mobilenet_yolov3_lite_test.prototxt

name: "MobileNet-YOLO"
layer {
  name: "data"
  type: "AnnotatedData"
  top: "data"
  top: "label"
  #top: "seg_label"
  include {
    phase: TEST
  }
  transform_param {
    scale: 0.007843
    mean_value: 127.5
    mean_value: 127.5
    mean_value: 127.5
	force_color: true
    resize_param {
      prob: 1.0
      resize_mode: WARP
      height: 416
      width: 416
      interp_mode: LINEAR
    }
  }
  data_param {
    source: "examples/coco/coco_minival_lmdb"
    batch_size: 1
    backend: LMDB
  }
  annotated_data_param {
    batch_sampler {
    }
    label_map_file:  "data/coco/labelmap_coco.prototxt"
  }
}
#layer {
#  name: "silence"
#  type: "Silence"
#  bottom: "seg_label"
#  phase: TEST
#}
layer {
  name: "conv0"
  type: "Convolution"
  bottom: "data"
  top: "conv0"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv0/bn"
  type: "BatchNorm"
  bottom: "conv0"
  top: "conv0"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv0/scale"
  type: "Scale"
  bottom: "conv0"
  top: "conv0"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv0/relu"
  type: "ReLU"
  bottom: "conv0"
  top: "conv0"
}
layer {
  name: "conv1/dw"
  type: "DepthwiseConvolution"
  bottom: "conv0"
  top: "conv1/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 32
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 32
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv1/dw/bn"
  type: "BatchNorm"
  bottom: "conv1/dw"
  top: "conv1/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv1/dw/scale"
  type: "Scale"
  bottom: "conv1/dw"
  top: "conv1/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv1/dw/relu"
  type: "ReLU"
  bottom: "conv1/dw"
  top: "conv1/dw"
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "conv1/dw"
  top: "conv1"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
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
  }
}
layer {
  name: "conv1/scale"
  type: "Scale"
  bottom: "conv1"
  top: "conv1"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv1/relu"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}
layer {
  name: "conv2/dw"
  type: "DepthwiseConvolution"
  bottom: "conv1"
  top: "conv2/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 64
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 64
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv2/dw/bn"
  type: "BatchNorm"
  bottom: "conv2/dw"
  top: "conv2/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv2/dw/scale"
  type: "Scale"
  bottom: "conv2/dw"
  top: "conv2/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv2/dw/relu"
  type: "ReLU"
  bottom: "conv2/dw"
  top: "conv2/dw"
}
layer {
  name: "conv2"
  type: "Convolution"
  bottom: "conv2/dw"
  top: "conv2"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
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
  }
}
layer {
  name: "conv2/scale"
  type: "Scale"
  bottom: "conv2"
  top: "conv2"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv2/relu"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2"
}
layer {
  name: "conv3/dw"
  type: "DepthwiseConvolution"
  bottom: "conv2"
  top: "conv3/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 128
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3/dw/bn"
  type: "BatchNorm"
  bottom: "conv3/dw"
  top: "conv3/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3/dw/scale"
  type: "Scale"
  bottom: "conv3/dw"
  top: "conv3/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv3/dw/relu"
  type: "ReLU"
  bottom: "conv3/dw"
  top: "conv3/dw"
}
layer {
  name: "conv3"
  type: "Convolution"
  bottom: "conv3/dw"
  top: "conv3"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv3/bn"
  type: "BatchNorm"
  bottom: "conv3"
  top: "conv3"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv3/scale"
  type: "Scale"
  bottom: "conv3"
  top: "conv3"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv3/relu"
  type: "ReLU"
  bottom: "conv3"
  top: "conv3"
}
layer {
  name: "conv4/dw"
  type: "DepthwiseConvolution"
  bottom: "conv3"
  top: "conv4/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 128
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 128
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4/dw/bn"
  type: "BatchNorm"
  bottom: "conv4/dw"
  top: "conv4/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4/dw/scale"
  type: "Scale"
  bottom: "conv4/dw"
  top: "conv4/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv4/dw/relu"
  type: "ReLU"
  bottom: "conv4/dw"
  top: "conv4/dw"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv4/dw"
  top: "conv4"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv4/bn"
  type: "BatchNorm"
  bottom: "conv4"
  top: "conv4"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv4/scale"
  type: "Scale"
  bottom: "conv4"
  top: "conv4"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv4/relu"
  type: "ReLU"
  bottom: "conv4"
  top: "conv4"
}
layer {
  name: "conv5/dw"
  type: "DepthwiseConvolution"
  bottom: "conv4"
  top: "conv5/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 256
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5/dw/bn"
  type: "BatchNorm"
  bottom: "conv5/dw"
  top: "conv5/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5/dw/scale"
  type: "Scale"
  bottom: "conv5/dw"
  top: "conv5/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv5/dw/relu"
  type: "ReLU"
  bottom: "conv5/dw"
  top: "conv5/dw"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "conv5/dw"
  top: "conv5"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv5/bn"
  type: "BatchNorm"
  bottom: "conv5"
  top: "conv5"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv5/scale"
  type: "Scale"
  bottom: "conv5"
  top: "conv5"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv5/relu"
  type: "ReLU"
  bottom: "conv5"
  top: "conv5"
}
layer {
  name: "conv6/dw"
  type: "DepthwiseConvolution"
  bottom: "conv5"
  top: "conv6/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 256
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 256
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6/dw/bn"
  type: "BatchNorm"
  bottom: "conv6/dw"
  top: "conv6/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv6/dw/scale"
  type: "Scale"
  bottom: "conv6/dw"
  top: "conv6/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv6/dw/relu"
  type: "ReLU"
  bottom: "conv6/dw"
  top: "conv6/dw"
}
layer {
  name: "conv6"
  type: "Convolution"
  bottom: "conv6/dw"
  top: "conv6"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv6/bn"
  type: "BatchNorm"
  bottom: "conv6"
  top: "conv6"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv6/scale"
  type: "Scale"
  bottom: "conv6"
  top: "conv6"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv6/relu"
  type: "ReLU"
  bottom: "conv6"
  top: "conv6"
}
layer {
  name: "conv7/dw"
  type: "DepthwiseConvolution"
  bottom: "conv6"
  top: "conv7/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7/dw/bn"
  type: "BatchNorm"
  bottom: "conv7/dw"
  top: "conv7/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv7/dw/scale"
  type: "Scale"
  bottom: "conv7/dw"
  top: "conv7/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv7/dw/relu"
  type: "ReLU"
  bottom: "conv7/dw"
  top: "conv7/dw"
}
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "conv7/dw"
  top: "conv7"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv7/bn"
  type: "BatchNorm"
  bottom: "conv7"
  top: "conv7"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv7/scale"
  type: "Scale"
  bottom: "conv7"
  top: "conv7"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv7/relu"
  type: "ReLU"
  bottom: "conv7"
  top: "conv7"
}
layer {
  name: "conv8/dw"
  type: "DepthwiseConvolution"
  bottom: "conv7"
  top: "conv8/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3

