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April 22, 2020 02:00
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RTNet
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| name: "RTNet" | |
| layer{ | |
| type: "Input" | |
| name: "input" | |
| top: "img" | |
| top: "im_info" | |
| input_param{ | |
| shape { | |
| dim: 1 | |
| dim: 270 | |
| dim: 270 | |
| dim: 3 | |
| } | |
| shape { | |
| dim: 1 | |
| dim: 6 | |
| dim: 1 | |
| dim: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| type: "Permute" | |
| name: "permute" | |
| bottom: "img" | |
| top: "data" | |
| permute_param{ | |
| order: 0 | |
| order: 3 | |
| order: 1 | |
| order: 2 | |
| } | |
| } | |
| # ------------------------ conv1 ----------------------------- | |
| layer { | |
| bottom: "data" | |
| top: "conv1" | |
| name: "conv1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 7 | |
| pad: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "conv1" | |
| name: "bn_conv1" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "conv1" | |
| name: "scale_conv1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "conv1" | |
| name: "conv1_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "pool1" | |
| name: "pool1" | |
| type: "Pooling" | |
| pooling_param { | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 2 | |
| pool: MAX | |
| round_mode: 1 | |
| } | |
| } | |
| layer { | |
| bottom: "pool1" | |
| top: "res2a_branch1" | |
| name: "res2a_branch1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch1" | |
| top: "res2a_branch1" | |
| name: "bn2a_branch1" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch1" | |
| top: "res2a_branch1" | |
| name: "scale2a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "pool1" | |
| top: "res2a_branch2a" | |
| name: "res2a_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2a" | |
| name: "bn2a_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2a" | |
| name: "scale2a_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2a" | |
| name: "res2a_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2b" | |
| name: "res2a_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2b" | |
| name: "bn2a_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2b" | |
| name: "scale2a_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch1" | |
| bottom: "res2a_branch2b" | |
| top: "res2a" | |
| name: "res2a" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res2a" | |
| top: "res2a" | |
| name: "res2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2a" | |
| top: "res2b_branch2a" | |
| name: "res2b_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2a" | |
| name: "bn2b_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2a" | |
| name: "scale2b_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2a" | |
| name: "res2b_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2b" | |
| name: "res2b_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2b" | |
| name: "bn2b_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2b" | |
| name: "scale2b_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2a" | |
| bottom: "res2b_branch2b" | |
| top: "res2b" | |
| name: "res2b" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res2b" | |
| top: "res2b" | |
| name: "res2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2b" | |
| top: "res2c_branch2a" | |
| name: "res2c_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2a" | |
| name: "bn2c_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2a" | |
| name: "scale2c_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2a" | |
| name: "res2c_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2b" | |
| name: "res2c_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2b" | |
| name: "bn2c_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2b" | |
| name: "scale2c_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2b" | |
| bottom: "res2c_branch2b" | |
| top: "res2c" | |
| name: "res2c" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res2c" | |
| top: "res2c" | |
| name: "res2c_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2c" | |
| top: "res3a_branch1" | |
| name: "res3a_branch1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch1" | |
| top: "res3a_branch1" | |
| name: "bn3a_branch1" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch1" | |
| top: "res3a_branch1" | |
