| input: "data" | |
| input_shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 300 | |
| dim: 300 | |
| } | |
| layer { | |
| name: "data_bn" | |
| type: "BatchNorm" | |
| bottom: "data" | |
| top: "data_bn" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "data_scale" | |
| type: "Scale" | |
| bottom: "data_bn" | |
| top: "data_bn" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv1_h" | |
| type: "Convolution" | |
| bottom: "data_bn" | |
| top: "conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| pad: 3 | |
| kernel_size: 7 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| variance_norm: FAN_OUT | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv1_bn_h" | |
| type: "BatchNorm" | |
| bottom: "conv1_h" | |
| top: "conv1_h" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "conv1_scale_h" | |
| type: "Scale" | |
| bottom: "conv1_h" | |
| top: "conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv1_relu" | |
| type: "ReLU" | |
| bottom: "conv1_h" | |
| top: "conv1_h" | |
| } | |
| layer { | |
| name: "conv1_pool" | |
| type: "Pooling" | |
| bottom: "conv1_h" | |
| top: "conv1_pool" | |
| pooling_param { | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layer { | |
| name: "layer_64_1_conv1_h" | |
| type: "Convolution" | |
| bottom: "conv1_pool" | |
| top: "layer_64_1_conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_64_1_bn2_h" | |
| type: "BatchNorm" | |
| bottom: "layer_64_1_conv1_h" | |
| top: "layer_64_1_conv1_h" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "layer_64_1_scale2_h" | |
| type: "Scale" | |
| bottom: "layer_64_1_conv1_h" | |
| top: "layer_64_1_conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "layer_64_1_relu2" | |
| type: "ReLU" | |
| bottom: "layer_64_1_conv1_h" | |
| top: "layer_64_1_conv1_h" | |
| } | |
| layer { | |
| name: "layer_64_1_conv2_h" | |
| type: "Convolution" | |
| bottom: "layer_64_1_conv1_h" | |
| top: "layer_64_1_conv2_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_64_1_sum" | |
| type: "Eltwise" | |
| bottom: "layer_64_1_conv2_h" | |
| bottom: "conv1_pool" | |
| top: "layer_64_1_sum" | |
| } | |
| layer { | |
| name: "layer_128_1_bn1_h" | |
| type: "BatchNorm" | |
| bottom: "layer_64_1_sum" | |
| top: "layer_128_1_bn1_h" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "layer_128_1_scale1_h" | |
| type: "Scale" | |
| bottom: "layer_128_1_bn1_h" | |
| top: "layer_128_1_bn1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "layer_128_1_relu1" | |
| type: "ReLU" | |
| bottom: "layer_128_1_bn1_h" | |
| top: "layer_128_1_bn1_h" | |
| } | |
| layer { | |
| name: "layer_128_1_conv1_h" | |
| type: "Convolution" | |
| bottom: "layer_128_1_bn1_h" | |
| top: "layer_128_1_conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_128_1_bn2" | |
| type: "BatchNorm" | |
| bottom: "layer_128_1_conv1_h" | |
| top: "layer_128_1_conv1_h" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "layer_128_1_scale2" | |
| type: "Scale" | |
| bottom: "layer_128_1_conv1_h" | |
| top: "layer_128_1_conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "layer_128_1_relu2" | |
| type: "ReLU" | |
| bottom: "layer_128_1_conv1_h" | |
| top: "layer_128_1_conv1_h" | |
| } | |
| layer { | |
| name: "layer_128_1_conv2" | |
| type: "Convolution" | |
| bottom: "layer_128_1_conv1_h" | |
| top: "layer_128_1_conv2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_128_1_conv_expand_h" | |
| type: "Convolution" | |
| bottom: "layer_128_1_bn1_h" | |
| top: "layer_128_1_conv_expand_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_128_1_sum" | |
| type: "Eltwise" | |
| bottom: "layer_128_1_conv2" | |
| bottom: "layer_128_1_conv_expand_h" | |
| top: "layer_128_1_sum" | |
| } | |
| layer { | |
| name: "layer_256_1_bn1" | |
| type: "BatchNorm" | |
| bottom: "layer_128_1_sum" | |
| top: "layer_256_1_bn1" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "layer_256_1_scale1" | |
| type: "Scale" | |
| bottom: "layer_256_1_bn1" | |
| top: "layer_256_1_bn1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "layer_256_1_relu1" | |
| type: "ReLU" | |
| bottom: "layer_256_1_bn1" | |
| top: "layer_256_1_bn1" | |
| } | |
| layer { | |
| name: "layer_256_1_conv1" | |
| type: "Convolution" | |
| bottom: "layer_256_1_bn1" | |
| top: "layer_256_1_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_256_1_bn2" | |
| type: "BatchNorm" | |
| bottom: "layer_256_1_conv1" | |
| top: "layer_256_1_conv1" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "layer_256_1_scale2" | |
| type: "Scale" | |
| bottom: "layer_256_1_conv1" | |
| top: "layer_256_1_conv1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "layer_256_1_relu2" | |
