一、准备数据集
1) 下载数据集
Imagnet网站上下载了三类图片，分别是big cat、dog、fish，其中训练集的图片数一共是4149，测试集的图片数是1003，训练集和测试集的图片数比例4:1，将训练集的图片保存在train文件夹下，测试集图片保存在val文件夹下.
train、val文件夹下面均有bigcat、dog、fish三个文件夹，分别存放着对应类别的图片.
2) 利用python代码，生成train.txt、val.txt
train.txt、val.txt分别存储着训练集和测试集图片的文件名及其类别标签（注：bigcat:0、 dog:1、fish:2），格式如下：
n02084071_9865.JPEG 1
n02512053_3388.JPEG 2
n02512053_6294.JPEG 2
n02512053_2413.JPEG 2
n02084071_5655.JPEG 1
n02127808_9965.JPEG 0
n02127808_8206.JPEG 0
n02127808_4887.JPEG 0
n02512053_1952.JPEG 2
Python代码如下(可以先在windows环境下利用以下的代码生成txt)：
import os
import random trainPath = 'F:\\Resnet152\\train\\'
valPath = 'F:\\Resnet152\\val\\' train = {}
val = {} # add
for name in os.listdir(trainPath + "bigcat\\"):
train[name] = 0 # add
for name in os.listdir(trainPath + "dog\\"):
train[name] = 1 # add
for name in os.listdir(trainPath + "fish\\"):
train[name] = 2 # add
for name in os.listdir(valPath + "bigcat\\"):
val[name] = 0 # add
for name in os.listdir(valPath + "dog\\"):
val[name] = 1 # add
for name in os.listdir(valPath + "fish\\"):
val[name] = 2 ftrain = open("F:\\Resnet152\\train\\train.txt", 'w')
fval = open("F:\\Resnet152\\val\\val.txt", 'w') trainName = []
valName = []
for (item) in train:
trainName.append(item) for item in val:
valName.append(item) random.shuffle(trainName)
random.shuffle(valName) for name in trainName:
label = train[name]
ftrain.write(name + " " + str(label) + "\n") for name in valName:
label = val[name]
fval.write(name + " " + str(label) + "\n") ftrain.close()
fval.close()
3) 生成数据集
编写lmdb.sh脚本文件，利用train.txt、val.txt生成train_lmdb、val_lmdb
lmdb.sh脚本代码如下
#!/usr/bin/env sh
# Create the face_48 lmdb inputs
# N.B. set the path to the face_48 train + val data dirs EXAMPLE=/home/wy/ResNet152 #lmdb生成后存放目录
DATA=/home/wy/ResNet152 #train.txt、val.txt存放目录
TOOLS=/home/wy/caffe/build/tools #caffe安装目录 TRAIN_DATA_ROOT=/home/wy/ResNet152/train/
VAL_DATA_ROOT=/home/wy/ResNet152/val/ # Set RESIZE=true to resize the images to 224 x 224. Leave as false if images have
# already been resized using another tool.
RESIZE=true
if $RESIZE; then
RESIZE_HEIGHT=224 #resize图片大小
RESIZE_WIDTH=224
else
RESIZE_HEIGHT=0
RESIZE_WIDTH=0
fi if [ ! -d "$TRAIN_DATA_ROOT" ]; then
echo "Error: TRAIN_DATA_ROOT is not a path to a directory: $TRAIN_DATA_ROOT"
echo "Set the TRAIN_DATA_ROOT variable in create_face_48.sh to the path" \
"where the face_48 training data is stored."
exit 1
fi if [ ! -d "$VAL_DATA_ROOT" ]; then
echo "Error: VAL_DATA_ROOT is not a path to a directory: $VAL_DATA_ROOT"
echo "Set the VAL_DATA_ROOT variable in create_face_48.sh to the path" \
"where the face_48 validation data is stored."
exit 1
fi echo "Creating train lmdb..." GLOG_logtostderr=1 $TOOLS/convert_imageset \
--resize_height=$RESIZE_HEIGHT \
--resize_width=$RESIZE_WIDTH \
--shuffle \
$TRAIN_DATA_ROOT \
$DATA/train.txt \
$EXAMPLE/train_lmdb echo "Creating val lmdb..." GLOG_logtostderr=1 $TOOLS/convert_imageset \
--resize_height=$RESIZE_HEIGHT \
--resize_width=$RESIZE_WIDTH \
--shuffle \
$VAL_DATA_ROOT \
$DATA/val.txt \
$EXAMPLE/val_lmdb echo "Done."
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注：上述代码中有RESIZE_HEIGHT=224、RESIZE_WIDTH=224，因为使用的是ResNet网络，
需要统一图片大小，如果使用的网络对图片大小无要求，或者已经是224*224大小的图片，可不进行resize操作
linux系统终端中执行sh lmdb.sh即可生成lmdb文件，完成数据集的生成工作
执行结束后，会在ResNet152目录下，生成两个文件夹,分别是train_lmdb、val_lmdb
4) 计算图片平均值
训练网络图片时，需要对图片做减均值处理，先将图片平均值保存到文件中，在训练网络中直接引用，先介绍如何生成图片平均值文件，后面引用的时候会特别注明，命令如下：
/home/wy/caffe/build/tools/compute_image_mean /home/wy/ResNet152/train_lmdb /home/wy/ResNet152/mean.binaryproto
利用Caffe安装目录下面的compute_image_mean.bin进行图片平均值的计算，输入的是train_lmdb，输出的为mean.binaryproto
二、修改网络配置文件
修改配置之前，先列出需要的文件：train_val.prototxt、deploy.prototxt、solver.prototxt（三个文件的具体内容会在博客最后给出）
1) train_val.prototxt
文件名train_val包括train和val，可以先这样理解每进行500次训练的时候，会进行一次验证，方便输出供训练者观察情况，既然这样，就需要在这个文件里面指定train数据集和val数据集
关于train_val.prototxt中其余部分的代码均是ResNet152的网络结构代码，无需修改
2) deploy.prototxt
deploy.prototxt主要是当模型训练出来以后，利用模型对用户提交的一张图片进行分类应用的时候使用的网络文件，只需要进行一次前向传播计算输入图片所属类别的概率值，所以，此文件里面没有损失函数层的定义
3) solver.prototxt
文件指定训练的相关规则和参数，具体内容介绍见下图中的标注
三、训练网络
网络文件编辑完后，即可开始训练网络，可直接在linux终端输入以下命令
/home/wy/caffe/build/tools/caffe train --solver=/home/wy/ResNet152/solver.prototxt
前者是caffe安装目录路径，后者是solver.prototxt存放路径，回车后即可开始训练；也可创建train.sh脚本文件，文件中保存上述指令
此时，在linux终端(导航到train.sh存放的路径)，输入sh train.sh即可
训练过程中的一张图
四、测试图片
用训练出的model进行图片的预测
/home/wy/caffe/build/examples/cpp_classification/classification.bin /home/wy/ResNet152/deploy.prototxt /home/wy/ResNet152/model/solver_iter_60000.caffemodel /home/wy/ResNet152/mean.binaryproto /home/wy/ResNet152/class_name.txt /home/wy/ResNet152/testImages/ISIC_0000001.jpg
在linux下输入上述命令，即可对图片’ISIC_0000001.jpg’进行预测
其中，class_name.txt文件中内容（和trainx.txt中标签要对应）：
0 bigcat
1 dog
2 fish
测试图片：
看下测试结果（测试的时候换了台电脑,所以发现目录不太一样）：
所以，属于bigcat的概率为0.9999，属于fish的概率为0.0001，属于dog的概率为0
train_val.prototxt
name: "ResNet-152"
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 224
mean_file: "/home/wy/ResNet152/mean.binaryproto"
}
data_param {
source: "/home/wy/ResNet152/train_lmdb"
batch_size: 1
backend: LMDB
}
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
mirror: false
crop_size: 224
mean_file:"/usr/develop/repertory/ResNet152/mean.binaryproto"
}
data_param {
source: "/usr/develop/repertory/ResNet152/val_lmdb"
batch_size: 1
backend: LMDB
}
} layer {
bottom: "data"
top: "conv1"
name: "conv1"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 7
pad: 3
stride: 2
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "conv1"
top: "conv1"
name: "bn_conv1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "conv1"
top: "conv1"
name: "scale_conv1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "conv1"
top: "conv1"
name: "conv1_relu"
type: "ReLU"
} layer {
bottom: "conv1"
top: "pool1"
name: "pool1"
type: "Pooling"
pooling_param {
kernel_size: 3
stride: 2
pool: MAX
}
} layer {
bottom: "pool1"
top: "res2a_branch1"
name: "res2a_branch1"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2a_branch1"
top: "res2a_branch1"
name: "bn2a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2a_branch1"
top: "res2a_branch1"
name: "scale2a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "pool1"
top: "res2a_branch2a"
name: "res2a_branch2a"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2a_branch2a"
top: "res2a_branch2a"
name: "bn2a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2a_branch2a"
top: "res2a_branch2a"
name: "scale2a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2a_branch2a"
top: "res2a_branch2a"
name: "res2a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res2a_branch2a"
top: "res2a_branch2b"
name: "res2a_branch2b"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2a_branch2b"
top: "res2a_branch2b"
name: "bn2a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2a_branch2b"
top: "res2a_branch2b"
name: "scale2a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2a_branch2b"
top: "res2a_branch2b"
name: "res2a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res2a_branch2b"
top: "res2a_branch2c"
name: "res2a_branch2c"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2a_branch2c"
top: "res2a_branch2c"
name: "bn2a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2a_branch2c"
top: "res2a_branch2c"
name: "scale2a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2a_branch1"
bottom: "res2a_branch2c"
top: "res2a"
name: "res2a"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res2a"
top: "res2a"
name: "res2a_relu"
type: "ReLU"
} layer {
bottom: "res2a"
top: "res2b_branch2a"
name: "res2b_branch2a"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2b_branch2a"
top: "res2b_branch2a"
name: "bn2b_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2b_branch2a"
top: "res2b_branch2a"
name: "scale2b_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2b_branch2a"
top: "res2b_branch2a"
name: "res2b_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res2b_branch2a"
top: "res2b_branch2b"
name: "res2b_branch2b"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2b_branch2b"
top: "res2b_branch2b"
name: "bn2b_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2b_branch2b"
top: "res2b_branch2b"
name: "scale2b_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2b_branch2b"
top: "res2b_branch2b"
name: "res2b_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res2b_branch2b"
top: "res2b_branch2c"
name: "res2b_branch2c"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2b_branch2c"
top: "res2b_branch2c"
name: "bn2b_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2b_branch2c"
top: "res2b_branch2c"
name: "scale2b_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2a"
bottom: "res2b_branch2c"
top: "res2b"
name: "res2b"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res2b"
top: "res2b"
name: "res2b_relu"
type: "ReLU"
} layer {
bottom: "res2b"
top: "res2c_branch2a"
name: "res2c_branch2a"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2c_branch2a"
top: "res2c_branch2a"
name: "bn2c_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2c_branch2a"
top: "res2c_branch2a"
name: "scale2c_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2c_branch2a"
top: "res2c_branch2a"
name: "res2c_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res2c_branch2a"
top: "res2c_branch2b"
name: "res2c_branch2b"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2c_branch2b"
top: "res2c_branch2b"
name: "bn2c_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2c_branch2b"
top: "res2c_branch2b"
name: "scale2c_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2c_branch2b"
top: "res2c_branch2b"
name: "res2c_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res2c_branch2b"
top: "res2c_branch2c"
name: "res2c_branch2c"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res2c_branch2c"
top: "res2c_branch2c"
name: "bn2c_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res2c_branch2c"
top: "res2c_branch2c"
name: "scale2c_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2b"
bottom: "res2c_branch2c"
top: "res2c"
name: "res2c"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res2c"
top: "res2c"
name: "res2c_relu"
type: "ReLU"
} layer {
bottom: "res2c"
top: "res3a_branch1"
name: "res3a_branch1"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3a_branch1"
top: "res3a_branch1"
name: "bn3a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3a_branch1"
top: "res3a_branch1"
name: "scale3a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2c"
top: "res3a_branch2a"
name: "res3a_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3a_branch2a"
top: "res3a_branch2a"
name: "bn3a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3a_branch2a"
top: "res3a_branch2a"
name: "scale3a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3a_branch2a"
top: "res3a_branch2a"
name: "res3a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3a_branch2a"
top: "res3a_branch2b"
name: "res3a_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3a_branch2b"
top: "res3a_branch2b"
name: "bn3a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3a_branch2b"
top: "res3a_branch2b"
name: "scale3a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3a_branch2b"
top: "res3a_branch2b"
name: "res3a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3a_branch2b"
top: "res3a_branch2c"
name: "res3a_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3a_branch2c"
top: "res3a_branch2c"
name: "bn3a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3a_branch2c"
top: "res3a_branch2c"
name: "scale3a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3a_branch1"
bottom: "res3a_branch2c"
top: "res3a"
name: "res3a"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3a"
top: "res3a"
name: "res3a_relu"
type: "ReLU"
} layer {
bottom: "res3a"
top: "res3b1_branch2a"
name: "res3b1_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b1_branch2a"
top: "res3b1_branch2a"
name: "bn3b1_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b1_branch2a"
top: "res3b1_branch2a"
name: "scale3b1_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b1_branch2a"
top: "res3b1_branch2a"
name: "res3b1_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b1_branch2a"
top: "res3b1_branch2b"
name: "res3b1_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b1_branch2b"
top: "res3b1_branch2b"
name: "bn3b1_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b1_branch2b"
top: "res3b1_branch2b"
name: "scale3b1_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b1_branch2b"
top: "res3b1_branch2b"
name: "res3b1_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b1_branch2b"
top: "res3b1_branch2c"
name: "res3b1_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b1_branch2c"
top: "res3b1_branch2c"
name: "bn3b1_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b1_branch2c"
top: "res3b1_branch2c"
name: "scale3b1_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3a"
bottom: "res3b1_branch2c"
top: "res3b1"
name: "res3b1"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3b1"
top: "res3b1"
name: "res3b1_relu"
type: "ReLU"
} layer {
bottom: "res3b1"
top: "res3b2_branch2a"
name: "res3b2_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b2_branch2a"
top: "res3b2_branch2a"
name: "bn3b2_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b2_branch2a"
top: "res3b2_branch2a"
name: "scale3b2_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b2_branch2a"
top: "res3b2_branch2a"
name: "res3b2_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b2_branch2a"
top: "res3b2_branch2b"
name: "res3b2_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b2_branch2b"
top: "res3b2_branch2b"
name: "bn3b2_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b2_branch2b"
top: "res3b2_branch2b"
name: "scale3b2_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b2_branch2b"
top: "res3b2_branch2b"
name: "res3b2_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b2_branch2b"
top: "res3b2_branch2c"
name: "res3b2_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b2_branch2c"
top: "res3b2_branch2c"
name: "bn3b2_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b2_branch2c"
top: "res3b2_branch2c"
name: "scale3b2_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b1"
bottom: "res3b2_branch2c"
top: "res3b2"
name: "res3b2"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3b2"
top: "res3b2"
name: "res3b2_relu"
type: "ReLU"
} layer {
bottom: "res3b2"
top: "res3b3_branch2a"
name: "res3b3_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b3_branch2a"
top: "res3b3_branch2a"
name: "bn3b3_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b3_branch2a"
top: "res3b3_branch2a"
name: "scale3b3_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b3_branch2a"
top: "res3b3_branch2a"
name: "res3b3_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b3_branch2a"
top: "res3b3_branch2b"
name: "res3b3_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b3_branch2b"
top: "res3b3_branch2b"
name: "bn3b3_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b3_branch2b"
top: "res3b3_branch2b"
name: "scale3b3_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b3_branch2b"
top: "res3b3_branch2b"
name: "res3b3_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b3_branch2b"
top: "res3b3_branch2c"
name: "res3b3_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b3_branch2c"
top: "res3b3_branch2c"
name: "bn3b3_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b3_branch2c"
top: "res3b3_branch2c"
name: "scale3b3_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b2"
bottom: "res3b3_branch2c"
top: "res3b3"
name: "res3b3"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3b3"
top: "res3b3"
name: "res3b3_relu"
type: "ReLU"
} layer {
bottom: "res3b3"
top: "res3b4_branch2a"
name: "res3b4_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b4_branch2a"
top: "res3b4_branch2a"
name: "bn3b4_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b4_branch2a"
top: "res3b4_branch2a"
name: "scale3b4_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b4_branch2a"
top: "res3b4_branch2a"
name: "res3b4_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b4_branch2a"
top: "res3b4_branch2b"
name: "res3b4_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b4_branch2b"
top: "res3b4_branch2b"
name: "bn3b4_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b4_branch2b"
top: "res3b4_branch2b"
name: "scale3b4_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b4_branch2b"
top: "res3b4_branch2b"
name: "res3b4_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b4_branch2b"
top: "res3b4_branch2c"
name: "res3b4_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b4_branch2c"
top: "res3b4_branch2c"
name: "bn3b4_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b4_branch2c"
top: "res3b4_branch2c"
name: "scale3b4_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b3"
bottom: "res3b4_branch2c"
top: "res3b4"
name: "res3b4"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3b4"
top: "res3b4"
name: "res3b4_relu"
type: "ReLU"
} layer {
bottom: "res3b4"
top: "res3b5_branch2a"
name: "res3b5_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b5_branch2a"
top: "res3b5_branch2a"
name: "bn3b5_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b5_branch2a"
top: "res3b5_branch2a"
name: "scale3b5_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b5_branch2a"
top: "res3b5_branch2a"
name: "res3b5_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b5_branch2a"
top: "res3b5_branch2b"
name: "res3b5_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b5_branch2b"
top: "res3b5_branch2b"
name: "bn3b5_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b5_branch2b"
top: "res3b5_branch2b"
name: "scale3b5_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b5_branch2b"
top: "res3b5_branch2b"
name: "res3b5_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b5_branch2b"
top: "res3b5_branch2c"
name: "res3b5_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b5_branch2c"
top: "res3b5_branch2c"
name: "bn3b5_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b5_branch2c"
top: "res3b5_branch2c"
name: "scale3b5_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b4"
