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ResNet50-mnc3stage.prototxt
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| name: "ResNet50" | |
| layer { | |
| name: 'input-data' | |
| type: 'Python' | |
| top: 'data' | |
| top: 'im_info' | |
| top: 'gt_boxes' | |
| top: 'gt_masks' | |
| top: 'mask_info' | |
| python_param { | |
| module: 'multitask_network_cascades.pylayer.mnc_data_layer' | |
| layer: 'MNCDataLayer' | |
| param_str: "{ 'num_classes': 2 }" | |
| } | |
| } | |
| # ------------ Convolution ----------- | |
| layer { | |
| bottom: "data" | |
| top: "conv1" | |
| name: "conv1" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 7 | |
| pad: 3 | |
| stride: 2 | |
| } | |
| } | |
| 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 | |
| } | |
| } | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch1" | |
| top: "res2a_branch1" | |
| name: "scale2a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "pool1" | |
| top: "res2a_branch2a" | |
| name: "res2a_branch2a" | |
| type: "Convolution" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2a" | |
| top: "res2a_branch2a" | |
| name: "scale2a_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2b" | |
| top: "res2a_branch2b" | |
| name: "scale2a_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2a_branch2c" | |
| top: "res2a_branch2c" | |
| name: "scale2a_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2a" | |
| top: "res2b_branch2a" | |
| name: "scale2b_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2b" | |
| top: "res2b_branch2b" | |
| name: "scale2b_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2b_branch2c" | |
| top: "res2b_branch2c" | |
| name: "scale2b_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2a" | |
| top: "res2c_branch2a" | |
| name: "scale2c_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2b" | |
| top: "res2c_branch2b" | |
| name: "scale2c_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c_branch2c" | |
| top: "res2c_branch2c" | |
| name: "scale2c_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch1" | |
| top: "res3a_branch1" | |
| name: "scale3a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res2c" | |
| top: "res3a_branch2a" | |
| name: "res3a_branch2a" | |
| type: "Convolution" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2a" | |
| top: "res3a_branch2a" | |
| name: "scale3a_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2b" | |
| top: "res3a_branch2b" | |
| name: "scale3a_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3a_branch2c" | |
| top: "res3a_branch2c" | |
| name: "scale3a_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2a" | |
| top: "res3b_branch2a" | |
| name: "scale3b_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2b" | |
| top: "res3b_branch2b" | |
| name: "scale3b_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3b_branch2c" | |
| top: "res3b_branch2c" | |
| name: "scale3b_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2a" | |
| top: "res3c_branch2a" | |
| name: "scale3c_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2b" | |
| top: "res3c_branch2b" | |
| name: "scale3c_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3c_branch2c" | |
| top: "res3c_branch2c" | |
| name: "scale3c_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2a" | |
| top: "res3d_branch2a" | |
| name: "scale3d_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2b" | |
| top: "res3d_branch2b" | |
| name: "scale3d_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d_branch2c" | |
| top: "res3d_branch2c" | |
| name: "scale3d_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch1" | |
| top: "res4a_branch1" | |
| name: "scale4a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res3d" | |
| top: "res4a_branch2a" | |
| name: "res4a_branch2a" | |
| type: "Convolution" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2a" | |
| top: "res4a_branch2a" | |
| name: "scale4a_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2b" | |
| top: "res4a_branch2b" | |
