anylabeling-gpu 0.4.6

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

+⭐ Follow vietanhdev for project updates.

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 YOLOv8, Segment Anything (SAM, SAM2).
• Text detection, recognition and KIE (Key Information Extraction) labeling.
• Multiple languages availables: English, Vietnamese, Chinese.

I. Install and run

1. Download and run executable

• Download and run newest version from Releases.
• For MacOS:
  • After installing, go to Applications folder
  • Right click on the app and select Open
  • From the second time, you can open the app normally using Launchpad

2. 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 PyQt5 using Conda:

conda install -c conda-forge pyqt==5.15.9

• Install anylabeling:

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

• Start labeling:

anylabeling

II. 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

III. Build executable

• Install PyInstaller:

pip install -r requirements-dev.txt

• Build:

bash build_executable.sh

• Check the outputs in: dist/.

IV. Contribution

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

V. Star history

VI. References

• Labeling UI built with ideas and components from LabelImg, LabelMe.
• Auto-labeling with Segment Anything Models, MobileSAM.
• Auto-labeling with YOLOv8.