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Added OpenCV to Image Processing #635

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Added OpenCV to Image Processing
Oct 26, 2015
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Updated OpenCV
Oct 26, 2015
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Oct 28, 2015
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Oct 31, 2015
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50 changes: 49 additions & 1 deletion docs/scenarios/imaging.rst
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Expand Up @@ -5,11 +5,16 @@ Image Manipulation
.. todo::
Add introduction about image manipulation and its Python libraries.

Most image processing and manipulation techniques can be carried out effectively using
two libraries: Python Imaging Library (PIL) and OpenSource Computer Vision (OpenCV).

A brief description of both is given below.

Python Imaging Library
----------------------

The `Python Imaging Library <http://www.pythonware.com/products/pil/>`_, or PIL
for short, is *the* library for image manipulation in Python. Unfortunately,
for short, is one of the core libraries for image manipulation in Python. Unfortunately,
its development has stagnated, with its last release in 2009.

Luckily for you, there's an actively-developed fork of PIL called
Expand Down Expand Up @@ -55,3 +60,46 @@ Example

There are more examples of the Pillow library in the
`Pillow tutorial <http://pillow.readthedocs.org/en/3.0.x/handbook/tutorial.html>`_.


OpenSource Computer Vision
--------------------------

OpenSource Computer Vision, more commonly known as OpenCV, is a more advanced image manipulation and processing software than PIL. It has been implemented in several
languages and is widely used.

Installation
~~~~~~~~~~~~

In Python, image processing using OpenCV is implemented using the ``cv2`` and ``NumPy`` modules.
The `installation instructions for OpenCV <http://docs.opencv.org/2.4/doc/tutorials/introduction/table_of_content_introduction/table_of_content_introduction.html#table-of-content-introduction>`_ should guide you through configuring the project for yourself.

NumPy can be downloaded from the Python Package Index(PyPI):

.. code-block:: console

$ pip install numpy


Example
~~~~~~~

.. code-block:: python

from cv2 import *
import numpy as np
#Read Image
img = cv2.imread('testimg.jpg')
#Display Image
cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

#Applying Grayscale filter to image
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

#Saving filtered image to new file
cv2.imwrite('graytest.jpg',gray)

There are more Python-implemented examples of OpenCV in this `collection of tutorials <http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_tutorials.html>`_.