| name: "scale4a_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4a_branch2c" | |
| top: "res4a_branch2c" | |
| name: "scale4a_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2a" | |
| top: "res4b_branch2a" | |
| name: "scale4b_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2b" | |
| top: "res4b_branch2b" | |
| name: "scale4b_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4b_branch2c" | |
| top: "res4b_branch2c" | |
| name: "scale4b_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2a" | |
| top: "res4c_branch2a" | |
| name: "scale4c_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2b" | |
| top: "res4c_branch2b" | |
| name: "scale4c_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4c_branch2c" | |
| top: "res4c_branch2c" | |
| name: "scale4c_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2a" | |
| top: "res4d_branch2a" | |
| name: "scale4d_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2b" | |
| top: "res4d_branch2b" | |
| name: "scale4d_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4d_branch2c" | |
| top: "res4d_branch2c" | |
| name: "scale4d_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2a" | |
| top: "res4e_branch2a" | |
| name: "scale4e_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2b" | |
| top: "res4e_branch2b" | |
| name: "scale4e_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4e_branch2c" | |
| top: "res4e_branch2c" | |
| name: "scale4e_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2a" | |
| top: "res4f_branch2a" | |
| name: "scale4f_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2b" | |
| top: "res4f_branch2b" | |
| name: "scale4f_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res4f_branch2c" | |
| top: "res4f_branch2c" | |
| name: "scale4f_branch2c" | |
| type: "Scale" | |
| 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" | |
| } | |
| #------------ RPN ------------ | |
| layer { | |
| name: "rpn_conv_3x3" | |
| type: "Convolution" | |
| bottom: "res4f" | |
| top: "rpn_output" | |
| param { lr_mult: 1.0 } | |
| param { lr_mult: 2.0 } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 pad: 1 stride: 1 | |
| weight_filler { type: "gaussian" std: 0.01 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| name: "rpn_relu_3x3" | |
| type: "ReLU" | |
| bottom: "rpn_output" | |
| top: "rpn_output" | |
| } | |
| layer { | |
| name: "rpn_cls_score" | |
| type: "Convolution" | |
| bottom: "rpn_output" | |
| top: "rpn_cls_score" | |
| param { lr_mult: 1.0 } | |
| param { lr_mult: 2.0 } | |
| convolution_param { | |
| num_output: 18 # 2(bg/fg) * 9(anchors) | |
| kernel_size: 1 pad: 0 stride: 1 | |
| weight_filler { type: "gaussian" std: 0.01 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| name: "rpn_bbox_pred" | |
| type: "Convolution" | |
| bottom: "rpn_output" | |
| top: "rpn_bbox_pred" | |
| param { lr_mult: 1.0 } | |
| param { lr_mult: 2.0 } | |
| convolution_param { | |
| num_output: 36 # 4 * 9(anchors) | |
| kernel_size: 1 pad: 0 stride: 1 | |
| weight_filler { type: "gaussian" std: 0.01 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| bottom: "rpn_cls_score" | |
| top: "rpn_cls_score_reshape" | |
| name: "rpn_cls_score_reshape" | |
| type: "Reshape" | |
| reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } } | |
| } | |
| #------------ Anchor to Proposal ------------ | |
| layer { | |
| name: "rpn_cls_prob" | |
| type: "Softmax" | |
| bottom: "rpn_cls_score_reshape" | |
| top: "rpn_cls_prob" | |
| } | |
| layer { | |
| name: 'rpn_cls_prob_reshape' | |
| type: 'Reshape' | |
| bottom: 'rpn_cls_prob' | |
| top: 'rpn_cls_prob_reshape' | |
| reshape_param { shape { dim: 0 dim: 18 dim: -1 dim: 0 } } | |
| } | |
| layer { | |
| name: 'proposal' | |
| type: 'Python' | |
| bottom: 'rpn_cls_prob_reshape' | |
| bottom: 'rpn_bbox_pred' | |
| bottom: 'im_info' | |
| propagate_down: 0 | |
| propagate_down: 1 | |
| propagate_down: 0 | |
| top: 'rpn_rois' | |
| top: 'rpn_rois_index' | |
| python_param { | |
| module: 'multitask_network_cascades.pylayer.proposal_layer' | |
