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ML data annotations made super easy for teams. Just upload data, add your team and build training/evaluation dataset in hours.
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bazaar diableing console loggin Jan 31, 2019
hope Update May 12, 2019
.DS_Store diableing console loggin Jan 31, 2019
.gitignore fixing Dockerfile for the new folder structure of the codebase Jan 30, 2019
LICENSE adding license Mar 18, 2019 Update May 1, 2019


NER tagging in Documents

Full length document annotations (PDF, Doc, Text etc).

Image Segmentation

    Draw free form polygons and generate image masks.

POS tagging

    A super easy interface to tag for PoS/NER in sentences.


[Note: As on March 2019, please use the branch master_with_dist as the main master branch has some build issues w.r.t dist folder]

Can run as a docker image as well. Here is the docker file specifying all the steps for setting things up:

If you rather have it run as a non-docker service, then see below.

Two main subcomponents:

  1. Hope: Java-mysql based backend.
Its a maven project, please install maven and then:
# cd hope
# mvn package -DskipTests <-- will build the .jar file.

The service is based on dropwizard and taken a config file on startup. This config file specifies the MYSQL end-points, 
password and the port to run the service on.

Setup mysql server as in:

# java -server -jar dataturks-1.0-SNAPSHOT.jar server onprem.yml
  1. Bazaar: React based front-end.

Mac Setup :

brew install node@8
brew link node@8
conda create -n bazaar python=2.7 anaconda
conda activate bazaar
xcode-select --install
sudo xcode-select -s /Applications/
rm -rf node_modules
npm rebuild node-sass
npm install
npm run dev  

Linux Setup: Install Node Js etc. #sudo apt-get -y install build-essential &&
curl -sL | bash &&
apt-get install --yes nodejs &&
node -v &&
npm -v && \ npm i -g nodemon &&
nodemon -v &&
apt-get clean

  # cd bazaar
  # npm install && npm run build-onprem

Run the service:
 # npm run start-onprem
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