bottom: "res3b5_branch2c"
top: "res3b5"
name: "res3b5"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3b5"
top: "res3b5"
name: "res3b5_relu"
type: "ReLU"
} layer {
bottom: "res3b5"
top: "res3b6_branch2a"
name: "res3b6_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b6_branch2a"
top: "res3b6_branch2a"
name: "bn3b6_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b6_branch2a"
top: "res3b6_branch2a"
name: "scale3b6_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b6_branch2a"
top: "res3b6_branch2a"
name: "res3b6_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b6_branch2a"
top: "res3b6_branch2b"
name: "res3b6_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b6_branch2b"
top: "res3b6_branch2b"
name: "bn3b6_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b6_branch2b"
top: "res3b6_branch2b"
name: "scale3b6_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b6_branch2b"
top: "res3b6_branch2b"
name: "res3b6_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b6_branch2b"
top: "res3b6_branch2c"
name: "res3b6_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b6_branch2c"
top: "res3b6_branch2c"
name: "bn3b6_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b6_branch2c"
top: "res3b6_branch2c"
name: "scale3b6_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b5"
bottom: "res3b6_branch2c"
top: "res3b6"
name: "res3b6"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3b6"
top: "res3b6"
name: "res3b6_relu"
type: "ReLU"
} layer {
bottom: "res3b6"
top: "res3b7_branch2a"
name: "res3b7_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b7_branch2a"
top: "res3b7_branch2a"
name: "bn3b7_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b7_branch2a"
top: "res3b7_branch2a"
name: "scale3b7_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b7_branch2a"
top: "res3b7_branch2a"
name: "res3b7_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b7_branch2a"
top: "res3b7_branch2b"
name: "res3b7_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b7_branch2b"
top: "res3b7_branch2b"
name: "bn3b7_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b7_branch2b"
top: "res3b7_branch2b"
name: "scale3b7_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b7_branch2b"
top: "res3b7_branch2b"
name: "res3b7_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b7_branch2b"
top: "res3b7_branch2c"
name: "res3b7_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res3b7_branch2c"
top: "res3b7_branch2c"
name: "bn3b7_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res3b7_branch2c"
top: "res3b7_branch2c"
name: "scale3b7_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b6"
bottom: "res3b7_branch2c"
top: "res3b7"
name: "res3b7"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res3b7"
top: "res3b7"
name: "res3b7_relu"
type: "ReLU"
} layer {
bottom: "res3b7"
top: "res4a_branch1"
name: "res4a_branch1"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4a_branch1"
top: "res4a_branch1"
name: "bn4a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4a_branch1"
top: "res4a_branch1"
name: "scale4a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b7"
top: "res4a_branch2a"
name: "res4a_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4a_branch2a"
top: "res4a_branch2a"
name: "bn4a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4a_branch2a"
top: "res4a_branch2a"
name: "scale4a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4a_branch2a"
top: "res4a_branch2a"
name: "res4a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4a_branch2a"
top: "res4a_branch2b"
name: "res4a_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4a_branch2b"
top: "res4a_branch2b"
name: "bn4a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4a_branch2b"
top: "res4a_branch2b"
name: "scale4a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4a_branch2b"
top: "res4a_branch2b"
name: "res4a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4a_branch2b"
top: "res4a_branch2c"
name: "res4a_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4a_branch2c"
top: "res4a_branch2c"
name: "bn4a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4a_branch2c"
top: "res4a_branch2c"
name: "scale4a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4a_branch1"
bottom: "res4a_branch2c"
top: "res4a"
name: "res4a"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4a"
top: "res4a"
name: "res4a_relu"
type: "ReLU"
} layer {
bottom: "res4a"
top: "res4b1_branch2a"
name: "res4b1_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b1_branch2a"
top: "res4b1_branch2a"
name: "bn4b1_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b1_branch2a"
top: "res4b1_branch2a"
name: "scale4b1_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b1_branch2a"
top: "res4b1_branch2a"
name: "res4b1_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b1_branch2a"
top: "res4b1_branch2b"
name: "res4b1_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b1_branch2b"
top: "res4b1_branch2b"
name: "bn4b1_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b1_branch2b"
top: "res4b1_branch2b"
name: "scale4b1_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b1_branch2b"
top: "res4b1_branch2b"
name: "res4b1_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b1_branch2b"
top: "res4b1_branch2c"
name: "res4b1_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b1_branch2c"
top: "res4b1_branch2c"
name: "bn4b1_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b1_branch2c"
top: "res4b1_branch2c"
name: "scale4b1_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4a"
bottom: "res4b1_branch2c"
top: "res4b1"
name: "res4b1"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b1"
top: "res4b1"
name: "res4b1_relu"
type: "ReLU"
} layer {
bottom: "res4b1"
top: "res4b2_branch2a"
name: "res4b2_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b2_branch2a"
top: "res4b2_branch2a"
name: "bn4b2_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b2_branch2a"
top: "res4b2_branch2a"
name: "scale4b2_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b2_branch2a"
top: "res4b2_branch2a"
name: "res4b2_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b2_branch2a"
top: "res4b2_branch2b"
name: "res4b2_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b2_branch2b"
top: "res4b2_branch2b"
name: "bn4b2_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b2_branch2b"
top: "res4b2_branch2b"
name: "scale4b2_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b2_branch2b"
top: "res4b2_branch2b"
name: "res4b2_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b2_branch2b"
top: "res4b2_branch2c"
name: "res4b2_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b2_branch2c"
top: "res4b2_branch2c"
name: "bn4b2_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b2_branch2c"
top: "res4b2_branch2c"
name: "scale4b2_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b1"
bottom: "res4b2_branch2c"
top: "res4b2"
name: "res4b2"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b2"
top: "res4b2"
name: "res4b2_relu"
type: "ReLU"
} layer {
bottom: "res4b2"
top: "res4b3_branch2a"
name: "res4b3_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b3_branch2a"
top: "res4b3_branch2a"
name: "bn4b3_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b3_branch2a"
top: "res4b3_branch2a"
name: "scale4b3_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b3_branch2a"
top: "res4b3_branch2a"
name: "res4b3_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b3_branch2a"
top: "res4b3_branch2b"
name: "res4b3_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b3_branch2b"
top: "res4b3_branch2b"
name: "bn4b3_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b3_branch2b"
top: "res4b3_branch2b"
name: "scale4b3_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b3_branch2b"
top: "res4b3_branch2b"
name: "res4b3_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b3_branch2b"
top: "res4b3_branch2c"
name: "res4b3_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b3_branch2c"
top: "res4b3_branch2c"
name: "bn4b3_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b3_branch2c"
top: "res4b3_branch2c"
name: "scale4b3_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b2"
bottom: "res4b3_branch2c"
top: "res4b3"
name: "res4b3"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b3"
top: "res4b3"
name: "res4b3_relu"
type: "ReLU"
} layer {
bottom: "res4b3"
top: "res4b4_branch2a"
name: "res4b4_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b4_branch2a"
top: "res4b4_branch2a"
name: "bn4b4_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b4_branch2a"
top: "res4b4_branch2a"
name: "scale4b4_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b4_branch2a"
top: "res4b4_branch2a"
name: "res4b4_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b4_branch2a"
top: "res4b4_branch2b"
name: "res4b4_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b4_branch2b"
top: "res4b4_branch2b"
name: "bn4b4_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b4_branch2b"
top: "res4b4_branch2b"
name: "scale4b4_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b4_branch2b"
top: "res4b4_branch2b"
name: "res4b4_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b4_branch2b"
top: "res4b4_branch2c"
name: "res4b4_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b4_branch2c"
top: "res4b4_branch2c"
name: "bn4b4_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b4_branch2c"
top: "res4b4_branch2c"
name: "scale4b4_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b3"
bottom: "res4b4_branch2c"
top: "res4b4"
name: "res4b4"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b4"
top: "res4b4"
name: "res4b4_relu"
type: "ReLU"
} layer {
bottom: "res4b4"
top: "res4b5_branch2a"
name: "res4b5_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b5_branch2a"
top: "res4b5_branch2a"
name: "bn4b5_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b5_branch2a"
top: "res4b5_branch2a"
name: "scale4b5_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b5_branch2a"
top: "res4b5_branch2a"
name: "res4b5_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b5_branch2a"
top: "res4b5_branch2b"
name: "res4b5_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b5_branch2b"
top: "res4b5_branch2b"
name: "bn4b5_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b5_branch2b"
top: "res4b5_branch2b"
name: "scale4b5_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b5_branch2b"
top: "res4b5_branch2b"
name: "res4b5_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b5_branch2b"
top: "res4b5_branch2c"
name: "res4b5_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b5_branch2c"
top: "res4b5_branch2c"
name: "bn4b5_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b5_branch2c"
top: "res4b5_branch2c"
name: "scale4b5_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b4"
bottom: "res4b5_branch2c"
top: "res4b5"
name: "res4b5"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b5"
top: "res4b5"
name: "res4b5_relu"
type: "ReLU"
} layer {
bottom: "res4b5"
top: "res4b6_branch2a"
name: "res4b6_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b6_branch2a"
top: "res4b6_branch2a"
name: "bn4b6_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b6_branch2a"
top: "res4b6_branch2a"
name: "scale4b6_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b6_branch2a"
top: "res4b6_branch2a"
name: "res4b6_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b6_branch2a"
top: "res4b6_branch2b"
name: "res4b6_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b6_branch2b"
top: "res4b6_branch2b"
name: "bn4b6_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b6_branch2b"
top: "res4b6_branch2b"
name: "scale4b6_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b6_branch2b"
top: "res4b6_branch2b"
name: "res4b6_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b6_branch2b"
top: "res4b6_branch2c"
name: "res4b6_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b6_branch2c"
top: "res4b6_branch2c"
name: "bn4b6_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b6_branch2c"
top: "res4b6_branch2c"
name: "scale4b6_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b5"
bottom: "res4b6_branch2c"
top: "res4b6"
name: "res4b6"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b6"
top: "res4b6"
name: "res4b6_relu"
type: "ReLU"
} layer {
bottom: "res4b6"
top: "res4b7_branch2a"
name: "res4b7_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b7_branch2a"
top: "res4b7_branch2a"
name: "bn4b7_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b7_branch2a"
top: "res4b7_branch2a"
name: "scale4b7_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b7_branch2a"
top: "res4b7_branch2a"
name: "res4b7_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b7_branch2a"
top: "res4b7_branch2b"
name: "res4b7_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b7_branch2b"
top: "res4b7_branch2b"
name: "bn4b7_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b7_branch2b"
top: "res4b7_branch2b"
name: "scale4b7_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b7_branch2b"
top: "res4b7_branch2b"
name: "res4b7_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b7_branch2b"
top: "res4b7_branch2c"
name: "res4b7_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b7_branch2c"
top: "res4b7_branch2c"
name: "bn4b7_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b7_branch2c"
top: "res4b7_branch2c"
name: "scale4b7_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b6"
bottom: "res4b7_branch2c"
top: "res4b7"
name: "res4b7"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b7"
top: "res4b7"
name: "res4b7_relu"
type: "ReLU"
} layer {
bottom: "res4b7"
top: "res4b8_branch2a"
name: "res4b8_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b8_branch2a"
top: "res4b8_branch2a"
name: "bn4b8_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b8_branch2a"
top: "res4b8_branch2a"
name: "scale4b8_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b8_branch2a"
top: "res4b8_branch2a"
name: "res4b8_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b8_branch2a"
top: "res4b8_branch2b"
name: "res4b8_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b8_branch2b"
top: "res4b8_branch2b"
name: "bn4b8_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b8_branch2b"
top: "res4b8_branch2b"
name: "scale4b8_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b8_branch2b"
top: "res4b8_branch2b"
name: "res4b8_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b8_branch2b"
top: "res4b8_branch2c"
name: "res4b8_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b8_branch2c"
top: "res4b8_branch2c"
name: "bn4b8_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b8_branch2c"
top: "res4b8_branch2c"
name: "scale4b8_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b7"
bottom: "res4b8_branch2c"
top: "res4b8"
name: "res4b8"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b8"
top: "res4b8"
name: "res4b8_relu"
type: "ReLU"
} layer {
bottom: "res4b8"
top: "res4b9_branch2a"
name: "res4b9_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b9_branch2a"
top: "res4b9_branch2a"
name: "bn4b9_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b9_branch2a"
top: "res4b9_branch2a"
name: "scale4b9_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b9_branch2a"
top: "res4b9_branch2a"
name: "res4b9_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b9_branch2a"
top: "res4b9_branch2b"
name: "res4b9_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b9_branch2b"
top: "res4b9_branch2b"
name: "bn4b9_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b9_branch2b"
top: "res4b9_branch2b"
name: "scale4b9_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b9_branch2b"
top: "res4b9_branch2b"
name: "res4b9_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b9_branch2b"
top: "res4b9_branch2c"
name: "res4b9_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b9_branch2c"
top: "res4b9_branch2c"
name: "bn4b9_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b9_branch2c"
top: "res4b9_branch2c"
name: "scale4b9_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b8"
bottom: "res4b9_branch2c"
top: "res4b9"
name: "res4b9"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b9"
top: "res4b9"
name: "res4b9_relu"
type: "ReLU"
} layer {
bottom: "res4b9"
top: "res4b10_branch2a"
name: "res4b10_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b10_branch2a"
top: "res4b10_branch2a"
name: "bn4b10_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b10_branch2a"
top: "res4b10_branch2a"
name: "scale4b10_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b10_branch2a"
top: "res4b10_branch2a"
name: "res4b10_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b10_branch2a"
top: "res4b10_branch2b"
name: "res4b10_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b10_branch2b"
top: "res4b10_branch2b"
name: "bn4b10_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b10_branch2b"
top: "res4b10_branch2b"
name: "scale4b10_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b10_branch2b"
top: "res4b10_branch2b"
name: "res4b10_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b10_branch2b"
top: "res4b10_branch2c"
name: "res4b10_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b10_branch2c"
top: "res4b10_branch2c"
name: "bn4b10_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b10_branch2c"
top: "res4b10_branch2c"
name: "scale4b10_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b9"
bottom: "res4b10_branch2c"
top: "res4b10"
name: "res4b10"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b10"
top: "res4b10"
name: "res4b10_relu"
type: "ReLU"
} layer {
bottom: "res4b10"
top: "res4b11_branch2a"
name: "res4b11_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b11_branch2a"
top: "res4b11_branch2a"
name: "bn4b11_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b11_branch2a"
top: "res4b11_branch2a"
name: "scale4b11_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b11_branch2a"
top: "res4b11_branch2a"
name: "res4b11_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b11_branch2a"
top: "res4b11_branch2b"
