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| name: "StructureFeatureNet" | |
| #-------------- Train data ----------------- | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: false | |
| mean_value: 128 | |
| mean_value: 128 | |
| mean_value: 128 | |
| } | |
| data_param { | |
| source: "cache/lsp/LMDB/LMDB_train_data" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "labelmask" | |
| include { | |
| phase: TRAIN | |
| } | |
| data_param { | |
| source: "cache/lsp/LMDB/LMDB_train_labelmap" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "slice_label_train" | |
| type: "Slice" | |
| bottom: "labelmask" | |
| include{phase: TRAIN} | |
| ## Example of label with a shape N x 3 x 1 x 1 | |
| top: "label0" | |
| top: "mask" | |
| slice_param { | |
| axis: 1 | |
| slice_point: 26 # 26 points and 1 mask to select points | |
| } | |
| } | |
| layer { | |
| name: "mix" | |
| type: "Data" | |
| top: "mix" | |
| include { | |
| phase: TRAIN | |
| } | |
| data_param { | |
| source: "cache/lsp/LMDB/LMDB_train_mix" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| } | |
| layer{ | |
| name: "label2mix" | |
| type: "LabelMix" | |
| bottom: "label0" | |
| bottom: "mix" | |
| include{phase: TRAIN} | |
| label_mix_param{ | |
| mix_num: 13 | |
| } | |
| top: "label" | |
| } | |
| #-------------- TEST ----------------------- | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| mirror: false | |
| mean_value: 128 | |
| mean_value: 128 | |
| mean_value: 128 | |
| } | |
| data_param { | |
| source: "cache/lsp/LMDB/LMDB_val_data" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "labelmask" | |
| include { | |
| phase: TEST | |
| } | |
| data_param { | |
| source: "cache/lsp/LMDB/LMDB_val_labelmap" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "slice_label_val" | |
| type: "Slice" | |
| bottom: "labelmask" | |
| include{phase: TEST} | |
| ## Example of label with a shape N x 3 x 1 x 1 | |
| top: "label0" | |
| top: "mask" | |
| slice_param { | |
| axis: 1 | |
| slice_point: 26 | |
| } | |
| } | |
| layer { | |
| name: "mix" | |
| type: "Data" | |
| top: "mix" | |
| include { | |
| phase: TEST | |
| } | |
| data_param { | |
| source: "cache/lsp/LMDB/LMDB_val_mix" | |
| batch_size: 1 | |
| backend: LMDB | |
| } | |
| } | |
| layer{ | |
| name: "label2mix" | |
| type: "LabelMix" | |
| bottom: "label0" | |
| bottom: "mix" | |
| include{phase: TEST} | |
| label_mix_param{ | |
| mix_num: 13 | |
| } | |
| top: "label" | |
| } | |
| #################################################### | |
| #-------------- conv 1 --------------- | |
| layer { | |
| name: "conv1_1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu1_1" | |
| type: "ReLU" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| } | |
| layer { | |
| name: "conv1_2" | |
| type: "Convolution" | |
| bottom: "conv1_1" | |
| top: "conv1_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu1_2" | |
| type: "ReLU" | |
| bottom: "conv1_2" | |
| top: "conv1_2" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1_2" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| #-------------- conv 2 --------------- | |
| layer { | |
| name: "conv2_1" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv2_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu2_1" | |
| type: "ReLU" | |
| bottom: "conv2_1" | |
| top: "conv2_1" | |
| } | |
| layer { | |
| name: "conv2_2" | |
| type: "Convolution" | |
| bottom: "conv2_1" | |
| top: "conv2_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu2_2" | |
| type: "ReLU" | |
| bottom: "conv2_2" | |
| top: "conv2_2" | |
| } | |
| layer { | |
| name: "pool2" | |
| type: "Pooling" | |
| bottom: "conv2_2" | |
| top: "pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| #-------------- conv 3 --------------- | |
| layer { | |
| name: "conv3_1" | |
| type: "Convolution" | |
| bottom: "pool2" | |
| top: "conv3_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu3_1" | |
| type: "ReLU" | |
| bottom: "conv3_1" | |
| top: "conv3_1" | |
| } | |
| layer { | |
| name: "conv3_2" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv3_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu3_2" | |
| type: "ReLU" | |
| bottom: "conv3_2" | |
| top: "conv3_2" | |
| } | |
| layer { | |
| name: "conv3_3" | |
| type: "Convolution" | |
| bottom: "conv3_2" | |
| top: "conv3_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu3_3" | |
| type: "ReLU" | |
| bottom: "conv3_3" | |
| top: "conv3_3" | |
| } | |
| layer { | |
| name: "pool3" | |
| type: "Pooling" | |
| bottom: "conv3_3" | |
| top: "pool3" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| #---------------- conv 4 (3)---------------------- | |
| layer { | |
| name: "conv4_1" | |
| type: "Convolution" | |
| bottom: "pool3" | |
| top: "conv4_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu4_1" | |
| type: "ReLU" | |
| bottom: "conv4_1" | |
| top: "conv4_1" | |
| } | |
| layer { | |
| name: "conv4_2" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv4_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu4_2" | |
| type: "ReLU" | |
| bottom: "conv4_2" | |
| top: "conv4_2" | |
| } | |
| layer { | |
| name: "conv4_3" | |
| type: "Convolution" | |
| bottom: "conv4_2" | |
| top: "conv4_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu4_3" | |
| type: "ReLU" | |
| bottom: "conv4_3" | |
| top: "pool4" | |
| } | |
| #layer { | |
| # name: "pool4" | |
| # type: "Pooling" | |
| # bottom: "conv4_3" | |
| # top: "pool4" | |
| # pooling_param { | |
| # pool: MAX | |
| # kernel_size: 2 | |
| # stride: 2 | |
| # } | |
| #} | |
| #---------------- conv 5 ---------------------- | |
| layer { | |
| name: "conv5_1" | |
| type: "Convolution" | |
| bottom: "pool4" | |
| top: "conv5_1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu5_1" | |
| type: "ReLU" | |
| bottom: "conv5_1" | |
| top: "conv5_1" | |
| } | |
| layer { | |
| name: "conv5_2" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv5_2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu5_2" | |
| type: "ReLU" | |
| bottom: "conv5_2" | |
| top: "conv5_2" | |
| } | |
| layer { | |
| name: "conv5_3" | |
| type: "Convolution" | |
| bottom: "conv5_2" | |
| top: "conv5_3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layer { | |
| name: "relu5_3" | |
| type: "ReLU" | |
| bottom: "conv5_3" | |
| top: "pool5" | |
| } | |
| #---------------- fconv layers ---------------------- | |
| layer { | |
| name: "fcn6_new" | |
| type: "Convolution" | |
| bottom: "pool5" | |
| top: "fconv6" | |
| param { | |
| lr_mult: 10 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 20 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 1024 # if your gpu memory is large enough, using pre-train 4096 can get better performance | |
| kernel_size: 7 | |
| pad: 3 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.001 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| #---------------- BN ----------------- | |
| layer { # if you use pre-trained model, you can remove this layer. | |
| name: "fconv6_bn" type: "BN" bottom: "fconv6" top: "fconv6_bn" | |
| param { lr_mult: 1 decay_mult: 0 } | |
| param { lr_mult: 1 decay_mult: 0 } | |
| bn_param { | |
| slope_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu6" | |
| type: "ReLU" | |
| bottom: "fconv6_bn" | |
| top: "fconv6_bn" | |
| } | |
| layer { | |
| name: "drop6" | |
| type: "ChannelDropout" | |
| bottom: "fconv6_bn" | |
| top: "fconv6_bn" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| ############################################################################# | |
| #---------------------- seperated layers ------------------------------- | |
| ############################################################################# | |
| ####################################################### | |
| #-------------- fconv7_7 ----------------- | |
| layer {name: "fconv7_7" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_7" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_7" type: "ReLU" bottom: "fconv7_7" top: "fconv7_7+"} | |
| #--------- pass info from: 7 to 6 (7*7*2) ---------------- | |
