yolo.prototxt

name: "YOLONET"
layer {
  name: "data"
  type: "Input"
  top: "data"
  input_param { shape: { dim: 1 dim: 3 dim: 416 dim: 416 } }
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 32
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn1"
  type: "BatchNorm"
  bottom: "conv1"
  top: "bn1"
}
layer {
  name: "scale1"
  type: "Scale"
  bottom: "bn1"
  top: "scale1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "scale1"
  top: "scale1"
  relu_param{
    negative_slope: 0.1
  }		
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "scale1"
  top: "pool1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer{
  name: "conv2"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2"
  convolution_param {
    num_output: 64
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn2"
  type: "BatchNorm"
  bottom: "conv2"
  top: "bn2"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale2"
  type: "Scale"
  bottom: "bn2"
  top: "scale2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "scale2"
  top: "scale2"
  relu_param{
    negative_slope: 0.1
  }   
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "scale2"
  top: "pool2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer{
  name: "conv3"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3"
  convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn3"
  type: "BatchNorm"
  bottom: "conv3"
  top: "bn3"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale3"
  type: "Scale"
  bottom: "bn3"
  top: "scale3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "scale3"
  top: "scale3"
  relu_param{
    negative_slope: 0.1
  }		
}


layer{
  name: "conv4"
  type: "Convolution"
  bottom: "scale3"
  top: "conv4"
  convolution_param {
    num_output: 64
    kernel_size: 1
    pad: 0 #??
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn4"
  type: "BatchNorm"
  bottom: "conv4"
  top: "bn4"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale4"
  type: "Scale"
  bottom: "bn4"
  top: "scale4"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "scale4"
  top: "scale4"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv5"
  type: "Convolution"
  bottom: "scale4"
  top: "conv5"
  convolution_param {
    num_output: 128
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn5"
  type: "BatchNorm"
  bottom: "conv5"
  top: "bn5"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale5"
  type: "Scale"
  bottom: "bn5"
  top: "scale5"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "scale5"
  top: "scale5"
  relu_param{
    negative_slope: 0.1
  }		
}
layer {
  name: "pool5"
  type: "Pooling"
  bottom: "scale5"
  top: "pool5"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer{
  name: "conv6"
  type: "Convolution"
  bottom: "pool5"
  top: "conv6"
  convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn6"
  type: "BatchNorm"
  bottom: "conv6"
  top: "bn6"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale6"
  type: "Scale"
  bottom: "bn6"
  top: "scale6"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "scale6"
  top: "scale6"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv7"
  type: "Convolution"
  bottom: "scale6"
  top: "conv7"
  convolution_param {
    num_output: 128
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn7"
  type: "BatchNorm"
  bottom: "conv7"
  top: "bn7"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale7"
  type: "Scale"
  bottom: "bn7"
  top: "scale7"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "scale7"
  top: "scale7"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv8"
  type: "Convolution"
  bottom: "scale7"
  top: "conv8"
  convolution_param {
    num_output: 256
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn8"
  type: "BatchNorm"
  bottom: "conv8"
  top: "bn8"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale8"
  type: "Scale"
  bottom: "bn8"
  top: "scale8"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu8"
  type: "ReLU"
  bottom: "scale8"
  top: "scale8"
  relu_param{
    negative_slope: 0.1
  }		
}
layer {
  name: "pool8"
  type: "Pooling"
  bottom: "scale8"
  top: "pool8"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer{
  name: "conv9"
  type: "Convolution"
  bottom: "pool8"
  top: "conv9"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn9"
  type: "BatchNorm"
  bottom: "conv9"
  top: "bn9"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale9"
  type: "Scale"
  bottom: "bn9"
  top: "scale9"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu9"
  type: "ReLU"
  bottom: "scale9"
  top: "scale9"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv10"
  type: "Convolution"
  bottom: "scale9"
  top: "conv10"
  convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn10"
  type: "BatchNorm"
  bottom: "conv10"
  top: "bn10"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale10"
  type: "Scale"
  bottom: "bn10"
  top: "scale10"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu10"
  type: "ReLU"
  bottom: "scale10"
  top: "scale10"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv11"
  type: "Convolution"
  bottom: "scale10"
  top: "conv11"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn11"
  type: "BatchNorm"
  bottom: "conv11"
  top: "bn11"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale11"
  type: "Scale"
  bottom: "bn11"
  top: "scale11"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu11"
  type: "ReLU"
  bottom: "scale11"
  top: "scale11"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv12"
  type: "Convolution"
  bottom: "scale11"
  top: "conv12"
  convolution_param {
    num_output: 256
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn12"
  type: "BatchNorm"
  bottom: "conv12"
  top: "bn12"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale12"
  type: "Scale"
  bottom: "bn12"
  top: "scale12"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu12"
  type: "ReLU"
  bottom: "scale12"
  top: "scale12"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv13"
  type: "Convolution"
  bottom: "scale12"
  top: "conv13"
  convolution_param {
    num_output: 512
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn13"
  type: "BatchNorm"
  bottom: "conv13"
  top: "bn13"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale13"
  type: "Scale"
  bottom: "bn13"
  top: "scale13"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu13"
  type: "ReLU"
  bottom: "scale13"
  top: "scale13"
  relu_param{
    negative_slope: 0.1
  }		
}
layer {
  name: "pool13"
  type: "Pooling"
  bottom: "scale13"
  top: "pool13"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}

