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April 22, 2020 09:00
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| name: "RESNET_Mask-RCNN" | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 224 | |
| input_dim: 224 | |
| input: "rois" | |
| input_dim: 1 # to be changed on-the-fly to num ROIs | |
| input_dim: 5 # [batch ind, x1, y1, x2, y2] zero-based indexing | |
| input_dim: 1 | |
| input_dim: 1 | |
| input: "labels" | |
| input_dim: 1 # to be changed on-the-fly to match num ROIs | |
| input_dim: 1 | |
| input_dim: 1 | |
| input_dim: 1 | |
| input: "bbox_targets" | |
| input_dim: 1 # to be changed on-the-fly to match num ROIs | |
| input_dim: 324 # 4 * (K+1) (=81) classes | |
| input_dim: 1 | |
| input_dim: 1 | |
| input: "bbox_loss_weights" | |
| input_dim: 1 # to be changed on-the-fly to match num ROIs | |
| input_dim: 324 # 4 * (K+1) (=81) classes | |
| input_dim: 1 | |
| input_dim: 1 | |
| input: "mask_targets" | |
| input_dim: 1 #to be changed on-the-fly to match num ROIs | |
| input_dim: 81 | |
| input_dim: 28 | |
| input_dim: 28 | |
| layer { | |
| bottom: "data" | |
| top: "conv1" | |
| name: "conv1" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 7 | |
| pad: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "conv1" | |
| name: "bn_conv1" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "conv1" | |
| name: "scale_conv1" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "conv1" | |
| name: "conv1_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv1" | |
| top: "pool1" | |
| name: "pool1" | |
| type: "Pooling" | |
| pooling_param { | |
| kernel_size: 3 | |
| stride: 2 | |
| pool: MAX | |
| } | |
| } | |
| layer { | |
| bottom: "pool1" | |
| top: "res2a_branch1" | |
| name: "res2a_branch1" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch1" | |
| top: "res2a_branch1" | |
| name: "bn2a_branch1" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch1" | |
| top: "res2a_branch1" | |
| name: "scale2a_branch1" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "pool1" | |
| top: "res2a_branch2a" | |
| name: "res2a_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2a" | |
| name: "bn2a_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2a" | |
| name: "scale2a_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2b" | |
| name: "bn2a_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2b" | |
| name: "scale2a_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2b" | |
| name: "res2a_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2c" | |
| name: "res2a_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2c" | |
| top: "res2a_branch2c" | |
| name: "bn2a_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2c" | |
| top: "res2a_branch2c" | |
| name: "scale2a_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch1" | |
| bottom: "res2a_branch2c" | |
| top: "res2a" | |
| name: "res2a" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res2a" | |
| top: "res2a" | |
| name: "res2a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2a" | |
| top: "res2b_branch2a" | |
| name: "res2b_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2a" | |
| name: "bn2b_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2a" | |
| name: "scale2b_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2b" | |
| name: "bn2b_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2b" | |
| name: "scale2b_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2b" | |
| name: "res2b_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2c" | |
| name: "res2b_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2c" | |
| top: "res2b_branch2c" | |
| name: "bn2b_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2c" | |
| top: "res2b_branch2c" | |
| name: "scale2b_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a" | |
| bottom: "res2b_branch2c" | |
| top: "res2b" | |
| name: "res2b" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res2b" | |
| top: "res2b" | |
| name: "res2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2b" | |
| top: "res2c_branch2a" | |
| name: "res2c_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2a" | |
| name: "bn2c_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2a" | |
| name: "scale2c_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2b" | |
| name: "bn2c_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2b" | |
| name: "scale2c_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2b" | |
| name: "res2c_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2c" | |
| name: "res2c_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2c" | |
| top: "res2c_branch2c" | |
| name: "bn2c_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2c" | |
| top: "res2c_branch2c" | |
| name: "scale2c_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b" | |
