train.prototxt

name: "ResNet-50"
layer {
  top: "data"
  top: "label_01_88x44"
  top: "label_02_44x88"
  top: "label_03_64x64"
  top: "label_04_176x88"
  top: "label_05_88x176"
  top: "label_06_128x128"
  top: "label_07_352x176"
  top: "label_08_176x352"
  top: "label_09_256x256"
  top: "label_10_704x352"
  top: "label_11_352x704"
  top: "label_12_512x512"
  top: "gt_boxes"
  name: "data"
  type: "DetectionData"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    mean_value: 104
    mean_value: 117
    mean_value: 123
  }
  detection_data_param {
    root_folder: "/your/path/to/coco/images/"
    source: "../../../data/coco/window_file_coco_train2017.txt"
    batch_size: 1
    short_size: 600
    long_size: 1000
    min_gt_width: 5
    min_gt_height: 5
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    stride: 16
    field_w: 88
    field_w: 44
    field_w: 64
    field_w: 176
    field_w: 88
    field_w: 128
    field_w: 352
    field_w: 176
    field_w: 256
    field_w: 704
    field_w: 352
    field_w: 512
    field_h: 44
    field_h: 88
    field_h: 64
    field_h: 88
    field_h: 176
    field_h: 128
    field_h: 176
    field_h: 352
    field_h: 256
    field_h: 352
    field_h: 704
    field_h: 512
    fg_threshold: 0.7
    ignore_fg_threshold: 0.4
    anchor_ignore_margin_ratio: 0.5
    shuffle: "random_aspect"
    output_gt_boxes: true
    distort_param {
      brightness_prob: 0.5
      brightness_delta: 32
      contrast_prob: 0.5
      contrast_lower: 0.5
      contrast_upper: 1.5
      hue_prob: 0.5
      hue_delta: 18
      saturation_prob: 0.5
      saturation_lower: 0.5
      saturation_upper: 1.5
      random_order_prob: 0.0
    }
  }
}
layer {
  name: "label_group"
  type: "Concat"
  bottom: "label_01_88x44"
  bottom: "label_02_44x88"
  bottom: "label_03_64x64"
  bottom: "label_04_176x88"
  bottom: "label_05_88x176"
  bottom: "label_06_128x128"
  bottom: "label_07_352x176"
  bottom: "label_08_176x352"
  bottom: "label_09_256x256"
  bottom: "label_10_704x352"
  bottom: "label_11_352x704"
  bottom: "label_12_512x512"
  top: "label_group"
  concat_param {
    axis: 1
  }
}
layer {
  name: "label_group_reshape"
  bottom: "label_group"
  top: "label_group_reshape"
  type: "Reshape"
  reshape_param { 
    shape { dim: -1 dim: 6 dim: 0 dim: 0 } 
  }
}
# ------------------------ conv1 -----------------------------
layer {
    bottom: "data"
    top: "conv1"
    name: "conv1"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 7
        pad: 3
        stride: 2
    }
    param {
        lr_mult: 0.0
    }
    param {
        lr_mult: 0.0
    }
    
}

layer {
    bottom: "conv1"
    top: "conv1"
    name: "scale_conv1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "conv1"
    top: "conv1"
    name: "conv1_relu"
    type: "ReLU"
}

layer {
    bottom: "conv1"
    top: "pool1"
    name: "pool1"
    type: "Pooling"
    pooling_param {
        kernel_size: 3
        stride: 2
        pool: MAX
    }
}

layer {
    bottom: "pool1"
    top: "res2a_branch1"
    name: "res2a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch1"
    top: "res2a_branch1"
    name: "scale2a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "pool1"
    top: "res2a_branch2a"
    name: "res2a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "scale2a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2a"
    name: "res2a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2a_branch2a"
    top: "res2a_branch2b"
    name: "res2a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "scale2a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2b"
    name: "res2a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2a_branch2b"
    top: "res2a_branch2c"
    name: "res2a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch2c"
    top: "res2a_branch2c"
    name: "scale2a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a_branch1"
    bottom: "res2a_branch2c"
    top: "res2a"
    name: "res2a"
    type: "Eltwise"
}

layer {
    bottom: "res2a"
    top: "res2a"
    name: "res2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2a"
    top: "res2b_branch2a"
    name: "res2b_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "scale2b_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2a"
    name: "res2b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2b_branch2a"
    top: "res2b_branch2b"
    name: "res2b_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "scale2b_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2b"
    name: "res2b_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2b_branch2b"
    top: "res2b_branch2c"
    name: "res2b_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2b_branch2c"
    top: "res2b_branch2c"
    name: "scale2b_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2a"
    bottom: "res2b_branch2c"
    top: "res2b"
    name: "res2b"
    type: "Eltwise"
}

