In today’s digital world, we come across lots of digital images. In case, we are working with Python programming language, it provides lot of image processing libraries to add image processing capabilities to digital images.

Some of the most common image processing libraries are: OpenCV, Scikit-image, Pillow, Mahotas and more. However, in this tutorial, we are only focusing on Pillow library and will try to explore various capabilities of this module.

What is Pillow?

Pillow or the Python Imaging Library (PIL) fork by Jeffrey A.Clark and contributors, is a powerful Python library for working with digital images and Image processing. It”s built on top of the Python Image Library (PIL) and offers a wide range of functionalities for working with images. It provides extensive functionality for opening, manipulating and saving images in various formats. Pillow is a widely used tool in applications involving image processing, computer vision, web development, graphic design and more.

Pillow offers a wide range of tools and functions for image processing, allowing you to perform tasks such as −

• Opening and Loading Images − Pillow allows us to open and load images in various formats making them available for processing.
• Resizing and Scaling − We can resize images to specific dimensions, scale them up or down and generate thumbnails.
• Cropping − Image cropping involves removing unwanted portions of an image to focus on a specific region.
• Rotation and Flipping − Images can be rotated to correct orientation or for creative purposes. We can also flip images horizontally or vertically.
• Color Adjustment − Pillow provides functions to adjust image properties, including brightness, contrast and color balance.
• Filtering and Effects − Image filtering involves applying filters like blurring, sharpening, edge detection and various effects to enhance or modify the appearance of images.
• Text and Drawing − We can add text, shapes and drawings to images which is useful for annotation and labeling.
• Color Mode Conversion − Pillow supports converting images between different color modes such as RGB, grayscale and CMYK.
• Histogram Equalization − This is a technique for enhancing the contrast of an image by redistributing pixel values.
• Image Filtering − We can apply custom convolution filters to images allowing for advanced image processing operations.
• Geometric Transformations − Pillow supports geometric transformations like affine and perspective transformations which are used for tasks such as correcting image distortion.
• Merging and Compositing − We can merge multiple images or overlay images to create composite images or visual effects.
• Metadata Handling − Pillow allows us to access and modify image metadata such as EXIF and ICC profiles which can be useful for data extraction and management.
• Data Access and Analysis − We can access and manipulate pixel data at a low level enabling more advanced image processing and analysis tasks.

Why Pillow?

Pillow is a preferred choice for image processing in Python due to its −

• Image Processing Capabilities − Pillow provides a comprehensive set of tools for image manipulation such as opening, editing, enhancing and saving images. It supports various image formats for making it versatile for handling different types of image data.
• Ease of Use − Python as a high-level programming language is known for its readability and simplicity. Pillow inherits these characteristics and making it easy for developers to work with images even if they have minimal experience in image processing.
• Platform Independence − Python is platform-independent and so is Pillow. This means we can use Pillow to process images on different operating systems without worrying about compatibility issues.
• Abundance of Documentation − Python and Pillow have extensive documentation, tutorials and a supportive community which simplifies the learning curve for newcomers and provides a wealth of resources for experienced developers.
• Integration with Other Libraries − Python can seamlessly integrate Pillow with other popular libraries and frameworks such as NumPy and OpenCV for advanced image processing and computer vision tasks.
• Open Source − Both Python and Pillow are open-source which means they are free to use and continually improved by a large community of contributors.

Basic Example

Here is a basic example to get you started with Pillow.

Opening and Displaying an Image

This example demonstrates how to open and display an image in Python Pillow.

from PIL import Image

#Load an image
loaded_image = Image.open("Images/logo-w.png")

# Display the image
loaded_image.show()

Output

The above code will load an image from the specified path and display it using the default image viewer on your system.