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May 12, 2018 17:18
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| name: "face-pose estimation MobileNetV2 t4" | |
| # transform_param { | |
| # scale: 0.017 | |
| # mirror: false | |
| # crop_size: 224 | |
| # mean_value: [103.94,116.78,123.68] | |
| # } | |
| # Enter your network definition here. | |
| # Use Shift+Enter to update the visualization. | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 128 | |
| input_dim: 128 | |
| #################################### | |
| #################################### | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "conv2_1/expand" | |
| type: "Convolution" | |
| bottom: "conv1" | |
| top: "conv2_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu2_1/expand" | |
| type: "ReLU" | |
| bottom: "conv2_1/expand" | |
| top: "conv2_1/expand" | |
| } | |
| layer { | |
| name: "conv2_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv2_1/expand" | |
| top: "conv2_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 32 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu2_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv2_1/dwise" | |
| top: "conv2_1/dwise" | |
| } | |
| layer { | |
| name: "conv2_1/linear" | |
| type: "Convolution" | |
| bottom: "conv2_1/dwise" | |
| top: "conv2_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/expand" | |
| type: "Convolution" | |
| bottom: "conv2_1/linear" | |
| top: "conv2_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu2_2/expand" | |
| type: "ReLU" | |
| bottom: "conv2_2/expand" | |
| top: "conv2_2/expand" | |
| } | |
| layer { | |
| name: "conv2_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv2_2/expand" | |
| top: "conv2_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 96 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu2_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv2_2/dwise" | |
| top: "conv2_2/dwise" | |
| } | |
| layer { | |
| name: "conv2_2/linear" | |
| type: "Convolution" | |
| bottom: "conv2_2/dwise" | |
| top: "conv2_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/expand" | |
| type: "Convolution" | |
| bottom: "conv2_2/linear" | |
| top: "conv3_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu3_1/expand" | |
| type: "ReLU" | |
| bottom: "conv3_1/expand" | |
| top: "conv3_1/expand" | |
| } | |
| layer { | |
| name: "conv3_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv3_1/expand" | |
| top: "conv3_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 144 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu3_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv3_1/dwise" | |
| top: "conv3_1/dwise" | |
| } | |
| layer { | |
| name: "conv3_1/linear" | |
| type: "Convolution" | |
| bottom: "conv3_1/dwise" | |
| top: "conv3_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_3_1" | |
| type: "Eltwise" | |
| bottom: "conv2_2/linear" | |
| bottom: "conv3_1/linear" | |
| top: "block_3_1" | |
| } | |
| layer { | |
| name: "conv3_2/expand" | |
| type: "Convolution" | |
| bottom: "block_3_1" | |
| top: "conv3_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu3_2/expand" | |
| type: "ReLU" | |
| bottom: "conv3_2/expand" | |
| top: "conv3_2/expand" | |
| } | |
| layer { | |
| name: "conv3_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv3_2/expand" | |
| top: "conv3_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 144 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 144 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu3_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv3_2/dwise" | |
| top: "conv3_2/dwise" | |
| } | |
| layer { | |
| name: "conv3_2/linear" | |
| type: "Convolution" | |
| bottom: "conv3_2/dwise" | |
| top: "conv3_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/expand" | |
| type: "Convolution" | |
| bottom: "conv3_2/linear" | |
| top: "conv4_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_1/expand" | |
| type: "ReLU" | |
| bottom: "conv4_1/expand" | |
| top: "conv4_1/expand" | |
| } | |
| layer { | |
| name: "conv4_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_1/expand" | |
| top: "conv4_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu4_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_1/dwise" | |
| top: "conv4_1/dwise" | |
| } | |
| layer { | |
| name: "conv4_1/linear" | |
| type: "Convolution" | |
| bottom: "conv4_1/dwise" | |
| top: "conv4_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_4_1" | |
| type: "Eltwise" | |
| bottom: "conv3_2/linear" | |
| bottom: "conv4_1/linear" | |
| top: "block_4_1" | |
| } | |
| layer { | |
| name: "conv4_2/expand" | |
| type: "Convolution" | |
| bottom: "block_4_1" | |
| top: "conv4_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_2/expand" | |
| type: "ReLU" | |
| bottom: "conv4_2/expand" | |
| top: "conv4_2/expand" | |
| } | |
| layer { | |
| name: "conv4_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_2/expand" | |
| top: "conv4_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu4_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_2/dwise" | |
| top: "conv4_2/dwise" | |
| } | |
| layer { | |
| name: "conv4_2/linear" | |
| type: "Convolution" | |
| bottom: "conv4_2/dwise" | |
| top: "conv4_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_4_2" | |
| type: "Eltwise" | |
| bottom: "block_4_1" | |
| bottom: "conv4_2/linear" | |
| top: "block_4_2" | |
| } | |
