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Open source text annotation tool for machine learning practitioner.
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README.md

doccano

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doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence to sequence tasks. So, you can create labeled data for sentiment analysis, named entity recognition, text summarization and so on. Just create a project, upload data and start annotating. You can build a dataset in hours.

Demo

You can try the annotation demo.

Named Entity Recognition

Features

  • Collaborative annotation
  • Multi-language support
  • Mobile support
  • Emoji 😄 support
  • Dark theme
  • RESTful API

Usage

Two options to run doccano:

  • (Recommended) Docker Compose
  • Docker

Docker Compose

$ git clone https://github.com/doccano/doccano.git
$ cd doccano
$ docker-compose -f docker-compose.prod.yml up

Access http://0.0.0.0/.

Note the superuser account credentials located in the docker-compose.prod.yml file:

ADMIN_USERNAME: "admin"
ADMIN_PASSWORD: "password"

Note: If you want to add annotators, see Frequently Asked Questions

Docker

As a one-time setup, create a Docker container for Doccano:

docker pull chakkiworks/doccano
docker container create --name doccano \
  -e "ADMIN_USERNAME=admin" \
  -e "ADMIN_EMAIL=admin@example.com" \
  -e "ADMIN_PASSWORD=password" \
  -p 8000:8000 chakkiworks/doccano

Next, start Doccano by running the container:

docker container start doccano

To stop the container, run docker container stop doccano -t 5. All data created in the container will persist across restarts.

Access http://127.0.0.1:8000/.

One-click Deployment

Service Button
AWS[^1] AWS CloudFormation Launch Stack SVG Button
Azure Deploy to Azure
GCP[^2] GCP Cloud Run PNG Button
Heroku Deploy

[^1]: (1) EC2 KeyPair cannot be created automatically, so make sure you have an existing EC2 KeyPair in one region. Or create one yourself. (2) If you want to access doccano via HTTPS in AWS, here is an instruction. [^2]: Although this is a very cheap option, it is only suitable for very small teams (up to 80 concurrent requests). Read more on Cloud Run docs.

Contribution

As with any software, doccano is under continuous development. If you have requests for features, please file an issue describing your request. Also, if you want to see work towards a specific feature, feel free to contribute by working towards it. The standard procedure is to fork the repository, add a feature, fix a bug, then file a pull request that your changes are to be merged into the main repository and included in the next release.

Here are some tips might be helpful. How to Contribute to Doccano Project

Citation

@misc{doccano,
  title={{doccano}: Text Annotation Tool for Human},
  url={https://github.com/doccano/doccano},
  note={Software available from https://github.com/doccano/doccano},
  author={
    Hiroki Nakayama and
    Takahiro Kubo and
    Junya Kamura and
    Yasufumi Taniguchi and
    Xu Liang},
  year={2018},
}

Contact

For help and feedback, please feel free to contact the author.

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