| layer {name: "fconv7_7to6_step1" type: "Convolution" bottom: "fconv7_7+" top: "fconv7_7to6_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_7to6_step1" type: "ReLU" bottom: "fconv7_7to6_step1" top: "fconv7_7to6_step1"} | |
| #---- step 2 ------ | |
| layer {name: "fconv7_7to6_step2" type: "Convolution" bottom: "fconv7_7to6_step1" top: "fconv7_7to6_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ################################################## | |
| #-------------- fconv7_6 9*9*2 ----------------- | |
| layer {name: "fconv7_6" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_6" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #------------------ add info comed from 6---------------------------- | |
| layer {name: "Pass_7to6" type: "Eltwise" bottom:"fconv7_7to6_step2" bottom:"fconv7_6" top: "fconv7_6+"} | |
| layer {name: "relu7_6" type: "ReLU" bottom: "fconv7_6+" top: "fconv7_6+"} | |
| #--------- pass info from: 6 to 5 (7*7*2) ---------------- | |
| layer {name: "fconv7_6to5_step1" type: "Convolution" bottom: "fconv7_6+" top: "fconv7_6to5_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_6to5_step1" type: "ReLU" bottom: "fconv7_6to5_step1" top: "fconv7_6to5_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_6to5_step2" type: "Convolution" bottom: "fconv7_6to5_step1" top: "fconv7_6to5_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_5 ----------------- | |
| layer {name: "fconv7_5" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_5" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from: point 6 ---------------- | |
| layer {name: "Pass_6to5" type: "Eltwise" bottom:"fconv7_6to5_step2" bottom:"fconv7_5" top: "fconv7_5+"} | |
| layer {name: "relu7_5" type: "ReLU" bottom: "fconv7_5+" top: "fconv7_5+"} | |
| #--------- pass info from: 5 to 4 (7*7*2) ---------------- | |
| layer {name: "fconv7_5to4_step1" type: "Convolution" bottom: "fconv7_5+" top: "fconv7_5to4_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_5to4_step1" type: "ReLU" bottom: "fconv7_5to4_step1" top: "fconv7_5to4_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_5to4_step2" type: "Convolution" bottom: "fconv7_5to4_step1" top: "fconv7_5to4_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_4 ----------------- | |
| layer {name: "fconv7_4" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_4" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 5 to 4 ---------------- | |
| layer {name: "Pass_5to4" type: "Eltwise" bottom:"fconv7_5to4_step2" bottom:"fconv7_4" top: "fconv7_4+"} | |
| layer {name: "relu7_4" type: "ReLU" bottom: "fconv7_4+" top: "fconv7_4+"} | |
| #--------- pass info from: 4 to 3 (7*7*2) ---------------- | |
| layer {name: "fconv7_4to3_step1" type: "Convolution" bottom: "fconv7_4+" top: "fconv7_4to3_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_4to3_step1" type: "ReLU" bottom: "fconv7_4to3_step1" top: "fconv7_4to3_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_4to3_step2" type: "Convolution" bottom: "fconv7_4to3_step1" top: "fconv7_4to3_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_14 ----------------- | |
| layer {name: "fconv7_14" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_14" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_14" type: "ReLU" bottom: "fconv7_14" top: "fconv7_14+"} | |
| #--------- pass info from: 14 to 13 (7*7*2) ---------------- | |
| layer {name: "fconv7_14to13_step1" type: "Convolution" bottom: "fconv7_14+" top: "fconv7_14to13_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_14to13_step1" type: "ReLU" bottom: "fconv7_14to13_step1" top: "fconv7_14to13_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_14to13_step2" type: "Convolution" bottom: "fconv7_14to13_step1" top: "fconv7_14to13_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_13 ----------------- | |
| layer {name: "fconv7_13" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_13" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 14 to 13 ---------------- | |
| layer {name: "Pass_14to13" type: "Eltwise" bottom:"fconv7_14to13_step2" bottom:"fconv7_13" top: "fconv7_13+"} | |
| layer {name: "relu7_13" type: "ReLU" bottom: "fconv7_13+" top: "fconv7_13+"} | |
| #--------- pass info from: 13 to 12 (7*7*2) ---------------- | |
| layer {name: "fconv7_13to12_step1" type: "Convolution" bottom: "fconv7_13+" top: "fconv7_13to12_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_13to12_step1" type: "ReLU" bottom: "fconv7_13to12_step1" top: "fconv7_13to12_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_13to12_step2" type: "Convolution" bottom: "fconv7_13to12_step1" top: "fconv7_13to12_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_12 ----------------- | |
| layer {name: "fconv7_12" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_12" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 13 to 12 ---------------- | |
| layer {name: "Pass_13to12" type: "Eltwise" bottom:"fconv7_13to12_step2" bottom:"fconv7_12" top: "fconv7_12+"} | |
| layer {name: "relu7_12" type: "ReLU" bottom: "fconv7_12+" top: "fconv7_12+"} | |
| #--------- pass info from: 12 to 11 (7*7*2) ---------------- | |
| layer {name: "fconv7_12to11_step1" type: "Convolution" bottom: "fconv7_12+" top: "fconv7_12to11_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_12to11_step1" type: "ReLU" bottom: "fconv7_12to11_step1" top: "fconv7_12to11_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_12to11_step2" type: "Convolution" bottom: "fconv7_12to11_step1" top: "fconv7_12to11_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_11 ----------------- | |
| layer {name: "fconv7_11" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_11" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 12 to 11 ---------------- | |
| layer {name: "Pass_12to11" type: "Eltwise" bottom:"fconv7_12to11_step2" bottom:"fconv7_11" top: "fconv7_11+"} | |
| layer {name: "relu7_11" type: "ReLU" bottom: "fconv7_11+" top: "fconv7_11+"} | |
| #--------- pass info from: 11 to 10 (7*7*2) ---------------- | |
| layer {name: "fconv7_11to10_step1" type: "Convolution" bottom: "fconv7_11+" top: "fconv7_11to10_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_11to10_step1" type: "ReLU" bottom: "fconv7_11to10_step1" top: "fconv7_11to10_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_11to10_step2" type: "Convolution" bottom: "fconv7_11to10_step1" top: "fconv7_11to10_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_10 ----------------- | |
| layer {name: "fconv7_10" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_10" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 11 to 10 ---------------- | |
| layer {name: "Pass_11to10" type: "Eltwise" bottom:"fconv7_11to10_step2" bottom:"fconv7_10" top: "fconv7_10+"} | |
| layer {name: "relu7_10" type: "ReLU" bottom: "fconv7_10+" top: "fconv7_10+"} | |
| #--------- pass info from: 10 to 9 (7*7*2) ---------------- | |
| layer {name: "fconv7_10to9_step1" type: "Convolution" bottom: "fconv7_10+" top: "fconv7_10to9_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_10to9_step1" type: "ReLU" bottom: "fconv7_10to9_step1" top: "fconv7_10to9_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_10to9_step2" type: "Convolution" bottom: "fconv7_10to9_step1" top: "fconv7_10to9_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_9 ----------------- | |
| layer {name: "fconv7_9" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_9" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 10 to 9 ---------------- | |
| layer {name: "Pass_10to9" type: "Eltwise" bottom:"fconv7_10to9_step2" bottom:"fconv7_9" top: "fconv7_9+"} | |
| layer {name: "relu7_9" type: "ReLU" bottom: "fconv7_9+" top: "fconv7_9+"} | |
| #--------- pass info from: 9 to 8 (7*7*2) ---------------- | |
| layer {name: "fconv7_9to8_step1" type: "Convolution" bottom: "fconv7_9+" top: "fconv7_9to8_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_9to8_step1" type: "ReLU" bottom: "fconv7_9to8_step1" top: "fconv7_9to8_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_9to8_step2" type: "Convolution" bottom: "fconv7_9to8_step1" top: "fconv7_9to8_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_8 ----------------- | |
| layer {name: "fconv7_8" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_8" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 9 to 8 ---------------- | |
