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YoloLabel

github.com

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Spec score 7.2 #21 of 24 in AI Image Annotation Tools

What it is

YoloLabel is a free GUI for drawing object bounding boxes on images used to train YOLO neural networks. It loads JPG or PNG files from a directory and creates boxes with a two-click method. Labels can be moved, resized, copied, pasted, undone, and redone, then exported as YOLO TXT. The desktop app has downloads for Windows x64, Linux x64, and macOS on Apple Silicon, and its repository uses the MIT License. Local assisted labeling runs Ultralytics models exported to ONNX, including YOLOv5, YOLOv8, YOLO11, YOLO12, and YOLOv26, with single-image or dataset batch processing. YoloLabel AI adds cloud open-vocabulary detection through an API key and optional prompt; requests handle up to 20 images. Building from source uses Qt 6, while ONNX Runtime is optional unless local auto-labeling is required.

Spec sheet

Purpose
YoloLabel is a GUI for marking object bounding boxes in images to train YOLO neural networks.Read 30 Sep 2026 · github.com
Support
The cloud service lists [email protected] as its contact email for questions about its terms and privacy policy.Read 30 Sep 2026 · yololabel.com
License
The desktop repository is licensed under the MIT License, which permits use, modification, distribution, and sale subject to its stated conditions.Read 30 Sep 2026 · github.com
Maker
The maker’s GitHub profile identifies developer0hye as Yonghye Kwon.Read 30 Sep 2026 · github.com
Annotation
It supports manual bounding box labeling and uses a two left-click method to create boxes.Read 30 Sep 2026 · github.com
Batch labeling
With a loaded ONNX model, users can auto-label the current image or batch-process all images in the dataset.Read 30 Sep 2026 · github.com
Build requirement
Building from source with auto-label support requires ONNX Runtime; without it, the app works without that feature.Read 30 Sep 2026 · github.com
Cloud API
YoloLabel AI provides a REST API that accepts images and prompts and returns detections and YOLO-format labels.Read 30 Sep 2026 · yololabel.com
Cloud batch limit
Cloud Auto Label All submits images in batches of up to 20 per request.Read 30 Sep 2026 · github.com
Cloud data retention
The cloud service says it retains job metadata for 90 days and account and usage records while an account is active.Read 30 Sep 2026 · yololabel.com
Cloud image handling
The cloud service privacy policy says uploaded images are processed in memory, discarded after inference, and not used to train models.Read 30 Sep 2026 · yololabel.com
Cloud integration
YoloLabel integrates with yololabel.com for cloud open-vocabulary object detection, using an API key and optional detection prompt.Read 30 Sep 2026 · github.com
Cloud limits
The cloud service terms state that the free tier includes 100 images per month with no SLA, unused quota does not roll over, and over-limit requests return HTTP 402.Read 30 Sep 2026 · yololabel.com
Cloud security
The cloud privacy policy says it uses HTTPS, bcrypt password hashing, and short-lived JWTs with refresh token rotation.Read 30 Sep 2026 · yololabel.com
Download platforms
The README lists prebuilt downloads for Windows x64, Linux x64, and macOS on Apple Silicon.Read 30 Sep 2026 · github.com
Downloads
Prebuilt desktop downloads are listed for Windows x64, Linux x64, and macOS Apple Silicon.Read 30 Sep 2026 · github.com
Image formats
The README says to load .jpg or .png images from a directory.Read 30 Sep 2026 · github.com
Image tools
The app includes real-time contrast adjustment and a usage timer that runs while its window is focused.Read 30 Sep 2026 · github.com
Local auto-labeling
It can run local inference with Ultralytics detection models exported to ONNX, including YOLOv5, YOLOv8, YOLO11, YOLO12, and YOLOv26.Read 30 Sep 2026 · github.com
Manual annotation
It uses a two-click method to create boxes and includes tools to move, resize, copy, paste, undo, and redo annotations.Read 30 Sep 2026 · github.com
Source build
The project says it can be built from source with Qt 6; ONNX Runtime is optional for builds that need local auto-labeling.Read 30 Sep 2026 · github.com
Supported models
The README lists YOLOv5, YOLOv8, YOLO11, YOLO12, YOLOv26, and end-to-end ONNX models as supported for auto-labeling.Read 30 Sep 2026 · github.com
Usage caveat
The README warns that moving the horizontal image slider does not automatically save the last processed image.Read 30 Sep 2026 · github.com

Strong points and limits

Strong points

  • Free desktop application with MIT license
  • Supports Windows, Linux, and Apple Silicon macOS
  • Provides move, resize, copy, paste, undo, and redo
  • Runs several Ultralytics ONNX models locally
  • Exports annotations as YOLO TXT

Limits

  • Source builds require Qt 6
  • ONNX Runtime is needed for local auto-labeling
  • Cloud free tier allows 100 images monthly
  • Moving the image slider may not save the last image

Who it suits

It suits developers and dataset annotators preparing YOLO training labels on desktop systems. Teams can add local ONNX inference or the separate cloud detection API when assisted labeling is needed.

Verdict

YoloLabel offers manual bounding-box work plus optional local and cloud assistance across major desktop platforms. Review the build dependencies and cloud quota if your workflow depends on automated labeling.

Where Specifiction places it

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