    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv8/dw/bn"
  type: "BatchNorm"
  bottom: "conv8/dw"
  top: "conv8/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv8/dw/scale"
  type: "Scale"
  bottom: "conv8/dw"
  top: "conv8/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv8/dw/relu"
  type: "ReLU"
  bottom: "conv8/dw"
  top: "conv8/dw"
}
layer {
  name: "conv8"
  type: "Convolution"
  bottom: "conv8/dw"
  top: "conv8"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv8/bn"
  type: "BatchNorm"
  bottom: "conv8"
  top: "conv8"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv8/scale"
  type: "Scale"
  bottom: "conv8"
  top: "conv8"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv8/relu"
  type: "ReLU"
  bottom: "conv8"
  top: "conv8"
}
layer {
  name: "conv9/dw"
  type: "DepthwiseConvolution"
  bottom: "conv8"
  top: "conv9/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv9/dw/bn"
  type: "BatchNorm"
  bottom: "conv9/dw"
  top: "conv9/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv9/dw/scale"
  type: "Scale"
  bottom: "conv9/dw"
  top: "conv9/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv9/dw/relu"
  type: "ReLU"
  bottom: "conv9/dw"
  top: "conv9/dw"
}
layer {
  name: "conv9"
  type: "Convolution"
  bottom: "conv9/dw"
  top: "conv9"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv9/bn"
  type: "BatchNorm"
  bottom: "conv9"
  top: "conv9"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv9/scale"
  type: "Scale"
  bottom: "conv9"
  top: "conv9"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv9/relu"
  type: "ReLU"
  bottom: "conv9"
  top: "conv9"
}
layer {
  name: "conv10/dw"
  type: "DepthwiseConvolution"
  bottom: "conv9"
  top: "conv10/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv10/dw/bn"
  type: "BatchNorm"
  bottom: "conv10/dw"
  top: "conv10/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv10/dw/scale"
  type: "Scale"
  bottom: "conv10/dw"
  top: "conv10/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv10/dw/relu"
  type: "ReLU"
  bottom: "conv10/dw"
  top: "conv10/dw"
}
layer {
  name: "conv10"
  type: "Convolution"
  bottom: "conv10/dw"
  top: "conv10"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv10/bn"
  type: "BatchNorm"
  bottom: "conv10"
  top: "conv10"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv10/scale"
  type: "Scale"
  bottom: "conv10"
  top: "conv10"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv10/relu"
  type: "ReLU"
  bottom: "conv10"
  top: "conv10"
}
layer {
  name: "conv11/dw"
  type: "DepthwiseConvolution"
  bottom: "conv10"
  top: "conv11/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv11/dw/bn"
  type: "BatchNorm"
  bottom: "conv11/dw"
  top: "conv11/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv11/dw/scale"
  type: "Scale"
  bottom: "conv11/dw"
  top: "conv11/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv11/dw/relu"
  type: "ReLU"
  bottom: "conv11/dw"
  top: "conv11/dw"
}
layer {
  name: "conv11"
  type: "Convolution"
  bottom: "conv11/dw"
  top: "conv11"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv11/bn"
  type: "BatchNorm"
  bottom: "conv11"
  top: "conv11"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv11/scale"
  type: "Scale"
  bottom: "conv11"
  top: "conv11"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv11/relu"
  type: "ReLU"
  bottom: "conv11"
  top: "conv11"
}
layer {
  name: "conv12/dw"
  type: "DepthwiseConvolution"
  bottom: "conv11"
  top: "conv12/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    stride: 2
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv12/dw/bn"
  type: "BatchNorm"
  bottom: "conv12/dw"
  top: "conv12/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv12/dw/scale"
  type: "Scale"
  bottom: "conv12/dw"
  top: "conv12/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv12/dw/relu"
  type: "ReLU"
  bottom: "conv12/dw"
  top: "conv12/dw"
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "conv12/dw"
  top: "conv12"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv12/bn"
  type: "BatchNorm"
  bottom: "conv12"
  top: "conv12"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv12/scale"
  type: "Scale"
  bottom: "conv12"
  top: "conv12"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv12/relu"
  type: "ReLU"
  bottom: "conv12"
  top: "conv12"
}
layer {
  name: "conv13/dw"
  type: "DepthwiseConvolution"
  bottom: "conv12"
  top: "conv13/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1024
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv13/dw/bn"
  type: "BatchNorm"
  bottom: "conv13/dw"
  top: "conv13/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv13/dw/scale"
  type: "Scale"
  bottom: "conv13/dw"
  top: "conv13/dw"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv13/dw/relu"
  type: "ReLU"
  bottom: "conv13/dw"
  top: "conv13/dw"
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "conv13/dw"
  top: "conv13"
  param {
    lr_mult: 0.1
    decay_mult: 0.1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv13/bn"
  type: "BatchNorm"
  bottom: "conv13"
  top: "conv13"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv13/scale"
  type: "Scale"
  bottom: "conv13"
  top: "conv13"
  param {
    lr_mult: 0.1
    decay_mult: 0.0
  }
  param {
    lr_mult: 0.2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv13/relu"
  type: "ReLU"
  bottom: "conv13"
  top: "conv13"
}