| layer {name: "Pass_9to8" type: "Eltwise" bottom:"fconv7_9to8_step2" bottom:"fconv7_8" top: "fconv7_8+"} | |
| layer {name: "relu7_8" type: "ReLU" bottom: "fconv7_8+" top: "fconv7_8+"} | |
| #--------- pass info from: 8 to 3 (7*7*2) ---------------- | |
| layer {name: "fconv7_8to3_step1" type: "Convolution" bottom: "fconv7_8+" top: "fconv7_8to3_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_8to3_step1" type: "ReLU" bottom: "fconv7_8to3_step1" top: "fconv7_8to3_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_8to3_step2" type: "Convolution" bottom: "fconv7_8to3_step1" top: "fconv7_8to3_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_3 ----------------- | |
| layer {name: "fconv7_3" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_3" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 4 8 to 3 ---------------- | |
| layer {name: "Pass_84to3" type: "Eltwise" bottom:"fconv7_8to3_step2" bottom:"fconv7_4to3_step2" bottom:"fconv7_3" top: "fconv7_3+"} | |
| layer {name: "relu7_3" type: "ReLU" bottom: "fconv7_3+" top: "fconv7_3+"} | |
| #--------- pass info from: 3 to 2 (7*7*2) ---------------- | |
| layer {name: "fconv7_3to2_step1" type: "Convolution" bottom: "fconv7_3+" top: "fconv7_3to2_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_3to2_step1" type: "ReLU" bottom: "fconv7_3to2_step1" top: "fconv7_3to2_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_3to2_step2" type: "Convolution" bottom: "fconv7_3to2_step1" top: "fconv7_3to2_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_19 ----------------- | |
| layer {name: "fconv7_19" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_19" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_19" type: "ReLU" bottom: "fconv7_19" top: "fconv7_19+"} | |
| #--------- pass info from: 19 to 18 (7*7*2) ---------------- | |
| layer {name: "fconv7_19to18_step1" type: "Convolution" bottom: "fconv7_19+" top: "fconv7_19to18_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_19to18_step1" type: "ReLU" bottom: "fconv7_19to18_step1" top: "fconv7_19to18_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_19to18_step2" type: "Convolution" bottom: "fconv7_19to18_step1" top: "fconv7_19to18_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_18 ----------------- | |
| layer {name: "fconv7_18" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_18" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 19 to 18 ---------------- | |
| layer {name: "Pass_19to18" type: "Eltwise" bottom:"fconv7_19to18_step2" bottom:"fconv7_18" top: "fconv7_18+"} | |
| layer {name: "relu7_18" type: "ReLU" bottom: "fconv7_18+" top: "fconv7_18+"} | |
| #--------- pass info from: 18 to 17 (7*7*2) ---------------- | |
| layer {name: "fconv7_18to17_step1" type: "Convolution" bottom: "fconv7_18+" top: "fconv7_18to17_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_18to17_step1" type: "ReLU" bottom: "fconv7_18to17_step1" top: "fconv7_18to17_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_18to17_step2" type: "Convolution" bottom: "fconv7_18to17_step1" top: "fconv7_18to17_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_17 ----------------- | |
| layer {name: "fconv7_17" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_17" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 18 to 17 ---------------- | |
| layer {name: "Pass_18to17" type: "Eltwise" bottom:"fconv7_18to17_step2" bottom:"fconv7_17" top: "fconv7_17+"} | |
| layer {name: "relu7_17" type: "ReLU" bottom: "fconv7_17+" top: "fconv7_17+"} | |
| #--------- pass info from: 17 to 16 (7*7*2) ---------------- | |
| layer {name: "fconv7_17to16_step1" type: "Convolution" bottom: "fconv7_17+" top: "fconv7_17to16_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_17to16_step1" type: "ReLU" bottom: "fconv7_17to16_step1" top: "fconv7_17to16_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_17to16_step2" type: "Convolution" bottom: "fconv7_17to16_step1" top: "fconv7_17to16_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_16 ----------------- | |
| layer {name: "fconv7_16" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_16" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 17 to 16 ---------------- | |
| layer {name: "Pass_17to16" type: "Eltwise" bottom:"fconv7_17to16_step2" bottom:"fconv7_16" top: "fconv7_16+"} | |
| layer {name: "relu7_16" type: "ReLU" bottom: "fconv7_16+" top: "fconv7_16+"} | |
| #--------- pass info from: 16 to 15 (7*7*2) ---------------- | |
| layer {name: "fconv7_16to15_step1" type: "Convolution" bottom: "fconv7_16+" top: "fconv7_16to15_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_16to15_step1" type: "ReLU" bottom: "fconv7_16to15_step1" top: "fconv7_16to15_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_16to15_step2" type: "Convolution" bottom: "fconv7_16to15_step1" top: "fconv7_16to15_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_26 ----------------- | |
| layer {name: "fconv7_26" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_26" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_26" type: "ReLU" bottom: "fconv7_26" top: "fconv7_26+"} | |
| #--------- pass info from: 26 to 25 (7*7*2) ---------------- | |
| layer {name: "fconv7_26to25_step1" type: "Convolution" bottom: "fconv7_26+" top: "fconv7_26to25_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_26to25_step1" type: "ReLU" bottom: "fconv7_26to25_step1" top: "fconv7_26to25_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_26to25_step2" type: "Convolution" bottom: "fconv7_26to25_step1" top: "fconv7_26to25_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_25 ----------------- | |
| layer {name: "fconv7_25" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_25" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 26 to 25 ---------------- | |
| layer {name: "Pass_26to25" type: "Eltwise" bottom:"fconv7_26to25_step2" bottom:"fconv7_25" top: "fconv7_25+"} | |
| layer {name: "relu7_25" type: "ReLU" bottom: "fconv7_25+" top: "fconv7_25+"} | |
| #--------- pass info from: 25 to 24 (7*7*2) ---------------- | |
| layer {name: "fconv7_25to24_step1" type: "Convolution" bottom: "fconv7_25+" top: "fconv7_25to24_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_25to24_step1" type: "ReLU" bottom: "fconv7_25to24_step1" top: "fconv7_25to24_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_25to24_step2" type: "Convolution" bottom: "fconv7_25to24_step1" top: "fconv7_25to24_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_24 ----------------- | |
| layer {name: "fconv7_24" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_24" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 25 to 24 ---------------- | |
| layer {name: "Pass_25to24" type: "Eltwise" bottom:"fconv7_25to24_step2" bottom:"fconv7_24" top: "fconv7_24+"} | |
| layer {name: "relu7_24" type: "ReLU" bottom: "fconv7_24+" top: "fconv7_24+"} | |
| #--------- pass info from: 24 to 23 (7*7*2) ---------------- | |
| layer {name: "fconv7_24to23_step1" type: "Convolution" bottom: "fconv7_24+" top: "fconv7_24to23_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_24to23_step1" type: "ReLU" bottom: "fconv7_24to23_step1" top: "fconv7_24to23_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_24to23_step2" type: "Convolution" bottom: "fconv7_24to23_step1" top: "fconv7_24to23_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_23 ----------------- | |
| layer {name: "fconv7_23" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_23" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 24 to 23 ---------------- | |
| layer {name: "Pass_24to23" type: "Eltwise" bottom:"fconv7_24to23_step2" bottom:"fconv7_23" top: "fconv7_23+"} | |
| layer {name: "relu7_23" type: "ReLU" bottom: "fconv7_23+" top: "fconv7_23+"} | |
| #--------- pass info from: 23 to 22 (7*7*2) ---------------- | |
| layer {name: "fconv7_23to22_step1" type: "Convolution" bottom: "fconv7_23+" top: "fconv7_23to22_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_23to22_step1" type: "ReLU" bottom: "fconv7_23to22_step1" top: "fconv7_23to22_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_23to22_step2" type: "Convolution" bottom: "fconv7_23to22_step1" top: "fconv7_23to22_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_22 ----------------- | |
