install opencv4.6.0 with CUDA for Jetson

參考 https://forums.developer.nvidia.com/t/best-way-to-install-opencv-with-cuda-on-jetpack-5-xavier-nx-opencv-for-tegra/222777

下載 install_opencv4.6.0_jetson.sh 備份如下

#!/bin/bash

#

# Copyright (c) 2022, NVIDIA CORPORATION.  All rights reserved.

#

# NVIDIA Corporation and its licensors retain all intellectual property

# and proprietary rights in and to this software, related documentation

# and any modifications thereto.  Any use, reproduction, disclosure or

# distribution of this software and related documentation without an express

# license agreement from NVIDIA Corporation is strictly prohibited.

#

version="4.6.0"

folder="workspace"

for (( ; ; ))

do

    echo "Do you want to remove the default OpenCV (yes/no)?"

    read rm_old

    if [ "$rm_old" = "yes" ]; then

        echo "** Remove other OpenCV first"

        sudo apt -y purge *libopencv*

break

    elif [ "$rm_old" = "no" ]; then

break

    fi

done

echo "------------------------------------"

echo "** Install requirement (1/4)"

echo "------------------------------------"

sudo apt-get update

sudo apt-get install -y build-essential cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev

sudo apt-get install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev

sudo apt-get install -y python3.8-dev python-dev python-numpy python3-numpy

sudo apt-get install -y libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libdc1394-22-dev

sudo apt-get install -y libv4l-dev v4l-utils qv4l2 v4l2ucp

sudo apt-get install -y curl

echo "------------------------------------"

echo "** Download opencv "${version}" (2/4)"

echo "------------------------------------"

mkdir $folder

cd ${folder}

curl -L https://github.com/opencv/opencv/archive/${version}.zip -o opencv-${version}.zip

curl -L https://github.com/opencv/opencv_contrib/archive/${version}.zip -o opencv_contrib-${version}.zip

unzip opencv-${version}.zip

unzip opencv_contrib-${version}.zip

rm opencv-${version}.zip opencv_contrib-${version}.zip

cd opencv-${version}/

echo "------------------------------------"

echo "** Build opencv "${version}" (3/4)"

echo "------------------------------------"

mkdir release

cd release/

cmake -D WITH_CUDA=ON -D WITH_CUDNN=ON -D CUDA_ARCH_BIN="7.2,8.7" -D CUDA_ARCH_PTX="" -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-${version}/modules -D WITH_GSTREAMER=ON -D WITH_LIBV4L=ON -D BUILD_opencv_python3=ON -D BUILD_TESTS=OFF -D BUILD_PERF_TESTS=OFF -D BUILD_EXAMPLES=OFF -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..

make -j$(nproc)

echo "------------------------------------"

echo "** Install opencv "${version}" (4/4)"

echo "------------------------------------"

sudo make install

echo 'export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH' >> ~/.bashrc

echo 'export PYTHONPATH=/usr/local/lib/python3.8/site-packages/:$PYTHONPATH' >> ~/.bashrc

source ~/.bashrc

echo "** Install opencv "${version}" successfully"

echo "** Bye :)"

將 cv2 加到 python3 中

$ export PYTHONPATH=$PYTHONPATH:/usr/local/lib/python3.8/site-packages

$ python3

>>> import cv2

>>> cnt = cv2.cuda.getCudaEnabledDeviceCount()

>>> cnt

1 表示有 CUDA

Jetpack L4T 35.1.0 風扇

jtop 無法在這個版本控制和查看 風扇

$ vi get_fan.sh

TEMP=`cat /sys/class/hwmon/hwmon0/temp1_input`

TEMP=$(echo "scale=2; ${TEMP}/1000" | bc)

echo Thermal=${TEMP}C

PWM=`cat /sys/class/hwmon/hwmon2/pwm1`

RPM=`cat /sys/class/hwmon/hwmon1/rpm`

echo FAN=$(( PWM * 100 / 255 ))% ${RPM}rpm

tensorflow 在 Xavier 出現 cannot allocate memory in static TLS block 錯誤

其實會出現這個問題是 gym tensorflow 衝突 原因

解決這個問題，就部會出現下列問題

Traceback (most recent call last):

  File "/home/UserName/envs/tf2.10.0/lib/python3.8/site-packages/tensorflow/python/pywrap_tensorflow.py", line 62, in <module>

    from tensorflow.python._pywrap_tensorflow_internal import *

ImportError: /home/UserName/envs/tf2.10.0/lib/python3.8/site-packages/tensorflow/python/../../tensorflow_cpu_aws.libs/libgomp-d22c30c5.so.1.0.0: cannot allocate memory in static TLS block

$ vi .bashrc

export LD_PRELOAD=/home/UserName/envs/tf2.10.0/lib/python3.8/site-packages/tensorflow/python/../../tensorflow_cpu_aws.libs/libgomp-d22c30c5.so.1.0.0

安裝 Xavier JetPack 5.0.2

Download NVIDIA SDK Manager 1.8.4

https://developer.nvidia.com/nvidia-sdk-manager

選擇 .deb Ubuntu

$ sudo dpkg -i sdkmanager_1.8.4-10431_amd64.deb

[sudo] password for mark: 

Selecting previously unselected package sdkmanager.

(Reading database ... 340238 files and directories currently installed.)

Preparing to unpack sdkmanager_1.8.4-10431_amd64.deb ...

Unpacking sdkmanager (1.8.4-10431) ...

dpkg: dependency problems prevent configuration of sdkmanager:

 sdkmanager depends on libgconf-2-4; however:

  Package libgconf-2-4 is not installed.

 sdkmanager depends on libcanberra-gtk-module; however:

  Package libcanberra-gtk-module is not installed.

dpkg: error processing package sdkmanager (--install):

 dependency problems - leaving unconfigured

Processing triggers for gnome-menus (3.13.3-11ubuntu1.1) ...

