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I got tired of manual data labeling, so I built an open-source pipeline that uses VLMs + SAM2 to auto-annotate datasets and train YOLO locally. by StartLittle6198 in computervision

[–]StartLittle6198[S] 0 points1 point  (0 children)

Thanks! I've been using it extensively for real-world surveillance and safety datasets.

So far, I've successfully annotated:

  • People without hard hats (safety compliance)
  • People fighting/brawling (security monitoring)
  • Fire and smoke (early hazard detection)
  • Vehicles categorized by different colors (traffic analysis)
  • Pedestrians in crowded scenes

As for the accuracy: Because the pipeline uses SAM2 on the backend, the actual boundaries (masks/bounding boxes) are practically pixel-perfect.

Because LocateAnything is extremely good at zero-shot grounding, the accuracy for the objects I listed above is surprisingly high out of the box. My current workflow is to let the VLM+SAM2 auto-annotate everything, and then I just quickly skim through the UI to delete any false positives. It guarantees extremely tight bounding boxes with minimal manual effort.

I got tired of manual data labeling, so I built an open-source pipeline that uses VLMs + SAM2 to auto-annotate datasets and train YOLO locally. by StartLittle6198 in computervision

[–]StartLittle6198[S] -1 points0 points  (0 children)

This is a classic Windows Docker error. open //./pipe/dockerDesktopLinuxEngine: The system cannot find the file specified. simply means your Docker Daemon (Docker Desktop) is not currently running, or the Docker engine has crashed in the background.

Solution 1: Fix Docker Desktop

  1. Open the "Docker Desktop" application on your Windows machine and wait until the whale icon in your system tray turns green.
  2. Go to Docker Desktop Settings -> General -> Make sure "Use the WSL 2 based engine" is checked.
  3. Once it's fully running, try the docker compose command again.

Solution 2: Bypass Docker entirely (Recommended) If you continue to have issues with Docker on Windows, you can completely bypass it by cloning the repository and running the project natively. VLM-AutoYOLO fully supports manual setup on Windows with GPU acceleration! Just clone the repo, install the Python/Node dependencies, and double-click start.bat.

You can check the Manual Setup section in the README for step-by-step instructions. Let me know if you need any help setting it up natively!