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July 14, 2016 17:32
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| name: "GoogLeNet" | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 224 | |
| input_dim: 224 | |
| layers { | |
| name: "conv1" | |
| type: CONVOLUTION | |
| bottom: "data" | |
| top: "conv1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 7 | |
| stride: 2 | |
| pad: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.015 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu1" | |
| type: RELU | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layers { | |
| name: "pool1" | |
| type: POOLING | |
| bottom: "conv1" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| layers { | |
| name: "norm1" | |
| type: LRN | |
| bottom: "pool1" | |
| top: "norm1" | |
| lrn_param { | |
| local_size: 5 | |
| alpha: 0.0001 | |
| beta: 0.75 | |
| } | |
| } | |
| layers { | |
| name: "reduction2" | |
| type: CONVOLUTION | |
| bottom: "norm1" | |
| top: "reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_reduction2" | |
| type: RELU | |
| bottom: "reduction2" | |
| top: "reduction2" | |
| } | |
| layers { | |
| name: "conv2" | |
| type: CONVOLUTION | |
| bottom: "reduction2" | |
| top: "conv2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 1 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.02 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu2" | |
| type: RELU | |
| bottom: "conv2" | |
| top: "conv2" | |
| } | |
| layers { | |
| name: "norm2" | |
| type: LRN | |
| bottom: "conv2" | |
| top: "norm2" | |
| lrn_param { | |
| local_size: 5 | |
| alpha: 0.0001 | |
| beta: 0.75 | |
| } | |
| } | |
| layers { | |
| name: "pool2" | |
| type: POOLING | |
| bottom: "norm2" | |
| top: "pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| # Inception module 1 *************** | |
| layers { | |
| name: "icp1_reduction1" | |
| type: CONVOLUTION | |
| bottom: "pool2" | |
| top: "icp1_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 96 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp1_reduction1" | |
| type: RELU | |
| bottom: "icp1_reduction1" | |
| top: "icp1_reduction1" | |
| } | |
| layers { | |
| name: "icp1_reduction2" | |
| type: CONVOLUTION | |
| bottom: "pool2" | |
| top: "icp1_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 16 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp1_reduction2" | |
| type: RELU | |
| bottom: "icp1_reduction2" | |
| top: "icp1_reduction2" | |
| } | |
| layers { | |
| name: "icp1_pool" | |
| type: POOLING | |
| bottom: "pool2" | |
| top: "icp1_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp1_out0" | |
| type: CONVOLUTION | |
| bottom: "pool2" | |
| top: "icp1_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp1_out0" | |
| type: RELU | |
| bottom: "icp1_out0" | |
| top: "icp1_out0" | |
| } | |
| layers { | |
| name: "icp1_out1" | |
| type: CONVOLUTION | |
| bottom: "icp1_reduction1" | |
| top: "icp1_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp1_out1" | |
| type: RELU | |
| bottom: "icp1_out1" | |
| top: "icp1_out1" | |
| } | |
| layers { | |
| name: "icp1_out2" | |
| type: CONVOLUTION | |
| bottom: "icp1_reduction2" | |
| top: "icp1_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 32 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp1_out2" | |
| type: RELU | |
| bottom: "icp1_out2" | |
| top: "icp1_out2" | |
| } | |
| layers { | |
| name: "icp1_out3" | |
| type: CONVOLUTION | |
| bottom: "icp1_pool" | |
| top: "icp1_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp1_out3" | |
| type: RELU | |
| bottom: "icp1_out3" | |
| top: "icp1_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp2_in" | |
| type: CONCAT | |
| bottom: "icp1_out0" | |
| bottom: "icp1_out1" | |
| bottom: "icp1_out2" | |
| bottom: "icp1_out3" | |
| top: "icp2_in" | |
| } | |
| # Inception module 2 *************** | |
| layers { | |
| name: "icp2_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp2_in" | |
| top: "icp2_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp2_reduction1" | |
| type: RELU | |
| bottom: "icp2_reduction1" | |
| top: "icp2_reduction1" | |
| } | |
| layers { | |
| name: "icp2_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp2_in" | |
