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November 26, 2016 12:20
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| name: "PVANET" | |
| ################################################################################ | |
| ## Input | |
| ################################################################################ | |
| input: "data" | |
| input_shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 640 | |
| dim: 1056 | |
| } | |
| input: "im_info" | |
| input_shape { | |
| dim: 1 | |
| dim: 6 | |
| } | |
| ################################################################################ | |
| ## Convolution | |
| ################################################################################ | |
| layer { | |
| name: "conv1_1/conv" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1_1/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 16 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 3 | |
| pad_w: 3 | |
| kernel_h: 7 | |
| kernel_w: 7 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv1_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv1_1/conv" | |
| top: "conv1_1/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv1_1/neg" | |
| type: "Power" | |
| bottom: "conv1_1/conv" | |
| top: "conv1_1/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv1_1/concat" | |
| type: "Concat" | |
| bottom: "conv1_1/conv" | |
| bottom: "conv1_1/neg" | |
| top: "conv1_1" | |
| } | |
| layer { | |
| name: "conv1_1/scale" | |
| type: "Scale" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv1_1/relu" | |
| type: "ReLU" | |
| bottom: "conv1_1" | |
| top: "conv1_1" | |
| } | |
| layer { | |
| name: "pool1" | |
| type: "Pooling" | |
| bottom: "conv1_1" | |
| top: "pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/1/conv" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv2_1/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/1" | |
| top: "conv2_1/1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv2_1/1" | |
| top: "conv2_1/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/1/relu" | |
| type: "ReLU" | |
| bottom: "conv2_1/1" | |
| top: "conv2_1/1" | |
| } | |
| layer { | |
| name: "conv2_1/2/conv" | |
| type: "Convolution" | |
| bottom: "conv2_1/1" | |
| top: "conv2_1/2/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/2/conv" | |
| top: "conv2_1/2/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/2/neg" | |
| type: "Power" | |
| bottom: "conv2_1/2/conv" | |
| top: "conv2_1/2/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/2/concat" | |
| type: "Concat" | |
| bottom: "conv2_1/2/conv" | |
| bottom: "conv2_1/2/neg" | |
| top: "conv2_1/2" | |
| } | |
| layer { | |
| name: "conv2_1/2/scale" | |
| type: "Scale" | |
| bottom: "conv2_1/2" | |
| top: "conv2_1/2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/2/relu" | |
| type: "ReLU" | |
| bottom: "conv2_1/2" | |
| top: "conv2_1/2" | |
| } | |
| layer { | |
| name: "conv2_1/3/conv" | |
| type: "Convolution" | |
| bottom: "conv2_1/2" | |
| top: "conv2_1/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/3" | |
| top: "conv2_1/3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/3/bn_scale" | |
| type: "Scale" | |
| bottom: "conv2_1/3" | |
| top: "conv2_1/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/proj" | |
| type: "Convolution" | |
| bottom: "pool1" | |
| top: "conv2_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/proj_bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_1/proj" | |
| top: "conv2_1/proj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1/proj_bn_scale" | |
| type: "Scale" | |
| bottom: "conv2_1/proj" | |
| top: "conv2_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_1" | |
| type: "Eltwise" | |
| bottom: "conv2_1/3" | |
| bottom: "conv2_1/proj" | |
| top: "conv2_1" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/1/conv" | |
| type: "Convolution" | |
| bottom: "conv2_1" | |
| top: "conv2_2/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/1" | |
| top: "conv2_2/1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv2_2/1" | |
| top: "conv2_2/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/1/relu" | |
| type: "ReLU" | |
| bottom: "conv2_2/1" | |
| top: "conv2_2/1" | |
| } | |
| layer { | |
| name: "conv2_2/2/conv" | |
| type: "Convolution" | |
| bottom: "conv2_2/1" | |
| top: "conv2_2/2/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/2/conv" | |
| top: "conv2_2/2/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/2/neg" | |
| type: "Power" | |
| bottom: "conv2_2/2/conv" | |
| top: "conv2_2/2/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/2/concat" | |
| type: "Concat" | |
| bottom: "conv2_2/2/conv" | |
| bottom: "conv2_2/2/neg" | |
| top: "conv2_2/2" | |
| } | |
| layer { | |
| name: "conv2_2/2/scale" | |
| type: "Scale" | |
| bottom: "conv2_2/2" | |
| top: "conv2_2/2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/2/relu" | |
| type: "ReLU" | |
| bottom: "conv2_2/2" | |
| top: "conv2_2/2" | |
| } | |
| layer { | |
| name: "conv2_2/3/conv" | |
| type: "Convolution" | |
| bottom: "conv2_2/2" | |
| top: "conv2_2/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_2/3" | |
| top: "conv2_2/3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/3/bn_scale" | |
| type: "Scale" | |
| bottom: "conv2_2/3" | |
| top: "conv2_2/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_2/input" | |
| type: "Power" | |
| bottom: "conv2_1" | |
| top: "conv2_2/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2_2" | |
| type: "Eltwise" | |
| bottom: "conv2_2/3" | |
| bottom: "conv2_2/input" | |
| top: "conv2_2" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/1/conv" | |
| type: "Convolution" | |
| bottom: "conv2_2" | |
| top: "conv2_3/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_3/1" | |
| top: "conv2_3/1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv2_3/1" | |
| top: "conv2_3/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/1/relu" | |
| type: "ReLU" | |
| bottom: "conv2_3/1" | |
| top: "conv2_3/1" | |
| } | |
| layer { | |
| name: "conv2_3/2/conv" | |
| type: "Convolution" | |
| bottom: "conv2_3/1" | |
| top: "conv2_3/2/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_3/2/conv" | |
| top: "conv2_3/2/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/2/neg" | |
