Skip to main content

AnyLabeling

🌟 AnyLabeling 🌟

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

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

PyPI license open issues Pypi Downloads Documentation Follow

AnyLearning-Banner

ai-flow 62b3c222

AnyLabeling

Auto Labeling with Segment Anything

AnyLabeling-SegmentAnything

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

Install from Pypi

  • Requirements: Python 3.11+. 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

Star History Chart

References

Release files for anylabeling 0.4.37

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for anylabeling 0.4.37
File Size Uploaded
anylabeling-0.4.37.tar.gz 634.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for anylabeling 0.4.37
File Interpreter ABI Platform
anylabeling-0.4.37-py3-none-any.whl Python 3 none any Details

Total release size: 1.3 MB

Release files / anylabeling-0.4.37.tar.gz

Download URL anylabeling-0.4.37.tar.gz
Size 634.7 kB
Tags Source
SHA-256 checksum
How to use checksums
c1dc56d19e39fe4da0a0e1df4840aa3e1d2cf2659052ce49e6119a32336b4d72
BLAKE2b-256 checksum
How to use checksums
545ea524da867d41d87370d3871fe9796346120f9d2bb033f61a8bde50a12b09
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Aug 29, 2026.

Transparency log

Release files / anylabeling-0.4.37-py3-none-any.whl

Download URL anylabeling-0.4.37-py3-none-any.whl
Size 688.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
0c9da66e8f3ce198e777a5bd76107aadc6fa36db7ccc48d9d7be6935cd7644f3
BLAKE2b-256 checksum
How to use checksums
ad2fe86ad34604d37dea48d2fdef1337120200163e2f00a3a1d664861098b748
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Aug 29, 2026.

Transparency log

Release history Release notifications | RSS feed

0.4.43

2 release files

0.4.42

2 release files

0.4.40

2 release files

0.4.39

2 release files

0.4.38

2 release files

This release

0.4.37 This release

2 release files

0.4.36

2 release files

0.4.35

2 release files

0.4.34

2 release files

0.4.33

2 release files

0.4.32

2 release files

0.4.31

2 release files

0.4.16

2 release files

0.4.15

2 release files

0.4.14

2 release files

0.4.12

2 release files

0.4.11

2 release files

0.4.10

2 release files

0.4.8

2 release files

0.4.6

2 release files

0.4.5

2 release files

0.4.3

2 release files

0.4.2

2 release files

0.4.1

2 release files

0.4.0

2 release files

0.3.3

2 release files

0.3.2

2 release files

0.3.0

2 release files

0.2.24

2 release files

0.2.14

2 release files

0.2.13

2 release files

0.2.12

2 release files

0.2.11

2 release files

0.2.10

2 release files

0.2.9

2 release files

0.2.8

2 release files

0.2.7

2 release files

0.2.6

2 release files

0.2.4

2 release files

0.2.3

2 release files

0.2.2

2 release files

0.1.6

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

0.0.9

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page