name: "age" input: "data" input_shape { dim: 1 dim: 3 dim: 120 dim: 120 } layer { name: "conv1" type: "Convolution" bottom: "data" top: "conv_blob1" convolution_param { num_output: 32 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm1" type: "BatchNorm" bottom: "conv_blob1" top: "batch_norm_blob1" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale1" type: "Scale" bottom: "batch_norm_blob1" top: "batch_norm_blob1" scale_param { bias_term: true } } layer { name: "relu1" type: "ReLU" bottom: "batch_norm_blob1" top: "relu_blob1" } layer { name: "conv2" type: "Convolution" bottom: "relu_blob1" top: "conv_blob2" convolution_param { num_output: 32 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm2" type: "BatchNorm" bottom: "conv_blob2" top: "batch_norm_blob2" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale2" type: "Scale" bottom: "batch_norm_blob2" top: "batch_norm_blob2" scale_param { bias_term: true } } layer { name: "relu2" type: "ReLU" bottom: "batch_norm_blob2" top: "relu_blob2" } layer { name: "conv3" type: "Convolution" bottom: "relu_blob2" top: "conv_blob3" convolution_param { num_output: 32 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm3" type: "BatchNorm" bottom: "conv_blob3" top: "batch_norm_blob3" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale3" type: "Scale" bottom: "batch_norm_blob3" top: "batch_norm_blob3" scale_param { bias_term: true } } layer { name: "add1" type: "Eltwise" bottom: "batch_norm_blob3" bottom: "relu_blob1" top: "add_blob1" eltwise_param { operation: SUM } } layer { name: "relu3" type: "ReLU" bottom: "add_blob1" top: "relu_blob3" } layer { name: "conv4" type: "Convolution" bottom: "relu_blob3" top: "conv_blob4" convolution_param { num_output: 32 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm4" type: "BatchNorm" bottom: "conv_blob4" top: "batch_norm_blob4" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale4" type: "Scale" bottom: "batch_norm_blob4" top: "batch_norm_blob4" scale_param { bias_term: true } } layer { name: "relu4" type: "ReLU" bottom: "batch_norm_blob4" top: "relu_blob4" } layer { name: "conv5" type: "Convolution" bottom: "relu_blob4" top: "conv_blob5" convolution_param { num_output: 32 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm5" type: "BatchNorm" bottom: "conv_blob5" top: "batch_norm_blob5" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale5" type: "Scale" bottom: "batch_norm_blob5" top: "batch_norm_blob5" scale_param { bias_term: true } } layer { name: "add2" type: "Eltwise" bottom: "batch_norm_blob5" bottom: "relu_blob3" top: "add_blob2" eltwise_param { operation: SUM } } layer { name: "relu5" type: "ReLU" bottom: "add_blob2" top: "relu_blob5" } layer { name: "conv6" type: "Convolution" bottom: "relu_blob5" top: "conv_blob6" convolution_param { num_output: 64 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm6" type: "BatchNorm" bottom: "conv_blob6" top: "batch_norm_blob6" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale6" type: "Scale" bottom: "batch_norm_blob6" top: "batch_norm_blob6" scale_param { bias_term: true } } layer { name: "relu6" type: "ReLU" bottom: "batch_norm_blob6" top: "relu_blob6" } layer { name: "conv7" type: "Convolution" bottom: "relu_blob6" top: "conv_blob7" convolution_param { num_output: 64 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm7" type: "BatchNorm" bottom: "conv_blob7" top: "batch_norm_blob7" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale7" type: "Scale" bottom: "batch_norm_blob7" top: "batch_norm_blob7" scale_param { bias_term: true } } layer { name: "conv8" type: "Convolution" bottom: "relu_blob5" top: "conv_blob8" convolution_param { num_output: 64 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm8" type: "BatchNorm" bottom: "conv_blob8" top: "batch_norm_blob8" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale8" type: "Scale" bottom: "batch_norm_blob8" top: "batch_norm_blob8" scale_param { bias_term: true } } layer { name: "add3" type: "Eltwise" bottom: "batch_norm_blob7" bottom: "batch_norm_blob8" top: "add_blob3" eltwise_param { operation: SUM } } layer { name: "relu7" type: "ReLU" bottom: "add_blob3" top: "relu_blob7" } layer { name: "conv9" type: "Convolution" bottom: "relu_blob7" top: "conv_blob9" convolution_param { num_output: 64 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm9" type: "BatchNorm" bottom: "conv_blob9" top: "batch_norm_blob9" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale9" type: "Scale" bottom: "batch_norm_blob9" top: "batch_norm_blob9" scale_param { bias_term: true } } layer { name: "relu8" type: "ReLU" bottom: "batch_norm_blob9" top: "relu_blob8" } layer { name: "conv10" type: "Convolution" bottom: "relu_blob8" top: "conv_blob10" convolution_param { num_output: 64 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm10" type: "BatchNorm" bottom: "conv_blob10" top: "batch_norm_blob10" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale10" type: "Scale" bottom: "batch_norm_blob10" top: "batch_norm_blob10" scale_param { bias_term: true } } layer { name: "add4" type: "Eltwise" bottom: "batch_norm_blob10" bottom: "relu_blob7" top: "add_blob4" eltwise_param { operation: SUM } } layer { name: "relu9" type: "ReLU" bottom: "add_blob4" top: "relu_blob9" } layer { name: "conv11" type: "Convolution" bottom: "relu_blob9" top: "conv_blob11" convolution_param { num_output: 128 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm11" type: "BatchNorm" bottom: "conv_blob11" top: "batch_norm_blob11" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale11" type: "Scale" bottom: "batch_norm_blob11" top: "batch_norm_blob11" scale_param { bias_term: true } } layer { name: "relu10" type: "ReLU" bottom: "batch_norm_blob11" top: "relu_blob10" } layer { name: "conv12" type: "Convolution" bottom: "relu_blob10" top: "conv_blob12" convolution_param { num_output: 128 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm12" type: "BatchNorm" bottom: "conv_blob12" top: "batch_norm_blob12" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale12" type: "Scale" bottom: "batch_norm_blob12" top: "batch_norm_blob12" scale_param { bias_term: true } } layer { name: "conv13" type: "Convolution" bottom: "relu_blob9" top: "conv_blob13" convolution_param { num_output: 128 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm13" type: "BatchNorm" bottom: "conv_blob13" top: "batch_norm_blob13" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale13" type: "Scale" bottom: "batch_norm_blob13" top: "batch_norm_blob13" scale_param { bias_term: true } } layer { name: "add5" type: "Eltwise" bottom: "batch_norm_blob12" bottom: "batch_norm_blob13" top: "add_blob5" eltwise_param { operation: SUM } } layer { name: "relu11" type: "ReLU" bottom: "add_blob5" top: "relu_blob11" } layer { name: "conv14" type: "Convolution" bottom: "relu_blob11" top: "conv_blob14" convolution_param { num_output: 128 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm14" type: "BatchNorm" bottom: "conv_blob14" top: "batch_norm_blob14" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale14" type: "Scale" bottom: "batch_norm_blob14" top: "batch_norm_blob14" scale_param { bias_term: true } } layer { name: "relu12" type: "ReLU" bottom: "batch_norm_blob14" top: "relu_blob12" } layer { name: "conv15" type: "Convolution" bottom: "relu_blob12" top: "conv_blob15" convolution_param { num_output: 128 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm15" type: "BatchNorm" bottom: "conv_blob15" top: "batch_norm_blob15" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale15" type: "Scale" bottom: "batch_norm_blob15" top: "batch_norm_blob15" scale_param { bias_term: true } } layer { name: "add6" type: "Eltwise" bottom: "batch_norm_blob15" bottom: "relu_blob11" top: "add_blob6" eltwise_param { operation: SUM } } layer { name: "relu13" type: "ReLU" bottom: "add_blob6" top: "relu_blob13" } layer { name: "conv16" type: "Convolution" bottom: "relu_blob13" top: "conv_blob16" convolution_param { num_output: 256 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm16" type: "BatchNorm" bottom: "conv_blob16" top: "batch_norm_blob16" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale16" type: "Scale" bottom: "batch_norm_blob16" top: "batch_norm_blob16" scale_param { bias_term: true } } layer { name: "relu14" type: "ReLU" bottom: "batch_norm_blob16" top: "relu_blob14" } layer { name: "conv17" type: "Convolution" bottom: "relu_blob14" top: "conv_blob17" convolution_param { num_output: 256 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm17" type: "BatchNorm" bottom: "conv_blob17" top: "batch_norm_blob17" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale17" type: "Scale" bottom: "batch_norm_blob17" top: "batch_norm_blob17" scale_param { bias_term: true } } layer { name: "conv18" type: "Convolution" bottom: "relu_blob13" top: "conv_blob18" convolution_param { num_output: 256 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm18" type: "BatchNorm" bottom: "conv_blob18" top: "batch_norm_blob18" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale18" type: "Scale" bottom: "batch_norm_blob18" top: "batch_norm_blob18" scale_param { bias_term: true } } layer { name: "add7" type: "Eltwise" bottom: "batch_norm_blob17" bottom: "batch_norm_blob18" top: "add_blob7" eltwise_param { operation: SUM } } layer { name: "relu15" type: "ReLU" bottom: "add_blob7" top: "relu_blob15" } layer { name: "conv19" type: "Convolution" bottom: "relu_blob15" top: "conv_blob19" convolution_param { num_output: 256 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm19" type: "BatchNorm" bottom: "conv_blob19" top: "batch_norm_blob19" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale19" type: "Scale" bottom: "batch_norm_blob19" top: "batch_norm_blob19" scale_param { bias_term: true } } layer { name: "relu16" type: "ReLU" bottom: "batch_norm_blob19" top: "relu_blob16" } layer { name: "conv20" type: "Convolution" bottom: "relu_blob16" top: "conv_blob20" convolution_param { num_output: 256 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "batch_norm20" type: "BatchNorm" bottom: "conv_blob20" top: "batch_norm_blob20" batch_norm_param { use_global_stats: true eps: 9.9999997e-06 } } layer { name: "bn_scale20" type: "Scale" bottom: "batch_norm_blob20" top: "batch_norm_blob20" scale_param { bias_term: true } } layer { name: "add8" type: "Eltwise" bottom: "batch_norm_blob20" bottom: "relu_blob15" top: "add_blob8" eltwise_param { operation: SUM } } layer { name: "relu17" type: "ReLU" bottom: "add_blob8" top: "relu_blob17" } # layer { # name: "ave_pool1" # type: "Pooling" # bottom: "relu_blob17" # top: "ave_pool_blob1" # pooling_param { # pool: AVE # kernel_size: 15 # stride: 15 # } # } layer { name: "ave_pool1" type: "Pooling" bottom: "relu_blob17" top: "tmp" pooling_param { pool: AVE kernel_size: 5 stride: 5 } } layer { name: "ave_pool2" type: "Pooling" bottom: "tmp" top: "ave_pool_blob1" pooling_param { pool: AVE kernel_size: 3 stride: 3 } } layer { name: "view1" type: "Reshape" bottom: "ave_pool_blob1" top: "view_blob1" reshape_param { shape { dim: 0 dim: -1 } } } layer { name: "fc1" type: "InnerProduct" bottom: "view_blob1" top: "fc_blob1" inner_product_param { num_output: 96 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "age_softmax" type: "Softmax" bottom: "fc_blob1" top: "age_out" }