Last active
August 1, 2017 01:54
-
-
Save hustzxd/7037707785009f03f7f5ae9740e7a98a to your computer and use it in GitHub Desktop.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: "YOLONET" | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data_bgr" | |
| top: "label" | |
| include { | |
| phase: TRAIN | |
| } | |
| transform_param { | |
| mirror: true | |
| crop_size: 416 | |
| scale: 0.00390625 | |
| } | |
| data_param { | |
| source: "./examples/imagenet/lmdb/ilsvrc12_train_lmdb" | |
| batch_size: 15 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "data" | |
| type: "Data" | |
| top: "data_bgr" | |
| top: "label" | |
| include { | |
| phase: TEST | |
| } | |
| transform_param { | |
| scale: 0.00390625 | |
| } | |
| data_param { | |
| # source: "../../../data/yolo/lmdb/test2007_lmdb" | |
| source: "./examples/imagenet/lmdb/ilsvrc12_val_lmdb" | |
| batch_size: 5 | |
| backend: LMDB | |
| } | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data_bgr" | |
| top: "conv1" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn1" | |
| type: "BatchNorm" | |
| bottom: "conv1" | |
| top: "conv1" | |
| } | |
| layer { | |
| name: "scale1" | |
| type: "Scale" | |
| bottom: "conv1" | |
| top: "conv1" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| #default 1, 0 | |
| scale_param { | |
| bias_term: true | |
| filler { | |
| value: 1 | |
| } | |
| bias_filler { | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv2" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn2" | |
| type: "BatchNorm" | |
| bottom: "conv2" | |
| top: "conv2" | |
| } | |
| layer { | |
| name: "scale2" | |
| type: "Scale" | |
| bottom: "conv2" | |
| top: "conv2" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu2" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool2" | |
| type: "Pooling" | |
| bottom: "conv2" | |
| top: "pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "pool2" | |
| top: "conv3" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn3" | |
| type: "BatchNorm" | |
| bottom: "conv3" | |
| top: "conv3" | |
| } | |
| layer { | |
| name: "scale3" | |
| type: "Scale" | |
| bottom: "conv3" | |
| top: "conv3" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu3" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "conv3" | |
| top: "conv4" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 1 | |
| pad: 0 #?? | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn4" | |
| type: "BatchNorm" | |
| bottom: "conv4" | |
| top: "conv4" | |
| } | |
| layer { | |
| name: "scale4" | |
| type: "Scale" | |
| bottom: "conv4" | |
| top: "conv4" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu4" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "conv4" | |
| top: "conv5" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn5" | |
| type: "BatchNorm" | |
| bottom: "conv5" | |
| top: "conv5" | |
| } | |
| layer { | |
| name: "scale5" | |
| type: "Scale" | |
| bottom: "conv5" | |
| top: "conv5" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu5" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool5" | |
| type: "Pooling" | |
| bottom: "conv5" | |
| top: "pool5" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "pool5" | |
| top: "conv6" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn6" | |
| type: "BatchNorm" | |
| bottom: "conv6" | |
| top: "conv6" | |
| } | |
| layer { | |
| name: "scale6" | |
| type: "Scale" | |
| bottom: "conv6" | |
| top: "conv6" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu6" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv7" | |
| type: "Convolution" | |
| bottom: "conv6" | |
| top: "conv7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn7" | |
| type: "BatchNorm" | |
| bottom: "conv7" | |
| top: "conv7" | |
| } | |
| layer { | |
| name: "scale7" | |
| type: "Scale" | |
| bottom: "conv7" | |
| top: "conv7" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu7" | |
| type: "ReLU" | |
| bottom: "conv7" | |
| top: "conv7" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv8" | |
| type: "Convolution" | |
| bottom: "conv7" | |
| top: "conv8" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn8" | |
| type: "BatchNorm" | |
