02 软件环境.md · 知行合一/nvidia_jetson_nano_practice

## 软件环境

### 常用软件安装

- 软件安装
```
sudo apt-get update
sudo apt full-upgrade
sudo apt-get install libhdf5-serial-dev hdf5-tools zlib1g-dev zip libjpeg8-dev libhdf5-dev  python3-pip
sudo apt-get install git cmake libpython3-dev python3-numpy
sudo apt-get install libgtk2.0-dev pkg-config
sudo apt-get install libcanberra-gtk-module
```
- python库安装
```
pip3 install cython
pip3 install numpy
pip3 install jupyter notebook jypyterlab
```

- jetson性能查看工具

用来查看jetson-nano的CPU、GPU、内存、硬盘等资源的利用情况
```
sudo pip3 install jetson-stats
sudo jtop
```
![](https://arloseimg.oss-cn-hangzhou.aliyuncs.com/20200227105638.png)

### jetson相关软件安装

- [opencv](https://github.com/opencv/opencv/archive/4.2.0.zip)
```
unzip 4.2.0.zip
cd opencv-4.2.0
mkdir build
cd build
cmake ..
make -j4
sudo make install
```

- dlib

```
wget http://dlib.net/files/dlib-19.17.tar.bz2 
tar jxvf dlib-19.17.tar.bz2
cd dlib-19.17
```
修改cudnn_dlibapi.cpp
```
vim dlib/cuda/cudnn_dlibapi.cpp
comment line 854
    //forward_algo = forward_best_algo;
```
编译
```
sudo python3 setup.py install
```

- [pytorch](https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/)

```
wget https://nvidia.box.com/shared/static/ncgzus5o23uck9i5oth2n8n06k340l6k.whl -O torch-1.4.0-cp36-cp36m-linux_aarch64.whl
sudo apt-get install python3-pip libopenblas-base
pip3 install Cython
pip3 install numpy torch-1.4.0-cp36-cp36m-linux_aarch64.whl
```
[torch whl百度云链接（提取码:7i5x）](https://pan.baidu.com/s/15cmS0FHQxGL8-yWc_pCxUQ)

验证pytorch是否安装成功
```
import torch
print(torch.__version__)
print('CUDA available: ' + str(torch.cuda.is_available()))
print('cuDNN version: ' + str(torch.backends.cudnn.version()))
a = torch.cuda.FloatTensor(2).zero_()
print('Tensor a = ' + str(a))
b = torch.randn(2).cuda()
print('Tensor b = ' + str(b))
c = a + b
print('Tensor c = ' + str(c))
```
- torchvision
```
$ sudo apt-get install libjpeg-dev zlib1g-dev
$ git clone --branch v0.5.0 https://github.com/pytorch/vision torchvision
$ cd torchvision
$ sudo python3 setup.py install
```
验证torchvision是否安装成功
```
import torchvision
print(torchvision.__version__)
```

- tensorflow(选装)
```
$ sudo apt-get install libhdf5-serial-dev hdf5-tools libhdf5-dev zlib1g-dev zip libjpeg8-dev
$ sudo apt-get install python3-pip
$ sudo pip3 install -U pip
$ sudo pip3 install -U numpy grpcio absl-py py-cpuinfo psutil portpicker six mock requests gast h5py astor termcolor protobuf keras-applications keras-preprocessing wrapt google-pasta
$ sudo pip3 install --pre --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v42 tensorflow-gpu==1.14.0+nv19.7
```
时间会有点久 安装好后测试下有没有装好
```
python3
Python 3.6.7 (default, Oct 22 2018, 11:32:17)
[GCC 8.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
'1.13.1'
```
有版本提示即安装完成

python调用TensorFlow时出现FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecate

numpy降级试试
```
sudo pip3 install numpy==1.16.0
```
降级后就没有出现警告了

- npm

```
wget https://nodejs.org/dist/v12.13.0/node-v12.13.0-linux-arm64.tar.xz
tar -xJf node-v12.13.0-linux-arm64.tar.xz
cd node-v12.13.0-linux-arm64
sudo cp -R * /usr/local/
node -v
npm -v
```

### 常见问题

#### 默认软件源安装和更新速度太慢，可以替换为国内源
```
sudo cp /etc/apt/sources.list /etc/apt/sources.list.bak # 将原镜像源文件做一个备份

#用自己喜欢的方式，把源文件的内容，替换成如下
sudo vim /etc/apt/sources.list #vim方式
sudo gedit /etc/apt/sources.list #图形界面用gedit编辑

#文件内容删除，替换成如下内容，这是清华的源
deb http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic main multiverse restricted universe
deb http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-security main multiverse restricted universe
deb http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-updates main multiverse restricted universe
deb http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-backports main multiverse restricted universe
deb-src http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic main multiverse restricted universe
deb-src http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-security main multiverse restricted universe
deb-src http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-updates main multiverse restricted universe
deb-src http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ bionic-backports main multiverse restricted universe
```
#### python库安装也比较慢，可以在后面加入douban源
```
-i http://pypi.douban.com/simple --trusted-host pypi.douban.com
```
或者直接换源
```
mkdir ~/.pip
vim ~/.pip/pip.conf
```
填入以下内容：
```
[global]
index-url = https://pypi.tuna.tsinghua.edu.cn/simple 
trusted-host = pypi.tuna.tsinghua.edu.cn
```