layer {
  name: "conv15/dw"
  type: "DepthwiseConvolution"
  bottom: "conv13"
  top: "conv15/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 1024
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv15/dw/bn"
  type: "BatchNorm"
  bottom: "conv15/dw"
  top: "conv15/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv15/dw/scale"
  type: "Scale"
  bottom: "conv15/dw"
  top: "conv15/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv15/dw/relu"
  type: "ReLU"
  bottom: "conv15/dw"
  top: "conv15/dw"
}
layer {
  name: "conv15"
  type: "Convolution"
  bottom: "conv15/dw"
  top: "conv15"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv15/bn"
  type: "BatchNorm"
  bottom: "conv15"
  top: "conv15"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv15/scale"
  type: "Scale"
  bottom: "conv15"
  top: "conv15"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv15/relu"
  type: "ReLU"
  bottom: "conv15"
  top: "conv15"
}

layer {
  name: "conv16_new"
  type: "Convolution"
  bottom: "conv15"
  top: "conv16_new"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    #group: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv16_new/bn"
  type: "BatchNorm"
  bottom: "conv16_new"
  top: "conv16_new"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv16_new/scale"
  type: "Scale"
  bottom: "conv16_new"
  top: "conv16_new"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv16_new/relu"
  type: "ReLU"
  bottom: "conv16_new"
  top: "conv16_new"
}