| name: "scale3a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res2c" | |
| top: "res3a_branch2a" | |
| name: "res3a_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2a" | |
| name: "bn3a_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2a" | |
| name: "scale3a_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2a" | |
| name: "res3a_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2b" | |
| name: "res3a_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2b" | |
| name: "bn3a_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2b" | |
| name: "scale3a_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch1" | |
| bottom: "res3a_branch2b" | |
| top: "res3a" | |
| name: "res3a" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res3a" | |
| top: "res3a" | |
| name: "res3a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3a" | |
| top: "res3b_branch2a" | |
| name: "res3b_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2a" | |
| name: "bn3b_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2a" | |
| name: "scale3b_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2a" | |
| name: "res3b_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2b" | |
| name: "res3b_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2b" | |
| name: "bn3b_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2b" | |
| name: "scale3b_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3a" | |
| bottom: "res3b_branch2b" | |
| top: "res3b" | |
| name: "res3b" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res3b" | |
| top: "res3b" | |
| name: "res3b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3b" | |
| top: "res3c_branch2a" | |
| name: "res3c_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2a" | |
| top: "res3c_branch2a" | |
| name: "bn3c_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2a" | |
| top: "res3c_branch2a" | |
| name: "scale3c_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2a" | |
| top: "res3c_branch2a" | |
| name: "res3c_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3c_branch2a" | |
| top: "res3c_branch2b" | |
| name: "res3c_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2b" | |
| top: "res3c_branch2b" | |
| name: "bn3c_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2b" | |
| top: "res3c_branch2b" | |
| name: "scale3c_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3b" | |
| bottom: "res3c_branch2b" | |
| top: "res3c" | |
| name: "res3c" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res3c" | |
| top: "res3c" | |
| name: "res3c_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3c" | |
| top: "res3d_branch2a" | |
| name: "res3d_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2a" | |
| top: "res3d_branch2a" | |
| name: "bn3d_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2a" | |
| top: "res3d_branch2a" | |
| name: "scale3d_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2a" | |
| top: "res3d_branch2a" | |
| name: "res3d_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3d_branch2a" | |
| top: "res3d_branch2b" | |
| name: "res3d_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2b" | |
| top: "res3d_branch2b" | |
| name: "bn3d_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2b" | |
| top: "res3d_branch2b" | |
| name: "scale3d_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3c" | |
| bottom: "res3d_branch2b" | |
| top: "res3d" | |
| name: "res3d" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res3d" | |
| top: "res3d" | |
| name: "res3d_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3d" | |
| top: "res4a_branch1" | |
| name: "res4a_branch1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch1" | |
| top: "res4a_branch1" | |
| name: "bn4a_branch1" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch1" | |
| top: "res4a_branch1" | |
| name: "scale4a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res3d" | |
| top: "res4a_branch2a" | |
| name: "res4a_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2a" | |
| top: "res4a_branch2a" | |
| name: "bn4a_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2a" | |
| top: "res4a_branch2a" | |
| name: "scale4a_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2a" | |
| top: "res4a_branch2a" | |
| name: "res4a_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4a_branch2a" | |
| top: "res4a_branch2b" | |
| name: "res4a_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2b" | |
