8 Best Python Image Processing Libraries

Here are the best open-source Python image processing libraries for your applications. You can use these for tasks such as image analysis, object detection, image manipulation, and more.

Certain Python libraries are a fork of the Python Imaging Library (PIL) and provide a wide range of image processing capabilities, including image resizing, rotation, and color manipulation. These libraries offer a wide range of tools for image manipulation, such as filtering, transformation, and feature detection. They also include machine learning algorithms that can be used for object detection and image recognition tasks. Developers also get support for several image file formats, such as JPEG, PNG, and TIFF. And a plugin framework that allows developers to add support for additional file formats.

We have handpicked top and trending open-source Python image processing libraries for your next project. All these libraries are widely used in industry and research. And choosing one depends on the specific needs and the complexity of the task to be performed.

OpenCV:

• Used for computer vision and image processing tasks.
• Provides functions and algorithms for image processing, object detection and tracking, and machine learning.
• Offers support for cross-platform application development.

Pillow:

• Used in Artificial Intelligence, Computer Vision, Deep Learning applications, etc.
• It’s a fork of the Python Imaging Library (PIL).
• Provides simple and efficient tools for image processing and manipulation.

scikit-image:

• Used in Artificial Intelligence, Computer Vision, OpenCV, Numpy applications, etc.
• Provides a wide range of tools for image processing and analysis.
• Features include segmentation, filtering, feature extraction, and more.
• It’s an image processing library built on top of NumPy.

mahotas:

• Used for computer vision and image processing tasks.
• It includes filtering, segmentation, feature extraction algorithms, and more.
• Supports 2.7, 3.4+ Python versions.

imageio:

• Used for reading and writing image data in various formats.
• Supports animated images, video, volumetric data, and scientific formats.
• It can be used to convert between image formats, read video files, and more.
• It’s an easy-to-install cross-platform library that runs on Python 3.7+.

pyvips:

• Used in Artificial Intelligence, Computer Vision, OpenCV applications, etc.
• It’s a Python binding for the VIPS image processing library.
• Provides fast, memory-efficient image processing algorithms for large images.

Wand:

• Used for displaying, converting, and editing image and vector files.
• It’s a simple and easy-to-use Python interface to the ImageMagick image manipulation library.
• Offers a wide range of image manipulation operations, such as resizing, cropping, color correction, etc.
• Supports Python 2.7, 3.3+, and PyPy.

PyTesseract:

• Used to recognize and "read" the text embedded in images.
• Also can be used for optical character recognition.
• It’s a Python wrapper for Google's Tesseract-OCR Engine.
• Supports various image formats, including jpeg, png, gif, bmp, and tiff.