layer {
    name: "upsample_new"
    type: "Upsample"
    bottom: "conv16_new"
    top: "upsample_new" 
    upsample_param {
        scale: 2
    }
}
layer {
  name: "conv17/dw"
  type: "DepthwiseConvolution"
  bottom: "conv11"
  top: "conv17/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv17/dw/bn"
  type: "BatchNorm"
  bottom: "conv17/dw"
  top: "conv17/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv17/dw/scale"
  type: "Scale"
  bottom: "conv17/dw"
  top: "conv17/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv17/dw/relu"
  type: "ReLU"
  bottom: "conv17/dw"
  top: "conv17/dw"
}
layer {
  name: "conv17"
  type: "Convolution"
  bottom: "conv17/dw"
  top: "conv17"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv17/bn"
  type: "BatchNorm"
  bottom: "conv17"
  top: "conv17"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv17/scale"
  type: "Scale"
  bottom: "conv17"
  top: "conv17"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv17/relu"
  type: "ReLU"
  bottom: "conv17"
  top: "conv17"
}
layer {
  name: "conv17/sum"
  type: "Eltwise"
  bottom: "upsample_new"
  bottom: "conv17"
  top: "conv17/sum"
}
layer {
  name: "conv18_plus"
  type: "Convolution"
  bottom: "conv17/sum"
  top: "conv18_plus"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv18_plus/bn"
  type: "BatchNorm"
  bottom: "conv18_plus"
  top: "conv18_plus"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv18_plus/scale"
  type: "Scale"
  bottom: "conv18_plus"
  top: "conv18_plus"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv18_plus/relu"
  type: "ReLU"
  bottom: "conv18_plus"
  top: "conv18_plus"
}
layer {
  name: "conv18/dw"
  type: "DepthwiseConvolution"
  bottom: "conv18_plus"
  top: "conv18/dw"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 512
    bias_term: false
    pad: 1
    kernel_size: 3
    group: 512
    engine: CAFFE
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv18/dw/bn"
  type: "BatchNorm"
  bottom: "conv18/dw"
  top: "conv18/dw"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv18/dw/scale"
  type: "Scale"
  bottom: "conv18/dw"
  top: "conv18/dw"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv18/dw/relu"
  type: "ReLU"
  bottom: "conv18/dw"
  top: "conv18/dw"
}
layer {
  name: "conv18_new"
  type: "Convolution"
  bottom: "conv18/dw"
  top: "conv18_new"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  convolution_param {
    num_output: 1024
    bias_term: false
    kernel_size: 1
    weight_filler {
      type: "msra"
    }
  }
}
layer {
  name: "conv18_new/bn"
  type: "BatchNorm"
  bottom: "conv18_new"
  top: "conv18_new"
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
  param {
    lr_mult: 0
    decay_mult: 0
  }
}
layer {
  name: "conv18_new/scale"
  type: "Scale"
  bottom: "conv18_new"
  top: "conv18_new"
  param {
    lr_mult: 1
    decay_mult: 0.0
  }
  param {
    lr_mult: 2
    decay_mult: 0.0
  }
  scale_param {
    filler {
      value: 1
    }
    bias_term: true
    bias_filler {
      value: 0
    }
  }
}
layer {
  name: "conv18_new/relu"
  type: "ReLU"
  bottom: "conv18_new"
  top: "conv18_new"
}


layer {
  name: "conv22"
  type: "Convolution"
  bottom: "conv15"
  top: "conv22"
    param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 255
    kernel_size: 1
    pad: 0
    stride: 1
    weight_filler {
      type: "xavier"
    }
	bias_filler {
      value: 0
    }
  }
}

layer {
  name: "conv23_new"
  type: "Convolution"
  bottom: "conv18_new"
  top: "conv23_new"
    param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 255
    kernel_size: 1
    pad: 0
    stride: 1
    weight_filler {
      type: "xavier"
    }
	bias_filler {
      value: 0
    }
  }
}

layer {
  name: "detection_out"
  type: "Yolov3DetectionOutput"
  bottom: "conv22"
  bottom: "conv23_new"
  top: "detection_out"
  include {
	phase: TEST
  }
  yolov3_detection_output_param {
    confidence_threshold: 0.01
	nms_threshold: 0.45
    num_classes: 80
	
	
	#10,14,  23,27,  37,58,  81,82,  135,169,  344,319
    biases: 10
    biases: 14
    biases: 23
    biases: 27
    biases: 37
    biases: 58
    biases: 81
    biases: 82
    biases: 135
    biases: 169
	biases: 344
    biases: 319
	
    mask:3
    mask:4
    mask:5	
    mask:0
    mask:1
    mask:2
    anchors_scale:32
    anchors_scale:16
    mask_group_num:2
  }
}
layer {
  name: "detection_eval_50"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_50"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.5
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_55"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_55"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.55
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_60"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_60"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.60
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_65"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_65"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.65
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_70"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_70"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.70
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_75"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_75"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.75
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_80"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_80"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.80
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_85"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_85"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.85
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_90"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_90"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.90
    evaluate_difficult_gt: false
  }
}
layer {
  name: "detection_eval_95"
  type: "DetectionEvaluate"
  bottom: "detection_out"
  bottom: "label"
  top: "detection_eval_95"

  detection_evaluate_param {
    num_classes: 81
    background_label_id: 0
    overlap_threshold: 0.95
    evaluate_difficult_gt: false
  }
}