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March 13, 2018 15:13
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| name: "exp_113_cls" | |
| layer { | |
| name: "data" | |
| type: "EnhancedImageData" | |
| top: "data" | |
| top: "label" | |
| enhanced_image_data_param { | |
| root_folder: "/data/shuhao/images/" | |
| source: "/home/shuhao/share/mrdk/train_all_bbox.txt" | |
| batch_size: 256 | |
| shuffle: true | |
| data_type: IMAGE | |
| data_num: 1 | |
| label_type: REAL | |
| label_num: 4 | |
| force_gray: true | |
| thread_num: 16 | |
| cache_in_gb: 150 | |
| data_process_param { | |
| normalize_type: CONSTANT | |
| normalize_subtractor: 127 | |
| normalize_divider: 1 | |
| crop_type: CENTER | |
| crop_h: 112 | |
| crop_w: 112 | |
| label_type: POINT | |
| has_weight: false | |
| enable_trans: true | |
| trans_x_rng { | |
| type: UNIFORM | |
| min: -112 | |
| max: 112 | |
| } | |
| trans_y_rng { | |
| type: UNIFORM | |
| min: -112 | |
| max: 112 | |
| } | |
| # enable_rotate: true | |
| # rotate_rng { | |
| # type: UNIFORM | |
| # min: -30 | |
| # max: 30 | |
| # } | |
| enable_zoom: true | |
| zoom_rng { | |
| type: UNIFORM | |
| min: 0.35 | |
| max: 0.65 | |
| } | |
| enable_noise: true | |
| noise_rng { | |
| type: UNIFORM | |
| min: -10 | |
| max: 10 | |
| } | |
| enable_occlusion: true | |
| occlusion_size_rng { | |
| type: UNIFORM | |
| min: 5 | |
| max: 50 | |
| } | |
| occlusion_center_rng { | |
| type: UNIFORM | |
| min: 0 | |
| max: 112 | |
| } | |
| occlusion_color_rng { | |
| type: UNIFORM | |
| min: 0 | |
| max: 255 | |
| } | |
| } | |
| } | |
| include { | |
| phase: TRAIN | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "EnhancedImageData" | |
| top: "data" | |
| top: "label" | |
| enhanced_image_data_param { | |
| root_folder: "/data/shuhao/images/" | |
| source: "/home/shuhao/share/mrdk/test_all_bbox.txt" | |
| batch_size: 256 | |
| shuffle: true | |
| data_type: IMAGE | |
| data_num: 1 | |
| label_type: REAL | |
| label_num: 4 | |
| force_gray: true | |
| thread_num: 16 | |
| cache_in_gb: 10 | |
| data_process_param { | |
| normalize_type: CONSTANT | |
| normalize_subtractor: 127 | |
| normalize_divider: 1 | |
| crop_type: CENTER | |
| crop_h: 112 | |
| crop_w: 112 | |
| label_type: POINT | |
| has_weight: false | |
| enable_trans: true | |
| trans_x_rng { | |
| type: UNIFORM | |
| min: -112 | |
| max: 112 | |
| } | |
| trans_y_rng { | |
| type: UNIFORM | |
| min: -112 | |
| max: 112 | |
| } | |
| enable_zoom: true | |
| zoom_rng { | |
| type: UNIFORM | |
| min: 0.35 | |
| max: 0.65 | |
| } | |
| } | |
| } | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| # net --------------------------- | |
| layer { | |
| name: "conv1/3x3_s2" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1/3x3_s2" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 6 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1/relu_3x3_s2" | |
| type: "ReLU" | |
| bottom: "conv1/3x3_s2" | |
| top: "conv1/3x3_s2" | |
| } | |
| layer { | |
| name: "pool1/3x3_s2" | |
| type: "Pooling" | |
| bottom: "conv1/3x3_s2" | |
| top: "pool1/3x3_s2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "pool1/3x3_s2" | |
| top: "conv2_1_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv2_1_1x1_reduce" | |
| top: "conv2_1_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_2_1" | |
| type: "ShuffleChannel" | |
| bottom: "conv2_1_1x1_reduce" | |
| top: "shuffle_2_1" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_2_1" | |
| top: "conv2_1_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 15 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_1_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv2_1_3x3" | |
| top: "conv2_1_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 54 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "pool2_1/3x3_shortcut" | |
| type: "Pooling" | |
| bottom: "pool1/3x3_s2" | |
| top: "pool2_1/3x3_shortcut" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "concat2_1" | |
| type: "Concat" | |
| bottom: "conv2_1_1x1_increase" | |
| bottom: "pool2_1/3x3_shortcut" | |
| top: "concat2_1" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/relu" | |
| type: "ReLU" | |
| bottom: "concat2_1" | |
| top: "concat2_1" | |
| } | |
| layer { | |
| name: "conv2_2_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "concat2_1" | |
| top: "conv2_2_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv2_2_1x1_reduce" | |
| top: "conv2_2_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_2_2" | |
| type: "ShuffleChannel" | |
| bottom: "conv2_2_1x1_reduce" | |
| top: "shuffle_2_2" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_2_2" | |
| top: "conv2_2_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 15 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv2_2_3x3" | |
| top: "conv2_2_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_2" | |
| type: "Eltwise" | |
| bottom: "concat2_1" | |
| bottom: "conv2_2_1x1_increase" | |
| top: "conv2_2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/relu" | |
| type: "ReLU" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| } | |
| layer { | |
| name: "conv2_3_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv2_2" | |
| top: "conv2_3_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv2_3_1x1_reduce" | |
| top: "conv2_3_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_2_3" | |
| type: "ShuffleChannel" | |
| bottom: "conv2_3_1x1_reduce" | |
| top: "shuffle_2_3" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_2_3" | |