| bottom: "res2c_branch2c" | |
| top: "res2c" | |
| name: "res2c" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res2c" | |
| top: "res2c" | |
| name: "res2c_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res2c" | |
| top: "res3a_branch1" | |
| name: "res3a_branch1" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch1" | |
| top: "res3a_branch1" | |
| name: "bn3a_branch1" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch1" | |
| top: "res3a_branch1" | |
| name: "scale3a_branch1" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c" | |
| top: "res3a_branch2a" | |
| name: "res3a_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2a" | |
| name: "bn3a_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2a" | |
| name: "scale3a_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2b" | |
| name: "bn3a_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2b" | |
| name: "scale3a_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2b" | |
| name: "res3a_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2c" | |
| name: "res3a_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2c" | |
| top: "res3a_branch2c" | |
| name: "bn3a_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2c" | |
| top: "res3a_branch2c" | |
| name: "scale3a_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch1" | |
| bottom: "res3a_branch2c" | |
| top: "res3a" | |
| name: "res3a" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res3a" | |
| top: "res3a" | |
| name: "res3a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3a" | |
| top: "res3b_branch2a" | |
| name: "res3b_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2a" | |
| name: "bn3b_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2a" | |
| name: "scale3b_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2b" | |
| name: "bn3b_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2b" | |
| name: "scale3b_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2b" | |
| name: "res3b_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2c" | |
| name: "res3b_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2c" | |
| top: "res3b_branch2c" | |
| name: "bn3b_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2c" | |
| top: "res3b_branch2c" | |
| name: "scale3b_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a" | |
| bottom: "res3b_branch2c" | |
| top: "res3b" | |
| name: "res3b" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res3b" | |
| top: "res3b" | |
| name: "res3b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3b" | |
| top: "res3c_branch2a" | |
| name: "res3c_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2a" | |
| top: "res3c_branch2a" | |
| name: "bn3c_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2a" | |
| top: "res3c_branch2a" | |
| name: "scale3c_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2b" | |
| top: "res3c_branch2b" | |
| name: "bn3c_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2b" | |
| top: "res3c_branch2b" | |
| name: "scale3c_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2b" | |
| top: "res3c_branch2b" | |
| name: "res3c_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3c_branch2b" | |
| top: "res3c_branch2c" | |
| name: "res3c_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2c" | |
| top: "res3c_branch2c" | |
| name: "bn3c_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2c" | |
| top: "res3c_branch2c" | |
| name: "scale3c_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b" | |
| bottom: "res3c_branch2c" | |
| top: "res3c" | |
| name: "res3c" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res3c" | |
| top: "res3c" | |
| name: "res3c_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3c" | |
| top: "res3d_branch2a" | |
| name: "res3d_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2a" | |
| top: "res3d_branch2a" | |
| name: "bn3d_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2a" | |
| top: "res3d_branch2a" | |
| name: "scale3d_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2b" | |
| top: "res3d_branch2b" | |
| name: "bn3d_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2b" | |
| top: "res3d_branch2b" | |
| name: "scale3d_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2b" | |
| top: "res3d_branch2b" | |
| name: "res3d_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3d_branch2b" | |
| top: "res3d_branch2c" | |
| name: "res3d_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2c" | |
| top: "res3d_branch2c" | |
| name: "bn3d_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2c" | |
| top: "res3d_branch2c" | |
| name: "scale3d_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c" | |
| bottom: "res3d_branch2c" | |
| top: "res3d" | |