layer {
    bottom: "res2b"
    top: "res2b"
    name: "res2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2b"
    top: "res2c_branch2a"
    name: "res2c_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2a"
    name: "scale2c_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2a"
    name: "res2c_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res2c_branch2a"
    top: "res2c_branch2b"
    name: "res2c_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2b"
    name: "scale2c_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2b"
    name: "res2c_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res2c_branch2b"
    top: "res2c_branch2c"
    name: "res2c_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 0.0
    }
}

layer {
    bottom: "res2c_branch2c"
    top: "res2c_branch2c"
    name: "scale2c_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2b"
    bottom: "res2c_branch2c"
    top: "res2c"
    name: "res2c"
    type: "Eltwise"
}

layer {
    bottom: "res2c"
    top: "res2c"
    name: "res2c_relu"
    type: "ReLU"
}

layer {
    bottom: "res2c"
    top: "res3a_branch1"
    name: "res3a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch1"
    top: "res3a_branch1"
    name: "scale3a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res2c"
    top: "res3a_branch2a"
    name: "res3a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "scale3a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2a"
    name: "res3a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3a_branch2a"
    top: "res3a_branch2b"
    name: "res3a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "scale3a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2b"
    name: "res3a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3a_branch2b"
    top: "res3a_branch2c"
    name: "res3a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3a_branch2c"
    top: "res3a_branch2c"
    name: "scale3a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a_branch1"
    bottom: "res3a_branch2c"
    top: "res3a"
    name: "res3a"
    type: "Eltwise"
}

layer {
    bottom: "res3a"
    top: "res3a"
    name: "res3a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3a"
    top: "res3b_branch2a"
    name: "res3b_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "scale3b_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2a"
    name: "res3b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b_branch2a"
    top: "res3b_branch2b"
    name: "res3b_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2b"
    name: "scale3b_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2b"
    name: "res3b_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b_branch2b"
    top: "res3b_branch2c"
    name: "res3b_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3b_branch2c"
    top: "res3b_branch2c"
    name: "scale3b_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3a"
    bottom: "res3b_branch2c"
    top: "res3b"
    name: "res3b"
    type: "Eltwise"
}

layer {
    bottom: "res3b"
    top: "res3b"
    name: "res3b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3b"
    top: "res3c_branch2a"
    name: "res3c_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3c_branch2a"
    top: "res3c_branch2a"
    name: "scale3c_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3c_branch2a"
    top: "res3c_branch2a"
    name: "res3c_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3c_branch2a"
    top: "res3c_branch2b"
    name: "res3c_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3c_branch2b"
    top: "res3c_branch2b"
    name: "scale3c_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3c_branch2b"
    top: "res3c_branch2b"
    name: "res3c_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3c_branch2b"
    top: "res3c_branch2c"
    name: "res3c_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3c_branch2c"
    top: "res3c_branch2c"
    name: "scale3c_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3b"
    bottom: "res3c_branch2c"
    top: "res3c"
    name: "res3c"
    type: "Eltwise"
}

layer {
    bottom: "res3c"
    top: "res3c"
    name: "res3c_relu"
    type: "ReLU"
}

layer {
    bottom: "res3c"
    top: "res3d_branch2a"
    name: "res3d_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3d_branch2a"
    top: "res3d_branch2a"
    name: "scale3d_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3d_branch2a"
    top: "res3d_branch2a"
    name: "res3d_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res3d_branch2a"
    top: "res3d_branch2b"
    name: "res3d_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3d_branch2b"
    top: "res3d_branch2b"
    name: "scale3d_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3d_branch2b"
    top: "res3d_branch2b"
    name: "res3d_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res3d_branch2b"
    top: "res3d_branch2c"
    name: "res3d_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res3d_branch2c"
    top: "res3d_branch2c"
    name: "scale3d_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3c"
    bottom: "res3d_branch2c"
    top: "res3d"
    name: "res3d"
    type: "Eltwise"
}

layer {
    bottom: "res3d"
    top: "res3d"
    name: "res3d_relu"
    type: "ReLU"
}

