Created
March 26, 2020 06:22
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name: "Attention-56" | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 224 | |
input_dim: 224 | |
layer{ | |
name: "conv1" | |
type: "Convolution" | |
bottom: "data" | |
top: "conv1" | |
convolution_param { | |
num_output: 64 | |
pad: 3 | |
kernel_size: 7 | |
stride: 2 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "conv1/bn" | |
type: "BN" | |
bottom: "conv1" | |
top: "conv1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "conv1/bn/relu" | |
type: "ReLU" | |
bottom: "conv1/bn" | |
top: "conv1/bn" | |
} | |
layer{ | |
name: "pool1_3x3_s2" | |
type: "Pooling" | |
bottom: "conv1/bn" | |
top: "pool1_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer{ | |
name: "pool1_3x3_s2/bn" | |
type: "BN" | |
bottom: "pool1_3x3_s2" | |
top: "pool1_3x3_s2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pool1_3x3_s2/bn/relu" | |
type: "ReLU" | |
bottom: "pool1_3x3_s2/bn" | |
top: "pool1_3x3_s2/bn" | |
} | |
layer{ | |
name: "pre_res_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "pool1_3x3_s2/bn" | |
top: "pre_res_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "pre_res_1/branch1/conv1_1x1" | |
top: "pre_res_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_1/branch1/conv1_1x1/bn" | |
top: "pre_res_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "pre_res_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "pre_res_1/branch1/conv1_1x1/bn" | |
top: "pre_res_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "pre_res_1/branch1/conv2_3x3" | |
top: "pre_res_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_1/branch1/conv2_3x3/bn" | |
top: "pre_res_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "pre_res_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "pre_res_1/branch1/conv2_3x3/bn" | |
top: "pre_res_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_1/branch2/conv1_1x1" | |
type: "Convolution" | |
bottom: "pool1_3x3_s2/bn" | |
top: "pre_res_1/branch2/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_1" | |
type: "Eltwise" | |
bottom: "pre_res_1/branch2/conv1_1x1" | |
bottom: "pre_res_1/branch1/conv3_1x1" | |
top: "pre_res_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "pre_res_1/bn" | |
type: "BN" | |
bottom: "pre_res_1" | |
top: "pre_res_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_1/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_1/bn" | |
top: "pre_res_1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "pre_res_1/bn" | |
top: "AttentionA_1/trunk/res1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res1/branch1/conv1_1x1" | |
top: "AttentionA_1/trunk/res1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/trunk/res1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/trunk/res1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res1/branch1/conv2_3x3" | |
top: "AttentionA_1/trunk/res1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/trunk/res1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/trunk/res1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/trunk/res1/branch1/conv3_1x1" | |
bottom: "pre_res_1" | |
top: "AttentionA_1/trunk/res1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res1" | |
top: "AttentionA_1/trunk/res1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res1/bn" | |
top: "AttentionA_1/trunk/res1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res1/bn" | |
top: "AttentionA_1/trunk/res2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res2/branch1/conv1_1x1" | |
top: "AttentionA_1/trunk/res2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res2/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/trunk/res2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res2/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/trunk/res2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res2/branch1/conv2_3x3" | |
top: "AttentionA_1/trunk/res2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res2/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/trunk/res2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res2/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/trunk/res2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2" | |
type: "Eltwise" | |
bottom: "AttentionA_1/trunk/res2/branch1/conv3_1x1" | |
bottom: "AttentionA_1/trunk/res1" | |
top: "AttentionA_1/trunk/res2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res2" | |
top: "AttentionA_1/trunk/res2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res2/bn" | |
top: "AttentionA_1/trunk/res2/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res2/bn" | |
top: "AttentionA_1/trunk/res3/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res3/branch1/conv1_1x1" | |
top: "AttentionA_1/trunk/res3/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res3/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/trunk/res3/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res3/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/trunk/res3/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/trunk/res3/branch1/conv2_3x3" | |
top: "AttentionA_1/trunk/res3/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/trunk/res3/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/trunk/res3/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/trunk/res3/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/trunk/res3/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/trunk/res3" | |
type: "Eltwise" | |
bottom: "AttentionA_1/trunk/res3/branch1/conv3_1x1" | |
bottom: "AttentionA_1/trunk/res2" | |
top: "AttentionA_1/trunk/res3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool1_3x3_s2" | |
type: "Pooling" | |
bottom: "AttentionA_1/trunk/res1" | |