| type: "ReLU" | |
| bottom: "layer_256_1_conv1" | |
| top: "layer_256_1_conv1" | |
| } | |
| layer { | |
| name: "layer_256_1_conv2" | |
| type: "Convolution" | |
| bottom: "layer_256_1_conv1" | |
| top: "layer_256_1_conv2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_256_1_conv_expand" | |
| type: "Convolution" | |
| bottom: "layer_256_1_bn1" | |
| top: "layer_256_1_conv_expand" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_256_1_sum" | |
| type: "Eltwise" | |
| bottom: "layer_256_1_conv2" | |
| bottom: "layer_256_1_conv_expand" | |
| top: "layer_256_1_sum" | |
| } | |
| layer { | |
| name: "layer_512_1_bn1" | |
| type: "BatchNorm" | |
| bottom: "layer_256_1_sum" | |
| top: "layer_512_1_bn1" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "layer_512_1_scale1" | |
| type: "Scale" | |
| bottom: "layer_512_1_bn1" | |
| top: "layer_512_1_bn1" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "layer_512_1_relu1" | |
| type: "ReLU" | |
| bottom: "layer_512_1_bn1" | |
| top: "layer_512_1_bn1" | |
| } | |
| layer { | |
| name: "layer_512_1_conv1_h" | |
| type: "Convolution" | |
| bottom: "layer_512_1_bn1" | |
| top: "layer_512_1_conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 # 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_512_1_bn2_h" | |
| type: "BatchNorm" | |
| bottom: "layer_512_1_conv1_h" | |
| top: "layer_512_1_conv1_h" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "layer_512_1_scale2_h" | |
| type: "Scale" | |
| bottom: "layer_512_1_conv1_h" | |
| top: "layer_512_1_conv1_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "layer_512_1_relu2" | |
| type: "ReLU" | |
| bottom: "layer_512_1_conv1_h" | |
| top: "layer_512_1_conv1_h" | |
| } | |
| layer { | |
| name: "layer_512_1_conv2_h" | |
| type: "Convolution" | |
| bottom: "layer_512_1_conv1_h" | |
| top: "layer_512_1_conv2_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 2 # 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| dilation: 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_512_1_conv_expand_h" | |
| type: "Convolution" | |
| bottom: "layer_512_1_bn1" | |
| top: "layer_512_1_conv_expand_h" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 # 2 | |
| weight_filler { | |
| type: "msra" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "layer_512_1_sum" | |
| type: "Eltwise" | |
| bottom: "layer_512_1_conv2_h" | |
| bottom: "layer_512_1_conv_expand_h" | |
| top: "layer_512_1_sum" | |
| } | |
| layer { | |
| name: "last_bn_h" | |
| type: "BatchNorm" | |
| bottom: "layer_512_1_sum" | |
| top: "layer_512_1_sum" | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| param { | |
| lr_mult: 0.0 | |
| } | |
| } | |
| layer { | |
| name: "last_scale_h" | |
| type: "Scale" | |
| bottom: "layer_512_1_sum" | |
| top: "layer_512_1_sum" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 1.0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "last_relu" | |
| type: "ReLU" | |
| bottom: "layer_512_1_sum" | |
| top: "fc7" | |
| } | |
| layer { | |
| name: "conv6_1_h" | |
| type: "Convolution" | |
| bottom: "fc7" | |
| top: "conv6_1_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_1_relu" | |
| type: "ReLU" | |
| bottom: "conv6_1_h" | |
| top: "conv6_1_h" | |
| } | |
| layer { | |
| name: "conv6_2_h" | |
| type: "Convolution" | |
| bottom: "conv6_1_h" | |
| top: "conv6_2_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_relu" | |
| type: "ReLU" | |
| bottom: "conv6_2_h" | |
| top: "conv6_2_h" | |
| } | |
| layer { | |
| name: "conv7_1_h" | |
| type: "Convolution" | |
| bottom: "conv6_2_h" | |
| top: "conv7_1_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_1_relu" | |
| type: "ReLU" | |
| bottom: "conv7_1_h" | |
| top: "conv7_1_h" | |
| } | |
| layer { | |
| name: "conv7_2_h" | |
| type: "Convolution" | |
| bottom: "conv7_1_h" | |
| top: "conv7_2_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 2 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_relu" | |
| type: "ReLU" | |
| bottom: "conv7_2_h" | |
| top: "conv7_2_h" | |
| } | |
| layer { | |
| name: "conv8_1_h" | |
| type: "Convolution" | |
| bottom: "conv7_2_h" | |
| top: "conv8_1_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_1_relu" | |
| type: "ReLU" | |
| bottom: "conv8_1_h" | |
| top: "conv8_1_h" | |
| } | |
| layer { | |
| name: "conv8_2_h" | |
| type: "Convolution" | |
| bottom: "conv8_1_h" | |
| top: "conv8_2_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_relu" | |
| type: "ReLU" | |
| bottom: "conv8_2_h" | |
| top: "conv8_2_h" | |
| } | |
| layer { | |
| name: "conv9_1_h" | |
