morphomath

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Description

This module enables efficient morphological erosion and dilatation. It uses the kernel subdivision algorithm implemented in C, with multithreading.

Features

Works for any tensor dimension, 2d for images, 3d for videos…
The morphological structuring element decomposition logarithmically reduces temporal complexity.
Functions can be parallelized to take advantage of all the CPU threads, in exchange of higher edge effects.
Functions can be compiled dynamically in C to reduce side-effects and overhead, in exchange for a longer loading time.

Examples

import morphomath, cv2
path = morphomath.utils.get_project_root() / "media" / "image.png"
img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
dilate = morphomath.Dilatation([[0, 1, 0], [0, 1, 0], [1, 1, 1]]).decomposed()
print(dilate)
cv2.imwrite("result.png", dilate(img))

Before

After

Development Status
- 4 - Beta
Intended Audience
- Developers
- Science/Research
Natural Language
- English
Operating System
- POSIX :: Linux
Programming Language
- C
- Python :: 3
Topic
- Multimedia :: Graphics :: 3D Modeling
- Scientific/Engineering :: Image Processing

Metadata

Development Status
- 4 - Beta
Intended Audience
- Developers
- Science/Research
Natural Language
- English
Operating System
- POSIX :: Linux
Programming Language
- C
- Python :: 3
Topic
- Multimedia :: Graphics :: 3D Modeling
- Scientific/Engineering :: Image Processing

Release files for morphomath 0.0.2

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

Source distribution (sdist)

Source distribution for morphomath 0.0.2
File	Size	Uploaded
morphomath-0.0.2.tar.gz	64.9 kB	Nov 10, 2025	Details

Release files / morphomath-0.0.2.tar.gz

Download URL	morphomath-0.0.2.tar.gz
Size	64.9 kB
Tags	Source
SHA-256 checksum How to use checksums	`92bd52c73fea375d044ea30149fdd024aa5ba5226afa55973a2e91e3a354030c`
BLAKE2b-256 checksum How to use checksums	`03a3e0895cb7671e0e2e90dc381828130f0fb5521adf4607494bb1540180acf3`
Upload date	Nov 10, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.14.0`