infant_train_test_23d_resnet_fcn.prototxt

# concat and skip connection to adujst # of channels, i aslo use bn 10/21/2016
layer {
  name: "data"
  type: "HDF5Data"
  top: "dataMR"
  top: "dataSeg"
  include {
    phase: TRAIN 
  }
  hdf5_data_param {
    source: "./trainInfant_list.txt"
    batch_size: 10
    shuffle: true 
  }
}
layer {
  name: "data"
  type: "HDF5Data"
  top: "dataMR2D"
  top: "dataSeg2D"
  include {
    phase: TEST
  }
  hdf5_data_param {
    source: "./testInfant_list.txt"
    batch_size: 10
    shuffle: true
  }
}
#-------------layer group 1---------------
# the conv1a layer begins
#branch1 for conv1a
layer {
  name: "conv1a_branch1"
  type: "Convolution"
  bottom: "dataMR2D"
  top: "conv1a_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 96 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn1_branch1"
  type: "BatchNorm"
  bottom: "conv1a_branch1"
  top: "conv1a_bn_branch1"
}
layer {
	bottom: "conv1a_bn_branch1"
	top: "conv1a_scale_branch1"
	name: "scale_conv1a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
#branch2 for conv1a
layer {
  name: "conv1a_branch2a"
  type: "Convolution"
  bottom: "dataMR2D"
  top: "conv1a_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn1_branch2a"
  type: "BatchNorm"
  bottom: "conv1a_branch2a"
  top: "conv1a_bn_branch2a"
}
layer {
	bottom: "conv1a_bn_branch2a"
	top: "conv1a_scale_branch2a"
	name: "scale_conv1a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu1a_branch2a"
  type: "ReLU" 
  bottom: "conv1a_scale_branch2a"
  top: "conv1a_scale_branch2a"
}
layer {
  name: "conv1a_branch2b"
  type: "Convolution"
  bottom: "conv1a_scale_branch2a"
  top: "conv1a_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn1_branch2b"
  type: "BatchNorm"
  bottom: "conv1a_branch2b"
  top: "conv1a_bn_branch2b"
}
layer {
	bottom: "conv1a_bn_branch2b"
	top: "conv1a_scale_branch2b"
	name: "scale_conv1a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu1a_branch2b"
  type: "ReLU" 
  bottom: "conv1a_scale_branch2b"
  top: "conv1a_scale_branch2b"
}
layer {
  name: "conv1a_branch2c"
  type: "Convolution"
  bottom: "conv1a_scale_branch2b"
  top: "conv1a_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 96 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn1_branch2c"
  type: "BatchNorm"
  bottom: "conv1a_branch2c"
  top: "conv1a_bn_branch2c"
}
layer {
	bottom: "conv1a_bn_branch2c"
	top: "conv1a_scale_branch2c"
	name: "scale_conv1a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
	bottom: "conv1a_scale_branch1"
	bottom: "conv1a_scale_branch2c"
	top: "conv1a_scale"
	name: "elt1a"
	type: "Eltwise"
}
layer {
  name: "relu1a"
  type: "ReLU" 
  bottom: "conv1a_scale"
  top: "conv1a_scale"
}
# the conv1b layer begins
#branch1 for conv1b
layer {
  name: "conv1b_branch1"
  type: "Convolution"
  bottom: "conv1a_scale"
  top: "conv1b_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 96 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn2_branch1"
  type: "BatchNorm"
  bottom: "conv1b_branch1"
  top: "conv1b_bn_branch1"
}
layer {
	bottom: "conv1b_bn_branch1"
	top: "conv1b_scale_branch1"
	name: "scale_conv1b_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
#branch2 for conv1b
layer {
  name: "conv1b_branch2a"
  type: "Convolution"
  bottom: "conv1a_scale"
  top: "conv1b_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn2_branch2a"
  type: "BatchNorm"
  bottom: "conv1b_branch2a"
  top: "conv1b_bn_branch2a"
}
layer {
	bottom: "conv1b_bn_branch2a"
	top: "conv1b_scale_branch2a"
	name: "scale_conv1b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu1b_branch2a"
  type: "ReLU" 
  bottom: "conv1b_scale_branch2a"
  top: "conv1b_scale_branch2a"
}
layer {
  name: "conv1b_branch2b"
  type: "Convolution"
  bottom: "conv1b_scale_branch2a"
  top: "conv1b_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn2_branch2b"
