name: "Darkent2Caffe"
input: "data"
input_dim: 1
input_dim: 3
input_dim: 416
input_dim: 416

layer {
    bottom: "data"
    top: "layer1-conv"
    name: "layer1-conv"
    type: "Convolution"
    convolution_param {
        num_output: 16
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer1-conv"
    top: "layer1-conv"
    name: "layer1-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer1-conv"
    top: "layer1-conv"
    name: "layer1-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer1-conv"
    top: "layer1-conv"
    name: "layer1-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer1-conv"
    top: "layer2-maxpool"
    name: "layer2-maxpool"
    type: "Pooling"
    pooling_param {
        kernel_size: 2
        stride: 2
        pool: MAX
    }
}
layer {
    bottom: "layer2-maxpool"
    top: "layer3-conv"
    name: "layer3-conv"
    type: "Convolution"
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer3-conv"
    top: "layer3-conv"
    name: "layer3-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer3-conv"
    top: "layer3-conv"
    name: "layer3-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer3-conv"
    top: "layer3-conv"
    name: "layer3-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer3-conv"
    top: "layer4-maxpool"
    name: "layer4-maxpool"
    type: "Pooling"
    pooling_param {
        kernel_size: 2
        stride: 2
        pool: MAX
    }
}
layer {
    bottom: "layer4-maxpool"
    top: "layer5-conv"
    name: "layer5-conv"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer5-conv"
    top: "layer5-conv"
    name: "layer5-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer5-conv"
    top: "layer5-conv"
    name: "layer5-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer5-conv"
    top: "layer5-conv"
    name: "layer5-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer5-conv"
    top: "layer6-maxpool"
    name: "layer6-maxpool"
    type: "Pooling"
    pooling_param {
        kernel_size: 2
        stride: 2
        pool: MAX
    }
}
layer {
    bottom: "layer6-maxpool"
    top: "layer7-conv"
    name: "layer7-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer7-conv"
    top: "layer7-conv"
    name: "layer7-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer7-conv"
    top: "layer7-conv"
    name: "layer7-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer7-conv"
    top: "layer7-conv"
    name: "layer7-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer7-conv"
    top: "layer8-maxpool"
    name: "layer8-maxpool"
    type: "Pooling"
    pooling_param {
        kernel_size: 2
        stride: 2
        pool: MAX
    }
}
layer {
    bottom: "layer8-maxpool"
    top: "layer9-conv"
    name: "layer9-conv"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer9-conv"
    top: "layer9-conv"
    name: "layer9-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer9-conv"
    top: "layer9-conv"
    name: "layer9-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer9-conv"
    top: "layer9-conv"
    name: "layer9-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer9-conv"
    top: "layer10-maxpool"
    name: "layer10-maxpool"
    type: "Pooling"
    pooling_param {
        kernel_size: 2
        stride: 2
        pool: MAX
    }
}
layer {
    bottom: "layer10-maxpool"
    top: "layer11-conv"
    name: "layer11-conv"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer11-conv"
    top: "layer11-conv"
    name: "layer11-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer11-conv"
    top: "layer11-conv"
    name: "layer11-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer11-conv"
    top: "layer11-conv"
    name: "layer11-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer11-conv"
    top: "layer12-maxpool"
    name: "layer12-maxpool"
    type: "Pooling"
    pooling_param {
        kernel_size: 1
        stride: 1
        pool: MAX
    }
}
layer {
    bottom: "layer12-maxpool"
    top: "layer13-conv"
    name: "layer13-conv"
    type: "Convolution"
    convolution_param {
        num_output: 1024
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer13-conv"
    top: "layer13-conv"
    name: "layer13-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer13-conv"
    top: "layer13-conv"
    name: "layer13-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer13-conv"
    top: "layer13-conv"
    name: "layer13-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer13-conv"
    top: "layer14-conv"
    name: "layer14-conv"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer14-conv"
    top: "layer14-conv"
    name: "layer14-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer14-conv"
    top: "layer14-conv"
    name: "layer14-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer14-conv"
    top: "layer14-conv"
    name: "layer14-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer14-conv"
    top: "layer15-conv"
    name: "layer15-conv"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer15-conv"
    top: "layer15-conv"
    name: "layer15-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer15-conv"
    top: "layer15-conv"
    name: "layer15-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer15-conv"
    top: "layer15-conv"
    name: "layer15-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer15-conv"
    top: "layer16-conv"
    name: "layer16-conv"
    type: "Convolution"
    convolution_param {
        num_output: 33
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: true
    }
}
layer {
    bottom: "layer16-conv"
    type: "Concat"
    top: "layer17-yolo"
    name: "layer17-yolo"
}
layer {
    bottom: "layer14-conv"
    top: "layer18-route"
    name: "layer18-route"
    type: "Concat"
}
layer {
    bottom: "layer18-route"
    top: "layer19-conv"
    name: "layer19-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer19-conv"
    top: "layer19-conv"
    name: "layer19-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer19-conv"
    top: "layer19-conv"
    name: "layer19-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer19-conv"
    top: "layer19-conv"
    name: "layer19-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer19-conv"
    top: "layer20-upsample"
    name: "layer20-upsample"
    type: "Upsample"
    #upsample_param {
    #    scale: 2
    #}
}
layer {
    bottom: "layer20-upsample"
    bottom: "layer9-conv"
    top: "layer21-route"
    name: "layer21-route"
    type: "Concat"
}
layer {
    bottom: "layer21-route"
    top: "layer22-conv"
    name: "layer22-conv"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer22-conv"
    top: "layer22-conv"
    name: "layer22-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer22-conv"
    top: "layer22-conv"
    name: "layer22-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer22-conv"
    top: "layer22-conv"
    name: "layer22-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer22-conv"
    top: "layer23-conv"
    name: "layer23-conv"
    type: "Convolution"
    convolution_param {
        num_output: 33
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: true
    }
}
layer {
    bottom: "layer16-conv"
    bottom: "layer23-conv"
    top: "yolo-det"
    name: "yolo-det"
    type: "Yolo"
}