The difference between opencv and python

Python (Recommended learning: Python video tutorial)

is the famous "Uncle Turtle" Guido van Rossum in A programming language written during the Christmas period of 1989 to kill the boring Christmas.

Python is an interpreted, object-oriented, high-level programming language with dynamic data types.

Python provides us with a very complete basic code library, covering a large number of contents such as networks, files, GUIs, databases, texts, etc. It is vividly called "built-in batteries (batteries included)". Developed in Python, many functions do not need to be written from scratch, just use ready-made ones.

In addition to the built-in libraries, Python also has a large number of third-party libraries, which are things developed by others for you to use directly. Of course, if the code you develop is well encapsulated, it can also be used as a third-party library for others to use.

Uncle Gui positions Python as "elegant", "clear", and "simple", so Python programs always look simple and easy to understand. Beginners learning Python will not only get started easily, but will also go deeper in the future. You can write very, very complex programs.

OpenCV

is a cross-platform computer vision library released under the BSD license (open source) and can run on Linux, Windows, Android and Mac OS operating systems. It is lightweight and efficient - it consists of a series of C functions and a small number of C classes. It also provides interfaces in Python, Ruby, MATLAB and other languages, and implements many common algorithms in image processing and computer vision.

OpenCV is written in C language, and its main interface is also C language, but it still retains a large number of C language interfaces. The library also has extensive interfaces to Python, Java and MATLAB/OCTAVE (version 2.5). API interface functions for these languages ​​can be obtained through online documentation. Now it also provides support for C#, Ch, Ruby, and GO.

All new developments and algorithms use C interface. A GPU interface using CUDA was also implemented in September 2010.

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