learnopencv/GOTURN/goturn.prototxt

name: "GOTURN"

input: "data1"
input_dim: 1
input_dim: 3
input_dim: 227
input_dim: 227

input: "data2"
input_dim: 1
input_dim: 3
input_dim: 227
input_dim: 227

layer {
  name: "conv11"
  type: "Convolution"
  bottom: "data1"
  top: "conv11"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    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: "relu11"
  type: "ReLU"
  bottom: "conv11"
  top: "conv11"
}
layer {
  name: "pool11"
  type: "Pooling"
  bottom: "conv11"
  top: "pool11"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm11"
  type: "LRN"
  bottom: "pool11"
  top: "norm11"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "norm11"
  top: "conv12"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 2
    kernel_size: 5
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu12"
  type: "ReLU"
  bottom: "conv12"
  top: "conv12"
}
layer {
  name: "pool12"
  type: "Pooling"
  bottom: "conv12"
  top: "pool12"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm12"
  type: "LRN"
  bottom: "pool12"
  top: "norm12"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "norm12"
  top: "conv13"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    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: "relu13"
  type: "ReLU"
  bottom: "conv13"
  top: "conv13"
}
layer {
  name: "conv14"
  type: "Convolution"
  bottom: "conv13"
  top: "conv14"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu14"
  type: "ReLU"
  bottom: "conv14"
  top: "conv14"
}
layer {
  name: "conv15"
  type: "Convolution"
  bottom: "conv14"
  top: "conv15"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu15"
  type: "ReLU"
  bottom: "conv15"
  top: "conv15"
}
layer {
  name: "pool15"
  type: "Pooling"
  bottom: "conv15"
  top: "pool15"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}


layer {
  name: "conv21"
  type: "Convolution"
  bottom: "data2"
  top: "conv21"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    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: "relu21"
  type: "ReLU"
  bottom: "conv21"
  top: "conv21"
}
layer {
  name: "pool21"
  type: "Pooling"
  bottom: "conv21"
  top: "pool21"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm21"
  type: "LRN"
  bottom: "pool21"
  top: "norm21"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv22"
  type: "Convolution"
  bottom: "norm21"
  top: "conv22"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 2
    kernel_size: 5
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu22"
  type: "ReLU"
  bottom: "conv22"
  top: "conv22"
}
layer {
  name: "pool22"
  type: "Pooling"
  bottom: "conv22"
  top: "pool22"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm22"
  type: "LRN"
  bottom: "pool22"
  top: "norm22"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv23"
  type: "Convolution"
  bottom: "norm22"
  top: "conv23"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    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: "relu23"
  type: "ReLU"
  bottom: "conv23"
  top: "conv23"
}
layer {
  name: "conv24"
  type: "Convolution"
  bottom: "conv23"
  top: "conv24"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu24"
  type: "ReLU"
  bottom: "conv24"
  top: "conv24"
}
layer {
  name: "conv25"
  type: "Convolution"
  bottom: "conv24"
  top: "conv25"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu25"
  type: "ReLU"
  bottom: "conv25"
  top: "conv25"
}
layer {
  name: "pool25"
  type: "Pooling"
  bottom: "conv25"
  top: "pool25"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}

layer {
	name: "concat1"
	type: "Concat"
	bottom: "pool15"
	bottom: "pool25"
	top: "poolConcat"
}

layer {
  name: "fc6"
  type: "InnerProduct"
  bottom: "poolConcat"
  top: "fc6"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    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: "drop6"
  type: "Dropout"
  bottom: "fc6"
  top: "fc6"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "fc7"
  type: "InnerProduct"
  bottom: "fc6"
  top: "fc7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    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"
}
layer {
  name: "drop7"
  type: "Dropout"
  bottom: "fc7"
  top: "fc7"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "fc8"
  type: "InnerProduct"
  bottom: "fc7"
  top: "fc8"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 4
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "scale"
  bottom: "fc8"
  top: "out"
  type: "Power"
  power_param {
    power: 1
    scale: 10
    shift: 0
  }
}