#Klein prototext

name: "TVG_CRF_RNN_COCO_VOC_TRAIN_3_CLASSES"
layer {
  name: "data_rgb"
  type: "Data"
  top: "data"
  data_param {
    source: "/home/hesam/Prog_Python_linux/Medical_tests/converted/train_images_lmdb"
    backend: LMDB
    batch_size: 1
  }
  include: { phase: TRAIN }
}

layer {
  name: "data_label"
  type: "Data"
  top: "label"
  data_param {
    source: "/home/hesam/Prog_Python_linux/Medical_tests/converted/train_labels_lmdb"
    backend: LMDB
    batch_size: 1
  }
  include: { phase: TRAIN }
}

layer {
  name: "data_rgb"
  type: "Data"
  top: "data"
  data_param {
    source: "/home/hesam/Prog_Python_linux/Medical_tests/converted/test_images_lmdb"
    backend: LMDB
    batch_size: 1
  }
  include: { phase: TEST }
}
layer {
  name: "data_label"
  type: "Data"
  top: "label"
  data_param {
    source: "/home/hesam/Prog_Python_linux/Medical_tests/converted/test_labels_lmdb"
    backend: LMDB
    batch_size: 1
  }
  include: { phase: TEST }
}

layer {
  name: "conv1_1"
  type: "Convolution"
  bottom: "data"
  top: "conv1_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 100
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
layer {
  name: "relu1_2"
  type: "ReLU"
  bottom: "conv1_2"
  top: "conv1_2"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1_2"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv2_1"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 128
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
layer {
  name: "relu2_2"
  type: "ReLU"
  bottom: "conv2_2"
  top: "conv2_2"
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2_2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv3_1"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
layer {
  name: "relu3_3"
  type: "ReLU"
  bottom: "conv3_3"
  top: "conv3_3"
}
layer {
  name: "pool3"
  type: "Pooling"
  bottom: "conv3_3"
  top: "pool3"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv4_1"
  type: "Convolution"
  bottom: "pool3"
  top: "conv4_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
layer {
  name: "relu4_3"
  type: "ReLU"
  bottom: "conv4_3"
  top: "conv4_3"
}
layer {
  name: "pool4"
  type: "Pooling"
  bottom: "conv4_3"
  top: "pool4"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv5_1"
  type: "Convolution"
  bottom: "pool4"
  top: "conv5_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
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: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 512
    pad: 1
    kernel_size: 3
    engine: CAFFE
  }
}
layer {
  name: "relu5_3"
  type: "ReLU"
  bottom: "conv5_3"
  top: "conv5_3"
}
layer {
  name: "pool5"
  type: "Pooling"
  bottom: "conv5_3"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "fc6"
  type: "Convolution"
  bottom: "pool5"
  top: "fc6"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4096
    kernel_size: 7
    engine: CAFFE
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "fc6"
  top: "fc6"
}
layer {
  name: "drop6"
  type: "Dropout"
  bottom: "fc6"
  top: "fc6"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "fc7"
  type: "Convolution"
  bottom: "fc6"
  top: "fc7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4096
    kernel_size: 1
    engine: CAFFE
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "fc7"
  top: "fc7"
}
layer {
  name: "drop7"
  type: "Dropout"
  bottom: "fc7"
  top: "fc7"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "score-fr-new"
  type: "Convolution"
  bottom: "fc7"
  top: "score"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2 #21
    kernel_size: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer {
  name: "score2-new"
  type: "Deconvolution"
  bottom: "score"
  top: "score2-new"
  param {
    lr_mult: 1
  }
  convolution_param {
    num_output: 2 #21
    kernel_size: 4
    stride: 2
    weight_filler: { type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2 }
  }
}
layer {
  name: "score-pool4-new"
  type: "Convolution"
  bottom: "pool4"
  top: "score-pool4-new"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2 #21
    kernel_size: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer { type: 'Crop' name: 'crop' bottom: 'score-pool4-new' bottom: 'score2-new'
  top: 'score-pool4c' }
layer {
  name: "fuse"
  type: "Eltwise"
  bottom: "score2-new"
  bottom: "score-pool4c"
  top: "score-fused"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "score4-new"
  type: "Deconvolution"
  bottom: "score-fused"
  top: "score4-new"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 2 #21
    bias_term: false
    kernel_size: 4
    stride: 2
    weight_filler: { type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2 }
  }
}
layer {
  name: "score-pool3-new"
  type: "Convolution"
  bottom: "pool3"
  top: "score-pool3-new"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2 #21
    kernel_size: 1
    engine: CAFFE
    weight_filler {
      type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2
    }
  }
}
layer { type: 'Crop' name: 'crop' bottom: 'score-pool3-new' bottom: 'score4-new'
  top: 'score-pool3c' }
layer {
  name: "fuse"
  type: "Eltwise"
  bottom: "score4-new"
  bottom: "score-pool3c"
  top: "score-final"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "upsample-new"
  type: "Deconvolution"
  bottom: "score-final"
  top: "bigscore"
  param {
    lr_mult: 0
  }
  convolution_param {
    num_output: 2 #21
    bias_term: false
    kernel_size: 16
    stride: 8
    weight_filler: { type: "xavier"
      std: 0.1
    }
    bias_filler {
      type: "constant"
      value: 0.2 }
  }
}
layer { type: 'Crop' name: 'crop' bottom: 'bigscore' bottom: 'data' top: 'coarse' }

layer { type: 'Split' name: 'splitting'
  bottom: 'coarse' top: 'unary' top: 'Q0'
}

layer {
  name: "inference1-new"#if you set name "inference1", code will load parameters from caffemodel.
  type: "MultiStageMeanfield"
  bottom: "unary"
  bottom: "Q0"
  bottom: "data"
  top: "pred"
  param {
    lr_mult: 10000#learning rate for W_G
  }
  param {
  lr_mult: 10000#learning rate for W_B
  }
  param {
  lr_mult: 1000 #learning rate for compatiblity transform matrix
  }
  multi_stage_meanfield_param {
	#spatial_filter_weights_str: "3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3"
	#bilateral_filter_weights_str: "5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5"
	num_iterations: 10
	compatibility_mode: POTTS
	threshold: 2
	theta_alpha: 160
	theta_beta: 3
	theta_gamma: 3
  }
}
layer {
  name: "loss"
  type: "SoftmaxWithLoss"
  bottom: "pred"
  bottom: "label"
  top: "loss"
  loss_param {
    ignore_label: 255
    normalize: false
  }
  include: { phase: TRAIN }
}