv7_3"
  top: "conv7_3norm"
  batch_norm_param{ }
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
  param {lr_mult: 0 decay_mult: 0}
}
# *****************
# ***** conv8 *****
# *****************
layer {
  name: "conv8_1"
  type: "Deconvolution"
  bottom: "conv7_3norm"
  top: "conv8_1"
  convolution_param {
    num_output: 256
    kernel_size: 4
    pad: 1
    dilation: 1
    stride: 2
  }
}
layer {
  name: "relu8_1"
  type: "ReLU"
  bottom: "conv8_1"
  top: "conv8_1"
}
layer {
  name: "conv8_2"
  type: "Convolution"
  bottom: "conv8_1"
  top: "conv8_2"
  convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu8_2"
  type: "ReLU"
  bottom: "conv8_2"
  top: "conv8_2"
}
layer {
  name: "conv8_3"
  type: "Convolution"
  bottom: "conv8_2"
  top: "conv8_3"
  convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    dilation: 1
  }
}
layer {
  name: "relu8_3"
  type: "ReLU"
  bottom: "conv8_3"
  top: "conv8_3"
}
# *******************
# ***** Softmax *****
# *******************
layer {
  name: "conv8_313"
  type: "Convolution"
  bottom: "conv8_3"
  top: "conv8_313"
  convolution_param {
    num_output: 313
    kernel_size: 1
    stride: 1
    dilation: 1
  }
}
layer {
  name: "Reheat8"
  type: "Eltwise"
  bottom: "conv8_313"
  bottom: "Trecip"
  top: "conv8_313_rh"
  eltwise_param {
    operation: 0
  }
}
layer {
  name: "Softmax8"
  type: "Softmax"
  bottom: "conv8_313_rh"
  top: "class8_313_rh"
}
# ********************
# ***** Decoding *****
# ********************
layer {
  name: "class8_ab"
  type: "Convolution"
  bottom: "class8_313_rh"
  top: "class8_ab"
  convolution_param {
    num_output: 2
    kernel_size: 1
    stride: 1
    dilation: 1
  }
}
layer {
  name: "Silence"
  type: "Silence"
  bottom: "class8_ab"
}