| bottom: "conv8" | |
| top: "conv8" | |
| } | |
| layer { | |
| name: "scale8" | |
| type: "Scale" | |
| bottom: "conv8" | |
| top: "conv8" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu8" | |
| type: "ReLU" | |
| bottom: "conv8" | |
| top: "conv8" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool8" | |
| type: "Pooling" | |
| bottom: "conv8" | |
| top: "pool8" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv9" | |
| type: "Convolution" | |
| bottom: "pool8" | |
| top: "conv9" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn9" | |
| type: "BatchNorm" | |
| bottom: "conv9" | |
| top: "conv9" | |
| } | |
| layer { | |
| name: "scale9" | |
| type: "Scale" | |
| bottom: "conv9" | |
| top: "conv9" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu9" | |
| type: "ReLU" | |
| bottom: "conv9" | |
| top: "conv9" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv10" | |
| type: "Convolution" | |
| bottom: "conv9" | |
| top: "conv10" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn10" | |
| type: "BatchNorm" | |
| bottom: "conv10" | |
| top: "conv10" | |
| } | |
| layer { | |
| name: "scale10" | |
| type: "Scale" | |
| bottom: "conv10" | |
| top: "conv10" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu10" | |
| type: "ReLU" | |
| bottom: "conv10" | |
| top: "conv10" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv11" | |
| type: "Convolution" | |
| bottom: "conv10" | |
| top: "conv11" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn11" | |
| type: "BatchNorm" | |
| bottom: "conv11" | |
| top: "conv11" | |
| } | |
| layer { | |
| name: "scale11" | |
| type: "Scale" | |
| bottom: "conv11" | |
| top: "conv11" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu11" | |
| type: "ReLU" | |
| bottom: "conv11" | |
| top: "conv11" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv12" | |
| type: "Convolution" | |
| bottom: "conv11" | |
| top: "conv12" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn12" | |
| type: "BatchNorm" | |
| bottom: "conv12" | |
| top: "conv12" | |
| } | |
| layer { | |
| name: "scale12" | |
| type: "Scale" | |
| bottom: "conv12" | |
| top: "conv12" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu12" | |
| type: "ReLU" | |
| bottom: "conv12" | |
| top: "conv12" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv13" | |
| type: "Convolution" | |
| bottom: "conv12" | |
| top: "conv13" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn13" | |
| type: "BatchNorm" | |
| bottom: "conv13" | |
| top: "conv13" | |
| } | |
| layer { | |
| name: "scale13" | |
| type: "Scale" | |
| bottom: "conv13" | |
| top: "conv13" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu13" | |
| type: "ReLU" | |
| bottom: "conv13" | |
| top: "conv13" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool13" | |
| type: "Pooling" | |
| bottom: "conv13" | |
| top: "pool13" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv14" | |
| type: "Convolution" | |
| bottom: "pool13" | |
| top: "conv14" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn14" | |
| type: "BatchNorm" | |
| bottom: "conv14" | |
| top: "conv14" | |
| } | |
| layer { | |
| name: "scale14" | |
| type: "Scale" | |
| bottom: "conv14" | |
| top: "conv14" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu14" | |
| type: "ReLU" | |
| bottom: "conv14" | |
| top: "conv14" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv15" | |
| type: "Convolution" | |
| bottom: "conv14" | |
| top: "conv15" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn15" | |
| type: "BatchNorm" | |
| bottom: "conv15" | |
| top: "conv15" | |
| } | |
| layer { | |
| name: "scale15" | |
| type: "Scale" | |
| bottom: "conv15" | |
| top: "conv15" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu15" | |
| type: "ReLU" | |
| bottom: "conv15" | |
| top: "conv15" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv16" | |
| type: "Convolution" | |
| bottom: "conv15" | |
| top: "conv16" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn16" | |
| type: "BatchNorm" | |
| bottom: "conv16" | |
| top: "conv16" | |
| } | |
| layer { | |
| name: "scale16" | |
| type: "Scale" | |
| bottom: "conv16" | |
