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NVIDIA Jetson Nano Developer Kit EXPIRED

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Newegg has NVIDIA Jetson Nano Developer Kit on sale for $79 when you apply $20 off promo code 93XPD65 in cart. Shipping is free. Thanks StealTheDeals
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  • Sale is valid for today only, 12/8/19 or while supplies last.
  • Experience powerful and efficient AI, computer vision, and high-performance computing.

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Edited December 8, 2019 at 10:57 AM by
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For most people, if you don't already know the difference between the two, the Raspberry Pi 4 is the best choice.

The NVIDIA Jetson Nano and Raspberry Pi 4 are both several times faster than any previous SBC. Unless you have some limiting constraint like cost or weight, there isn't any reason to consider anything other than one these two.

The Raspberry Pi has a slightly faster general purpose ARM processor. Most importantly the software ecosystem is far more mature. If you want to use this as a system to tinker, learn and do various paint by numbers projects, the Raspberry is a better option for this reason alone.

The NVIDIA is the clear choice for for robotics and AI. It's big advantage over the RPI is for projects that use TensorFlow or other ML framework. If you have the ability to do this kind of project with an SBC, you likely already knew this.
59 Helpful?
There was a medium article where they walked you through a level of recognition using python code and this board. https://link.medium.com/UMzp25Sbg2

Link was through mobile but the article title is "Build a Hardware-based Face Recognition System for $150 with the Nvidia Jetson Nano and Python" by Adam Geitgey
18 Helpful?
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 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)
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 69 mm x 45 mm, 260-pin edge connector
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#3
Thanks. Got one for my son
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#4
What is size of ram and flash ?
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#5
what are some of the use cases for this ? Is it better than a raspberry pi 4 ?
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#6
Quote from SmartGazelle1697
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what are some of the use cases for this ? Is it better than a raspberry pi 4 ?
Learning Machine Learning. Computer Vision. Build your own Tesla

Getting Started
https://developer.nvidia.com/embe...ano-devkit
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#7
Quote from cgigate
:
What is size of ram and flash ?
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 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)
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 69 mm x 45 mm, 260-pin edge connector
Reply Helpful Comment? 12 0
Last edited by yegle December 8, 2019 at 11:01 AM.
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12-08-2019 at 10:59 AM
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#9
Quote from SmartGazelle1697
:
what are some of the use cases for this ? Is it better than a raspberry pi 4 ?
There are some discussion on Reddit to use this with Plex server. By a quick look, it seems like it can at lease serve H264 encoded 1080p very well, and has the potential to hardcode accelerate H265 4k video.
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#10
Can this run some raspbian version of Linux to use as hrpc? Typically nvda video processing is better right?
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12-08-2019 at 11:04 AM
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#12
Quote from didadi
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Can this run some raspbian version of Linux to use as hrpc? Typically nvda video processing is better right?
check this page https://elinux.org/Jetson_Nano
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#13
can this be made into a 4k capable HTPC?
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#14
Great, being waiting for a RPI type machine learning board to run own home surveillance camera person/facial detection (in chinese style Smilie) so no google IQ fees. this might just be capable enough to handle that than a desktop which burns a lot electric.

From Amazon review:
The software available for this unit is free for download IF you register and IF you can stand nVidia's forum format. Worst of all is the method nVidia chose to be able to boot this beast from SD card. Also, it ONLY supports booting from SD card. The above 2 unpleasant parts almost cost it a star, but it is so great overall that it still gets 5 stars.
Very capable board for developing your AI software. Not nearly as fast as dedicated AI hadware or even a good desktop at learning. It's still more than adequate for a portable device you can experiment with in the field (after you let a strong machine do the learning.)
It is a big plus that nVidia adopted the RPi pinouts on it's 40 pin section, but watch out for the small but not insignificant differences or you could release the magic smoke
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#15
Quote from worthmining
:
Great, being waiting for a RPI type machine learning board to run own home surveillance camera person/facial detection.
I tried and failed to build a facial recognition door lock using the RPi and Windows IOT. The system did work sometimes, but it was far to unreliable for practical use. It was more proof of concept. I still have all the gear sitting in drawer unused. Could you point me to a tutorial for something similar using this board.
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