Difference between revisions of "Jetson Nano"

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= Software Support =  
 
= Software Support =  
<div style="width:50%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
+
<div style="width:40%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
* [https://developer.nvidia.com/embedded/jetpack JetPack 4.2]
+
* [https://developer.nvidia.com/embedded/jetpack JetPack 4.2.2]
* [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra R32.1] (L4T)
+
* [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra R32.2.1] (L4T)
 
* Linux kernel 4.9
 
* Linux kernel 4.9
* Ubuntu 18.04 LTS aarch64
+
* Ubuntu 18.04 aarch64
* CUDA Toolkit 10.0
+
* [https://developer.nvidia.com/cuda-toolkit CUDA Toolkit] 10.0.326
* cuDNN 7.3.1
+
* [https://developer.nvidia.com/cudnn cuDNN] 7.5.0
* [https://developer.nvidia.com/tensorrt TensorRT] 5.0.6
+
* [https://developer.nvidia.com/tensorrt TensorRT] 5.1.6
* TensorFlow 1.31.1
+
* [https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html TensorFlow] 1.14.0
 
* [https://developer.nvidia.com/embedded/visionworks VisionWorks] 1.6
 
* [https://developer.nvidia.com/embedded/visionworks VisionWorks] 1.6
 
* OpenCV 3.3.1
 
* OpenCV 3.3.1
* OpenGL 4.6  
+
* OpenGL 4.6 / OpenGL ES 3.2.5
* OpenGL ES 3.2
+
* Vulkan 1.1.1
* EGL 1.5
+
* [http://developer.nvidia.com/embedded/dlc/l4t-multimedia-api-reference-32-1 L4T Multimedia API] (Argus 0.97)
* Vulkan 1.1
 
 
* GStreamer 1.14.1
 
* GStreamer 1.14.1
 
* V4L2 media controller support
 
* V4L2 media controller support
 +
* [https://developer.nvidia.com/nsight-systems NVIDIA Nsight Systems] 2019.4
 +
* [https://developer.nvidia.com/nsight-graphics NVIDIA Nsight Graphics] 2019.2
 +
* [https://developer.nvidia.com/nsight-compute NVIDIA Nsight Compute] 1.0
 
</div>
 
</div>
 +
 +
See the '''[[Jetson Zoo]]''' for more software packages to install on top of JetPack.
  
 
= Guides and Tutorials =
 
= Guides and Tutorials =
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<div style="width:75%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
 
<div style="width:75%;column-count:2;-moz-column-count:2;-webkit-column-count:2">
 
* [https://docs.nvidia.com/jetson/l4t/index.html L4T Kernel Development Guide]
 
* [https://docs.nvidia.com/jetson/l4t/index.html L4T Kernel Development Guide]
 +
* [[Jetson/Clone|Clone & Restore]]
 
* [https://github.com/jtagxhub/jetpack-agx-build Jetson Nano Build Assistant Scripts]
 
* [https://github.com/jtagxhub/jetpack-agx-build Jetson Nano Build Assistant Scripts]
 +
* [[Jetson/FAQ/BSP|BSP FAQ]]
 
* [https://devtalk.nvidia.com/default/topic/1048640/jetson-nano/power-supply-considerations-for-jetson-nano-developer-kit/ Power Supply Considerations]
 
* [https://devtalk.nvidia.com/default/topic/1048640/jetson-nano/power-supply-considerations-for-jetson-nano-developer-kit/ Power Supply Considerations]
 
* [[Jetson/Nano/Upstream|Upstream Development Guide]]
 
* [[Jetson/Nano/Upstream|Upstream Development Guide]]
 
* [https://devtalk.nvidia.com/default/topic/1049811/jetson-nano/cuda-and-vision-works-demos/post/5328027/#5328027 CUDA and VisionWorks Samples]
 
* [https://devtalk.nvidia.com/default/topic/1049811/jetson-nano/cuda-and-vision-works-demos/post/5328027/#5328027 CUDA and VisionWorks Samples]
* [https://devtalk.nvidia.com/default/topic/1048817/jetson-nano/3d-cad-step-model-for-jetson-nano/post/5325051/#5325051 Preliminary 3D CAD Model]
+
* [https://devtalk.nvidia.com/default/topic/1052324/jetson-nano/jetson-nano-aws-greengrass-/post/5341970/#5341970 Install AWS Greengrass] - IoT framework
 
* [https://support.rackspace.com/how-to/create-a-linux-swap-file/ Mounting a SWAP File]
 
* [https://support.rackspace.com/how-to/create-a-linux-swap-file/ Mounting a SWAP File]
 
