jetson tx2 编译及运行faster-rcnn的物体检测例程demo

环境：jetson tx2 + jetpack 3.2（cuda9.0+cudnn5）

第一步：下载源码

git clone --recursive https://github.com/rbgirshick/py-faster-rcnn.git

第二步：复制makefile，编译过caffe的肯定很熟悉

cp Makefile.config.example Makefile.config

第三步：修改Makefile和Makefile.config里面的内容，和编译caffe时候很像

Makefile:
修改为：
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

Makefile.config:
修改成为以下内容
# cuDNN acceleration switch (uncomment to build with cuDNN).
USE_CUDNN := 1

# Uncomment if you're using OpenCV 3
OPENCV_VERSION := 3

# Uncomment to support layers written in Python (will link against Python libs)
WITH_PYTHON_LAYER := 1

# We need to be able to find Python.h and numpy/arrayobject.h.
PYTHON_INCLUDE := /usr/include/python2.7 \
		/usr/local/lib/python2.7/dist-packages/numpy/core/include

# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /aarch64-linux-gnu/hdf5/serial

第四步：进入py-faster-rcnn/lib目录下

make

第五步：JetPack3.2 的cudnn版本新需要替换一些文件

1）找到caffe中的
include/caffe/layers/cudnn_relu_layer.hpp,
src/caffe/layers/cudnn_relu_layer.cpp,
src/caffe/layers/cudnn_relu_layer.cu

include/caffe/layers/cudnn_sigmoid_layer.hpp
src/caffe/layers/cudnn_sigmoid_layer.cpp
src/caffe/layers/cudnn_sigmoid_layer.cu

include/caffe/layers/cudnn_tanh_layer.hpp
src/caffe/layers/cudnn_tanh_layer.cpp
src/caffe/layers/cudnn_tanh_layer.cu

include/caffe/util/cudnn.hpp

替换掉faster-rcnn对应的文件

2）将 faster rcnn 中的 src/caffe/layers/cudnn_conv_layer.cu 文件中的两个函数

cudnnConvolutionBackwardData_v3 函数名替换为 cudnnConvolutionBackwardData

cudnnConvolutionBackwardFilter_v3函数名替换为 cudnnConvolutionBackwardFilter

第六步：编译

caffe-fast-rcnn目录下：

make -j8 && make pycaffe

第七步：下载模型

1）在终端下载：
cd $FRCN_ROOT
./data/scripts/fetch_faster_rcnn_models.sh
速度很慢，会出现time out

2）使用aria2+uget+firefox的方法下载百度云上的模型文件
sudo add-apt-repository ppa:plushuang-tw/uget-stable
sudo add-apt-repository ppa:t-tujikawa/ppa
sudo apt-get install aria2
sudo apt-get install uget

将firefox的百度云文件导出为aria2文件，在uget里下载即可（类似迅雷链接）
下载前需要配置一下uge，很简单网上有教程

下面是模型的aria2的文本，复制到uget新建下载任务就可
https://d.pcs.baidu.com/file/7e9db88ca720b26f069e934b5a974d3e?fid=3106987140-250528-1079755257952860&dstime=1532435155&rt=sh&sign=FDtAERV-DCb740ccc5511e5e8fedcff06b081203-1%2BBYMqQg72ypDN%2B2jWPmL2Smdb0%3D&expires=8h&chkv=1&chkbd=0&chkpc=&dp-logid=139394917580929411&dp-callid=0&r=252466376
 header=User-Agent: netdisk;5.3.4.5;PC;PC-Windows;5.1.2600;WindowsBaiduYunGuanJia
 header=Referer: https://pan.baidu.com/disk/home
 header=Cookie: pcsett=1532521194-dab94490173bbdb1a4df6dc4745cbaef
 out="faster_rcnn_models.tar"

下载完成后解压到data目录下

第八步：运行demo

./data/scripts/fetch_faster_rcnn_models.sh

一共十张照片

遇到的一些问题：

make: * [.build_release/examples/cifar10/convert_cifar_data.bin] 错误
make: *** [.build_release/tools/caffe.bin] Error 1

1）make clean 重新编译
2）delete /usr/lib/libcaffe.so文件

[.build_release/tools/extract_features.bin] Error 1
看看makefile.config里面是否用到了anaconda，若有注释掉

jetson tx2 编译及运行faster-rcnn的物体检测例程demo

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