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- Hacker News
- > LLMs and VLMs, Running Inside OpenCV…Qwen 2.5, Gemma 3, PaliGemma, and the GPT-2 / GPT-4 family
Why these specific models / versions?
by hbcondo714 - Yes, it's weird that they're so old.by mkl
- Great to hear.
OpenCV was so easy and smooth to set up for doing tasks like generating thumbnails from uploads from arbitrary photo uploads regardless of format (including funky new formats like webp, avif, or heic).
by trollbridge - Image augmentations library Albumentations is heavily based on OpenCV, which allows it to beat torchvision, Kornia, PIL, and other similar libraries.
But there is still a huge room for improvement in terms of performance, as for some low level operations StringZilla or Numkong are faster, for some, especially for float32 images, numpy is the best.
The most annoying component is that OpenCV is limited to input shapes like (H, W, C), which limits its application to videos and volumes with shapes (X, H, W, C)
by ternaus - A few years ago I was using OpenCV is a commercial Android SDK (it might still be being used; also because iOS provided almost all of those "needs" ready-made and Android just didn't, neither did Firebase, or Jetpack suites/tools). I was the one who had added it in the SDK. There was a lot I/we could do but as an Android developer (barely any exposure to CV or even C/C++) what I felt we lacked was documentation, a community. We struggled with even shaving off parts that we did not want to ship with our SDK. Speed was such an issue. The problem was someone who just wanted to use the lib (on mobile) a lot of things felt esoteric and out of reach i.e difficult. It didn't have to be.Sadly LLM wasn't at full speed back then, barely useable, not even talked about. Something like this would have been a perfect use case of AI/LLM. A coder, not from the exact/specific field the tool was made in/from, but being able to take full advantage of its capabilities in a nuanced/selective manner.by shelled
- does this mean im actually able to try object detection in opencv now? i mean i know basic image processing techniques, and i know "in theory" how ML works but ive never really seen a case where i can just say "heres an image now detect all the apples". theres always 1. find a model that has the knowledge, 2. hook it up to an inference engine, 3. do something useful. i always get stuck at 1.by globalnode
- moondream is a beastby shenberg
- Roboflow is your friend.by Npovview
- That seems to be the way things are going.
Large general models have taken over in NLP, and (outside of embedded/low latency applications) it seems like they are coming for CV next.
So you should soon be able to have large generic model that can detect whatever for you.
It's already pretty much possible with open-vocabulary detectors like SAM3, where you could just prompt it with "Apple": https://ai.meta.com/research/sam3/
by fnands - YOLO has basically solved that for my use cases for a couple years now. If you want labels that are not in the pretrained labels it's also easy to fine-tune, provided you're willing to label 200 or so images
If you need something less restricted to existing labels (say wanting all the red apples, or all cardboard signs) SAM3 is great, as the sibling comment says
by wongarsu - OpenCV being in the list of Pyodide modules [0] was the biggest boon for my online teaching experience because remotely dealing with install woes (corporate proxies & cie) was a show stopper for regular Python. I'm hoping that they will package this new version and that it will bring the new neural networks engines goodies to the no-install crowd !
[0] https://pyodide.org/en/latest/usage/packages-in-pyodide.html
by wolfgangK - How can I learn the practical side of computer vision in 2026?
I'm not interested in understanding papers or the math behind it, but rather in how to put a system into production, whether it's object detection, running 20 cameras in parallel on a single computer, like sizing hardware for a specific task, and so on.
Any tips?
- One of the great things about OpenCV is how ubiquitous it is, there's a ton samples online and well represented in frontier model training data. I recently vibe-coded an object detector for my own personal photo library so I could separate out my pictures with humans in them. Very approachable with Codex + feeding it a sample from Github.by eastof
- Try a coding agent for writing and tuning the OpenCV part, and have it explain its choices. That's probably the most practical path to shipping a working system.
Speaking from experience: never used OpenCV before, recently vibe coded a tool that makes supercuts of pool videos, trimming each clip from the cue ball's first strike to when the motion stops.
by yayitswei - By doing it. Decide on a small project, like tracking your cat, detecting food items in your fridge, then take it step by step.
Then do a slightly more ambitious project. Start with something very simple.
It also heavily depends on what you already know regarding programming, image processing etc.
by bonoboTP - They really improved the performance. I tested yolov8 medium segmentation model on intel i7 11th gen cpu.
Opencv 4.11 : ~255ms Opencv 5.0.0 : ~185ms
with the same code.
by arcanine - Intel never really improved their memory controller and busses and it shows.by bobmcnamara
- AI written release post and it shows...by GreenSalem
- Indeed. Well written, clear, informative and to the point.by jampekka
- Written by AI for AI?
- Yeah, blatant "it's not x, it's y":
> This is not just another incremental release. OpenCV 5 is a major step forward.
by xdennis - The diagrams definitely look like LLM output as wellby _qua
- I think Technical posts should be written with 3 levels of audiences in mind. Expert, Middle, Beginner. But I guess that is not necessary, since AIs can cut the flab easily.by Npovview
- I can't say for sure, but there is a suspicious amount of "it's not x, it's y". At least there are no em-dashes.by oceansky
- Quite a good release although not sure why they invest so much time into their ONNX engine. I don't think they have enough stuff and big pockets to compete with ONNXRuntime, CoreAI, ExecuTorch, LiteRT.
I'm happy they added option for ONNXRuntime. I wish their cv.dnn was mostly that unified wrapper around many different backends (ONNXRuntime, Executorch, LiteRT, CoreAI) and maybe just some tooling around it (performance metrics tools, model downloads etc). Transformers(.js) approach looks better for me.
Wish they also invested more time into better production ready Camera I/O (for mobiles, device/format discovery, manual settings, depthmap support, etc) and better Highgui that could use different backends (skia, webgpu) and on mobiles.
by pzo - > One practical detail is worth knowing. The new engine is CPU-only at the moment, so if you select a non-CPU backend and target (for example CUDA or OpenVINO through setPreferableBackend and setPreferableTarget), you will want the classic engine.
So there's room for even better performance!
by ftchd - No one uses ONNXRuntime (nor the new engine in OpenCV 5) in production. For anything performance-sensitive, one would run models under TensorRT, as an example.by nnevatie
- It's certainly a choice to make your headline feature a new ONNX engine, feature a bunch of comparisons how it's better than ONNXRuntime, while casually mentioning on the side that the cool new much faster engine is CPU-only
Sure, running models on the CPU is very much a thing in computer vision (the benchmarked YOLOv8n has 37M params). But this whole announcement feels more like OpenCV catching up to the modern world, not "The Biggest Leap in Years for Computer Vision"
Still great, needing fewer libraries is a good thing, but maybe a bit oversold
by wongarsu - The thing I love about OpenCV is that it remains hands down the best library for simply loading images and video. I've never even used any of its fancy computer vision features, but if I need to load a video file and look at the pixels - which I did need to do recently for an art project - OpenCV does it in about four lines of code.by plasticeagle
- What are you looking for in the pixels?by deadbabe