dynamicgenetics/the-learning-machine

Public engagement project using interactive human-in-the-loop online machine learning to teach machines to recognise human emotion (in development)

the-learning-machine's Issues

Frontend: faces could go beyond new hexagon boundaries

First public shout out to @OliverDavis for the new improvements to the UI (see branch: launch)
It is simply OUTSTANDING 🤩

(See screenshots below - cc/ @ninadicara )

Also (from Screenshot 1):
faces should be constrained within the new Hexagon Boundaries.

Frontend: Not-Human Classification also updates Bar Charts

Dragging a face to "not-human" also updates the bar charts of performance.
We should check this out when we'll link backend integration.

Branch: launch

Backend: Add `stats` JSON object to `BackendResponse`

Continuing in this issue the conversation started in the latest PR

(@OliverDavis comment)

How about this as a return object for both the annotate and forget endpoints?

{ "data": [current return object], "stats": {name, value for model fit stats} }

RE: I think that makes lots of sense. Also, appending the new stats objects to the current backend response is super quick to do too.

I think we should just decide what the stats object should contain, and which metric we want to calculate.

One first hypothesis can be to generate a per-class score (e.g. per-class precision), along with an overall score for all the faces currently on the board.

In other words, the stats object can have the following structure:

{
  stats: { 
      happy: happy score in [0, 1]
      sad: sad score  in [0, 1]
      angry: angry score  in [0, 1]
      disgust: disgust score  in [0, 1]
      fear: fear score  in [0, 1]
      surprise: surprise score  in [0, 1]
      overall: overall global score  in [0, 1]
}

When a new face will come in, updated scores for old 24 + 1 faces on the board will be returned.

Would that make any sense?

Donuts do not update in Frontend for images on board

The donuts do not change nor updates after image annotation, despite values from backend are passed to frontend changed.

This is particularly easy to spot if default number of images is decreased (e.g. to 2 ) and a non-retrained model is used (as it's the case of having heavy shifts in performance)

After a quick check, I noticed that the refreshNodeArray function in d8r.js updates links from server response, but doesn't do anything with donuts.

Isn't there were the donut update should be performed ?