| top: "conv2_3_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 15 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv2_3_3x3" | |
| top: "conv2_3_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_3" | |
| type: "Eltwise" | |
| bottom: "conv2_2" | |
| bottom: "conv2_3_1x1_increase" | |
| top: "conv2_3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/relu" | |
| type: "ReLU" | |
| bottom: "conv2_3" | |
| top: "conv2_3" | |
| } | |
| layer { | |
| name: "conv2_4_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv2_3" | |
| top: "conv2_4_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_4_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv2_4_1x1_reduce" | |
| top: "conv2_4_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_2_4" | |
| type: "ShuffleChannel" | |
| bottom: "conv2_4_1x1_reduce" | |
| top: "shuffle_2_4" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv2_4_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_2_4" | |
| top: "conv2_4_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 15 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 15 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_4_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv2_4_3x3" | |
| top: "conv2_4_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv2_4" | |
| type: "Eltwise" | |
| bottom: "conv2_3" | |
| bottom: "conv2_4_1x1_increase" | |
| top: "conv2_4" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv2_4/relu" | |
| type: "ReLU" | |
| bottom: "conv2_4" | |
| top: "conv2_4" | |
| } | |
| layer { | |
| name: "conv3_1_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv2_4" | |
| top: "conv3_1_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_1_1x1_reduce" | |
| top: "conv3_1_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_1" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_1_1x1_reduce" | |
| top: "shuffle_3_1" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_1" | |
| top: "conv3_1_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_1_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_1_3x3" | |
| top: "conv3_1_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "pool3_1/3x3_shortcut" | |
| type: "Pooling" | |
| bottom: "conv2_4" | |
| top: "pool3_1/3x3_shortcut" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "concat3_1" | |
| type: "Concat" | |
| bottom: "conv3_1_1x1_increase" | |
| bottom: "pool3_1/3x3_shortcut" | |
| top: "concat3_1" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/relu" | |
| type: "ReLU" | |
| bottom: "concat3_1" | |
| top: "concat3_1" | |
| } | |
| layer { | |
| name: "conv3_2_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "concat3_1" | |
| top: "conv3_2_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_2_1x1_reduce" | |
| top: "conv3_2_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_2" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_2_1x1_reduce" | |
| top: "shuffle_3_2" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_2" | |
| top: "conv3_2_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_2_3x3" | |
| top: "conv3_2_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_2" | |
| type: "Eltwise" | |
| bottom: "concat3_1" | |
| bottom: "conv3_2_1x1_increase" | |
| top: "conv3_2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/relu" | |
| type: "ReLU" | |
| bottom: "conv3_2" | |
| top: "conv3_2" | |
| } | |
| layer { | |
| name: "conv3_3_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_2" | |
| top: "conv3_3_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_3_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_3_1x1_reduce" | |
| top: "conv3_3_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_3" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_3_1x1_reduce" | |
| top: "shuffle_3_3" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_3" | |
| top: "conv3_3_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_3_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_3_3x3" | |
| top: "conv3_3_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_3" | |
| type: "Eltwise" | |
| bottom: "conv3_2" | |
| bottom: "conv3_3_1x1_increase" | |
| top: "conv3_3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/relu" | |
| type: "ReLU" | |
| bottom: "conv3_3" | |
| top: "conv3_3" | |
| } | |
| layer { | |
| name: "conv3_4_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_3" | |
| top: "conv3_4_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_4_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_4_1x1_reduce" | |
| top: "conv3_4_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_4" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_4_1x1_reduce" | |
| top: "shuffle_3_4" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_4_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_4" | |
| top: "conv3_4_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_4_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_4_3x3" | |
| top: "conv3_4_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_4" | |
| type: "Eltwise" | |
| bottom: "conv3_3" | |
| bottom: "conv3_4_1x1_increase" | |
| top: "conv3_4" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/relu" | |
| type: "ReLU" | |
| bottom: "conv3_4" | |
| top: "conv3_4" | |
| } | |
| layer { | |
| name: "conv3_5_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_4" | |
| top: "conv3_5_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_5_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_5_1x1_reduce" | |
