Jetson Nano开箱

1、Jetson Nano 官方资料下载
Jetson Nano Developer Kit官方介绍
 Get-Started-With-Jetson-Nano-Devkit
Jetson-Nano-Dev-Kit-Sd-Card-Image
NVIDIA Jetson-Nano-Resources
Jetson Nano Wiki
Jetson Nano Upstream

图为科技Jetson Nano 运行通用案例分享(持续更新）

Jetson Nano 对应的DeepStream 2019Q2 才会发布，目前采用Nano 做的项目还是比较受限，期待DS 有更高的性能表现！

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2、Jetson Nano刷机

Nano MicroSD卡刷机工具：SDCardFormatter 和 balenaEtcher
Nano MicroSD卡系统镜像：jetson-nano-sd-r32.1-2019-03-18.zip (5.6GB)，但解压缩后大约12GB多，运行在Micro SD卡，因此SD卡务必16GB及以上且高速UHS（参考NV 说明)，否则刷TF卡镜像和系统软件运行时会慢如牛，你想砸了Nano或TF卡!
MicroSD卡选型可参考文章: 一文看懂各种储存卡:TF卡、SD/SDHC/SDXC卡、CF卡和Class等级

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TF卡（Nano运行）测试方法（无其他软件运行)：
SanDisk --- UHS-I接口兼容(Speed: Class10 + A1)

写入速度测试：
$ dd count=1k bs=1M if=/dev/zero of=/home/nvidia/tst.img
1024+0 records in
1024+0 records out
1073741824 bytes (1.1 GB, 1.0 GiB) copied, 47.5029 s, 22.6 MB/s

读取速度测试：
$ sudo apt-get install hdparm
$ sudo hdparm -t /dev/mmcblk0p1
/dev/mmcblk0p1:
 Timing buffered disk reads: 244 MB in  3.01 seconds =  81.19 MB/sec

SanDisk --- UHS-I接口兼容(Speed: U3 + V30 + A1)

读取速度测试：
$ sudo apt-get install hdparm
$ sudo hdparm -t /dev/mmcblk0p1
/dev/mmcblk0p1:
 Timing buffered disk reads: 258 MB in  3.01 seconds =  85.61 MB/sec

写入速度测试：
nvidia@tw-Nano:~$ dd count=1k bs=1M if=/dev/zero of=/home/nvidia/tst.img
1024+0 records in
1024+0 records out
1073741824 bytes (1.1 GB, 1.0 GiB) copied, 8.68056 s, 124 MB/s

刷机过程如图：

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3、供电USB 5V 2A 供电自动开机（外加了一个风扇）

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AC Adapter 必须5V 开机

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4. Jetson Nano套件特性

硬件接口

Ports & Interfaces

4x USB 3.0 A (Host)

USB 2.0 Micro B (Device)

MIPI CSI-2 x2 (15-position Camera Flex Connector)

HDMI 2.0

DisplayPort

Gigabit Ethernet (RJ45)

M.2 Key-E with PCIe x1

MicroSD card slot

(3x) I2C, (2x) SPI, UART, I2S, GPIOs

软件列表

JetPack 4.2

Linux4Tegra R32.1 (L4T)

Linux kernel 4.9

Ubuntu 18.04 LTS aarch64

CUDA Toolkit 10.0

cuDNN 7.3.1

TensorRT 5.0.6

TensorFlow 1.31.1

VisionWorks 1.6

OpenCV 3.3.1

OpenGL 4.6

OpenGL ES 3.2

EGL 1.5

Vulkan 1.1

GStreamer 1.14.1

V4L2 media controller support

5. 指导资料和教程文档

System Tools系统工具

Deep Learning深度学习资料

Hello AI World (jetson-inference)
TensorFlow 1.13.1 Installer (pip wheel)
PyTorch 1.1 Installer (pip wheel)
See the NVIDIA AI-IoT GitHub for other coding resources on deploying AI and deep learning.

Robotics 机器人应用

NVIDIA JetBot (AI-powered robotics kit)
jetbot_ros (ROS nodes for JetBot)
ROS Melodic (ROS install guide)
ros_deep_learning (jetson-inference nodes)

Camera 模组

Leopard Imaging LI-IMX219-MIPI-FF-NANO
Raspberry Pi Camera v2 (IMX219)
Stereolabs ZED (stereo camera)

CUDA 10（路径：/usr/local/cuda/，但未加入环境变量）
运行如下命令添加环境变量：
export PATH=${PATH}:/usr/local/cuda/bin
export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64

sudo apt-get update
sudo apt-get install samba
sudo apt-get install python3-pip

Tensorflow 1.13.1
pip3 install --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v42 tensorflow-gpu==1.13.1+nv19.3 --user
安装过程若报错hdf5，请安装：
sudo apt-get install libhdf5-serial-dev

PS: Nano features list:
Nano 不支持SATA 硬盘，但可以通过如下方式：
1.USB3 SATA dongle
2.M.2 Key-E to Mini-PCIe adapter (未验证）
"$sudo nvpmodel -m 1" ---> Nano run in 5W (Power：5V1A)
"$sudo nvpmodel -m 0" ---> Nano run in 10W (Power：5V2A)
Supported video codecs: H.265, H.264, VP8, VP9 (VP9 decode only)
HEVC encoder supports 10-bit color, but B-frames are not supported

最后编辑于：2020.08.28 16:15:38