* [https://www.jetsonhacks.com/2019/04/25/jetson-nano-run-on-usb-drive/ Booting from SSD]
 
* [https://www.jetsonhacks.com/2019/04/25/jetson-nano-run-on-usb-drive/ Booting from SSD]
 
* [https://www.jetsonhacks.com/nvidia-jetson-nano-j41-header-pinout/ GPIO Header Pin-out]
 
* [https://www.jetsonhacks.com/nvidia-jetson-nano-j41-header-pinout/ GPIO Header Pin-out]
* [https://github.com/rt-net/JetsonNano_DT_SPI Enabling SPI in DTS]
+
* [https://github.com/jwatte/jetson-gpio-example GPIO Direct Access from C]
 +
* [https://github.com/rt-net/JetsonNano_DT_SPI Enabling SPI in DTS (R32.1)]
 +
* [https://github.com/gtjoseph/jetson-nano-support/tree/l4t_32.2.1 Enabling SPI in DTS (R32.2.1)]
 
* [https://devtalk.nvidia.com/default/topic/1050026/jetson-nano/read-serial-number-of-jetson-nano/post/5329191/#5329191 Reading Serial Number]
 
* [https://devtalk.nvidia.com/default/topic/1050026/jetson-nano/read-serial-number-of-jetson-nano/post/5329191/#5329191 Reading Serial Number]
 
* [https://gist.github.com/dusty-nv/e4314241677cf38f40d556931d0c4a38 Reading MAC Address]
 
* [https://gist.github.com/dusty-nv/e4314241677cf38f40d556931d0c4a38 Reading MAC Address]
 
* [https://github.com/rbonghi/jetson_easy jetson_easy] - automatic setup/scripting
 
* [https://github.com/rbonghi/jetson_easy jetson_easy] - automatic setup/scripting
 
* [https://github.com/rbonghi/jetson_stats jetson_stats] - jtop, service and other tools
 
* [https://github.com/rbonghi/jetson_stats jetson_stats] - jtop, service and other tools
* [https://devtalk.nvidia.com/default/topic/1052324/jetson-nano/jetson-nano-aws-greengrass-/post/5341970/#5341970 Install AWS Greengrass] - IoT framework
 
 
* [https://github.com/pvaret/rtl8192cu-fixes rtl8192cu-fixes] - patched Edimax EW-7811 Wi-Fi driver
 
* [https://github.com/pvaret/rtl8192cu-fixes rtl8192cu-fixes] - patched Edimax EW-7811 Wi-Fi driver
 
</div>
 
</div>
  
 
=== Deep Learning ===
 
=== Deep Learning ===
 +
See the '''[[Jetson Zoo]]''' for more resources on deploying AI and deep learning.
 +
 
* [https://github.com/dusty-nv/jetson-inference Hello AI World] (jetson-inference)
 
* [https://github.com/dusty-nv/jetson-inference Hello AI World] (jetson-inference)
* [https://developer.nvidia.com/embedded/downloads#?search=TensorFlow TensorFlow 1.13.1 Installer] (pip wheel)
+
* [https://developer.nvidia.com/embedded/downloads#?search=TensorFlow TensorFlow Installer] (pip wheel)
* [https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/ PyTorch 1.1 Installer] (pip wheel)
+
* [https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/ PyTorch Installer] (pip wheel)
 
* [https://devtalk.nvidia.com/default/topic/1049293/jetson-nano/i-was-unable-to-compile-and-install-mxnet-on-the-jetson-nano-is-there-an-official-installation-tutorial-/post/5326170/#5326170 MXNet 1.4 Installer] (pip wheel)
 
* [https://devtalk.nvidia.com/default/topic/1049293/jetson-nano/i-was-unable-to-compile-and-install-mxnet-on-the-jetson-nano-is-there-an-official-installation-tutorial-/post/5326170/#5326170 MXNet 1.4 Installer] (pip wheel)
 +
* [https://devtalk.nvidia.com/default/topic/1065203/jetson-nano/paddlepaddle-for-jetson-nano-version-1-5-2-now-available/ PaddlePaddle Installer] (pip wheel)
 
* [https://devtalk.nvidia.com/default/topic/1050377/jetson-nano/deep-learning-inference-benchmarking-instructions/ Deep Learning Inference Benchmarking Instructions]
 
* [https://devtalk.nvidia.com/default/topic/1050377/jetson-nano/deep-learning-inference-benchmarking-instructions/ Deep Learning Inference Benchmarking Instructions]
 
* [https://medium.com/swlh/how-to-run-tensorflow-object-detection-model-on-jetson-nano-8f8c6d4352e8 TensorFlow Object Detection With TensorRT] (TF-TRT)
 
