name: "Darknet2Caffe"
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: 32
        kernel_size: 3
        pad: 1
        stride: 2
        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-conv"
    name: "layer2-conv"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 2
        bias_term: false
    }
}
layer {
    bottom: "layer2-conv"
    top: "layer2-conv"
    name: "layer2-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer2-conv"
    top: "layer2-conv"
    name: "layer2-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer2-conv"
    top: "layer2-conv"
    name: "layer2-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer2-conv"
    top: "layer3-conv"
    name: "layer3-conv"
    type: "Convolution"
    convolution_param {
        num_output: 64
        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:"layer2-conv"
    top: "layer300-conv"
    name: "layer300-conv"
    type: "Convolution"
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer300-conv"
    top: "layer300-conv"
    name: "layer300-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer300-conv"
    top: "layer300-conv"
    name: "layer300-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer300-conv"
    top: "layer300-conv"
    name: "layer300-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
#######################################################
layer {
    bottom: "layer300-conv"
    top: "layer4-route"
    name: "layer4-route"
    type: "Concat"
}
layer {
    bottom: "layer4-route"
    top: "layer5-conv"
    name: "layer5-conv"
    type: "Convolution"
    convolution_param {
        num_output: 32
        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-conv"
    name: "layer6-conv"
    type: "Convolution"
    convolution_param {
        num_output: 32
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer6-conv"
    top: "layer6-conv"
    name: "layer6-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer6-conv"
    top: "layer6-conv"
    name: "layer6-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer6-conv"
    top: "layer6-conv"
    name: "layer6-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer6-conv"
    bottom: "layer5-conv"
    top: "layer7-route"
    name: "layer7-route"
    type: "Concat"
}
layer {
    bottom: "layer7-route"
    top: "layer8-conv"
    name: "layer8-conv"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer8-conv"
    top: "layer8-conv"
    name: "layer8-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer8-conv"
    top: "layer8-conv"
    name: "layer8-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer8-conv"
    top: "layer8-conv"
    name: "layer8-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer3-conv"
    bottom: "layer8-conv"
    top: "layer9-route"
    name: "layer9-route"
    type: "Concat"
}
layer {
    bottom: "layer9-route"
    top: "layer10-maxpool"
    name: "layer10-maxpool"
    type: "Pooling"
    pooling_param {
        stride: 2
        pool: MAX
        kernel_size: 2
        pad: 0
    }
}
layer {
    bottom: "layer10-maxpool"
    top: "layer11-conv"
    name: "layer11-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        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: "layer10-maxpool"
    top: "layer110-conv"
    name: "layer110-conv"
    type: "Convolution"
    convolution_param {
        num_output: 64
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer110-conv"
    top: "layer110-conv"
    name: "layer110-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer110-conv"
    top: "layer110-conv"
    name: "layer110-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer110-conv"
    top: "layer110-conv"
    name: "layer110-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
##########################################################
layer {
    bottom: "layer110-conv"
    top: "layer12-route"
    name: "layer12-route"
    type: "Concat"
}
layer {
    bottom: "layer12-route"
    top: "layer13-conv"
    name: "layer13-conv"
    type: "Convolution"
    convolution_param {
        num_output: 64
        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: 64
        kernel_size: 3
        pad: 1
        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"
    bottom: "layer13-conv"
    top: "layer15-route"
    name: "layer15-route"
    type: "Concat"
}
layer {
    bottom: "layer15-route"
    top: "layer16-conv"
    name: "layer16-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer16-conv"
    top: "layer16-conv"
    name: "layer16-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer16-conv"
    top: "layer16-conv"
    name: "layer16-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer16-conv"
    top: "layer16-conv"
    name: "layer16-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer11-conv"
    bottom: "layer16-conv"
    top: "layer17-route"
    name: "layer17-route"
    type: "Concat"
}
layer {
    bottom: "layer17-route"
    top: "layer18-maxpool"
    name: "layer18-maxpool"
    type: "Pooling"
    pooling_param {
        stride: 2
        pool: MAX
        kernel_size: 2
        pad: 0
    }
}
layer {
    bottom: "layer18-maxpool"
    top: "layer19-conv"
    name: "layer19-conv"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        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: "layer18-maxpool"
    top: "layer190-conv"
    name: "layer190-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer190-conv"