| top: "res4a_branch2b" | |
| name: "bn4a_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2b" | |
| top: "res4a_branch2b" | |
| name: "scale4a_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch1" | |
| bottom: "res4a_branch2b" | |
| top: "res4a" | |
| name: "res4a" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res4a" | |
| top: "res4a" | |
| name: "res4a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4a" | |
| top: "res4b_branch2a" | |
| name: "res4b_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2a" | |
| top: "res4b_branch2a" | |
| name: "bn4b_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2a" | |
| top: "res4b_branch2a" | |
| name: "scale4b_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2a" | |
| top: "res4b_branch2a" | |
| name: "res4b_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4b_branch2a" | |
| top: "res4b_branch2b" | |
| name: "res4b_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2b" | |
| top: "res4b_branch2b" | |
| name: "bn4b_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2b" | |
| top: "res4b_branch2b" | |
| name: "scale4b_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4a" | |
| bottom: "res4b_branch2b" | |
| top: "res4b" | |
| name: "res4b" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res4b" | |
| top: "res4b" | |
| name: "res4b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4b" | |
| top: "res4c_branch2a" | |
| name: "res4c_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2a" | |
| top: "res4c_branch2a" | |
| name: "bn4c_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2a" | |
| top: "res4c_branch2a" | |
| name: "scale4c_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2a" | |
| top: "res4c_branch2a" | |
| name: "res4c_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4c_branch2a" | |
| top: "res4c_branch2b" | |
| name: "res4c_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2b" | |
| top: "res4c_branch2b" | |
| name: "bn4c_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2b" | |
| top: "res4c_branch2b" | |
| name: "scale4c_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4b" | |
| bottom: "res4c_branch2b" | |
| top: "res4c" | |
| name: "res4c" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res4c" | |
| top: "res4c" | |
| name: "res4c_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4c" | |
| top: "res4d_branch2a" | |
| name: "res4d_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2a" | |
| top: "res4d_branch2a" | |
| name: "bn4d_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2a" | |
| top: "res4d_branch2a" | |
| name: "scale4d_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2a" | |
| top: "res4d_branch2a" | |
| name: "res4d_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4d_branch2a" | |
| top: "res4d_branch2b" | |
| name: "res4d_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2b" | |
| top: "res4d_branch2b" | |
| name: "bn4d_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2b" | |
| top: "res4d_branch2b" | |
| name: "scale4d_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4c" | |
| bottom: "res4d_branch2b" | |
| top: "res4d" | |
| name: "res4d" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res4d" | |
| top: "res4d" | |
| name: "res4d_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4d" | |
| top: "res4e_branch2a" | |
| name: "res4e_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2a" | |
| top: "res4e_branch2a" | |
| name: "bn4e_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2a" | |
| top: "res4e_branch2a" | |
| name: "scale4e_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2a" | |
| top: "res4e_branch2a" | |
| name: "res4e_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4e_branch2a" | |
| top: "res4e_branch2b" | |
| name: "res4e_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2b" | |
| top: "res4e_branch2b" | |
| name: "bn4e_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2b" | |
| top: "res4e_branch2b" | |
| name: "scale4e_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4d" | |
| bottom: "res4e_branch2b" | |
| top: "res4e" | |
| name: "res4e" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res4e" | |
| top: "res4e" | |
| name: "res4e_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4e" | |
| top: "res4f_branch2a" | |
| name: "res4f_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2a" | |
