(Adaptive) Histogram Equalization library for Python, written in Rust
Project description
ahe
A minimalist Python library for Adaptive Histogram Equalization, combining the expressiveness of a user-friendly Python interface with the raw power of a low-level implementation.
Development status
[!WARNING]
aheis pre-alpha software
ahe is developed in the open, but currently unstable.
- essential features are missing:
- boundary conditions
- contrast limitations
- documentation, examples and references are currently lacking
- binaries are not published
Installation
[!WARNING] pre-built binaries (wheels) are not published at this stage. A rust compiler toolchain is needed in order to install this package.
$ python -m pip install ahe
Usage
[!IMPORTANT] TODO
Migrating from scikit-image
Why
Put simply, if all your project needs from scikit-image is skimage.exposure.equalize_(adapt)hist, ahe provides a much more lightweight and portable replacement.
ahe has no runtime dependencies beyond numpy. Additionally, its binaries are orders of magnitude lighter than scikit-image's, as well as future-compatible with yet-unreleased versions of Python.
(*: numpy itself, as the common dependency to ahe and scikit-image is excluded from this graph)
[!IMPORTANT] TODO
- better performance
- improved guarantees on transformation invariants
How
[!IMPORTANT] TODO
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Source Distribution
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Provenance
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