name: "res4b11_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b11_branch2b"
top: "res4b11_branch2b"
name: "bn4b11_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b11_branch2b"
top: "res4b11_branch2b"
name: "scale4b11_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b11_branch2b"
top: "res4b11_branch2b"
name: "res4b11_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b11_branch2b"
top: "res4b11_branch2c"
name: "res4b11_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b11_branch2c"
top: "res4b11_branch2c"
name: "bn4b11_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b11_branch2c"
top: "res4b11_branch2c"
name: "scale4b11_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b10"
bottom: "res4b11_branch2c"
top: "res4b11"
name: "res4b11"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b11"
top: "res4b11"
name: "res4b11_relu"
type: "ReLU"
} layer {
bottom: "res4b11"
top: "res4b12_branch2a"
name: "res4b12_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b12_branch2a"
top: "res4b12_branch2a"
name: "bn4b12_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b12_branch2a"
top: "res4b12_branch2a"
name: "scale4b12_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b12_branch2a"
top: "res4b12_branch2a"
name: "res4b12_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b12_branch2a"
top: "res4b12_branch2b"
name: "res4b12_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b12_branch2b"
top: "res4b12_branch2b"
name: "bn4b12_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b12_branch2b"
top: "res4b12_branch2b"
name: "scale4b12_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b12_branch2b"
top: "res4b12_branch2b"
name: "res4b12_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b12_branch2b"
top: "res4b12_branch2c"
name: "res4b12_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b12_branch2c"
top: "res4b12_branch2c"
name: "bn4b12_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b12_branch2c"
top: "res4b12_branch2c"
name: "scale4b12_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b11"
bottom: "res4b12_branch2c"
top: "res4b12"
name: "res4b12"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b12"
top: "res4b12"
name: "res4b12_relu"
type: "ReLU"
} layer {
bottom: "res4b12"
top: "res4b13_branch2a"
name: "res4b13_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b13_branch2a"
top: "res4b13_branch2a"
name: "bn4b13_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b13_branch2a"
top: "res4b13_branch2a"
name: "scale4b13_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b13_branch2a"
top: "res4b13_branch2a"
name: "res4b13_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b13_branch2a"
top: "res4b13_branch2b"
name: "res4b13_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b13_branch2b"
top: "res4b13_branch2b"
name: "bn4b13_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b13_branch2b"
top: "res4b13_branch2b"
name: "scale4b13_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b13_branch2b"
top: "res4b13_branch2b"
name: "res4b13_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b13_branch2b"
top: "res4b13_branch2c"
name: "res4b13_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b13_branch2c"
top: "res4b13_branch2c"
name: "bn4b13_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b13_branch2c"
top: "res4b13_branch2c"
name: "scale4b13_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b12"
bottom: "res4b13_branch2c"
top: "res4b13"
name: "res4b13"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b13"
top: "res4b13"
name: "res4b13_relu"
type: "ReLU"
} layer {
bottom: "res4b13"
top: "res4b14_branch2a"
name: "res4b14_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b14_branch2a"
top: "res4b14_branch2a"
name: "bn4b14_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b14_branch2a"
top: "res4b14_branch2a"
name: "scale4b14_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b14_branch2a"
top: "res4b14_branch2a"
name: "res4b14_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b14_branch2a"
top: "res4b14_branch2b"
name: "res4b14_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b14_branch2b"
top: "res4b14_branch2b"
name: "bn4b14_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b14_branch2b"
top: "res4b14_branch2b"
name: "scale4b14_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b14_branch2b"
top: "res4b14_branch2b"
name: "res4b14_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b14_branch2b"
top: "res4b14_branch2c"
name: "res4b14_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b14_branch2c"
top: "res4b14_branch2c"
name: "bn4b14_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b14_branch2c"
top: "res4b14_branch2c"
name: "scale4b14_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b13"
bottom: "res4b14_branch2c"
top: "res4b14"
name: "res4b14"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b14"
top: "res4b14"
name: "res4b14_relu"
type: "ReLU"
} layer {
bottom: "res4b14"
top: "res4b15_branch2a"
name: "res4b15_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b15_branch2a"
top: "res4b15_branch2a"
name: "bn4b15_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b15_branch2a"
top: "res4b15_branch2a"
name: "scale4b15_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b15_branch2a"
top: "res4b15_branch2a"
name: "res4b15_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b15_branch2a"
top: "res4b15_branch2b"
name: "res4b15_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b15_branch2b"
top: "res4b15_branch2b"
name: "bn4b15_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b15_branch2b"
top: "res4b15_branch2b"
name: "scale4b15_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b15_branch2b"
top: "res4b15_branch2b"
name: "res4b15_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b15_branch2b"
top: "res4b15_branch2c"
name: "res4b15_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b15_branch2c"
top: "res4b15_branch2c"
name: "bn4b15_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b15_branch2c"
top: "res4b15_branch2c"
name: "scale4b15_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b14"
bottom: "res4b15_branch2c"
top: "res4b15"
name: "res4b15"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b15"
top: "res4b15"
name: "res4b15_relu"
type: "ReLU"
} layer {
bottom: "res4b15"
top: "res4b16_branch2a"
name: "res4b16_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b16_branch2a"
top: "res4b16_branch2a"
name: "bn4b16_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b16_branch2a"
top: "res4b16_branch2a"
name: "scale4b16_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b16_branch2a"
top: "res4b16_branch2a"
name: "res4b16_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b16_branch2a"
top: "res4b16_branch2b"
name: "res4b16_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b16_branch2b"
top: "res4b16_branch2b"
name: "bn4b16_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b16_branch2b"
top: "res4b16_branch2b"
name: "scale4b16_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b16_branch2b"
top: "res4b16_branch2b"
name: "res4b16_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b16_branch2b"
top: "res4b16_branch2c"
name: "res4b16_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b16_branch2c"
top: "res4b16_branch2c"
name: "bn4b16_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b16_branch2c"
top: "res4b16_branch2c"
name: "scale4b16_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b15"
bottom: "res4b16_branch2c"
top: "res4b16"
name: "res4b16"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b16"
top: "res4b16"
name: "res4b16_relu"
type: "ReLU"
} layer {
bottom: "res4b16"
top: "res4b17_branch2a"
name: "res4b17_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b17_branch2a"
top: "res4b17_branch2a"
name: "bn4b17_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b17_branch2a"
top: "res4b17_branch2a"
name: "scale4b17_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b17_branch2a"
top: "res4b17_branch2a"
name: "res4b17_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b17_branch2a"
top: "res4b17_branch2b"
name: "res4b17_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b17_branch2b"
top: "res4b17_branch2b"
name: "bn4b17_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b17_branch2b"
top: "res4b17_branch2b"
name: "scale4b17_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b17_branch2b"
top: "res4b17_branch2b"
name: "res4b17_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b17_branch2b"
top: "res4b17_branch2c"
name: "res4b17_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b17_branch2c"
top: "res4b17_branch2c"
name: "bn4b17_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b17_branch2c"
top: "res4b17_branch2c"
name: "scale4b17_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b16"
bottom: "res4b17_branch2c"
top: "res4b17"
name: "res4b17"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b17"
top: "res4b17"
name: "res4b17_relu"
type: "ReLU"
} layer {
bottom: "res4b17"
top: "res4b18_branch2a"
name: "res4b18_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b18_branch2a"
top: "res4b18_branch2a"
name: "bn4b18_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b18_branch2a"
top: "res4b18_branch2a"
name: "scale4b18_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b18_branch2a"
top: "res4b18_branch2a"
name: "res4b18_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b18_branch2a"
top: "res4b18_branch2b"
name: "res4b18_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b18_branch2b"
top: "res4b18_branch2b"
name: "bn4b18_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b18_branch2b"
top: "res4b18_branch2b"
name: "scale4b18_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b18_branch2b"
top: "res4b18_branch2b"
name: "res4b18_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b18_branch2b"
top: "res4b18_branch2c"
name: "res4b18_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b18_branch2c"
top: "res4b18_branch2c"
name: "bn4b18_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b18_branch2c"
top: "res4b18_branch2c"
name: "scale4b18_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b17"
bottom: "res4b18_branch2c"
top: "res4b18"
name: "res4b18"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b18"
top: "res4b18"
name: "res4b18_relu"
type: "ReLU"
} layer {
bottom: "res4b18"
top: "res4b19_branch2a"
name: "res4b19_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b19_branch2a"
top: "res4b19_branch2a"
name: "bn4b19_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b19_branch2a"
top: "res4b19_branch2a"
name: "scale4b19_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b19_branch2a"
top: "res4b19_branch2a"
name: "res4b19_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b19_branch2a"
top: "res4b19_branch2b"
name: "res4b19_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b19_branch2b"
top: "res4b19_branch2b"
name: "bn4b19_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b19_branch2b"
top: "res4b19_branch2b"
name: "scale4b19_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b19_branch2b"
top: "res4b19_branch2b"
name: "res4b19_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b19_branch2b"
top: "res4b19_branch2c"
name: "res4b19_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b19_branch2c"
top: "res4b19_branch2c"
name: "bn4b19_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b19_branch2c"
top: "res4b19_branch2c"
name: "scale4b19_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b18"
bottom: "res4b19_branch2c"
top: "res4b19"
name: "res4b19"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b19"
top: "res4b19"
name: "res4b19_relu"
type: "ReLU"
} layer {
bottom: "res4b19"
top: "res4b20_branch2a"
name: "res4b20_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b20_branch2a"
top: "res4b20_branch2a"
name: "bn4b20_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b20_branch2a"
top: "res4b20_branch2a"
name: "scale4b20_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b20_branch2a"
top: "res4b20_branch2a"
name: "res4b20_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b20_branch2a"
top: "res4b20_branch2b"
name: "res4b20_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b20_branch2b"
top: "res4b20_branch2b"
name: "bn4b20_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b20_branch2b"
top: "res4b20_branch2b"
name: "scale4b20_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b20_branch2b"
top: "res4b20_branch2b"
name: "res4b20_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b20_branch2b"
top: "res4b20_branch2c"
name: "res4b20_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b20_branch2c"
top: "res4b20_branch2c"
name: "bn4b20_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b20_branch2c"
top: "res4b20_branch2c"
name: "scale4b20_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b19"
bottom: "res4b20_branch2c"
top: "res4b20"
name: "res4b20"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b20"
top: "res4b20"
name: "res4b20_relu"
type: "ReLU"
} layer {
bottom: "res4b20"
top: "res4b21_branch2a"
name: "res4b21_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b21_branch2a"
top: "res4b21_branch2a"
name: "bn4b21_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b21_branch2a"
top: "res4b21_branch2a"
name: "scale4b21_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b21_branch2a"
top: "res4b21_branch2a"
name: "res4b21_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b21_branch2a"
top: "res4b21_branch2b"
name: "res4b21_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b21_branch2b"
top: "res4b21_branch2b"
name: "bn4b21_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b21_branch2b"
top: "res4b21_branch2b"
name: "scale4b21_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b21_branch2b"
top: "res4b21_branch2b"
name: "res4b21_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b21_branch2b"
top: "res4b21_branch2c"
name: "res4b21_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b21_branch2c"
top: "res4b21_branch2c"
name: "bn4b21_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b21_branch2c"
top: "res4b21_branch2c"
name: "scale4b21_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b20"
bottom: "res4b21_branch2c"
top: "res4b21"
name: "res4b21"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b21"
top: "res4b21"
name: "res4b21_relu"
type: "ReLU"
} layer {
bottom: "res4b21"
top: "res4b22_branch2a"
name: "res4b22_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b22_branch2a"
top: "res4b22_branch2a"
name: "bn4b22_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b22_branch2a"
top: "res4b22_branch2a"
name: "scale4b22_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b22_branch2a"
top: "res4b22_branch2a"
name: "res4b22_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b22_branch2a"
top: "res4b22_branch2b"
name: "res4b22_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b22_branch2b"
top: "res4b22_branch2b"
name: "bn4b22_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b22_branch2b"
top: "res4b22_branch2b"
name: "scale4b22_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b22_branch2b"
top: "res4b22_branch2b"
name: "res4b22_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b22_branch2b"
top: "res4b22_branch2c"
name: "res4b22_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b22_branch2c"
top: "res4b22_branch2c"
name: "bn4b22_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b22_branch2c"
top: "res4b22_branch2c"
name: "scale4b22_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b21"
bottom: "res4b22_branch2c"
top: "res4b22"
name: "res4b22"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b22"
top: "res4b22"
name: "res4b22_relu"
type: "ReLU"
} layer {
bottom: "res4b22"
top: "res4b23_branch2a"
name: "res4b23_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b23_branch2a"
top: "res4b23_branch2a"
name: "bn4b23_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b23_branch2a"
top: "res4b23_branch2a"
name: "scale4b23_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b23_branch2a"
top: "res4b23_branch2a"
name: "res4b23_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b23_branch2a"
top: "res4b23_branch2b"
name: "res4b23_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b23_branch2b"
top: "res4b23_branch2b"
name: "bn4b23_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b23_branch2b"
top: "res4b23_branch2b"
name: "scale4b23_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b23_branch2b"
top: "res4b23_branch2b"
name: "res4b23_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b23_branch2b"
top: "res4b23_branch2c"
name: "res4b23_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b23_branch2c"
top: "res4b23_branch2c"
name: "bn4b23_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b23_branch2c"
top: "res4b23_branch2c"
name: "scale4b23_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b22"
bottom: "res4b23_branch2c"
top: "res4b23"
name: "res4b23"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b23"
top: "res4b23"
name: "res4b23_relu"
type: "ReLU"
} layer {
bottom: "res4b23"
top: "res4b24_branch2a"
name: "res4b24_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b24_branch2a"
top: "res4b24_branch2a"
name: "bn4b24_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b24_branch2a"
top: "res4b24_branch2a"
name: "scale4b24_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b24_branch2a"
top: "res4b24_branch2a"
name: "res4b24_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b24_branch2a"
top: "res4b24_branch2b"
name: "res4b24_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b24_branch2b"
top: "res4b24_branch2b"
name: "bn4b24_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b24_branch2b"
top: "res4b24_branch2b"
name: "scale4b24_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b24_branch2b"
top: "res4b24_branch2b"
name: "res4b24_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b24_branch2b"
top: "res4b24_branch2c"