| layer {name: "fconv7_22" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_22" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 23 to 22 ---------------- | |
| layer {name: "Pass_23to22" type: "Eltwise" bottom:"fconv7_23to22_step2" bottom:"fconv7_22" top: "fconv7_22+"} | |
| layer {name: "relu7_22" type: "ReLU" bottom: "fconv7_22+" top: "fconv7_22+"} | |
| #--------- pass info from: 22 to 21 (7*7*2) ---------------- | |
| layer {name: "fconv7_22to21_step1" type: "Convolution" bottom: "fconv7_22+" top: "fconv7_22to21_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_22to21_step1" type: "ReLU" bottom: "fconv7_22to21_step1" top: "fconv7_22to21_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_22to21_step2" type: "Convolution" bottom: "fconv7_22to21_step1" top: "fconv7_22to21_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_21 ----------------- | |
| layer {name: "fconv7_21" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_21" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 22 to 21 ---------------- | |
| layer {name: "Pass_22to21" type: "Eltwise" bottom:"fconv7_22to21_step2" bottom:"fconv7_21" top: "fconv7_21+"} | |
| layer {name: "relu7_21" type: "ReLU" bottom: "fconv7_21+" top: "fconv7_21+"} | |
| #--------- pass info from: 21 to 20 (7*7*2) ---------------- | |
| layer {name: "fconv7_21to20_step1" type: "Convolution" bottom: "fconv7_21+" top: "fconv7_21to20_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_21to20_step1" type: "ReLU" bottom: "fconv7_21to20_step1" top: "fconv7_21to20_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_21to20_step2" type: "Convolution" bottom: "fconv7_21to20_step1" top: "fconv7_21to20_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_20 ----------------- | |
| layer {name: "fconv7_20" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_20" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 21 to 20 ---------------- | |
| layer {name: "Pass_21to20" type: "Eltwise" bottom:"fconv7_21to20_step2" bottom:"fconv7_20" top: "fconv7_20+"} | |
| layer {name: "relu7_20" type: "ReLU" bottom: "fconv7_20+" top: "fconv7_20+"} | |
| #--------- pass info from: 20 to 15 (7*7*2) ---------------- | |
| layer {name: "fconv7_20to15_step1" type: "Convolution" bottom: "fconv7_20+" top: "fconv7_20to15_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_20to15_step1" type: "ReLU" bottom: "fconv7_20to15_step1" top: "fconv7_20to15_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_20to15_step2" type: "Convolution" bottom: "fconv7_20to15_step1" top: "fconv7_20to15_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_15 ----------------- | |
| layer {name: "fconv7_15" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_15" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 16 and 20 to 15 ---------------- | |
| layer {name: "Pass_1620to15" type: "Eltwise" bottom:"fconv7_20to15_step2" bottom:"fconv7_16to15_step2" bottom:"fconv7_15" top: "fconv7_15+"} | |
| layer {name: "relu7_15" type: "ReLU" bottom: "fconv7_15+" top: "fconv7_15+"} | |
| #--------- pass info from: 15 to 14 (7*7*2) ---------------- | |
| layer {name: "fconv7_15to2_step1" type: "Convolution" bottom: "fconv7_15+" top: "fconv7_15to2_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_15to2_step1" type: "ReLU" bottom: "fconv7_15to2_step1" top: "fconv7_15to2_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_15to2_step2" type: "Convolution" bottom: "fconv7_15to2_step1" top: "fconv7_15to2_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_2 ----------------- | |
| layer {name: "fconv7_2" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_2" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 15 and 3 to 2 ---------------- | |
| layer {name: "Pass_153to2" type: "Eltwise" bottom:"fconv7_15to2_step2" bottom:"fconv7_3to2_step2" bottom:"fconv7_2" top: "fconv7_2+"} | |
| layer {name: "relu7_2" type: "ReLU" bottom: "fconv7_2+" top: "fconv7_2+"} | |
| #--------- pass info from: 2 to 1 (7*7*2) ---------------- | |
| layer {name: "fconv7_2to1_step1" type: "Convolution" bottom: "fconv7_2+" top: "fconv7_2to1_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relu7_2to1_step1" type: "ReLU" bottom: "fconv7_2to1_step1" top: "fconv7_2to1_step1"} | |
| #----step 2 | |
| layer {name: "fconv7_2to1_step2" type: "Convolution" bottom: "fconv7_2to1_step1" top: "fconv7_2to1_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_1 ----------------- | |
| layer {name: "fconv7_1" type: "Convolution" bottom: "fconv6_bn" top: "fconv7_1" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 2 to 1 ---------------- | |
| layer {name: "Pass_2to1" type: "Eltwise" bottom:"fconv7_2to1_step2" bottom:"fconv7_1" top: "fconv7_1+"} | |
| layer {name: "relu7_1" type: "ReLU" bottom: "fconv7_1+" top: "fconv7_1+"} | |
| ################################################################################## | |
| #---------------------- seperated layers revert --------------------------------- | |
| ################################################################################## | |
| ################################################################################## | |
| #---------------------- seperated layers revert --------------------------------- | |
| ################################################################################## | |
| ################################################################################## | |
| #---------------------- seperated layers revert --------------------------------- | |
| ################################################################################## | |
| ################################################################################## | |
| #---------------------- seperated layers revert --------------------------------- | |
| ################################################################################## | |
| ################################################################################## | |
| #---------------------- seperated layers revert --------------------------------- | |
| ################################################################################## | |
| ################################################################################## | |
| #---------------------- seperated layers revert --------------------------------- | |
| ################################################################################## | |
| ####################################################### | |
| #-------------- fconv7_1 ----------------- | |
| layer {name: "fconvb27_1" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_1" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_1" type: "ReLU" bottom: "fconvb27_1" top: "fconvb27_1+"} | |
| #--------- pass info from: 1 to 2 (7*7*2) ---------------- | |
| layer {name: "fconvb27_1to2_step1" type: "Convolution" bottom: "fconvb27_1+" top: "fconvb27_1to2_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_1to2_step1" type: "ReLU" bottom: "fconvb27_1to2_step1" top: "fconvb27_1to2_step1"} | |
| #---- step 2 ------ | |
| layer {name: "fconvb27_1to2_step2" type: "Convolution" bottom: "fconvb27_1to2_step1" top: "fconvb27_1to2_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_2 ----------------- | |
| layer {name: "fconvb27_2" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_2" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 1 and 2 ---------------- | |
| layer {name: "Pass_b2_1to2" type: "Eltwise" bottom:"fconvb27_1to2_step2" bottom:"fconvb27_2" top: "fconvb27_2+"} | |
| layer {name: "relub27_2" type: "ReLU" bottom: "fconvb27_2+" top: "fconvb27_2+"} | |
| #--------- pass info from: 2 to 3 (7*7*2) ---------------- | |
| layer {name: "fconvb27_2to3_step1" type: "Convolution" bottom: "fconvb27_2+" top: "fconvb27_2to3_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_2to3_step1" type: "ReLU" bottom: "fconvb27_2to3_step1" top: "fconvb27_2to3_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_2to3_step2" type: "Convolution" bottom: "fconvb27_2to3_step1" top: "fconvb27_2to3_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- pass info from: 2 to 15 (7*7*2) ---------------- | |
