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Open Source Computer Vision Library
https://opencv.org/
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1790 lines
28 KiB
1790 lines
28 KiB
# This file is based on deploy.prototxt but might be used for input resolution less than 300x300 |
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input: "data" |
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input_shape { |
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dim: 1 |
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dim: 3 |
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dim: 300 |
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dim: 300 |
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} |
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|
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layer { |
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name: "data_bn" |
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type: "BatchNorm" |
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bottom: "data" |
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top: "data_bn" |
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param { |
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lr_mult: 0.0 |
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} |
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param { |
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lr_mult: 0.0 |
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} |
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param { |
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lr_mult: 0.0 |
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} |
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} |
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layer { |
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name: "data_scale" |
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type: "Scale" |
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bottom: "data_bn" |
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top: "data_bn" |
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param { |
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lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
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param { |
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lr_mult: 2.0 |
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decay_mult: 1.0 |
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} |
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scale_param { |
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bias_term: true |
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} |
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} |
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layer { |
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name: "conv1_h" |
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type: "Convolution" |
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bottom: "data_bn" |
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top: "conv1_h" |
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param { |
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lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
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param { |
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lr_mult: 2.0 |
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decay_mult: 1.0 |
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} |
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convolution_param { |
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num_output: 32 |
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pad: 3 |
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kernel_size: 7 |
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stride: 2 |
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weight_filler { |
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type: "msra" |
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variance_norm: FAN_OUT |
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} |
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bias_filler { |
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type: "constant" |
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value: 0.0 |
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} |
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} |
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} |
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layer { |
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name: "conv1_bn_h" |
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type: "BatchNorm" |
