Biblioteca educativa para procesamiento digital de imagenes y vision por computador clasica (filtros, ORB, Viola-Jones).
Project description
Vixel
Biblioteca Python educativa de procesamiento digital de imágenes y visión por computador clásica: filtros punto a punto / convolución, ORB con homografía, y Viola-Jones (Haar cascades).
Versión actual: ver pyproject.toml o python -c "import vixel; print(vixel.__version__)".
Instalación
pip install vixel
(Mientras desarrollas desde el repo:)
pip install -e .
Uso rápido desde Python
from vixel.filters import FILTERS, negative_image, sobel_edge
png_bytes = open("foto.png", "rb").read()
out = negative_image(png_bytes)
# out["image_bytes"], out["image_base64"], out["meta"]
out2 = FILTERS["box_blur"](png_bytes, {"size": 5})
ORB y Viola-Jones (el mismo contrato dict con PNG + meta):
from vixel.vision import run_orb, run_viola_jones, resolve_cascade_path
target = open("plantilla.jpg", "rb").read()
scene = open("escena.jpg", "rb").read()
r = run_orb(target, scene)
cascade_xml = resolve_cascade_path("face_default")
rj = run_viola_jones(scene, cascade_xml)
print(rj["meta"]["boxes"])
Especificaciones de parámetros:
from vixel.specs import FILTER_SPECS, VISION_SPECS
Estructura del paquete
| Ruta | Rol |
|---|---|
vixel/filters/ |
Filtros punto a punto y por convolución. |
vixel/vision/ |
ORB con homografía y Viola-Jones. |
vixel/io/ |
Codecs de entrada/salida de imagen. |
vixel/specs.py |
Catálogo estático de parámetros. |
tests/ |
Pruebas de humo. |
docs/ |
Documentación de la biblioteca. |
Dependencias runtime de la librería
NumPy, Pillow, OpenCV (opencv-python-headless).
Autores
- Samuel Leonel Pacheco
- Valentina Tabares Bonilla
Licencia
MIT — véase LICENSE.
Subir a PyPI
pip install build twine
python -m build
twine upload dist/*
Ajusta [project.urls] en pyproject.toml con la URL real de tu repositorio antes de publicar.
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