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September 30, 2018 07:53
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| name: "MobileNet-SSD" | |
| input: "data" | |
| input_shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 300 | |
| dim: 300 | |
| } | |
| layer { | |
| name: "conv0" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv0" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv0/relu" | |
| type: "ReLU" | |
| bottom: "conv0" | |
| top: "conv0" | |
| } | |
| layer { | |
| name: "conv1/dw" | |
| type: "Convolution" | |
| bottom: "conv0" | |
| top: "conv1/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 32 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv1/dw" | |
| top: "conv1/dw" | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "conv1/dw" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/relu" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "conv2/dw" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "conv2/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 64 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv2/dw" | |
| top: "conv2/dw" | |
| } | |
| layer { | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "conv2/dw" | |
| top: "conv2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2/relu" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| } | |
| layer { | |
| name: "conv3/dw" | |
| type: "Convolution" | |
| bottom: "conv2" | |
| top: "conv3/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 128 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv3/dw" | |
| top: "conv3/dw" | |
| } | |
| layer { | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "conv3/dw" | |
| top: "conv3" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3/relu" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| } | |
| layer { | |
| name: "conv4/dw" | |
| type: "Convolution" | |
| bottom: "conv3" | |
| top: "conv4/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 128 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv4/dw" | |
| top: "conv4/dw" | |
| } | |
| layer { | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv4/dw" | |
| top: "conv4" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4/relu" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| } | |
| layer { | |
| name: "conv5/dw" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| top: "conv5/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 256 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv5/dw" | |
| top: "conv5/dw" | |
| } | |
| layer { | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv5/dw" | |
| top: "conv5" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5/relu" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| } | |
| layer { | |
| name: "conv6/dw" | |
| type: "Convolution" | |
| bottom: "conv5" | |
| top: "conv6/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 256 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv6/dw" | |
| top: "conv6/dw" | |
| } | |
| layer { | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "conv6/dw" | |
| top: "conv6" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6/relu" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| } | |
| layer { | |
| name: "conv7/dw" | |
| type: "Convolution" | |
| bottom: "conv6" | |
| top: "conv7/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv7/dw" | |
| top: "conv7/dw" | |
| } | |
| layer { | |
| name: "conv7" | |
| type: "Convolution" | |
| bottom: "conv7/dw" | |
| top: "conv7" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7/relu" | |
| type: "ReLU" | |
| bottom: "conv7" | |
| top: "conv7" | |
| } | |
| layer { | |
| name: "conv8/dw" | |
| type: "Convolution" | |
| bottom: "conv7" | |
| top: "conv8/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv8/dw" | |
| top: "conv8/dw" | |
| } | |
| layer { | |
| name: "conv8" | |
| type: "Convolution" | |
| bottom: "conv8/dw" | |
| top: "conv8" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8/relu" | |
| type: "ReLU" | |
| bottom: "conv8" | |
| top: "conv8" | |
| } | |
| layer { | |
| name: "conv9/dw" | |
| type: "Convolution" | |
| bottom: "conv8" | |
| top: "conv9/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv9/dw" | |
| top: "conv9/dw" | |
| } | |
| layer { | |
| name: "conv9" | |
| type: "Convolution" | |
| bottom: "conv9/dw" | |
| top: "conv9" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9/relu" | |
| type: "ReLU" | |
| bottom: "conv9" | |
| top: "conv9" | |
| } | |
| layer { | |
| name: "conv10/dw" | |
| type: "Convolution" | |
| bottom: "conv9" | |
| top: "conv10/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv10/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv10/dw" | |
| top: "conv10/dw" | |
| } | |
| layer { | |
| name: "conv10" | |
| type: "Convolution" | |
| bottom: "conv10/dw" | |
| top: "conv10" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv10/relu" | |
| type: "ReLU" | |
| bottom: "conv10" | |
| top: "conv10" | |
| } | |
| layer { | |
| name: "conv11/dw" | |
| type: "Convolution" | |
| bottom: "conv10" | |
| top: "conv11/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv11/dw" | |
| top: "conv11/dw" | |
| } | |
| layer { | |
| name: "conv11" | |
| type: "Convolution" | |
| bottom: "conv11/dw" | |
| top: "conv11" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11/relu" | |
| type: "ReLU" | |
| bottom: "conv11" | |
| top: "conv11" | |
| } | |
| layer { | |
| name: "conv12/dw" | |
| type: "Convolution" | |
| bottom: "conv11" | |
| top: "conv12/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| group: 512 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv12/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv12/dw" | |
| top: "conv12/dw" | |
| } | |
| layer { | |
| name: "conv12" | |
| type: "Convolution" | |
| bottom: "conv12/dw" | |
| top: "conv12" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv12/relu" | |
| type: "ReLU" | |
| bottom: "conv12" | |