layer {
    bottom: "res3d"
    top: "res4a_branch1"
    name: "res4a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch1"
    top: "res4a_branch1"
    name: "scale4a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res3d"
    top: "res4a_branch2a"
    name: "res4a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 2
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2a"
    name: "scale4a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2a"
    name: "res4a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4a_branch2a"
    top: "res4a_branch2b"
    name: "res4a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2b"
    name: "scale4a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2b"
    name: "res4a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4a_branch2b"
    top: "res4a_branch2c"
    name: "res4a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4a_branch2c"
    top: "res4a_branch2c"
    name: "scale4a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a_branch1"
    bottom: "res4a_branch2c"
    top: "res4a"
    name: "res4a"
    type: "Eltwise"
}

layer {
    bottom: "res4a"
    top: "res4a"
    name: "res4a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4a"
    top: "res4b_branch2a"
    name: "res4b_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b_branch2a"
    top: "res4b_branch2a"
    name: "scale4b_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b_branch2a"
    top: "res4b_branch2a"
    name: "res4b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b_branch2a"
    top: "res4b_branch2b"
    name: "res4b_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b_branch2b"
    top: "res4b_branch2b"
    name: "scale4b_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b_branch2b"
    top: "res4b_branch2b"
    name: "res4b_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b_branch2b"
    top: "res4b_branch2c"
    name: "res4b_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4b_branch2c"
    top: "res4b_branch2c"
    name: "scale4b_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4a"
    bottom: "res4b_branch2c"
    top: "res4b"
    name: "res4b"
    type: "Eltwise"
}

layer {
    bottom: "res4b"
    top: "res4b"
    name: "res4b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4b"
    top: "res4c_branch2a"
    name: "res4c_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4c_branch2a"
    top: "res4c_branch2a"
    name: "scale4c_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4c_branch2a"
    top: "res4c_branch2a"
    name: "res4c_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4c_branch2a"
    top: "res4c_branch2b"
    name: "res4c_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4c_branch2b"
    top: "res4c_branch2b"
    name: "scale4c_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4c_branch2b"
    top: "res4c_branch2b"
    name: "res4c_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4c_branch2b"
    top: "res4c_branch2c"
    name: "res4c_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4c_branch2c"
    top: "res4c_branch2c"
    name: "scale4c_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4b"
    bottom: "res4c_branch2c"
    top: "res4c"
    name: "res4c"
    type: "Eltwise"
}

layer {
    bottom: "res4c"
    top: "res4c"
    name: "res4c_relu"
    type: "ReLU"
}

layer {
    bottom: "res4c"
    top: "res4d_branch2a"
    name: "res4d_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4d_branch2a"
    top: "res4d_branch2a"
    name: "scale4d_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4d_branch2a"
    top: "res4d_branch2a"
    name: "res4d_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4d_branch2a"
    top: "res4d_branch2b"
    name: "res4d_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4d_branch2b"
    top: "res4d_branch2b"
    name: "scale4d_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4d_branch2b"
    top: "res4d_branch2b"
    name: "res4d_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4d_branch2b"
    top: "res4d_branch2c"
    name: "res4d_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4d_branch2c"
    top: "res4d_branch2c"
    name: "scale4d_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4c"
    bottom: "res4d_branch2c"
    top: "res4d"
    name: "res4d"
    type: "Eltwise"
}

layer {
    bottom: "res4d"
    top: "res4d"
    name: "res4d_relu"
    type: "ReLU"
}

layer {
    bottom: "res4d"
    top: "res4e_branch2a"
    name: "res4e_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4e_branch2a"
    top: "res4e_branch2a"
    name: "scale4e_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4e_branch2a"
    top: "res4e_branch2a"
    name: "res4e_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4e_branch2a"
    top: "res4e_branch2b"
    name: "res4e_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4e_branch2b"
    top: "res4e_branch2b"
    name: "scale4e_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4e_branch2b"
    top: "res4e_branch2b"
    name: "res4e_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4e_branch2b"
    top: "res4e_branch2c"
    name: "res4e_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4e_branch2c"
    top: "res4e_branch2c"
    name: "scale4e_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4d"
    bottom: "res4e_branch2c"
    top: "res4e"
    name: "res4e"
    type: "Eltwise"
}

layer {
    bottom: "res4e"
    top: "res4e"
    name: "res4e_relu"
    type: "ReLU"
}

