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What is the Python Pillow Concept?

The standard image processing package for the Python language is the Python Imaging Library (extension of PIL). It includes simple image processing capabilities that help with image creation, editing, and saving. 2011 saw the end of support for the Python Imaging Library, although a project called pillow forked the PIL project and added Python 3.x support to it. PIL will be replaced going forward with Pillow, according to the announcement. BMP, PNG, JPEG, and TIFF are just a few of the many image file formats that Pillow can open. By developing new file decoders, the library promotes the addition of support for newer formats in the library.

Python is not already installed in this module. Therefore, run the following command in the command line to install it:

  • Pillow install pip

Note: Python and PIL are frequently preinstalled on different Linux distributions. Also follow the online booting coding courses at Edureify for more details. 

Features of Python Pillow

(1)Bringing up and showing the picture:-

The open() and show() functions are provided by the Pillow module to read and display the picture, respectively. Pillow initially converts the image to a.png format (on the Windows operating system) and saves it in a temporary buffer before showing it.

(2) Resize the picture:-

An image that has been scaled is what resize() returns. When a picture is resized, interpolation takes place, which causes the quality to fluctuate depending on whether the image is being upscaled (enlarged to a larger dimension than the original) or downscaled (resized to a lower Image then original).

(3)The image is being saved:- The save() function stores the image in the specified file. If no format is supplied, the appropriate format is inferred, if at all possible, from the filename extension. Instead of using a filename, you can use a file object. In this situation, the format must always be specified.

Combine images

(4) Merging the Images:- A group of single band photos can be combined into a new multiband image using the Image.merge() function.


Difference between PIL and Pillow Python

Python:- The Python Imaging Library is a free and open-source extra library that enhances support for accessing, modifying, and saving a wide range of image file formats. It works with Windows, Mac OS X, and Linux. PIL 1.1.7, which was released in September 2009 and works with Python, is the most recent version.

PIL:- The PIL fork created by Alex Clark and Contributors is called Pillow. The Python Imaging Library (PIL) was created by Contributors and Fredrik Lundh. Your Python interpreter gains the ability to process images thanks to the Python Imaging Library.

This library offers a wide range of file format compatibility, a productive internal representation, and moderately potent image processing features. The primary picture library is built for quick access to information held in a few fundamental pixel formats. It ought to serve as a strong starting point for a broad image processing tool.

Starting with a pillow

(1) Open a picture with open() first :- The image object is represented by the PIL. Image. Image class. The open() method, which is used to open the image, is provided by this class.

(2) Using show() to show the image :- The image is displayed using this technique. Pillow initially converts the image to a.png format (on the Windows operating system) and saves it in a temporary buffer before showing it. Consequently, some of the original image file format’s properties could be lost as a result of the conversion of the image format to.png (like animation). Finding out details about the opened image.

(3) Obtaining the image’s mode (colour mode):- The type and depth of each pixel in the image are revealed by the mode attribute. The range of an 8-bit pixel is 0-255, while that of a 1-bit pixel is 0–1. This module provides a variety of modes.

(4) Rotating an image with rotate(): The areas of the image with no pixel values are filled with black (for non-alpha images) or completely transparent pixels after the image has been rotated (for images supporting transparency).

(5)When resizing an image with the resize. Function, interpolation occurs, which alters the image’s quality whether it is being downsized or upscaled (resized to a higher dimension than original)

Example of Python Pillow


size = (60, 60)

img = Image. open(retest. Png”)

rig = imgreite(size, resample = Image. BILINEAR)

 # resized_test.png => Destination path

rimg. save(“resized_test.png”) 

 # Opening the new image

image = Image. open(r” resized _ test.png”)

print(image. size)



The Pillow python is a helpful tutorial and along with this you must be aware of some of the concepts which are also covered in the online coding bootcamp courses at Edureify. The concepts of python which is important are as follows:-

Frequently Asked Questions (FAQs)

Q:- What is Pillow in Python used for?

Ans:- The Pillow library contains all the basic image processing functionality. You can do image resizing, rotation and transformation. Pillow module allows you to pull some statistics data out of image using histogram method, which later can be used for statistical analysis and automatic contrast enhancement.

Q:- Is Pillow built into Python?

PIL is an abbreviation of Python Imaging Library and it adds image processing to Python. In 2011, PIL has been discontinued—its unofficial successor framework Pillow for image processing is an actively maintained and user-friendly alternative for Python 3.

Q:- How do I know if pillow is installed?

Ans:-  To check if PIL is successfully installed, open up the python terminal by typing python3 in the terminal. This will open up the python3 interactive console now type the following command to check the current version of the PIL. This will output the currently installed version of the PIL.

Q:- What is PIL image image?

Ans:- PIL is the Python Imaging Library which provides the python interpreter with image editing capabilities. The Image module provides a class with the same name which is used to represent a PIL image.

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