Forked from victorhcm/VGG_FACE_deploy_updated.prototxt
Created
October 4, 2016 09:05
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Updated VGG_FACE prototxt
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name: "VGG_FACE_16_layer" | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 224 | |
input_dim: 224 | |
layer { | |
name: "data" | |
type: "Data" | |
top: "data" | |
top: "label" | |
} | |
layer { | |
bottom: "data" | |
top: "conv1_1" | |
name: "conv1_1" | |
type: "Convolution" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv1_1" | |
top: "conv1_1" | |
name: "relu1_1" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv1_1" | |
top: "conv1_2" | |
name: "conv1_2" | |
type: "Convolution" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv1_2" | |
top: "conv1_2" | |
name: "relu1_2" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv1_2" | |
top: "pool1" | |
name: "pool1" | |
type: "Pooling" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
bottom: "pool1" | |
top: "conv2_1" | |
name: "conv2_1" | |
type: "Convolution" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv2_1" | |
top: "conv2_1" | |
name: "relu2_1" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv2_1" | |
top: "conv2_2" | |
name: "conv2_2" | |
type: "Convolution" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv2_2" | |
top: "conv2_2" | |
name: "relu2_2" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv2_2" | |
top: "pool2" | |
name: "pool2" | |
type: "Pooling" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
bottom: "pool2" | |
top: "conv3_1" | |
name: "conv3_1" | |
type: "Convolution" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv3_1" | |
top: "conv3_1" | |
name: "relu3_1" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv3_1" | |
top: "conv3_2" | |
name: "conv3_2" | |
type: "Convolution" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv3_2" | |
top: "conv3_2" | |
name: "relu3_2" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv3_2" | |
top: "conv3_3" | |
name: "conv3_3" | |
type: "Convolution" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv3_3" | |
top: "conv3_3" | |
name: "relu3_3" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv3_3" | |
top: "pool3" | |
name: "pool3" | |
type: "Pooling" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
bottom: "pool3" | |
top: "conv4_1" | |
name: "conv4_1" | |
type: "Convolution" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv4_1" | |
top: "conv4_1" | |
name: "relu4_1" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv4_1" | |
top: "conv4_2" | |
name: "conv4_2" | |
type: "Convolution" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv4_2" | |
top: "conv4_2" | |
name: "relu4_2" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv4_2" | |
top: "conv4_3" | |
name: "conv4_3" | |
type: "Convolution" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv4_3" | |
top: "conv4_3" | |
name: "relu4_3" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv4_3" | |
top: "pool4" | |
name: "pool4" | |
type: "Pooling" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
bottom: "pool4" | |
top: "conv5_1" | |
name: "conv5_1" | |
type: "Convolution" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv5_1" | |
top: "conv5_1" | |
name: "relu5_1" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv5_1" | |
top: "conv5_2" | |
name: "conv5_2" | |
type: "Convolution" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv5_2" | |
top: "conv5_2" | |
name: "relu5_2" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv5_2" | |
top: "conv5_3" | |
name: "conv5_3" | |
type: "Convolution" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
} | |
} | |
layer { | |
bottom: "conv5_3" | |
top: "conv5_3" | |
name: "relu5_3" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "conv5_3" | |
top: "pool5" | |
name: "pool5" | |
type: "Pooling" | |
pooling_param { | |
pool: MAX | |
kernel_size: 2 | |
stride: 2 | |
} | |
} | |
layer { | |
bottom: "pool5" | |
top: "fc6" | |
name: "fc6" | |
type: "InnerProduct" | |
inner_product_param { | |
num_output: 4096 | |
} | |
} | |
layer { | |
bottom: "fc6" | |
top: "fc6" | |
name: "relu6" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "fc6" | |
top: "fc6" | |
name: "drop6" | |
type: "Dropout" | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
layer { | |
bottom: "fc6" | |
top: "fc7" | |
name: "fc7" | |
type: "InnerProduct" | |
inner_product_param { | |
num_output: 4096 | |
} | |
} | |
layer { | |
bottom: "fc7" | |
top: "fc7" | |
name: "relu7" | |
type: "ReLU" | |
} | |
layer { | |
bottom: "fc7" | |
top: "fc7" | |
name: "drop7" | |
type: "Dropout" | |
dropout_param { | |
dropout_ratio: 0.5 | |
} | |
} | |
layer { | |
bottom: "fc7" | |
top: "fc8" | |
name: "fc8" | |
type: "InnerProduct" | |
inner_product_param { | |
num_output: 2622 | |
} | |
} | |
layer { | |
bottom: "fc8" | |
top: "prob" | |
name: "prob" | |
type: "Softmax" | |
} |
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