train.prototxt

name: "FaceBoxes"
layer {
  name: "data"
  type: "AnnotatedData"
  top: "data"
  top: "label"
  include {
    phase: TRAIN
  }
  transform_param {
    mirror: true
    mean_value: 104
    mean_value: 117
    mean_value: 123
    resize_param {
      prob: 1
      resize_mode: WARP
      height: 1024
      width: 1024
      interp_mode: LINEAR
      interp_mode: AREA
      interp_mode: NEAREST
      interp_mode: CUBIC
      interp_mode: LANCZOS4
    }
    emit_constraint {
      emit_type: CENTER
    }
    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
    }
    expand_param {
      prob: 0.5
      max_expand_ratio: 4.0
    }
  }
  data_param {
    source: "/home/ly/workspace/caffe-master/data/face/WIDER/face/lmdb/face_trainval_lmdb/"
    batch_size: 32
    backend: LMDB
  }
  annotated_data_param {
    batch_sampler {
      max_sample: 1
      max_trials: 1
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.1
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.3
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.5
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.7
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        min_jaccard_overlap: 0.9
      }
      max_sample: 1
      max_trials: 50
    }
    batch_sampler {
      sampler {
        min_scale: 0.3
        max_scale: 1.0
        min_aspect_ratio: 0.5
        max_aspect_ratio: 2.0
      }
      sample_constraint {
        max_jaccard_overlap: 1.0
      }
      max_sample: 1
      max_trials: 50
    }
    label_map_file: "/home/ly/workspace/caffe-master/data/face/labelmap_face.prototxt"
  }
}
#conv1
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 0
    kernel_size: 7
	stride: 4
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "conv1/bn"
  type: "BatchNorm"
  bottom: "conv1"
  top: "conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv1/neg"
  type: "Power"
  bottom: "conv1"
  top: "conv1/neg"
  power_param {
    power: 1
    scale: -1.0
    shift: 0
  }
}

layer {
  name: "conv1/concat"
  type: "Concat"
  bottom: "conv1"
  bottom: "conv1/neg"
  top: "conv1_CR"
}

layer {
  name: "conv1/scale"
  type: "Scale"
  bottom: "conv1_CR"
  top: "conv1_CR"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv1/relu"
  type: "ReLU"
  bottom: "conv1_CR"
  top: "conv1_CR"
}

layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1_CR"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
#conv2
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  convolution_param {
    num_output: 64
    pad: 0
    kernel_size: 5
	stride: 2
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "conv2/bn"
  type: "BatchNorm"
  bottom: "conv2"
  top: "conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv2/neg"
  type: "Power"
  bottom: "conv2"
  top: "conv2/neg"
  power_param {
    power: 1
    scale: -1.0
    shift: 0
  }
}

layer {
  name: "conv2/concat"
  type: "Concat"
  bottom: "conv2"
  bottom: "conv2/neg"
  top: "conv2_CR"
}

layer {
  name: "conv2/scale"
  type: "Scale"
  bottom: "conv2_CR"
  top: "conv2_CR"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 2.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv2/relu"
  type: "ReLU"
  bottom: "conv2_CR"
  top: "conv2_CR"
}

layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2_CR"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
#Inception1
layer {
  name: "conv3/incep0/conv"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3/incep0/conv"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv3/incep0/bn"
  type: "BatchNorm"
  bottom: "conv3/incep0/conv"
  top: "conv3/incep0/conv"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv3/incep0/bn_scale"
  type: "Scale"
  bottom: "conv3/incep0/conv"
  top: "conv3/incep0/conv"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv3/incep0/relu"
  type: "ReLU"
  bottom: "conv3/incep0/conv"
  top: "conv3/incep0/conv"
}

layer {
  name: "conv3/incep1/conv1"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3/incep1/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv3/incep1/bn1"
  type: "BatchNorm"
  bottom: "conv3/incep1/conv1"
  top: "conv3/incep1/conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv3/incep1/bn_scale1"
  type: "Scale"
  bottom: "conv3/incep1/conv1"
  top: "conv3/incep1/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv3/incep1/relu1"
  type: "ReLU"
  bottom: "conv3/incep1/conv1"
  top: "conv3/incep1/conv1"
}

