Jetson Convenience Script

by FREE WING

http://www.neko.ne.jp/~freewing/

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

Caffe doesn't support cuDNN v8.0 .
So require disable USE_CUDNN .
https://forums.developer.nvidia.com/t/jetpack-4-4-l4t-r32-4-3-production-release/140870/21

NVIDIA Jetson Nano、Jetson Xavier NX Developer Kit HEADLESS MODE Setup
You can use a Jetson Xavier NX Developer Kit in headless mode, that is , without attaching a display .

* Caution *
Need to Disconnect Display Cable or Power off Display .
If JETSON Detects the Display , It will not go into HEADLESS MODE Setup .

WiFi Setup

http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_setup_wifi_connection_nmcli/

SSID='WIFI-SSID'
PASSWORD='PLAIN-PASSWORD'

sudo nmcli device wifi connect $SSID password $PASSWORD

sudo nmcli con add type wifi con-name $SSID ifname wlan0 ssid $SSID
sudo nmcli con modify $SSID wifi-sec.key-mgmt wpa-psk
sudo nmcli con modify $SSID wifi-sec.psk $PASSWORD
sudo nmcli con up $SSID
sleep 5
sudo nmcli con up $SSID

sudo nmcli dev wifi rescan
nmcli dev wifi list

sudo ifconfig wlan0 up
ifconfig wlan0
ifconfig -s wlan0

Jetson Nano / Jetson Xavier NX initialize

http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_xavier_nx_2020_initialize/
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_2020_initialize/

# Auto detect Nano or Xavier
cd
git clone https://github.com/FREEWING-JP/Jetson_Convenience_Script --depth 1
cd
bash ./Jetson_Convenience_Script/JetPack/1st_jetson_initialize.sh

source .bashrc
 or 
sudo reboot

# sudo visudo
sudo visudo
Defaults        env_reset, timestamp_timeout=-1
 or 
echo 'Defaults env_reset, timestamp_timeout=-1' | sudo EDITOR='tee -a' visudo

Optional deb package

cd
git clone https://github.com/FREEWING-JP/Jetson_Convenience_Script 00_deb -b 00_deb
mv ./00_deb/00_deb/* ./00_deb/
# */
ls -l ./00_deb

CMake 3.17.5

https://github.com/Kitware/CMake
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia__jetson_build_newest_cmake/

# for Build OpenPose
cd
bash ./Jetson_Convenience_Script/CMake/inst_CMake.sh

# Create .deb install package
bash ./Jetson_Convenience_Script/CMake/create_CMake_deb.sh

libjpeg-turbo 2.0.5 (libjpeg v8)

https://github.com/libjpeg-turbo/libjpeg-turbo
http://lfsbookja.osdn.jp/BLFS/svn-ja/general/libjpeg.html
-D WITH_JPEG8=ON This switch enables compatibility with libjpeg version 8 .
https://libjpeg-turbo.org/About/TurboJPEG
"libjpeg-turbo" != "TurboJPEG"

cd
bash ./Jetson_Convenience_Script/libjpeg-turbo/inst_libjpeg-turbo_205.sh

OpenBLAS develop

https://github.com/xianyi/OpenBLAS

cd
bash ./Jetson_Convenience_Script/OpenBLAS/inst_OpenBLAS.sh

Bazel 3.5.0

https://bazel.build/
https://github.com/bazelbuild/bazel/tree/3.5.0

cd
bash ./Jetson_Convenience_Script/Bazel/inst_Bazel_350.sh

OpenCV 3.x

https://github.com/opencv/opencv
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_build_opencv_3410/

# OpenCV 3.4.10
cd
bash ./Jetson_Convenience_Script/OpenCV/inst_OpenCV3410.sh

# OpenCV 3.4.9
cd
bash ./Jetson_Convenience_Script/OpenCV/inst_OpenCV349.sh

OpenCV 4.4.0 with cuDNN 8.0, GStreamer, V4L Video4Linux

cd
bash ./Jetson_Convenience_Script/OpenCV/inst_OpenCV440.sh

# Create .deb install package
bash ./Jetson_Convenience_Script/OpenCV/create_OpenCV_deb.sh

Caffe master

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

https://github.com/BVLC/caffe
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_build_caffe_google_deep_dream/