| top: "icp2_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp2_reduction2" | |
| type: RELU | |
| bottom: "icp2_reduction2" | |
| top: "icp2_reduction2" | |
| } | |
| layers { | |
| name: "icp2_pool" | |
| type: POOLING | |
| bottom: "icp2_in" | |
| top: "icp2_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp2_out0" | |
| type: CONVOLUTION | |
| bottom: "icp2_in" | |
| top: "icp2_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp2_out0" | |
| type: RELU | |
| bottom: "icp2_out0" | |
| top: "icp2_out0" | |
| } | |
| layers { | |
| name: "icp2_out1" | |
| type: CONVOLUTION | |
| bottom: "icp2_reduction1" | |
| top: "icp2_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 192 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp2_out1" | |
| type: RELU | |
| bottom: "icp2_out1" | |
| top: "icp2_out1" | |
| } | |
| layers { | |
| name: "icp2_out2" | |
| type: CONVOLUTION | |
| bottom: "icp2_reduction2" | |
| top: "icp2_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 96 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp2_out2" | |
| type: RELU | |
| bottom: "icp2_out2" | |
| top: "icp2_out2" | |
| } | |
| layers { | |
| name: "icp2_out3" | |
| type: CONVOLUTION | |
| bottom: "icp2_pool" | |
| top: "icp2_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp2_out3" | |
| type: RELU | |
| bottom: "icp2_out3" | |
| top: "icp2_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp2_out" | |
| type: CONCAT | |
| bottom: "icp2_out0" | |
| bottom: "icp2_out1" | |
| bottom: "icp2_out2" | |
| bottom: "icp2_out3" | |
| top: "icp2_out" | |
| } | |
| layers { | |
| name: "icp3_in" | |
| type: POOLING | |
| bottom: "icp2_out" | |
| top: "icp3_in" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| # Inception module 3 *************** | |
| layers { | |
| name: "icp3_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp3_in" | |
| top: "icp3_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 96 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp3_reduction1" | |
| type: RELU | |
| bottom: "icp3_reduction1" | |
| top: "icp3_reduction1" | |
| } | |
| layers { | |
| name: "icp3_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp3_in" | |
| top: "icp3_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 16 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp3_reduction2" | |
| type: RELU | |
| bottom: "icp3_reduction2" | |
| top: "icp3_reduction2" | |
| } | |
| layers { | |
| name: "icp3_pool" | |
| type: POOLING | |
| bottom: "icp3_in" | |
| top: "icp3_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp3_out0" | |
| type: CONVOLUTION | |
| bottom: "icp3_in" | |
| top: "icp3_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp3_out0" | |
| type: RELU | |
| bottom: "icp3_out0" | |
| top: "icp3_out0" | |
| } | |
| layers { | |
| name: "icp3_out1" | |
| type: CONVOLUTION | |
| bottom: "icp3_reduction1" | |
| top: "icp3_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 208 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp3_out1" | |
| type: RELU | |
| bottom: "icp3_out1" | |
| top: "icp3_out1" | |
| } | |
| layers { | |
| name: "icp3_out2" | |
| type: CONVOLUTION | |
| bottom: "icp3_reduction2" | |
| top: "icp3_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 48 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp3_out2" | |
| type: RELU | |
| bottom: "icp3_out2" | |
| top: "icp3_out2" | |
| } | |
| layers { | |
| name: "icp3_out3" | |
| type: CONVOLUTION | |
| bottom: "icp3_pool" | |
| top: "icp3_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp3_out3" | |
| type: RELU | |
| bottom: "icp3_out3" | |
| top: "icp3_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp3_out" | |
| type: CONCAT | |
| bottom: "icp3_out0" | |
| bottom: "icp3_out1" | |
| bottom: "icp3_out2" | |
| bottom: "icp3_out3" | |
| top: "icp3_out" | |
| } | |
| # first classification branch ************ | |
| layers { | |
| name: "cls1_pool" | |
| type: POOLING | |
| bottom: "icp3_out" | |
| top: "cls1_pool" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 5 | |
| stride: 3 | |
| pad: 0 | |
| # this padding is somewhat special | |
| } | |
| } | |
| layers { | |
| name: "cls1_reduction_pose" | |
| type: CONVOLUTION | |
