Tech riderRev. 5 Oct 2026
  1. 1Runs onAPI, Linux, Mac, self-hosted, Windows
  2. 2CostsFree plan
2 lines stated Written from the maker's own pages: mindee.github.io
The docTR homepage

Overview

docTR is ranked #3 of 40 in OCR software on Specifiction, made by docTR. It runs on API, Linux, macOS, Self-hosted, Windows. There is a free plan.

docTR plans and pricing

All plans
docTR open-source Python library Free Python 3.11 or higher · install with pip, Git, or Docker mindee.github.io · 5 Oct 2026

Compared on OCR software

Free plan
Yesmindee.github.io

Facts

Primary platform
desktopmindee.github.io · 23 Sept 2026
Supported inputs
bothmindee.github.io · 23 Sept 2026
Purpose
docTR is a deep learning OCR library for locating and recognizing text in documents, intended for document automation and research.mindee.github.io · 5 Oct 2026
OCR pipeline
Its pretrained OCR predictors use a two-stage text detection and recognition pipeline.mindee.github.io · 5 Oct 2026
Layout analysis
A layout predictor detects document regions such as tables, figures, and headers.mindee.github.io · 5 Oct 2026
Inputs and outputs
The quickstart shows loading PDFs, images, and web pages and exporting results as plain text or a JSON-serializable dictionary.mindee.github.io · 5 Oct 2026
Inference
The project describes its predictors as optimized for inference on both CPU and GPU.mindee.github.io · 5 Oct 2026
Customization
Users can train custom detection, recognition, layout, and table structure models when pretrained models do not meet their needs.mindee.github.io · 5 Oct 2026
Integrations
The documentation describes loading and sharing models through the Hugging Face Hub.mindee.github.io · 5 Oct 2026
Deployment
The project provides a minimal REST API deployment template and a browser demo.mindee.github.io · 5 Oct 2026
Installation
The library can be installed with pip or from Git, and official Docker images are available from GitHub Container Registry.mindee.github.io · 5 Oct 2026
Requirements
The installation guide requires Python 3.11 or higher.mindee.github.io · 5 Oct 2026
Security considerations
For AWS Lambda, the guide says to disable multiprocessing and set the model cache directory within /tmp to comply with Lambda's write restrictions.mindee.github.io · 5 Oct 2026
License
The project identifies its license as Apache License 2.0.github.com · 5 Oct 2026
Support
The contribution guide directs users with questions to GitHub Discussions and also mentions a #doctr channel on Slack.mindee.github.io · 5 Oct 2026
OCR features
It provides pretrained two-stage text detection and recognition predictors and a layout analysis predictor for regions such as tables, figures, and headers.mindee.github.io · 5 Oct 2026
Input formats
docTR can read PDFs, images, and web pages, with HTML input requiring the optional html extra.mindee.github.io · 5 Oct 2026
Output
OCR results can be rendered as plain text or exported as a JSON-serialisable nested dictionary.mindee.github.io · 5 Oct 2026
Extra modules
The contrib module includes an artefact detector for items such as logos, QR codes, and barcodes, and requires onnxruntime.mindee.github.io · 5 Oct 2026
Installation requirement
The library requires Python 3.11 or higher and can be installed from pip, Git, or an official Docker image.mindee.github.io · 5 Oct 2026
Pretrained weights
Pretrained weights are downloaded on first use and cached locally for later calls.mindee.github.io · 5 Oct 2026
Support resources
The documentation provides community resources and tools, and invites users to submit issues or pull requests for community models.mindee.github.io · 5 Oct 2026
Maker
The project documentation says docTR is actively maintained by Mindee.mindee.github.io · 5 Oct 2026

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