Python: The Best Image Processing Libraries
In this blog post, we will take a look at some of the best image processing libraries in Python. We’ll spend time looking at their strengths and weaknesses to help you pick one that is right for your needs!
OpenCV
The Open Computer Vision Library, or simply OpenCV, is a collection of powerful image processing tools. It was originally developed for use in the video game industry but has since found widespread success outside of it as well! If you are looking for an open-source alternative to MATLAB, then this might be your best bet.
Matplotlib
The matplotlib library is a plotting library for Python. It can be used to generate plots in either the “Matlab” style or the more traditional gnuplot-style, depending on your preference. Best of all, it’s actually built into NumPy; simply use np.show() and you'll be on your way!
Numpy
While not exactly an image processing library, NumPy is one of the most important libraries for scientific computing in Python today. It provides powerful tools like linear algebra and Fourier transforms that make it easier to work with images. If you are doing serious mathematics or data analysis with your images, then this is probably the library you want to use.
ImageMagick
ImageMagick is a software suite for processing images. It has its own programming language that allows users to manipulate their image files in many ways, including resizing, adjusting color balance, or applying filters and effects. Image processing with ImageMagick can be done from the command line or through a graphical interface.
Pillow
The Pillow library is a fork of the PIL library that aims to be more user-friendly and maintainable. It includes many of the same features as PIL but also adds support for animated GIFs, JPEG2000 files, and WebP images. If you are looking for a drop-in replacement for PIL, then this is probably your best bet!
Scikit-image
The Scikit-image library is a collection of image processing algorithms that are designed to be easy to use and understand. It includes algorithms for common tasks like edge detection, feature extraction, and image restoration. If you are just starting out in image processing, then this is a good library to check out!
That’s it for our roundup of the best image processing libraries in Python!
We hope this gives you a better idea of which one is right for your needs. If you have any questions, feel free to leave a comment below!