layer {
  name: "conv3/incep1/conv2"
  type: "Convolution"
  bottom: "conv3/incep1/conv1"
  top: "conv3/incep1/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
	weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv3/incep1/bn2"
  type: "BatchNorm"
  bottom: "conv3/incep1/conv2"
  top: "conv3/incep1/conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv3/incep1/bn_scale2"
  type: "Scale"
  bottom: "conv3/incep1/conv2"
  top: "conv3/incep1/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv3/incep1/relu2"
  type: "ReLU"
  bottom: "conv3/incep1/conv2"
  top: "conv3/incep1/conv2"
}

layer {
  name: "conv3/incep2/conv1"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3/incep2/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv3/incep2/bn1"
  type: "BatchNorm"
  bottom: "conv3/incep2/conv1"
  top: "conv3/incep2/conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv3/incep2/bn_scale1"
  type: "Scale"
  bottom: "conv3/incep2/conv1"
  top: "conv3/incep2/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv3/incep2/relu1"
  type: "ReLU"
  bottom: "conv3/incep2/conv1"
  top: "conv3/incep2/conv1"
}

layer {
  name: "conv3/incep2/conv2"
  type: "Convolution"
  bottom: "conv3/incep2/conv1"
  top: "conv3/incep2/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv3/incep2/bn2"
  type: "BatchNorm"
  bottom: "conv3/incep2/conv2"
  top: "conv3/incep2/conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv3/incep2/bn_scale2"
  type: "Scale"
  bottom: "conv3/incep2/conv2"
  top: "conv3/incep2/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv3/incep2/relu2"
  type: "ReLU"
  bottom: "conv3/incep2/conv2"
  top: "conv3/incep2/conv2"
}

layer {
  name: "conv3/incep2/conv3"
  type: "Convolution"
  bottom: "conv3/incep2/conv2"
  top: "conv3/incep2/conv3"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv3/incep2/bn3"
  type: "BatchNorm"
  bottom: "conv3/incep2/conv3"
  top: "conv3/incep2/conv3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv3/incep2/bn_scale3"
  type: "Scale"
  bottom: "conv3/incep2/conv3"
  top: "conv3/incep2/conv3"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv3/incep2/relu3"
  type: "ReLU"
  bottom: "conv3/incep2/conv3"
  top: "conv3/incep2/conv3"
}

layer {
  name: "conv3/incep3/pool"
  type: "Pooling"
  bottom: "pool2"
  top: "conv3/incep3/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}

layer {
  name: "conv3/incep3/conv"
  type: "Convolution"
  bottom: "conv3/incep3/pool"
  top: "conv3/incep3/conv"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv3/incep3/bn"
  type: "BatchNorm"
  bottom: "conv3/incep3/conv"
  top: "conv3/incep3/conv"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv3/incep3/bn_scale"
  type: "Scale"
  bottom: "conv3/incep3/conv"
  top: "conv3/incep3/conv"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv3/incep3/relu"
  type: "ReLU"
  bottom: "conv3/incep3/conv"
  top: "conv3/incep3/conv"
}

layer {
  name: "conv3/incep"
  type: "Concat"
  bottom: "conv3/incep0/conv"
  bottom: "conv3/incep1/conv2"
  bottom: "conv3/incep2/conv3"
  bottom: "conv3/incep3/conv"
  top: "conv3/incep"
}
#Inception2
layer {
  name: "conv4/incep0/conv"
  type: "Convolution"
  bottom: "conv3/incep"
  top: "conv4/incep0/conv"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv4/incep0/bn"
  type: "BatchNorm"
  bottom: "conv4/incep0/conv"
  top: "conv4/incep0/conv"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv4/incep0/bn_scale"
  type: "Scale"
  bottom: "conv4/incep0/conv"
  top: "conv4/incep0/conv"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv4/incep0/relu"
  type: "ReLU"
  bottom: "conv4/incep0/conv"
  top: "conv4/incep0/conv"
}