#### 内存不够，如何增加swap空间

```
sudo fallocate -l 4G /swapfile   # 创建swap分区，分区大小设置为4G，可自己调节
sudo chmod 600 /swapfile         # 修改swap分区使用权限，只允许root用户访问
sudo mkswap /swapfile            # 将文件标记为swap空间
sudo swapon /swapfile            # 启用swap空间，关机再开机后，需要再次利用此命令启用swap空间
free -h                          # 验证swap空间是否可用
```

#### 关闭图形用户界面

关闭图形用户界面可以为程序运行空出更多的资源
```
#关闭图形用户界面
sudo systemctl set-default multi-user.target
sudo reboot
 
#启用图形用户界面
sudo systemctl set-default graphical.target
sudo reboot
```

#### github在网络情况不稳定下克隆项目时，可能会出现如下错误: Clone failed RPC failed; curl 56 GnuTLS recv error (-54): Error in the pull function. The remote end hung up unexpectedly early EOF index-pack failed.

解决方法: 加大httpBuffer
```
$ git config --global http.postBuffer 524288000
```
或修改配置文件~/.bashrc，在下面加以下三行：
```
export GIT_TRACE_PACKET=1
export GIT_TRACE=1
export GIT_CURL_VERBOSE=1
```
或者只下载项目文件的最新版本:
```
git clone https://github.com/dusty-nv/jetson-inference --depth 1
```
或者转存github项目到gitee上，再从gitee上clone项目到本地。

#### Linux中Python和pip的安装及“AttributeError：module 'pip.__main__' has no attribute '_main'错误”
---
正确安装方法：

```
sudo apt-get install python-pip python-dev build-essential  #下载并安装pip
pip install --upgrade pip  #更新pip
```
更新完pip之后，新版的pip需要按照网上的教程修改配置文件才能用，修改过程如下：

```
#打开pip的配置文件
#这里一定要记得加sudo，也就是以管理员身份打开，否则没有权限修改文件
sudo gedit /usr/bin/pip

#按照以下内容修改文件的对应部分
from pip import __main__
if __name__ == '__main__':
    sys.exit(__main__._main())
```
如果上面的错，就把文件先改回去，多更新几遍，然后再按这个方法修改文件就可以了，直到你输入pip会提示你pip的各种命令使用方法，就成功了。

### 参考链接
- [Nvidia Developer Forums](https://devtalk.nvidia.com/)
- [Github awesome-jetson-nano](https://github.com/elloza/awesome-jetson-nano)
- [Github nano_build_opencv](https://github.com/mdegans/nano_build_opencv)
- [Github jetson_stats](https://github.com/rbonghi/jetson_stats)
- [Github jetson_nano](https://github.com/jkjung-avt/jetson_nano)
- [Github jetcard](https://github.com/NVIDIA-AI-IOT/jetcard)
- [Github nano_playground](https://github.com/uutzinger/nano_playground)
- [玩转Jetson Nano（二）检查已安装组件](https://blog.csdn.net/beckhans/article/details/89138876)
- [玩转Jetson Nano（三）安装TensorFlow GPU](https://blog.csdn.net/beckhans/article/details/89146881)
- [玩转Jetson Nano（六）安装caffe](https://blog.csdn.net/beckhans/article/details/89393280)
- [玩转Jetson Nano（十）安装pytorch](https://blog.csdn.net/beckhans/article/details/91386429)
- [玩转Jetson Nano（十一）无显示器使用nano的问题](https://blog.csdn.net/beckhans/article/details/101352020)
- [Jetson Nano开箱配置及tensorflow-gpu、keras安装（一）](https://blog.csdn.net/alphonse2017/article/details/89493645)
- [内存不足，创建swapfile](https://support.rackspace.com/how-to/create-a-linux-swap-file/)
- [开启vnc](https://blog.csdn.net/Billio/article/details/103122415)
- [Jetson-nano 使用中的一些技巧](https://zhuanlan.zhihu.com/p/80809006)
- [nodejs](https://devtalk.nvidia.com/default/topic/1065664/jetson-nano/how-to-install-node-js-/)
- [如何远程访问Jetson NANO](https://cloud.tencent.com/developer/article/1541204)
- [TX2入门教程软件篇-安装Jupyter](https://www.ncnynl.com/archives/201910/3373.html)
- [Jetson Nano安装 Jupyter lab](https://www.cnblogs.com/cloudrivers/p/12233456.html)

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