| layer {name: "fconvb27_2to15_step1" type: "Convolution" bottom: "fconvb27_2+" top: "fconvb27_2to15_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_2to15_step1" type: "ReLU" bottom: "fconvb27_2to15_step1" top: "fconvb27_2to15_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_2to15_step2" type: "Convolution" bottom: "fconvb27_2to15_step1" top: "fconvb27_2to15_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_3 ----------------- | |
| layer {name: "fconvb27_3" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_3" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 2 to 3 ---------------- | |
| layer {name: "Pass_b2_2to3" type: "Eltwise" bottom:"fconvb27_2to3_step2" bottom:"fconvb27_3" top: "fconvb27_3+"} | |
| layer {name: "relub27_3" type: "ReLU" bottom: "fconvb27_3+" top: "fconvb27_3+"} | |
| #--------- pass info from: 3 to 4 (7*7*2) ---------------- | |
| layer {name: "fconvb27_3to4_step1" type: "Convolution" bottom: "fconvb27_3+" top: "fconvb27_3to4_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_3to4_step1" type: "ReLU" bottom: "fconvb27_3to4_step1" top: "fconvb27_3to4_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_3to4_step2" type: "Convolution" bottom: "fconvb27_3to4_step1" top: "fconvb27_3to4_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- pass info from: 3 to 8 (7*7*2) ---------------- | |
| layer {name: "fconvb27_3to8_step1" type: "Convolution" bottom: "fconvb27_3+" top: "fconvb27_3to8_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_3to8_step1" type: "ReLU" bottom: "fconvb27_3to8_step1" top: "fconvb27_3to8_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_3to8_step2" type: "Convolution" bottom: "fconvb27_3to8_step1" top: "fconvb27_3to8_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_4 ----------------- | |
| layer {name: "fconvb27_4" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_4" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 3 to 4 ---------------- | |
| layer {name: "Pass_b2_3to4" type: "Eltwise" bottom:"fconvb27_3to4_step2" bottom:"fconvb27_4" top: "fconvb27_4+"} | |
| layer {name: "relub27_4" type: "ReLU" bottom: "fconvb27_4+" top: "fconvb27_4+"} | |
| #--------- pass info from: 4 to 5 (7*7*2) ---------------- | |
| layer {name: "fconvb27_4to5_step1" type: "Convolution" bottom: "fconvb27_4+" top: "fconvb27_4to5_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_4to5_step1" type: "ReLU" bottom: "fconvb27_4to5_step1" top: "fconvb27_4to5_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_4to5_step2" type: "Convolution" bottom: "fconvb27_4to5_step1" top: "fconvb27_4to5_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_5 ----------------- | |
| layer {name: "fconvb27_5" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_5" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from: point 4 ---------------- | |
| layer {name: "Pass_b2_4to5" type: "Eltwise" bottom:"fconvb27_4to5_step2" bottom:"fconvb27_5" top: "fconvb27_5+"} | |
| layer {name: "relub27_5" type: "ReLU" bottom: "fconvb27_5+" top: "fconvb27_5+"} | |
| #--------- pass info from: 5 to 6 (7*7*2) ---------------- | |
| layer {name: "fconvb27_5to6_step1" type: "Convolution" bottom: "fconvb27_5+" top: "fconvb27_5to6_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_5to4_step1" type: "ReLU" bottom: "fconvb27_5to6_step1" top: "fconvb27_5to6_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_5to6_step2" type: "Convolution" bottom: "fconvb27_5to6_step1" top: "fconvb27_5to6_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ################################################## | |
| #-------------- fconv7_6 ----------------- | |
| layer {name: "fconvb27_6" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_6" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #------------------ add info comed from 5---------------------------- | |
| layer {name: "Pass_b2_5to6" type: "Eltwise" bottom:"fconvb27_5to6_step2" bottom:"fconvb27_6" top: "fconvb27_6+"} | |
| layer {name: "relub27_6" type: "ReLU" bottom: "fconvb27_6+" top: "fconvb27_6+"} | |
| #--------- pass info from: 6 to 7 (7*7*2) ---------------- | |
| layer {name: "fconvb27_6to7_step1" type: "Convolution" bottom: "fconvb27_6+" top: "fconvb27_6to7_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_6to7_step1" type: "ReLU" bottom: "fconvb27_6to7_step1" top: "fconvb27_6to7_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_6to7_step2" type: "Convolution" bottom: "fconvb27_6to7_step1" top: "fconvb27_6to7_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_7 ----------------- | |
| layer {name: "fconvb27_7" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_7" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #------------------ add info comed from 6---------------------------- | |
| layer {name: "Pass_b2_6to7" type: "Eltwise" bottom:"fconvb27_6to7_step2" bottom:"fconvb27_7" top: "fconvb27_7+"} | |
| layer {name: "relub27_7" type: "ReLU" bottom: "fconvb27_7+" top: "fconvb27_7+"} | |
| ####################################################### | |
| #-------------- fconv7_8 ----------------- | |
| layer {name: "fconvb27_8" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_8" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 3 to 8 ---------------- | |
| layer {name: "Pass_b2_3to8" type: "Eltwise" bottom:"fconvb27_3to8_step2" bottom:"fconvb27_8" top: "fconvb27_8+"} | |
| layer {name: "relub27_8" type: "ReLU" bottom: "fconvb27_8+" top: "fconvb27_8+"} | |
| #--------- pass info from: 8 to 9 (7*7*2) ---------------- | |
| layer {name: "fconvb27_8to9_step1" type: "Convolution" bottom: "fconvb27_8+" top: "fconvb27_8to9_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_8to9_step1" type: "ReLU" bottom: "fconvb27_8to9_step1" top: "fconvb27_8to9_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_8to9_step2" type: "Convolution" bottom: "fconvb27_8to9_step1" top: "fconvb27_8to9_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_9 ----------------- | |
| layer {name: "fconvb27_9" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_9" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 8 to 9 ---------------- | |
| layer {name: "Pass_b2_8to9" type: "Eltwise" bottom:"fconvb27_8to9_step2" bottom:"fconvb27_9" top: "fconvb27_9+"} | |
| layer {name: "relub27_9" type: "ReLU" bottom: "fconvb27_9+" top: "fconvb27_9+"} | |
| #--------- pass info from: 9 to 10 (7*7*2) ---------------- | |
| layer {name: "fconvb27_9to10_step1" type: "Convolution" bottom: "fconvb27_9+" top: "fconvb27_9to10_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_9to10_step1" type: "ReLU" bottom: "fconvb27_9to10_step1" top: "fconvb27_9to10_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_9to10_step2" type: "Convolution" bottom: "fconvb27_9to10_step1" top: "fconvb27_9to10_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_10 ----------------- | |
| layer {name: "fconvb27_10" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_10" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 9 to 10 ---------------- | |
| layer {name: "Pass_b2_9to10" type: "Eltwise" bottom:"fconvb27_9to10_step2" bottom:"fconvb27_10" top: "fconvb27_10+"} | |
| layer {name: "relub27_10" type: "ReLU" bottom: "fconvb27_10+" top: "fconvb27_10+"} | |
| #--------- pass info from: 10 to 11 (7*7*2) ---------------- | |
| layer {name: "fconvb27_10to11_step1" type: "Convolution" bottom: "fconvb27_10+" top: "fconvb27_10to11_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_10to9_step1" type: "ReLU" bottom: "fconvb27_10to11_step1" top: "fconvb27_10to11_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_10to11_step2" type: "Convolution" bottom: "fconvb27_10to11_step1" top: "fconvb27_10to11_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_11 ----------------- | |
| layer {name: "fconvb27_11" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_11" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 12 to 11 ---------------- | |
| layer {name: "Pass_b2_12to11" type: "Eltwise" bottom:"fconvb27_10to11_step2" bottom:"fconvb27_11" top: "fconvb27_11+"} | |
| layer {name: "relub27_11" type: "ReLU" bottom: "fconvb27_11+" top: "fconvb27_11+"} | |