layer {
  name: "conv4/incep1/conv1"
  type: "Convolution"
  bottom: "conv3/incep"
  top: "conv4/incep1/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv4/incep1/bn1"
  type: "BatchNorm"
  bottom: "conv4/incep1/conv1"
  top: "conv4/incep1/conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv4/incep1/bn_scale1"
  type: "Scale"
  bottom: "conv4/incep1/conv1"
  top: "conv4/incep1/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv4/incep1/relu1"
  type: "ReLU"
  bottom: "conv4/incep1/conv1"
  top: "conv4/incep1/conv1"
}

layer {
  name: "conv4/incep1/conv2"
  type: "Convolution"
  bottom: "conv4/incep1/conv1"
  top: "conv4/incep1/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv4/incep1/bn2"
  type: "BatchNorm"
  bottom: "conv4/incep1/conv2"
  top: "conv4/incep1/conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv4/incep1/bn_scale2"
  type: "Scale"
  bottom: "conv4/incep1/conv2"
  top: "conv4/incep1/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv4/incep1/relu2"
  type: "ReLU"
  bottom: "conv4/incep1/conv2"
  top: "conv4/incep1/conv2"
}

layer {
  name: "conv4/incep2/conv1"
  type: "Convolution"
  bottom: "conv3/incep"
  top: "conv4/incep2/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv4/incep2/bn1"
  type: "BatchNorm"
  bottom: "conv4/incep2/conv1"
  top: "conv4/incep2/conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv4/incep2/bn_scale1"
  type: "Scale"
  bottom: "conv4/incep2/conv1"
  top: "conv4/incep2/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv4/incep2/relu1"
  type: "ReLU"
  bottom: "conv4/incep2/conv1"
  top: "conv4/incep2/conv1"
}

layer {
  name: "conv4/incep2/conv2"
  type: "Convolution"
  bottom: "conv4/incep2/conv1"
  top: "conv4/incep2/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv4/incep2/bn2"
  type: "BatchNorm"
  bottom: "conv4/incep2/conv2"
  top: "conv4/incep2/conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv4/incep2/bn_scale2"
  type: "Scale"
  bottom: "conv4/incep2/conv2"
  top: "conv4/incep2/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv4/incep2/relu2"
  type: "ReLU"
  bottom: "conv4/incep2/conv2"
  top: "conv4/incep2/conv2"
}

layer {
  name: "conv4/incep2/conv3"
  type: "Convolution"
  bottom: "conv4/incep2/conv2"
  top: "conv4/incep2/conv3"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv4/incep2/bn3"
  type: "BatchNorm"
  bottom: "conv4/incep2/conv3"
  top: "conv4/incep2/conv3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv4/incep2/bn_scale3"
  type: "Scale"
  bottom: "conv4/incep2/conv3"
  top: "conv4/incep2/conv3"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv4/incep2/relu3"
  type: "ReLU"
  bottom: "conv4/incep2/conv3"
  top: "conv4/incep2/conv3"
}

layer {
  name: "conv4/incep3/pool"
  type: "Pooling"
  bottom: "conv3/incep"
  top: "conv4/incep3/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}

layer {
  name: "conv4/incep3/conv"
  type: "Convolution"
  bottom: "conv4/incep3/pool"
  top: "conv4/incep3/conv"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv4/incep3/bn"
  type: "BatchNorm"
  bottom: "conv4/incep3/conv"
  top: "conv4/incep3/conv"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv4/incep3/bn_scale"
  type: "Scale"
  bottom: "conv4/incep3/conv"
  top: "conv4/incep3/conv"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv4/incep3/relu"
  type: "ReLU"
  bottom: "conv4/incep3/conv"
  top: "conv4/incep3/conv"
}