| layer { | |
| name: "conv4_3/expand" | |
| type: "Convolution" | |
| bottom: "block_4_2" | |
| top: "conv4_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_3/expand" | |
| type: "ReLU" | |
| bottom: "conv4_3/expand" | |
| top: "conv4_3/expand" | |
| } | |
| layer { | |
| name: "conv4_3/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_3/expand" | |
| top: "conv4_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 192 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu4_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_3/dwise" | |
| top: "conv4_3/dwise" | |
| } | |
| layer { | |
| name: "conv4_3/linear" | |
| type: "Convolution" | |
| bottom: "conv4_3/dwise" | |
| top: "conv4_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/expand" | |
| type: "Convolution" | |
| bottom: "conv4_3/linear" | |
| top: "conv4_4/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_4/expand" | |
| type: "ReLU" | |
| bottom: "conv4_4/expand" | |
| top: "conv4_4/expand" | |
| } | |
| layer { | |
| name: "conv4_4/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_4/expand" | |
| top: "conv4_4/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu4_4/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_4/dwise" | |
| top: "conv4_4/dwise" | |
| } | |
| layer { | |
| name: "conv4_4/linear" | |
| type: "Convolution" | |
| bottom: "conv4_4/dwise" | |
| top: "conv4_4/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_4_4" | |
| type: "Eltwise" | |
| bottom: "conv4_3/linear" | |
| bottom: "conv4_4/linear" | |
| top: "block_4_4" | |
| } | |
| layer { | |
| name: "conv4_5/expand" | |
| type: "Convolution" | |
| bottom: "block_4_4" | |
| top: "conv4_5/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_5/expand" | |
| type: "ReLU" | |
| bottom: "conv4_5/expand" | |
| top: "conv4_5/expand" | |
| } | |
| layer { | |
| name: "conv4_5/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_5/expand" | |
| top: "conv4_5/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu4_5/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_5/dwise" | |
| top: "conv4_5/dwise" | |
| } | |
| layer { | |
| name: "conv4_5/linear" | |
| type: "Convolution" | |
| bottom: "conv4_5/dwise" | |
| top: "conv4_5/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_4_5" | |
| type: "Eltwise" | |
| bottom: "block_4_4" | |
| bottom: "conv4_5/linear" | |
| top: "block_4_5" | |
| } | |
| layer { | |
| name: "conv4_6/expand" | |
| type: "Convolution" | |
| bottom: "block_4_5" | |
| top: "conv4_6/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_6/expand" | |
| type: "ReLU" | |
| bottom: "conv4_6/expand" | |
| top: "conv4_6/expand" | |
| } | |
| layer { | |
| name: "conv4_6/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_6/expand" | |
| top: "conv4_6/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu4_6/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_6/dwise" | |
| top: "conv4_6/dwise" | |
| } | |
| layer { | |
| name: "conv4_6/linear" | |
| type: "Convolution" | |
| bottom: "conv4_6/dwise" | |
| top: "conv4_6/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_4_6" | |
| type: "Eltwise" | |
| bottom: "block_4_5" | |
| bottom: "conv4_6/linear" | |
| top: "block_4_6" | |
| } | |
| layer { | |
| name: "conv4_7/expand" | |
| type: "Convolution" | |
| bottom: "block_4_6" | |
| top: "conv4_7/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu4_7/expand" | |
| type: "ReLU" | |
| bottom: "conv4_7/expand" | |
| top: "conv4_7/expand" | |
| } | |
| layer { | |
| name: "conv4_7/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv4_7/expand" | |
| top: "conv4_7/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 384 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu4_7/dwise" | |
| type: "ReLU" | |
| bottom: "conv4_7/dwise" | |
| top: "conv4_7/dwise" | |
| } | |
| layer { | |
| name: "conv4_7/linear" | |
| type: "Convolution" | |
| bottom: "conv4_7/dwise" | |
| top: "conv4_7/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/expand" | |
| type: "Convolution" | |
| bottom: "conv4_7/linear" | |
| top: "conv5_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu5_1/expand" | |
| type: "ReLU" | |
| bottom: "conv5_1/expand" | |
| top: "conv5_1/expand" | |
| } | |
| layer { | |
| name: "conv5_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv5_1/expand" | |
| top: "conv5_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu5_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_1/dwise" | |
| top: "conv5_1/dwise" | |
| } | |
| layer { | |
| name: "conv5_1/linear" | |
| type: "Convolution" | |
| bottom: "conv5_1/dwise" | |
| top: "conv5_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_5_1" | |
| type: "Eltwise" | |
| bottom: "conv4_7/linear" | |
| bottom: "conv5_1/linear" | |
| top: "block_5_1" | |
| } | |
| layer { | |
| name: "conv5_2/expand" | |
| type: "Convolution" | |
| bottom: "block_5_1" | |
| top: "conv5_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu5_2/expand" | |
| type: "ReLU" | |
| bottom: "conv5_2/expand" | |
| top: "conv5_2/expand" | |
| } | |
| layer { | |
| name: "conv5_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv5_2/expand" | |
| top: "conv5_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu5_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_2/dwise" | |
| top: "conv5_2/dwise" | |
| } | |
| layer { | |
| name: "conv5_2/linear" | |
| type: "Convolution" | |
| bottom: "conv5_2/dwise" | |