Processing triggers for desktop-file-utils (0.23-1ubuntu3.18.04.2) ...

Processing triggers for mime-support (3.60ubuntu1) ...

Processing triggers for hicolor-icon-theme (0.17-2) ...

Errors were encountered while processing:

 sdkmanager

出錯，使用下列命令修正

$ sudo apt --fix-broken install

$ sdkmanager

ADDITIONAL SDKS/DeepStream 要打勾

按 CONTINUE TO STEP 02

勾選 I accept the terms and conditions of the license aggrements

按 CONTINUE TO STEP 03

選擇 Manual Setup = Jetson AGX Xavier

角落起算

1. Power Button

2. Force Recovery Button

3. Reset Button

將 xavier 40-Pin 邊的(電源指示燈旁的) USB 連接至安裝主機

關機後先壓工程模式鍵（Recovery）再同時按壓電源鍵（Power），兩秒後放開進入工程模式

開啟螢幕，等待 Xavier 安裝完成開啟登入畫面

不用登入，按下 Install，繼續等待

$ sudo apt-get install python3-pip

$ sudo -H pip3 install jetson-stats

$ sudo systemctl restart jetson_stats.service

$ sudo jtop

$ sudo vi /etc/nvfancontrol.conf

        FAN_PROFILE full {

                #TEMP   HYST    PWM     RPM

                0       8       255     3640

                140     0       255     3640

        }

FAN_DEFAULT_PROFILE quite

FAN_DEFAULT_PROFILE cool

$ sudo systemctl stop nvfancontrol.service

$ sudo rm /var/lib/nvfancontrol/status

$ sudo vi /etc/nvfancontrol.conf

$ sudo systemctl start nvfancontrol.service

$ sudo cat /var/lib/nvfancontrol/status

$ sudo apt update

$ mkdir -p ~/.config/autostart

$ cp /usr/share/applications/vino-server.desktop ~/.config/autostart/

$ gsettings set org.gnome.Vino prompt-enabled false

$ gsettings set org.gnome.Vino require-encryption false

$ gsettings set org.gnome.Vino prompt-enabled false

$ gsettings set org.gnome.Vino require-encryption false

$ gsettings set org.gnome.Vino authentication-methods "['vnc']"

$ gsettings set org.gnome.Vino vnc-password $(echo -n 'ChangeToYourPasswd'|base64)

$ sudo vi /etc/gdm3/custom.conf

WaylandEnable=false

AutomaticLoginEnable = true

AutomaticLogin = UserLoginName

但發現 vino 比 x11vnc 慢，所以刪除 vino-server.desktop, 回復 custom.conf，改安裝 x11vnc

$ sudo apt-get install x11vnc

$ x11vnc -storepasswd

$ vi x11vnc_0.sh #其中124為gdm的user id, 可在 /etc/passwd 查詢

sudo /usr/bin/x11vnc -display :0 -auth /var/run/user/124/gdm/Xauthority -rfbauth /home/UserName/.vnc/passwd

$ cat x11vnc_1.sh

DISP=`ps -u $(id -u) -o pid= | \

    while read pid; do

        cat /proc/$pid/environ 2>/dev/null | tr '\0' '\n' | grep '^DISPLAY=:'

    done | grep -o ':[0-9]*' | sort -u`

DISPLAY=$DISP x11vnc -rfbport 5900 -rfbauth /home/UserName/.vnc/passwd

$ chmod +x x11vnc_0.sh x11vnc_1.sh

$ ./x11vnc_0.sh

使用 vnc client 登入，並輸入使用者名稱和密碼，然後變成黑畫面

別擔心此時主機已經登入，直接關閉 vnc client

$ ./x11vnc_1.sh

在使用一次 vnc client 登入即可

$ sudo apt-get install xserver-xorg-video-dummy

$ sudo vi /etc/X11/xorg.conf

Section "Module"

    Disable     "dri"

    SubSection  "extmod"

    Option  "omit xfree86-dga"

    EndSubSection

EndSection

Section "Device"

    Identifier  "Tegra0"

    Driver      "nvidia"

    # 必須改成 false, 否則未接螢幕時, vino 會顯示 nvidia 的 long

    Option      "AllowEmptyInitialConfiguration" "false"

EndSection

Section "ServerFlags"

    Option "AutoAddGPU" "false"

EndSection

Section "Screen"

    Identifier  "Nvidia Screen"

    Device      "Tegra0"

EndSection

Section "Device"

    Identifier  "Dummy Video Device"

    Driver      "dummy"

    VideoRam    256000

EndSection

Section "Monitor"

    Identifier  "Dummy Monitor"

    HorizSync   5.0-1000.0

    VertRefresh 5.0-200.0

    Modeline    "1920x1080" 173.00 1920 2048 2248 2576 1080 1083 1088 1120 -hsync +vsync

EndSection

Section "Screen"

    Identifier  "Dummy Screen"

    Monitor     "Dummy Monitor"

    Device      "Dummy Video Device"

    SubSection  "Display"

        Depth   24

        Virtual 1920 1080

    EndSubSection

EndSection

Section "ServerLayout"

    Identifier "Main Layout"

    Screen 0 "Nvidia Screen"

    Screen 1 "Dummy Screen"

EndSection

vi vino.sh

#!/bin/bash

### BEGIN INIT INFO

# Provides:          vino-server

# Required-Start:    $local_fs

# Required-Stop:     $local_fs

# Should-Start:

# Should-Stop:

# X-Start-Before:

# X-Stop-After:

# Default-Start:     2 3 4 5

# Default-Stop:      0 1 6

# Short-Description: vino-server

### END INIT INFO

PIDFILE="/tmp/vino-server.pid"

NAME="vino-server"

