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| name: "CNN" | |
| input: "data" | |
| input_shape { | |
| dim: 1 | |
| dim: 3 | |
| dim: 224 | |
| dim: 224 | |
| } | |
| layer { | |
| name: "conv1" | |
| type: "Convolution" | |
| bottom: "data" | |
| top: "conv1" | |
| convolution_param { | |
| num_output: 16 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu1" | |
| type: "ReLU" | |
| bottom: "conv1" | |
| top: "conv1" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "max_pool1" | |
| type: "Pooling" | |
| bottom: "conv1" | |
| top: "max_pool1" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv2" | |
| type: "Convolution" | |
| bottom: "max_pool1" | |
| top: "conv2" | |
| convolution_param { | |
| num_output: 32 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu2" | |
| type: "ReLU" | |
| bottom: "conv2" | |
| top: "conv2" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "max_pool2" | |
| type: "Pooling" | |
| bottom: "conv2" | |
| top: "max_pool2" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv3" | |
| type: "Convolution" | |
| bottom: "max_pool2" | |
| top: "conv3" | |
| convolution_param { | |
| num_output: 64 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu3" | |
| type: "ReLU" | |
| bottom: "conv3" | |
| top: "conv3" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "max_pool3" | |
| type: "Pooling" | |
| bottom: "conv3" | |
| top: "max_pool3" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv4" | |
| type: "Convolution" | |
| bottom: "max_pool3" | |
| top: "conv4" | |
| convolution_param { | |
| num_output: 128 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu4" | |
| type: "ReLU" | |
| bottom: "conv4" | |
| top: "conv4" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "max_pool4" | |
| type: "Pooling" | |
| bottom: "conv4" | |
| top: "max_pool4" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv5" | |
| type: "Convolution" | |
| bottom: "max_pool4" | |
| top: "conv5" | |
| convolution_param { | |
| num_output: 256 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu5" | |
| type: "ReLU" | |
| bottom: "conv5" | |
| top: "conv5" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "max_pool5" | |
| type: "Pooling" | |
| bottom: "conv5" | |
| top: "max_pool5" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv6" | |
| type: "Convolution" | |
| bottom: "max_pool5" | |
| top: "conv6" | |
| convolution_param { | |
| num_output: 512 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu6" | |
| type: "ReLU" | |
| bottom: "conv6" | |
| top: "conv6" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "max_pool6" | |
| type: "Pooling" | |
| bottom: "conv6" | |
| top: "max_pool6" | |
| pooling_param { | |
| pool: MAX | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "conv7" | |
| type: "Convolution" | |
| bottom: "max_pool6" | |
| top: "conv7" | |
| convolution_param { | |
| num_output: 1024 | |
| kernel_size: 3 | |
| pad: 1 | |
| stride: 1 | |
| } | |
| } | |
| layer { | |
| name: "relu7" | |
| type: "ReLU" | |
| bottom: "conv7" | |
| top: "conv7" | |
| relu_param{ | |
| negative_slope: 0.1 | |
| } | |
| } | |
| layer { | |
| name: "ave_pool7" | |
| type: "Pooling" | |
| bottom: "conv7" | |
| top: "ave_pool7" | |
| pooling_param { | |
| pool: AVE | |
| kernel_size: 2 | |
| stride: 2 | |
| } | |
| } | |
| layer{ | |
| name: "Fully Connected" | |
| type: "InnerProduct" | |
| bottom: "ave_pool7" | |
| top: "result" | |
| inner_product_param { | |
| num_output: 7 | |
| weight_filler { | |
| type: "gaussian" | |
| std: 0.01 | |
| } | |
| bias_filler { | |
| type: "constant" | |
| value: 0 | |
| } | |
| } | |
| } | |
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