Computer vision is a branch of artificial intelligence (AI) that permits computers and systems to extract useful information from digital photos, videos, and other visual inputs and initiate actions or make recommendations based on that data. Image processing, which is the phenomenon of manipulating or editing, or performing some operations on a picture to extract features from it, is required to extract this information. We’ll go over among the cool image processing libraries in Python in this text.
1. OpenCV
OpenCV is certainly one of the fastest and most generally used libraries for image processing and computer vision applications. It’s supported by Github, with over a thousand contributors contributing to the event of the library. Created by Intel in 1999, it supports many languages like C, C++, Java, and the most well-liked Python. OpenCV offers around 2500 algorithms to assist construct models for face recognition, object detection, image segmentation, etc.
2. Mahotas
Mahotas is a complicated python library for image processing and computer vision that provides advanced functionalities like thresholding, convolution, morphological processing, and way more. It was written in C++, which makes it fast.
3.SimpleCV
SimpleCV may be regarded as a easier version of OpenCV. It’s a python framework. It doesn’t require many image processing prerequisites and ideas like color spaces, buffer management, eigenvalues, etc. Due to this fact, it’s beginner-friendly.
4. Pillow
Pillow relies on the Python Imaging Library (PIL). This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. It encompasses several image processing activities, including point operations, filtering, manipulating, etc.
5. Scikit-Image
Scikit-Image is an open-source python library for image processing. By transforming the unique pictures, it uses NumPy arrays as image objects. As NumPy is inbuilt C programming, it’s a really fast & effective library for image processing. It includes algorithms for Filtering, Morphology,
Feature detection, Segmentation, Geometric transformations, Color space manipulation, etc.
6. SimplelTK
SimpleITK is an open-source library that provides multi-dimensional image evaluation. Unlike most image processing and computer vision libraries that consider images as arrays, it treats images as a set of points in space. It supports languages like Python, R, Java, C#, Lua, Ruby, TCL, and C++.
7. SciPy
SciPy is principally used for scientific and mathematical computations, but it may even be used for image processing and computer vision by importing relevant modules of the library. It may offer image processing functions similar to Convolution, Face Detection, Feature Extraction, Image Segmentation, etc.
8. Pgmagick
Pgmagick is a GraphicsMagick python binding for image manipulation. It aids in image processing functions similar to scaling, rotation, sharpening, gradient images, and so forth. It may handle over 88 different image formats.
9. Seaborn
Seaborn is some of the popular python libraries amongst data scientists since it helps understand the correlation between various data points. It is because it offers excellent visualizations that make the model comprehensible and attractive.
10. Matplotlib
Matplotlib is a python library known for creating visualizations, but it may even be used for image processing. It may be used to extract information out of the image. It shouldn’t be supportive of all file formats.
11. Numpy
Numpy is a widely used library for machine learning models. It may be utilized in image processing to assist manipulate pixels, mask pixel values, and image cropping.
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Mansi
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Consultant Intern: Currently in her third yr of B.Tech from Indian Institute of Technology(IIT), Goa. She is an ML enthusiast and has a keen interest in Data Science. She is a superb learner and tries to be well versed with the most recent developments in Artificial Intelligence.
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