| type: "Power" | |
| bottom: "conv2_3/2/conv" | |
| top: "conv2_3/2/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/2/concat" | |
| type: "Concat" | |
| bottom: "conv2_3/2/conv" | |
| bottom: "conv2_3/2/neg" | |
| top: "conv2_3/2" | |
| } | |
| layer { | |
| name: "conv2_3/2/scale" | |
| type: "Scale" | |
| bottom: "conv2_3/2" | |
| top: "conv2_3/2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/2/relu" | |
| type: "ReLU" | |
| bottom: "conv2_3/2" | |
| top: "conv2_3/2" | |
| } | |
| layer { | |
| name: "conv2_3/3/conv" | |
| type: "Convolution" | |
| bottom: "conv2_3/2" | |
| top: "conv2_3/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv2_3/3" | |
| top: "conv2_3/3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/3/bn_scale" | |
| type: "Scale" | |
| bottom: "conv2_3/3" | |
| top: "conv2_3/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv2_3/input" | |
| type: "Power" | |
| bottom: "conv2_2" | |
| top: "conv2_3/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv2_3" | |
| type: "Eltwise" | |
| bottom: "conv2_3/3" | |
| bottom: "conv2_3/input" | |
| top: "conv2_3" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/1/conv" | |
| type: "Convolution" | |
| bottom: "conv2_3" | |
| top: "conv3_1/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/1" | |
| top: "conv3_1/1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_1/1" | |
| top: "conv3_1/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/1/relu" | |
| type: "ReLU" | |
| bottom: "conv3_1/1" | |
| top: "conv3_1/1" | |
| } | |
| layer { | |
| name: "conv3_1/2/conv" | |
| type: "Convolution" | |
| bottom: "conv3_1/1" | |
| top: "conv3_1/2/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/2/conv" | |
| top: "conv3_1/2/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/2/neg" | |
| type: "Power" | |
| bottom: "conv3_1/2/conv" | |
| top: "conv3_1/2/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/2/concat" | |
| type: "Concat" | |
| bottom: "conv3_1/2/conv" | |
| bottom: "conv3_1/2/neg" | |
| top: "conv3_1/2" | |
| } | |
| layer { | |
| name: "conv3_1/2/scale" | |
| type: "Scale" | |
| bottom: "conv3_1/2" | |
| top: "conv3_1/2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/2/relu" | |
| type: "ReLU" | |
| bottom: "conv3_1/2" | |
| top: "conv3_1/2" | |
| } | |
| layer { | |
| name: "conv3_1/3/conv" | |
| type: "Convolution" | |
| bottom: "conv3_1/2" | |
| top: "conv3_1/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/3" | |
| top: "conv3_1/3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/3/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_1/3" | |
| top: "conv3_1/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/proj" | |
| type: "Convolution" | |
| bottom: "conv2_3" | |
| top: "conv3_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/proj_bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_1/proj" | |
| top: "conv3_1/proj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1/proj_bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_1/proj" | |
| top: "conv3_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_1" | |
| type: "Eltwise" | |
| bottom: "conv3_1/3" | |
| bottom: "conv3_1/proj" | |
| top: "conv3_1" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/1/conv" | |
| type: "Convolution" | |
| bottom: "conv3_1" | |
| top: "conv3_2/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/1" | |
| top: "conv3_2/1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_2/1" | |
| top: "conv3_2/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/1/relu" | |
| type: "ReLU" | |
| bottom: "conv3_2/1" | |
| top: "conv3_2/1" | |
| } | |
| layer { | |
| name: "conv3_2/2/conv" | |
| type: "Convolution" | |
| bottom: "conv3_2/1" | |
| top: "conv3_2/2/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/2/conv" | |
| top: "conv3_2/2/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/2/neg" | |
| type: "Power" | |
| bottom: "conv3_2/2/conv" | |
| top: "conv3_2/2/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/2/concat" | |
| type: "Concat" | |
| bottom: "conv3_2/2/conv" | |
| bottom: "conv3_2/2/neg" | |
| top: "conv3_2/2" | |
| } | |
| layer { | |
| name: "conv3_2/2/scale" | |
| type: "Scale" | |
| bottom: "conv3_2/2" | |
| top: "conv3_2/2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/2/relu" | |
| type: "ReLU" | |
| bottom: "conv3_2/2" | |
| top: "conv3_2/2" | |
| } | |
| layer { | |
| name: "conv3_2/3/conv" | |
| type: "Convolution" | |
| bottom: "conv3_2/2" | |
| top: "conv3_2/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_2/3" | |
| top: "conv3_2/3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/3/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_2/3" | |
| top: "conv3_2/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_2/input" | |
| type: "Power" | |
| bottom: "conv3_1" | |
| top: "conv3_2/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3_2" | |
| type: "Eltwise" | |
| bottom: "conv3_2/3" | |
| bottom: "conv3_2/input" | |
| top: "conv3_2" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/1/conv" | |
| type: "Convolution" | |
| bottom: "conv3_2" | |
| top: "conv3_3/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_3/1" | |
| top: "conv3_3/1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_3/1" | |
| top: "conv3_3/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/1/relu" | |
| type: "ReLU" | |
| bottom: "conv3_3/1" | |
| top: "conv3_3/1" | |
| } | |
| layer { | |
| name: "conv3_3/2/conv" | |
| type: "Convolution" | |
| bottom: "conv3_3/1" | |
| top: "conv3_3/2/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_3/2/conv" | |
| top: "conv3_3/2/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/2/neg" | |
| type: "Power" | |
| bottom: "conv3_3/2/conv" | |
| top: "conv3_3/2/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/2/concat" | |
| type: "Concat" | |
| bottom: "conv3_3/2/conv" | |
| bottom: "conv3_3/2/neg" | |
| top: "conv3_3/2" | |
| } | |
| layer { | |
| name: "conv3_3/2/scale" | |
| type: "Scale" | |
| bottom: "conv3_3/2" | |
| top: "conv3_3/2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/2/relu" | |
| type: "ReLU" | |
| bottom: "conv3_3/2" | |
| top: "conv3_3/2" | |
| } | |
| layer { | |
| name: "conv3_3/3/conv" | |