layer {
  name: "conv4/incep"
  type: "Concat"
  bottom: "conv4/incep0/conv"
  bottom: "conv4/incep1/conv2"
  bottom: "conv4/incep2/conv3"
  bottom: "conv4/incep3/conv"
  top: "conv4/incep"
}

layer {
  name: "conv5/incep0/conv"
  type: "Convolution"
  bottom: "conv4/incep"
  top: "conv5/incep0/conv"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv5/incep0/bn"
  type: "BatchNorm"
  bottom: "conv5/incep0/conv"
  top: "conv5/incep0/conv"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv5/incep0/bn_scale"
  type: "Scale"
  bottom: "conv5/incep0/conv"
  top: "conv5/incep0/conv"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv5/incep0/relu"
  type: "ReLU"
  bottom: "conv5/incep0/conv"
  top: "conv5/incep0/conv"
}

layer {
  name: "conv5/incep1/conv1"
  type: "Convolution"
  bottom: "conv4/incep"
  top: "conv5/incep1/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv5/incep1/bn1"
  type: "BatchNorm"
  bottom: "conv5/incep1/conv1"
  top: "conv5/incep1/conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv5/incep1/bn_scale1"
  type: "Scale"
  bottom: "conv5/incep1/conv1"
  top: "conv5/incep1/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv5/incep1/relu1"
  type: "ReLU"
  bottom: "conv5/incep1/conv1"
  top: "conv5/incep1/conv1"
}

layer {
  name: "conv5/incep1/conv2"
  type: "Convolution"
  bottom: "conv5/incep1/conv1"
  top: "conv5/incep1/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv5/incep1/bn2"
  type: "BatchNorm"
  bottom: "conv5/incep1/conv2"
  top: "conv5/incep1/conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv5/incep1/bn_scale2"
  type: "Scale"
  bottom: "conv5/incep1/conv2"
  top: "conv5/incep1/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv5/incep1/relu2"
  type: "ReLU"
  bottom: "conv5/incep1/conv2"
  top: "conv5/incep1/conv2"
}

layer {
  name: "conv5/incep2/conv1"
  type: "Convolution"
  bottom: "conv4/incep"
  top: "conv5/incep2/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 24
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv5/incep2/bn1"
  type: "BatchNorm"
  bottom: "conv5/incep2/conv1"
  top: "conv5/incep2/conv1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv5/incep2/bn_scale1"
  type: "Scale"
  bottom: "conv5/incep2/conv1"
  top: "conv5/incep2/conv1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv5/incep2/relu1"
  type: "ReLU"
  bottom: "conv5/incep2/conv1"
  top: "conv5/incep2/conv1"
}

layer {
  name: "conv5/incep2/conv2"
  type: "Convolution"
  bottom: "conv5/incep2/conv1"
  top: "conv5/incep2/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv5/incep2/bn2"
  type: "BatchNorm"
  bottom: "conv5/incep2/conv2"
  top: "conv5/incep2/conv2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv5/incep2/bn_scale2"
  type: "Scale"
  bottom: "conv5/incep2/conv2"
  top: "conv5/incep2/conv2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv5/incep2/relu2"
  type: "ReLU"
  bottom: "conv5/incep2/conv2"
  top: "conv5/incep2/conv2"
}

layer {
  name: "conv5/incep2/conv3"
  type: "Convolution"
  bottom: "conv5/incep2/conv2"
  top: "conv5/incep2/conv3"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 1
  }
}

layer {
  name: "conv5/incep2/bn3"
  type: "BatchNorm"
  bottom: "conv5/incep2/conv3"
  top: "conv5/incep2/conv3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv5/incep2/bn_scale3"
  type: "Scale"
  bottom: "conv5/incep2/conv3"
  top: "conv5/incep2/conv3"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv5/incep2/relu3"
  type: "ReLU"
  bottom: "conv5/incep2/conv3"
  top: "conv5/incep2/conv3"
}

layer {
  name: "conv5/incep3/pool"
  type: "Pooling"
  bottom: "conv4/incep"
  top: "conv5/incep3/pool"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 1
    pad: 1
  }
}