JetPack	USE_CUDNN=1	USE_CUDNN=0
4.4 PR	NG	OK
4.4 DP	OK	OK
4.3 PR	OK	OK

# with OpenCV 3.x (JetPack 4.2)
# with OpenCV 4.x (JetPack 4.3 or 4.4)
# Auto detect OpenCV 3.x/ 4.x with OpenCV 4.x patch
# support JetPack 4.4 production release disable cuDNN
cd
bash ./Jetson_Convenience_Script/Caffe/inst_Caffe.sh

# Special adapted for OpenCV 4.1 and Python 3.6+
# https://github.com/Qengineering/caffe
# Install OpenCV 4.1.2 and Caffe on Ubuntu 18.04 for Python 3
# https://qengineering.eu/install-caffe-on-ubuntu-18.04-with-opencv-4.1.html
# with OpenCV 4.x
cd
bash ./Jetson_Convenience_Script/Caffe/inst_Caffe_Qengineering.sh

# Caffe installation on Xavier
# https://forums.developer.nvidia.com/t/caffe-installation-on-xavier/67730
# with OpenCV 3.x
cd
bash ./Jetson_Convenience_Script/Caffe/inst_Caffe_NVIDIA.sh

Caffe Deep Dreamer (Google's DeepDream)

https://github.com/kesara/deepdreamer
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_build_caffe_google_deep_dream/

# Auto detect Python 2/ Python 3 with Python 2 patch
cd
bash ./Jetson_Convenience_Script/Caffe/inst_DeepDreamer.sh

OpenPose v1.6.0

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

https://github.com/CMU-Perceptual-Computing-Lab/openpose
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_2020_build_openpose/
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_xavier_nx_2020_build_openpose/

JetPack	OpenPose builtin Caffe	external Caffe	external NVIDIA Caffe v0.17.3
4.4 PR	OK (without cuDNN)	NG (without cuDNN)	OK (without cuDNN)
4.4 DP	OK	NG	OK
4.3 PR	OK	NG	OK

# Auto detect JetPack 4.3 or 4.4
# Auto detect OpenCV 3.x/ 4.x for Build OpenPose's Caffe
# external Caffe version should be 0.17.3 (ex. OpenPose internal/ NVIDIA Caffe)
# Require CMake Version 3.12 or above
# support JetPack 4.4 production release without cuDNN 8.0
cd
bash ./Jetson_Convenience_Script/OpenPose/inst_OpenPose.sh

tf-pose-estimation master

https://github.com/ildoonet/tf-pose-estimation
https://github.com/gsethi2409/tf-pose-estimation
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_jetpack_tf_pose_estimation_setup/

# with TensorFlow v1.x
cd
bash ./Jetson_Convenience_Script/tf-pose-estimation/inst_tf-pose-estimation.sh

# with TensorFlow v2.x
# https://github.com/gsethi2409/tf-pose-estimation
cd
bash ./Jetson_Convenience_Script/tf-pose-estimation/inst_tf-pose-estimation_tf_v2.sh

StyleGAN

https://github.com/NVlabs/stylegan
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_tensorflow_stylegan/
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_tensorflow_stylegan_pretty_anime_face/

# with TensorFlow v1.x
cd
bash ./Jetson_Convenience_Script/StyleGAN/inst_StyleGAN.sh

StyleGAN2

https://github.com/NVlabs/stylegan2
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_tensorflow_stylegan2/

# with TensorFlow v1.x
cd
bash ./Jetson_Convenience_Script/StyleGAN2/inst_StyleGAN2.sh

NVIDIA Caffe v0.17.3

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

https://github.com/nvidia/caffe
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_build_nvcaffe_google_deep_dream/

JetPack	USE_CUDNN=1	USE_CUDNN=0
4.4 PR	NG	OK
4.4 DP	OK	OK
4.3 PR	OK	OK

# with OpenCV 3.x (JetPack 4.2)
# with OpenCV 4.x (JetPack 4.3 or 4.4)
# Auto detect OpenCV 3.x/ 4.x with OpenCV 4.x patch
# support JetPack 4.4 production release disable cuDNN
cd
bash ./Jetson_Convenience_Script/NV_Caffe/inst_NV_Caffe.sh