GREPFILTER="/usr/lib/vino/vino-server"

service_kill() {

       ### kill -9

       PIDS="`ps aux |grep -v grep |grep -P "${GREPFILTER}" |awk '{print $2}' | tr '\n' ' ' `"

       if [ -n "$PIDS" ]; then

           echo "sleep 5"

           sleep 5

           PIDS="`ps aux |grep -v grep |grep -P "${GREPFILTER}" |awk '{print $2}' | tr '\n' ' ' `"

           if [ -n "$PIDS" ]; then

               echo "kill -9 ${PIDS}"

               kill -9 ${PIDS}

           fi

       fi

       if [ -f ${PIDFILE} ]; then

           echo "rm ${PIDFILE}"

           rm ${PIDFILE}

       fi

}

service_status() {

       PID="`cat ${PIDFILE}`"

       if [ -n "$PID" ]; then

           echo "${PIDFILE} : ${PID}"

       else

           echo "file doesnt' exist : ${PIDFILE}"

       fi

       PIDS="`ps aux |grep -v grep |grep -P "${GREPFILTER}" |awk '{print $2}' | tr '\n' ' ' `"

       if [ -n "$PIDS" ]; then

           echo "PROCESSES:"

           echo "$PIDS"

       fi

}

service_start() {

       PIDS="`ps aux |grep -v grep |grep -P "${GREPFILTER}" |awk '{print $2}' | tr '\n' ' ' `"

       if [ -n "$PIDS" ]; then

            echo "process is present : ${PIDS}"

            echo $PIDS > ${PIDFILE}

            chmod 644 ${PIDFILE}

            exit 0

       else

            gconftool-2 -s -t bool /desktop/gnome/remote_access/enabled true

            gconftool-2 --type bool --set /desktop/gnome/remote_access/prompt_enabled 0

            export DISPLAY=:0.0

            /usr/lib/vino/vino-server --sm-disable &

            sleep 2

            PIDS="`ps aux |grep -v grep |grep -P "${GREPFILTER}" |awk '{print $2}' | tr '\n' ' ' `"

            if [ -n "$PIDS" ]; then

                 echo "$PIDS"

                 echo $PIDS > ${PIDFILE}

                 chmod 644 ${PIDFILE}

            fi

       fi

}

service_stop() {

       PIDS="`ps aux |grep -v grep |grep -P "${GREPFILTER}" |awk '{print $2}' | tr '\n' ' ' `"

       if [ -n "$PIDS" ]; then

           echo "kill ${PIDS}"

           kill ${PIDS}

       fi

       if [ -f ${PIDFILE} ]; then

           echo "rm ${PIDFILE}"

           rm ${PIDFILE}

       fi

}

case $1 in

   start)

     service_start;;

   stop)

     service_stop;

     service_kill;;

   kill)

     service_kill;;

   restart)

     service_stop;

     service_start;;

   status)

     service_status;;

   *)

     echo "usage: $0 {start|stop|kill|restart|status}" ;

     echo "example: $0 start" ;

esac

exit 0

Mount Disks

按左下角 Show Applications, 輸入 Disks

按下 Disks

選擇左側儲存裝置

按設定按鈕，選擇 Edit Mount Options

User Session Defaults 選擇 OFF

輸入 Mount Point

按下 Mount selected partition

Ubuntu 中文輸入

Xavier

$ sudo apt install ibus-chewing

System Settings/Language Support

按 Install / Remove Langeages...

點選 Chinese (traditional)

按 Apply

$ sudo reboot

System Settings/Text Entry

按 + 選 Chinese (chewing)(IBus)

$ sudo reboot

auto mount nfs after boot

$ sudo vi /etc/fstab

ip:/folder /media/folder        auto    noauto,x-systemd.automount 0 0

Install JetPack 4.6

參考 https://yingrenn.blogspot.com/2020/05/install-jetpack-44.html

$ sudo apt update

$ sudo dpkg -i sdkmanager_1.6.1-8175_amd64.deb

(Reading database ... 346387 files and directories currently installed.)

Preparing to unpack sdkmanager_1.6.1-8175_amd64.deb ...

Unpacking sdkmanager (1.6.1-8175) over (1.6.1-8175) ...

dpkg: dependency problems prevent configuration of sdkmanager:

 sdkmanager depends on libgconf-2-4; however:

  Package libgconf-2-4 is not installed.

 sdkmanager depends on libcanberra-gtk-module; however:

  Package libcanberra-gtk-module is not installed.

dpkg: error processing package sdkmanager (--install):

 dependency problems - leaving unconfigured

Processing triggers for gnome-menus (3.13.3-11ubuntu1.1) ...

Processing triggers for desktop-file-utils (0.23-1ubuntu3.18.04.2) ...

Processing triggers for mime-support (3.60ubuntu1) ...

Processing triggers for hicolor-icon-theme (0.17-2) ...

Errors were encountered while processing:

 sdkmanager

出錯，使用下列命令

$ sudo apt --fix-broken install

$ sdkmanager

Install JetPack 4.4

https://developer.nvidia.com/embedded/jetpack

$ sudo apt update
$ sudo apt-get install python

選擇 Download the NVIDIA SDK Manager
$ sudo dpkg -i sdkmanager_1.1.0-6343_amd64.deb

$ sdkmanager

此時會檢查記憶體空間和螢幕解析度
硬碟要求也越來越大

輸入 NVIDIA DEVELOPER 帳號密碼

在 Step 01, 選 Target Hardware: Jetson AGX Xavier

CONTINUE TO STEP 02
勾選 I accept the terms and conditions of the license agreements
CONTINUE TO STEP 03
輸入 root 密碼
連接 Xavier 40-Pin 邊的 usb, 到安裝主機的 usb
會使用此連線(192.168.55.1)到被安裝主機

