Image by Editor
In today’s world, data plays a vital role in every industry vertical. Images can be one of the sources of extracting data. An image can be defined as a matrix of pixels, and each pixel represents a color that can be treated as a data value.
Image Processing comes in handy to uncover underlying data from any image. It helps you extract, manipulate, and filter data from an image. The main objective of image processing is to uncover some valuable information from images.
There are various applications of image processing, such as image sharpening, image restoration, pattern recognition, video processing, etc. Most image processing applications come under data analysis and data science.
And when it comes to data analysis, the only language that comes to our mind is Python. It is also the most preferred language for image processing because of its extensive set of libraries, which makes it very easy for developers to perform complex operations using simple lines of code.
Let’s have a look at some of the Python libraries which are primarily used for image processing.
Here is a list of the best Python libraries that help you manipulate images easily. All of them are easy to use and allow you to extract the underlying data from images.
1. OpenCV
OpenCV (Open Source Computer Vision Library) is a popular Python Data Visualation library. It is an open-source library that is available for various programming languages, including C++, Java as well as assembly language.
This library was developed by Intel using the C++ programming language, and it was designed for real-time computer vision. It is ideal for executing computationally intensive computer vision programs.
Install
As OpenCV is a third-party library, we can install it for our Python environment using the Python pip package manager tool.
pip install opencv-python
Example
# import opencv
import cv2
# Read the image
image = cv2.imread('tesla.png')
# grayscale the image
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.imshow('Original Image', image)
cv2.imshow('Grayscale Image', gray_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
Output
2. Pillow (PIL)
Pillow is another popular Python image processing library. It is the most basic image processing library that every beginner can start with. It is also known as PIL, which stands for Python Imaging Library.
PIL library comes with different file formatter extensions that provide powerful and complex features to perform image processing. If we compare PIL with OpenCV, PIL is a lightweight library with fewer features, making it easy to learn and handle for a new Python developer who has just entered the realm of image processing.
Install
PIL is also a third-party open-source library, and it can be installed using the pip install command.
Example
GrayScale an Image in Python using Pillow
from PIL import Image
with Image.open("tesla.png") as im:
#show the original image
im.show("Original Image")
#convert into grayscale
grayscaleImg = im.convert("L")
#show the grayscale image
grayscaleImg.show()
Output
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