Top 5 Python OCR Libraries for Extracting Text from Images

Understand and master OCR tools for text localization and recognition

Photo by Anna Sullivan on Unsplash

Optical Character Recognition is an old, but still challenging problem that involves the detection and recognition of text from unstructured data, including images and PDF documents. It has cool applications in banking, e-commerce and content moderation in social media.

But as with everything topic in data science, there is a huge amount of resources when trying to learn how to solve the OCR task. This is why I am writing this tutorial, which can help you on getting started.

In this article, I am going to show some Python libraries that can allow you to fastly extract text from images without struggling too much. The explanation of the libraries is followed by a practical example. The dataset used is taken from Kaggle. To simplify the concepts, I am just using an image of the film Rush.

Let’s get started!

Image from textOCR dataset. Source.

Table of contents:

1. pytesseract
2. EasyOCR
3. Keras-OCR