picfixPy

A DSCI-524 collaborative software development project

Project Overview

Image enhancement is typically done with a full-scale editing software such as Adobe Photoshop or GIMP, but what if we just want to quickly touch up an image during prototyping in a programming environment?

picfixPy allows users to quickly enhance images in an integrated development environment (IDE) (e.g. Jupyter notebook, PyCharm) without powering up an image editing software. Users can quickly adjust the sharpness, contrast, and vibrance of .png images, by simply calling the corresponding functions. This package currently offers three essential image enhancement functions, and we hope to implement additional features in the near future.

To install

pip install git+https://github.com/UBC-MDS/picfixPy.git

To upgrade

pip install --upgrade git+https://github.com/UBC-MDS/picfixPy.git

To use

sharpen(): enhance the sharpness of your image

from picfixPy.sharpen import sharpen
sharpen('input.png', 4, False, 'sharpen_output.png')

Arguments:

• input_img: path to an input image
• intensity: level of sharpness enhancement, between 0 and 10, defaults to 5.
• display: print image to console if True, defaults to False.
• output_img: path to save the output image

contrast(): enhance the contrast of your image

from picfixPy.contrast import contrast
contrast('input.png', 4, False, 'contrast_output.png')

Arguments:

• input_img: path to an input image
• intensity: level of contrast enhancement, between 0 and 10, defaults to 5.
• display: print image to console if True, defaults to False.
• output_img: path to save the output image

vibrance(): enhance the colour vibrance of your image

from picfixPy.vibrance import vibrance
vibrance('input.png', 4, False, 'vibrance_output.png')

Arguments:

• input_img: path to an input image
• intensity: level of vibrance enhancement, between -10 and 10, defaults to 5.
• display: print image to console if True, defaults to False.
• output_img: path to save the output image

Supported image types

• .jpg
• .png
• .tiff

Dependencies

• numpy
• matplotlib
• scikit-image

Tests and test coverage

Fitting into the Python ecosystem

OpenCV provides Python with an immersive package for complex image processing. However, even for basic image enhancements, users typically still have to dig into a substantial amount of documentation and implementation details. This project offers a simple alternative, allowing users to have the ability to enhance images quickly during prototyping without the overhead of heavy library resources.

Team Members

Name	Github handle
Miliban Keyim	mkeyim
George J. J. Wu	GeorgeJJW
Mani Kohli	ksm45