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doc/py_tutorials/py_setup/py_intro/py_intro.rst
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@ -7,45 +7,41 @@ Introduction to OpenCV-Python Tutorials
OpenCV
===============
OpenCV was started at Intel in 1999 by **Gary Bradsky** and the first release came out in 2000. **Vadim Pisarevsky** joined Gary Bradsky to manage Intel's Russian software OpenCV team. In 2005, OpenCV was used on Stanley, the vehicle who won 2005 DARPA Grand Challenge. Later its active development continued under the support of Willow Garage, with Gary Bradsky and Vadim Pisarevsky leading the project. Right now, OpenCV supports a lot of algorithms related to Computer Vision and Machine Learning and it is expanding day-by-day.
OpenCV was started at Intel in 1999 by **Gary Bradsky**, and the first release came out in 2000. **Vadim Pisarevsky** joined Gary Bradsky to manage Intel's Russian software OpenCV team. In 2005, OpenCV was used on Stanley, the vehicle that won the 2005 DARPA Grand Challenge. Later, its active development continued under the support of Willow Garage with Gary Bradsky and Vadim Pisarevsky leading the project. OpenCV now supports a multitude of algorithms related to Computer Vision and Machine Learning and is expanding day by day.
Currently OpenCV supports a wide variety of programming languages like C++, Python, Java etc and is available on different platforms including Windows, Linux, OS X, Android, iOS etc. Also, interfaces based on CUDA and OpenCL are also under active development for high-speed GPU operations.
OpenCV supports a wide variety of programming languages such as C++, Python, Java, etc., and is available on different platforms including Windows, Linux, OS X, Android, and iOS. Interfaces for high-speed GPU operations based on CUDA and OpenCL are also under active development.
OpenCV-Python is the Python API of OpenCV. It combines the best qualities of OpenCV C++ API and Python language.
OpenCV-Python is the Python API for OpenCV, combining the best qualities of the OpenCV C++ API and the Python language.
OpenCV-Python
===============
Python is a general purpose programming language started by **Guido van Rossum**, which became very popular in short time mainly because of its simplicity and code readability. It enables the programmer to express his ideas in fewer lines of code without reducing any readability.
OpenCV-Python is a library of Python bindings designed to solve computer vision problems.
Compared to other languages like C/C++, Python is slower. But another important feature of Python is that it can be easily extended with C/C++. This feature helps us to write computationally intensive codes in C/C++ and create a Python wrapper for it so that we can use these wrappers as Python modules. This gives us two advantages: first, our code is as fast as original C/C++ code (since it is the actual C++ code working in background) and second, it is very easy to code in Python. This is how OpenCV-Python works, it is a Python wrapper around original C++ implementation.
Python is a general purpose programming language started by **Guido van Rossum** that became very popular very quickly, mainly because of its simplicity and code readability. It enables the programmer to express ideas in fewer lines of code without reducing readability.
And the support of Numpy makes the task more easier. **Numpy** is a highly optimized library for numerical operations. It gives a MATLAB-style syntax. All the OpenCV array structures are converted to-and-from Numpy arrays. So whatever operations you can do in Numpy, you can combine it with OpenCV, which increases number of weapons in your arsenal. Besides that, several other libraries like SciPy, Matplotlib which supports Numpy can be used with this.
Compared to languages like C/C++, Python is slower. That said, Python can be easily extended with C/C++, which allows us to write computationally intensive code in C/C++ and create Python wrappers that can be used as Python modules. This gives us two advantages: first, the code is as fast as the original C/C++ code (since it is the actual C++ code working in background) and second, it easier to code in Python than C/C++. OpenCV-Python is a Python wrapper for the original OpenCV C++ implementation.
So OpenCV-Python is an appropriate tool for fast prototyping of computer vision problems.
OpenCV-Python makes use of **Numpy**, which is a highly optimized library for numerical operations with a MATLAB-style syntax. All the OpenCV array structures are converted to and from Numpy arrays. This also makes it easier to integrate with other libraries that use Numpy such as SciPy and Matplotlib.
OpenCV-Python Tutorials
=============================
OpenCV introduces a new set of tutorials which will guide you through various functions available in OpenCV-Python. **This guide is mainly focused on OpenCV 3.x version** (although most of the tutorials will work with OpenCV 2.x also).
OpenCV introduces a new set of tutorials which will guide you through various functions available in OpenCV-Python. **This guide is mainly focused on OpenCV 3.x version** (although most of the tutorials will also work with OpenCV 2.x).
A prior knowledge on Python and Numpy is required before starting because they won't be covered in this guide. **Especially, a good knowledge on Numpy is must to write optimized codes in OpenCV-Python.**
Prior knowledge of Python and Numpy is recommended as they won't be covered in this guide. **Proficiency with Numpy is a must in order to write optimized code using OpenCV-Python.**
This tutorial has been started by *Abid Rahman K.* as part of Google Summer of Code 2013 program, under the guidance of *Alexander Mordvintsev*.
This tutorial was originally started by *Abid Rahman K.* as part of the Google Summer of Code 2013 program under the guidance of *Alexander Mordvintsev*.
OpenCV Needs You !!!
==========================
Since OpenCV is an open source initiative, all are welcome to make contributions to this library. And it is same for this tutorial also.
Since OpenCV is an open source initiative, all are welcome to make contributions to the library, documentation, and tutorials. If you find any mistake in this tutorial (from a small spelling mistake to an egregious error in code or concept), feel free to correct it by cloning OpenCV in `GitHub <https://github.com/Itseez/opencv>`_ and submitting a pull request. OpenCV developers will check your pull request, give you important feedback and (once it passes the approval of the reviewer) it will be merged into OpenCV. You will then become an open source contributor :-)
So, if you find any mistake in this tutorial (whether it be a small spelling mistake or a big error in code or concepts, whatever), feel free to correct it.
And that will be a good task for freshers who begin to contribute to open source projects. Just fork the OpenCV in github, make necessary corrections and send a pull request to OpenCV. OpenCV developers will check your pull request, give you important feedback and once it passes the approval of the reviewer, it will be merged to OpenCV. Then you become a open source contributor. Similar is the case with other tutorials, documentation etc.
As new modules are added to OpenCV-Python, this tutorial will have to be expanded. So those who knows about particular algorithm can write up a tutorial which includes a basic theory of the algorithm and a code showing basic usage of the algorithm and submit it to OpenCV.
As new modules are added to OpenCV-Python, this tutorial will have to be expanded. If you are familiar with a particular algorithm and can write up a tutorial including basic theory of the algorithm and code showing example usage, please do so.
Remember, we **together** can make this project a great success !!!