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| 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 | |
| } | |
| } |
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