| top: "res4f_branch2a" | |
| name: "bn4f_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2a" | |
| top: "res4f_branch2a" | |
| name: "scale4f_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2a" | |
| top: "res4f_branch2a" | |
| name: "res4f_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4f_branch2a" | |
| top: "res4f_branch2b" | |
| name: "res4f_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2b" | |
| top: "res4f_branch2b" | |
| name: "bn4f_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2b" | |
| top: "res4f_branch2b" | |
| name: "scale4f_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4e" | |
| bottom: "res4f_branch2b" | |
| top: "res4f" | |
| name: "res4f" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res4f" | |
| top: "res4f" | |
| name: "res4f_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4f" | |
| top: "res5a_branch1" | |
| name: "res5a_branch1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1" | |
| top: "res5a_branch1" | |
| name: "bn5a_branch1" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1" | |
| top: "res5a_branch1" | |
| name: "scale5a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res4f" | |
| top: "res5a_branch2a" | |
| name: "res5a_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a" | |
| top: "res5a_branch2a" | |
| name: "bn5a_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a" | |
| top: "res5a_branch2a" | |
| name: "scale5a_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a" | |
| top: "res5a_branch2a" | |
| name: "res5a_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5a_branch2a" | |
| top: "res5a_branch2b" | |
| name: "res5a_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| dilation: 2 | |
| pad: 2 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b" | |
| top: "res5a_branch2b" | |
| name: "bn5a_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b" | |
| top: "res5a_branch2b" | |
| name: "scale5a_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1" | |
| bottom: "res5a_branch2b" | |
| top: "res5a" | |
| name: "res5a" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res5a" | |
| top: "res5a" | |
| name: "res5a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5a" | |
| top: "res5b_branch2a" | |
| name: "res5b_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| dilation: 2 | |
| pad: 2 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2a" | |
| name: "bn5b_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2a" | |
| name: "scale5b_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2a" | |
| name: "res5b_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2b" | |
| name: "res5b_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| dilation: 2 | |
| pad: 2 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b" | |
| top: "res5b_branch2b" | |
| name: "bn5b_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b" | |
| top: "res5b_branch2b" | |
| name: "scale5b_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res5a" | |
| bottom: "res5b_branch2b" | |
| top: "res5b" | |
| name: "res5b" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res5b" | |
| top: "res5b" | |
| name: "res5b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5b" | |
| top: "res5c_branch2a" | |
| name: "res5c_branch2a" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| dilation: 2 | |
| pad: 2 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a" | |
| top: "res5c_branch2a" | |
| name: "bn5c_branch2a" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a" | |
| top: "res5c_branch2a" | |
| name: "scale5c_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a" | |
| top: "res5c_branch2a" | |
| name: "res5c_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5c_branch2a" | |
| top: "res5c_branch2b" | |
| name: "res5c_branch2b" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| dilation: 2 | |
| pad: 2 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b" | |
| top: "res5c_branch2b" | |
| name: "bn5c_branch2b" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b" | |
| top: "res5c_branch2b" | |
| name: "scale5c_branch2b" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| bottom: "res5b" | |
| bottom: "res5c_branch2b" | |
| top: "res5c" | |
| name: "res5c" | |
| type: "Eltwise" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| bottom: "res5c" | |
| top: "res5c" | |
