Factual package intelligence from PyPI

rescale4dl 0.2.3 package intelligence

A systematic approach for determining optimal image resolution in deep learning-based microscopy segmentation, balancing accuracy with acquisition/storage costs.

pip install rescale4dl

Current version
0.2.3
Python requirement
<3.13,>=3.10
License
MIT
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
106.2 KiB
Release history
3 releases with files
Median release cadence
231 days

rescale4dl dependencies

PyPI declares 26 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. imageio >=2.33.1
  2. jupyter >=1.1.1
  3. matplotlib >=3.9.2
  4. pandas >=2.2.3
  5. pillow >=11.0.0
  6. pypdf >=4.2.0
  7. scikit-image >=0.22.0
  8. scikit-learn >=1.5.2
  9. scipy >=1.14.1
  10. seaborn >=0.13.2
  11. setuptools >=68.2.2
  12. tifffile >=2024.12.12

The compact report shows 12 of 26 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

rescale4dl publishes 1 wheel and 1 source archive for version 0.2.3. Wheel platform tags: any.

Declared Python classifiers: 3.10.

Security snapshot for rescale4dl 0.2.3

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.

Metadata completeness

PyPI does not currently declare: project URL. PyDeps marks these fields as unknown instead of guessing values.

Release activity and sources

PyPI lists 3 releases with files. The first dated release is ; 2 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .

The project does not publish external project URLs in its PyPI metadata.