layer {
    bottom: "res4e"
    top: "res4f_branch2a"
    name: "res4f_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4f_branch2a"
    top: "res4f_branch2a"
    name: "scale4f_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4f_branch2a"
    top: "res4f_branch2a"
    name: "res4f_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res4f_branch2a"
    top: "res4f_branch2b"
    name: "res4f_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4f_branch2b"
    top: "res4f_branch2b"
    name: "scale4f_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4f_branch2b"
    top: "res4f_branch2b"
    name: "res4f_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res4f_branch2b"
    top: "res4f_branch2c"
    name: "res4f_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res4f_branch2c"
    top: "res4f_branch2c"
    name: "scale4f_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4e"
    bottom: "res4f_branch2c"
    top: "res4f"
    name: "res4f"
    type: "Eltwise"
}

layer {
    bottom: "res4f"
    top: "res4f"
    name: "res4f_relu"
    type: "ReLU"
}

layer {
    bottom: "res4f"
    top: "res5a_branch1"
    name: "res5a_branch1"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch1"
    top: "res5a_branch1"
    name: "scale5a_branch1"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res4f"
    top: "res5a_branch2a"
    name: "res5a_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2a"
    name: "scale5a_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5a_branch2a"
    bottom: "res5a_branch2a"
    name: "res5a_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5a_branch2a"
    top: "res5a_branch2b"
    name: "res5a_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        dilation: 2
        pad: 2
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2b"
    name: "scale5a_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5a_branch2b"
    bottom: "res5a_branch2b"
    name: "res5a_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5a_branch2b"
    top: "res5a_branch2c"
    name: "res5a_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5a_branch2c"
    top: "res5a_branch2c"
    name: "scale5a_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a_branch1"
    bottom: "res5a_branch2c"
    top: "res5a"
    name: "res5a"
    type: "Eltwise"
}

layer {
    bottom: "res5a"
    top: "res5a"
    name: "res5a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5a"
    top: "res5b_branch2a"
    name: "res5b_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2a"
    name: "scale5b_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5b_branch2a"
    bottom: "res5b_branch2a"
    name: "res5b_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5b_branch2a"
    top: "res5b_branch2b"
    name: "res5b_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        dilation: 2
        pad: 2
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2b"
    name: "scale5b_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5b_branch2b"
    bottom: "res5b_branch2b"
    name: "res5b_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5b_branch2b"
    top: "res5b_branch2c"
    name: "res5b_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5b_branch2c"
    top: "res5b_branch2c"
    name: "scale5b_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5a"
    bottom: "res5b_branch2c"
    top: "res5b"
    name: "res5b"
    type: "Eltwise"
}

layer {
    bottom: "res5b"
    top: "res5b"
    name: "res5b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5b"
    top: "res5c_branch2a"
    name: "res5c_branch2a"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2a"
    name: "scale5c_branch2a"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5c_branch2a"
    bottom: "res5c_branch2a"
    name: "res5c_branch2a_relu"
    type: "ReLU"
}

layer {
    bottom: "res5c_branch2a"
    top: "res5c_branch2b"
    name: "res5c_branch2b"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        dilation: 2
        pad: 2
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2b"
    name: "scale5c_branch2b"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    top: "res5c_branch2b"
    bottom: "res5c_branch2b"
    name: "res5c_branch2b_relu"
    type: "ReLU"
}

layer {
    bottom: "res5c_branch2b"
    top: "res5c_branch2c"
    name: "res5c_branch2c"
    type: "Convolution"
    convolution_param {
        num_output: 2048
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
    param {
        lr_mult: 1.0
    }
}

layer {
    bottom: "res5c_branch2c"
    top: "res5c_branch2c"
    name: "scale5c_branch2c"
    type: "Scale"
    scale_param {
        bias_term: true
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
    param {
        lr_mult: 0.0
        decay_mult: 0.0
    }
}

layer {
    bottom: "res5b"
    bottom: "res5c_branch2c"
    top: "res5c"
    name: "res5c"
    type: "Eltwise"
}

layer {
    bottom: "res5c"
    top: "res5c"
    name: "res5c_relu"
    type: "ReLU"
}