| name: "res5c_relu" | |
| type: "ReLU" | |
| } | |
| layer{ | |
| name: "rpn_deconv" | |
| type: "Deconvolution" | |
| bottom: "res4f" | |
| top: "rpn/output" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 4 | |
| pad: 1 | |
| stride: 2 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "ReLU" | |
| name: "rpn_relu" | |
| bottom: "rpn/output" | |
| top: "rpn/output" | |
| } | |
| layer{ | |
| name: "rpn_cls_score" | |
| type: "Convolution" | |
| bottom: "rpn/output" | |
| top: "rpn_cls_score" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.010000 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| name: "rpn_bbox_pred" | |
| type: "Convolution" | |
| bottom: "rpn/output" | |
| top: "rpn_bbox_pred" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.010000 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer { | |
| type: 'Reshape' | |
| name: 'rpn_cls_score_reshape' | |
| bottom: 'rpn_cls_score' | |
| top: 'rpn_cls_score_reshape' | |
| reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } } | |
| } | |
| layer { | |
| type: "Softmax" | |
| name:"rpn_cls_prob" | |
| bottom: "rpn_cls_score_reshape" | |
| top: "rpn_cls_prob" | |
| softmax_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| type: 'Reshape' | |
| name: 'rpn_cls_prob_reshape' | |
| bottom: 'rpn_cls_prob' | |
| top: 'rpn_cls_prob_reshape' | |
| reshape_param { shape { dim: 0 dim: 30 dim: -1 dim: 0 } } | |
| } | |
| layer{ | |
| name: "conv_new" | |
| type: "Deconvolution" | |
| bottom: "res5c" | |
| top: "conv_new" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 4 | |
| pad: 1 | |
| stride: 2 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "ReLU" | |
| name: "conv_new_relu" | |
| bottom: "conv_new" | |
| top: "conv_new" | |
| } | |
| layer{ | |
| name: "conv_left_kx1" | |
| type: "Convolution" | |
| bottom: "conv_new" | |
| top: "conv_left_kx1" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_h: 9 | |
| kernel_w: 1 | |
| pad_h: 4 | |
| pad_w: 0 | |
| stride_h: 1 | |
| stride_w: 1 | |
| dilation: 1 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.010000 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "ReLU" | |
| name: "conv_left_kx1_relu" | |
| bottom: "conv_left_kx1" | |
| top: "conv_left_kx1" | |
| } | |
| layer{ | |
| name: "conv_left_1xk" | |
| type: "Convolution" | |
| bottom: "conv_left_kx1" | |
| top: "conv_left_1xk" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 490 | |
| kernel_h: 1 | |
| kernel_w: 9 | |
| pad_h: 0 | |
| pad_w: 4 | |
| stride_h: 1 | |
| stride_w: 1 | |
| dilation: 1 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.010000 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "ReLU" | |
| name: "conv_left_1xk_relu" | |
| bottom: "conv_left_1xk" | |
| top: "conv_left_1xk" | |
| } | |
| layer{ | |
| name: "conv_right_1xk" | |
| type: "Convolution" | |
| bottom: "conv_new" | |
| top: "conv_right_1xk" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_h: 1 | |
| kernel_w: 9 | |
| pad_h: 0 | |
| pad_w: 4 | |
| stride_h: 1 | |
| stride_w: 1 | |
| dilation: 1 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.010000 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "ReLU" | |
| name: "conv_right_1xk_relu" | |
| bottom: "conv_right_1xk" | |
| top: "conv_right_1xk" | |
| } | |
| layer{ | |
| name: "conv_right_kx1" | |
| type: "Convolution" | |
| bottom: "conv_right_1xk" | |
| top: "conv_right_kx1" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| convolution_param { | |
| num_output: 490 | |
| kernel_h: 9 | |
| kernel_w: 1 | |
| pad_h: 4 | |
| pad_w: 0 | |
| stride_h: 1 | |
| stride_w: 1 | |
| dilation: 1 | |
| dilation: 1 | |
| weight_filler { | |
| type: "msra" | |
| std: 0.010000 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "ReLU" | |
| name: "conv_right_kx1_relu" | |
| bottom: "conv_right_kx1" | |
| top: "conv_right_kx1" | |
| } | |
| layer{ | |
| type: "Eltwise" | |
| name: "ft_add_left_right" | |
| bottom: "conv_left_1xk" | |
| bottom: "conv_right_kx1" | |
| top: "ft_add_left_right" | |
| eltwise_param{ | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| type: 'RPNProposalSSD' | |
| name: 'proposal' | |
| bottom: 'rpn_cls_prob_reshape' | |
| bottom: 'rpn_bbox_pred' | |
| bottom: 'im_info' | |
| top: 'rois' | |
| bbox_reg_param { | |
| bbox_mean: 0.000437 | |
| bbox_mean: 0.002586 | |
| bbox_mean: -0.123953 | |
| bbox_mean: -0.081469 | |