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bottom: "conv1_h" |
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top: "conv1_h" |
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param { |
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lr_mult: 0.0 |
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} |
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param { |
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lr_mult: 0.0 |
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} |
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param { |
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lr_mult: 0.0 |
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} |
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} |
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layer { |
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name: "conv1_scale_h" |
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type: "Scale" |
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bottom: "conv1_h" |
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top: "conv1_h" |
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param { |
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lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
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param { |
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lr_mult: 2.0 |
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decay_mult: 1.0 |
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} |
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scale_param { |
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bias_term: true |
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} |
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} |
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layer { |
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name: "conv1_relu" |
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type: "ReLU" |
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bottom: "conv1_h" |
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top: "conv1_h" |
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} |
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layer { |
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name: "conv1_pool" |
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type: "Pooling" |
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bottom: "conv1_h" |
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top: "conv1_pool" |
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pooling_param { |
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kernel_size: 3 |
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stride: 2 |
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} |
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} |
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layer { |
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name: "layer_64_1_conv1_h" |
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type: "Convolution" |
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bottom: "conv1_pool" |
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top: "layer_64_1_conv1_h" |
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param { |
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lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
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convolution_param { |
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num_output: 32 |
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bias_term: false |
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pad: 1 |
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kernel_size: 3 |
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stride: 1 |
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weight_filler { |
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type: "msra" |
|
} |
|
bias_filler { |
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type: "constant" |
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value: 0.0 |
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} |
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} |
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} |
|
layer { |
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name: "layer_64_1_bn2_h" |
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type: "BatchNorm" |
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bottom: "layer_64_1_conv1_h" |
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top: "layer_64_1_conv1_h" |
|
param { |
|
lr_mult: 0.0 |
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} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
