NVIDIA Jetson Nano Developer Kit-B01 Gets an Extra Camera Connector

Jetson Nano Developer Kit B01

Launched in March 2019, NVIDIA Jetson Nano developer kit offered an AI development platform for an affordable $99. The kit is comprised of Jetson Nano module and a carrier board, and the version I received last November ended with “A02”. Jetson Nano developer kit is now getting updated with B01 carrier board that adds an extra MIPI CSI connector and other few changes, including compatibility with NVIDIA Jetson Nano production module (with eMMC flash instead of MicroSD card). Jetson Nano developer kit-B01 specifications: B01 Jetson Nano CPU Module 128-core Maxwell GPU Quad-core Arm A57 processor @ 1.43 GHz System Memory  – 4GB 64-bit LPDDR4 @ 25.6 GB/s Storage  – microSD card slot Video Encode – 4K @ 30 | 4x 1080p @ 30 | 9x 720p @ 30 (H.264/H.265) Video Decode – 4K @ 60 | 2x 4K @ 30 | 8x 1080p @ 30 | 18x 720p @ 30 (H.264/H.265) Dimensions – 70 x 45 mm B01 Baseboard 260-pin …

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Testing NVIDIA Jetson Nano Developer Kit with and without Fan

Jetson Nano 52Pi-ICE Tower Cooling Fan

A few weeks ago I received NVIDIA Jetson Nano for review together with 52Pi ICE Tower cooling fan which Seeed Studio included in the package, and yesterday I wrote a getting started guide showing how to setup the board, and play with inference samples leveraging the board’s AI capabilities. I’ll now test the board with the stock heatsink in both 5W and 10W modes, and see if thermal throttling does occur, and then I’ll fit the tower cooling fan to find out if we can extract more performance that way and how much lower the CPU temperature is. Jetson Nano Stress Tests with Stock Heatsink Let’s install SBC-Bench testing utility, check it’s properly installed, and run it in 5W mode: The temperature never went over 44.5°C, and no throttling occurred. tegrastats during 7-zip multi-core test: Only two Cortex-A57 cores are used even under load, and power consumption is around 3.3 Watts. Let’s run sbc-bench in 10W mode: The maximum temperature …

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Getting Started with NVIDIA Jetson Nano Devkit: Inference using Images, RTSP Video Stream

Jetson Nano RTSP Stream Inference

Last month I received NVIDIA Jetson Nano developer kit together with 52Pi ICE Tower Cooling Fan, and the main goal was to compare the performance of the board with the stock heatsink or 52Pi heatsink + fan combo. But the stock heatsink does a very good job of cooling the board, and typical CPU stress tests do not make the processor throttle at all. So I had to stress the GPU as well, as it takes some efforts to set it up all, so I’ll report my experience configuring the board, and running AI test programs including running objects detection on an RTSP video stream. Setting up NVIDIA Jetson Nano Board Preparing the board is very much like you’d do with other SBC’s such as the Raspberry Pi, and NVIDIA has a nicely put getting started guide, so I won’t go into too many details here. To summarize: Download the latest firmware image (nv-jetson-nano-sd-card-image-r32.2.3.zip at the time of the review) …

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NVIDIA Jetson Nano Review with 52Pi ICE Tower Cooling Fan – Part 1: Unboxing

Jetson Nano Review with ICE Tower Cooling Fan

If you remember soon after Raspberry Pi 4 launch, there were talks about the SBC overheating under load, and depending on room temperature and workload a heatsink may be needed for the board to perform optimally at all times. This gave birth to “interesting” solutions such as 52Pi ICE Tower Cooling Fan, an oversized cooling solution for Raspberry Pi 4. It does the job however, and it allows me to overclock Raspberry Pi 4 to 2.0 GHz while keeping the CPU temperature under 55°C in a room at 28°C. But the latest Raspberry Pi Foundation board is not the only SBC to suffer from overheating, as at least one user noticed the board would just shutdown under load. The solution was to switch from 10W mode to 5W mode, not an ideal solution since it’s also lowering performance. But 52Pi is coming to the rescue again, as they adapted their ICE tower cooling fan to Jetson Nano SBC. Seeed Studio …

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NVIDIA Jetson Xavier NX SoM Delivers up to 21 TOPS for AI Workloads at the Edge