name: "res4b24_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b24_branch2c"
top: "res4b24_branch2c"
name: "bn4b24_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b24_branch2c"
top: "res4b24_branch2c"
name: "scale4b24_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b23"
bottom: "res4b24_branch2c"
top: "res4b24"
name: "res4b24"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b24"
top: "res4b24"
name: "res4b24_relu"
type: "ReLU"
} layer {
bottom: "res4b24"
top: "res4b25_branch2a"
name: "res4b25_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b25_branch2a"
top: "res4b25_branch2a"
name: "bn4b25_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b25_branch2a"
top: "res4b25_branch2a"
name: "scale4b25_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b25_branch2a"
top: "res4b25_branch2a"
name: "res4b25_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b25_branch2a"
top: "res4b25_branch2b"
name: "res4b25_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b25_branch2b"
top: "res4b25_branch2b"
name: "bn4b25_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b25_branch2b"
top: "res4b25_branch2b"
name: "scale4b25_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b25_branch2b"
top: "res4b25_branch2b"
name: "res4b25_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b25_branch2b"
top: "res4b25_branch2c"
name: "res4b25_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b25_branch2c"
top: "res4b25_branch2c"
name: "bn4b25_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b25_branch2c"
top: "res4b25_branch2c"
name: "scale4b25_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b24"
bottom: "res4b25_branch2c"
top: "res4b25"
name: "res4b25"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b25"
top: "res4b25"
name: "res4b25_relu"
type: "ReLU"
} layer {
bottom: "res4b25"
top: "res4b26_branch2a"
name: "res4b26_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b26_branch2a"
top: "res4b26_branch2a"
name: "bn4b26_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b26_branch2a"
top: "res4b26_branch2a"
name: "scale4b26_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b26_branch2a"
top: "res4b26_branch2a"
name: "res4b26_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b26_branch2a"
top: "res4b26_branch2b"
name: "res4b26_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b26_branch2b"
top: "res4b26_branch2b"
name: "bn4b26_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b26_branch2b"
top: "res4b26_branch2b"
name: "scale4b26_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b26_branch2b"
top: "res4b26_branch2b"
name: "res4b26_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b26_branch2b"
top: "res4b26_branch2c"
name: "res4b26_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b26_branch2c"
top: "res4b26_branch2c"
name: "bn4b26_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b26_branch2c"
top: "res4b26_branch2c"
name: "scale4b26_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b25"
bottom: "res4b26_branch2c"
top: "res4b26"
name: "res4b26"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b26"
top: "res4b26"
name: "res4b26_relu"
type: "ReLU"
} layer {
bottom: "res4b26"
top: "res4b27_branch2a"
name: "res4b27_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b27_branch2a"
top: "res4b27_branch2a"
name: "bn4b27_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b27_branch2a"
top: "res4b27_branch2a"
name: "scale4b27_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b27_branch2a"
top: "res4b27_branch2a"
name: "res4b27_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b27_branch2a"
top: "res4b27_branch2b"
name: "res4b27_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b27_branch2b"
top: "res4b27_branch2b"
name: "bn4b27_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b27_branch2b"
top: "res4b27_branch2b"
name: "scale4b27_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b27_branch2b"
top: "res4b27_branch2b"
name: "res4b27_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b27_branch2b"
top: "res4b27_branch2c"
name: "res4b27_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b27_branch2c"
top: "res4b27_branch2c"
name: "bn4b27_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b27_branch2c"
top: "res4b27_branch2c"
name: "scale4b27_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b26"
bottom: "res4b27_branch2c"
top: "res4b27"
name: "res4b27"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b27"
top: "res4b27"
name: "res4b27_relu"
type: "ReLU"
} layer {
bottom: "res4b27"
top: "res4b28_branch2a"
name: "res4b28_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b28_branch2a"
top: "res4b28_branch2a"
name: "bn4b28_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b28_branch2a"
top: "res4b28_branch2a"
name: "scale4b28_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b28_branch2a"
top: "res4b28_branch2a"
name: "res4b28_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b28_branch2a"
top: "res4b28_branch2b"
name: "res4b28_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b28_branch2b"
top: "res4b28_branch2b"
name: "bn4b28_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b28_branch2b"
top: "res4b28_branch2b"
name: "scale4b28_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b28_branch2b"
top: "res4b28_branch2b"
name: "res4b28_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b28_branch2b"
top: "res4b28_branch2c"
name: "res4b28_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b28_branch2c"
top: "res4b28_branch2c"
name: "bn4b28_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b28_branch2c"
top: "res4b28_branch2c"
name: "scale4b28_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b27"
bottom: "res4b28_branch2c"
top: "res4b28"
name: "res4b28"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b28"
top: "res4b28"
name: "res4b28_relu"
type: "ReLU"
} layer {
bottom: "res4b28"
top: "res4b29_branch2a"
name: "res4b29_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b29_branch2a"
top: "res4b29_branch2a"
name: "bn4b29_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b29_branch2a"
top: "res4b29_branch2a"
name: "scale4b29_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b29_branch2a"
top: "res4b29_branch2a"
name: "res4b29_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b29_branch2a"
top: "res4b29_branch2b"
name: "res4b29_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b29_branch2b"
top: "res4b29_branch2b"
name: "bn4b29_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b29_branch2b"
top: "res4b29_branch2b"
name: "scale4b29_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b29_branch2b"
top: "res4b29_branch2b"
name: "res4b29_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b29_branch2b"
top: "res4b29_branch2c"
name: "res4b29_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b29_branch2c"
top: "res4b29_branch2c"
name: "bn4b29_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b29_branch2c"
top: "res4b29_branch2c"
name: "scale4b29_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b28"
bottom: "res4b29_branch2c"
top: "res4b29"
name: "res4b29"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b29"
top: "res4b29"
name: "res4b29_relu"
type: "ReLU"
} layer {
bottom: "res4b29"
top: "res4b30_branch2a"
name: "res4b30_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b30_branch2a"
top: "res4b30_branch2a"
name: "bn4b30_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b30_branch2a"
top: "res4b30_branch2a"
name: "scale4b30_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b30_branch2a"
top: "res4b30_branch2a"
name: "res4b30_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b30_branch2a"
top: "res4b30_branch2b"
name: "res4b30_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b30_branch2b"
top: "res4b30_branch2b"
name: "bn4b30_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b30_branch2b"
top: "res4b30_branch2b"
name: "scale4b30_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b30_branch2b"
top: "res4b30_branch2b"
name: "res4b30_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b30_branch2b"
top: "res4b30_branch2c"
name: "res4b30_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b30_branch2c"
top: "res4b30_branch2c"
name: "bn4b30_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b30_branch2c"
top: "res4b30_branch2c"
name: "scale4b30_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b29"
bottom: "res4b30_branch2c"
top: "res4b30"
name: "res4b30"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b30"
top: "res4b30"
name: "res4b30_relu"
type: "ReLU"
} layer {
bottom: "res4b30"
top: "res4b31_branch2a"
name: "res4b31_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b31_branch2a"
top: "res4b31_branch2a"
name: "bn4b31_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b31_branch2a"
top: "res4b31_branch2a"
name: "scale4b31_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b31_branch2a"
top: "res4b31_branch2a"
name: "res4b31_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b31_branch2a"
top: "res4b31_branch2b"
name: "res4b31_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b31_branch2b"
top: "res4b31_branch2b"
name: "bn4b31_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b31_branch2b"
top: "res4b31_branch2b"
name: "scale4b31_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b31_branch2b"
top: "res4b31_branch2b"
name: "res4b31_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b31_branch2b"
top: "res4b31_branch2c"
name: "res4b31_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b31_branch2c"
top: "res4b31_branch2c"
name: "bn4b31_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b31_branch2c"
top: "res4b31_branch2c"
name: "scale4b31_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b30"
bottom: "res4b31_branch2c"
top: "res4b31"
name: "res4b31"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b31"
top: "res4b31"
name: "res4b31_relu"
type: "ReLU"
} layer {
bottom: "res4b31"
top: "res4b32_branch2a"
name: "res4b32_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b32_branch2a"
top: "res4b32_branch2a"
name: "bn4b32_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b32_branch2a"
top: "res4b32_branch2a"
name: "scale4b32_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b32_branch2a"
top: "res4b32_branch2a"
name: "res4b32_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b32_branch2a"
top: "res4b32_branch2b"
name: "res4b32_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b32_branch2b"
top: "res4b32_branch2b"
name: "bn4b32_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b32_branch2b"
top: "res4b32_branch2b"
name: "scale4b32_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b32_branch2b"
top: "res4b32_branch2b"
name: "res4b32_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b32_branch2b"
top: "res4b32_branch2c"
name: "res4b32_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b32_branch2c"
top: "res4b32_branch2c"
name: "bn4b32_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b32_branch2c"
top: "res4b32_branch2c"
name: "scale4b32_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b31"
bottom: "res4b32_branch2c"
top: "res4b32"
name: "res4b32"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b32"
top: "res4b32"
name: "res4b32_relu"
type: "ReLU"
} layer {
bottom: "res4b32"
top: "res4b33_branch2a"
name: "res4b33_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b33_branch2a"
top: "res4b33_branch2a"
name: "bn4b33_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b33_branch2a"
top: "res4b33_branch2a"
name: "scale4b33_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b33_branch2a"
top: "res4b33_branch2a"
name: "res4b33_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b33_branch2a"
top: "res4b33_branch2b"
name: "res4b33_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b33_branch2b"
top: "res4b33_branch2b"
name: "bn4b33_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b33_branch2b"
top: "res4b33_branch2b"
name: "scale4b33_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b33_branch2b"
top: "res4b33_branch2b"
name: "res4b33_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b33_branch2b"
top: "res4b33_branch2c"
name: "res4b33_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b33_branch2c"
top: "res4b33_branch2c"
name: "bn4b33_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b33_branch2c"
top: "res4b33_branch2c"
name: "scale4b33_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b32"
bottom: "res4b33_branch2c"
top: "res4b33"
name: "res4b33"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b33"
top: "res4b33"
name: "res4b33_relu"
type: "ReLU"
} layer {
bottom: "res4b33"
top: "res4b34_branch2a"
name: "res4b34_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b34_branch2a"
top: "res4b34_branch2a"
name: "bn4b34_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b34_branch2a"
top: "res4b34_branch2a"
name: "scale4b34_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b34_branch2a"
top: "res4b34_branch2a"
name: "res4b34_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b34_branch2a"
top: "res4b34_branch2b"
name: "res4b34_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b34_branch2b"
top: "res4b34_branch2b"
name: "bn4b34_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b34_branch2b"
top: "res4b34_branch2b"
name: "scale4b34_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b34_branch2b"
top: "res4b34_branch2b"
name: "res4b34_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b34_branch2b"
top: "res4b34_branch2c"
name: "res4b34_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b34_branch2c"
top: "res4b34_branch2c"
name: "bn4b34_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b34_branch2c"
top: "res4b34_branch2c"
name: "scale4b34_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b33"
bottom: "res4b34_branch2c"
top: "res4b34"
name: "res4b34"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b34"
top: "res4b34"
name: "res4b34_relu"
type: "ReLU"
} layer {
bottom: "res4b34"
top: "res4b35_branch2a"
name: "res4b35_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b35_branch2a"
top: "res4b35_branch2a"
name: "bn4b35_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b35_branch2a"
top: "res4b35_branch2a"
name: "scale4b35_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b35_branch2a"
top: "res4b35_branch2a"
name: "res4b35_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b35_branch2a"
top: "res4b35_branch2b"
name: "res4b35_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b35_branch2b"
top: "res4b35_branch2b"
name: "bn4b35_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b35_branch2b"
top: "res4b35_branch2b"
name: "scale4b35_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b35_branch2b"
top: "res4b35_branch2b"
name: "res4b35_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b35_branch2b"
top: "res4b35_branch2c"
name: "res4b35_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res4b35_branch2c"
top: "res4b35_branch2c"
name: "bn4b35_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res4b35_branch2c"
top: "res4b35_branch2c"
name: "scale4b35_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b34"
bottom: "res4b35_branch2c"
top: "res4b35"
name: "res4b35"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res4b35"
top: "res4b35"
name: "res4b35_relu"
type: "ReLU"
} layer {
bottom: "res4b35"
top: "res5a_branch1"
name: "res5a_branch1"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5a_branch1"
top: "res5a_branch1"
name: "bn5a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5a_branch1"
top: "res5a_branch1"
name: "scale5a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b35"
top: "res5a_branch2a"
name: "res5a_branch2a"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 2
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5a_branch2a"
top: "res5a_branch2a"
name: "bn5a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5a_branch2a"
top: "res5a_branch2a"
name: "scale5a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5a_branch2a"
top: "res5a_branch2a"
name: "res5a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res5a_branch2a"
top: "res5a_branch2b"
name: "res5a_branch2b"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5a_branch2b"
top: "res5a_branch2b"
name: "bn5a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5a_branch2b"
top: "res5a_branch2b"
name: "scale5a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5a_branch2b"
top: "res5a_branch2b"
name: "res5a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res5a_branch2b"
top: "res5a_branch2c"
name: "res5a_branch2c"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5a_branch2c"
top: "res5a_branch2c"
name: "bn5a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5a_branch2c"
top: "res5a_branch2c"
name: "scale5a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5a_branch1"
bottom: "res5a_branch2c"
top: "res5a"
name: "res5a"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res5a"
top: "res5a"
name: "res5a_relu"
type: "ReLU"
} layer {
bottom: "res5a"
top: "res5b_branch2a"
name: "res5b_branch2a"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5b_branch2a"
top: "res5b_branch2a"
name: "bn5b_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5b_branch2a"
top: "res5b_branch2a"
name: "scale5b_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5b_branch2a"
top: "res5b_branch2a"
name: "res5b_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res5b_branch2a"
top: "res5b_branch2b"
name: "res5b_branch2b"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5b_branch2b"
top: "res5b_branch2b"
name: "bn5b_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5b_branch2b"
top: "res5b_branch2b"
name: "scale5b_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5b_branch2b"
top: "res5b_branch2b"
name: "res5b_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res5b_branch2b"
top: "res5b_branch2c"
name: "res5b_branch2c"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5b_branch2c"
top: "res5b_branch2c"
name: "bn5b_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5b_branch2c"