top: "AttentionA_1/mask/down_sample/pool1_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool1_3x3_s2/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/pool1_3x3_s2" | |
top: "AttentionA_1/mask/down_sample/pool1_3x3_s2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool1_3x3_s2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/pool1_3x3_s2/bn" | |
top: "AttentionA_1/mask/down_sample/pool1_3x3_s2/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/pool1_3x3_s2/bn" | |
top: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/down_sample/pool1_3x3_s2" | |
top: "AttentionA_1/mask/down_sample/res1_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool2_3x3_s2" | |
type: "Pooling" | |
bottom: "AttentionA_1/mask/down_sample/res1_1" | |
top: "AttentionA_1/mask/down_sample/pool2_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool2_3x3_s2/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/pool2_3x3_s2" | |
top: "AttentionA_1/mask/down_sample/pool2_3x3_s2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool2_3x3_s2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/pool2_3x3_s2/bn" | |
top: "AttentionA_1/mask/down_sample/pool2_3x3_s2/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/pool2_3x3_s2/bn" | |
top: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res2_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/down_sample/pool2_3x3_s2" | |
top: "AttentionA_1/mask/down_sample/res2_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool3_3x3_s2" | |
type: "Pooling" | |
bottom: "AttentionA_1/mask/down_sample/res2_1" | |
top: "AttentionA_1/mask/down_sample/pool3_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool3_3x3_s2/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/pool3_3x3_s2" | |
top: "AttentionA_1/mask/down_sample/pool3_3x3_s2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/pool3_3x3_s2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/pool3_3x3_s2/bn" | |
top: "AttentionA_1/mask/down_sample/pool3_3x3_s2/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/pool3_3x3_s2/bn" | |
top: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res3_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/down_sample/pool3_3x3_s2" | |
top: "AttentionA_1/mask/down_sample/res3_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res3_1" | |
top: "AttentionA_1/mask/down_sample/res3_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/bn" | |
top: "AttentionA_1/mask/down_sample/res3_1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res3_1/bn" | |
top: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res3_2/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res3_2/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/down_sample/res3_2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res3_2" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/down_sample/res3_2/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/down_sample/res3_1" | |
top: "AttentionA_1/mask/down_sample/res3_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/interp_3" | |
type: "Interp" | |
bottom: "AttentionA_1/mask/down_sample/res3_2" | |
bottom: "AttentionA_1/mask/down_sample/res2_1" | |
top: "AttentionA_1/mask/up_sample/interp_3" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res2_1" | |
top: "AttentionA_1/mask/down_sample/res2_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res2_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/bn" | |
top: "AttentionA_1/mask/down_sample/res2_1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res2_1/bn" | |
top: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/skip/res2/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/skip/res2/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/skip/res2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res2" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/skip/res2/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/down_sample/res2_1" | |
top: "AttentionA_1/mask/skip/res2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample2" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/skip/res2" | |
bottom: "AttentionA_1/mask/up_sample/interp_3" | |
top: "AttentionA_1/mask/up_sample2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample2/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/up_sample2" | |
top: "AttentionA_1/mask/up_sample2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/up_sample2/bn" | |
top: "AttentionA_1/mask/up_sample2/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/up_sample2/bn" | |
top: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/up_sample/res2_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/up_sample/res2_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/up_sample/res2_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res2_1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/up_sample/res2_1/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/up_sample2" | |
top: "AttentionA_1/mask/up_sample/res2_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/interp_2" | |
type: "Interp" | |
bottom: "AttentionA_1/mask/up_sample/res2_1" | |
bottom: "AttentionA_1/mask/down_sample/res1_1" | |
top: "AttentionA_1/mask/up_sample/interp_2" | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/down_sample/res1_1" | |
top: "AttentionA_1/mask/down_sample/res1_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/down_sample/res1_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/bn" | |
top: "AttentionA_1/mask/down_sample/res1_1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/down_sample/res1_1/bn" | |