| type: "Convolution" | |
| bottom: "conv3_3/2" | |
| top: "conv3_3/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_3/3" | |
| top: "conv3_3/3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/3/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_3/3" | |
| top: "conv3_3/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_3/input" | |
| type: "Power" | |
| bottom: "conv3_2" | |
| top: "conv3_3/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3_3" | |
| type: "Eltwise" | |
| bottom: "conv3_3/3" | |
| bottom: "conv3_3/input" | |
| top: "conv3_3" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/1/conv" | |
| type: "Convolution" | |
| bottom: "conv3_3" | |
| top: "conv3_4/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_4/1" | |
| top: "conv3_4/1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_4/1" | |
| top: "conv3_4/1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/1/relu" | |
| type: "ReLU" | |
| bottom: "conv3_4/1" | |
| top: "conv3_4/1" | |
| } | |
| layer { | |
| name: "conv3_4/2/conv" | |
| type: "Convolution" | |
| bottom: "conv3_4/1" | |
| top: "conv3_4/2/conv" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/2/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_4/2/conv" | |
| top: "conv3_4/2/conv" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/2/neg" | |
| type: "Power" | |
| bottom: "conv3_4/2/conv" | |
| top: "conv3_4/2/neg" | |
| power_param { | |
| power: 1 | |
| scale: -1.0 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/2/concat" | |
| type: "Concat" | |
| bottom: "conv3_4/2/conv" | |
| bottom: "conv3_4/2/neg" | |
| top: "conv3_4/2" | |
| } | |
| layer { | |
| name: "conv3_4/2/scale" | |
| type: "Scale" | |
| bottom: "conv3_4/2" | |
| top: "conv3_4/2" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/2/relu" | |
| type: "ReLU" | |
| bottom: "conv3_4/2" | |
| top: "conv3_4/2" | |
| } | |
| layer { | |
| name: "conv3_4/3/conv" | |
| type: "Convolution" | |
| bottom: "conv3_4/2" | |
| top: "conv3_4/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/3/bn" | |
| type: "BatchNorm" | |
| bottom: "conv3_4/3" | |
| top: "conv3_4/3" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/3/bn_scale" | |
| type: "Scale" | |
| bottom: "conv3_4/3" | |
| top: "conv3_4/3" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv3_4/input" | |
| type: "Power" | |
| bottom: "conv3_3" | |
| top: "conv3_4/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv3_4" | |
| type: "Eltwise" | |
| bottom: "conv3_4/3" | |
| bottom: "conv3_4/input" | |
| top: "conv3_4" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv3_4" | |
| top: "conv4_1/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/incep/0" | |
| top: "conv4_1/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/incep/0" | |
| top: "conv4_1/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1/incep/0" | |
| top: "conv4_1/incep/0" | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv3_4" | |
| top: "conv4_1/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/incep/1_reduce" | |
| top: "conv4_1/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/incep/1_reduce" | |
| top: "conv4_1/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1/incep/1_reduce" | |
| top: "conv4_1/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1/incep/1_reduce" | |
| top: "conv4_1/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/incep/1_0" | |
| top: "conv4_1/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/incep/1_0" | |
| top: "conv4_1/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1/incep/1_0" | |
| top: "conv4_1/incep/1_0" | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv3_4" | |
| top: "conv4_1/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/incep/2_reduce" | |
| top: "conv4_1/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/incep/2_reduce" | |
| top: "conv4_1/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1/incep/2_reduce" | |
| top: "conv4_1/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1/incep/2_reduce" | |
| top: "conv4_1/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/incep/2_0" | |
| top: "conv4_1/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/incep/2_0" | |
| top: "conv4_1/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1/incep/2_0" | |
| top: "conv4_1/incep/2_0" | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1/incep/2_0" | |
| top: "conv4_1/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/incep/2_1" | |
| top: "conv4_1/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/incep/2_1" | |
| top: "conv4_1/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1/incep/2_1" | |
| top: "conv4_1/incep/2_1" | |
| } | |
| layer { | |
| name: "conv4_1/incep/pool" | |
| type: "Pooling" | |
| bottom: "conv3_4" | |
| top: "conv4_1/incep/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/poolproj/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1/incep/pool" | |
| top: "conv4_1/incep/poolproj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/poolproj/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/incep/poolproj" | |
| top: "conv4_1/incep/poolproj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/poolproj/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/incep/poolproj" | |
| top: "conv4_1/incep/poolproj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/incep/poolproj/relu" | |
| type: "ReLU" | |
| bottom: "conv4_1/incep/poolproj" | |
| top: "conv4_1/incep/poolproj" | |
| } | |
| layer { | |
| name: "conv4_1/incep" | |
| type: "Concat" | |
| bottom: "conv4_1/incep/0" | |
| bottom: "conv4_1/incep/1_0" | |
| bottom: "conv4_1/incep/2_1" | |
| bottom: "conv4_1/incep/poolproj" | |
| top: "conv4_1/incep" | |
| } | |
| layer { | |
| name: "conv4_1/out/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1/incep" | |
| top: "conv4_1/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/out" | |
| top: "conv4_1/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/out" | |
| top: "conv4_1/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/proj" | |
| type: "Convolution" | |
| bottom: "conv3_4" | |
| top: "conv4_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/proj_bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_1/proj" | |
