Overview
reComputer J2022 - Edge AI Computer is an edge AI computer from Seeed Studio built on the NVIDIA Jetson Xavier NX 16GB module. Its GPU is 384-core NVIDIA Volta™ GPU. It carries 8 GB 128-bit LPDDR4x @ 51.2GB/s. Seeed publishes a fixed price for this configuration.
Key Features
- Built on the Xavier NX (not the production version) module
- GPU: 384-core NVIDIA Volta™ GPU
- CPU: 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6 MB L2 + 4 MB L3
- Memory: 8 GB 128-bit LPDDR4x @ 51.2GB/s
- Storage: MicroSD (Card not included)
- Networking: 1*RJ45 Gigabit Ethernet Connector (10/100/1000)
Ideal For
teams deploying Jetson Xavier NX 16GB-class inference at the edge in a finished, cased unit
Product
NVIDIA Jetson Xavier NX Developer Kit
Module
Xavier NX (not the production version)
AI Perf
21 TOPS
GPU
384-core NVIDIA Volta™ GPU
CPU
6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6 MB L2 + 4 MB L3
Memory
8 GB 128-bit LPDDR4x @ 51.2GB/s
Storage
MicroSD (Card not included)
Video encoder
2x 4K @ 30 | 6x 1080p @ 60 | 14x 1080p @ 30 (H.265/H.264)
Video decoder
2x 4K @ 60 | 4x 4K @ 30 | 12x 1080p @ 60 | 32x 1080p @ 30 (H.265) 2x 4K @ 30 | 6x 1080p @ 60 | 16x 1080p @ 30 (H.264)
Gigabit Ethernet
1*RJ45 Gigabit Ethernet Connector (10/100/1000)
USB
4 * USB 3.1 Type A Connector; 1 * Micro-USB port for Device mode;
CSI Camera Connect
2*CSI Camera (15 pos, 1mm pitch, MIPI CSI-2 )
Display
1*HDMI Type A; 1*DP
FAN
1* FAN connector(5V PWM)
M.2 KEY E
1*M.2 Key E(WiFi/BT included)
M.2 KEY M
1*M.2 Key M
RTC
-
Multifunctional port
1* 40-Pin header
Power Requirements
DC Jack 19V 4.74A (MAX 90W)
Mechanical
103 mm x 90.5 mm x 31 mm
Acrylic Cover
1
Aluminum Frame
1
Jetson Xavier NX 16GB module
1
Aluminum heatsink with fan
1
Carrier Board
1
12V/5A(Barrel Jack 5.5/2.5mm) Power Adapter (Power cord not included)
1
Hand-size edge AI device
built with Jetson Xavier NX 16GB Production Module, delivering 384 NVIDIA CUDA® cores delivers up to 21 TOPs AI performance with a small form factor of 130mm x120mm x 50mm.
NVIDIA Jetson Xavier NX Dev Kit alternative
the carrier board brings rich IOs including a Gigabit Ethernet port, 4 USB 3.1 ports, an HDMI port, and a DP port
Pre-installed NVIDIA JetPack
support the entire Jetson software stack and various developer tools for building fast and robust AI application provided by Seeed Edge AI partners, helps develop innovative AI solution for manufacturing, logistics, retail, service, agriculture, smart city, healthcare, and life sciences, etc
Feature
Expandable with the onboard interfaces and reComputer case, able to mount on the wall with mounting holes on the back.
Feature
Traffic management license plate detection car detection pedestrian detection
Feature
license plate detection
Feature
car detection
Feature
pedestrian detection
Industry 4.0
helmet detection, hard hat detection, and custom PPE detection visual anomaly detection using NVIDIA Deepstream IoT
Feature
helmet detection, hard hat detection, and custom PPE detection
Feature
visual anomaly detection using NVIDIA Deepstream IoT
Retail
sentiment analysis(webinar: learn your customer with AI by Zenus smart camera), retail store items detection
sentiment analysis(webinar
learn your customer with AI by Zenus smart camera),
Feature
retail store items detection
Robotics
under-ice sensing ROV warehouse towing robot
Feature
under-ice sensing ROV
Feature
warehouse towing robot
Edge AI into the Wild
Wildfire detection
Agriculture
weeding machines, Tractors, Livestock detection
Healthcare
medical imaging analysis
Feature
Edge AI no code Vision tool, Seeed latest open-source project for deploying AI application within 3 nodes.
Feature
NVIDIA DeepStream SDK delivers a complete streaming analytics toolkit for AI-based multi-sensor processing and video and image understanding on Jetson.
Feature
NVIDIA TAO tool kit, built on TensorFlow and PyTorch, is a low-code version of the NVIDIA TAO framework that accelerates the model training
alwaysAI
build, train, and deploy computer vision applications directly at the edge of reComputer. Get free access to 100+ pre-trained Computer Vision Models and train custom AI models in the cloud in a few clicks via enterprise subscription. Check out our wiki guide to get started with alwaysAI.
Edge Impulse
the easiest embedded machine learning pipeline for deploying audio, classification, and object detection applications at the edge with zero dependencies on the cloud.
Feature
Roboflow provides tools to convert raw images into a custom-trained computer vision model of object detection and classification and deploy the model for use in applications. See the full documentation for deploying to NVIDIA Jetson with Roboflow.
YOLOv5 by Ultralytics
use transfer learning to realize few-shot object detection with YOLOv5 which needs only a very few training samples. See our step-by-step wiki tutorials
Deci
optimize your models on NVIDIA Jetson Nano. Check the webinar at Deci of Automatically Benchmark and Optimize Runtime Performance on NVIDIA Jetson Nano and Xavier NX Devices
Feature
NVIDIA® Riva is a GPU-accelerated SDK for building Speech AI applications that are customized for your use case and deliver real-time performance.
Feature
NVIDIA Isaac ROS GEMs are hardware-accelerated packages that make it easier for ROS developers to build high-performance solutions on NVIDIA hardware. Learn more about NVIDIA Developer Tools
Feature
Cogniteam Nimbus is a cloud-based solution that allows developers to manage autonomous robots more effectively. Nimbus platform supports NVIDIA® Jetson™ and ISAAC SDK and GEMs out-of-the-box. Check out our webinar on connecting your ROS Project to the Cloud with Nimbus.
Feature
We have already installed JetPack 5.1.1 system in the reComputer and you can directly use it by powering it on.
Feature
Please check our wiki for reflashing Jetpack and expanding the storage.
Feature
We'd like to hear from you, welcome to join our Discord channel to share your thoughts (Jetson edge AI)
Prices may vary. Verify on vendor site.
Quick Specs
- Product
- NVIDIA Jetson Xavier NX Developer Kit
- Module
- Xavier NX (not the production version)
- AI Perf
- 21 TOPS
- GPU
- 384-core NVIDIA Volta™ GPU
- CPU
- 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6 MB L2 + 4 MB L3
- Memory
- 8 GB 128-bit LPDDR4x @ 51.2GB/s