name: "VGG_FACE_16_layers" input: "data" input_dim: 1 input_dim: 3 input_dim: 224 input_dim: 224 layers { bottom: "data" top: "conv1_1" name: "conv1_1" type: CONVOLUTION convolution_param { num_output: 64 pad: 1 kernel_size: 3 } } layers { bottom: "conv1_1" top: "conv1_1" name: "relu1_1" type: RELU } layers { bottom: "conv1_1" top: "conv1_2" name: "conv1_2" type: CONVOLUTION convolution_param { num_output: 64 pad: 1 kernel_size: 3 } } layers { bottom: "conv1_2" top: "conv1_2" name: "relu1_2" type: RELU } layers { bottom: "conv1_2" top: "pool1" name: "pool1" type: POOLING pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layers { bottom: "pool1" top: "conv2_1" name: "conv2_1" type: CONVOLUTION convolution_param { num_output: 128 pad: 1 kernel_size: 3 } } layers { bottom: "conv2_1" top: "conv2_1" name: "relu2_1" type: RELU } layers { bottom: "conv2_1" top: "conv2_2" name: "conv2_2" type: CONVOLUTION convolution_param { num_output: 128 pad: 1 kernel_size: 3 } } layers { bottom: "conv2_2" top: "conv2_2" name: "relu2_2" type: RELU } layers { bottom: "conv2_2" top: "pool2" name: "pool2" type: POOLING pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layers { bottom: "pool2" top: "conv3_1" name: "conv3_1" type: CONVOLUTION convolution_param { num_output: 256 pad: 1 kernel_size: 3 } } layers { bottom: "conv3_1" top: "conv3_1" name: "relu3_1" type: RELU } layers { bottom: "conv3_1" top: "conv3_2" name: "conv3_2" type: CONVOLUTION convolution_param { num_output: 256 pad: 1 kernel_size: 3 } } layers { bottom: "conv3_2" top: "conv3_2" name: "relu3_2" type: RELU } layers { bottom: "conv3_2" top: "conv3_3" name: "conv3_3" type: CONVOLUTION convolution_param { num_output: 256 pad: 1 kernel_size: 3 } } layers { bottom: "conv3_3" top: "conv3_3" name: "relu3_3" type: RELU } layers { bottom: "conv3_3" top: "pool3" name: "pool3" type: POOLING pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layers { bottom: "pool3" top: "conv4_1" name: "conv4_1" type: CONVOLUTION convolution_param { num_output: 512 pad: 1 kernel_size: 3 } } layers { bottom: "conv4_1" top: "conv4_1" name: "relu4_1" type: RELU } layers { bottom: "conv4_1" top: "conv4_2" name: "conv4_2" type: CONVOLUTION convolution_param { num_output: 512 pad: 1 kernel_size: 3 } } layers { bottom: "conv4_2" top: "conv4_2" name: "relu4_2" type: RELU } layers { bottom: "conv4_2" top: "conv4_3" name: "conv4_3" type: CONVOLUTION convolution_param { num_output: 512 pad: 1 kernel_size: 3 } } layers { bottom: "conv4_3" top: "conv4_3" name: "relu4_3" type: RELU } layers { bottom: "conv4_3" top: "pool4" name: "pool4" type: POOLING pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layers { bottom: "pool4" top: "conv5_1" name: "conv5_1" type: CONVOLUTION convolution_param { num_output: 512 pad: 1 kernel_size: 3 } } layers { bottom: "conv5_1" top: "conv5_1" name: "relu5_1" type: RELU } layers { bottom: "conv5_1" top: "conv5_2" name: "conv5_2" type: CONVOLUTION convolution_param { num_output: 512 pad: 1 kernel_size: 3 } } layers { bottom: "conv5_2" top: "conv5_2" name: "relu5_2" type: RELU } layers { bottom: "conv5_2" top: "conv5_3" name: "conv5_3" type: CONVOLUTION convolution_param { num_output: 512 pad: 1 kernel_size: 3 } } layers { bottom: "conv5_3" top: "conv5_3" name: "relu5_3" type: RELU } layers { bottom: "conv5_3" top: "pool5" name: "pool5" type: POOLING pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layers { bottom: "pool5" top: "fc6" name: "fc6" type: INNER_PRODUCT inner_product_param { num_output: 4096 } } layers { bottom: "fc6" top: "fc6" name: "relu6" type: RELU } layers { bottom: "fc6" top: "fc6" name: "drop6" type: DROPOUT dropout_param { dropout_ratio: 0.5 } } layers { bottom: "fc6" top: "fc7" name: "fc7" type: INNER_PRODUCT inner_product_param { num_output: 4096 } }