YOLO26 Object Detection

[tbc725]

I'm not sure if this project died, but here is a skeleton of YOLO26 for Windows CPU.

This is basically taking YOLOv8 and modifying it so it works with YOLO26 and CPU only. I did not test the GPU part.

Important

• The user will need to download the YOLO26 models manually from Ultralytics and put them into the "assets" folder.
• The user will need to copy the “bin” folder from the YOLOv8 modules and then update their Ultralytics module to the latest version.
• CPU only. GPU not tested.
• Windows only. Did not try on other platforms.

skeleton-ObjectDetectionYOLO26.zip

[simshaun]

Thanks. If you're a noob like me:

To download the YOLO26 models:

Go to https://huggingface.co/Ultralytics/YOLO26/tree/main
Look for the variants you want. I downloaded the yolo26n.pt, yolo26s.pt, and yolo26m.pt files to try out.

To update the Ultralytics model to the latest version:

Navigate down into your modules folder to somewhere like this:
C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLO26\bin\windows\python39\venv\Scripts

Open your terminal in that folder, then run .\python.exe -m pip install -U ultralytics

---

I'm testing this out on a Beelink EQ13 with an Intel N200 processor.

YOLO26s, ~500ms to detect.
YOLO26m, ~950ms to detect.
YOLO26l, ~1200ms to detect

Not bad.

[MarkDRenard]

A complete community-developed Object Detection YOLO26 module for CodeProject.AI v2.9.5 specifically optimized for Windows x64 environments with NVIDIA RTX GPUs is available for download. The integration allows security pipelines (such as Blue Iris systems) to leverage the performance advancements of Ultralytics YOLO26, including, NMS-free direct inference, optimized CPU performance and improved small-object recognition.

Key Specifications & Architecture: Built for Python 3.12, CUDA 12.4 and cuDNN 9 running natively within the module's isolated container, there is no need to modify or reconfigure existing CUDA or cuDNN global installations within the Windows environment. A fully self-contained module that handles automated downloading for Detection, Segmentation and Custom models hosted on the MarkDRenard CodeProject.AI Modules GitHub Repository: https://github.com/MarkDRenard/CodeProject.AI-Modules

As a self-contained YOLO26 Detection module, adding it to your setup will trigger automated post-installation integrity checks to verify that models are correctly loaded into your CodeProject.AI instance. Integrating YOLO26 into your CodeProject.AL ecosystem, paired with software like Blue Iris, provides distinct advantages over older YOLO models.

For added security and to allow mobile app access without opening public WAN ports on your router, using a private mesh like a Tailscale Network is good option too.

If interested, check it out! Thanks, -mark

[tbc725]

Thanks a lot for your hard work!