top: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/skip/res1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/skip/res1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/skip/res1/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/down_sample/res1_1" | |
top: "AttentionA_1/mask/skip/res1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/skip/res1" | |
bottom: "AttentionA_1/mask/up_sample/interp_2" | |
top: "AttentionA_1/mask/up_sample1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/up_sample1" | |
top: "AttentionA_1/mask/up_sample1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/up_sample1/bn" | |
top: "AttentionA_1/mask/up_sample1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/up_sample1/bn" | |
top: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1" | |
top: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3" | |
top: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/mask/up_sample/res1_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/res1_1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/mask/up_sample/res1_1/branch1/conv3_1x1" | |
bottom: "AttentionA_1/mask/up_sample1" | |
top: "AttentionA_1/mask/up_sample/res1_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/interp_1" | |
type: "Interp" | |
bottom: "AttentionA_1/mask/up_sample/res1_1" | |
bottom: "AttentionA_1/trunk/res3" | |
top: "AttentionA_1/mask/up_sample/interp_1" | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/interp_1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/up_sample/interp_1" | |
top: "AttentionA_1/mask/up_sample/interp_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/up_sample/interp_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/up_sample/interp_1/bn" | |
top: "AttentionA_1/mask/up_sample/interp_1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/linear_1" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/up_sample/interp_1/bn" | |
top: "AttentionA_1/mask/linear_1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/linear_1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/mask/linear_1" | |
top: "AttentionA_1/mask/linear_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask/linear_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/mask/linear_1/bn" | |
top: "AttentionA_1/mask/linear_1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/mask/linear_2" | |
type: "Convolution" | |
bottom: "AttentionA_1/mask/linear_1/bn" | |
top: "AttentionA_1/mask/linear_2" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/mask" | |
type: "Sigmoid" | |
bottom: "AttentionA_1/mask/linear_2" | |
top: "AttentionA_1/mask" | |
} | |
layer{ | |
name: "AttentionA_1_residual" | |
type: "Eltwise" | |
bottom: "AttentionA_1/trunk/res3" | |
bottom: "AttentionA_1/mask" | |
top: "AttentionA_1_residual" | |
eltwise_param { | |
operation: PROD | |
} | |
} | |
layer{ | |
name: "AttentionA_1/fusion" | |
type: "Eltwise" | |
bottom: "AttentionA_1_residual" | |
bottom: "AttentionA_1/trunk/res3" | |
top: "AttentionA_1/fusion" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/fusion/bn" | |
type: "BN" | |
bottom: "AttentionA_1/fusion" | |
top: "AttentionA_1/fusion/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/fusion/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/fusion/bn" | |
top: "AttentionA_1/fusion/bn" | |
} | |
layer{ | |
name: "AttentionA_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/fusion/bn" | |
top: "AttentionA_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 64 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionA_1/branch1/conv1_1x1" | |
top: "AttentionA_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionA_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionA_1/branch1/conv1_1x1/bn" | |
top: "AttentionA_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 64 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionA_1/branch1/conv2_3x3" | |
top: "AttentionA_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionA_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/branch1/conv2_3x3/bn" | |
top: "AttentionA_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionA_1" | |
type: "Eltwise" | |
bottom: "AttentionA_1/branch1/conv3_1x1" | |
bottom: "AttentionA_1/fusion" | |
top: "AttentionA_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionA_1/bn" | |
type: "BN" | |
bottom: "AttentionA_1" | |
top: "AttentionA_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionA_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionA_1/bn" | |
top: "AttentionA_1/bn" | |
} | |
layer{ | |
name: "pre_res_2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/bn" | |
top: "pre_res_2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "pre_res_2/branch1/conv1_1x1" | |
top: "pre_res_2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_2/branch1/conv1_1x1/bn" | |
top: "pre_res_2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "pre_res_2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "pre_res_2/branch1/conv1_1x1/bn" | |
top: "pre_res_2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "pre_res_2/branch1/conv2_3x3" | |
top: "pre_res_2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_2/branch1/conv2_3x3/bn" | |
top: "pre_res_2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "pre_res_2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "pre_res_2/branch1/conv2_3x3/bn" | |
top: "pre_res_2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_2/branch2/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionA_1/bn" | |
top: "pre_res_2/branch2/conv1_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 2 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_2" | |
type: "Eltwise" | |
bottom: "pre_res_2/branch2/conv1_1x1" | |
bottom: "pre_res_2/branch1/conv3_1x1" | |