layer{
  name: "conv14"
  type: "Convolution"
  bottom: "pool13"
  top: "conv14"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn14"
  type: "BatchNorm"
  bottom: "conv14"
  top: "bn14"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale14"
  type: "Scale"
  bottom: "bn14"
  top: "scale14"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu14"
  type: "ReLU"
  bottom: "scale14"
  top: "scale14"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv15"
  type: "Convolution"
  bottom: "scale14"
  top: "conv15"
  convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn15"
  type: "BatchNorm"
  bottom: "conv15"
  top: "bn15"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale15"
  type: "Scale"
  bottom: "bn15"
  top: "scale15"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu15"
  type: "ReLU"
  bottom: "scale15"
  top: "scale15"
  relu_param{
    negative_slope: 0.1
  }		
}


layer{
  name: "conv16"
  type: "Convolution"
  bottom: "scale15"
  top: "conv16"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn16"
  type: "BatchNorm"
  bottom: "conv16"
  top: "bn16"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale16"
  type: "Scale"
  bottom: "bn16"
  top: "scale16"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu16"
  type: "ReLU"
  bottom: "scale16"
  top: "scale16"
  relu_param{
    negative_slope: 0.1
  }		
}

layer{
  name: "conv17"
  type: "Convolution"
  bottom: "scale16"
  top: "conv17"
  convolution_param {
    num_output: 512
    kernel_size: 1
    pad: 0
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn17"
  type: "BatchNorm"
  bottom: "conv17"
  top: "bn17"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale17"
  type: "Scale"
  bottom: "bn17"
  top: "scale17"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu17"
  type: "ReLU"
  bottom: "scale17"
  top: "scale17"
  relu_param{
    negative_slope: 0.1
  }		
}


layer{
  name: "conv18"
  type: "Convolution"
  bottom: "scale17"
  top: "conv18"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn18"
  type: "BatchNorm"
  bottom: "conv18"
  top: "bn18"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale18"
  type: "Scale"
  bottom: "bn18"
  top: "scale18"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu18"
  type: "ReLU"
  bottom: "scale18"
  top: "scale18"
  relu_param{
    negative_slope: 0.1
  }		
}



layer{
  name: "conv19"
  type: "Convolution"
  bottom: "scale18"
  top: "conv19"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn19"
  type: "BatchNorm"
  bottom: "conv19"
  top: "bn19"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale19"
  type: "Scale"
  bottom: "bn19"
  top: "scale19"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu19"
  type: "ReLU"
  bottom: "scale19"
  top: "scale19"
  relu_param{
    negative_slope: 0.1
  }		
}



layer{
  name: "conv20"
  type: "Convolution"
  bottom: "scale19"
  top: "conv20"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }

}
layer {
  name: "bn20"
  type: "BatchNorm"
  bottom: "conv20"
  top: "bn20"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale20"
  type: "Scale"
  bottom: "bn20"
  top: "scale20"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu20"
  type: "ReLU"
  bottom: "scale20"
  top: "scale20"
  relu_param {
    negative_slope: 0.1
  }		
}

layer {
  name: "concat1"
  type: "Concat"
  bottom: "scale13"
  top: "concat1"
}

layer {
  name: "reorg1"
  type: "Reorg"
  bottom: "concat1"
  top: "reorg1"
  reorg_param {
    stride: 2
  }
}

layer {
  name: "concat2"
  type: "Concat"
  bottom: "reorg1"
  bottom: "scale20"
  top: "concat2"
}

layer{
  name: "conv21"
  type: "Convolution"
  bottom: "concat2"
  top: "conv21"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    pad: 1
    stride: 1
    bias_term: false
  }
}
layer {
  name: "bn21"
  type: "BatchNorm"
  bottom: "conv21"
  top: "bn21"
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
  param {
    lr_mult: 0
  }
}
layer {
  name: "scale21"
  type: "Scale"
  bottom: "bn21"
  top: "scale21"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu21"
  type: "ReLU"
  bottom: "scale21"
  top: "scale21"
  relu_param{
    negative_slope: 0.1
  }		
}

layer {
  name: "conv22"
  type: "Convolution"
  bottom: "scale21"
  top: "conv22"
  convolution_param {
    num_output: 425
    kernel_size: 1
    pad: 0
    stride: 1
  }
}

layer {
  name: "region1"
  type: "Region"
  bottom: "conv22"
  top: "region1"
  region_param {
    classes: 80
    coords: 4
    boxes_of_each_grid: 5
    softmax: true
  }
}
#http://ethereon.github.io/netscope/#/gist/9640ecb59a75f230446e7c70d2f8bcf3