  type: "BatchNorm"
  bottom: "conv1b_branch2b"
  top: "conv1b_bn_branch2b"
}
layer {
	bottom: "conv1b_bn_branch2b"
	top: "conv1b_scale_branch2b"
	name: "scale_conv1b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu1b_branch2b"
  type: "ReLU" 
  bottom: "conv1b_scale_branch2b"
  top: "conv1b_scale_branch2b"
}
layer {
  name: "conv1b_branch2c"
  type: "Convolution"
  bottom: "conv1b_scale_branch2b"
  top: "conv1b_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 96 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn2_branch2c"
  type: "BatchNorm"
  bottom: "conv1b_branch2c"
  top: "conv1b_bn_branch2c"
}
layer {
	bottom: "conv1b_bn_branch2c"
	top: "conv1b_scale_branch2c"
	name: "scale_conv1b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
	bottom: "conv1b_scale_branch1"
	bottom: "conv1b_scale_branch2c"
	top: "conv1b_scale"
	name: "elt1b"
	type: "Eltwise"
}
layer {
  name: "relu1b"
  type: "ReLU" 
  bottom: "conv1b_scale"
  top: "conv1b_scale"
}
#the conv1c layer begins
#branch1 for conv1c
layer {
  name: "conv1c_branch1"
  type: "Convolution"
  bottom: "conv1b_scale"
  top: "conv1c_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 96 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn3_branch1"
  type: "BatchNorm"
  bottom: "conv1c_branch1"
  top: "conv1c_bn_branch1"
}
layer {
	bottom: "conv1c_bn_branch1"
	top: "conv1c_scale_branch1"
	name: "scale_conv1c_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
#branch2 for conv1c
layer {
  name: "conv1c_branch2a"
  type: "Convolution"
  bottom: "conv1b_scale"
  top: "conv1c_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn3_branch2a"
  type: "BatchNorm"
  bottom: "conv1c_branch2a"
  top: "conv1c_bn_branch2a"
}
layer {
	bottom: "conv1c_bn_branch2a"
	top: "conv1c_scale_branch2a"
	name: "scale_conv1c_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu1c_branch2b"
  type: "ReLU" 
  bottom: "conv1c_scale_branch2a"
  top: "conv1c_scale_branch2a"
}
layer {
  name: "conv1c_branch2b"
  type: "Convolution"
  bottom: "conv1c_scale_branch2a"
  top: "conv1c_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn3_branch2b"
  type: "BatchNorm"
  bottom: "conv1c_branch2b"
  top: "conv1c_bn_branch2b"
}
layer {
	bottom: "conv1c_bn_branch2b"
	top: "conv1c_scale_branch2b"
	name: "scale_conv1c_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu1c_branch2b"
  type: "ReLU" 
  bottom: "conv1c_scale_branch2b"
  top: "conv1c_scale_branch2b"
}
layer {
  name: "conv1c_branch2c"
  type: "Convolution"
  bottom: "conv1c_scale_branch2b"
  top: "conv1c_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 96 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn3_branch2c"
  type: "BatchNorm"
  bottom: "conv1c_branch2c"
  top: "conv1c_bn_branch2c"
}
layer {
	bottom: "conv1c_bn_branch2c"
	top: "conv1c_scale_branch2c"
	name: "scale_conv1c_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
	bottom: "conv1c_scale_branch1"
	bottom: "conv1c_scale_branch2c"
	top: "conv1c_scale"
	name: "elt1c"
	type: "Eltwise"
}
layer {
  name: "relu1c"
  type: "ReLU" 
  bottom: "conv1c_scale"
  top: "conv1c_scale"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1c_scale"
  top: "pool1"
  pooling_param {
    #pool: AVE 
    pool: MAX 
    kernel_size: 3
    stride: 2
    engine: CUDNN
  }
}
#-------------layer group 2---------------
# the conv2a layer begins
#branch1 for conv2a
layer {
  name: "conv2a_branch1"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2a_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn4_branch1"
  type: "BatchNorm"
  bottom: "conv2a_branch1"
  top: "conv2a_bn_branch1"
}
layer {
	bottom: "conv2a_bn_branch1"
	top: "conv2a_scale_branch1"
	name: "scale_conv2a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
#branch2 for conv2a
layer {
