anylabeling 0.4.35

Effortless data labeling with AI support

🌟 AnyLabeling 🌟

Effortless data labeling with AI support from YOLO and Segment Anything!

AnyLabeling = LabelImg + Labelme + Improved UI + Auto-labeling

Auto Labeling with Segment Anything

• Youtube Demo: https://www.youtube.com/watch?v=5qVJiYNX5Kk
• Documentation: https://anylabeling.nrl.ai

Features:

• Image annotation for polygon, rectangle, circle, line and point.
• Auto-labeling with YOLOv8 (object detection).
• Auto-labeling with Segment Anything family:
  • SAM (ViT-B / ViT-L / ViT-H) and MobileSAM
  • SAM 2 and SAM 2.1 (Hiera-Tiny / Small / Base+ / Large)
  • SAM 3 (ViT-H) — open-vocabulary segmentation with text prompts
• Text detection, recognition and KIE (Key Information Extraction) labeling.
• Multiple languages availables: English, Vietnamese, Chinese.

Supported Models

Model	Prompt Types	Notes
SAM ViT-B / ViT-L / ViT-H	Point, Rectangle	Original Segment Anything
MobileSAM	Point, Rectangle	Lightweight SAM
SAM 2 Hiera-Tiny / Small / Base+ / Large	Point, Rectangle	Meta SAM 2
SAM 2.1 Hiera-Tiny / Small / Base+ / Large	Point, Rectangle	Improved SAM 2
SAM 3 ViT-H	Text, Point, Rectangle	Open-vocabulary; text drives detection
YOLOv8n / s / m / l / x	—	Object detection & auto-labeling

All models are downloaded automatically on first use from Hugging Face.

Install and Run

1. Download and run executable

• Download and run newest version from Releases.
• For MacOS:
  • Download the folder mode build (AnyLabeling-Folder.zip) from Releases
  • See macOS folder mode instructions for details

Install from Pypi

• Requirements: Python 3.10+. Recommended: Python 3.12.

• Recommended: Miniconda/Anaconda.

• Create environment:

conda create -n anylabeling python=3.12
conda activate anylabeling

• (For macOS only) Install PyQt6 using Conda:

conda install -c conda-forge pyqt=6

• Install anylabeling:

pip install anylabeling # or pip install anylabeling-gpu for GPU support

• Start labeling:

anylabeling

Documentation

Website: https://anylabeling.nrl.ai/

Applications

Object Detection	Recognition	Facial Landmark Detection	2D Pose Estimation
2D Lane Detection	OCR	Medical Imaging	Instance Segmentation
Image Tagging	Rotation	And more!
		Your applications here!

Development

• Install packages:

pip install -r requirements-dev.txt
# or pip install -r requirements-macos-dev.txt for MacOS

• Generate resources:

pyrcc5 -o anylabeling/resources/resources.py anylabeling/resources/resources.qrc

• Run app:

python anylabeling/app.py

Build executable

• Install PyInstaller:

pip install -r requirements-dev.txt

• Build:

bash build_executable.sh

• Check the outputs in: dist/.

Contribution

If you want to contribute to AnyLabeling, please read Contribution Guidelines.

Star history

References

• Labeling UI built with ideas and components from LabelImg, LabelMe.
• Auto-labeling with Segment Anything (SAM, SAM 2, SAM 2.1, SAM 3), MobileSAM.
• Auto-labeling with YOLOv8.
• Icons from FlatIcon: DinosoftLabs, Freepik, Vectoricons, HideMaru.