| bottom: "cls1_pool" | |
| top: "cls1_reduction" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_cls1_reduction" | |
| type: RELU | |
| bottom: "cls1_reduction" | |
| top: "cls1_reduction" | |
| } | |
| layers { | |
| name: "cls1_fc1_pose" | |
| type: INNER_PRODUCT | |
| bottom: "cls1_reduction" | |
| top: "cls1_fc1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 1024 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_cls1_fc1" | |
| type: RELU | |
| bottom: "cls1_fc1" | |
| top: "cls1_fc1" | |
| } | |
| layers { | |
| name: "cls1_drop" | |
| type: DROPOUT | |
| bottom: "cls1_fc1" | |
| top: "cls1_fc1" | |
| dropout_param { | |
| dropout_ratio: 0.7 | |
| } | |
| } | |
| layers { | |
| name: "cls1_fc_pose_xyz" | |
| type: INNER_PRODUCT | |
| bottom: "cls1_fc1" | |
| top: "cls1_fc_xyz" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.5 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "cls1_fc_pose_wpqr" | |
| type: INNER_PRODUCT | |
| bottom: "cls1_fc1" | |
| top: "cls1_fc_wpqr" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 4 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| # Inception module 4 *************** | |
| layers { | |
| name: "icp4_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp3_out" | |
| top: "icp4_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 112 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp4_reduction1" | |
| type: RELU | |
| bottom: "icp4_reduction1" | |
| top: "icp4_reduction1" | |
| } | |
| layers { | |
| name: "icp4_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp3_out" | |
| top: "icp4_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 24 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp4_reduction2" | |
| type: RELU | |
| bottom: "icp4_reduction2" | |
| top: "icp4_reduction2" | |
| } | |
| layers { | |
| name: "icp4_pool" | |
| type: POOLING | |
| bottom: "icp3_out" | |
| top: "icp4_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp4_out0" | |
| type: CONVOLUTION | |
| bottom: "icp3_out" | |
| top: "icp4_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 160 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp4_out0" | |
| type: RELU | |
| bottom: "icp4_out0" | |
| top: "icp4_out0" | |
| } | |
| layers { | |
| name: "icp4_out1" | |
| type: CONVOLUTION | |
| bottom: "icp4_reduction1" | |
| top: "icp4_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 224 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp4_out1" | |
| type: RELU | |
| bottom: "icp4_out1" | |
| top: "icp4_out1" | |
| } | |
| layers { | |
| name: "icp4_out2" | |
| type: CONVOLUTION | |
| bottom: "icp4_reduction2" | |
| top: "icp4_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp4_out2" | |
| type: RELU | |
| bottom: "icp4_out2" | |
| top: "icp4_out2" | |
| } | |
| layers { | |
| name: "icp4_out3" | |
| type: CONVOLUTION | |
| bottom: "icp4_pool" | |
| top: "icp4_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp4_out3" | |
| type: RELU | |
| bottom: "icp4_out3" | |
| top: "icp4_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp4_out" | |
| type: CONCAT | |
| bottom: "icp4_out0" | |
| bottom: "icp4_out1" | |
| bottom: "icp4_out2" | |
| bottom: "icp4_out3" | |
| top: "icp4_out" | |
| } | |
| # Inception module 5 *************** | |
| layers { | |
| name: "icp5_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp4_out" | |
| top: "icp5_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp5_reduction1" | |
| type: RELU | |
| bottom: "icp5_reduction1" | |
| top: "icp5_reduction1" | |
| } | |
| layers { | |
| name: "icp5_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp4_out" | |
| top: "icp5_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 24 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp5_reduction2" | |
| type: RELU | |
| bottom: "icp5_reduction2" | |
| top: "icp5_reduction2" | |
| } | |
| layers { | |
| name: "icp5_pool" | |
| type: POOLING | |
| bottom: "icp4_out" | |
| top: "icp5_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp5_out0" | |
| type: CONVOLUTION | |
| bottom: "icp4_out" | |
| top: "icp5_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp5_out0" | |
| type: RELU | |
| bottom: "icp5_out0" | |
| top: "icp5_out0" | |
| } | |
| layers { | |