* [https://medium.com/swlh/how-to-run-tensorflow-object-detection-model-on-jetson-nano-8f8c6d4352e8 TensorFlow Object Detection With TensorRT] (TF-TRT)
 
* [https://developer.ridgerun.com/wiki/index.php?title=GstInference RidgeRun's GstInference]
 
* [https://developer.ridgerun.com/wiki/index.php?title=GstInference RidgeRun's GstInference]
 
* [https://developer.ridgerun.com/wiki/index.php?title=R2Inference RidgeRun's R2Inference]
 
* [https://developer.ridgerun.com/wiki/index.php?title=R2Inference RidgeRun's R2Inference]
 
See the [https://github.com/NVIDIA-AI-IOT/ NVIDIA AI-IoT GitHub] for other coding resources on deploying AI and deep learning.
 
  
 
=== Robotics ===
 
=== Robotics ===
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==== Cameras ====
 
==== Cameras ====
 
* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-nano-cameras/3mp-mipi-camera.asp e-CAM30_CUNANO] (3.4 MP MIPI Camera)
 
* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-nano-cameras/3mp-mipi-camera.asp e-CAM30_CUNANO] (3.4 MP MIPI Camera)
 +
* e-con Systems [https://www.e-consystems.com/nvidia-cameras/jetson-agx-xavier-cameras/stereo-camera.asp STEEReoCAM™] (2.0 MP MIPI Stereo Camera)
 
* Logitech [https://www.logitech.com/en-us/product/hd-webcam-c270 C270] (USB webcam)
 
* Logitech [https://www.logitech.com/en-us/product/hd-webcam-c270 C270] (USB webcam)
 
* Logitech [https://www.amazon.com/Logitech-Widescreen-Calling-Recording-Desktop/dp/B006JH8T3S C920] (USB webcam)
 
* Logitech [https://www.amazon.com/Logitech-Widescreen-Calling-Recording-Desktop/dp/B006JH8T3S C920] (USB webcam)
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* Auvidea [https://auvidea.eu/product/70780/ JN30] (module carrier)
 
* Auvidea [https://auvidea.eu/product/70780/ JN30] (module carrier)
 
* Auvidea [https://auvidea.eu/product/70781/ JN30-LC] (module carrier)
 
* Auvidea [https://auvidea.eu/product/70781/ JN30-LC] (module carrier)
 +
* Leopard Imaging [https://leopardimaging.com/product/li-nano-cb/ LI-NANO-CB] (module carrier)
 +
* Realtimes [http://www.realtimes.cn/cn/product/rtso-6001.html RTSO-6001] (module carrier)
  
 
==== Enclosures ====
 
==== Enclosures ====
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* [https://github.com/dudasdavid/Jetson-nano-case Jetson-nano-case] (3D-printable enclosure)
 
* [https://github.com/dudasdavid/Jetson-nano-case Jetson-nano-case] (3D-printable enclosure)
 
* [https://www.amazon.com/Geekworm-NVIDIA-Enclosure-Control-Developer/dp/B07RRRX121 Geekworm Jetson Nano Case] (metal enclosure)
 
* [https://www.amazon.com/Geekworm-NVIDIA-Enclosure-Control-Developer/dp/B07RRRX121 Geekworm Jetson Nano Case] (metal enclosure)
 +
* [https://www.amazon.com/GeeekPi-NVIDIA-Cooling-Control-Developer/dp/B07VVJNXMB/ GeeekPi Jetson Nano Case] (metal enclosure)
 +
* [https://www.amazon.com/Case-Jetson-Nano-Compatible-Peripherals/dp/B07VTNSS4S Waveshare Jetson Nano Case] (metal enclosure)
 
* [https://www.kksb-cases.us/collections/nvidia/products/kksb-jetson-nano-case-black# KKSB Jetson Nano Case] (metal enclosure)
 
* [https://www.kksb-cases.us/collections/nvidia/products/kksb-jetson-nano-case-black# KKSB Jetson Nano Case] (metal enclosure)
* [https://www.iotamy.com/Jetson-Nano-IP67-Fanless-Aluminium-Enclosure IP67 Fanless Aluminum Enclosure] (metal enclosure)
+
* [https://www.iotamy.com/Jetson-Nano-IP67-Fanless-Aluminium-Enclosure IP67 Fanless Aluminum Case] (metal enclosure)
 +
* [https://www.picocluster.com/collections/jeston-nano PicoCluster] (cluster chassis)
  