    top: "layer190-conv"
    name: "layer190-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer190-conv"
    top: "layer190-conv"
    name: "layer190-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer190-conv"
    top: "layer190-conv"
    name: "layer190-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
##################################################
layer {
    bottom: "layer190-conv"
    top: "layer20-route"
    name: "layer20-route"
    type: "Concat"
}
layer {
    bottom: "layer20-route"
    top: "layer21-conv"
    name: "layer21-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer21-conv"
    top: "layer21-conv"
    name: "layer21-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer21-conv"
    top: "layer21-conv"
    name: "layer21-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer21-conv"
    top: "layer21-conv"
    name: "layer21-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer21-conv"
    top: "layer22-conv"
    name: "layer22-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        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"
    bottom: "layer21-conv"
    top: "layer23-route"
    name: "layer23-route"
    type: "Concat"
}
layer {
    bottom: "layer23-route"
    top: "layer24-conv"
    name: "layer24-conv"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer24-conv"
    top: "layer24-conv"
    name: "layer24-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer24-conv"
    top: "layer24-conv"
    name: "layer24-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer24-conv"
    top: "layer24-conv"
    name: "layer24-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer19-conv"
    bottom: "layer24-conv"
    top: "layer25-route"
    name: "layer25-route"
    type: "Concat"
}
layer {
    bottom: "layer25-route"
    top: "layer26-maxpool"
    name: "layer26-maxpool"
    type: "Pooling"
    pooling_param {
        stride: 2
        pool: MAX
        kernel_size: 2
        pad: 0
    }
}
layer {
    bottom: "layer26-maxpool"
    top: "layer27-conv"
    name: "layer27-conv"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer27-conv"
    top: "layer27-conv"
    name: "layer27-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer27-conv"
    top: "layer27-conv"
    name: "layer27-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer27-conv"
    top: "layer27-conv"
    name: "layer27-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer27-conv"
    top: "layer28-conv"
    name: "layer28-conv"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer28-conv"
    top: "layer28-conv"
    name: "layer28-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer28-conv"
    top: "layer28-conv"
    name: "layer28-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer28-conv"
    top: "layer28-conv"
    name: "layer28-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer28-conv"
    top: "layer29-conv"
    name: "layer29-conv"
    type: "Convolution"
    convolution_param {
        num_output: 512
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer29-conv"
    top: "layer29-conv"
    name: "layer29-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer29-conv"
    top: "layer29-conv"
    name: "layer29-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer29-conv"
    top: "layer29-conv"
    name: "layer29-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer29-conv"
    top: "layer30-conv"
    name: "layer30-conv"
    type: "Convolution"
    convolution_param {
        num_output: 255
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: true
    }
}
layer {
    bottom: "layer28-conv"
    top: "layer32-route"
    name: "layer32-route"
    type: "Concat"
}
layer {
    bottom: "layer32-route"
    top: "layer33-conv"
    name: "layer33-conv"
    type: "Convolution"
    convolution_param {
        num_output: 128
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer33-conv"
    top: "layer33-conv"
    name: "layer33-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer33-conv"
    top: "layer33-conv"
    name: "layer33-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer33-conv"
    top: "layer33-conv"
    name: "layer33-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer33-conv"
    top: "layer34-upsample"
    name: "layer34-upsample"
    type: "Upsample"
    upsample_param {
        scale: 2
    }
}
layer {
    bottom: "layer34-upsample"
    bottom: "layer23-route"
    top: "layer35-route"
    name: "layer35-route"
    type: "Concat"
}
layer {
    bottom: "layer35-route"
    top: "layer36-conv"
    name: "layer36-conv"
    type: "Convolution"
    convolution_param {
        num_output: 256
        kernel_size: 3
        pad: 1
        stride: 1
        bias_term: false
    }
}
layer {
    bottom: "layer36-conv"
    top: "layer36-conv"
    name: "layer36-bn"
    type: "BatchNorm"
    batch_norm_param {
        use_global_stats: true
    }
}
layer {
    bottom: "layer36-conv"
    top: "layer36-conv"
    name: "layer36-scale"
    type: "Scale"
    scale_param {
        bias_term: true
    }
}
layer {
    bottom: "layer36-conv"
    top: "layer36-conv"
    name: "layer36-act"
    type: "ReLU"
    relu_param {
        negative_slope: 0.1
    }
}
layer {
    bottom: "layer36-conv"
    top: "layer37-conv"
    name: "layer37-conv"
    type: "Convolution"
    convolution_param {
        num_output: 255
        kernel_size: 1
        pad: 0
        stride: 1
        bias_term: true
    }
}