| name: "icp5_out1" | |
| type: CONVOLUTION | |
| bottom: "icp5_reduction1" | |
| top: "icp5_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp5_out1" | |
| type: RELU | |
| bottom: "icp5_out1" | |
| top: "icp5_out1" | |
| } | |
| layers { | |
| name: "icp5_out2" | |
| type: CONVOLUTION | |
| bottom: "icp5_reduction2" | |
| top: "icp5_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp5_out2" | |
| type: RELU | |
| bottom: "icp5_out2" | |
| top: "icp5_out2" | |
| } | |
| layers { | |
| name: "icp5_out3" | |
| type: CONVOLUTION | |
| bottom: "icp5_pool" | |
| top: "icp5_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp5_out3" | |
| type: RELU | |
| bottom: "icp5_out3" | |
| top: "icp5_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp5_out" | |
| type: CONCAT | |
| bottom: "icp5_out0" | |
| bottom: "icp5_out1" | |
| bottom: "icp5_out2" | |
| bottom: "icp5_out3" | |
| top: "icp5_out" | |
| } | |
| # Inception module 6 *************** | |
| layers { | |
| name: "icp6_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp5_out" | |
| top: "icp6_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 144 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp6_reduction1" | |
| type: RELU | |
| bottom: "icp6_reduction1" | |
| top: "icp6_reduction1" | |
| } | |
| layers { | |
| name: "icp6_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp5_out" | |
| top: "icp6_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp6_reduction2" | |
| type: RELU | |
| bottom: "icp6_reduction2" | |
| top: "icp6_reduction2" | |
| } | |
| layers { | |
| name: "icp6_pool" | |
| type: POOLING | |
| bottom: "icp5_out" | |
| top: "icp6_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp6_out0" | |
| type: CONVOLUTION | |
| bottom: "icp5_out" | |
| top: "icp6_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 112 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp6_out0" | |
| type: RELU | |
| bottom: "icp6_out0" | |
| top: "icp6_out0" | |
| } | |
| layers { | |
| name: "icp6_out1" | |
| type: CONVOLUTION | |
| bottom: "icp6_reduction1" | |
| top: "icp6_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 288 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp6_out1" | |
| type: RELU | |
| bottom: "icp6_out1" | |
| top: "icp6_out1" | |
| } | |
| layers { | |
| name: "icp6_out2" | |
| type: CONVOLUTION | |
| bottom: "icp6_reduction2" | |
| top: "icp6_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp6_out2" | |
| type: RELU | |
| bottom: "icp6_out2" | |
| top: "icp6_out2" | |
| } | |
| layers { | |
| name: "icp6_out3" | |
| type: CONVOLUTION | |
| bottom: "icp6_pool" | |
| top: "icp6_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp6_out3" | |
| type: RELU | |
| bottom: "icp6_out3" | |
| top: "icp6_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp6_out" | |
| type: CONCAT | |
| bottom: "icp6_out0" | |
| bottom: "icp6_out1" | |
| bottom: "icp6_out2" | |
| bottom: "icp6_out3" | |
| top: "icp6_out" | |
| } | |
| # second classification branch ************ | |
| layers { | |
| name: "cls2_pool" | |
| type: POOLING | |
| bottom: "icp6_out" | |
| top: "cls2_pool" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 5 | |
| stride: 3 | |
| pad: 0 | |
| # this padding is somewhat special | |
| } | |
| } | |
| layers { | |
| name: "cls2_reduction_pose" | |
| type: CONVOLUTION | |
| bottom: "cls2_pool" | |
| top: "cls2_reduction" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_cls2_reduction" | |
| type: RELU | |
| bottom: "cls2_reduction" | |
| top: "cls2_reduction" | |
| } | |
| layers { | |
| name: "cls2_fc1" | |
| type: INNER_PRODUCT | |
| bottom: "cls2_reduction" | |
| top: "cls2_fc1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 1024 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_cls2_fc1" | |
| type: RELU | |
| bottom: "cls2_fc1" | |
| top: "cls2_fc1" | |
| } | |
| layers { | |
| name: "cls2_drop" | |
| type: DROPOUT | |
| bottom: "cls2_fc1" | |
| top: "cls2_fc1" | |
| dropout_param { | |
| dropout_ratio: 0.7 | |
| } | |
| } | |
| layers { | |
| name: "cls2_fc_pose_xyz" | |
| type: INNER_PRODUCT | |
| bottom: "cls2_fc1" | |
| top: "cls2_fc_xyz" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.5 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "cls2_fc_pose_wpqr" | |