top: "pre_res_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "pre_res_2/bn" | |
type: "BN" | |
bottom: "pre_res_2" | |
top: "pre_res_2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_2/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_2/bn" | |
top: "pre_res_2/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "pre_res_2/bn" | |
top: "AttentionB_1/trunk/res1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res1/branch1/conv1_1x1" | |
top: "AttentionB_1/trunk/res1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/trunk/res1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/trunk/res1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res1/branch1/conv2_3x3" | |
top: "AttentionB_1/trunk/res1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/trunk/res1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/trunk/res1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1" | |
type: "Eltwise" | |
bottom: "AttentionB_1/trunk/res1/branch1/conv3_1x1" | |
bottom: "pre_res_2" | |
top: "AttentionB_1/trunk/res1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res1" | |
top: "AttentionB_1/trunk/res1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res1/bn" | |
top: "AttentionB_1/trunk/res1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res1/bn" | |
top: "AttentionB_1/trunk/res2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res2/branch1/conv1_1x1" | |
top: "AttentionB_1/trunk/res2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res2/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/trunk/res2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res2/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/trunk/res2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res2/branch1/conv2_3x3" | |
top: "AttentionB_1/trunk/res2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res2/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/trunk/res2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res2/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/trunk/res2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2" | |
type: "Eltwise" | |
bottom: "AttentionB_1/trunk/res2/branch1/conv3_1x1" | |
bottom: "AttentionB_1/trunk/res1" | |
top: "AttentionB_1/trunk/res2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res2" | |
top: "AttentionB_1/trunk/res2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res2/bn" | |
top: "AttentionB_1/trunk/res2/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res2/bn" | |
top: "AttentionB_1/trunk/res3/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res3/branch1/conv1_1x1" | |
top: "AttentionB_1/trunk/res3/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res3/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/trunk/res3/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res3/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/trunk/res3/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/trunk/res3/branch1/conv2_3x3" | |
top: "AttentionB_1/trunk/res3/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/trunk/res3/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/trunk/res3/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/trunk/res3/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/trunk/res3/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/trunk/res3" | |
type: "Eltwise" | |
bottom: "AttentionB_1/trunk/res3/branch1/conv3_1x1" | |
bottom: "AttentionB_1/trunk/res2" | |
top: "AttentionB_1/trunk/res3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/pool1_3x3_s2" | |
type: "Pooling" | |
bottom: "AttentionB_1/trunk/res1" | |
top: "AttentionB_1/mask/down_sample/pool1_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/pool1_3x3_s2/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/pool1_3x3_s2" | |
top: "AttentionB_1/mask/down_sample/pool1_3x3_s2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/pool1_3x3_s2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/pool1_3x3_s2/bn" | |
top: "AttentionB_1/mask/down_sample/pool1_3x3_s2/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/pool1_3x3_s2/bn" | |
top: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
top: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
top: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1" | |
type: "Eltwise" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
bottom: "AttentionB_1/mask/down_sample/pool1_3x3_s2" | |
top: "AttentionB_1/mask/down_sample/res1_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/pool2_3x3_s2" | |
type: "Pooling" | |
bottom: "AttentionB_1/mask/down_sample/res1_1" | |
top: "AttentionB_1/mask/down_sample/pool2_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/pool2_3x3_s2/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/pool2_3x3_s2" | |
top: "AttentionB_1/mask/down_sample/pool2_3x3_s2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/pool2_3x3_s2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/pool2_3x3_s2/bn" | |
top: "AttentionB_1/mask/down_sample/pool2_3x3_s2/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/pool2_3x3_s2/bn" | |
top: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1" | |
top: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3" | |
top: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/down_sample/res2_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1" | |
type: "Eltwise" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/branch1/conv3_1x1" | |
bottom: "AttentionB_1/mask/down_sample/pool2_3x3_s2" | |
top: "AttentionB_1/mask/down_sample/res2_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res2_1" | |
top: "AttentionB_1/mask/down_sample/res2_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/bn" | |