| name: "res3d" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res3d" | |
| top: "res3d" | |
| name: "res3d_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res3d" | |
| top: "res4a_branch1" | |
| name: "res4a_branch1" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch1" | |
| top: "res4a_branch1" | |
| name: "bn4a_branch1" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch1" | |
| top: "res4a_branch1" | |
| name: "scale4a_branch1" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d" | |
| top: "res4a_branch2a" | |
| name: "res4a_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2a" | |
| top: "res4a_branch2a" | |
| name: "bn4a_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2a" | |
| top: "res4a_branch2a" | |
| name: "scale4a_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2b" | |
| top: "res4a_branch2b" | |
| name: "bn4a_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2b" | |
| top: "res4a_branch2b" | |
| name: "scale4a_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2b" | |
| top: "res4a_branch2b" | |
| name: "res4a_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4a_branch2b" | |
| top: "res4a_branch2c" | |
| name: "res4a_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2c" | |
| top: "res4a_branch2c" | |
| name: "bn4a_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2c" | |
| top: "res4a_branch2c" | |
| name: "scale4a_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch1" | |
| bottom: "res4a_branch2c" | |
| top: "res4a" | |
| name: "res4a" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res4a" | |
| top: "res4a" | |
| name: "res4a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4a" | |
| top: "res4b_branch2a" | |
| name: "res4b_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2a" | |
| top: "res4b_branch2a" | |
| name: "bn4b_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2a" | |
| top: "res4b_branch2a" | |
| name: "scale4b_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2b" | |
| top: "res4b_branch2b" | |
| name: "bn4b_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2b" | |
| top: "res4b_branch2b" | |
| name: "scale4b_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2b" | |
| top: "res4b_branch2b" | |
| name: "res4b_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4b_branch2b" | |
| top: "res4b_branch2c" | |
| name: "res4b_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2c" | |
| top: "res4b_branch2c" | |
| name: "bn4b_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2c" | |
| top: "res4b_branch2c" | |
| name: "scale4b_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a" | |
| bottom: "res4b_branch2c" | |
| top: "res4b" | |
| name: "res4b" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res4b" | |
| top: "res4b" | |
| name: "res4b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4b" | |
| top: "res4c_branch2a" | |
| name: "res4c_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2a" | |
| top: "res4c_branch2a" | |
| name: "bn4c_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2a" | |
| top: "res4c_branch2a" | |
| name: "scale4c_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2b" | |
| top: "res4c_branch2b" | |
| name: "bn4c_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2b" | |
| top: "res4c_branch2b" | |
| name: "scale4c_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2b" | |
| top: "res4c_branch2b" | |
| name: "res4c_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4c_branch2b" | |
| top: "res4c_branch2c" | |
| name: "res4c_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2c" | |
| top: "res4c_branch2c" | |
| name: "bn4c_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2c" | |
| top: "res4c_branch2c" | |
| name: "scale4c_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b" | |
| bottom: "res4c_branch2c" | |
| top: "res4c" | |
| name: "res4c" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res4c" | |
| top: "res4c" | |
| name: "res4c_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4c" | |
| top: "res4d_branch2a" | |
| name: "res4d_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2a" | |
| top: "res4d_branch2a" | |
| name: "bn4d_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2a" | |
| top: "res4d_branch2a" | |
| name: "scale4d_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2b" | |
| top: "res4d_branch2b" | |
| name: "bn4d_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2b" | |
| top: "res4d_branch2b" | |
| name: "scale4d_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2b" | |
| top: "res4d_branch2b" | |
| name: "res4d_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4d_branch2b" | |
| top: "res4d_branch2c" | |
| name: "res4d_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2c" | |
| top: "res4d_branch2c" | |