} |
|
layer { |
|
name: "layer_64_1_scale2_h" |
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type: "Scale" |
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bottom: "layer_64_1_conv1_h" |
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top: "layer_64_1_conv1_h" |
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param { |
|
lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
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param { |
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lr_mult: 2.0 |
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decay_mult: 1.0 |
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} |
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scale_param { |
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bias_term: true |
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} |
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} |
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layer { |
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name: "layer_64_1_relu2" |
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type: "ReLU" |
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bottom: "layer_64_1_conv1_h" |
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top: "layer_64_1_conv1_h" |
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} |
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layer { |
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name: "layer_64_1_conv2_h" |
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type: "Convolution" |
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bottom: "layer_64_1_conv1_h" |
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top: "layer_64_1_conv2_h" |
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param { |
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lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
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convolution_param { |
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num_output: 32 |
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bias_term: false |
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pad: 1 |
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kernel_size: 3 |
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stride: 1 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
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type: "constant" |
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value: 0.0 |
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} |
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} |
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} |
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layer { |
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name: "layer_64_1_sum" |
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type: "Eltwise" |
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bottom: "layer_64_1_conv2_h" |
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bottom: "conv1_pool" |
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top: "layer_64_1_sum" |
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} |
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layer { |
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name: "layer_128_1_bn1_h" |
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type: "BatchNorm" |
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bottom: "layer_64_1_sum" |
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top: "layer_128_1_bn1_h" |
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param { |
|
lr_mult: 0.0 |
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} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
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} |
|
} |
|
layer { |
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name: "layer_128_1_scale1_h" |
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type: "Scale" |
|
bottom: "layer_128_1_bn1_h" |
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top: "layer_128_1_bn1_h" |
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param { |
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lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
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param { |
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lr_mult: 2.0 |
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decay_mult: 1.0 |
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} |
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scale_param { |
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bias_term: true |
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} |
|
} |
