/microdraw

Collaborative vectorial annotation tool for ultra high resolution data.

Primary LanguageJavaScriptGNU General Public License v3.0GPL-3.0

MicroDraw

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microdraw-vervet

MicroDraw is a collaborative vectorial annotation tool for ultra high resolution data, such as that produced by high-throughput histology.

Data visualisation uses OpenSeadragon, and data annotation uses Paper.js.

Developer install instructions

as of 2018-07-09

Basic Steps

without docker

  • install nodejs

  • install mongo

  • checkout the repository git clone https://github.com/r03ert0/microdraw.git

  • cd microdraw

  • install the project

    • cd into microdraw
    • npm install
  • run the project

    • in one terminal window start mongod database and leave it run
    • in another terminal: cd into microdraw folder: npm start
  • open http://localhost:3000 to see MicroDraws landing page and click any of the data links provided

  • test data can be viewed at http://localhost:3000/data?source=/test_data/cat.json

with docker

Users management

Microdraw utilises passportjs to manage user login. By default, Microdraw is configured to use Github and local strageties.

You may also want to set the session secret by setting the environment variable: SESSION_SECRET=MySuperDuperSecret

Enable Github signin strategy

  • Get your Github developer keys for your local microdraw url
  • copy paste client id, client secret and callback URL into ./app/auth/github-keys.json

Enable Local signin strategy

  • Set environment variable: LOCALSIGNIN=true

n.b. it is highly advised to not use local strategies to manage users unless absolutely necessary.

Annotations management

Microdraw uses mongodb to manage the annotations by default. You may choose to use a different solution, by replacing ./app/db/db.js and replace with your own backend.

You can set a custom endpoint for mongodb by setting the environment variable : MONGODB=url-to-mongo:27017/db_name

Set up your own local data folder

  • cd to /public directory, put yourDataFolder here which must contain
    • a folder with the folders with your data tiles in dzi format
    • the .dzi file containing the information about your data (generated by the converter)
    • a json file containing information about your data in the following form:
    {
      "pixelsPerMeter": 1000000,
      "tileSources": [
        "yourDataFolder/yourData.dzi"
      ]
    }
    

License

This project is licensed under GNU GPL v3 or any later version.