| bbox_std: 0.126770 | |
| bbox_std: 0.095741 | |
| bbox_std: 0.317300 | |
| bbox_std: 0.281042 | |
| } | |
| detection_output_ssd_param { | |
| heat_map_a: 8 | |
| min_size_h: 6.160560 | |
| min_size_w: 6.160560 | |
| min_size_mode: HEIGHT_OR_WIDTH | |
| threshold_objectness: 0.200000 | |
| gen_anchor_param { | |
| anchor_width: 9.232984 | |
| anchor_height: 27.726680 | |
| anchor_width: 16.000000 | |
| anchor_height: 16.000000 | |
| anchor_width: 27.712813 | |
| anchor_height: 9.237604 | |
| anchor_width: 18.465969 | |
| anchor_height: 55.453359 | |
| anchor_width: 32.000000 | |
| anchor_height: 32.000000 | |
| anchor_width: 55.425626 | |
| anchor_height: 18.475209 | |
| anchor_width: 36.931937 | |
| anchor_height: 110.906719 | |
| anchor_width: 64.000000 | |
| anchor_height: 64.000000 | |
| anchor_width: 110.851252 | |
| anchor_height: 36.950417 | |
| anchor_width: 73.863875 | |
| anchor_height: 221.813438 | |
| anchor_width: 128.000000 | |
| anchor_height: 128.000000 | |
| anchor_width: 221.702503 | |
| anchor_height: 73.900834 | |
| anchor_width: 147.727750 | |
| anchor_height: 443.626876 | |
| anchor_width: 256.000000 | |
| anchor_height: 256.000000 | |
| anchor_width: 443.405007 | |
| anchor_height: 147.801669 | |
| } | |
| refine_out_of_map_bbox: true | |
| nms_param { | |
| overlap_ratio: 0.700000 | |
| top_n: 300 | |
| max_candidate_n: 3000 | |
| use_soft_nms: false | |
| voting: false | |
| vote_iou: 0.700000 | |
| } | |
| } | |
| } | |
| layer { | |
| type: 'DFMBPSROIAlign' | |
| name: 'psroi_rois' | |
| bottom: 'ft_add_left_right' | |
| bottom: 'rois' | |
| top: 'psroi_rois' | |
| dfmb_psroi_pooling_param { | |
| heat_map_a: 8 | |
| output_dim: 10 | |
| group_height: 7 | |
| group_width: 7 | |
| pooled_height: 7 | |
| pooled_width: 7 | |
| pad_ratio: 0.000000 | |
| sample_per_part: 4 | |
| } | |
| } | |
| layer{ | |
| type: "InnerProduct" | |
| name: "inner_rois" | |
| bottom: "psroi_rois" | |
| top: "inner_rois" | |
| param{ | |
| name: "weight2d_inner_rois" | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| name: "bias2d_inner_rois" | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| inner_product_param { | |
| num_output: 2048 | |
| weight_filler { | |
| type: "msra" | |
| value: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "ReLU" | |
| name: "inner_rois_relu" | |
| bottom: "inner_rois" | |
| top: "inner_rois" | |
| } | |
| layer{ | |
| type: "InnerProduct" | |
| name: "inner_cls_score_rois" | |
| bottom: "inner_rois" | |
| top: "cls_score" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| inner_product_param { | |
| num_output: 4 | |
| weight_filler { | |
| type: "msra" | |
| value: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer{ | |
| type: "InnerProduct" | |
| name: "inner_bbox_pred_rois" | |
| bottom: "inner_rois" | |
| top: "bbox_pred" | |
| param{ | |
| lr_mult: 1.000000 | |
| decay_mult: 1.000000 | |
| } | |
| param { | |
| lr_mult: 2.000000 | |
| decay_mult: 0.000000 | |
| } | |
| inner_product_param { | |
| num_output: 16 | |
| weight_filler { | |
| type: "msra" | |
| value: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.000000 | |
| } | |
| } | |
| } | |
| layer { | |
| type: "Softmax" | |
| name:"cls_score_softmax" | |
| bottom: "cls_score" | |
| top: "cls_score_softmax" | |
| softmax_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| type: 'RCNNProposal' | |
| name: 'rcnn_proposal' | |
| bottom: 'cls_score_softmax' | |
| bottom: 'bbox_pred' | |
| bottom: 'rois' | |
| bottom: 'im_info' | |
| top: 'bboxes' | |
| bbox_reg_param { | |
| bbox_mean: 0.000000 | |
| bbox_mean: 0.000000 | |
| bbox_mean: 0.000000 | |
| bbox_mean: 0.000000 | |
| bbox_std: 0.100000 | |
| bbox_std: 0.100000 | |
| bbox_std: 0.200000 | |
| bbox_std: 0.200000 | |
| } | |
| detection_output_ssd_param { | |
| num_class: 3 | |
| rpn_proposal_output_score: true | |
| regress_agnostic: false | |
| min_size_h: 8.800800 | |
| min_size_w: 8.800800 | |
| min_size_mode: HEIGHT_OR_WIDTH | |
| threshold_objectness: 0.100000 | |
| threshold: 0.100000 | |
| threshold: 0.100000 | |
| threshold: 0.100000 | |
| refine_out_of_map_bbox: true | |
| nms_param { | |
| overlap_ratio: 0.500000 | |
| top_n: 5 | |
| max_candidate_n: 300 | |
| use_soft_nms: false | |
| voting: false | |
| vote_iou: 0.600000 | |
| } | |
| } | |
| } |
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