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layer { |
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name: "layer_128_1_relu1" |
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type: "ReLU" |
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bottom: "layer_128_1_bn1_h" |
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top: "layer_128_1_bn1_h" |
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} |
|
layer { |
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name: "layer_128_1_conv1_h" |
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type: "Convolution" |
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bottom: "layer_128_1_bn1_h" |
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top: "layer_128_1_conv1_h" |
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param { |
|
lr_mult: 1.0 |
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decay_mult: 1.0 |
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} |
|
convolution_param { |
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num_output: 128 |
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bias_term: false |
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pad: 1 |
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kernel_size: 3 |
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stride: 2 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
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type: "constant" |
|
value: 0.0 |
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} |
|
} |
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} |
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layer { |
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name: "layer_128_1_bn2" |
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type: "BatchNorm" |
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bottom: "layer_128_1_conv1_h" |
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top: "layer_128_1_conv1_h" |
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param { |
|
lr_mult: 0.0 |
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} |
|
param { |
|
lr_mult: 0.0 |
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} |
|
param { |
|
lr_mult: 0.0 |
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} |
|
} |
|
layer { |
|
name: "layer_128_1_scale2" |
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type: "Scale" |
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bottom: "layer_128_1_conv1_h" |
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top: "layer_128_1_conv1_h" |
|
param { |
|
lr_mult: 1.0 |
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decay_mult: 1.0 |
|
} |
|
param { |
|
lr_mult: 2.0 |
|
decay_mult: 1.0 |
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} |
|
scale_param { |
|
bias_term: true |
|
} |
|
} |
|
layer { |
|
name: "layer_128_1_relu2" |
|
type: "ReLU" |
|
bottom: "layer_128_1_conv1_h" |
|
top: "layer_128_1_conv1_h" |
|
} |
|
layer { |
|
name: "layer_128_1_conv2" |
|
type: "Convolution" |
|
bottom: "layer_128_1_conv1_h" |
|
top: "layer_128_1_conv2" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 128 |
|
bias_term: false |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_128_1_conv_expand_h" |
|
type: "Convolution" |
|
bottom: "layer_128_1_bn1_h" |
|
top: "layer_128_1_conv_expand_h" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 128 |
|
bias_term: false |
|
pad: 0 |
|
kernel_size: 1 |
|
stride: 2 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_128_1_sum" |
|
type: "Eltwise" |
|
bottom: "layer_128_1_conv2" |
|
bottom: "layer_128_1_conv_expand_h" |
|
top: "layer_128_1_sum" |
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} |
|
layer { |
|
name: "layer_256_1_bn1" |
|
type: "BatchNorm" |
|
bottom: "layer_128_1_sum" |
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top: "layer_256_1_bn1" |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
} |
|
layer { |
|
name: "layer_256_1_scale1" |
|
type: "Scale" |
|
bottom: "layer_256_1_bn1" |
|
top: "layer_256_1_bn1" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
param { |
|
lr_mult: 2.0 |
|
decay_mult: 1.0 |
|
} |
|
scale_param { |
|
bias_term: true |
|
} |
|
} |
|
layer { |
|
name: "layer_256_1_relu1" |
|
type: "ReLU" |
|
bottom: "layer_256_1_bn1" |
|
top: "layer_256_1_bn1" |
|
} |
|
layer { |
|
name: "layer_256_1_conv1" |
|
type: "Convolution" |
|
bottom: "layer_256_1_bn1" |
|
top: "layer_256_1_conv1" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 256 |
|
bias_term: false |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 2 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_256_1_bn2" |
|
type: "BatchNorm" |
|
bottom: "layer_256_1_conv1" |
|
top: "layer_256_1_conv1" |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
