How to choose the right programming language for your next computer vision project?
In this article, we will list some of the most suitable programming languages for implementing computer vision systems, in my experience all of them as some pros

There are several programming languages suitable for implementing computer vision systems, some of them easy to learn and some of them hard for a new developer. This article will present you with 3 programming languages that you want to consider while implementing a computer vision system.

MATLAB

MATLAB is a program for analyzing data, creating algorithms, and creating models that engineers and scientists use every day

👍 Pros:

• MATLAB is widely used in academia, especially for prototyping and testing new ideas.
• MATLAB is well known as a programming language with very good algorithm implementations and extensive toolbox options, with its integrated graphical interface, MATLAB lets you edit code, display output, plot figures, manipulate data, and more, all of them in MATLAB IDE.
• MATLAB known for its built-in vector variables that make vector-like programming to be very convenient, MATLAB provides an easy debugging experience with a good user experience.

👎 Cons:

• MATLAB is not designed for a production environment, another major con is that MATLAB costs around 2500$ for a standard license, plus a yearly fee.
• A major drawback of MATLAB is that it is extremely slow in executing code, and the learning curve is quite long since its syntax is different from general-purpose programming languages, such as C, C++, and Python.

C++, also known as the “C with Classes” programming language, is a general-purpose programming language developed by Bjarne Stroustrup

👍 Pros:

• C++ enables its users to run the same program on different operating systems easily.
• One of C++’s biggest benefits is its object-oriented model that includes concepts like classes, inheritance, polymorphism, data abstraction, and encapsulation, expanding reusability and reliability.
• Embedded systems and compilers leverage C++ for low-level machine manipulation.
• In C++, the programmer has access to control over memory management, but this comes at a cost as there is a greater responsibility to manage memory as opposed to it being handled by the Garbage Collector.
• C++ can handle small datasets as well as large ones, and it can handle intensive processes.

👎 Cons:

• On the other hand, C++ is quite hard for beginners, If you have no experience programming in C++, It’s probably more productive to try Python instead
• Pointers in C/C++ are a complex notion, utilizing an excessive amount of memory. The use of generalized pointers, such as ‘wild pointers’, can cause the app to crash or function erratically.

Python

The Python programming language is an interpreted, general-purpose language. Python uses a significant indentation in its design emphasizes code readability. The language implements an object-oriented approach to enable programmers to write logical, clear code for both small and large projects

👍 Pros:

• Python is aimed for both new and experienced coders to be able to convert ideas into code easily.
• As one of the most mature, prevalent, and well-supported languages in the area of machine learning, Python is a natural choice for running computer vision code.
• Computer vision can be implemented through the Python programming language, allowing developers to carry out visualization-based tasks at high speeds.
• Python is commonly used in machine learning. Data scientists invest their time contributing because it’s fairly simple to write code in Python, and it’s free and open-source.

👎 Cons:

- Python is an interpreted language, so it often sacrifices the speed of a compiled language and it leads to slow code execution

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