[binary classfication prototxt] #caffe

quality_mobile_branch.nobn.prototxt

name: "quality_mobile_branch"
input: "blob1"
input_dim: 1
input_dim: 3
input_dim: 96
input_dim: 96
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "blob1"
  top: "conv_blob1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    dilation: 1
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "conv_blob1"
  top: "relu_blob1"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "relu_blob1"
  top: "conv_blob2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 32
    bias_term: true
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    dilation: 1
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "conv_blob2"
  top: "relu_blob2"
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "relu_blob2"
  top: "conv_blob3"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 24
    bias_term: true
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    dilation: 1
  }
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "conv_blob3"
  top: "relu_blob3"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "relu_blob3"
  top: "conv_blob4"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 48
    bias_term: true
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    dilation: 1
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "conv_blob4"
  top: "relu_blob4"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "relu_blob4"
  top: "conv_blob5"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 32
    bias_term: true
    pad: 1
    kernel_size: 3
    group: 1
    stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    dilation: 1
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "conv_blob5"
  top: "relu_blob5"
}
layer {
  name: "conv6"
  type: "Convolution"
  bottom: "relu_blob5"
  top: "conv_blob6"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 24
    bias_term: true
    pad: 1
    kernel_size: 3
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    dilation: 1
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "conv_blob6"
  top: "relu_blob6"
}
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "relu_blob6"
  top: "conv_blob7"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0.0
  }
  convolution_param {
    num_output: 16
    bias_term: true
    pad: 0
    kernel_size: 1
    group: 1
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0.0
    }
    dilation: 1
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "conv_blob7"
  top: "relu_blob7"
}
layer {
  name: "view1"
  type: "Reshape"
  bottom: "relu_blob7"
  top: "view_blob1"
  reshape_param {
    shape {
      dim: 0
      dim: -1
    }
  }
}
layer {
  name: "fc1"
  type: "InnerProduct"
  bottom: "view_blob1"
  top: "fc_blob1"
  inner_product_param {
    num_output: 2
    bias_term: true
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "quality_prob"
  type: "Softmax"
  bottom: "fc_blob1"
  top: "quality_prob"
}