Factual package intelligence from PyPI

Mpox-Trinet 0.9.0 package intelligence

Tri-Net v2 — reproducible deep-learning framework for Mpox skin-lesion diagnosis

pip install mpox-trinet

Current version
0.9.0
Python requirement
>=3.10
License
MIT License
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
111.1 KiB
Release history
1 releases with files
Median release cadence
Not enough dated releases

Mpox-Trinet dependencies

PyPI declares 20 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. tensorflow ==2.16.2
  2. numpy ==1.26.4
  3. pandas ==2.2.2
  4. scikit-learn ==1.5.1
  5. scipy ==1.13.1
  6. pyswarms ==1.3.0
  7. xgboost ==2.1.1
  8. pillow ==10.4.0
  9. opencv-python ==4.10.0.84
  10. matplotlib ==3.9.2
  11. seaborn ==0.13.2
  12. joblib ==1.4.2
  13. tqdm ==4.66.5
  14. kaggle ==2.2.3
  15. typer >=0.12
  16. pyyaml >=6.0

The compact report shows 18 of 20 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

Mpox-Trinet publishes 1 wheel and 1 source archive for version 0.9.0. Wheel platform tags: any.

No version-specific Python classifiers are declared.

Security snapshot for Mpox-Trinet 0.9.0

An OSV query completed on and found 0 known vulnerabilities affecting this version. 0 advisories are classified as critical. 0 advisories appear in the CISA Known Exploited Vulnerabilities catalog.

Release activity and sources

PyPI lists 1 release with files. The first dated release is ; 1 release falls within the 365 days preceding the latest dated release. The current release files were uploaded on .