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docTR documentation
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Getting started

  • Installation
  • docTR Notebooks

Using docTR

  • Choosing the right model
  • Choose a ready to use dataset
  • Integrate contributions into your pipeline
  • Share your model with the community
  • Preparing your model for inference
  • Train your own model
  • AWS Lambda

Community

  • Community resources

Package Reference

  • doctr.contrib
  • doctr.datasets
  • doctr.io
  • doctr.models
  • doctr.transforms
  • doctr.utils

Contributing

  • Contributor Covenant Code of Conduct
  • Contributing to docTR

Notes

  • Changelog
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docTR NotebooksΒΆ

Here are some notebooks compiled for users to better leverage the library capabilities:

Notebook

Description

Colab

[Quicktour]

A presentation of the main features of docTR

https://colab.research.google.com/assets/colab-badge.svg

[Export as PDF/A]

Produce searchable PDFs from docTR results

https://colab.research.google.com/assets/colab-badge.svg

[Using standalone predictors]

Showcase how to use detection, recognition, and orientation predictors

https://colab.research.google.com/assets/colab-badge.svg

[Dealing with rotated documents]

A presentation on how to handle documents containing rotations

https://colab.research.google.com/assets/colab-badge.svg
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