(You can jump to the conclusion if you are not interested in the maths)
Exact number of images tested: 14’537
How many must be discarded: 90% of 14’537: 13’083
Total identified by Futura Photo to be discarded: 10’095
Bridge: 13’083-10’095=2’988 : images that are no duplicates of anything, not really missed in terms of technical terms (acutance and exposure) but just not interesting. This part is not accessible to AI unless you start to implement a rule “not interesting picture” which is not trivial at all but not out of reach that being said. Anyway, it exists and must be considered.
AI in Camera Futura can discard 10’095/13’083 * 100 = 77% of images to be discarded, that does not sound bad at all to me.
But reality is different, there are “false positive” (FP: wrongly detected to be discarded, painful) and “false negative” (FN: missed to be detected).
Below the FP rates per rule. I am also adjusting the duplicates FP as some images are wrongly chosen. How much ? Typically, by experience, 10% (1 for 10, meaning 9 are true positive).
FP rate measured: (218*0+493*0.2+0*31+7.6*1’972+7’616*(10+1.2)+207*18.4+320*2.8)/(3’241+7’616) = 9.7 % (we considered the whole set of duplicates of course for this calculation)
FN rate measured: (218*17+493*4.3+0*31+10.5*1’972+7’616*16.7+207*22.2+320*0)/(3241+7’616)=14.5%
This means whereas 77% of images are flagged as “discarded”, it is more: 77-14.5=62.5 % and 9.7% wrongly flagged. For the calculation I will subtract this number as it will require a manual override from the user: 62.5-9.7=52.8 %
This means “a little bit less than half of the photos to be discarded are actually discarded” and on top of them, “a little bit less than 10% has been wrongly discarded”.