layer {
  name: "conv5/incep3/conv"
  type: "Convolution"
  bottom: "conv5/incep3/pool"
  top: "conv5/incep3/conv"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 32
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv5/incep3/bn"
  type: "BatchNorm"
  bottom: "conv5/incep3/conv"
  top: "conv5/incep3/conv"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv5/incep3/bn_scale"
  type: "Scale"
  bottom: "conv5/incep3/conv"
  top: "conv5/incep3/conv"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv5/incep3/relu"
  type: "ReLU"
  bottom: "conv5/incep3/conv"
  top: "conv5/incep3/conv"
}

layer {
  name: "conv5/incep"
  type: "Concat"
  bottom: "conv5/incep0/conv"
  bottom: "conv5/incep1/conv2"
  bottom: "conv5/incep2/conv3"
  bottom: "conv5/incep3/conv"
  top: "conv5/incep"
}

layer {
  name: "Inception3/conv/loc1"
  type: "Convolution"
  bottom: "conv5/incep"
  top: "Inception3/conv/loc1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "Inception3/conv/loc1/perm"
  type: "Permute"
  bottom: "Inception3/conv/loc1"
  top: "Inception3/conv/loc1/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "Inception3/conv/loc1/flat"
  type: "Flatten"
  bottom: "Inception3/conv/loc1/perm"
  top: "Inception3/conv/loc1/flat"
  flatten_param {
    axis: 1
  }
} 

layer {
  name: "Inception3/conv/conf1"
  type: "Convolution"
  bottom: "conv5/incep"
  top: "Inception3/conv/conf1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "Inception3/conv/conf1/perm"
  type: "Permute"
  bottom: "Inception3/conv/conf1"
  top: "Inception3/conv/conf1/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "Inception3/conv/conf1/flat"
  type: "Flatten"
  bottom: "Inception3/conv/conf1/perm"
  top: "Inception3/conv/conf1/flat"
  flatten_param {
    axis: 1
  }
}

layer {
  name: "Inception3/conv/priorbox1"
  type: "PriorBox"
  bottom: "conv5/incep"
  bottom: "data"
  top: "Inception3/conv/priorbox1"
  prior_box_param {
    min_size: 32
    aspect_ratio: 1
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}

layer {
  name: "Inception3/conv/loc2"
  type: "Convolution"
  bottom: "conv5/incep"
  top: "Inception3/conv/loc2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "Inception3/conv/loc2/perm"
  type: "Permute"
  bottom: "Inception3/conv/loc2"
  top: "Inception3/conv/loc2/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "Inception3/conv/loc2/flat"
  type: "Flatten"
  bottom: "Inception3/conv/loc2/perm"
  top: "Inception3/conv/loc2/flat"
  flatten_param {
    axis: 1
  }
} 

layer {
  name: "Inception3/conv/conf2"
  type: "Convolution"
  bottom: "conv5/incep"
  top: "Inception3/conv/conf2"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "Inception3/conv/conf2/perm"
  type: "Permute"
  bottom: "Inception3/conv/conf2"
  top: "Inception3/conv/conf2/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "Inception3/conv/conf2/flat"
  type: "Flatten"
  bottom: "Inception3/conv/conf2/perm"
  top: "Inception3/conv/conf2/flat"
  flatten_param {
    axis: 1
  }
}

layer {
  name: "Inception3/conv/priorbox2"
  type: "PriorBox"
  bottom: "conv5/incep"
  bottom: "data"
  top: "Inception3/conv/priorbox2"
  prior_box_param {
    min_size: 64
    aspect_ratio: 1
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}

layer {
  name: "Inception3/conv/loc3"
  type: "Convolution"
  bottom: "conv5/incep"
  top: "Inception3/conv/loc3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "Inception3/conv/loc3/perm"
  type: "Permute"
  bottom: "Inception3/conv/loc3"
  top: "Inception3/conv/loc3/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "Inception3/conv/loc3/flat"
  type: "Flatten"
  bottom: "Inception3/conv/loc3/perm"
  top: "Inception3/conv/loc3/flat"
  flatten_param {
    axis: 1
  }
} 

