Today is Canada’s Thanksgiving. Let me do something extra on Jetson Orin Orin.
1. My Working Environment
1 | ➜ ~ lsb_release -a |
2. Flash From Scratch
2.1 Entering Recovery Mode
In order to enter the Recovery Mode, we need to connect Jetson Orin Nano’s Pin 9 and Pin 10 with a jumper, and then turn on the power, and connect the Jetson Orin Nano with your desktop, here in my case, Ubuntu 24.04.1 LTS.
2.2 lsusb
1 | ➜ Resource git:(master) lsusb | grep NVIDIA |
2.3 Install Jetson Software with SDK Manager
To use SDK Manager, we need a Ubuntu 22.04.5 LTS or Ubuntu 20.04.6 LTS. In my case, I tried with Ubuntu 20.04.6 LTS.
| Step 01 | Step 02 |
|---|---|
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Get stucked at:
2.4 Jetson Orin Nano Tutorial: SSD Install, Boot, and JetPack Setup
What can I say?
😞😢😭
My comment: so complicated. I’m too lazy to follow.
2.5 dd Is My Favorite Tool
For some reasons, on my Jetson Orin Nano, there is NO TF card slot, but a 128G SSD instead.
😳😳😳
Therefore, in my case, my BEST solution is to flash the SSD directly.
Simply download and unzip JetPack 6.1 Orin Nano SD Card Image first. Then, do dd:
1 | ➜ jetson sudo dd bs=1M if=sd-blob.img of=/dev/sdb conv=fsync |
However, again, it’s NOT working.
😞😢😭
3. My LAST and FINAL Attempt - Jetson Linux Developer Guide Quick Start
I watched the entire video below, and was expecting a good result.
3.1 Before Flash
Let’s try to do sudo ./apply_binaries.sh again:
1 | ➜ Linux_for_Tegra sudo ./apply_binaries.sh |
3.2 DANGER
Right before I tried to run the following command:
1 | sudo ./tools/kernel_flash/l4t_initrd_flash.sh --external-device nvme0n1p1 \ |
I noticed nvme0n1p1 !!! I got another SSD connected to my desktop and listed as nvme0n1p1 ALREADY.
1 | ➜ Linux_for_Tegra lsblk |
A whole bunch of command lines are to be used, in order to let my OS not load nvme0n1:
3.2.1 Umount
1 | sudo umount /dev/nvme0n1p1 |
3.2.2 Check nvmes
1 | ➜ lspci | grep -i nvme |
3.2.3 Find the Correct nvme‘s PCI
1 | ➜ sudo udevadm info --query=all --name=/dev/nvme0n1 | grep ID_PATH |
3.2.4 Unbind the Corresponding nvme
1 | ➜ Linux_for_Tegra echo "0000:01:00.0" | sudo tee /sys/bus/pci/drivers/nvme/unbind |
3.3 Flash
Now, ALL ready. Let’s flash.
3.3.1 Package Preparations
You may still have to install a couple of more packages on your host Ubuntu 24.04.1 LTS:
sshpassabootimgnfs-kernel-server
3.3.2 Run l4t_initrd_flash.sh
However, in the end, in my case, on my host Ubuntu 24.04.1 LTS, I got:
1 | ➜ Linux_for_Tegra sudo ./tools/kernel_flash/l4t_initrd_flash.sh --external-device nvme0n1p1 \ |
Extremely sad now:
😭😭😭😭😭😭
I Believe, there is ALWAYS a way out. Solution is finally found at JetPack 6.1 Release Announcement. It’s simply because I used a wrong command to flash. Try again:
1 | sudo ./tools/kernel_flash/l4t_initrd_flash.sh --external-device nvme0n1p1 -c tools/kernel_flash/flash_l4t_t234_nvme.xml -p '-c bootloader/generic/cfg/flash_t234_qspi.xml' --showlogs --network usb0 jetson-orin-nano-devkit internal |
This time, succeed.
4. Demonstration of Jetson Orin Nano
4.1 Initial Login Without ssh
You need the DP - DisplayPort. I got to purchase this new calbe iCAN 28AWG 1080p DisplayPort to HDMI Cable Male to Male Gold-plated White Color - 3 ft., in order to successfully display for Jetson Orin Nano’s first-time running.
4.2 ssh Into Jetson Orin Nano After ssh Is Enabled
4.3 jeston_release
4.4 jtop
4.5 jetson_clocks
4.6 tegrastats
4.7 nvidia-smi
5. Demonstration of YOLOv11 on Jetson Orin Nano
You can find PyTorch for JetPack 6.1 in Jetson Download Center. However….
5.1 Current Issue
- JetPack 6.1 Release Announcement
- PyTorch for Jetson - To the latest, it ONLY has the support for PyTorch v2.3.0, JetPack 6.0 (L4T R36.2 / R36.3) + CUDA 12.2.
- Installing PyTorch for Jetson Platform - Until today, October 17, 2024, what I can reach so far is this .pdf file: Guide Of Installing PyTorch For Jetson Platform.
5.2 Make YOLOv11 On Jetson Orin Nano Work With GPU
Solution:
pip install ultralytics- Overwrite
torchinstalled withultralyticsby PyTorch for JetPack 6.1 - Build torchvision from source
To successfully build torchvision from source, you may need to allocate more swap memory:
1 | sudo fallocate -l 4G /swapfile |
Otherwise, you may meet the following error:
1 | c++: fatal error: Killed signal terminated program cc1plus |
ChatGPT explained it as:
1 | The error you're encountering while building torchvision seems to be caused by your system running out of resources, particularly memory. The message c++: fatal error: Killed signal terminated program cc1plus often indicates that the system killed the process due to memory exhaustion. |
| ssh & neofetch | PyTorch for JetPack 6.1 Cuda Enabled |
|---|---|
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| YOLOv11 Initialization | YOLOv11 GPU |
|---|---|
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The End.
