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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: "conv1" | |
| } | |
| layer { | |
| name: "scale1" | |
| type: "Scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1" | |
| 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: "conv2" | |
| } | |
| layer { | |
| name: "scale2" | |
| type: "Scale" | |
| bottom: "conv2" | |
| top: "conv2" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool2" | |
| type: "Pooling" | |
| bottom: "conv2" | |
| 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: "conv3" | |
| } | |
| layer { | |
| name: "scale3" | |
| type: "Scale" | |
| bottom: "conv3" | |
| top: "conv3" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv3" | |
| 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: "conv4" | |
| } | |
| layer { | |
| name: "scale4" | |
| type: "Scale" | |
| bottom: "conv4" | |
| top: "conv4" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| 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: "conv5" | |
| } | |
| layer { | |
| name: "scale5" | |
| type: "Scale" | |
| bottom: "conv5" | |
| top: "conv5" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool5" | |
| type: "Pooling" | |
| bottom: "conv5" | |
| 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: "conv6" | |
| } | |
| layer { | |
| name: "scale6" | |
| type: "Scale" | |
| bottom: "conv6" | |
| top: "conv6" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv7" | |
| type: "Convolution" | |
| bottom: "conv6" | |
| 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: "conv7" | |
| } | |
| layer { | |
| name: "scale7" | |
| type: "Scale" | |
| bottom: "conv7" | |
| top: "conv7" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu7" | |
| type: "ReLU" | |
| bottom: "conv7" | |
| top: "conv7" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv8" | |
| type: "Convolution" | |
| bottom: "conv7" | |
| 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: "conv8" | |
| } | |
| layer { | |
| name: "scale8" | |
| type: "Scale" | |
| bottom: "conv8" | |
| top: "conv8" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu8" | |
| type: "ReLU" | |
| bottom: "conv8" | |
| top: "conv8" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool8" | |
| type: "Pooling" | |
| bottom: "conv8" | |
| 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: "conv9" | |
| } | |
| layer { | |
| name: "scale9" | |
| type: "Scale" | |
| bottom: "conv9" | |
| top: "conv9" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu9" | |
| type: "ReLU" | |
| bottom: "conv9" | |
| top: "conv9" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv10" | |
| type: "Convolution" | |
| bottom: "conv9" | |
| 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: "conv10" | |
| } | |
| layer { | |
| name: "scale10" | |
| type: "Scale" | |
| bottom: "conv10" | |
| top: "conv10" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu10" | |
| type: "ReLU" | |
| bottom: "conv10" | |
| top: "conv10" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv11" | |
| type: "Convolution" | |
| bottom: "conv10" | |
| 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: "conv11" | |
| } | |
| layer { | |
| name: "scale11" | |
| type: "Scale" | |
| bottom: "conv11" | |
| top: "conv11" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu11" | |
| type: "ReLU" | |
| bottom: "conv11" | |
| top: "conv11" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv12" | |
| type: "Convolution" | |
| bottom: "conv11" | |
| 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: "conv12" | |
| } | |
| layer { | |
| name: "scale12" | |
| type: "Scale" | |
| bottom: "conv12" | |
| top: "conv12" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu12" | |
| type: "ReLU" | |
| bottom: "conv12" | |
| top: "conv12" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv13" | |
| type: "Convolution" | |
| bottom: "conv12" | |
| 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: "conv13" | |
| } | |
| layer { | |
| name: "scale13" | |
| type: "Scale" | |
| bottom: "conv13" | |
| top: "conv13" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu13" | |
| type: "ReLU" | |
| bottom: "conv13" | |
| top: "conv13" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool13" | |
| type: "Pooling" | |
| bottom: "conv13" | |
| 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: "conv14" | |
| } | |
| layer { | |
| name: "scale14" | |
| type: "Scale" | |
| bottom: "conv14" | |
| top: "conv14" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu14" | |