選擇 Automatic setup 或 Manual setup
Automatic 是要在已經安裝過，可以 login 的機器
輸入 IP, Username, Password

Finish
Manual 可以用在未安裝的機器
Force Recover button
Power button
同時放開

輸入 IP, Username, Password

切換到被安裝主機繼續設定
選擇鍵盤，時區，主機名稱，使用者名稱，密碼

jetson_clocks.sh 已經改成 jetson_clocks

sudo apt-get install python3-pip
sudo pip3 install jetson-stats
sudo vi /etc/rc.local
#!/bin/bash
sleep 10
sudo sh -c 'echo 100 > /sys/devices/pwm-fan/target_pwm'
sudo chmod u+x /etc/rc.local

安裝中文

System Settings/Language Support
sudo apt-get install ibus-chewing
reboot
System Settings/Text Entry
+ Chinese (Chewing)(IBus)
Switch to next source using: Ctrl+Space

sudo apt-get install x11vnc
sudo x11vnc -storepasswd
sudo chmod 644 ~/.vnc/passwd

設定預設聲音輸出
sudo vi /etc/pulse/default.pa
最底部
#set-default-sink output
set-default-sink 0
#set-default-sink input

設定 menu & title bar 大小
/usr/bin/gsettings set com.ubuntu.user-interface scale-factor "{'HDMI-0': 16}"

設定 滑鼠游標 大小
gsettings set org.gnome.desktop.interface cursor-size 48

自動執行
收尋/Startup Applications

Ubuntu 設定預設聲音輸出

參考 How do you set a default audio output device in Ubuntu 18.04?
參考 How to change pulseaudio sink with “pacmd set-default-sink” during playback?

vidia@nvidia-desktop:~$ pactl list short

sources 0 alsa_output.platform-3510000.hda.hdmi-stereo-extra2.monitor module-alsa-card.c s16le 2ch 44100Hz SUSPENDED 

1 alsa_output.platform-sound.analog-stereo.monitor module-alsa-card.c s16le 2ch 44100Hz SUSPENDED 

2 alsa_input.platform-sound.analog-stereo module-alsa-card.c s16le 2ch 44100Hz SUSPENDED

nvidia@nvidia-desktop:~$ sudo vi /etc/pulse/default.pa  

### Make some devices default 

#set-default-sink output 

set-default-sink 0 

#set-default-source input

nvidia@nvidia-desktop:~$ pacmd list-sinks
2 sink(s) available.
  * index: 0
name: <alsa_output.platform-3510000.hda.hdmi-stereo-extra2>
driver: <module-alsa-card.c>

    index: 1

name: <alsa_output.platform-sound.analog-stereo>

driver: <module-alsa-card.c>

nvidia@nvidia-desktop:~$ pacmd set-default-sink 1

nvidia@nvidia-desktop:~$ pacmd set-default-sink 0

Build OpenCV 3.4 with CUDA

Build OpenCV 3.4 on NVIDIA Jetson AGX Xavier Developer Kit

原先內建的 OpenCV 放在 /usr

心建立的會放在 /usr/local

$ git clone https://github.com/jetsonhacks/buildOpenCVXavier.git
$ cd buildOpenCVXavier
$ git checkout v1.0
$ ./buildOpenCV.sh

sudo ln -s /usr/local/lib/python3.6/dist-packages/cv2.cpython-36m-aarch64-linux-gnu.so envs/OpenAiGym/lib/python3.6/site-packages/

使用 TensorRT, 載入 frozen_model.pb 太慢

使用 TensorRT 就是要加快 inference 的速度
沒想到載入模型時，速度超慢

上網查到 extremely long model loading time problem
發現主要原因為 protobuf 使用 python
改用 cpp 才能改善速度

文章上使用 protobuf 3.6.1
但是我的 protobuf 使用 3.8.0
所以把相關參數改成 3.8.0
並把 protobuf 安裝在 python 的 virtualenv 上

sudo /usr/local/cuda-10.0/bin/nvprof --log-file=profile_freeze.log /mnt/XavierSSD/envs/OpenAiGym/bin/python inference.py

玩 OpenAI Gym Atari 遊戲

參考 Playing the OpenAI Gym Atari Games

sudo apt-get build-dep python-pygame
pip install pygame
pip install matplotlib
sudo apt-get install python3-tk

mkdir -p gym/utils
下載 play.py 到 gym/utils

執行

import gym
from gym.utils.play import play
env = gym.make("MontezumaRevengeNoFrameskip-v4")
play(env, zoom=4)

Nvidia Jetson AGX Xavier 之 Qt 安裝

參考 How to install PyQt4 on Tx2
sudo apt-get install libqt4-dev qt4-dev-tools python-qt4-dev pyqt4-dev-tools
sudo apt-get install python-qt4
sudo apt-get install python3-pyqt4


參考 Install Qt Creator on NVIDIA Jetson TK1
sudo apt-get install build-essential qt5-default qtcreator -y
開啟 Qt Creator
選擇 Tools/Options/Build & Run/Compilers
Add/GCC
Compiler path: /usr/bin/gcc
選擇 Tools/Options/Build & Run/Kits

Manual/Desktop (default)

