name: "CaffeNet" layers { name: "data" type: WINDOW_DATA top: "data" top: "label" window_data_param { source: "window_file_caltech_train_10Hz_wneg2.txt" mean_file: "imagenet_mean.binaryproto" batch_size: 128 crop_size: 227 mirror: true fg_threshold: 0.5 bg_threshold: 0.5 fg_fraction: 0.25 context_pad: 16 crop_mode: "square" } } layers { name: "conv1" type: CONVOLUTION bottom: "data" top: "conv1" blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 96 kernel_size: 11 stride: 4 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0 } } } layers { name: "relu1" type: RELU bottom: "conv1" top: "conv1" } layers { name: "pool1" type: POOLING bottom: "conv1" top: "pool1" pooling_param { pool: MAX kernel_size: 3 stride: 2 } } layers { name: "norm1" type: LRN bottom: "pool1" top: "norm1" lrn_param { local_size: 5 alpha: 0.0001 beta: 0.75 } } layers { name: "conv2" type: CONVOLUTION bottom: "norm1" top: "conv2" blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 256 pad: 2 kernel_size: 5 group: 2 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 1 } } } layers { name: "relu2" type: RELU bottom: "conv2" top: "conv2" } layers { name: "pool2" type: POOLING bottom: "conv2" top: "pool2" pooling_param { pool: MAX kernel_size: 3 stride: 2 } } layers { name: "norm2" type: LRN bottom: "pool2" top: "norm2" lrn_param { local_size: 5 alpha: 0.0001 beta: 0.75 } } layers { name: "conv3" type: CONVOLUTION bottom: "norm2" top: "conv3" blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 384 pad: 1 kernel_size: 3 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0 } } } layers { name: "relu3" type: RELU bottom: "conv3" top: "conv3" } layers { name: "conv4" type: CONVOLUTION bottom: "conv3" top: "conv4" blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 384 pad: 1 kernel_size: 3 group: 2 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 1 } } } layers { name: "relu4" type: RELU bottom: "conv4" top: "conv4" } layers { name: "conv5" type: CONVOLUTION bottom: "conv4" top: "conv5" blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 convolution_param { num_output: 256 pad: 1 kernel_size: 3 group: 2 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 1 } } } layers { name: "relu5" type: RELU bottom: "conv5" top: "conv5" } layers { name: "pool5" type: POOLING bottom: "conv5" top: "pool5" pooling_param { pool: MAX kernel_size: 3 stride: 2 } } layers { name: "fc6" type: INNER_PRODUCT bottom: "pool5" top: "fc6" blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 inner_product_param { num_output: 4096 weight_filler { type: "gaussian" std: 0.005 } bias_filler { type: "constant" value: 1 } } } layers { name: "relu6" type: RELU bottom: "fc6" top: "fc6" } layers { name: "drop6" type: DROPOUT bottom: "fc6" top: "fc6" dropout_param { dropout_ratio: 0.5 } } layers { name: "fc7" type: INNER_PRODUCT bottom: "fc6" top: "fc7" blobs_lr: 1 blobs_lr: 2 weight_decay: 1 weight_decay: 0 inner_product_param { num_output: 4096 weight_filler { type: "gaussian" std: 0.005 } bias_filler { type: "constant" value: 1 } } } layers { name: "relu7" type: RELU bottom: "fc7" top: "fc7" } layers { name: "drop7" type: DROPOUT bottom: "fc7" top: "fc7" dropout_param { dropout_ratio: 0.5 } } layers { name: "fc8_inria" type: INNER_PRODUCT bottom: "fc7" top: "fc8_inria" blobs_lr: 10 blobs_lr: 20 weight_decay: 1 weight_decay: 0 inner_product_param { num_output: 2 weight_filler { type: "gaussian" std: 0.01 } bias_filler { type: "constant" value: 0 } } } layers { name: "loss" type: SOFTMAX_LOSS bottom: "fc8_inria" bottom: "label" }