| type: INNER_PRODUCT | |
| bottom: "cls2_fc1" | |
| top: "cls2_fc_wpqr" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 4 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| # Inception module 7 *************** | |
| layers { | |
| name: "icp7_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp6_out" | |
| top: "icp7_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 160 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp7_reduction1" | |
| type: RELU | |
| bottom: "icp7_reduction1" | |
| top: "icp7_reduction1" | |
| } | |
| layers { | |
| name: "icp7_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp6_out" | |
| top: "icp7_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp7_reduction2" | |
| type: RELU | |
| bottom: "icp7_reduction2" | |
| top: "icp7_reduction2" | |
| } | |
| layers { | |
| name: "icp7_pool" | |
| type: POOLING | |
| bottom: "icp6_out" | |
| top: "icp7_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp7_out0" | |
| type: CONVOLUTION | |
| bottom: "icp6_out" | |
| top: "icp7_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp7_out0" | |
| type: RELU | |
| bottom: "icp7_out0" | |
| top: "icp7_out0" | |
| } | |
| layers { | |
| name: "icp7_out1" | |
| type: CONVOLUTION | |
| bottom: "icp7_reduction1" | |
| top: "icp7_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 320 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp7_out1" | |
| type: RELU | |
| bottom: "icp7_out1" | |
| top: "icp7_out1" | |
| } | |
| layers { | |
| name: "icp7_out2" | |
| type: CONVOLUTION | |
| bottom: "icp7_reduction2" | |
| top: "icp7_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp7_out2" | |
| type: RELU | |
| bottom: "icp7_out2" | |
| top: "icp7_out2" | |
| } | |
| layers { | |
| name: "icp7_out3" | |
| type: CONVOLUTION | |
| bottom: "icp7_pool" | |
| top: "icp7_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp7_out3" | |
| type: RELU | |
| bottom: "icp7_out3" | |
| top: "icp7_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp7_out" | |
| type: CONCAT | |
| bottom: "icp7_out0" | |
| bottom: "icp7_out1" | |
| bottom: "icp7_out2" | |
| bottom: "icp7_out3" | |
| top: "icp7_out" | |
| } | |
| layers { | |
| name: "icp8_in" | |
| type: POOLING | |
| bottom: "icp7_out" | |
| top: "icp8_in" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| # Inception module 8 *************** | |
| layers { | |
| name: "icp8_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp8_in" | |
| top: "icp8_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 160 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp8_reduction1" | |
| type: RELU | |
| bottom: "icp8_reduction1" | |
| top: "icp8_reduction1" | |
| } | |
| layers { | |
| name: "icp8_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp8_in" | |
| top: "icp8_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 32 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp8_reduction2" | |
| type: RELU | |
| bottom: "icp8_reduction2" | |
| top: "icp8_reduction2" | |
| } | |
| layers { | |
| name: "icp8_pool" | |
| type: POOLING | |
| bottom: "icp8_in" | |
| top: "icp8_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp8_out0" | |
| type: CONVOLUTION | |
| bottom: "icp8_in" | |
| top: "icp8_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 256 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp8_out0" | |
| type: RELU | |
| bottom: "icp8_out0" | |
| top: "icp8_out0" | |
| } | |
| layers { | |
| name: "icp8_out1" | |
| type: CONVOLUTION | |
| bottom: "icp8_reduction1" | |
| top: "icp8_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 320 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp8_out1" | |
| type: RELU | |
| bottom: "icp8_out1" | |
| top: "icp8_out1" | |
| } | |
| layers { | |
| name: "icp8_out2" | |
| type: CONVOLUTION | |
| bottom: "icp8_reduction2" | |
| top: "icp8_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp8_out2" | |
| type: RELU | |
| bottom: "icp8_out2" | |
| top: "icp8_out2" | |
| } | |
| layers { | |
| name: "icp8_out3" | |
| type: CONVOLUTION | |
| bottom: "icp8_pool" | |
| top: "icp8_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp8_out3" | |
| type: RELU | |