| #--------- pass info from: 11 to 12(7*7*2) ---------------- | |
| layer {name: "fconvb27_11to12_step1" type: "Convolution" bottom: "fconvb27_11+" top: "fconvb27_11to12_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_11to12_step1" type: "ReLU" bottom: "fconvb27_11to12_step1" top: "fconvb27_11to12_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_11to12_step2" type: "Convolution" bottom: "fconvb27_11to12_step1" top: "fconvb27_11to12_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_12 ----------------- | |
| layer {name: "fconvb27_12" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_12" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 11 to 12 ---------------- | |
| layer {name: "Pass_b2_11to12" type: "Eltwise" bottom:"fconvb27_11to12_step2" bottom:"fconvb27_12" top: "fconvb27_12+"} | |
| layer {name: "relub27_12" type: "ReLU" bottom: "fconvb27_12+" top: "fconvb27_12+"} | |
| #--------- pass info from: 12 to 13 (7*7*2) ---------------- | |
| layer {name: "fconvb27_12to13_step1" type: "Convolution" bottom: "fconvb27_12+" top: "fconvb27_12to13_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_12to13_step1" type: "ReLU" bottom: "fconvb27_12to13_step1" top: "fconvb27_12to13_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_12to13_step2" type: "Convolution" bottom: "fconvb27_12to13_step1" top: "fconvb27_12to13_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_13 ----------------- | |
| layer {name: "fconvb27_13" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_13" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 12 to 13 ---------------- | |
| layer {name: "Pass_b2_12to13" type: "Eltwise" bottom:"fconvb27_12to13_step2" bottom:"fconvb27_13" top: "fconvb27_13+"} | |
| layer {name: "relub27_13" type: "ReLU" bottom: "fconvb27_13+" top: "fconvb27_13+"} | |
| #--------- pass info from: 13 to 14 (7*7*2) ---------------- | |
| layer {name: "fconvb27_13to14_step1" type: "Convolution" bottom: "fconvb27_13+" top: "fconvb27_13to14_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_13to14_step1" type: "ReLU" bottom: "fconvb27_13to14_step1" top: "fconvb27_13to14_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_13to14_step2" type: "Convolution" bottom: "fconvb27_13to14_step1" top: "fconvb27_13to14_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_14 ----------------- | |
| layer {name: "fconvb27_14" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_14" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 13 to 14 ---------------- | |
| layer {name: "Pass_b2_13to14" type: "Eltwise" bottom:"fconvb27_13to14_step2" bottom:"fconvb27_14" top: "fconvb27_14+"} | |
| layer {name: "relub27_14" type: "ReLU" bottom: "fconvb27_14+" top: "fconvb27_14+"} | |
| ####################################################### | |
| #-------------- fconv7_15 ----------------- | |
| layer {name: "fconvb27_15" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_15" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 2 to 15 ---------------- | |
| layer {name: "Pass_b2_2to15" type: "Eltwise" bottom:"fconvb27_2to15_step2" bottom:"fconvb27_15" top: "fconvb27_15+"} | |
| layer {name: "relub27_15" type: "ReLU" bottom: "fconvb27_15+" top: "fconvb27_15+"} | |
| #--------- pass info from: 15 to 16 (7*7*2) ---------------- | |
| layer {name: "fconvb27_15to16_step1" type: "Convolution" bottom: "fconvb27_15+" top: "fconvb27_15to16_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_15to16_step1" type: "ReLU" bottom: "fconvb27_15to16_step1" top: "fconvb27_15to16_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_15to16_step2" type: "Convolution" bottom: "fconvb27_15to16_step1" top: "fconvb27_15to16_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- pass info from: 15 to 20 (7*7*2) ---------------- | |
| layer {name: "fconvb27_15to20_step1" type: "Convolution" bottom: "fconvb27_15+" top: "fconvb27_15to20_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_15to20_step1" type: "ReLU" bottom: "fconvb27_15to20_step1" top: "fconvb27_15to20_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_15to20_step2" type: "Convolution" bottom: "fconvb27_15to20_step1" top: "fconvb27_15to20_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_16 ----------------- | |
| layer {name: "fconvb27_16" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_16" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 15 to 16 ---------------- | |
| layer {name: "Pass_b2_15to16" type: "Eltwise" bottom:"fconvb27_15to16_step2" bottom:"fconvb27_16" top: "fconvb27_16+"} | |
| layer {name: "relub27_16" type: "ReLU" bottom: "fconvb27_16+" top: "fconvb27_16+"} | |
| #--------- pass info from: 16 to 17 (7*7*2) ---------------- | |
| layer {name: "fconvb27_16to17_step1" type: "Convolution" bottom: "fconvb27_16+" top: "fconvb27_16to17_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_16to17_step1" type: "ReLU" bottom: "fconvb27_16to17_step1" top: "fconvb27_16to17_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_16to17_step2" type: "Convolution" bottom: "fconvb27_16to17_step1" top: "fconvb27_16to17_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_17 ----------------- | |
| layer {name: "fconvb27_17" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_17" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 16 to 17 ---------------- | |
| layer {name: "Pass_b2_16to17" type: "Eltwise" bottom:"fconvb27_16to17_step2" bottom:"fconvb27_17" top: "fconvb27_17+"} | |
| layer {name: "relub27_17" type: "ReLU" bottom: "fconvb27_17+" top: "fconvb27_17+"} | |
| #--------- pass info from: 17 to 18 (7*7*2) ---------------- | |
| layer {name: "fconvb27_17to18_step1" type: "Convolution" bottom: "fconvb27_17+" top: "fconvb27_17to18_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_17to18_step1" type: "ReLU" bottom: "fconvb27_17to18_step1" top: "fconvb27_17to18_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_17to18_step2" type: "Convolution" bottom: "fconvb27_17to18_step1" top: "fconvb27_17to18_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_18 ----------------- | |
| layer {name: "fconvb27_18" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_18" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 17 to 18 ---------------- | |
| layer {name: "Pass_b2_17to18" type: "Eltwise" bottom:"fconvb27_17to18_step2" bottom:"fconvb27_18" top: "fconvb27_18+"} | |
| layer {name: "relub27_18" type: "ReLU" bottom: "fconvb27_18+" top: "fconvb27_18+"} | |
| #--------- pass info from: 18 to 19 (7*7*2) ---------------- | |
| layer {name: "fconvb27_18to19_step1" type: "Convolution" bottom: "fconvb27_18+" top: "fconvb27_18to19_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_18to19_step1" type: "ReLU" bottom: "fconvb27_18to19_step1" top: "fconvb27_18to19_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_18to19_step2" type: "Convolution" bottom: "fconvb27_18to19_step1" top: "fconvb27_18to19_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_19 ----------------- | |
| layer {name: "fconvb27_19" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_19" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 18 to 19 ---------------- | |
| layer {name: "Pass_b2_18to19" type: "Eltwise" bottom:"fconvb27_18to19_step2" bottom:"fconvb27_19" top: "fconvb27_19+"} | |
| layer {name: "relub27_19" type: "ReLU" bottom: "fconvb27_19+" top: "fconvb27_19+"} | |
| ####################################################### | |
| #-------------- fconv7_20 ----------------- | |
| layer {name: "fconvb27_20" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_20" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 15 to 20 ---------------- | |
| layer {name: "Pass_b2_15to20" type: "Eltwise" bottom:"fconvb27_15to20_step2" bottom:"fconvb27_20" top: "fconvb27_20+"} | |
| layer {name: "relub27_20" type: "ReLU" bottom: "fconvb27_20+" top: "fconvb27_20+"} | |
| #--------- pass info from: 20 to 21 (7*7*2) ---------------- | |
| layer {name: "fconvb27_20to21_step1" type: "Convolution" bottom: "fconvb27_20+" top: "fconvb27_20to21_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_20to21step1" type: "ReLU" bottom: "fconvb27_20to21_step1" top: "fconvb27_20to21_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_20to21_step2" type: "Convolution" bottom: "fconvb27_20to21_step1" top: "fconvb27_20to21_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_21 ----------------- | |