| top: "conv4_1/proj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1/proj_bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_1/proj" | |
| top: "conv4_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_1" | |
| type: "Eltwise" | |
| bottom: "conv4_1/out" | |
| bottom: "conv4_1/proj" | |
| top: "conv4_1" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv4_2/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/incep/0" | |
| top: "conv4_2/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_2/incep/0" | |
| top: "conv4_2/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2/incep/0" | |
| top: "conv4_2/incep/0" | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv4_2/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/incep/1_reduce" | |
| top: "conv4_2/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_2/incep/1_reduce" | |
| top: "conv4_2/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2/incep/1_reduce" | |
| top: "conv4_2/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_2/incep/1_reduce" | |
| top: "conv4_2/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/incep/1_0" | |
| top: "conv4_2/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_2/incep/1_0" | |
| top: "conv4_2/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2/incep/1_0" | |
| top: "conv4_2/incep/1_0" | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_1" | |
| top: "conv4_2/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/incep/2_reduce" | |
| top: "conv4_2/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_2/incep/2_reduce" | |
| top: "conv4_2/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2/incep/2_reduce" | |
| top: "conv4_2/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_2/incep/2_reduce" | |
| top: "conv4_2/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/incep/2_0" | |
| top: "conv4_2/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_2/incep/2_0" | |
| top: "conv4_2/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2/incep/2_0" | |
| top: "conv4_2/incep/2_0" | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv4_2/incep/2_0" | |
| top: "conv4_2/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/incep/2_1" | |
| top: "conv4_2/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_2/incep/2_1" | |
| top: "conv4_2/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv4_2/incep/2_1" | |
| top: "conv4_2/incep/2_1" | |
| } | |
| layer { | |
| name: "conv4_2/incep" | |
| type: "Concat" | |
| bottom: "conv4_2/incep/0" | |
| bottom: "conv4_2/incep/1_0" | |
| bottom: "conv4_2/incep/2_1" | |
| top: "conv4_2/incep" | |
| } | |
| layer { | |
| name: "conv4_2/out/conv" | |
| type: "Convolution" | |
| bottom: "conv4_2/incep" | |
| top: "conv4_2/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_2/out" | |
| top: "conv4_2/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_2/out" | |
| top: "conv4_2/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_2/input" | |
| type: "Power" | |
| bottom: "conv4_1" | |
| top: "conv4_2/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv4_2" | |
| type: "Eltwise" | |
| bottom: "conv4_2/out" | |
| bottom: "conv4_2/input" | |
| top: "conv4_2" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_2" | |
| top: "conv4_3/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/incep/0" | |
| top: "conv4_3/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_3/incep/0" | |
| top: "conv4_3/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3/incep/0" | |
| top: "conv4_3/incep/0" | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_2" | |
| top: "conv4_3/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/incep/1_reduce" | |
| top: "conv4_3/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_3/incep/1_reduce" | |
| top: "conv4_3/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3/incep/1_reduce" | |
| top: "conv4_3/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_3/incep/1_reduce" | |
| top: "conv4_3/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/incep/1_0" | |
| top: "conv4_3/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_3/incep/1_0" | |
| top: "conv4_3/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3/incep/1_0" | |
| top: "conv4_3/incep/1_0" | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_2" | |
| top: "conv4_3/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/incep/2_reduce" | |
| top: "conv4_3/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_3/incep/2_reduce" | |
| top: "conv4_3/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3/incep/2_reduce" | |
| top: "conv4_3/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_3/incep/2_reduce" | |
| top: "conv4_3/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/incep/2_0" | |
| top: "conv4_3/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_3/incep/2_0" | |
| top: "conv4_3/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3/incep/2_0" | |
| top: "conv4_3/incep/2_0" | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv4_3/incep/2_0" | |
| top: "conv4_3/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/incep/2_1" | |
| top: "conv4_3/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_3/incep/2_1" | |
| top: "conv4_3/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv4_3/incep/2_1" | |
| top: "conv4_3/incep/2_1" | |
| } | |
| layer { | |
| name: "conv4_3/incep" | |
| type: "Concat" | |
| bottom: "conv4_3/incep/0" | |
| bottom: "conv4_3/incep/1_0" | |
| bottom: "conv4_3/incep/2_1" | |
| top: "conv4_3/incep" | |
| } | |
| layer { | |
| name: "conv4_3/out/conv" | |
| type: "Convolution" | |
| bottom: "conv4_3/incep" | |
| top: "conv4_3/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_3/out" | |
| top: "conv4_3/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_3/out" | |
| top: "conv4_3/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_3/input" | |
| type: "Power" | |
| bottom: "conv4_2" | |
| top: "conv4_3/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv4_3" | |
| type: "Eltwise" | |
| bottom: "conv4_3/out" | |
| bottom: "conv4_3/input" | |
| top: "conv4_3" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_3" | |
| top: "conv4_4/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/incep/0" | |
| top: "conv4_4/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_4/incep/0" | |