} |
|
layer { |
|
name: "layer_256_1_scale2" |
|
type: "Scale" |
|
bottom: "layer_256_1_conv1" |
|
top: "layer_256_1_conv1" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
param { |
|
lr_mult: 2.0 |
|
decay_mult: 1.0 |
|
} |
|
scale_param { |
|
bias_term: true |
|
} |
|
} |
|
layer { |
|
name: "layer_256_1_relu2" |
|
type: "ReLU" |
|
bottom: "layer_256_1_conv1" |
|
top: "layer_256_1_conv1" |
|
} |
|
layer { |
|
name: "layer_256_1_conv2" |
|
type: "Convolution" |
|
bottom: "layer_256_1_conv1" |
|
top: "layer_256_1_conv2" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 256 |
|
bias_term: false |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_256_1_conv_expand" |
|
type: "Convolution" |
|
bottom: "layer_256_1_bn1" |
|
top: "layer_256_1_conv_expand" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 256 |
|
bias_term: false |
|
pad: 0 |
|
kernel_size: 1 |
|
stride: 2 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_256_1_sum" |
|
type: "Eltwise" |
|
bottom: "layer_256_1_conv2" |
|
bottom: "layer_256_1_conv_expand" |
|
top: "layer_256_1_sum" |
|
} |
|
layer { |
|
name: "layer_512_1_bn1" |
|
type: "BatchNorm" |
|
bottom: "layer_256_1_sum" |
|
top: "layer_512_1_bn1" |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
} |
|
layer { |
|
name: "layer_512_1_scale1" |
|
type: "Scale" |
|
bottom: "layer_512_1_bn1" |
|
top: "layer_512_1_bn1" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
param { |
|
lr_mult: 2.0 |
|
decay_mult: 1.0 |
|
} |
|
scale_param { |
|
bias_term: true |
|
} |
|
} |
|
layer { |
|
name: "layer_512_1_relu1" |
|
type: "ReLU" |
|
bottom: "layer_512_1_bn1" |
|
top: "layer_512_1_bn1" |
|
} |
|
layer { |
|
name: "layer_512_1_conv1_h" |
|
type: "Convolution" |
|
bottom: "layer_512_1_bn1" |
|
top: "layer_512_1_conv1_h" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 128 |
|
bias_term: false |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 # 2 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_512_1_bn2_h" |
|
type: "BatchNorm" |
|
bottom: "layer_512_1_conv1_h" |
|
top: "layer_512_1_conv1_h" |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
} |
|
layer { |
|
name: "layer_512_1_scale2_h" |
|
type: "Scale" |
|
bottom: "layer_512_1_conv1_h" |
|
top: "layer_512_1_conv1_h" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
param { |
|
lr_mult: 2.0 |
|
decay_mult: 1.0 |
|
} |
|
scale_param { |
|
bias_term: true |
|
} |
|
} |
|
layer { |
|
name: "layer_512_1_relu2" |
|
type: "ReLU" |
|
bottom: "layer_512_1_conv1_h" |
|
top: "layer_512_1_conv1_h" |
|
} |
|
layer { |
|
name: "layer_512_1_conv2_h" |
|
type: "Convolution" |
|
bottom: "layer_512_1_conv1_h" |
|
top: "layer_512_1_conv2_h" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 256 |
|
bias_term: false |
|
pad: 2 # 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
dilation: 2 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_512_1_conv_expand_h" |
|
type: "Convolution" |
|
bottom: "layer_512_1_bn1" |
|
top: "layer_512_1_conv_expand_h" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
convolution_param { |
|
num_output: 256 |
|
bias_term: false |
|
pad: 0 |
|
kernel_size: 1 |
|
stride: 1 # 2 |
|
weight_filler { |
|
type: "msra" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0.0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "layer_512_1_sum" |
|
type: "Eltwise" |
|
bottom: "layer_512_1_conv2_h" |
|
bottom: "layer_512_1_conv_expand_h" |
|
top: "layer_512_1_sum" |
|
} |
|
layer { |
|
name: "last_bn_h" |
|
type: "BatchNorm" |
|
bottom: "layer_512_1_sum" |
|
top: "layer_512_1_sum" |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
param { |
|
lr_mult: 0.0 |
|
} |
|
} |
|
layer { |
|
name: "last_scale_h" |
|
type: "Scale" |
|
bottom: "layer_512_1_sum" |
|
top: "layer_512_1_sum" |
|
param { |
|
lr_mult: 1.0 |
|
decay_mult: 1.0 |
|
} |
|
param { |
|
lr_mult: 2.0 |
|
decay_mult: 1.0 |
|
} |
|
scale_param { |
|
bias_term: true |
|
} |
|
} |
|
layer { |
|
name: "last_relu" |
|
type: "ReLU" |
|
bottom: "layer_512_1_sum" |
|
top: "fc7" |
|
} |
|
|
|
layer { |
|
name: "conv6_1_h" |
|
type: "Convolution" |
|
bottom: "fc7" |
|
top: "conv6_1_h" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 128 |
|
pad: 0 |
|
kernel_size: 1 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv6_1_relu" |
|
type: "ReLU" |
|
bottom: "conv6_1_h" |
|
top: "conv6_1_h" |
|
} |
|
layer { |
|
name: "conv6_2_h" |
|
type: "Convolution" |
|
bottom: "conv6_1_h" |
|
top: "conv6_2_h" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 256 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 2 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_relu" |
|
type: "ReLU" |
|
bottom: "conv6_2_h" |
|
top: "conv6_2_h" |
|
} |
|
layer { |
|
name: "conv7_1_h" |
|
type: "Convolution" |
|
