Computer Vision should tell us how sure it is of its suggestions

Thank you! Even a someone else’s guess helps me have a perspective.
Next “easy” question…if I don’t want to immediately provide my id then I think there is a keyword I can use that means I’ll come back to it. I saw something to the effect of this when I was reading some instructions as it applies to offline mode. But I can’t find that material again…so what do I enter to submit an observation but I am not currently ready to even give an id guess?

And what about the observations with multiple pictures? I’m assuming you mean the confidence score to be shown for the primary photo. When I have multiple photos, I usually check by making each one the primary photo and seeing what the computer vision says. I look for repeats to help narrow it down. But in the end, I try to pick the photo that shows most of the plant, as that is what will be the thumbnail. Close ups of plants seem to work better for the accuracy of the computer vision, but some humans don’t want to look at just a close up (usually of a flower) and nothing else. I could be wrong, but I know I get frustrated at looking at observation after observation of only the flower (which, for Ranunculus is not very helpful), so sometimes will I skip over those. So, point is the CV may only be 50% sure for the primary photo, but 75% for a close up of the leaves (and maybe only 10% for a stem shot). The data may not be as useful as one would think.


@Rboinco, there is a thing called “placeholder text” which is what you can write in that will not count as an ID. However, I think that puts things into the “unknown” bin which is not very useful. I would put a guess in that you KNOW to be true…like insect, fungi, mammal, plant, etc. Then others can help narrow it down. If you have a guess or guesses, put them as a comment.


should be a new topic :)

You could put a tag, something like “revisit”, then when you are ready you can search for your observations that have that tag. I use chrome bookmarks folder to manage my “come back to this later” ones.

And there is nothing inherantly wrong with letting the community have a go in the mean time. Sometimes IDs are easy for some people who deal with those things all the time. As an example, I do my identifying in two passes… the first pass is as they turn up in the “needs ID” pool, and I only ID those I can be reasonably sure from the photo without having to pick up a book/reference. Then when I have time, I go back through old observations and look to ID from resources/books. There is no point in spending 10-20 minutes hunting through books if someone else can rattle off the ID in seconds. After it has been in the needs ID pool for longer than a week, then it is more likely to be one that needs looking up (depending on the taxa/difficulty of course)

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Hopefully without straying too much off topic, what about the ability to add an (optional) bounding box to photos? In theory, this could be used to restrict AI training to a certain part of the image, and could be visible to help identifiers work out what to identify.

I’ve often used MS Paint to circle an organism in an image - being able to do this natively would be useful.




And remember placeholder text disappears when an ID is added. Better to leave the text in a comment.


One simple and unobtrusive way you could make the confidence data available would be to add it as a title attribute to the “Visually similar” span in the suggestion interface. That way you could see the confidence score by hovering over the text. It would be a subtle addition, but at least it would make it available for folks that were interested.


It’s the words “pretty sure” that adds false confidence to the Algorithm ID.

I particularly like this “fig”



Some relevant comments from Ken-ichi:


even if we don’t call it confidence or probability, i think it would still be useful to see the “score”.


Presumably one could make a relative scale, where the first choice would be one (or zero), and the following ones would be fractions of one (or negative numbers). This could illustrate the differences between the 10 options. Does one stand out, or are they basically all equally likely?

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I would be concerned that many users, especially new users, would misinterpret any displayed numeric value as some level of relative confidence. I concur with @kueda that some would overly rely on the *cryptic opinion of this black box" and not their own judgement. Student users would be one group of new users who might overly rely on displayed values.


Just to argue with myself, maybe including such numbers would allow people to make better choices among the black box outputs. Counter counter argument: the problem is over-confidence in a numerical rating when the right answer isn’t even on the list. Counter counter counter argument: that’s already a problem. Counter counter counter counter argument: we’re all doomed and should be spending our time learning post-apocalyptic survival skills.


On it:


i think the scores are basically a measure of visual match and possibly some other factors like presence of observations of a taxon nearby. i think that’s why iNat staff don’t want people thinking of it as a probability or confidence.

so, for example, suppose you have 3 brothers A, B, and C. A & B are identical twins. suppose you take a picture of A and run it through a computer vision algorithm similar to iNaturalist’s. i would expect that CV to return scores that might be like this:
F: 0.97 – the family of A, B, & C
A: 0.95
B: 0.93
C: 0.65
D: 0.35 – D is the boy who lives next door.

so obviously, the CV couldn’t be both 95% sure the photo was of A and also 93% sure that it was of B, nor would it make sense to assign 95% probability of A and at the same time assign 93% probability of B, but by seeing the relative scores, you could see that the CV was saying that A and B were way better potential matches than C or D.


32 posts were split to a new topic: Chrome extension showing Computer Vision confidence

I like what @psium suggested. Perhaps it can be a % similarity [to other photos of which are RG]

98% similar to [photos of] genus A
92% similar to [photos of] species X
91% similar to [photos of] species Y
75% similar to [photos of] species z

With an option to view the top ~10 ranking IDs in the Identotron on a separate tab, this will also show where the nearest observations have been to try and eliminate Australian species suggestions for African observations.


I agree, people would tend to read the higher “match” percentage the wrong way and jump on the identification without really looking closely at it.

This is already a bit of an issue (sometimes I even have to stop myself from doing it).

I think it’s best if the AI suggestions are left general. I like the “pretty sure” wording as well, that reminds people that it’s not a certain ID.


If you need some book references, hit me up…