top: "AttentionB_1/mask/down_sample/res2_1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res2_1/bn" | |
top: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1" | |
top: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res2_2/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3" | |
top: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res2_2/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/down_sample/res2_2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res2_2" | |
type: "Eltwise" | |
bottom: "AttentionB_1/mask/down_sample/res2_2/branch1/conv3_1x1" | |
bottom: "AttentionB_1/mask/down_sample/res2_1" | |
top: "AttentionB_1/mask/down_sample/res2_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/interp_2" | |
type: "Interp" | |
bottom: "AttentionB_1/mask/down_sample/res2_2" | |
bottom: "AttentionB_1/mask/down_sample/res1_1" | |
top: "AttentionB_1/mask/up_sample/interp_2" | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/down_sample/res1_1" | |
top: "AttentionB_1/mask/down_sample/res1_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/down_sample/res1_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/bn" | |
top: "AttentionB_1/mask/down_sample/res1_1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/down_sample/res1_1/bn" | |
top: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1" | |
top: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/skip/res1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3" | |
top: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/skip/res1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/skip/res1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/skip/res1" | |
type: "Eltwise" | |
bottom: "AttentionB_1/mask/skip/res1/branch1/conv3_1x1" | |
bottom: "AttentionB_1/mask/down_sample/res1_1" | |
top: "AttentionB_1/mask/skip/res1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample1" | |
type: "Eltwise" | |
bottom: "AttentionB_1/mask/skip/res1" | |
bottom: "AttentionB_1/mask/up_sample/interp_2" | |
top: "AttentionB_1/mask/up_sample1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/up_sample1" | |
top: "AttentionB_1/mask/up_sample1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/up_sample1/bn" | |
top: "AttentionB_1/mask/up_sample1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/up_sample1/bn" | |
top: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1" | |
top: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/up_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3" | |
top: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/up_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/mask/up_sample/res1_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/res1_1" | |
type: "Eltwise" | |
bottom: "AttentionB_1/mask/up_sample/res1_1/branch1/conv3_1x1" | |
bottom: "AttentionB_1/mask/up_sample1" | |
top: "AttentionB_1/mask/up_sample/res1_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/interp_1" | |
type: "Interp" | |
bottom: "AttentionB_1/mask/up_sample/res1_1" | |
bottom: "AttentionB_1/trunk/res3" | |
top: "AttentionB_1/mask/up_sample/interp_1" | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/interp_1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/up_sample/interp_1" | |
top: "AttentionB_1/mask/up_sample/interp_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/up_sample/interp_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/up_sample/interp_1/bn" | |
top: "AttentionB_1/mask/up_sample/interp_1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/linear_1" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/up_sample/interp_1/bn" | |
top: "AttentionB_1/mask/linear_1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/linear_1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/mask/linear_1" | |
top: "AttentionB_1/mask/linear_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask/linear_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/mask/linear_1/bn" | |
top: "AttentionB_1/mask/linear_1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/mask/linear_2" | |
type: "Convolution" | |
bottom: "AttentionB_1/mask/linear_1/bn" | |
top: "AttentionB_1/mask/linear_2" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/mask" | |
type: "Sigmoid" | |
bottom: "AttentionB_1/mask/linear_2" | |
top: "AttentionB_1/mask" | |
} | |
layer{ | |
name: "AttentionB_1_residual" | |
type: "Eltwise" | |
bottom: "AttentionB_1/trunk/res3" | |
bottom: "AttentionB_1/mask" | |
top: "AttentionB_1_residual" | |
eltwise_param { | |
operation: PROD | |
} | |
} | |
layer{ | |
name: "AttentionB_1/fusion" | |
type: "Eltwise" | |
bottom: "AttentionB_1_residual" | |
bottom: "AttentionB_1/trunk/res3" | |
top: "AttentionB_1/fusion" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/fusion/bn" | |
type: "BN" | |
bottom: "AttentionB_1/fusion" | |
top: "AttentionB_1/fusion/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/fusion/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/fusion/bn" | |
top: "AttentionB_1/fusion/bn" | |
} | |
layer{ | |
name: "AttentionB_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/fusion/bn" | |
top: "AttentionB_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 128 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionB_1/branch1/conv1_1x1" | |
top: "AttentionB_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionB_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionB_1/branch1/conv1_1x1/bn" | |
top: "AttentionB_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 128 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionB_1/branch1/conv2_3x3" | |
top: "AttentionB_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionB_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/branch1/conv2_3x3/bn" | |