| name: "bn4d_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2c" | |
| top: "res4d_branch2c" | |
| name: "scale4d_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c" | |
| bottom: "res4d_branch2c" | |
| top: "res4d" | |
| name: "res4d" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res4d" | |
| top: "res4d" | |
| name: "res4d_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4d" | |
| top: "res4e_branch2a" | |
| name: "res4e_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2a" | |
| top: "res4e_branch2a" | |
| name: "bn4e_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2a" | |
| top: "res4e_branch2a" | |
| name: "scale4e_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2b" | |
| top: "res4e_branch2b" | |
| name: "bn4e_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2b" | |
| top: "res4e_branch2b" | |
| name: "scale4e_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2b" | |
| top: "res4e_branch2b" | |
| name: "res4e_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4e_branch2b" | |
| top: "res4e_branch2c" | |
| name: "res4e_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2c" | |
| top: "res4e_branch2c" | |
| name: "bn4e_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2c" | |
| top: "res4e_branch2c" | |
| name: "scale4e_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d" | |
| bottom: "res4e_branch2c" | |
| top: "res4e" | |
| name: "res4e" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res4e" | |
| top: "res4e" | |
| name: "res4e_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4e" | |
| top: "res4f_branch2a" | |
| name: "res4f_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2a" | |
| top: "res4f_branch2a" | |
| name: "bn4f_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2a" | |
| top: "res4f_branch2a" | |
| name: "scale4f_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2b" | |
| top: "res4f_branch2b" | |
| name: "bn4f_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2b" | |
| top: "res4f_branch2b" | |
| name: "scale4f_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2b" | |
| top: "res4f_branch2b" | |
| name: "res4f_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4f_branch2b" | |
| top: "res4f_branch2c" | |
| name: "res4f_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2c" | |
| top: "res4f_branch2c" | |
| name: "bn4f_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2c" | |
| top: "res4f_branch2c" | |
| name: "scale4f_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e" | |
| bottom: "res4f_branch2c" | |
| top: "res4f" | |
| name: "res4f" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res4f" | |
| top: "res4f" | |
| name: "res4f_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res4f" | |
| top: "res5a_branch1" | |
| name: "res5a_branch1" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1" | |
| top: "res5a_branch1" | |
| name: "bn5a_branch1" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1" | |
| top: "res5a_branch1" | |
| name: "scale5a_branch1" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f" | |
| top: "res5a_branch2a" | |
| name: "res5a_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a" | |
| top: "res5a_branch2a" | |
| name: "bn5a_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a" | |
| top: "res5a_branch2a" | |
| name: "scale5a_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b" | |
| top: "res5a_branch2b" | |
| name: "bn5a_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b" | |
| top: "res5a_branch2b" | |
| name: "scale5a_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b" | |
| top: "res5a_branch2b" | |
| name: "res5a_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5a_branch2b" | |
| top: "res5a_branch2c" | |
| name: "res5a_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2c" | |
| top: "res5a_branch2c" | |
| name: "bn5a_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2c" | |
| top: "res5a_branch2c" | |
| name: "scale5a_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1" | |
| bottom: "res5a_branch2c" | |
| top: "res5a" | |
| name: "res5a" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res5a" | |
| top: "res5a" | |
| name: "res5a_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5a" | |
| top: "res5b_branch2a" | |
| name: "res5b_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2a" | |
| name: "bn5b_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2a" | |
| name: "scale5b_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2a" | |
| name: "res5b_branch2a_relu" | |
| type: "ReLU" | |
| } | |
| #Learning starts here | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2b" | |
| name: "res5b_branch2b" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b" | |
| top: "res5b_branch2b" | |