Compiler: GCC

sudo apt-get install python3-pyqt5

sudo apt-get install pyqt5-dev-tools

sudo apt-get install qttools5-dev-tools
cp -r /usr/lib/python3/dist-packages/PyQt5 ~/XavierSSD/envs/OpenAiGym/lib/python3.6/site-packages/

wget "https://www.riverbankcomputing.com/static/Downloads/sip/sip-4.19.14.tar.gz"

wget 網址已經不存在

改從 https://distfiles.macports.org/py-sip/ 下載

tar -zxf sip-4.19.14.tar.gz

cd sip-4.19.14/

python configure.py

make

make install

Xavier OpenAI Gym

使用PyTorch，OpenAI Gym和Gazebo機器人模擬器爲NVIDIA Jetson深度強化學習GPU庫
PyTorch Install problem (Solved)
Robot Operating System (ROS) on NVIDIA Jetson AGX Xavier Developer Kit
TX2 - Jetson Reinforcement - cmake -- configuring incomplete
Install Gazebo using Ubuntu packages
NVIDIA Xavier - Deep Learning - Deep Learning Tutorials - Jetson Reinforcement
Ubuntu gazebo package
nvidia@jetson-0423418048807:~$ apt-cache madison gazebo9
   gazebo9 | 9.8.0-1~bionic | http://packages.osrfoundation.org/gazebo/ubuntu-stable bionic/main arm64 Packages
   gazebo9 | 9.0.0+dfsg5-3ubuntu1 | http://ports.ubuntu.com/ubuntu-ports bionic/universe arm64 Packages
    gazebo | 9.0.0+dfsg5-3ubuntu1 | http://ports.ubuntu.com/ubuntu-ports bionic/universe Sources
nvidia@jetson-0423418048807:~$
nvidia@jetson-0423418048807:~$ apt-cache madison libgazebo9-dev
libgazebo9-dev | 9.8.0-1~bionic | http://packages.osrfoundation.org/gazebo/ubuntu-stable bionic/main arm64 Packages
libgazebo9-dev | 9.0.0+dfsg5-3ubuntu1 | http://ports.ubuntu.com/ubuntu-ports bionic/universe arm64 Packages
    gazebo | 9.0.0+dfsg5-3ubuntu1 | http://ports.ubuntu.com/ubuntu-ports bionic/universe Sources
nvidia@jetson-0423418048807:~$

nvidia@jetson-0423418048807:~$ sudo apt-get install gazebo9=9.0.0+dfsg5-3ubuntu1

nvidia@jetson-0423418048807:~$ sudo apt-get install libgazebo9-dev=9.0.0+dfsg5-3ubuntu1

Error [REST.cc:205] during startup gazebo

Getting Started with Gym
Errors during install sklearn.
How to install opencv-python for python3.6
Installing everything
GitHub atari_py
python3 setup.py build
python3 setup.py install
pip3 install cffi
sudo apt install libffi-dev

Nvidia Jetson AGX Xavier Build tensorflow 1.13

參考 Building Tensorflow 1.13 on Jetson Xavier

安裝 bazel
nvidia@jetson-0423418048807:~/XavierSSD/Downloads$ wget https://github.com/bazelbuild/bazel/releases/download/0.19.2/bazel-0.19.2-dist.zip
nvidia@jetson-0423418048807:~/XavierSSD/Downloads$ mkdir bazel
nvidia@jetson-0423418048807:~/XavierSSD/Downloads$ cd bazel

nvidia@jetson-0423418048807:~/XavierSSD/Downloads/bazel$ unzip bazel-0.19.2-dist.zip

nvidia@jetson-0423418048807:~/XavierSSD/Downloads/bazel$ env EXTRA_BAZEL_ARGS="--host_javabase=@local_jdk//:jdk" bash ./compile.sh

nvidia@jetson-0423418048807:~/XavierSSD/Downloads/bazel$ cd ..

nvidia@jetson-0423418048807:~/XavierSSD/Downloads$ mv bazel ~/XavierSSD

nvidia@jetson-0423418048807:~/XavierSSD/Downloads$ cd ../bazel/

nvidia@jetson-0423418048807:~/XavierSSD/bazel$ vi ~/.bashrc

加入下一行到檔案底部，並且也執行一遍

export PATH=~/XavierSSD/bazel/output${PATH:+:${PATH}}

下載 tensorflow

nvidia@jetson-0423418048807:~/XavierSSD/bazel$ cd ..

nvidia@jetson-0423418048807:~/XavierSSD$ git clone https://github.com/tensorflow/tensorflow.git

nvidia@jetson-0423418048807:~/XavierSSD$ cd tensorflow/

設定 git 環境，取得 r1.13 版

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git config --global user.email "name@yahoo.com.tw"

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git config --global user.name "name"

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git checkout r1.13

為 Nvidia Jetson AGX Xavier 修改
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ vi tensorflow/lite/kernels/internal/BUILD

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git add tensorflow/lite/kernels/internal/BUILD

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git commit -m "Update 1"

[r1.13 982e077b2a] Update 1

 1 file changed, 3 deletions(-)

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git log

commit 982e077b2a4e2123f7a299dbaf95d97383303d17 (HEAD -> r1.13)

Author: name <name@yahoo.com.tw>

Date:   Mon Jun 24 14:49:30 2019 +0800

    Update 1

commit 93dd14dce2e8751bcaab0a0eb363d55eb0cc5813 (origin/r1.13)

Author: Mihai Maruseac <mihaimaruseac@google.com>

Date:   Tue May 21 10:08:18 2019 -0700

    Update png_archive version to 1.6.37

    PiperOrigin-RevId: 249272809

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git diff 93dd1 982e0

diff --git a/tensorflow/lite/kernels/internal/BUILD b/tensorflow/lite/kernels/internal/BUILD

index 4be3226938..7226f96fdf 100644

--- a/tensorflow/lite/kernels/internal/BUILD

+++ b/tensorflow/lite/kernels/internal/BUILD

@@ -22,15 +22,12 @@ HARD_FP_FLAGS_IF_APPLICABLE = select({

 NEON_FLAGS_IF_APPLICABLE = select({

     ":arm": [

         "-O3",

-        "-mfpu=neon",

     ],

     ":armeabi-v7a": [

         "-O3",

-        "-mfpu=neon",

     ],

     ":armv7a": [

         "-O3",

-        "-mfpu=neon",

     ],

     "//conditions:default": [

         "-O3",

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ vi third_party/aws/BUILD.bazel