top: "res5b_branch2c"
name: "scale5b_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5a"
bottom: "res5b_branch2c"
top: "res5b"
name: "res5b"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res5b"
top: "res5b"
name: "res5b_relu"
type: "ReLU"
} layer {
bottom: "res5b"
top: "res5c_branch2a"
name: "res5c_branch2a"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5c_branch2a"
top: "res5c_branch2a"
name: "bn5c_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5c_branch2a"
top: "res5c_branch2a"
name: "scale5c_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5c_branch2a"
top: "res5c_branch2a"
name: "res5c_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res5c_branch2a"
top: "res5c_branch2b"
name: "res5c_branch2b"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5c_branch2b"
top: "res5c_branch2b"
name: "bn5c_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5c_branch2b"
top: "res5c_branch2b"
name: "scale5c_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5c_branch2b"
top: "res5c_branch2b"
name: "res5c_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res5c_branch2b"
top: "res5c_branch2c"
name: "res5c_branch2c"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 1
weight_filler {
type: "msra"
}
bias_term: false }
} layer {
bottom: "res5c_branch2c"
top: "res5c_branch2c"
name: "bn5c_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: false
}
} layer {
bottom: "res5c_branch2c"
top: "res5c_branch2c"
name: "scale5c_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5b"
bottom: "res5c_branch2c"
top: "res5c"
name: "res5c"
type: "Eltwise"
eltwise_param {
operation: SUM
}
} layer {
bottom: "res5c"
top: "res5c"
name: "res5c_relu"
type: "ReLU"
} layer {
bottom: "res5c"
top: "pool5"
name: "pool5"
type: "Pooling"
pooling_param {
kernel_size: 7
stride: 1
pool: AVE
}
} layer {
bottom: "pool5"
top: "fc3"
name: "fc3"
type: "InnerProduct"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 1
}
inner_product_param {
num_output: 3
weight_filler {
type: "xavier"
}
bias_filler {
type: "constant"
value: 0
}
}
} layer {
bottom: "fc3"
bottom: "label"
name: "loss"
type: "SoftmaxWithLoss"
top: "loss"
} layer {
name: "probt"
type: "Softmax"
bottom: "fc3"
top: "probt"
include {
phase: TEST
}
} layer {
bottom: "fc3"
bottom: "label"
top: "accuracy@1"
name: "accuracy/top1"
type: "Accuracy"
accuracy_param {
top_k: 1
}
}
deploy.prototxt
name: "ResNet-152"
input: "data"
input_shape {
dim: 1
dim: 3
dim: 224
dim: 224
} layer {
bottom: "data"
top: "conv1"
name: "conv1"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 7
pad: 3
stride: 2
bias_term: false
}
} layer {
bottom: "conv1"
top: "conv1"
name: "bn_conv1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "conv1"
top: "conv1"
name: "scale_conv1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "conv1"
bottom: "conv1"
name: "conv1_relu"
type: "ReLU"
} layer {
bottom: "conv1"
top: "pool1"
name: "pool1"
type: "Pooling"
pooling_param {
kernel_size: 3
stride: 2
pool: MAX
}
} layer {
bottom: "pool1"
top: "res2a_branch1"
name: "res2a_branch1"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res2a_branch1"
top: "res2a_branch1"
name: "bn2a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2a_branch1"
top: "res2a_branch1"
name: "scale2a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "pool1"
top: "res2a_branch2a"
name: "res2a_branch2a"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res2a_branch2a"
top: "res2a_branch2a"
name: "bn2a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2a_branch2a"
top: "res2a_branch2a"
name: "scale2a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res2a_branch2a"
bottom: "res2a_branch2a"
name: "res2a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res2a_branch2a"
top: "res2a_branch2b"
name: "res2a_branch2b"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res2a_branch2b"
top: "res2a_branch2b"
name: "bn2a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2a_branch2b"
top: "res2a_branch2b"
name: "scale2a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res2a_branch2b"
bottom: "res2a_branch2b"
name: "res2a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res2a_branch2b"
top: "res2a_branch2c"
name: "res2a_branch2c"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res2a_branch2c"
top: "res2a_branch2c"
name: "bn2a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2a_branch2c"
top: "res2a_branch2c"
name: "scale2a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2a_branch1"
bottom: "res2a_branch2c"
top: "res2a"
name: "res2a"
type: "Eltwise"
} layer {
bottom: "res2a"
top: "res2a"
name: "res2a_relu"
type: "ReLU"
} layer {
bottom: "res2a"
top: "res2b_branch2a"
name: "res2b_branch2a"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res2b_branch2a"
top: "res2b_branch2a"
name: "bn2b_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2b_branch2a"
top: "res2b_branch2a"
name: "scale2b_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res2b_branch2a"
bottom: "res2b_branch2a"
name: "res2b_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res2b_branch2a"
top: "res2b_branch2b"
name: "res2b_branch2b"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res2b_branch2b"
top: "res2b_branch2b"
name: "bn2b_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2b_branch2b"
top: "res2b_branch2b"
name: "scale2b_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res2b_branch2b"
bottom: "res2b_branch2b"
name: "res2b_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res2b_branch2b"
top: "res2b_branch2c"
name: "res2b_branch2c"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res2b_branch2c"
top: "res2b_branch2c"
name: "bn2b_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2b_branch2c"
top: "res2b_branch2c"
name: "scale2b_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2a"
bottom: "res2b_branch2c"
top: "res2b"
name: "res2b"
type: "Eltwise"
} layer {
bottom: "res2b"
top: "res2b"
name: "res2b_relu"
type: "ReLU"
} layer {
bottom: "res2b"
top: "res2c_branch2a"
name: "res2c_branch2a"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res2c_branch2a"
top: "res2c_branch2a"
name: "bn2c_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2c_branch2a"
top: "res2c_branch2a"
name: "scale2c_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res2c_branch2a"
bottom: "res2c_branch2a"
name: "res2c_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res2c_branch2a"
top: "res2c_branch2b"
name: "res2c_branch2b"
type: "Convolution"
convolution_param {
num_output: 64
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res2c_branch2b"
top: "res2c_branch2b"
name: "bn2c_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2c_branch2b"
top: "res2c_branch2b"
name: "scale2c_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res2c_branch2b"
bottom: "res2c_branch2b"
name: "res2c_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res2c_branch2b"
top: "res2c_branch2c"
name: "res2c_branch2c"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res2c_branch2c"
top: "res2c_branch2c"
name: "bn2c_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res2c_branch2c"
top: "res2c_branch2c"
name: "scale2c_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2b"
bottom: "res2c_branch2c"
top: "res2c"
name: "res2c"
type: "Eltwise"
} layer {
bottom: "res2c"
top: "res2c"
name: "res2c_relu"
type: "ReLU"
} layer {
bottom: "res2c"
top: "res3a_branch1"
name: "res3a_branch1"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 2
bias_term: false
}
} layer {
bottom: "res3a_branch1"
top: "res3a_branch1"
name: "bn3a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3a_branch1"
top: "res3a_branch1"
name: "scale3a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res2c"
top: "res3a_branch2a"
name: "res3a_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 2
bias_term: false
}
} layer {
bottom: "res3a_branch2a"
top: "res3a_branch2a"
name: "bn3a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3a_branch2a"
top: "res3a_branch2a"
name: "scale3a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3a_branch2a"
bottom: "res3a_branch2a"
name: "res3a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3a_branch2a"
top: "res3a_branch2b"
name: "res3a_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3a_branch2b"
top: "res3a_branch2b"
name: "bn3a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3a_branch2b"
top: "res3a_branch2b"
name: "scale3a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3a_branch2b"
bottom: "res3a_branch2b"
name: "res3a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3a_branch2b"
top: "res3a_branch2c"
name: "res3a_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3a_branch2c"
top: "res3a_branch2c"
name: "bn3a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3a_branch2c"
top: "res3a_branch2c"
name: "scale3a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3a_branch1"
bottom: "res3a_branch2c"
top: "res3a"
name: "res3a"
type: "Eltwise"
} layer {
bottom: "res3a"
top: "res3a"
name: "res3a_relu"
type: "ReLU"
} layer {
bottom: "res3a"
top: "res3b1_branch2a"
name: "res3b1_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b1_branch2a"
top: "res3b1_branch2a"
name: "bn3b1_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b1_branch2a"
top: "res3b1_branch2a"
name: "scale3b1_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b1_branch2a"
bottom: "res3b1_branch2a"
name: "res3b1_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b1_branch2a"
top: "res3b1_branch2b"
name: "res3b1_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3b1_branch2b"
top: "res3b1_branch2b"
name: "bn3b1_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b1_branch2b"
top: "res3b1_branch2b"
name: "scale3b1_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b1_branch2b"
bottom: "res3b1_branch2b"
name: "res3b1_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b1_branch2b"
top: "res3b1_branch2c"
name: "res3b1_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b1_branch2c"
top: "res3b1_branch2c"
name: "bn3b1_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b1_branch2c"
top: "res3b1_branch2c"
name: "scale3b1_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3a"
bottom: "res3b1_branch2c"
top: "res3b1"
name: "res3b1"
type: "Eltwise"
} layer {
bottom: "res3b1"
top: "res3b1"
name: "res3b1_relu"
type: "ReLU"
} layer {
bottom: "res3b1"
top: "res3b2_branch2a"
name: "res3b2_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b2_branch2a"
top: "res3b2_branch2a"
name: "bn3b2_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b2_branch2a"
top: "res3b2_branch2a"
name: "scale3b2_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b2_branch2a"
bottom: "res3b2_branch2a"
name: "res3b2_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b2_branch2a"
top: "res3b2_branch2b"
name: "res3b2_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3b2_branch2b"
top: "res3b2_branch2b"
name: "bn3b2_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b2_branch2b"
top: "res3b2_branch2b"
name: "scale3b2_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b2_branch2b"
bottom: "res3b2_branch2b"
name: "res3b2_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b2_branch2b"
top: "res3b2_branch2c"
name: "res3b2_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b2_branch2c"
top: "res3b2_branch2c"
name: "bn3b2_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b2_branch2c"
top: "res3b2_branch2c"
name: "scale3b2_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b1"
bottom: "res3b2_branch2c"
top: "res3b2"
name: "res3b2"
type: "Eltwise"
} layer {
bottom: "res3b2"
top: "res3b2"
name: "res3b2_relu"
type: "ReLU"
} layer {
bottom: "res3b2"
top: "res3b3_branch2a"
name: "res3b3_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b3_branch2a"
top: "res3b3_branch2a"
name: "bn3b3_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b3_branch2a"
top: "res3b3_branch2a"
name: "scale3b3_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b3_branch2a"
bottom: "res3b3_branch2a"
name: "res3b3_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b3_branch2a"
top: "res3b3_branch2b"
name: "res3b3_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3b3_branch2b"
top: "res3b3_branch2b"
name: "bn3b3_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b3_branch2b"
top: "res3b3_branch2b"
name: "scale3b3_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b3_branch2b"
bottom: "res3b3_branch2b"
name: "res3b3_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b3_branch2b"
top: "res3b3_branch2c"
name: "res3b3_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b3_branch2c"
top: "res3b3_branch2c"
name: "bn3b3_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b3_branch2c"
top: "res3b3_branch2c"
name: "scale3b3_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b2"
bottom: "res3b3_branch2c"
top: "res3b3"
name: "res3b3"
type: "Eltwise"
} layer {
bottom: "res3b3"
top: "res3b3"
name: "res3b3_relu"
type: "ReLU"
} layer {
bottom: "res3b3"
top: "res3b4_branch2a"
name: "res3b4_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b4_branch2a"
top: "res3b4_branch2a"
name: "bn3b4_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b4_branch2a"
top: "res3b4_branch2a"
name: "scale3b4_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b4_branch2a"
bottom: "res3b4_branch2a"
name: "res3b4_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b4_branch2a"
top: "res3b4_branch2b"
name: "res3b4_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3b4_branch2b"
top: "res3b4_branch2b"
name: "bn3b4_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b4_branch2b"
top: "res3b4_branch2b"
name: "scale3b4_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b4_branch2b"
bottom: "res3b4_branch2b"
name: "res3b4_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b4_branch2b"
top: "res3b4_branch2c"
name: "res3b4_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b4_branch2c"
top: "res3b4_branch2c"
name: "bn3b4_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b4_branch2c"
top: "res3b4_branch2c"
name: "scale3b4_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b3"
bottom: "res3b4_branch2c"
top: "res3b4"
name: "res3b4"
type: "Eltwise"
} layer {
bottom: "res3b4"
top: "res3b4"
name: "res3b4_relu"
type: "ReLU"
} layer {
bottom: "res3b4"
top: "res3b5_branch2a"
name: "res3b5_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b5_branch2a"
top: "res3b5_branch2a"
name: "bn3b5_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b5_branch2a"
top: "res3b5_branch2a"
name: "scale3b5_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b5_branch2a"
bottom: "res3b5_branch2a"
name: "res3b5_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b5_branch2a"
top: "res3b5_branch2b"
name: "res3b5_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3b5_branch2b"
top: "res3b5_branch2b"
name: "bn3b5_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b5_branch2b"
top: "res3b5_branch2b"
name: "scale3b5_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b5_branch2b"
bottom: "res3b5_branch2b"
name: "res3b5_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b5_branch2b"
top: "res3b5_branch2c"
name: "res3b5_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b5_branch2c"
top: "res3b5_branch2c"
name: "bn3b5_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b5_branch2c"
top: "res3b5_branch2c"
name: "scale3b5_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b4"
bottom: "res3b5_branch2c"
top: "res3b5"
name: "res3b5"
type: "Eltwise"
} layer {
bottom: "res3b5"
top: "res3b5"
name: "res3b5_relu"
type: "ReLU"
} layer {
bottom: "res3b5"
top: "res3b6_branch2a"
name: "res3b6_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b6_branch2a"
top: "res3b6_branch2a"
name: "bn3b6_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b6_branch2a"
top: "res3b6_branch2a"
name: "scale3b6_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b6_branch2a"
bottom: "res3b6_branch2a"
name: "res3b6_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b6_branch2a"
top: "res3b6_branch2b"
name: "res3b6_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3b6_branch2b"
top: "res3b6_branch2b"
name: "bn3b6_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b6_branch2b"
top: "res3b6_branch2b"
name: "scale3b6_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b6_branch2b"
bottom: "res3b6_branch2b"
name: "res3b6_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b6_branch2b"
top: "res3b6_branch2c"
name: "res3b6_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b6_branch2c"
top: "res3b6_branch2c"
name: "bn3b6_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b6_branch2c"
top: "res3b6_branch2c"
name: "scale3b6_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b5"
bottom: "res3b6_branch2c"
top: "res3b6"
name: "res3b6"
type: "Eltwise"
} layer {
bottom: "res3b6"
top: "res3b6"
name: "res3b6_relu"
type: "ReLU"
} layer {
bottom: "res3b6"
top: "res3b7_branch2a"
name: "res3b7_branch2a"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b7_branch2a"
top: "res3b7_branch2a"
name: "bn3b7_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b7_branch2a"
top: "res3b7_branch2a"
name: "scale3b7_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b7_branch2a"
bottom: "res3b7_branch2a"
name: "res3b7_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res3b7_branch2a"
top: "res3b7_branch2b"
name: "res3b7_branch2b"
type: "Convolution"
convolution_param {
num_output: 128
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res3b7_branch2b"
top: "res3b7_branch2b"
name: "bn3b7_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b7_branch2b"
top: "res3b7_branch2b"
name: "scale3b7_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res3b7_branch2b"
bottom: "res3b7_branch2b"
name: "res3b7_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res3b7_branch2b"
top: "res3b7_branch2c"
name: "res3b7_branch2c"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res3b7_branch2c"
top: "res3b7_branch2c"
name: "bn3b7_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res3b7_branch2c"
top: "res3b7_branch2c"
