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Description
Continuing in this issue the conversation started in the latest PR
(@OliverDavis comment)
How about this as a return object for both the
annotate
andforget
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?