layer {
  name: "input_1"
  type: "Input"
  top: "input_1"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 272
      dim: 480
    }
  }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "input_1"
  top: "conv1"
  convolution_param {
    num_output: 32
    pad_h: 3
    pad_w: 3
    kernel_h: 7
    kernel_w: 7
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "bn_conv1"
  type: "Scale"
  bottom: "conv1"
  top: "bn_conv1"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "activation_1/Relu"
  type: "ReLU"
  bottom: "bn_conv1"
  top: "activation_1/Relu"
}
layer {
  name: "block_1a_conv_1"
  type: "Convolution"
  bottom: "activation_1/Relu"
  top: "block_1a_conv_1"
  convolution_param {
    num_output: 64
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "block_1a_conv_shortcut"
  type: "Convolution"
  bottom: "activation_1/Relu"
  top: "block_1a_conv_shortcut"
  convolution_param {
    num_output: 64
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "block_1a_bn_1"
  type: "Scale"
  bottom: "block_1a_conv_1"
  top: "block_1a_bn_1"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "block_1a_bn_shortcut"
  type: "Scale"
  bottom: "block_1a_conv_shortcut"
  top: "block_1a_bn_shortcut"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "activation_2/Relu"
  type: "ReLU"
  bottom: "block_1a_bn_1"
  top: "activation_2/Relu"
}
layer {
  name: "block_1a_conv_2"
  type: "Convolution"
  bottom: "activation_2/Relu"
  top: "block_1a_conv_2"
  convolution_param {
    num_output: 64
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "block_1a_bn_2"
  type: "Scale"
  bottom: "block_1a_conv_2"
  top: "block_1a_bn_2"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "add_1"
  type: "Eltwise"
  bottom: "block_1a_bn_2"
  bottom: "block_1a_bn_shortcut"
  top: "add_1"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "activation_3/Relu"
  type: "ReLU"
  bottom: "add_1"
  top: "activation_3/Relu"
}
layer {
  name: "block_2a_conv_1"
  type: "Convolution"
  bottom: "activation_3/Relu"
  top: "block_2a_conv_1"
  convolution_param {
    num_output: 128
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "block_2a_conv_shortcut"
  type: "Convolution"
  bottom: "activation_3/Relu"
  top: "block_2a_conv_shortcut"
  convolution_param {
    num_output: 128
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "block_2a_bn_1"
  type: "Scale"
  bottom: "block_2a_conv_1"
  top: "block_2a_bn_1"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "block_2a_bn_shortcut"
  type: "Scale"
  bottom: "block_2a_conv_shortcut"
  top: "block_2a_bn_shortcut"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "activation_4/Relu"
  type: "ReLU"
  bottom: "block_2a_bn_1"
  top: "activation_4/Relu"
}
layer {
  name: "block_2a_conv_2"
  type: "Convolution"
  bottom: "activation_4/Relu"
  top: "block_2a_conv_2"
  convolution_param {
    num_output: 128
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "block_2a_bn_2"
  type: "Scale"
  bottom: "block_2a_conv_2"
  top: "block_2a_bn_2"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "add_2"
  type: "Eltwise"
  bottom: "block_2a_bn_2"
  bottom: "block_2a_bn_shortcut"
  top: "add_2"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "activation_5/Relu"
  type: "ReLU"
  bottom: "add_2"
  top: "activation_5/Relu"
}
layer {
  name: "block_3a_conv_1"
  type: "Convolution"
  bottom: "activation_5/Relu"
  top: "block_3a_conv_1"
  convolution_param {
    num_output: 232
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "block_3a_conv_shortcut"
  type: "Convolution"
  bottom: "activation_5/Relu"
  top: "block_3a_conv_shortcut"
  convolution_param {
    num_output: 200
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 2
    stride_w: 2
  }
}
layer {
  name: "block_3a_bn_1"
  type: "Scale"
  bottom: "block_3a_conv_1"
  top: "block_3a_bn_1"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "block_3a_bn_shortcut"
  type: "Scale"
  bottom: "block_3a_conv_shortcut"
  top: "block_3a_bn_shortcut"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "activation_6/Relu"
  type: "ReLU"
  bottom: "block_3a_bn_1"
  top: "activation_6/Relu"
}
layer {
  name: "block_3a_conv_2"
  type: "Convolution"
  bottom: "activation_6/Relu"
  top: "block_3a_conv_2"
  convolution_param {
    num_output: 200
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "block_3a_bn_2"
  type: "Scale"
  bottom: "block_3a_conv_2"
  top: "block_3a_bn_2"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "add_3"
  type: "Eltwise"
  bottom: "block_3a_bn_2"
  bottom: "block_3a_bn_shortcut"
  top: "add_3"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "activation_7/Relu"
  type: "ReLU"
  bottom: "add_3"
  top: "activation_7/Relu"
}
layer {
  name: "block_4a_conv_1"
  type: "Convolution"
  bottom: "activation_7/Relu"
  top: "block_4a_conv_1"
  convolution_param {
    num_output: 152
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "block_4a_conv_shortcut"
  type: "Convolution"
  bottom: "activation_7/Relu"
  top: "block_4a_conv_shortcut"
  convolution_param {
    num_output: 176
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "block_4a_bn_1"
  type: "Scale"
  bottom: "block_4a_conv_1"
  top: "block_4a_bn_1"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "block_4a_bn_shortcut"
  type: "Scale"
  bottom: "block_4a_conv_shortcut"
  top: "block_4a_bn_shortcut"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "activation_8/Relu"
  type: "ReLU"
  bottom: "block_4a_bn_1"
  top: "activation_8/Relu"
}
layer {
  name: "block_4a_conv_2"
  type: "Convolution"
  bottom: "activation_8/Relu"
  top: "block_4a_conv_2"
  convolution_param {
    num_output: 176
    pad_h: 1
    pad_w: 1
    kernel_h: 3
    kernel_w: 3
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "block_4a_bn_2"
  type: "Scale"
  bottom: "block_4a_conv_2"
  top: "block_4a_bn_2"
  scale_param {
    axis: 1
    bias_term: true
  }
}
layer {
  name: "add_4"
  type: "Eltwise"
  bottom: "block_4a_bn_2"
  bottom: "block_4a_bn_shortcut"
  top: "add_4"
  eltwise_param {
    operation: SUM
  }
}
layer {
  name: "activation_9/Relu"
  type: "ReLU"
  bottom: "add_4"
  top: "activation_9/Relu"
}
layer {
  name: "conv2d_bbox"
  type: "Convolution"
  bottom: "activation_9/Relu"
  top: "conv2d_bbox"
  convolution_param {
    num_output: 16
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv2d_cov"
  type: "Convolution"
  bottom: "activation_9/Relu"
  top: "conv2d_cov"
  convolution_param {
    num_output: 4
    pad_h: 0
    pad_w: 0
    kernel_h: 1
    kernel_w: 1
    stride_h: 1
    stride_w: 1
  }
}
layer {
  name: "conv2d_cov/Sigmoid"
  type: "Sigmoid"
  bottom: "conv2d_cov"
  top: "conv2d_cov/Sigmoid"
}