Top 5 Python libraries for Computer vision

Computer vision is the field of computer science that focuses on replicating parts of the complexity of the human visual system and enabling computers to identify and process objects in images and videos in the same way that humans do.
Today core concepts of Computer vision are already being integrated into major products that we use every day, for example:
Self-Driving Cars, Facial Recognition, Healthcare, etc.

These are the top 5 Python libraries that you can use for Computer Vision:

1. OpenCV open Source Computer Vision Library. 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 the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.

2. Face Recognition – Simple facial recognition library. Recognize and manipulate faces from Python or from the command line with the world’s simplest face recognition library. Built using dlib‘s state-of-the-art face recognition built with deep learning. The model has an accuracy of 99.38% on the Labeled Faces in the Wild benchmark.

3. SimpleCV – SimpleCV is a framework for Open Source Machine Vision, using OpenCV and the Python programming language. It provides a concise, readable interface for cameras, image manipulation, feature extraction, and format conversion. Our mission is to give casual users a comprehensive interface for basic machine vision functions and an elegant programming interface for advanced users.

4. Kornia – Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.

5. pytesseract – Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and “read” the text embedded in images. Python-tesseract is a wrapper for Google’s Tesseract-OCR Engine. It is also useful as a stand-alone invocation script to tesseract, as it can read all image types supported by the Pillow and Leptonica imaging libraries, including jpeg, png, gif, bmp, tiff, and others. Additionally, if used as a script, Python-tesseract will print the recognized text instead of writing it to a file.

These are my favorite Python libraries that I use each day for computer vision. There are many other libraries for CV, if you think I’ve left an important one, please leave one in the comments.

Thank you all.

原文链接：Top 5 Python libraries for Computer vision