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  • 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.
  • 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

  • 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?

  • 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.

  • AI written release post and it shows...
  • 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!

  • 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.

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