NVIDIA FFmpeg for Jetson Nano

https://github.com/jocover/jetson-ffmpeg

NVIDIA FFmpeg for Jetson Xavier NX master

https://developer.nvidia.com/ffmpeg

NVIDIA FFmpeg for Jetson Nano / Jetson Xavier NX

http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_2020_build_ffmpeg/

# Auto detect Nano or Xavier
cd
bash ./Jetson_Convenience_Script/NV_FFmpeg/inst_NV_FFmpeg.sh

# 2020/09 disable x265
# ffmpeg --enable-libx265
# ERROR: x265 not found using pkg-config

TensorFlow

https://github.com/tensorflow/tensorflow
https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html
https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform-release-notes/tf-jetson-rel.html
Official TensorFlow for Jetson Nano!
https://forums.developer.nvidia.com/t/official-tensorflow-for-jetson-nano/71770
Official TensorFlow for Jetson AGX XavierNX
https://forums.developer.nvidia.com/t/official-tensorflow-for-jetson-agx-xaviernx/141306
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_jetpack_tensorflow_setup/

TensorFlow v1.x

# TensorFlow v1.15.2
# Auto detect JetPack 4.3 or 4.4
cd
bash ./Jetson_Convenience_Script/TensorFlow/inst_tf1.sh

TensorFlow v2.x

# TensorFlow v2.1.0
# Auto detect JetPack 4.3 or 4.4
cd
bash ./Jetson_Convenience_Script/TensorFlow/inst_tf2.sh

Pytorch

https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-6-0-now-available/72048

# Pytorch v1.4.0 / torchvision v0.5.0 / Python 3.6
cd
bash ./Jetson_Convenience_Script/PyTorch/inst_PyTorch_v1_4_Python3.sh

# Pytorch v1.5.0 / torchvision v0.6.0 / Python 3.6
cd
bash ./Jetson_Convenience_Script/PyTorch/inst_PyTorch_v1_5_Python3.sh

# Pytorch v1.6.0 / torchvision v0.7.0 / Python 3.6
cd
bash ./Jetson_Convenience_Script/PyTorch/inst_PyTorch_v1_6_Python3.sh

DATA BASE

Redis
Memcached
MongoDB

Redis 6.0.8

https://redis.io/

# Redis
cd
bash ./Jetson_Convenience_Script/Redis/inst_Redis.sh

Memcached 1.6.7

https://memcached.org/
https://github.com/memcached/memcached

# Memcached
cd
bash ./Jetson_Convenience_Script/Memcached/inst_Memcached.sh

MongoDB 3.x / 4.x

https://www.mongodb.com/
https://github.com/mongodb/mongo
32GB SD-Card is Not Enough to Build MongoDB

# MongoDB 3.6.3-0ubuntu1.1 all
apt search mongodb
sudo apt install -y mongodb

# MongoDB 3.4.14
# https://github.com/mongodb/mongo/tree/r3.4.14
cd
bash ./Jetson_Convenience_Script/MongoDB/inst_MongoDB_3414.sh

# MongoDB 3.6.8
# https://github.com/mongodb/mongo/tree/r3.6.8
cd
bash ./Jetson_Convenience_Script/MongoDB/inst_MongoDB_368.sh

# MongoDB 3.6.20
# https://github.com/mongodb/mongo/tree/r3.6.20
cd
bash ./Jetson_Convenience_Script/MongoDB/inst_MongoDB_3620.sh

# MongoDB 4.2.0
# https://github.com/mongodb/mongo/tree/r4.2.0
cd
bash ./Jetson_Convenience_Script/MongoDB/inst_MongoDB_420.sh

# MongoDB 4.2.9
# https://github.com/mongodb/mongo/tree/r4.2.9
cd
bash ./Jetson_Convenience_Script/MongoDB/inst_MongoDB_429.sh

# MongoDB 4.4.1
# https://github.com/mongodb/mongo/tree/r4.4.1
cd
bash ./Jetson_Convenience_Script/MongoDB/inst_MongoDB_441.sh

# MongoDB 4.7.0
# https://github.com/mongodb/mongo/tree/r4.7.0
cd
bash ./Jetson_Convenience_Script/MongoDB/inst_MongoDB_470.sh

Visual Studio Code

https://github.com/Microsoft/vscode
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_build_visual_studio_code_oss/

# Visual Studio Code 1.35.0
# for Jetson Nano
cd
bash ./Jetson_Convenience_Script/Visual_Studio_Code/inst_Visual_Studio_Code_1350.sh

