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PRODUCT DETAILS

Tip

Raspberry Pi Camera Module V2 is released recently, it is perfectly compatible with NVIDIA® Jetson Nano™ Developer Kit. High resolution in images and videos and easy to be plugged in, get one and have the best experience for your media project.  

Description

The NVIDIA® Jetson Nano™ Developer Kit delivers the compute performance to run modern AI workloads at an unprecedented size, power, and cost. Developers, learners, and makers can now run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.

The developer kit can be powered by micro-USB and comes with extensive I/Os, ranging from GPIO to CSI. This makes it simple for developers to connect a diverse set of new sensors to enable a variety of AI applications. It’s incredibly power-efficient, consuming as little as 5 watts.

Jetson Nano is also supported by NVIDIA JetPack, which includes a board support package (BSP), Linux OS, NVIDIA CUDA®, cuDNN, and TensorRT™ software libraries for deep learning, computer vision, GPU computing, multimedia processing, and much more. The software is even available using an easy-to-flash SD card image, making it fast and easy to get started.

The same JetPack SDK is used across the entire NVIDIA Jetson™ family of products and is fully compatible with NVIDIA’s world-leading AI platform for training and deploying AI software. This proven software stack reduces complexity and overall effort for developers. 

Key Features

 Jetson Nano Module

  • 128-core NVIDIA Maxwell™ GPU
  • Quad-core ARM® A57 CPU
  • 4 GB 64-bit LPDDR4
  • 10/100/1000BASE-T Ethernet 

 Power Options

  • Micro-USB 5V 2A
  • DC power adapter 5V 4A

 I/O

  • USB 3.0 Type A
  • USB 2.0 Micro-B
  • HDMI/DisplayPort
  • M.2 Key E
  • Gigabit Ethernet
  • GPIOs, I2C, I2S, SPI, UART
  • MIPI-CSI camera connector
  • Fan connector
  • PoE connector

 Kit Contents

  • NVIDIA Jetson Nano module and carrier board
  • Quick Start Guide and Support Guide  

Changes with the B01 Kit

114992260114992261114992262114992263114992264114992265114992270
Diagonal Field of View (FOV) 77° 77° 130° 160° 160° 200° 83°
IR LED Modules None 2 None None 2 None None
Aperture 2.0 2.0 1.8 2.35 2.35 2.0 /
Focal Length 2.96mm 2.96mm 1.88mm 3.15mm 3.15mm 0.87mm 2.6mm
Lens Construction 4P 4P 4E+IR 6G+IR 6G+IR 1G4P+IR /
Distortion <1% <1% <7.6% <14.3% <14.3% <18.6% <1%
EFL 2.93mm 2.93mm 1.85mm 3.15mm 3.15mm 0.9mm /
BFL (Optical) 1.16mm 1.16mm 1.95mm 3.15mm 3.15mm 1.41mm /

Reinforce Your Projects with Grove Pi HAT

If you want to use Grove sensors with Jetson Nano, grab the grove.py Python library and get your sensors up in running in minutes! Currently, there are more than 20 Grove modules supported on Jetson Nano and we will keep adding more. You can connect Grove modules using Base HAT for Raspberry Pi or Raspberry Pi Zero with Jetson Nano.

 

Note

We provide a wide selection of AI-related products including Machine Learning, Computer Vision, Edge Computing, Speech Recognition & NLP and Neural Networks Acceleration. Check here for more products you may need.

We are also calling for feedback and inputs from the developers. Any suggestions on the product features are welcomed at Seeed Forum!

Specifications

  • GPU: 128-core Maxwell
  • CPU:Quad-core ARM A57 @ 1.43 GHz
  • Memory: 4 GB 64-bit LPDDR4 25.6 GB/s
  • Storage: microSD (not included)
  • Video Encoder: 4K @ 30 | 4x 1080p @ 30 | 9x 720p @ 30 (H.264/H.265)
  • Video Decoder: 4K @ 60 | 2x 4K @ 30 | 8x 1080p @ 30 | 18x 720p @ 30|(H.264/H.265)
  • Camera: 2x 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

Version Change Information for B01 from A02

  • The B01 revision carrier is compatible with the production specification Jetson Nano module. The A02 revision carrier is not.
  • Removed Button Header [J40] Position
  • Removed Serial Port Header [J44] Position
  • Adjusted the Position of Power Select Jumper [J48]
  • Adjusted the Position of Camera Connector [J13]
  • Added Camera Connector [J49] location
  • Factory JetPack Upgrade from 4.2 SDK to 4.3 SDK

ECCN/HTS

HSCODE 8543709990
UPC

REVIEWS

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  1. Rating
    100%
    Good CoM to learn AI
    I'm very satisfied with this CoM on price over performance, with US$99 its absolutely the best Dev Kit ever to learn Deep Learning and Computer Vision, even better it lets you run multiple neural networks in parallel for applications like image classification, object detection, and segmentation.
    Only one problem that bother me, even though it has 2 MIPI CSI camera connector, its not synchronized with each other and cannot do depth disparity, maybe in later release NVIDIA should consider about this, so we can have 3D stereo depth synchronized camera capability using these MIPI CSI connectors onboard without using special shield or hat. Cheers!
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