| name: "bn5b_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b" | |
| top: "res5b_branch2b" | |
| name: "scale5b_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b" | |
| top: "res5b_branch2b" | |
| name: "res5b_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5b_branch2b" | |
| top: "res5b_branch2c" | |
| name: "res5b_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2c" | |
| top: "res5b_branch2c" | |
| name: "bn5b_branch2c" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2c" | |
| top: "res5b_branch2c" | |
| name: "scale5b_branch2c" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a" | |
| bottom: "res5b_branch2c" | |
| top: "res5b" | |
| name: "res5b" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res5b" | |
| top: "res5b" | |
| name: "res5b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5b" | |
| top: "res5c_branch2a" | |
| name: "res5c_branch2a" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a" | |
| top: "res5c_branch2a" | |
| name: "bn5c_branch2a" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a" | |
| top: "res5c_branch2a" | |
| name: "scale5c_branch2a" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b" | |
| top: "res5c_branch2b" | |
| name: "bn5c_branch2b" | |
| type: "BatchNorm" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b" | |
| top: "res5c_branch2b" | |
| name: "scale5c_branch2b" | |
| type: "Scale" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b" | |
| top: "res5c_branch2b" | |
| name: "res5c_branch2b_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5c_branch2b" | |
| top: "res5c_branch2c" | |
| name: "res5c_branch2c" | |
| type: "Convolution" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| #---------------ROIPool -------------------------- | |
| # | |
| #layer { | |
| # bottom: "res5c_branch2c" | |
| # bottom: "rois" | |
| # top: "roi_pool" | |
| # name: "roi_pool" | |
| # type: "ROIPooling" | |
| # roi_pooling_param { | |
| # pooled_w: 7 | |
| # pooled_h: 7 | |
| # spatial_scale: 0.0312 # (1/32) | |
| # } | |
| #} | |
| #---------------ROIAlign -------------------------- | |
| layer { | |
| bottom: "res5c_branch2c" | |
| bottom: "rois" | |
| top: "align" | |
| name: "align" | |
| type: "ROIAlign" | |
| roi_align_param { | |
| pooled_w: 7 | |
| pooled_h: 7 | |
| spatial_scale: 0.0312 # (1/32) | |
| } | |
| } | |
| #---------------Mask Branch -------------------------- | |
| layer { | |
| bottom: "align" | |
| top: "conv_mask1" | |
| name: "conv_mask1" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| bottom: 'conv_mask1' | |
| top: 'conv_mask1-bn' | |
| name: 'conv_mask1-bn' | |
| type: 'BatchNorm' | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask1-bn" | |
| top: "conv_mask1-bn" | |
| name: "scale_conv_mask1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask1-bn" | |
| top: "conv_mask1-bn" | |
| name: "relu_conv1" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv_mask1-bn" | |
| top: "conv_mask1-bn" | |
| name: "drop_conv1" | |
| type: "Dropout" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask1-bn" | |
| top: "deconv_mask1" | |
| name: "deconv_mask1" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| type: "Deconvolution" | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 2 | |
| stride: 2 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| bottom: 'deconv_mask1' | |
| top: 'deconv_mask1-bn' | |
| name: 'deconv_mask1-bn' | |
| type: 'BatchNorm' | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| bottom: "deconv_mask1-bn" | |
| top: "deconv_mask1-bn" | |
| name: "scale_deconv_mask1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "deconv_mask1-bn" | |
| top: "deconv_mask1-bn" | |
| name: "relu_deconv1" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "deconv_mask1-bn" | |
| top: "conv_mask2" | |
| name: "conv_mask2" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| bottom: 'conv_mask2' | |
| top: 'conv_mask2-bn' | |
| name: 'conv_mask2-bn' | |
| type: 'BatchNorm' | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask2-bn" | |
| top: "conv_mask2-bn" | |
| name: "scale_conv_mask2" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask2-bn" | |
| top: "conv_mask2-bn" | |
| name: "relu_conv2" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv_mask2-bn" | |
| top: "conv_mask2-bn" | |
| name: "drop_conv2" | |
| type: "Dropout" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask2-bn" | |
| top: "conv_mask3" | |
| name: "conv_mask3" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| bottom: 'conv_mask3' | |
| top: 'conv_mask3-bn' | |
| name: 'conv_mask3-bn' | |
| type: 'BatchNorm' | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask3-bn" | |
| top: "conv_mask3-bn" | |
| name: "scale_conv_mask3" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask3-bn" | |
