Python Computer Vision Libraries Every Developer Should Know

Python is one of the most popular languages of the current age. It has gained more popularity with the rise of Artificial Intelligence and Machine Learning. Developers of these domains prefer python for coding and developing applications.
Since Computer Vision falls under a wide umbrella of Artificial Intelligence, python is widely used for CV-related applications. In this article, we will discuss the gold standard libraries for python that are used for the development of computer vision applications.

OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.
The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc.

Keras
Keras is an API designed with humans in mind rather than machines. Keras follows best practices for reducing cognitive load. It offers consistent & simple APIs, minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides.
Keras is the most used deep learning framework among the top-5 winning tea
ms on Kaggle.
Built on top of TensorFlow 2, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod.

Matplotlib
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible.
Create publication-quality plots.
Make interactive figures that can zoom, pan, update.
Customize visual style and layout.
Export to many file formats.
Embed in JupyterLab and Graphical User Interfaces.
Use a rich array of third-party packages built on Matplotlib.

Scikit-Image
scikit-image is an open-source image processing library for the Python programming language. It comprises a wide collection of algorithms for image processing such as segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more.

Imutils
Imutils is a series of convenience functions to make basic image processing functions such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and both Python 2.7 and Python 3.

SciPy
SciPy is a free and open-source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers, and other tasks common in science and engineering.

Pillow
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X, and Linux.
This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities.
The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.

NumPy
NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms basic linear algebra, basic statistical operations, random simulation and much more. At the core of the NumPy package, is the ndarray object. This encapsulates n-dimensional arrays of homogeneous data types, with many operations being performed in compiled code for performance.

TensorFlow
TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on the training and inference of deep neural networks.
It is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications.

In this article, we discussed the most popular libraries that allow computer vision applications to be deployed and manipulated. These libraries are a gold standard for anyone who wants to enter the domain of Computer Vision in Python.

images.cv provide you with an easy way to build image datasets.
15K+ categories to choose from
Consistent folders structure for easy parsing
Advanced tools for dataset pre-processing: image format, data split, image size and data augmentation.

Visit images.cv to learn more