In order to evaluate quality of ML models, as well as to create “ImageNet for source core” there is a need for tools to automate the data collection/labeling/annotation.
First you need OAuth application on github. Read how to create it.
On a page with your application you will need Client ID and Client Secret
Copy .env.tpl to .env and set tokens there.
docker build -t srcd/code-annotation .
docker run --env-file .env --rm -p 8080:8080 srcd/code-annotationgo get github.com/src-d/code-annotation/...
cd $GOPATH/github.com/src-d/code-annotation
make serveBackend:
make gorun
Frontend:
If you want to benifit from frontend hot reloading feature this line in your .env file:
UI_DOMAIN=http://127.0.0.1:3000
And then restart server.
To run frontend in dev mode:
yarn
yarn start
Please take a look at CONTRIBUTING file to see how to contribute in this project, get more information about the dashboard architecture and how to launch it for development purposes.
GPLv3, see LICENSE