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README.md
doccano
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.
Features
- Collaborative annotation
- Multi-language support
- Mobile support
- Emoji 😄 support
- Dark theme
- RESTful API
Usage
Three options to run doccano:
- pip(experimental)
- Docker
- Docker Compose
- production
- development
For docker and docker compose, you need to install dependencies:
pip installation
To install doccano, simply run:
pip install doccano
After installation, simply run the following command:
# Initialize database.
doccano init
# Create a super user.
doccano createuser --username admin --password pass
# Start the webserver.
doccano webserver -p 8000
And in another terminal, run the following command:
# Start the task queue.
doccano task
Go to http://0.0.0.0:8000/.
Docker
As a one-time setup, create a Docker container as follows:
docker pull doccano/doccano
docker container create --name doccano \
-e "ADMIN_USERNAME=admin" \
-e "ADMIN_EMAIL=admin@example.com" \
-e "ADMIN_PASSWORD=password" \
-p 8000:8000 doccano/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.
Go to http://127.0.0.1:8000/.
Docker Compose
You need to clone the repository:
git clone https://github.com/doccano/doccano.git
cd doccano
Note for Windows developers: Be sure to configure git to correctly handle line endings or you may encounter status code 127
errors while running the services in future steps. Running with the git config options below will ensure your git directory correctly handles line endings.
git clone https://github.com/doccano/doccano.git --config core.autocrlf=input
Production
Set the superuser account credentials in the docker-compose.prod.yml
file:
ADMIN_USERNAME: "admin"
ADMIN_PASSWORD: "password"
If you use Google Analytics, set the tracking:
GOOGLE_TRACKING_ID: "UA-12345678-1"
Run doccano:
$ docker-compose -f docker-compose.prod.yml up
Go to http://0.0.0.0/.
Development
Set the superuser account credentials in the docker-compose.dev.yml
file:
ADMIN_USERNAME: "admin"
ADMIN_PASSWORD: "password"
Run Doccano:
$ docker-compose -f docker-compose.dev.yml up
Go to http://127.0.0.1:3000/.
Run Backend API-Tests:
You can run the API-Tests for the backend with the following command:
docker exec doccano_backend_1 pipenv run app/manage.py test api
Add annotators (optionally)
If you want to add annotators/annotation approvers, see Frequently Asked Questions
One-click Deployment
Service | Button |
---|---|
AWS1 | |
Azure | |
GCP2 | |
Heroku |
Documentation
See here.
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.
-
(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. ↩︎
-
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. ↩︎