name: "scale3b7_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b6"
bottom: "res3b7_branch2c"
top: "res3b7"
name: "res3b7"
type: "Eltwise"
} layer {
bottom: "res3b7"
top: "res3b7"
name: "res3b7_relu"
type: "ReLU"
} layer {
bottom: "res3b7"
top: "res4a_branch1"
name: "res4a_branch1"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 2
bias_term: false
}
} layer {
bottom: "res4a_branch1"
top: "res4a_branch1"
name: "bn4a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4a_branch1"
top: "res4a_branch1"
name: "scale4a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res3b7"
top: "res4a_branch2a"
name: "res4a_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 2
bias_term: false
}
} layer {
bottom: "res4a_branch2a"
top: "res4a_branch2a"
name: "bn4a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4a_branch2a"
top: "res4a_branch2a"
name: "scale4a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4a_branch2a"
bottom: "res4a_branch2a"
name: "res4a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4a_branch2a"
top: "res4a_branch2b"
name: "res4a_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4a_branch2b"
top: "res4a_branch2b"
name: "bn4a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4a_branch2b"
top: "res4a_branch2b"
name: "scale4a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4a_branch2b"
bottom: "res4a_branch2b"
name: "res4a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4a_branch2b"
top: "res4a_branch2c"
name: "res4a_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4a_branch2c"
top: "res4a_branch2c"
name: "bn4a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4a_branch2c"
top: "res4a_branch2c"
name: "scale4a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4a_branch1"
bottom: "res4a_branch2c"
top: "res4a"
name: "res4a"
type: "Eltwise"
} layer {
bottom: "res4a"
top: "res4a"
name: "res4a_relu"
type: "ReLU"
} layer {
bottom: "res4a"
top: "res4b1_branch2a"
name: "res4b1_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b1_branch2a"
top: "res4b1_branch2a"
name: "bn4b1_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b1_branch2a"
top: "res4b1_branch2a"
name: "scale4b1_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b1_branch2a"
bottom: "res4b1_branch2a"
name: "res4b1_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b1_branch2a"
top: "res4b1_branch2b"
name: "res4b1_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b1_branch2b"
top: "res4b1_branch2b"
name: "bn4b1_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b1_branch2b"
top: "res4b1_branch2b"
name: "scale4b1_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b1_branch2b"
bottom: "res4b1_branch2b"
name: "res4b1_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b1_branch2b"
top: "res4b1_branch2c"
name: "res4b1_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b1_branch2c"
top: "res4b1_branch2c"
name: "bn4b1_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b1_branch2c"
top: "res4b1_branch2c"
name: "scale4b1_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4a"
bottom: "res4b1_branch2c"
top: "res4b1"
name: "res4b1"
type: "Eltwise"
} layer {
bottom: "res4b1"
top: "res4b1"
name: "res4b1_relu"
type: "ReLU"
} layer {
bottom: "res4b1"
top: "res4b2_branch2a"
name: "res4b2_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b2_branch2a"
top: "res4b2_branch2a"
name: "bn4b2_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b2_branch2a"
top: "res4b2_branch2a"
name: "scale4b2_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b2_branch2a"
bottom: "res4b2_branch2a"
name: "res4b2_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b2_branch2a"
top: "res4b2_branch2b"
name: "res4b2_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b2_branch2b"
top: "res4b2_branch2b"
name: "bn4b2_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b2_branch2b"
top: "res4b2_branch2b"
name: "scale4b2_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b2_branch2b"
bottom: "res4b2_branch2b"
name: "res4b2_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b2_branch2b"
top: "res4b2_branch2c"
name: "res4b2_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b2_branch2c"
top: "res4b2_branch2c"
name: "bn4b2_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b2_branch2c"
top: "res4b2_branch2c"
name: "scale4b2_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b1"
bottom: "res4b2_branch2c"
top: "res4b2"
name: "res4b2"
type: "Eltwise"
} layer {
bottom: "res4b2"
top: "res4b2"
name: "res4b2_relu"
type: "ReLU"
} layer {
bottom: "res4b2"
top: "res4b3_branch2a"
name: "res4b3_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b3_branch2a"
top: "res4b3_branch2a"
name: "bn4b3_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b3_branch2a"
top: "res4b3_branch2a"
name: "scale4b3_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b3_branch2a"
bottom: "res4b3_branch2a"
name: "res4b3_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b3_branch2a"
top: "res4b3_branch2b"
name: "res4b3_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b3_branch2b"
top: "res4b3_branch2b"
name: "bn4b3_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b3_branch2b"
top: "res4b3_branch2b"
name: "scale4b3_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b3_branch2b"
bottom: "res4b3_branch2b"
name: "res4b3_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b3_branch2b"
top: "res4b3_branch2c"
name: "res4b3_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b3_branch2c"
top: "res4b3_branch2c"
name: "bn4b3_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b3_branch2c"
top: "res4b3_branch2c"
name: "scale4b3_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b2"
bottom: "res4b3_branch2c"
top: "res4b3"
name: "res4b3"
type: "Eltwise"
} layer {
bottom: "res4b3"
top: "res4b3"
name: "res4b3_relu"
type: "ReLU"
} layer {
bottom: "res4b3"
top: "res4b4_branch2a"
name: "res4b4_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b4_branch2a"
top: "res4b4_branch2a"
name: "bn4b4_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b4_branch2a"
top: "res4b4_branch2a"
name: "scale4b4_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b4_branch2a"
bottom: "res4b4_branch2a"
name: "res4b4_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b4_branch2a"
top: "res4b4_branch2b"
name: "res4b4_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b4_branch2b"
top: "res4b4_branch2b"
name: "bn4b4_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b4_branch2b"
top: "res4b4_branch2b"
name: "scale4b4_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b4_branch2b"
bottom: "res4b4_branch2b"
name: "res4b4_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b4_branch2b"
top: "res4b4_branch2c"
name: "res4b4_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b4_branch2c"
top: "res4b4_branch2c"
name: "bn4b4_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b4_branch2c"
top: "res4b4_branch2c"
name: "scale4b4_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b3"
bottom: "res4b4_branch2c"
top: "res4b4"
name: "res4b4"
type: "Eltwise"
} layer {
bottom: "res4b4"
top: "res4b4"
name: "res4b4_relu"
type: "ReLU"
} layer {
bottom: "res4b4"
top: "res4b5_branch2a"
name: "res4b5_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b5_branch2a"
top: "res4b5_branch2a"
name: "bn4b5_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b5_branch2a"
top: "res4b5_branch2a"
name: "scale4b5_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b5_branch2a"
bottom: "res4b5_branch2a"
name: "res4b5_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b5_branch2a"
top: "res4b5_branch2b"
name: "res4b5_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b5_branch2b"
top: "res4b5_branch2b"
name: "bn4b5_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b5_branch2b"
top: "res4b5_branch2b"
name: "scale4b5_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b5_branch2b"
bottom: "res4b5_branch2b"
name: "res4b5_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b5_branch2b"
top: "res4b5_branch2c"
name: "res4b5_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b5_branch2c"
top: "res4b5_branch2c"
name: "bn4b5_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b5_branch2c"
top: "res4b5_branch2c"
name: "scale4b5_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b4"
bottom: "res4b5_branch2c"
top: "res4b5"
name: "res4b5"
type: "Eltwise"
} layer {
bottom: "res4b5"
top: "res4b5"
name: "res4b5_relu"
type: "ReLU"
} layer {
bottom: "res4b5"
top: "res4b6_branch2a"
name: "res4b6_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b6_branch2a"
top: "res4b6_branch2a"
name: "bn4b6_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b6_branch2a"
top: "res4b6_branch2a"
name: "scale4b6_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b6_branch2a"
bottom: "res4b6_branch2a"
name: "res4b6_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b6_branch2a"
top: "res4b6_branch2b"
name: "res4b6_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b6_branch2b"
top: "res4b6_branch2b"
name: "bn4b6_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b6_branch2b"
top: "res4b6_branch2b"
name: "scale4b6_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b6_branch2b"
bottom: "res4b6_branch2b"
name: "res4b6_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b6_branch2b"
top: "res4b6_branch2c"
name: "res4b6_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b6_branch2c"
top: "res4b6_branch2c"
name: "bn4b6_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b6_branch2c"
top: "res4b6_branch2c"
name: "scale4b6_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b5"
bottom: "res4b6_branch2c"
top: "res4b6"
name: "res4b6"
type: "Eltwise"
} layer {
bottom: "res4b6"
top: "res4b6"
name: "res4b6_relu"
type: "ReLU"
} layer {
bottom: "res4b6"
top: "res4b7_branch2a"
name: "res4b7_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b7_branch2a"
top: "res4b7_branch2a"
name: "bn4b7_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b7_branch2a"
top: "res4b7_branch2a"
name: "scale4b7_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b7_branch2a"
bottom: "res4b7_branch2a"
name: "res4b7_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b7_branch2a"
top: "res4b7_branch2b"
name: "res4b7_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b7_branch2b"
top: "res4b7_branch2b"
name: "bn4b7_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b7_branch2b"
top: "res4b7_branch2b"
name: "scale4b7_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b7_branch2b"
bottom: "res4b7_branch2b"
name: "res4b7_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b7_branch2b"
top: "res4b7_branch2c"
name: "res4b7_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b7_branch2c"
top: "res4b7_branch2c"
name: "bn4b7_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b7_branch2c"
top: "res4b7_branch2c"
name: "scale4b7_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b6"
bottom: "res4b7_branch2c"
top: "res4b7"
name: "res4b7"
type: "Eltwise"
} layer {
bottom: "res4b7"
top: "res4b7"
name: "res4b7_relu"
type: "ReLU"
} layer {
bottom: "res4b7"
top: "res4b8_branch2a"
name: "res4b8_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b8_branch2a"
top: "res4b8_branch2a"
name: "bn4b8_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b8_branch2a"
top: "res4b8_branch2a"
name: "scale4b8_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b8_branch2a"
bottom: "res4b8_branch2a"
name: "res4b8_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b8_branch2a"
top: "res4b8_branch2b"
name: "res4b8_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b8_branch2b"
top: "res4b8_branch2b"
name: "bn4b8_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b8_branch2b"
top: "res4b8_branch2b"
name: "scale4b8_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b8_branch2b"
bottom: "res4b8_branch2b"
name: "res4b8_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b8_branch2b"
top: "res4b8_branch2c"
name: "res4b8_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b8_branch2c"
top: "res4b8_branch2c"
name: "bn4b8_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b8_branch2c"
top: "res4b8_branch2c"
name: "scale4b8_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b7"
bottom: "res4b8_branch2c"
top: "res4b8"
name: "res4b8"
type: "Eltwise"
} layer {
bottom: "res4b8"
top: "res4b8"
name: "res4b8_relu"
type: "ReLU"
} layer {
bottom: "res4b8"
top: "res4b9_branch2a"
name: "res4b9_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b9_branch2a"
top: "res4b9_branch2a"
name: "bn4b9_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b9_branch2a"
top: "res4b9_branch2a"
name: "scale4b9_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b9_branch2a"
bottom: "res4b9_branch2a"
name: "res4b9_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b9_branch2a"
top: "res4b9_branch2b"
name: "res4b9_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b9_branch2b"
top: "res4b9_branch2b"
name: "bn4b9_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b9_branch2b"
top: "res4b9_branch2b"
name: "scale4b9_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b9_branch2b"
bottom: "res4b9_branch2b"
name: "res4b9_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b9_branch2b"
top: "res4b9_branch2c"
name: "res4b9_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b9_branch2c"
top: "res4b9_branch2c"
name: "bn4b9_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b9_branch2c"
top: "res4b9_branch2c"
name: "scale4b9_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b8"
bottom: "res4b9_branch2c"
top: "res4b9"
name: "res4b9"
type: "Eltwise"
} layer {
bottom: "res4b9"
top: "res4b9"
name: "res4b9_relu"
type: "ReLU"
} layer {
bottom: "res4b9"
top: "res4b10_branch2a"
name: "res4b10_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b10_branch2a"
top: "res4b10_branch2a"
name: "bn4b10_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b10_branch2a"
top: "res4b10_branch2a"
name: "scale4b10_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b10_branch2a"
bottom: "res4b10_branch2a"
name: "res4b10_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b10_branch2a"
top: "res4b10_branch2b"
name: "res4b10_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b10_branch2b"
top: "res4b10_branch2b"
name: "bn4b10_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b10_branch2b"
top: "res4b10_branch2b"
name: "scale4b10_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b10_branch2b"
bottom: "res4b10_branch2b"
name: "res4b10_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b10_branch2b"
top: "res4b10_branch2c"
name: "res4b10_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b10_branch2c"
top: "res4b10_branch2c"
name: "bn4b10_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b10_branch2c"
top: "res4b10_branch2c"
name: "scale4b10_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b9"
bottom: "res4b10_branch2c"
top: "res4b10"
name: "res4b10"
type: "Eltwise"
} layer {
bottom: "res4b10"
top: "res4b10"
name: "res4b10_relu"
type: "ReLU"
} layer {
bottom: "res4b10"
top: "res4b11_branch2a"
name: "res4b11_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b11_branch2a"
top: "res4b11_branch2a"
name: "bn4b11_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b11_branch2a"
top: "res4b11_branch2a"
name: "scale4b11_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b11_branch2a"
bottom: "res4b11_branch2a"
name: "res4b11_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b11_branch2a"
top: "res4b11_branch2b"
name: "res4b11_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b11_branch2b"
top: "res4b11_branch2b"
name: "bn4b11_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b11_branch2b"
top: "res4b11_branch2b"
name: "scale4b11_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b11_branch2b"
bottom: "res4b11_branch2b"
name: "res4b11_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b11_branch2b"
top: "res4b11_branch2c"
name: "res4b11_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b11_branch2c"
top: "res4b11_branch2c"
name: "bn4b11_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b11_branch2c"
top: "res4b11_branch2c"
name: "scale4b11_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b10"
bottom: "res4b11_branch2c"
top: "res4b11"
name: "res4b11"
type: "Eltwise"
} layer {
bottom: "res4b11"
top: "res4b11"
name: "res4b11_relu"
type: "ReLU"
} layer {
bottom: "res4b11"
top: "res4b12_branch2a"
name: "res4b12_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b12_branch2a"
top: "res4b12_branch2a"
name: "bn4b12_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b12_branch2a"
top: "res4b12_branch2a"
name: "scale4b12_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b12_branch2a"
bottom: "res4b12_branch2a"
name: "res4b12_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b12_branch2a"
top: "res4b12_branch2b"
name: "res4b12_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b12_branch2b"
top: "res4b12_branch2b"
name: "bn4b12_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b12_branch2b"
top: "res4b12_branch2b"
name: "scale4b12_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b12_branch2b"
bottom: "res4b12_branch2b"
name: "res4b12_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b12_branch2b"
top: "res4b12_branch2c"
name: "res4b12_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b12_branch2c"
top: "res4b12_branch2c"
name: "bn4b12_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b12_branch2c"
top: "res4b12_branch2c"
name: "scale4b12_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b11"
bottom: "res4b12_branch2c"
top: "res4b12"
name: "res4b12"
type: "Eltwise"
} layer {
bottom: "res4b12"
top: "res4b12"
name: "res4b12_relu"
type: "ReLU"
} layer {
bottom: "res4b12"
top: "res4b13_branch2a"
name: "res4b13_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b13_branch2a"
top: "res4b13_branch2a"
name: "bn4b13_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b13_branch2a"
top: "res4b13_branch2a"
name: "scale4b13_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b13_branch2a"
bottom: "res4b13_branch2a"
