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tratamiento-de-imagenes

https://github.com/cabema1000/tratamiento-de-imagenes

Science Score: 44.0%

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Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: Cabema1000
  • License: mpl-2.0
  • Language: Python
  • Default Branch: main
  • Size: 1.28 MB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 9 months ago · Last pushed 9 months ago
Metadata Files
Readme License Citation

README.md

Image Processing with Convolution Kernels

A Python project demonstrating image processing using common convolution kernels for sharpening, edge detection, and blurring effects.

Features

  • Load and prepare images (grayscale conversion, resizing)
  • Apply multiple convolution kernels sequentially
  • Supported operations:
    • Sharpening (enhance image details)
    • Edge detection (highlight boundaries)
    • Blurring (smoothing effect)
  • Visualize each processing step
  • Matrix inspection for debugging

Example Code

Load and prepare original image

python img = Images("2.jpg", target_size=(500, 500), grayscale=True) img.show_img((500, 500)) # Resized image for better visualization, target size is not necessarily the same as the visualization size original_matrix = img.get_matrix(verbose=True)

Imagen original

Apply sharpen kernel

python kernel_sharpen = CommonKernels.sharpen() convoluted_sharp = Kernel(img_matrix=original_matrix, kernel_matrix=kernel_sharpen).get_result() Create and show sharpened image python img_sharp = img.create_from_matrix(convoluted_sharp) img_sharp.show_img((500, 500)) Imagen original

Apply second kernel (edge detection) over previous image

python kernel_edge = CommonKernels.edge_detection() convoluted_edge = Kernel(img_matrix=convoluted_sharp, kernel_matrix=kernel_edge).get_result()

Create and show edge-detected image

python img_edge = img.create_from_matrix(convoluted_edge) img_edge.show_img((500, 500))

Imagen original

Apply third kernel (Box blur) over previous image

python print("\n=== Aplicando Kernel Blur ===") kernel_blur = CommonKernels.blur(size=5) Create and show final blurred image

python img_final = img.create_from_matrix(convoluted_blur) img_final.show_img((500, 500)) Imagen original

Owner

  • Login: Cabema1000
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Beltrán Martínez
    given-names: Carlos
title: "Tratamiento de imagenes"
version: 1.0.0
url: https://github.com/Cabema1000/Tratamiento-de-imagenes
date-released: 2025-06-13
license: Mozilla Public License 2.0

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Dependencies

requirements.txt pypi
  • Pillow >=9.0.0
  • numpy >=1.22.0