Metadata-Version: 1.1
Name: NoteShrinker
Version: 0.2.0
Summary: Smart shrinking of the size and color palette of images
Home-page: https://github.com/ghandic/NoteShrinker
Author: Andrew Challis
Author-email: andrewchallis@hotmail.com
License: MIT
Description: NoteShrinker
        ==========
        
        ![GitHub stars](https://img.shields.io/github/stars/ghandic/NoteShrinker.svg?style=social&label=Stars)
        ![Docker build](https://img.shields.io/docker/automated/challisa/noteshrinker.svg)
        ![Travis build](https://travis-ci.org/ghandic/NoteShrinker.svg?branch=master)
        ![Package version](https://img.shields.io/pypi/v/NoteShrinker.svg)
        ![License](https://img.shields.io/github/license/ghandic/NoteShrinker.svg)
        
        This Repo packages up the work from [Mark Zucker](https://github.com/mzucker/noteshrink) into a python module and cli script
        
        Convert scans of handwritten notes to beautiful, compact *PDFs* [see full writeup](https://mzucker.github.io/2016/09/20/noteshrink.html)
        
        Note this package does not convert to PDF as the original module relies on ImageMagick, this is very easy to implement yourself.
        
        
        Examples
        ------------
        These examples use the default settings in the Python module.
        
        Original            |  NoteShrunk
        :-------------------------:|:-------------------------:
        **Size: 1.4MB**![Original example 1](Examples/Input/us_tax_form_1937.jpg?raw=true "Original US Tax return form from 1937")  |  **Size: 516KB**![NoteShunk example 1](Examples/Output/us_tax_form_1937.png?raw=true "NoteShrunk US Tax return form from 1937")
        **Size: 73KB**![Original example 2](Examples/Input/winston_churchhill_letter.jpg?raw=true "Original letter from Winston Churchhill")  |  **Size: 51KB**![NoteShunk example 2](Examples/Output/winston_churchhill_letter.png?raw=true "NoteShrunk letter from Winston Churchhill")
        **Size: 132KB**![Original example 3](Examples/Input/Restraint_of_domestic_animals.jpg?raw=true "Original page from 'Restraint of domestic animals'")| **Size: 109KB**![NoteShunk example 3](Examples/Output/Restraint_of_domestic_animals.png?raw=true "NoteShrunk page from 'Restraint of domestic animals'")
        
        
        Requirements
        ------------
        
        -  Python 2 or 3
        -  NumPy 1.10 or later
        -  SciPy
        -  Image module from PIL or Pillow
        
        
        Installation
        -----
        
        **Ensure you have Numpy, SciPy and PIL installed:**
        
        ```python
        pip install numpy scipy pillow
        ```
        
        ```python
        pip install NoteShrinker
        ```
        
        Usage
        -----
        
        **Docker**
        ```bash
        docker run -v $PWD/Examples/Input:/imgs challisa/noteshrinker /imgs/us_tax_form_1937.jpg -w
        ```
        
        **Command line**
        ```bash
            note-shrinker IMAGE1 [IMAGE2 ...]
        ```
        
        **Integrating into your Python scripts**
        
        ```python
        from NoteShrinker import NoteShrinker
        
        # Create a NoteShrink object full of images, either an array of filepaths, PIL images or numpy arrays
        ns = NoteShrinker(['test.png'], **args)
        
        # Shrink the images by calling the shrink method, this returns an array of PIL images encoded as RGB
        shrunk = ns.shrink()
        
        # Carry on with your image processing...
        for img in shrunk:
           img.save('example.png')
        ```
        
Keywords: noteshrink
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Multimedia :: Graphics
