Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

opencv.org

Post reply on HN
Print view View original

41–50 of 160 posts

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#41

Post by pzo »

nnevatie wrote: post #17
ftchd wrote: post #10

> 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!

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.

how are supposed to use TensorRT on iOS, iPadOS, Android or even Web? Production is not only cloud.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#42

Post by _the_inflator »

sebmellen wrote: post #18
leoncos wrote: post #2

When I use Codex/Claude to complete a computer vision task, such as extracting assets from an image, OpenCV is their default solution. However, I believe that using YOLO and other methods is outdated. The best solution now is to directly use Nano Banana or other AI image models. A paper has proven that image generation models can perform most CV tasks well. I believe the new OpenCV should become a wrapper for VLM or…

Great, let me know when those models can run on-server and process/analyze streams of ID images with less than 100ms of latency. You’ll need to make sure you have a massive set of training data including all manner of slightly blurred and slightly distorted ID cards

Exactly, and all on an embedded system with quite restrictive settings and no overclocked Intel lastest generation combined with NVIDIA's 10k graphic cards.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#43

Post by pzo »

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.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#44

Post by charcircuit »

wongarsu wrote: post #16
leoncos wrote: post #2

When I use Codex/Claude to complete a computer vision task, such as extracting assets from an image, OpenCV is their default solution. However, I believe that using YOLO and other methods is outdated. The best solution now is to directly use Nano Banana or other AI image models. A paper has proven that image generation models can perform most CV tasks well. I believe the new OpenCV should become a wrapper for VLM or…

I can get great results from a YOLO model with 30M to maybe 300M params. To get decent CV from a LLM 8B params is the absolute minimum, closer to 30B for interesting tasks I might be on board about LLMs being the future of OCR (though many would disagree), but for general CV they are very inefficient for very limited benefit

>for very limited benefit

Due to how simple they are to work with they will become popular. Compare NLP before and after GPT-3. GPT-3 majorly brought down the complexity and skill needed for doing NLP tasks even if traditional NLP is much much faster. Ultimately ease of development will win out and the industry will work towards optimizing running such LLMs to make it cheap enough to run.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#45

Post by _the_inflator »

leoncos wrote: post #2

When I use Codex/Claude to complete a computer vision task, such as extracting assets from an image, OpenCV is their default solution. However, I believe that using YOLO and other methods is outdated. The best solution now is to directly use Nano Banana or other AI image models. A paper has proven that image generation models can perform most CV tasks well. I believe the new OpenCV should become a wrapper for VLM or…

"When I use..."

Dude, in business we think in terms of large numbers, internationally easily in billion times processing images. This wouldn't cut it.

Also, do you buy the mega expensive super individually designed shoes from the best shoemaker there is to march along though some dirt or simply stick to gumboots?

OpenCV is used behind the scenes for many of the fancy stuff those major AI provider pretend to do. Claude is a huge system and not a LLM anymore.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#46

Post by charcircuit »

_the_inflator wrote: post #42
sebmellen wrote: post #18

Earlier quoted context omitted.

Great, let me know when those models can run on-server and process/analyze streams of ID images with less than 100ms of latency. You’ll need to make sure you have a massive set of training data including all manner of slightly blurred and slightly distorted ID cards

Exactly, and all on an embedded system with quite restrictive settings and no overclocked Intel lastest generation combined with NVIDIA's 10k graphic cards.

Embedded systems can make network calls to powerful, GPU equipped servers.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#47

Post by trklausss »

VadimPR wrote: post #24
wongarsu wrote: post #13

Earlier quoted context omitted.

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 worl…

The release post is AI-written with little human oversight and it shows.

This is what I hate about AI. Not that people use it, it's great to accelerate specific workflows, make less mistakes etc. It's just blindly trusting it and just saying "Make a post about a CV library release, make no mistakes" and calling it a day.

Where is the human creativity in writing release notes gone?

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#48

Post by VulgarExigency »

claytongulick wrote: post #39
VadimPR wrote: post #24

Earlier quoted context omitted.

The release post is AI-written with little human oversight and it shows.

I had to stop reading after: "This is not just another incremental release. OpenCV 5 is a major step forward." If a human can't be bothered to write a piece, I can't be bothered to read it.

The endless deluge of AI prose really wears on the soul once you start noticing it.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#49

Post by Hendrikto »

regularfry wrote: post #9
leoncos wrote: post #2

When I use Codex/Claude to complete a computer vision task, such as extracting assets from an image, OpenCV is their default solution. However, I believe that using YOLO and other methods is outdated. The best solution now is to directly use Nano Banana or other AI image models. A paper has proven that image generation models can perform most CV tasks well. I believe the new OpenCV should become a wrapper for VLM or…

I've built hardware with a pi zero 2 + pi cam running a mildly fine-tuned YOLO doing local-only object detection as a USB-OTG device, in a use case where any off-device API calls would have been totally unacceptable, and where the object detection was part of the human interaction loop with a hard ceiling of 300ms on the total interaction time of which the object detection was only one process among many. We're not g…

> API calls just aren't on the menu

Even if they were an option, your 300ms latency requirement would exclude them anyway.

Re: OpenCV 5 Is Here: The Biggest Leap in Years for Computer Vision

#50

Post by antonvs »

nnevatie wrote: post #17
ftchd wrote: post #10

> 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!

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.

We use this in production:

https://docs.rs/onnxruntime/latest/onnxruntime/

It’s a Rust wrapper around ONNX Runtime. We currently serve 5+ million inference requests per day for a highly performance-sensitive application, for a long list of major enterprise clients. We don’t use GPUs for inference, because it would be cost-prohibitive. We launch tens of thousands of VMs per day to run these workloads.

Post reply on HN