| layer: 'ProposalLayer' | |
| param_str: "{ 'feat_stride': 16, 'use_clip': 1, 'clip_base': 512 }" | |
| } | |
| } | |
| layer { | |
| name: 'roi-data' | |
| type: 'Python' | |
| bottom: 'rpn_rois' | |
| bottom: 'gt_boxes' | |
| bottom: 'im_info' | |
| bottom: 'gt_masks' | |
| bottom: 'mask_info' | |
| bottom: 'rpn_rois_index' | |
| propagate_down: 1 | |
| propagate_down: 0 | |
| propagate_down: 0 | |
| propagate_down: 0 | |
| propagate_down: 0 | |
| propagate_down: 0 | |
| top: 'rois' | |
| top: 'labels' | |
| top: 'bbox_targets' | |
| top: 'bbox_inside_weights' | |
| top: 'bbox_outside_weights' | |
| top: 'mask_targets' | |
| top: 'mask_weight' | |
| top: 'gt_masks_info' | |
| top: 'fg_inds' | |
| top: 'bg_inds' | |
| python_param { | |
| module: 'multitask_network_cascades.pylayer.proposal_target_layer' | |
| layer: 'ProposalTargetLayer' | |
| param_str: "{'num_classes': 2, 'bp_all': 1}" | |
| } | |
| } | |
| layer { | |
| name: 'rpn-data' | |
| type: 'Python' | |
| bottom: 'rpn_cls_score' | |
| bottom: 'gt_boxes' | |
| bottom: 'im_info' | |
| bottom: 'fg_inds' | |
| bottom: 'bg_inds' | |
| top: 'rpn_labels' | |
| top: 'rpn_bbox_targets' | |
| top: 'rpn_bbox_inside_weights' | |
| top: 'rpn_bbox_outside_weights' | |
| python_param { | |
| module: 'multitask_network_cascades.pylayer.anchor_target_layer' | |
| layer: 'AnchorTargetLayer' | |
| param_str: "{'feat_stride': 16}" | |
| } | |
| } | |
| #------------ RPN loss ------------ | |
| # put rpn loss here since we need | |
| # proposal's index first | |
| layer { | |
| name: "rpn_loss_cls" | |
| type: "SoftmaxWithLoss" | |
| bottom: "rpn_cls_score_reshape" | |
| bottom: "rpn_labels" | |
| propagate_down: 1 | |
| propagate_down: 0 | |
| top: "rpn_cls_loss" | |
| loss_weight: 1 | |
| loss_param { | |
| ignore_label: -1 | |
| normalize: true | |
| } | |
| } | |
| layer { | |
| name: "rpn_loss_bbox" | |
| type: "SmoothL1Loss" | |
| bottom: "rpn_bbox_pred" | |
| bottom: "rpn_bbox_targets" | |
| bottom: 'rpn_bbox_inside_weights' | |
| bottom: 'rpn_bbox_outside_weights' | |
| top: "rpn_loss_bbox" | |
| loss_weight: 1 | |
| smooth_l1_loss_param { sigma: 3.0 } | |
| } | |
| #------------ Roi Warping ------------ | |
| layer { | |
| name: "roi_interpolate_conv5" | |
| type: "ROIWarping" | |
| bottom: "res4f" | |
| bottom: "rois" | |
| propagate_down: 1 | |
| propagate_down: 1 | |
| top: "roi_interpolate_conv5" | |
| roi_warping_param { | |
| pooled_w: 14 | |
| pooled_h: 14 | |
| spatial_scale: 0.0625 # 1/16 | |
| } | |
| } | |
| #------------ Mask Estimation ------------ | |
| layer { | |
| name: "fc6_maskest" | |
| type: "InnerProduct" | |
| bottom: "roi_interpolate_conv5" | |
| top: "fc6_maskest" | |
| param { | |
| name: "fc6_maskest_w" | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| name: "fc6_maskest_b" | |
| lr_mult: 2.0 | |
| } | |
| inner_product_param { | |
| num_output: 256 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.001 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6_maskest" | |
| type: "ReLU" | |
| bottom: "fc6_maskest" | |
| top: "fc6_maskest" | |
| } | |
| layer { | |
| name: "mask_pred" | |
| type: "InnerProduct" | |
| bottom: "fc6_maskest" | |
| top: "mask_pred" | |
| param { | |
| name: "mask_pred_w" | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| name: "mask_pred_b" | |
| lr_mult: 2.0 | |
| } | |
| inner_product_param { | |
| num_output: 441 # 21 * 21 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.001 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss_mask" | |
| type: "SigmoidCrossEntropyLoss" | |
| bottom: "mask_pred" | |
| bottom: "mask_targets" | |
| bottom: "mask_weight" | |
| propagate_down: 1 | |
| propagate_down: 0 | |
| propagate_down: 0 | |
| top: "loss_mask" | |
| loss_weight: 2 | |
| } | |
| #------------ Mask resize ------------ | |
| # get masks from sigmoid prediction | |
| # and use it for mask pooling | |
| layer { | |
| name: "mask_output" | |
| type: "Sigmoid" | |
| bottom: "mask_pred" | |
| top: "mask_output" | |
| } | |
| layer { | |