top: "AttentionB_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionB_1" | |
type: "Eltwise" | |
bottom: "AttentionB_1/branch1/conv3_1x1" | |
bottom: "AttentionB_1/fusion" | |
top: "AttentionB_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionB_1/bn" | |
type: "BN" | |
bottom: "AttentionB_1" | |
top: "AttentionB_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionB_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionB_1/bn" | |
top: "AttentionB_1/bn" | |
} | |
layer{ | |
name: "pre_res_3/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/bn" | |
top: "pre_res_3/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_3/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "pre_res_3/branch1/conv1_1x1" | |
top: "pre_res_3/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_3/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_3/branch1/conv1_1x1/bn" | |
top: "pre_res_3/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "pre_res_3/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "pre_res_3/branch1/conv1_1x1/bn" | |
top: "pre_res_3/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_3/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "pre_res_3/branch1/conv2_3x3" | |
top: "pre_res_3/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_3/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_3/branch1/conv2_3x3/bn" | |
top: "pre_res_3/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "pre_res_3/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "pre_res_3/branch1/conv2_3x3/bn" | |
top: "pre_res_3/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_3/branch2/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionB_1/bn" | |
top: "pre_res_3/branch2/conv1_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 2 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "pre_res_3" | |
type: "Eltwise" | |
bottom: "pre_res_3/branch2/conv1_1x1" | |
bottom: "pre_res_3/branch1/conv3_1x1" | |
top: "pre_res_3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "pre_res_3/bn" | |
type: "BN" | |
bottom: "pre_res_3" | |
top: "pre_res_3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "pre_res_3/bn/relu" | |
type: "ReLU" | |
bottom: "pre_res_3/bn" | |
top: "pre_res_3/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "pre_res_3/bn" | |
top: "AttentionC_1/trunk/res1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res1/branch1/conv1_1x1" | |
top: "AttentionC_1/trunk/res1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res1/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/trunk/res1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res1/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/trunk/res1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res1/branch1/conv2_3x3" | |
top: "AttentionC_1/trunk/res1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res1/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/trunk/res1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res1/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/trunk/res1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1" | |
type: "Eltwise" | |
bottom: "AttentionC_1/trunk/res1/branch1/conv3_1x1" | |
bottom: "pre_res_3" | |
top: "AttentionC_1/trunk/res1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res1" | |
top: "AttentionC_1/trunk/res1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res1/bn" | |
top: "AttentionC_1/trunk/res1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res1/bn" | |
top: "AttentionC_1/trunk/res2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res2/branch1/conv1_1x1" | |
top: "AttentionC_1/trunk/res2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res2/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/trunk/res2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res2/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/trunk/res2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res2/branch1/conv2_3x3" | |
top: "AttentionC_1/trunk/res2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res2/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/trunk/res2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res2/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/trunk/res2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2" | |
type: "Eltwise" | |
bottom: "AttentionC_1/trunk/res2/branch1/conv3_1x1" | |
bottom: "AttentionC_1/trunk/res1" | |
top: "AttentionC_1/trunk/res2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res2" | |
top: "AttentionC_1/trunk/res2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res2/bn" | |
top: "AttentionC_1/trunk/res2/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res2/bn" | |
top: "AttentionC_1/trunk/res3/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res3/branch1/conv1_1x1" | |
top: "AttentionC_1/trunk/res3/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res3/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/trunk/res3/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res3/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/trunk/res3/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionC_1/trunk/res3/branch1/conv2_3x3" | |
top: "AttentionC_1/trunk/res3/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/trunk/res3/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/trunk/res3/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/trunk/res3/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/trunk/res3/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/trunk/res3" | |
type: "Eltwise" | |
bottom: "AttentionC_1/trunk/res3/branch1/conv3_1x1" | |
bottom: "AttentionC_1/trunk/res2" | |
top: "AttentionC_1/trunk/res3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/pool1_3x3_s2" | |