bottom: "conv6_2_h" |
|
top: "conv7_1_h" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 64 |
|
pad: 0 |
|
kernel_size: 1 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv7_1_relu" |
|
type: "ReLU" |
|
bottom: "conv7_1_h" |
|
top: "conv7_1_h" |
|
} |
|
layer { |
|
name: "conv7_2_h" |
|
type: "Convolution" |
|
bottom: "conv7_1_h" |
|
top: "conv7_2_h" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 128 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 2 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_relu" |
|
type: "ReLU" |
|
bottom: "conv7_2_h" |
|
top: "conv7_2_h" |
|
} |
|
layer { |
|
name: "conv8_1_h" |
|
type: "Convolution" |
|
bottom: "conv7_2_h" |
|
top: "conv8_1_h" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 64 |
|
pad: 0 |
|
kernel_size: 1 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv8_1_relu" |
|
type: "ReLU" |
|
bottom: "conv8_1_h" |
|
top: "conv8_1_h" |
|
} |
|
layer { |
|
name: "conv8_2_h" |
|
type: "Convolution" |
|
bottom: "conv8_1_h" |
|
top: "conv8_2_h" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 128 |
|
pad: 0 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_relu" |
|
type: "ReLU" |
|
bottom: "conv8_2_h" |
|
top: "conv8_2_h" |
|
} |
|
# layer { |
|
# name: "conv9_1_h" |
|
# type: "Convolution" |
|
# bottom: "conv8_2_h" |
|
# top: "conv9_1_h" |
|
# param { |
|
# lr_mult: 1 |
|
# decay_mult: 1 |
|
# } |
|
# param { |
|
# lr_mult: 2 |
|
# decay_mult: 0 |
|
# } |
|
# convolution_param { |
|
# num_output: 64 |
|
# pad: 0 |
|
# kernel_size: 1 |
|
# stride: 1 |
|
# weight_filler { |
|
# type: "xavier" |
|
# } |
|
# bias_filler { |
|
# type: "constant" |
|
# value: 0 |
|
# } |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_1_relu" |
|
# type: "ReLU" |
|
# bottom: "conv9_1_h" |
|
# top: "conv9_1_h" |
|
# } |
|
# layer { |
|
# name: "conv9_2_h" |
|
# type: "Convolution" |
|
# bottom: "conv9_1_h" |
|
# top: "conv9_2_h" |
|
# param { |
|
# lr_mult: 1 |
|
# decay_mult: 1 |
|
# } |
|
# param { |
|
# lr_mult: 2 |
|
# decay_mult: 0 |
|
# } |
|
# convolution_param { |
|
# num_output: 128 |
|
# pad: 0 |
|
# kernel_size: 3 |
|
# stride: 1 |
|
# weight_filler { |
|
# type: "xavier" |
|
# } |
|
# bias_filler { |
|
# type: "constant" |
|
# value: 0 |
|
# } |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_2_relu" |
|
# type: "ReLU" |
|
# bottom: "conv9_2_h" |
|
# top: "conv9_2_h" |
|
# } |
|
layer { |
|
name: "conv4_3_norm" |
|
type: "Normalize" |
|
bottom: "layer_256_1_bn1" |
|
top: "conv4_3_norm" |
|
norm_param { |
|
across_spatial: false |
|
scale_filler { |
|
type: "constant" |
|
value: 20 |
|
} |
|
channel_shared: false |
|
} |
|
} |
|
layer { |
|
name: "conv4_3_norm_mbox_loc" |
|
type: "Convolution" |
|
bottom: "conv4_3_norm" |
|
top: "conv4_3_norm_mbox_loc" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 16 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv4_3_norm_mbox_loc_perm" |
|
type: "Permute" |
|
bottom: "conv4_3_norm_mbox_loc" |
|
top: "conv4_3_norm_mbox_loc_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv4_3_norm_mbox_loc_flat" |
|
type: "Flatten" |
|
bottom: "conv4_3_norm_mbox_loc_perm" |
|
top: "conv4_3_norm_mbox_loc_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv4_3_norm_mbox_conf" |
|
type: "Convolution" |
|
bottom: "conv4_3_norm" |
|
top: "conv4_3_norm_mbox_conf" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 8 # 84 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv4_3_norm_mbox_conf_perm" |
|
type: "Permute" |
|
bottom: "conv4_3_norm_mbox_conf" |
|
top: "conv4_3_norm_mbox_conf_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv4_3_norm_mbox_conf_flat" |
|
type: "Flatten" |
|
bottom: "conv4_3_norm_mbox_conf_perm" |
|
top: "conv4_3_norm_mbox_conf_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv4_3_norm_mbox_priorbox" |
|
type: "PriorBox" |
|
bottom: "conv4_3_norm" |
|
bottom: "data" |
|
top: "conv4_3_norm_mbox_priorbox" |
|
prior_box_param { |
|
min_size: 30.0 |
|
max_size: 60.0 |
|
aspect_ratio: 2 |
|
flip: true |
|
clip: false |
|
variance: 0.1 |
|
variance: 0.1 |
|
variance: 0.2 |
|
variance: 0.2 |
|
step: 8 |
|
offset: 0.5 |
|
} |
|
} |
|
layer { |
|
name: "fc7_mbox_loc" |
|
type: "Convolution" |
|
bottom: "fc7" |
|
top: "fc7_mbox_loc" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 24 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "fc7_mbox_loc_perm" |
|
type: "Permute" |
|
bottom: "fc7_mbox_loc" |
|
top: "fc7_mbox_loc_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "fc7_mbox_loc_flat" |
|
type: "Flatten" |
|
bottom: "fc7_mbox_loc_perm" |
|
top: "fc7_mbox_loc_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "fc7_mbox_conf" |
|
type: "Convolution" |
|
bottom: "fc7" |
|