# Visual Studio Code 1.47.2
# for Jetson Xavier
cd
bash ./Jetson_Convenience_Script/Visual_Studio_Code/inst_Visual_Studio_Code_1472.sh

Vino VNC Server

https://gitlab.gnome.org/GNOME/vino/
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_enable_vino_vnc_server_headless_mode/

cd
bash ./Jetson_Convenience_Script/Vino_VNC/inst_Vino_VNC.sh

Benchmark

http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_benchmark_full_load/

# UnixBench byte-unixbench
# https://github.com/kdlucas/byte-unixbench
cd
bash ./Jetson_Convenience_Script/Benchmark/inst_UnixBench.sh

# Benchmarks Targeted for Jetson Xavier NX (Using GPU+2DLA)
# https://github.com/NVIDIA-AI-IOT/jetson_benchmarks
cd
bash ./Jetson_Convenience_Script/Benchmark/inst_jetson_benchmarks.sh

Jetson stats

https://github.com/rbonghi/jetson_stats

# Install
sudo -H pip install -U jetson-stats
sudo reboot

Jetson Hello AI World

https://developer.nvidia.com/embedded/twodaystoademo
https://github.com/dusty-nv/jetson-inference
http://www.neko.ne.jp/~freewing/raspberry_pi/nvidia_jetson_nano_sample_application/

# Building the Project from Source
# https://github.com/dusty-nv/jetson-inference/blob/master/docs/building-repo.md

# git and cmake
sudo apt-get update
sudo apt-get install -y git cmake

# Python Development Packages
sudo apt-get install -y libpython3-dev python3-numpy

# Cloning the Repo
cd
git clone https://github.com/dusty-nv/jetson-inference --depth 1
cd jetson-inference
# or --recursive
git submodule update --init

# Configuring with CMake
mkdir build
cd build
cmake ../

# Compiling the Project
make -j$(nproc)
sudo make install
sudo ldconfig

tree ./aarch64

Name		Name	Last commit message	Last commit date
Latest commit History 181 Commits
Bazel		Bazel
Benchmark		Benchmark
CMake		CMake
Caffe		Caffe
JetPack		JetPack
Memcached		Memcached
MongoDB		MongoDB
NV_Caffe		NV_Caffe
NV_FFmpeg		NV_FFmpeg
OpenBLAS		OpenBLAS
OpenCV		OpenCV
OpenPose		OpenPose
PyTorch		PyTorch
Redis		Redis
StyleGAN		StyleGAN
StyleGAN2		StyleGAN2
TensorFlow		TensorFlow
Vino_VNC		Vino_VNC
Visual_Studio_Code		Visual_Studio_Code
libjpeg-turbo		libjpeg-turbo
llvm		llvm
tf-pose-estimation		tf-pose-estimation
LICENSE		LICENSE
README.md		README.md
bell.sh		bell.sh

License

Tidus1991/Jetson_Convenience_Script

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Jetson Convenience Script

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

for Jetson Nano / Jetson Xavier NX Developer Kit

NVIDIA JetPack

Jetson Nano / Jetson Xavier NX HEADLESS MODE Setup

WiFi Setup

Jetson Nano / Jetson Xavier NX initialize

Optional deb package

CMake 3.17.5

libjpeg-turbo 2.0.5 (libjpeg v8)

OpenBLAS develop

Bazel 3.5.0

OpenCV 3.x

OpenCV 4.4.0 with cuDNN 8.0, GStreamer, V4L Video4Linux

Caffe master

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

Caffe Deep Dreamer (Google's DeepDream)

OpenPose v1.6.0

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

tf-pose-estimation master

StyleGAN

StyleGAN2

NVIDIA Caffe v0.17.3

JetPack 4.4 production release L4T 32.4.3 Can't build Caffe and OpenPose with cuDNN 8.0

NVIDIA FFmpeg for Jetson Nano

NVIDIA FFmpeg for Jetson Xavier NX master

NVIDIA FFmpeg for Jetson Nano / Jetson Xavier NX

TensorFlow

TensorFlow v1.x

TensorFlow v2.x

Pytorch

DATA BASE

Redis 6.0.8

Memcached 1.6.7

MongoDB 3.x / 4.x

Visual Studio Code

Vino VNC Server

Benchmark

Jetson stats

Jetson Hello AI World

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