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An image handling, processing, & editing library for Python.

Project description


An image processing, editing & handling library in Python.

Version History

0.0.1 - InDev
0.0.2 - Brightness module added, main classes, internal + misc functions
0.0.3 - Color overlay module added
0.1.0 - HSL Module Added
0.1.1 - Convolutional Framework + Blur functions added
0.1.2 - Create kernel based on blur type
0.1.3 - Added pixelation
0.1.4 - Added edge detection
0.2.0 - Graphics module added
0.2.1 - Resize feature added
0.2.2 - File naming & formatting features added
0.3.0 - Composition module added
1.0.0 - Initial Release
1.0.1 - Bug Fixes 1.0.2 - Test Framework
1.0.3 - Depth support added for ImageVolume (CURRENT)


pyifx contains 4 main modules, giving users access to functions such as:

  • HSL Modification
  • Convolution-based functions
  • Image format conversion & resizing
  • And much more.

pyifx also allows for images to be read in from directories instead of individually importing them, allowing for image modification processes to be automated.

A full list of features is available in the user guide & documentation.

Code Example

The code block below perfectly details the use of the library.
import pyifx

# Creating the image
image = pyifx.misc.PyifxImage(input_path="path/to/img.png", output_path="path/to/new_img.png")

# Creating the volume
volume = pyifx.misc.ImageVolume(input_path="lots/of/images/", output_path="lots/of/images/modified/", prefix="_")

#Creating the list
image_2 = pyifx.misc.PyifxImage(input_path="different/path/to/img.png", output_path="different/path/to/new_img.png")
image_list = [image, image_2]

brightened_image = pyifx.hsl.brighten(image, 50)
brightened_list = pyifx.hsl.brighten(image_list, 50)

For more information about using the library, read the image classes and usage pages of the user guide, which go into more detail about using the library.


To install the library, use the command below:

	pip install pyifx

This will install the library and its dependencies (if needed).


The documentation of this project can be found here.


TBA - The testing portion of the contribution section is currently being written.


To learn more about using the library, read the image classes and usage pages of the user guide, which go into more detail about using it.


To learn how to contribute to the project, read the contribution guide.

Note: The contribution guide for testers is still being added.


MIT © 2019 Jad Khalili.

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