| layer {name: "fconvb27_21" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_21" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 20 to 21 ---------------- | |
| layer {name: "Pass_b2_20to21" type: "Eltwise" bottom:"fconvb27_20to21_step2" bottom:"fconvb27_21" top: "fconvb27_21+"} | |
| layer {name: "relub27_21" type: "ReLU" bottom: "fconvb27_21+" top: "fconvb27_21+"} | |
| #--------- pass info from: 21 to 22 (7*7*2) ---------------- | |
| layer {name: "fconvb27_21to22_step1" type: "Convolution" bottom: "fconvb27_21+" top: "fconvb27_21to22_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_21to22_step1" type: "ReLU" bottom: "fconvb27_21to22_step1" top: "fconvb27_21to22_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_21to22_step2" type: "Convolution" bottom: "fconvb27_21to22_step1" top: "fconvb27_21to22_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_22 ----------------- | |
| layer {name: "fconvb27_22" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_22" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 21 to 22 ---------------- | |
| layer {name: "Pass_b2_21to22" type: "Eltwise" bottom:"fconvb27_21to22_step2" bottom:"fconvb27_22" top: "fconvb27_22+"} | |
| layer {name: "relub27_22" type: "ReLU" bottom: "fconvb27_22+" top: "fconvb27_22+"} | |
| #--------- pass info from: 22 to 23 (7*7*2) ---------------- | |
| layer {name: "fconvb27_22to23_step1" type: "Convolution" bottom: "fconvb27_22+" top: "fconvb27_22to23_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_22to23_step1" type: "ReLU" bottom: "fconvb27_22to23_step1" top: "fconvb27_22to23_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_22to23_step2" type: "Convolution" bottom: "fconvb27_22to23_step1" top: "fconvb27_22to23_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_23 ----------------- | |
| layer {name: "fconvb27_23" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_23" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 22 to 23 ---------------- | |
| layer {name: "Pass_b2_22to23" type: "Eltwise" bottom:"fconvb27_22to23_step2" bottom:"fconvb27_23" top: "fconvb27_23+"} | |
| layer {name: "relub27_23" type: "ReLU" bottom: "fconvb27_23+" top: "fconvb27_23+"} | |
| #--------- pass info from: 23 to 24 (7*7*2) ---------------- | |
| layer {name: "fconvb27_23to24_step1" type: "Convolution" bottom: "fconvb27_23+" top: "fconvb27_23to24_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_23to24_step1" type: "ReLU" bottom: "fconvb27_23to24_step1" top: "fconvb27_23to24_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_23to24_step2" type: "Convolution" bottom: "fconvb27_23to24_step1" top: "fconvb27_23to24_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_24 ----------------- | |
| layer {name: "fconvb27_24" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_24" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 23 to 24 ---------------- | |
| layer {name: "Pass_b2_23to24" type: "Eltwise" bottom:"fconvb27_23to24_step2" bottom:"fconvb27_24" top: "fconvb27_24+"} | |
| layer {name: "relub27_24" type: "ReLU" bottom: "fconvb27_24+" top: "fconvb27_24+"} | |
| #--------- pass info from: 24 to 25 (7*7*2) ---------------- | |
| layer {name: "fconvb27_24to25_step1" type: "Convolution" bottom: "fconvb27_24+" top: "fconvb27_24to25_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_24to23_step1" type: "ReLU" bottom: "fconvb27_24to25_step1" top: "fconvb27_24to25_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_24to25_step2" type: "Convolution" bottom: "fconvb27_24to25_step1" top: "fconvb27_24to25_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_25 ----------------- | |
| layer {name: "fconvb27_25" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_25" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 24 to 25 ---------------- | |
| layer {name: "Pass_b2_24to25" type: "Eltwise" bottom:"fconvb27_24to25_step2" bottom:"fconvb27_25" top: "fconvb27_25+"} | |
| layer {name: "relub27_25" type: "ReLU" bottom: "fconvb27_25+" top: "fconvb27_25+"} | |
| #--------- pass info from: 25 to 26 (7*7*2) ---------------- | |
| layer {name: "fconvb27_25to26_step1" type: "Convolution" bottom: "fconvb27_25+" top: "fconvb27_25to26_step1" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 64 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_25to26_step1" type: "ReLU" bottom: "fconvb27_25to26_step1" top: "fconvb27_25to26_step1"} | |
| #----step 2 | |
| layer {name: "fconvb27_25to26_step2" type: "Convolution" bottom: "fconvb27_25to26_step1" top: "fconvb27_25to26_step2" param {lr_mult: 10 decay_mult: 2} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:7 pad: 3 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| ####################################################### | |
| #-------------- fconv7_26 ----------------- | |
| layer {name: "fconvb27_26" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_26" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 128 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #--------- collect info from 25 to 26 ---------------- | |
| layer {name: "Pass_b2_25to26" type: "Eltwise" bottom:"fconvb27_25to26_step2" bottom:"fconvb27_26" top: "fconvb27_26+"} | |
| layer {name: "relub27_26" type: "ReLU" bottom: "fconvb27_26+" top: "fconvb27_26+"} | |
| ####################################################### | |
| #-------------- negative ----------------- | |
| ####################################################### | |
| #-------------- fconv7_27 ----------------- | |
| layer {name: "fconvb27_27" type: "Convolution" bottom: "fconv6_bn" top: "fconvb27_27" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param { num_output: 512 kernel_size:1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| layer {name: "relub27_27" type: "ReLU" bottom: "fconvb27_27" top: "fconvb27_27+"} | |
| layer { | |
| name: "drop7_27" | |
| type: "ChannelDropout" | |
| bottom: "fconvb27_27+" | |
| top: "fconvb27_27+" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| ############################################################################################################################# | |
| # Concate 2 branches | |
| ############################################################################################################################## | |
| layer { name: "fconv7_1_concat" type: "Concat" bottom: "fconv7_1+" bottom: "fconvb27_1+" top: "fconv7_1_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_2_concat" type: "Concat" bottom: "fconv7_2+" bottom: "fconvb27_2+" top: "fconv7_2_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_3_concat" type: "Concat" bottom: "fconv7_3+" bottom: "fconvb27_3+" top: "fconv7_3_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_4_concat" type: "Concat" bottom: "fconv7_4+" bottom: "fconvb27_4+" top: "fconv7_4_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_5_concat" type: "Concat" bottom: "fconv7_5+" bottom: "fconvb27_5+" top: "fconv7_5_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_6_concat" type: "Concat" bottom: "fconv7_6+" bottom: "fconvb27_6+" top: "fconv7_6_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_7_concat" type: "Concat" bottom: "fconv7_7+" bottom: "fconvb27_7+" top: "fconv7_7_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_8_concat" type: "Concat" bottom: "fconv7_8+" bottom: "fconvb27_8+" top: "fconv7_8_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_9_concat" type: "Concat" bottom: "fconv7_9+" bottom: "fconvb27_9+" top: "fconv7_9_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_10_concat" type: "Concat" bottom: "fconv7_10+" bottom: "fconvb27_10+" top: "fconv7_10_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_11_concat" type: "Concat" bottom: "fconv7_11+" bottom: "fconvb27_11+" top: "fconv7_11_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_12_concat" type: "Concat" bottom: "fconv7_12+" bottom: "fconvb27_12+" top: "fconv7_12_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_13_concat" type: "Concat" bottom: "fconv7_13+" bottom: "fconvb27_13+" top: "fconv7_13_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_14_concat" type: "Concat" bottom: "fconv7_14+" bottom: "fconvb27_14+" top: "fconv7_14_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_15_concat" type: "Concat" bottom: "fconv7_15+" bottom: "fconvb27_15+" top: "fconv7_15_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_16_concat" type: "Concat" bottom: "fconv7_16+" bottom: "fconvb27_16+" top: "fconv7_16_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_17_concat" type: "Concat" bottom: "fconv7_17+" bottom: "fconvb27_17+" top: "fconv7_17_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_18_concat" type: "Concat" bottom: "fconv7_18+" bottom: "fconvb27_18+" top: "fconv7_18_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_19_concat" type: "Concat" bottom: "fconv7_19+" bottom: "fconvb27_19+" top: "fconv7_19_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_20_concat" type: "Concat" bottom: "fconv7_20+" bottom: "fconvb27_20+" top: "fconv7_20_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_21_concat" type: "Concat" bottom: "fconv7_21+" bottom: "fconvb27_21+" top: "fconv7_21_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_22_concat" type: "Concat" bottom: "fconv7_22+" bottom: "fconvb27_22+" top: "fconv7_22_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_23_concat" type: "Concat" bottom: "fconv7_23+" bottom: "fconvb27_23+" top: "fconv7_23_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_24_concat" type: "Concat" bottom: "fconv7_24+" bottom: "fconvb27_24+" top: "fconv7_24_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_25_concat" type: "Concat" bottom: "fconv7_25+" bottom: "fconvb27_25+" top: "fconv7_25_concat" concat_param { axis: 1 }} | |
| layer { name: "fconv7_26_concat" type: "Concat" bottom: "fconv7_26+" bottom: "fconvb27_26+" top: "fconv7_26_concat" concat_param { axis: 1 }} | |
| ######################################################## | |
| #------------------- fconv9 ---------------------------- | |
| #-------------- fconv9_1 ----------------- | |
| layer {name: "fconv9_1" type: "Convolution" bottom: "fconv7_1_concat" top: "fconv9_1" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_2 ----------------- | |
| layer {name: "fconv9_2" type: "Convolution" bottom: "fconv7_2_concat" top: "fconv9_2" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_3 ----------------- | |
| layer {name: "fconv9_3" type: "Convolution" bottom: "fconv7_3_concat" top: "fconv9_3" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_4 ----------------- | |
| layer {name: "fconv9_4" type: "Convolution" bottom: "fconv7_4_concat" top: "fconv9_4" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_5 ----------------- | |
| layer {name: "fconv9_5" type: "Convolution" bottom: "fconv7_5_concat" top: "fconv9_5" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_6 ----------------- | |
| layer {name: "fconv9_6" type: "Convolution" bottom: "fconv7_6_concat" top: "fconv9_6" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_7 ----------------- | |
| layer {name: "fconv9_7" type: "Convolution" bottom: "fconv7_7_concat" top: "fconv9_7" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_8 ----------------- | |
| layer {name: "fconv9_8" type: "Convolution" bottom: "fconv7_8_concat" top: "fconv9_8" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_9 ----------------- | |
| layer {name: "fconv9_9" type: "Convolution" bottom: "fconv7_9_concat" top: "fconv9_9" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.01} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_10 ----------------- | |
| layer {name: "fconv9_10" type: "Convolution" bottom: "fconv7_10_concat" top: "fconv9_10" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_11 ----------------- | |
| layer {name: "fconv9_11" type: "Convolution" bottom: "fconv7_11_concat" top: "fconv9_11" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_12 ----------------- | |
| layer {name: "fconv9_12" type: "Convolution" bottom: "fconv7_12_concat" top: "fconv9_12" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_13 ----------------- | |
| layer {name: "fconv9_13" type: "Convolution" bottom: "fconv7_13_concat" top: "fconv9_13" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_14 ----------------- | |
| layer {name: "fconv9_14" type: "Convolution" bottom: "fconv7_14_concat" top: "fconv9_14" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_15 ----------------- | |
| layer {name: "fconv9_15" type: "Convolution" bottom: "fconv7_15_concat" top: "fconv9_15" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_16 ----------------- | |
| layer {name: "fconv9_16" type: "Convolution" bottom: "fconv7_16_concat" top: "fconv9_16" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_17 ----------------- | |
| layer {name: "fconv9_17" type: "Convolution" bottom: "fconv7_17_concat" top: "fconv9_17" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_18 ----------------- | |
| layer {name: "fconv9_18" type: "Convolution" bottom: "fconv7_18_concat" top: "fconv9_18" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_19 ----------------- | |
| layer {name: "fconv9_19" type: "Convolution" bottom: "fconv7_19_concat" top: "fconv9_19" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_20----------------- | |
| layer {name: "fconv9_20" type: "Convolution" bottom: "fconv7_20_concat" top: "fconv9_20" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_21----------------- | |
| layer {name: "fconv9_21" type: "Convolution" bottom: "fconv7_21_concat" top: "fconv9_21" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_22----------------- | |
| layer {name: "fconv9_22" type: "Convolution" bottom: "fconv7_22_concat" top: "fconv9_22" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_23----------------- | |
| layer {name: "fconv9_23" type: "Convolution" bottom: "fconv7_23_concat" top: "fconv9_23" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_24----------------- | |
| layer {name: "fconv9_24" type: "Convolution" bottom: "fconv7_24_concat" top: "fconv9_24" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_25----------------- | |
| layer {name: "fconv9_25" type: "Convolution" bottom: "fconv7_25_concat" top: "fconv9_25" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_26----------------- | |
| layer {name: "fconv9_26" type: "Convolution" bottom: "fconv7_26_concat" top: "fconv9_26" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 13 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| #-------------- fconv9_27----------------- | |
| layer {name: "fconv9_27" type: "Convolution" bottom: "fconvb27_27+" top: "fconv9_27" param {lr_mult: 10 decay_mult: 1} param {lr_mult: 20 decay_mult: 0} | |
| convolution_param {num_output: 1 kernel_size: 1 pad: 0 weight_filler {type: "gaussian" std: 0.1} bias_filler {type: "constant" value: 0}}} | |
| # ----- concat ----- | |
| layer { | |
| name: "fconv9" | |
| type: "Concat" | |
| bottom: "fconv9_1" | |
| bottom: "fconv9_2" | |
| bottom: "fconv9_3" | |
| bottom: "fconv9_4" | |
| bottom: "fconv9_5" | |
| bottom: "fconv9_6" | |
| bottom: "fconv9_7" | |
| bottom: "fconv9_8" | |
| bottom: "fconv9_9" | |
| bottom: "fconv9_10" | |
| bottom: "fconv9_11" | |
| bottom: "fconv9_12" | |
| bottom: "fconv9_13" | |
| bottom: "fconv9_14" | |
| bottom: "fconv9_15" | |
| bottom: "fconv9_16" | |
| bottom: "fconv9_17" | |
| bottom: "fconv9_18" | |
| bottom: "fconv9_19" | |
| bottom: "fconv9_20" | |
| bottom: "fconv9_21" | |
| bottom: "fconv9_22" | |
| bottom: "fconv9_23" | |
| bottom: "fconv9_24" | |
| bottom: "fconv9_25" | |
| bottom: "fconv9_26" | |
| bottom: "fconv9_27" | |
| top: "fconv9" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| ####################################### | |
| #------------- loss ------------------- | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLossMask" | |
| bottom: "fconv9" | |
| bottom: "label" | |
| bottom: "mask" | |
| top: "loss" | |
| softmax_mask_param{ | |
| use_inria: 1 | |
| inria_neg_ratio: 0.01 | |
| use_neg: 1 | |
| neg_ratio: 0.5 | |
| neg_weight: 0.5 | |
| } | |
| } |
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