| bottom: "icp8_out3" | |
| top: "icp8_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp8_out" | |
| type: CONCAT | |
| bottom: "icp8_out0" | |
| bottom: "icp8_out1" | |
| bottom: "icp8_out2" | |
| bottom: "icp8_out3" | |
| top: "icp8_out" | |
| } | |
| # Inception module 9 *************** | |
| layers { | |
| name: "icp9_reduction1" | |
| type: CONVOLUTION | |
| bottom: "icp8_out" | |
| top: "icp9_reduction1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 192 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp9_reduction1" | |
| type: RELU | |
| bottom: "icp9_reduction1" | |
| top: "icp9_reduction1" | |
| } | |
| layers { | |
| name: "icp9_reduction2" | |
| type: CONVOLUTION | |
| bottom: "icp8_out" | |
| top: "icp9_reduction2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 48 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp9_reduction2" | |
| type: RELU | |
| bottom: "icp9_reduction2" | |
| top: "icp9_reduction2" | |
| } | |
| layers { | |
| name: "icp9_pool" | |
| type: POOLING | |
| bottom: "icp8_out" | |
| top: "icp9_pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 1 | |
| pad: 1 | |
| } | |
| } | |
| # *********** | |
| layers { | |
| name: "icp9_out0" | |
| type: CONVOLUTION | |
| bottom: "icp8_out" | |
| top: "icp9_out0" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 384 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp9_out0" | |
| type: RELU | |
| bottom: "icp9_out0" | |
| top: "icp9_out0" | |
| } | |
| layers { | |
| name: "icp9_out1" | |
| type: CONVOLUTION | |
| bottom: "icp9_reduction1" | |
| top: "icp9_out1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 384 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.04 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp9_out1" | |
| type: RELU | |
| bottom: "icp9_out1" | |
| top: "icp9_out1" | |
| } | |
| layers { | |
| name: "icp9_out2" | |
| type: CONVOLUTION | |
| bottom: "icp9_reduction2" | |
| top: "icp9_out2" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 2 | |
| kernel_size: 5 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.08 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp9_out2" | |
| type: RELU | |
| bottom: "icp9_out2" | |
| top: "icp9_out2" | |
| } | |
| layers { | |
| name: "icp9_out3" | |
| type: CONVOLUTION | |
| bottom: "icp9_pool" | |
| top: "icp9_out3" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_icp9_out3" | |
| type: RELU | |
| bottom: "icp9_out3" | |
| top: "icp9_out3" | |
| } | |
| # Concat them together | |
| layers { | |
| name: "icp9_out" | |
| type: CONCAT | |
| bottom: "icp9_out0" | |
| bottom: "icp9_out1" | |
| bottom: "icp9_out2" | |
| bottom: "icp9_out3" | |
| top: "icp9_out" | |
| } | |
| # third classification branch | |
| layers { | |
| name: "cls3_pool" | |
| type: POOLING | |
| bottom: "icp9_out" | |
| top: "cls3_pool" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 7 | |
| stride: 1 | |
| pad: 0 | |
| # This padding is somewhat special | |
| } | |
| } | |
| layers { | |
| name: "cls3_fc1_pose" | |
| type: INNER_PRODUCT | |
| bottom: "cls3_pool" | |
| top: "cls3_fc1" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 2048 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "relu_cls3_fc1_2" | |
| type: RELU | |
| bottom: "cls3_fc1" | |
| top: "cls3_fc1" | |
| } | |
| layers { | |
| name: "cls3_drop" | |
| type: DROPOUT | |
| bottom: "cls3_fc1" | |
| top: "cls3_fc1" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layers { | |
| name: "cls3_fc_pose_xyz" | |
| type: INNER_PRODUCT | |
| bottom: "cls3_fc1" | |
| top: "cls3_fc_xyz" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.5 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layers { | |
| name: "cls3_fc_pose_wpqr" | |
| type: INNER_PRODUCT | |
| bottom: "cls3_fc1" | |
| top: "cls3_fc_wpqr" | |
| blobs_lr: 1 | |
| blobs_lr: 2 | |
| weight_decay: 1 | |
| weight_decay: 0 | |
| inner_product_param { | |
| num_output: 4 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } |
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Hi Colegleason,
I am a new user and I have trained the posenet model by using my own dataset and now I want to get predictions from this model.
Can you please advise me how to achieve that?
Regards