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Author - Md Istiak Tanvir (eruddro@gmail.com) Asma Akter (asmaul9377@gmail.com)

Overview -

image-sharpner is a lightweight and efficient image enhancement library designed to improve edge clarity, restore fine textures, and enhance visual details through an adaptive multi-frequency sharpening technique. The package supports both grayscale and color images and works seamlessly with popular computer vision pipelines.

Key Features -

  1. Adaptive multi-frequency sharpening to enhance details without amplifying noise
  2. Preserves natural textures and avoids halo artifacts
  3. Works with underwater, low-light, and blurred images
  4. Fast, NumPy-based implementation compatible with OpenCV
  5. Easy integration into machine learning, deep learning, and image-processing workflows

Why Use This Package? Traditional sharpening filters often overshoot edges, create ringing artifacts, or boost noise in smooth regions.

Installation -

pip install image-sharpner

Usage Example -

from image_prep import image_sharpner

#Insert Image path -

image_sharpner('abc.jpg')

Supported Image Types - jpg/png/jpeg/webmp

Compatibility - Python 3.7+ NumPy OpenCV

License - MIT License

Release files for image-sharpner 1.0.1

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

Source distribution (sdist)

Source distribution for image-sharpner 1.0.1
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Table of built distributions (wheels) for image-sharpner 1.0.1
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image_sharpner-1.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 10.0 kB

Release files / image_sharpner-1.0.1.tar.gz

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