![]() ![]() ![]() ![]() It's supported by a MUCH LARGER user community. Jumping in without actually learning it can be very frustrating if coming from Matlab but in particular once you learn how well and universally it handles iteration, it is quite beautiful! It's user friendly, once you really understand itsįunctionality and features. It's comparable to Matlab in speed, both in writing an application and its execution. It's Free (although Octave served that purpose for me, but Octave is I wanted to share here some main points that influenced me and why I am such a big fan of Python for this application space. Matlab still rules in integrated hardware and co-simulation solutions, and I have access to both tools, yet I prefer using Python for general signal processing simulation and analysis. Six years ago I gravitated over to Python out of curiosity and it has since completely replaced Matlab as my tool of choice meeting all my needs for signal processing. I have spent the first 20 years of my career working extensively in MATLAB for signal processing applications. Meantime you’ll get where you are going in style, and with power to It’s built with an audacious goal of changing theįuture, and it might. But it doesn’t offer a great pure driving Chances are you’re going to want to borrow It can do everything you want, and it’s built to do some things It’s ubiquitous and beloved by many (in the It’sĮxpensive rock-solid attracts a disproportionate amount MATLAB is the BMW sedan of the scientific computing world. Meticulous documentation and decades of contributed MATLAB It’s probably still the easiest to learn for basic Python (compared to BMW sedan, Ford pickup and Testa) Toby Driscoll (more balanced): Matlab vs. For RealPython (biased): MATLAB vs Python: Why and How to Make the Switch.SciLab: Image Processing & Computer Vision.OpenCV: Open Source Computer Vision Library.Icy: Open Source Image Processing Software.ImageJ: Image Processing and Analysis in Java.You can also use (free) open source software, with contributed toolboxes and plugins, that often benefit from external publications. On my side, I would switch to Python for machine learning and data science, but I will stick to Matlab for most of my signal processing and image analysis works for a while. Globally, as long as you grow solid image processing skills, I would think what mostly differ between Matlab and Python are the cost and the trendiness. Python now has a large community, and has developed toolsets like Scikit-Image, and there is a tutorial for instance at Scikit-image: image processing. When the workflow is set, if you care of speed, efficiency, etc., it is time to pass the algorithmic prototyping over to real programmers (C++, or lower level, which I can't do). To that respect, Matlab is great at designing and fine tuning algorithms, possesses a lot of documentation and help that you can follow step-by-step, and enjoys a long list of contributed toolboxes, esp. In my case, I mostly engineer algorithms as prototypes and proofs of concepts, that can stay as them, or are turned into "solid programs" by people that are better at, and like better, programming with the rules-of-art in lower levels languages, depending on the target. But laziness sometimes drives you to sticking to your first language, reusing old librairies. So if you find a book that you like on "Python for computer vision with exercises" or "Image processing theory and practice with Matlab, that could be interesting starting points.Īlso, your programming tastes and skills may evolve, and learning a first programming language helps you learning a second one in general. For learning from scratch, I would not suggest a programming language alone, but instead the couple "teaching materials" (book, lecture notes) + "exercises with a specific programming language". ![]()
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