Image Compression Toolkit - Python

Two ways to compress your images!

Contributors

Project Summary

This Python package specializes in reducing the size of images. It contains three main functions :crop(), compress() and image_size(). The crop() function reduces the size of an image by reducing the height and width of the image to the size specified by the user. The compress() function reduces the file size of an image by reducing the number of bits used in each colour channel of the image. The image_size function calculates the size of the image in bytes. The size returned can then used to check if the compress() function did its job correctly. The package could be used by people to reduce the size of images (dimensions or file size), which could then be uploaded to social media platforms or other websites and applications that have limits on image size.

Functions

crop(img_path, H, W, out_path)
- Description: This function reduces the image to the specified size by removing rows and columns of pixels from the borders.
- Inputs:

Parameter	Type	Description
`img_path`	`string`	File path to a `png` image
`H`	`int`	Desired height of the cropped image
`W`	`int`	Desired width of the cropped image
`out_path`	`string`	File path to where to save the cropped `png` image

Output:
- string, file path to cropped image (png image with size H x W)
compress(image, b, out_path)
- Description: This function compresses the image by reducing the number of bits for each channel based on user input.
- Inputs:

Parameter	Type	Description
`img_path`	`string`	File path to a `png` image
`b`	`int`	An integer between 1 and 8; number of bits used for each channel in the compressed image
`out_path`	`string`	File path to where to save the compressed `png` image

Output:
- string, file path to the compressed png image
image_size(image)
- Description: Calculates and returns the size of an image in bytes.
- Input:
  - string, file path to a png image
- Output:
  - int, size of the image in bytes

Installation

To install this package, use the following command:

pip install git+https://github.com/UBC-MDS/image-compression-toolkit-python.git

Usage

Task	In a Script (after, `import imageCompress`)
Crop `image.png` to size 10 X 15	`imageCompress.crop("../image.png", H = 10, W = 15, "..//cropped_image.png")`
Compress an `image.png` to 5 bits per channel	`imageCompress.compress("..//image.png", b = 5, "..//compressed_image.png")`
Get the size of `image.png`	`imageCompress.image_size("..//image.png")`

Examples

The following examples use the bigger_test.png image from the data folder, displayed below.

To get the size of the image:

import imageCompress
imageCompress.image_size("../data/bigger_test.png")

This returns the size of the image in bytes.

To crop the image:

imageCompress.crop("../data/bigger_test.png", 175, 200, "../data/cropped_img.png")

This returns the absolute file path to the cropped image, as specified in the out_path argument of the function. The cropped image is shown below.

..data/cropped_img.png

To compress the image:

imageCompress.compress("..data/bigger_test.png", 2, "../data/compressed_img.png")

This returns the absolute file path to the compressed image. The compressed image is shown below.

..data/compressed_img.png

Test Results

Branch Coverage

Related Packages

There already are packages for image processing in R and Python:

The existing packages are comprehensive and provide many functions such as transformations, filters, file conversions and other advanced functions. Our package focuses specifically on image compression and reducing image size using K-means clustering. This package is not a wrapper or an improvement of an existing package. It simply uses an unsupervised learning algorithm (K-means clustering) to reduce the number of bits used to represent an image.

adityashrm21 / image-compression-toolkit-python