| top: "conv12" | |
| } | |
| layer { | |
| name: "conv13/dw" | |
| type: "Convolution" | |
| bottom: "conv12" | |
| top: "conv13/dw" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 1024 | |
| engine: CAFFE | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13/dw/relu" | |
| type: "ReLU" | |
| bottom: "conv13/dw" | |
| top: "conv13/dw" | |
| } | |
| layer { | |
| name: "conv13" | |
| type: "Convolution" | |
| bottom: "conv13/dw" | |
| top: "conv13" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13/relu" | |
| type: "ReLU" | |
| bottom: "conv13" | |
| top: "conv13" | |
| } | |
| layer { | |
| name: "conv14_1" | |
| type: "Convolution" | |
| bottom: "conv13" | |
| top: "conv14_1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv14_1/relu" | |
| type: "ReLU" | |
| bottom: "conv14_1" | |
| top: "conv14_1" | |
| } | |
| layer { | |
| name: "conv14_2" | |
| type: "Convolution" | |
| bottom: "conv14_1" | |
| top: "conv14_2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv14_2/relu" | |
| type: "ReLU" | |
| bottom: "conv14_2" | |
| top: "conv14_2" | |
| } | |
| layer { | |
| name: "conv15_1" | |
| type: "Convolution" | |
| bottom: "conv14_2" | |
| top: "conv15_1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv15_1/relu" | |
| type: "ReLU" | |
| bottom: "conv15_1" | |
| top: "conv15_1" | |
| } | |
| layer { | |
| name: "conv15_2" | |
| type: "Convolution" | |
| bottom: "conv15_1" | |
| top: "conv15_2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv15_2/relu" | |
| type: "ReLU" | |
| bottom: "conv15_2" | |
| top: "conv15_2" | |
| } | |
| layer { | |
| name: "conv16_1" | |
| type: "Convolution" | |
| bottom: "conv15_2" | |
| top: "conv16_1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16_1/relu" | |
| type: "ReLU" | |
| bottom: "conv16_1" | |
| top: "conv16_1" | |
| } | |
| layer { | |
| name: "conv16_2" | |
| type: "Convolution" | |
| bottom: "conv16_1" | |
| top: "conv16_2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16_2/relu" | |
| type: "ReLU" | |
| bottom: "conv16_2" | |
| top: "conv16_2" | |
| } | |
| layer { | |
| name: "conv17_1" | |
| type: "Convolution" | |
| bottom: "conv16_2" | |
| top: "conv17_1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17_1/relu" | |
| type: "ReLU" | |
| bottom: "conv17_1" | |
| top: "conv17_1" | |
| } | |
| layer { | |
| name: "conv17_2" | |
| type: "Convolution" | |
| bottom: "conv17_1" | |
| top: "conv17_2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17_2/relu" | |
| type: "ReLU" | |
| bottom: "conv17_2" | |
| top: "conv17_2" | |
| } | |
| layer { | |
| name: "conv11_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv11" | |
| top: "conv11_mbox_loc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 12 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv11_mbox_loc" | |
| top: "conv11_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv11_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv11_mbox_loc_perm" | |
| top: "conv11_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv11_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv11" | |
| top: "conv11_mbox_conf" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 63 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv11_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv11_mbox_conf" | |
| top: "conv11_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv11_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv11_mbox_conf_perm" | |
| top: "conv11_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv11_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv11" | |
| bottom: "data" | |
| top: "conv11_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 60.0 | |
| aspect_ratio: 2.0 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv13_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv13" | |
| top: "conv13_mbox_loc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv13_mbox_loc" | |
| top: "conv13_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv13_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv13_mbox_loc_perm" | |
| top: "conv13_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv13_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv13" | |
| top: "conv13_mbox_conf" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 126 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv13_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv13_mbox_conf" | |
| top: "conv13_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv13_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv13_mbox_conf_perm" | |
| top: "conv13_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv13_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv13" | |
| bottom: "data" | |
| top: "conv13_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 105.0 | |
| max_size: 150.0 | |
| aspect_ratio: 2.0 | |
| aspect_ratio: 3.0 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv14_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv14_2" | |
| top: "conv14_2_mbox_loc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv14_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv14_2_mbox_loc" | |
| top: "conv14_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv14_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv14_2_mbox_loc_perm" | |
| top: "conv14_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv14_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv14_2" | |
| top: "conv14_2_mbox_conf" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 126 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv14_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv14_2_mbox_conf" | |
| top: "conv14_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv14_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv14_2_mbox_conf_perm" | |
| top: "conv14_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv14_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv14_2" | |
| bottom: "data" | |