name: "res4b13_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b13_branch2a"
top: "res4b13_branch2b"
name: "res4b13_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b13_branch2b"
top: "res4b13_branch2b"
name: "bn4b13_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b13_branch2b"
top: "res4b13_branch2b"
name: "scale4b13_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b13_branch2b"
bottom: "res4b13_branch2b"
name: "res4b13_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b13_branch2b"
top: "res4b13_branch2c"
name: "res4b13_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b13_branch2c"
top: "res4b13_branch2c"
name: "bn4b13_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b13_branch2c"
top: "res4b13_branch2c"
name: "scale4b13_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b12"
bottom: "res4b13_branch2c"
top: "res4b13"
name: "res4b13"
type: "Eltwise"
} layer {
bottom: "res4b13"
top: "res4b13"
name: "res4b13_relu"
type: "ReLU"
} layer {
bottom: "res4b13"
top: "res4b14_branch2a"
name: "res4b14_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b14_branch2a"
top: "res4b14_branch2a"
name: "bn4b14_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b14_branch2a"
top: "res4b14_branch2a"
name: "scale4b14_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b14_branch2a"
bottom: "res4b14_branch2a"
name: "res4b14_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b14_branch2a"
top: "res4b14_branch2b"
name: "res4b14_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b14_branch2b"
top: "res4b14_branch2b"
name: "bn4b14_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b14_branch2b"
top: "res4b14_branch2b"
name: "scale4b14_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b14_branch2b"
bottom: "res4b14_branch2b"
name: "res4b14_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b14_branch2b"
top: "res4b14_branch2c"
name: "res4b14_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b14_branch2c"
top: "res4b14_branch2c"
name: "bn4b14_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b14_branch2c"
top: "res4b14_branch2c"
name: "scale4b14_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b13"
bottom: "res4b14_branch2c"
top: "res4b14"
name: "res4b14"
type: "Eltwise"
} layer {
bottom: "res4b14"
top: "res4b14"
name: "res4b14_relu"
type: "ReLU"
} layer {
bottom: "res4b14"
top: "res4b15_branch2a"
name: "res4b15_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b15_branch2a"
top: "res4b15_branch2a"
name: "bn4b15_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b15_branch2a"
top: "res4b15_branch2a"
name: "scale4b15_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b15_branch2a"
bottom: "res4b15_branch2a"
name: "res4b15_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b15_branch2a"
top: "res4b15_branch2b"
name: "res4b15_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b15_branch2b"
top: "res4b15_branch2b"
name: "bn4b15_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b15_branch2b"
top: "res4b15_branch2b"
name: "scale4b15_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b15_branch2b"
bottom: "res4b15_branch2b"
name: "res4b15_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b15_branch2b"
top: "res4b15_branch2c"
name: "res4b15_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b15_branch2c"
top: "res4b15_branch2c"
name: "bn4b15_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b15_branch2c"
top: "res4b15_branch2c"
name: "scale4b15_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b14"
bottom: "res4b15_branch2c"
top: "res4b15"
name: "res4b15"
type: "Eltwise"
} layer {
bottom: "res4b15"
top: "res4b15"
name: "res4b15_relu"
type: "ReLU"
} layer {
bottom: "res4b15"
top: "res4b16_branch2a"
name: "res4b16_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b16_branch2a"
top: "res4b16_branch2a"
name: "bn4b16_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b16_branch2a"
top: "res4b16_branch2a"
name: "scale4b16_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b16_branch2a"
bottom: "res4b16_branch2a"
name: "res4b16_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b16_branch2a"
top: "res4b16_branch2b"
name: "res4b16_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b16_branch2b"
top: "res4b16_branch2b"
name: "bn4b16_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b16_branch2b"
top: "res4b16_branch2b"
name: "scale4b16_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b16_branch2b"
bottom: "res4b16_branch2b"
name: "res4b16_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b16_branch2b"
top: "res4b16_branch2c"
name: "res4b16_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b16_branch2c"
top: "res4b16_branch2c"
name: "bn4b16_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b16_branch2c"
top: "res4b16_branch2c"
name: "scale4b16_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b15"
bottom: "res4b16_branch2c"
top: "res4b16"
name: "res4b16"
type: "Eltwise"
} layer {
bottom: "res4b16"
top: "res4b16"
name: "res4b16_relu"
type: "ReLU"
} layer {
bottom: "res4b16"
top: "res4b17_branch2a"
name: "res4b17_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b17_branch2a"
top: "res4b17_branch2a"
name: "bn4b17_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b17_branch2a"
top: "res4b17_branch2a"
name: "scale4b17_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b17_branch2a"
bottom: "res4b17_branch2a"
name: "res4b17_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b17_branch2a"
top: "res4b17_branch2b"
name: "res4b17_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b17_branch2b"
top: "res4b17_branch2b"
name: "bn4b17_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b17_branch2b"
top: "res4b17_branch2b"
name: "scale4b17_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b17_branch2b"
bottom: "res4b17_branch2b"
name: "res4b17_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b17_branch2b"
top: "res4b17_branch2c"
name: "res4b17_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b17_branch2c"
top: "res4b17_branch2c"
name: "bn4b17_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b17_branch2c"
top: "res4b17_branch2c"
name: "scale4b17_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b16"
bottom: "res4b17_branch2c"
top: "res4b17"
name: "res4b17"
type: "Eltwise"
} layer {
bottom: "res4b17"
top: "res4b17"
name: "res4b17_relu"
type: "ReLU"
} layer {
bottom: "res4b17"
top: "res4b18_branch2a"
name: "res4b18_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b18_branch2a"
top: "res4b18_branch2a"
name: "bn4b18_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b18_branch2a"
top: "res4b18_branch2a"
name: "scale4b18_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b18_branch2a"
bottom: "res4b18_branch2a"
name: "res4b18_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b18_branch2a"
top: "res4b18_branch2b"
name: "res4b18_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b18_branch2b"
top: "res4b18_branch2b"
name: "bn4b18_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b18_branch2b"
top: "res4b18_branch2b"
name: "scale4b18_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b18_branch2b"
bottom: "res4b18_branch2b"
name: "res4b18_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b18_branch2b"
top: "res4b18_branch2c"
name: "res4b18_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b18_branch2c"
top: "res4b18_branch2c"
name: "bn4b18_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b18_branch2c"
top: "res4b18_branch2c"
name: "scale4b18_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b17"
bottom: "res4b18_branch2c"
top: "res4b18"
name: "res4b18"
type: "Eltwise"
} layer {
bottom: "res4b18"
top: "res4b18"
name: "res4b18_relu"
type: "ReLU"
} layer {
bottom: "res4b18"
top: "res4b19_branch2a"
name: "res4b19_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b19_branch2a"
top: "res4b19_branch2a"
name: "bn4b19_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b19_branch2a"
top: "res4b19_branch2a"
name: "scale4b19_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b19_branch2a"
bottom: "res4b19_branch2a"
name: "res4b19_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b19_branch2a"
top: "res4b19_branch2b"
name: "res4b19_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b19_branch2b"
top: "res4b19_branch2b"
name: "bn4b19_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b19_branch2b"
top: "res4b19_branch2b"
name: "scale4b19_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b19_branch2b"
bottom: "res4b19_branch2b"
name: "res4b19_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b19_branch2b"
top: "res4b19_branch2c"
name: "res4b19_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b19_branch2c"
top: "res4b19_branch2c"
name: "bn4b19_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b19_branch2c"
top: "res4b19_branch2c"
name: "scale4b19_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b18"
bottom: "res4b19_branch2c"
top: "res4b19"
name: "res4b19"
type: "Eltwise"
} layer {
bottom: "res4b19"
top: "res4b19"
name: "res4b19_relu"
type: "ReLU"
} layer {
bottom: "res4b19"
top: "res4b20_branch2a"
name: "res4b20_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b20_branch2a"
top: "res4b20_branch2a"
name: "bn4b20_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b20_branch2a"
top: "res4b20_branch2a"
name: "scale4b20_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b20_branch2a"
bottom: "res4b20_branch2a"
name: "res4b20_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b20_branch2a"
top: "res4b20_branch2b"
name: "res4b20_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b20_branch2b"
top: "res4b20_branch2b"
name: "bn4b20_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b20_branch2b"
top: "res4b20_branch2b"
name: "scale4b20_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b20_branch2b"
bottom: "res4b20_branch2b"
name: "res4b20_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b20_branch2b"
top: "res4b20_branch2c"
name: "res4b20_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b20_branch2c"
top: "res4b20_branch2c"
name: "bn4b20_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b20_branch2c"
top: "res4b20_branch2c"
name: "scale4b20_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b19"
bottom: "res4b20_branch2c"
top: "res4b20"
name: "res4b20"
type: "Eltwise"
} layer {
bottom: "res4b20"
top: "res4b20"
name: "res4b20_relu"
type: "ReLU"
} layer {
bottom: "res4b20"
top: "res4b21_branch2a"
name: "res4b21_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b21_branch2a"
top: "res4b21_branch2a"
name: "bn4b21_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b21_branch2a"
top: "res4b21_branch2a"
name: "scale4b21_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b21_branch2a"
bottom: "res4b21_branch2a"
name: "res4b21_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b21_branch2a"
top: "res4b21_branch2b"
name: "res4b21_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b21_branch2b"
top: "res4b21_branch2b"
name: "bn4b21_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b21_branch2b"
top: "res4b21_branch2b"
name: "scale4b21_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b21_branch2b"
bottom: "res4b21_branch2b"
name: "res4b21_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b21_branch2b"
top: "res4b21_branch2c"
name: "res4b21_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b21_branch2c"
top: "res4b21_branch2c"
name: "bn4b21_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b21_branch2c"
top: "res4b21_branch2c"
name: "scale4b21_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b20"
bottom: "res4b21_branch2c"
top: "res4b21"
name: "res4b21"
type: "Eltwise"
} layer {
bottom: "res4b21"
top: "res4b21"
name: "res4b21_relu"
type: "ReLU"
} layer {
bottom: "res4b21"
top: "res4b22_branch2a"
name: "res4b22_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b22_branch2a"
top: "res4b22_branch2a"
name: "bn4b22_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b22_branch2a"
top: "res4b22_branch2a"
name: "scale4b22_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b22_branch2a"
bottom: "res4b22_branch2a"
name: "res4b22_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b22_branch2a"
top: "res4b22_branch2b"
name: "res4b22_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b22_branch2b"
top: "res4b22_branch2b"
name: "bn4b22_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b22_branch2b"
top: "res4b22_branch2b"
name: "scale4b22_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b22_branch2b"
bottom: "res4b22_branch2b"
name: "res4b22_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b22_branch2b"
top: "res4b22_branch2c"
name: "res4b22_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b22_branch2c"
top: "res4b22_branch2c"
name: "bn4b22_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b22_branch2c"
top: "res4b22_branch2c"
name: "scale4b22_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b21"
bottom: "res4b22_branch2c"
top: "res4b22"
name: "res4b22"
type: "Eltwise"
} layer {
bottom: "res4b22"
top: "res4b22"
name: "res4b22_relu"
type: "ReLU"
} layer {
bottom: "res4b22"
top: "res4b23_branch2a"
name: "res4b23_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b23_branch2a"
top: "res4b23_branch2a"
name: "bn4b23_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b23_branch2a"
top: "res4b23_branch2a"
name: "scale4b23_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b23_branch2a"
bottom: "res4b23_branch2a"
name: "res4b23_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b23_branch2a"
top: "res4b23_branch2b"
name: "res4b23_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b23_branch2b"
top: "res4b23_branch2b"
name: "bn4b23_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b23_branch2b"
top: "res4b23_branch2b"
name: "scale4b23_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b23_branch2b"
bottom: "res4b23_branch2b"
name: "res4b23_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b23_branch2b"
top: "res4b23_branch2c"
name: "res4b23_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b23_branch2c"
top: "res4b23_branch2c"
name: "bn4b23_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b23_branch2c"
top: "res4b23_branch2c"
name: "scale4b23_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b22"
bottom: "res4b23_branch2c"
top: "res4b23"
name: "res4b23"
type: "Eltwise"
} layer {
bottom: "res4b23"
top: "res4b23"
name: "res4b23_relu"
type: "ReLU"
} layer {
bottom: "res4b23"
top: "res4b24_branch2a"
name: "res4b24_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b24_branch2a"
top: "res4b24_branch2a"
name: "bn4b24_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b24_branch2a"
top: "res4b24_branch2a"
name: "scale4b24_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b24_branch2a"
bottom: "res4b24_branch2a"
name: "res4b24_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b24_branch2a"
top: "res4b24_branch2b"
name: "res4b24_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b24_branch2b"
top: "res4b24_branch2b"
name: "bn4b24_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b24_branch2b"
top: "res4b24_branch2b"
name: "scale4b24_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b24_branch2b"
bottom: "res4b24_branch2b"
name: "res4b24_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b24_branch2b"
top: "res4b24_branch2c"
name: "res4b24_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b24_branch2c"
top: "res4b24_branch2c"
name: "bn4b24_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b24_branch2c"
top: "res4b24_branch2c"
name: "scale4b24_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b23"
bottom: "res4b24_branch2c"
top: "res4b24"
name: "res4b24"
type: "Eltwise"
} layer {
bottom: "res4b24"
top: "res4b24"
name: "res4b24_relu"
type: "ReLU"
} layer {
bottom: "res4b24"
top: "res4b25_branch2a"
name: "res4b25_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b25_branch2a"
top: "res4b25_branch2a"
name: "bn4b25_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b25_branch2a"
top: "res4b25_branch2a"
name: "scale4b25_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b25_branch2a"
bottom: "res4b25_branch2a"
name: "res4b25_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b25_branch2a"
top: "res4b25_branch2b"
name: "res4b25_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b25_branch2b"
top: "res4b25_branch2b"
name: "bn4b25_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b25_branch2b"
top: "res4b25_branch2b"
name: "scale4b25_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b25_branch2b"
bottom: "res4b25_branch2b"
name: "res4b25_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b25_branch2b"
top: "res4b25_branch2c"
name: "res4b25_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b25_branch2c"
top: "res4b25_branch2c"
name: "bn4b25_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b25_branch2c"
top: "res4b25_branch2c"
name: "scale4b25_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b24"
bottom: "res4b25_branch2c"
top: "res4b25"
name: "res4b25"
type: "Eltwise"
} layer {
bottom: "res4b25"
top: "res4b25"
name: "res4b25_relu"
type: "ReLU"
} layer {
bottom: "res4b25"
top: "res4b26_branch2a"
name: "res4b26_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b26_branch2a"
top: "res4b26_branch2a"
name: "bn4b26_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b26_branch2a"
top: "res4b26_branch2a"
name: "scale4b26_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b26_branch2a"
bottom: "res4b26_branch2a"
name: "res4b26_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b26_branch2a"
top: "res4b26_branch2b"
name: "res4b26_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b26_branch2b"
top: "res4b26_branch2b"
name: "bn4b26_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b26_branch2b"
top: "res4b26_branch2b"
name: "scale4b26_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b26_branch2b"
bottom: "res4b26_branch2b"
name: "res4b26_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b26_branch2b"
top: "res4b26_branch2c"
