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ILGNet_v4.prototxt
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name: "resnet_inception"
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 224
mean_file: ""
}
data_param {
source: "train_lmdb"
batch_size: 32
backend: LMDB
shuffle: true
}
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
mirror: false
crop_size: 224
mean_file: ""
}
data_param {
source: "val_lmdb"
batch_size: 32
backend: LMDB
}
}
#########################conv1
layer {
name: "conv1/7x7_s3"
type: "Convolution"
bottom: "data"
top: "conv1/7x7_s3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 7
stride: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv1/relu_7x7"
type: "PReLU"
bottom: "conv1/7x7_s3"
top: "conv1/7x7_s3"
}
layer {
name: "pool1/3x3_s2"
type: "Pooling"
bottom: "conv1/7x7_s3"
top: "pool1/3x3_s2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
#############################conv2_x
################inception 2a
layer {
name: "inception_2a/3x3_reduce"
type: "Convolution"
bottom: "pool1/3x3_s2"
top: "inception_2a/3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2a/relu_3x3_reduce"
type: "PReLU"
bottom: "inception_2a/3x3_reduce"
top: "inception_2a/3x3_reduce"
}
layer {
name: "inception_2a/3x3"
type: "Convolution"
bottom: "inception_2a/3x3_reduce"
top: "inception_2a/3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2a/relu_3x3"
type: "PReLU"
bottom: "inception_2a/3x3"
top: "inception_2a/3x3"
}
layer {
name: "inception_2a/5x5_reduce"
type: "Convolution"
bottom: "pool1/3x3_s2"
top: "inception_2a/5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2a/relu_5x5_reduce"
type: "PReLU"
bottom: "inception_2a/5x5_reduce"
top: "inception_2a/5x5_reduce"
}
layer {
name: "inception_2a/5x5"
type: "Convolution"
bottom: "inception_2a/5x5_reduce"
top: "inception_2a/5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 2
kernel_size: 5
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2a/relu_5x5"
type: "PReLU"
bottom: "inception_2a/5x5"
top: "inception_2a/5x5"
}
layer {
name: "inception_2a/1x1"
type: "Convolution"
bottom: "pool1/3x3_s2"
top: "inception_2a/1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2a/relu_1x1"
type: "PReLU"
bottom: "inception_2a/1x1"
top: "inception_2a/1x1"
}
layer {
name: "inception_2a/output"
type: "Concat"
bottom: "inception_2a/3x3"
bottom: "inception_2a/5x5"
bottom: "inception_2a/1x1"
top: "inception_2a/output"
}
layer {
name: "inception_2a/output_proj"
type: "Convolution"
bottom: "inception_2a/output"
top: "inception_2a/output_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
#############conv2_1 shotcut
layer {
name: "conv2_1/1x1_s1_1_sc"
type: "Convolution"
bottom: "pool1/3x3_s2"
top: "conv2_1/1x1_s1_1_sc"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
stride: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
##################conv2_1 eltwise_sum
layer {
name: "conv2_1"
type: "Eltwise"
bottom: "conv2_1/1x1_s1_1_sc"
bottom: "inception_2a/output_proj"
top: "conv2_1"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_1_bn"
type: "BN"
bottom: "conv2_1"
top: "conv2_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0.001
}
moving_average: true
}
}
layer {
name: "conv2_1/relu"
type: "ReLU"
bottom: "conv2_1"
top: "conv2_1"
}
###############################conv2_2
################inception 2b
layer {
name: "inception_2b/3x3_reduce"
type: "Convolution"
bottom: "conv2_1"
top: "inception_2b/3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2b/relu_3x3_reduce"
type: "PReLU"
bottom: "inception_2b/3x3_reduce"
top: "inception_2b/3x3_reduce"
}
layer {
name: "inception_2b/3x3"
type: "Convolution"
bottom: "inception_2b/3x3_reduce"
top: "inception_2b/3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2b/relu_3x3"
type: "PReLU"
bottom: "inception_2b/3x3"
top: "inception_2b/3x3"
}
layer {
name: "inception_2b/5x5_reduce"
type: "Convolution"
bottom: "conv2_1"
top: "inception_2b/5x5_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 16
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2b/relu_5x5_reduce"
type: "PReLU"
bottom: "inception_2b/5x5_reduce"
top: "inception_2b/5x5_reduce"
}
layer {
name: "inception_2b/5x5"
type: "Convolution"
bottom: "inception_2b/5x5_reduce"
top: "inception_2b/5x5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
pad: 2
kernel_size: 5
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2b/relu_5x5"
type: "PReLU"
bottom: "inception_2b/5x5"
top: "inception_2b/5x5"
}
layer {
name: "inception_2b/1x1"
type: "Convolution"
bottom: "conv2_1"
