ThinkRobotics Edge AI Device with NVIDIA Jetson Orin™ NX 16GB module (J4012)
ThinkRobotics Edge AI Device is built with Jetson Orin NX 16GB - a powerful and compact intelligent edge box to bring up to 100 TOPS modern AI performance to the edge, which offers up to 5X the performance of Jetson Xavier NX and up to 3X the performance of Jetson AGX Xavier. Combining the NVIDIA Ampere™ GPU architecture with 64-bit operating capability, Orin NX integrates advanced multi-function video and image processing, and NVIDIA Deep Learning Accelerators.
The full system includes one NVIDIA Jetson Orin™ NX 16GB production module, SEEED Studio reComputer J401 carrier board, a heatsink, AW-CB375NF Dual-Band Wireless NIC WiFi5 module, a power adapter installed in a 3D printed carbon fiber case. The device is preinstalled with JetPack 5.1 on the included 240GB NVMe SSD, simplifies development, and fits for deployment for edge AI solution providers working in video analytics, object detection, natural language processing, medical imaging, and robotics across industries of smart cities, security, industrial automation, smart factories.
Features
- Brilliant AI Performance for production: on-device processing with up to 100 TOPS AI performance with low power and low latency
- Hand-size edge AI device: compact size at 130mm x120mm x 58.5mm, includes NVIDIA Jetson Orin™ NX 16GB production module, a cooling fan with a heatsink, enclosure, and a power adapter. Support desktop, wall mount, fit in anywhere
- Expandable with rich I/Os: 4x USB 3.2, HDMI 2.1, 2xCSI, 1xRJ45 for GbE, M.2 Key E, M.2 Key M, CAN, and GPIO.
- Accelerate solution to market: pre-installed Jetpack with NVIDIA JetPack™ 5.1 on the included 128GB NVMe SSD, Linux OS BSP, 128GB SSD, support Jetson software and leading AI frameworks and software platforms
- Comprehensive certificates: FCC, CE, RoHS
Description
With rich extension modules, industrial peripherals, and thermal management, reComputer for Jetson is ready to help you accelerate and scale the next-gen AI product by deploying popular DNN models and ML frameworks to the edge and inferencing with high performance, for tasks like real-time classification and object detection, pose estimation, semantic segmentation, and natural language processing (NLP).
At Seeed Studio, you will find everything you want to work with the NVIDIA Jetson Platform – official NVIDIA Jetson Dev Kits, Seeed-designed carrier boards, edge devices, as well as accessories.
SEEED Studio has prepared abundant guides to get started with NVIDIA Jetson using leading AI frameworks and software. For example, with Deepstream and TensorRT, developers can deploy custom YOLOv5 models on Jetson Orin at over 100FPS
Developers Tools
Pre-installed Jetpack for fast development and edge AI integration
Jetson software stack begins with NVIDIA JetPack™ SDK which provides a full development environment and includes CUDA-X accelerated libraries and other NVIDIA technologies to kickstart your development. JetPack includes the Jetson Linux Driver package which provides the Linux kernel, bootloader, NVIDIA drivers, flashing utilities, sample filesystem, and toolchains for the Jetson platform. It also includes security features, over-the-air update capabilities, and much more.
Computer Vision and embedded machine learning
- NVIDIA DeepStream SDK delivers a complete streaming analytics toolkit for AI-based multi-sensor processing and video and image understanding on Jetson.
- 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.
- 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
Speech AI
-
NVIDIA® Riva is a GPU-accelerated SDK for building Speech AI applications that are customized for your use case and deliver real-time performance.
Remote Fleet Management
Enable secure OTA and remote device management with Allxon. Unlock 90 days free trial with code H4U-NMW-CPK.
Robot and ROS Development
- 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
- 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.
Hardware Overview
Interface-rich reference carrier board
Seeed carrier board for reComputer J4012 is a high-performance, interface-rich board, providing HDMI 2.1, Gigabit Ethernet, USB 3.2, M.2 key E, M.2 key M, CSI camera, CAN, GPIO, I2C, I2S, fan, and other rich peripheral interfaces.
Take advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capabilities to all your embedded AI and edge systems.
Part List
|
NVDIA Jetson Orin™ NX 16GB |
x1 |
|
Seeed carrier board (reComputer J401) |
x1 |
|
240GB NVMe SSD |
x1 |
|
Aluminum heatsink with fan |
x1 |
|
Aluminum case (black) |
x1 |
|
12V/5A power adapter |
x1 |
FAQ
What type of RTC is recommended for RTC socket?
CR1220 and ML1220. The non-rechargeable design of the RTC circuit of the carrier board allows both rechargeable and non-rechargeable RTC batteries to be used.