top: "fc7_mbox_conf" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 12 # 126 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "fc7_mbox_conf_perm" |
|
type: "Permute" |
|
bottom: "fc7_mbox_conf" |
|
top: "fc7_mbox_conf_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "fc7_mbox_conf_flat" |
|
type: "Flatten" |
|
bottom: "fc7_mbox_conf_perm" |
|
top: "fc7_mbox_conf_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "fc7_mbox_priorbox" |
|
type: "PriorBox" |
|
bottom: "fc7" |
|
bottom: "data" |
|
top: "fc7_mbox_priorbox" |
|
prior_box_param { |
|
min_size: 60.0 |
|
max_size: 111.0 |
|
aspect_ratio: 2 |
|
aspect_ratio: 3 |
|
flip: true |
|
clip: false |
|
variance: 0.1 |
|
variance: 0.1 |
|
variance: 0.2 |
|
variance: 0.2 |
|
step: 16 |
|
offset: 0.5 |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_mbox_loc" |
|
type: "Convolution" |
|
bottom: "conv6_2_h" |
|
top: "conv6_2_mbox_loc" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 24 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_mbox_loc_perm" |
|
type: "Permute" |
|
bottom: "conv6_2_mbox_loc" |
|
top: "conv6_2_mbox_loc_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_mbox_loc_flat" |
|
type: "Flatten" |
|
bottom: "conv6_2_mbox_loc_perm" |
|
top: "conv6_2_mbox_loc_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_mbox_conf" |
|
type: "Convolution" |
|
bottom: "conv6_2_h" |
|
top: "conv6_2_mbox_conf" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 12 # 126 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_mbox_conf_perm" |
|
type: "Permute" |
|
bottom: "conv6_2_mbox_conf" |
|
top: "conv6_2_mbox_conf_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_mbox_conf_flat" |
|
type: "Flatten" |
|
bottom: "conv6_2_mbox_conf_perm" |
|
top: "conv6_2_mbox_conf_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv6_2_mbox_priorbox" |
|
type: "PriorBox" |
|
bottom: "conv6_2_h" |
|
bottom: "data" |
|
top: "conv6_2_mbox_priorbox" |
|
prior_box_param { |
|
min_size: 111.0 |
|
max_size: 162.0 |
|
aspect_ratio: 2 |
|
aspect_ratio: 3 |
|
flip: true |
|
clip: false |
|
variance: 0.1 |
|
variance: 0.1 |
|
variance: 0.2 |
|
variance: 0.2 |
|
step: 32 |
|
offset: 0.5 |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_mbox_loc" |
|
type: "Convolution" |
|
bottom: "conv7_2_h" |
|
top: "conv7_2_mbox_loc" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 24 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_mbox_loc_perm" |
|
type: "Permute" |
|
bottom: "conv7_2_mbox_loc" |
|
top: "conv7_2_mbox_loc_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_mbox_loc_flat" |
|
type: "Flatten" |
|
bottom: "conv7_2_mbox_loc_perm" |
|
top: "conv7_2_mbox_loc_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_mbox_conf" |
|
type: "Convolution" |
|
bottom: "conv7_2_h" |
|
top: "conv7_2_mbox_conf" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 12 # 126 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_mbox_conf_perm" |
|
type: "Permute" |
|
bottom: "conv7_2_mbox_conf" |
|
top: "conv7_2_mbox_conf_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_mbox_conf_flat" |
|
type: "Flatten" |
|
bottom: "conv7_2_mbox_conf_perm" |
|
top: "conv7_2_mbox_conf_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv7_2_mbox_priorbox" |
|
type: "PriorBox" |
|
bottom: "conv7_2_h" |
|
bottom: "data" |
|
top: "conv7_2_mbox_priorbox" |
|
prior_box_param { |
|
min_size: 162.0 |
|
max_size: 213.0 |
|
aspect_ratio: 2 |
|
aspect_ratio: 3 |
|
flip: true |
|
clip: false |
|
variance: 0.1 |
|
variance: 0.1 |
|
variance: 0.2 |
|
variance: 0.2 |
|
step: 64 |
|
offset: 0.5 |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_mbox_loc" |
|
type: "Convolution" |
|
bottom: "conv8_2_h" |
|
top: "conv8_2_mbox_loc" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 16 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_mbox_loc_perm" |
|
type: "Permute" |
|
bottom: "conv8_2_mbox_loc" |
|
top: "conv8_2_mbox_loc_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_mbox_loc_flat" |
|
type: "Flatten" |
|
bottom: "conv8_2_mbox_loc_perm" |
|
top: "conv8_2_mbox_loc_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_mbox_conf" |
|
type: "Convolution" |
|
bottom: "conv8_2_h" |
|
top: "conv8_2_mbox_conf" |
|
param { |
|
lr_mult: 1 |
|
decay_mult: 1 |
|
} |
|
param { |
|
lr_mult: 2 |
|
decay_mult: 0 |
|
} |
|
convolution_param { |
|
num_output: 8 # 84 |
|
pad: 1 |
|
kernel_size: 3 |
|
stride: 1 |
|
weight_filler { |
|
type: "xavier" |
|
} |
|
bias_filler { |
|
type: "constant" |
|
value: 0 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_mbox_conf_perm" |
|
type: "Permute" |
|
bottom: "conv8_2_mbox_conf" |
|
top: "conv8_2_mbox_conf_perm" |
|
permute_param { |
|
order: 0 |
|
order: 2 |
|
order: 3 |
|
order: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_mbox_conf_flat" |
|
type: "Flatten" |
