EasyOCR

EasyOCR is an open-source optical character recognition (OCR) library for Python designed to extract text from images and documents. Built on PyTorch, it uses deep learning-based models to detect and recognize text across a wide range of languages. The project is maintained by Jaided AI and released under the Apache 2.0 license.

Key features include broad language coverage (over 80 languages, including Latin, Chinese, Japanese, Korean, Arabic, Cyrillic, and more), ease of use through a simple API, and the ability to run on both CPU and GPU. The API centers on a Reader class; users initialize it with a list of languages and call readtext on an image to obtain a list of results. Each result provides the detected text, its bounding box, and a confidence score. Pre-trained models are provided for many languages, and users can fine-tune or train models for additional languages if needed.

Architecture and performance: EasyOCR employs a two-stage pipeline with a text detector that locates text regions and a recognizer that transcribes them. This separation allows it to handle diverse layouts and scripts. The library supports common image formats and is suitable for use in notebooks, scripts, and server environments. It can be extended or integrated into preprocessing, translation, or digitization workflows.

Limitations: Accuracy depends on image quality, text orientation, and language complexity. Some scripts are more challenging, and very large documents may require preprocessing or post-processing. Hardware constraints can affect processing speed, especially for high-resolution images or large batches.

See also: the official EasyOCR GitHub repository and documentation for installation instructions, examples, and language model details.