#========================== rpn ===============================
layer {
  name: "rpn_conv"
  type: "Convolution"
  bottom: "res4f"
  top: "rpn_conv"
  param { lr_mult: 1.0 }
  param { lr_mult: 2.0 }
  convolution_param {
    num_output: 512
    kernel_size: 3 pad: 1 stride: 1
    weight_filler { type: "gaussian" std: 0.01 }
    bias_filler { type: "constant" value: 0 }
  }
}
layer {
  name: "rpn_relu"
  type: "ReLU"
  bottom: "rpn_conv"
  top: "rpn_conv"
}
layer {
  name: "rpn_cls"
  type: "Convolution"
  bottom: "rpn_conv"
  top: "rpn_cls"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "rpn_cls_reshape"
  bottom: "rpn_cls"
  top: "rpn_cls_reshape"
  type: "Reshape"
  reshape_param { 
    shape { dim: -1 dim: 2 dim: 0 dim: 0 } 
  }
}
layer {
  name: "rpn_bbox"
  type: "Convolution"
  bottom: "rpn_conv"
  top: "rpn_bbox"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 48
    pad: 0
    kernel_size: 1
    weight_filler {
      type: "gaussian"
      std: 0.001
    }
    bias_filler {
      type: "constant"
    }
  }
}
layer {
  name: "rpn_bbox_reshape"
  bottom: "rpn_bbox"
  top: "rpn_bbox_reshape"
  type: "Reshape"
  reshape_param { 
    shape { dim: -1 dim: 4 dim: 0 dim: 0 } 
  }
}
layer {
  name: "rpn_loss"
  type: "DetectionGroupLoss"
  bottom: "rpn_cls_reshape"
  bottom: "rpn_bbox_reshape"
  bottom: "label_group_reshape"
  top: "rpn_loss"
  detection_group_loss_param {
    batch_size: 256
    cls_num: 2
    lambda: 1
    field_w: 88
    field_w: 44
    field_w: 64
    field_w: 176
    field_w: 88
    field_w: 128
    field_w: 352
    field_w: 176
    field_w: 256
    field_w: 704
    field_w: 352
    field_w: 512
    field_h: 44
    field_h: 88
    field_h: 64
    field_h: 88
    field_h: 176
    field_h: 128
    field_h: 176
    field_h: 352
    field_h: 256
    field_h: 352
    field_h: 704
    field_h: 512
    stride: 16
    field_whr: 8
    field_xyr: 1
    bg_threshold: 0.3
    bg_multiple: 1
    neg_mining_type: "random"
    objectness: true
    pos_neg_weighted: false
    bbox_loss_type: "Smooth_L1"
  }
  loss_weight: 1.0
}
layer {
  name: "rpn_accuracy"
  type: "DetectionGroupAccuracy"
  bottom: "rpn_cls_reshape"
  bottom: "rpn_bbox_reshape"
  bottom: "label_group_reshape"
  top: "rpn_accuracy"
  top: "rpn_bboxiou"
  detection_group_accuracy_param {
    cls_num: 2
    field_w: 88
    field_w: 44
    field_w: 64
    field_w: 176
    field_w: 88
    field_w: 128
    field_w: 352
    field_w: 176
    field_w: 256
    field_w: 704
    field_w: 352
    field_w: 512
    field_h: 44
    field_h: 88
    field_h: 64
    field_h: 88
    field_h: 176
    field_h: 128
    field_h: 176
    field_h: 352
    field_h: 256
    field_h: 352
    field_h: 704
    field_h: 512
    stride: 16
    field_whr: 8
    field_xyr: 1
    objectness: true
  }
}

#=================== proposal ======================
layer {
  name: "rpn_prob_reshape"
  type: "Softmax"
  bottom: "rpn_cls_reshape"
  top: "rpn_prob_reshape"
  softmax_param {
    axis: 1
  }
}
layer {
  name: "proposals"
  type: "BoxGroupOutput"
  bottom: "rpn_prob_reshape"
  bottom: "rpn_bbox_reshape"
  top: "proposals"
  box_group_output_param {
    fg_thr: 0.05
    iou_thr: 0.7
    nms_type: "IOU"
    box_group_param {
      field_w: 88
      field_w: 44
      field_w: 64
      field_w: 176
      field_w: 88
      field_w: 128
      field_w: 352
      field_w: 176
      field_w: 256
      field_w: 704
      field_w: 352
      field_w: 512
      field_h: 44
      field_h: 88
      field_h: 64
      field_h: 88
      field_h: 176
      field_h: 128
      field_h: 176
      field_h: 352
      field_h: 256
      field_h: 352
      field_h: 704
      field_h: 512
      stride: 16
    }
    field_whr: 8
    field_xyr: 1
    max_nms_num: 4000
    min_size: 5
  }
  propagate_down: 0
  propagate_down: 0
}

