Skip to main content

Effortless data labeling with AI support

Project description

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

AnyLabeling

I. Install and run

conda create -n anylabeling python=3.8
conda activate anylabeling
  • (For macOS only) Install PyQt5 using Conda:
conda install -c conda-forge pyqt==5.15.7
  • Install anylabeling:
pip install anylabeling
  • Run app:
anylabeling

Or

python -m anylabeling.app

II. Development

  • 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. References

  • Labeling UI built with ideas and components from LabelImg, labelme.
  • Icons: Flat Icons

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

anylabeling-0.2.7.tar.gz (661.3 kB view details)

Uploaded Source

Built Distribution

anylabeling-0.2.7-py3-none-any.whl (698.3 kB view details)

Uploaded Python 3

File details

Details for the file anylabeling-0.2.7.tar.gz.

File metadata

  • Download URL: anylabeling-0.2.7.tar.gz
  • Upload date:
  • Size: 661.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for anylabeling-0.2.7.tar.gz
Algorithm Hash digest
SHA256 1e0ad26ff391bda7f26b4bf43c2593a57dfa747c16c7663a6319e5a74ffe976b
MD5 f4f2927fe0ae5234a36a4b6ff089c871
BLAKE2b-256 d08932de9293fed2d963b9ae8af6670839d933387888d8629176762f5e497875

See more details on using hashes here.

File details

Details for the file anylabeling-0.2.7-py3-none-any.whl.

File metadata

  • Download URL: anylabeling-0.2.7-py3-none-any.whl
  • Upload date:
  • Size: 698.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.3

File hashes

Hashes for anylabeling-0.2.7-py3-none-any.whl
Algorithm Hash digest
SHA256 376aa5c7f855054c02f97f44f2c7529c4fb86701752171e27c70556498dafb49
MD5 034a541c18a652c8e2dfb805e88e01d8
BLAKE2b-256 4c9528d834128eb522172076a4c1f15d0ceedb0a54080a7568b2d53c3534034a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page