name: "res4b26_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b26_branch2c"
top: "res4b26_branch2c"
name: "bn4b26_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b26_branch2c"
top: "res4b26_branch2c"
name: "scale4b26_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b25"
bottom: "res4b26_branch2c"
top: "res4b26"
name: "res4b26"
type: "Eltwise"
} layer {
bottom: "res4b26"
top: "res4b26"
name: "res4b26_relu"
type: "ReLU"
} layer {
bottom: "res4b26"
top: "res4b27_branch2a"
name: "res4b27_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b27_branch2a"
top: "res4b27_branch2a"
name: "bn4b27_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b27_branch2a"
top: "res4b27_branch2a"
name: "scale4b27_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b27_branch2a"
bottom: "res4b27_branch2a"
name: "res4b27_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b27_branch2a"
top: "res4b27_branch2b"
name: "res4b27_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b27_branch2b"
top: "res4b27_branch2b"
name: "bn4b27_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b27_branch2b"
top: "res4b27_branch2b"
name: "scale4b27_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b27_branch2b"
bottom: "res4b27_branch2b"
name: "res4b27_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b27_branch2b"
top: "res4b27_branch2c"
name: "res4b27_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b27_branch2c"
top: "res4b27_branch2c"
name: "bn4b27_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b27_branch2c"
top: "res4b27_branch2c"
name: "scale4b27_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b26"
bottom: "res4b27_branch2c"
top: "res4b27"
name: "res4b27"
type: "Eltwise"
} layer {
bottom: "res4b27"
top: "res4b27"
name: "res4b27_relu"
type: "ReLU"
} layer {
bottom: "res4b27"
top: "res4b28_branch2a"
name: "res4b28_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b28_branch2a"
top: "res4b28_branch2a"
name: "bn4b28_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b28_branch2a"
top: "res4b28_branch2a"
name: "scale4b28_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b28_branch2a"
bottom: "res4b28_branch2a"
name: "res4b28_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b28_branch2a"
top: "res4b28_branch2b"
name: "res4b28_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b28_branch2b"
top: "res4b28_branch2b"
name: "bn4b28_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b28_branch2b"
top: "res4b28_branch2b"
name: "scale4b28_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b28_branch2b"
bottom: "res4b28_branch2b"
name: "res4b28_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b28_branch2b"
top: "res4b28_branch2c"
name: "res4b28_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b28_branch2c"
top: "res4b28_branch2c"
name: "bn4b28_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b28_branch2c"
top: "res4b28_branch2c"
name: "scale4b28_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b27"
bottom: "res4b28_branch2c"
top: "res4b28"
name: "res4b28"
type: "Eltwise"
} layer {
bottom: "res4b28"
top: "res4b28"
name: "res4b28_relu"
type: "ReLU"
} layer {
bottom: "res4b28"
top: "res4b29_branch2a"
name: "res4b29_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b29_branch2a"
top: "res4b29_branch2a"
name: "bn4b29_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b29_branch2a"
top: "res4b29_branch2a"
name: "scale4b29_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b29_branch2a"
bottom: "res4b29_branch2a"
name: "res4b29_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b29_branch2a"
top: "res4b29_branch2b"
name: "res4b29_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b29_branch2b"
top: "res4b29_branch2b"
name: "bn4b29_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b29_branch2b"
top: "res4b29_branch2b"
name: "scale4b29_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b29_branch2b"
bottom: "res4b29_branch2b"
name: "res4b29_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b29_branch2b"
top: "res4b29_branch2c"
name: "res4b29_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b29_branch2c"
top: "res4b29_branch2c"
name: "bn4b29_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b29_branch2c"
top: "res4b29_branch2c"
name: "scale4b29_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b28"
bottom: "res4b29_branch2c"
top: "res4b29"
name: "res4b29"
type: "Eltwise"
} layer {
bottom: "res4b29"
top: "res4b29"
name: "res4b29_relu"
type: "ReLU"
} layer {
bottom: "res4b29"
top: "res4b30_branch2a"
name: "res4b30_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b30_branch2a"
top: "res4b30_branch2a"
name: "bn4b30_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b30_branch2a"
top: "res4b30_branch2a"
name: "scale4b30_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b30_branch2a"
bottom: "res4b30_branch2a"
name: "res4b30_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b30_branch2a"
top: "res4b30_branch2b"
name: "res4b30_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b30_branch2b"
top: "res4b30_branch2b"
name: "bn4b30_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b30_branch2b"
top: "res4b30_branch2b"
name: "scale4b30_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b30_branch2b"
bottom: "res4b30_branch2b"
name: "res4b30_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b30_branch2b"
top: "res4b30_branch2c"
name: "res4b30_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b30_branch2c"
top: "res4b30_branch2c"
name: "bn4b30_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b30_branch2c"
top: "res4b30_branch2c"
name: "scale4b30_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b29"
bottom: "res4b30_branch2c"
top: "res4b30"
name: "res4b30"
type: "Eltwise"
} layer {
bottom: "res4b30"
top: "res4b30"
name: "res4b30_relu"
type: "ReLU"
} layer {
bottom: "res4b30"
top: "res4b31_branch2a"
name: "res4b31_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b31_branch2a"
top: "res4b31_branch2a"
name: "bn4b31_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b31_branch2a"
top: "res4b31_branch2a"
name: "scale4b31_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b31_branch2a"
bottom: "res4b31_branch2a"
name: "res4b31_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b31_branch2a"
top: "res4b31_branch2b"
name: "res4b31_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b31_branch2b"
top: "res4b31_branch2b"
name: "bn4b31_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b31_branch2b"
top: "res4b31_branch2b"
name: "scale4b31_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b31_branch2b"
bottom: "res4b31_branch2b"
name: "res4b31_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b31_branch2b"
top: "res4b31_branch2c"
name: "res4b31_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b31_branch2c"
top: "res4b31_branch2c"
name: "bn4b31_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b31_branch2c"
top: "res4b31_branch2c"
name: "scale4b31_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b30"
bottom: "res4b31_branch2c"
top: "res4b31"
name: "res4b31"
type: "Eltwise"
} layer {
bottom: "res4b31"
top: "res4b31"
name: "res4b31_relu"
type: "ReLU"
} layer {
bottom: "res4b31"
top: "res4b32_branch2a"
name: "res4b32_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b32_branch2a"
top: "res4b32_branch2a"
name: "bn4b32_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b32_branch2a"
top: "res4b32_branch2a"
name: "scale4b32_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b32_branch2a"
bottom: "res4b32_branch2a"
name: "res4b32_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b32_branch2a"
top: "res4b32_branch2b"
name: "res4b32_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b32_branch2b"
top: "res4b32_branch2b"
name: "bn4b32_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b32_branch2b"
top: "res4b32_branch2b"
name: "scale4b32_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b32_branch2b"
bottom: "res4b32_branch2b"
name: "res4b32_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b32_branch2b"
top: "res4b32_branch2c"
name: "res4b32_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b32_branch2c"
top: "res4b32_branch2c"
name: "bn4b32_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b32_branch2c"
top: "res4b32_branch2c"
name: "scale4b32_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b31"
bottom: "res4b32_branch2c"
top: "res4b32"
name: "res4b32"
type: "Eltwise"
} layer {
bottom: "res4b32"
top: "res4b32"
name: "res4b32_relu"
type: "ReLU"
} layer {
bottom: "res4b32"
top: "res4b33_branch2a"
name: "res4b33_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b33_branch2a"
top: "res4b33_branch2a"
name: "bn4b33_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b33_branch2a"
top: "res4b33_branch2a"
name: "scale4b33_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b33_branch2a"
bottom: "res4b33_branch2a"
name: "res4b33_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b33_branch2a"
top: "res4b33_branch2b"
name: "res4b33_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b33_branch2b"
top: "res4b33_branch2b"
name: "bn4b33_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b33_branch2b"
top: "res4b33_branch2b"
name: "scale4b33_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b33_branch2b"
bottom: "res4b33_branch2b"
name: "res4b33_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b33_branch2b"
top: "res4b33_branch2c"
name: "res4b33_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b33_branch2c"
top: "res4b33_branch2c"
name: "bn4b33_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b33_branch2c"
top: "res4b33_branch2c"
name: "scale4b33_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b32"
bottom: "res4b33_branch2c"
top: "res4b33"
name: "res4b33"
type: "Eltwise"
} layer {
bottom: "res4b33"
top: "res4b33"
name: "res4b33_relu"
type: "ReLU"
} layer {
bottom: "res4b33"
top: "res4b34_branch2a"
name: "res4b34_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b34_branch2a"
top: "res4b34_branch2a"
name: "bn4b34_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b34_branch2a"
top: "res4b34_branch2a"
name: "scale4b34_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b34_branch2a"
bottom: "res4b34_branch2a"
name: "res4b34_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b34_branch2a"
top: "res4b34_branch2b"
name: "res4b34_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b34_branch2b"
top: "res4b34_branch2b"
name: "bn4b34_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b34_branch2b"
top: "res4b34_branch2b"
name: "scale4b34_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b34_branch2b"
bottom: "res4b34_branch2b"
name: "res4b34_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b34_branch2b"
top: "res4b34_branch2c"
name: "res4b34_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b34_branch2c"
top: "res4b34_branch2c"
name: "bn4b34_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b34_branch2c"
top: "res4b34_branch2c"
name: "scale4b34_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b33"
bottom: "res4b34_branch2c"
top: "res4b34"
name: "res4b34"
type: "Eltwise"
} layer {
bottom: "res4b34"
top: "res4b34"
name: "res4b34_relu"
type: "ReLU"
} layer {
bottom: "res4b34"
top: "res4b35_branch2a"
name: "res4b35_branch2a"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b35_branch2a"
top: "res4b35_branch2a"
name: "bn4b35_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b35_branch2a"
top: "res4b35_branch2a"
name: "scale4b35_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b35_branch2a"
bottom: "res4b35_branch2a"
name: "res4b35_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res4b35_branch2a"
top: "res4b35_branch2b"
name: "res4b35_branch2b"
type: "Convolution"
convolution_param {
num_output: 256
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res4b35_branch2b"
top: "res4b35_branch2b"
name: "bn4b35_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b35_branch2b"
top: "res4b35_branch2b"
name: "scale4b35_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res4b35_branch2b"
bottom: "res4b35_branch2b"
name: "res4b35_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res4b35_branch2b"
top: "res4b35_branch2c"
name: "res4b35_branch2c"
type: "Convolution"
convolution_param {
num_output: 1024
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res4b35_branch2c"
top: "res4b35_branch2c"
name: "bn4b35_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res4b35_branch2c"
top: "res4b35_branch2c"
name: "scale4b35_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b34"
bottom: "res4b35_branch2c"
top: "res4b35"
name: "res4b35"
type: "Eltwise"
} layer {
bottom: "res4b35"
top: "res4b35"
name: "res4b35_relu"
type: "ReLU"
} layer {
bottom: "res4b35"
top: "res5a_branch1"
name: "res5a_branch1"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 2
bias_term: false
}
} layer {
bottom: "res5a_branch1"
top: "res5a_branch1"
name: "bn5a_branch1"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5a_branch1"
top: "res5a_branch1"
name: "scale5a_branch1"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res4b35"
top: "res5a_branch2a"
name: "res5a_branch2a"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 2
bias_term: false
}
} layer {
bottom: "res5a_branch2a"
top: "res5a_branch2a"
name: "bn5a_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5a_branch2a"
top: "res5a_branch2a"
name: "scale5a_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res5a_branch2a"
bottom: "res5a_branch2a"
name: "res5a_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res5a_branch2a"
top: "res5a_branch2b"
name: "res5a_branch2b"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res5a_branch2b"
top: "res5a_branch2b"
name: "bn5a_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5a_branch2b"
top: "res5a_branch2b"
name: "scale5a_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res5a_branch2b"
bottom: "res5a_branch2b"
name: "res5a_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res5a_branch2b"
top: "res5a_branch2c"
name: "res5a_branch2c"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res5a_branch2c"
top: "res5a_branch2c"
name: "bn5a_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5a_branch2c"
top: "res5a_branch2c"
name: "scale5a_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5a_branch1"
bottom: "res5a_branch2c"
top: "res5a"
name: "res5a"
type: "Eltwise"
} layer {
bottom: "res5a"
top: "res5a"
name: "res5a_relu"
type: "ReLU"
} layer {
bottom: "res5a"
top: "res5b_branch2a"
name: "res5b_branch2a"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res5b_branch2a"
top: "res5b_branch2a"
name: "bn5b_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5b_branch2a"
top: "res5b_branch2a"
name: "scale5b_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res5b_branch2a"
bottom: "res5b_branch2a"
name: "res5b_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res5b_branch2a"
top: "res5b_branch2b"
name: "res5b_branch2b"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res5b_branch2b"
top: "res5b_branch2b"
name: "bn5b_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5b_branch2b"
top: "res5b_branch2b"
name: "scale5b_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res5b_branch2b"
bottom: "res5b_branch2b"
name: "res5b_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res5b_branch2b"
top: "res5b_branch2c"
name: "res5b_branch2c"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res5b_branch2c"
top: "res5b_branch2c"
name: "bn5b_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5b_branch2c"
top: "res5b_branch2c"
name: "scale5b_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5a"
bottom: "res5b_branch2c"
top: "res5b"
name: "res5b"
type: "Eltwise"
} layer {
bottom: "res5b"
top: "res5b"
name: "res5b_relu"
type: "ReLU"
} layer {
bottom: "res5b"
top: "res5c_branch2a"
name: "res5c_branch2a"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res5c_branch2a"
top: "res5c_branch2a"
name: "bn5c_branch2a"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5c_branch2a"
top: "res5c_branch2a"
name: "scale5c_branch2a"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res5c_branch2a"
bottom: "res5c_branch2a"
name: "res5c_branch2a_relu"
type: "ReLU"
} layer {
bottom: "res5c_branch2a"
top: "res5c_branch2b"
name: "res5c_branch2b"
type: "Convolution"
convolution_param {
num_output: 512
kernel_size: 3
pad: 1
stride: 1
bias_term: false
}
} layer {
bottom: "res5c_branch2b"
top: "res5c_branch2b"
name: "bn5c_branch2b"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5c_branch2b"
top: "res5c_branch2b"
name: "scale5c_branch2b"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
top: "res5c_branch2b"
bottom: "res5c_branch2b"
name: "res5c_branch2b_relu"
type: "ReLU"
} layer {
bottom: "res5c_branch2b"
top: "res5c_branch2c"
name: "res5c_branch2c"
type: "Convolution"
convolution_param {
num_output: 2048
kernel_size: 1
pad: 0
stride: 1
bias_term: false
}
} layer {
bottom: "res5c_branch2c"
top: "res5c_branch2c"
name: "bn5c_branch2c"
type: "BatchNorm"
batch_norm_param {
use_global_stats: true
}
} layer {
bottom: "res5c_branch2c"
top: "res5c_branch2c"
name: "scale5c_branch2c"
type: "Scale"
scale_param {
bias_term: true
}
} layer {
bottom: "res5b"
bottom: "res5c_branch2c"
top: "res5c"
name: "res5c"
type: "Eltwise"
} layer {
bottom: "res5c"
top: "res5c"
name: "res5c_relu"
type: "ReLU"
} layer {
bottom: "res5c"
top: "pool5"
name: "pool5"
type: "Pooling"
pooling_param {
kernel_size: 7
stride: 1
pool: AVE
}
} layer {
bottom: "pool5"
top: "fc3"
name: "fc3"
type: "InnerProduct"
inner_product_param {
num_output: 3
}
} layer {
bottom: "fc3"
top: "prob"
name: "prob"
type: "Softmax"
}
solver.prototxt
net: "/home/wy/ResNet152/train_val.prototxt"
test_iter: 1003
test_interval: 4000
test_initialization: false
display: 100
average_loss: 100
base_lr: 0.05
lr_policy: "step"
stepsize: 150000
gamma: 0.1
max_iter: 600000
momentum: 0.9
weight_decay: 0.0001
snapshot: 40000
snapshot_prefix: "/home/wy/ResNet152/model/"
solver_mode: GPU
作为一枚技术小白，写这篇笔记的时候参考了很多博客论文，在这里表示感谢，同时，未经同意，请勿转载....