type: "Pooling" | |
bottom: "AttentionC_1/trunk/res1" | |
top: "AttentionC_1/mask/down_sample/pool1_3x3_s2" | |
pooling_param { | |
pool: MAX | |
kernel_size: 3 | |
stride: 2 | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/pool1_3x3_s2/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/down_sample/pool1_3x3_s2" | |
top: "AttentionC_1/mask/down_sample/pool1_3x3_s2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/pool1_3x3_s2/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/down_sample/pool1_3x3_s2/bn" | |
top: "AttentionC_1/mask/down_sample/pool1_3x3_s2/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/down_sample/pool1_3x3_s2/bn" | |
top: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1" | |
top: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3" | |
top: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1" | |
type: "Eltwise" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/branch1/conv3_1x1" | |
bottom: "AttentionC_1/mask/down_sample/pool1_3x3_s2" | |
top: "AttentionC_1/mask/down_sample/res1_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/down_sample/res1_1" | |
top: "AttentionC_1/mask/down_sample/res1_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/bn" | |
top: "AttentionC_1/mask/down_sample/res1_1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/down_sample/res1_1/bn" | |
top: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1" | |
top: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/down_sample/res1_2/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3" | |
top: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/down_sample/res1_2/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/mask/down_sample/res1_2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/down_sample/res1_2" | |
type: "Eltwise" | |
bottom: "AttentionC_1/mask/down_sample/res1_2/branch1/conv3_1x1" | |
bottom: "AttentionC_1/mask/down_sample/res1_1" | |
top: "AttentionC_1/mask/down_sample/res1_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/up_sample/interp_1" | |
type: "Interp" | |
bottom: "AttentionC_1/mask/down_sample/res1_2" | |
bottom: "AttentionC_1/trunk/res3" | |
top: "AttentionC_1/mask/up_sample/interp_1" | |
} | |
layer{ | |
name: "AttentionC_1/mask/up_sample/interp_1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/up_sample/interp_1" | |
top: "AttentionC_1/mask/up_sample/interp_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/up_sample/interp_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/up_sample/interp_1/bn" | |
top: "AttentionC_1/mask/up_sample/interp_1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/linear_1" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/up_sample/interp_1/bn" | |
top: "AttentionC_1/mask/linear_1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/linear_1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/mask/linear_1" | |
top: "AttentionC_1/mask/linear_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask/linear_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/mask/linear_1/bn" | |
top: "AttentionC_1/mask/linear_1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/mask/linear_2" | |
type: "Convolution" | |
bottom: "AttentionC_1/mask/linear_1/bn" | |
top: "AttentionC_1/mask/linear_2" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/mask" | |
type: "Sigmoid" | |
bottom: "AttentionC_1/mask/linear_2" | |
top: "AttentionC_1/mask" | |
} | |
layer{ | |
name: "AttentionC_1_residual" | |
type: "Eltwise" | |
bottom: "AttentionC_1/trunk/res3" | |
bottom: "AttentionC_1/mask" | |
top: "AttentionC_1_residual" | |
eltwise_param { | |
operation: PROD | |
} | |
} | |
layer{ | |
name: "AttentionC_1/fusion" | |
type: "Eltwise" | |
bottom: "AttentionC_1_residual" | |
bottom: "AttentionC_1/trunk/res3" | |
top: "AttentionC_1/fusion" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionC_1/fusion/bn" | |
type: "BN" | |
bottom: "AttentionC_1/fusion" | |
top: "AttentionC_1/fusion/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/fusion/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/fusion/bn" | |
top: "AttentionC_1/fusion/bn" | |
} | |
layer{ | |
name: "AttentionC_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/fusion/bn" | |
top: "AttentionC_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 256 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "AttentionC_1/branch1/conv1_1x1" | |
top: "AttentionC_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "AttentionC_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "AttentionC_1/branch1/conv1_1x1/bn" | |
top: "AttentionC_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 256 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "AttentionC_1/branch1/conv2_3x3" | |
top: "AttentionC_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "AttentionC_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/branch1/conv2_3x3/bn" | |
top: "AttentionC_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 1024 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "AttentionC_1" | |
type: "Eltwise" | |
bottom: "AttentionC_1/branch1/conv3_1x1" | |
bottom: "AttentionC_1/fusion" | |
top: "AttentionC_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "AttentionC_1/bn" | |
type: "BN" | |
bottom: "AttentionC_1" | |
top: "AttentionC_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "AttentionC_1/bn/relu" | |
type: "ReLU" | |
bottom: "AttentionC_1/bn" | |
top: "AttentionC_1/bn" | |
} | |
layer{ | |
name: "post_res_4_1/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/bn" | |
top: "post_res_4_1/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_1/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "post_res_4_1/branch1/conv1_1x1" | |