| type: "Convolution" | |
| bottom: "conv8_2_h" | |
| top: "conv9_1_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| pad: 0 | |
| kernel_size: 1 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_1_relu" | |
| type: "ReLU" | |
| bottom: "conv9_1_h" | |
| top: "conv9_1_h" | |
| } | |
| layer { | |
| name: "conv9_2_h" | |
| type: "Convolution" | |
| bottom: "conv9_1_h" | |
| top: "conv9_2_h" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_relu" | |
| type: "ReLU" | |
| bottom: "conv9_2_h" | |
| top: "conv9_2_h" | |
| } | |
| layer { | |
| name: "conv4_3_norm" | |
| type: "Normalize" | |
| bottom: "layer_256_1_bn1" | |
| top: "conv4_3_norm" | |
| norm_param { | |
| across_spatial: false | |
| scale_filler { | |
| type: "constant" | |
| value: 20 | |
| } | |
| channel_shared: false | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv4_3_norm" | |
| top: "conv4_3_norm_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv4_3_norm_mbox_loc" | |
| top: "conv4_3_norm_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv4_3_norm_mbox_loc_perm" | |
| top: "conv4_3_norm_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv4_3_norm" | |
| top: "conv4_3_norm_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 8 # 84 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv4_3_norm_mbox_conf" | |
| top: "conv4_3_norm_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv4_3_norm_mbox_conf_perm" | |
| top: "conv4_3_norm_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3_norm_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv4_3_norm" | |
| bottom: "data" | |
| top: "conv4_3_norm_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 30.0 | |
| max_size: 60.0 | |
| aspect_ratio: 2 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 8 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_loc" | |
| type: "Convolution" | |
| bottom: "fc7" | |
| top: "fc7_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "fc7_mbox_loc" | |
| top: "fc7_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "fc7_mbox_loc_perm" | |
| top: "fc7_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_conf" | |
| type: "Convolution" | |
| bottom: "fc7" | |
| top: "fc7_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 12 # 126 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "fc7_mbox_conf" | |
| top: "fc7_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "fc7_mbox_conf_perm" | |
| top: "fc7_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "fc7_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "fc7" | |
| bottom: "data" | |
| top: "fc7_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 60.0 | |
| max_size: 111.0 | |
| aspect_ratio: 2 | |
| aspect_ratio: 3 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 16 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv6_2_h" | |
| top: "conv6_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv6_2_mbox_loc" | |
| top: "conv6_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv6_2_mbox_loc_perm" | |
| top: "conv6_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv6_2_h" | |
| top: "conv6_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 12 # 126 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv6_2_mbox_conf" | |
| top: "conv6_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv6_2_mbox_conf_perm" | |
| top: "conv6_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv6_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv6_2_h" | |
| bottom: "data" | |
| top: "conv6_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 111.0 | |
| max_size: 162.0 | |
| aspect_ratio: 2 | |
| aspect_ratio: 3 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 32 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv7_2_h" | |
| top: "conv7_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv7_2_mbox_loc" | |
| top: "conv7_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv7_2_mbox_loc_perm" | |
| top: "conv7_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv7_2_h" | |
| top: "conv7_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 12 # 126 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv7_2_mbox_conf" | |
| top: "conv7_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv7_2_mbox_conf_perm" | |
| top: "conv7_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv7_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv7_2_h" | |
| bottom: "data" | |
| top: "conv7_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 162.0 | |
| max_size: 213.0 | |
| aspect_ratio: 2 | |
| aspect_ratio: 3 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 64 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv8_2_h" | |