| top: "conv3_5_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_5" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_5_1x1_reduce" | |
| top: "shuffle_3_5" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_5_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_5" | |
| top: "conv3_5_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_5_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_5_3x3" | |
| top: "conv3_5_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_5" | |
| type: "Eltwise" | |
| bottom: "conv3_4" | |
| bottom: "conv3_5_1x1_increase" | |
| top: "conv3_5" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_5/relu" | |
| type: "ReLU" | |
| bottom: "conv3_5" | |
| top: "conv3_5" | |
| } | |
| layer { | |
| name: "conv3_6_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_5" | |
| top: "conv3_6_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_6_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_6_1x1_reduce" | |
| top: "conv3_6_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_6" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_6_1x1_reduce" | |
| top: "shuffle_3_6" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_6_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_6" | |
| top: "conv3_6_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_6_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_6_3x3" | |
| top: "conv3_6_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_6" | |
| type: "Eltwise" | |
| bottom: "conv3_5" | |
| bottom: "conv3_6_1x1_increase" | |
| top: "conv3_6" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_6/relu" | |
| type: "ReLU" | |
| bottom: "conv3_6" | |
| top: "conv3_6" | |
| } | |
| layer { | |
| name: "conv3_7_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_6" | |
| top: "conv3_7_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_7_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_7_1x1_reduce" | |
| top: "conv3_7_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_7" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_7_1x1_reduce" | |
| top: "shuffle_3_7" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_7_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_7" | |
| top: "conv3_7_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_7_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_7_3x3" | |
| top: "conv3_7_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_7" | |
| type: "Eltwise" | |
| bottom: "conv3_6" | |
| bottom: "conv3_7_1x1_increase" | |
| top: "conv3_7" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_7/relu" | |
| type: "ReLU" | |
| bottom: "conv3_7" | |
| top: "conv3_7" | |
| } | |
| layer { | |
| name: "conv3_8_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_7" | |
| top: "conv3_8_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_8_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv3_8_1x1_reduce" | |
| top: "conv3_8_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_3_8" | |
| type: "ShuffleChannel" | |
| bottom: "conv3_8_1x1_reduce" | |
| top: "shuffle_3_8" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv3_8_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_3_8" | |
| top: "conv3_8_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 30 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 30 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_8_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv3_8_3x3" | |
| top: "conv3_8_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv3_8" | |
| type: "Eltwise" | |
| bottom: "conv3_7" | |
| bottom: "conv3_8_1x1_increase" | |
| top: "conv3_8" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv3_8/relu" | |
| type: "ReLU" | |
| bottom: "conv3_8" | |
| top: "conv3_8" | |
| } | |
| layer { | |
| name: "conv4_1_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv3_8" | |
| top: "conv4_1_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1_1x1_reduce" | |
| top: "conv4_1_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_4_1" | |
| type: "ShuffleChannel" | |
| bottom: "conv4_1_1x1_reduce" | |
| top: "shuffle_4_1" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_4_1" | |
| top: "conv4_1_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 60 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_1_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_1_3x3" | |
| top: "conv4_1_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 120 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "pool4_1/3x3_shortcut" | |
| type: "Pooling" | |
| bottom: "conv3_8" | |
| top: "pool4_1/3x3_shortcut" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "concat4_1" | |
| type: "Concat" | |
| bottom: "conv4_1_1x1_increase" | |
| bottom: "pool4_1/3x3_shortcut" | |
| top: "concat4_1" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/relu" | |
| type: "ReLU" | |
| bottom: "concat4_1" | |
| top: "concat4_1" | |
| } | |
| layer { | |
| name: "conv4_2_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "concat4_1" | |
| top: "conv4_2_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2_1x1_reduce" | |
| top: "conv4_2_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_4_2" | |
| type: "ShuffleChannel" | |
| bottom: "conv4_2_1x1_reduce" | |
| top: "shuffle_4_2" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_4_2" | |
| top: "conv4_2_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 60 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_2_3x3" | |
| top: "conv4_2_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 240 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_2" | |