#=================== data prepare for frcnn ======================
layer {
  bottom: "proposals"
  bottom: "gt_boxes"
  top: "rois"
  top: "proposal_labels"
  top: "proposal_targets"
  top: "box_inside_weights"
  top: "box_outside_weights"
  top: "match_gt_boxes"
  name: "proposal_info"
  type: "ProposalTarget"
  include {
    phase: TRAIN
  }
  proposal_target_param {
    cls_num: 81
    batch_size: 256
    fg_fraction: 0.25
    num_img_per_batch: 1
    fg_thr: 0.5
    bg_thr_hg: 0.5
    bg_thr_lw: 0.0
    img_width: 600
    img_height: 600
  }
  bbox_reg_param {
    cls_aware: false
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.1 bbox_std: 0.1 bbox_std: 0.2 bbox_std: 0.2
  }
  propagate_down: 0
  propagate_down: 0
}

#=================== 1st stage ======================
layer {
    bottom: "res5c"
    top: "conv_new_1"
    name: "conv_new_1"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}

layer {
    bottom: "conv_new_1"
    top: "conv_new_1"
    name: "conv_new_1_relu"
    type: "ReLU"
}

layer {
    bottom: "conv_new_1"
    top: "rfcn_cls"
    name: "rfcn_cls"
    type: "Convolution"
    convolution_param {
        num_output: 3969 #81*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}
layer {
    bottom: "conv_new_1"
    top: "rfcn_bbox"
    name: "rfcn_bbox"
    type: "Convolution"
    convolution_param {
        num_output: 392 #8*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 1.0
    }
    param {
        lr_mult: 2.0
    }
}

#--------------position sensitive RoI pooling--------------
layer {
    bottom: "rfcn_cls"
    bottom: "rois"
    top: "psroipooled_cls_rois"
    name: "psroipooled_cls_rois"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 81
        group_size: 7
    }
    propagate_down: true
    propagate_down: false
}

layer {
    bottom: "psroipooled_cls_rois"
    top: "cls_pred"
    name: "ave_cls_pred_rois"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}

layer {
    bottom: "rfcn_bbox"
    bottom: "rois"
    top: "psroipooled_loc_rois"
    name: "psroipooled_loc_rois"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 8
        group_size: 7
    }
    propagate_down: true
    propagate_down: false
}

layer {
    bottom: "psroipooled_loc_rois"
    top: "bbox_pred"
    name: "ave_bbox_pred_rois"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}

#-----------------------output------------------------
layer {
  bottom: "cls_pred"
  bottom: "proposal_labels"
  top: "loss_cls"
  name: "loss_cls"
  type: "SoftmaxWithLoss"
  loss_weight: 1
  propagate_down: 1
  propagate_down: 0
}
layer {
  name: "cls_accuracy"
  type: "Accuracy"
  bottom: "cls_pred"
  bottom: "proposal_labels"
  top: "cls_accuracy"
}
layer {
  name: "loss_bbox"
  type: "SmoothL1Loss"
  bottom: "bbox_pred"
  bottom: "proposal_targets"
  bottom: "box_inside_weights"
  bottom: "box_outside_weights"
  top: "loss_bbox"
  loss_weight: 1
  propagate_down: 1
  propagate_down: 0
  propagate_down: 0
  propagate_down: 0
}
layer {
  name: "bbox_iou"
  type: "BboxAccuracy"
  bottom: "bbox_pred"
  bottom: "rois"
  bottom: "match_gt_boxes"
  top: "bbox_iou"
  top: "bbox_iou_pre"
  bbox_reg_param {
    cls_aware: false
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.1 bbox_std: 0.1 bbox_std: 0.2 bbox_std: 0.2
  }
}

#=================== second stage ======================
layer {
  name: "proposals_2nd"
  type: "DecodeBBox"
  bottom: "bbox_pred"
  bottom: "rois"
  bottom: "match_gt_boxes"
  top: "proposals_2nd"
  bbox_reg_param {
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.1 bbox_std: 0.1 bbox_std: 0.2 bbox_std: 0.2
  }
  propagate_down: 0
  propagate_down: 0
  propagate_down: 0
}

layer {
  bottom: "proposals_2nd"
  bottom: "gt_boxes"
  top: "rois_2nd"
  top: "proposal_labels_2nd"
  top: "proposal_targets_2nd"
  top: "box_inside_weights_2nd"
  top: "box_outside_weights_2nd"
  top: "match_gt_boxes_2nd"
  name: "proposal_info_2nd"
  type: "ProposalTarget"
  include {
    phase: TRAIN
  }
  proposal_target_param {
    cls_num: 81
    batch_size: -1
    fg_fraction: 0.25
    num_img_per_batch: 1
    fg_thr: 0.6
    bg_thr_hg: 0.6
    bg_thr_lw: 0.0
    img_width: 600
    img_height: 600
  }
  bbox_reg_param {
    cls_aware: false
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.05 bbox_std: 0.05 bbox_std: 0.1 bbox_std: 0.1
  }
  propagate_down: 0
  propagate_down: 0
}