  name: "conv2a_branch2a"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2a_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn4_branch2a"
  type: "BatchNorm"
  bottom: "conv2a_branch2a"
  top: "conv2a_bn_branch2a"
}
layer {
	bottom: "conv2a_bn_branch2a"
	top: "conv2a_scale_branch2a"
	name: "scale_conv2a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu2a_branch2a"
  type: "ReLU" 
  bottom: "conv2a_scale_branch2a"
  top: "conv2a_scale_branch2a"
}
layer {
  name: "conv2a_branch2b"
  type: "Convolution"
  bottom: "conv2a_scale_branch2a"
  top: "conv2a_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn4_branch2b"
  type: "BatchNorm"
  bottom: "conv2a_branch2b"
  top: "conv2a_bn_branch2b"
}
layer {
	bottom: "conv2a_bn_branch2b"
	top: "conv2a_scale_branch2b"
	name: "scale_conv2a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu2a_branch2b"
  type: "ReLU" 
  bottom: "conv2a_scale_branch2b"
  top: "conv2a_scale_branch2b"
}
layer {
  name: "conv2a_branch2c"
  type: "Convolution"
  bottom: "conv2a_scale_branch2b"
  top: "conv2a_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn4_branch2c"
  type: "BatchNorm"
  bottom: "conv2a_branch2c"
  top: "conv2a_bn_branch2c"
}
layer {
	bottom: "conv2a_bn_branch2c"
	top: "conv2a_scale_branch2c"
	name: "scale_conv2a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
	bottom: "conv2a_scale_branch1"
	bottom: "conv2a_scale_branch2c"
	top: "conv2a_scale"
	name: "elt2a"
	type: "Eltwise"
}
layer {
  name: "relu2a"
  type: "ReLU" 
  bottom: "conv2a_scale"
  top: "conv2a_scale"
}
# the conv2b layer begins
#branch1 for conv2b
layer {
  name: "conv2b_branch1"
  type: "Convolution"
  bottom: "conv2a_scale"
  top: "conv2b_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn5_branch1"
  type: "BatchNorm"
  bottom: "conv2b_branch1"
  top: "conv2b_bn_branch1"
}
layer {
	bottom: "conv2b_bn_branch1"
	top: "conv2b_scale_branch1"
	name: "scale_conv2b_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
#branch2 for conv2b
layer {
  name: "conv2b_branch2a"
  type: "Convolution"
  bottom: "conv2a_scale"
  top: "conv2b_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn5_branch2a"
  type: "BatchNorm"
  bottom: "conv2b_branch2a"
  top: "conv2b_bn_branch2a"
}
layer {
	bottom: "conv2b_bn_branch2a"
	top: "conv2b_scale_branch2a"
	name: "scale_conv2b_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu2b_branch2a"
  type: "ReLU" 
  bottom: "conv2b_scale_branch2a"
  top: "conv2b_scale_branch2a"
}
layer {
  name: "conv2b_branch2b"
  type: "Convolution"
  bottom: "conv2b_scale_branch2a"
  top: "conv2b_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn5_branch2b"
  type: "BatchNorm"
  bottom: "conv2b_branch2b"
  top: "conv2b_bn_branch2b"
}
layer {
	bottom: "conv2b_bn_branch2b"
	top: "conv2b_scale_branch2b"
	name: "scale_conv2b_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu2b_branch2b"
  type: "ReLU" 
  bottom: "conv2b_scale_branch2b"
  top: "conv2b_scale_branch2b"
}
layer {
  name: "conv2b_branch2c"
  type: "Convolution"
  bottom: "conv2b_scale_branch2b"
  top: "conv2b_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn5_branch2c"
  type: "BatchNorm"
  bottom: "conv2b_branch2c"
  top: "conv2b_bn_branch2c"
}
layer {
	bottom: "conv2b_bn_branch2c"
	top: "conv2b_scale_branch2c"
	name: "scale_conv2b_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
	bottom: "conv2b_scale_branch1"
	bottom: "conv2b_scale_branch2c"
	top: "conv2b_scale"
	name: "elt2b"
	type: "Eltwise"
}
layer {
  name: "relu2b"
  type: "ReLU" 
  bottom: "conv2b_scale"
  top: "conv2b_scale"
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2b_scale"
  top: "pool2"
  pooling_param {
    #pool: AVE
    pool: MAX 
    kernel_size: 3
    stride: 2
    engine: CUDNN
  }
}
#-------------layer group 3---------------
# the conv3a layer begins
#branch1 for conv3a
layer {