| top: "conv8_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv8_2_mbox_loc" | |
| top: "conv8_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv8_2_mbox_loc_perm" | |
| top: "conv8_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv8_2_h" | |
| top: "conv8_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 8 # 84 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv8_2_mbox_conf" | |
| top: "conv8_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv8_2_mbox_conf_perm" | |
| top: "conv8_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv8_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv8_2_h" | |
| bottom: "data" | |
| top: "conv8_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 213.0 | |
| max_size: 264.0 | |
| aspect_ratio: 2 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 100 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_loc" | |
| type: "Convolution" | |
| bottom: "conv9_2_h" | |
| top: "conv9_2_mbox_loc" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_loc_perm" | |
| type: "Permute" | |
| bottom: "conv9_2_mbox_loc" | |
| top: "conv9_2_mbox_loc_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_loc_flat" | |
| type: "Flatten" | |
| bottom: "conv9_2_mbox_loc_perm" | |
| top: "conv9_2_mbox_loc_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_conf" | |
| type: "Convolution" | |
| bottom: "conv9_2_h" | |
| top: "conv9_2_mbox_conf" | |
| param { | |
| lr_mult: 1 | |
| decay_mult: 1 | |
| } | |
| param { | |
| lr_mult: 2 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 8 # 84 | |
| pad: 1 | |
| kernel_size: 3 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_conf_perm" | |
| type: "Permute" | |
| bottom: "conv9_2_mbox_conf" | |
| top: "conv9_2_mbox_conf_perm" | |
| permute_param { | |
| order: 0 | |
| order: 2 | |
| order: 3 | |
| order: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_conf_flat" | |
| type: "Flatten" | |
| bottom: "conv9_2_mbox_conf_perm" | |
| top: "conv9_2_mbox_conf_flat" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv9_2_mbox_priorbox" | |
| type: "PriorBox" | |
| bottom: "conv9_2_h" | |
| bottom: "data" | |
| top: "conv9_2_mbox_priorbox" | |
| prior_box_param { | |
| min_size: 264.0 | |
| max_size: 315.0 | |
| aspect_ratio: 2 | |
| flip: true | |
| clip: false | |
| variance: 0.1 | |
| variance: 0.1 | |
| variance: 0.2 | |
| variance: 0.2 | |
| step: 300 | |
| offset: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "mbox_loc" | |
| type: "Concat" | |
| bottom: "conv4_3_norm_mbox_loc_flat" | |
| bottom: "fc7_mbox_loc_flat" | |
| bottom: "conv6_2_mbox_loc_flat" | |
| bottom: "conv7_2_mbox_loc_flat" | |
| bottom: "conv8_2_mbox_loc_flat" | |
| bottom: "conv9_2_mbox_loc_flat" | |
| top: "mbox_loc" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf" | |
| type: "Concat" | |
| bottom: "conv4_3_norm_mbox_conf_flat" | |
| bottom: "fc7_mbox_conf_flat" | |
| bottom: "conv6_2_mbox_conf_flat" | |
| bottom: "conv7_2_mbox_conf_flat" | |
| bottom: "conv8_2_mbox_conf_flat" | |
| bottom: "conv9_2_mbox_conf_flat" | |
| top: "mbox_conf" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "mbox_priorbox" | |
| type: "Concat" | |
| bottom: "conv4_3_norm_mbox_priorbox" | |
| bottom: "fc7_mbox_priorbox" | |
| bottom: "conv6_2_mbox_priorbox" | |
| bottom: "conv7_2_mbox_priorbox" | |
| bottom: "conv8_2_mbox_priorbox" | |
| bottom: "conv9_2_mbox_priorbox" | |
| top: "mbox_priorbox" | |
| concat_param { | |
| axis: 2 | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf_reshape" | |
| type: "Reshape" | |
| bottom: "mbox_conf" | |
| top: "mbox_conf_reshape" | |
| reshape_param { | |
| shape { | |
| dim: 0 | |
| dim: -1 | |
| dim: 2 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf_softmax" | |
| type: "Softmax" | |
| bottom: "mbox_conf_reshape" | |
| top: "mbox_conf_softmax" | |
| softmax_param { | |
| axis: 2 | |
| } | |
| } | |
| layer { | |
| name: "mbox_conf_flatten" | |
| type: "Flatten" | |
| bottom: "mbox_conf_softmax" | |
| top: "mbox_conf_flatten" | |
| flatten_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "detection_out" | |
| type: "DetectionOutput" | |
| bottom: "mbox_loc" | |
| bottom: "mbox_conf_flatten" | |
| bottom: "mbox_priorbox" | |
| top: "detection_out" | |
| include { | |
| phase: TEST | |
| } | |
| detection_output_param { | |
| num_classes: 2 | |
| share_location: true | |
| background_label_id: 0 | |
| nms_param { | |
| nms_threshold: 0.45 | |
| top_k: 400 | |
| } | |
| code_type: CENTER_SIZE | |
| keep_top_k: 200 | |
| confidence_threshold: 0.01 | |
| } | |
| } | |