#--------------position sensitive RoI pooling--------------
layer {
    bottom: "res5c"
    top: "conv_new_2"
    name: "conv_new_2"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 2.0
    }
    param {
        lr_mult: 4.0
    }
}

layer {
    bottom: "conv_new_2"
    top: "conv_new_2"
    name: "conv_new_2_relu"
    type: "ReLU"
}

layer {
    bottom: "conv_new_2"
    top: "rfcn_cls_2nd"
    name: "rfcn_cls_2nd"
    type: "Convolution"
    convolution_param {
        num_output: 3969 #81*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 2.0
    }
    param {
        lr_mult: 4.0
    }
}
layer {
    bottom: "conv_new_2"
    top: "rfcn_bbox_2nd"
    name: "rfcn_bbox_2nd"
    type: "Convolution"
    convolution_param {
        num_output: 392 #8*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 2.0
    }
    param {
        lr_mult: 4.0
    }
}

layer {
    bottom: "rfcn_cls_2nd"
    bottom: "rois_2nd"
    top: "psroipooled_cls_rois_2nd"
    name: "psroipooled_cls_rois_2nd"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 81
        group_size: 7
    }
    propagate_down: true
    propagate_down: false
}

layer {
    bottom: "psroipooled_cls_rois_2nd"
    top: "cls_pred_2nd"
    name: "ave_cls_pred_rois_2nd"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}

layer {
    bottom: "rfcn_bbox_2nd"
    bottom: "rois_2nd"
    top: "psroipooled_loc_rois_2nd"
    name: "psroipooled_loc_rois_2nd"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 8
        group_size: 7
    }
    propagate_down: true
    propagate_down: false
}

layer {
    bottom: "psroipooled_loc_rois_2nd"
    top: "bbox_pred_2nd"
    name: "ave_bbox_pred_rois_2nd"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}

#-----------------------output------------------------
layer {
  bottom: "cls_pred_2nd"
  bottom: "proposal_labels_2nd"
  top: "loss_cls_2nd"
  name: "loss_cls_2nd"
  type: "SoftmaxWithLoss"
  loss_weight: 0.5
  propagate_down: 1
  propagate_down: 0
}
layer {
  name: "cls_accuracy_2nd"
  type: "Accuracy"
  bottom: "cls_pred_2nd"
  bottom: "proposal_labels_2nd"
  top: "cls_accuracy_2nd"
}
layer {
  name: "loss_bbox_2nd"
  type: "SmoothL1Loss"
  bottom: "bbox_pred_2nd"
  bottom: "proposal_targets_2nd"
  bottom: "box_inside_weights_2nd"
  bottom: "box_outside_weights_2nd"
  top: "loss_bbox_2nd"
  loss_weight: 0.5
  propagate_down: 1
  propagate_down: 0
  propagate_down: 0
  propagate_down: 0
}
layer {
  name: "bbox_iou_2nd"
  type: "BboxAccuracy"
  bottom: "bbox_pred_2nd"
  bottom: "rois_2nd"
  bottom: "match_gt_boxes_2nd"
  top: "bbox_iou_2nd"
  top: "bbox_iou_pre_2nd"
  bbox_reg_param {
    cls_aware: false
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.05 bbox_std: 0.05 bbox_std: 0.1 bbox_std: 0.1
  }
}

#=================== third stage ======================
layer {
  name: "proposals_3rd"
  type: "DecodeBBox"
  bottom: "bbox_pred_2nd"
  bottom: "rois_2nd"
  bottom: "match_gt_boxes_2nd"
  top: "proposals_3rd"
  bbox_reg_param {
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.05 bbox_std: 0.05 bbox_std: 0.1 bbox_std: 0.1
  }
  propagate_down: 0
  propagate_down: 0
  propagate_down: 0
}

layer {
  bottom: "proposals_3rd"
  bottom: "gt_boxes"
  top: "rois_3rd"
  top: "proposal_labels_3rd"
  top: "proposal_targets_3rd"
  top: "box_inside_weights_3rd"
  top: "box_outside_weights_3rd"
  top: "match_gt_boxes_3rd"
  name: "proposal_info_3rd"
  type: "ProposalTarget"
  include {
    phase: TRAIN
  }
  proposal_target_param {
    cls_num: 81
    batch_size: -1
    fg_fraction: 0.25
    num_img_per_batch: 1
    fg_thr: 0.7
    bg_thr_hg: 0.7
    bg_thr_lw: 0.0
    img_width: 600
    img_height: 600
  }
  bbox_reg_param {
    cls_aware: false
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.033 bbox_std: 0.033 bbox_std: 0.067 bbox_std: 0.067
  }
  propagate_down: 0
  propagate_down: 0
}