  name: "conv3a_branch1"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3a_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn6_branch1"
  type: "BatchNorm"
  bottom: "conv3a_branch1"
  top: "conv3a_bn_branch1"
}
layer {
	bottom: "conv3a_bn_branch1"
	top: "conv3a_scale_branch1"
	name: "scale_conv3a_branch1"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
#branch2 for conv3a
layer {
  name: "conv3a_branch3a"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3a_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn6_branch2a"
  type: "BatchNorm"
  bottom: "conv3a_branch2a"
  top: "conv3a_bn_branch2a"
}
layer {
	bottom: "conv3a_bn_branch2a"
	top: "conv3a_scale_branch2a"
	name: "scale_conv3a_branch2a"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu3a_branch2a"
  type: "ReLU" 
  bottom: "conv3a_scale_branch2a"
  top: "conv3a_scale_branch2a"
}
layer {
  name: "conv3a_branch2b"
  type: "Convolution"
  bottom: "conv3a_scale_branch2a"
  top: "conv3a_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn6_branch2b"
  type: "BatchNorm"
  bottom: "conv3a_branch2b"
  top: "conv3a_bn_branch2b"
}
layer {
	bottom: "conv3a_bn_branch2b"
	top: "conv3a_scale_branch2b"
	name: "scale_conv3a_branch2b"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
  name: "relu3a_branch2b"
  type: "ReLU" 
  bottom: "conv3a_scale_branch2b"
  top: "conv3a_scale_branch2b"
}
layer {
  name: "conv3a_branch2c"
  type: "Convolution"
  bottom: "conv3a_scale_branch2b"
  top: "conv3a_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64 
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
## BN
layer {
  name: "bn6_branch2c"
  type: "BatchNorm"
  bottom: "conv3a_branch2c"
  top: "conv3a_bn_branch2c"
}
layer {
	bottom: "conv3a_bn_branch2c"
	top: "conv3a_scale_branch2c"
	name: "scale_conv3a_branch2c"
	type: "Scale"
	scale_param {
		bias_term: true
	}
}
layer {
	bottom: "conv3a_scale_branch1"
	bottom: "conv3a_scale_branch2c"
	top: "conv3a_scale"
	name: "elt3a"
	type: "Eltwise"
}
layer {
  name: "relu3a"
  type: "ReLU" 
  bottom: "conv3a_scale"
  top: "conv3a_scale"
}
layer {
  name: "pool3"
  type: "Pooling"
  bottom: "conv3a_scale"
  top: "pool3"
  pooling_param {
    #pool: AVE
    pool: MAX 
    kernel_size: 3
    stride: 2
    engine: CUDNN
  }
}
#------------layer group 4-------------
layer {
  name: "deconv4"
  type: "Deconvolution"
  bottom: "pool3" #size is 4*4*4
  top: "deconv4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    #bias_term: false
    engine: CAFFE
    kernel_size: 4
    pad: 1
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "deconv4"
  top: "deconv4"
}
#bottleneck architecture for conv4 begins
#branch 1 for conv4
layer {
  name: "conv4_branch1"
  type: "Convolution"
  bottom: "deconv4"
  top: "conv4_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
#branch 2 for conv4
layer {
  name: "conv4_branch2a"
  type: "Convolution"
  bottom: "deconv4"
  top: "conv4_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu4_branc2a"
  type: "ReLU" 
  bottom: "conv4_branch2a"
  top: "conv4_branch2a"
}
layer {
  name: "conv4_branch2b"
  type: "Convolution"
  bottom: "conv4_branch2a"
  top: "conv4_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu4_branc2b"
  type: "ReLU" 
  bottom: "conv4_branch2b"
  top: "conv4_branch2b"
}
layer {
  name: "conv4_branch2c"
  type: "Convolution"
  bottom: "conv4_branch2b"
  top: "conv4_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
	bottom: "conv4_branch1"
	bottom: "conv4_branch2c"
	top: "conv4"
	name: "elt4"
	type: "Eltwise"
}
layer {
  name: "relu4"
  type: "ReLU" 
  bottom: "conv4"
  top: "conv4"
}
#------------layer group 5-------------
layer {
  name: "deconv5"
  type: "Deconvolution"
  bottom: "conv4"
  top: "deconv5"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    #bias_term: false
    engine: CAFFE
    kernel_size: 4
