yolov5
ROCm
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yolov5 | ROCm | |
---|---|---|
129 | 198 | |
46,738 | 3,637 | |
2.9% | - | |
8.9 | 0.0 | |
7 days ago | 4 months ago | |
Python | Python | |
GNU Affero General Public License v3.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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yolov5
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จำแนกสายพันธ์ุหมากับแมวง่ายๆด้วยYoLoV5
Ref https://www.youtube.com/watch?v=0GwnxFNfZhM https://github.com/ultralytics/yolov5 https://dev.to/gfstealer666/kaaraich-yolo-alkrithuemainkaartrwcchcchabwatthu-object-detection-3lef https://www.kaggle.com/datasets/devdgohil/the-oxfordiiit-pet-dataset/data
- How would i go about having YOLO v5 return me a list from left to right of all detected objects in an image?
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Building a Drowsiness Detection Web App from scratch - pt2
!git clone https://github.com/ultralytics/yolov5.git ## Navigate to the model %cd yolov5/ ## Install requirements !pip install -r requirements.txt ## Download the YOLOv5 model !wget https://github.com/ultralytics/yolov5/releases/download/v6.0/yolov5s.pt
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[Help: Project] Transfer Learning on YOLOv8
Specifically what I did was take the coco128.yaml, added 6 new classes from Dataset A (which have already been converted to YOLO Darknet TXT), from index 0-5 and subsequently adjusted the indices of the other COCO classes. The I proceeded to train and validate on Dataset A for 20 epochs.
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Changing labels of default YOLOv5 model
I am using the default YOLOv5m6 model here with sahi/yolov5 library for my object detection project. I want to change just some of labels - for example when YOLO detects a human, I want it to label the human as "threat", not "person". Is there any way I can do it just changing some code, or I should train the model from scratch by just changing labels?
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First time working with computer vision, need help figuring out a problem in my model
You should add them without annotations. Go through this.
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AI Camera?
You are correct and if you check the firmware, it's yet another famous 3rd party project without attribution, namely https://github.com/ultralytics/yolov5
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First non-default print on K1 - success
On one side, being a Linux user for 24 years now, it annoys me that they rip off code and claiming it as theirs again, thus violating licenses, but on the other thanks to k3d's exploit I'm able to tinker more with the machine and if needed do (selective) updates by hand then with a closed source system. It's not just "klipper", with klipper, fluidd and moonraker, it's also ffmpeg and mjpegstreamer. It's gonna be interesting since they also use a project that isn't just GPL, but APGL (in short "If your software gives service online, you have to publish the source code of it and any library that it borrows functions from.") - they use yolov5 (for AI).
- How does the background class work in object detection?
ROCm
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AMD May Get Across the CUDA Moat
Yep, did exactly that. IMO he threw a fit, even though AMD was working with him squashing bugs. https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
- ROCm 5.7.0 Release
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ROCm Is AMD's #1 Priority, Executive Says
Ok, I wonder what's wrong. maybe it's this? https://stackoverflow.com/questions/4959621/error-1001-in-cl...
Nope. Anything about this on the arch wiki? Nope
This bug report[2] from 2021? Maybe I need to update my groups.
[2]: https://github.com/RadeonOpenCompute/ROCm/issues/1411
$ ls -la /dev/kfd
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Simplifying GPU Application Development with HMM
HMM is, I believe, a Linux feature.
AMD added HMM support in ROCm 5.0 according to this: https://github.com/RadeonOpenCompute/ROCm/blob/develop/CHANG...
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AMD Ryzen APU turned into a 16GB VRAM GPU and it can run Stable Diffusion
Woot AMD now supports APU? I sold my notebook as i hit a wall when trying rocm [1] Is there a list oft Wirkung apu's ?
[1] https://github.com/RadeonOpenCompute/ROCm/issues/1587
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Nvidia's CUDA Monopoly
Last I heard he's abandoned working with AMD products.
https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
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Nvidia H100 GPUs: Supply and Demand
They're talking about the meltdown he had on stream [1] (in front of the mentioned pirate flag), that ended with him saying he'd stop using AMD hardware [2]. He recanted this two weeks after talking with AMD [3].
Maybe he'll succeed, but this definitely doesn't scream stability to me. I'd be wary of investing money into his ventures (but then I'm not a VC, so what do I know).
[1] https://www.youtube.com/watch?v=Mr0rWJhv9jU
[2] https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
[3] https://twitter.com/realGeorgeHotz/status/166980346408248934...
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Open or closed source Nvidia driver?
As for rocm support on consumer devices, AMD wont even clarify what devices are supported. https://github.com/RadeonOpenCompute/ROCm/pull/1738
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Why Nvidia Keeps Winning: The Rise of an AI Giant
He flamed out, then is back after Lisa Su called him (lmao)
https://geohot.github.io/blog/jekyll/update/2023/05/24/the-t...
https://www.youtube.com/watch?v=Mr0rWJhv9jU
https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
https://geohot.github.io/blog/jekyll/update/2023/06/07/a-div...
On a personal level that youtube doesn't make him come off looking that good... like people are trying to get patches to him and generally soothe him/damage control and he's just being a bit of a manchild. And it sounds like that's the general course of events around a lot of his "efforts".
On the other hand he's not wrong either, having this private build inside AMD and not even validating official, supported configurations for the officially supported non-private builds they show to the world isn't a good look, and that's just the very start of the problems around ROCm. AMD's OpenCL runtime was never stable or good either and every experience I've heard with it was "we spent so much time fighting AMD-specific runtime bugs and specs jank that what we ended up with was essentially vendor-proprietary anyway".
On the other other hand, it sounds like AMD know this is a mess and has some big stability/maturity improvements in the pipeline. It seems clear from some of the smoke coming out of the building that they're cooking on more general ROCm support for RDNA cards, and generally working to patch the maturity and stability issues he's talking about. I hate the "wait for drivers/new software release bro it's gonna fix everything" that surrounds AMD products but in this case I'm at least hopeful they seem to understand the problem, even if it's completely absurdly late.
Some of what he was viewing as "the process happening in secret" was likely people doing rush patches on the latest build to accommodate him, and he comes off as berating them over it. Again, like, that stream just comes off as "mercurial manchild" not coding genius. And everyone knew the driver situation is bad, that's why there's notionally alpha for him to realize here in the first place. He's bumping into moneymakers, and getting mad about it.
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Disable "SetTensor/CopyTensor" console logging.
I tried to train another model using InceptionResNetV2 and the same issues happens. Also, this happens even using the model.predict() method if using the GPU. Probably this is an issue related to the AMD Radeon RX 6700 XT or some mine misconfiguration. System Inormation: ArchLinux 6.1.32-1-lts - AMD Radeon RX 6700 XT - gfx1031 Opened issues: - https://github.com/RadeonOpenCompute/ROCm/issues/2250 - https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/issues/2125
What are some alternatives?
mmdetection - OpenMMLab Detection Toolbox and Benchmark
tensorflow-directml - Fork of TensorFlow accelerated by DirectML
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
rocm-arch - A collection of Arch Linux PKGBUILDS for the ROCm platform
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
oneAPI.jl - Julia support for the oneAPI programming toolkit.
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
SHARK - SHARK - High Performance Machine Learning Distribution
OpenCV - Open Source Computer Vision Library
llama.cpp - LLM inference in C/C++