top: "inception_2b/1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 32
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_2b/relu_1x1"
type: "PReLU"
bottom: "inception_2b/1x1"
top: "inception_2b/1x1"
}
layer {
name: "inception_2b/output"
type: "Concat"
bottom: "inception_2b/3x3"
bottom: "inception_2b/5x5"
bottom: "inception_2b/1x1"
top: "inception_2b/output"
}
layer {
name: "inception_2b/output_proj"
type: "Convolution"
bottom: "inception_2b/output"
top: "inception_2b/output_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
##################conv2_2 eltwise_sum
layer {
name: "conv2_2"
type: "Eltwise"
bottom: "conv2_1"
bottom: "inception_2b/output_proj"
top: "conv2_2"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv2_2_bn"
type: "BN"
bottom: "conv2_2"
top: "conv2_2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0.001
}
moving_average: true
}
}
layer {
name: "conv2_2/relu"
type: "ReLU"
bottom: "conv2_2"
top: "conv2_2"
}
##############pooling2
layer {
name: "conv_pooling2/3x3"
type: "Convolution"
bottom: "conv2_2"
top: "conv_pooling2/3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 3
stride: 2
pad:1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "conv_pooling2/relu_3x3"
type: "PReLU"
bottom: "conv_pooling2/3x3"
top: "conv_pooling2/3x3"
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2_2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "pooling2/output"
type: "Concat"
bottom: "conv_pooling2/3x3"
bottom: "pool2"
top: "pooling2/output"
}
###########################conv3_x
################inception 3a
layer {
name: "inception_3a/1x1"
type: "Convolution"
bottom: "pooling2/output"
top: "inception_3a/1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_3a/relu_1x1"
type: "PReLU"
bottom: "inception_3a/1x1"
top: "inception_3a/1x1"
}
layer {
name: "inception_3a/3x3_reduce"
type: "Convolution"
bottom: "pooling2/output"
top: "inception_3a/3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_3a/relu_3x3_reduce"
type: "PReLU"
bottom: "inception_3a/3x3_reduce"
top: "inception_3a/3x3_reduce"
}
layer {
name: "inception_3a/3x3"
type: "Convolution"
bottom: "inception_3a/3x3_reduce"
top: "inception_3a/3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_3a/relu_3x3"
type: "PReLU"
bottom: "inception_3a/3x3"
top: "inception_3a/3x3"
}
layer {
name: "inception_3a/output"
type: "Concat"
bottom: "inception_3a/1x1"
bottom: "inception_3a/3x3"
top: "inception_3a/output"
}
layer {
name: "inception_3a/output_proj"
type: "Convolution"
bottom: "inception_3a/output"
top: "inception_3a/output_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
##################conv3_1 eltwise_sum
layer {
name: "conv3_1"
type: "Eltwise"
bottom: "pooling2/output"
bottom: "inception_3a/output_proj"
top: "conv3_1"
eltwise_param {
operation: SUM
}
}
layer {
name: "conv3_1_bn"
type: "BN"
bottom: "conv3_1"
top: "conv3_1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 1
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
param {
lr_mult: 0
decay_mult: 0
}
bn_param {
slope_filler {
type: "constant"
value: 1
}
bias_filler {
type: "constant"
value: 0.001
}
moving_average: true
}
}
layer {
name: "conv3_1/relu"
type: "ReLU"
bottom: "conv3_1"
top: "conv3_1"
}
#######################conv3_2
################inception 3b
layer {
name: "inception_3b/1x1"
type: "Convolution"
bottom: "conv3_1"
top: "inception_3b/1x1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_3b/relu_1x1"
type: "PReLU"
bottom: "inception_3b/1x1"
top: "inception_3b/1x1"
}
layer {
name: "inception_3b/3x3_reduce"
type: "Convolution"
bottom: "conv3_1"
top: "inception_3b/3x3_reduce"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 64
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_3b/relu_3x3_reduce"
type: "PReLU"
bottom: "inception_3b/3x3_reduce"
top: "inception_3b/3x3_reduce"
}
layer {
name: "inception_3b/3x3"
type: "Convolution"
bottom: "inception_3b/3x3_reduce"
top: "inception_3b/3x3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 128
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "inception_3b/relu_3x3"
type: "PReLU"
bottom: "inception_3b/3x3"
top: "inception_3b/3x3"
}
layer {
name: "inception_3b/output"
type: "Concat"
bottom: "inception_3b/1x1"
bottom: "inception_3b/3x3"
top: "inception_3b/output"
}
layer {
name: "inception_3b/output_proj"
type: "Convolution"
bottom: "inception_3b/output"
top: "inception_3b/output_proj"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
kernel_size: 1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
##################conv3_2 eltwise_sum