layer {
  name: "Inception3/conv/conf3"
  type: "Convolution"
  bottom: "conv5/incep"
  top: "Inception3/conv/conf3"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "Inception3/conv/conf3/perm"
  type: "Permute"
  bottom: "Inception3/conv/conf3"
  top: "Inception3/conv/conf3/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "Inception3/conv/conf3/flat"
  type: "Flatten"
  bottom: "Inception3/conv/conf3/perm"
  top: "Inception3/conv/conf3/flat"
  flatten_param {
    axis: 1
  }
}

layer {
  name: "Inception3/conv/priorbox3"
  type: "PriorBox"
  bottom: "conv5/incep"
  bottom: "data"
  top: "Inception3/conv/priorbox3"
  prior_box_param {
    min_size: 128
    aspect_ratio: 1
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}

layer {
  name: "conv6_1"
  type: "Convolution"
  bottom: "conv5/incep"
  top: "conv6_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv6/bn1"
  type: "BatchNorm"
  bottom: "conv6_1"
  top: "conv6_1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv6/bn_scale1"
  type: "Scale"
  bottom: "conv6_1"
  top: "conv6_1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv6/relu1"
  type: "ReLU"
  bottom: "conv6_1"
  top: "conv6_1"
}

layer {
  name: "conv6_2"
  type: "Convolution"
  bottom: "conv6_1"
  top: "conv6_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 2
  }
}

layer {
  name: "conv6/bn2"
  type: "BatchNorm"
  bottom: "conv6_2"
  top: "conv6_2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv6/bn_scale2"
  type: "Scale"
  bottom: "conv6_2"
  top: "conv6_2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv6/relu2"
  type: "ReLU"
  bottom: "conv6_2"
  top: "conv6_2"
}

layer {
  name: "conv6/loc"
  type: "Convolution"
  bottom: "conv6_2"
  top: "conv6/loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "conv6/loc/perm"
  type: "Permute"
  bottom: "conv6/loc"
  top: "conv6/loc/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "conv6/loc/perm/flat"
  type: "Flatten"
  bottom: "conv6/loc/perm"
  top: "conv6/loc/perm/flat"
  flatten_param {
    axis: 1
  }
}

layer {
  name: "conv6/conf"
  type: "Convolution"
  bottom: "conv6_2"
  top: "conv6/conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "conv6/conf/perm"
  type: "Permute"
  bottom: "conv6/conf"
  top: "conv6/conf/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "conv6/conf/perm/flat"
  type: "Flatten"
  bottom: "conv6/conf/perm"
  top: "conv6/conf/perm/flat"
  flatten_param {
    axis: 1
  }
}

layer {
  name: "conv6/priorbox"
  type: "PriorBox"
  bottom: "conv6_2"
  bottom: "data"
  top: "conv6/priorbox"
  prior_box_param {
    min_size: 256
    aspect_ratio: 1
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}

layer {
  name: "conv7_1"
  type: "Convolution"
  bottom: "conv6_2"
  top: "conv7_1"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 128
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 0
    kernel_size: 1
    stride: 1
  }
}

layer {
  name: "conv7/bn1"
  type: "BatchNorm"
  bottom: "conv7_1"
  top: "conv7_1"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv7/bn_scale1"
  type: "Scale"
  bottom: "conv7_1"
  top: "conv7_1"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv7/relu1"
  type: "ReLU"
  bottom: "conv7_1"
  top: "conv7_1"
}

layer {
  name: "conv7_2"
  type: "Convolution"
  bottom: "conv7_1"
  top: "conv7_2"
  param {
    lr_mult: 1.0
    decay_mult: 1.0
  }
  convolution_param {
    num_output: 256
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
    pad: 1
    kernel_size: 3
    stride: 2
  }
}

layer {
  name: "conv7/bn2"
  type: "BatchNorm"
  bottom: "conv7_2"
  top: "conv7_2"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  batch_norm_param {
    use_global_stats: false
  }
}