| top: "conv4_4/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4/incep/0" | |
| top: "conv4_4/incep/0" | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_3" | |
| top: "conv4_4/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/incep/1_reduce" | |
| top: "conv4_4/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_4/incep/1_reduce" | |
| top: "conv4_4/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4/incep/1_reduce" | |
| top: "conv4_4/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_4/incep/1_reduce" | |
| top: "conv4_4/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/incep/1_0" | |
| top: "conv4_4/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_4/incep/1_0" | |
| top: "conv4_4/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4/incep/1_0" | |
| top: "conv4_4/incep/1_0" | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_3" | |
| top: "conv4_4/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 24 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/incep/2_reduce" | |
| top: "conv4_4/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_4/incep/2_reduce" | |
| top: "conv4_4/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4/incep/2_reduce" | |
| top: "conv4_4/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_4/incep/2_reduce" | |
| top: "conv4_4/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/incep/2_0" | |
| top: "conv4_4/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_4/incep/2_0" | |
| top: "conv4_4/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4/incep/2_0" | |
| top: "conv4_4/incep/2_0" | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv4_4/incep/2_0" | |
| top: "conv4_4/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 48 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/incep/2_1" | |
| top: "conv4_4/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_4/incep/2_1" | |
| top: "conv4_4/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv4_4/incep/2_1" | |
| top: "conv4_4/incep/2_1" | |
| } | |
| layer { | |
| name: "conv4_4/incep" | |
| type: "Concat" | |
| bottom: "conv4_4/incep/0" | |
| bottom: "conv4_4/incep/1_0" | |
| bottom: "conv4_4/incep/2_1" | |
| top: "conv4_4/incep" | |
| } | |
| layer { | |
| name: "conv4_4/out/conv" | |
| type: "Convolution" | |
| bottom: "conv4_4/incep" | |
| top: "conv4_4/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 256 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv4_4/out" | |
| top: "conv4_4/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv4_4/out" | |
| top: "conv4_4/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv4_4/input" | |
| type: "Power" | |
| bottom: "conv4_3" | |
| top: "conv4_4/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv4_4" | |
| type: "Eltwise" | |
| bottom: "conv4_4/out" | |
| bottom: "conv4_4/input" | |
| top: "conv4_4" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv4_4" | |
| top: "conv5_1/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/incep/0" | |
| top: "conv5_1/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/incep/0" | |
| top: "conv5_1/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1/incep/0" | |
| top: "conv5_1/incep/0" | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_4" | |
| top: "conv5_1/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/incep/1_reduce" | |
| top: "conv5_1/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/incep/1_reduce" | |
| top: "conv5_1/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1/incep/1_reduce" | |
| top: "conv5_1/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1/incep/1_reduce" | |
| top: "conv5_1/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/incep/1_0" | |
| top: "conv5_1/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/incep/1_0" | |
| top: "conv5_1/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1/incep/1_0" | |
| top: "conv5_1/incep/1_0" | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv4_4" | |
| top: "conv5_1/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/incep/2_reduce" | |
| top: "conv5_1/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/incep/2_reduce" | |
| top: "conv5_1/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1/incep/2_reduce" | |
| top: "conv5_1/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1/incep/2_reduce" | |
| top: "conv5_1/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/incep/2_0" | |
| top: "conv5_1/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/incep/2_0" | |
| top: "conv5_1/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1/incep/2_0" | |
| top: "conv5_1/incep/2_0" | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1/incep/2_0" | |
| top: "conv5_1/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/incep/2_1" | |
| top: "conv5_1/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/incep/2_1" | |
| top: "conv5_1/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1/incep/2_1" | |
| top: "conv5_1/incep/2_1" | |
| } | |
| layer { | |
| name: "conv5_1/incep/pool" | |
| type: "Pooling" | |
| bottom: "conv4_4" | |
| top: "conv5_1/incep/pool" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/poolproj/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1/incep/pool" | |
| top: "conv5_1/incep/poolproj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/poolproj/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/incep/poolproj" | |
| top: "conv5_1/incep/poolproj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/poolproj/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/incep/poolproj" | |
| top: "conv5_1/incep/poolproj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/incep/poolproj/relu" | |
| type: "ReLU" | |
| bottom: "conv5_1/incep/poolproj" | |
| top: "conv5_1/incep/poolproj" | |
| } | |
| layer { | |
| name: "conv5_1/incep" | |
| type: "Concat" | |
| bottom: "conv5_1/incep/0" | |
| bottom: "conv5_1/incep/1_0" | |
| bottom: "conv5_1/incep/2_1" | |
| bottom: "conv5_1/incep/poolproj" | |
| top: "conv5_1/incep" | |
| } | |
| layer { | |
| name: "conv5_1/out/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1/incep" | |
| top: "conv5_1/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/out" | |
| top: "conv5_1/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/out" | |