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git add third_party/aws/BUILD.bazel

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git commit -m "Update 2"

[r1.13 a3d6ea2fce] Update 2

 1 file changed, 1 insertion(+), 1 deletion(-)

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git log
commit a3d6ea2fce8fff7bcf74ee52cd77074416d24bf2 (HEAD -> r1.13)
Author: mark <ingrenn@yahoo.com.tw>
Date:   Mon Jun 24 14:56:09 2019 +0800

    Update 2

commit 982e077b2a4e2123f7a299dbaf95d97383303d17
Author: mark <ingrenn@yahoo.com.tw>
Date:   Mon Jun 24 14:49:30 2019 +0800

    Update 1

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git diff 982e0 a3d6ea
diff --git a/third_party/aws/BUILD.bazel b/third_party/aws/BUILD.bazel
index 5426f79e46..e08f8fc108 100644
--- a/third_party/aws/BUILD.bazel
+++ b/third_party/aws/BUILD.bazel
@@ -24,7 +24,7 @@ cc_library(
         "@org_tensorflow//tensorflow:raspberry_pi_armeabi": glob([
             "aws-cpp-sdk-core/source/platform/linux-shared/*.cpp",
         ]),
-        "//conditions:default": [],
+        "//conditions:default": glob(["aws-cpp-sdk-core/source/platform/linux-shared/*.cpp",]),
     }) + glob([
         "aws-cpp-sdk-core/include/**/*.h",
         "aws-cpp-sdk-core/source/*.cpp",
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ vi third_party/gpus/crosstool/BUILD.tpl
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git add third_party/gpus/cro
sstool/BUILD.tpl
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git commit -m "Update 3"
[r1.13 65ad3b64e5] Update 3
 1 file changed, 1 insertion(+)
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git log
commit 65ad3b64e5f16b3496628bee800fabf825a7c1ce (HEAD -> r1.13)
Author: mark <ingrenn@yahoo.com.tw>
Date:   Mon Jun 24 15:04:22 2019 +0800

    Update 3

commit a3d6ea2fce8fff7bcf74ee52cd77074416d24bf2
Author: mark <ingrenn@yahoo.com.tw>
Date:   Mon Jun 24 14:56:09 2019 +0800

    Update 2

commit 982e077b2a4e2123f7a299dbaf95d97383303d17
Author: mark <ingrenn@yahoo.com.tw>
Date:   Mon Jun 24 14:49:30 2019 +0800

    Update 1

commit 93dd14dce2e8751bcaab0a0eb363d55eb0cc5813 (origin/r1.13)
Author: Mihai Maruseac <mihaimaruseac@google.com>
Date:   Tue May 21 10:08:18 2019 -0700

    Update png_archive version to 1.6.37
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ git diff a3d6ea 65ad3
diff --git a/third_party/gpus/crosstool/BUILD.tpl b/third_party/gpus/crosstool/BUILD.tpl
index db76306ffb..184cd35b87 100644
--- a/third_party/gpus/crosstool/BUILD.tpl
+++ b/third_party/gpus/crosstool/BUILD.tpl
@@ -24,6 +24,7 @@ cc_toolchain_suite(
         "x64_windows|msvc-cl": ":cc-compiler-windows",
         "x64_windows": ":cc-compiler-windows",
         "arm": ":cc-compiler-local",
+        "aarch64": ":cc-compiler-local",
         "k8": ":cc-compiler-local",
         "piii": ":cc-compiler-local",
         "ppc": ":cc-compiler-local",
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$
修改完成

安裝所需版本的 g++ 和 gcc
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ sudo apt-get install g++-5
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ sudo apt-get install gcc-5

設定編譯環境
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ ./configure
Extracting Bazel installation...
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.19.2- (@non-git) installed.
Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python3


Found possible Python library paths:
  /usr/lib/python3.6/dist-packages
  /usr/lib/python3/dist-packages
  /usr/local/lib/python3.6/dist-packages
Please input the desired Python library path to use.  Default is [/usr/lib/python3.6/dist-packages]

Do you wish to build TensorFlow with XLA JIT support? [Y/n]: n
No XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]: n
No OpenCL SYCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with ROCm support? [y/N]: n
No ROCm support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: y
CUDA support will be enabled for TensorFlow.

Please specify the CUDA SDK version you want to use. [Leave empty to default to CUDA 10.0]:


Please specify the location where CUDA 10.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: /usr/local/cuda-10.0


Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7]: 7.3


Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda-10.0]: /usr/lib/aarch64-linux-gnu


Do you wish to build TensorFlow with TensorRT support? [y/N]: y
TensorRT support will be enabled for TensorFlow.

Please specify the location where TensorRT is installed. [Default is /usr/lib/aarch64-linux-gnu]:


Please specify the locally installed NCCL version you want to use. [Default is to use https://github.com/nvidia/nccl]:


Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 3.5,7.0]: 7.2


Do you want to use clang as CUDA compiler? [y/N]: n
nvcc will be used as CUDA compiler.

Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]: /usr/bin/gcc-5


Do you wish to build TensorFlow with MPI support? [y/N]: n
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native -Wno-sign-compare]:


Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: n
Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
        --config=mkl            # Build with MKL support.
        --config=monolithic     # Config for mostly static monolithic build.
        --config=gdr            # Build with GDR support.
        --config=verbs          # Build with libverbs support.
        --config=ngraph         # Build with Intel nGraph support.
        --config=dynamic_kernels        # (Experimental) Build kernels into separate shared objects.
Preconfigured Bazel build configs to DISABLE default on features:
        --config=noaws          # Disable AWS S3 filesystem support.
        --config=nogcp          # Disable GCP support.
        --config=nohdfs         # Disable HDFS support.
        --config=noignite       # Disable Apacha Ignite support.
        --config=nokafka        # Disable Apache Kafka support.
        --config=nonccl         # Disable NVIDIA NCCL support.
Configuration finished
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

建立 tensorflow 安裝資料
此處會執行很久，甚至會報錯，如找不到 numpy 等
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ bazel build --config=opt --config=nonccl //tensorflow/tools/pip_package:build_pip_package --incompatible_remove_native_http_archive=false --verbose_failures --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
產生 tensorflow-1.13.1-cp36-cp36m-linux_aarch64.whl
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ sudo bazel-bin/tensorflow/tools/pip_package/build_pip_package ../


移除舊的 tensorflow，並安裝新的
nvidia@jetson-0423418048807:~$ source XavierSSD/envs/tensorflow/bin/activate
(tensorflow) nvidia@jetson-0423418048807:~$ cd XavierSSD/tensorflow/
((tensorflow) nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ pip3 uninstall tensorflow-gpu
(tensorflow) nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ pip3 install ../tensorflow-1.13.1-cp36-cp36m-linux_aarch64.whl
(tensorflow) nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ deactivate
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

建立 tensorflow c++ 的 shared library libtensorflow_cc.so
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ bazel build --config=opt --config=nonccl //tensorflow:libtensorflow_cc.so --incompatible_remove_native_http_archive=false --verbose_failures --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0"
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ ls -al bazel-bin/tensorflow/
libtensorflow_cc.so
-r-xr-xr-x 1 nvidia nvidia 303026864 Jun 25 12:22 bazel-bin/tensorflow/libtensorflow_cc.so
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ mkdir tensorflow/cc/example

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ vi tensorflow/cc/example/example.cc

// tensorflow/cc/example/example.cc

#include "tensorflow/cc/client/client_session.h"
#include "tensorflow/cc/ops/standard_ops.h"
#include "tensorflow/core/framework/tensor.h"

int main() {
  using namespace tensorflow;
  using namespace tensorflow::ops;
  Scope root = Scope::NewRootScope();
  // Matrix A = [3 2; -1 0]
  auto A = Const(root, { {3.f, 2.f}, {-1.f, 0.f} });
  // Vector b = [3 5]
  auto b = Const(root, { {3.f, 5.f} });
  // v = Ab^T
  auto v = MatMul(root.WithOpName("v"), A, b, MatMul::TransposeB(true));
  std::vector<Tensor> outputs;
  ClientSession session(root);
  // Run and fetch v
  TF_CHECK_OK(session.Run({v}, &outputs));
  // Expect outputs[0] == [19; -3]
  LOG(INFO) << outputs[0].matrix<float>();
  return 0;
}

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ vi tensorflow/cc/example/BUILD

load("//tensorflow:tensorflow.bzl", "tf_cc_binary")

tf_cc_binary(
    name = "example",
    srcs = ["example.cc"],
    deps = [
        "//tensorflow/cc:cc_ops",
        "//tensorflow/cc:client_session",
        "//tensorflow/core:tensorflow",
    ],
)

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

編譯範例 example.cc

nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ bazel build -c opt //tensorflow/cc/example:example

跑了好久，測試執行
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$ bazel-bin/tensorflow/cc/exam
ple/example
2019-06-25 16:10:03.922559: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:965] ARM64 does not support NUMA - returning NUMA node zero
2019-06-25 16:10:03.922959: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: Xavier major: 7 minor: 2 memoryClockRate(GHz): 1.5
pciBusID: 0000:00:00.0
totalMemory: 15.45GiB freeMemory: 8.57GiB
2019-06-25 16:10:03.923054: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-06-25 16:10:03.924346: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-06-25 16:10:03.924409: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]      0
2019-06-25 16:10:03.924452: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0:   N
2019-06-25 16:10:03.925152: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8340 MB memory) -> physical GPU (device: 0, name: Xavier, pci bus id: 0000:00:00.0, compute capability: 7.2)
2019-06-25 16:10:07.582973: I tensorflow/cc/example/example.cc:22] 19
-3
nvidia@jetson-0423418048807:~/XavierSSD/tensorflow$

nvidia@jetson-0423418048807:~/XavierSSD$ git clone https://github.com/bitbionic/

keras-to-tensorflow.git
Cloning into 'keras-to-tensorflow'...
remote: Enumerating objects: 3719, done.
remote: Total 3719 (delta 0), reused 0 (delta 0), pack-reused 3719
Receiving objects: 100% (3719/3719), 227.81 MiB | 786.00 KiB/s, done.
Resolving deltas: 100% (7/7), done.
Checking out files: 100% (3688/3688), done.
nvidia@jetson-0423418048807:~/XavierSSD$
nvidia@jetson-0423418048807:~/XavierSSD$ cd keras-to-tensorflow
nvidia@jetson-0423418048807:~/XavierSSD/keras-to-tensorflow$ vi main.c
因為編譯時會有兩種錯誤
data.ToString(); 改成 std::string(data);
tensorflow::StringPiece(file_name).ends_with(".png")
改成
tensorflow::str_util::EndsWith(file_name, ".png")

nvidia@jetson-0423418048807:~/XavierSSD/keras-to-tensorflow$
nvidia@jetson-0423418048807:~/XavierSSD/keras-to-tensorflow$ g++-5 -std=gnu++11 -c ./main.cpp -D_GLIBCXX_USE_CXX11_ABI=0     -I../tensorflow     -I../tensorflow/bazel-tensorflow/external/eigen_archive     -I../tensorflow/bazel-tensorflow/external/protobuf_archive/src     -I../tensorflow/bazel-tensorflow/external/com_google_absl     -I../tensorflow/bazel-genfiles

