Difference between 2 Jetson Nano Developer Kit SD Card images from NVIDIA

Autonomous Machines Jetson & Embedded Systems Jetson Nano
#1

The Jetson Nano course has an image of 7.1 GB titled: ‘dlinano_v1-0-0_image_20GB.zip’ on https://developer.download.nvidia.com/training/nano/dlinano_v1-0-0_image_20GB.zip

and the Jetson Nano getting started page has an image of 5.3 GB titled: ‘jetson-nano-sd-r32.1.1-2019-05-31.zip’ on https://developer.download.nvidia.com/assets/embedded/downloads/jetson-nano-sd-card-image/r32.1.1-2019-05-31/jetson-nano-sd-r32.1.1-2019-05-31.zip?HWa9JvcNT_59F7mPDKa-J0-AJcrGzmgrVlS7rLdZoUdbFFxUMB3arvNiNeRFhnG6wEiHemNSxZE73HViEeS8RFvKyFr3A1NeRlUwaF8T_9AD8EWDfGPKsPw0dupeZCLY6ezjNtrW562qYoT49FsFcLyka

What’s the difference between the 2 if someone has downloaded and tried both?

#2

The DLI Nano image comes with additional components pre-installed that are required for the DLI Nano course, including PyTorch, JupyterLab, ect.

#3

dear all,

i am using a 64 gb sandisk sdcard to write dlinano_v1-0-0_image_20GB using balenaetcher.
at my desktop it creates 12 sdcard partitions. However, the jetson nano (dev kit) cannot boot.
please help. thank you.

warmest regards,
suryadi

#4

Hi suryadi, have you previously been able to boot your Nano from the normal (non-DLI) image?

If so, you may want to try re-formatting and re-flashing your SD card.

If this is the first time you have booted the device, try re-flashing your SD card with the normal image as a test. Do you see a green LED and any activity from HDMI or serial port? You may want to try one of the power supplies from the Nano Supported Components List.

#5

Dear Dusty,

Before I try flashing Jetpack 4.2.1, I can use my Jetson Nano Jetpack 4.2 (login, browsing internet from inside it). After trying several times failed using SDKManager and $ sudo ./flash.sh jetson-nano-qspi mmcblk0p1 (recovery mode) with a 32 GB SDcard for Jetpack 4.2.1.

Then I use balena etcher (without go through sudo flash thing) and succeed with a 16 GB SDcard for Jetpack 4.2.1.

Then I issue command:
$ sudo apt upgrade
(it run successfully too). I think this sdcard is too small.

After that I try to use a 32 GB and a 64 GB with many failed attempts using balena ether within Windows 10 and ubuntu 18.04 environment for both DLI and Jetpack 4.2.1 images.

I put back my 16 GB sdcard into Jetson Nano, but it failed booting too now.
My Jetson Nano still can do a recovery mode and $ sudo ./flash.sh jetson-nano-qspi mmcblk0p1, but stuck at writing APP stages.

Writing partition APP with system.img
[ 76.9557 ] [..... ] 010%
Error: Return value 1
Command tegradevflash --pt flash.xml.bin --storageinfo storage_info.bin --create
Failed flashing t210ref.

My sdcard latch still in good condition, it can hold sdcard correctly.

Is there any way to know that my Jetson Nano in good or broken condition?

Please check this thread, for more complete story
https://devtalk.nvidia.com/default/topic/1060712/jetson-nano/frustated-etching-jetpack-4-2-1-for-nano/post/5371863/#5371863

Thank you very much in advance.

Warmest Regards,
Suryadi

#6

Kind of ridiculous that we have to jump through these kinds of hoops as beginners to get the correct notebooks in order to work through the NVidia AI course. The courses look useful at first glance, but the documentation desires much to be considered an efficient way to get up and running in these technologies.
It’s taken me a few days and flashing a few different SD images to finally get at these notebooks which are referenced in this course.
https://courses.nvidia.com/courses/course-v1:DLI+C-RX-02+V1/courseware/b2e02e999d9247eb8e33e893ca052206/26aa9f8bdaa948d9b068a8275c89e546/?child=first