NVIDIA® Jetson Nano™ Developer Kit
NVIDIA® Jetson Nano™ Developer Kit is a small,
powerful computer that lets you run run multiple neural networks in parallel for applications like image classification,
object detection, segmentation, and speech processing.
All in an easy-to-use platform that runs in as little as 5 watts.
It’s simpler than ever to get started!
Just insert a microSD card with the system image, boot the developer kit, and begin using the latest NVIDIA JetPack SDK.
JetPack is compatible with NVIDIA’s world-leading AI platform for training and deploying AI software.
The same JetPack SDK is used across the entire NVIDIA Jetson™ family of products.
Plus, it’s compatible with NVIDIA’s world-leading AI platform for training and deploying AI software,
reducing complexity and effort for developers.
|CPU||Quad-core ARM A57 @ 1.43 GHz|
|Memory||4 GB 64-bit LPDDR4 25.6 GB/s|
|Storage||microSD (not included)|
|Video Encode||4x 1080p @ 30 | 9x 720p @ 30 (H.264/H.265)|
|Video Decode||2x 4K @ 30 | 8x 1080p @ 30 | 18x 720p @ 30 (H.264/H.265)|
|Camera||1x MIPI CSI-2 DPHY lanes|
|Connectivity||Gigabit Ethernet, M.2 Key E|
|Display||HDMI 2.0 and eDP 1.4|
|USB||4x USB 3.0, USB 2.0 Micro-B|
|Others||GPIO, I2C, I2S, SPI, UART|
|Mechanical||100 mm x 80 mm x 29 mm|
- 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)
- Download Center: [ https://developer.nvidia.com/embedded/downloads#?search=Jetson%20Nano Download Center ]
- Jetson Nano Developer Kit User Guide PDF file: File:Jetson Nano Developer Kit User Guide.pdf
Guides and Tutorials
This section contains recipes for following along on Jetson Nano.
- RidgeRun's GstInterpipe (GStreamer plug-in for communication between two or more independent pipelines)
- RidgeRun's GstRRWebRTC (GStreamer plug-in that turns pipelines into WebRTC compliant endpoints)
- RidgeRun's GstRTSPSink (GStreamer element for high performance streaming to multiple computers using the RTSP/RTP protocols)
- RidgeRun's Gstreamer Daemon - GstD (GStreamer framework for controlling audio and video streaming using TCP connection messages)
- RidgeRun's GstCUDA (RidgeRun CUDA ZeroCopy for GStreamer)
- RidgerRun's GstPTZR (GStreamer Pan Tilt Zoom and Rotate Element)
- RidgeRun's GstColorTransfer (GStreamer plug-in that transfers the color scheme from a reference to a target image)
- Hello AI World (jetson-inference)
- TensorFlow 1.13.1 Installer (pip wheel)
- PyTorch 1.1 Installer (pip wheel)
- MXNet 1.4 Installer (pip wheel)
- Deep Learning Inference Benchmarking Instructions
- TensorFlow Object Detection With TensorRT (TF-TRT)
- RidgeRun's GstInference
- RidgeRun's R2Inference
See the NVIDIA AI-IoT GitHub for other coding resources on deploying AI and deep learning.
- NVIDIA JetBot (AI-powered robotics kit)
- jetbot_ros (ROS nodes for JetBot)
- ROS Melodic (ROS install guide)
- ros_deep_learning (jetson-inference nodes)
See the Jetson Nano Supported Components List for devices that have been qualified by NVIDIA to work with Jetson Nano.
- FAQ:[| Jetson Nano FAQ]
- Q: My Camera is no responding, why?
A: Only Support offical camera on Version V2.1
- Q: What is 12V power supply DC cable's Specifications?
A: It is 5.5 x 2.5 mm, and Negtive outside, positive inside.
Please follow the link: [ Jetson Nano Developer Kit Open Box | https://youtu.be/P48qLppAqKc ]