docTR: Document Text Recognition

State-of-the-art Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch

DocTR provides an easy and powerful way to extract valuable information from your documents:

  • 🧾 for automation: seamlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents.

  • 👩‍🔬 for research: quickly compare your own architectures speed & performances with state-of-art models on public datasets.

Main Features

  • 🤖 Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters

  • ⚡ User-friendly, 3 lines of code to load a document and extract text with a predictor

  • 🚀 State-of-the-art performance on public document datasets, comparable with GoogleVision/AWS Textract

  • ⚡ Optimized for inference speed on both CPU & GPU

  • 🐦 Light package, minimal dependencies

  • 🛠️ Actively maintained by Mindee

  • 🏭 Easy integration (available templates for browser demo & API deployment)

Model zoo

Text detection models

Text recognition models

Supported datasets