docTR vs PaddleOCR

docTR is a free deep-learning OCR library for finding and recognizing text in documents, aimed at document automation and research. Its pretrained OCR predictors first detect text and then recognize it, while a layout predictor identifies regions such as tables, figures, and headers. It reads PDFs and images; web-page input requires the optional HTML extra. Results can be rendered as plain text or exported as a JSON-serializable nested dictionary. The project describes its predictors as optimized for CPU and GPU inference. Users can train custom detection, recognition, layout, and table-structure models when pretrained models are not suitable. Documentation covers loading and sharing models through the Hugging Face Hub, and includes a minimal REST API deployment template and a browser demo. Installation is available through pip, Git, or official Docker images. The library requires Python 3.11 or higher, and pretrained weights download on first use and are cached locally. For AWS Lambda, the guide advises disabling multiprocessing and placing the model cache within /tmp. The project uses the Apache License 2.0.

PaddleOCR is an open-source OCR and document-processing toolkit for extracting text and structure from documents. Its PP-StructureV3 component turns complex PDFs and document images into Markdown and JSON while preserving their organization, and supports table extraction. PaddleOCR-VL handles multilingual document parsing across 109 languages, while PP-OCRv6 supports 50 languages in one model. PaddleOCR 3.0 also recognizes handwriting. For large document collections, PP-ChatOCRv4 extracts key information and integrates ERNIE 4.5. Models can be used online through the official website or called through an API; the official free API allows up to 20,000 pages of document parsing per day. Documentation describes local, C++, service, Android, iOS, and browser deployment options, among others. The license permits use, modification, distribution, and sale without restriction. SDK languages listed are Python, TypeScript, and Go. Support is available through GitHub Issues. One compatibility note: code written for PaddleOCR 2.x may not run with version 3.x.