- jetson-inference VS openpose
- jetson-inference VS tensorflow
- jetson-inference VS onnx-tensorrt
- jetson-inference VS TensorRT
- jetson-inference VS obs-studio
- jetson-inference VS trt_pose_hand
- jetson-inference VS sway
- jetson-inference VS YOLOv4-Tiny-in-UnityCG-HLSL
- jetson-inference VS tensorrt_demos
- jetson-inference VS lemon-dataset
Jetson-inference Alternatives
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TensorRT
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better jetson-inference alternative or higher similarity.
jetson-inference reviews and mentions
Posts with mentions or reviews of jetson-inference.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-03-04.
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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...
They provide some SSD-Mobilenet-v2 here:
https://github.com/dusty-nv/jetson-inference
Also they want you to train it using their "DIGITS" interface which works but doesn't support any more recent networks.
I really wish Nvidia would stop trying to reinvent the wheel in training and focus on keeping up with being able to properly parse all the operations in the latest state-of-the-art networks coded in Pytorch and TF 2.x.
- 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
Stats
Basic jetson-inference repo stats
9
5,601
8.3
6 days ago
dusty-nv/jetson-inference is an open source project licensed under MIT License which is an OSI approved license.
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