yolo-relu.prototxt

name: "yolo-relu"
input: "data"
input_shape {
  dim: 1
  dim: 3
  dim: 448
  dim: 448
}
layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data"
  top: "conv1"
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 2
    pad: 3
    bias_term: false
  }
}
layer {
  name: "bn1"
  type: "BatchNorm"
  bottom: "conv1"
  top: "bn1"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale1"
  type: "Scale"
  bottom: "bn1"
  top: "scale1"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu1"
  type: "ReLU"
  bottom: "scale1"
  top: "scale1"
}
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: 192
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn2"
  type: "BatchNorm"
  bottom: "conv2"
  top: "bn2"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale2"
  type: "Scale"
  bottom: "bn2"
  top: "scale2"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu2"
  type: "ReLU"
  bottom: "scale2"
  top: "scale2"
}
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: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn3"
  type: "BatchNorm"
  bottom: "conv3"
  top: "bn3"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale3"
  type: "Scale"
  bottom: "bn3"
  top: "scale3"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu3"
  type: "ReLU"
  bottom: "scale3"
  top: "scale3"
}
layer {
  name: "conv4"
  type: "Convolution"
  bottom: "scale3"
  top: "conv4"
  convolution_param {
    num_output: 256
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn4"
  type: "BatchNorm"
  bottom: "conv4"
  top: "bn4"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale4"
  type: "Scale"
  bottom: "bn4"
  top: "scale4"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "scale4"
  top: "scale4"
}
layer {
  name: "conv5"
  type: "Convolution"
  bottom: "scale4"
  top: "conv5"
  convolution_param {
    num_output: 256
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn5"
  type: "BatchNorm"
  bottom: "conv5"
  top: "bn5"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale5"
  type: "Scale"
  bottom: "bn5"
  top: "scale5"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "scale5"
  top: "scale5"
}
layer {
  name: "conv6"
  type: "Convolution"
  bottom: "scale5"
  top: "conv6"
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn6"
  type: "BatchNorm"
  bottom: "conv6"
  top: "bn6"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale6"
  type: "Scale"
  bottom: "bn6"
  top: "scale6"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "scale6"
  top: "scale6"
}
layer {
  name: "pool6"
  type: "Pooling"
  bottom: "scale6"
  top: "pool6"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv7"
  type: "Convolution"
  bottom: "pool6"
  top: "conv7"
  convolution_param {
    num_output: 256
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn7"
  type: "BatchNorm"
  bottom: "conv7"
  top: "bn7"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale7"
  type: "Scale"
  bottom: "bn7"
  top: "scale7"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "scale7"
  top: "scale7"
}
layer {
  name: "conv8"
  type: "Convolution"
  bottom: "scale7"
  top: "conv8"
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn8"
  type: "BatchNorm"
  bottom: "conv8"
  top: "bn8"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale8"
  type: "Scale"
  bottom: "bn8"
  top: "scale8"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu8"
  type: "ReLU"
  bottom: "scale8"
  top: "scale8"
}
layer {
  name: "conv9"
  type: "Convolution"
  bottom: "scale8"
  top: "conv9"
  convolution_param {
    num_output: 256
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn9"
  type: "BatchNorm"
  bottom: "conv9"
  top: "bn9"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale9"
  type: "Scale"
  bottom: "bn9"
  top: "scale9"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu9"
  type: "ReLU"
  bottom: "scale9"
  top: "scale9"
}
layer {
  name: "conv10"
  type: "Convolution"
  bottom: "scale9"
  top: "conv10"
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn10"
  type: "BatchNorm"
  bottom: "conv10"
  top: "bn10"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale10"
  type: "Scale"
  bottom: "bn10"
  top: "scale10"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu10"
  type: "ReLU"
  bottom: "scale10"
  top: "scale10"
}
layer {
  name: "conv11"
  type: "Convolution"
  bottom: "scale10"
  top: "conv11"
  convolution_param {
    num_output: 256
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn11"
  type: "BatchNorm"
  bottom: "conv11"
  top: "bn11"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale11"
  type: "Scale"
  bottom: "bn11"
  top: "scale11"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu11"
  type: "ReLU"
  bottom: "scale11"
  top: "scale11"
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "scale11"
  top: "conv12"
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn12"
  type: "BatchNorm"
  bottom: "conv12"
  top: "bn12"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale12"
  type: "Scale"
  bottom: "bn12"
  top: "scale12"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu12"
  type: "ReLU"
  bottom: "scale12"
  top: "scale12"
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "scale12"
  top: "conv13"
  convolution_param {
    num_output: 256
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn13"
  type: "BatchNorm"
  bottom: "conv13"
  top: "bn13"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale13"