| top: "conv5_1/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/proj" | |
| type: "Convolution" | |
| bottom: "conv4_4" | |
| top: "conv5_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| param { | |
| lr_mult: 0.2 | |
| decay_mult: 0.0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 2 | |
| stride_w: 2 | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/proj_bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_1/proj" | |
| top: "conv5_1/proj" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1/proj_bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_1/proj" | |
| top: "conv5_1/proj" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_1" | |
| type: "Eltwise" | |
| bottom: "conv5_1/out" | |
| bottom: "conv5_1/proj" | |
| top: "conv5_1" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv5_2/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/incep/0" | |
| top: "conv5_2/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_2/incep/0" | |
| top: "conv5_2/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2/incep/0" | |
| top: "conv5_2/incep/0" | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv5_2/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/incep/1_reduce" | |
| top: "conv5_2/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_2/incep/1_reduce" | |
| top: "conv5_2/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2/incep/1_reduce" | |
| top: "conv5_2/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_2/incep/1_reduce" | |
| top: "conv5_2/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/incep/1_0" | |
| top: "conv5_2/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_2/incep/1_0" | |
| top: "conv5_2/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2/incep/1_0" | |
| top: "conv5_2/incep/1_0" | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv5_1" | |
| top: "conv5_2/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/incep/2_reduce" | |
| top: "conv5_2/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_2/incep/2_reduce" | |
| top: "conv5_2/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2/incep/2_reduce" | |
| top: "conv5_2/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_2/incep/2_reduce" | |
| top: "conv5_2/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/incep/2_0" | |
| top: "conv5_2/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_2/incep/2_0" | |
| top: "conv5_2/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2/incep/2_0" | |
| top: "conv5_2/incep/2_0" | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv5_2/incep/2_0" | |
| top: "conv5_2/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/incep/2_1" | |
| top: "conv5_2/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_2/incep/2_1" | |
| top: "conv5_2/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv5_2/incep/2_1" | |
| top: "conv5_2/incep/2_1" | |
| } | |
| layer { | |
| name: "conv5_2/incep" | |
| type: "Concat" | |
| bottom: "conv5_2/incep/0" | |
| bottom: "conv5_2/incep/1_0" | |
| bottom: "conv5_2/incep/2_1" | |
| top: "conv5_2/incep" | |
| } | |
| layer { | |
| name: "conv5_2/out/conv" | |
| type: "Convolution" | |
| bottom: "conv5_2/incep" | |
| top: "conv5_2/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_2/out" | |
| top: "conv5_2/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_2/out" | |
| top: "conv5_2/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_2/input" | |
| type: "Power" | |
| bottom: "conv5_1" | |
| top: "conv5_2/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv5_2" | |
| type: "Eltwise" | |
| bottom: "conv5_2/out" | |
| bottom: "conv5_2/input" | |
| top: "conv5_2" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_2" | |
| top: "conv5_3/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/incep/0" | |
| top: "conv5_3/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_3/incep/0" | |
| top: "conv5_3/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3/incep/0" | |
| top: "conv5_3/incep/0" | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv5_2" | |
| top: "conv5_3/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/incep/1_reduce" | |
| top: "conv5_3/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_3/incep/1_reduce" | |
| top: "conv5_3/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3/incep/1_reduce" | |
| top: "conv5_3/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_3/incep/1_reduce" | |
| top: "conv5_3/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/incep/1_0" | |
| top: "conv5_3/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_3/incep/1_0" | |
| top: "conv5_3/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3/incep/1_0" | |
| top: "conv5_3/incep/1_0" | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv5_2" | |
| top: "conv5_3/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/incep/2_reduce" | |
| top: "conv5_3/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_3/incep/2_reduce" | |
| top: "conv5_3/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3/incep/2_reduce" | |
| top: "conv5_3/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_3/incep/2_reduce" | |
| top: "conv5_3/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/incep/2_0" | |
| top: "conv5_3/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_3/incep/2_0" | |
| top: "conv5_3/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3/incep/2_0" | |
| top: "conv5_3/incep/2_0" | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv5_3/incep/2_0" | |
| top: "conv5_3/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/incep/2_1" | |
| top: "conv5_3/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_3/incep/2_1" | |
| top: "conv5_3/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv5_3/incep/2_1" | |
| top: "conv5_3/incep/2_1" | |
| } | |
| layer { | |
| name: "conv5_3/incep" | |
| type: "Concat" | |
| bottom: "conv5_3/incep/0" | |
| bottom: "conv5_3/incep/1_0" | |
| bottom: "conv5_3/incep/2_1" | |
| top: "conv5_3/incep" | |
| } | |
| layer { | |
| name: "conv5_3/out/conv" | |
| type: "Convolution" | |
| bottom: "conv5_3/incep" | |
| top: "conv5_3/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_3/out" | |
| top: "conv5_3/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_3/out" | |