#--------------position sensitive RoI pooling--------------
layer {
    bottom: "res5c"
    top: "conv_new_3"
    name: "conv_new_3"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 4.0
    }
    param {
        lr_mult: 8.0
    }
}

layer {
    bottom: "conv_new_3"
    top: "conv_new_3"
    name: "conv_new_3_relu"
    type: "ReLU"
}

layer {
    bottom: "conv_new_3"
    top: "rfcn_cls_3rd"
    name: "rfcn_cls_3rd"
    type: "Convolution"
    convolution_param {
        num_output: 3969 #81*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 4.0
    }
    param {
        lr_mult: 8.0
    }
}
layer {
    bottom: "conv_new_3"
    top: "rfcn_bbox_3rd"
    name: "rfcn_bbox_3rd"
    type: "Convolution"
    convolution_param {
        num_output: 392 #8*(7^2) cls_num*(score_maps_size^2)
        kernel_size: 1
        pad: 0
        weight_filler {
            type: "gaussian"
            std: 0.01
        }
        bias_filler {
            type: "constant"
            value: 0
        }
    }
    param {
        lr_mult: 4.0
    }
    param {
        lr_mult: 8.0
    }
}

layer {
    bottom: "rfcn_cls_3rd"
    bottom: "rois_3rd"
    top: "psroipooled_cls_rois_3rd"
    name: "psroipooled_cls_rois_3rd"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 81
        group_size: 7
    }
    propagate_down: true
    propagate_down: false
}

layer {
    bottom: "psroipooled_cls_rois_3rd"
    top: "cls_pred_3rd"
    name: "ave_cls_pred_rois_3rd"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}

layer {
    bottom: "rfcn_bbox_3rd"
    bottom: "rois_3rd"
    top: "psroipooled_loc_rois_3rd"
    name: "psroipooled_loc_rois_3rd"
    type: "PSROIPooling"
    psroi_pooling_param {
        spatial_scale: 0.0625
        output_dim: 8
        group_size: 7
    }
    propagate_down: true
    propagate_down: false
}

layer {
    bottom: "psroipooled_loc_rois_3rd"
    top: "bbox_pred_3rd"
    name: "ave_bbox_pred_rois_3rd"
    type: "Pooling"
    pooling_param {
        pool: AVE
        kernel_size: 7
        stride: 7
    }
}

#-----------------------output------------------------
layer {
  bottom: "cls_pred_3rd"
  bottom: "proposal_labels_3rd"
  top: "loss_cls_3rd"
  name: "loss_cls_3rd"
  type: "SoftmaxWithLoss"
  loss_weight: 0.25
  propagate_down: 1
  propagate_down: 0
}
layer {
  name: "cls_accuracy_3rd"
  type: "Accuracy"
  bottom: "cls_pred_3rd"
  bottom: "proposal_labels_3rd"
  top: "cls_accuracy_3rd"
}
layer {
  name: "loss_bbox_3rd"
  type: "SmoothL1Loss"
  bottom: "bbox_pred_3rd"
  bottom: "proposal_targets_3rd"
  bottom: "box_inside_weights_3rd"
  bottom: "box_outside_weights_3rd"
  top: "loss_bbox_3rd"
  loss_weight: 0.25
  propagate_down: 1
  propagate_down: 0
  propagate_down: 0
  propagate_down: 0
}
layer {
  name: "bbox_iou_3rd"
  type: "BboxAccuracy"
  bottom: "bbox_pred_3rd"
  bottom: "rois_3rd"
  bottom: "match_gt_boxes_3rd"
  top: "bbox_iou_3rd"
  top: "bbox_iou_pre_3rd"
  bbox_reg_param {
    cls_aware: false
    bbox_mean: 0 bbox_mean: 0 bbox_mean: 0 bbox_mean: 0
    bbox_std: 0.033 bbox_std: 0.033 bbox_std: 0.067 bbox_std: 0.067
  }
}