docTR vs Surya

docTR (Document Text Recognition) is an open-source OCR toolkit developed by Mindee, with its initial public release in March 2021 under the Apache 2.0 license. It provides end-to-end document text recognition through a two-stage pipeline consisting of text detection and text recognition, both implemented as deep learning models. docTR supports multiple detection architectures including DBNet and LinkNet, and recognition architectures including CRNN and SAR, with both TensorFlow and PyTorch backends available.

docTR is designed for reading text in document images including scanned PDFs, photographs of printed documents, and forms. It handles multilingual text recognition across standard Latin-script languages and is deployable through Roboflow Inference. It is suited for document digitization pipelines, automated form processing, and applications requiring accurate structured text extraction from document images.

Surya is an OCR and document layout analysis toolkit developed by Vikram Paruchuri and distributed via Mindee, first released in January 2024 under the GPL-3.0 license. It supports text recognition across more than 90 languages, document layout detection, reading order prediction, table recognition, and equation detection, providing a comprehensive set of tools for extracting structured information from document images.

Surya is designed to operate without cloud API dependencies, running fully on local hardware with support for CPU and GPU inference. It is commonly used for digitizing scanned documents, extracting text from PDFs with complex layouts, and building automated document processing pipelines.