  type: "Scale"
  bottom: "bn13"
  top: "scale13"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu13"
  type: "ReLU"
  bottom: "scale13"
  top: "scale13"
}
layer {
  name: "conv14"
  type: "Convolution"
  bottom: "scale13"
  top: "conv14"
  convolution_param {
    num_output: 512
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn14"
  type: "BatchNorm"
  bottom: "conv14"
  top: "bn14"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale14"
  type: "Scale"
  bottom: "bn14"
  top: "scale14"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu14"
  type: "ReLU"
  bottom: "scale14"
  top: "scale14"
}
layer {
  name: "conv15"
  type: "Convolution"
  bottom: "scale14"
  top: "conv15"
  convolution_param {
    num_output: 512
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn15"
  type: "BatchNorm"
  bottom: "conv15"
  top: "bn15"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale15"
  type: "Scale"
  bottom: "bn15"
  top: "scale15"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu15"
  type: "ReLU"
  bottom: "scale15"
  top: "scale15"
}
layer {
  name: "conv16"
  type: "Convolution"
  bottom: "scale15"
  top: "conv16"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn16"
  type: "BatchNorm"
  bottom: "conv16"
  top: "bn16"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale16"
  type: "Scale"
  bottom: "bn16"
  top: "scale16"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu16"
  type: "ReLU"
  bottom: "scale16"
  top: "scale16"
}
layer {
  name: "pool16"
  type: "Pooling"
  bottom: "scale16"
  top: "pool16"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "conv17"
  type: "Convolution"
  bottom: "pool16"
  top: "conv17"
  convolution_param {
    num_output: 512
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn17"
  type: "BatchNorm"
  bottom: "conv17"
  top: "bn17"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale17"
  type: "Scale"
  bottom: "bn17"
  top: "scale17"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu17"
  type: "ReLU"
  bottom: "scale17"
  top: "scale17"
}
layer {
  name: "conv18"
  type: "Convolution"
  bottom: "scale17"
  top: "conv18"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn18"
  type: "BatchNorm"
  bottom: "conv18"
  top: "bn18"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale18"
  type: "Scale"
  bottom: "bn18"
  top: "scale18"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu18"
  type: "ReLU"
  bottom: "scale18"
  top: "scale18"
}
layer {
  name: "conv19"
  type: "Convolution"
  bottom: "scale18"
  top: "conv19"
  convolution_param {
    num_output: 512
    kernel_size: 1
    stride: 1
    pad: 0
    bias_term: false
  }
}
layer {
  name: "bn19"
  type: "BatchNorm"
  bottom: "conv19"
  top: "bn19"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale19"
  type: "Scale"
  bottom: "bn19"
  top: "scale19"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu19"
  type: "ReLU"
  bottom: "scale19"
  top: "scale19"
}
layer {
  name: "conv20"
  type: "Convolution"
  bottom: "scale19"
  top: "conv20"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn20"
  type: "BatchNorm"
  bottom: "conv20"
  top: "bn20"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale20"
  type: "Scale"
  bottom: "bn20"
  top: "scale20"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu20"
  type: "ReLU"
  bottom: "scale20"
  top: "scale20"
}
layer {
  name: "conv21"
  type: "Convolution"
  bottom: "scale20"
  top: "conv21"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn21"
  type: "BatchNorm"
  bottom: "conv21"
  top: "bn21"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale21"
  type: "Scale"
  bottom: "bn21"
  top: "scale21"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu21"
  type: "ReLU"
  bottom: "scale21"
  top: "scale21"
}
layer {
  name: "conv22"
  type: "Convolution"
  bottom: "scale21"
  top: "conv22"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    stride: 2
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn22"
  type: "BatchNorm"
  bottom: "conv22"
  top: "bn22"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale22"
  type: "Scale"
  bottom: "bn22"
  top: "scale22"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu22"
  type: "ReLU"
  bottom: "scale22"
  top: "scale22"
}
layer {
  name: "conv23"
  type: "Convolution"
  bottom: "scale22"
  top: "conv23"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn23"
  type: "BatchNorm"
  bottom: "conv23"
  top: "bn23"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale23"
  type: "Scale"
  bottom: "bn23"
  top: "scale23"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu23"
  type: "ReLU"
  bottom: "scale23"
  top: "scale23"
}
layer {
  name: "conv24"
  type: "Convolution"
  bottom: "scale23"
  top: "conv24"
  convolution_param {
    num_output: 1024
    kernel_size: 3
    stride: 1
    pad: 1
    bias_term: false
  }
}
layer {
  name: "bn24"
  type: "BatchNorm"
  bottom: "conv24"
  top: "bn24"
  batch_norm_param {
    use_global_stats: true
  }
}
layer {
  name: "scale24"
  type: "Scale"
  bottom: "bn24"
  top: "scale24"
  scale_param {
    bias_term: true
  }
}
layer {
  name: "relu24"
  type: "ReLU"
  bottom: "scale24"
  top: "scale24"
}
layer {
  name: "pool24"
  type: "Pooling"
  bottom: "scale24"
  top: "pool24"
  pooling_param {
    pool: AVE
    kernel_size: 7
  }
}
layer {
  name: "fc25"
  type: "InnerProduct"
  bottom: "pool24"
  top: "fc25"
  inner_product_param {
    num_output: 1470
  }
}