| name: "mask_proposal" | |
| type: 'Python' | |
| bottom: 'mask_output' | |
| bottom: 'gt_masks' | |
| bottom: 'gt_masks_info' | |
| propagate_down: 1 | |
| propagate_down: 0 | |
| propagate_down: 0 | |
| top: 'mask_proposal' | |
| top: 'mask_proposal_label' | |
| python_param { | |
| module: 'multitask_network_cascades.pylayer.mask_layer' | |
| layer: 'MaskLayer' | |
| } | |
| } | |
| layer { | |
| name: "mask_resize" | |
| type: "MaskResize" | |
| bottom: "mask_proposal" | |
| top: "mask_proposal_resize" | |
| mask_resize_param { | |
| output_height: 14 | |
| output_width: 14 | |
| } | |
| } | |
| #------------ Box Features ------------ | |
| layer { | |
| name: "roi_interpolate_conv5_box" | |
| type: "Pooling" | |
| bottom: "roi_interpolate_conv5" | |
| top: "roi_interpolate_conv5_box" | |
| pooling_param { | |
| kernel_size: 2 | |
| stride: 1 | |
| pad: 0 | |
| pool: MAX | |
| } | |
| } | |
| layer { | |
| bottom: "roi_interpolate_conv5_box" | |
| top: "res5a_branch1" | |
| name: "res5a_branch1" | |
| type: "Convolution" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1" | |
| top: "res5a_branch1" | |
| name: "scale5a_branch1" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "roi_interpolate_conv5_box" | |
| top: "res5a_branch2a" | |
| name: "res5a_branch2a" | |
| type: "Convolution" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a" | |
| top: "res5a_branch2a" | |
| name: "scale5a_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b" | |
| top: "res5a_branch2b" | |
| name: "scale5a_branch2b" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2c" | |
| top: "res5a_branch2c" | |
| name: "scale5a_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a" | |
| top: "res5b_branch2a" | |
| name: "scale5b_branch2a" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| 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: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| 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 | |
| } | |
| } | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2c" | |
| top: "res5b_branch2c" | |
| name: "scale5b_branch2c" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a" | |
| top: "res5c_branch2a" | |
| name: "scale5c_branch2a" | |
| type: "Scale" | |
| 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" | |
| 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" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b" | |
| top: "res5c_branch2b" | |
| name: "scale5c_branch2b" | |
| type: "Scale" | |
| 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" | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2c" | |
| top: "res5c_branch2c" | |
| name: "bn5c_branch2c" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2c" | |
| top: "res5c_branch2c" | |
| name: "scale5c_branch2c" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b" | |
| bottom: "res5c_branch2c" | |
| top: "res5c" | |
| name: "res5c" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res5c" | |
| top: "res5c" | |
| name: "res5c_relu" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5c" | |
| top: "pool5" | |
| name: "pool5" | |
| type: "Pooling" | |
| pooling_param { | |
| kernel_size: 7 | |
| stride: 1 | |
| pool: AVE | |
| } | |
| } | |
| #------------ Mask Features ------------ | |
| layer { | |
| name: "mask_pooling" | |
| type: "MaskPooling" | |
| propagate_down: 1 | |
| propagate_down: 1 | |
| bottom: "roi_interpolate_conv5" | |
| bottom: "mask_proposal_resize" | |
| top: "roi_mask_conv5" | |
| } | |
| layer { | |
| name: "roi_interpolate_conv5_mask" | |
| type: "Pooling" | |
| bottom: "roi_mask_conv5" | |
| top: "roi_interpolate_conv5_mask" | |
| pooling_param { | |
| kernel_size: 2 | |
| stride: 1 | |
| pad: 0 | |
| pool: MAX | |
| } | |
| } | |
| layer { | |
| bottom: "roi_interpolate_conv5_mask" | |
| top: "res5a_branch1_mask" | |
| name: "res5a_branch1_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1_mask" | |
| top: "res5a_branch1_mask" | |
| name: "bn5a_branch1_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1_mask" | |