Nvidia Jetson AGX Xavier 之 darknet 安裝

nvidia@jetson-0423418048807:~/XavierSSD$ export PATH=${PATH}:/usr/local/cuda/bin
nvidia@jetson-0423418048807:~/XavierSSD$ export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64

nvidia@jetson-0423418048807:~/XavierSSD$ git clone https://github.com/pjreddie/darknet

nvidia@jetson-0423418048807:~/XavierSSD$ cd darknet/

nvidia@jetson-0423418048807:~/XavierSSD/darknet$ vi Makefile 修改下列三行

GPU=1

CUDNN=1

OPENCV=1

nvidia@jetson-0423418048807:~/XavierSSD$ make

Nvidia Jetson AGX Xavier 測試

測試 CUDA
nvidia@jetson-0423418048807:~$ cd NVIDIA_CUDA-10.0_Samples/
nvidia@jetson-0423418048807:~/NVIDIA_CUDA-10.0_Samples$ cd bin/aarch64/linux/release/

nvidia@jetson-0423418048807:~/NVIDIA_CUDA-10.0_Samples/bin/aarch64/linux/release$ ./oceanFFT

nvidia@jetson-0423418048807:~/NVIDIA_CUDA-10.0_Samples/bin/aarch64/linux/release$ ./nbody -fullscreen -numbodies=16384

測試 tegra

nvidia@jetson-0423418048807:~$ cd tegra_multimedia_api/samples/backend/
nvidia@jetson-0423418048807:~/tegra_multimedia_api/samples/backend$
nvidia@jetson-0423418048807:~/tegra_multimedia_api/samples/backend$ ./backend 1 ../../data/Video/sample_outdoor_car_1080p_10fps.h264 H264 --trt-deployfile ../../data/Model/GoogleNet_one_class/GoogleNet_modified_oneClass_halfHD.prototxt --trt-modelfile ../../data/Model/GoogleNet_one_class/GoogleNet_modified_oneClass_halfHD.caffemodel --trt-mode 1 --trt-proc-interval 1 -fps 10
這裡會等很久

安裝 VisionWorks-1.6-Samples

nvidia@jetson-0423418048807:~$ /usr/share/visionworks/sources/install-samples.sh ~/

Creating the /home/nvidia//VisionWorks-1.6-Samples directory...

Copying VisionWorks samples to /home/nvidia//VisionWorks-1.6-Samples...

Finished copying VisionWorks samples

nvidia@jetson-0423418048807:~$ cd VisionWorks-1.6-Samples/

nvidia@jetson-0423418048807:~/VisionWorks-1.6-Samples$ make -j8

測試 VisionWorks-1.6-Samples

nvidia@jetson-0423418048807:~/VisionWorks-1.6-Samples/bin/aarch64/linux/release$ ls

nvx_demo_feature_tracker        nvx_sample_nvgstcamera_capture

nvx_demo_feature_tracker_nvxcu  nvx_sample_object_tracker_nvxcu

nvx_demo_hough_transform        nvx_sample_opencv_npp_interop

nvx_demo_motion_estimation      nvx_sample_opengl_interop

nvx_demo_stereo_matching        nvx_sample_player

nvx_demo_video_stabilizer

Nvidia Jetson AGX Xavier 運作模式，溫度，風扇

參考 NVPModel – NVIDIA Jetson AGX Xavier Developer Kit

sudo nvpmodel -q
查詢目前模式

sudo nvpmodel -m 0
設定成全力運行模式

0: 全力運行
1: 10W
2: 15W
3: 30W

sudo ./jetson_clocks.sh -show
顯示目前運作狀態

sudo ./jetson_clocks.sh
全力運作


0: 全力運作
1: 10W
2: 15W 預設值
3: 30W

sudo apt-get install lm-sensors
sudo sensors-detect 千萬不能執行，會當機
sensors 察看目前溫度

圖形介面的 sensor
sudo apt-get install psensor
psensor

專門為 NVIDIA jetson 準備的工具
Basic scripts and function to improve the performance in your NVIDIA Jetson
sudo apt-get install python3-pip
sudo -H pip3 install jetson-stats
jtop 即是 top for jetson
執行時使用 sudo jtop
其中第一個頁籤 1 ALL，中的 Sensor PMIC 一直是 100.00C，不知為何？
第三頁籤 3 CTRL，用 "+"、"-" 控制 NVP model

jetson-release 查詢 NVIDIA jetson 資訊

開機啟動風扇
sudo vi /etc/rc.local
#!/bin/bash
sleep 10
sudo sh -c 'echo 100 > /sys/devices/pwm-fan/target_pwm'

sudo chmod u+x /etc/rc.local

Nvidia Jetson AGX Xavier 之 WOL

poweroff 無法喚醒
sudo systemctl suspend
才可以喚醒，據說功耗 1.5-2W


sudo apt-get install ethtool

vi wol.sh
sudo ethtool -s wth0 wol g
sudo systemctl suspend


sudo ethtool eth0 (顯示 eth0 的設定)
Supports Wake-on: g (支援 wol)
Wake-on: d (wol 未啟動)
Wake-on: g (wol 啟動)

Nvidia Jetson AGX Xavier 安裝中文輸入法

參考 Ubuntu 類似微軟注音的輸入法 - hime 詞音輸入法

Ctrl+Space 啟動中文輸入
Shift 中英文切換
Ctrl+Alt+4 符號表

nvidia@jetson-0423418048807:~$ sudo apt-get install ibus-chewing

重新開機

System Settings/Language Support
Install / Remove Languages...
Add Chinese (traditional)
Keyboard input method system: ibus

在 Ubuntu 18.04 中新增新酷音輸入法

How can I use chewing(zhuyin) input method?
ubuntu 英文版中安裝新酷音輸入法
讓 Linux 下的中文輸入法更接近微軟新注音使用體驗
Ubuntu: fcitx + chewing 新酷音輸入法