jetson-inference
wlroots
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jetson-inference | wlroots | |
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11 | 107 | |
7,294 | 1,969 | |
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8.5 | 9.8 | |
about 1 month ago | over 2 years ago | |
C++ | C | |
MIT License | MIT License |
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jetson-inference
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Can this NVIDIA Jetson Nano handle advanced machine learning tasks?
Jetson Nano’s are obsolete and no longer supported; but to answer your question, this might be a good place to start.
- help with project involving object detection and tracking with camera
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Jetson Nano 2GB Issues During Training (Out Of Memory / Process Killed) & Other Questions!
I’m trying to do the tutorial, where they retrain the neural network to detect fruits (jetson-inference/pytorch-ssd.md at master · dusty-nv/jetson-inference · GitHub 1)
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Jetson Nano
Jetson-Inference is another amazing resource to get started on. This will allow you to try out a number of neural networks (classification, detection, and segmentation) all with your own data or with sample images included in the repo.
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Pretrained image classification model for nuts and bolts (or similar)
Hello! I'm looking for some pre trained image classification models to use on a Jetson Nano. I already know about the model zoo and the pre trained models included in the https://github.com/dusty-nv/jetson-inference repo. For demonstration purposes, however, I need a model trained on small objects from the context of production, ideally nuts, bolts, and similar small objects. Does anyone happen to know a source for this? Thanks a lot!
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PyTorch 1.8 release with AMD ROCm support
> They provide some SSD-Mobilenet-v2 here: https://github.com/dusty-nv/jetson-inference
I was aware of that repository but from taking a cursory look at it I had thought dusty was just converting models from PyTorch to TensorRT, like here[0, 1]. Am I missing something?
> I get 140 fps on a Xavier NX
That really is impressive. Holy shit.
[0]: https://github.com/dusty-nv/jetson-inference/blob/master/doc...
[1]: https://github.com/dusty-nv/jetson-inference/issues/896#issu...
- NVIDIA DLSS released as a plugin for Unreal Engine 4
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Help getting started
If you have a screen and keyboard and mouse plugged into the Nano, I would recommend starting with Hello AI World on https://github.com/dusty-nv/jetson-inference#hello-ai-world
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I'm tired of this anti-Wayland horseshit
Well, don't get me wrong. I do like my Jetson Nano. For a hobbyist who likes to tinker with machine learning in their spare time it's definitely a product cool and there are quite a few repositories on Github[0, 1] with sample code.
Unfortunately… that's about it. There is little documentation about
- how to build a custom OS image (necessary if you're thinking about using Jetson as part of your own product, i.e. a large-scale deployment). What proprietary drivers and libraries do I need to install? Nvidia basically says, here's a Ubuntu image with the usual GUI, complete driver stack and everything – take it or leave it. Unfortunately, the GUI alone is eating up a lot of the precious CPU and GPU resources, so using that OS image is no option.
- how deployment works on production modules (as opposed to the non-production module in the Developer Kit)
- what production modules are available in the first place ("Please refer to our partners")
- what wifi dongles are compatible (the most recent Jetson Nano comes w/o wifi)
- how to convert your custom models to TensorRT, what you need to pay attention to etc. (The official docs basically say: Have a look at the following nondescript sample code. Good luck.)
- … (I'm sure I'm forgetting many other things that I've struggled with over the past months)
Anyway. It's not that this information isn't out there somewhere in some blog post, some Github repo or some thread on the Nvidia forums[2]. (Though I have yet to find a reliably working wifi dongle…) But it usually takes you days orweeks to find it. From a product which is supposed to be industry-grade I would have expected more.
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Basic Teaching
https://github.com/dusty-nv/jetson-inference#system-setup
wlroots
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Xorg being removed. What does this mean?
>barrier has been unmaintained for a long time.
As if not having new features added for 2 years makes it stop working? barrier is perfectly fine on normal linux desktop installs. I actually use synergy 1.x personally which has been "unmaintained" for much, much longer. Except synergy 1.x will compile and run on anything from windows 98 to ubuntu 5 to debian 12. You can't get a waynergy or inputleap to compile on an OS more than 2 years old. And even then, as you say, it's crapshoot if the particular wayland will have libei; many like sway are actively hostile to it and never will: https://github.com/swaywm/wlroots/issues/2378
- Does Wayland use less battery than x11 in Fedora Linux?
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Arch Linux odd question
It looks like they actually patched it to filter those modes out, so presumably it worked out of the box and was considered undesirable: https://github.com/swaywm/wlroots/issues/3038
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Asahi Linux To Users: Please Stop Using X.Org
I haven't experienced any of those. The video game performance hit may be due to vsync, but I don't play games so I haven't noticed.
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If I install a distro without a GUI, can I still launch graphical applications (like a Firefox window, for example)?
You can however use tinywl. It is an example Wayland compositor that can't do more than displaying one application.
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Nearest-neighbor scaling on XWayland apps?
Sway/wlroots has implemented this, but I can't find any discussion for KDE.
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Wofi is SO superior to Rofi
wlroots is archived on github. Is it abandoned? Just saying, that only means they moved git hosts :-D
- wayland-protocols update to allow tearing
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Wayland harder for DE developers?
A lot of compositors are based no the wlroots lirbary. So they are still sharing the development effort and have a common base, its just in the form of a library rather than a display server.
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What does gamescope output to?
gamescope use wlroots
What are some alternatives?
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
wlroots-eglstreams - A modular Wayland compositor library with EGLStreams support
onnx-tensorrt - ONNX-TensorRT: TensorRT backend for ONNX
nvidia-patch - This patch removes restriction on maximum number of simultaneous NVENC video encoding sessions imposed by Nvidia to consumer-grade GPUs.
tensorflow - An Open Source Machine Learning Framework for Everyone
leftwm - A tiling window manager for Adventurers
yolov5-deepsort-tensorrt - A c++ implementation of yolov5 and deepsort
sway - i3-compatible Wayland compositor
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
wayfire - A modular and extensible wayland compositor
obs-studio - OBS Studio - Free and open source software for live streaming and screen recording
x11docker - Run GUI applications and desktops in docker and podman containers. Focus on security.