    pad: 1
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "deconv5"
  top: "deconv5"
}
#bottleneck architecture for conv5 begins
#branch 1 for conv5
layer {
  name: "conv5_branch1"
  type: "Convolution"
  bottom: "deconv5"
  top: "conv5_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
#branch 2 for conv5
layer {
  name: "conv5_branch2a"
  type: "Convolution"
  bottom: "deconv5"
  top: "conv5_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu5_branc2a"
  type: "ReLU" 
  bottom: "conv5_branch2a"
  top: "conv5_branch2a"
}
layer {
  name: "conv5_branch2b"
  type: "Convolution"
  bottom: "conv5_branch2a"
  top: "conv5_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu5_branc2b"
  type: "ReLU" 
  bottom: "conv5_branch2b"
  top: "conv5_branch2b"
}
layer {
  name: "conv5_branch2c"
  type: "Convolution"
  bottom: "conv5_branch2b"
  top: "conv5_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
	bottom: "conv5_branch1"
	bottom: "conv5_branch2c"
	top: "conv5"
	name: "elt5"
	type: "Eltwise"
}
layer {
  name: "relu5"
  type: "ReLU" 
  bottom: "conv5"
  top: "conv5"
}
#------------layer group 6-------------
layer {
  name: "deconv6"
  type: "Deconvolution"
  bottom: "conv5"
  top: "deconv6"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    #bias_term: false
    engine: CAFFE
    kernel_size: 4
    pad: 1
    stride: 2
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "deconv6"
  top: "deconv6"
}
#bottleneck architecture for conv6 begins
#branch 1 for conv6
layer {
  name: "conv6_branch1"
  type: "Convolution"
  bottom: "deconv6"
  top: "conv6_branch1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
#branch 2 for conv6
layer {
  name: "conv6_branch2a"
  type: "Convolution"
  bottom: "deconv6"
  top: "conv6_branch2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu6_branc2a"
  type: "ReLU" 
  bottom: "conv6_branch2a"
  top: "conv6_branch2a"
}
layer {
  name: "conv6_branch2b"
  type: "Convolution"
  bottom: "conv6_branch2a"
  top: "conv6_branch2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu6_branc2b"
  type: "ReLU" 
  bottom: "conv6_branch2b"
  top: "conv6_branch2b"
}
layer {
  name: "conv6_branch2c"
  type: "Convolution"
  bottom: "conv6_branch2b"
  top: "conv6_branch2c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 1
    pad: 0
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
	bottom: "conv6_branch1"
	bottom: "conv6_branch2c"
	top: "conv6"
	name: "elt6"
	type: "Eltwise"
}
layer {
  name: "relu6"
  type: "ReLU" 
  bottom: "conv6"
  top: "conv6"
}
#last conv before softmax
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "conv6"
  top: "conv7"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 4 
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      #std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu7"
  type: "ReLU" 
  bottom: "conv7"
  top: "conv7"
}
layer {
  name: "loss"
  type: "SoftmaxWithLossW"
  bottom: "conv7"
  bottom: "dataSeg"
  top: "loss"
  softmax_lossw_param {
    weight_labels: 0
    weight_labels: 1
    weight_labels: 2 
    weight_labels: 3
    labels_weight: 1
    labels_weight: 4
    labels_weight: 8
    labels_weight: 6
  }
  loss_param {
    ignore_label: -1
  }
  softmax_param {
    axis: 1
  }
  include: { phase: TRAIN }
}
layer {
  name: "loss"
  type: "SoftmaxWithLossW"
  bottom: "conv7"
  bottom: "dataSeg"
  top: "loss"
  softmax_lossw_param {
    weight_labels: 0
    weight_labels: 1
    weight_labels: 2 
    weight_labels: 3
    labels_weight: 1
    labels_weight: 4
    labels_weight: 8
    labels_weight: 6
  }
  loss_param {
    ignore_label: -1
  }
  softmax_param {
    axis: 1
  }
  include: { phase: TEST }
}

#layer {
#  name: "frscore"
#  type: "Crop"
#  bottom: "upscore"
#  bottom: "data"
#  top: "score"
#  crop_param {
#    axis: 2
#    offset: 19
#  }
#}