| top: "conv5_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_5_2" | |
| type: "Eltwise" | |
| bottom: "block_5_1" | |
| bottom: "conv5_2/linear" | |
| top: "block_5_2" | |
| } | |
| layer { | |
| name: "conv5_3/expand" | |
| type: "Convolution" | |
| bottom: "block_5_2" | |
| top: "conv5_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu5_3/expand" | |
| type: "ReLU" | |
| bottom: "conv5_3/expand" | |
| top: "conv5_3/expand" | |
| } | |
| layer { | |
| name: "conv5_3/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv5_3/expand" | |
| top: "conv5_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 576 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 576 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu5_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv5_3/dwise" | |
| top: "conv5_3/dwise" | |
| } | |
| layer { | |
| name: "conv5_3/linear" | |
| type: "Convolution" | |
| bottom: "conv5_3/dwise" | |
| top: "conv5_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_1/expand" | |
| type: "Convolution" | |
| bottom: "conv5_3/linear" | |
| top: "conv6_1/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6_1/expand" | |
| type: "ReLU" | |
| bottom: "conv6_1/expand" | |
| top: "conv6_1/expand" | |
| } | |
| layer { | |
| name: "conv6_1/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6_1/expand" | |
| top: "conv6_1/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu6_1/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_1/dwise" | |
| top: "conv6_1/dwise" | |
| } | |
| layer { | |
| name: "conv6_1/linear" | |
| type: "Convolution" | |
| bottom: "conv6_1/dwise" | |
| top: "conv6_1/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_6_1" | |
| type: "Eltwise" | |
| bottom: "conv5_3/linear" | |
| bottom: "conv6_1/linear" | |
| top: "block_6_1" | |
| } | |
| layer { | |
| name: "conv6_2/expand" | |
| type: "Convolution" | |
| bottom: "block_6_1" | |
| top: "conv6_2/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6_2/expand" | |
| type: "ReLU" | |
| bottom: "conv6_2/expand" | |
| top: "conv6_2/expand" | |
| } | |
| layer { | |
| name: "conv6_2/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6_2/expand" | |
| top: "conv6_2/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu6_2/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_2/dwise" | |
| top: "conv6_2/dwise" | |
| } | |
| layer { | |
| name: "conv6_2/linear" | |
| type: "Convolution" | |
| bottom: "conv6_2/dwise" | |
| top: "conv6_2/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 160 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "block_6_2" | |
| type: "Eltwise" | |
| bottom: "block_6_1" | |
| bottom: "conv6_2/linear" | |
| top: "block_6_2" | |
| } | |
| layer { | |
| name: "conv6_3/expand" | |
| type: "Convolution" | |
| bottom: "block_6_2" | |
| top: "conv6_3/expand" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6_3/expand" | |
| type: "ReLU" | |
| bottom: "conv6_3/expand" | |
| top: "conv6_3/expand" | |
| } | |
| layer { | |
| name: "conv6_3/dwise" | |
| type: "DepthwiseConvolution" | |
| bottom: "conv6_3/expand" | |
| top: "conv6_3/dwise" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 960 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 960 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| engine: CAFFE | |
| } | |
| } | |
| layer { | |
| name: "relu6_3/dwise" | |
| type: "ReLU" | |
| bottom: "conv6_3/dwise" | |
| top: "conv6_3/dwise" | |
| } | |
| layer { | |
| name: "conv6_3/linear" | |
| type: "Convolution" | |
| bottom: "conv6_3/dwise" | |
| top: "conv6_3/linear" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 320 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_4" | |
| type: "Convolution" | |
| bottom: "conv6_3/linear" | |
| top: "conv6_4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1280 | |
| bias_term: true | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6_4" | |
| type: "ReLU" | |
| bottom: "conv6_4" | |
| top: "conv6_4" | |
| } | |
| ######################### | |
| layer { | |
| name: "conv_points_v4" | |
| type: "Convolution" | |
| bottom: "conv6_4" | |
| top: "conv_points" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 136 | |
| bias_term: true | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu_points" | |
| type: "ReLU" | |
| bottom: "conv_points" | |
| top: "conv_points" | |
| } | |
| layer { | |
| name: "output_points_68_v2" | |
| type: "InnerProduct" | |
| bottom: "conv_points" | |
| top: "output_points" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| } | |
| inner_product_param { | |
| num_output: 136 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } | |
| ##################### | |
| layer { | |
| name: "conv_aspects_v4" | |
| type: "Convolution" | |
| bottom: "conv6_4" | |
| top: "conv_aspects" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 3 | |
| bias_term: true | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu_aspects" | |
| type: "ReLU" | |
| bottom: "conv_aspects" | |
| top: "conv_aspects" | |
| } | |
| layer { | |
| name: "output_aspects_3_v2" | |
| type: "InnerProduct" | |
| bottom: "conv_aspects" | |
| top: "output_aspects" | |
| param { | |
| lr_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| } | |
| inner_product_param { | |
| num_output: 3 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| } | |
| } | |
| } |
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