| top: "res5a_branch1_mask" | |
| name: "scale5a_branch1_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "roi_interpolate_conv5_mask" | |
| top: "res5a_branch2a_mask" | |
| name: "res5a_branch2a_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 2 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a_mask" | |
| top: "res5a_branch2a_mask" | |
| name: "bn5a_branch2a_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a_mask" | |
| top: "res5a_branch2a_mask" | |
| name: "scale5a_branch2a_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2a_mask" | |
| top: "res5a_branch2a_mask" | |
| name: "res5a_branch2a_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5a_branch2a_mask" | |
| top: "res5a_branch2b_mask" | |
| name: "res5a_branch2b_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b_mask" | |
| top: "res5a_branch2b_mask" | |
| name: "bn5a_branch2b_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b_mask" | |
| top: "res5a_branch2b_mask" | |
| name: "scale5a_branch2b_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2b_mask" | |
| top: "res5a_branch2b_mask" | |
| name: "res5a_branch2b_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5a_branch2b_mask" | |
| top: "res5a_branch2c_mask" | |
| name: "res5a_branch2c_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2c_mask" | |
| top: "res5a_branch2c_mask" | |
| name: "bn5a_branch2c_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch2c_mask" | |
| top: "res5a_branch2c_mask" | |
| name: "scale5a_branch2c_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_branch1_mask" | |
| bottom: "res5a_branch2c_mask" | |
| top: "res5a_mask" | |
| name: "res5a_mask" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res5a_mask" | |
| top: "res5a_mask" | |
| name: "res5a_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5a_mask" | |
| top: "res5b_branch2a_mask" | |
| name: "res5b_branch2a_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a_mask" | |
| top: "res5b_branch2a_mask" | |
| name: "bn5b_branch2a_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a_mask" | |
| top: "res5b_branch2a_mask" | |
| name: "scale5b_branch2a_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2a_mask" | |
| top: "res5b_branch2a_mask" | |
| name: "res5b_branch2a_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5b_branch2a_mask" | |
| top: "res5b_branch2b_mask" | |
| name: "res5b_branch2b_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b_mask" | |
| top: "res5b_branch2b_mask" | |
| name: "bn5b_branch2b_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b_mask" | |
| top: "res5b_branch2b_mask" | |
| name: "scale5b_branch2b_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2b_mask" | |
| top: "res5b_branch2b_mask" | |
| name: "res5b_branch2b_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5b_branch2b_mask" | |
| top: "res5b_branch2c_mask" | |
| name: "res5b_branch2c_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2c_mask" | |
| top: "res5b_branch2c_mask" | |
| name: "bn5b_branch2c_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_branch2c_mask" | |
| top: "res5b_branch2c_mask" | |
| name: "scale5b_branch2c_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5a_mask" | |
| bottom: "res5b_branch2c_mask" | |
| top: "res5b_mask" | |
| name: "res5b_mask" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res5b_mask" | |
| top: "res5b_mask" | |
| name: "res5b_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5b_mask" | |
| top: "res5c_branch2a_mask" | |
| name: "res5c_branch2a_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a_mask" | |
| top: "res5c_branch2a_mask" | |
| name: "bn5c_branch2a_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a_mask" | |
| top: "res5c_branch2a_mask" | |
| name: "scale5c_branch2a_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2a_mask" | |
| top: "res5c_branch2a_mask" | |
| name: "res5c_branch2a_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5c_branch2a_mask" | |
| top: "res5c_branch2b_mask" | |
