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Yans2019 Annotation hackathon
Home Page: https://datastudio.google.com/u/0/reporting/1nrzE6eXPYiT_fz4dYwp6W1QLcz6iUUKG/page/WgVy
License: MIT License
Python 98.94%
Dockerfile 1.06%
yans-2019-annotation-hackathon's Introduction
YANS 2019: Annotation Hackathon
Detail
![annotator workflow](./images/annotation_workflow.png)
- You can easily deploy doccano by Heroku Button.
![annotator workflow](./images/backend_workflow.png)
- S3 bucket:
yans.2019.js
- Google book id:
1WDwojAFoswN_rBe0P31sKECcWeku25fgLtAG7ZSbAUo
- Lambda function is triggerd by S3 upload. Lambda implementation is defined at
yans/function/lambda_function.py
.
- Slack => S3: Integromat
- Run Training: AWS
- Use ECS to run Dockerfile
- Japanese NER model is based on GiNZA.
- Prepare data
- Download and preprocess:
python yans/data/prepare.py
- Train by data
python yans/data/train.py
- If
--local
is set, use local data
directory and else use S3.
- Evaluate model
python yans/data/evaluate.py
- If
--local
is set, use local data
directory and else use S3.
- Rule based annotation
python yans/annotation/annotate.py
![result.png](/images/result.png)
yans-2019-annotation-hackathon's People
Contributors