Metadata-Version: 2.1
Name: instakit
Version: 0.9.0
Summary: Image processors for django-imagekit - based on Pillow, SciPy, and scikit-image
Home-page: https://github.com/fish2000/instakit
Download-URL: https://github.com/fish2000/instakit/zipball/master
Author: Alexander Böhn
Author-email: fish2000@gmail.com
License: MIT
Keywords: django imagekit instakit fish2000 image processing image analysis image comparison halftone dithering Photoshop acv curves PIL Pillow Cython NumPy SciPy scikit-image
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: OS Independent
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Description-Content-Type: text/markdown
License-File: LICENSE.txt

Instakit: Filters and Tools; BYO Facebook Buyout
=====================================

Image processors and filters - inspired by Instagram, built on top of the
PIL/Pillow, SciPy and scikit-image packages, accelerated with Cython, and
ready to use with PILKit and the django-imagekit framework.

Included are filters for Atkinson and Floyd-Steinberg dithering, dot-pitch
halftoning (with GCR and per-channel pipeline processors), classes exposing
image-processing pipeline data as NumPy ND-arrays, Gaussian kernel functions,
processors for applying channel-based LUT curves to images from Photoshop
.acv files, imagekit-ready processors furnishing streamlined access to a wide
schmorgasbord of Pillow's many image adjustment algorithms (e.g. noise, blur,
and sharpen functions, histogram-based operations like Brightness/Contrast,
among others), an implementation of the entropy-based smart-crop algorithm
many will recognize from the easy-thumbnails Django app - and much more.