| name: "res5c_branch2b_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b_mask" | |
| top: "res5c_branch2b_mask" | |
| name: "bn5c_branch2b_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b_mask" | |
| top: "res5c_branch2b_mask" | |
| name: "scale5c_branch2b_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2b_mask" | |
| top: "res5c_branch2b_mask" | |
| name: "res5c_branch2b_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5c_branch2b_mask" | |
| top: "res5c_branch2c_mask" | |
| name: "res5c_branch2c_mask" | |
| type: "Convolution" | |
| convolution_param { | |
| num_output: 2048 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2c_mask" | |
| top: "res5c_branch2c_mask" | |
| name: "bn5c_branch2c_mask" | |
| type: "BatchNorm" | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5c_branch2c_mask" | |
| top: "res5c_branch2c_mask" | |
| name: "scale5c_branch2c_mask" | |
| type: "Scale" | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| bottom: "res5b_mask" | |
| bottom: "res5c_branch2c_mask" | |
| top: "res5c_mask" | |
| name: "res5c_mask" | |
| type: "Eltwise" | |
| } | |
| layer { | |
| bottom: "res5c_mask" | |
| top: "res5c_mask" | |
| name: "res5c_relu_mask" | |
| type: "ReLU" | |
| } | |
| layer { | |
| bottom: "res5c_mask" | |
| top: "pool5_mask" | |
| name: "pool5_mask" | |
| type: "Pooling" | |
| pooling_param { | |
| kernel_size: 7 | |
| stride: 1 | |
| pool: AVE | |
| } | |
| } | |
| #----- Concat Box-Mask Feature ----- | |
| layer { | |
| name: "join_box_mask" | |
| type: "Concat" | |
| bottom: "pool5_mask" | |
| bottom: "pool5" | |
| top: "join_box_mask" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| #----- Box-level Classification ----- | |
| layer { | |
| name: "cls_score" | |
| type: "InnerProduct" | |
| bottom: "join_box_mask" | |
| top: "cls_score" | |
| param { | |
| name: "cls_score_w" | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| name: "cls_score_b" | |
| lr_mult: 2.0 | |
| } | |
| inner_product_param { | |
| num_output: 2 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss_cls" | |
| type: "SoftmaxWithLoss" | |
| bottom: "cls_score" | |
| bottom: "labels" | |
| propagate_down: 1 | |
| propagate_down: 0 | |
| top: "cls_loss" | |
| loss_weight: 1 | |
| loss_param { | |
| ignore_label: -1 | |
| normalize: true | |
| } | |
| } | |
| #----- Mask-level Classification ----- | |
| layer { | |
| name: "seg_cls_score" | |
| type: "InnerProduct" | |
| bottom: "join_box_mask" | |
| top: "seg_cls_score" | |
| param { | |
| name: "seg_cls_score_w" | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| name: "seg_cls_score_b" | |
| lr_mult: 2.0 | |
| } | |
| inner_product_param { | |
| num_output: 2 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss_seg_cls" | |
| type: "SoftmaxWithLoss" | |
| bottom: "seg_cls_score" | |
| bottom: "mask_proposal_label" | |
| propagate_down: 1 | |
| propagate_down: 0 | |
| top: "seg_cls_loss" | |
| loss_weight: 1.0 | |
| loss_param { | |
| ignore_label: -1 | |
| normalize: true | |
| } | |
| } | |
| #----- Bounding-box Regression ----- | |
| layer { | |
| name: "bbox_pred" | |
| type: "InnerProduct" | |
| bottom: "join_box_mask" | |
| top: "bbox_pred" | |
| param { | |
| name: "bbox_pred_w" | |
| lr_mult: 1.0 | |
| } | |
| param { | |
| name: "bbox_pred_b" | |
| lr_mult: 2.0 | |
| } | |
| inner_product_param { | |
| num_output: 8 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.001 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "loss_bbox" | |
| type: "SmoothL1Loss" | |
| bottom: "bbox_pred" | |
| bottom: "bbox_targets" | |
| bottom: 'bbox_inside_weights' | |
| bottom: 'bbox_outside_weights' | |
| top: "bbox_loss" | |
| loss_weight: 1 | |
| } | |
| layer { | |
| name: "accuracy_seg" | |
| type: "Accuracy" | |
| bottom: "seg_cls_score" | |
| bottom: "mask_proposal_label" | |
| top: "accuracy_seg" | |
| } | |
| layer { | |
| name: "accuracy_det" | |
| type: "Accuracy" | |
| bottom: "cls_score" | |
| bottom: "labels" | |
| top: "accuracy_det" | |
| } |
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