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tutorial_template.rst

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Title of Doc comes here

Goals

Explain here following things:

Theory

  • Some intuitive explanation of algorithm is given here
  • If needed, give some equations as inline g(i,j) or next line as,
g(i,h) = \sum_{k,l} f(i+k, j+l) h(k,l)
  • If required, a Numpy implementation of algorithm also can be given as a separate subsection

Subsection Python Implementation [optional]

Numpy code comes here. To add code, do as follows :

import cv2
import numpy as np

print 'import done'

OpenCV sample

Here comes the original OpenCV code with explanation. Result also can included in this itself.

To add image, do as follows :

Smoothing with a median filter

Notes, warnings, Todo etc can be done as follows :

Note

The explanation below belongs to the book

Warning

The explanation below belongs to the book

.. todo::
   The explanation below belongs to the book

.. seealso::
   The explanation below belongs to the book

external urls are given as Python which points to python site.

Internal url is called as Tutorial-Template

A book is cited as [Szeliski]

Common Errors [optional]

We can show solutions for some common mistakes while using certain functionalities, if any.

Exercises [optional]

Here we can give some additional tasks for reader to do

  • like read and understand more advanced code on the same algorithm.
  • Related SOF and answers.opencv.org questions
  • Our own questions or tasks

Additional Resources [optional]

Give references if any for better understanding of algorithm, like any standard textbooks, web links etc. Numbered references are given as

  1. Learning OpenCV
  2. Computer Vision Models
[Szeliski]Computer Vision Models