top: "post_res_4_1/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_1/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_1/branch1/conv1_1x1/bn" | |
top: "post_res_4_1/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "post_res_4_1/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "post_res_4_1/branch1/conv1_1x1/bn" | |
top: "post_res_4_1/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
stride: 2 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_1/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "post_res_4_1/branch1/conv2_3x3" | |
top: "post_res_4_1/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_1/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_1/branch1/conv2_3x3/bn" | |
top: "post_res_4_1/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "post_res_4_1/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "post_res_4_1/branch1/conv2_3x3/bn" | |
top: "post_res_4_1/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_1/branch2/conv1_1x1" | |
type: "Convolution" | |
bottom: "AttentionC_1/bn" | |
top: "post_res_4_1/branch2/conv1_1x1" | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 2 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_1" | |
type: "Eltwise" | |
bottom: "post_res_4_1/branch2/conv1_1x1" | |
bottom: "post_res_4_1/branch1/conv3_1x1" | |
top: "post_res_4_1" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "post_res_4_1/bn" | |
type: "BN" | |
bottom: "post_res_4_1" | |
top: "post_res_4_1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_1/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_1/bn" | |
top: "post_res_4_1/bn" | |
} | |
layer{ | |
name: "post_res_4_2/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "post_res_4_1/bn" | |
top: "post_res_4_2/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_2/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "post_res_4_2/branch1/conv1_1x1" | |
top: "post_res_4_2/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_2/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_2/branch1/conv1_1x1/bn" | |
top: "post_res_4_2/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "post_res_4_2/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "post_res_4_2/branch1/conv1_1x1/bn" | |
top: "post_res_4_2/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_2/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "post_res_4_2/branch1/conv2_3x3" | |
top: "post_res_4_2/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_2/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_2/branch1/conv2_3x3/bn" | |
top: "post_res_4_2/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "post_res_4_2/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "post_res_4_2/branch1/conv2_3x3/bn" | |
top: "post_res_4_2/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_2" | |
type: "Eltwise" | |
bottom: "post_res_4_2/branch1/conv3_1x1" | |
bottom: "post_res_4_1" | |
top: "post_res_4_2" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "post_res_4_2/bn" | |
type: "BN" | |
bottom: "post_res_4_2" | |
top: "post_res_4_2/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_2/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_2/bn" | |
top: "post_res_4_2/bn" | |
} | |
layer{ | |
name: "post_res_4_3/branch1/conv1_1x1" | |
type: "Convolution" | |
bottom: "post_res_4_2/bn" | |
top: "post_res_4_3/branch1/conv1_1x1" | |
convolution_param { | |
num_output: 512 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_3/branch1/conv1_1x1/bn" | |
type: "BN" | |
bottom: "post_res_4_3/branch1/conv1_1x1" | |
top: "post_res_4_3/branch1/conv1_1x1/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_3/branch1/conv1_1x1/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_3/branch1/conv1_1x1/bn" | |
top: "post_res_4_3/branch1/conv1_1x1/bn" | |
} | |
layer{ | |
name: "post_res_4_3/branch1/conv2_3x3" | |
type: "Convolution" | |
bottom: "post_res_4_3/branch1/conv1_1x1/bn" | |
top: "post_res_4_3/branch1/conv2_3x3" | |
convolution_param { | |
num_output: 512 | |
pad: 1 | |
kernel_size: 3 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_3/branch1/conv2_3x3/bn" | |
type: "BN" | |
bottom: "post_res_4_3/branch1/conv2_3x3" | |
top: "post_res_4_3/branch1/conv2_3x3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_3/branch1/conv2_3x3/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_3/branch1/conv2_3x3/bn" | |
top: "post_res_4_3/branch1/conv2_3x3/bn" | |
} | |
layer{ | |
name: "post_res_4_3/branch1/conv3_1x1" | |
type: "Convolution" | |
bottom: "post_res_4_3/branch1/conv2_3x3/bn" | |
top: "post_res_4_3/branch1/conv3_1x1" | |
convolution_param { | |
num_output: 2048 | |
pad: 0 | |
kernel_size: 1 | |
stride: 1 | |
bias_term: false | |
} | |
} | |
layer{ | |
name: "post_res_4_3" | |
type: "Eltwise" | |
bottom: "post_res_4_3/branch1/conv3_1x1" | |
bottom: "post_res_4_2" | |
top: "post_res_4_3" | |
eltwise_param { | |
operation: SUM | |
} | |
} | |
layer{ | |
name: "post_res_4_3/bn" | |
type: "BN" | |
bottom: "post_res_4_3" | |
top: "post_res_4_3/bn" | |
bn_param { | |
frozen: true | |
} | |
} | |
layer{ | |
name: "post_res_4_3/bn/relu" | |
type: "ReLU" | |
bottom: "post_res_4_3/bn" | |
top: "post_res_4_3/bn" | |
} | |
layer{ | |
name: "ave_pool" | |
type: "Pooling" | |
bottom: "post_res_4_3/bn" | |
top: "ave_pool" | |
pooling_param { | |
pool: AVE | |
kernel_size: 7 | |
stride: 1 | |
} | |
} | |
layer{ | |
name: "classifier" | |
type: "InnerProduct" | |
bottom: "ave_pool" | |
top: "classifier" | |
inner_product_param { | |
num_output: 1000 | |
} | |
} | |
layer{ | |
name: "cls" | |
type: "Softmax" | |
bottom: "classifier" | |
top: "cls" | |
} | |
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