 
==== Power Supplies ====
 
==== Power Supplies ====
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* Adafruit [https://www.adafruit.com/product/1995 GEO151UB] (5V⎓2.5A MicroUSB adapter)
 
* Adafruit [https://www.adafruit.com/product/1995 GEO151UB] (5V⎓2.5A MicroUSB adapter)
 
* Adafruit [https://www.adafruit.com/product/1466 GEO241DA-0540] (5V⎓4A DC barrel jack adapter)
 
* Adafruit [https://www.adafruit.com/product/1466 GEO241DA-0540] (5V⎓4A DC barrel jack adapter)
 +
* Geekworm [https://www.amazon.com/dp/B07413Q5Y4 5V⎓4A DC barrel jack adapter]
 
* GeekPi [https://www.amazon.com/dp/B07CYZ9GZZ ABT025050] (5V⎓2.5A MicroUSB Adapter with ON/OFF Switch)
 
* GeekPi [https://www.amazon.com/dp/B07CYZ9GZZ ABT025050] (5V⎓2.5A MicroUSB Adapter with ON/OFF Switch)
 
* Pwr+ [https://www.amazon.com/dp/B00L88M8TE PWR-TA05035N] (5V⎓3.5A MicroUSB AC Adapter)
 
* Pwr+ [https://www.amazon.com/dp/B00L88M8TE PWR-TA05035N] (5V⎓3.5A MicroUSB AC Adapter)
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==== Storage ====
 
==== Storage ====
* Geekworm [https://geekworm.com/products/nvidia-jetson-nano-25-inch-sata-ssd-hdd-shield SATA SSD/HDD Shield] (USB3 SATA shield)
+
* Geekworm [https://www.amazon.com/dp/B07T9FQ293 SATA SSD/HDD Shield] (USB3 SATA shield)
 +
* Geekworm [https://www.amazon.com/dp/B07TYKM7TCSATA NVMe SSD Shield] (USB3 SATA shield)
  
 
==== Other ====
 
==== Other ====

Revision as of 12:15, 22 November 2019

NVIDIA Jetson Nano is an embedded system-on-module (SoM) and developer kit from the NVIDIA Jetson family, including an integrated 128-core Maxwell GPU, quad-core ARM A57 64-bit CPU, 4GB LPDDR4 memory, along with support for MIPI CSI-2 and PCIe Gen2 high-speed I/O.

Useful for deploying computer vision and deep learning, Jetson Nano runs Linux and provides 472 GFLOPS of FP16 compute performance with 5-10W of power consumption.

Jetson Nano is currently available as the Jetson Nano Developer Kit for $99, with the production compute module coming in June 2019. See the wiki of the other Jetson's here.

  Technical BlogNVIDIA Jetson Nano Brings AI to Everyone


Jetson Nano Family.png

Jetson Nano Developer Kit

The Jetson Nano Developer Kit is an easy way to get started using Jetson Nano, including the module, carrier board, and software. It costs $99 and is available from distributors worldwide.

Jetson Nano Developer Kit.png

What's Included

  • 80x100mm Reference Carrier Board
  • Jetson Nano Module with passive heatsink
  • Pop-Up Stand
  • Getting Started Guide

(the complete devkit with module and heatsink weighs 138 grams)

What You Will Need

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

Getting Started

Availability

The devkit is available for $99 from the NVIDIA webstore and global distributors, including:

For the full list, refer to the Region Selector.

Software Support

See the Jetson Zoo for more software packages to install on top of JetPack.

Guides and Tutorials

This section contains recipes for following along on Jetson Nano.

System Tools

Deep Learning

See the Jetson Zoo for more resources on deploying AI and deep learning.

Robotics

Multimedia

V4L2 drivers for cameras

Design FAQs

There are some useful FAQs for Jetson Nano design, link is here.

Ecosystem Products and Sensors

The following are 3rd-party accessories, peripherals, and cameras available for Jetson Nano.

Cameras

Carriers

Enclosures

Power Supplies

See the Power Supply section and this forum post for more information about selecting proper power adapters.

Battery Packs

  • INUI 10000mAh (dual 5V⎓3A Micro-USB)
  • Krisdonia 25000mAh (5V⎓3A Micro-USB / DC barrel jack)

Wireless

Storage

Other

See the Jetson Nano Supported Components List for devices that have been qualified by NVIDIA to work with Jetson Nano.

Getting Help

If you have a technical question or bug report, please visit the Jetson Nano Developer Forum and search or start a new topic.

See the official Support page on Embedded Developer Zone for warranty and RMA information.

For NVIDIA webstore Customer Service, please see the My Account page or contact 1-800-797-6530.