| type: "Eltwise" | |
| bottom: "concat4_1" | |
| bottom: "conv4_2_1x1_increase" | |
| top: "conv4_2" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| } | |
| layer { | |
| name: "conv4_3_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_2" | |
| top: "conv4_3_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3_1x1_reduce" | |
| top: "conv4_3_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_4_3" | |
| type: "ShuffleChannel" | |
| bottom: "conv4_3_1x1_reduce" | |
| top: "shuffle_4_3" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_4_3" | |
| top: "conv4_3_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 60 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_3_3x3" | |
| top: "conv4_3_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 240 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3" | |
| type: "Eltwise" | |
| bottom: "conv4_2" | |
| bottom: "conv4_3_1x1_increase" | |
| top: "conv4_3" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3" | |
| top: "conv4_3" | |
| } | |
| layer { | |
| name: "conv4_4_1x1_reduce" | |
| type: "Convolution" | |
| bottom: "conv4_3" | |
| top: "conv4_4_1x1_reduce" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4_1x1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4_1x1_reduce" | |
| top: "conv4_4_1x1_reduce" | |
| } | |
| layer { | |
| name: "shuffle_4_4" | |
| type: "ShuffleChannel" | |
| bottom: "conv4_4_1x1_reduce" | |
| top: "shuffle_4_4" | |
| shuffle_channel_param { | |
| group: 3 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4_3x3" | |
| type: "Convolution" | |
| bottom: "shuffle_4_4" | |
| top: "conv4_4_3x3" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 60 | |
| bias_term: true | |
| pad: 1 | |
| kernel_size: 3 | |
| group: 60 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4_1x1_increase" | |
| type: "Convolution" | |
| bottom: "conv4_4_3x3" | |
| top: "conv4_4_1x1_increase" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 240 | |
| bias_term: true | |
| pad: 0 | |
| kernel_size: 1 | |
| group: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_4" | |
| type: "Eltwise" | |
| bottom: "conv4_3" | |
| bottom: "conv4_4_1x1_increase" | |
| top: "conv4_4" | |
| eltwise_param { | |
| operation: SUM | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4" | |
| top: "conv4_4" | |
| } | |
| layer { | |
| name: "pool5/7x7_s1" | |
| type: "Pooling" | |
| bottom: "conv4_4" | |
| top: "pool5/7x7_s1" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 4 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "pool5/7x7_s1" | |
| type: "Gather" | |
| bottom: "pool5/7x7_s1" | |
| top: "pool5/7x7_s1_gather" | |
| } | |
| layer { | |
| name: "fc6" | |
| type: "InnerProduct" | |
| bottom: "pool5/7x7_s1_gather" | |
| top: "fc6" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 256 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| std: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6" | |
| type: "ReLU" | |
| bottom: "fc6" | |
| top: "fc6" | |
| } | |
| layer { | |
| name: "fc7" | |
| type: "InnerProduct" | |
| bottom: "fc6" | |
| top: "fc7" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 256 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| std: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu7" | |
| type: "ReLU" | |
| bottom: "fc7" | |
| top: "fc7" | |
| } | |
| layer { | |
| name: "fc8" | |
| type: "InnerProduct" | |
| bottom: "fc7" | |
| top: "fc8" | |
| param { | |
| lr_mult: 0 # 1 | |
| decay_mult: 0 # 1 | |
| } | |
| param { | |
| lr_mult: 0 # 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 4 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| std: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc6_cls" | |
| type: "InnerProduct" | |
| bottom: "pool5/7x7_s1_gather" | |
| top: "fc6_cls" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 256 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc6_cls/relu" | |
| type: "ReLU" | |
| bottom: "fc6_cls" | |
| top: "fc6_cls" | |
| } | |
| layer { | |
| name: "fc7_cls" | |
| type: "InnerProduct" | |
| bottom: "fc6_cls" | |
| top: "fc7_cls" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 256 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc7_cls/relu" | |
| type: "ReLU" | |
| bottom: "fc7_cls" | |
| top: "fc7_cls" | |
| } | |
| layer { | |
| name: "fc8_cls" | |
| type: "InnerProduct" | |
| bottom: "fc7_cls" | |
| top: "fc8_cls" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 2 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| # loss layer ---------------------------------------- | |
| layer { | |
| name: "label_gather" | |
| type: "Gather" | |
| bottom: "label" | |
| top: "label_gather" | |
| } | |
| layer { | |
| name: "alignment_accuracy" | |
| type: "AlignmentAccuracy" | |
| bottom: "fc8" | |
| bottom: "label_gather" | |
| top: "alignment_accuracy" | |
| top: "error" | |
| alignment_accuracy_param{ | |
| ref_start: 0 | |
| ref_end: 1 | |
| use_mean_shape: false | |
| accuracy_for_each_point: true | |
| } | |
| } | |
| layer { | |
| name: "cls_label" | |
| type: "Threshold" | |
| bottom: "error" | |
| top: "cls_label" | |
| threshold_param { | |
| threshold: 0.2 | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "fc8_cls" | |
| bottom: "cls_label" | |
| top: "loss" | |
| } | |
| layer { | |
| name: "accuracy" | |
| type: "Accuracy" | |
| bottom: "fc8_cls" | |
| bottom: "cls_label" | |
| top: "accuracy" | |
| include { | |
| phase: TEST | |
| } | |
| } |
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