ResNet_18_deploy.prototxt
name: "ResNet-18"
layer { name: "data" type: "Input" top: "data" input_param { shape: { dim: 10 dim: 3 dim: 224 dim: 224 } } } layer { bottom: "data" top: "conv1" name: "conv1" type: "Convolution" convolution_param { num_output: 64 kernel_size: 7 pad: 3 stride: 2 bias_term: false } } layer { bottom: "conv1" top: "conv1" name: "bn_conv1" type: "BatchNorm" } layer { bottom: "conv1" top: "conv1" name: "scale_conv1" type: "Scale" scale_param { bias_term: true } } layer { bottom: "conv1" top: "conv1" name: "conv1_relu" type: "ReLU" } layer { bottom: "conv1" top: "pool1" name: "pool1" type: "Pooling" pooling_param { kernel_size: 3 stride: 2 pool: MAX } } layer { bottom: "pool1" top: "res2a_branch1" name: "res2a_branch1" type: "Convolution" convolution_param { num_output: 64 kernel_size: 1 pad: 0 stride: 1 bias_term: false } } layer { bottom: "res2a_branch1" top: "res2a_branch1" name: "bn2a_branch1" type: "BatchNorm" } layer { bottom: "res2a_branch1" top: "res2a_branch1" name: "scale2a_branch1" type: "Scale" scale_param { bias_term: true } } layer { bottom: "pool1" top: "res2a_branch2a" name: "res2a_branch2a" type: "Convolution" convolution_param { num_output: 64 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res2a_branch2a" top: "res2a_branch2a" name: "bn2a_branch2a" type: "BatchNorm" } layer { bottom: "res2a_branch2a" top: "res2a_branch2a" name: "scale2a_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res2a_branch2a" top: "res2a_branch2a" name: "res2a_branch2a_relu" type: "ReLU" } layer { bottom: "res2a_branch2a" top: "res2a_branch2b" name: "res2a_branch2b" type: "Convolution" convolution_param { num_output: 64 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res2a_branch2b" top: "res2a_branch2b" name: "bn2a_branch2b" type: "BatchNorm" } layer { bottom: "res2a_branch2b" top: "res2a_branch2b" name: "scale2a_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res2a_branch1" bottom: "res2a_branch2b" top: "res2a" name: "res2a" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res2a" top: "res2a" name: "res2a_relu" type: "ReLU" } layer { bottom: "res2a" top: "res2b_branch2a" name: "res2b_branch2a" type: "Convolution" convolution_param { num_output: 64 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res2b_branch2a" top: "res2b_branch2a" name: "bn2b_branch2a" type: "BatchNorm" } layer { bottom: "res2b_branch2a" top: "res2b_branch2a" name: "scale2b_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res2b_branch2a" top: "res2b_branch2a" name: "res2b_branch2a_relu" type: "ReLU" } layer { bottom: "res2b_branch2a" top: "res2b_branch2b" name: "res2b_branch2b" type: "Convolution" convolution_param { num_output: 64 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res2b_branch2b" top: "res2b_branch2b" name: "bn2b_branch2b" type: "BatchNorm" } layer { bottom: "res2b_branch2b" top: "res2b_branch2b" name: "scale2b_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res2a" bottom: "res2b_branch2b" top: "res2b" name: "res2b" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res2b" top: "res2b" name: "res2b_relu" type: "ReLU" } layer { bottom: "res2b" top: "res3a_branch1" name: "res3a_branch1" type: "Convolution" convolution_param { num_output: 128 kernel_size: 1 pad: 0 stride: 2 bias_term: false } } layer { bottom: "res3a_branch1" top: "res3a_branch1" name: "bn3a_branch1" type: "BatchNorm" } layer { bottom: "res3a_branch1" top: "res3a_branch1" name: "scale3a_branch1" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res2b" top: "res3a_branch2a" name: "res3a_branch2a" type: "Convolution" convolution_param { num_output: 128 kernel_size: 3 pad: 1 stride: 2 bias_term: false } } layer { bottom: "res3a_branch2a" top: "res3a_branch2a" name: "bn3a_branch2a" type: "BatchNorm" } layer { bottom: "res3a_branch2a" top: "res3a_branch2a" name: "scale3a_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res3a_branch2a" top: "res3a_branch2a" name: "res3a_branch2a_relu" type: "ReLU" } layer { bottom: "res3a_branch2a" top: "res3a_branch2b" name: "res3a_branch2b" type: "Convolution" convolution_param { num_output: 128 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res3a_branch2b" top: "res3a_branch2b" name: "bn3a_branch2b" type: "BatchNorm" } layer { bottom: "res3a_branch2b" top: "res3a_branch2b" name: "scale3a_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res3a_branch1" bottom: "res3a_branch2b" top: "res3a" name: "res3a" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res3a" top: "res3a" name: "res3a_relu" type: "ReLU" } layer { bottom: "res3a" top: "res3b_branch2a" name: "res3b_branch2a" type: "Convolution" convolution_param { num_output: 128 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res3b_branch2a" top: "res3b_branch2a" name: "bn3b_branch2a" type: "BatchNorm" } layer { bottom: "res3b_branch2a" top: "res3b_branch2a" name: "scale3b_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res3b_branch2a" top: "res3b_branch2a" name: "res3b_branch2a_relu" type: "ReLU" } layer { bottom: "res3b_branch2a" top: "res3b_branch2b" name: "res3b_branch2b" type: "Convolution" convolution_param { num_output: 128 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res3b_branch2b" top: "res3b_branch2b" name: "bn3b_branch2b" type: "BatchNorm" } layer { bottom: "res3b_branch2b" top: "res3b_branch2b" name: "scale3b_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res3a" bottom: "res3b_branch2b" top: "res3b" name: "res3b" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res3b" top: "res3b" name: "res3b_relu" type: "ReLU" } layer { bottom: "res3b" top: "res4a_branch1" name: "res4a_branch1" type: "Convolution" convolution_param { num_output: 256 kernel_size: 1 pad: 0 stride: 2 bias_term: false } } layer { bottom: "res4a_branch1" top: "res4a_branch1" name: "bn4a_branch1" type: "BatchNorm" } layer { bottom: "res4a_branch1" top: "res4a_branch1" name: "scale4a_branch1" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res3b" top: "res4a_branch2a" name: "res4a_branch2a" type: "Convolution" convolution_param { num_output: 256 kernel_size: 3 pad: 1 stride: 2 bias_term: false } } layer { bottom: "res4a_branch2a" top: "res4a_branch2a" name: "bn4a_branch2a" type: "BatchNorm" } layer { bottom: "res4a_branch2a" top: "res4a_branch2a" name: "scale4a_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res4a_branch2a" top: "res4a_branch2a" name: "res4a_branch2a_relu" type: "ReLU" } layer { bottom: "res4a_branch2a" top: "res4a_branch2b" name: "res4a_branch2b" type: "Convolution" convolution_param { num_output: 256 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res4a_branch2b" top: "res4a_branch2b" name: "bn4a_branch2b" type: "BatchNorm" } layer { bottom: "res4a_branch2b" top: "res4a_branch2b" name: "scale4a_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res4a_branch1" bottom: "res4a_branch2b" top: "res4a" name: "res4a" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res4a" top: "res4a" name: "res4a_relu" type: "ReLU" } layer { bottom: "res4a" top: "res4b_branch2a" name: "res4b_branch2a" type: "Convolution" convolution_param { num_output: 256 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res4b_branch2a" top: "res4b_branch2a" name: "bn4b_branch2a" type: "BatchNorm" } layer { bottom: "res4b_branch2a" top: "res4b_branch2a" name: "scale4b_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res4b_branch2a" top: "res4b_branch2a" name: "res4b_branch2a_relu" type: "ReLU" } layer { bottom: "res4b_branch2a" top: "res4b_branch2b" name: "res4b_branch2b" type: "Convolution" convolution_param { num_output: 256 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res4b_branch2b" top: "res4b_branch2b" name: "bn4b_branch2b" type: "BatchNorm" } layer { bottom: "res4b_branch2b" top: "res4b_branch2b" name: "scale4b_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res4a" bottom: "res4b_branch2b" top: "res4b" name: "res4b" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res4b" top: "res4b" name: "res4b_relu" type: "ReLU" } layer { bottom: "res4b" top: "res5a_branch1" name: "res5a_branch1" type: "Convolution" convolution_param { num_output: 512 kernel_size: 1 pad: 0 stride: 2 bias_term: false } } layer { bottom: "res5a_branch1" top: "res5a_branch1" name: "bn5a_branch1" type: "BatchNorm" } layer { bottom: "res5a_branch1" top: "res5a_branch1" name: "scale5a_branch1" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res4b" top: "res5a_branch2a" name: "res5a_branch2a" type: "Convolution" convolution_param { num_output: 512 kernel_size: 3 pad: 1 stride: 2 bias_term: false } } layer { bottom: "res5a_branch2a" top: "res5a_branch2a" name: "bn5a_branch2a" type: "BatchNorm" } layer { bottom: "res5a_branch2a" top: "res5a_branch2a" name: "scale5a_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res5a_branch2a" top: "res5a_branch2a" name: "res5a_branch2a_relu" type: "ReLU" } layer { bottom: "res5a_branch2a" top: "res5a_branch2b" name: "res5a_branch2b" type: "Convolution" convolution_param { num_output: 512 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res5a_branch2b" top: "res5a_branch2b" name: "bn5a_branch2b" type: "BatchNorm" } layer { bottom: "res5a_branch2b" top: "res5a_branch2b" name: "scale5a_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res5a_branch1" bottom: "res5a_branch2b" top: "res5a" name: "res5a" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res5a" top: "res5a" name: "res5a_relu" type: "ReLU" } layer { bottom: "res5a" top: "res5b_branch2a" name: "res5b_branch2a" type: "Convolution" convolution_param { num_output: 512 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res5b_branch2a" top: "res5b_branch2a" name: "bn5b_branch2a" type: "BatchNorm" } layer { bottom: "res5b_branch2a" top: "res5b_branch2a" name: "scale5b_branch2a" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res5b_branch2a" top: "res5b_branch2a" name: "res5b_branch2a_relu" type: "ReLU" } layer { bottom: "res5b_branch2a" top: "res5b_branch2b" name: "res5b_branch2b" type: "Convolution" convolution_param { num_output: 512 kernel_size: 3 pad: 1 stride: 1 bias_term: false } } layer { bottom: "res5b_branch2b" top: "res5b_branch2b" name: "bn5b_branch2b" type: "BatchNorm" } layer { bottom: "res5b_branch2b" top: "res5b_branch2b" name: "scale5b_branch2b" type: "Scale" scale_param { bias_term: true } } layer { bottom: "res5a" bottom: "res5b_branch2b" top: "res5b" name: "res5b" type: "Eltwise" eltwise_param { operation: SUM } } layer { bottom: "res5b" top: "res5b" name: "res5b_relu" type: "ReLU" } layer { bottom: "res5b" top: "pool5" name: "pool5" type: "Pooling" pooling_param { kernel_size: 7 stride: 1 pool: AVE } } layer { bottom: "pool5" top: "fc1000" name: "fc1000" type: "InnerProduct" param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 1 } inner_product_param { num_output: 3 } } layer { name: "prob" type: "Softmax" bottom: "fc1000" top: "prob"}
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