| type: "ReLU" | |
| bottom: "conv14" | |
| top: "conv14" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv15" | |
| type: "Convolution" | |
| bottom: "conv14" | |
| 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: "conv15" | |
| } | |
| layer { | |
| name: "scale15" | |
| type: "Scale" | |
| bottom: "conv15" | |
| top: "conv15" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu15" | |
| type: "ReLU" | |
| bottom: "conv15" | |
| top: "conv15" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv16" | |
| type: "Convolution" | |
| bottom: "conv15" | |
| 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: "conv16" | |
| } | |
| layer { | |
| name: "scale16" | |
| type: "Scale" | |
| bottom: "conv16" | |
| top: "conv16" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu16" | |
| type: "ReLU" | |
| bottom: "conv16" | |
| top: "conv16" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv17" | |
| type: "Convolution" | |
| bottom: "conv16" | |
| 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: "conv17" | |
| } | |
| layer { | |
| name: "scale17" | |
| type: "Scale" | |
| bottom: "conv17" | |
| top: "conv17" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu17" | |
| type: "ReLU" | |
| bottom: "conv17" | |
| top: "conv17" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv18" | |
| type: "Convolution" | |
| bottom: "conv17" | |
| 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: "conv18" | |
| } | |
| layer { | |
| name: "scale18" | |
| type: "Scale" | |
| bottom: "conv18" | |
| top: "conv18" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu18" | |
| type: "ReLU" | |
| bottom: "conv18" | |
| top: "conv18" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv19" | |
| type: "Convolution" | |
| bottom: "conv18" | |
| 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: "conv19" | |
| } | |
| layer { | |
| name: "scale19" | |
| type: "Scale" | |
| bottom: "conv19" | |
| top: "conv19" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu19" | |
| type: "ReLU" | |
| bottom: "conv19" | |
| top: "conv19" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv20" | |
| type: "Convolution" | |
| bottom: "conv19" | |
| 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: "conv20" | |
| } | |
| layer { | |
| name: "scale20" | |
| type: "Scale" | |
| bottom: "conv20" | |
| top: "conv20" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu20" | |
| type: "ReLU" | |
| bottom: "conv20" | |
| top: "conv20" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "reorg1" | |
| type: "Reorg" | |
| bottom: "conv13" | |
| top: "reorg1" | |
| reorg_param { | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "concat2" | |
| type: "Concat" | |
| bottom: "reorg1" | |
| bottom: "conv20" | |
| 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: "conv21" | |
| } | |
| layer { | |
| name: "scale21" | |
| type: "Scale" | |
| bottom: "conv21" | |
| top: "conv21" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu21" | |
| type: "ReLU" | |
| bottom: "conv21" | |
| top: "conv21" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "conv22" | |
| type: "Convolution" | |
| bottom: "conv21" | |
| top: "conv22" | |
| convolution_param { | |
| num_output: 125 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| } | |
| } | |
| # layer { | |
| # name: "relu22" | |
| # type: "ReLU" | |
| # bottom: "conv22" | |
| # top: "conv22" | |
| # } | |
| layer{ | |
| name: "permute" | |
| type: "Permute" | |
| bottom: "conv22" | |
| top: "permute_conv_22" | |
| permute_param {order: 0 order: 2 order: 3 order: 1} | |
| } | |
| # layer { | |
| # name: "region1" | |
| # type: "Region" | |
| # bottom: "permute_conv_22" | |
| # top: "region1" | |
| # region_param { | |
| # classes: 20 | |
| # # coords: 4 | |
| # boxes_of_each_grid: 5 | |
| # softmax: true | |
| # } | |
| # } | |
| layer { | |
| name: "region_output" | |
| type: "RegionOutput" | |
| bottom: "permute_conv_22" | |
| top: "region_output" | |
| region_output_param { | |
| softmax: true | |
| classes: 20 | |
| # coords: 4 | |
| boxes_of_each_grid: 5 | |
| thres_nms: 0.4 | |
| thres_prob: 0.25 | |
| anchor_coords {pw: 1.08 ph: 1.19} | |
| anchor_coords {pw: 3.42 ph: 4.41} | |
| anchor_coords {pw: 6.63 ph: 11.38} | |
| anchor_coords {pw: 9.42 ph: 5.11} | |
| anchor_coords {pw: 16.62 ph: 10.52} | |
| } | |
| } | |
| #http://ethereon.github.io/netscope/#/gist/9640ecb59a75f230446e7c70d2f8bcf3 |
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