NVIDIA Jetson Xavier NX

NVIDIA has just announced Jetson Xavier NX system-on-module, with the company claiming it is the “world’s smallest, most powerful AI supercomputer for robotic and embedded computing devices at the edge” with a 70x45mm “Jetson Nano” form factor, and delivering either up to 14 TOPS at 10 Watts or 21 TOPS at 15 Watts. The company expects the module to be used in small commercial robots, drones, intelligent high-resolution sensors for factory logistics and production lines, optical inspection, network video recorders, portable medical devices, and other industrial IoT systems. Jetson Xavier NX specifications: SoC – NVIDIA Xavier with 6-core NVIDIA Carmel ARM v8.2 64-bit CPU, 6MB L2 + 4MB L3 caches, and a 384-core NVIDIA Volta GPU with 48 Tensor Cores, 2x NVDLA deep learning accelerators delivering up to 21 TOPS at 15 Watts System Memory – 8 GB 128-bit LPDDR4x @ 51.2GB/s Storage – 16 GB eMMC 5.1 flash Video Encode 2x464MP/sec 2x 4K @ 30 (HEVC) 6x 1080p @ …

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NVIDIA Launches Upgraded Shield TV with Tegra X1+ Processor

Shield TV 2019 vs Shield TV Pro 2019

Ever since NVIDIA launched the Shield TV in 2015 it features in lists of best Android TV boxes in the $200 budget range, although it can raise to close to $300 if you do not live in a country where the Shield TV is not officially sold. The company launched a more compact version in 2017, and NVIDIA just officially announced upgraded Shield TV and Shield TV Pro 2019 models with a more powerful Tegra X1+ Processor delivering a 25% boost, as well as  Dolby Atmos and Dolby Vision support. As you can see from the photo above the Shield TV now has a completely different cylindrical design, while the Shield TV Pro keeps the traditional design of the box. However, both share many of the same specifications: SoC – NVIDIA Tegra X1+ processor with a 256-core NVIDIA GPU Memory & Storage Shield: 2 GB RAM; 8GB eMMC flash; MicroSD card slot Shield Pro: 3GB RAM; 16GB eMMC flash; MicroSD card …

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Waveshare Jetbot AI Kit for NVIDIA Jetson Nano Board Sells for $100 and Up

NVIDIA Jetbot

NVIDIA Jetson Nano developer kit was launched for $99 last March with impressive specifications for the price including one module with four Arm Cortex-A57 cores, a 128-core Maxwell GPU, and 4GB LPDDR4 RAM. The company also introduced Jetbot robot based on the new board, with all instructions available on Github, but until now you had to put some efforts to build it up as the fairly long list of parts had to be purchased or 3D printed separately. It’s now become easier, as Waveshare has started selling their Jetbot AI kit on Amazon for $122.99 without Jetson Nano, and $259.99 with, meaning you may be better off purchasing NVIDIA board separately for around $100, or you may purchase the complete kit directly on Waveshare website for $215.99 plus shipping, or $99.99 without the SBC. Jetbot AI kit content: Optional NVIDIA Jetson Nano SBC 64GB micro SD Card Metal box Camera holder Acrylic piece Jetbot expansion board with battery holder, motor …

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ZED Depth and Motion Tracking Camera Supports NVIDIA Jetson Nano Board

ZED depth camera Jetson Nano

When NVIDIA launched their low cost Jetson Nano development board earlier this week, one reader asked whether it would support binocular depth mapping. It turns out Stereo Labs has updated the SDK (Software Development Kit) for the ZED depth and motion tracking camera in order to support the latest NVIDIA developer kit. Jetson Nano can manage depth and positional tracking at 30 fps in PERFORMANCE mode with 720p resolution, and while the more powerful and expensive Jetson TX2 achieves doubles the performance at 60 fps, it does so at a much higher cost. ZED depth and motion tracking camera specifications: Video 2.2K @ 15 fps (4416×1242 resolution) 1080p @ 30 fps (3840×1080 resolution) 720p @ 60 fps (2560×720 resolution) WVGA @ 100 fps (1344×376 resolution) Depth Resolution – Same as selected video resolution Range – 0.5 to 20 m Format – 32-bits Stereo Baseline – 120 mm Motion 6-axis Pose Accuracy Position – +/- 1mm Orientation – 0.1° Frequency – …

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