|
bottom: "conv8_2_mbox_conf_perm" |
|
top: "conv8_2_mbox_conf_flat" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "conv8_2_mbox_priorbox" |
|
type: "PriorBox" |
|
bottom: "conv8_2_h" |
|
bottom: "data" |
|
top: "conv8_2_mbox_priorbox" |
|
prior_box_param { |
|
min_size: 213.0 |
|
max_size: 264.0 |
|
aspect_ratio: 2 |
|
flip: true |
|
clip: false |
|
variance: 0.1 |
|
variance: 0.1 |
|
variance: 0.2 |
|
variance: 0.2 |
|
step: 100 |
|
offset: 0.5 |
|
} |
|
} |
|
# layer { |
|
# name: "conv9_2_mbox_loc" |
|
# type: "Convolution" |
|
# bottom: "conv9_2_h" |
|
# top: "conv9_2_mbox_loc" |
|
# param { |
|
# lr_mult: 1 |
|
# decay_mult: 1 |
|
# } |
|
# param { |
|
# lr_mult: 2 |
|
# decay_mult: 0 |
|
# } |
|
# convolution_param { |
|
# num_output: 16 |
|
# pad: 1 |
|
# kernel_size: 3 |
|
# stride: 1 |
|
# weight_filler { |
|
# type: "xavier" |
|
# } |
|
# bias_filler { |
|
# type: "constant" |
|
# value: 0 |
|
# } |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_2_mbox_loc_perm" |
|
# type: "Permute" |
|
# bottom: "conv9_2_mbox_loc" |
|
# top: "conv9_2_mbox_loc_perm" |
|
# permute_param { |
|
# order: 0 |
|
# order: 2 |
|
# order: 3 |
|
# order: 1 |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_2_mbox_loc_flat" |
|
# type: "Flatten" |
|
# bottom: "conv9_2_mbox_loc_perm" |
|
# top: "conv9_2_mbox_loc_flat" |
|
# flatten_param { |
|
# axis: 1 |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_2_mbox_conf" |
|
# type: "Convolution" |
|
# bottom: "conv9_2_h" |
|
# top: "conv9_2_mbox_conf" |
|
# param { |
|
# lr_mult: 1 |
|
# decay_mult: 1 |
|
# } |
|
# param { |
|
# lr_mult: 2 |
|
# decay_mult: 0 |
|
# } |
|
# convolution_param { |
|
# num_output: 8 # 84 |
|
# pad: 1 |
|
# kernel_size: 3 |
|
# stride: 1 |
|
# weight_filler { |
|
# type: "xavier" |
|
# } |
|
# bias_filler { |
|
# type: "constant" |
|
# value: 0 |
|
# } |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_2_mbox_conf_perm" |
|
# type: "Permute" |
|
# bottom: "conv9_2_mbox_conf" |
|
# top: "conv9_2_mbox_conf_perm" |
|
# permute_param { |
|
# order: 0 |
|
# order: 2 |
|
# order: 3 |
|
# order: 1 |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_2_mbox_conf_flat" |
|
# type: "Flatten" |
|
# bottom: "conv9_2_mbox_conf_perm" |
|
# top: "conv9_2_mbox_conf_flat" |
|
# flatten_param { |
|
# axis: 1 |
|
# } |
|
# } |
|
# layer { |
|
# name: "conv9_2_mbox_priorbox" |
|
# type: "PriorBox" |
|
# bottom: "conv9_2_h" |
|
# bottom: "data" |
|
# top: "conv9_2_mbox_priorbox" |
|
# prior_box_param { |
|
# min_size: 264.0 |
|
# max_size: 315.0 |
|
# aspect_ratio: 2 |
|
# flip: true |
|
# clip: false |
|
# variance: 0.1 |
|
# variance: 0.1 |
|
# variance: 0.2 |
|
# variance: 0.2 |
|
# step: 300 |
|
# offset: 0.5 |
|
# } |
|
# } |
|
layer { |
|
name: "mbox_loc" |
|
type: "Concat" |
|
bottom: "conv4_3_norm_mbox_loc_flat" |
|
bottom: "fc7_mbox_loc_flat" |
|
bottom: "conv6_2_mbox_loc_flat" |
|
bottom: "conv7_2_mbox_loc_flat" |
|
bottom: "conv8_2_mbox_loc_flat" |
|
# bottom: "conv9_2_mbox_loc_flat" |
|
top: "mbox_loc" |
|
concat_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "mbox_conf" |
|
type: "Concat" |
|
bottom: "conv4_3_norm_mbox_conf_flat" |
|
bottom: "fc7_mbox_conf_flat" |
|
bottom: "conv6_2_mbox_conf_flat" |
|
bottom: "conv7_2_mbox_conf_flat" |
|
bottom: "conv8_2_mbox_conf_flat" |
|
# bottom: "conv9_2_mbox_conf_flat" |
|
top: "mbox_conf" |
|
concat_param { |
|
axis: 1 |
|
} |
|
} |
|
layer { |
|
name: "mbox_priorbox" |
|
type: "Concat" |
|
bottom: "conv4_3_norm_mbox_priorbox" |
|
bottom: "fc7_mbox_priorbox" |
|
bottom: "conv6_2_mbox_priorbox" |
|
bottom: "conv7_2_mbox_priorbox" |
|
bottom: "conv8_2_mbox_priorbox" |
|
# bottom: "conv9_2_mbox_priorbox" |
|
top: "mbox_priorbox" |
|
concat_param { |
|
axis: 2 |
|
} |
|
} |
|
|
|
layer { |
|
name: "mbox_conf_reshape" |
|
type: "Reshape" |
|
bottom: "mbox_conf" |
|
top: "mbox_conf_reshape" |
|
reshape_param { |
|
shape { |
|
dim: 0 |
|
dim: -1 |
|
dim: 2 |
|
} |
|
} |
|
} |
|
layer { |
|
name: "mbox_conf_softmax" |
|
type: "Softmax" |
|
bottom: "mbox_conf_reshape" |
|
top: "mbox_conf_softmax" |
|
softmax_param { |
|
axis: 2 |
|
} |
|
} |
|
layer { |
|
name: "mbox_conf_flatten" |
|
type: "Flatten" |
|
bottom: "mbox_conf_softmax" |
|
top: "mbox_conf_flatten" |
|
flatten_param { |
|
axis: 1 |
|
} |
|
} |
|
|
|
layer { |
|
name: "detection_out" |
|
type: "DetectionOutput" |
|
bottom: "mbox_loc" |
|
bottom: "mbox_conf_flatten" |
|
bottom: "mbox_priorbox" |
|
top: "detection_out" |
|
include { |
|
phase: TEST |
|
} |
|
detection_output_param { |
|
num_classes: 2 |
|
share_location: true |
|
background_label_id: 0 |
|
nms_param { |
|
nms_threshold: 0.45 |
|
top_k: 400 |
|
} |
|
code_type: CENTER_SIZE |
|
keep_top_k: 200 |
|
confidence_threshold: 0.01 |
|
} |
|
}
|
|
|