Deephub-common NPM

DeepHub Processes Standards and Guidelines

Kindly generated mostly by GitHub Copilot.

Introduction

This document describes the communication standards for the DeepHub software. It is intended to be a living document that will be updated as the software evolves.

HOW TO PUBLISH A NEW VERSION OF DH COMMON PACKAGE

git pull
git status
npm run build
## change a new version in package.json(manually)
## then the version is setted, run:
npm version
git commit -am "[version patch or minor or mayor]" # example: 1.1.0
git tag v1.1.0 # with example
npm publish
git push
git push --tags

Communication Standards

General

The DeepHub software is designed to be modular and extensible. This means that the software is designed to be able to be extended with new modules that can be added to the software. This also means that the software is designed to be able to be used in a variety of different ways. The communication standards are designed to allow for this flexibility and avoid magic numbers and strings that are hard to understand and maintain.

Cases

Frontend labels format

The frontend labels are the ones created from leaflet and displayed on the map.

class_name: (string) The type or specie for the selected object.
class_id: (int) The id of the selected object. Enumared from 1 to the n-th object.

Example:

{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {
        "class_name": 1,
        "class_id": 1
      },
      "geometry": {
        "type": "Polygon",
        "coordinates": []
      }
    },
    {
      "type": "Feature",
      "properties": {
        "class_name": 1,
        "class_id": 2
      },
      "geometry": {
        "type": "Polygon",
        "coordinates": []
      }
    }
  ]
}

Frontend ML Handler

When the frontend sends a train/predict request to the ML Handler, the ML Handler will send a response back to the frontend. The response will be a JSON object with the following fields:

BEGIN: (string) The beginning of the training/prediction process.
END: (string) The end of the training/prediction process.

Front/Back WebSocket Communication

When the frontend sends a request to the backend, the backend will send a response back to the frontend. The response will be a JSON object with the following fields:

TILER BEGIN FOR:{uuid}: (string) The beginning of the tiling process.
[TILER] GENERATING RGB TILES FOR:{uuid}: (string) The beginning of the RGB tiling process. ...