| 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 |
| } |
| } |
|
|
