Image Processing With the Python Pillow Library

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January 08, 2025
Image Processing With the Python Pillow Library
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Python Pillow allows you to manipulate images and perform basic image processing tasks. As a fork of the Python Imaging Library (PIL), Pillow supports image formats like JPEG, PNG, and more, enabling you to read, edit, and save images. With Python Pillow, you can crop, resize, rotate, and apply filters to images, making it a versatile tool for image manipulation.

Pillow is often used for high-level image processing tasks and exploratory work. While not the fastest library, it offers a gentle learning curve and a comprehensive set of features for basic to intermediate image processing needs. You can enhance its capabilities by integrating it with NumPy for pixel-level manipulations and creating animations.

By the end of this tutorial, you’ll understand that:

  • Python Pillow is used for image manipulation and basic image processing.
  • Pillow offers reasonable speed for its intended use cases.
  • PIL is the original library, while Pillow is its actively maintained fork.
  • You read an image in Python Pillow using Image.open() from the PIL module.
  • Pillow is used for its ease of use, versatility, and integration with NumPy.

With these insights, you’re ready to dive into the world of image processing with Python Pillow. You’ll use several images in this tutorial, which you can download from the tutorial’s image repository:

With these images in hand, you’re now ready to get started with Pillow.

Basic Image Operations With the Python Pillow Library

The Python Pillow library is a fork of an older library called PIL. PIL stands for Python Imaging Library, and it’s the original library that enabled Python to deal with images. PIL was discontinued in 2011 and only supports Python 2. To use its developers’ own description, Pillow is the friendly PIL fork that kept the library alive and includes support for Python 3.

There’s more than one module in Python to deal with images and perform image processing. If you want to deal with images directly by manipulating their pixels, then you can use NumPy and SciPy. Other popular libraries for image processing are OpenCV, scikit-image, and Mahotas. Some of these libraries are faster and more powerful than Pillow.

However, Pillow remains an important tool for dealing with images. It provides image processing features that are similar to ones found in image processing software such as Photoshop. Pillow is often the preferred option for high-level image processing tasks that don’t require more advanced image processing expertise. It’s also often used for exploratory work when dealing with images.

Pillow also has the advantage of being widely used by the Python community, and it doesn’t have the same steep learning curve as some of the other image processing libraries.

You’ll need to install the library before you can use it. You can install Pillow using pip within a virtual environment:

Windows PowerShell 
PS> python -m venv venv
PS> .\venv\Scripts\activate
(venv) PS> python -m pip install Pillow
Shell 
$ python -m venv venv
$ source venv/bin/activate
(venv) $ python -m pip install Pillow

Now that you’ve installed the package, you’re ready to start familiarizing yourself with the Python Pillow library and perform basic manipulations of images.

The Image Module and Image Class in Pillow

The main class defined in Pillow is the Image class. When you read an image using Pillow, the image is stored in an object of type Image.

For the code in this section, you’ll need the image file named buildings.jpg (image credit), which you can find in the image repository for this tutorial:

You can place this image file in the project folder that you’re working in.

When exploring images with Pillow, it’s best to use an interactive REPL environment. You’ll start by opening the image that you just downloaded:

Python 
>>> from PIL import Image
>>> filename = "buildings.jpg"
>>> with Image.open(filename) as img:
...     img.load()
...

>>> type(img)
<class 'PIL.JpegImagePlugin.JpegImageFile'>

>>> isinstance(img, Image.Image)
True

You might expect to import from Pillow instead of from PIL. You did install Pillow, after all, not PIL. However, Pillow is a fork of the PIL library. Therefore, you’ll still need to use PIL when importing into your code.

You call the open() function to read the image from the file and .load() to read the image into memory so that the file can now be closed. You use a with statement to create a context manager to ensure the file is closed as soon as it’s no longer needed.

Read the full article at https://realpython.com/image-processing-with-the-python-pillow-library/ »

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January 08, 2025 at 07:30PM
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