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| name: "DFA_lower_cascade" | |
| layer { | |
| name: "data" | |
| type: "Input" | |
| top: "data" | |
| input_param { shape: { dim: 1 dim: 3 dim: 224 dim: 224 } } | |
| } | |
| layer { | |
| name: "last_stage_data" | |
| type: "Input" | |
| top: "prediction" | |
| input_param { shape: { dim: 1 dim: 1 dim: 1 dim: 8 } } | |
| } | |
| # Processing Layers | |
| layer { | |
| bottom: "data" | |
| top: "conv1_1" | |
| name: "conv1_1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| name: "relu1_1" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv1_1" | |
| top: "conv1_2" | |
| name: "conv1_2" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| name: "relu1_2" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv1_2" | |
| top: "pool1" | |
| name: "pool1" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "pool1" | |
| top: "conv2_1" | |
| name: "conv2_1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| name: "relu2_1" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv2_1" | |
| top: "conv2_2" | |
| name: "conv2_2" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| name: "relu2_2" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv2_2" | |
| top: "pool2" | |
| name: "pool2" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "pool2" | |
| top: "conv3_1" | |
| name: "conv3_1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| name: "relu3_1" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv3_1" | |
| top: "conv3_2" | |
| name: "conv3_2" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv3_2" | |
| top: "conv3_2" | |
| name: "relu3_2" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv3_2" | |
| top: "conv3_3" | |
| name: "conv3_3" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv3_3" | |
| top: "conv3_3" | |
| name: "relu3_3" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv3_3" | |
| top: "pool3" | |
| name: "pool3" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "pool3" | |
| top: "conv4_1" | |
| name: "conv4_1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| name: "relu4_1" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv4_1" | |
| top: "conv4_2" | |
| name: "conv4_2" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| name: "relu4_2" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv4_2" | |
| top: "conv4_3" | |
| name: "conv4_3" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv4_3" | |
| top: "conv4_3" | |
| name: "relu4_3" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv4_3" | |
| top: "pool4" | |
| name: "pool4" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "pool4" | |
| top: "conv5_1" | |
| name: "conv5_1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv5_1" | |
| top: "conv5_1" | |
| name: "relu5_1" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv5_1" | |
| top: "conv5_2" | |
| name: "conv5_2" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv5_2" | |
| top: "conv5_2" | |
| name: "relu5_2" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv5_2" | |
| top: "conv5_3" | |
| name: "conv5_3" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| bottom: "conv5_3" | |
| top: "conv5_3" | |
| name: "relu5_3" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv5_3" | |
| top: "pool5" | |
| name: "pool5" | |
| type: "Pooling" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "pool5" | |
| top: "fc6" | |
| name: "fc6" | |
| type: "InnerProduct" | |
| inner_product_param { | |
| num_output: 4096 | |
| } | |
| } | |
| # last stage prediction | |
| layer { | |
| bottom: "prediction" | |
| top: "fc_pre" | |
| name: "fc_pre" | |
| type: "InnerProduct" | |
| inner_product_param { | |
| num_output: 512 | |
| } | |
| } | |
| # Concat Layer | |
| layer { | |
| name: "fc6_pre" | |
| type: "Concat" | |
| top: "fc6_pre" | |
| bottom: "fc6" | |
| bottom: "fc_pre" | |
| } | |
| layer { | |
| bottom: "fc6_pre" | |
| top: "fc6_pre" | |
| name: "relu6" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "fc6_pre" | |
| top: "fc6_pre" | |
| name: "drop6" | |
| type: "Dropout" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| bottom: "fc6_pre" | |
| top: "fc7_pre" | |
| name: "fc7_pre" | |
| type: "InnerProduct" | |
| inner_product_param { | |
| num_output: 4096 | |
| } | |
| } | |
| layer { | |
| bottom: "fc7_pre" | |
| top: "fc7_pre" | |
| name: "relu7" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "fc7_pre" | |
| top: "fc7_pre" | |
| name: "drop7" | |
| type: "Dropout" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| # Target Layers | |
| layer { | |
| name: "fc8_hardlabel" | |
| type: "InnerProduct" | |
| bottom: "fc7_pre" | |
| top: "fc8_hardlabel" | |
| inner_product_param { | |
| num_output:20 | |
| } | |
| } | |
| layer { | |
| name: "fc8_landmarks" | |
| type: "InnerProduct" | |
| bottom: "fc7_pre" | |
| top: "fc8_landmarks" | |
| inner_product_param { | |
| num_output: 8 | |
| } | |
| } | |
| layer { | |
| name: "fc8_visibility_1" | |
| type: "InnerProduct" | |
| bottom: "fc7_pre" | |
| top: "fc8_visibility_1" | |
| inner_product_param { | |
| num_output:3 | |
| } | |
| } | |
| layer { | |
| name: "fc8_visibility_2" | |
| type: "InnerProduct" | |
| bottom: "fc7_pre" | |
| top: "fc8_visibility_2" | |
| inner_product_param { | |
| num_output: 3 | |
| } | |
| } | |
| layer { | |
| name: "fc8_visibility_3" | |
| type: "InnerProduct" | |
| bottom: "fc7_pre" | |
| top: "fc8_visibility_3" | |
| inner_product_param { | |
| num_output: 3 | |
| } | |
| } | |
| layer { | |
| name: "fc8_visibility_4" | |
| type: "InnerProduct" | |
| bottom: "fc7_pre" | |
| top: "fc8_visibility_4" | |
| inner_product_param { | |
| num_output: 3 | |
| } | |
| } | |
| # Concat Layer | |
| layer { | |
| name: "fc8" | |
| type: "Concat" | |
| top: "fc8" | |
| bottom: "fc8_landmarks" | |
| bottom: "fc8_visibility_1" | |
| bottom: "fc8_visibility_2" | |
| bottom: "fc8_visibility_3" | |
| bottom: "fc8_visibility_4" | |
| } |
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