YoloLabel

At a glance

• Editor score
  6.9 / 10
• Pricing
  Free plan
• Best for
  Simple YOLO bounding-box labeling
• Free plan
  Yes
• Paid from
  Free
• AI-assisted labeling
  Yes
• Facts checked
  21 Sep 2026

• Where it wins

  • Free, open-source desktop app for Windows, macOS, and Linux
  • Local and batch ONNX auto-labeling for image datasets
  • Exports normalized YOLO bounding-box TXT files

• Where it doesn't

  • Supports bounding-box annotation rather than multiple annotation types
  • Workflow and integrations are narrower than broader labeling platforms
  • Cloud auto-labeling depends on the optional yololabel.com integration

Our verdict on YoloLabel

YoloLabel is a free, open-source desktop GUI for creating object-detection datasets for YOLO training. It is aimed at developers, researchers, and computer-vision teams that need a focused way to label image folders with bounding boxes. The application supports JPG, PNG, and BMP files, loads class names from TXT or NAMES files, and provides a two-click box-drawing workflow. Editing, deletion, undo, and redo support make it suitable for reviewing and refining annotations on a local machine.

Its strongest fit is a YOLO-centered workflow that values local control and direct output. The published feature set includes local ONNX object-detection auto-labeling, batch auto-labeling across image datasets, and YOLO-compatible normalized TXT exports. Those capabilities can reduce repetitive labeling work while keeping the core application self-hosted. YoloLabel also provides binaries for Windows, Linux, and Apple Silicon macOS, alongside source builds, giving teams several desktop deployment options. The optional yololabel.com integration adds a cloud route for AI-assisted detection when local inference is not the preferred approach.

The trade-off is focus. YoloLabel is built around bounding boxes and YOLO TXT output, so it is better suited to straightforward object-detection projects than teams needing a broader annotation system or a larger integration ecosystem. Its workflow centers on image folders, class lists, local editing, and batch labeling rather than a more expansive collaboration or review environment. Choose YoloLabel when free, open-source desktop labeling and YOLO output are the priority. Consider an alternative if your project requires annotation types beyond bounding boxes, deeper workflow features, or wider platform integrations.

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YoloLabel pricing

YoloLabel fact sheet

YoloLabel integrations

YoloLabel lists 1 integrations on its own site.

• yololabel.com

Alternatives to YoloLabel

• CVATA broad annotation workspace with flexible deployment, AI assistance, and team workflows.9.4
• RoboflowA broad computer vision workspace spanning annotation, training, evaluation, and deployment.9.2
• BasicAIA broad annotation platform with a free plan, model assistance, and private deployment.9.1

See all YoloLabel alternatives →

Featured on iTechGuides

YoloLabel is listed in our AI Image Annotation Tools directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update