| top: "conv_mask3-bn" | |
| name: "relu_conv3" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv_mask3-bn" | |
| top: "conv_mask4" | |
| name: "conv_mask4" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| bottom: 'conv_mask4' | |
| top: 'conv_mask4-bn' | |
| name: 'conv_mask4-bn' | |
| type: 'BatchNorm' | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask4-bn" | |
| top: "conv_mask4-bn" | |
| name: "scale_conv_mask4" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask4-bn" | |
| top: "conv_mask4-bn" | |
| name: "relu_conv4" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv_mask4-bn" | |
| top: "conv_mask5" | |
| name: "conv_mask5" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| bottom: 'conv_mask5' | |
| top: 'conv_mask5-bn' | |
| name: 'conv_mask5-bn' | |
| type: 'BatchNorm' | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask5-bn" | |
| top: "conv_mask5-bn" | |
| name: "scale_conv_mask5" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "conv_mask5-bn" | |
| top: "conv_mask5-bn" | |
| name: "relu_conv5" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "conv_mask5-bn" | |
| top: "deconv_mask2" | |
| name: "deconv_mask2" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| type: "Deconvolution" | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 2 | |
| stride: 2 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| bottom: 'deconv_mask2' | |
| top: 'deconv_mask2-bn' | |
| name: 'deconv_mask2-bn' | |
| type: 'BatchNorm' | |
| batch_norm_param { | |
| use_global_stats: false | |
| } | |
| } | |
| layer { | |
| bottom: "deconv_mask2-bn" | |
| top: "deconv_mask2-bn" | |
| name: "scale_deconv_mask1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "deconv_mask2-bn" | |
| top: "deconv_mask2-bn" | |
| name: "relu_deconv2" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "deconv_mask2-bn" | |
| top: "conv_mask6" | |
| name: "conv_mask6" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 81 | |
| pad: 1 | |
| kernel_size: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" # initialize the biases to zero (0) | |
| value: 0 | |
| } | |
| } | |
| } | |
| #---------------FC Branch -------------------------- | |
| layer { | |
| bottom: "align" | |
| top: "fc6" | |
| name: "fc6" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "InnerProduct" | |
| inner_product_param { | |
| num_output: 4096 | |
| } | |
| } | |
| layer { | |
| bottom: "fc6" | |
| top: "fc6" | |
| name: "relu6" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "fc6" | |
| top: "fc6" | |
| name: "drop6" | |
| type: "Dropout" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| bottom: "fc6" | |
| top: "fc7" | |
| name: "fc7" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "InnerProduct" | |
| inner_product_param { | |
| num_output: 4096 | |
| } | |
| } | |
| layer { | |
| bottom: "fc7" | |
| top: "fc7" | |
| name: "relu7" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "fc7" | |
| top: "fc7" | |
| name: "drop7" | |
| type: "Dropout" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| #---------------Class Prediction Branch -------------------------- | |
| layer { | |
| bottom: "fc7" | |
| top: "cls_score" | |
| name: "cls_score" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| type: "InnerProduct" | |
| inner_product_param { | |
| num_output: 81 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| #---------------Bounding Box Prediction Branch -------------------------- | |
| layer { | |
| bottom: "fc7" | |
| top: "bbox_pred" | |
| name: "bbox_pred" | |
| type: "InnerProduct" | |
| param { | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| } | |
| inner_product_param { | |
| num_output: 324 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.001 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| #---------------Class Loss -------------------------- | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "cls_score" | |
| bottom: "labels" | |
| top: "loss_cls" | |
| loss_weight: 1 | |
| } | |
| layer { | |
| name: "accuarcy" | |
| type: "Accuracy" | |
| bottom: "cls_score" | |
| bottom: "labels" | |
| top: "accuarcy" | |
| } | |
| #---------------BB Loss -------------------------- | |
| layer { | |
| name: "loss_bbox" | |
| type: "SmoothL1Loss" | |
| bottom: "bbox_pred" | |
| bottom: "bbox_targets" | |
| bottom: "bbox_loss_weights" | |
| top: "loss_bbox" | |
| loss_weight: 1 | |
| } | |
| #---------------Mask Loss -------------------------- | |
| layer { | |
| name: "loss_mask" | |
| type: "SigmoidCrossEntropyLoss" | |
| bottom: "conv_mask6" | |
| bottom: "mask_targets" | |
| top: "loss_mask" | |
| loss_weight: 1 | |
| loss_param { | |
| ignore_label: -1 | |
| } | |
| } | |
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