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| name: "CaffeNet" | |
| input: "data" | |
| input_dim: 1 | |
| input_dim: 3 | |
| input_dim: 227 | |
| input_dim: 227 | |
| layers { | |
| name: "conv1" | |
| type: CONVOLUTION | |
| bottom: "data" | |
| top: "conv1" | |
| convolution_param { | |
| num_output: 96 | |
| kernel_size: 7 | |
| stride: 4 | |
| } | |
| } | |
| 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" | |
| convolution_param { | |
| num_output: 256 | |
| pad: 2 | |
| kernel_size: 5 | |
| } | |
| } | |
| 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" | |
| convolution_param { | |
| num_output: 384 | |
| pad: 1 | |
| kernel_size: 3 | |
| } | |
| } | |
| layers{ | |
| name: "relu3" | |
| type: RELU | |
| bottom: "conv3" | |
| top: "conv3" | |
| } | |
| layers { | |
| name: "pool5" | |
| type: POOLING | |
| bottom: "conv3" | |
| top: "pool5" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 3 | |
| stride: 2 | |
| } | |
| } | |
| layers { | |
| name: "fc6" | |
| type: INNER_PRODUCT | |
| bottom: "pool5" | |
| top: "fc6" | |
| inner_product_param { | |
| num_output: 512 | |
| } | |
| } | |
| 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" | |
| inner_product_param { | |
| num_output: 512 | |
| } | |
| } | |
| 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" | |
| type: INNER_PRODUCT | |
| bottom: "fc7" | |
| top: "fc8" | |
| inner_product_param { | |
| num_output: 8 | |
| } | |
| } | |
| layers { | |
| name: "prob" | |
| type: SOFTMAX | |
| bottom: "fc8" | |
| top: "prob" | |
| } | |