| top: "conv14_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 150.0 | |
| max_size: 195.0 | |
| aspect_ratio: 2.0 | |
| aspect_ratio: 3.0 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv15_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv15_2" | |
| top: "conv15_2_mbox_loc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv15_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv15_2_mbox_loc" | |
| top: "conv15_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv15_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv15_2_mbox_loc_perm" | |
| top: "conv15_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv15_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv15_2" | |
| top: "conv15_2_mbox_conf" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 126 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv15_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv15_2_mbox_conf" | |
| top: "conv15_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv15_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv15_2_mbox_conf_perm" | |
| top: "conv15_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv15_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv15_2" | |
| bottom: "data" | |
| top: "conv15_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 195.0 | |
| max_size: 240.0 | |
| aspect_ratio: 2.0 | |
| aspect_ratio: 3.0 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv16_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv16_2" | |
| top: "conv16_2_mbox_loc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv16_2_mbox_loc" | |
| top: "conv16_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv16_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv16_2_mbox_loc_perm" | |
| top: "conv16_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv16_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv16_2" | |
| top: "conv16_2_mbox_conf" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 126 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv16_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv16_2_mbox_conf" | |
| top: "conv16_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv16_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv16_2_mbox_conf_perm" | |
| top: "conv16_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv16_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv16_2" | |
| bottom: "data" | |
| top: "conv16_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 240.0 | |
| max_size: 285.0 | |
| aspect_ratio: 2.0 | |
| aspect_ratio: 3.0 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv17_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv17_2" | |
| top: "conv17_2_mbox_loc" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv17_2_mbox_loc" | |
| top: "conv17_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv17_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv17_2_mbox_loc_perm" | |
| top: "conv17_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv17_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv17_2" | |
| top: "conv17_2_mbox_conf" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 126 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv17_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv17_2_mbox_conf" | |
| top: "conv17_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv17_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv17_2_mbox_conf_perm" | |
| top: "conv17_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv17_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv17_2" | |
| bottom: "data" | |
| top: "conv17_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 285.0 | |
| max_size: 300.0 | |
| aspect_ratio: 2.0 | |
| aspect_ratio: 3.0 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "mbox_loc" | |
| type: "Concat" | |
| bottom: "conv11_mbox_loc_flat" | |
| bottom: "conv13_mbox_loc_flat" | |
| bottom: "conv14_2_mbox_loc_flat" | |
| bottom: "conv15_2_mbox_loc_flat" | |
| bottom: "conv16_2_mbox_loc_flat" | |
| bottom: "conv17_2_mbox_loc_flat" | |
| top: "mbox_loc" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf" | |
| type: "Concat" | |
| bottom: "conv11_mbox_conf_flat" | |
| bottom: "conv13_mbox_conf_flat" | |
| bottom: "conv14_2_mbox_conf_flat" | |
| bottom: "conv15_2_mbox_conf_flat" | |
| bottom: "conv16_2_mbox_conf_flat" | |
| bottom: "conv17_2_mbox_conf_flat" | |
| top: "mbox_conf" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "mbox_priorbox" | |
| type: "Concat" | |
| bottom: "conv11_mbox_priorbox" | |
| bottom: "conv13_mbox_priorbox" | |
| bottom: "conv14_2_mbox_priorbox" | |
| bottom: "conv15_2_mbox_priorbox" | |
| bottom: "conv16_2_mbox_priorbox" | |
| bottom: "conv17_2_mbox_priorbox" | |
| top: "mbox_priorbox" | |
| concat_param { | |
| axis: 2 | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf_reshape" | |
| type: "Reshape" | |
| bottom: "mbox_conf" | |
| top: "mbox_conf_reshape" | |
| reshape_param { | |
| shape { | |
| dim: 0 | |
| dim: -1 | |
| dim: 21 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf_softmax" | |
| type: "Softmax" | |
| bottom: "mbox_conf_reshape" | |
| top: "mbox_conf_softmax" | |
| softmax_param { | |
| axis: 2 | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf_flatten" | |
| type: "Flatten" | |
| bottom: "mbox_conf_softmax" | |
| top: "mbox_conf_flatten" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "detection_out" | |
| type: "DetectionOutput" | |
| bottom: "mbox_loc" | |
| bottom: "mbox_conf_flatten" | |
| bottom: "mbox_priorbox" | |
| top: "detection_out" | |
| include { | |
| phase: TEST | |
| } | |
| detection_output_param { | |
| num_classes: 21 | |
| share_location: true | |
| background_label_id: 0 | |
| nms_param { | |
| nms_threshold: 0.45 | |
| top_k: 100 | |
| } | |
| code_type: CENTER_SIZE | |
| keep_top_k: 100 | |
| confidence_threshold: 0.25 | |
| } | |
| } |
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