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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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