| top: "conv5_3/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_3/input" | |
| type: "Power" | |
| bottom: "conv5_2" | |
| top: "conv5_3/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv5_3" | |
| type: "Eltwise" | |
| bottom: "conv5_3/out" | |
| bottom: "conv5_3/input" | |
| top: "conv5_3" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_3" | |
| top: "conv5_4/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_4/incep/0" | |
| top: "conv5_4/incep/0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_4/incep/0" | |
| top: "conv5_4/incep/0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_4/incep/0" | |
| top: "conv5_4/incep/0" | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv5_3" | |
| top: "conv5_4/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 96 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_4/incep/1_reduce" | |
| top: "conv5_4/incep/1_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_4/incep/1_reduce" | |
| top: "conv5_4/incep/1_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_4/incep/1_reduce" | |
| top: "conv5_4/incep/1_reduce" | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_4/incep/1_reduce" | |
| top: "conv5_4/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 192 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_4/incep/1_0" | |
| top: "conv5_4/incep/1_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_4/incep/1_0" | |
| top: "conv5_4/incep/1_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/1_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_4/incep/1_0" | |
| top: "conv5_4/incep/1_0" | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_reduce/conv" | |
| type: "Convolution" | |
| bottom: "conv5_3" | |
| top: "conv5_4/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 32 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_reduce/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_4/incep/2_reduce" | |
| top: "conv5_4/incep/2_reduce" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_reduce/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_4/incep/2_reduce" | |
| top: "conv5_4/incep/2_reduce" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_reduce/relu" | |
| type: "ReLU" | |
| bottom: "conv5_4/incep/2_reduce" | |
| top: "conv5_4/incep/2_reduce" | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_0/conv" | |
| type: "Convolution" | |
| bottom: "conv5_4/incep/2_reduce" | |
| top: "conv5_4/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_0/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_4/incep/2_0" | |
| top: "conv5_4/incep/2_0" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_0/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_4/incep/2_0" | |
| top: "conv5_4/incep/2_0" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_0/relu" | |
| type: "ReLU" | |
| bottom: "conv5_4/incep/2_0" | |
| top: "conv5_4/incep/2_0" | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_1/conv" | |
| type: "Convolution" | |
| bottom: "conv5_4/incep/2_0" | |
| top: "conv5_4/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 64 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 1 | |
| pad_w: 1 | |
| kernel_h: 3 | |
| kernel_w: 3 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_1/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_4/incep/2_1" | |
| top: "conv5_4/incep/2_1" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_1/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_4/incep/2_1" | |
| top: "conv5_4/incep/2_1" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/incep/2_1/relu" | |
| type: "ReLU" | |
| bottom: "conv5_4/incep/2_1" | |
| top: "conv5_4/incep/2_1" | |
| } | |
| layer { | |
| name: "conv5_4/incep" | |
| type: "Concat" | |
| bottom: "conv5_4/incep/0" | |
| bottom: "conv5_4/incep/1_0" | |
| bottom: "conv5_4/incep/2_1" | |
| top: "conv5_4/incep" | |
| } | |
| layer { | |
| name: "conv5_4/out/conv" | |
| type: "Convolution" | |
| bottom: "conv5_4/incep" | |
| top: "conv5_4/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0.1 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| bias_term: false | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| pad_h: 0 | |
| pad_w: 0 | |
| kernel_h: 1 | |
| kernel_w: 1 | |
| stride_h: 1 | |
| stride_w: 1 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/out/bn" | |
| type: "BatchNorm" | |
| bottom: "conv5_4/out" | |
| top: "conv5_4/out" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/out/bn_scale" | |
| type: "Scale" | |
| bottom: "conv5_4/out" | |
| top: "conv5_4/out" | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0.1 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "conv5_4/input" | |
| type: "Power" | |
| bottom: "conv5_3" | |
| top: "conv5_4/input" | |
| power_param { | |
| power: 1 | |
| scale: 1 | |
| shift: 0 | |
| } | |
| } | |
| layer { | |
| name: "conv5_4" | |
| type: "Eltwise" | |
| bottom: "conv5_4/out" | |
| bottom: "conv5_4/input" | |
| top: "conv5_4" | |
| eltwise_param { | |
| operation: SUM | |
| coeff: 1 | |
| coeff: 1 | |
| } | |
| } | |
| ### hyper feature ### | |
| layer { | |
| name: "downsample" | |
| type: "Pooling" | |
| bottom: "conv3_4" | |
| top: "downsample" | |
| pooling_param { | |
| kernel_size: 3 | |
| stride: 2 | |
| pad: 0 | |
| pool: MAX | |
| } | |
| } | |
| layer { | |
| name: "upsample" | |
| type: "Deconvolution" | |
| bottom: "conv5_4" | |
| top: "upsample" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| kernel_size: 4 | |
| pad: 1 | |
| stride: 2 | |
| group: 384 | |
| bias_term: false | |
| weight_filler: { | |
| type: "bilinear" | |
| } | |
| } | |
| } | |
| layer { | |
| name: "concat" | |
| bottom: "downsample" | |
| bottom: "conv4_4" | |
| bottom: "upsample" | |
| top: "concat" | |
| type: "Concat" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| layer { | |
| name: "convf_rpn" | |
| type: "Convolution" | |
| bottom: "concat" | |
| top: "convf_rpn" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reluf_rpn" | |
| type: "ReLU" | |
| bottom: "convf_rpn" | |
| top: "convf_rpn" | |
| } | |
| layer { | |
| name: "convf_2" | |
| type: "Convolution" | |
| bottom: "concat" | |
| top: "convf_2" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0 | |
| } | |
