Working with Images in Python: Installing and Using Pillow

Introduction

Python is a versatile language, and image processing is a common task in many applications. The Python Imaging Library (PIL) was the standard for image manipulation for many years. However, PIL development has ceased. Fortunately, a actively maintained fork called Pillow provides full compatibility with PIL and adds many new features. This tutorial will guide you through installing Pillow and demonstrate its basic usage.

Why Pillow?

Pillow is a powerful and easy-to-use library for opening, manipulating, and saving many different image file formats. It’s a great choice for:

Basic image operations (resizing, cropping, rotating)
Applying filters and effects
Image format conversion
Creating thumbnails
Image analysis and data extraction

Installation

The recommended way to install Pillow is using pip, the Python package installer. Open your terminal or command prompt and run the following command:

pip install Pillow

If you have multiple Python versions installed and want to ensure you install Pillow for a specific version (e.g., Python 3), you can use:

python3 -m pip install Pillow

Troubleshooting Installation Issues:

On macOS, you might encounter issues during installation related to missing system dependencies. While generally pip install Pillow handles dependencies automatically, if you run into problems, you may need to ensure you have the necessary build tools installed. These are typically included with Xcode and the Xcode Command Line Tools.

Basic Usage

Now that Pillow is installed, let’s explore how to use it.

1. Opening an Image:

First, import the Image module from the PIL namespace:

from PIL import Image

To open an image, use the Image.open() function:

try:
    img = Image.open("my_image.jpg") # Replace "my_image.jpg" with your image file
    print("Image opened successfully!")
except FileNotFoundError:
    print("Image file not found.")
except Exception as e:
    print(f"Error opening image: {e}")

2. Displaying Image Information:

You can access various properties of the image, such as its format, size, and mode:

print(f"Format: {img.format}")
print(f"Size: {img.size}") # (width, height)
print(f"Mode: {img.mode}") # e.g., RGB, L (grayscale)

3. Basic Image Manipulation:

Here are a few simple operations you can perform:

Resizing:

resized_img = img.resize((200, 150)) # New width and height
resized_img.save("resized_image.jpg")

Rotating:

rotated_img = img.rotate(90) # Rotate 90 degrees clockwise
rotated_img.save("rotated_image.jpg")

Converting to Grayscale:

grayscale_img = img.convert("L") # "L" mode represents grayscale
grayscale_img.save("grayscale_image.jpg")

4. Saving an Image:

Use the save() method to save the modified image to a file:

resized_img.save("new_image.png") # You can specify the format

Complete Example

Here’s a complete example that opens an image, resizes it, converts it to grayscale, and saves the result:

from PIL import Image

try:
    img = Image.open("my_image.jpg")
    resized_img = img.resize((300, 200))
    grayscale_img = resized_img.convert("L")
    grayscale_img.save("processed_image.png")
    print("Image processed and saved successfully!")
except FileNotFoundError:
    print("Image file not found.")
except Exception as e:
    print(f"An error occurred: {e}")

Remember to replace "my_image.jpg" with the actual path to your image file.

Further Exploration

Pillow offers a wealth of functionalities beyond the basics covered in this tutorial. Explore the official Pillow documentation (https://pillow.readthedocs.io/en/stable/) to learn about:

Image filtering
Drawing on images
Pixel access and manipulation
Advanced image processing techniques