doctr

doctr is a Python library designed for optical character recognition (OCR) tasks, specifically focusing on document analysis. It provides a user-friendly interface to access and utilize deep learning models for extracting text from images of documents. The library is built upon popular deep learning frameworks, making it accessible for researchers and developers.

The core functionality of doctr revolves around its pre-trained models. These models have been trained on large datasets of documents and are capable of identifying and transcribing text with high accuracy. doctr supports various document layouts, including scanned documents, invoices, and forms. It can handle different fonts, languages, and image qualities.

Beyond basic text extraction, doctr offers features that aid in more complex document understanding. This can include capabilities for layout analysis, where the system identifies different regions of a document such as text blocks, tables, and images. It also supports information extraction, allowing users to define specific fields or entities to be retrieved from the document.

The library's design emphasizes simplicity and extensibility. Users can easily integrate doctr into their existing Python projects and customize its behavior for specific OCR needs. This makes it a valuable tool for applications ranging from automated data entry and document digitization to natural language processing and information retrieval. The project aims to democratize access to powerful OCR technology.