Metadata-Version: 2.1
Name: phycv
Version: 1.1.1
Summary: physics-inspired computer vision algorithms
Author: Jalali-Lab
Author-email: ucla.photonics.lab@gmail.com
License: UNKNOWN
Keywords: python,image processing,computational imaging,computer vision,physics-inspired algorithm
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
License-File: LICENSE
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# PhyCV - The First Physics-inspired Computer Vision Library

Welcome to PhyCV ! The First Physics-inspired Computer Vision Python library developed by Jalali-Lab @ UCLA.


### *Release Notes*
- **Version 1.1.1**

  Fix minor bugs in `page_create_edge`.

- **Version 1.1.0**

  The `load_img` method now supports loading images from both an image files and image arrays.

- **Version 1.0.0**
  
  The first release of PhyCV is available!


## Introduction
PhyCV is a Physics-inspired Computer Vision Python library. PhyCV has a new class of computer vision algorithms that emulates the propagation of light through a physical medium with natural and engineered diffractive properties followed by coherent detection. Unlike traditional algorithms that are a sequence of hand-crafted empirical rules, physics-inspired algorithms leverage physical laws of nature as blueprints. These algorithms can, in principle, be implemented in real physical devices for fast and efficient computation.  Currently, PhyCV includes Phase-Stretch Transform (PST) and Phase-Stretch Adaptive Gradient-field Extractor (PAGE). Each algorthm has CPU and GPU versions. For full documentation, please refer to the [GitHub Page](https://github.com/JalaliLabUCLA/phycv).

