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kurnianggoro/Attention56

Created March 26, 2020 06:22
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Attention56
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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