mirror of
https://github.com/kennethreitz/python-guide.git
synced 2026-06-05 14:50:19 +00:00
Adam Chainz
af7d603e97
As per [their blog post of the 27th April](https://blog.readthedocs.com/securing-subdomains/) ‘Securing subdomains’: > Starting today, Read the Docs will start hosting projects from subdomains on the domain readthedocs.io, instead of on readthedocs.org. This change addresses some security concerns around site cookies while hosting user generated data on the same domain as our dashboard. Test Plan: Manually visited all the links I’ve modified.
108 lines
3.0 KiB
ReStructuredText
108 lines
3.0 KiB
ReStructuredText
==================
|
|
Image Manipulation
|
|
==================
|
|
|
|
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 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
|
|
`Pillow <http://python-pillow.github.io/>`_ - it's easier to install, runs on
|
|
all operating systems, and supports Python 3.
|
|
|
|
Installation
|
|
~~~~~~~~~~~~
|
|
|
|
Before installing Pillow, you'll have to install Pillow's prerequisites. Find
|
|
the instructions for your platform in the
|
|
`Pillow installation instructions <https://pillow.readthedocs.io/en/3.0.0/installation.html>`_.
|
|
|
|
After that, it's straightforward:
|
|
|
|
.. code-block:: console
|
|
|
|
$ pip install Pillow
|
|
|
|
Example
|
|
~~~~~~~
|
|
|
|
.. code-block:: python
|
|
|
|
from PIL import Image, ImageFilter
|
|
#Read image
|
|
im = Image.open( 'image.jpg' )
|
|
#Display image
|
|
im.show()
|
|
|
|
#Applying a filter to the image
|
|
im_sharp = im.filter( ImageFilter.SHARPEN )
|
|
#Saving the filtered image to a new file
|
|
im_sharp.save( 'image_sharpened.jpg', 'JPEG' )
|
|
|
|
#Splitting the image into its respective bands, i.e. Red, Green,
|
|
#and Blue for RGB
|
|
r,g,b = im_sharp.split()
|
|
|
|
#Viewing EXIF data embedded in image
|
|
exif_data = im._getexif()
|
|
exif_data
|
|
|
|
There are more examples of the Pillow library in the
|
|
`Pillow tutorial <https://pillow.readthedocs.io/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
|
|
<https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html>`_.
|