layer {
  name: "conv7/bn_scale2"
  type: "Scale"
  bottom: "conv7_2"
  top: "conv7_2"
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  param {
    lr_mult: 1.0
    decay_mult: 0
  }
  scale_param {
    bias_term: true
  }
}

layer {
  name: "conv7/relu2"
  type: "ReLU"
  bottom: "conv7_2"
  top: "conv7_2"
}

layer {
  name: "conv7/loc"
  type: "Convolution"
  bottom: "conv7_2"
  top: "conv7/loc"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 4
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "conv7/loc/perm"
  type: "Permute"
  bottom: "conv7/loc"
  top: "conv7/loc/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "conv7/loc/perm/flat"
  type: "Flatten"
  bottom: "conv7/loc/perm"
  top: "conv7/loc/perm/flat"
  flatten_param {
    axis: 1
  }
}

layer {
  name: "conv7/conf"
  type: "Convolution"
  bottom: "conv7_2"
  top: "conv7/conf"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 2
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "xavier"
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}

layer {
  name: "conv7/conf/perm"
  type: "Permute"
  bottom: "conv7/conf"
  top: "conv7/conf/perm"
  permute_param {
    order: 0
    order: 2
    order: 3
    order: 1
  }
}

layer {
  name: "conv7/conf/perm/flat"
  type: "Flatten"
  bottom: "conv7/conf/perm"
  top: "conv7/conf/perm/flat"
  flatten_param {
    axis: 1
  }
}

layer {
  name: "conv7/priorbox"
  type: "PriorBox"
  bottom: "conv7_2"
  bottom: "data"
  top: "conv7/priorbox"
  prior_box_param {
    min_size: 512
    aspect_ratio: 1
    flip: true
    clip: true
    variance: 0.1
    variance: 0.1
    variance: 0.2
    variance: 0.2
  }
}

layer {
  name: "mbox_loc"
  type: "Concat"
  bottom: "Inception3/conv/loc1/flat"
  bottom: "Inception3/conv/loc2/flat"
  bottom: "Inception3/conv/loc3/flat"
  bottom: "conv6/loc/perm/flat"
  bottom: "conv7/loc/perm/flat"
  top: "mbox_loc"
  concat_param {
    axis: 1
  }
}

layer {
  name: "mbox_conf"
  type: "Concat"
  bottom: "Inception3/conv/conf1/flat"
  bottom: "Inception3/conv/conf2/flat"
  bottom: "Inception3/conv/conf3/flat"
  bottom: "conv6/conf/perm/flat"
  bottom: "conv7/conf/perm/flat"
  top: "mbox_conf"
  concat_param {
    axis: 1
  }
}

layer {
  name: "mbox_priorbox"
  type: "Concat"
  bottom: "Inception3/conv/priorbox1"
  bottom: "Inception3/conv/priorbox2"
  bottom: "Inception3/conv/priorbox3"
  bottom: "conv6/priorbox"
  bottom: "conv7/priorbox"
  top: "mbox_priorbox"
  concat_param {
    axis: 2
  }
}

layer {
  name: "mbox_loss"
  type: "MultiBoxLoss"
  bottom: "mbox_loc"
  bottom: "mbox_conf"
  bottom: "mbox_priorbox"
  bottom: "label"
  top: "mbox_loss"
  include {
    phase: TRAIN
  }
  propagate_down: true
  propagate_down: true
  propagate_down: false
  propagate_down: false
  loss_param {
    normalization: VALID
  }
  multibox_loss_param {
    loc_loss_type: SMOOTH_L1
    conf_loss_type: SOFTMAX
    loc_weight: 1.0
    num_classes: 2
    share_location: true
    match_type: PER_PREDICTION
    overlap_threshold: 0.5
    use_prior_for_matching: true
    background_label_id: 0
    use_difficult_gt: true
    do_neg_mining: true
    neg_pos_ratio: 3.0
    neg_overlap: 0.5
    code_type: CENTER_SIZE
  }
}