| top: "conv16" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu16" | |
| type: "ReLU" | |
| bottom: "conv16" | |
| top: "conv16" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv17" | |
| type: "Convolution" | |
| bottom: "conv16" | |
| top: "conv17" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn17" | |
| type: "BatchNorm" | |
| bottom: "conv17" | |
| top: "conv17" | |
| } | |
| layer { | |
| name: "scale17" | |
| type: "Scale" | |
| bottom: "conv17" | |
| top: "conv17" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu17" | |
| type: "ReLU" | |
| bottom: "conv17" | |
| top: "conv17" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv18" | |
| type: "Convolution" | |
| bottom: "conv17" | |
| top: "conv18" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn18" | |
| type: "BatchNorm" | |
| bottom: "conv18" | |
| top: "conv18" | |
| } | |
| layer { | |
| name: "scale18" | |
| type: "Scale" | |
| bottom: "conv18" | |
| top: "conv18" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu18" | |
| type: "ReLU" | |
| bottom: "conv18" | |
| top: "conv18" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv19" | |
| type: "Convolution" | |
| bottom: "conv18" | |
| top: "conv19" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn19" | |
| type: "BatchNorm" | |
| bottom: "conv19" | |
| top: "conv19" | |
| } | |
| layer { | |
| name: "scale19" | |
| type: "Scale" | |
| bottom: "conv19" | |
| top: "conv19" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu19" | |
| type: "ReLU" | |
| bottom: "conv19" | |
| top: "conv19" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer{ | |
| name: "conv20" | |
| type: "Convolution" | |
| bottom: "conv19" | |
| top: "conv20" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn20" | |
| type: "BatchNorm" | |
| bottom: "conv20" | |
| top: "conv20" | |
| } | |
| layer { | |
| name: "scale20" | |
| type: "Scale" | |
| bottom: "conv20" | |
| top: "conv20" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu20" | |
| type: "ReLU" | |
| bottom: "conv20" | |
| top: "conv20" | |
| relu_param { | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "reorg1" | |
| type: "Reorg" | |
| bottom: "conv13" | |
| top: "reorg1" | |
| reorg_param { | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "concat1" | |
| type: "Concat" | |
| bottom: "reorg1" | |
| bottom: "conv20" | |
| top: "concat1" | |
| } | |
| layer{ | |
| name: "conv21" | |
| type: "Convolution" | |
| bottom: "concat1" | |
| top: "conv21" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "bn21" | |
| type: "BatchNorm" | |
| bottom: "conv21" | |
| top: "conv21" | |
| } | |
| layer { | |
| name: "scale21" | |
| type: "Scale" | |
| bottom: "conv21" | |
| top: "conv21" | |
| param { # scale | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| param { # bias | |
| lr_mult: 1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "relu21" | |
| type: "ReLU" | |
| bottom: "conv21" | |
| top: "conv21" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "pool21" | |
| type: "Pooling" | |
| bottom: "conv21" | |
| top: "pool21" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "fc7" | |
| type: "InnerProduct" | |
| bottom: "pool21" | |
| top: "fc7" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 4096 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.005 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "relu7" | |
| type: "ReLU" | |
| bottom: "fc7" | |
| top: "fc7" | |
| } | |
| layer { | |
| name: "drop7" | |
| type: "Dropout" | |
| bottom: "fc7" | |
| top: "fc7" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "fc8" | |
| type: "InnerProduct" | |
| bottom: "fc7" | |
| top: "fc8" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| inner_product_param { | |
| num_output: 1000 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "accuracy" | |
| type: "Accuracy" | |
| bottom: "fc8" | |
| bottom: "label" | |
| top: "accuracy" | |
| include { | |
| phase: TEST | |
| } | |
| } | |
| layer { | |
| name: "loss" | |
| type: "SoftmaxWithLoss" | |
| bottom: "fc8" | |
| bottom: "label" | |
| top: "loss" | |
| } |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment