https://github.com/neurophant/enimda

Entropy-based image border detection
https://github.com/neurophant/enimda

Last synced: 3 days ago
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Entropy-based image border detection

• Host: GitHub
• URL: https://github.com/neurophant/enimda
• Owner: neurophant
• License: mit
• Created: 2016-05-20T20:11:46.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-06-21T21:13:52.000Z (over 2 years ago)
• Last Synced: 2024-10-13T17:49:01.956Z (about 1 month ago)
• Language: Python
• Size: 92.8 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.txt

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README

        
ENIMDA

======

Entropy-based image border detection algorithm: finds out if your image has

borders or whitespaces around and helps you to trim border providing whitespace

offsets for every side of a picture, supports animated GIFs.

|pypi| |travisci|

.. |pypi| image:: https://badge.fury.io/py/enimda.svg

    :target: https://badge.fury.io/py/enimda

    :alt: pypi version

.. |travisci| image:: https://travis-ci.org/embali/enimda.svg?branch=master

    :target: https://travis-ci.org/embali/enimda

    :alt: travis ci build status

Algorithm (simplified)

----------------------

For each side of the image starting from top, rotating image counterclockwise

to keep side of interest on top:

* Get upper block 25% of image height

* Get lower block with the same height as the upper one

* Calculate entropy for both blocks and their difference

* Make upper block 1px less

* Repeat from p.2 until we hit image edge

* Border is between blocks with entropy difference maximum

.. image:: https://raw.githubusercontent.com/embali/enimda/master/algorithm.gif

    :alt: Sliding from center to edge - searching for maximum entropy difference

    :width: 300

    :height: 300

Requirements

------------

Python 3.5+

Setup

-----

.. code-block:: bash

    

    python-3.6 -m venv .env

    source .env/bin/activate

    pip install enimda

Usage

-----

Find if image has borders:

.. code-block:: python

    from enimda import ENIMDA

    # Load target image

    em = ENIMDA(fp='test.jpg')

    # Scan for borders with high precision

    borders = em.scan(fast=False)

    # Print found image borders (tuple): top, right, bottom, left

    print(borders)

Demo

----

For demo please refer to `ENIMDA Demo `_

Also it lives at `Picture Instruments `_ as 'Remove borders'

instrument

Tests

-----

Run tests: py.test