| convolution_param { | |
| num_output: 384 | |
| kernel_size: 1 | |
| pad: 0 | |
| stride: 1 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "reluf_2" | |
| type: "ReLU" | |
| bottom: "convf_2" | |
| top: "convf_2" | |
| } | |
| layer { | |
| name: "concat_convf" | |
| bottom: "convf_rpn" | |
| bottom: "convf_2" | |
| top: "convf" | |
| type: "Concat" | |
| concat_param { | |
| axis: 1 | |
| } | |
| } | |
| ################################################################################ | |
| ## RPN | |
| ################################################################################ | |
| ### RPN conv ### | |
| layer { | |
| name: "rpn_conv1" | |
| type: "Convolution" | |
| bottom: "convf_rpn" | |
| top: "rpn_conv1" | |
| param { lr_mult: 1.0 decay_mult: 1.0 } | |
| param { lr_mult: 2.0 decay_mult: 0 } | |
| convolution_param { | |
| num_output: 384 kernel_size: 3 pad: 1 stride: 1 | |
| weight_filler { type: "gaussian" std: 0.01 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| name: "rpn_relu1" | |
| type: "ReLU" | |
| bottom: "rpn_conv1" | |
| top: "rpn_conv1" | |
| } | |
| layer { | |
| name: "rpn_cls_score" | |
| type: "Convolution" | |
| bottom: "rpn_conv1" | |
| top: "rpn_cls_score" | |
| param { lr_mult: 1.0 decay_mult: 1.0 } | |
| param { lr_mult: 2.0 decay_mult: 0 } | |
| convolution_param { | |
| num_output: 50 # 2(bg/fg) * 25(anchors) | |
| kernel_size: 1 pad: 0 stride: 1 | |
| weight_filler { type: "gaussian" std: 0.01 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| name: "rpn_bbox_pred" | |
| type: "Convolution" | |
| bottom: "rpn_conv1" | |
| top: "rpn_bbox_pred" | |
| param { lr_mult: 1.0 decay_mult: 1.0 } | |
| param { lr_mult: 2.0 decay_mult: 0 } | |
| convolution_param { | |
| num_output: 100 # 4 * 25(anchors) | |
| kernel_size: 1 pad: 0 stride: 1 | |
| weight_filler { type: "gaussian" std: 0.01 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| bottom: "rpn_cls_score" | |
| top: "rpn_cls_score_reshape" | |
| name: "rpn_cls_score_reshape" | |
| type: "Reshape" | |
| reshape_param { shape { dim: 0 dim: 2 dim: -1 dim: 0 } } | |
| } | |
| ################################################################################ | |
| ## Proposal | |
| ################################################################################ | |
| layer { | |
| name: "rpn_cls_prob" | |
| type: "Softmax" | |
| bottom: "rpn_cls_score_reshape" | |
| top: "rpn_cls_prob" | |
| } | |
| layer { | |
| name: 'rpn_cls_prob_reshape' | |
| type: 'Reshape' | |
| bottom: 'rpn_cls_prob' | |
| top: 'rpn_cls_prob_reshape' | |
| reshape_param { shape { dim: 0 dim: 50 dim: -1 dim: 0 } } | |
| } | |
| layer { | |
| name: 'proposal' | |
| type: 'Proposal' | |
| bottom: 'rpn_cls_prob_reshape' | |
| bottom: 'rpn_bbox_pred' | |
| bottom: 'im_info' | |
| top: 'rois' | |
| top: 'scores' | |
| proposal_param { | |
| ratio: 0.5 ratio: 0.667 ratio: 1.0 ratio: 1.5 ratio: 2.0 | |
| scale: 3 scale: 6 scale: 9 scale: 16 scale: 32 | |
| base_size: 16 | |
| feat_stride: 16 | |
| pre_nms_topn: 12000 | |
| post_nms_topn: 200 | |
| nms_thresh: 0.7 | |
| min_size: 16 | |
| } | |
| } | |
| ################################################################################ | |
| ## RCNN | |
| ################################################################################ | |
| layer { | |
| name: "roi_pool_conv5" | |
| type: "ROIPooling" | |
| bottom: "convf" | |
| bottom: "rois" | |
| top: "roi_pool_conv5" | |
| roi_pooling_param { | |
| pooled_w: 6 | |
| pooled_h: 6 | |
| spatial_scale: 0.0625 # 1/16 | |
| } | |
| } | |
| layer { | |
| name: "fc6" | |
| type: "InnerProduct" | |
| bottom: "roi_pool_conv5" | |
| top: "fc6" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 4096 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc6/bn" | |
| type: "BatchNorm" | |
| bottom: "fc6" | |
| top: "fc6" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "fc6/scale" | |
| type: "Scale" | |
| bottom: "fc6" | |
| top: "fc6" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "fc6/dropout" | |
| type: "Dropout" | |
| bottom: "fc6" | |
| top: "fc6" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "fc6/relu" | |
| type: "ReLU" | |
| bottom: "fc6" | |
| top: "fc6" | |
| } | |
| layer { | |
| name: "fc7" | |
| type: "InnerProduct" | |
| bottom: "fc6" | |
| top: "fc7" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 1.0 | |
| } | |
| param { | |
| lr_mult: 2.0 | |
| decay_mult: 0.0 | |
| } | |
| inner_product_param { | |
| num_output: 4096 | |
| weight_filler { | |
| type: "xavier" | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0.1 | |
| } | |
| } | |
| } | |
| layer { | |
| name: "fc7/bn" | |
| type: "BatchNorm" | |
| bottom: "fc7" | |
| top: "fc7" | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 0 | |
| decay_mult: 0 | |
| } | |
| batch_norm_param { | |
| use_global_stats: true | |
| } | |
| } | |
| layer { | |
| name: "fc7/scale" | |
| type: "Scale" | |
| bottom: "fc7" | |
| top: "fc7" | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0 | |
| } | |
| param { | |
| lr_mult: 1.0 | |
| decay_mult: 0 | |
| } | |
| scale_param { | |
| bias_term: true | |
| } | |
| } | |
| layer { | |
| name: "fc7/dropout" | |
| type: "Dropout" | |
| bottom: "fc7" | |
| top: "fc7" | |
| dropout_param { | |
| dropout_ratio: 0.5 | |
| } | |
| } | |
| layer { | |
| name: "fc7/relu" | |
| type: "ReLU" | |
| bottom: "fc7" | |
| top: "fc7" | |
| } | |
| layer { | |
| name: "cls_score" | |
| type: "InnerProduct" | |
| bottom: "fc7" | |
| top: "cls_score" | |
| param { lr_mult: 1.0 decay_mult: 1.0 } | |
| param { lr_mult: 2.0 decay_mult: 0 } | |
| inner_product_param { | |
| num_output: 21 | |
| weight_filler { type: "gaussian" std: 0.01 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| name: "bbox_pred" | |
| type: "InnerProduct" | |
| bottom: "fc7" | |
| top: "bbox_pred" | |
| param { lr_mult: 1.0 decay_mult: 1.0 } | |
| param { lr_mult: 2.0 decay_mult: 0 } | |
| inner_product_param { | |
| num_output: 84 | |
| weight_filler { type: "gaussian" std: 0.001 } | |
| bias_filler { type: "constant" value: 0 } | |
| } | |
| } | |
| layer { | |
| name: "cls_prob" | |
| type: "Softmax" | |
| bottom: "cls_score" | |
| top: "cls_prob" | |
| } |
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